2024-06-05 00:31:20,417 - mmdet - INFO - Environment info: ------------------------------------------------------------ sys.platform: linux Python: 3.9.19 (main, May 6 2024, 19:43:03) [GCC 11.2.0] CUDA available: True GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.7/ NVCC: Cuda compilation tools, release 11.7, V11.7.99 GCC: gcc (GCC) 7.3.0 PyTorch: 1.12.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.3.2 (built against CUDA 11.5) - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.13.0+cu113 OpenCV: 4.9.0 MMCV: 1.7.0 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 11.7 MMDetection: 2.25.3+d72f4e5 ------------------------------------------------------------ 2024-06-05 00:31:21,965 - mmdet - INFO - Distributed training: True 2024-06-05 00:31:23,686 - mmdet - INFO - Config: model = dict( type='MaskRCNN', backbone=dict( type='PIIPThreeBranch', n_points=4, deform_num_heads=16, cffn_ratio=0.25, deform_ratio=0.5, with_cffn=True, interact_attn_type='deform', interaction_drop_path_rate=0.4, interaction_proj=False, norm_layer='none', branch1=dict( real_size=672, pretrain_img_size=384, patch_size=16, pretrain_patch_size=16, depth=24, embed_dim=1024, num_heads=16, mlp_ratio=4, qkv_bias=True, init_values=1.0, with_cp=True, use_flash_attn=True, qk_normalization=False, layerscale_force_fp32=False, with_fpn=False, drop_path_rate=0.4, interaction_indexes=[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11], [12, 13], [14, 15], [16, 17], [18, 19], [20, 21], [22, 23]], pretrained= 'pretrained/L_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.1-sd_0.1--imagenet2012-steps_20k-lr_0.01-res_384.pth', norm_layer_type='LayerNorm', mlp_type='fused_mlp', window_attn=[ True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True ], window_size=[ 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28 ], img_norm_cfg=dict( mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True)), branch2=dict( real_size=1120, pretrain_img_size=384, patch_size=16, pretrain_patch_size=16, depth=12, embed_dim=768, num_heads=12, mlp_ratio=4, qkv_bias=True, init_values=1.0, with_cp=True, use_flash_attn=True, qk_normalization=False, layerscale_force_fp32=False, with_fpn=False, drop_path_rate=0.3, interaction_indexes=[[0, 0], [1, 1], [2, 2], [3, 3], [4, 4], [5, 5], [6, 6], [7, 7], [8, 8], [9, 9], [10, 10], [11, 11]], pretrained= 'pretrained/B_16-i21k-300ep-lr_0.001-aug_medium1-wd_0.1-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.01-res_384.pth', norm_layer_type='LayerNorm', mlp_type='fused_mlp', window_attn=[ True, True, True, True, True, True, True, True, True, True, True, True ], window_size=[28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28], img_norm_cfg=dict( mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True)), branch3=dict( real_size=1568, pretrain_img_size=384, patch_size=16, pretrain_patch_size=16, depth=12, embed_dim=384, num_heads=6, mlp_ratio=4, qkv_bias=True, init_values=1.0, with_cp=True, use_flash_attn=True, qk_normalization=False, layerscale_force_fp32=False, with_fpn=False, drop_path_rate=0.2, interaction_indexes=[[0, 0], [1, 1], [2, 2], [3, 3], [4, 4], [5, 5], [6, 6], [7, 7], [8, 8], [9, 9], [10, 10], [11, 11]], pretrained= 'pretrained/S_16-i21k-300ep-lr_0.001-aug_light1-wd_0.03-do_0.0-sd_0.0--imagenet2012-steps_20k-lr_0.03-res_384.pth', norm_layer_type='LayerNorm', mlp_type='fused_mlp', window_attn=[ True, True, True, True, True, True, True, True, True, True, True, True ], window_size=[28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28], img_norm_cfg=dict( mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True))), neck=dict( type='FPN', in_channels=[1024, 1024, 1024, 1024], out_channels=256, num_outs=5), rpn_head=dict( type='RPNHead', in_channels=256, feat_channels=256, anchor_generator=dict( type='AnchorGenerator', scales=[8], ratios=[0.5, 1.0, 2.0], strides=[4, 8, 16, 32, 64]), bbox_coder=dict( type='DeltaXYWHBBoxCoder', target_means=[0.0, 0.0, 0.0, 0.0], target_stds=[1.0, 1.0, 1.0, 1.0]), loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0), loss_bbox=dict(type='L1Loss', loss_weight=1.0)), roi_head=dict( type='StandardRoIHead', bbox_roi_extractor=dict( type='SingleRoIExtractor', roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0), out_channels=256, featmap_strides=[4, 8, 16, 32]), bbox_head=dict( type='Shared2FCBBoxHead', in_channels=256, fc_out_channels=1024, roi_feat_size=7, num_classes=80, bbox_coder=dict( type='DeltaXYWHBBoxCoder', target_means=[0.0, 0.0, 0.0, 0.0], target_stds=[0.1, 0.1, 0.2, 0.2]), reg_class_agnostic=False, loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0), loss_bbox=dict(type='L1Loss', loss_weight=1.0)), mask_roi_extractor=dict( type='SingleRoIExtractor', roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0), out_channels=256, featmap_strides=[4, 8, 16, 32]), mask_head=dict( type='FCNMaskHead', num_convs=4, in_channels=256, conv_out_channels=256, num_classes=80, loss_mask=dict( type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))), train_cfg=dict( rpn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.7, neg_iou_thr=0.3, min_pos_iou=0.3, match_low_quality=True, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=256, pos_fraction=0.5, neg_pos_ub=-1, add_gt_as_proposals=False), allowed_border=-1, pos_weight=-1, debug=False), rpn_proposal=dict( nms_pre=2000, max_per_img=1000, nms=dict(type='nms', iou_threshold=0.7), min_bbox_size=0), rcnn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.5, min_pos_iou=0.5, match_low_quality=True, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), mask_size=28, pos_weight=-1, debug=False)), test_cfg=dict( rpn=dict( nms_pre=1000, max_per_img=1000, nms=dict(type='nms', iou_threshold=0.7), min_bbox_size=0), rcnn=dict( score_thr=0.05, nms=dict(type='nms', iou_threshold=0.5), max_per_img=100, mask_thr_binary=0.5))) dataset_type = 'CocoDataset' data_root = 'data/coco/' img_norm_cfg = dict( mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True, with_mask=True), dict(type='Resize', img_scale=(1568, 941), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict( type='Normalize', mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True), dict(type='Pad', size_divisor=224), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']) ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1568, 941), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True), dict(type='Pad', size_divisor=224), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ] data = dict( samples_per_gpu=2, workers_per_gpu=2, train=dict( type='CocoDataset', ann_file='data/coco/annotations/instances_train2017.json', img_prefix='data/coco/train2017/', pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True, with_mask=True), dict(type='Resize', img_scale=(1568, 941), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict( type='Normalize', mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True), dict(type='Pad', size_divisor=224), dict(type='DefaultFormatBundle'), dict( type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']) ]), val=dict( type='CocoDataset', ann_file='data/coco/annotations/instances_val2017.json', img_prefix='data/coco/val2017/', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1568, 941), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True), dict(type='Pad', size_divisor=224), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ]), test=dict( type='CocoDataset', ann_file='data/coco/annotations/instances_val2017.json', img_prefix='data/coco/val2017/', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1568, 941), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[127.5, 127.5, 127.5], std=[127.5, 127.5, 127.5], to_rgb=True), dict(type='Pad', size_divisor=224), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ])) evaluation = dict(metric=['bbox', 'segm'], interval=1, save_best=None) optimizer = dict( type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05, constructor='CustomLayerDecayOptimizerConstructorMMDet', paramwise_cfg=dict( num_layers=24, layer_decay_rate=0.85, skip_stride=[2, 2])) optimizer_config = dict(grad_clip=None) lr_config = dict( policy='step', warmup='linear', warmup_iters=500, warmup_ratio=0.001, step=[8, 11]) runner = dict(type='EpochBasedRunner', max_epochs=12) checkpoint_config = dict(interval=1, deepspeed=True, max_keep_ckpts=1) log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')]) custom_hooks = [dict(type='ToBFloat16HookMMDet', priority=49)] dist_params = dict(backend='nccl') log_level = 'INFO' load_from = None resume_from = None workflow = [('train', 1)] opencv_num_threads = 0 mp_start_method = 'fork' auto_scale_lr = dict(enable=False, base_batch_size=16) deepspeed = True deepspeed_config = 'zero_configs/adam_zero1_bf16.json' custom_imports = dict( imports=['mmdet.mmcv_custom'], allow_failed_imports=False) work_dir = './work_dirs/mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup' auto_resume = True gpu_ids = range(0, 8) 2024-06-05 00:31:28,690 - mmdet - INFO - Set random seed to 1129759902, deterministic: False 2024-06-05 00:31:33,291 - mmdet - INFO - _IncompatibleKeys(missing_keys=['blocks.0.ls1.gamma', 'blocks.0.ls2.gamma', 'blocks.1.ls1.gamma', 'blocks.1.ls2.gamma', 'blocks.2.ls1.gamma', 'blocks.2.ls2.gamma', 'blocks.3.ls1.gamma', 'blocks.3.ls2.gamma', 'blocks.4.ls1.gamma', 'blocks.4.ls2.gamma', 'blocks.5.ls1.gamma', 'blocks.5.ls2.gamma', 'blocks.6.ls1.gamma', 'blocks.6.ls2.gamma', 'blocks.7.ls1.gamma', 'blocks.7.ls2.gamma', 'blocks.8.ls1.gamma', 'blocks.8.ls2.gamma', 'blocks.9.ls1.gamma', 'blocks.9.ls2.gamma', 'blocks.10.ls1.gamma', 'blocks.10.ls2.gamma', 'blocks.11.ls1.gamma', 'blocks.11.ls2.gamma', 'blocks.12.ls1.gamma', 'blocks.12.ls2.gamma', 'blocks.13.ls1.gamma', 'blocks.13.ls2.gamma', 'blocks.14.ls1.gamma', 'blocks.14.ls2.gamma', 'blocks.15.ls1.gamma', 'blocks.15.ls2.gamma', 'blocks.16.ls1.gamma', 'blocks.16.ls2.gamma', 'blocks.17.ls1.gamma', 'blocks.17.ls2.gamma', 'blocks.18.ls1.gamma', 'blocks.18.ls2.gamma', 'blocks.19.ls1.gamma', 'blocks.19.ls2.gamma', 'blocks.20.ls1.gamma', 'blocks.20.ls2.gamma', 'blocks.21.ls1.gamma', 'blocks.21.ls2.gamma', 'blocks.22.ls1.gamma', 'blocks.22.ls2.gamma', 'blocks.23.ls1.gamma', 'blocks.23.ls2.gamma'], unexpected_keys=['cls_token', 'norm.weight', 'norm.bias']) 2024-06-05 00:31:34,516 - mmdet - INFO - _IncompatibleKeys(missing_keys=['blocks.0.ls1.gamma', 'blocks.0.ls2.gamma', 'blocks.1.ls1.gamma', 'blocks.1.ls2.gamma', 'blocks.2.ls1.gamma', 'blocks.2.ls2.gamma', 'blocks.3.ls1.gamma', 'blocks.3.ls2.gamma', 'blocks.4.ls1.gamma', 'blocks.4.ls2.gamma', 'blocks.5.ls1.gamma', 'blocks.5.ls2.gamma', 'blocks.6.ls1.gamma', 'blocks.6.ls2.gamma', 'blocks.7.ls1.gamma', 'blocks.7.ls2.gamma', 'blocks.8.ls1.gamma', 'blocks.8.ls2.gamma', 'blocks.9.ls1.gamma', 'blocks.9.ls2.gamma', 'blocks.10.ls1.gamma', 'blocks.10.ls2.gamma', 'blocks.11.ls1.gamma', 'blocks.11.ls2.gamma'], unexpected_keys=['cls_token', 'norm.weight', 'norm.bias']) 2024-06-05 00:31:35,117 - mmdet - INFO - _IncompatibleKeys(missing_keys=['blocks.0.ls1.gamma', 'blocks.0.ls2.gamma', 'blocks.1.ls1.gamma', 'blocks.1.ls2.gamma', 'blocks.2.ls1.gamma', 'blocks.2.ls2.gamma', 'blocks.3.ls1.gamma', 'blocks.3.ls2.gamma', 'blocks.4.ls1.gamma', 'blocks.4.ls2.gamma', 'blocks.5.ls1.gamma', 'blocks.5.ls2.gamma', 'blocks.6.ls1.gamma', 'blocks.6.ls2.gamma', 'blocks.7.ls1.gamma', 'blocks.7.ls2.gamma', 'blocks.8.ls1.gamma', 'blocks.8.ls2.gamma', 'blocks.9.ls1.gamma', 'blocks.9.ls2.gamma', 'blocks.10.ls1.gamma', 'blocks.10.ls2.gamma', 'blocks.11.ls1.gamma', 'blocks.11.ls2.gamma'], unexpected_keys=['cls_token', 'norm.weight', 'norm.bias']) 2024-06-05 00:33:00,510 - mmdet - INFO - initialize FPN with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'} 2024-06-05 00:33:00,996 - mmdet - INFO - initialize RPNHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01} 2024-06-05 00:33:01,051 - mmdet - INFO - initialize Shared2FCBBoxHead with init_cfg [{'type': 'Normal', 'std': 0.01, 'override': {'name': 'fc_cls'}}, {'type': 'Normal', 'std': 0.001, 'override': {'name': 'fc_reg'}}, {'type': 'Xavier', 'distribution': 'uniform', 'override': [{'name': 'shared_fcs'}, {'name': 'cls_fcs'}, {'name': 'reg_fcs'}]}] Name of parameter - Initialization information backbone.w1 - torch.Size([]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.w2 - torch.Size([]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.w3 - torch.Size([]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.pos_embed - torch.Size([1, 577, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.patch_embed.proj.weight - torch.Size([1024, 3, 16, 16]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.patch_embed.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.0.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.1.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.2.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.3.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.4.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.5.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.6.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.7.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.8.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.9.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.10.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.11.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.12.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.13.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.14.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.15.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.16.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.17.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.18.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.19.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.20.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.21.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.22.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.norm1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.norm1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.attn.qkv.weight - torch.Size([3072, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.attn.qkv.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.attn.proj.weight - torch.Size([1024, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.attn.proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.ls1.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.norm2.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.norm2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.mlp.fc1.weight - torch.Size([4096, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.mlp.fc1.bias - torch.Size([4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.mlp.fc2.weight - torch.Size([1024, 4096]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.mlp.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch1.blocks.23.ls2.gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.pos_embed - torch.Size([1, 577, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.patch_embed.proj.weight - torch.Size([768, 3, 16, 16]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.patch_embed.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.0.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.1.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.2.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.3.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.4.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.5.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.6.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.7.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.8.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.9.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.10.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.norm1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.norm1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.ls1.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.norm2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.norm2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.mlp.fc1.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.mlp.fc1.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.mlp.fc2.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.mlp.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch2.blocks.11.ls2.gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.pos_embed - torch.Size([1, 577, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.patch_embed.proj.weight - torch.Size([384, 3, 16, 16]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.patch_embed.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.0.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.1.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.2.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.3.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.4.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.5.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.6.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.7.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.8.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.9.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.10.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.norm1.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.norm1.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.attn.qkv.weight - torch.Size([1152, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.attn.qkv.bias - torch.Size([1152]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.attn.proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.attn.proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.ls1.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.norm2.weight - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.norm2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.mlp.fc1.weight - torch.Size([1536, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.mlp.fc1.bias - torch.Size([1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.mlp.fc2.weight - torch.Size([384, 1536]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.mlp.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.branch3.blocks.11.ls2.gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.2.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.3.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.4.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.5.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.6.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.7.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.8.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.9.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.10.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ca_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.cffn_gamma - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.output_proj.weight - torch.Size([1024, 512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.output_proj.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.value_proj.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.attn.value_proj.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc1.weight - torch.Size([256, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc2.weight - torch.Size([1024, 256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch2to1_injector.ffn.fc2.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.value_proj.weight - torch.Size([384, 1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_12.branch1to2_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ca_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.cffn_gamma - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight - torch.Size([128, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.attention_weights.weight - torch.Size([64, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.output_proj.weight - torch.Size([768, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.output_proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.value_proj.weight - torch.Size([384, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.attn.value_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc1.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc1.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight - torch.Size([192, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc2.weight - torch.Size([768, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch2to1_injector.ffn.fc2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ca_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.cffn_gamma - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight - torch.Size([128, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.sampling_offsets.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.attention_weights.weight - torch.Size([64, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.attention_weights.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.output_proj.weight - torch.Size([384, 192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.output_proj.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.value_proj.weight - torch.Size([192, 768]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.attn.value_proj.bias - torch.Size([192]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc1.weight - torch.Size([96, 384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight - torch.Size([96, 1, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc2.weight - torch.Size([384, 96]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc2.bias - torch.Size([384]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.0.weight - torch.Size([1024, 1024, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.3.weight - torch.Size([1024, 1024, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.4.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch1.4.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.0.weight - torch.Size([1024, 768, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.3.weight - torch.Size([1024, 1024, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.4.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch2.4.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.0.weight - torch.Size([1024, 384, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.3.weight - torch.Size([1024, 1024, 3, 3]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.4.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.merge_branch3.4.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.0.weight - torch.Size([1024, 1024, 2, 2]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.3.weight - torch.Size([1024, 1024, 2, 2]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn1.3.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn2.0.weight - torch.Size([1024, 1024, 2, 2]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.fpn2.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.0.conv.weight - torch.Size([256, 1024, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.0.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.1.conv.weight - torch.Size([256, 1024, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.1.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.2.conv.weight - torch.Size([256, 1024, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.2.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.3.conv.weight - torch.Size([256, 1024, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.3.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=uniform, bias=0 neck.fpn_convs.0.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=uniform, bias=0 neck.fpn_convs.1.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=uniform, bias=0 neck.fpn_convs.2.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.3.conv.weight - torch.Size([256, 256, 3, 3]): XavierInit: gain=1, distribution=uniform, bias=0 neck.fpn_convs.3.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN rpn_head.rpn_conv.weight - torch.Size([256, 256, 3, 3]): NormalInit: mean=0, std=0.01, bias=0 rpn_head.rpn_conv.bias - torch.Size([256]): NormalInit: mean=0, std=0.01, bias=0 rpn_head.rpn_cls.weight - torch.Size([3, 256, 1, 1]): NormalInit: mean=0, std=0.01, bias=0 rpn_head.rpn_cls.bias - torch.Size([3]): NormalInit: mean=0, std=0.01, bias=0 rpn_head.rpn_reg.weight - torch.Size([12, 256, 1, 1]): NormalInit: mean=0, std=0.01, bias=0 rpn_head.rpn_reg.bias - torch.Size([12]): NormalInit: mean=0, std=0.01, bias=0 roi_head.bbox_head.fc_cls.weight - torch.Size([81, 1024]): NormalInit: mean=0, std=0.01, bias=0 roi_head.bbox_head.fc_cls.bias - torch.Size([81]): NormalInit: mean=0, std=0.01, bias=0 roi_head.bbox_head.fc_reg.weight - torch.Size([320, 1024]): NormalInit: mean=0, std=0.001, bias=0 roi_head.bbox_head.fc_reg.bias - torch.Size([320]): NormalInit: mean=0, std=0.001, bias=0 roi_head.bbox_head.shared_fcs.0.weight - torch.Size([1024, 12544]): XavierInit: gain=1, distribution=uniform, bias=0 roi_head.bbox_head.shared_fcs.0.bias - torch.Size([1024]): XavierInit: gain=1, distribution=uniform, bias=0 roi_head.bbox_head.shared_fcs.1.weight - torch.Size([1024, 1024]): XavierInit: gain=1, distribution=uniform, bias=0 roi_head.bbox_head.shared_fcs.1.bias - torch.Size([1024]): XavierInit: gain=1, distribution=uniform, bias=0 roi_head.mask_head.convs.0.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule roi_head.mask_head.convs.0.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN roi_head.mask_head.convs.1.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule roi_head.mask_head.convs.1.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN roi_head.mask_head.convs.2.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule roi_head.mask_head.convs.2.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN roi_head.mask_head.convs.3.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule roi_head.mask_head.convs.3.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN roi_head.mask_head.upsample.weight - torch.Size([256, 256, 2, 2]): Initialized by user-defined `init_weights` in FCNMaskHead roi_head.mask_head.upsample.bias - torch.Size([256]): Initialized by user-defined `init_weights` in FCNMaskHead roi_head.mask_head.conv_logits.weight - torch.Size([80, 256, 1, 1]): Initialized by user-defined `init_weights` in FCNMaskHead roi_head.mask_head.conv_logits.bias - torch.Size([80]): Initialized by user-defined `init_weights` in FCNMaskHead 2024-06-05 00:33:18,567 - mmdet - INFO - {'num_layers': 24, 'layer_decay_rate': 0.85, 'skip_stride': [2, 2]} 2024-06-05 00:33:18,567 - mmdet - INFO - Build LayerDecayOptimizerConstructor 0.850000 - 26 2024-06-05 00:33:18,580 - mmdet - INFO - Param groups = { "layer_25_decay": { "param_names": [ "backbone.w1", "backbone.w2", "backbone.w3", "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.output_proj.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.attn.value_proj.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc1.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.0.interaction_units_12.branch2to1_injector.ffn.fc2.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.attention_weights.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.output_proj.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.attn.value_proj.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc1.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.0.interaction_units_12.branch1to2_injector.ffn.fc2.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.output_proj.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.attn.value_proj.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc1.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.0.interaction_units_23.branch2to1_injector.ffn.fc2.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.attention_weights.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.output_proj.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.attn.value_proj.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc1.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.0.interaction_units_23.branch1to2_injector.ffn.fc2.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.output_proj.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.attn.value_proj.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc1.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.1.interaction_units_12.branch2to1_injector.ffn.fc2.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.attention_weights.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.output_proj.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.attn.value_proj.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc1.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.1.interaction_units_12.branch1to2_injector.ffn.fc2.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.output_proj.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.attn.value_proj.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc1.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.1.interaction_units_23.branch2to1_injector.ffn.fc2.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.sampling_offsets.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.attention_weights.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.output_proj.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.attn.value_proj.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc1.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.1.interaction_units_23.branch1to2_injector.ffn.fc2.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.output_proj.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.attn.value_proj.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc1.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.2.interaction_units_12.branch2to1_injector.ffn.fc2.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.sampling_offsets.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.attention_weights.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.output_proj.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.attn.value_proj.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc1.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.dwconv.dwconv.weight", "backbone.interactions.2.interaction_units_12.branch1to2_injector.ffn.fc2.weight", "backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.sampling_offsets.weight", "backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.attention_weights.weight", "backbone.interactions.2.interaction_units_23.branch2to1_injector.attn.output_proj.weight", 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"backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc1.bias", "backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.dwconv.dwconv.bias", "backbone.interactions.11.interaction_units_23.branch1to2_injector.ffn.fc2.bias", "backbone.merge_branch1.1.weight", "backbone.merge_branch1.1.bias", "backbone.merge_branch1.4.weight", "backbone.merge_branch1.4.bias", "backbone.merge_branch2.1.weight", "backbone.merge_branch2.1.bias", "backbone.merge_branch2.4.weight", "backbone.merge_branch2.4.bias", "backbone.merge_branch3.1.weight", "backbone.merge_branch3.1.bias", "backbone.merge_branch3.4.weight", "backbone.merge_branch3.4.bias", "backbone.fpn1.0.bias", "backbone.fpn1.1.weight", "backbone.fpn1.1.bias", "backbone.fpn1.3.bias", "backbone.fpn2.0.bias", "neck.lateral_convs.0.conv.bias", "neck.lateral_convs.1.conv.bias", "neck.lateral_convs.2.conv.bias", "neck.lateral_convs.3.conv.bias", "neck.fpn_convs.0.conv.bias", "neck.fpn_convs.1.conv.bias", "neck.fpn_convs.2.conv.bias", "neck.fpn_convs.3.conv.bias", "rpn_head.rpn_conv.bias", "rpn_head.rpn_cls.bias", "rpn_head.rpn_reg.bias", "roi_head.bbox_head.fc_cls.bias", "roi_head.bbox_head.fc_reg.bias", "roi_head.bbox_head.shared_fcs.0.bias", "roi_head.bbox_head.shared_fcs.1.bias", "roi_head.mask_head.convs.0.conv.bias", "roi_head.mask_head.convs.1.conv.bias", "roi_head.mask_head.convs.2.conv.bias", "roi_head.mask_head.convs.3.conv.bias", "roi_head.mask_head.upsample.bias", "roi_head.mask_head.conv_logits.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 } } 2024-06-05 00:33:42,643 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled. 2024-06-05 00:33:43,048 - mmdet - INFO - Start running, work_dir: /mnt/petrelfs/PIIP/mmdetection/work_dirs/mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup 2024-06-05 00:33:43,048 - mmdet - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) StepLrUpdaterHook (49 ) ToBFloat16HookMMDet (NORMAL ) DeepspeedCheckpointHook (LOW ) DeepspeedDistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_epoch: (VERY_HIGH ) StepLrUpdaterHook (NORMAL ) DistSamplerSeedHook (LOW ) IterTimerHook (LOW ) DeepspeedDistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_iter: (VERY_HIGH ) StepLrUpdaterHook (LOW ) IterTimerHook (LOW ) DeepspeedDistEvalHook -------------------- after_train_iter: (ABOVE_NORMAL) OptimizerHook (NORMAL ) DeepspeedCheckpointHook (LOW ) IterTimerHook (LOW ) DeepspeedDistEvalHook (VERY_LOW ) TextLoggerHook -------------------- after_train_epoch: (NORMAL ) DeepspeedCheckpointHook (LOW ) DeepspeedDistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_val_epoch: (NORMAL ) DistSamplerSeedHook (LOW ) IterTimerHook (VERY_LOW ) TextLoggerHook -------------------- before_val_iter: (LOW ) IterTimerHook -------------------- after_val_iter: (LOW ) IterTimerHook -------------------- after_val_epoch: (VERY_LOW ) TextLoggerHook -------------------- after_run: (VERY_LOW ) TextLoggerHook -------------------- 2024-06-05 00:33:43,048 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs 2024-06-05 00:33:43,058 - mmdet - INFO - Checkpoints will be saved to /mnt/petrelfs/PIIP/mmdetection/work_dirs/mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup by HardDiskBackend. 2024-06-05 00:34:34,166 - mmdet - INFO - Epoch [1][50/7330] lr: 9.890e-06, eta: 1 day, 0:57:13, time: 1.022, data_time: 0.126, memory: 11010, loss_rpn_cls: 0.6013, loss_rpn_bbox: 0.1303, loss_cls: 1.9325, acc: 60.7715, loss_bbox: 0.0281, loss_mask: 1.0845, loss: 3.7767 2024-06-05 00:35:16,254 - mmdet - INFO - Epoch [1][100/7330] lr: 1.988e-05, eta: 22:44:32, time: 0.842, data_time: 0.048, memory: 11154, loss_rpn_cls: 0.2916, loss_rpn_bbox: 0.1051, loss_cls: 0.3744, acc: 95.5222, loss_bbox: 0.1400, loss_mask: 0.7487, loss: 1.6599 2024-06-05 00:35:58,877 - mmdet - INFO - Epoch [1][150/7330] lr: 2.987e-05, eta: 22:05:01, time: 0.852, data_time: 0.048, memory: 11154, loss_rpn_cls: 0.2454, loss_rpn_bbox: 0.1031, loss_cls: 0.3309, acc: 95.2622, loss_bbox: 0.1495, loss_mask: 0.6951, loss: 1.5240 2024-06-05 00:36:41,158 - mmdet - INFO - Epoch [1][200/7330] lr: 3.986e-05, eta: 21:42:25, time: 0.846, data_time: 0.061, memory: 11154, loss_rpn_cls: 0.2235, loss_rpn_bbox: 0.1046, loss_cls: 0.3027, acc: 95.5115, loss_bbox: 0.1403, loss_mask: 0.6808, loss: 1.4519 2024-06-05 00:37:23,661 - mmdet - INFO - Epoch [1][250/7330] lr: 4.985e-05, eta: 21:29:52, time: 0.850, data_time: 0.058, memory: 11154, loss_rpn_cls: 0.1942, loss_rpn_bbox: 0.1050, loss_cls: 0.3621, acc: 94.4297, loss_bbox: 0.1875, loss_mask: 0.6686, loss: 1.5175 2024-06-05 00:38:06,292 - mmdet - INFO - Epoch [1][300/7330] lr: 5.984e-05, eta: 21:21:51, time: 0.852, data_time: 0.062, memory: 11189, loss_rpn_cls: 0.1566, loss_rpn_bbox: 0.1053, loss_cls: 0.4450, acc: 93.1877, loss_bbox: 0.2397, loss_mask: 0.6528, loss: 1.5995 2024-06-05 00:38:48,879 - mmdet - INFO - Epoch [1][350/7330] lr: 6.983e-05, eta: 21:15:48, time: 0.852, data_time: 0.055, memory: 11253, loss_rpn_cls: 0.1361, loss_rpn_bbox: 0.1009, loss_cls: 0.4508, acc: 92.7273, loss_bbox: 0.2579, loss_mask: 0.6244, loss: 1.5700 2024-06-05 00:39:31,465 - mmdet - INFO - Epoch [1][400/7330] lr: 7.982e-05, eta: 21:11:03, time: 0.852, data_time: 0.066, memory: 11253, loss_rpn_cls: 0.1281, loss_rpn_bbox: 0.1001, loss_cls: 0.4929, acc: 91.7107, loss_bbox: 0.2941, loss_mask: 0.5936, loss: 1.6088 2024-06-05 00:40:14,394 - mmdet - INFO - Epoch [1][450/7330] lr: 8.981e-05, eta: 21:08:19, time: 0.859, data_time: 0.056, memory: 11259, loss_rpn_cls: 0.1113, loss_rpn_bbox: 0.1009, loss_cls: 0.4847, acc: 91.6943, loss_bbox: 0.2955, loss_mask: 0.5677, loss: 1.5601 2024-06-05 00:40:57,948 - mmdet - INFO - Epoch [1][500/7330] lr: 9.980e-05, eta: 21:07:48, time: 0.871, data_time: 0.063, memory: 11318, loss_rpn_cls: 0.1022, loss_rpn_bbox: 0.0948, loss_cls: 0.4657, acc: 91.5754, loss_bbox: 0.2991, loss_mask: 0.5254, loss: 1.4873 2024-06-05 00:41:41,171 - mmdet - INFO - Epoch [1][550/7330] lr: 1.000e-04, eta: 21:06:19, time: 0.864, data_time: 0.059, memory: 11321, loss_rpn_cls: 0.0987, loss_rpn_bbox: 0.0984, loss_cls: 0.4948, acc: 90.9402, loss_bbox: 0.3188, loss_mask: 0.5228, loss: 1.5335 2024-06-05 00:42:23,954 - mmdet - INFO - Epoch [1][600/7330] lr: 1.000e-04, eta: 21:04:00, time: 0.856, data_time: 0.054, memory: 11321, loss_rpn_cls: 0.0920, loss_rpn_bbox: 0.0926, loss_cls: 0.4702, acc: 90.6514, loss_bbox: 0.3345, loss_mask: 0.4992, loss: 1.4886 2024-06-05 00:43:06,280 - mmdet - INFO - Epoch [1][650/7330] lr: 1.000e-04, eta: 21:00:51, time: 0.847, data_time: 0.049, memory: 11321, loss_rpn_cls: 0.0901, loss_rpn_bbox: 0.0886, loss_cls: 0.4360, acc: 90.7097, loss_bbox: 0.3290, loss_mask: 0.4747, loss: 1.4184 2024-06-05 00:43:49,075 - mmdet - INFO - Epoch [1][700/7330] lr: 1.000e-04, eta: 20:59:02, time: 0.856, data_time: 0.064, memory: 11321, loss_rpn_cls: 0.0842, loss_rpn_bbox: 0.0941, loss_cls: 0.4263, acc: 90.4709, loss_bbox: 0.3355, loss_mask: 0.4642, loss: 1.4043 2024-06-05 00:44:32,392 - mmdet - INFO - Epoch [1][750/7330] lr: 1.000e-04, eta: 20:58:22, time: 0.866, data_time: 0.057, memory: 11349, loss_rpn_cls: 0.0831, loss_rpn_bbox: 0.0922, loss_cls: 0.4104, acc: 90.3208, loss_bbox: 0.3419, loss_mask: 0.4674, loss: 1.3950 2024-06-05 00:45:18,590 - mmdet - INFO - Epoch [1][800/7330] lr: 1.000e-04, eta: 21:02:56, time: 0.924, data_time: 0.066, memory: 11349, loss_rpn_cls: 0.0834, loss_rpn_bbox: 0.0910, loss_cls: 0.4256, acc: 89.7073, loss_bbox: 0.3641, loss_mask: 0.4581, loss: 1.4221 2024-06-05 00:46:12,054 - mmdet - INFO - Epoch [1][850/7330] lr: 1.000e-04, eta: 21:19:17, time: 1.069, data_time: 0.065, memory: 11349, loss_rpn_cls: 0.0721, loss_rpn_bbox: 0.0869, loss_cls: 0.4144, acc: 89.7690, loss_bbox: 0.3587, loss_mask: 0.4417, loss: 1.3738 2024-06-05 00:46:55,343 - mmdet - INFO - Epoch [1][900/7330] lr: 1.000e-04, eta: 21:17:16, time: 0.865, data_time: 0.057, memory: 11349, loss_rpn_cls: 0.0756, loss_rpn_bbox: 0.0915, loss_cls: 0.3873, acc: 90.2239, loss_bbox: 0.3484, loss_mask: 0.4304, loss: 1.3332 2024-06-05 00:47:38,677 - mmdet - INFO - Epoch [1][950/7330] lr: 1.000e-04, eta: 21:15:32, time: 0.867, data_time: 0.055, memory: 11349, loss_rpn_cls: 0.0686, loss_rpn_bbox: 0.0818, loss_cls: 0.3763, acc: 90.3496, loss_bbox: 0.3396, loss_mask: 0.4237, loss: 1.2899 2024-06-05 00:48:21,975 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 00:48:21,975 - mmdet - INFO - Epoch [1][1000/7330] lr: 1.000e-04, eta: 21:13:49, time: 0.866, data_time: 0.045, memory: 11349, loss_rpn_cls: 0.0741, loss_rpn_bbox: 0.0865, loss_cls: 0.3855, acc: 89.7673, loss_bbox: 0.3605, loss_mask: 0.4260, loss: 1.3326 2024-06-05 00:49:04,974 - mmdet - INFO - Epoch [1][1050/7330] lr: 1.000e-04, eta: 21:11:46, time: 0.860, data_time: 0.058, memory: 11349, loss_rpn_cls: 0.0667, loss_rpn_bbox: 0.0808, loss_cls: 0.3747, acc: 89.8875, loss_bbox: 0.3658, loss_mask: 0.4151, loss: 1.3031 2024-06-05 00:49:48,158 - mmdet - INFO - Epoch [1][1100/7330] lr: 1.000e-04, eta: 21:10:06, time: 0.864, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0727, loss_rpn_bbox: 0.0855, loss_cls: 0.3695, acc: 89.8928, loss_bbox: 0.3597, loss_mask: 0.4161, loss: 1.3035 2024-06-05 00:50:31,173 - mmdet - INFO - Epoch [1][1150/7330] lr: 1.000e-04, eta: 21:08:18, time: 0.860, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0652, loss_rpn_bbox: 0.0813, loss_cls: 0.3674, acc: 89.8770, loss_bbox: 0.3595, loss_mask: 0.4036, loss: 1.2768 2024-06-05 00:51:13,838 - mmdet - INFO - Epoch [1][1200/7330] lr: 1.000e-04, eta: 21:06:09, time: 0.853, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0675, loss_rpn_bbox: 0.0849, loss_cls: 0.3725, acc: 89.6694, loss_bbox: 0.3685, loss_mask: 0.4140, loss: 1.3073 2024-06-05 00:51:57,201 - mmdet - INFO - Epoch [1][1250/7330] lr: 1.000e-04, eta: 21:04:57, time: 0.867, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0645, loss_rpn_bbox: 0.0825, loss_cls: 0.3578, acc: 89.9299, loss_bbox: 0.3571, loss_mask: 0.4095, loss: 1.2714 2024-06-05 00:52:40,644 - mmdet - INFO - Epoch [1][1300/7330] lr: 1.000e-04, eta: 21:03:52, time: 0.869, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0699, loss_rpn_bbox: 0.0852, loss_cls: 0.3654, acc: 89.6104, loss_bbox: 0.3680, loss_mask: 0.4093, loss: 1.2978 2024-06-05 00:53:24,138 - mmdet - INFO - Epoch [1][1350/7330] lr: 1.000e-04, eta: 21:02:51, time: 0.870, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0606, loss_rpn_bbox: 0.0793, loss_cls: 0.3407, acc: 90.2217, loss_bbox: 0.3504, loss_mask: 0.3963, loss: 1.2273 2024-06-05 00:54:21,810 - mmdet - INFO - Epoch [1][1400/7330] lr: 1.000e-04, eta: 21:16:29, time: 1.153, data_time: 0.320, memory: 11350, loss_rpn_cls: 0.0632, loss_rpn_bbox: 0.0815, loss_cls: 0.3539, acc: 89.7571, loss_bbox: 0.3646, loss_mask: 0.3925, loss: 1.2557 2024-06-05 00:55:05,289 - mmdet - INFO - Epoch [1][1450/7330] lr: 1.000e-04, eta: 21:14:59, time: 0.870, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0610, loss_rpn_bbox: 0.0877, loss_cls: 0.3544, acc: 89.5281, loss_bbox: 0.3757, loss_mask: 0.3867, loss: 1.2656 2024-06-05 00:55:48,703 - mmdet - INFO - Epoch [1][1500/7330] lr: 1.000e-04, eta: 21:13:28, time: 0.868, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0599, loss_rpn_bbox: 0.0820, loss_cls: 0.3568, acc: 89.6001, loss_bbox: 0.3705, loss_mask: 0.3952, loss: 1.2643 2024-06-05 00:56:31,620 - mmdet - INFO - Epoch [1][1550/7330] lr: 1.000e-04, eta: 21:11:34, time: 0.858, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0586, loss_rpn_bbox: 0.0759, loss_cls: 0.3478, acc: 89.8760, loss_bbox: 0.3581, loss_mask: 0.3826, loss: 1.2230 2024-06-05 00:57:14,065 - mmdet - INFO - Epoch [1][1600/7330] lr: 1.000e-04, eta: 21:09:17, time: 0.849, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0542, loss_rpn_bbox: 0.0719, loss_cls: 0.3219, acc: 90.4421, loss_bbox: 0.3424, loss_mask: 0.3704, loss: 1.1608 2024-06-05 00:57:56,995 - mmdet - INFO - Epoch [1][1650/7330] lr: 1.000e-04, eta: 21:07:31, time: 0.858, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0569, loss_rpn_bbox: 0.0764, loss_cls: 0.3258, acc: 90.4146, loss_bbox: 0.3442, loss_mask: 0.3694, loss: 1.1727 2024-06-05 00:58:39,727 - mmdet - INFO - Epoch [1][1700/7330] lr: 1.000e-04, eta: 21:05:41, time: 0.855, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0546, loss_rpn_bbox: 0.0772, loss_cls: 0.3378, acc: 89.9609, loss_bbox: 0.3551, loss_mask: 0.3673, loss: 1.1920 2024-06-05 00:59:22,680 - mmdet - INFO - Epoch [1][1750/7330] lr: 1.000e-04, eta: 21:04:05, time: 0.859, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0608, loss_rpn_bbox: 0.0781, loss_cls: 0.3521, acc: 89.5820, loss_bbox: 0.3658, loss_mask: 0.3876, loss: 1.2445 2024-06-05 01:00:05,587 - mmdet - INFO - Epoch [1][1800/7330] lr: 1.000e-04, eta: 21:02:29, time: 0.858, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0585, loss_rpn_bbox: 0.0751, loss_cls: 0.3315, acc: 89.9932, loss_bbox: 0.3574, loss_mask: 0.3688, loss: 1.1914 2024-06-05 01:00:48,573 - mmdet - INFO - Epoch [1][1850/7330] lr: 1.000e-04, eta: 21:01:00, time: 0.860, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0533, loss_rpn_bbox: 0.0789, loss_cls: 0.3300, acc: 89.9456, loss_bbox: 0.3546, loss_mask: 0.3716, loss: 1.1885 2024-06-05 01:01:44,181 - mmdet - INFO - Epoch [1][1900/7330] lr: 1.000e-04, eta: 21:09:05, time: 1.112, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0513, loss_rpn_bbox: 0.0716, loss_cls: 0.3128, acc: 90.4854, loss_bbox: 0.3361, loss_mask: 0.3656, loss: 1.1374 2024-06-05 01:02:27,816 - mmdet - INFO - Epoch [1][1950/7330] lr: 1.000e-04, eta: 21:07:53, time: 0.873, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0520, loss_rpn_bbox: 0.0762, loss_cls: 0.3365, acc: 89.6934, loss_bbox: 0.3667, loss_mask: 0.3680, loss: 1.1993 2024-06-05 01:03:11,693 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 01:03:11,693 - mmdet - INFO - Epoch [1][2000/7330] lr: 1.000e-04, eta: 21:06:54, time: 0.878, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0580, loss_rpn_bbox: 0.0798, loss_cls: 0.3328, acc: 89.7893, loss_bbox: 0.3619, loss_mask: 0.3573, loss: 1.1898 2024-06-05 01:03:54,691 - mmdet - INFO - Epoch [1][2050/7330] lr: 1.000e-04, eta: 21:05:19, time: 0.860, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0516, loss_rpn_bbox: 0.0750, loss_cls: 0.3213, acc: 90.1399, loss_bbox: 0.3534, loss_mask: 0.3528, loss: 1.1541 2024-06-05 01:04:37,996 - mmdet - INFO - Epoch [1][2100/7330] lr: 1.000e-04, eta: 21:03:59, time: 0.866, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0553, loss_rpn_bbox: 0.0769, loss_cls: 0.3220, acc: 90.0654, loss_bbox: 0.3507, loss_mask: 0.3628, loss: 1.1677 2024-06-05 01:05:21,327 - mmdet - INFO - Epoch [1][2150/7330] lr: 1.000e-04, eta: 21:02:42, time: 0.867, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0534, loss_rpn_bbox: 0.0772, loss_cls: 0.3147, acc: 90.1340, loss_bbox: 0.3521, loss_mask: 0.3561, loss: 1.1536 2024-06-05 01:06:04,165 - mmdet - INFO - Epoch [1][2200/7330] lr: 1.000e-04, eta: 21:01:06, time: 0.857, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0512, loss_rpn_bbox: 0.0749, loss_cls: 0.3053, acc: 90.6030, loss_bbox: 0.3364, loss_mask: 0.3537, loss: 1.1216 2024-06-05 01:06:48,244 - mmdet - INFO - Epoch [1][2250/7330] lr: 1.000e-04, eta: 21:00:21, time: 0.882, data_time: 0.072, memory: 11350, loss_rpn_cls: 0.0500, loss_rpn_bbox: 0.0759, loss_cls: 0.3212, acc: 90.0835, loss_bbox: 0.3530, loss_mask: 0.3473, loss: 1.1474 2024-06-05 01:07:31,256 - mmdet - INFO - Epoch [1][2300/7330] lr: 1.000e-04, eta: 20:58:56, time: 0.860, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0753, loss_cls: 0.3154, acc: 90.2214, loss_bbox: 0.3490, loss_mask: 0.3541, loss: 1.1427 2024-06-05 01:08:14,105 - mmdet - INFO - Epoch [1][2350/7330] lr: 1.000e-04, eta: 20:57:26, time: 0.857, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0524, loss_rpn_bbox: 0.0740, loss_cls: 0.3220, acc: 89.9846, loss_bbox: 0.3487, loss_mask: 0.3570, loss: 1.1540 2024-06-05 01:08:57,654 - mmdet - INFO - Epoch [1][2400/7330] lr: 1.000e-04, eta: 20:56:24, time: 0.871, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0528, loss_rpn_bbox: 0.0770, loss_cls: 0.3286, acc: 89.7942, loss_bbox: 0.3582, loss_mask: 0.3570, loss: 1.1736 2024-06-05 01:09:40,561 - mmdet - INFO - Epoch [1][2450/7330] lr: 1.000e-04, eta: 20:55:00, time: 0.858, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0478, loss_rpn_bbox: 0.0729, loss_cls: 0.3061, acc: 90.3398, loss_bbox: 0.3420, loss_mask: 0.3463, loss: 1.1151 2024-06-05 01:10:23,893 - mmdet - INFO - Epoch [1][2500/7330] lr: 1.000e-04, eta: 20:53:52, time: 0.867, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0526, loss_rpn_bbox: 0.0735, loss_cls: 0.3234, acc: 89.9194, loss_bbox: 0.3534, loss_mask: 0.3505, loss: 1.1533 2024-06-05 01:11:06,691 - mmdet - INFO - Epoch [1][2550/7330] lr: 1.000e-04, eta: 20:52:27, time: 0.856, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0458, loss_rpn_bbox: 0.0688, loss_cls: 0.3138, acc: 90.2036, loss_bbox: 0.3413, loss_mask: 0.3453, loss: 1.1150 2024-06-05 01:11:49,706 - mmdet - INFO - Epoch [1][2600/7330] lr: 1.000e-04, eta: 20:51:11, time: 0.860, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0457, loss_rpn_bbox: 0.0689, loss_cls: 0.3144, acc: 90.1204, loss_bbox: 0.3474, loss_mask: 0.3471, loss: 1.1236 2024-06-05 01:12:32,779 - mmdet - INFO - Epoch [1][2650/7330] lr: 1.000e-04, eta: 20:49:58, time: 0.861, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0494, loss_rpn_bbox: 0.0702, loss_cls: 0.2972, acc: 90.5264, loss_bbox: 0.3391, loss_mask: 0.3407, loss: 1.0966 2024-06-05 01:13:15,530 - mmdet - INFO - Epoch [1][2700/7330] lr: 1.000e-04, eta: 20:48:36, time: 0.855, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0491, loss_rpn_bbox: 0.0715, loss_cls: 0.3105, acc: 90.3274, loss_bbox: 0.3430, loss_mask: 0.3435, loss: 1.1176 2024-06-05 01:13:58,255 - mmdet - INFO - Epoch [1][2750/7330] lr: 1.000e-04, eta: 20:47:15, time: 0.854, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0453, loss_rpn_bbox: 0.0702, loss_cls: 0.2916, acc: 90.6589, loss_bbox: 0.3356, loss_mask: 0.3457, loss: 1.0884 2024-06-05 01:14:41,930 - mmdet - INFO - Epoch [1][2800/7330] lr: 1.000e-04, eta: 20:46:24, time: 0.873, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0449, loss_rpn_bbox: 0.0691, loss_cls: 0.3096, acc: 90.4226, loss_bbox: 0.3350, loss_mask: 0.3332, loss: 1.0918 2024-06-05 01:15:25,314 - mmdet - INFO - Epoch [1][2850/7330] lr: 1.000e-04, eta: 20:45:24, time: 0.868, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0459, loss_rpn_bbox: 0.0745, loss_cls: 0.3265, acc: 89.9399, loss_bbox: 0.3541, loss_mask: 0.3488, loss: 1.1498 2024-06-05 01:16:08,446 - mmdet - INFO - Epoch [1][2900/7330] lr: 1.000e-04, eta: 20:44:18, time: 0.863, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0694, loss_cls: 0.2967, acc: 90.7061, loss_bbox: 0.3271, loss_mask: 0.3297, loss: 1.0686 2024-06-05 01:16:59,887 - mmdet - INFO - Epoch [1][2950/7330] lr: 1.000e-04, eta: 20:47:11, time: 1.028, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0495, loss_rpn_bbox: 0.0733, loss_cls: 0.3086, acc: 90.2529, loss_bbox: 0.3443, loss_mask: 0.3353, loss: 1.1110 2024-06-05 01:17:47,414 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 01:17:47,414 - mmdet - INFO - Epoch [1][3000/7330] lr: 1.000e-04, eta: 20:48:07, time: 0.951, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0462, loss_rpn_bbox: 0.0702, loss_cls: 0.3083, acc: 90.2673, loss_bbox: 0.3337, loss_mask: 0.3363, loss: 1.0947 2024-06-05 01:18:30,486 - mmdet - INFO - Epoch [1][3050/7330] lr: 1.000e-04, eta: 20:46:55, time: 0.861, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0437, loss_rpn_bbox: 0.0665, loss_cls: 0.2974, acc: 90.5662, loss_bbox: 0.3328, loss_mask: 0.3288, loss: 1.0693 2024-06-05 01:19:13,566 - mmdet - INFO - Epoch [1][3100/7330] lr: 1.000e-04, eta: 20:45:44, time: 0.862, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0463, loss_rpn_bbox: 0.0729, loss_cls: 0.3029, acc: 90.5007, loss_bbox: 0.3330, loss_mask: 0.3356, loss: 1.0908 2024-06-05 01:19:57,600 - mmdet - INFO - Epoch [1][3150/7330] lr: 1.000e-04, eta: 20:45:00, time: 0.881, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0470, loss_rpn_bbox: 0.0710, loss_cls: 0.3135, acc: 90.0862, loss_bbox: 0.3466, loss_mask: 0.3314, loss: 1.1095 2024-06-05 01:20:40,980 - mmdet - INFO - Epoch [1][3200/7330] lr: 1.000e-04, eta: 20:43:58, time: 0.868, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0692, loss_cls: 0.2913, acc: 90.6799, loss_bbox: 0.3302, loss_mask: 0.3308, loss: 1.0700 2024-06-05 01:21:23,841 - mmdet - INFO - Epoch [1][3250/7330] lr: 1.000e-04, eta: 20:42:44, time: 0.857, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0439, loss_rpn_bbox: 0.0680, loss_cls: 0.2849, acc: 90.8801, loss_bbox: 0.3276, loss_mask: 0.3326, loss: 1.0570 2024-06-05 01:22:06,738 - mmdet - INFO - Epoch [1][3300/7330] lr: 1.000e-04, eta: 20:41:31, time: 0.858, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0476, loss_rpn_bbox: 0.0692, loss_cls: 0.3054, acc: 90.1819, loss_bbox: 0.3476, loss_mask: 0.3285, loss: 1.0983 2024-06-05 01:22:50,352 - mmdet - INFO - Epoch [1][3350/7330] lr: 1.000e-04, eta: 20:40:38, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0463, loss_rpn_bbox: 0.0743, loss_cls: 0.3077, acc: 90.2651, loss_bbox: 0.3427, loss_mask: 0.3342, loss: 1.1052 2024-06-05 01:23:33,955 - mmdet - INFO - Epoch [1][3400/7330] lr: 1.000e-04, eta: 20:39:44, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0452, loss_rpn_bbox: 0.0712, loss_cls: 0.2933, acc: 90.8435, loss_bbox: 0.3233, loss_mask: 0.3354, loss: 1.0684 2024-06-05 01:24:16,936 - mmdet - INFO - Epoch [1][3450/7330] lr: 1.000e-04, eta: 20:38:36, time: 0.860, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0434, loss_rpn_bbox: 0.0695, loss_cls: 0.2836, acc: 90.8286, loss_bbox: 0.3276, loss_mask: 0.3278, loss: 1.0519 2024-06-05 01:25:00,378 - mmdet - INFO - Epoch [1][3500/7330] lr: 1.000e-04, eta: 20:37:39, time: 0.869, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0440, loss_rpn_bbox: 0.0723, loss_cls: 0.2987, acc: 90.3120, loss_bbox: 0.3446, loss_mask: 0.3281, loss: 1.0877 2024-06-05 01:25:43,351 - mmdet - INFO - Epoch [1][3550/7330] lr: 1.000e-04, eta: 20:36:31, time: 0.859, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0659, loss_cls: 0.2959, acc: 90.6846, loss_bbox: 0.3279, loss_mask: 0.3274, loss: 1.0615 2024-06-05 01:26:26,754 - mmdet - INFO - Epoch [1][3600/7330] lr: 1.000e-04, eta: 20:35:34, time: 0.868, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0458, loss_rpn_bbox: 0.0709, loss_cls: 0.2948, acc: 90.7947, loss_bbox: 0.3320, loss_mask: 0.3227, loss: 1.0661 2024-06-05 01:27:10,103 - mmdet - INFO - Epoch [1][3650/7330] lr: 1.000e-04, eta: 20:34:37, time: 0.867, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0406, loss_rpn_bbox: 0.0669, loss_cls: 0.2932, acc: 90.4031, loss_bbox: 0.3366, loss_mask: 0.3260, loss: 1.0632 2024-06-05 01:27:53,451 - mmdet - INFO - Epoch [1][3700/7330] lr: 1.000e-04, eta: 20:33:39, time: 0.867, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0670, loss_cls: 0.2884, acc: 90.8918, loss_bbox: 0.3249, loss_mask: 0.3189, loss: 1.0477 2024-06-05 01:28:36,768 - mmdet - INFO - Epoch [1][3750/7330] lr: 1.000e-04, eta: 20:32:42, time: 0.867, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0461, loss_rpn_bbox: 0.0697, loss_cls: 0.2917, acc: 90.6113, loss_bbox: 0.3290, loss_mask: 0.3205, loss: 1.0568 2024-06-05 01:29:20,583 - mmdet - INFO - Epoch [1][3800/7330] lr: 1.000e-04, eta: 20:31:56, time: 0.876, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0439, loss_rpn_bbox: 0.0682, loss_cls: 0.3078, acc: 90.1699, loss_bbox: 0.3415, loss_mask: 0.3206, loss: 1.0819 2024-06-05 01:30:03,686 - mmdet - INFO - Epoch [1][3850/7330] lr: 1.000e-04, eta: 20:30:55, time: 0.862, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0432, loss_rpn_bbox: 0.0678, loss_cls: 0.2942, acc: 90.4797, loss_bbox: 0.3361, loss_mask: 0.3225, loss: 1.0637 2024-06-05 01:30:47,213 - mmdet - INFO - Epoch [1][3900/7330] lr: 1.000e-04, eta: 20:30:02, time: 0.871, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0432, loss_rpn_bbox: 0.0698, loss_cls: 0.2950, acc: 90.5063, loss_bbox: 0.3325, loss_mask: 0.3269, loss: 1.0674 2024-06-05 01:31:30,427 - mmdet - INFO - Epoch [1][3950/7330] lr: 1.000e-04, eta: 20:29:04, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0667, loss_cls: 0.2883, acc: 90.8032, loss_bbox: 0.3201, loss_mask: 0.3183, loss: 1.0369 2024-06-05 01:32:15,662 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 01:32:15,662 - mmdet - INFO - Epoch [1][4000/7330] lr: 1.000e-04, eta: 20:28:48, time: 0.905, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0447, loss_rpn_bbox: 0.0689, loss_cls: 0.2900, acc: 90.6987, loss_bbox: 0.3277, loss_mask: 0.3212, loss: 1.0524 2024-06-05 01:33:07,339 - mmdet - INFO - Epoch [1][4050/7330] lr: 1.000e-04, eta: 20:30:45, time: 1.034, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0427, loss_rpn_bbox: 0.0652, loss_cls: 0.2815, acc: 91.0796, loss_bbox: 0.3132, loss_mask: 0.3125, loss: 1.0152 2024-06-05 01:33:50,367 - mmdet - INFO - Epoch [1][4100/7330] lr: 1.000e-04, eta: 20:29:41, time: 0.861, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0637, loss_cls: 0.2851, acc: 90.7878, loss_bbox: 0.3245, loss_mask: 0.3160, loss: 1.0313 2024-06-05 01:34:33,838 - mmdet - INFO - Epoch [1][4150/7330] lr: 1.000e-04, eta: 20:28:47, time: 0.869, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0388, loss_rpn_bbox: 0.0659, loss_cls: 0.2778, acc: 91.0688, loss_bbox: 0.3164, loss_mask: 0.3152, loss: 1.0141 2024-06-05 01:35:17,132 - mmdet - INFO - Epoch [1][4200/7330] lr: 1.000e-04, eta: 20:27:49, time: 0.866, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0664, loss_cls: 0.2812, acc: 90.9019, loss_bbox: 0.3169, loss_mask: 0.3167, loss: 1.0241 2024-06-05 01:36:00,480 - mmdet - INFO - Epoch [1][4250/7330] lr: 1.000e-04, eta: 20:26:53, time: 0.867, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0643, loss_cls: 0.2743, acc: 90.9971, loss_bbox: 0.3202, loss_mask: 0.3120, loss: 1.0091 2024-06-05 01:36:43,908 - mmdet - INFO - Epoch [1][4300/7330] lr: 1.000e-04, eta: 20:25:58, time: 0.868, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0633, loss_cls: 0.2726, acc: 91.0669, loss_bbox: 0.3194, loss_mask: 0.3152, loss: 1.0100 2024-06-05 01:37:27,215 - mmdet - INFO - Epoch [1][4350/7330] lr: 1.000e-04, eta: 20:25:02, time: 0.867, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0669, loss_cls: 0.2953, acc: 90.4385, loss_bbox: 0.3295, loss_mask: 0.3206, loss: 1.0569 2024-06-05 01:38:10,597 - mmdet - INFO - Epoch [1][4400/7330] lr: 1.000e-04, eta: 20:24:07, time: 0.868, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0696, loss_cls: 0.2829, acc: 91.0051, loss_bbox: 0.3175, loss_mask: 0.3126, loss: 1.0272 2024-06-05 01:38:53,773 - mmdet - INFO - Epoch [1][4450/7330] lr: 1.000e-04, eta: 20:23:08, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0619, loss_cls: 0.3008, acc: 90.3772, loss_bbox: 0.3348, loss_mask: 0.3195, loss: 1.0572 2024-06-05 01:39:37,051 - mmdet - INFO - Epoch [1][4500/7330] lr: 1.000e-04, eta: 20:22:12, time: 0.866, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0658, loss_cls: 0.2891, acc: 90.7500, loss_bbox: 0.3267, loss_mask: 0.3154, loss: 1.0405 2024-06-05 01:40:20,619 - mmdet - INFO - Epoch [1][4550/7330] lr: 1.000e-04, eta: 20:21:22, time: 0.871, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0436, loss_rpn_bbox: 0.0676, loss_cls: 0.3018, acc: 90.3096, loss_bbox: 0.3387, loss_mask: 0.3159, loss: 1.0676 2024-06-05 01:41:04,273 - mmdet - INFO - Epoch [1][4600/7330] lr: 1.000e-04, eta: 20:20:33, time: 0.873, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0694, loss_cls: 0.2895, acc: 90.7446, loss_bbox: 0.3263, loss_mask: 0.3186, loss: 1.0458 2024-06-05 01:41:47,279 - mmdet - INFO - Epoch [1][4650/7330] lr: 1.000e-04, eta: 20:19:32, time: 0.860, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0428, loss_rpn_bbox: 0.0672, loss_cls: 0.2832, acc: 90.8572, loss_bbox: 0.3223, loss_mask: 0.3239, loss: 1.0395 2024-06-05 01:42:30,530 - mmdet - INFO - Epoch [1][4700/7330] lr: 1.000e-04, eta: 20:18:37, time: 0.865, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0619, loss_cls: 0.2827, acc: 90.8259, loss_bbox: 0.3212, loss_mask: 0.3120, loss: 1.0190 2024-06-05 01:43:13,931 - mmdet - INFO - Epoch [1][4750/7330] lr: 1.000e-04, eta: 20:17:44, time: 0.868, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0404, loss_rpn_bbox: 0.0665, loss_cls: 0.2923, acc: 90.5291, loss_bbox: 0.3265, loss_mask: 0.3098, loss: 1.0357 2024-06-05 01:43:56,750 - mmdet - INFO - Epoch [1][4800/7330] lr: 1.000e-04, eta: 20:16:41, time: 0.856, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0643, loss_cls: 0.2762, acc: 91.0898, loss_bbox: 0.3130, loss_mask: 0.3065, loss: 1.0003 2024-06-05 01:44:39,727 - mmdet - INFO - Epoch [1][4850/7330] lr: 1.000e-04, eta: 20:15:41, time: 0.860, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0389, loss_rpn_bbox: 0.0640, loss_cls: 0.2759, acc: 90.8325, loss_bbox: 0.3206, loss_mask: 0.3135, loss: 1.0129 2024-06-05 01:45:22,769 - mmdet - INFO - Epoch [1][4900/7330] lr: 1.000e-04, eta: 20:14:43, time: 0.861, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0371, loss_rpn_bbox: 0.0643, loss_cls: 0.2740, acc: 91.0012, loss_bbox: 0.3128, loss_mask: 0.3086, loss: 0.9969 2024-06-05 01:46:05,773 - mmdet - INFO - Epoch [1][4950/7330] lr: 1.000e-04, eta: 20:13:45, time: 0.860, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0417, loss_rpn_bbox: 0.0633, loss_cls: 0.2749, acc: 91.0239, loss_bbox: 0.3170, loss_mask: 0.3113, loss: 1.0082 2024-06-05 01:46:49,351 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 01:46:49,352 - mmdet - INFO - Epoch [1][5000/7330] lr: 1.000e-04, eta: 20:12:56, time: 0.872, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0432, loss_rpn_bbox: 0.0669, loss_cls: 0.2888, acc: 90.5537, loss_bbox: 0.3245, loss_mask: 0.3123, loss: 1.0356 2024-06-05 01:47:32,378 - mmdet - INFO - Epoch [1][5050/7330] lr: 1.000e-04, eta: 20:11:59, time: 0.860, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0391, loss_rpn_bbox: 0.0623, loss_cls: 0.2750, acc: 91.0554, loss_bbox: 0.3146, loss_mask: 0.3006, loss: 0.9916 2024-06-05 01:48:26,818 - mmdet - INFO - Epoch [1][5100/7330] lr: 1.000e-04, eta: 20:14:07, time: 1.089, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0636, loss_cls: 0.2812, acc: 90.9399, loss_bbox: 0.3162, loss_mask: 0.3096, loss: 1.0127 2024-06-05 01:49:10,190 - mmdet - INFO - Epoch [1][5150/7330] lr: 1.000e-04, eta: 20:13:13, time: 0.867, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0397, loss_rpn_bbox: 0.0656, loss_cls: 0.2879, acc: 90.5552, loss_bbox: 0.3336, loss_mask: 0.3152, loss: 1.0419 2024-06-05 01:49:53,103 - mmdet - INFO - Epoch [1][5200/7330] lr: 1.000e-04, eta: 20:12:13, time: 0.858, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0602, loss_cls: 0.2704, acc: 91.1833, loss_bbox: 0.3093, loss_mask: 0.3103, loss: 0.9854 2024-06-05 01:50:36,606 - mmdet - INFO - Epoch [1][5250/7330] lr: 1.000e-04, eta: 20:11:22, time: 0.870, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0384, loss_rpn_bbox: 0.0650, loss_cls: 0.2790, acc: 90.9438, loss_bbox: 0.3169, loss_mask: 0.3105, loss: 1.0098 2024-06-05 01:51:19,710 - mmdet - INFO - Epoch [1][5300/7330] lr: 1.000e-04, eta: 20:10:25, time: 0.862, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0630, loss_cls: 0.2646, acc: 91.2993, loss_bbox: 0.3120, loss_mask: 0.3150, loss: 0.9942 2024-06-05 01:52:03,146 - mmdet - INFO - Epoch [1][5350/7330] lr: 1.000e-04, eta: 20:09:33, time: 0.869, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0639, loss_cls: 0.2904, acc: 90.5103, loss_bbox: 0.3331, loss_mask: 0.3114, loss: 1.0389 2024-06-05 01:52:46,204 - mmdet - INFO - Epoch [1][5400/7330] lr: 1.000e-04, eta: 20:08:36, time: 0.861, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0407, loss_rpn_bbox: 0.0618, loss_cls: 0.2674, acc: 91.3171, loss_bbox: 0.3062, loss_mask: 0.3045, loss: 0.9806 2024-06-05 01:53:29,515 - mmdet - INFO - Epoch [1][5450/7330] lr: 1.000e-04, eta: 20:07:43, time: 0.866, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0411, loss_rpn_bbox: 0.0640, loss_cls: 0.2784, acc: 90.9277, loss_bbox: 0.3227, loss_mask: 0.3082, loss: 1.0144 2024-06-05 01:54:12,766 - mmdet - INFO - Epoch [1][5500/7330] lr: 1.000e-04, eta: 20:06:49, time: 0.865, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0380, loss_rpn_bbox: 0.0621, loss_cls: 0.2632, acc: 91.3281, loss_bbox: 0.3109, loss_mask: 0.3019, loss: 0.9762 2024-06-05 01:54:55,726 - mmdet - INFO - Epoch [1][5550/7330] lr: 1.000e-04, eta: 20:05:51, time: 0.860, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0593, loss_cls: 0.2759, acc: 91.1084, loss_bbox: 0.3080, loss_mask: 0.3073, loss: 0.9906 2024-06-05 01:55:39,579 - mmdet - INFO - Epoch [1][5600/7330] lr: 1.000e-04, eta: 20:05:07, time: 0.877, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0376, loss_rpn_bbox: 0.0624, loss_cls: 0.2808, acc: 90.8120, loss_bbox: 0.3213, loss_mask: 0.3096, loss: 1.0117 2024-06-05 01:56:22,490 - mmdet - INFO - Epoch [1][5650/7330] lr: 1.000e-04, eta: 20:04:09, time: 0.858, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0635, loss_cls: 0.2684, acc: 91.0618, loss_bbox: 0.3126, loss_mask: 0.3093, loss: 0.9916 2024-06-05 01:57:05,606 - mmdet - INFO - Epoch [1][5700/7330] lr: 1.000e-04, eta: 20:03:14, time: 0.862, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0637, loss_cls: 0.2630, acc: 91.2979, loss_bbox: 0.3097, loss_mask: 0.3019, loss: 0.9809 2024-06-05 01:57:48,472 - mmdet - INFO - Epoch [1][5750/7330] lr: 1.000e-04, eta: 20:02:15, time: 0.857, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0607, loss_cls: 0.2757, acc: 90.8271, loss_bbox: 0.3166, loss_mask: 0.3089, loss: 0.9960 2024-06-05 01:58:31,709 - mmdet - INFO - Epoch [1][5800/7330] lr: 1.000e-04, eta: 20:01:22, time: 0.865, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0637, loss_cls: 0.2675, acc: 91.0535, loss_bbox: 0.3143, loss_mask: 0.3041, loss: 0.9895 2024-06-05 01:59:15,480 - mmdet - INFO - Epoch [1][5850/7330] lr: 1.000e-04, eta: 20:00:37, time: 0.875, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0600, loss_cls: 0.2646, acc: 91.3206, loss_bbox: 0.3052, loss_mask: 0.3029, loss: 0.9705 2024-06-05 01:59:58,491 - mmdet - INFO - Epoch [1][5900/7330] lr: 1.000e-04, eta: 19:59:41, time: 0.860, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0623, loss_cls: 0.2732, acc: 91.2268, loss_bbox: 0.3072, loss_mask: 0.3013, loss: 0.9792 2024-06-05 02:00:41,797 - mmdet - INFO - Epoch [1][5950/7330] lr: 1.000e-04, eta: 19:58:49, time: 0.866, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0396, loss_rpn_bbox: 0.0645, loss_cls: 0.2778, acc: 90.9224, loss_bbox: 0.3156, loss_mask: 0.3030, loss: 1.0006 2024-06-05 02:01:25,075 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 02:01:25,075 - mmdet - INFO - Epoch [1][6000/7330] lr: 1.000e-04, eta: 19:57:58, time: 0.866, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0616, loss_cls: 0.2702, acc: 91.2043, loss_bbox: 0.3079, loss_mask: 0.3045, loss: 0.9843 2024-06-05 02:02:08,641 - mmdet - INFO - Epoch [1][6050/7330] lr: 1.000e-04, eta: 19:57:10, time: 0.871, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0382, loss_rpn_bbox: 0.0624, loss_cls: 0.2748, acc: 90.9648, loss_bbox: 0.3161, loss_mask: 0.3101, loss: 1.0016 2024-06-05 02:02:51,890 - mmdet - INFO - Epoch [1][6100/7330] lr: 1.000e-04, eta: 19:56:18, time: 0.865, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0624, loss_cls: 0.2677, acc: 91.2798, loss_bbox: 0.3026, loss_mask: 0.3011, loss: 0.9738 2024-06-05 02:03:40,875 - mmdet - INFO - Epoch [1][6150/7330] lr: 1.000e-04, eta: 19:56:43, time: 0.980, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0620, loss_cls: 0.2670, acc: 91.3596, loss_bbox: 0.3017, loss_mask: 0.3027, loss: 0.9754 2024-06-05 02:04:28,908 - mmdet - INFO - Epoch [1][6200/7330] lr: 1.000e-04, eta: 19:56:54, time: 0.961, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0375, loss_rpn_bbox: 0.0647, loss_cls: 0.2656, acc: 91.2146, loss_bbox: 0.3058, loss_mask: 0.3064, loss: 0.9800 2024-06-05 02:05:12,333 - mmdet - INFO - Epoch [1][6250/7330] lr: 1.000e-04, eta: 19:56:03, time: 0.868, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0393, loss_rpn_bbox: 0.0607, loss_cls: 0.2685, acc: 91.1711, loss_bbox: 0.3029, loss_mask: 0.3040, loss: 0.9753 2024-06-05 02:05:55,429 - mmdet - INFO - Epoch [1][6300/7330] lr: 1.000e-04, eta: 19:55:09, time: 0.862, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0621, loss_cls: 0.2816, acc: 90.6582, loss_bbox: 0.3287, loss_mask: 0.3078, loss: 1.0223 2024-06-05 02:06:38,403 - mmdet - INFO - Epoch [1][6350/7330] lr: 1.000e-04, eta: 19:54:13, time: 0.859, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0377, loss_rpn_bbox: 0.0640, loss_cls: 0.2631, acc: 91.4521, loss_bbox: 0.2994, loss_mask: 0.2966, loss: 0.9608 2024-06-05 02:07:21,493 - mmdet - INFO - Epoch [1][6400/7330] lr: 1.000e-04, eta: 19:53:19, time: 0.862, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0600, loss_cls: 0.2718, acc: 91.0781, loss_bbox: 0.3123, loss_mask: 0.3017, loss: 0.9826 2024-06-05 02:08:04,113 - mmdet - INFO - Epoch [1][6450/7330] lr: 1.000e-04, eta: 19:52:19, time: 0.852, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0592, loss_cls: 0.2507, acc: 91.7356, loss_bbox: 0.2933, loss_mask: 0.2931, loss: 0.9306 2024-06-05 02:08:46,971 - mmdet - INFO - Epoch [1][6500/7330] lr: 1.000e-04, eta: 19:51:22, time: 0.858, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0602, loss_cls: 0.2647, acc: 91.1924, loss_bbox: 0.3089, loss_mask: 0.3019, loss: 0.9725 2024-06-05 02:09:29,956 - mmdet - INFO - Epoch [1][6550/7330] lr: 1.000e-04, eta: 19:50:27, time: 0.860, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0365, loss_rpn_bbox: 0.0632, loss_cls: 0.2766, acc: 91.1182, loss_bbox: 0.3085, loss_mask: 0.2992, loss: 0.9840 2024-06-05 02:10:12,735 - mmdet - INFO - Epoch [1][6600/7330] lr: 1.000e-04, eta: 19:49:30, time: 0.856, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0578, loss_cls: 0.2701, acc: 91.3799, loss_bbox: 0.3009, loss_mask: 0.3000, loss: 0.9669 2024-06-05 02:10:55,319 - mmdet - INFO - Epoch [1][6650/7330] lr: 1.000e-04, eta: 19:48:30, time: 0.852, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0384, loss_rpn_bbox: 0.0587, loss_cls: 0.2640, acc: 91.2219, loss_bbox: 0.3049, loss_mask: 0.2955, loss: 0.9615 2024-06-05 02:11:38,364 - mmdet - INFO - Epoch [1][6700/7330] lr: 1.000e-04, eta: 19:47:37, time: 0.861, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0358, loss_rpn_bbox: 0.0610, loss_cls: 0.2781, acc: 90.9563, loss_bbox: 0.3054, loss_mask: 0.3009, loss: 0.9812 2024-06-05 02:12:21,181 - mmdet - INFO - Epoch [1][6750/7330] lr: 1.000e-04, eta: 19:46:41, time: 0.856, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0581, loss_cls: 0.2567, acc: 91.5552, loss_bbox: 0.2969, loss_mask: 0.2968, loss: 0.9455 2024-06-05 02:13:04,501 - mmdet - INFO - Epoch [1][6800/7330] lr: 1.000e-04, eta: 19:45:50, time: 0.866, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0389, loss_rpn_bbox: 0.0643, loss_cls: 0.2779, acc: 90.9360, loss_bbox: 0.3173, loss_mask: 0.2987, loss: 0.9972 2024-06-05 02:13:47,561 - mmdet - INFO - Epoch [1][6850/7330] lr: 1.000e-04, eta: 19:44:57, time: 0.861, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0604, loss_cls: 0.2643, acc: 91.3899, loss_bbox: 0.2995, loss_mask: 0.3039, loss: 0.9653 2024-06-05 02:14:30,776 - mmdet - INFO - Epoch [1][6900/7330] lr: 1.000e-04, eta: 19:44:06, time: 0.864, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0603, loss_cls: 0.2774, acc: 90.9487, loss_bbox: 0.3170, loss_mask: 0.3077, loss: 0.9998 2024-06-05 02:15:13,420 - mmdet - INFO - Epoch [1][6950/7330] lr: 1.000e-04, eta: 19:43:09, time: 0.853, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0577, loss_cls: 0.2577, acc: 91.5991, loss_bbox: 0.2927, loss_mask: 0.2987, loss: 0.9410 2024-06-05 02:15:56,232 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 02:15:56,232 - mmdet - INFO - Epoch [1][7000/7330] lr: 1.000e-04, eta: 19:42:13, time: 0.856, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0612, loss_cls: 0.2695, acc: 91.2263, loss_bbox: 0.3066, loss_mask: 0.2994, loss: 0.9734 2024-06-05 02:16:39,552 - mmdet - INFO - Epoch [1][7050/7330] lr: 1.000e-04, eta: 19:41:24, time: 0.866, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0649, loss_cls: 0.2678, acc: 91.1343, loss_bbox: 0.3049, loss_mask: 0.2936, loss: 0.9693 2024-06-05 02:17:22,570 - mmdet - INFO - Epoch [1][7100/7330] lr: 1.000e-04, eta: 19:40:31, time: 0.860, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0593, loss_cls: 0.2607, acc: 91.2388, loss_bbox: 0.3123, loss_mask: 0.3025, loss: 0.9715 2024-06-05 02:18:05,559 - mmdet - INFO - Epoch [1][7150/7330] lr: 1.000e-04, eta: 19:39:38, time: 0.860, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0602, loss_cls: 0.2714, acc: 91.0637, loss_bbox: 0.3068, loss_mask: 0.3006, loss: 0.9733 2024-06-05 02:18:50,900 - mmdet - INFO - Epoch [1][7200/7330] lr: 1.000e-04, eta: 19:39:12, time: 0.907, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0615, loss_cls: 0.2751, acc: 91.0911, loss_bbox: 0.3104, loss_mask: 0.3014, loss: 0.9847 2024-06-05 02:19:41,886 - mmdet - INFO - Epoch [1][7250/7330] lr: 1.000e-04, eta: 19:39:48, time: 1.020, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0599, loss_cls: 0.2666, acc: 91.0676, loss_bbox: 0.3145, loss_mask: 0.2985, loss: 0.9776 2024-06-05 02:20:25,130 - mmdet - INFO - Epoch [1][7300/7330] lr: 1.000e-04, eta: 19:38:57, time: 0.865, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0353, loss_rpn_bbox: 0.0589, loss_cls: 0.2642, acc: 91.2932, loss_bbox: 0.2998, loss_mask: 0.2901, loss: 0.9484 2024-06-05 02:20:52,308 - mmdet - INFO - Saving checkpoint at 1 epochs 2024-06-05 02:22:39,905 - mmdet - INFO - Evaluating bbox... 2024-06-05 02:23:09,073 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.318 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.563 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.326 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.169 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.347 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.466 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.247 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.487 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.617 2024-06-05 02:23:09,074 - mmdet - INFO - Evaluating segm... 2024-06-05 02:23:39,024 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.309 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.529 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.320 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.119 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.333 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.517 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.424 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.424 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.424 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.203 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.469 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.626 2024-06-05 02:23:39,598 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 02:23:39,598 - mmdet - INFO - Epoch(val) [1][625] bbox_mAP: 0.3180, bbox_mAP_50: 0.5630, bbox_mAP_75: 0.3260, bbox_mAP_s: 0.1690, bbox_mAP_m: 0.3470, bbox_mAP_l: 0.4660, bbox_mAP_copypaste: 0.318 0.563 0.326 0.169 0.347 0.466, segm_mAP: 0.3090, segm_mAP_50: 0.5290, segm_mAP_75: 0.3200, segm_mAP_s: 0.1190, segm_mAP_m: 0.3330, segm_mAP_l: 0.5170, segm_mAP_copypaste: 0.309 0.529 0.320 0.119 0.333 0.517 2024-06-05 02:24:28,177 - mmdet - INFO - Epoch [2][50/7330] lr: 1.000e-04, eta: 19:33:51, time: 0.971, data_time: 0.116, memory: 11350, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0567, loss_cls: 0.2497, acc: 91.5869, loss_bbox: 0.2956, loss_mask: 0.2888, loss: 0.9270 2024-06-05 02:25:11,841 - mmdet - INFO - Epoch [2][100/7330] lr: 1.000e-04, eta: 19:33:07, time: 0.873, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0621, loss_cls: 0.2462, acc: 91.6746, loss_bbox: 0.2927, loss_mask: 0.2877, loss: 0.9216 2024-06-05 02:25:55,285 - mmdet - INFO - Epoch [2][150/7330] lr: 1.000e-04, eta: 19:32:21, time: 0.869, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0597, loss_cls: 0.2495, acc: 91.4968, loss_bbox: 0.2935, loss_mask: 0.2911, loss: 0.9283 2024-06-05 02:26:39,300 - mmdet - INFO - Epoch [2][200/7330] lr: 1.000e-04, eta: 19:31:40, time: 0.880, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0636, loss_cls: 0.2558, acc: 91.3367, loss_bbox: 0.3117, loss_mask: 0.2961, loss: 0.9623 2024-06-05 02:27:22,612 - mmdet - INFO - Epoch [2][250/7330] lr: 1.000e-04, eta: 19:30:53, time: 0.866, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0567, loss_cls: 0.2544, acc: 91.4890, loss_bbox: 0.3041, loss_mask: 0.2967, loss: 0.9450 2024-06-05 02:28:11,024 - mmdet - INFO - Epoch [2][300/7330] lr: 1.000e-04, eta: 19:30:58, time: 0.968, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0580, loss_cls: 0.2506, acc: 91.5957, loss_bbox: 0.2941, loss_mask: 0.2952, loss: 0.9296 2024-06-05 02:29:09,307 - mmdet - INFO - Epoch [2][350/7330] lr: 1.000e-04, eta: 19:32:47, time: 1.166, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0558, loss_cls: 0.2497, acc: 91.6309, loss_bbox: 0.2940, loss_mask: 0.2923, loss: 0.9253 2024-06-05 02:29:53,034 - mmdet - INFO - Epoch [2][400/7330] lr: 1.000e-04, eta: 19:32:02, time: 0.875, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0354, loss_rpn_bbox: 0.0616, loss_cls: 0.2584, acc: 91.2268, loss_bbox: 0.3069, loss_mask: 0.2897, loss: 0.9519 2024-06-05 02:30:37,710 - mmdet - INFO - Epoch [2][450/7330] lr: 1.000e-04, eta: 19:31:27, time: 0.894, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0345, loss_rpn_bbox: 0.0605, loss_cls: 0.2530, acc: 91.4299, loss_bbox: 0.3016, loss_mask: 0.2894, loss: 0.9392 2024-06-05 02:31:20,432 - mmdet - INFO - Epoch [2][500/7330] lr: 1.000e-04, eta: 19:30:32, time: 0.854, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0536, loss_cls: 0.2384, acc: 92.0437, loss_bbox: 0.2785, loss_mask: 0.2753, loss: 0.8751 2024-06-05 02:32:03,622 - mmdet - INFO - Epoch [2][550/7330] lr: 1.000e-04, eta: 19:29:42, time: 0.864, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0566, loss_cls: 0.2498, acc: 91.6821, loss_bbox: 0.2879, loss_mask: 0.2836, loss: 0.9113 2024-06-05 02:32:46,885 - mmdet - INFO - Epoch [2][600/7330] lr: 1.000e-04, eta: 19:28:52, time: 0.865, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0597, loss_cls: 0.2514, acc: 91.6270, loss_bbox: 0.2969, loss_mask: 0.2865, loss: 0.9273 2024-06-05 02:33:30,744 - mmdet - INFO - Epoch [2][650/7330] lr: 1.000e-04, eta: 19:28:09, time: 0.877, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0593, loss_cls: 0.2583, acc: 91.3381, loss_bbox: 0.3065, loss_mask: 0.2934, loss: 0.9526 2024-06-05 02:34:14,459 - mmdet - INFO - Epoch [2][700/7330] lr: 1.000e-04, eta: 19:27:24, time: 0.874, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0632, loss_cls: 0.2583, acc: 91.3425, loss_bbox: 0.3057, loss_mask: 0.2926, loss: 0.9568 2024-06-05 02:34:58,414 - mmdet - INFO - Epoch [2][750/7330] lr: 1.000e-04, eta: 19:26:41, time: 0.879, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0612, loss_cls: 0.2577, acc: 91.2773, loss_bbox: 0.3081, loss_mask: 0.2904, loss: 0.9500 2024-06-05 02:35:41,715 - mmdet - INFO - Epoch [2][800/7330] lr: 1.000e-04, eta: 19:25:53, time: 0.866, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0585, loss_cls: 0.2562, acc: 91.4084, loss_bbox: 0.3011, loss_mask: 0.2887, loss: 0.9380 2024-06-05 02:36:25,736 - mmdet - INFO - Epoch [2][850/7330] lr: 1.000e-04, eta: 19:25:11, time: 0.880, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0596, loss_cls: 0.2509, acc: 91.6604, loss_bbox: 0.2916, loss_mask: 0.2904, loss: 0.9257 2024-06-05 02:37:09,684 - mmdet - INFO - Epoch [2][900/7330] lr: 1.000e-04, eta: 19:24:28, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0598, loss_cls: 0.2428, acc: 91.8113, loss_bbox: 0.2873, loss_mask: 0.2859, loss: 0.9081 2024-06-05 02:37:52,945 - mmdet - INFO - Epoch [2][950/7330] lr: 1.000e-04, eta: 19:23:39, time: 0.865, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0606, loss_cls: 0.2504, acc: 91.5349, loss_bbox: 0.2942, loss_mask: 0.2919, loss: 0.9302 2024-06-05 02:38:36,451 - mmdet - INFO - Epoch [2][1000/7330] lr: 1.000e-04, eta: 19:22:52, time: 0.870, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0584, loss_cls: 0.2541, acc: 91.4124, loss_bbox: 0.3053, loss_mask: 0.2886, loss: 0.9425 2024-06-05 02:39:20,583 - mmdet - INFO - Epoch [2][1050/7330] lr: 1.000e-04, eta: 19:22:11, time: 0.883, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0550, loss_cls: 0.2463, acc: 91.7253, loss_bbox: 0.2915, loss_mask: 0.2852, loss: 0.9092 2024-06-05 02:40:04,451 - mmdet - INFO - Epoch [2][1100/7330] lr: 1.000e-04, eta: 19:21:28, time: 0.877, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0602, loss_cls: 0.2525, acc: 91.4170, loss_bbox: 0.2981, loss_mask: 0.2875, loss: 0.9308 2024-06-05 02:40:48,619 - mmdet - INFO - Epoch [2][1150/7330] lr: 1.000e-04, eta: 19:20:48, time: 0.883, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0608, loss_cls: 0.2560, acc: 91.3149, loss_bbox: 0.3002, loss_mask: 0.2837, loss: 0.9335 2024-06-05 02:41:31,503 - mmdet - INFO - Epoch [2][1200/7330] lr: 1.000e-04, eta: 19:19:55, time: 0.858, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0546, loss_cls: 0.2450, acc: 91.8765, loss_bbox: 0.2852, loss_mask: 0.2776, loss: 0.8927 2024-06-05 02:42:14,913 - mmdet - INFO - Epoch [2][1250/7330] lr: 1.000e-04, eta: 19:19:08, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0600, loss_cls: 0.2545, acc: 91.3054, loss_bbox: 0.3047, loss_mask: 0.2889, loss: 0.9419 2024-06-05 02:42:58,801 - mmdet - INFO - Epoch [2][1300/7330] lr: 1.000e-04, eta: 19:18:25, time: 0.878, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0561, loss_cls: 0.2458, acc: 91.6426, loss_bbox: 0.2923, loss_mask: 0.2891, loss: 0.9161 2024-06-05 02:43:41,948 - mmdet - INFO - Epoch [2][1350/7330] lr: 1.000e-04, eta: 19:17:35, time: 0.863, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0569, loss_cls: 0.2452, acc: 91.6262, loss_bbox: 0.2905, loss_mask: 0.2872, loss: 0.9131 2024-06-05 02:44:25,023 - mmdet - INFO - Epoch [2][1400/7330] lr: 1.000e-04, eta: 19:16:44, time: 0.861, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0582, loss_cls: 0.2506, acc: 91.4958, loss_bbox: 0.2977, loss_mask: 0.2846, loss: 0.9222 2024-06-05 02:45:07,953 - mmdet - INFO - Epoch [2][1450/7330] lr: 1.000e-04, eta: 19:15:53, time: 0.859, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0588, loss_cls: 0.2452, acc: 91.6475, loss_bbox: 0.2973, loss_mask: 0.2863, loss: 0.9199 2024-06-05 02:45:50,790 - mmdet - INFO - Epoch [2][1500/7330] lr: 1.000e-04, eta: 19:15:00, time: 0.857, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0580, loss_cls: 0.2478, acc: 91.6775, loss_bbox: 0.2867, loss_mask: 0.2885, loss: 0.9132 2024-06-05 02:46:40,072 - mmdet - INFO - Epoch [2][1550/7330] lr: 1.000e-04, eta: 19:15:05, time: 0.986, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0558, loss_cls: 0.2327, acc: 92.1296, loss_bbox: 0.2778, loss_mask: 0.2821, loss: 0.8811 2024-06-05 02:47:38,241 - mmdet - INFO - Epoch [2][1600/7330] lr: 1.000e-04, eta: 19:16:29, time: 1.163, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0584, loss_cls: 0.2404, acc: 91.9717, loss_bbox: 0.2851, loss_mask: 0.2834, loss: 0.9003 2024-06-05 02:48:21,089 - mmdet - INFO - Epoch [2][1650/7330] lr: 1.000e-04, eta: 19:15:35, time: 0.857, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0558, loss_cls: 0.2350, acc: 92.0603, loss_bbox: 0.2794, loss_mask: 0.2791, loss: 0.8795 2024-06-05 02:49:04,386 - mmdet - INFO - Epoch [2][1700/7330] lr: 1.000e-04, eta: 19:14:46, time: 0.866, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0570, loss_cls: 0.2481, acc: 91.5508, loss_bbox: 0.2967, loss_mask: 0.2827, loss: 0.9171 2024-06-05 02:49:47,994 - mmdet - INFO - Epoch [2][1750/7330] lr: 1.000e-04, eta: 19:14:00, time: 0.872, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0561, loss_cls: 0.2430, acc: 91.7729, loss_bbox: 0.2932, loss_mask: 0.2791, loss: 0.9032 2024-06-05 02:50:31,553 - mmdet - INFO - Epoch [2][1800/7330] lr: 1.000e-04, eta: 19:13:13, time: 0.872, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0557, loss_cls: 0.2357, acc: 92.1145, loss_bbox: 0.2804, loss_mask: 0.2774, loss: 0.8815 2024-06-05 02:51:14,976 - mmdet - INFO - Epoch [2][1850/7330] lr: 1.000e-04, eta: 19:12:25, time: 0.868, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0585, loss_cls: 0.2449, acc: 91.6433, loss_bbox: 0.3009, loss_mask: 0.2818, loss: 0.9173 2024-06-05 02:51:58,810 - mmdet - INFO - Epoch [2][1900/7330] lr: 1.000e-04, eta: 19:11:41, time: 0.877, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0591, loss_cls: 0.2481, acc: 91.6050, loss_bbox: 0.2931, loss_mask: 0.2844, loss: 0.9193 2024-06-05 02:52:42,930 - mmdet - INFO - Epoch [2][1950/7330] lr: 1.000e-04, eta: 19:10:59, time: 0.882, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0582, loss_cls: 0.2485, acc: 91.6130, loss_bbox: 0.2910, loss_mask: 0.2863, loss: 0.9164 2024-06-05 02:53:26,675 - mmdet - INFO - Epoch [2][2000/7330] lr: 1.000e-04, eta: 19:10:14, time: 0.875, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0534, loss_cls: 0.2350, acc: 92.0916, loss_bbox: 0.2785, loss_mask: 0.2815, loss: 0.8793 2024-06-05 02:54:10,275 - mmdet - INFO - Epoch [2][2050/7330] lr: 1.000e-04, eta: 19:09:28, time: 0.872, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0319, loss_rpn_bbox: 0.0553, loss_cls: 0.2487, acc: 91.7766, loss_bbox: 0.2834, loss_mask: 0.2827, loss: 0.9020 2024-06-05 02:54:54,114 - mmdet - INFO - Epoch [2][2100/7330] lr: 1.000e-04, eta: 19:08:44, time: 0.877, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0593, loss_cls: 0.2533, acc: 91.3279, loss_bbox: 0.3067, loss_mask: 0.2928, loss: 0.9448 2024-06-05 02:55:37,337 - mmdet - INFO - Epoch [2][2150/7330] lr: 1.000e-04, eta: 19:07:54, time: 0.864, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0595, loss_cls: 0.2542, acc: 91.5774, loss_bbox: 0.2972, loss_mask: 0.2871, loss: 0.9297 2024-06-05 02:56:20,735 - mmdet - INFO - Epoch [2][2200/7330] lr: 1.000e-04, eta: 19:07:06, time: 0.868, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0536, loss_cls: 0.2405, acc: 91.7292, loss_bbox: 0.2890, loss_mask: 0.2817, loss: 0.8960 2024-06-05 02:57:04,421 - mmdet - INFO - Epoch [2][2250/7330] lr: 1.000e-04, eta: 19:06:21, time: 0.874, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0553, loss_cls: 0.2352, acc: 91.9958, loss_bbox: 0.2862, loss_mask: 0.2859, loss: 0.8955 2024-06-05 02:57:48,741 - mmdet - INFO - Epoch [2][2300/7330] lr: 1.000e-04, eta: 19:05:41, time: 0.886, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0575, loss_cls: 0.2496, acc: 91.4397, loss_bbox: 0.2998, loss_mask: 0.2805, loss: 0.9210 2024-06-05 02:58:32,802 - mmdet - INFO - Epoch [2][2350/7330] lr: 1.000e-04, eta: 19:04:58, time: 0.881, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0586, loss_cls: 0.2464, acc: 91.5481, loss_bbox: 0.2971, loss_mask: 0.2891, loss: 0.9240 2024-06-05 02:59:16,414 - mmdet - INFO - Epoch [2][2400/7330] lr: 1.000e-04, eta: 19:04:12, time: 0.872, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0575, loss_cls: 0.2428, acc: 91.8086, loss_bbox: 0.2866, loss_mask: 0.2873, loss: 0.9062 2024-06-05 03:00:00,390 - mmdet - INFO - Epoch [2][2450/7330] lr: 1.000e-04, eta: 19:03:29, time: 0.880, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0584, loss_cls: 0.2477, acc: 91.4661, loss_bbox: 0.2950, loss_mask: 0.2845, loss: 0.9199 2024-06-05 03:00:44,437 - mmdet - INFO - Epoch [2][2500/7330] lr: 1.000e-04, eta: 19:02:47, time: 0.881, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0580, loss_cls: 0.2469, acc: 91.6433, loss_bbox: 0.2911, loss_mask: 0.2822, loss: 0.9126 2024-06-05 03:01:27,310 - mmdet - INFO - Epoch [2][2550/7330] lr: 1.000e-04, eta: 19:01:55, time: 0.857, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0568, loss_cls: 0.2399, acc: 91.8774, loss_bbox: 0.2884, loss_mask: 0.2832, loss: 0.9000 2024-06-05 03:02:34,520 - mmdet - INFO - Epoch [2][2600/7330] lr: 1.000e-04, eta: 19:04:14, time: 1.344, data_time: 0.536, memory: 11350, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0530, loss_cls: 0.2495, acc: 91.5674, loss_bbox: 0.2862, loss_mask: 0.2760, loss: 0.8939 2024-06-05 03:03:18,060 - mmdet - INFO - Epoch [2][2650/7330] lr: 1.000e-04, eta: 19:03:27, time: 0.871, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0590, loss_cls: 0.2462, acc: 91.5657, loss_bbox: 0.2943, loss_mask: 0.2794, loss: 0.9113 2024-06-05 03:04:01,597 - mmdet - INFO - Epoch [2][2700/7330] lr: 1.000e-04, eta: 19:02:39, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0583, loss_cls: 0.2460, acc: 91.5916, loss_bbox: 0.2958, loss_mask: 0.2813, loss: 0.9139 2024-06-05 03:04:45,682 - mmdet - INFO - Epoch [2][2750/7330] lr: 1.000e-04, eta: 19:01:56, time: 0.882, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0576, loss_cls: 0.2483, acc: 91.7900, loss_bbox: 0.2892, loss_mask: 0.2821, loss: 0.9087 2024-06-05 03:05:35,389 - mmdet - INFO - Epoch [2][2800/7330] lr: 1.000e-04, eta: 19:01:56, time: 0.994, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0624, loss_cls: 0.2518, acc: 91.4495, loss_bbox: 0.2990, loss_mask: 0.2848, loss: 0.9315 2024-06-05 03:06:33,961 - mmdet - INFO - Epoch [2][2850/7330] lr: 1.000e-04, eta: 19:03:03, time: 1.171, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0580, loss_cls: 0.2449, acc: 91.5117, loss_bbox: 0.2952, loss_mask: 0.2780, loss: 0.9073 2024-06-05 03:07:17,181 - mmdet - INFO - Epoch [2][2900/7330] lr: 1.000e-04, eta: 19:02:12, time: 0.864, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0544, loss_cls: 0.2409, acc: 91.8477, loss_bbox: 0.2810, loss_mask: 0.2794, loss: 0.8862 2024-06-05 03:08:00,775 - mmdet - INFO - Epoch [2][2950/7330] lr: 1.000e-04, eta: 19:01:25, time: 0.872, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0565, loss_cls: 0.2454, acc: 91.7505, loss_bbox: 0.2880, loss_mask: 0.2784, loss: 0.8993 2024-06-05 03:08:44,740 - mmdet - INFO - Epoch [2][3000/7330] lr: 1.000e-04, eta: 19:00:40, time: 0.879, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0577, loss_cls: 0.2503, acc: 91.5916, loss_bbox: 0.2881, loss_mask: 0.2797, loss: 0.9075 2024-06-05 03:09:27,566 - mmdet - INFO - Epoch [2][3050/7330] lr: 1.000e-04, eta: 18:59:46, time: 0.856, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0530, loss_cls: 0.2409, acc: 91.8557, loss_bbox: 0.2854, loss_mask: 0.2811, loss: 0.8910 2024-06-05 03:10:10,651 - mmdet - INFO - Epoch [2][3100/7330] lr: 1.000e-04, eta: 18:58:55, time: 0.862, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0551, loss_cls: 0.2368, acc: 91.9917, loss_bbox: 0.2785, loss_mask: 0.2784, loss: 0.8804 2024-06-05 03:10:54,058 - mmdet - INFO - Epoch [2][3150/7330] lr: 1.000e-04, eta: 18:58:06, time: 0.868, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0558, loss_cls: 0.2399, acc: 91.7576, loss_bbox: 0.2865, loss_mask: 0.2786, loss: 0.8897 2024-06-05 03:11:37,768 - mmdet - INFO - Epoch [2][3200/7330] lr: 1.000e-04, eta: 18:57:19, time: 0.874, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0561, loss_cls: 0.2441, acc: 91.7734, loss_bbox: 0.2861, loss_mask: 0.2777, loss: 0.8937 2024-06-05 03:12:21,289 - mmdet - INFO - Epoch [2][3250/7330] lr: 1.000e-04, eta: 18:56:31, time: 0.870, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0544, loss_cls: 0.2450, acc: 91.7417, loss_bbox: 0.2908, loss_mask: 0.2803, loss: 0.9026 2024-06-05 03:13:04,778 - mmdet - INFO - Epoch [2][3300/7330] lr: 1.000e-04, eta: 18:55:43, time: 0.870, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0306, loss_rpn_bbox: 0.0553, loss_cls: 0.2406, acc: 91.7207, loss_bbox: 0.2855, loss_mask: 0.2815, loss: 0.8935 2024-06-05 03:13:48,358 - mmdet - INFO - Epoch [2][3350/7330] lr: 1.000e-04, eta: 18:54:55, time: 0.872, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0583, loss_cls: 0.2434, acc: 91.7048, loss_bbox: 0.2952, loss_mask: 0.2782, loss: 0.9075 2024-06-05 03:14:31,647 - mmdet - INFO - Epoch [2][3400/7330] lr: 1.000e-04, eta: 18:54:06, time: 0.866, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0592, loss_cls: 0.2460, acc: 91.7151, loss_bbox: 0.2923, loss_mask: 0.2807, loss: 0.9150 2024-06-05 03:15:15,115 - mmdet - INFO - Epoch [2][3450/7330] lr: 1.000e-04, eta: 18:53:17, time: 0.870, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0566, loss_cls: 0.2502, acc: 91.4897, loss_bbox: 0.2932, loss_mask: 0.2835, loss: 0.9147 2024-06-05 03:15:58,161 - mmdet - INFO - Epoch [2][3500/7330] lr: 1.000e-04, eta: 18:52:26, time: 0.861, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0524, loss_cls: 0.2394, acc: 91.9856, loss_bbox: 0.2797, loss_mask: 0.2717, loss: 0.8741 2024-06-05 03:16:41,915 - mmdet - INFO - Epoch [2][3550/7330] lr: 1.000e-04, eta: 18:51:40, time: 0.875, data_time: 0.073, memory: 11350, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0595, loss_cls: 0.2493, acc: 91.4778, loss_bbox: 0.2963, loss_mask: 0.2865, loss: 0.9223 2024-06-05 03:17:24,529 - mmdet - INFO - Epoch [2][3600/7330] lr: 1.000e-04, eta: 18:50:46, time: 0.852, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0533, loss_cls: 0.2358, acc: 91.9509, loss_bbox: 0.2823, loss_mask: 0.2822, loss: 0.8821 2024-06-05 03:18:07,798 - mmdet - INFO - Epoch [2][3650/7330] lr: 1.000e-04, eta: 18:49:56, time: 0.865, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0538, loss_cls: 0.2480, acc: 91.6328, loss_bbox: 0.2845, loss_mask: 0.2678, loss: 0.8842 2024-06-05 03:18:51,577 - mmdet - INFO - Epoch [2][3700/7330] lr: 1.000e-04, eta: 18:49:11, time: 0.876, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0561, loss_cls: 0.2453, acc: 91.7800, loss_bbox: 0.2843, loss_mask: 0.2744, loss: 0.8892 2024-06-05 03:19:35,303 - mmdet - INFO - Epoch [2][3750/7330] lr: 1.000e-04, eta: 18:48:24, time: 0.875, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0548, loss_cls: 0.2440, acc: 91.7439, loss_bbox: 0.2816, loss_mask: 0.2735, loss: 0.8844 2024-06-05 03:20:18,561 - mmdet - INFO - Epoch [2][3800/7330] lr: 1.000e-04, eta: 18:47:35, time: 0.865, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0555, loss_cls: 0.2354, acc: 92.0442, loss_bbox: 0.2782, loss_mask: 0.2768, loss: 0.8762 2024-06-05 03:21:02,129 - mmdet - INFO - Epoch [2][3850/7330] lr: 1.000e-04, eta: 18:46:48, time: 0.871, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0580, loss_cls: 0.2483, acc: 91.5454, loss_bbox: 0.2905, loss_mask: 0.2807, loss: 0.9101 2024-06-05 03:21:45,631 - mmdet - INFO - Epoch [2][3900/7330] lr: 1.000e-04, eta: 18:46:00, time: 0.870, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0591, loss_cls: 0.2478, acc: 91.7124, loss_bbox: 0.2872, loss_mask: 0.2838, loss: 0.9103 2024-06-05 03:22:29,330 - mmdet - INFO - Epoch [2][3950/7330] lr: 1.000e-04, eta: 18:45:14, time: 0.874, data_time: 0.079, memory: 11350, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0582, loss_cls: 0.2433, acc: 91.7236, loss_bbox: 0.2877, loss_mask: 0.2751, loss: 0.8970 2024-06-05 03:23:12,423 - mmdet - INFO - Epoch [2][4000/7330] lr: 1.000e-04, eta: 18:44:24, time: 0.862, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0524, loss_cls: 0.2444, acc: 91.7568, loss_bbox: 0.2864, loss_mask: 0.2695, loss: 0.8811 2024-06-05 03:24:02,799 - mmdet - INFO - Epoch [2][4050/7330] lr: 1.000e-04, eta: 18:44:22, time: 1.008, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0547, loss_cls: 0.2340, acc: 92.0239, loss_bbox: 0.2819, loss_mask: 0.2732, loss: 0.8756 2024-06-05 03:24:57,911 - mmdet - INFO - Epoch [2][4100/7330] lr: 1.000e-04, eta: 18:44:52, time: 1.102, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0515, loss_cls: 0.2366, acc: 91.9319, loss_bbox: 0.2841, loss_mask: 0.2778, loss: 0.8793 2024-06-05 03:25:41,357 - mmdet - INFO - Epoch [2][4150/7330] lr: 1.000e-04, eta: 18:44:04, time: 0.869, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0563, loss_cls: 0.2395, acc: 91.8110, loss_bbox: 0.2874, loss_mask: 0.2799, loss: 0.8944 2024-06-05 03:26:24,493 - mmdet - INFO - Epoch [2][4200/7330] lr: 1.000e-04, eta: 18:43:14, time: 0.863, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0536, loss_cls: 0.2392, acc: 91.8647, loss_bbox: 0.2820, loss_mask: 0.2695, loss: 0.8751 2024-06-05 03:27:07,865 - mmdet - INFO - Epoch [2][4250/7330] lr: 1.000e-04, eta: 18:42:25, time: 0.867, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0535, loss_cls: 0.2421, acc: 91.8303, loss_bbox: 0.2824, loss_mask: 0.2782, loss: 0.8838 2024-06-05 03:27:50,548 - mmdet - INFO - Epoch [2][4300/7330] lr: 1.000e-04, eta: 18:41:31, time: 0.854, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0506, loss_cls: 0.2277, acc: 92.1299, loss_bbox: 0.2729, loss_mask: 0.2719, loss: 0.8508 2024-06-05 03:28:33,869 - mmdet - INFO - Epoch [2][4350/7330] lr: 1.000e-04, eta: 18:40:42, time: 0.866, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0535, loss_cls: 0.2357, acc: 92.0178, loss_bbox: 0.2792, loss_mask: 0.2789, loss: 0.8762 2024-06-05 03:29:17,381 - mmdet - INFO - Epoch [2][4400/7330] lr: 1.000e-04, eta: 18:39:55, time: 0.870, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0594, loss_cls: 0.2437, acc: 91.7686, loss_bbox: 0.2865, loss_mask: 0.2791, loss: 0.9002 2024-06-05 03:30:00,594 - mmdet - INFO - Epoch [2][4450/7330] lr: 1.000e-04, eta: 18:39:05, time: 0.864, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0554, loss_cls: 0.2455, acc: 91.7773, loss_bbox: 0.2885, loss_mask: 0.2843, loss: 0.9029 2024-06-05 03:30:44,220 - mmdet - INFO - Epoch [2][4500/7330] lr: 1.000e-04, eta: 18:38:18, time: 0.872, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0573, loss_cls: 0.2443, acc: 91.7324, loss_bbox: 0.2866, loss_mask: 0.2760, loss: 0.8958 2024-06-05 03:31:27,362 - mmdet - INFO - Epoch [2][4550/7330] lr: 1.000e-04, eta: 18:37:28, time: 0.863, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0530, loss_cls: 0.2382, acc: 91.9082, loss_bbox: 0.2865, loss_mask: 0.2815, loss: 0.8874 2024-06-05 03:32:10,384 - mmdet - INFO - Epoch [2][4600/7330] lr: 1.000e-04, eta: 18:36:37, time: 0.860, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0541, loss_cls: 0.2345, acc: 92.0549, loss_bbox: 0.2808, loss_mask: 0.2779, loss: 0.8760 2024-06-05 03:32:53,507 - mmdet - INFO - Epoch [2][4650/7330] lr: 1.000e-04, eta: 18:35:47, time: 0.862, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0566, loss_cls: 0.2347, acc: 91.8872, loss_bbox: 0.2838, loss_mask: 0.2724, loss: 0.8790 2024-06-05 03:33:36,799 - mmdet - INFO - Epoch [2][4700/7330] lr: 1.000e-04, eta: 18:34:58, time: 0.866, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0581, loss_cls: 0.2422, acc: 91.6440, loss_bbox: 0.2920, loss_mask: 0.2766, loss: 0.9002 2024-06-05 03:34:20,162 - mmdet - INFO - Epoch [2][4750/7330] lr: 1.000e-04, eta: 18:34:10, time: 0.867, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0538, loss_cls: 0.2376, acc: 91.9736, loss_bbox: 0.2765, loss_mask: 0.2753, loss: 0.8744 2024-06-05 03:35:03,197 - mmdet - INFO - Epoch [2][4800/7330] lr: 1.000e-04, eta: 18:33:20, time: 0.861, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0570, loss_cls: 0.2391, acc: 91.7310, loss_bbox: 0.2901, loss_mask: 0.2804, loss: 0.8976 2024-06-05 03:35:46,319 - mmdet - INFO - Epoch [2][4850/7330] lr: 1.000e-04, eta: 18:32:30, time: 0.862, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0557, loss_cls: 0.2305, acc: 92.2515, loss_bbox: 0.2718, loss_mask: 0.2804, loss: 0.8727 2024-06-05 03:36:30,035 - mmdet - INFO - Epoch [2][4900/7330] lr: 1.000e-04, eta: 18:31:44, time: 0.874, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0571, loss_cls: 0.2431, acc: 91.6809, loss_bbox: 0.2889, loss_mask: 0.2760, loss: 0.8948 2024-06-05 03:37:13,743 - mmdet - INFO - Epoch [2][4950/7330] lr: 1.000e-04, eta: 18:30:58, time: 0.874, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0558, loss_cls: 0.2445, acc: 91.5464, loss_bbox: 0.2942, loss_mask: 0.2824, loss: 0.9079 2024-06-05 03:37:56,827 - mmdet - INFO - Epoch [2][5000/7330] lr: 1.000e-04, eta: 18:30:08, time: 0.862, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0555, loss_cls: 0.2331, acc: 91.9202, loss_bbox: 0.2807, loss_mask: 0.2766, loss: 0.8749 2024-06-05 03:38:40,398 - mmdet - INFO - Epoch [2][5050/7330] lr: 1.000e-04, eta: 18:29:21, time: 0.871, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0542, loss_cls: 0.2365, acc: 91.9377, loss_bbox: 0.2849, loss_mask: 0.2779, loss: 0.8833 2024-06-05 03:39:23,657 - mmdet - INFO - Epoch [2][5100/7330] lr: 1.000e-04, eta: 18:28:32, time: 0.865, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0551, loss_cls: 0.2318, acc: 92.0007, loss_bbox: 0.2879, loss_mask: 0.2792, loss: 0.8835 2024-06-05 03:40:07,180 - mmdet - INFO - Epoch [2][5150/7330] lr: 1.000e-04, eta: 18:27:45, time: 0.870, data_time: 0.080, memory: 11350, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0547, loss_cls: 0.2392, acc: 91.7886, loss_bbox: 0.2836, loss_mask: 0.2748, loss: 0.8810 2024-06-05 03:40:50,238 - mmdet - INFO - Epoch [2][5200/7330] lr: 1.000e-04, eta: 18:26:55, time: 0.861, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0519, loss_cls: 0.2258, acc: 92.4504, loss_bbox: 0.2618, loss_mask: 0.2671, loss: 0.8348 2024-06-05 03:41:33,096 - mmdet - INFO - Epoch [2][5250/7330] lr: 1.000e-04, eta: 18:26:04, time: 0.857, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0556, loss_cls: 0.2344, acc: 92.0278, loss_bbox: 0.2763, loss_mask: 0.2832, loss: 0.8797 2024-06-05 03:42:18,740 - mmdet - INFO - Epoch [2][5300/7330] lr: 1.000e-04, eta: 18:25:30, time: 0.913, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0540, loss_cls: 0.2293, acc: 92.0750, loss_bbox: 0.2763, loss_mask: 0.2717, loss: 0.8607 2024-06-05 03:43:08,542 - mmdet - INFO - Epoch [2][5350/7330] lr: 1.000e-04, eta: 18:25:20, time: 0.996, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0556, loss_cls: 0.2445, acc: 91.6060, loss_bbox: 0.2895, loss_mask: 0.2745, loss: 0.8936 2024-06-05 03:44:01,377 - mmdet - INFO - Epoch [2][5400/7330] lr: 1.000e-04, eta: 18:25:28, time: 1.057, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0554, loss_cls: 0.2336, acc: 92.1284, loss_bbox: 0.2724, loss_mask: 0.2735, loss: 0.8653 2024-06-05 03:44:45,242 - mmdet - INFO - Epoch [2][5450/7330] lr: 1.000e-04, eta: 18:24:43, time: 0.877, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0547, loss_cls: 0.2413, acc: 91.6804, loss_bbox: 0.2831, loss_mask: 0.2736, loss: 0.8840 2024-06-05 03:45:28,848 - mmdet - INFO - Epoch [2][5500/7330] lr: 1.000e-04, eta: 18:23:56, time: 0.872, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0566, loss_cls: 0.2459, acc: 91.6921, loss_bbox: 0.2856, loss_mask: 0.2776, loss: 0.8985 2024-06-05 03:46:11,899 - mmdet - INFO - Epoch [2][5550/7330] lr: 1.000e-04, eta: 18:23:06, time: 0.861, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0532, loss_cls: 0.2270, acc: 92.2683, loss_bbox: 0.2705, loss_mask: 0.2665, loss: 0.8477 2024-06-05 03:46:55,415 - mmdet - INFO - Epoch [2][5600/7330] lr: 1.000e-04, eta: 18:22:18, time: 0.870, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0531, loss_cls: 0.2303, acc: 92.1213, loss_bbox: 0.2787, loss_mask: 0.2754, loss: 0.8665 2024-06-05 03:47:38,827 - mmdet - INFO - Epoch [2][5650/7330] lr: 1.000e-04, eta: 18:21:30, time: 0.868, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0542, loss_cls: 0.2388, acc: 91.8848, loss_bbox: 0.2737, loss_mask: 0.2729, loss: 0.8694 2024-06-05 03:48:21,938 - mmdet - INFO - Epoch [2][5700/7330] lr: 1.000e-04, eta: 18:20:41, time: 0.862, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0496, loss_cls: 0.2250, acc: 92.2312, loss_bbox: 0.2678, loss_mask: 0.2666, loss: 0.8377 2024-06-05 03:49:05,245 - mmdet - INFO - Epoch [2][5750/7330] lr: 1.000e-04, eta: 18:19:52, time: 0.866, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0502, loss_cls: 0.2340, acc: 92.0259, loss_bbox: 0.2742, loss_mask: 0.2725, loss: 0.8581 2024-06-05 03:49:48,349 - mmdet - INFO - Epoch [2][5800/7330] lr: 1.000e-04, eta: 18:19:03, time: 0.862, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0521, loss_cls: 0.2345, acc: 91.9241, loss_bbox: 0.2804, loss_mask: 0.2726, loss: 0.8683 2024-06-05 03:50:31,804 - mmdet - INFO - Epoch [2][5850/7330] lr: 1.000e-04, eta: 18:18:15, time: 0.869, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0545, loss_cls: 0.2433, acc: 91.7517, loss_bbox: 0.2810, loss_mask: 0.2774, loss: 0.8864 2024-06-05 03:51:14,950 - mmdet - INFO - Epoch [2][5900/7330] lr: 1.000e-04, eta: 18:17:26, time: 0.863, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0535, loss_cls: 0.2277, acc: 92.1196, loss_bbox: 0.2752, loss_mask: 0.2721, loss: 0.8588 2024-06-05 03:51:58,106 - mmdet - INFO - Epoch [2][5950/7330] lr: 1.000e-04, eta: 18:16:37, time: 0.863, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0517, loss_cls: 0.2323, acc: 92.0652, loss_bbox: 0.2746, loss_mask: 0.2691, loss: 0.8561 2024-06-05 03:52:41,665 - mmdet - INFO - Epoch [2][6000/7330] lr: 1.000e-04, eta: 18:15:50, time: 0.871, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0528, loss_cls: 0.2337, acc: 92.0222, loss_bbox: 0.2816, loss_mask: 0.2728, loss: 0.8705 2024-06-05 03:53:25,005 - mmdet - INFO - Epoch [2][6050/7330] lr: 1.000e-04, eta: 18:15:02, time: 0.867, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0555, loss_cls: 0.2436, acc: 91.6782, loss_bbox: 0.2865, loss_mask: 0.2785, loss: 0.8937 2024-06-05 03:54:08,395 - mmdet - INFO - Epoch [2][6100/7330] lr: 1.000e-04, eta: 18:14:14, time: 0.868, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0586, loss_cls: 0.2419, acc: 91.8752, loss_bbox: 0.2811, loss_mask: 0.2703, loss: 0.8834 2024-06-05 03:54:51,531 - mmdet - INFO - Epoch [2][6150/7330] lr: 1.000e-04, eta: 18:13:25, time: 0.863, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0536, loss_cls: 0.2334, acc: 92.0320, loss_bbox: 0.2794, loss_mask: 0.2739, loss: 0.8687 2024-06-05 03:55:34,386 - mmdet - INFO - Epoch [2][6200/7330] lr: 1.000e-04, eta: 18:12:35, time: 0.857, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0518, loss_cls: 0.2278, acc: 92.2856, loss_bbox: 0.2727, loss_mask: 0.2671, loss: 0.8491 2024-06-05 03:56:18,192 - mmdet - INFO - Epoch [2][6250/7330] lr: 1.000e-04, eta: 18:11:50, time: 0.876, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0595, loss_cls: 0.2424, acc: 91.6965, loss_bbox: 0.2871, loss_mask: 0.2740, loss: 0.8958 2024-06-05 03:57:01,325 - mmdet - INFO - Epoch [2][6300/7330] lr: 1.000e-04, eta: 18:11:01, time: 0.863, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0536, loss_cls: 0.2347, acc: 91.9434, loss_bbox: 0.2749, loss_mask: 0.2684, loss: 0.8604 2024-06-05 03:57:44,507 - mmdet - INFO - Epoch [2][6350/7330] lr: 1.000e-04, eta: 18:10:12, time: 0.864, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0509, loss_cls: 0.2361, acc: 91.9875, loss_bbox: 0.2781, loss_mask: 0.2712, loss: 0.8626 2024-06-05 03:58:27,909 - mmdet - INFO - Epoch [2][6400/7330] lr: 1.000e-04, eta: 18:09:24, time: 0.868, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0573, loss_cls: 0.2380, acc: 91.7803, loss_bbox: 0.2803, loss_mask: 0.2742, loss: 0.8814 2024-06-05 03:59:11,153 - mmdet - INFO - Epoch [2][6450/7330] lr: 1.000e-04, eta: 18:08:36, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0494, loss_cls: 0.2260, acc: 92.2451, loss_bbox: 0.2685, loss_mask: 0.2674, loss: 0.8375 2024-06-05 03:59:54,458 - mmdet - INFO - Epoch [2][6500/7330] lr: 1.000e-04, eta: 18:07:48, time: 0.866, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0541, loss_cls: 0.2400, acc: 91.7744, loss_bbox: 0.2809, loss_mask: 0.2747, loss: 0.8792 2024-06-05 04:00:37,950 - mmdet - INFO - Epoch [2][6550/7330] lr: 1.000e-04, eta: 18:07:01, time: 0.870, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0538, loss_cls: 0.2350, acc: 91.9761, loss_bbox: 0.2789, loss_mask: 0.2671, loss: 0.8659 2024-06-05 04:01:26,990 - mmdet - INFO - Epoch [2][6600/7330] lr: 1.000e-04, eta: 18:06:44, time: 0.981, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0545, loss_cls: 0.2320, acc: 92.0242, loss_bbox: 0.2742, loss_mask: 0.2753, loss: 0.8657 2024-06-05 04:02:24,199 - mmdet - INFO - Epoch [2][6650/7330] lr: 1.000e-04, eta: 18:07:10, time: 1.144, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0501, loss_cls: 0.2221, acc: 92.3643, loss_bbox: 0.2633, loss_mask: 0.2686, loss: 0.8324 2024-06-05 04:03:07,647 - mmdet - INFO - Epoch [2][6700/7330] lr: 1.000e-04, eta: 18:06:22, time: 0.869, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0550, loss_cls: 0.2413, acc: 91.6672, loss_bbox: 0.2886, loss_mask: 0.2767, loss: 0.8930 2024-06-05 04:03:51,538 - mmdet - INFO - Epoch [2][6750/7330] lr: 1.000e-04, eta: 18:05:37, time: 0.878, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0550, loss_cls: 0.2443, acc: 91.5898, loss_bbox: 0.2912, loss_mask: 0.2745, loss: 0.8964 2024-06-05 04:04:34,956 - mmdet - INFO - Epoch [2][6800/7330] lr: 1.000e-04, eta: 18:04:50, time: 0.868, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0519, loss_cls: 0.2314, acc: 92.1970, loss_bbox: 0.2684, loss_mask: 0.2705, loss: 0.8507 2024-06-05 04:05:18,169 - mmdet - INFO - Epoch [2][6850/7330] lr: 1.000e-04, eta: 18:04:01, time: 0.864, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0515, loss_cls: 0.2301, acc: 92.0498, loss_bbox: 0.2713, loss_mask: 0.2729, loss: 0.8554 2024-06-05 04:06:01,357 - mmdet - INFO - Epoch [2][6900/7330] lr: 1.000e-04, eta: 18:03:12, time: 0.864, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0527, loss_cls: 0.2391, acc: 91.9316, loss_bbox: 0.2734, loss_mask: 0.2733, loss: 0.8661 2024-06-05 04:06:44,541 - mmdet - INFO - Epoch [2][6950/7330] lr: 1.000e-04, eta: 18:02:24, time: 0.864, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0565, loss_cls: 0.2380, acc: 91.9265, loss_bbox: 0.2777, loss_mask: 0.2734, loss: 0.8758 2024-06-05 04:07:27,655 - mmdet - INFO - Epoch [2][7000/7330] lr: 1.000e-04, eta: 18:01:35, time: 0.862, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0514, loss_cls: 0.2298, acc: 92.0415, loss_bbox: 0.2717, loss_mask: 0.2684, loss: 0.8482 2024-06-05 04:08:11,137 - mmdet - INFO - Epoch [2][7050/7330] lr: 1.000e-04, eta: 18:00:48, time: 0.870, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0552, loss_cls: 0.2484, acc: 91.4434, loss_bbox: 0.2900, loss_mask: 0.2729, loss: 0.8969 2024-06-05 04:08:54,947 - mmdet - INFO - Epoch [2][7100/7330] lr: 1.000e-04, eta: 18:00:02, time: 0.876, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0555, loss_cls: 0.2419, acc: 91.6814, loss_bbox: 0.2848, loss_mask: 0.2720, loss: 0.8851 2024-06-05 04:09:38,185 - mmdet - INFO - Epoch [2][7150/7330] lr: 1.000e-04, eta: 17:59:14, time: 0.865, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0506, loss_cls: 0.2264, acc: 92.2549, loss_bbox: 0.2692, loss_mask: 0.2695, loss: 0.8434 2024-06-05 04:10:21,530 - mmdet - INFO - Epoch [2][7200/7330] lr: 1.000e-04, eta: 17:58:26, time: 0.867, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0518, loss_cls: 0.2248, acc: 92.2134, loss_bbox: 0.2703, loss_mask: 0.2657, loss: 0.8410 2024-06-05 04:11:04,542 - mmdet - INFO - Epoch [2][7250/7330] lr: 1.000e-04, eta: 17:57:37, time: 0.860, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0520, loss_cls: 0.2324, acc: 92.1738, loss_bbox: 0.2699, loss_mask: 0.2780, loss: 0.8631 2024-06-05 04:11:47,743 - mmdet - INFO - Epoch [2][7300/7330] lr: 1.000e-04, eta: 17:56:49, time: 0.864, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0536, loss_cls: 0.2413, acc: 91.7236, loss_bbox: 0.2824, loss_mask: 0.2707, loss: 0.8784 2024-06-05 04:12:14,534 - mmdet - INFO - Saving checkpoint at 2 epochs 2024-06-05 04:14:02,377 - mmdet - INFO - Evaluating bbox... 2024-06-05 04:14:30,792 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.616 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.414 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.200 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.417 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.548 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.505 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.505 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.505 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.286 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.685 2024-06-05 04:14:30,792 - mmdet - INFO - Evaluating segm... 2024-06-05 04:14:58,198 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.356 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.579 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.375 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.139 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.384 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.468 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.468 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.468 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.231 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.520 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.678 2024-06-05 04:14:58,641 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 04:14:58,642 - mmdet - INFO - Epoch(val) [2][625] bbox_mAP: 0.3790, bbox_mAP_50: 0.6160, bbox_mAP_75: 0.4140, bbox_mAP_s: 0.2000, bbox_mAP_m: 0.4170, bbox_mAP_l: 0.5480, bbox_mAP_copypaste: 0.379 0.616 0.414 0.200 0.417 0.548, segm_mAP: 0.3560, segm_mAP_50: 0.5790, segm_mAP_75: 0.3750, segm_mAP_s: 0.1390, segm_mAP_m: 0.3840, segm_mAP_l: 0.5810, segm_mAP_copypaste: 0.356 0.579 0.375 0.139 0.384 0.581 2024-06-05 04:15:45,968 - mmdet - INFO - Epoch [3][50/7330] lr: 1.000e-04, eta: 17:53:43, time: 0.946, data_time: 0.134, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0526, loss_cls: 0.2306, acc: 92.0496, loss_bbox: 0.2753, loss_mask: 0.2637, loss: 0.8477 2024-06-05 04:16:29,379 - mmdet - INFO - Epoch [3][100/7330] lr: 1.000e-04, eta: 17:52:56, time: 0.868, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0490, loss_cls: 0.2156, acc: 92.4419, loss_bbox: 0.2652, loss_mask: 0.2602, loss: 0.8146 2024-06-05 04:17:13,591 - mmdet - INFO - Epoch [3][150/7330] lr: 1.000e-04, eta: 17:52:13, time: 0.884, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0529, loss_cls: 0.2221, acc: 92.2395, loss_bbox: 0.2697, loss_mask: 0.2627, loss: 0.8335 2024-06-05 04:18:02,648 - mmdet - INFO - Epoch [3][200/7330] lr: 1.000e-04, eta: 17:51:54, time: 0.981, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0519, loss_cls: 0.2247, acc: 92.0203, loss_bbox: 0.2771, loss_mask: 0.2634, loss: 0.8448 2024-06-05 04:18:46,278 - mmdet - INFO - Epoch [3][250/7330] lr: 1.000e-04, eta: 17:51:08, time: 0.873, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0479, loss_cls: 0.2081, acc: 92.5928, loss_bbox: 0.2650, loss_mask: 0.2583, loss: 0.8038 2024-06-05 04:19:32,479 - mmdet - INFO - Epoch [3][300/7330] lr: 1.000e-04, eta: 17:50:35, time: 0.924, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0522, loss_cls: 0.2213, acc: 92.2781, loss_bbox: 0.2680, loss_mask: 0.2666, loss: 0.8354 2024-06-05 04:20:27,488 - mmdet - INFO - Epoch [3][350/7330] lr: 1.000e-04, eta: 17:50:45, time: 1.100, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0516, loss_cls: 0.2200, acc: 92.2969, loss_bbox: 0.2702, loss_mask: 0.2663, loss: 0.8329 2024-06-05 04:21:11,878 - mmdet - INFO - Epoch [3][400/7330] lr: 1.000e-04, eta: 17:50:02, time: 0.888, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0541, loss_cls: 0.2256, acc: 92.0359, loss_bbox: 0.2752, loss_mask: 0.2637, loss: 0.8440 2024-06-05 04:21:55,938 - mmdet - INFO - Epoch [3][450/7330] lr: 1.000e-04, eta: 17:49:18, time: 0.881, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0512, loss_cls: 0.2217, acc: 92.2505, loss_bbox: 0.2729, loss_mask: 0.2573, loss: 0.8269 2024-06-05 04:22:40,527 - mmdet - INFO - Epoch [3][500/7330] lr: 1.000e-04, eta: 17:48:37, time: 0.892, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0502, loss_cls: 0.2357, acc: 91.8025, loss_bbox: 0.2829, loss_mask: 0.2656, loss: 0.8610 2024-06-05 04:23:24,078 - mmdet - INFO - Epoch [3][550/7330] lr: 1.000e-04, eta: 17:47:51, time: 0.871, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0521, loss_cls: 0.2218, acc: 92.1875, loss_bbox: 0.2710, loss_mask: 0.2614, loss: 0.8312 2024-06-05 04:24:07,389 - mmdet - INFO - Epoch [3][600/7330] lr: 1.000e-04, eta: 17:47:03, time: 0.866, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0498, loss_cls: 0.2085, acc: 92.5947, loss_bbox: 0.2561, loss_mask: 0.2550, loss: 0.7927 2024-06-05 04:24:51,856 - mmdet - INFO - Epoch [3][650/7330] lr: 1.000e-04, eta: 17:46:21, time: 0.889, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0546, loss_cls: 0.2300, acc: 91.8169, loss_bbox: 0.2855, loss_mask: 0.2696, loss: 0.8668 2024-06-05 04:25:36,272 - mmdet - INFO - Epoch [3][700/7330] lr: 1.000e-04, eta: 17:45:39, time: 0.888, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0520, loss_cls: 0.2266, acc: 92.1584, loss_bbox: 0.2713, loss_mask: 0.2597, loss: 0.8353 2024-06-05 04:26:19,603 - mmdet - INFO - Epoch [3][750/7330] lr: 1.000e-04, eta: 17:44:52, time: 0.867, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0502, loss_cls: 0.2145, acc: 92.4802, loss_bbox: 0.2661, loss_mask: 0.2612, loss: 0.8171 2024-06-05 04:27:04,090 - mmdet - INFO - Epoch [3][800/7330] lr: 1.000e-04, eta: 17:44:10, time: 0.890, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0548, loss_cls: 0.2304, acc: 91.7959, loss_bbox: 0.2856, loss_mask: 0.2694, loss: 0.8681 2024-06-05 04:27:46,950 - mmdet - INFO - Epoch [3][850/7330] lr: 1.000e-04, eta: 17:43:20, time: 0.857, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0515, loss_cls: 0.2146, acc: 92.5820, loss_bbox: 0.2631, loss_mask: 0.2543, loss: 0.8078 2024-06-05 04:28:31,140 - mmdet - INFO - Epoch [3][900/7330] lr: 1.000e-04, eta: 17:42:37, time: 0.884, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0523, loss_cls: 0.2271, acc: 91.8538, loss_bbox: 0.2809, loss_mask: 0.2715, loss: 0.8560 2024-06-05 04:29:15,598 - mmdet - INFO - Epoch [3][950/7330] lr: 1.000e-04, eta: 17:41:55, time: 0.889, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0531, loss_cls: 0.2272, acc: 92.0208, loss_bbox: 0.2798, loss_mask: 0.2601, loss: 0.8451 2024-06-05 04:29:59,698 - mmdet - INFO - Epoch [3][1000/7330] lr: 1.000e-04, eta: 17:41:11, time: 0.882, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0541, loss_cls: 0.2232, acc: 92.1431, loss_bbox: 0.2788, loss_mask: 0.2688, loss: 0.8518 2024-06-05 04:30:42,583 - mmdet - INFO - Epoch [3][1050/7330] lr: 1.000e-04, eta: 17:40:22, time: 0.858, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0483, loss_cls: 0.2081, acc: 92.5750, loss_bbox: 0.2590, loss_mask: 0.2505, loss: 0.7897 2024-06-05 04:31:26,966 - mmdet - INFO - Epoch [3][1100/7330] lr: 1.000e-04, eta: 17:39:39, time: 0.888, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0528, loss_cls: 0.2198, acc: 92.4556, loss_bbox: 0.2627, loss_mask: 0.2618, loss: 0.8229 2024-06-05 04:32:10,514 - mmdet - INFO - Epoch [3][1150/7330] lr: 1.000e-04, eta: 17:38:53, time: 0.871, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0537, loss_cls: 0.2168, acc: 92.4905, loss_bbox: 0.2633, loss_mask: 0.2612, loss: 0.8237 2024-06-05 04:32:54,703 - mmdet - INFO - Epoch [3][1200/7330] lr: 1.000e-04, eta: 17:38:10, time: 0.884, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0535, loss_cls: 0.2286, acc: 91.9941, loss_bbox: 0.2764, loss_mask: 0.2655, loss: 0.8506 2024-06-05 04:33:38,556 - mmdet - INFO - Epoch [3][1250/7330] lr: 1.000e-04, eta: 17:37:25, time: 0.877, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0544, loss_cls: 0.2243, acc: 92.1021, loss_bbox: 0.2752, loss_mask: 0.2628, loss: 0.8417 2024-06-05 04:34:22,464 - mmdet - INFO - Epoch [3][1300/7330] lr: 1.000e-04, eta: 17:36:40, time: 0.878, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0522, loss_cls: 0.2213, acc: 92.1768, loss_bbox: 0.2732, loss_mask: 0.2635, loss: 0.8357 2024-06-05 04:35:06,118 - mmdet - INFO - Epoch [3][1350/7330] lr: 1.000e-04, eta: 17:35:55, time: 0.873, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0516, loss_cls: 0.2260, acc: 92.1807, loss_bbox: 0.2691, loss_mask: 0.2609, loss: 0.8355 2024-06-05 04:35:49,214 - mmdet - INFO - Epoch [3][1400/7330] lr: 1.000e-04, eta: 17:35:07, time: 0.862, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0493, loss_cls: 0.2121, acc: 92.4319, loss_bbox: 0.2618, loss_mask: 0.2617, loss: 0.8099 2024-06-05 04:36:35,958 - mmdet - INFO - Epoch [3][1450/7330] lr: 1.000e-04, eta: 17:34:35, time: 0.935, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0526, loss_cls: 0.2247, acc: 91.9917, loss_bbox: 0.2778, loss_mask: 0.2705, loss: 0.8536 2024-06-05 04:37:23,760 - mmdet - INFO - Epoch [3][1500/7330] lr: 1.000e-04, eta: 17:34:07, time: 0.956, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0527, loss_cls: 0.2260, acc: 92.0354, loss_bbox: 0.2715, loss_mask: 0.2624, loss: 0.8386 2024-06-05 04:38:09,888 - mmdet - INFO - Epoch [3][1550/7330] lr: 1.000e-04, eta: 17:33:33, time: 0.923, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0486, loss_cls: 0.2132, acc: 92.5710, loss_bbox: 0.2619, loss_mask: 0.2596, loss: 0.8085 2024-06-05 04:39:07,078 - mmdet - INFO - Epoch [3][1600/7330] lr: 1.000e-04, eta: 17:33:46, time: 1.144, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0491, loss_cls: 0.2175, acc: 92.3677, loss_bbox: 0.2696, loss_mask: 0.2550, loss: 0.8174 2024-06-05 04:39:50,727 - mmdet - INFO - Epoch [3][1650/7330] lr: 1.000e-04, eta: 17:33:00, time: 0.873, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0499, loss_cls: 0.2194, acc: 92.3340, loss_bbox: 0.2731, loss_mask: 0.2638, loss: 0.8315 2024-06-05 04:40:34,069 - mmdet - INFO - Epoch [3][1700/7330] lr: 1.000e-04, eta: 17:32:13, time: 0.867, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0494, loss_cls: 0.2204, acc: 92.2754, loss_bbox: 0.2685, loss_mask: 0.2548, loss: 0.8202 2024-06-05 04:41:17,768 - mmdet - INFO - Epoch [3][1750/7330] lr: 1.000e-04, eta: 17:31:27, time: 0.874, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0513, loss_cls: 0.2210, acc: 92.1628, loss_bbox: 0.2708, loss_mask: 0.2678, loss: 0.8361 2024-06-05 04:42:01,086 - mmdet - INFO - Epoch [3][1800/7330] lr: 1.000e-04, eta: 17:30:40, time: 0.866, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0521, loss_cls: 0.2158, acc: 92.2734, loss_bbox: 0.2675, loss_mask: 0.2631, loss: 0.8243 2024-06-05 04:42:44,887 - mmdet - INFO - Epoch [3][1850/7330] lr: 1.000e-04, eta: 17:29:55, time: 0.876, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0513, loss_cls: 0.2194, acc: 92.1948, loss_bbox: 0.2706, loss_mask: 0.2595, loss: 0.8272 2024-06-05 04:43:28,231 - mmdet - INFO - Epoch [3][1900/7330] lr: 1.000e-04, eta: 17:29:07, time: 0.867, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0502, loss_cls: 0.2180, acc: 92.4089, loss_bbox: 0.2675, loss_mask: 0.2599, loss: 0.8218 2024-06-05 04:44:12,336 - mmdet - INFO - Epoch [3][1950/7330] lr: 1.000e-04, eta: 17:28:23, time: 0.882, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0522, loss_cls: 0.2124, acc: 92.4490, loss_bbox: 0.2627, loss_mask: 0.2583, loss: 0.8133 2024-06-05 04:44:56,851 - mmdet - INFO - Epoch [3][2000/7330] lr: 1.000e-04, eta: 17:27:41, time: 0.890, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0537, loss_cls: 0.2285, acc: 91.9795, loss_bbox: 0.2748, loss_mask: 0.2603, loss: 0.8445 2024-06-05 04:45:40,785 - mmdet - INFO - Epoch [3][2050/7330] lr: 1.000e-04, eta: 17:26:56, time: 0.879, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0543, loss_cls: 0.2198, acc: 92.2349, loss_bbox: 0.2741, loss_mask: 0.2622, loss: 0.8369 2024-06-05 04:46:24,967 - mmdet - INFO - Epoch [3][2100/7330] lr: 1.000e-04, eta: 17:26:13, time: 0.884, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0550, loss_cls: 0.2194, acc: 92.2595, loss_bbox: 0.2726, loss_mask: 0.2595, loss: 0.8332 2024-06-05 04:47:08,299 - mmdet - INFO - Epoch [3][2150/7330] lr: 1.000e-04, eta: 17:25:25, time: 0.867, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0504, loss_cls: 0.2188, acc: 92.2361, loss_bbox: 0.2659, loss_mask: 0.2577, loss: 0.8187 2024-06-05 04:47:51,980 - mmdet - INFO - Epoch [3][2200/7330] lr: 1.000e-04, eta: 17:24:40, time: 0.874, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0494, loss_cls: 0.2196, acc: 92.3250, loss_bbox: 0.2703, loss_mask: 0.2616, loss: 0.8281 2024-06-05 04:48:35,104 - mmdet - INFO - Epoch [3][2250/7330] lr: 1.000e-04, eta: 17:23:52, time: 0.863, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0456, loss_cls: 0.2143, acc: 92.5764, loss_bbox: 0.2545, loss_mask: 0.2520, loss: 0.7895 2024-06-05 04:49:18,688 - mmdet - INFO - Epoch [3][2300/7330] lr: 1.000e-04, eta: 17:23:05, time: 0.872, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0505, loss_cls: 0.2121, acc: 92.6018, loss_bbox: 0.2607, loss_mask: 0.2554, loss: 0.8015 2024-06-05 04:50:02,646 - mmdet - INFO - Epoch [3][2350/7330] lr: 1.000e-04, eta: 17:22:21, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0508, loss_cls: 0.2223, acc: 92.2703, loss_bbox: 0.2676, loss_mask: 0.2530, loss: 0.8191 2024-06-05 04:50:45,616 - mmdet - INFO - Epoch [3][2400/7330] lr: 1.000e-04, eta: 17:21:32, time: 0.859, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0486, loss_cls: 0.2165, acc: 92.4592, loss_bbox: 0.2621, loss_mask: 0.2556, loss: 0.8068 2024-06-05 04:51:29,954 - mmdet - INFO - Epoch [3][2450/7330] lr: 1.000e-04, eta: 17:20:49, time: 0.887, data_time: 0.072, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0509, loss_cls: 0.2150, acc: 92.4905, loss_bbox: 0.2605, loss_mask: 0.2569, loss: 0.8095 2024-06-05 04:52:13,407 - mmdet - INFO - Epoch [3][2500/7330] lr: 1.000e-04, eta: 17:20:03, time: 0.869, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0516, loss_cls: 0.2222, acc: 92.2522, loss_bbox: 0.2729, loss_mask: 0.2641, loss: 0.8370 2024-06-05 04:52:57,402 - mmdet - INFO - Epoch [3][2550/7330] lr: 1.000e-04, eta: 17:19:18, time: 0.880, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0507, loss_cls: 0.2222, acc: 92.2698, loss_bbox: 0.2693, loss_mask: 0.2611, loss: 0.8288 2024-06-05 04:53:41,376 - mmdet - INFO - Epoch [3][2600/7330] lr: 1.000e-04, eta: 17:18:34, time: 0.879, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0523, loss_cls: 0.2224, acc: 92.2759, loss_bbox: 0.2668, loss_mask: 0.2599, loss: 0.8274 2024-06-05 04:54:25,062 - mmdet - INFO - Epoch [3][2650/7330] lr: 1.000e-04, eta: 17:17:48, time: 0.874, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0502, loss_cls: 0.2173, acc: 92.3960, loss_bbox: 0.2615, loss_mask: 0.2591, loss: 0.8116 2024-06-05 04:55:12,675 - mmdet - INFO - Epoch [3][2700/7330] lr: 1.000e-04, eta: 17:17:18, time: 0.952, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0556, loss_cls: 0.2293, acc: 92.0361, loss_bbox: 0.2771, loss_mask: 0.2673, loss: 0.8551 2024-06-05 04:55:59,498 - mmdet - INFO - Epoch [3][2750/7330] lr: 1.000e-04, eta: 17:16:46, time: 0.936, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0502, loss_cls: 0.2134, acc: 92.4963, loss_bbox: 0.2652, loss_mask: 0.2578, loss: 0.8124 2024-06-05 04:56:45,583 - mmdet - INFO - Epoch [3][2800/7330] lr: 1.000e-04, eta: 17:16:09, time: 0.922, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0493, loss_cls: 0.2098, acc: 92.6318, loss_bbox: 0.2591, loss_mask: 0.2632, loss: 0.8054 2024-06-05 04:57:42,016 - mmdet - INFO - Epoch [3][2850/7330] lr: 1.000e-04, eta: 17:16:15, time: 1.129, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0546, loss_cls: 0.2323, acc: 91.9375, loss_bbox: 0.2749, loss_mask: 0.2613, loss: 0.8494 2024-06-05 04:58:25,438 - mmdet - INFO - Epoch [3][2900/7330] lr: 1.000e-04, eta: 17:15:28, time: 0.868, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0452, loss_cls: 0.2170, acc: 92.4456, loss_bbox: 0.2621, loss_mask: 0.2584, loss: 0.8057 2024-06-05 04:59:09,722 - mmdet - INFO - Epoch [3][2950/7330] lr: 1.000e-04, eta: 17:14:45, time: 0.886, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0540, loss_cls: 0.2166, acc: 92.2971, loss_bbox: 0.2658, loss_mask: 0.2577, loss: 0.8201 2024-06-05 04:59:53,560 - mmdet - INFO - Epoch [3][3000/7330] lr: 1.000e-04, eta: 17:13:59, time: 0.877, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0513, loss_cls: 0.2126, acc: 92.5417, loss_bbox: 0.2608, loss_mask: 0.2603, loss: 0.8114 2024-06-05 05:00:37,102 - mmdet - INFO - Epoch [3][3050/7330] lr: 1.000e-04, eta: 17:13:13, time: 0.871, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0493, loss_cls: 0.2215, acc: 92.0508, loss_bbox: 0.2738, loss_mask: 0.2594, loss: 0.8313 2024-06-05 05:01:21,033 - mmdet - INFO - Epoch [3][3100/7330] lr: 1.000e-04, eta: 17:12:28, time: 0.879, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0531, loss_cls: 0.2153, acc: 92.4402, loss_bbox: 0.2636, loss_mask: 0.2608, loss: 0.8171 2024-06-05 05:02:04,823 - mmdet - INFO - Epoch [3][3150/7330] lr: 1.000e-04, eta: 17:11:43, time: 0.876, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0491, loss_cls: 0.2261, acc: 92.1267, loss_bbox: 0.2739, loss_mask: 0.2584, loss: 0.8335 2024-06-05 05:02:48,485 - mmdet - INFO - Epoch [3][3200/7330] lr: 1.000e-04, eta: 17:10:57, time: 0.873, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0516, loss_cls: 0.2177, acc: 92.3782, loss_bbox: 0.2602, loss_mask: 0.2632, loss: 0.8210 2024-06-05 05:03:31,657 - mmdet - INFO - Epoch [3][3250/7330] lr: 1.000e-04, eta: 17:10:09, time: 0.863, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0496, loss_cls: 0.2192, acc: 92.3474, loss_bbox: 0.2640, loss_mask: 0.2609, loss: 0.8183 2024-06-05 05:04:14,689 - mmdet - INFO - Epoch [3][3300/7330] lr: 1.000e-04, eta: 17:09:20, time: 0.861, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0464, loss_cls: 0.2149, acc: 92.5352, loss_bbox: 0.2557, loss_mask: 0.2520, loss: 0.7935 2024-06-05 05:04:58,071 - mmdet - INFO - Epoch [3][3350/7330] lr: 1.000e-04, eta: 17:08:33, time: 0.868, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0501, loss_cls: 0.2162, acc: 92.4756, loss_bbox: 0.2548, loss_mask: 0.2515, loss: 0.7974 2024-06-05 05:05:41,633 - mmdet - INFO - Epoch [3][3400/7330] lr: 1.000e-04, eta: 17:07:47, time: 0.871, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0483, loss_cls: 0.2127, acc: 92.5713, loss_bbox: 0.2575, loss_mask: 0.2591, loss: 0.8037 2024-06-05 05:06:25,476 - mmdet - INFO - Epoch [3][3450/7330] lr: 1.000e-04, eta: 17:07:02, time: 0.877, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0517, loss_cls: 0.2243, acc: 92.2542, loss_bbox: 0.2666, loss_mask: 0.2604, loss: 0.8281 2024-06-05 05:07:08,941 - mmdet - INFO - Epoch [3][3500/7330] lr: 1.000e-04, eta: 17:06:15, time: 0.869, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0518, loss_cls: 0.2130, acc: 92.4629, loss_bbox: 0.2620, loss_mask: 0.2597, loss: 0.8120 2024-06-05 05:07:52,678 - mmdet - INFO - Epoch [3][3550/7330] lr: 1.000e-04, eta: 17:05:30, time: 0.875, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0475, loss_cls: 0.2134, acc: 92.4338, loss_bbox: 0.2661, loss_mask: 0.2566, loss: 0.8063 2024-06-05 05:08:35,746 - mmdet - INFO - Epoch [3][3600/7330] lr: 1.000e-04, eta: 17:04:42, time: 0.861, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0513, loss_cls: 0.2107, acc: 92.4851, loss_bbox: 0.2647, loss_mask: 0.2546, loss: 0.8090 2024-06-05 05:09:19,554 - mmdet - INFO - Epoch [3][3650/7330] lr: 1.000e-04, eta: 17:03:57, time: 0.876, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0528, loss_cls: 0.2247, acc: 92.1140, loss_bbox: 0.2797, loss_mask: 0.2629, loss: 0.8480 2024-06-05 05:10:02,467 - mmdet - INFO - Epoch [3][3700/7330] lr: 1.000e-04, eta: 17:03:08, time: 0.858, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0466, loss_cls: 0.2046, acc: 92.8828, loss_bbox: 0.2474, loss_mask: 0.2532, loss: 0.7757 2024-06-05 05:10:45,920 - mmdet - INFO - Epoch [3][3750/7330] lr: 1.000e-04, eta: 17:02:21, time: 0.869, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0522, loss_cls: 0.2163, acc: 92.2512, loss_bbox: 0.2663, loss_mask: 0.2595, loss: 0.8199 2024-06-05 05:11:29,612 - mmdet - INFO - Epoch [3][3800/7330] lr: 1.000e-04, eta: 17:01:36, time: 0.874, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0468, loss_cls: 0.2120, acc: 92.4812, loss_bbox: 0.2563, loss_mask: 0.2542, loss: 0.7920 2024-06-05 05:12:13,521 - mmdet - INFO - Epoch [3][3850/7330] lr: 1.000e-04, eta: 17:00:51, time: 0.878, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0512, loss_cls: 0.2197, acc: 92.3562, loss_bbox: 0.2661, loss_mask: 0.2618, loss: 0.8235 2024-06-05 05:12:57,248 - mmdet - INFO - Epoch [3][3900/7330] lr: 1.000e-04, eta: 17:00:06, time: 0.875, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0479, loss_cls: 0.2088, acc: 92.7271, loss_bbox: 0.2551, loss_mask: 0.2521, loss: 0.7868 2024-06-05 05:13:44,080 - mmdet - INFO - Epoch [3][3950/7330] lr: 1.000e-04, eta: 16:59:32, time: 0.937, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0495, loss_cls: 0.2233, acc: 92.2156, loss_bbox: 0.2706, loss_mask: 0.2657, loss: 0.8319 2024-06-05 05:14:30,372 - mmdet - INFO - Epoch [3][4000/7330] lr: 1.000e-04, eta: 16:58:56, time: 0.926, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0486, loss_cls: 0.2095, acc: 92.8047, loss_bbox: 0.2495, loss_mask: 0.2551, loss: 0.7887 2024-06-05 05:15:15,824 - mmdet - INFO - Epoch [3][4050/7330] lr: 1.000e-04, eta: 16:58:17, time: 0.909, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0477, loss_cls: 0.2131, acc: 92.5959, loss_bbox: 0.2581, loss_mask: 0.2546, loss: 0.7970 2024-06-05 05:16:10,620 - mmdet - INFO - Epoch [3][4100/7330] lr: 1.000e-04, eta: 16:58:12, time: 1.096, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0484, loss_cls: 0.2139, acc: 92.6074, loss_bbox: 0.2587, loss_mask: 0.2568, loss: 0.8026 2024-06-05 05:16:53,950 - mmdet - INFO - Epoch [3][4150/7330] lr: 1.000e-04, eta: 16:57:25, time: 0.866, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0478, loss_cls: 0.2099, acc: 92.5776, loss_bbox: 0.2609, loss_mask: 0.2508, loss: 0.7931 2024-06-05 05:17:37,552 - mmdet - INFO - Epoch [3][4200/7330] lr: 1.000e-04, eta: 16:56:39, time: 0.872, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0497, loss_cls: 0.2190, acc: 92.3167, loss_bbox: 0.2630, loss_mask: 0.2622, loss: 0.8198 2024-06-05 05:18:21,380 - mmdet - INFO - Epoch [3][4250/7330] lr: 1.000e-04, eta: 16:55:53, time: 0.877, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0536, loss_cls: 0.2216, acc: 92.1921, loss_bbox: 0.2722, loss_mask: 0.2585, loss: 0.8316 2024-06-05 05:19:05,287 - mmdet - INFO - Epoch [3][4300/7330] lr: 1.000e-04, eta: 16:55:08, time: 0.878, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0511, loss_cls: 0.2196, acc: 92.2417, loss_bbox: 0.2638, loss_mask: 0.2575, loss: 0.8168 2024-06-05 05:19:48,485 - mmdet - INFO - Epoch [3][4350/7330] lr: 1.000e-04, eta: 16:54:21, time: 0.864, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0479, loss_cls: 0.2100, acc: 92.7085, loss_bbox: 0.2558, loss_mask: 0.2539, loss: 0.7907 2024-06-05 05:20:31,802 - mmdet - INFO - Epoch [3][4400/7330] lr: 1.000e-04, eta: 16:53:34, time: 0.866, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0496, loss_cls: 0.2200, acc: 92.4507, loss_bbox: 0.2581, loss_mask: 0.2544, loss: 0.8069 2024-06-05 05:21:15,106 - mmdet - INFO - Epoch [3][4450/7330] lr: 1.000e-04, eta: 16:52:47, time: 0.866, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0467, loss_cls: 0.2108, acc: 92.7285, loss_bbox: 0.2507, loss_mask: 0.2515, loss: 0.7834 2024-06-05 05:21:58,606 - mmdet - INFO - Epoch [3][4500/7330] lr: 1.000e-04, eta: 16:52:00, time: 0.870, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0507, loss_cls: 0.2169, acc: 92.3284, loss_bbox: 0.2649, loss_mask: 0.2601, loss: 0.8160 2024-06-05 05:22:42,509 - mmdet - INFO - Epoch [3][4550/7330] lr: 1.000e-04, eta: 16:51:15, time: 0.878, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0494, loss_cls: 0.2115, acc: 92.4941, loss_bbox: 0.2614, loss_mask: 0.2598, loss: 0.8079 2024-06-05 05:23:25,951 - mmdet - INFO - Epoch [3][4600/7330] lr: 1.000e-04, eta: 16:50:29, time: 0.869, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0480, loss_cls: 0.2087, acc: 92.6384, loss_bbox: 0.2539, loss_mask: 0.2535, loss: 0.7882 2024-06-05 05:24:09,592 - mmdet - INFO - Epoch [3][4650/7330] lr: 1.000e-04, eta: 16:49:43, time: 0.873, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0500, loss_cls: 0.2200, acc: 92.2739, loss_bbox: 0.2673, loss_mask: 0.2630, loss: 0.8264 2024-06-05 05:24:52,945 - mmdet - INFO - Epoch [3][4700/7330] lr: 1.000e-04, eta: 16:48:56, time: 0.867, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0506, loss_cls: 0.2160, acc: 92.4487, loss_bbox: 0.2582, loss_mask: 0.2521, loss: 0.8023 2024-06-05 05:25:36,539 - mmdet - INFO - Epoch [3][4750/7330] lr: 1.000e-04, eta: 16:48:10, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0511, loss_cls: 0.2115, acc: 92.5469, loss_bbox: 0.2593, loss_mask: 0.2618, loss: 0.8088 2024-06-05 05:26:20,004 - mmdet - INFO - Epoch [3][4800/7330] lr: 1.000e-04, eta: 16:47:24, time: 0.869, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0507, loss_cls: 0.2193, acc: 92.4314, loss_bbox: 0.2657, loss_mask: 0.2552, loss: 0.8161 2024-06-05 05:27:03,827 - mmdet - INFO - Epoch [3][4850/7330] lr: 1.000e-04, eta: 16:46:38, time: 0.876, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0478, loss_cls: 0.2107, acc: 92.7156, loss_bbox: 0.2498, loss_mask: 0.2531, loss: 0.7850 2024-06-05 05:27:47,486 - mmdet - INFO - Epoch [3][4900/7330] lr: 1.000e-04, eta: 16:45:53, time: 0.873, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0501, loss_cls: 0.2220, acc: 92.2607, loss_bbox: 0.2652, loss_mask: 0.2580, loss: 0.8225 2024-06-05 05:28:31,191 - mmdet - INFO - Epoch [3][4950/7330] lr: 1.000e-04, eta: 16:45:07, time: 0.874, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0485, loss_cls: 0.2164, acc: 92.4067, loss_bbox: 0.2611, loss_mask: 0.2596, loss: 0.8105 2024-06-05 05:29:15,020 - mmdet - INFO - Epoch [3][5000/7330] lr: 1.000e-04, eta: 16:44:22, time: 0.877, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0513, loss_cls: 0.2122, acc: 92.4651, loss_bbox: 0.2598, loss_mask: 0.2561, loss: 0.8039 2024-06-05 05:29:58,010 - mmdet - INFO - Epoch [3][5050/7330] lr: 1.000e-04, eta: 16:43:34, time: 0.860, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0508, loss_cls: 0.2107, acc: 92.5151, loss_bbox: 0.2532, loss_mask: 0.2564, loss: 0.7957 2024-06-05 05:30:41,518 - mmdet - INFO - Epoch [3][5100/7330] lr: 1.000e-04, eta: 16:42:48, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0490, loss_cls: 0.2040, acc: 92.8418, loss_bbox: 0.2497, loss_mask: 0.2484, loss: 0.7775 2024-06-05 05:31:25,565 - mmdet - INFO - Epoch [3][5150/7330] lr: 1.000e-04, eta: 16:42:03, time: 0.881, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0521, loss_cls: 0.2282, acc: 92.0874, loss_bbox: 0.2710, loss_mask: 0.2564, loss: 0.8336 2024-06-05 05:32:12,966 - mmdet - INFO - Epoch [3][5200/7330] lr: 1.000e-04, eta: 16:41:31, time: 0.948, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0519, loss_cls: 0.2204, acc: 92.2446, loss_bbox: 0.2676, loss_mask: 0.2578, loss: 0.8245 2024-06-05 05:32:58,586 - mmdet - INFO - Epoch [3][5250/7330] lr: 1.000e-04, eta: 16:40:52, time: 0.912, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0509, loss_cls: 0.2205, acc: 92.2571, loss_bbox: 0.2677, loss_mask: 0.2613, loss: 0.8273 2024-06-05 05:33:45,270 - mmdet - INFO - Epoch [3][5300/7330] lr: 1.000e-04, eta: 16:40:16, time: 0.934, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0542, loss_cls: 0.2229, acc: 92.0796, loss_bbox: 0.2708, loss_mask: 0.2568, loss: 0.8307 2024-06-05 05:34:38,390 - mmdet - INFO - Epoch [3][5350/7330] lr: 1.000e-04, eta: 16:40:03, time: 1.062, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0489, loss_cls: 0.2132, acc: 92.4939, loss_bbox: 0.2558, loss_mask: 0.2551, loss: 0.7956 2024-06-05 05:35:22,018 - mmdet - INFO - Epoch [3][5400/7330] lr: 1.000e-04, eta: 16:39:17, time: 0.873, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0494, loss_cls: 0.2144, acc: 92.5388, loss_bbox: 0.2586, loss_mask: 0.2586, loss: 0.8055 2024-06-05 05:36:05,917 - mmdet - INFO - Epoch [3][5450/7330] lr: 1.000e-04, eta: 16:38:32, time: 0.878, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0523, loss_cls: 0.2188, acc: 92.3025, loss_bbox: 0.2647, loss_mask: 0.2621, loss: 0.8233 2024-06-05 05:36:48,828 - mmdet - INFO - Epoch [3][5500/7330] lr: 1.000e-04, eta: 16:37:43, time: 0.858, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0468, loss_cls: 0.2068, acc: 92.7749, loss_bbox: 0.2496, loss_mask: 0.2563, loss: 0.7837 2024-06-05 05:37:31,435 - mmdet - INFO - Epoch [3][5550/7330] lr: 1.000e-04, eta: 16:36:54, time: 0.852, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0477, loss_cls: 0.2052, acc: 92.8193, loss_bbox: 0.2442, loss_mask: 0.2571, loss: 0.7781 2024-06-05 05:38:15,005 - mmdet - INFO - Epoch [3][5600/7330] lr: 1.000e-04, eta: 16:36:08, time: 0.872, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0490, loss_cls: 0.2177, acc: 92.4172, loss_bbox: 0.2590, loss_mask: 0.2591, loss: 0.8081 2024-06-05 05:38:58,565 - mmdet - INFO - Epoch [3][5650/7330] lr: 1.000e-04, eta: 16:35:22, time: 0.871, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0486, loss_cls: 0.2051, acc: 92.8965, loss_bbox: 0.2422, loss_mask: 0.2550, loss: 0.7740 2024-06-05 05:39:43,003 - mmdet - INFO - Epoch [3][5700/7330] lr: 1.000e-04, eta: 16:34:39, time: 0.889, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0518, loss_cls: 0.2282, acc: 91.9463, loss_bbox: 0.2739, loss_mask: 0.2610, loss: 0.8410 2024-06-05 05:40:26,601 - mmdet - INFO - Epoch [3][5750/7330] lr: 1.000e-04, eta: 16:33:53, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0481, loss_cls: 0.2183, acc: 92.2637, loss_bbox: 0.2640, loss_mask: 0.2580, loss: 0.8153 2024-06-05 05:41:10,037 - mmdet - INFO - Epoch [3][5800/7330] lr: 1.000e-04, eta: 16:33:06, time: 0.869, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0490, loss_cls: 0.2057, acc: 92.6802, loss_bbox: 0.2552, loss_mask: 0.2526, loss: 0.7875 2024-06-05 05:41:53,438 - mmdet - INFO - Epoch [3][5850/7330] lr: 1.000e-04, eta: 16:32:20, time: 0.868, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0520, loss_cls: 0.2195, acc: 92.3074, loss_bbox: 0.2654, loss_mask: 0.2646, loss: 0.8271 2024-06-05 05:42:37,111 - mmdet - INFO - Epoch [3][5900/7330] lr: 1.000e-04, eta: 16:31:34, time: 0.873, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0479, loss_cls: 0.2118, acc: 92.4565, loss_bbox: 0.2677, loss_mask: 0.2577, loss: 0.8096 2024-06-05 05:43:21,286 - mmdet - INFO - Epoch [3][5950/7330] lr: 1.000e-04, eta: 16:30:50, time: 0.883, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0500, loss_cls: 0.2245, acc: 92.1089, loss_bbox: 0.2697, loss_mask: 0.2595, loss: 0.8296 2024-06-05 05:44:05,180 - mmdet - INFO - Epoch [3][6000/7330] lr: 1.000e-04, eta: 16:30:05, time: 0.878, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0539, loss_cls: 0.2234, acc: 92.1338, loss_bbox: 0.2697, loss_mask: 0.2592, loss: 0.8305 2024-06-05 05:44:48,571 - mmdet - INFO - Epoch [3][6050/7330] lr: 1.000e-04, eta: 16:29:19, time: 0.868, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0481, loss_cls: 0.2109, acc: 92.4880, loss_bbox: 0.2555, loss_mask: 0.2510, loss: 0.7886 2024-06-05 05:45:32,335 - mmdet - INFO - Epoch [3][6100/7330] lr: 1.000e-04, eta: 16:28:33, time: 0.875, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0486, loss_cls: 0.2099, acc: 92.7180, loss_bbox: 0.2516, loss_mask: 0.2487, loss: 0.7824 2024-06-05 05:46:15,807 - mmdet - INFO - Epoch [3][6150/7330] lr: 1.000e-04, eta: 16:27:47, time: 0.869, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0517, loss_cls: 0.2099, acc: 92.6497, loss_bbox: 0.2530, loss_mask: 0.2536, loss: 0.7942 2024-06-05 05:46:58,814 - mmdet - INFO - Epoch [3][6200/7330] lr: 1.000e-04, eta: 16:26:59, time: 0.860, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0497, loss_cls: 0.2072, acc: 92.7285, loss_bbox: 0.2551, loss_mask: 0.2617, loss: 0.7992 2024-06-05 05:47:42,033 - mmdet - INFO - Epoch [3][6250/7330] lr: 1.000e-04, eta: 16:26:12, time: 0.864, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0479, loss_cls: 0.2105, acc: 92.6609, loss_bbox: 0.2527, loss_mask: 0.2562, loss: 0.7923 2024-06-05 05:48:25,670 - mmdet - INFO - Epoch [3][6300/7330] lr: 1.000e-04, eta: 16:25:27, time: 0.873, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0508, loss_cls: 0.2101, acc: 92.6216, loss_bbox: 0.2498, loss_mask: 0.2550, loss: 0.7900 2024-06-05 05:49:09,079 - mmdet - INFO - Epoch [3][6350/7330] lr: 1.000e-04, eta: 16:24:40, time: 0.868, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0480, loss_cls: 0.2111, acc: 92.5920, loss_bbox: 0.2530, loss_mask: 0.2581, loss: 0.7952 2024-06-05 05:49:52,797 - mmdet - INFO - Epoch [3][6400/7330] lr: 1.000e-04, eta: 16:23:55, time: 0.874, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0531, loss_cls: 0.2174, acc: 92.3232, loss_bbox: 0.2681, loss_mask: 0.2572, loss: 0.8208 2024-06-05 05:50:38,732 - mmdet - INFO - Epoch [3][6450/7330] lr: 1.000e-04, eta: 16:23:16, time: 0.919, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0495, loss_cls: 0.2171, acc: 92.3845, loss_bbox: 0.2590, loss_mask: 0.2506, loss: 0.7993 2024-06-05 05:51:25,113 - mmdet - INFO - Epoch [3][6500/7330] lr: 1.000e-04, eta: 16:22:39, time: 0.928, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0471, loss_cls: 0.2106, acc: 92.6492, loss_bbox: 0.2555, loss_mask: 0.2527, loss: 0.7902 2024-06-05 05:52:10,712 - mmdet - INFO - Epoch [3][6550/7330] lr: 1.000e-04, eta: 16:22:00, time: 0.912, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0531, loss_cls: 0.2284, acc: 91.9861, loss_bbox: 0.2768, loss_mask: 0.2711, loss: 0.8560 2024-06-05 05:53:05,682 - mmdet - INFO - Epoch [3][6600/7330] lr: 1.000e-04, eta: 16:21:50, time: 1.099, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0485, loss_cls: 0.2178, acc: 92.3918, loss_bbox: 0.2600, loss_mask: 0.2539, loss: 0.8050 2024-06-05 05:53:49,443 - mmdet - INFO - Epoch [3][6650/7330] lr: 1.000e-04, eta: 16:21:04, time: 0.875, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0471, loss_cls: 0.2203, acc: 92.4568, loss_bbox: 0.2536, loss_mask: 0.2564, loss: 0.8005 2024-06-05 05:54:32,708 - mmdet - INFO - Epoch [3][6700/7330] lr: 1.000e-04, eta: 16:20:17, time: 0.865, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0477, loss_cls: 0.2107, acc: 92.3796, loss_bbox: 0.2602, loss_mask: 0.2596, loss: 0.8026 2024-06-05 05:55:16,282 - mmdet - INFO - Epoch [3][6750/7330] lr: 1.000e-04, eta: 16:19:31, time: 0.871, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0480, loss_cls: 0.2129, acc: 92.5991, loss_bbox: 0.2559, loss_mask: 0.2615, loss: 0.8019 2024-06-05 05:56:00,605 - mmdet - INFO - Epoch [3][6800/7330] lr: 1.000e-04, eta: 16:18:48, time: 0.886, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0522, loss_cls: 0.2185, acc: 92.2378, loss_bbox: 0.2646, loss_mask: 0.2552, loss: 0.8167 2024-06-05 05:56:44,373 - mmdet - INFO - Epoch [3][6850/7330] lr: 1.000e-04, eta: 16:18:02, time: 0.875, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0473, loss_cls: 0.2064, acc: 92.8069, loss_bbox: 0.2497, loss_mask: 0.2476, loss: 0.7771 2024-06-05 05:57:28,319 - mmdet - INFO - Epoch [3][6900/7330] lr: 1.000e-04, eta: 16:17:18, time: 0.879, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0463, loss_cls: 0.2096, acc: 92.6116, loss_bbox: 0.2582, loss_mask: 0.2527, loss: 0.7904 2024-06-05 05:58:12,914 - mmdet - INFO - Epoch [3][6950/7330] lr: 1.000e-04, eta: 16:16:35, time: 0.892, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0506, loss_cls: 0.2190, acc: 92.2729, loss_bbox: 0.2634, loss_mask: 0.2590, loss: 0.8183 2024-06-05 05:58:56,524 - mmdet - INFO - Epoch [3][7000/7330] lr: 1.000e-04, eta: 16:15:49, time: 0.872, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0469, loss_cls: 0.2150, acc: 92.4958, loss_bbox: 0.2608, loss_mask: 0.2569, loss: 0.8030 2024-06-05 05:59:39,919 - mmdet - INFO - Epoch [3][7050/7330] lr: 1.000e-04, eta: 16:15:02, time: 0.868, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0457, loss_cls: 0.2055, acc: 92.8533, loss_bbox: 0.2490, loss_mask: 0.2473, loss: 0.7706 2024-06-05 06:00:23,410 - mmdet - INFO - Epoch [3][7100/7330] lr: 1.000e-04, eta: 16:14:16, time: 0.870, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0498, loss_cls: 0.2123, acc: 92.5781, loss_bbox: 0.2524, loss_mask: 0.2519, loss: 0.7920 2024-06-05 06:01:07,204 - mmdet - INFO - Epoch [3][7150/7330] lr: 1.000e-04, eta: 16:13:31, time: 0.876, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0482, loss_cls: 0.2174, acc: 92.4146, loss_bbox: 0.2638, loss_mask: 0.2546, loss: 0.8081 2024-06-05 06:01:51,506 - mmdet - INFO - Epoch [3][7200/7330] lr: 1.000e-04, eta: 16:12:47, time: 0.886, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0525, loss_cls: 0.2192, acc: 92.3374, loss_bbox: 0.2592, loss_mask: 0.2549, loss: 0.8109 2024-06-05 06:02:35,245 - mmdet - INFO - Epoch [3][7250/7330] lr: 1.000e-04, eta: 16:12:02, time: 0.875, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0485, loss_cls: 0.2123, acc: 92.5100, loss_bbox: 0.2584, loss_mask: 0.2587, loss: 0.8023 2024-06-05 06:03:18,456 - mmdet - INFO - Epoch [3][7300/7330] lr: 1.000e-04, eta: 16:11:15, time: 0.864, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0517, loss_cls: 0.2131, acc: 92.4951, loss_bbox: 0.2598, loss_mask: 0.2639, loss: 0.8141 2024-06-05 06:03:45,246 - mmdet - INFO - Saving checkpoint at 3 epochs 2024-06-05 06:05:34,801 - mmdet - INFO - Evaluating bbox... 2024-06-05 06:06:03,746 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.403 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.645 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.438 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.447 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.562 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.535 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.535 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.535 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.327 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.583 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.702 2024-06-05 06:06:03,746 - mmdet - INFO - Evaluating segm... 2024-06-05 06:06:39,838 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.376 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.607 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.398 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.156 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.410 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.602 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.495 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.495 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.495 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.266 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.548 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.696 2024-06-05 06:06:40,393 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 06:06:40,395 - mmdet - INFO - Epoch(val) [3][625] bbox_mAP: 0.4030, bbox_mAP_50: 0.6450, bbox_mAP_75: 0.4380, bbox_mAP_s: 0.2280, bbox_mAP_m: 0.4470, bbox_mAP_l: 0.5620, bbox_mAP_copypaste: 0.403 0.645 0.438 0.228 0.447 0.562, segm_mAP: 0.3760, segm_mAP_50: 0.6070, segm_mAP_75: 0.3980, segm_mAP_s: 0.1560, segm_mAP_m: 0.4100, segm_mAP_l: 0.6020, segm_mAP_copypaste: 0.376 0.607 0.398 0.156 0.410 0.602 2024-06-05 06:07:27,287 - mmdet - INFO - Epoch [4][50/7330] lr: 1.000e-04, eta: 16:08:53, time: 0.937, data_time: 0.118, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0480, loss_cls: 0.2064, acc: 92.5320, loss_bbox: 0.2626, loss_mask: 0.2504, loss: 0.7893 2024-06-05 06:08:12,998 - mmdet - INFO - Epoch [4][100/7330] lr: 1.000e-04, eta: 16:08:14, time: 0.914, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0500, loss_cls: 0.2053, acc: 92.6523, loss_bbox: 0.2593, loss_mask: 0.2551, loss: 0.7926 2024-06-05 06:08:56,977 - mmdet - INFO - Epoch [4][150/7330] lr: 1.000e-04, eta: 16:07:30, time: 0.879, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0483, loss_cls: 0.2041, acc: 92.6006, loss_bbox: 0.2587, loss_mask: 0.2524, loss: 0.7851 2024-06-05 06:09:42,505 - mmdet - INFO - Epoch [4][200/7330] lr: 1.000e-04, eta: 16:06:50, time: 0.911, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0461, loss_cls: 0.1933, acc: 93.0308, loss_bbox: 0.2484, loss_mask: 0.2456, loss: 0.7536 2024-06-05 06:10:34,208 - mmdet - INFO - Epoch [4][250/7330] lr: 1.000e-04, eta: 16:06:28, time: 1.034, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0499, loss_cls: 0.2110, acc: 92.5068, loss_bbox: 0.2615, loss_mask: 0.2484, loss: 0.7937 2024-06-05 06:11:17,996 - mmdet - INFO - Epoch [4][300/7330] lr: 1.000e-04, eta: 16:05:43, time: 0.875, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0497, loss_cls: 0.2044, acc: 92.6333, loss_bbox: 0.2597, loss_mask: 0.2505, loss: 0.7858 2024-06-05 06:12:01,959 - mmdet - INFO - Epoch [4][350/7330] lr: 1.000e-04, eta: 16:04:58, time: 0.880, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0469, loss_cls: 0.2007, acc: 92.6814, loss_bbox: 0.2543, loss_mask: 0.2515, loss: 0.7753 2024-06-05 06:12:46,101 - mmdet - INFO - Epoch [4][400/7330] lr: 1.000e-04, eta: 16:04:14, time: 0.883, data_time: 0.071, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0486, loss_cls: 0.1990, acc: 92.8696, loss_bbox: 0.2540, loss_mask: 0.2472, loss: 0.7723 2024-06-05 06:13:29,675 - mmdet - INFO - Epoch [4][450/7330] lr: 1.000e-04, eta: 16:03:29, time: 0.871, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0473, loss_cls: 0.1983, acc: 92.9224, loss_bbox: 0.2479, loss_mask: 0.2494, loss: 0.7654 2024-06-05 06:14:13,720 - mmdet - INFO - Epoch [4][500/7330] lr: 1.000e-04, eta: 16:02:44, time: 0.881, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0482, loss_cls: 0.2013, acc: 92.8098, loss_bbox: 0.2495, loss_mask: 0.2460, loss: 0.7662 2024-06-05 06:14:57,171 - mmdet - INFO - Epoch [4][550/7330] lr: 1.000e-04, eta: 16:01:58, time: 0.869, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0467, loss_cls: 0.1946, acc: 93.1292, loss_bbox: 0.2461, loss_mask: 0.2479, loss: 0.7566 2024-06-05 06:15:41,436 - mmdet - INFO - Epoch [4][600/7330] lr: 1.000e-04, eta: 16:01:15, time: 0.885, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0475, loss_cls: 0.1910, acc: 93.1277, loss_bbox: 0.2445, loss_mask: 0.2438, loss: 0.7473 2024-06-05 06:16:25,325 - mmdet - INFO - Epoch [4][650/7330] lr: 1.000e-04, eta: 16:00:30, time: 0.878, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0486, loss_cls: 0.2095, acc: 92.4839, loss_bbox: 0.2642, loss_mask: 0.2553, loss: 0.7992 2024-06-05 06:17:09,059 - mmdet - INFO - Epoch [4][700/7330] lr: 1.000e-04, eta: 15:59:45, time: 0.875, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0511, loss_cls: 0.2067, acc: 92.5876, loss_bbox: 0.2554, loss_mask: 0.2475, loss: 0.7850 2024-06-05 06:17:52,830 - mmdet - INFO - Epoch [4][750/7330] lr: 1.000e-04, eta: 15:59:00, time: 0.875, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0486, loss_cls: 0.1983, acc: 92.7991, loss_bbox: 0.2474, loss_mask: 0.2493, loss: 0.7657 2024-06-05 06:18:36,220 - mmdet - INFO - Epoch [4][800/7330] lr: 1.000e-04, eta: 15:58:13, time: 0.868, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0449, loss_cls: 0.1945, acc: 92.9849, loss_bbox: 0.2508, loss_mask: 0.2459, loss: 0.7587 2024-06-05 06:19:19,863 - mmdet - INFO - Epoch [4][850/7330] lr: 1.000e-04, eta: 15:57:28, time: 0.872, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0476, loss_cls: 0.2018, acc: 92.7588, loss_bbox: 0.2479, loss_mask: 0.2461, loss: 0.7637 2024-06-05 06:20:03,171 - mmdet - INFO - Epoch [4][900/7330] lr: 1.000e-04, eta: 15:56:42, time: 0.867, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0461, loss_cls: 0.2035, acc: 92.7432, loss_bbox: 0.2528, loss_mask: 0.2519, loss: 0.7772 2024-06-05 06:20:47,105 - mmdet - INFO - Epoch [4][950/7330] lr: 1.000e-04, eta: 15:55:57, time: 0.879, data_time: 0.076, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0484, loss_cls: 0.2085, acc: 92.5461, loss_bbox: 0.2607, loss_mask: 0.2513, loss: 0.7896 2024-06-05 06:21:31,869 - mmdet - INFO - Epoch [4][1000/7330] lr: 1.000e-04, eta: 15:55:15, time: 0.895, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0517, loss_cls: 0.2105, acc: 92.4102, loss_bbox: 0.2666, loss_mask: 0.2484, loss: 0.8010 2024-06-05 06:22:16,221 - mmdet - INFO - Epoch [4][1050/7330] lr: 1.000e-04, eta: 15:54:31, time: 0.887, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0478, loss_cls: 0.2078, acc: 92.5818, loss_bbox: 0.2556, loss_mask: 0.2446, loss: 0.7776 2024-06-05 06:23:00,068 - mmdet - INFO - Epoch [4][1100/7330] lr: 1.000e-04, eta: 15:53:46, time: 0.877, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0475, loss_cls: 0.2012, acc: 92.7979, loss_bbox: 0.2581, loss_mask: 0.2545, loss: 0.7840 2024-06-05 06:23:43,797 - mmdet - INFO - Epoch [4][1150/7330] lr: 1.000e-04, eta: 15:53:01, time: 0.875, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0465, loss_cls: 0.1989, acc: 92.8870, loss_bbox: 0.2440, loss_mask: 0.2483, loss: 0.7602 2024-06-05 06:24:27,587 - mmdet - INFO - Epoch [4][1200/7330] lr: 1.000e-04, eta: 15:52:16, time: 0.876, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0480, loss_cls: 0.2006, acc: 92.8823, loss_bbox: 0.2503, loss_mask: 0.2497, loss: 0.7715 2024-06-05 06:25:11,232 - mmdet - INFO - Epoch [4][1250/7330] lr: 1.000e-04, eta: 15:51:31, time: 0.873, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0507, loss_cls: 0.2044, acc: 92.4377, loss_bbox: 0.2606, loss_mask: 0.2484, loss: 0.7863 2024-06-05 06:25:54,785 - mmdet - INFO - Epoch [4][1300/7330] lr: 1.000e-04, eta: 15:50:45, time: 0.871, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0492, loss_cls: 0.2034, acc: 92.7217, loss_bbox: 0.2511, loss_mask: 0.2469, loss: 0.7727 2024-06-05 06:26:41,555 - mmdet - INFO - Epoch [4][1350/7330] lr: 1.000e-04, eta: 15:50:08, time: 0.935, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0500, loss_cls: 0.2048, acc: 92.5774, loss_bbox: 0.2529, loss_mask: 0.2490, loss: 0.7786 2024-06-05 06:27:29,594 - mmdet - INFO - Epoch [4][1400/7330] lr: 1.000e-04, eta: 15:49:35, time: 0.960, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0461, loss_cls: 0.2047, acc: 92.7217, loss_bbox: 0.2542, loss_mask: 0.2532, loss: 0.7791 2024-06-05 06:28:15,089 - mmdet - INFO - Epoch [4][1450/7330] lr: 1.000e-04, eta: 15:48:55, time: 0.910, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0479, loss_cls: 0.2046, acc: 92.6423, loss_bbox: 0.2534, loss_mask: 0.2520, loss: 0.7781 2024-06-05 06:29:05,943 - mmdet - INFO - Epoch [4][1500/7330] lr: 1.000e-04, eta: 15:48:29, time: 1.017, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0487, loss_cls: 0.1998, acc: 92.7432, loss_bbox: 0.2516, loss_mask: 0.2497, loss: 0.7703 2024-06-05 06:29:48,821 - mmdet - INFO - Epoch [4][1550/7330] lr: 1.000e-04, eta: 15:47:42, time: 0.858, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0457, loss_cls: 0.2051, acc: 92.7617, loss_bbox: 0.2508, loss_mask: 0.2506, loss: 0.7732 2024-06-05 06:30:32,195 - mmdet - INFO - Epoch [4][1600/7330] lr: 1.000e-04, eta: 15:46:55, time: 0.867, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0467, loss_cls: 0.1940, acc: 92.9819, loss_bbox: 0.2410, loss_mask: 0.2391, loss: 0.7415 2024-06-05 06:31:18,533 - mmdet - INFO - Epoch [4][1650/7330] lr: 1.000e-04, eta: 15:46:17, time: 0.927, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0487, loss_cls: 0.1934, acc: 93.0620, loss_bbox: 0.2423, loss_mask: 0.2481, loss: 0.7539 2024-06-05 06:32:02,539 - mmdet - INFO - Epoch [4][1700/7330] lr: 1.000e-04, eta: 15:45:33, time: 0.880, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0449, loss_cls: 0.1993, acc: 92.8987, loss_bbox: 0.2479, loss_mask: 0.2424, loss: 0.7557 2024-06-05 06:32:46,375 - mmdet - INFO - Epoch [4][1750/7330] lr: 1.000e-04, eta: 15:44:48, time: 0.877, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0465, loss_cls: 0.2045, acc: 92.8022, loss_bbox: 0.2526, loss_mask: 0.2454, loss: 0.7708 2024-06-05 06:33:31,985 - mmdet - INFO - Epoch [4][1800/7330] lr: 1.000e-04, eta: 15:44:08, time: 0.912, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0484, loss_cls: 0.2064, acc: 92.6719, loss_bbox: 0.2521, loss_mask: 0.2504, loss: 0.7781 2024-06-05 06:34:15,072 - mmdet - INFO - Epoch [4][1850/7330] lr: 1.000e-04, eta: 15:43:21, time: 0.862, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0456, loss_cls: 0.1996, acc: 92.7969, loss_bbox: 0.2482, loss_mask: 0.2455, loss: 0.7606 2024-06-05 06:34:58,121 - mmdet - INFO - Epoch [4][1900/7330] lr: 1.000e-04, eta: 15:42:34, time: 0.861, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0466, loss_cls: 0.2026, acc: 92.6899, loss_bbox: 0.2507, loss_mask: 0.2469, loss: 0.7685 2024-06-05 06:35:42,001 - mmdet - INFO - Epoch [4][1950/7330] lr: 1.000e-04, eta: 15:41:49, time: 0.878, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0488, loss_cls: 0.2087, acc: 92.5796, loss_bbox: 0.2538, loss_mask: 0.2449, loss: 0.7780 2024-06-05 06:36:25,474 - mmdet - INFO - Epoch [4][2000/7330] lr: 1.000e-04, eta: 15:41:03, time: 0.870, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0446, loss_cls: 0.1972, acc: 92.9363, loss_bbox: 0.2433, loss_mask: 0.2451, loss: 0.7507 2024-06-05 06:37:09,220 - mmdet - INFO - Epoch [4][2050/7330] lr: 1.000e-04, eta: 15:40:18, time: 0.875, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0452, loss_cls: 0.1992, acc: 92.8994, loss_bbox: 0.2462, loss_mask: 0.2433, loss: 0.7557 2024-06-05 06:37:52,481 - mmdet - INFO - Epoch [4][2100/7330] lr: 1.000e-04, eta: 15:39:31, time: 0.865, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0436, loss_cls: 0.1934, acc: 93.0779, loss_bbox: 0.2413, loss_mask: 0.2428, loss: 0.7416 2024-06-05 06:38:36,293 - mmdet - INFO - Epoch [4][2150/7330] lr: 1.000e-04, eta: 15:38:46, time: 0.876, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0468, loss_cls: 0.1999, acc: 92.7534, loss_bbox: 0.2515, loss_mask: 0.2440, loss: 0.7637 2024-06-05 06:39:20,086 - mmdet - INFO - Epoch [4][2200/7330] lr: 1.000e-04, eta: 15:38:01, time: 0.876, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0445, loss_cls: 0.1983, acc: 92.7742, loss_bbox: 0.2546, loss_mask: 0.2475, loss: 0.7659 2024-06-05 06:40:04,019 - mmdet - INFO - Epoch [4][2250/7330] lr: 1.000e-04, eta: 15:37:17, time: 0.879, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0497, loss_cls: 0.2085, acc: 92.4709, loss_bbox: 0.2630, loss_mask: 0.2499, loss: 0.7965 2024-06-05 06:40:48,081 - mmdet - INFO - Epoch [4][2300/7330] lr: 1.000e-04, eta: 15:36:32, time: 0.881, data_time: 0.079, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0502, loss_cls: 0.2182, acc: 92.2349, loss_bbox: 0.2612, loss_mask: 0.2542, loss: 0.8066 2024-06-05 06:41:31,745 - mmdet - INFO - Epoch [4][2350/7330] lr: 1.000e-04, eta: 15:35:47, time: 0.873, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0496, loss_cls: 0.2064, acc: 92.6023, loss_bbox: 0.2553, loss_mask: 0.2530, loss: 0.7854 2024-06-05 06:42:15,265 - mmdet - INFO - Epoch [4][2400/7330] lr: 1.000e-04, eta: 15:35:01, time: 0.870, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0487, loss_cls: 0.2098, acc: 92.4807, loss_bbox: 0.2579, loss_mask: 0.2529, loss: 0.7902 2024-06-05 06:42:58,346 - mmdet - INFO - Epoch [4][2450/7330] lr: 1.000e-04, eta: 15:34:14, time: 0.862, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0468, loss_cls: 0.1987, acc: 92.8340, loss_bbox: 0.2473, loss_mask: 0.2490, loss: 0.7635 2024-06-05 06:43:41,841 - mmdet - INFO - Epoch [4][2500/7330] lr: 1.000e-04, eta: 15:33:29, time: 0.870, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0478, loss_cls: 0.2044, acc: 92.7861, loss_bbox: 0.2558, loss_mask: 0.2466, loss: 0.7760 2024-06-05 06:44:25,089 - mmdet - INFO - Epoch [4][2550/7330] lr: 1.000e-04, eta: 15:32:42, time: 0.865, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0460, loss_cls: 0.1991, acc: 92.8250, loss_bbox: 0.2485, loss_mask: 0.2496, loss: 0.7640 2024-06-05 06:45:08,424 - mmdet - INFO - Epoch [4][2600/7330] lr: 1.000e-04, eta: 15:31:56, time: 0.866, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0444, loss_cls: 0.1989, acc: 92.9348, loss_bbox: 0.2475, loss_mask: 0.2492, loss: 0.7599 2024-06-05 06:45:57,247 - mmdet - INFO - Epoch [4][2650/7330] lr: 1.000e-04, eta: 15:31:24, time: 0.977, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0483, loss_cls: 0.2098, acc: 92.4294, loss_bbox: 0.2641, loss_mask: 0.2536, loss: 0.7989 2024-06-05 06:46:40,914 - mmdet - INFO - Epoch [4][2700/7330] lr: 1.000e-04, eta: 15:30:39, time: 0.873, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0468, loss_cls: 0.2031, acc: 92.8032, loss_bbox: 0.2471, loss_mask: 0.2519, loss: 0.7707 2024-06-05 06:47:33,415 - mmdet - INFO - Epoch [4][2750/7330] lr: 1.000e-04, eta: 15:30:16, time: 1.050, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0466, loss_cls: 0.2021, acc: 92.8000, loss_bbox: 0.2555, loss_mask: 0.2486, loss: 0.7743 2024-06-05 06:48:16,905 - mmdet - INFO - Epoch [4][2800/7330] lr: 1.000e-04, eta: 15:29:30, time: 0.870, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0453, loss_cls: 0.1951, acc: 92.9109, loss_bbox: 0.2475, loss_mask: 0.2410, loss: 0.7500 2024-06-05 06:49:00,469 - mmdet - INFO - Epoch [4][2850/7330] lr: 1.000e-04, eta: 15:28:45, time: 0.871, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0474, loss_cls: 0.1965, acc: 92.9458, loss_bbox: 0.2465, loss_mask: 0.2412, loss: 0.7523 2024-06-05 06:49:44,176 - mmdet - INFO - Epoch [4][2900/7330] lr: 1.000e-04, eta: 15:27:59, time: 0.874, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0467, loss_cls: 0.2023, acc: 92.7668, loss_bbox: 0.2483, loss_mask: 0.2485, loss: 0.7661 2024-06-05 06:50:30,158 - mmdet - INFO - Epoch [4][2950/7330] lr: 1.000e-04, eta: 15:27:20, time: 0.920, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0487, loss_cls: 0.1936, acc: 93.1455, loss_bbox: 0.2445, loss_mask: 0.2440, loss: 0.7523 2024-06-05 06:51:13,324 - mmdet - INFO - Epoch [4][3000/7330] lr: 1.000e-04, eta: 15:26:33, time: 0.863, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0460, loss_cls: 0.1961, acc: 93.0269, loss_bbox: 0.2404, loss_mask: 0.2466, loss: 0.7527 2024-06-05 06:51:59,329 - mmdet - INFO - Epoch [4][3050/7330] lr: 1.000e-04, eta: 15:25:54, time: 0.921, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0462, loss_cls: 0.1917, acc: 93.1772, loss_bbox: 0.2389, loss_mask: 0.2446, loss: 0.7419 2024-06-05 06:52:43,541 - mmdet - INFO - Epoch [4][3100/7330] lr: 1.000e-04, eta: 15:25:10, time: 0.884, data_time: 0.081, memory: 11350, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0509, loss_cls: 0.2091, acc: 92.5979, loss_bbox: 0.2620, loss_mask: 0.2517, loss: 0.7969 2024-06-05 06:53:26,942 - mmdet - INFO - Epoch [4][3150/7330] lr: 1.000e-04, eta: 15:24:24, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0432, loss_cls: 0.1925, acc: 93.0908, loss_bbox: 0.2362, loss_mask: 0.2400, loss: 0.7328 2024-06-05 06:54:10,510 - mmdet - INFO - Epoch [4][3200/7330] lr: 1.000e-04, eta: 15:23:38, time: 0.872, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0461, loss_cls: 0.2033, acc: 92.7908, loss_bbox: 0.2507, loss_mask: 0.2503, loss: 0.7711 2024-06-05 06:54:53,769 - mmdet - INFO - Epoch [4][3250/7330] lr: 1.000e-04, eta: 15:22:52, time: 0.865, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0477, loss_cls: 0.2011, acc: 92.7925, loss_bbox: 0.2543, loss_mask: 0.2499, loss: 0.7744 2024-06-05 06:55:37,251 - mmdet - INFO - Epoch [4][3300/7330] lr: 1.000e-04, eta: 15:22:06, time: 0.870, data_time: 0.039, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0461, loss_cls: 0.1934, acc: 93.0513, loss_bbox: 0.2419, loss_mask: 0.2403, loss: 0.7442 2024-06-05 06:56:20,331 - mmdet - INFO - Epoch [4][3350/7330] lr: 1.000e-04, eta: 15:21:19, time: 0.862, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0481, loss_cls: 0.2048, acc: 92.7512, loss_bbox: 0.2480, loss_mask: 0.2456, loss: 0.7678 2024-06-05 06:57:04,122 - mmdet - INFO - Epoch [4][3400/7330] lr: 1.000e-04, eta: 15:20:34, time: 0.876, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0461, loss_cls: 0.1963, acc: 92.9541, loss_bbox: 0.2421, loss_mask: 0.2409, loss: 0.7480 2024-06-05 06:57:47,608 - mmdet - INFO - Epoch [4][3450/7330] lr: 1.000e-04, eta: 15:19:49, time: 0.870, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0472, loss_cls: 0.2043, acc: 92.7930, loss_bbox: 0.2522, loss_mask: 0.2479, loss: 0.7727 2024-06-05 06:58:30,232 - mmdet - INFO - Epoch [4][3500/7330] lr: 1.000e-04, eta: 15:19:01, time: 0.853, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0440, loss_cls: 0.1902, acc: 93.1384, loss_bbox: 0.2408, loss_mask: 0.2446, loss: 0.7407 2024-06-05 06:59:14,136 - mmdet - INFO - Epoch [4][3550/7330] lr: 1.000e-04, eta: 15:18:16, time: 0.878, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0481, loss_cls: 0.2066, acc: 92.6802, loss_bbox: 0.2543, loss_mask: 0.2478, loss: 0.7804 2024-06-05 06:59:57,619 - mmdet - INFO - Epoch [4][3600/7330] lr: 1.000e-04, eta: 15:17:30, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0439, loss_cls: 0.1963, acc: 93.1101, loss_bbox: 0.2380, loss_mask: 0.2458, loss: 0.7451 2024-06-05 07:00:41,254 - mmdet - INFO - Epoch [4][3650/7330] lr: 1.000e-04, eta: 15:16:45, time: 0.873, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0452, loss_cls: 0.2014, acc: 92.9211, loss_bbox: 0.2457, loss_mask: 0.2447, loss: 0.7573 2024-06-05 07:01:24,788 - mmdet - INFO - Epoch [4][3700/7330] lr: 1.000e-04, eta: 15:15:59, time: 0.871, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0509, loss_cls: 0.2102, acc: 92.6287, loss_bbox: 0.2561, loss_mask: 0.2504, loss: 0.7915 2024-06-05 07:02:08,624 - mmdet - INFO - Epoch [4][3750/7330] lr: 1.000e-04, eta: 15:15:15, time: 0.877, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0481, loss_cls: 0.2002, acc: 92.7615, loss_bbox: 0.2484, loss_mask: 0.2447, loss: 0.7641 2024-06-05 07:02:52,573 - mmdet - INFO - Epoch [4][3800/7330] lr: 1.000e-04, eta: 15:14:30, time: 0.879, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0486, loss_cls: 0.2045, acc: 92.7310, loss_bbox: 0.2551, loss_mask: 0.2542, loss: 0.7864 2024-06-05 07:03:36,148 - mmdet - INFO - Epoch [4][3850/7330] lr: 1.000e-04, eta: 15:13:45, time: 0.871, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0481, loss_cls: 0.2063, acc: 92.6211, loss_bbox: 0.2562, loss_mask: 0.2489, loss: 0.7811 2024-06-05 07:04:24,303 - mmdet - INFO - Epoch [4][3900/7330] lr: 1.000e-04, eta: 15:13:10, time: 0.963, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0460, loss_cls: 0.2046, acc: 92.8098, loss_bbox: 0.2496, loss_mask: 0.2492, loss: 0.7703 2024-06-05 07:05:07,090 - mmdet - INFO - Epoch [4][3950/7330] lr: 1.000e-04, eta: 15:12:23, time: 0.856, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0466, loss_cls: 0.2068, acc: 92.6855, loss_bbox: 0.2470, loss_mask: 0.2444, loss: 0.7656 2024-06-05 07:05:57,516 - mmdet - INFO - Epoch [4][4000/7330] lr: 1.000e-04, eta: 15:11:54, time: 1.009, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0469, loss_cls: 0.1997, acc: 92.9426, loss_bbox: 0.2422, loss_mask: 0.2459, loss: 0.7574 2024-06-05 07:06:43,145 - mmdet - INFO - Epoch [4][4050/7330] lr: 1.000e-04, eta: 15:11:13, time: 0.913, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0513, loss_cls: 0.2097, acc: 92.6006, loss_bbox: 0.2512, loss_mask: 0.2580, loss: 0.7931 2024-06-05 07:07:27,102 - mmdet - INFO - Epoch [4][4100/7330] lr: 1.000e-04, eta: 15:10:28, time: 0.879, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0474, loss_cls: 0.2021, acc: 92.9099, loss_bbox: 0.2465, loss_mask: 0.2486, loss: 0.7653 2024-06-05 07:08:10,558 - mmdet - INFO - Epoch [4][4150/7330] lr: 1.000e-04, eta: 15:09:43, time: 0.869, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0462, loss_cls: 0.1932, acc: 93.0620, loss_bbox: 0.2392, loss_mask: 0.2399, loss: 0.7391 2024-06-05 07:08:56,828 - mmdet - INFO - Epoch [4][4200/7330] lr: 1.000e-04, eta: 15:09:03, time: 0.925, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0465, loss_cls: 0.2035, acc: 92.7422, loss_bbox: 0.2530, loss_mask: 0.2461, loss: 0.7714 2024-06-05 07:09:40,312 - mmdet - INFO - Epoch [4][4250/7330] lr: 1.000e-04, eta: 15:08:18, time: 0.869, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0502, loss_cls: 0.2070, acc: 92.5498, loss_bbox: 0.2585, loss_mask: 0.2515, loss: 0.7900 2024-06-05 07:10:23,659 - mmdet - INFO - Epoch [4][4300/7330] lr: 1.000e-04, eta: 15:07:32, time: 0.867, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0473, loss_cls: 0.2051, acc: 92.7942, loss_bbox: 0.2489, loss_mask: 0.2463, loss: 0.7686 2024-06-05 07:11:09,990 - mmdet - INFO - Epoch [4][4350/7330] lr: 1.000e-04, eta: 15:06:53, time: 0.927, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0456, loss_cls: 0.1994, acc: 92.9250, loss_bbox: 0.2420, loss_mask: 0.2422, loss: 0.7499 2024-06-05 07:11:53,185 - mmdet - INFO - Epoch [4][4400/7330] lr: 1.000e-04, eta: 15:06:06, time: 0.864, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0455, loss_cls: 0.1958, acc: 93.0854, loss_bbox: 0.2375, loss_mask: 0.2439, loss: 0.7438 2024-06-05 07:12:36,507 - mmdet - INFO - Epoch [4][4450/7330] lr: 1.000e-04, eta: 15:05:20, time: 0.866, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0434, loss_cls: 0.1911, acc: 93.2148, loss_bbox: 0.2364, loss_mask: 0.2386, loss: 0.7296 2024-06-05 07:13:19,946 - mmdet - INFO - Epoch [4][4500/7330] lr: 1.000e-04, eta: 15:04:34, time: 0.869, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0467, loss_cls: 0.2002, acc: 92.7788, loss_bbox: 0.2496, loss_mask: 0.2456, loss: 0.7635 2024-06-05 07:14:03,785 - mmdet - INFO - Epoch [4][4550/7330] lr: 1.000e-04, eta: 15:03:50, time: 0.877, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0490, loss_cls: 0.2110, acc: 92.4502, loss_bbox: 0.2539, loss_mask: 0.2457, loss: 0.7832 2024-06-05 07:14:47,377 - mmdet - INFO - Epoch [4][4600/7330] lr: 1.000e-04, eta: 15:03:04, time: 0.872, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0489, loss_cls: 0.1991, acc: 92.9236, loss_bbox: 0.2461, loss_mask: 0.2481, loss: 0.7632 2024-06-05 07:15:30,545 - mmdet - INFO - Epoch [4][4650/7330] lr: 1.000e-04, eta: 15:02:18, time: 0.863, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0483, loss_cls: 0.2007, acc: 92.7622, loss_bbox: 0.2479, loss_mask: 0.2510, loss: 0.7708 2024-06-05 07:16:14,471 - mmdet - INFO - Epoch [4][4700/7330] lr: 1.000e-04, eta: 15:01:33, time: 0.879, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0493, loss_cls: 0.2035, acc: 92.6704, loss_bbox: 0.2479, loss_mask: 0.2464, loss: 0.7687 2024-06-05 07:16:57,887 - mmdet - INFO - Epoch [4][4750/7330] lr: 1.000e-04, eta: 15:00:47, time: 0.868, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0485, loss_cls: 0.2083, acc: 92.6782, loss_bbox: 0.2506, loss_mask: 0.2493, loss: 0.7808 2024-06-05 07:17:41,712 - mmdet - INFO - Epoch [4][4800/7330] lr: 1.000e-04, eta: 15:00:02, time: 0.876, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0471, loss_cls: 0.2079, acc: 92.4878, loss_bbox: 0.2601, loss_mask: 0.2492, loss: 0.7854 2024-06-05 07:18:24,975 - mmdet - INFO - Epoch [4][4850/7330] lr: 1.000e-04, eta: 14:59:16, time: 0.865, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0466, loss_cls: 0.2008, acc: 92.8037, loss_bbox: 0.2526, loss_mask: 0.2445, loss: 0.7653 2024-06-05 07:19:08,148 - mmdet - INFO - Epoch [4][4900/7330] lr: 1.000e-04, eta: 14:58:30, time: 0.863, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0462, loss_cls: 0.2067, acc: 92.5896, loss_bbox: 0.2543, loss_mask: 0.2464, loss: 0.7748 2024-06-05 07:19:51,469 - mmdet - INFO - Epoch [4][4950/7330] lr: 1.000e-04, eta: 14:57:44, time: 0.866, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0462, loss_cls: 0.2040, acc: 92.7673, loss_bbox: 0.2494, loss_mask: 0.2478, loss: 0.7664 2024-06-05 07:20:35,020 - mmdet - INFO - Epoch [4][5000/7330] lr: 1.000e-04, eta: 14:56:58, time: 0.871, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0449, loss_cls: 0.1935, acc: 93.0581, loss_bbox: 0.2392, loss_mask: 0.2436, loss: 0.7428 2024-06-05 07:21:17,955 - mmdet - INFO - Epoch [4][5050/7330] lr: 1.000e-04, eta: 14:56:12, time: 0.859, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0450, loss_cls: 0.2002, acc: 92.9678, loss_bbox: 0.2442, loss_mask: 0.2404, loss: 0.7508 2024-06-05 07:22:01,581 - mmdet - INFO - Epoch [4][5100/7330] lr: 1.000e-04, eta: 14:55:26, time: 0.873, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0492, loss_cls: 0.2087, acc: 92.5752, loss_bbox: 0.2571, loss_mask: 0.2457, loss: 0.7814 2024-06-05 07:22:49,397 - mmdet - INFO - Epoch [4][5150/7330] lr: 1.000e-04, eta: 14:54:50, time: 0.956, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0439, loss_cls: 0.1941, acc: 93.0779, loss_bbox: 0.2455, loss_mask: 0.2421, loss: 0.7449 2024-06-05 07:23:32,939 - mmdet - INFO - Epoch [4][5200/7330] lr: 1.000e-04, eta: 14:54:05, time: 0.871, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0470, loss_cls: 0.2029, acc: 92.7742, loss_bbox: 0.2498, loss_mask: 0.2502, loss: 0.7705 2024-06-05 07:24:21,391 - mmdet - INFO - Epoch [4][5250/7330] lr: 1.000e-04, eta: 14:53:30, time: 0.969, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0488, loss_cls: 0.2040, acc: 92.5886, loss_bbox: 0.2584, loss_mask: 0.2523, loss: 0.7851 2024-06-05 07:25:10,768 - mmdet - INFO - Epoch [4][5300/7330] lr: 1.000e-04, eta: 14:52:58, time: 0.988, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0468, loss_cls: 0.2008, acc: 92.7517, loss_bbox: 0.2497, loss_mask: 0.2425, loss: 0.7613 2024-06-05 07:25:53,982 - mmdet - INFO - Epoch [4][5350/7330] lr: 1.000e-04, eta: 14:52:12, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0447, loss_cls: 0.2003, acc: 92.9104, loss_bbox: 0.2462, loss_mask: 0.2380, loss: 0.7496 2024-06-05 07:26:37,789 - mmdet - INFO - Epoch [4][5400/7330] lr: 1.000e-04, eta: 14:51:27, time: 0.876, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0492, loss_cls: 0.2074, acc: 92.4971, loss_bbox: 0.2618, loss_mask: 0.2585, loss: 0.7984 2024-06-05 07:27:23,382 - mmdet - INFO - Epoch [4][5450/7330] lr: 1.000e-04, eta: 14:50:46, time: 0.912, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0446, loss_cls: 0.1908, acc: 93.2170, loss_bbox: 0.2402, loss_mask: 0.2436, loss: 0.7404 2024-06-05 07:28:06,422 - mmdet - INFO - Epoch [4][5500/7330] lr: 1.000e-04, eta: 14:49:59, time: 0.861, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0475, loss_cls: 0.1936, acc: 93.0923, loss_bbox: 0.2402, loss_mask: 0.2409, loss: 0.7430 2024-06-05 07:28:50,382 - mmdet - INFO - Epoch [4][5550/7330] lr: 1.000e-04, eta: 14:49:15, time: 0.879, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0475, loss_cls: 0.1967, acc: 93.0120, loss_bbox: 0.2468, loss_mask: 0.2391, loss: 0.7517 2024-06-05 07:29:37,052 - mmdet - INFO - Epoch [4][5600/7330] lr: 1.000e-04, eta: 14:48:36, time: 0.933, data_time: 0.035, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0457, loss_cls: 0.1979, acc: 92.9448, loss_bbox: 0.2439, loss_mask: 0.2401, loss: 0.7511 2024-06-05 07:30:20,774 - mmdet - INFO - Epoch [4][5650/7330] lr: 1.000e-04, eta: 14:47:51, time: 0.874, data_time: 0.076, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0481, loss_cls: 0.2002, acc: 92.8479, loss_bbox: 0.2433, loss_mask: 0.2454, loss: 0.7588 2024-06-05 07:31:04,475 - mmdet - INFO - Epoch [4][5700/7330] lr: 1.000e-04, eta: 14:47:06, time: 0.874, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0448, loss_cls: 0.2032, acc: 92.8035, loss_bbox: 0.2424, loss_mask: 0.2468, loss: 0.7588 2024-06-05 07:31:48,002 - mmdet - INFO - Epoch [4][5750/7330] lr: 1.000e-04, eta: 14:46:20, time: 0.871, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0456, loss_cls: 0.1975, acc: 92.8840, loss_bbox: 0.2480, loss_mask: 0.2471, loss: 0.7616 2024-06-05 07:32:31,149 - mmdet - INFO - Epoch [4][5800/7330] lr: 1.000e-04, eta: 14:45:34, time: 0.863, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0436, loss_cls: 0.1979, acc: 92.9441, loss_bbox: 0.2372, loss_mask: 0.2390, loss: 0.7372 2024-06-05 07:33:14,381 - mmdet - INFO - Epoch [4][5850/7330] lr: 1.000e-04, eta: 14:44:48, time: 0.865, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0460, loss_cls: 0.2012, acc: 92.8157, loss_bbox: 0.2481, loss_mask: 0.2393, loss: 0.7546 2024-06-05 07:33:58,146 - mmdet - INFO - Epoch [4][5900/7330] lr: 1.000e-04, eta: 14:44:03, time: 0.875, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0492, loss_cls: 0.1950, acc: 92.9497, loss_bbox: 0.2512, loss_mask: 0.2470, loss: 0.7652 2024-06-05 07:34:41,414 - mmdet - INFO - Epoch [4][5950/7330] lr: 1.000e-04, eta: 14:43:17, time: 0.865, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0458, loss_cls: 0.2003, acc: 92.7854, loss_bbox: 0.2454, loss_mask: 0.2458, loss: 0.7580 2024-06-05 07:35:24,838 - mmdet - INFO - Epoch [4][6000/7330] lr: 1.000e-04, eta: 14:42:31, time: 0.868, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0476, loss_cls: 0.1974, acc: 92.9575, loss_bbox: 0.2468, loss_mask: 0.2506, loss: 0.7650 2024-06-05 07:36:07,712 - mmdet - INFO - Epoch [4][6050/7330] lr: 1.000e-04, eta: 14:41:44, time: 0.857, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0424, loss_cls: 0.1980, acc: 93.0818, loss_bbox: 0.2346, loss_mask: 0.2405, loss: 0.7345 2024-06-05 07:36:50,794 - mmdet - INFO - Epoch [4][6100/7330] lr: 1.000e-04, eta: 14:40:58, time: 0.862, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0476, loss_cls: 0.1932, acc: 93.1189, loss_bbox: 0.2388, loss_mask: 0.2443, loss: 0.7453 2024-06-05 07:37:34,092 - mmdet - INFO - Epoch [4][6150/7330] lr: 1.000e-04, eta: 14:40:12, time: 0.866, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0487, loss_cls: 0.1980, acc: 92.8997, loss_bbox: 0.2474, loss_mask: 0.2473, loss: 0.7626 2024-06-05 07:38:17,621 - mmdet - INFO - Epoch [4][6200/7330] lr: 1.000e-04, eta: 14:39:26, time: 0.871, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0445, loss_cls: 0.2006, acc: 92.7732, loss_bbox: 0.2419, loss_mask: 0.2430, loss: 0.7516 2024-06-05 07:39:00,875 - mmdet - INFO - Epoch [4][6250/7330] lr: 1.000e-04, eta: 14:38:40, time: 0.865, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0448, loss_cls: 0.1968, acc: 93.0022, loss_bbox: 0.2429, loss_mask: 0.2403, loss: 0.7452 2024-06-05 07:39:44,379 - mmdet - INFO - Epoch [4][6300/7330] lr: 1.000e-04, eta: 14:37:55, time: 0.870, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0456, loss_cls: 0.2014, acc: 92.8079, loss_bbox: 0.2482, loss_mask: 0.2436, loss: 0.7614 2024-06-05 07:40:28,254 - mmdet - INFO - Epoch [4][6350/7330] lr: 1.000e-04, eta: 14:37:10, time: 0.877, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0488, loss_cls: 0.2129, acc: 92.4187, loss_bbox: 0.2517, loss_mask: 0.2452, loss: 0.7822 2024-06-05 07:41:13,680 - mmdet - INFO - Epoch [4][6400/7330] lr: 1.000e-04, eta: 14:36:29, time: 0.908, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0482, loss_cls: 0.2020, acc: 92.7461, loss_bbox: 0.2490, loss_mask: 0.2451, loss: 0.7656 2024-06-05 07:41:59,614 - mmdet - INFO - Epoch [4][6450/7330] lr: 1.000e-04, eta: 14:35:48, time: 0.919, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0467, loss_cls: 0.2029, acc: 92.7419, loss_bbox: 0.2532, loss_mask: 0.2461, loss: 0.7681 2024-06-05 07:42:45,510 - mmdet - INFO - Epoch [4][6500/7330] lr: 1.000e-04, eta: 14:35:08, time: 0.918, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0463, loss_cls: 0.1937, acc: 93.0859, loss_bbox: 0.2466, loss_mask: 0.2480, loss: 0.7550 2024-06-05 07:43:35,737 - mmdet - INFO - Epoch [4][6550/7330] lr: 1.000e-04, eta: 14:34:36, time: 1.005, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0456, loss_cls: 0.2016, acc: 92.8130, loss_bbox: 0.2505, loss_mask: 0.2455, loss: 0.7640 2024-06-05 07:44:19,469 - mmdet - INFO - Epoch [4][6600/7330] lr: 1.000e-04, eta: 14:33:51, time: 0.875, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0456, loss_cls: 0.1985, acc: 92.9214, loss_bbox: 0.2430, loss_mask: 0.2372, loss: 0.7462 2024-06-05 07:45:02,839 - mmdet - INFO - Epoch [4][6650/7330] lr: 1.000e-04, eta: 14:33:05, time: 0.867, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0428, loss_cls: 0.1964, acc: 93.0737, loss_bbox: 0.2429, loss_mask: 0.2422, loss: 0.7431 2024-06-05 07:45:48,201 - mmdet - INFO - Epoch [4][6700/7330] lr: 1.000e-04, eta: 14:32:24, time: 0.907, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0474, loss_cls: 0.2048, acc: 92.7537, loss_bbox: 0.2541, loss_mask: 0.2516, loss: 0.7804 2024-06-05 07:46:31,025 - mmdet - INFO - Epoch [4][6750/7330] lr: 1.000e-04, eta: 14:31:37, time: 0.857, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0457, loss_cls: 0.1948, acc: 93.1238, loss_bbox: 0.2343, loss_mask: 0.2419, loss: 0.7383 2024-06-05 07:47:14,542 - mmdet - INFO - Epoch [4][6800/7330] lr: 1.000e-04, eta: 14:30:51, time: 0.870, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0487, loss_cls: 0.2108, acc: 92.5522, loss_bbox: 0.2535, loss_mask: 0.2484, loss: 0.7847 2024-06-05 07:48:01,112 - mmdet - INFO - Epoch [4][6850/7330] lr: 1.000e-04, eta: 14:30:12, time: 0.931, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0423, loss_cls: 0.1939, acc: 93.1719, loss_bbox: 0.2322, loss_mask: 0.2428, loss: 0.7299 2024-06-05 07:48:44,501 - mmdet - INFO - Epoch [4][6900/7330] lr: 1.000e-04, eta: 14:29:27, time: 0.868, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0488, loss_cls: 0.1981, acc: 92.8030, loss_bbox: 0.2461, loss_mask: 0.2424, loss: 0.7607 2024-06-05 07:49:28,249 - mmdet - INFO - Epoch [4][6950/7330] lr: 1.000e-04, eta: 14:28:42, time: 0.875, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0424, loss_cls: 0.1958, acc: 92.9993, loss_bbox: 0.2404, loss_mask: 0.2435, loss: 0.7419 2024-06-05 07:50:12,136 - mmdet - INFO - Epoch [4][7000/7330] lr: 1.000e-04, eta: 14:27:57, time: 0.878, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0495, loss_cls: 0.2069, acc: 92.5737, loss_bbox: 0.2561, loss_mask: 0.2451, loss: 0.7808 2024-06-05 07:50:55,899 - mmdet - INFO - Epoch [4][7050/7330] lr: 1.000e-04, eta: 14:27:12, time: 0.875, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0466, loss_cls: 0.2084, acc: 92.5388, loss_bbox: 0.2573, loss_mask: 0.2553, loss: 0.7905 2024-06-05 07:51:39,464 - mmdet - INFO - Epoch [4][7100/7330] lr: 1.000e-04, eta: 14:26:27, time: 0.871, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0462, loss_cls: 0.1949, acc: 93.1172, loss_bbox: 0.2450, loss_mask: 0.2438, loss: 0.7502 2024-06-05 07:52:22,948 - mmdet - INFO - Epoch [4][7150/7330] lr: 1.000e-04, eta: 14:25:41, time: 0.870, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0447, loss_cls: 0.1860, acc: 93.2573, loss_bbox: 0.2376, loss_mask: 0.2460, loss: 0.7360 2024-06-05 07:53:06,770 - mmdet - INFO - Epoch [4][7200/7330] lr: 1.000e-04, eta: 14:24:56, time: 0.876, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0452, loss_cls: 0.2035, acc: 92.7283, loss_bbox: 0.2487, loss_mask: 0.2490, loss: 0.7700 2024-06-05 07:53:50,224 - mmdet - INFO - Epoch [4][7250/7330] lr: 1.000e-04, eta: 14:24:11, time: 0.869, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0482, loss_cls: 0.2009, acc: 92.7910, loss_bbox: 0.2449, loss_mask: 0.2436, loss: 0.7602 2024-06-05 07:54:33,930 - mmdet - INFO - Epoch [4][7300/7330] lr: 1.000e-04, eta: 14:23:26, time: 0.874, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0470, loss_cls: 0.1938, acc: 93.0376, loss_bbox: 0.2437, loss_mask: 0.2457, loss: 0.7526 2024-06-05 07:55:01,016 - mmdet - INFO - Saving checkpoint at 4 epochs 2024-06-05 07:56:49,474 - mmdet - INFO - Evaluating bbox... 2024-06-05 07:57:18,637 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.427 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.661 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.469 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.466 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.559 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.559 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.559 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.370 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.715 2024-06-05 07:57:18,638 - mmdet - INFO - Evaluating segm... 2024-06-05 07:57:45,866 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.388 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.627 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.413 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.172 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.423 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.608 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.509 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.509 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.509 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.695 2024-06-05 07:57:46,466 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 07:57:46,468 - mmdet - INFO - Epoch(val) [4][625] bbox_mAP: 0.4270, bbox_mAP_50: 0.6610, bbox_mAP_75: 0.4690, bbox_mAP_s: 0.2460, bbox_mAP_m: 0.4660, bbox_mAP_l: 0.5910, bbox_mAP_copypaste: 0.427 0.661 0.469 0.246 0.466 0.591, segm_mAP: 0.3880, segm_mAP_50: 0.6270, segm_mAP_75: 0.4130, segm_mAP_s: 0.1720, segm_mAP_m: 0.4230, segm_mAP_l: 0.6080, segm_mAP_copypaste: 0.388 0.627 0.413 0.172 0.423 0.608 2024-06-05 07:58:33,264 - mmdet - INFO - Epoch [5][50/7330] lr: 1.000e-04, eta: 14:21:27, time: 0.936, data_time: 0.106, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0453, loss_cls: 0.1901, acc: 93.0510, loss_bbox: 0.2422, loss_mask: 0.2365, loss: 0.7338 2024-06-05 07:59:21,053 - mmdet - INFO - Epoch [5][100/7330] lr: 1.000e-04, eta: 14:20:51, time: 0.956, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0441, loss_cls: 0.1862, acc: 93.1580, loss_bbox: 0.2369, loss_mask: 0.2391, loss: 0.7241 2024-06-05 08:00:06,793 - mmdet - INFO - Epoch [5][150/7330] lr: 1.000e-04, eta: 14:20:10, time: 0.915, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0452, loss_cls: 0.1881, acc: 93.1597, loss_bbox: 0.2377, loss_mask: 0.2374, loss: 0.7276 2024-06-05 08:00:52,198 - mmdet - INFO - Epoch [5][200/7330] lr: 1.000e-04, eta: 14:19:28, time: 0.908, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0467, loss_cls: 0.1871, acc: 93.2231, loss_bbox: 0.2420, loss_mask: 0.2421, loss: 0.7370 2024-06-05 08:01:35,688 - mmdet - INFO - Epoch [5][250/7330] lr: 1.000e-04, eta: 14:18:43, time: 0.870, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0467, loss_cls: 0.1930, acc: 92.9236, loss_bbox: 0.2453, loss_mask: 0.2472, loss: 0.7522 2024-06-05 08:02:19,009 - mmdet - INFO - Epoch [5][300/7330] lr: 1.000e-04, eta: 14:17:57, time: 0.866, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0438, loss_cls: 0.1909, acc: 93.0925, loss_bbox: 0.2379, loss_mask: 0.2343, loss: 0.7264 2024-06-05 08:03:02,417 - mmdet - INFO - Epoch [5][350/7330] lr: 1.000e-04, eta: 14:17:11, time: 0.869, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0435, loss_cls: 0.1819, acc: 93.3613, loss_bbox: 0.2387, loss_mask: 0.2382, loss: 0.7208 2024-06-05 08:03:45,951 - mmdet - INFO - Epoch [5][400/7330] lr: 1.000e-04, eta: 14:16:26, time: 0.871, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0424, loss_cls: 0.1821, acc: 93.3721, loss_bbox: 0.2371, loss_mask: 0.2412, loss: 0.7214 2024-06-05 08:04:29,424 - mmdet - INFO - Epoch [5][450/7330] lr: 1.000e-04, eta: 14:15:41, time: 0.870, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0458, loss_cls: 0.1904, acc: 93.0686, loss_bbox: 0.2412, loss_mask: 0.2382, loss: 0.7348 2024-06-05 08:05:13,985 - mmdet - INFO - Epoch [5][500/7330] lr: 1.000e-04, eta: 14:14:58, time: 0.891, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0439, loss_cls: 0.1872, acc: 93.1433, loss_bbox: 0.2388, loss_mask: 0.2328, loss: 0.7201 2024-06-05 08:05:57,370 - mmdet - INFO - Epoch [5][550/7330] lr: 1.000e-04, eta: 14:14:12, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0436, loss_cls: 0.1881, acc: 93.1755, loss_bbox: 0.2359, loss_mask: 0.2431, loss: 0.7292 2024-06-05 08:06:42,458 - mmdet - INFO - Epoch [5][600/7330] lr: 1.000e-04, eta: 14:13:30, time: 0.902, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0438, loss_cls: 0.1849, acc: 93.3933, loss_bbox: 0.2333, loss_mask: 0.2316, loss: 0.7113 2024-06-05 08:07:26,525 - mmdet - INFO - Epoch [5][650/7330] lr: 1.000e-04, eta: 14:12:46, time: 0.881, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0482, loss_cls: 0.1937, acc: 92.8997, loss_bbox: 0.2460, loss_mask: 0.2394, loss: 0.7466 2024-06-05 08:08:10,073 - mmdet - INFO - Epoch [5][700/7330] lr: 1.000e-04, eta: 14:12:00, time: 0.871, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0455, loss_cls: 0.1919, acc: 93.1514, loss_bbox: 0.2385, loss_mask: 0.2350, loss: 0.7311 2024-06-05 08:08:54,170 - mmdet - INFO - Epoch [5][750/7330] lr: 1.000e-04, eta: 14:11:16, time: 0.882, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0426, loss_cls: 0.1862, acc: 93.3015, loss_bbox: 0.2323, loss_mask: 0.2333, loss: 0.7121 2024-06-05 08:09:37,967 - mmdet - INFO - Epoch [5][800/7330] lr: 1.000e-04, eta: 14:10:32, time: 0.876, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0449, loss_cls: 0.1852, acc: 93.2031, loss_bbox: 0.2420, loss_mask: 0.2369, loss: 0.7277 2024-06-05 08:10:21,903 - mmdet - INFO - Epoch [5][850/7330] lr: 1.000e-04, eta: 14:09:47, time: 0.879, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0446, loss_cls: 0.1915, acc: 93.0903, loss_bbox: 0.2431, loss_mask: 0.2321, loss: 0.7314 2024-06-05 08:11:08,053 - mmdet - INFO - Epoch [5][900/7330] lr: 1.000e-04, eta: 14:09:07, time: 0.923, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0405, loss_cls: 0.1855, acc: 93.2317, loss_bbox: 0.2367, loss_mask: 0.2387, loss: 0.7179 2024-06-05 08:11:51,888 - mmdet - INFO - Epoch [5][950/7330] lr: 1.000e-04, eta: 14:08:22, time: 0.877, data_time: 0.080, memory: 11350, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0447, loss_cls: 0.1816, acc: 93.3999, loss_bbox: 0.2306, loss_mask: 0.2283, loss: 0.7039 2024-06-05 08:12:35,194 - mmdet - INFO - Epoch [5][1000/7330] lr: 1.000e-04, eta: 14:07:37, time: 0.866, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0451, loss_cls: 0.1852, acc: 93.2600, loss_bbox: 0.2398, loss_mask: 0.2421, loss: 0.7310 2024-06-05 08:13:18,955 - mmdet - INFO - Epoch [5][1050/7330] lr: 1.000e-04, eta: 14:06:52, time: 0.875, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0458, loss_cls: 0.1827, acc: 93.2859, loss_bbox: 0.2374, loss_mask: 0.2416, loss: 0.7273 2024-06-05 08:14:02,593 - mmdet - INFO - Epoch [5][1100/7330] lr: 1.000e-04, eta: 14:06:07, time: 0.873, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0461, loss_cls: 0.1894, acc: 93.0852, loss_bbox: 0.2406, loss_mask: 0.2362, loss: 0.7314 2024-06-05 08:14:46,059 - mmdet - INFO - Epoch [5][1150/7330] lr: 1.000e-04, eta: 14:05:21, time: 0.869, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0441, loss_cls: 0.1886, acc: 93.1316, loss_bbox: 0.2396, loss_mask: 0.2390, loss: 0.7300 2024-06-05 08:15:28,821 - mmdet - INFO - Epoch [5][1200/7330] lr: 1.000e-04, eta: 14:04:35, time: 0.855, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0416, loss_cls: 0.1795, acc: 93.5083, loss_bbox: 0.2285, loss_mask: 0.2362, loss: 0.7041 2024-06-05 08:16:13,196 - mmdet - INFO - Epoch [5][1250/7330] lr: 1.000e-04, eta: 14:03:51, time: 0.888, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0478, loss_cls: 0.1932, acc: 93.0149, loss_bbox: 0.2445, loss_mask: 0.2416, loss: 0.7473 2024-06-05 08:16:56,786 - mmdet - INFO - Epoch [5][1300/7330] lr: 1.000e-04, eta: 14:03:06, time: 0.872, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0475, loss_cls: 0.2002, acc: 92.9255, loss_bbox: 0.2450, loss_mask: 0.2424, loss: 0.7550 2024-06-05 08:17:44,408 - mmdet - INFO - Epoch [5][1350/7330] lr: 1.000e-04, eta: 14:02:28, time: 0.952, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0440, loss_cls: 0.1821, acc: 93.3389, loss_bbox: 0.2390, loss_mask: 0.2387, loss: 0.7216 2024-06-05 08:18:30,080 - mmdet - INFO - Epoch [5][1400/7330] lr: 1.000e-04, eta: 14:01:47, time: 0.913, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0441, loss_cls: 0.1895, acc: 93.1672, loss_bbox: 0.2358, loss_mask: 0.2348, loss: 0.7230 2024-06-05 08:19:16,181 - mmdet - INFO - Epoch [5][1450/7330] lr: 1.000e-04, eta: 14:01:07, time: 0.922, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0441, loss_cls: 0.1873, acc: 93.1921, loss_bbox: 0.2425, loss_mask: 0.2428, loss: 0.7358 2024-06-05 08:19:59,372 - mmdet - INFO - Epoch [5][1500/7330] lr: 1.000e-04, eta: 14:00:21, time: 0.864, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0427, loss_cls: 0.1870, acc: 93.2378, loss_bbox: 0.2377, loss_mask: 0.2366, loss: 0.7228 2024-06-05 08:20:42,309 - mmdet - INFO - Epoch [5][1550/7330] lr: 1.000e-04, eta: 13:59:35, time: 0.859, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0430, loss_cls: 0.1890, acc: 93.2561, loss_bbox: 0.2348, loss_mask: 0.2417, loss: 0.7267 2024-06-05 08:21:27,743 - mmdet - INFO - Epoch [5][1600/7330] lr: 1.000e-04, eta: 13:58:53, time: 0.909, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0448, loss_cls: 0.1856, acc: 93.3149, loss_bbox: 0.2373, loss_mask: 0.2406, loss: 0.7281 2024-06-05 08:22:13,924 - mmdet - INFO - Epoch [5][1650/7330] lr: 1.000e-04, eta: 13:58:13, time: 0.924, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0454, loss_cls: 0.1968, acc: 92.9988, loss_bbox: 0.2427, loss_mask: 0.2414, loss: 0.7456 2024-06-05 08:22:57,660 - mmdet - INFO - Epoch [5][1700/7330] lr: 1.000e-04, eta: 13:57:28, time: 0.875, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0458, loss_cls: 0.1899, acc: 93.0928, loss_bbox: 0.2432, loss_mask: 0.2427, loss: 0.7415 2024-06-05 08:23:41,769 - mmdet - INFO - Epoch [5][1750/7330] lr: 1.000e-04, eta: 13:56:44, time: 0.882, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0474, loss_cls: 0.1875, acc: 93.2505, loss_bbox: 0.2375, loss_mask: 0.2392, loss: 0.7305 2024-06-05 08:24:25,126 - mmdet - INFO - Epoch [5][1800/7330] lr: 1.000e-04, eta: 13:55:58, time: 0.867, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0445, loss_cls: 0.1953, acc: 93.0342, loss_bbox: 0.2409, loss_mask: 0.2351, loss: 0.7343 2024-06-05 08:25:12,150 - mmdet - INFO - Epoch [5][1850/7330] lr: 1.000e-04, eta: 13:55:19, time: 0.940, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0469, loss_cls: 0.1918, acc: 92.9995, loss_bbox: 0.2442, loss_mask: 0.2387, loss: 0.7430 2024-06-05 08:25:55,828 - mmdet - INFO - Epoch [5][1900/7330] lr: 1.000e-04, eta: 13:54:34, time: 0.874, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0440, loss_cls: 0.1844, acc: 93.2573, loss_bbox: 0.2358, loss_mask: 0.2366, loss: 0.7198 2024-06-05 08:26:39,659 - mmdet - INFO - Epoch [5][1950/7330] lr: 1.000e-04, eta: 13:53:50, time: 0.877, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0465, loss_cls: 0.1977, acc: 92.8503, loss_bbox: 0.2495, loss_mask: 0.2475, loss: 0.7625 2024-06-05 08:27:23,300 - mmdet - INFO - Epoch [5][2000/7330] lr: 1.000e-04, eta: 13:53:05, time: 0.873, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0455, loss_cls: 0.1877, acc: 93.1409, loss_bbox: 0.2363, loss_mask: 0.2410, loss: 0.7290 2024-06-05 08:28:07,217 - mmdet - INFO - Epoch [5][2050/7330] lr: 1.000e-04, eta: 13:52:20, time: 0.878, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0470, loss_cls: 0.1904, acc: 93.0588, loss_bbox: 0.2444, loss_mask: 0.2348, loss: 0.7360 2024-06-05 08:28:51,206 - mmdet - INFO - Epoch [5][2100/7330] lr: 1.000e-04, eta: 13:51:36, time: 0.880, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0479, loss_cls: 0.1962, acc: 92.7429, loss_bbox: 0.2513, loss_mask: 0.2403, loss: 0.7560 2024-06-05 08:29:38,253 - mmdet - INFO - Epoch [5][2150/7330] lr: 1.000e-04, eta: 13:50:57, time: 0.941, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0457, loss_cls: 0.1958, acc: 93.0605, loss_bbox: 0.2441, loss_mask: 0.2402, loss: 0.7467 2024-06-05 08:30:21,420 - mmdet - INFO - Epoch [5][2200/7330] lr: 1.000e-04, eta: 13:50:11, time: 0.863, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0434, loss_cls: 0.1939, acc: 93.0339, loss_bbox: 0.2448, loss_mask: 0.2411, loss: 0.7430 2024-06-05 08:31:04,994 - mmdet - INFO - Epoch [5][2250/7330] lr: 1.000e-04, eta: 13:49:26, time: 0.872, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0439, loss_cls: 0.1849, acc: 93.2920, loss_bbox: 0.2365, loss_mask: 0.2332, loss: 0.7165 2024-06-05 08:31:47,915 - mmdet - INFO - Epoch [5][2300/7330] lr: 1.000e-04, eta: 13:48:40, time: 0.858, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0401, loss_cls: 0.1800, acc: 93.4507, loss_bbox: 0.2319, loss_mask: 0.2379, loss: 0.7076 2024-06-05 08:32:31,978 - mmdet - INFO - Epoch [5][2350/7330] lr: 1.000e-04, eta: 13:47:55, time: 0.881, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0445, loss_cls: 0.1930, acc: 93.0010, loss_bbox: 0.2443, loss_mask: 0.2426, loss: 0.7437 2024-06-05 08:33:15,976 - mmdet - INFO - Epoch [5][2400/7330] lr: 1.000e-04, eta: 13:47:11, time: 0.880, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0462, loss_cls: 0.1910, acc: 93.1465, loss_bbox: 0.2404, loss_mask: 0.2369, loss: 0.7355 2024-06-05 08:34:00,057 - mmdet - INFO - Epoch [5][2450/7330] lr: 1.000e-04, eta: 13:46:27, time: 0.882, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0452, loss_cls: 0.1991, acc: 92.7908, loss_bbox: 0.2457, loss_mask: 0.2447, loss: 0.7554 2024-06-05 08:34:44,021 - mmdet - INFO - Epoch [5][2500/7330] lr: 1.000e-04, eta: 13:45:42, time: 0.879, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0454, loss_cls: 0.1892, acc: 93.2026, loss_bbox: 0.2394, loss_mask: 0.2407, loss: 0.7325 2024-06-05 08:35:27,502 - mmdet - INFO - Epoch [5][2550/7330] lr: 1.000e-04, eta: 13:44:57, time: 0.870, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0428, loss_cls: 0.1808, acc: 93.4639, loss_bbox: 0.2340, loss_mask: 0.2394, loss: 0.7163 2024-06-05 08:36:15,493 - mmdet - INFO - Epoch [5][2600/7330] lr: 1.000e-04, eta: 13:44:20, time: 0.960, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0437, loss_cls: 0.1867, acc: 93.2678, loss_bbox: 0.2348, loss_mask: 0.2394, loss: 0.7219 2024-06-05 08:37:01,043 - mmdet - INFO - Epoch [5][2650/7330] lr: 1.000e-04, eta: 13:43:38, time: 0.911, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0455, loss_cls: 0.1956, acc: 92.9238, loss_bbox: 0.2476, loss_mask: 0.2415, loss: 0.7504 2024-06-05 08:37:48,045 - mmdet - INFO - Epoch [5][2700/7330] lr: 1.000e-04, eta: 13:42:59, time: 0.940, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0440, loss_cls: 0.1956, acc: 93.0166, loss_bbox: 0.2388, loss_mask: 0.2381, loss: 0.7343 2024-06-05 08:38:31,528 - mmdet - INFO - Epoch [5][2750/7330] lr: 1.000e-04, eta: 13:42:14, time: 0.870, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0446, loss_cls: 0.1916, acc: 93.1494, loss_bbox: 0.2368, loss_mask: 0.2350, loss: 0.7269 2024-06-05 08:39:14,766 - mmdet - INFO - Epoch [5][2800/7330] lr: 1.000e-04, eta: 13:41:28, time: 0.865, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0460, loss_cls: 0.1893, acc: 93.1819, loss_bbox: 0.2429, loss_mask: 0.2427, loss: 0.7399 2024-06-05 08:40:00,530 - mmdet - INFO - Epoch [5][2850/7330] lr: 1.000e-04, eta: 13:40:47, time: 0.915, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0463, loss_cls: 0.1920, acc: 92.9255, loss_bbox: 0.2421, loss_mask: 0.2350, loss: 0.7342 2024-06-05 08:40:46,708 - mmdet - INFO - Epoch [5][2900/7330] lr: 1.000e-04, eta: 13:40:06, time: 0.924, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0483, loss_cls: 0.2016, acc: 92.6743, loss_bbox: 0.2515, loss_mask: 0.2401, loss: 0.7599 2024-06-05 08:41:29,936 - mmdet - INFO - Epoch [5][2950/7330] lr: 1.000e-04, eta: 13:39:21, time: 0.865, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0428, loss_cls: 0.1831, acc: 93.4819, loss_bbox: 0.2261, loss_mask: 0.2343, loss: 0.7046 2024-06-05 08:42:13,492 - mmdet - INFO - Epoch [5][3000/7330] lr: 1.000e-04, eta: 13:38:35, time: 0.871, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0460, loss_cls: 0.1859, acc: 93.2314, loss_bbox: 0.2370, loss_mask: 0.2370, loss: 0.7236 2024-06-05 08:42:57,351 - mmdet - INFO - Epoch [5][3050/7330] lr: 1.000e-04, eta: 13:37:51, time: 0.877, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0440, loss_cls: 0.1822, acc: 93.5039, loss_bbox: 0.2329, loss_mask: 0.2310, loss: 0.7093 2024-06-05 08:43:44,317 - mmdet - INFO - Epoch [5][3100/7330] lr: 1.000e-04, eta: 13:37:11, time: 0.939, data_time: 0.074, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0476, loss_cls: 0.1950, acc: 92.9041, loss_bbox: 0.2398, loss_mask: 0.2382, loss: 0.7404 2024-06-05 08:44:27,894 - mmdet - INFO - Epoch [5][3150/7330] lr: 1.000e-04, eta: 13:36:26, time: 0.872, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0447, loss_cls: 0.1894, acc: 93.0771, loss_bbox: 0.2368, loss_mask: 0.2360, loss: 0.7275 2024-06-05 08:45:11,324 - mmdet - INFO - Epoch [5][3200/7330] lr: 1.000e-04, eta: 13:35:41, time: 0.869, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0428, loss_cls: 0.1872, acc: 93.2397, loss_bbox: 0.2398, loss_mask: 0.2384, loss: 0.7263 2024-06-05 08:45:55,718 - mmdet - INFO - Epoch [5][3250/7330] lr: 1.000e-04, eta: 13:34:57, time: 0.888, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0491, loss_cls: 0.1881, acc: 93.1021, loss_bbox: 0.2411, loss_mask: 0.2379, loss: 0.7361 2024-06-05 08:46:39,256 - mmdet - INFO - Epoch [5][3300/7330] lr: 1.000e-04, eta: 13:34:12, time: 0.871, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0458, loss_cls: 0.1951, acc: 92.9885, loss_bbox: 0.2388, loss_mask: 0.2378, loss: 0.7372 2024-06-05 08:47:23,125 - mmdet - INFO - Epoch [5][3350/7330] lr: 1.000e-04, eta: 13:33:28, time: 0.877, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0452, loss_cls: 0.1882, acc: 93.0696, loss_bbox: 0.2386, loss_mask: 0.2373, loss: 0.7313 2024-06-05 08:48:09,239 - mmdet - INFO - Epoch [5][3400/7330] lr: 1.000e-04, eta: 13:32:47, time: 0.922, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0428, loss_cls: 0.1911, acc: 93.0344, loss_bbox: 0.2384, loss_mask: 0.2352, loss: 0.7246 2024-06-05 08:48:52,662 - mmdet - INFO - Epoch [5][3450/7330] lr: 1.000e-04, eta: 13:32:01, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0454, loss_cls: 0.1895, acc: 92.9961, loss_bbox: 0.2410, loss_mask: 0.2371, loss: 0.7318 2024-06-05 08:49:36,343 - mmdet - INFO - Epoch [5][3500/7330] lr: 1.000e-04, eta: 13:31:16, time: 0.874, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0444, loss_cls: 0.1949, acc: 92.9382, loss_bbox: 0.2418, loss_mask: 0.2446, loss: 0.7456 2024-06-05 08:50:19,938 - mmdet - INFO - Epoch [5][3550/7330] lr: 1.000e-04, eta: 13:30:31, time: 0.872, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0425, loss_cls: 0.1866, acc: 93.2468, loss_bbox: 0.2311, loss_mask: 0.2308, loss: 0.7093 2024-06-05 08:51:03,208 - mmdet - INFO - Epoch [5][3600/7330] lr: 1.000e-04, eta: 13:29:46, time: 0.865, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0444, loss_cls: 0.1861, acc: 93.2622, loss_bbox: 0.2348, loss_mask: 0.2406, loss: 0.7247 2024-06-05 08:51:46,743 - mmdet - INFO - Epoch [5][3650/7330] lr: 1.000e-04, eta: 13:29:01, time: 0.870, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0440, loss_cls: 0.1928, acc: 93.1140, loss_bbox: 0.2347, loss_mask: 0.2394, loss: 0.7297 2024-06-05 08:52:30,121 - mmdet - INFO - Epoch [5][3700/7330] lr: 1.000e-04, eta: 13:28:15, time: 0.868, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0421, loss_cls: 0.1839, acc: 93.3474, loss_bbox: 0.2305, loss_mask: 0.2348, loss: 0.7090 2024-06-05 08:53:13,954 - mmdet - INFO - Epoch [5][3750/7330] lr: 1.000e-04, eta: 13:27:31, time: 0.877, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0423, loss_cls: 0.1876, acc: 93.1741, loss_bbox: 0.2359, loss_mask: 0.2365, loss: 0.7213 2024-06-05 08:53:58,239 - mmdet - INFO - Epoch [5][3800/7330] lr: 1.000e-04, eta: 13:26:47, time: 0.886, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0463, loss_cls: 0.1979, acc: 92.7971, loss_bbox: 0.2435, loss_mask: 0.2453, loss: 0.7534 2024-06-05 08:54:46,906 - mmdet - INFO - Epoch [5][3850/7330] lr: 1.000e-04, eta: 13:26:10, time: 0.973, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0436, loss_cls: 0.1930, acc: 92.9160, loss_bbox: 0.2391, loss_mask: 0.2394, loss: 0.7339 2024-06-05 08:55:32,928 - mmdet - INFO - Epoch [5][3900/7330] lr: 1.000e-04, eta: 13:25:29, time: 0.920, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0450, loss_cls: 0.1977, acc: 92.7708, loss_bbox: 0.2473, loss_mask: 0.2409, loss: 0.7513 2024-06-05 08:56:18,849 - mmdet - INFO - Epoch [5][3950/7330] lr: 1.000e-04, eta: 13:24:48, time: 0.918, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0442, loss_cls: 0.1855, acc: 93.3032, loss_bbox: 0.2365, loss_mask: 0.2387, loss: 0.7234 2024-06-05 08:57:02,463 - mmdet - INFO - Epoch [5][4000/7330] lr: 1.000e-04, eta: 13:24:03, time: 0.872, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0452, loss_cls: 0.1943, acc: 92.9473, loss_bbox: 0.2418, loss_mask: 0.2349, loss: 0.7352 2024-06-05 08:57:47,361 - mmdet - INFO - Epoch [5][4050/7330] lr: 1.000e-04, eta: 13:23:20, time: 0.898, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0469, loss_cls: 0.1963, acc: 92.8733, loss_bbox: 0.2473, loss_mask: 0.2459, loss: 0.7572 2024-06-05 08:58:33,890 - mmdet - INFO - Epoch [5][4100/7330] lr: 1.000e-04, eta: 13:22:40, time: 0.931, data_time: 0.076, memory: 11350, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0439, loss_cls: 0.1934, acc: 93.0400, loss_bbox: 0.2376, loss_mask: 0.2362, loss: 0.7308 2024-06-05 08:59:19,401 - mmdet - INFO - Epoch [5][4150/7330] lr: 1.000e-04, eta: 13:21:58, time: 0.910, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0456, loss_cls: 0.1937, acc: 93.0811, loss_bbox: 0.2407, loss_mask: 0.2395, loss: 0.7392 2024-06-05 09:00:02,937 - mmdet - INFO - Epoch [5][4200/7330] lr: 1.000e-04, eta: 13:21:13, time: 0.871, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0451, loss_cls: 0.1940, acc: 93.0710, loss_bbox: 0.2378, loss_mask: 0.2406, loss: 0.7357 2024-06-05 09:00:47,427 - mmdet - INFO - Epoch [5][4250/7330] lr: 1.000e-04, eta: 13:20:29, time: 0.890, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0442, loss_cls: 0.1929, acc: 93.0452, loss_bbox: 0.2371, loss_mask: 0.2374, loss: 0.7316 2024-06-05 09:01:30,962 - mmdet - INFO - Epoch [5][4300/7330] lr: 1.000e-04, eta: 13:19:44, time: 0.871, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0427, loss_cls: 0.1894, acc: 93.1423, loss_bbox: 0.2349, loss_mask: 0.2385, loss: 0.7252 2024-06-05 09:02:18,113 - mmdet - INFO - Epoch [5][4350/7330] lr: 1.000e-04, eta: 13:19:04, time: 0.943, data_time: 0.077, memory: 11350, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0455, loss_cls: 0.2003, acc: 92.8640, loss_bbox: 0.2460, loss_mask: 0.2347, loss: 0.7467 2024-06-05 09:03:02,575 - mmdet - INFO - Epoch [5][4400/7330] lr: 1.000e-04, eta: 13:18:21, time: 0.889, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0502, loss_cls: 0.2008, acc: 92.8059, loss_bbox: 0.2470, loss_mask: 0.2438, loss: 0.7634 2024-06-05 09:03:45,780 - mmdet - INFO - Epoch [5][4450/7330] lr: 1.000e-04, eta: 13:17:35, time: 0.864, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0418, loss_cls: 0.1824, acc: 93.3201, loss_bbox: 0.2359, loss_mask: 0.2343, loss: 0.7106 2024-06-05 09:04:30,091 - mmdet - INFO - Epoch [5][4500/7330] lr: 1.000e-04, eta: 13:16:51, time: 0.886, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0485, loss_cls: 0.1948, acc: 92.8345, loss_bbox: 0.2454, loss_mask: 0.2381, loss: 0.7484 2024-06-05 09:05:13,534 - mmdet - INFO - Epoch [5][4550/7330] lr: 1.000e-04, eta: 13:16:06, time: 0.869, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0443, loss_cls: 0.1941, acc: 93.0635, loss_bbox: 0.2371, loss_mask: 0.2392, loss: 0.7349 2024-06-05 09:05:59,145 - mmdet - INFO - Epoch [5][4600/7330] lr: 1.000e-04, eta: 13:15:24, time: 0.912, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0433, loss_cls: 0.1899, acc: 93.1621, loss_bbox: 0.2349, loss_mask: 0.2352, loss: 0.7225 2024-06-05 09:06:42,371 - mmdet - INFO - Epoch [5][4650/7330] lr: 1.000e-04, eta: 13:14:38, time: 0.865, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0424, loss_cls: 0.1777, acc: 93.5239, loss_bbox: 0.2297, loss_mask: 0.2352, loss: 0.7042 2024-06-05 09:07:26,102 - mmdet - INFO - Epoch [5][4700/7330] lr: 1.000e-04, eta: 13:13:54, time: 0.875, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0426, loss_cls: 0.1874, acc: 93.1516, loss_bbox: 0.2329, loss_mask: 0.2359, loss: 0.7180 2024-06-05 09:08:10,316 - mmdet - INFO - Epoch [5][4750/7330] lr: 1.000e-04, eta: 13:13:10, time: 0.884, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0448, loss_cls: 0.1874, acc: 93.1455, loss_bbox: 0.2381, loss_mask: 0.2401, loss: 0.7302 2024-06-05 09:08:54,006 - mmdet - INFO - Epoch [5][4800/7330] lr: 1.000e-04, eta: 13:12:25, time: 0.874, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0441, loss_cls: 0.1881, acc: 93.1909, loss_bbox: 0.2323, loss_mask: 0.2411, loss: 0.7262 2024-06-05 09:09:37,516 - mmdet - INFO - Epoch [5][4850/7330] lr: 1.000e-04, eta: 13:11:40, time: 0.870, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0425, loss_cls: 0.1911, acc: 93.1699, loss_bbox: 0.2351, loss_mask: 0.2370, loss: 0.7239 2024-06-05 09:10:20,841 - mmdet - INFO - Epoch [5][4900/7330] lr: 1.000e-04, eta: 13:10:54, time: 0.866, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0410, loss_cls: 0.1831, acc: 93.3838, loss_bbox: 0.2311, loss_mask: 0.2331, loss: 0.7060 2024-06-05 09:11:04,775 - mmdet - INFO - Epoch [5][4950/7330] lr: 1.000e-04, eta: 13:10:10, time: 0.878, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0422, loss_cls: 0.1898, acc: 93.0686, loss_bbox: 0.2417, loss_mask: 0.2278, loss: 0.7184 2024-06-05 09:11:47,992 - mmdet - INFO - Epoch [5][5000/7330] lr: 1.000e-04, eta: 13:09:24, time: 0.865, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0420, loss_cls: 0.1827, acc: 93.3857, loss_bbox: 0.2300, loss_mask: 0.2326, loss: 0.7052 2024-06-05 09:12:31,932 - mmdet - INFO - Epoch [5][5050/7330] lr: 1.000e-04, eta: 13:08:39, time: 0.879, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0435, loss_cls: 0.1906, acc: 93.1458, loss_bbox: 0.2365, loss_mask: 0.2413, loss: 0.7328 2024-06-05 09:13:20,151 - mmdet - INFO - Epoch [5][5100/7330] lr: 1.000e-04, eta: 13:08:02, time: 0.964, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0460, loss_cls: 0.1895, acc: 93.0581, loss_bbox: 0.2375, loss_mask: 0.2392, loss: 0.7312 2024-06-05 09:14:05,956 - mmdet - INFO - Epoch [5][5150/7330] lr: 1.000e-04, eta: 13:07:20, time: 0.916, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0449, loss_cls: 0.1900, acc: 93.1594, loss_bbox: 0.2405, loss_mask: 0.2399, loss: 0.7353 2024-06-05 09:14:52,279 - mmdet - INFO - Epoch [5][5200/7330] lr: 1.000e-04, eta: 13:06:39, time: 0.926, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0434, loss_cls: 0.1855, acc: 93.3462, loss_bbox: 0.2281, loss_mask: 0.2449, loss: 0.7208 2024-06-05 09:15:35,792 - mmdet - INFO - Epoch [5][5250/7330] lr: 1.000e-04, eta: 13:05:54, time: 0.870, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0433, loss_cls: 0.1935, acc: 93.0718, loss_bbox: 0.2439, loss_mask: 0.2428, loss: 0.7417 2024-06-05 09:16:19,057 - mmdet - INFO - Epoch [5][5300/7330] lr: 1.000e-04, eta: 13:05:09, time: 0.865, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0437, loss_cls: 0.1924, acc: 93.0049, loss_bbox: 0.2403, loss_mask: 0.2354, loss: 0.7291 2024-06-05 09:17:04,986 - mmdet - INFO - Epoch [5][5350/7330] lr: 1.000e-04, eta: 13:04:27, time: 0.919, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0430, loss_cls: 0.1869, acc: 93.2625, loss_bbox: 0.2292, loss_mask: 0.2283, loss: 0.7071 2024-06-05 09:17:50,611 - mmdet - INFO - Epoch [5][5400/7330] lr: 1.000e-04, eta: 13:03:45, time: 0.912, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0422, loss_cls: 0.1840, acc: 93.3718, loss_bbox: 0.2348, loss_mask: 0.2383, loss: 0.7191 2024-06-05 09:18:33,907 - mmdet - INFO - Epoch [5][5450/7330] lr: 1.000e-04, eta: 13:03:00, time: 0.866, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0440, loss_cls: 0.1891, acc: 93.2419, loss_bbox: 0.2349, loss_mask: 0.2368, loss: 0.7237 2024-06-05 09:19:17,301 - mmdet - INFO - Epoch [5][5500/7330] lr: 1.000e-04, eta: 13:02:14, time: 0.868, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0455, loss_cls: 0.1891, acc: 93.1118, loss_bbox: 0.2336, loss_mask: 0.2360, loss: 0.7232 2024-06-05 09:20:01,183 - mmdet - INFO - Epoch [5][5550/7330] lr: 1.000e-04, eta: 13:01:30, time: 0.878, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0484, loss_cls: 0.1938, acc: 92.8784, loss_bbox: 0.2460, loss_mask: 0.2406, loss: 0.7491 2024-06-05 09:20:48,076 - mmdet - INFO - Epoch [5][5600/7330] lr: 1.000e-04, eta: 13:00:50, time: 0.938, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0466, loss_cls: 0.1981, acc: 92.7722, loss_bbox: 0.2461, loss_mask: 0.2420, loss: 0.7543 2024-06-05 09:21:31,536 - mmdet - INFO - Epoch [5][5650/7330] lr: 1.000e-04, eta: 13:00:05, time: 0.869, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0458, loss_cls: 0.1950, acc: 92.9392, loss_bbox: 0.2451, loss_mask: 0.2407, loss: 0.7464 2024-06-05 09:22:14,661 - mmdet - INFO - Epoch [5][5700/7330] lr: 1.000e-04, eta: 12:59:19, time: 0.862, data_time: 0.039, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0421, loss_cls: 0.1836, acc: 93.4299, loss_bbox: 0.2288, loss_mask: 0.2372, loss: 0.7083 2024-06-05 09:22:57,557 - mmdet - INFO - Epoch [5][5750/7330] lr: 1.000e-04, eta: 12:58:33, time: 0.858, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0442, loss_cls: 0.1845, acc: 93.3137, loss_bbox: 0.2352, loss_mask: 0.2363, loss: 0.7193 2024-06-05 09:23:41,005 - mmdet - INFO - Epoch [5][5800/7330] lr: 1.000e-04, eta: 12:57:47, time: 0.869, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0481, loss_cls: 0.1977, acc: 92.8403, loss_bbox: 0.2482, loss_mask: 0.2443, loss: 0.7586 2024-06-05 09:24:26,471 - mmdet - INFO - Epoch [5][5850/7330] lr: 1.000e-04, eta: 12:57:05, time: 0.909, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0412, loss_cls: 0.1849, acc: 93.4250, loss_bbox: 0.2286, loss_mask: 0.2310, loss: 0.7032 2024-06-05 09:25:16,700 - mmdet - INFO - Epoch [5][5900/7330] lr: 1.000e-04, eta: 12:56:30, time: 1.005, data_time: 0.186, memory: 11350, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0456, loss_cls: 0.1858, acc: 93.2620, loss_bbox: 0.2376, loss_mask: 0.2365, loss: 0.7260 2024-06-05 09:25:59,849 - mmdet - INFO - Epoch [5][5950/7330] lr: 1.000e-04, eta: 12:55:45, time: 0.863, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0428, loss_cls: 0.1893, acc: 93.1235, loss_bbox: 0.2367, loss_mask: 0.2373, loss: 0.7244 2024-06-05 09:26:43,841 - mmdet - INFO - Epoch [5][6000/7330] lr: 1.000e-04, eta: 12:55:00, time: 0.880, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0457, loss_cls: 0.1869, acc: 93.2402, loss_bbox: 0.2322, loss_mask: 0.2395, loss: 0.7246 2024-06-05 09:27:27,187 - mmdet - INFO - Epoch [5][6050/7330] lr: 1.000e-04, eta: 12:54:15, time: 0.867, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0456, loss_cls: 0.1827, acc: 93.4082, loss_bbox: 0.2282, loss_mask: 0.2368, loss: 0.7141 2024-06-05 09:28:10,332 - mmdet - INFO - Epoch [5][6100/7330] lr: 1.000e-04, eta: 12:53:29, time: 0.863, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0432, loss_cls: 0.1827, acc: 93.4260, loss_bbox: 0.2268, loss_mask: 0.2401, loss: 0.7129 2024-06-05 09:28:53,202 - mmdet - INFO - Epoch [5][6150/7330] lr: 1.000e-04, eta: 12:52:43, time: 0.857, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0406, loss_cls: 0.1826, acc: 93.5264, loss_bbox: 0.2301, loss_mask: 0.2351, loss: 0.7060 2024-06-05 09:29:37,002 - mmdet - INFO - Epoch [5][6200/7330] lr: 1.000e-04, eta: 12:51:58, time: 0.876, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0439, loss_cls: 0.1875, acc: 93.2354, loss_bbox: 0.2352, loss_mask: 0.2363, loss: 0.7218 2024-06-05 09:30:20,214 - mmdet - INFO - Epoch [5][6250/7330] lr: 1.000e-04, eta: 12:51:13, time: 0.864, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0430, loss_cls: 0.1819, acc: 93.3589, loss_bbox: 0.2288, loss_mask: 0.2327, loss: 0.7045 2024-06-05 09:31:04,455 - mmdet - INFO - Epoch [5][6300/7330] lr: 1.000e-04, eta: 12:50:29, time: 0.885, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0462, loss_cls: 0.1901, acc: 93.0940, loss_bbox: 0.2337, loss_mask: 0.2358, loss: 0.7252 2024-06-05 09:31:53,002 - mmdet - INFO - Epoch [5][6350/7330] lr: 1.000e-04, eta: 12:49:51, time: 0.971, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0450, loss_cls: 0.1912, acc: 93.1477, loss_bbox: 0.2409, loss_mask: 0.2399, loss: 0.7369 2024-06-05 09:32:41,193 - mmdet - INFO - Epoch [5][6400/7330] lr: 1.000e-04, eta: 12:49:13, time: 0.964, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0459, loss_cls: 0.1858, acc: 93.3882, loss_bbox: 0.2338, loss_mask: 0.2327, loss: 0.7161 2024-06-05 09:33:25,370 - mmdet - INFO - Epoch [5][6450/7330] lr: 1.000e-04, eta: 12:48:28, time: 0.883, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0446, loss_cls: 0.1882, acc: 93.1597, loss_bbox: 0.2385, loss_mask: 0.2335, loss: 0.7233 2024-06-05 09:34:09,593 - mmdet - INFO - Epoch [5][6500/7330] lr: 1.000e-04, eta: 12:47:44, time: 0.885, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0457, loss_cls: 0.1983, acc: 92.8186, loss_bbox: 0.2441, loss_mask: 0.2405, loss: 0.7485 2024-06-05 09:34:53,550 - mmdet - INFO - Epoch [5][6550/7330] lr: 1.000e-04, eta: 12:47:00, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0450, loss_cls: 0.1901, acc: 93.0691, loss_bbox: 0.2410, loss_mask: 0.2417, loss: 0.7368 2024-06-05 09:35:38,977 - mmdet - INFO - Epoch [5][6600/7330] lr: 1.000e-04, eta: 12:46:17, time: 0.908, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0454, loss_cls: 0.1942, acc: 92.8479, loss_bbox: 0.2492, loss_mask: 0.2422, loss: 0.7502 2024-06-05 09:36:24,786 - mmdet - INFO - Epoch [5][6650/7330] lr: 1.000e-04, eta: 12:45:36, time: 0.916, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0426, loss_cls: 0.1936, acc: 93.0217, loss_bbox: 0.2405, loss_mask: 0.2374, loss: 0.7342 2024-06-05 09:37:07,904 - mmdet - INFO - Epoch [5][6700/7330] lr: 1.000e-04, eta: 12:44:50, time: 0.862, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0420, loss_cls: 0.1775, acc: 93.6328, loss_bbox: 0.2218, loss_mask: 0.2327, loss: 0.6925 2024-06-05 09:37:52,041 - mmdet - INFO - Epoch [5][6750/7330] lr: 1.000e-04, eta: 12:44:06, time: 0.883, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0453, loss_cls: 0.1995, acc: 92.6980, loss_bbox: 0.2539, loss_mask: 0.2461, loss: 0.7646 2024-06-05 09:38:36,022 - mmdet - INFO - Epoch [5][6800/7330] lr: 1.000e-04, eta: 12:43:21, time: 0.880, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0423, loss_cls: 0.1948, acc: 93.0369, loss_bbox: 0.2380, loss_mask: 0.2430, loss: 0.7371 2024-06-05 09:39:22,522 - mmdet - INFO - Epoch [5][6850/7330] lr: 1.000e-04, eta: 12:42:40, time: 0.930, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0462, loss_cls: 0.1916, acc: 93.1057, loss_bbox: 0.2346, loss_mask: 0.2340, loss: 0.7272 2024-06-05 09:40:07,021 - mmdet - INFO - Epoch [5][6900/7330] lr: 1.000e-04, eta: 12:41:57, time: 0.890, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0484, loss_cls: 0.1997, acc: 92.8428, loss_bbox: 0.2472, loss_mask: 0.2410, loss: 0.7580 2024-06-05 09:40:51,423 - mmdet - INFO - Epoch [5][6950/7330] lr: 1.000e-04, eta: 12:41:13, time: 0.888, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0460, loss_cls: 0.1902, acc: 93.0723, loss_bbox: 0.2418, loss_mask: 0.2450, loss: 0.7438 2024-06-05 09:41:35,456 - mmdet - INFO - Epoch [5][7000/7330] lr: 1.000e-04, eta: 12:40:28, time: 0.881, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0453, loss_cls: 0.1950, acc: 92.8713, loss_bbox: 0.2431, loss_mask: 0.2373, loss: 0.7407 2024-06-05 09:42:19,552 - mmdet - INFO - Epoch [5][7050/7330] lr: 1.000e-04, eta: 12:39:44, time: 0.882, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0426, loss_cls: 0.1810, acc: 93.3643, loss_bbox: 0.2281, loss_mask: 0.2389, loss: 0.7100 2024-06-05 09:43:05,255 - mmdet - INFO - Epoch [5][7100/7330] lr: 1.000e-04, eta: 12:39:02, time: 0.914, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0434, loss_cls: 0.1798, acc: 93.4233, loss_bbox: 0.2277, loss_mask: 0.2367, loss: 0.7067 2024-06-05 09:43:49,385 - mmdet - INFO - Epoch [5][7150/7330] lr: 1.000e-04, eta: 12:38:18, time: 0.883, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0481, loss_cls: 0.1929, acc: 92.8965, loss_bbox: 0.2468, loss_mask: 0.2384, loss: 0.7461 2024-06-05 09:44:32,823 - mmdet - INFO - Epoch [5][7200/7330] lr: 1.000e-04, eta: 12:37:33, time: 0.869, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0425, loss_cls: 0.1838, acc: 93.2783, loss_bbox: 0.2290, loss_mask: 0.2354, loss: 0.7096 2024-06-05 09:45:17,434 - mmdet - INFO - Epoch [5][7250/7330] lr: 1.000e-04, eta: 12:36:49, time: 0.892, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0448, loss_cls: 0.1930, acc: 93.0100, loss_bbox: 0.2425, loss_mask: 0.2427, loss: 0.7427 2024-06-05 09:46:01,481 - mmdet - INFO - Epoch [5][7300/7330] lr: 1.000e-04, eta: 12:36:05, time: 0.881, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0485, loss_cls: 0.1960, acc: 92.9861, loss_bbox: 0.2410, loss_mask: 0.2436, loss: 0.7499 2024-06-05 09:46:28,838 - mmdet - INFO - Saving checkpoint at 5 epochs 2024-06-05 09:48:19,196 - mmdet - INFO - Evaluating bbox... 2024-06-05 09:48:46,217 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.437 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.670 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.481 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.256 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.479 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.566 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.566 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.566 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.366 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.615 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.727 2024-06-05 09:48:46,217 - mmdet - INFO - Evaluating segm... 2024-06-05 09:49:13,025 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.397 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.636 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.420 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.182 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.431 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.514 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.514 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.514 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.299 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.570 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.700 2024-06-05 09:49:13,468 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 09:49:13,469 - mmdet - INFO - Epoch(val) [5][625] bbox_mAP: 0.4370, bbox_mAP_50: 0.6700, bbox_mAP_75: 0.4810, bbox_mAP_s: 0.2560, bbox_mAP_m: 0.4790, bbox_mAP_l: 0.6060, bbox_mAP_copypaste: 0.437 0.670 0.481 0.256 0.479 0.606, segm_mAP: 0.3970, segm_mAP_50: 0.6360, segm_mAP_75: 0.4200, segm_mAP_s: 0.1820, segm_mAP_m: 0.4310, segm_mAP_l: 0.6140, segm_mAP_copypaste: 0.397 0.636 0.420 0.182 0.431 0.614 2024-06-05 09:50:05,411 - mmdet - INFO - Epoch [6][50/7330] lr: 1.000e-04, eta: 12:34:28, time: 1.039, data_time: 0.114, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0415, loss_cls: 0.1726, acc: 93.7373, loss_bbox: 0.2229, loss_mask: 0.2258, loss: 0.6794 2024-06-05 09:50:55,775 - mmdet - INFO - Epoch [6][100/7330] lr: 1.000e-04, eta: 12:33:52, time: 1.007, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0424, loss_cls: 0.1745, acc: 93.6245, loss_bbox: 0.2278, loss_mask: 0.2325, loss: 0.6946 2024-06-05 09:51:41,266 - mmdet - INFO - Epoch [6][150/7330] lr: 1.000e-04, eta: 12:33:10, time: 0.910, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0418, loss_cls: 0.1769, acc: 93.5144, loss_bbox: 0.2253, loss_mask: 0.2266, loss: 0.6881 2024-06-05 09:52:27,253 - mmdet - INFO - Epoch [6][200/7330] lr: 1.000e-04, eta: 12:32:28, time: 0.920, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0425, loss_cls: 0.1793, acc: 93.3193, loss_bbox: 0.2336, loss_mask: 0.2317, loss: 0.7040 2024-06-05 09:53:10,609 - mmdet - INFO - Epoch [6][250/7330] lr: 1.000e-04, eta: 12:31:43, time: 0.867, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0405, loss_cls: 0.1755, acc: 93.4409, loss_bbox: 0.2308, loss_mask: 0.2313, loss: 0.6937 2024-06-05 09:53:54,089 - mmdet - INFO - Epoch [6][300/7330] lr: 1.000e-04, eta: 12:30:58, time: 0.870, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0403, loss_cls: 0.1757, acc: 93.5396, loss_bbox: 0.2259, loss_mask: 0.2281, loss: 0.6855 2024-06-05 09:54:37,753 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 09:54:37,753 - mmdet - INFO - Epoch [6][350/7330] lr: 1.000e-04, eta: 12:30:13, time: 0.873, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0425, loss_cls: 0.1832, acc: 93.3555, loss_bbox: 0.2349, loss_mask: 0.2341, loss: 0.7133 2024-06-05 09:55:21,057 - mmdet - INFO - Epoch [6][400/7330] lr: 1.000e-04, eta: 12:29:28, time: 0.866, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0446, loss_cls: 0.1799, acc: 93.2825, loss_bbox: 0.2337, loss_mask: 0.2335, loss: 0.7086 2024-06-05 09:56:04,621 - mmdet - INFO - Epoch [6][450/7330] lr: 1.000e-04, eta: 12:28:43, time: 0.871, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0418, loss_cls: 0.1703, acc: 93.7600, loss_bbox: 0.2198, loss_mask: 0.2257, loss: 0.6750 2024-06-05 09:56:48,093 - mmdet - INFO - Epoch [6][500/7330] lr: 1.000e-04, eta: 12:27:58, time: 0.869, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0420, loss_cls: 0.1741, acc: 93.5703, loss_bbox: 0.2254, loss_mask: 0.2299, loss: 0.6869 2024-06-05 09:57:32,254 - mmdet - INFO - Epoch [6][550/7330] lr: 1.000e-04, eta: 12:27:13, time: 0.883, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0452, loss_cls: 0.1881, acc: 93.0117, loss_bbox: 0.2410, loss_mask: 0.2310, loss: 0.7225 2024-06-05 09:58:15,883 - mmdet - INFO - Epoch [6][600/7330] lr: 1.000e-04, eta: 12:26:29, time: 0.873, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0412, loss_cls: 0.1755, acc: 93.6199, loss_bbox: 0.2233, loss_mask: 0.2230, loss: 0.6785 2024-06-05 09:59:01,605 - mmdet - INFO - Epoch [6][650/7330] lr: 1.000e-04, eta: 12:25:46, time: 0.914, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0411, loss_cls: 0.1732, acc: 93.6367, loss_bbox: 0.2278, loss_mask: 0.2275, loss: 0.6859 2024-06-05 09:59:44,797 - mmdet - INFO - Epoch [6][700/7330] lr: 1.000e-04, eta: 12:25:01, time: 0.864, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0421, loss_cls: 0.1750, acc: 93.6018, loss_bbox: 0.2232, loss_mask: 0.2260, loss: 0.6834 2024-06-05 10:00:28,254 - mmdet - INFO - Epoch [6][750/7330] lr: 1.000e-04, eta: 12:24:16, time: 0.869, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0459, loss_cls: 0.1812, acc: 93.2903, loss_bbox: 0.2328, loss_mask: 0.2377, loss: 0.7143 2024-06-05 10:01:11,925 - mmdet - INFO - Epoch [6][800/7330] lr: 1.000e-04, eta: 12:23:31, time: 0.873, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0419, loss_cls: 0.1731, acc: 93.4863, loss_bbox: 0.2323, loss_mask: 0.2336, loss: 0.6972 2024-06-05 10:01:55,246 - mmdet - INFO - Epoch [6][850/7330] lr: 1.000e-04, eta: 12:22:46, time: 0.866, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0419, loss_cls: 0.1704, acc: 93.5728, loss_bbox: 0.2221, loss_mask: 0.2300, loss: 0.6807 2024-06-05 10:02:40,733 - mmdet - INFO - Epoch [6][900/7330] lr: 1.000e-04, eta: 12:22:03, time: 0.910, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0454, loss_cls: 0.1863, acc: 93.2883, loss_bbox: 0.2381, loss_mask: 0.2325, loss: 0.7202 2024-06-05 10:03:23,846 - mmdet - INFO - Epoch [6][950/7330] lr: 1.000e-04, eta: 12:21:18, time: 0.862, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0420, loss_cls: 0.1738, acc: 93.5269, loss_bbox: 0.2263, loss_mask: 0.2373, loss: 0.6974 2024-06-05 10:04:07,659 - mmdet - INFO - Epoch [6][1000/7330] lr: 1.000e-04, eta: 12:20:33, time: 0.876, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0439, loss_cls: 0.1707, acc: 93.6187, loss_bbox: 0.2283, loss_mask: 0.2321, loss: 0.6915 2024-06-05 10:04:51,087 - mmdet - INFO - Epoch [6][1050/7330] lr: 1.000e-04, eta: 12:19:48, time: 0.869, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0435, loss_cls: 0.1790, acc: 93.3950, loss_bbox: 0.2325, loss_mask: 0.2309, loss: 0.7033 2024-06-05 10:05:34,733 - mmdet - INFO - Epoch [6][1100/7330] lr: 1.000e-04, eta: 12:19:03, time: 0.873, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0441, loss_cls: 0.1787, acc: 93.4482, loss_bbox: 0.2317, loss_mask: 0.2311, loss: 0.7035 2024-06-05 10:06:17,629 - mmdet - INFO - Epoch [6][1150/7330] lr: 1.000e-04, eta: 12:18:17, time: 0.858, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0408, loss_cls: 0.1693, acc: 93.7876, loss_bbox: 0.2218, loss_mask: 0.2329, loss: 0.6812 2024-06-05 10:07:01,242 - mmdet - INFO - Epoch [6][1200/7330] lr: 1.000e-04, eta: 12:17:33, time: 0.872, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0431, loss_cls: 0.1763, acc: 93.5364, loss_bbox: 0.2250, loss_mask: 0.2321, loss: 0.6947 2024-06-05 10:07:44,615 - mmdet - INFO - Epoch [6][1250/7330] lr: 1.000e-04, eta: 12:16:47, time: 0.867, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0431, loss_cls: 0.1832, acc: 93.3457, loss_bbox: 0.2319, loss_mask: 0.2371, loss: 0.7118 2024-06-05 10:08:28,144 - mmdet - INFO - Epoch [6][1300/7330] lr: 1.000e-04, eta: 12:16:02, time: 0.871, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0402, loss_cls: 0.1731, acc: 93.6973, loss_bbox: 0.2196, loss_mask: 0.2259, loss: 0.6743 2024-06-05 10:09:18,358 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 10:09:18,358 - mmdet - INFO - Epoch [6][1350/7330] lr: 1.000e-04, eta: 12:15:26, time: 1.004, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0465, loss_cls: 0.1825, acc: 93.4099, loss_bbox: 0.2317, loss_mask: 0.2365, loss: 0.7162 2024-06-05 10:10:06,166 - mmdet - INFO - Epoch [6][1400/7330] lr: 1.000e-04, eta: 12:14:47, time: 0.956, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0408, loss_cls: 0.1715, acc: 93.7603, loss_bbox: 0.2199, loss_mask: 0.2280, loss: 0.6768 2024-06-05 10:10:52,015 - mmdet - INFO - Epoch [6][1450/7330] lr: 1.000e-04, eta: 12:14:05, time: 0.917, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0431, loss_cls: 0.1831, acc: 93.1992, loss_bbox: 0.2349, loss_mask: 0.2340, loss: 0.7116 2024-06-05 10:11:35,063 - mmdet - INFO - Epoch [6][1500/7330] lr: 1.000e-04, eta: 12:13:19, time: 0.861, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0403, loss_cls: 0.1741, acc: 93.5498, loss_bbox: 0.2243, loss_mask: 0.2223, loss: 0.6781 2024-06-05 10:12:18,114 - mmdet - INFO - Epoch [6][1550/7330] lr: 1.000e-04, eta: 12:12:34, time: 0.861, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0418, loss_cls: 0.1676, acc: 93.8464, loss_bbox: 0.2213, loss_mask: 0.2235, loss: 0.6715 2024-06-05 10:13:01,118 - mmdet - INFO - Epoch [6][1600/7330] lr: 1.000e-04, eta: 12:11:48, time: 0.860, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0411, loss_cls: 0.1703, acc: 93.6638, loss_bbox: 0.2190, loss_mask: 0.2302, loss: 0.6758 2024-06-05 10:13:44,316 - mmdet - INFO - Epoch [6][1650/7330] lr: 1.000e-04, eta: 12:11:02, time: 0.864, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0408, loss_cls: 0.1733, acc: 93.5750, loss_bbox: 0.2216, loss_mask: 0.2275, loss: 0.6791 2024-06-05 10:14:27,339 - mmdet - INFO - Epoch [6][1700/7330] lr: 1.000e-04, eta: 12:10:17, time: 0.860, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0402, loss_cls: 0.1791, acc: 93.4941, loss_bbox: 0.2312, loss_mask: 0.2371, loss: 0.7040 2024-06-05 10:15:10,615 - mmdet - INFO - Epoch [6][1750/7330] lr: 1.000e-04, eta: 12:09:32, time: 0.866, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0427, loss_cls: 0.1854, acc: 93.1626, loss_bbox: 0.2373, loss_mask: 0.2375, loss: 0.7201 2024-06-05 10:15:54,122 - mmdet - INFO - Epoch [6][1800/7330] lr: 1.000e-04, eta: 12:08:47, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0425, loss_cls: 0.1791, acc: 93.4890, loss_bbox: 0.2328, loss_mask: 0.2283, loss: 0.6983 2024-06-05 10:16:38,019 - mmdet - INFO - Epoch [6][1850/7330] lr: 1.000e-04, eta: 12:08:02, time: 0.878, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0464, loss_cls: 0.1891, acc: 93.1965, loss_bbox: 0.2354, loss_mask: 0.2351, loss: 0.7245 2024-06-05 10:17:25,572 - mmdet - INFO - Epoch [6][1900/7330] lr: 1.000e-04, eta: 12:07:22, time: 0.951, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0456, loss_cls: 0.1901, acc: 93.0815, loss_bbox: 0.2411, loss_mask: 0.2376, loss: 0.7326 2024-06-05 10:18:09,271 - mmdet - INFO - Epoch [6][1950/7330] lr: 1.000e-04, eta: 12:06:37, time: 0.874, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0413, loss_cls: 0.1813, acc: 93.2817, loss_bbox: 0.2331, loss_mask: 0.2319, loss: 0.7050 2024-06-05 10:18:52,917 - mmdet - INFO - Epoch [6][2000/7330] lr: 1.000e-04, eta: 12:05:53, time: 0.873, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0422, loss_cls: 0.1758, acc: 93.6167, loss_bbox: 0.2252, loss_mask: 0.2316, loss: 0.6915 2024-06-05 10:19:36,794 - mmdet - INFO - Epoch [6][2050/7330] lr: 1.000e-04, eta: 12:05:08, time: 0.878, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0428, loss_cls: 0.1921, acc: 92.9419, loss_bbox: 0.2408, loss_mask: 0.2295, loss: 0.7231 2024-06-05 10:20:20,563 - mmdet - INFO - Epoch [6][2100/7330] lr: 1.000e-04, eta: 12:04:23, time: 0.875, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0429, loss_cls: 0.1840, acc: 93.2622, loss_bbox: 0.2373, loss_mask: 0.2441, loss: 0.7258 2024-06-05 10:21:06,388 - mmdet - INFO - Epoch [6][2150/7330] lr: 1.000e-04, eta: 12:03:41, time: 0.917, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0439, loss_cls: 0.1859, acc: 93.1887, loss_bbox: 0.2334, loss_mask: 0.2342, loss: 0.7163 2024-06-05 10:21:49,614 - mmdet - INFO - Epoch [6][2200/7330] lr: 1.000e-04, eta: 12:02:56, time: 0.865, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0410, loss_cls: 0.1815, acc: 93.3076, loss_bbox: 0.2304, loss_mask: 0.2293, loss: 0.6995 2024-06-05 10:22:33,153 - mmdet - INFO - Epoch [6][2250/7330] lr: 1.000e-04, eta: 12:02:11, time: 0.871, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0440, loss_cls: 0.1823, acc: 93.4460, loss_bbox: 0.2316, loss_mask: 0.2289, loss: 0.7048 2024-06-05 10:23:16,715 - mmdet - INFO - Epoch [6][2300/7330] lr: 1.000e-04, eta: 12:01:26, time: 0.871, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0411, loss_cls: 0.1746, acc: 93.6096, loss_bbox: 0.2208, loss_mask: 0.2228, loss: 0.6769 2024-06-05 10:23:59,954 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 10:23:59,954 - mmdet - INFO - Epoch [6][2350/7330] lr: 1.000e-04, eta: 12:00:41, time: 0.865, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0403, loss_cls: 0.1807, acc: 93.4414, loss_bbox: 0.2299, loss_mask: 0.2271, loss: 0.6956 2024-06-05 10:24:43,279 - mmdet - INFO - Epoch [6][2400/7330] lr: 1.000e-04, eta: 11:59:56, time: 0.867, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0403, loss_cls: 0.1669, acc: 93.9707, loss_bbox: 0.2159, loss_mask: 0.2228, loss: 0.6635 2024-06-05 10:25:27,329 - mmdet - INFO - Epoch [6][2450/7330] lr: 1.000e-04, eta: 11:59:11, time: 0.881, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0440, loss_cls: 0.1897, acc: 92.9998, loss_bbox: 0.2409, loss_mask: 0.2323, loss: 0.7249 2024-06-05 10:26:10,753 - mmdet - INFO - Epoch [6][2500/7330] lr: 1.000e-04, eta: 11:58:26, time: 0.868, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0419, loss_cls: 0.1780, acc: 93.4907, loss_bbox: 0.2335, loss_mask: 0.2299, loss: 0.6993 2024-06-05 10:26:53,800 - mmdet - INFO - Epoch [6][2550/7330] lr: 1.000e-04, eta: 11:57:41, time: 0.861, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0392, loss_cls: 0.1716, acc: 93.8069, loss_bbox: 0.2214, loss_mask: 0.2266, loss: 0.6757 2024-06-05 10:27:43,748 - mmdet - INFO - Epoch [6][2600/7330] lr: 1.000e-04, eta: 11:57:04, time: 0.999, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0444, loss_cls: 0.1784, acc: 93.4802, loss_bbox: 0.2234, loss_mask: 0.2359, loss: 0.7002 2024-06-05 10:28:32,606 - mmdet - INFO - Epoch [6][2650/7330] lr: 1.000e-04, eta: 11:56:25, time: 0.977, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0445, loss_cls: 0.1805, acc: 93.2893, loss_bbox: 0.2375, loss_mask: 0.2343, loss: 0.7154 2024-06-05 10:29:18,794 - mmdet - INFO - Epoch [6][2700/7330] lr: 1.000e-04, eta: 11:55:44, time: 0.924, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0444, loss_cls: 0.1855, acc: 93.2090, loss_bbox: 0.2299, loss_mask: 0.2304, loss: 0.7088 2024-06-05 10:30:03,002 - mmdet - INFO - Epoch [6][2750/7330] lr: 1.000e-04, eta: 11:55:00, time: 0.884, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0454, loss_cls: 0.1868, acc: 93.1235, loss_bbox: 0.2412, loss_mask: 0.2316, loss: 0.7237 2024-06-05 10:30:46,883 - mmdet - INFO - Epoch [6][2800/7330] lr: 1.000e-04, eta: 11:54:15, time: 0.878, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0463, loss_cls: 0.1854, acc: 93.1831, loss_bbox: 0.2347, loss_mask: 0.2326, loss: 0.7171 2024-06-05 10:31:30,429 - mmdet - INFO - Epoch [6][2850/7330] lr: 1.000e-04, eta: 11:53:30, time: 0.871, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0429, loss_cls: 0.1852, acc: 93.2488, loss_bbox: 0.2322, loss_mask: 0.2342, loss: 0.7124 2024-06-05 10:32:14,284 - mmdet - INFO - Epoch [6][2900/7330] lr: 1.000e-04, eta: 11:52:46, time: 0.877, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0424, loss_cls: 0.1782, acc: 93.5208, loss_bbox: 0.2279, loss_mask: 0.2337, loss: 0.6995 2024-06-05 10:32:57,828 - mmdet - INFO - Epoch [6][2950/7330] lr: 1.000e-04, eta: 11:52:01, time: 0.871, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0420, loss_cls: 0.1704, acc: 93.7195, loss_bbox: 0.2240, loss_mask: 0.2235, loss: 0.6768 2024-06-05 10:33:41,171 - mmdet - INFO - Epoch [6][3000/7330] lr: 1.000e-04, eta: 11:51:15, time: 0.867, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0447, loss_cls: 0.1842, acc: 93.2568, loss_bbox: 0.2346, loss_mask: 0.2327, loss: 0.7145 2024-06-05 10:34:24,541 - mmdet - INFO - Epoch [6][3050/7330] lr: 1.000e-04, eta: 11:50:30, time: 0.867, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0415, loss_cls: 0.1790, acc: 93.4858, loss_bbox: 0.2245, loss_mask: 0.2317, loss: 0.6945 2024-06-05 10:35:08,007 - mmdet - INFO - Epoch [6][3100/7330] lr: 1.000e-04, eta: 11:49:45, time: 0.869, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0435, loss_cls: 0.1768, acc: 93.4207, loss_bbox: 0.2314, loss_mask: 0.2369, loss: 0.7064 2024-06-05 10:35:54,585 - mmdet - INFO - Epoch [6][3150/7330] lr: 1.000e-04, eta: 11:49:04, time: 0.932, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0414, loss_cls: 0.1708, acc: 93.7212, loss_bbox: 0.2214, loss_mask: 0.2200, loss: 0.6702 2024-06-05 10:36:38,046 - mmdet - INFO - Epoch [6][3200/7330] lr: 1.000e-04, eta: 11:48:19, time: 0.869, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0417, loss_cls: 0.1813, acc: 93.3853, loss_bbox: 0.2301, loss_mask: 0.2308, loss: 0.6999 2024-06-05 10:37:21,449 - mmdet - INFO - Epoch [6][3250/7330] lr: 1.000e-04, eta: 11:47:34, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0425, loss_cls: 0.1802, acc: 93.3184, loss_bbox: 0.2316, loss_mask: 0.2396, loss: 0.7134 2024-06-05 10:38:04,678 - mmdet - INFO - Epoch [6][3300/7330] lr: 1.000e-04, eta: 11:46:49, time: 0.865, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0433, loss_cls: 0.1798, acc: 93.4263, loss_bbox: 0.2303, loss_mask: 0.2321, loss: 0.7025 2024-06-05 10:38:48,107 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 10:38:48,108 - mmdet - INFO - Epoch [6][3350/7330] lr: 1.000e-04, eta: 11:46:04, time: 0.869, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0414, loss_cls: 0.1818, acc: 93.3706, loss_bbox: 0.2267, loss_mask: 0.2324, loss: 0.7008 2024-06-05 10:39:33,971 - mmdet - INFO - Epoch [6][3400/7330] lr: 1.000e-04, eta: 11:45:21, time: 0.917, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0436, loss_cls: 0.1819, acc: 93.3306, loss_bbox: 0.2296, loss_mask: 0.2317, loss: 0.7051 2024-06-05 10:40:17,514 - mmdet - INFO - Epoch [6][3450/7330] lr: 1.000e-04, eta: 11:44:37, time: 0.871, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0413, loss_cls: 0.1749, acc: 93.6580, loss_bbox: 0.2238, loss_mask: 0.2316, loss: 0.6880 2024-06-05 10:41:00,701 - mmdet - INFO - Epoch [6][3500/7330] lr: 1.000e-04, eta: 11:43:51, time: 0.864, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0431, loss_cls: 0.1711, acc: 93.6960, loss_bbox: 0.2227, loss_mask: 0.2277, loss: 0.6810 2024-06-05 10:41:44,384 - mmdet - INFO - Epoch [6][3550/7330] lr: 1.000e-04, eta: 11:43:06, time: 0.874, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0438, loss_cls: 0.1804, acc: 93.3801, loss_bbox: 0.2294, loss_mask: 0.2275, loss: 0.6972 2024-06-05 10:42:27,653 - mmdet - INFO - Epoch [6][3600/7330] lr: 1.000e-04, eta: 11:42:21, time: 0.865, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0427, loss_cls: 0.1796, acc: 93.4307, loss_bbox: 0.2279, loss_mask: 0.2305, loss: 0.6978 2024-06-05 10:43:11,281 - mmdet - INFO - Epoch [6][3650/7330] lr: 1.000e-04, eta: 11:41:36, time: 0.873, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0407, loss_cls: 0.1766, acc: 93.5435, loss_bbox: 0.2274, loss_mask: 0.2246, loss: 0.6846 2024-06-05 10:43:55,168 - mmdet - INFO - Epoch [6][3700/7330] lr: 1.000e-04, eta: 11:40:52, time: 0.878, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0443, loss_cls: 0.1889, acc: 93.1299, loss_bbox: 0.2397, loss_mask: 0.2364, loss: 0.7288 2024-06-05 10:44:39,304 - mmdet - INFO - Epoch [6][3750/7330] lr: 1.000e-04, eta: 11:40:08, time: 0.883, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0442, loss_cls: 0.1778, acc: 93.4236, loss_bbox: 0.2307, loss_mask: 0.2319, loss: 0.7024 2024-06-05 10:45:22,511 - mmdet - INFO - Epoch [6][3800/7330] lr: 1.000e-04, eta: 11:39:22, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0407, loss_cls: 0.1770, acc: 93.4841, loss_bbox: 0.2265, loss_mask: 0.2257, loss: 0.6867 2024-06-05 10:46:12,993 - mmdet - INFO - Epoch [6][3850/7330] lr: 1.000e-04, eta: 11:38:46, time: 1.010, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0426, loss_cls: 0.1760, acc: 93.5708, loss_bbox: 0.2234, loss_mask: 0.2323, loss: 0.6921 2024-06-05 10:47:02,869 - mmdet - INFO - Epoch [6][3900/7330] lr: 1.000e-04, eta: 11:38:08, time: 0.998, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0437, loss_cls: 0.1788, acc: 93.4700, loss_bbox: 0.2275, loss_mask: 0.2298, loss: 0.6984 2024-06-05 10:47:48,589 - mmdet - INFO - Epoch [6][3950/7330] lr: 1.000e-04, eta: 11:37:26, time: 0.914, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0419, loss_cls: 0.1747, acc: 93.5540, loss_bbox: 0.2285, loss_mask: 0.2321, loss: 0.6935 2024-06-05 10:48:32,453 - mmdet - INFO - Epoch [6][4000/7330] lr: 1.000e-04, eta: 11:36:41, time: 0.877, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0470, loss_cls: 0.1932, acc: 92.9426, loss_bbox: 0.2447, loss_mask: 0.2312, loss: 0.7360 2024-06-05 10:49:16,416 - mmdet - INFO - Epoch [6][4050/7330] lr: 1.000e-04, eta: 11:35:57, time: 0.879, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0428, loss_cls: 0.1797, acc: 93.4282, loss_bbox: 0.2320, loss_mask: 0.2326, loss: 0.7046 2024-06-05 10:50:00,547 - mmdet - INFO - Epoch [6][4100/7330] lr: 1.000e-04, eta: 11:35:13, time: 0.883, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0473, loss_cls: 0.1894, acc: 93.1545, loss_bbox: 0.2336, loss_mask: 0.2356, loss: 0.7273 2024-06-05 10:50:43,941 - mmdet - INFO - Epoch [6][4150/7330] lr: 1.000e-04, eta: 11:34:28, time: 0.868, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0419, loss_cls: 0.1768, acc: 93.5278, loss_bbox: 0.2281, loss_mask: 0.2365, loss: 0.7010 2024-06-05 10:51:27,383 - mmdet - INFO - Epoch [6][4200/7330] lr: 1.000e-04, eta: 11:33:42, time: 0.869, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0432, loss_cls: 0.1775, acc: 93.4990, loss_bbox: 0.2316, loss_mask: 0.2251, loss: 0.6930 2024-06-05 10:52:10,905 - mmdet - INFO - Epoch [6][4250/7330] lr: 1.000e-04, eta: 11:32:58, time: 0.871, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0449, loss_cls: 0.1848, acc: 93.3467, loss_bbox: 0.2282, loss_mask: 0.2361, loss: 0.7120 2024-06-05 10:52:54,415 - mmdet - INFO - Epoch [6][4300/7330] lr: 1.000e-04, eta: 11:32:13, time: 0.870, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0410, loss_cls: 0.1795, acc: 93.4546, loss_bbox: 0.2245, loss_mask: 0.2277, loss: 0.6894 2024-06-05 10:53:37,813 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 10:53:37,813 - mmdet - INFO - Epoch [6][4350/7330] lr: 1.000e-04, eta: 11:31:28, time: 0.868, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0396, loss_cls: 0.1742, acc: 93.6016, loss_bbox: 0.2257, loss_mask: 0.2280, loss: 0.6844 2024-06-05 10:54:24,548 - mmdet - INFO - Epoch [6][4400/7330] lr: 1.000e-04, eta: 11:30:46, time: 0.935, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0432, loss_cls: 0.1791, acc: 93.2839, loss_bbox: 0.2329, loss_mask: 0.2340, loss: 0.7058 2024-06-05 10:55:08,222 - mmdet - INFO - Epoch [6][4450/7330] lr: 1.000e-04, eta: 11:30:02, time: 0.874, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0434, loss_cls: 0.1837, acc: 93.2349, loss_bbox: 0.2344, loss_mask: 0.2340, loss: 0.7131 2024-06-05 10:55:52,215 - mmdet - INFO - Epoch [6][4500/7330] lr: 1.000e-04, eta: 11:29:17, time: 0.880, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0432, loss_cls: 0.1847, acc: 93.2510, loss_bbox: 0.2352, loss_mask: 0.2331, loss: 0.7135 2024-06-05 10:56:36,069 - mmdet - INFO - Epoch [6][4550/7330] lr: 1.000e-04, eta: 11:28:33, time: 0.877, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0410, loss_cls: 0.1845, acc: 93.3047, loss_bbox: 0.2273, loss_mask: 0.2314, loss: 0.7015 2024-06-05 10:57:19,380 - mmdet - INFO - Epoch [6][4600/7330] lr: 1.000e-04, eta: 11:27:47, time: 0.866, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0411, loss_cls: 0.1772, acc: 93.4595, loss_bbox: 0.2290, loss_mask: 0.2325, loss: 0.6966 2024-06-05 10:58:05,053 - mmdet - INFO - Epoch [6][4650/7330] lr: 1.000e-04, eta: 11:27:05, time: 0.913, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0440, loss_cls: 0.1842, acc: 93.3906, loss_bbox: 0.2336, loss_mask: 0.2264, loss: 0.7067 2024-06-05 10:58:48,720 - mmdet - INFO - Epoch [6][4700/7330] lr: 1.000e-04, eta: 11:26:20, time: 0.873, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0439, loss_cls: 0.1819, acc: 93.1833, loss_bbox: 0.2377, loss_mask: 0.2314, loss: 0.7123 2024-06-05 10:59:32,497 - mmdet - INFO - Epoch [6][4750/7330] lr: 1.000e-04, eta: 11:25:36, time: 0.876, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0441, loss_cls: 0.1824, acc: 93.3596, loss_bbox: 0.2290, loss_mask: 0.2323, loss: 0.7060 2024-06-05 11:00:15,788 - mmdet - INFO - Epoch [6][4800/7330] lr: 1.000e-04, eta: 11:24:50, time: 0.866, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0403, loss_cls: 0.1776, acc: 93.5649, loss_bbox: 0.2255, loss_mask: 0.2254, loss: 0.6846 2024-06-05 11:00:59,362 - mmdet - INFO - Epoch [6][4850/7330] lr: 1.000e-04, eta: 11:24:06, time: 0.871, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0401, loss_cls: 0.1739, acc: 93.7261, loss_bbox: 0.2185, loss_mask: 0.2290, loss: 0.6779 2024-06-05 11:01:43,239 - mmdet - INFO - Epoch [6][4900/7330] lr: 1.000e-04, eta: 11:23:21, time: 0.878, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0456, loss_cls: 0.1862, acc: 93.1328, loss_bbox: 0.2419, loss_mask: 0.2387, loss: 0.7304 2024-06-05 11:02:26,169 - mmdet - INFO - Epoch [6][4950/7330] lr: 1.000e-04, eta: 11:22:36, time: 0.859, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0395, loss_cls: 0.1735, acc: 93.6594, loss_bbox: 0.2186, loss_mask: 0.2260, loss: 0.6730 2024-06-05 11:03:10,253 - mmdet - INFO - Epoch [6][5000/7330] lr: 1.000e-04, eta: 11:21:51, time: 0.882, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0462, loss_cls: 0.1909, acc: 92.9307, loss_bbox: 0.2462, loss_mask: 0.2337, loss: 0.7362 2024-06-05 11:03:53,548 - mmdet - INFO - Epoch [6][5050/7330] lr: 1.000e-04, eta: 11:21:06, time: 0.866, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0432, loss_cls: 0.1769, acc: 93.5215, loss_bbox: 0.2250, loss_mask: 0.2303, loss: 0.6910 2024-06-05 11:04:43,854 - mmdet - INFO - Epoch [6][5100/7330] lr: 1.000e-04, eta: 11:20:29, time: 1.006, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0418, loss_cls: 0.1763, acc: 93.5989, loss_bbox: 0.2244, loss_mask: 0.2281, loss: 0.6885 2024-06-05 11:05:32,262 - mmdet - INFO - Epoch [6][5150/7330] lr: 1.000e-04, eta: 11:19:49, time: 0.968, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0441, loss_cls: 0.1837, acc: 93.1853, loss_bbox: 0.2390, loss_mask: 0.2361, loss: 0.7210 2024-06-05 11:06:18,092 - mmdet - INFO - Epoch [6][5200/7330] lr: 1.000e-04, eta: 11:19:07, time: 0.917, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0429, loss_cls: 0.1869, acc: 93.1362, loss_bbox: 0.2395, loss_mask: 0.2389, loss: 0.7260 2024-06-05 11:07:01,713 - mmdet - INFO - Epoch [6][5250/7330] lr: 1.000e-04, eta: 11:18:22, time: 0.872, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0457, loss_cls: 0.1878, acc: 93.1626, loss_bbox: 0.2362, loss_mask: 0.2341, loss: 0.7238 2024-06-05 11:07:45,051 - mmdet - INFO - Epoch [6][5300/7330] lr: 1.000e-04, eta: 11:17:37, time: 0.867, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0420, loss_cls: 0.1816, acc: 93.3459, loss_bbox: 0.2326, loss_mask: 0.2332, loss: 0.7070 2024-06-05 11:08:28,700 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 11:08:28,700 - mmdet - INFO - Epoch [6][5350/7330] lr: 1.000e-04, eta: 11:16:52, time: 0.873, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0444, loss_cls: 0.1827, acc: 93.3328, loss_bbox: 0.2260, loss_mask: 0.2277, loss: 0.6975 2024-06-05 11:09:12,190 - mmdet - INFO - Epoch [6][5400/7330] lr: 1.000e-04, eta: 11:16:07, time: 0.870, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0433, loss_cls: 0.1743, acc: 93.5632, loss_bbox: 0.2239, loss_mask: 0.2285, loss: 0.6868 2024-06-05 11:09:55,430 - mmdet - INFO - Epoch [6][5450/7330] lr: 1.000e-04, eta: 11:15:22, time: 0.865, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0412, loss_cls: 0.1878, acc: 93.0701, loss_bbox: 0.2331, loss_mask: 0.2372, loss: 0.7175 2024-06-05 11:10:38,923 - mmdet - INFO - Epoch [6][5500/7330] lr: 1.000e-04, eta: 11:14:37, time: 0.870, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0426, loss_cls: 0.1717, acc: 93.7373, loss_bbox: 0.2211, loss_mask: 0.2290, loss: 0.6820 2024-06-05 11:11:22,677 - mmdet - INFO - Epoch [6][5550/7330] lr: 1.000e-04, eta: 11:13:52, time: 0.875, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0440, loss_cls: 0.1731, acc: 93.6052, loss_bbox: 0.2227, loss_mask: 0.2329, loss: 0.6894 2024-06-05 11:12:06,015 - mmdet - INFO - Epoch [6][5600/7330] lr: 1.000e-04, eta: 11:13:07, time: 0.867, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0422, loss_cls: 0.1764, acc: 93.4988, loss_bbox: 0.2294, loss_mask: 0.2307, loss: 0.6953 2024-06-05 11:12:49,111 - mmdet - INFO - Epoch [6][5650/7330] lr: 1.000e-04, eta: 11:12:22, time: 0.862, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0402, loss_cls: 0.1725, acc: 93.7993, loss_bbox: 0.2187, loss_mask: 0.2335, loss: 0.6810 2024-06-05 11:13:35,349 - mmdet - INFO - Epoch [6][5700/7330] lr: 1.000e-04, eta: 11:11:40, time: 0.925, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0433, loss_cls: 0.1805, acc: 93.4573, loss_bbox: 0.2256, loss_mask: 0.2341, loss: 0.7012 2024-06-05 11:14:18,508 - mmdet - INFO - Epoch [6][5750/7330] lr: 1.000e-04, eta: 11:10:55, time: 0.863, data_time: 0.036, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0395, loss_cls: 0.1748, acc: 93.7075, loss_bbox: 0.2191, loss_mask: 0.2244, loss: 0.6739 2024-06-05 11:15:01,739 - mmdet - INFO - Epoch [6][5800/7330] lr: 1.000e-04, eta: 11:10:10, time: 0.865, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0427, loss_cls: 0.1810, acc: 93.4583, loss_bbox: 0.2263, loss_mask: 0.2275, loss: 0.6947 2024-06-05 11:15:45,659 - mmdet - INFO - Epoch [6][5850/7330] lr: 1.000e-04, eta: 11:09:25, time: 0.878, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0447, loss_cls: 0.1885, acc: 93.2056, loss_bbox: 0.2329, loss_mask: 0.2314, loss: 0.7178 2024-06-05 11:16:31,479 - mmdet - INFO - Epoch [6][5900/7330] lr: 1.000e-04, eta: 11:08:43, time: 0.916, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0460, loss_cls: 0.1853, acc: 93.1611, loss_bbox: 0.2358, loss_mask: 0.2350, loss: 0.7214 2024-06-05 11:17:14,703 - mmdet - INFO - Epoch [6][5950/7330] lr: 1.000e-04, eta: 11:07:58, time: 0.864, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0441, loss_cls: 0.1827, acc: 93.2537, loss_bbox: 0.2340, loss_mask: 0.2339, loss: 0.7120 2024-06-05 11:17:58,080 - mmdet - INFO - Epoch [6][6000/7330] lr: 1.000e-04, eta: 11:07:13, time: 0.868, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0439, loss_cls: 0.1885, acc: 93.1340, loss_bbox: 0.2362, loss_mask: 0.2417, loss: 0.7287 2024-06-05 11:18:41,765 - mmdet - INFO - Epoch [6][6050/7330] lr: 1.000e-04, eta: 11:06:28, time: 0.874, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0413, loss_cls: 0.1790, acc: 93.4292, loss_bbox: 0.2316, loss_mask: 0.2375, loss: 0.7071 2024-06-05 11:19:25,333 - mmdet - INFO - Epoch [6][6100/7330] lr: 1.000e-04, eta: 11:05:43, time: 0.871, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0429, loss_cls: 0.1821, acc: 93.3691, loss_bbox: 0.2291, loss_mask: 0.2355, loss: 0.7075 2024-06-05 11:20:08,558 - mmdet - INFO - Epoch [6][6150/7330] lr: 1.000e-04, eta: 11:04:58, time: 0.865, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0427, loss_cls: 0.1828, acc: 93.4104, loss_bbox: 0.2323, loss_mask: 0.2356, loss: 0.7104 2024-06-05 11:20:52,373 - mmdet - INFO - Epoch [6][6200/7330] lr: 1.000e-04, eta: 11:04:13, time: 0.876, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0444, loss_cls: 0.1827, acc: 93.3655, loss_bbox: 0.2286, loss_mask: 0.2293, loss: 0.7047 2024-06-05 11:21:35,712 - mmdet - INFO - Epoch [6][6250/7330] lr: 1.000e-04, eta: 11:03:28, time: 0.867, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0399, loss_cls: 0.1784, acc: 93.3745, loss_bbox: 0.2258, loss_mask: 0.2317, loss: 0.6926 2024-06-05 11:22:19,604 - mmdet - INFO - Epoch [6][6300/7330] lr: 1.000e-04, eta: 11:02:44, time: 0.878, data_time: 0.072, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0455, loss_cls: 0.1868, acc: 93.2483, loss_bbox: 0.2358, loss_mask: 0.2317, loss: 0.7169 2024-06-05 11:23:09,973 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 11:23:09,973 - mmdet - INFO - Epoch [6][6350/7330] lr: 1.000e-04, eta: 11:02:06, time: 1.007, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0406, loss_cls: 0.1805, acc: 93.3455, loss_bbox: 0.2266, loss_mask: 0.2321, loss: 0.6980 2024-06-05 11:23:58,399 - mmdet - INFO - Epoch [6][6400/7330] lr: 1.000e-04, eta: 11:01:26, time: 0.969, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0457, loss_cls: 0.1913, acc: 92.9812, loss_bbox: 0.2413, loss_mask: 0.2378, loss: 0.7346 2024-06-05 11:24:44,213 - mmdet - INFO - Epoch [6][6450/7330] lr: 1.000e-04, eta: 11:00:44, time: 0.916, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0431, loss_cls: 0.1822, acc: 93.3198, loss_bbox: 0.2350, loss_mask: 0.2358, loss: 0.7134 2024-06-05 11:25:27,507 - mmdet - INFO - Epoch [6][6500/7330] lr: 1.000e-04, eta: 10:59:59, time: 0.866, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0405, loss_cls: 0.1701, acc: 93.7949, loss_bbox: 0.2172, loss_mask: 0.2229, loss: 0.6666 2024-06-05 11:26:11,095 - mmdet - INFO - Epoch [6][6550/7330] lr: 1.000e-04, eta: 10:59:14, time: 0.872, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0440, loss_cls: 0.1802, acc: 93.4363, loss_bbox: 0.2283, loss_mask: 0.2325, loss: 0.7031 2024-06-05 11:26:54,188 - mmdet - INFO - Epoch [6][6600/7330] lr: 1.000e-04, eta: 10:58:29, time: 0.862, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0402, loss_cls: 0.1744, acc: 93.5632, loss_bbox: 0.2237, loss_mask: 0.2314, loss: 0.6873 2024-06-05 11:27:37,990 - mmdet - INFO - Epoch [6][6650/7330] lr: 1.000e-04, eta: 10:57:44, time: 0.876, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0397, loss_cls: 0.1764, acc: 93.5378, loss_bbox: 0.2250, loss_mask: 0.2322, loss: 0.6900 2024-06-05 11:28:21,070 - mmdet - INFO - Epoch [6][6700/7330] lr: 1.000e-04, eta: 10:56:59, time: 0.861, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0429, loss_cls: 0.1779, acc: 93.5054, loss_bbox: 0.2226, loss_mask: 0.2232, loss: 0.6839 2024-06-05 11:29:04,550 - mmdet - INFO - Epoch [6][6750/7330] lr: 1.000e-04, eta: 10:56:14, time: 0.870, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0399, loss_cls: 0.1717, acc: 93.6545, loss_bbox: 0.2199, loss_mask: 0.2271, loss: 0.6756 2024-06-05 11:29:48,337 - mmdet - INFO - Epoch [6][6800/7330] lr: 1.000e-04, eta: 10:55:29, time: 0.876, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0441, loss_cls: 0.1809, acc: 93.3984, loss_bbox: 0.2344, loss_mask: 0.2303, loss: 0.7086 2024-06-05 11:30:31,296 - mmdet - INFO - Epoch [6][6850/7330] lr: 1.000e-04, eta: 10:54:44, time: 0.859, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0410, loss_cls: 0.1757, acc: 93.5337, loss_bbox: 0.2197, loss_mask: 0.2254, loss: 0.6775 2024-06-05 11:31:14,788 - mmdet - INFO - Epoch [6][6900/7330] lr: 1.000e-04, eta: 10:53:59, time: 0.870, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0398, loss_cls: 0.1769, acc: 93.5959, loss_bbox: 0.2262, loss_mask: 0.2290, loss: 0.6874 2024-06-05 11:32:25,233 - mmdet - INFO - Epoch [6][6950/7330] lr: 1.000e-04, eta: 10:53:41, time: 1.409, data_time: 0.530, memory: 11350, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0460, loss_cls: 0.1900, acc: 93.0032, loss_bbox: 0.2434, loss_mask: 0.2420, loss: 0.7415 2024-06-05 11:33:08,344 - mmdet - INFO - Epoch [6][7000/7330] lr: 1.000e-04, eta: 10:52:56, time: 0.862, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0438, loss_cls: 0.1852, acc: 93.1482, loss_bbox: 0.2314, loss_mask: 0.2319, loss: 0.7103 2024-06-05 11:33:51,448 - mmdet - INFO - Epoch [6][7050/7330] lr: 1.000e-04, eta: 10:52:11, time: 0.862, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0417, loss_cls: 0.1770, acc: 93.5203, loss_bbox: 0.2226, loss_mask: 0.2258, loss: 0.6843 2024-06-05 11:34:35,513 - mmdet - INFO - Epoch [6][7100/7330] lr: 1.000e-04, eta: 10:51:26, time: 0.881, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0446, loss_cls: 0.1898, acc: 93.0479, loss_bbox: 0.2381, loss_mask: 0.2407, loss: 0.7325 2024-06-05 11:35:21,009 - mmdet - INFO - Epoch [6][7150/7330] lr: 1.000e-04, eta: 10:50:44, time: 0.910, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0423, loss_cls: 0.1772, acc: 93.4600, loss_bbox: 0.2272, loss_mask: 0.2312, loss: 0.6952 2024-06-05 11:36:04,445 - mmdet - INFO - Epoch [6][7200/7330] lr: 1.000e-04, eta: 10:49:59, time: 0.869, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0435, loss_cls: 0.1851, acc: 93.3416, loss_bbox: 0.2298, loss_mask: 0.2350, loss: 0.7125 2024-06-05 11:36:47,772 - mmdet - INFO - Epoch [6][7250/7330] lr: 1.000e-04, eta: 10:49:13, time: 0.867, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0446, loss_cls: 0.1826, acc: 93.3733, loss_bbox: 0.2263, loss_mask: 0.2303, loss: 0.7021 2024-06-05 11:37:31,877 - mmdet - INFO - Epoch [6][7300/7330] lr: 1.000e-04, eta: 10:48:29, time: 0.882, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0425, loss_cls: 0.1794, acc: 93.4270, loss_bbox: 0.2241, loss_mask: 0.2287, loss: 0.6936 2024-06-05 11:37:58,643 - mmdet - INFO - Saving checkpoint at 6 epochs 2024-06-05 11:39:49,475 - mmdet - INFO - Evaluating bbox... 2024-06-05 11:40:14,224 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.448 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.673 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.491 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.268 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.485 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.620 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.572 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.572 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.572 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.373 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.613 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.744 2024-06-05 11:40:14,224 - mmdet - INFO - Evaluating segm... 2024-06-05 11:40:47,804 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.406 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.638 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.432 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.190 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.436 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.624 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.518 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.518 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.518 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.563 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.710 2024-06-05 11:40:48,370 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 11:40:48,371 - mmdet - INFO - Epoch(val) [6][625] bbox_mAP: 0.4480, bbox_mAP_50: 0.6730, bbox_mAP_75: 0.4910, bbox_mAP_s: 0.2680, bbox_mAP_m: 0.4850, bbox_mAP_l: 0.6200, bbox_mAP_copypaste: 0.448 0.673 0.491 0.268 0.485 0.620, segm_mAP: 0.4060, segm_mAP_50: 0.6380, segm_mAP_75: 0.4320, segm_mAP_s: 0.1900, segm_mAP_m: 0.4360, segm_mAP_l: 0.6240, segm_mAP_copypaste: 0.406 0.638 0.432 0.190 0.436 0.624 2024-06-05 11:41:35,964 - mmdet - INFO - Epoch [7][50/7330] lr: 1.000e-04, eta: 10:46:55, time: 0.951, data_time: 0.129, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0412, loss_cls: 0.1735, acc: 93.5928, loss_bbox: 0.2219, loss_mask: 0.2262, loss: 0.6780 2024-06-05 11:42:22,296 - mmdet - INFO - Epoch [7][100/7330] lr: 1.000e-04, eta: 10:46:13, time: 0.927, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0395, loss_cls: 0.1659, acc: 93.8303, loss_bbox: 0.2210, loss_mask: 0.2264, loss: 0.6683 2024-06-05 11:43:06,242 - mmdet - INFO - Epoch [7][150/7330] lr: 1.000e-04, eta: 10:45:29, time: 0.879, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0406, loss_cls: 0.1687, acc: 93.7642, loss_bbox: 0.2205, loss_mask: 0.2242, loss: 0.6689 2024-06-05 11:43:50,160 - mmdet - INFO - Epoch [7][200/7330] lr: 1.000e-04, eta: 10:44:44, time: 0.878, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0404, loss_cls: 0.1708, acc: 93.6243, loss_bbox: 0.2189, loss_mask: 0.2315, loss: 0.6770 2024-06-05 11:44:33,903 - mmdet - INFO - Epoch [7][250/7330] lr: 1.000e-04, eta: 10:44:00, time: 0.875, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0381, loss_cls: 0.1613, acc: 93.9504, loss_bbox: 0.2125, loss_mask: 0.2181, loss: 0.6445 2024-06-05 11:45:17,995 - mmdet - INFO - Epoch [7][300/7330] lr: 1.000e-04, eta: 10:43:16, time: 0.882, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0416, loss_cls: 0.1730, acc: 93.6650, loss_bbox: 0.2274, loss_mask: 0.2246, loss: 0.6812 2024-06-05 11:46:03,041 - mmdet - INFO - Epoch [7][350/7330] lr: 1.000e-04, eta: 10:42:32, time: 0.901, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0427, loss_cls: 0.1763, acc: 93.4392, loss_bbox: 0.2282, loss_mask: 0.2243, loss: 0.6874 2024-06-05 11:46:47,620 - mmdet - INFO - Epoch [7][400/7330] lr: 1.000e-04, eta: 10:41:48, time: 0.891, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0413, loss_cls: 0.1717, acc: 93.5715, loss_bbox: 0.2262, loss_mask: 0.2253, loss: 0.6794 2024-06-05 11:47:31,943 - mmdet - INFO - Epoch [7][450/7330] lr: 1.000e-04, eta: 10:41:04, time: 0.887, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0425, loss_cls: 0.1729, acc: 93.5002, loss_bbox: 0.2279, loss_mask: 0.2259, loss: 0.6846 2024-06-05 11:48:15,707 - mmdet - INFO - Epoch [7][500/7330] lr: 1.000e-04, eta: 10:40:20, time: 0.875, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0397, loss_cls: 0.1659, acc: 93.8328, loss_bbox: 0.2215, loss_mask: 0.2290, loss: 0.6718 2024-06-05 11:48:59,747 - mmdet - INFO - Epoch [7][550/7330] lr: 1.000e-04, eta: 10:39:35, time: 0.881, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0432, loss_cls: 0.1659, acc: 93.8362, loss_bbox: 0.2211, loss_mask: 0.2273, loss: 0.6723 2024-06-05 11:49:43,655 - mmdet - INFO - Epoch [7][600/7330] lr: 1.000e-04, eta: 10:38:51, time: 0.878, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0405, loss_cls: 0.1730, acc: 93.4976, loss_bbox: 0.2269, loss_mask: 0.2226, loss: 0.6777 2024-06-05 11:50:26,892 - mmdet - INFO - Epoch [7][650/7330] lr: 1.000e-04, eta: 10:38:06, time: 0.865, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0385, loss_cls: 0.1654, acc: 93.8706, loss_bbox: 0.2191, loss_mask: 0.2206, loss: 0.6580 2024-06-05 11:51:10,768 - mmdet - INFO - Epoch [7][700/7330] lr: 1.000e-04, eta: 10:37:21, time: 0.878, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0423, loss_cls: 0.1735, acc: 93.5020, loss_bbox: 0.2276, loss_mask: 0.2331, loss: 0.6924 2024-06-05 11:51:54,248 - mmdet - INFO - Epoch [7][750/7330] lr: 1.000e-04, eta: 10:36:37, time: 0.870, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0412, loss_cls: 0.1665, acc: 93.9272, loss_bbox: 0.2165, loss_mask: 0.2251, loss: 0.6647 2024-06-05 11:52:37,622 - mmdet - INFO - Epoch [7][800/7330] lr: 1.000e-04, eta: 10:35:52, time: 0.867, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0390, loss_cls: 0.1609, acc: 94.0872, loss_bbox: 0.2137, loss_mask: 0.2243, loss: 0.6520 2024-06-05 11:53:24,502 - mmdet - INFO - Epoch [7][850/7330] lr: 1.000e-04, eta: 10:35:10, time: 0.938, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0416, loss_cls: 0.1702, acc: 93.7461, loss_bbox: 0.2236, loss_mask: 0.2261, loss: 0.6778 2024-06-05 11:54:08,192 - mmdet - INFO - Epoch [7][900/7330] lr: 1.000e-04, eta: 10:34:25, time: 0.874, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0406, loss_cls: 0.1690, acc: 93.6655, loss_bbox: 0.2244, loss_mask: 0.2251, loss: 0.6740 2024-06-05 11:54:51,844 - mmdet - INFO - Epoch [7][950/7330] lr: 1.000e-04, eta: 10:33:41, time: 0.873, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0411, loss_cls: 0.1709, acc: 93.6387, loss_bbox: 0.2218, loss_mask: 0.2274, loss: 0.6766 2024-06-05 11:55:36,114 - mmdet - INFO - Epoch [7][1000/7330] lr: 1.000e-04, eta: 10:32:57, time: 0.885, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0410, loss_cls: 0.1714, acc: 93.6350, loss_bbox: 0.2206, loss_mask: 0.2232, loss: 0.6729 2024-06-05 11:56:20,600 - mmdet - INFO - Epoch [7][1050/7330] lr: 1.000e-04, eta: 10:32:13, time: 0.890, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0422, loss_cls: 0.1733, acc: 93.6084, loss_bbox: 0.2228, loss_mask: 0.2247, loss: 0.6794 2024-06-05 11:57:04,327 - mmdet - INFO - Epoch [7][1100/7330] lr: 1.000e-04, eta: 10:31:28, time: 0.874, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0416, loss_cls: 0.1703, acc: 93.6414, loss_bbox: 0.2202, loss_mask: 0.2286, loss: 0.6773 2024-06-05 11:57:48,541 - mmdet - INFO - Epoch [7][1150/7330] lr: 1.000e-04, eta: 10:30:44, time: 0.884, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0397, loss_cls: 0.1657, acc: 93.7861, loss_bbox: 0.2199, loss_mask: 0.2255, loss: 0.6650 2024-06-05 11:58:33,212 - mmdet - INFO - Epoch [7][1200/7330] lr: 1.000e-04, eta: 10:30:00, time: 0.893, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0420, loss_cls: 0.1785, acc: 93.4905, loss_bbox: 0.2312, loss_mask: 0.2262, loss: 0.6940 2024-06-05 11:59:19,425 - mmdet - INFO - Epoch [7][1250/7330] lr: 1.000e-04, eta: 10:29:18, time: 0.924, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0422, loss_cls: 0.1768, acc: 93.5864, loss_bbox: 0.2242, loss_mask: 0.2309, loss: 0.6929 2024-06-05 12:00:06,257 - mmdet - INFO - Epoch [7][1300/7330] lr: 1.000e-04, eta: 10:28:36, time: 0.937, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0434, loss_cls: 0.1820, acc: 93.2671, loss_bbox: 0.2359, loss_mask: 0.2310, loss: 0.7090 2024-06-05 12:00:50,311 - mmdet - INFO - Epoch [7][1350/7330] lr: 1.000e-04, eta: 10:27:52, time: 0.881, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0419, loss_cls: 0.1697, acc: 93.7544, loss_bbox: 0.2208, loss_mask: 0.2276, loss: 0.6753 2024-06-05 12:01:36,178 - mmdet - INFO - Epoch [7][1400/7330] lr: 1.000e-04, eta: 10:27:09, time: 0.917, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0376, loss_cls: 0.1624, acc: 93.8606, loss_bbox: 0.2160, loss_mask: 0.2195, loss: 0.6509 2024-06-05 12:02:21,042 - mmdet - INFO - Epoch [7][1450/7330] lr: 1.000e-04, eta: 10:26:26, time: 0.897, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0434, loss_cls: 0.1719, acc: 93.6052, loss_bbox: 0.2283, loss_mask: 0.2256, loss: 0.6859 2024-06-05 12:03:05,122 - mmdet - INFO - Epoch [7][1500/7330] lr: 1.000e-04, eta: 10:25:42, time: 0.882, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0407, loss_cls: 0.1644, acc: 93.9133, loss_bbox: 0.2128, loss_mask: 0.2210, loss: 0.6549 2024-06-05 12:03:53,893 - mmdet - INFO - Epoch [7][1550/7330] lr: 1.000e-04, eta: 10:25:02, time: 0.975, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0379, loss_cls: 0.1574, acc: 94.1252, loss_bbox: 0.2078, loss_mask: 0.2167, loss: 0.6340 2024-06-05 12:04:38,386 - mmdet - INFO - Epoch [7][1600/7330] lr: 1.000e-04, eta: 10:24:18, time: 0.890, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0410, loss_cls: 0.1683, acc: 93.7644, loss_bbox: 0.2163, loss_mask: 0.2209, loss: 0.6625 2024-06-05 12:05:25,453 - mmdet - INFO - Epoch [7][1650/7330] lr: 1.000e-04, eta: 10:23:36, time: 0.941, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0412, loss_cls: 0.1722, acc: 93.7312, loss_bbox: 0.2212, loss_mask: 0.2258, loss: 0.6765 2024-06-05 12:06:09,365 - mmdet - INFO - Epoch [7][1700/7330] lr: 1.000e-04, eta: 10:22:52, time: 0.878, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0395, loss_cls: 0.1671, acc: 93.7734, loss_bbox: 0.2156, loss_mask: 0.2191, loss: 0.6555 2024-06-05 12:06:55,815 - mmdet - INFO - Epoch [7][1750/7330] lr: 1.000e-04, eta: 10:22:10, time: 0.929, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0410, loss_cls: 0.1694, acc: 93.6274, loss_bbox: 0.2252, loss_mask: 0.2261, loss: 0.6764 2024-06-05 12:07:40,133 - mmdet - INFO - Epoch [7][1800/7330] lr: 1.000e-04, eta: 10:21:26, time: 0.886, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0400, loss_cls: 0.1672, acc: 93.7717, loss_bbox: 0.2217, loss_mask: 0.2227, loss: 0.6664 2024-06-05 12:08:24,020 - mmdet - INFO - Epoch [7][1850/7330] lr: 1.000e-04, eta: 10:20:41, time: 0.878, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0379, loss_cls: 0.1619, acc: 94.0474, loss_bbox: 0.2110, loss_mask: 0.2216, loss: 0.6467 2024-06-05 12:09:08,169 - mmdet - INFO - Epoch [7][1900/7330] lr: 1.000e-04, eta: 10:19:57, time: 0.883, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0427, loss_cls: 0.1730, acc: 93.6567, loss_bbox: 0.2229, loss_mask: 0.2278, loss: 0.6833 2024-06-05 12:09:52,184 - mmdet - INFO - Epoch [7][1950/7330] lr: 1.000e-04, eta: 10:19:12, time: 0.880, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0415, loss_cls: 0.1742, acc: 93.4250, loss_bbox: 0.2295, loss_mask: 0.2293, loss: 0.6907 2024-06-05 12:10:35,724 - mmdet - INFO - Epoch [7][2000/7330] lr: 1.000e-04, eta: 10:18:28, time: 0.871, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0414, loss_cls: 0.1748, acc: 93.6130, loss_bbox: 0.2256, loss_mask: 0.2249, loss: 0.6822 2024-06-05 12:11:19,952 - mmdet - INFO - Epoch [7][2050/7330] lr: 1.000e-04, eta: 10:17:43, time: 0.885, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0376, loss_cls: 0.1658, acc: 93.8774, loss_bbox: 0.2172, loss_mask: 0.2245, loss: 0.6588 2024-06-05 12:12:07,643 - mmdet - INFO - Epoch [7][2100/7330] lr: 1.000e-04, eta: 10:17:02, time: 0.954, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0426, loss_cls: 0.1754, acc: 93.5640, loss_bbox: 0.2314, loss_mask: 0.2281, loss: 0.6943 2024-06-05 12:12:51,969 - mmdet - INFO - Epoch [7][2150/7330] lr: 1.000e-04, eta: 10:16:18, time: 0.887, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0413, loss_cls: 0.1708, acc: 93.6753, loss_bbox: 0.2164, loss_mask: 0.2223, loss: 0.6671 2024-06-05 12:13:35,911 - mmdet - INFO - Epoch [7][2200/7330] lr: 1.000e-04, eta: 10:15:34, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0430, loss_cls: 0.1756, acc: 93.5679, loss_bbox: 0.2299, loss_mask: 0.2297, loss: 0.6940 2024-06-05 12:14:20,395 - mmdet - INFO - Epoch [7][2250/7330] lr: 1.000e-04, eta: 10:14:50, time: 0.890, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0420, loss_cls: 0.1734, acc: 93.5449, loss_bbox: 0.2283, loss_mask: 0.2249, loss: 0.6849 2024-06-05 12:15:03,785 - mmdet - INFO - Epoch [7][2300/7330] lr: 1.000e-04, eta: 10:14:05, time: 0.868, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0399, loss_cls: 0.1682, acc: 93.8242, loss_bbox: 0.2142, loss_mask: 0.2161, loss: 0.6535 2024-06-05 12:15:47,187 - mmdet - INFO - Epoch [7][2350/7330] lr: 1.000e-04, eta: 10:13:20, time: 0.868, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0417, loss_cls: 0.1786, acc: 93.4648, loss_bbox: 0.2241, loss_mask: 0.2254, loss: 0.6866 2024-06-05 12:16:30,771 - mmdet - INFO - Epoch [7][2400/7330] lr: 1.000e-04, eta: 10:12:35, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0401, loss_cls: 0.1711, acc: 93.6899, loss_bbox: 0.2199, loss_mask: 0.2265, loss: 0.6733 2024-06-05 12:17:15,437 - mmdet - INFO - Epoch [7][2450/7330] lr: 1.000e-04, eta: 10:11:52, time: 0.893, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0417, loss_cls: 0.1693, acc: 93.7681, loss_bbox: 0.2190, loss_mask: 0.2220, loss: 0.6678 2024-06-05 12:18:01,335 - mmdet - INFO - Epoch [7][2500/7330] lr: 1.000e-04, eta: 10:11:09, time: 0.918, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0419, loss_cls: 0.1729, acc: 93.6399, loss_bbox: 0.2212, loss_mask: 0.2288, loss: 0.6820 2024-06-05 12:18:47,450 - mmdet - INFO - Epoch [7][2550/7330] lr: 1.000e-04, eta: 10:10:26, time: 0.922, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0433, loss_cls: 0.1773, acc: 93.4143, loss_bbox: 0.2299, loss_mask: 0.2271, loss: 0.6948 2024-06-05 12:19:32,431 - mmdet - INFO - Epoch [7][2600/7330] lr: 1.000e-04, eta: 10:09:43, time: 0.900, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0423, loss_cls: 0.1750, acc: 93.5046, loss_bbox: 0.2298, loss_mask: 0.2283, loss: 0.6910 2024-06-05 12:20:20,114 - mmdet - INFO - Epoch [7][2650/7330] lr: 1.000e-04, eta: 10:09:02, time: 0.953, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0420, loss_cls: 0.1748, acc: 93.5352, loss_bbox: 0.2220, loss_mask: 0.2279, loss: 0.6826 2024-06-05 12:21:03,480 - mmdet - INFO - Epoch [7][2700/7330] lr: 1.000e-04, eta: 10:08:17, time: 0.868, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0415, loss_cls: 0.1711, acc: 93.7488, loss_bbox: 0.2193, loss_mask: 0.2227, loss: 0.6708 2024-06-05 12:21:47,084 - mmdet - INFO - Epoch [7][2750/7330] lr: 1.000e-04, eta: 10:07:32, time: 0.872, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0408, loss_cls: 0.1680, acc: 93.7454, loss_bbox: 0.2191, loss_mask: 0.2282, loss: 0.6707 2024-06-05 12:22:37,261 - mmdet - INFO - Epoch [7][2800/7330] lr: 1.000e-04, eta: 10:06:53, time: 1.003, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0445, loss_cls: 0.1799, acc: 93.3071, loss_bbox: 0.2272, loss_mask: 0.2288, loss: 0.6966 2024-06-05 12:23:21,603 - mmdet - INFO - Epoch [7][2850/7330] lr: 1.000e-04, eta: 10:06:09, time: 0.887, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0434, loss_cls: 0.1762, acc: 93.4631, loss_bbox: 0.2286, loss_mask: 0.2308, loss: 0.6950 2024-06-05 12:24:10,114 - mmdet - INFO - Epoch [7][2900/7330] lr: 1.000e-04, eta: 10:05:29, time: 0.970, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0419, loss_cls: 0.1661, acc: 93.8691, loss_bbox: 0.2133, loss_mask: 0.2231, loss: 0.6609 2024-06-05 12:24:53,495 - mmdet - INFO - Epoch [7][2950/7330] lr: 1.000e-04, eta: 10:04:44, time: 0.868, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0383, loss_cls: 0.1634, acc: 93.8208, loss_bbox: 0.2174, loss_mask: 0.2204, loss: 0.6536 2024-06-05 12:25:40,754 - mmdet - INFO - Epoch [7][3000/7330] lr: 1.000e-04, eta: 10:04:02, time: 0.945, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0410, loss_cls: 0.1708, acc: 93.8044, loss_bbox: 0.2170, loss_mask: 0.2209, loss: 0.6655 2024-06-05 12:26:24,457 - mmdet - INFO - Epoch [7][3050/7330] lr: 1.000e-04, eta: 10:03:17, time: 0.874, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0422, loss_cls: 0.1735, acc: 93.6643, loss_bbox: 0.2179, loss_mask: 0.2277, loss: 0.6776 2024-06-05 12:27:08,013 - mmdet - INFO - Epoch [7][3100/7330] lr: 1.000e-04, eta: 10:02:33, time: 0.871, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0400, loss_cls: 0.1714, acc: 93.6936, loss_bbox: 0.2238, loss_mask: 0.2307, loss: 0.6813 2024-06-05 12:27:51,501 - mmdet - INFO - Epoch [7][3150/7330] lr: 1.000e-04, eta: 10:01:48, time: 0.869, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0391, loss_cls: 0.1710, acc: 93.7400, loss_bbox: 0.2203, loss_mask: 0.2238, loss: 0.6697 2024-06-05 12:28:35,411 - mmdet - INFO - Epoch [7][3200/7330] lr: 1.000e-04, eta: 10:01:03, time: 0.879, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0428, loss_cls: 0.1720, acc: 93.5935, loss_bbox: 0.2251, loss_mask: 0.2285, loss: 0.6849 2024-06-05 12:29:18,540 - mmdet - INFO - Epoch [7][3250/7330] lr: 1.000e-04, eta: 10:00:18, time: 0.863, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0377, loss_cls: 0.1605, acc: 94.0847, loss_bbox: 0.2098, loss_mask: 0.2271, loss: 0.6499 2024-06-05 12:30:05,706 - mmdet - INFO - Epoch [7][3300/7330] lr: 1.000e-04, eta: 9:59:36, time: 0.943, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0395, loss_cls: 0.1710, acc: 93.6025, loss_bbox: 0.2208, loss_mask: 0.2247, loss: 0.6717 2024-06-05 12:30:49,827 - mmdet - INFO - Epoch [7][3350/7330] lr: 1.000e-04, eta: 9:58:52, time: 0.882, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0414, loss_cls: 0.1668, acc: 93.8667, loss_bbox: 0.2166, loss_mask: 0.2235, loss: 0.6640 2024-06-05 12:31:33,487 - mmdet - INFO - Epoch [7][3400/7330] lr: 1.000e-04, eta: 9:58:07, time: 0.873, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0397, loss_cls: 0.1641, acc: 93.8770, loss_bbox: 0.2161, loss_mask: 0.2234, loss: 0.6581 2024-06-05 12:32:17,705 - mmdet - INFO - Epoch [7][3450/7330] lr: 1.000e-04, eta: 9:57:23, time: 0.884, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0396, loss_cls: 0.1677, acc: 93.8025, loss_bbox: 0.2157, loss_mask: 0.2247, loss: 0.6627 2024-06-05 12:33:01,448 - mmdet - INFO - Epoch [7][3500/7330] lr: 1.000e-04, eta: 9:56:39, time: 0.875, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0381, loss_cls: 0.1669, acc: 93.8528, loss_bbox: 0.2153, loss_mask: 0.2191, loss: 0.6544 2024-06-05 12:33:45,882 - mmdet - INFO - Epoch [7][3550/7330] lr: 1.000e-04, eta: 9:55:55, time: 0.889, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0420, loss_cls: 0.1799, acc: 93.3713, loss_bbox: 0.2336, loss_mask: 0.2302, loss: 0.7016 2024-06-05 12:34:30,011 - mmdet - INFO - Epoch [7][3600/7330] lr: 1.000e-04, eta: 9:55:10, time: 0.883, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0443, loss_cls: 0.1784, acc: 93.4849, loss_bbox: 0.2262, loss_mask: 0.2261, loss: 0.6914 2024-06-05 12:35:13,586 - mmdet - INFO - Epoch [7][3650/7330] lr: 1.000e-04, eta: 9:54:25, time: 0.872, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0399, loss_cls: 0.1691, acc: 93.7295, loss_bbox: 0.2192, loss_mask: 0.2222, loss: 0.6665 2024-06-05 12:35:57,331 - mmdet - INFO - Epoch [7][3700/7330] lr: 1.000e-04, eta: 9:53:41, time: 0.875, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0389, loss_cls: 0.1701, acc: 93.6787, loss_bbox: 0.2209, loss_mask: 0.2247, loss: 0.6699 2024-06-05 12:36:43,943 - mmdet - INFO - Epoch [7][3750/7330] lr: 1.000e-04, eta: 9:52:59, time: 0.932, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0422, loss_cls: 0.1772, acc: 93.3962, loss_bbox: 0.2233, loss_mask: 0.2251, loss: 0.6832 2024-06-05 12:37:29,707 - mmdet - INFO - Epoch [7][3800/7330] lr: 1.000e-04, eta: 9:52:16, time: 0.915, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0416, loss_cls: 0.1726, acc: 93.5588, loss_bbox: 0.2271, loss_mask: 0.2299, loss: 0.6882 2024-06-05 12:38:16,318 - mmdet - INFO - Epoch [7][3850/7330] lr: 1.000e-04, eta: 9:51:34, time: 0.932, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0413, loss_cls: 0.1709, acc: 93.7178, loss_bbox: 0.2201, loss_mask: 0.2315, loss: 0.6801 2024-06-05 12:39:00,237 - mmdet - INFO - Epoch [7][3900/7330] lr: 1.000e-04, eta: 9:50:49, time: 0.878, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0415, loss_cls: 0.1743, acc: 93.5962, loss_bbox: 0.2198, loss_mask: 0.2319, loss: 0.6844 2024-06-05 12:39:44,823 - mmdet - INFO - Epoch [7][3950/7330] lr: 1.000e-04, eta: 9:50:05, time: 0.892, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0425, loss_cls: 0.1771, acc: 93.4666, loss_bbox: 0.2277, loss_mask: 0.2346, loss: 0.6980 2024-06-05 12:40:28,683 - mmdet - INFO - Epoch [7][4000/7330] lr: 1.000e-04, eta: 9:49:21, time: 0.877, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0425, loss_cls: 0.1682, acc: 93.7595, loss_bbox: 0.2186, loss_mask: 0.2256, loss: 0.6708 2024-06-05 12:41:17,151 - mmdet - INFO - Epoch [7][4050/7330] lr: 1.000e-04, eta: 9:48:40, time: 0.969, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0413, loss_cls: 0.1670, acc: 93.9016, loss_bbox: 0.2136, loss_mask: 0.2228, loss: 0.6601 2024-06-05 12:42:05,048 - mmdet - INFO - Epoch [7][4100/7330] lr: 1.000e-04, eta: 9:47:59, time: 0.958, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0449, loss_cls: 0.1731, acc: 93.5745, loss_bbox: 0.2254, loss_mask: 0.2258, loss: 0.6867 2024-06-05 12:42:48,573 - mmdet - INFO - Epoch [7][4150/7330] lr: 1.000e-04, eta: 9:47:14, time: 0.870, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0432, loss_cls: 0.1757, acc: 93.5415, loss_bbox: 0.2279, loss_mask: 0.2262, loss: 0.6889 2024-06-05 12:43:35,792 - mmdet - INFO - Epoch [7][4200/7330] lr: 1.000e-04, eta: 9:46:32, time: 0.944, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0439, loss_cls: 0.1722, acc: 93.5859, loss_bbox: 0.2290, loss_mask: 0.2284, loss: 0.6893 2024-06-05 12:44:20,038 - mmdet - INFO - Epoch [7][4250/7330] lr: 1.000e-04, eta: 9:45:48, time: 0.885, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0414, loss_cls: 0.1716, acc: 93.5977, loss_bbox: 0.2214, loss_mask: 0.2285, loss: 0.6793 2024-06-05 12:45:04,353 - mmdet - INFO - Epoch [7][4300/7330] lr: 1.000e-04, eta: 9:45:04, time: 0.886, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0427, loss_cls: 0.1742, acc: 93.5820, loss_bbox: 0.2226, loss_mask: 0.2256, loss: 0.6823 2024-06-05 12:45:48,712 - mmdet - INFO - Epoch [7][4350/7330] lr: 1.000e-04, eta: 9:44:20, time: 0.887, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0422, loss_cls: 0.1742, acc: 93.5085, loss_bbox: 0.2285, loss_mask: 0.2248, loss: 0.6863 2024-06-05 12:46:32,813 - mmdet - INFO - Epoch [7][4400/7330] lr: 1.000e-04, eta: 9:43:35, time: 0.882, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0384, loss_cls: 0.1646, acc: 93.8848, loss_bbox: 0.2114, loss_mask: 0.2240, loss: 0.6527 2024-06-05 12:47:16,846 - mmdet - INFO - Epoch [7][4450/7330] lr: 1.000e-04, eta: 9:42:51, time: 0.880, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0391, loss_cls: 0.1658, acc: 93.8699, loss_bbox: 0.2191, loss_mask: 0.2258, loss: 0.6631 2024-06-05 12:48:00,670 - mmdet - INFO - Epoch [7][4500/7330] lr: 1.000e-04, eta: 9:42:06, time: 0.877, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0388, loss_cls: 0.1686, acc: 93.7366, loss_bbox: 0.2168, loss_mask: 0.2289, loss: 0.6683 2024-06-05 12:48:48,365 - mmdet - INFO - Epoch [7][4550/7330] lr: 1.000e-04, eta: 9:41:25, time: 0.953, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0436, loss_cls: 0.1740, acc: 93.4932, loss_bbox: 0.2249, loss_mask: 0.2274, loss: 0.6867 2024-06-05 12:49:33,142 - mmdet - INFO - Epoch [7][4600/7330] lr: 1.000e-04, eta: 9:40:41, time: 0.896, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0422, loss_cls: 0.1746, acc: 93.5515, loss_bbox: 0.2266, loss_mask: 0.2277, loss: 0.6882 2024-06-05 12:50:16,481 - mmdet - INFO - Epoch [7][4650/7330] lr: 1.000e-04, eta: 9:39:56, time: 0.867, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0392, loss_cls: 0.1663, acc: 93.8464, loss_bbox: 0.2175, loss_mask: 0.2225, loss: 0.6596 2024-06-05 12:51:00,946 - mmdet - INFO - Epoch [7][4700/7330] lr: 1.000e-04, eta: 9:39:12, time: 0.889, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0428, loss_cls: 0.1740, acc: 93.5193, loss_bbox: 0.2292, loss_mask: 0.2258, loss: 0.6887 2024-06-05 12:51:44,406 - mmdet - INFO - Epoch [7][4750/7330] lr: 1.000e-04, eta: 9:38:27, time: 0.870, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0391, loss_cls: 0.1746, acc: 93.6423, loss_bbox: 0.2213, loss_mask: 0.2236, loss: 0.6738 2024-06-05 12:52:28,677 - mmdet - INFO - Epoch [7][4800/7330] lr: 1.000e-04, eta: 9:37:43, time: 0.885, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0429, loss_cls: 0.1729, acc: 93.5242, loss_bbox: 0.2219, loss_mask: 0.2235, loss: 0.6786 2024-06-05 12:53:12,047 - mmdet - INFO - Epoch [7][4850/7330] lr: 1.000e-04, eta: 9:36:58, time: 0.867, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0390, loss_cls: 0.1665, acc: 93.7915, loss_bbox: 0.2164, loss_mask: 0.2241, loss: 0.6614 2024-06-05 12:53:56,064 - mmdet - INFO - Epoch [7][4900/7330] lr: 1.000e-04, eta: 9:36:14, time: 0.880, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0422, loss_cls: 0.1786, acc: 93.5066, loss_bbox: 0.2283, loss_mask: 0.2267, loss: 0.6924 2024-06-05 12:54:39,741 - mmdet - INFO - Epoch [7][4950/7330] lr: 1.000e-04, eta: 9:35:29, time: 0.874, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0417, loss_cls: 0.1701, acc: 93.7173, loss_bbox: 0.2186, loss_mask: 0.2306, loss: 0.6768 2024-06-05 12:55:26,070 - mmdet - INFO - Epoch [7][5000/7330] lr: 1.000e-04, eta: 9:34:46, time: 0.927, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0416, loss_cls: 0.1670, acc: 93.8384, loss_bbox: 0.2178, loss_mask: 0.2201, loss: 0.6618 2024-06-05 12:56:12,082 - mmdet - INFO - Epoch [7][5050/7330] lr: 1.000e-04, eta: 9:34:04, time: 0.920, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0426, loss_cls: 0.1677, acc: 93.9119, loss_bbox: 0.2167, loss_mask: 0.2252, loss: 0.6698 2024-06-05 12:56:59,560 - mmdet - INFO - Epoch [7][5100/7330] lr: 1.000e-04, eta: 9:33:22, time: 0.950, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0407, loss_cls: 0.1604, acc: 93.9858, loss_bbox: 0.2140, loss_mask: 0.2207, loss: 0.6520 2024-06-05 12:57:43,057 - mmdet - INFO - Epoch [7][5150/7330] lr: 1.000e-04, eta: 9:32:37, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0406, loss_cls: 0.1682, acc: 93.8298, loss_bbox: 0.2186, loss_mask: 0.2203, loss: 0.6637 2024-06-05 12:58:27,611 - mmdet - INFO - Epoch [7][5200/7330] lr: 1.000e-04, eta: 9:31:53, time: 0.891, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0432, loss_cls: 0.1752, acc: 93.5803, loss_bbox: 0.2273, loss_mask: 0.2343, loss: 0.6977 2024-06-05 12:59:14,199 - mmdet - INFO - Epoch [7][5250/7330] lr: 1.000e-04, eta: 9:31:11, time: 0.932, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0409, loss_cls: 0.1795, acc: 93.3777, loss_bbox: 0.2260, loss_mask: 0.2249, loss: 0.6889 2024-06-05 13:00:00,245 - mmdet - INFO - Epoch [7][5300/7330] lr: 1.000e-04, eta: 9:30:28, time: 0.921, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0408, loss_cls: 0.1743, acc: 93.5640, loss_bbox: 0.2251, loss_mask: 0.2305, loss: 0.6875 2024-06-05 13:00:47,184 - mmdet - INFO - Epoch [7][5350/7330] lr: 1.000e-04, eta: 9:29:46, time: 0.939, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0417, loss_cls: 0.1791, acc: 93.3635, loss_bbox: 0.2254, loss_mask: 0.2230, loss: 0.6861 2024-06-05 13:01:30,967 - mmdet - INFO - Epoch [7][5400/7330] lr: 1.000e-04, eta: 9:29:01, time: 0.876, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0419, loss_cls: 0.1781, acc: 93.5234, loss_bbox: 0.2220, loss_mask: 0.2317, loss: 0.6915 2024-06-05 13:02:16,610 - mmdet - INFO - Epoch [7][5450/7330] lr: 1.000e-04, eta: 9:28:18, time: 0.913, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0430, loss_cls: 0.1677, acc: 93.8762, loss_bbox: 0.2157, loss_mask: 0.2239, loss: 0.6664 2024-06-05 13:03:00,129 - mmdet - INFO - Epoch [7][5500/7330] lr: 1.000e-04, eta: 9:27:33, time: 0.870, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0405, loss_cls: 0.1714, acc: 93.7312, loss_bbox: 0.2191, loss_mask: 0.2225, loss: 0.6692 2024-06-05 13:03:43,864 - mmdet - INFO - Epoch [7][5550/7330] lr: 1.000e-04, eta: 9:26:48, time: 0.875, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0412, loss_cls: 0.1693, acc: 93.7815, loss_bbox: 0.2220, loss_mask: 0.2252, loss: 0.6740 2024-06-05 13:04:27,804 - mmdet - INFO - Epoch [7][5600/7330] lr: 1.000e-04, eta: 9:26:04, time: 0.879, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0436, loss_cls: 0.1757, acc: 93.5063, loss_bbox: 0.2322, loss_mask: 0.2388, loss: 0.7066 2024-06-05 13:05:11,829 - mmdet - INFO - Epoch [7][5650/7330] lr: 1.000e-04, eta: 9:25:20, time: 0.880, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0399, loss_cls: 0.1683, acc: 93.6729, loss_bbox: 0.2187, loss_mask: 0.2241, loss: 0.6665 2024-06-05 13:05:56,305 - mmdet - INFO - Epoch [7][5700/7330] lr: 1.000e-04, eta: 9:24:35, time: 0.890, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0444, loss_cls: 0.1790, acc: 93.4807, loss_bbox: 0.2310, loss_mask: 0.2272, loss: 0.6994 2024-06-05 13:06:39,728 - mmdet - INFO - Epoch [7][5750/7330] lr: 1.000e-04, eta: 9:23:51, time: 0.868, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0393, loss_cls: 0.1631, acc: 94.0547, loss_bbox: 0.2147, loss_mask: 0.2239, loss: 0.6566 2024-06-05 13:07:27,389 - mmdet - INFO - Epoch [7][5800/7330] lr: 1.000e-04, eta: 9:23:09, time: 0.953, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0404, loss_cls: 0.1696, acc: 93.8640, loss_bbox: 0.2125, loss_mask: 0.2241, loss: 0.6624 2024-06-05 13:08:11,169 - mmdet - INFO - Epoch [7][5850/7330] lr: 1.000e-04, eta: 9:22:24, time: 0.876, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0406, loss_cls: 0.1630, acc: 93.9082, loss_bbox: 0.2166, loss_mask: 0.2262, loss: 0.6615 2024-06-05 13:08:55,024 - mmdet - INFO - Epoch [7][5900/7330] lr: 1.000e-04, eta: 9:21:40, time: 0.877, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0446, loss_cls: 0.1757, acc: 93.4819, loss_bbox: 0.2293, loss_mask: 0.2329, loss: 0.6993 2024-06-05 13:09:39,341 - mmdet - INFO - Epoch [7][5950/7330] lr: 1.000e-04, eta: 9:20:56, time: 0.886, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0422, loss_cls: 0.1748, acc: 93.5493, loss_bbox: 0.2278, loss_mask: 0.2281, loss: 0.6911 2024-06-05 13:10:23,563 - mmdet - INFO - Epoch [7][6000/7330] lr: 1.000e-04, eta: 9:20:11, time: 0.884, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0408, loss_cls: 0.1688, acc: 93.7183, loss_bbox: 0.2226, loss_mask: 0.2234, loss: 0.6715 2024-06-05 13:11:07,687 - mmdet - INFO - Epoch [7][6050/7330] lr: 1.000e-04, eta: 9:19:27, time: 0.882, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0411, loss_cls: 0.1748, acc: 93.6133, loss_bbox: 0.2267, loss_mask: 0.2246, loss: 0.6847 2024-06-05 13:11:51,792 - mmdet - INFO - Epoch [7][6100/7330] lr: 1.000e-04, eta: 9:18:43, time: 0.882, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0424, loss_cls: 0.1733, acc: 93.5310, loss_bbox: 0.2264, loss_mask: 0.2293, loss: 0.6871 2024-06-05 13:12:36,598 - mmdet - INFO - Epoch [7][6150/7330] lr: 1.000e-04, eta: 9:17:59, time: 0.896, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0418, loss_cls: 0.1746, acc: 93.5581, loss_bbox: 0.2289, loss_mask: 0.2231, loss: 0.6844 2024-06-05 13:13:19,818 - mmdet - INFO - Epoch [7][6200/7330] lr: 1.000e-04, eta: 9:17:14, time: 0.864, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0363, loss_cls: 0.1633, acc: 93.9495, loss_bbox: 0.2133, loss_mask: 0.2236, loss: 0.6501 2024-06-05 13:14:06,808 - mmdet - INFO - Epoch [7][6250/7330] lr: 1.000e-04, eta: 9:16:32, time: 0.940, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0416, loss_cls: 0.1817, acc: 93.2974, loss_bbox: 0.2328, loss_mask: 0.2282, loss: 0.7010 2024-06-05 13:14:53,579 - mmdet - INFO - Epoch [7][6300/7330] lr: 1.000e-04, eta: 9:15:49, time: 0.935, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0398, loss_cls: 0.1708, acc: 93.6897, loss_bbox: 0.2193, loss_mask: 0.2232, loss: 0.6678 2024-06-05 13:15:40,329 - mmdet - INFO - Epoch [7][6350/7330] lr: 1.000e-04, eta: 9:15:07, time: 0.935, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0421, loss_cls: 0.1705, acc: 93.6655, loss_bbox: 0.2161, loss_mask: 0.2266, loss: 0.6711 2024-06-05 13:16:24,789 - mmdet - INFO - Epoch [7][6400/7330] lr: 1.000e-04, eta: 9:14:23, time: 0.889, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0435, loss_cls: 0.1715, acc: 93.6960, loss_bbox: 0.2240, loss_mask: 0.2285, loss: 0.6835 2024-06-05 13:17:08,720 - mmdet - INFO - Epoch [7][6450/7330] lr: 1.000e-04, eta: 9:13:38, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0418, loss_cls: 0.1789, acc: 93.3809, loss_bbox: 0.2290, loss_mask: 0.2317, loss: 0.6994 2024-06-05 13:17:54,690 - mmdet - INFO - Epoch [7][6500/7330] lr: 1.000e-04, eta: 9:12:55, time: 0.919, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0422, loss_cls: 0.1748, acc: 93.4414, loss_bbox: 0.2290, loss_mask: 0.2279, loss: 0.6901 2024-06-05 13:18:41,256 - mmdet - INFO - Epoch [7][6550/7330] lr: 1.000e-04, eta: 9:12:13, time: 0.931, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0405, loss_cls: 0.1676, acc: 93.8845, loss_bbox: 0.2179, loss_mask: 0.2274, loss: 0.6690 2024-06-05 13:19:27,093 - mmdet - INFO - Epoch [7][6600/7330] lr: 1.000e-04, eta: 9:11:30, time: 0.917, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0391, loss_cls: 0.1675, acc: 93.7869, loss_bbox: 0.2148, loss_mask: 0.2215, loss: 0.6586 2024-06-05 13:20:10,742 - mmdet - INFO - Epoch [7][6650/7330] lr: 1.000e-04, eta: 9:10:45, time: 0.873, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0417, loss_cls: 0.1662, acc: 93.9141, loss_bbox: 0.2144, loss_mask: 0.2184, loss: 0.6573 2024-06-05 13:20:56,370 - mmdet - INFO - Epoch [7][6700/7330] lr: 1.000e-04, eta: 9:10:02, time: 0.913, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0389, loss_cls: 0.1744, acc: 93.6257, loss_bbox: 0.2228, loss_mask: 0.2253, loss: 0.6768 2024-06-05 13:21:40,140 - mmdet - INFO - Epoch [7][6750/7330] lr: 1.000e-04, eta: 9:09:17, time: 0.875, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0400, loss_cls: 0.1738, acc: 93.7295, loss_bbox: 0.2227, loss_mask: 0.2269, loss: 0.6787 2024-06-05 13:22:23,863 - mmdet - INFO - Epoch [7][6800/7330] lr: 1.000e-04, eta: 9:08:32, time: 0.874, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0412, loss_cls: 0.1695, acc: 93.9019, loss_bbox: 0.2169, loss_mask: 0.2247, loss: 0.6698 2024-06-05 13:23:07,683 - mmdet - INFO - Epoch [7][6850/7330] lr: 1.000e-04, eta: 9:07:48, time: 0.877, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0397, loss_cls: 0.1696, acc: 93.7097, loss_bbox: 0.2185, loss_mask: 0.2257, loss: 0.6690 2024-06-05 13:23:51,838 - mmdet - INFO - Epoch [7][6900/7330] lr: 1.000e-04, eta: 9:07:03, time: 0.883, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0390, loss_cls: 0.1670, acc: 93.8669, loss_bbox: 0.2177, loss_mask: 0.2273, loss: 0.6659 2024-06-05 13:24:36,259 - mmdet - INFO - Epoch [7][6950/7330] lr: 1.000e-04, eta: 9:06:19, time: 0.888, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0459, loss_cls: 0.1824, acc: 93.3521, loss_bbox: 0.2312, loss_mask: 0.2374, loss: 0.7157 2024-06-05 13:25:20,741 - mmdet - INFO - Epoch [7][7000/7330] lr: 1.000e-04, eta: 9:05:35, time: 0.890, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0396, loss_cls: 0.1667, acc: 93.8535, loss_bbox: 0.2149, loss_mask: 0.2146, loss: 0.6509 2024-06-05 13:26:07,632 - mmdet - INFO - Epoch [7][7050/7330] lr: 1.000e-04, eta: 9:04:53, time: 0.938, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0398, loss_cls: 0.1694, acc: 93.7832, loss_bbox: 0.2131, loss_mask: 0.2242, loss: 0.6622 2024-06-05 13:26:52,183 - mmdet - INFO - Epoch [7][7100/7330] lr: 1.000e-04, eta: 9:04:09, time: 0.891, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0406, loss_cls: 0.1705, acc: 93.7317, loss_bbox: 0.2201, loss_mask: 0.2258, loss: 0.6723 2024-06-05 13:27:36,586 - mmdet - INFO - Epoch [7][7150/7330] lr: 1.000e-04, eta: 9:03:25, time: 0.888, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0419, loss_cls: 0.1687, acc: 93.8210, loss_bbox: 0.2157, loss_mask: 0.2262, loss: 0.6697 2024-06-05 13:28:20,259 - mmdet - INFO - Epoch [7][7200/7330] lr: 1.000e-04, eta: 9:02:40, time: 0.873, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0410, loss_cls: 0.1664, acc: 93.7949, loss_bbox: 0.2187, loss_mask: 0.2249, loss: 0.6658 2024-06-05 13:29:03,996 - mmdet - INFO - Epoch [7][7250/7330] lr: 1.000e-04, eta: 9:01:55, time: 0.875, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0394, loss_cls: 0.1715, acc: 93.6289, loss_bbox: 0.2239, loss_mask: 0.2256, loss: 0.6759 2024-06-05 13:29:47,642 - mmdet - INFO - Epoch [7][7300/7330] lr: 1.000e-04, eta: 9:01:11, time: 0.873, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0416, loss_cls: 0.1745, acc: 93.4939, loss_bbox: 0.2221, loss_mask: 0.2250, loss: 0.6792 2024-06-05 13:30:14,757 - mmdet - INFO - Saving checkpoint at 7 epochs 2024-06-05 13:32:00,646 - mmdet - INFO - Evaluating bbox... 2024-06-05 13:32:25,863 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.448 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.674 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.493 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.259 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.486 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.626 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.576 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.576 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.576 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.372 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.618 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.746 2024-06-05 13:32:25,864 - mmdet - INFO - Evaluating segm... 2024-06-05 13:32:55,954 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.401 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.637 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.427 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.181 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.433 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.627 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.519 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.519 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.519 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.302 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.566 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.711 2024-06-05 13:32:56,396 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 13:32:56,397 - mmdet - INFO - Epoch(val) [7][625] bbox_mAP: 0.4480, bbox_mAP_50: 0.6740, bbox_mAP_75: 0.4930, bbox_mAP_s: 0.2590, bbox_mAP_m: 0.4860, bbox_mAP_l: 0.6260, bbox_mAP_copypaste: 0.448 0.674 0.493 0.259 0.486 0.626, segm_mAP: 0.4010, segm_mAP_50: 0.6370, segm_mAP_75: 0.4270, segm_mAP_s: 0.1810, segm_mAP_m: 0.4330, segm_mAP_l: 0.6270, segm_mAP_copypaste: 0.401 0.637 0.427 0.181 0.433 0.627 2024-06-05 13:33:44,072 - mmdet - INFO - Epoch [8][50/7330] lr: 1.000e-04, eta: 8:59:43, time: 0.953, data_time: 0.123, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0387, loss_cls: 0.1624, acc: 94.0100, loss_bbox: 0.2162, loss_mask: 0.2205, loss: 0.6521 2024-06-05 13:34:28,021 - mmdet - INFO - Epoch [8][100/7330] lr: 1.000e-04, eta: 8:58:59, time: 0.879, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0386, loss_cls: 0.1629, acc: 93.8142, loss_bbox: 0.2158, loss_mask: 0.2221, loss: 0.6531 2024-06-05 13:35:12,014 - mmdet - INFO - Epoch [8][150/7330] lr: 1.000e-04, eta: 8:58:14, time: 0.880, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0406, loss_cls: 0.1646, acc: 93.7961, loss_bbox: 0.2190, loss_mask: 0.2169, loss: 0.6556 2024-06-05 13:35:55,301 - mmdet - INFO - Epoch [8][200/7330] lr: 1.000e-04, eta: 8:57:29, time: 0.866, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0403, loss_cls: 0.1609, acc: 93.9133, loss_bbox: 0.2114, loss_mask: 0.2180, loss: 0.6444 2024-06-05 13:36:38,615 - mmdet - INFO - Epoch [8][250/7330] lr: 1.000e-04, eta: 8:56:45, time: 0.866, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0375, loss_cls: 0.1624, acc: 93.9590, loss_bbox: 0.2127, loss_mask: 0.2218, loss: 0.6476 2024-06-05 13:37:22,008 - mmdet - INFO - Epoch [8][300/7330] lr: 1.000e-04, eta: 8:56:00, time: 0.868, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0381, loss_cls: 0.1610, acc: 93.9854, loss_bbox: 0.2148, loss_mask: 0.2170, loss: 0.6447 2024-06-05 13:38:07,864 - mmdet - INFO - Epoch [8][350/7330] lr: 1.000e-04, eta: 8:55:17, time: 0.917, data_time: 0.039, memory: 11350, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0356, loss_cls: 0.1598, acc: 94.0747, loss_bbox: 0.2080, loss_mask: 0.2169, loss: 0.6330 2024-06-05 13:38:51,523 - mmdet - INFO - Epoch [8][400/7330] lr: 1.000e-04, eta: 8:54:32, time: 0.873, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0393, loss_cls: 0.1661, acc: 93.8005, loss_bbox: 0.2184, loss_mask: 0.2251, loss: 0.6639 2024-06-05 13:39:37,778 - mmdet - INFO - Epoch [8][450/7330] lr: 1.000e-04, eta: 8:53:49, time: 0.925, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0387, loss_cls: 0.1558, acc: 94.0837, loss_bbox: 0.2142, loss_mask: 0.2192, loss: 0.6403 2024-06-05 13:40:21,066 - mmdet - INFO - Epoch [8][500/7330] lr: 1.000e-04, eta: 8:53:04, time: 0.866, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0385, loss_cls: 0.1598, acc: 94.0737, loss_bbox: 0.2086, loss_mask: 0.2211, loss: 0.6421 2024-06-05 13:41:07,425 - mmdet - INFO - Epoch [8][550/7330] lr: 1.000e-04, eta: 8:52:22, time: 0.927, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0393, loss_cls: 0.1589, acc: 93.9583, loss_bbox: 0.2111, loss_mask: 0.2181, loss: 0.6421 2024-06-05 13:41:51,311 - mmdet - INFO - Epoch [8][600/7330] lr: 1.000e-04, eta: 8:51:37, time: 0.878, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0418, loss_cls: 0.1693, acc: 93.6689, loss_bbox: 0.2257, loss_mask: 0.2270, loss: 0.6782 2024-06-05 13:42:44,008 - mmdet - INFO - Epoch [8][650/7330] lr: 1.000e-04, eta: 8:50:59, time: 1.054, data_time: 0.220, memory: 11350, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0416, loss_cls: 0.1570, acc: 94.1597, loss_bbox: 0.2143, loss_mask: 0.2184, loss: 0.6459 2024-06-05 13:43:28,035 - mmdet - INFO - Epoch [8][700/7330] lr: 1.000e-04, eta: 8:50:14, time: 0.881, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0375, loss_cls: 0.1494, acc: 94.3979, loss_bbox: 0.2043, loss_mask: 0.2182, loss: 0.6227 2024-06-05 13:44:12,229 - mmdet - INFO - Epoch [8][750/7330] lr: 1.000e-04, eta: 8:49:30, time: 0.884, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0405, loss_cls: 0.1717, acc: 93.6726, loss_bbox: 0.2195, loss_mask: 0.2242, loss: 0.6708 2024-06-05 13:44:55,478 - mmdet - INFO - Epoch [8][800/7330] lr: 1.000e-04, eta: 8:48:45, time: 0.865, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0390, loss_cls: 0.1606, acc: 94.0693, loss_bbox: 0.2137, loss_mask: 0.2186, loss: 0.6459 2024-06-05 13:45:41,379 - mmdet - INFO - Epoch [8][850/7330] lr: 1.000e-04, eta: 8:48:02, time: 0.918, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0410, loss_cls: 0.1624, acc: 93.9934, loss_bbox: 0.2122, loss_mask: 0.2168, loss: 0.6468 2024-06-05 13:46:26,150 - mmdet - INFO - Epoch [8][900/7330] lr: 1.000e-04, eta: 8:47:18, time: 0.895, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0419, loss_cls: 0.1670, acc: 93.7739, loss_bbox: 0.2155, loss_mask: 0.2225, loss: 0.6627 2024-06-05 13:47:09,554 - mmdet - INFO - Epoch [8][950/7330] lr: 1.000e-04, eta: 8:46:33, time: 0.868, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0374, loss_cls: 0.1604, acc: 93.9578, loss_bbox: 0.2120, loss_mask: 0.2184, loss: 0.6411 2024-06-05 13:47:53,538 - mmdet - INFO - Epoch [8][1000/7330] lr: 1.000e-04, eta: 8:45:49, time: 0.880, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0439, loss_cls: 0.1639, acc: 93.8752, loss_bbox: 0.2210, loss_mask: 0.2224, loss: 0.6665 2024-06-05 13:48:37,238 - mmdet - INFO - Epoch [8][1050/7330] lr: 1.000e-04, eta: 8:45:04, time: 0.874, data_time: 0.037, memory: 11350, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0366, loss_cls: 0.1498, acc: 94.4302, loss_bbox: 0.2032, loss_mask: 0.2145, loss: 0.6166 2024-06-05 13:49:21,189 - mmdet - INFO - Epoch [8][1100/7330] lr: 1.000e-04, eta: 8:44:20, time: 0.879, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0402, loss_cls: 0.1651, acc: 93.9314, loss_bbox: 0.2155, loss_mask: 0.2158, loss: 0.6507 2024-06-05 13:50:05,264 - mmdet - INFO - Epoch [8][1150/7330] lr: 1.000e-04, eta: 8:43:35, time: 0.881, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0402, loss_cls: 0.1614, acc: 93.9358, loss_bbox: 0.2154, loss_mask: 0.2211, loss: 0.6522 2024-06-05 13:50:49,326 - mmdet - INFO - Epoch [8][1200/7330] lr: 1.000e-04, eta: 8:42:51, time: 0.881, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0403, loss_cls: 0.1690, acc: 93.7188, loss_bbox: 0.2161, loss_mask: 0.2200, loss: 0.6606 2024-06-05 13:51:35,272 - mmdet - INFO - Epoch [8][1250/7330] lr: 1.000e-04, eta: 8:42:08, time: 0.919, data_time: 0.039, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0366, loss_cls: 0.1577, acc: 94.1477, loss_bbox: 0.2086, loss_mask: 0.2165, loss: 0.6332 2024-06-05 13:52:19,987 - mmdet - INFO - Epoch [8][1300/7330] lr: 1.000e-04, eta: 8:41:24, time: 0.894, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0408, loss_cls: 0.1675, acc: 93.7480, loss_bbox: 0.2177, loss_mask: 0.2216, loss: 0.6627 2024-06-05 13:53:03,889 - mmdet - INFO - Epoch [8][1350/7330] lr: 1.000e-04, eta: 8:40:39, time: 0.878, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0399, loss_cls: 0.1647, acc: 93.8101, loss_bbox: 0.2159, loss_mask: 0.2218, loss: 0.6559 2024-06-05 13:53:50,088 - mmdet - INFO - Epoch [8][1400/7330] lr: 1.000e-04, eta: 8:39:56, time: 0.924, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0393, loss_cls: 0.1669, acc: 93.8247, loss_bbox: 0.2196, loss_mask: 0.2245, loss: 0.6635 2024-06-05 13:54:34,038 - mmdet - INFO - Epoch [8][1450/7330] lr: 1.000e-04, eta: 8:39:12, time: 0.879, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0394, loss_cls: 0.1651, acc: 93.9258, loss_bbox: 0.2173, loss_mask: 0.2220, loss: 0.6587 2024-06-05 13:55:17,474 - mmdet - INFO - Epoch [8][1500/7330] lr: 1.000e-04, eta: 8:38:27, time: 0.869, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0368, loss_cls: 0.1570, acc: 94.1248, loss_bbox: 0.2098, loss_mask: 0.2191, loss: 0.6357 2024-06-05 13:56:00,927 - mmdet - INFO - Epoch [8][1550/7330] lr: 1.000e-04, eta: 8:37:42, time: 0.869, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0416, loss_cls: 0.1657, acc: 93.8862, loss_bbox: 0.2154, loss_mask: 0.2205, loss: 0.6572 2024-06-05 13:56:48,778 - mmdet - INFO - Epoch [8][1600/7330] lr: 1.000e-04, eta: 8:37:01, time: 0.957, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0392, loss_cls: 0.1630, acc: 93.9451, loss_bbox: 0.2146, loss_mask: 0.2201, loss: 0.6507 2024-06-05 13:57:32,638 - mmdet - INFO - Epoch [8][1650/7330] lr: 1.000e-04, eta: 8:36:16, time: 0.877, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0443, loss_cls: 0.1787, acc: 93.3616, loss_bbox: 0.2313, loss_mask: 0.2285, loss: 0.6991 2024-06-05 13:58:19,116 - mmdet - INFO - Epoch [8][1700/7330] lr: 1.000e-04, eta: 8:35:33, time: 0.930, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0402, loss_cls: 0.1682, acc: 93.7329, loss_bbox: 0.2205, loss_mask: 0.2236, loss: 0.6679 2024-06-05 13:59:06,315 - mmdet - INFO - Epoch [8][1750/7330] lr: 1.000e-04, eta: 8:34:51, time: 0.944, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0397, loss_cls: 0.1611, acc: 94.0190, loss_bbox: 0.2100, loss_mask: 0.2145, loss: 0.6399 2024-06-05 13:59:52,344 - mmdet - INFO - Epoch [8][1800/7330] lr: 1.000e-04, eta: 8:34:08, time: 0.921, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0408, loss_cls: 0.1635, acc: 93.8699, loss_bbox: 0.2133, loss_mask: 0.2157, loss: 0.6489 2024-06-05 14:00:36,287 - mmdet - INFO - Epoch [8][1850/7330] lr: 1.000e-04, eta: 8:33:23, time: 0.879, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0408, loss_cls: 0.1629, acc: 93.9724, loss_bbox: 0.2150, loss_mask: 0.2280, loss: 0.6605 2024-06-05 14:01:20,239 - mmdet - INFO - Epoch [8][1900/7330] lr: 1.000e-04, eta: 8:32:39, time: 0.879, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0403, loss_cls: 0.1686, acc: 93.7029, loss_bbox: 0.2193, loss_mask: 0.2258, loss: 0.6679 2024-06-05 14:02:04,196 - mmdet - INFO - Epoch [8][1950/7330] lr: 1.000e-04, eta: 8:31:54, time: 0.879, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0381, loss_cls: 0.1577, acc: 94.0618, loss_bbox: 0.2110, loss_mask: 0.2169, loss: 0.6361 2024-06-05 14:02:48,791 - mmdet - INFO - Epoch [8][2000/7330] lr: 1.000e-04, eta: 8:31:10, time: 0.892, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0385, loss_cls: 0.1588, acc: 94.0713, loss_bbox: 0.2087, loss_mask: 0.2215, loss: 0.6411 2024-06-05 14:03:32,085 - mmdet - INFO - Epoch [8][2050/7330] lr: 1.000e-04, eta: 8:30:26, time: 0.866, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0380, loss_cls: 0.1622, acc: 93.9827, loss_bbox: 0.2106, loss_mask: 0.2209, loss: 0.6459 2024-06-05 14:04:18,650 - mmdet - INFO - Epoch [8][2100/7330] lr: 1.000e-04, eta: 8:29:43, time: 0.931, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0413, loss_cls: 0.1671, acc: 93.7715, loss_bbox: 0.2229, loss_mask: 0.2238, loss: 0.6704 2024-06-05 14:05:02,601 - mmdet - INFO - Epoch [8][2150/7330] lr: 1.000e-04, eta: 8:28:58, time: 0.879, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0405, loss_cls: 0.1668, acc: 93.8066, loss_bbox: 0.2171, loss_mask: 0.2219, loss: 0.6602 2024-06-05 14:05:46,505 - mmdet - INFO - Epoch [8][2200/7330] lr: 1.000e-04, eta: 8:28:14, time: 0.878, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0396, loss_cls: 0.1659, acc: 93.8789, loss_bbox: 0.2166, loss_mask: 0.2236, loss: 0.6615 2024-06-05 14:06:30,133 - mmdet - INFO - Epoch [8][2250/7330] lr: 1.000e-04, eta: 8:27:29, time: 0.873, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0376, loss_cls: 0.1533, acc: 94.1987, loss_bbox: 0.2074, loss_mask: 0.2155, loss: 0.6261 2024-06-05 14:07:13,618 - mmdet - INFO - Epoch [8][2300/7330] lr: 1.000e-04, eta: 8:26:44, time: 0.870, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0416, loss_cls: 0.1680, acc: 93.6941, loss_bbox: 0.2211, loss_mask: 0.2306, loss: 0.6781 2024-06-05 14:07:57,631 - mmdet - INFO - Epoch [8][2350/7330] lr: 1.000e-04, eta: 8:26:00, time: 0.880, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0415, loss_cls: 0.1643, acc: 93.8562, loss_bbox: 0.2147, loss_mask: 0.2154, loss: 0.6507 2024-06-05 14:08:41,154 - mmdet - INFO - Epoch [8][2400/7330] lr: 1.000e-04, eta: 8:25:15, time: 0.870, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0397, loss_cls: 0.1591, acc: 94.0481, loss_bbox: 0.2145, loss_mask: 0.2201, loss: 0.6474 2024-06-05 14:09:24,321 - mmdet - INFO - Epoch [8][2450/7330] lr: 1.000e-04, eta: 8:24:30, time: 0.863, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0394, loss_cls: 0.1598, acc: 93.9443, loss_bbox: 0.2184, loss_mask: 0.2253, loss: 0.6565 2024-06-05 14:10:12,561 - mmdet - INFO - Epoch [8][2500/7330] lr: 1.000e-04, eta: 8:23:49, time: 0.965, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0435, loss_cls: 0.1713, acc: 93.6355, loss_bbox: 0.2255, loss_mask: 0.2284, loss: 0.6842 2024-06-05 14:10:55,936 - mmdet - INFO - Epoch [8][2550/7330] lr: 1.000e-04, eta: 8:23:04, time: 0.868, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0399, loss_cls: 0.1668, acc: 93.8503, loss_bbox: 0.2197, loss_mask: 0.2234, loss: 0.6629 2024-06-05 14:11:40,348 - mmdet - INFO - Epoch [8][2600/7330] lr: 1.000e-04, eta: 8:22:20, time: 0.888, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0420, loss_cls: 0.1739, acc: 93.5771, loss_bbox: 0.2277, loss_mask: 0.2267, loss: 0.6867 2024-06-05 14:12:26,144 - mmdet - INFO - Epoch [8][2650/7330] lr: 1.000e-04, eta: 8:21:36, time: 0.916, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0384, loss_cls: 0.1573, acc: 94.1257, loss_bbox: 0.2092, loss_mask: 0.2184, loss: 0.6383 2024-06-05 14:13:10,032 - mmdet - INFO - Epoch [8][2700/7330] lr: 1.000e-04, eta: 8:20:52, time: 0.878, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0388, loss_cls: 0.1571, acc: 94.1208, loss_bbox: 0.2133, loss_mask: 0.2267, loss: 0.6508 2024-06-05 14:13:53,794 - mmdet - INFO - Epoch [8][2750/7330] lr: 1.000e-04, eta: 8:20:07, time: 0.875, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0390, loss_cls: 0.1617, acc: 93.9973, loss_bbox: 0.2130, loss_mask: 0.2191, loss: 0.6465 2024-06-05 14:14:39,890 - mmdet - INFO - Epoch [8][2800/7330] lr: 1.000e-04, eta: 8:19:24, time: 0.922, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0388, loss_cls: 0.1649, acc: 93.8564, loss_bbox: 0.2142, loss_mask: 0.2155, loss: 0.6484 2024-06-05 14:15:26,234 - mmdet - INFO - Epoch [8][2850/7330] lr: 1.000e-04, eta: 8:18:41, time: 0.927, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0430, loss_cls: 0.1747, acc: 93.4998, loss_bbox: 0.2280, loss_mask: 0.2261, loss: 0.6894 2024-06-05 14:16:10,743 - mmdet - INFO - Epoch [8][2900/7330] lr: 1.000e-04, eta: 8:17:57, time: 0.890, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0410, loss_cls: 0.1550, acc: 94.1328, loss_bbox: 0.2105, loss_mask: 0.2189, loss: 0.6419 2024-06-05 14:17:00,944 - mmdet - INFO - Epoch [8][2950/7330] lr: 1.000e-04, eta: 8:17:17, time: 1.004, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0384, loss_cls: 0.1638, acc: 93.9058, loss_bbox: 0.2189, loss_mask: 0.2253, loss: 0.6597 2024-06-05 14:17:44,732 - mmdet - INFO - Epoch [8][3000/7330] lr: 1.000e-04, eta: 8:16:32, time: 0.876, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0379, loss_cls: 0.1570, acc: 94.2136, loss_bbox: 0.2057, loss_mask: 0.2208, loss: 0.6359 2024-06-05 14:18:30,754 - mmdet - INFO - Epoch [8][3050/7330] lr: 1.000e-04, eta: 8:15:49, time: 0.920, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0381, loss_cls: 0.1577, acc: 94.0994, loss_bbox: 0.2041, loss_mask: 0.2164, loss: 0.6303 2024-06-05 14:19:15,184 - mmdet - INFO - Epoch [8][3100/7330] lr: 1.000e-04, eta: 8:15:05, time: 0.889, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0406, loss_cls: 0.1663, acc: 93.9001, loss_bbox: 0.2132, loss_mask: 0.2191, loss: 0.6540 2024-06-05 14:19:59,133 - mmdet - INFO - Epoch [8][3150/7330] lr: 1.000e-04, eta: 8:14:20, time: 0.879, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0398, loss_cls: 0.1662, acc: 93.8323, loss_bbox: 0.2205, loss_mask: 0.2194, loss: 0.6612 2024-06-05 14:20:42,310 - mmdet - INFO - Epoch [8][3200/7330] lr: 1.000e-04, eta: 8:13:35, time: 0.864, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0361, loss_cls: 0.1512, acc: 94.2920, loss_bbox: 0.2038, loss_mask: 0.2181, loss: 0.6239 2024-06-05 14:21:26,463 - mmdet - INFO - Epoch [8][3250/7330] lr: 1.000e-04, eta: 8:12:51, time: 0.883, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0411, loss_cls: 0.1634, acc: 93.8423, loss_bbox: 0.2177, loss_mask: 0.2231, loss: 0.6613 2024-06-05 14:22:14,621 - mmdet - INFO - Epoch [8][3300/7330] lr: 1.000e-04, eta: 8:12:09, time: 0.963, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0415, loss_cls: 0.1642, acc: 93.9409, loss_bbox: 0.2204, loss_mask: 0.2278, loss: 0.6691 2024-06-05 14:22:58,791 - mmdet - INFO - Epoch [8][3350/7330] lr: 1.000e-04, eta: 8:11:25, time: 0.883, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0398, loss_cls: 0.1637, acc: 93.9277, loss_bbox: 0.2111, loss_mask: 0.2169, loss: 0.6462 2024-06-05 14:23:42,700 - mmdet - INFO - Epoch [8][3400/7330] lr: 1.000e-04, eta: 8:10:40, time: 0.878, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0397, loss_cls: 0.1672, acc: 93.8027, loss_bbox: 0.2166, loss_mask: 0.2250, loss: 0.6630 2024-06-05 14:24:26,056 - mmdet - INFO - Epoch [8][3450/7330] lr: 1.000e-04, eta: 8:09:55, time: 0.867, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0405, loss_cls: 0.1637, acc: 93.9780, loss_bbox: 0.2154, loss_mask: 0.2204, loss: 0.6536 2024-06-05 14:25:09,518 - mmdet - INFO - Epoch [8][3500/7330] lr: 1.000e-04, eta: 8:09:11, time: 0.869, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0402, loss_cls: 0.1619, acc: 94.0088, loss_bbox: 0.2154, loss_mask: 0.2202, loss: 0.6517 2024-06-05 14:25:53,055 - mmdet - INFO - Epoch [8][3550/7330] lr: 1.000e-04, eta: 8:08:26, time: 0.871, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0401, loss_cls: 0.1622, acc: 94.0547, loss_bbox: 0.2065, loss_mask: 0.2233, loss: 0.6469 2024-06-05 14:26:36,623 - mmdet - INFO - Epoch [8][3600/7330] lr: 1.000e-04, eta: 8:07:41, time: 0.871, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0367, loss_cls: 0.1628, acc: 94.0361, loss_bbox: 0.2116, loss_mask: 0.2177, loss: 0.6437 2024-06-05 14:27:19,852 - mmdet - INFO - Epoch [8][3650/7330] lr: 1.000e-04, eta: 8:06:56, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0371, loss_cls: 0.1566, acc: 94.1848, loss_bbox: 0.2100, loss_mask: 0.2212, loss: 0.6388 2024-06-05 14:28:03,687 - mmdet - INFO - Epoch [8][3700/7330] lr: 1.000e-04, eta: 8:06:12, time: 0.877, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0389, loss_cls: 0.1635, acc: 93.8931, loss_bbox: 0.2160, loss_mask: 0.2189, loss: 0.6509 2024-06-05 14:28:51,102 - mmdet - INFO - Epoch [8][3750/7330] lr: 1.000e-04, eta: 8:05:29, time: 0.948, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0384, loss_cls: 0.1637, acc: 94.0417, loss_bbox: 0.2122, loss_mask: 0.2141, loss: 0.6448 2024-06-05 14:29:34,843 - mmdet - INFO - Epoch [8][3800/7330] lr: 1.000e-04, eta: 8:04:45, time: 0.875, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0405, loss_cls: 0.1672, acc: 93.7771, loss_bbox: 0.2204, loss_mask: 0.2227, loss: 0.6658 2024-06-05 14:30:19,266 - mmdet - INFO - Epoch [8][3850/7330] lr: 1.000e-04, eta: 8:04:01, time: 0.888, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0387, loss_cls: 0.1674, acc: 93.8220, loss_bbox: 0.2217, loss_mask: 0.2165, loss: 0.6585 2024-06-05 14:31:06,204 - mmdet - INFO - Epoch [8][3900/7330] lr: 1.000e-04, eta: 8:03:18, time: 0.939, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0400, loss_cls: 0.1720, acc: 93.6003, loss_bbox: 0.2212, loss_mask: 0.2257, loss: 0.6739 2024-06-05 14:31:49,414 - mmdet - INFO - Epoch [8][3950/7330] lr: 1.000e-04, eta: 8:02:33, time: 0.864, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0405, loss_cls: 0.1687, acc: 93.8008, loss_bbox: 0.2212, loss_mask: 0.2228, loss: 0.6689 2024-06-05 14:32:33,923 - mmdet - INFO - Epoch [8][4000/7330] lr: 1.000e-04, eta: 8:01:49, time: 0.890, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0406, loss_cls: 0.1689, acc: 93.6682, loss_bbox: 0.2233, loss_mask: 0.2266, loss: 0.6753 2024-06-05 14:33:19,974 - mmdet - INFO - Epoch [8][4050/7330] lr: 1.000e-04, eta: 8:01:06, time: 0.921, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0383, loss_cls: 0.1587, acc: 94.0198, loss_bbox: 0.2084, loss_mask: 0.2132, loss: 0.6320 2024-06-05 14:34:05,150 - mmdet - INFO - Epoch [8][4100/7330] lr: 1.000e-04, eta: 8:00:22, time: 0.904, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0383, loss_cls: 0.1559, acc: 94.1064, loss_bbox: 0.2099, loss_mask: 0.2193, loss: 0.6372 2024-06-05 14:34:48,739 - mmdet - INFO - Epoch [8][4150/7330] lr: 1.000e-04, eta: 7:59:37, time: 0.872, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0384, loss_cls: 0.1644, acc: 94.0369, loss_bbox: 0.2051, loss_mask: 0.2139, loss: 0.6378 2024-06-05 14:35:37,924 - mmdet - INFO - Epoch [8][4200/7330] lr: 1.000e-04, eta: 7:58:56, time: 0.984, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0411, loss_cls: 0.1655, acc: 93.7839, loss_bbox: 0.2165, loss_mask: 0.2259, loss: 0.6642 2024-06-05 14:36:22,517 - mmdet - INFO - Epoch [8][4250/7330] lr: 1.000e-04, eta: 7:58:12, time: 0.892, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0406, loss_cls: 0.1630, acc: 93.9890, loss_bbox: 0.2128, loss_mask: 0.2185, loss: 0.6505 2024-06-05 14:37:08,165 - mmdet - INFO - Epoch [8][4300/7330] lr: 1.000e-04, eta: 7:57:28, time: 0.913, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0399, loss_cls: 0.1680, acc: 93.7986, loss_bbox: 0.2134, loss_mask: 0.2228, loss: 0.6595 2024-06-05 14:37:51,663 - mmdet - INFO - Epoch [8][4350/7330] lr: 1.000e-04, eta: 7:56:44, time: 0.870, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0392, loss_cls: 0.1575, acc: 94.1187, loss_bbox: 0.2096, loss_mask: 0.2198, loss: 0.6402 2024-06-05 14:38:34,900 - mmdet - INFO - Epoch [8][4400/7330] lr: 1.000e-04, eta: 7:55:59, time: 0.865, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0370, loss_cls: 0.1586, acc: 94.1292, loss_bbox: 0.2091, loss_mask: 0.2118, loss: 0.6305 2024-06-05 14:39:18,603 - mmdet - INFO - Epoch [8][4450/7330] lr: 1.000e-04, eta: 7:55:14, time: 0.874, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0384, loss_cls: 0.1606, acc: 94.0813, loss_bbox: 0.2104, loss_mask: 0.2211, loss: 0.6456 2024-06-05 14:40:02,953 - mmdet - INFO - Epoch [8][4500/7330] lr: 1.000e-04, eta: 7:54:30, time: 0.887, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0396, loss_cls: 0.1641, acc: 93.8379, loss_bbox: 0.2164, loss_mask: 0.2225, loss: 0.6579 2024-06-05 14:40:49,618 - mmdet - INFO - Epoch [8][4550/7330] lr: 1.000e-04, eta: 7:53:47, time: 0.933, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0419, loss_cls: 0.1625, acc: 93.9656, loss_bbox: 0.2099, loss_mask: 0.2176, loss: 0.6481 2024-06-05 14:41:33,056 - mmdet - INFO - Epoch [8][4600/7330] lr: 1.000e-04, eta: 7:53:02, time: 0.868, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0372, loss_cls: 0.1532, acc: 94.3770, loss_bbox: 0.2035, loss_mask: 0.2187, loss: 0.6258 2024-06-05 14:42:17,349 - mmdet - INFO - Epoch [8][4650/7330] lr: 1.000e-04, eta: 7:52:18, time: 0.886, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0419, loss_cls: 0.1754, acc: 93.4475, loss_bbox: 0.2328, loss_mask: 0.2310, loss: 0.6958 2024-06-05 14:43:02,626 - mmdet - INFO - Epoch [8][4700/7330] lr: 1.000e-04, eta: 7:51:34, time: 0.906, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0430, loss_cls: 0.1728, acc: 93.5659, loss_bbox: 0.2244, loss_mask: 0.2251, loss: 0.6811 2024-06-05 14:43:46,023 - mmdet - INFO - Epoch [8][4750/7330] lr: 1.000e-04, eta: 7:50:49, time: 0.868, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0394, loss_cls: 0.1626, acc: 93.9956, loss_bbox: 0.2139, loss_mask: 0.2252, loss: 0.6554 2024-06-05 14:44:29,921 - mmdet - INFO - Epoch [8][4800/7330] lr: 1.000e-04, eta: 7:50:05, time: 0.878, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0393, loss_cls: 0.1605, acc: 94.0327, loss_bbox: 0.2101, loss_mask: 0.2159, loss: 0.6400 2024-06-05 14:45:13,818 - mmdet - INFO - Epoch [8][4850/7330] lr: 1.000e-04, eta: 7:49:20, time: 0.878, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0394, loss_cls: 0.1672, acc: 93.7493, loss_bbox: 0.2158, loss_mask: 0.2207, loss: 0.6582 2024-06-05 14:45:57,071 - mmdet - INFO - Epoch [8][4900/7330] lr: 1.000e-04, eta: 7:48:36, time: 0.865, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0385, loss_cls: 0.1657, acc: 93.9451, loss_bbox: 0.2109, loss_mask: 0.2166, loss: 0.6451 2024-06-05 14:46:44,021 - mmdet - INFO - Epoch [8][4950/7330] lr: 1.000e-04, eta: 7:47:53, time: 0.939, data_time: 0.067, memory: 11350, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0371, loss_cls: 0.1647, acc: 93.9009, loss_bbox: 0.2141, loss_mask: 0.2209, loss: 0.6508 2024-06-05 14:47:28,046 - mmdet - INFO - Epoch [8][5000/7330] lr: 1.000e-04, eta: 7:47:08, time: 0.881, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0380, loss_cls: 0.1622, acc: 93.9841, loss_bbox: 0.2115, loss_mask: 0.2135, loss: 0.6408 2024-06-05 14:48:12,080 - mmdet - INFO - Epoch [8][5050/7330] lr: 1.000e-04, eta: 7:46:24, time: 0.881, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0401, loss_cls: 0.1648, acc: 93.9399, loss_bbox: 0.2154, loss_mask: 0.2179, loss: 0.6529 2024-06-05 14:48:58,249 - mmdet - INFO - Epoch [8][5100/7330] lr: 1.000e-04, eta: 7:45:41, time: 0.923, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0404, loss_cls: 0.1646, acc: 93.7954, loss_bbox: 0.2158, loss_mask: 0.2224, loss: 0.6578 2024-06-05 14:49:41,919 - mmdet - INFO - Epoch [8][5150/7330] lr: 1.000e-04, eta: 7:44:56, time: 0.873, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0396, loss_cls: 0.1686, acc: 93.7344, loss_bbox: 0.2118, loss_mask: 0.2196, loss: 0.6546 2024-06-05 14:50:26,049 - mmdet - INFO - Epoch [8][5200/7330] lr: 1.000e-04, eta: 7:44:12, time: 0.883, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0390, loss_cls: 0.1656, acc: 93.7974, loss_bbox: 0.2125, loss_mask: 0.2162, loss: 0.6481 2024-06-05 14:51:09,828 - mmdet - INFO - Epoch [8][5250/7330] lr: 1.000e-04, eta: 7:43:27, time: 0.876, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0390, loss_cls: 0.1653, acc: 93.8657, loss_bbox: 0.2132, loss_mask: 0.2197, loss: 0.6514 2024-06-05 14:51:56,054 - mmdet - INFO - Epoch [8][5300/7330] lr: 1.000e-04, eta: 7:42:44, time: 0.925, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0404, loss_cls: 0.1670, acc: 93.7180, loss_bbox: 0.2215, loss_mask: 0.2250, loss: 0.6694 2024-06-05 14:52:42,610 - mmdet - INFO - Epoch [8][5350/7330] lr: 1.000e-04, eta: 7:42:01, time: 0.931, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0426, loss_cls: 0.1706, acc: 93.6443, loss_bbox: 0.2192, loss_mask: 0.2235, loss: 0.6709 2024-06-05 14:53:25,793 - mmdet - INFO - Epoch [8][5400/7330] lr: 1.000e-04, eta: 7:41:16, time: 0.864, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0354, loss_cls: 0.1493, acc: 94.4404, loss_bbox: 0.1991, loss_mask: 0.2177, loss: 0.6140 2024-06-05 14:54:14,044 - mmdet - INFO - Epoch [8][5450/7330] lr: 1.000e-04, eta: 7:40:34, time: 0.965, data_time: 0.063, memory: 11350, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0400, loss_cls: 0.1634, acc: 93.8003, loss_bbox: 0.2141, loss_mask: 0.2213, loss: 0.6549 2024-06-05 14:54:57,543 - mmdet - INFO - Epoch [8][5500/7330] lr: 1.000e-04, eta: 7:39:49, time: 0.870, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0376, loss_cls: 0.1681, acc: 93.8374, loss_bbox: 0.2150, loss_mask: 0.2225, loss: 0.6583 2024-06-05 14:55:43,905 - mmdet - INFO - Epoch [8][5550/7330] lr: 1.000e-04, eta: 7:39:06, time: 0.927, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0419, loss_cls: 0.1695, acc: 93.7021, loss_bbox: 0.2193, loss_mask: 0.2258, loss: 0.6720 2024-06-05 14:56:27,793 - mmdet - INFO - Epoch [8][5600/7330] lr: 1.000e-04, eta: 7:38:22, time: 0.878, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0392, loss_cls: 0.1628, acc: 93.9934, loss_bbox: 0.2148, loss_mask: 0.2205, loss: 0.6522 2024-06-05 14:57:12,229 - mmdet - INFO - Epoch [8][5650/7330] lr: 1.000e-04, eta: 7:37:37, time: 0.889, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0405, loss_cls: 0.1727, acc: 93.6130, loss_bbox: 0.2231, loss_mask: 0.2204, loss: 0.6713 2024-06-05 14:57:55,803 - mmdet - INFO - Epoch [8][5700/7330] lr: 1.000e-04, eta: 7:36:53, time: 0.871, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0347, loss_cls: 0.1506, acc: 94.3970, loss_bbox: 0.2006, loss_mask: 0.2078, loss: 0.6066 2024-06-05 14:58:40,089 - mmdet - INFO - Epoch [8][5750/7330] lr: 1.000e-04, eta: 7:36:08, time: 0.886, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0405, loss_cls: 0.1684, acc: 93.7341, loss_bbox: 0.2135, loss_mask: 0.2205, loss: 0.6579 2024-06-05 14:59:26,199 - mmdet - INFO - Epoch [8][5800/7330] lr: 1.000e-04, eta: 7:35:25, time: 0.922, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0436, loss_cls: 0.1730, acc: 93.6035, loss_bbox: 0.2229, loss_mask: 0.2262, loss: 0.6821 2024-06-05 15:00:10,426 - mmdet - INFO - Epoch [8][5850/7330] lr: 1.000e-04, eta: 7:34:41, time: 0.884, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0414, loss_cls: 0.1716, acc: 93.6504, loss_bbox: 0.2213, loss_mask: 0.2240, loss: 0.6751 2024-06-05 15:00:53,603 - mmdet - INFO - Epoch [8][5900/7330] lr: 1.000e-04, eta: 7:33:56, time: 0.864, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0405, loss_cls: 0.1614, acc: 94.0959, loss_bbox: 0.2105, loss_mask: 0.2210, loss: 0.6486 2024-06-05 15:01:37,623 - mmdet - INFO - Epoch [8][5950/7330] lr: 1.000e-04, eta: 7:33:11, time: 0.880, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0427, loss_cls: 0.1688, acc: 93.6997, loss_bbox: 0.2217, loss_mask: 0.2202, loss: 0.6687 2024-06-05 15:02:21,510 - mmdet - INFO - Epoch [8][6000/7330] lr: 1.000e-04, eta: 7:32:27, time: 0.878, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0385, loss_cls: 0.1630, acc: 93.9153, loss_bbox: 0.2099, loss_mask: 0.2180, loss: 0.6434 2024-06-05 15:03:06,120 - mmdet - INFO - Epoch [8][6050/7330] lr: 1.000e-04, eta: 7:31:43, time: 0.892, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0464, loss_cls: 0.1754, acc: 93.5303, loss_bbox: 0.2283, loss_mask: 0.2312, loss: 0.6992 2024-06-05 15:03:49,933 - mmdet - INFO - Epoch [8][6100/7330] lr: 1.000e-04, eta: 7:30:58, time: 0.876, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0413, loss_cls: 0.1662, acc: 93.9077, loss_bbox: 0.2119, loss_mask: 0.2181, loss: 0.6529 2024-06-05 15:04:33,546 - mmdet - INFO - Epoch [8][6150/7330] lr: 1.000e-04, eta: 7:30:14, time: 0.872, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0418, loss_cls: 0.1721, acc: 93.6794, loss_bbox: 0.2161, loss_mask: 0.2217, loss: 0.6667 2024-06-05 15:05:20,236 - mmdet - INFO - Epoch [8][6200/7330] lr: 1.000e-04, eta: 7:29:31, time: 0.934, data_time: 0.074, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0406, loss_cls: 0.1694, acc: 93.8049, loss_bbox: 0.2182, loss_mask: 0.2273, loss: 0.6719 2024-06-05 15:06:03,766 - mmdet - INFO - Epoch [8][6250/7330] lr: 1.000e-04, eta: 7:28:46, time: 0.871, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0399, loss_cls: 0.1576, acc: 94.2690, loss_bbox: 0.2102, loss_mask: 0.2168, loss: 0.6415 2024-06-05 15:06:47,190 - mmdet - INFO - Epoch [8][6300/7330] lr: 1.000e-04, eta: 7:28:01, time: 0.868, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0413, loss_cls: 0.1640, acc: 93.8508, loss_bbox: 0.2171, loss_mask: 0.2203, loss: 0.6570 2024-06-05 15:07:33,482 - mmdet - INFO - Epoch [8][6350/7330] lr: 1.000e-04, eta: 7:27:18, time: 0.926, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0439, loss_cls: 0.1715, acc: 93.5911, loss_bbox: 0.2226, loss_mask: 0.2254, loss: 0.6797 2024-06-05 15:08:16,962 - mmdet - INFO - Epoch [8][6400/7330] lr: 1.000e-04, eta: 7:26:33, time: 0.870, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0387, loss_cls: 0.1592, acc: 94.0596, loss_bbox: 0.2087, loss_mask: 0.2263, loss: 0.6469 2024-06-05 15:09:00,799 - mmdet - INFO - Epoch [8][6450/7330] lr: 1.000e-04, eta: 7:25:49, time: 0.877, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0379, loss_cls: 0.1550, acc: 94.1433, loss_bbox: 0.2045, loss_mask: 0.2158, loss: 0.6274 2024-06-05 15:09:44,399 - mmdet - INFO - Epoch [8][6500/7330] lr: 1.000e-04, eta: 7:25:04, time: 0.872, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0384, loss_cls: 0.1654, acc: 93.8701, loss_bbox: 0.2151, loss_mask: 0.2201, loss: 0.6541 2024-06-05 15:10:32,316 - mmdet - INFO - Epoch [8][6550/7330] lr: 1.000e-04, eta: 7:24:22, time: 0.958, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0387, loss_cls: 0.1590, acc: 94.1184, loss_bbox: 0.2093, loss_mask: 0.2177, loss: 0.6397 2024-06-05 15:11:15,510 - mmdet - INFO - Epoch [8][6600/7330] lr: 1.000e-04, eta: 7:23:37, time: 0.864, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0392, loss_cls: 0.1533, acc: 94.4280, loss_bbox: 0.2002, loss_mask: 0.2212, loss: 0.6275 2024-06-05 15:12:01,799 - mmdet - INFO - Epoch [8][6650/7330] lr: 1.000e-04, eta: 7:22:54, time: 0.926, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0394, loss_cls: 0.1648, acc: 93.8633, loss_bbox: 0.2150, loss_mask: 0.2199, loss: 0.6541 2024-06-05 15:12:48,922 - mmdet - INFO - Epoch [8][6700/7330] lr: 1.000e-04, eta: 7:22:11, time: 0.942, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0424, loss_cls: 0.1715, acc: 93.6738, loss_bbox: 0.2202, loss_mask: 0.2240, loss: 0.6742 2024-06-05 15:13:35,241 - mmdet - INFO - Epoch [8][6750/7330] lr: 1.000e-04, eta: 7:21:27, time: 0.926, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0418, loss_cls: 0.1596, acc: 94.0745, loss_bbox: 0.2151, loss_mask: 0.2206, loss: 0.6519 2024-06-05 15:14:19,392 - mmdet - INFO - Epoch [8][6800/7330] lr: 1.000e-04, eta: 7:20:43, time: 0.883, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0407, loss_cls: 0.1707, acc: 93.6279, loss_bbox: 0.2204, loss_mask: 0.2236, loss: 0.6702 2024-06-05 15:15:03,390 - mmdet - INFO - Epoch [8][6850/7330] lr: 1.000e-04, eta: 7:19:59, time: 0.880, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0395, loss_cls: 0.1639, acc: 94.0020, loss_bbox: 0.2110, loss_mask: 0.2187, loss: 0.6467 2024-06-05 15:15:46,956 - mmdet - INFO - Epoch [8][6900/7330] lr: 1.000e-04, eta: 7:19:14, time: 0.871, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0401, loss_cls: 0.1658, acc: 93.8152, loss_bbox: 0.2198, loss_mask: 0.2186, loss: 0.6610 2024-06-05 15:16:30,168 - mmdet - INFO - Epoch [8][6950/7330] lr: 1.000e-04, eta: 7:18:29, time: 0.864, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0404, loss_cls: 0.1606, acc: 93.9995, loss_bbox: 0.2105, loss_mask: 0.2218, loss: 0.6474 2024-06-05 15:17:14,266 - mmdet - INFO - Epoch [8][7000/7330] lr: 1.000e-04, eta: 7:17:45, time: 0.882, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0403, loss_cls: 0.1616, acc: 94.0298, loss_bbox: 0.2124, loss_mask: 0.2207, loss: 0.6501 2024-06-05 15:18:00,439 - mmdet - INFO - Epoch [8][7050/7330] lr: 1.000e-04, eta: 7:17:01, time: 0.923, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0384, loss_cls: 0.1602, acc: 94.0439, loss_bbox: 0.2125, loss_mask: 0.2140, loss: 0.6395 2024-06-05 15:18:44,344 - mmdet - INFO - Epoch [8][7100/7330] lr: 1.000e-04, eta: 7:16:17, time: 0.878, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0388, loss_cls: 0.1692, acc: 93.7134, loss_bbox: 0.2209, loss_mask: 0.2211, loss: 0.6636 2024-06-05 15:19:27,693 - mmdet - INFO - Epoch [8][7150/7330] lr: 1.000e-04, eta: 7:15:32, time: 0.867, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0392, loss_cls: 0.1608, acc: 93.8967, loss_bbox: 0.2168, loss_mask: 0.2192, loss: 0.6502 2024-06-05 15:20:11,636 - mmdet - INFO - Epoch [8][7200/7330] lr: 1.000e-04, eta: 7:14:48, time: 0.879, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0396, loss_cls: 0.1667, acc: 93.7754, loss_bbox: 0.2169, loss_mask: 0.2202, loss: 0.6578 2024-06-05 15:20:55,768 - mmdet - INFO - Epoch [8][7250/7330] lr: 1.000e-04, eta: 7:14:03, time: 0.883, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0413, loss_cls: 0.1766, acc: 93.3530, loss_bbox: 0.2353, loss_mask: 0.2317, loss: 0.6999 2024-06-05 15:21:39,390 - mmdet - INFO - Epoch [8][7300/7330] lr: 1.000e-04, eta: 7:13:19, time: 0.872, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0388, loss_cls: 0.1563, acc: 94.1299, loss_bbox: 0.2057, loss_mask: 0.2151, loss: 0.6304 2024-06-05 15:22:06,710 - mmdet - INFO - Saving checkpoint at 8 epochs 2024-06-05 15:23:55,972 - mmdet - INFO - Evaluating bbox... 2024-06-05 15:24:24,048 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.454 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.681 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.501 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.271 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.495 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.629 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.579 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.579 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.579 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.377 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.626 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.748 2024-06-05 15:24:24,049 - mmdet - INFO - Evaluating segm... 2024-06-05 15:24:49,497 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.406 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.644 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.435 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.192 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.442 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.623 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.522 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.522 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.522 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.309 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.569 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.710 2024-06-05 15:24:49,882 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 15:24:49,883 - mmdet - INFO - Epoch(val) [8][625] bbox_mAP: 0.4540, bbox_mAP_50: 0.6810, bbox_mAP_75: 0.5010, bbox_mAP_s: 0.2710, bbox_mAP_m: 0.4950, bbox_mAP_l: 0.6290, bbox_mAP_copypaste: 0.454 0.681 0.501 0.271 0.495 0.629, segm_mAP: 0.4060, segm_mAP_50: 0.6440, segm_mAP_75: 0.4350, segm_mAP_s: 0.1920, segm_mAP_m: 0.4420, segm_mAP_l: 0.6230, segm_mAP_copypaste: 0.406 0.644 0.435 0.192 0.442 0.623 2024-06-05 15:25:41,858 - mmdet - INFO - Epoch [9][50/7330] lr: 1.000e-05, eta: 7:11:58, time: 1.039, data_time: 0.114, memory: 11350, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0385, loss_cls: 0.1540, acc: 94.1230, loss_bbox: 0.2072, loss_mask: 0.2108, loss: 0.6231 2024-06-05 15:26:24,909 - mmdet - INFO - Epoch [9][100/7330] lr: 1.000e-05, eta: 7:11:14, time: 0.861, data_time: 0.065, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0359, loss_cls: 0.1486, acc: 94.4004, loss_bbox: 0.1988, loss_mask: 0.2141, loss: 0.6101 2024-06-05 15:27:08,016 - mmdet - INFO - Epoch [9][150/7330] lr: 1.000e-05, eta: 7:10:29, time: 0.862, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0368, loss_cls: 0.1465, acc: 94.4241, loss_bbox: 0.2029, loss_mask: 0.2138, loss: 0.6128 2024-06-05 15:27:52,428 - mmdet - INFO - Epoch [9][200/7330] lr: 1.000e-05, eta: 7:09:44, time: 0.888, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0383, loss_cls: 0.1513, acc: 94.3010, loss_bbox: 0.2013, loss_mask: 0.2078, loss: 0.6113 2024-06-05 15:28:37,244 - mmdet - INFO - Epoch [9][250/7330] lr: 1.000e-05, eta: 7:09:00, time: 0.896, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0389, loss_cls: 0.1536, acc: 94.1633, loss_bbox: 0.2048, loss_mask: 0.2135, loss: 0.6236 2024-06-05 15:29:20,633 - mmdet - INFO - Epoch [9][300/7330] lr: 1.000e-05, eta: 7:08:16, time: 0.868, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0361, loss_cls: 0.1454, acc: 94.3940, loss_bbox: 0.1969, loss_mask: 0.2105, loss: 0.6006 2024-06-05 15:30:03,863 - mmdet - INFO - Epoch [9][350/7330] lr: 1.000e-05, eta: 7:07:31, time: 0.865, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0352, loss_cls: 0.1473, acc: 94.5212, loss_bbox: 0.1983, loss_mask: 0.2088, loss: 0.6027 2024-06-05 15:30:47,988 - mmdet - INFO - Epoch [9][400/7330] lr: 1.000e-05, eta: 7:06:47, time: 0.882, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0376, loss_cls: 0.1494, acc: 94.2700, loss_bbox: 0.2033, loss_mask: 0.2174, loss: 0.6190 2024-06-05 15:31:31,890 - mmdet - INFO - Epoch [9][450/7330] lr: 1.000e-05, eta: 7:06:02, time: 0.878, data_time: 0.072, memory: 11350, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0380, loss_cls: 0.1526, acc: 94.2192, loss_bbox: 0.2075, loss_mask: 0.2108, loss: 0.6217 2024-06-05 15:32:17,816 - mmdet - INFO - Epoch [9][500/7330] lr: 1.000e-05, eta: 7:05:19, time: 0.919, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0357, loss_cls: 0.1440, acc: 94.4438, loss_bbox: 0.1979, loss_mask: 0.2122, loss: 0.6015 2024-06-05 15:33:03,250 - mmdet - INFO - Epoch [9][550/7330] lr: 1.000e-05, eta: 7:04:35, time: 0.909, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0358, loss_cls: 0.1454, acc: 94.5469, loss_bbox: 0.1971, loss_mask: 0.2104, loss: 0.5999 2024-06-05 15:33:47,108 - mmdet - INFO - Epoch [9][600/7330] lr: 1.000e-05, eta: 7:03:51, time: 0.877, data_time: 0.066, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0371, loss_cls: 0.1482, acc: 94.3372, loss_bbox: 0.2024, loss_mask: 0.2133, loss: 0.6127 2024-06-05 15:34:31,398 - mmdet - INFO - Epoch [9][650/7330] lr: 1.000e-05, eta: 7:03:06, time: 0.886, data_time: 0.059, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0381, loss_cls: 0.1456, acc: 94.3784, loss_bbox: 0.2025, loss_mask: 0.2146, loss: 0.6131 2024-06-05 15:35:15,010 - mmdet - INFO - Epoch [9][700/7330] lr: 1.000e-05, eta: 7:02:22, time: 0.872, data_time: 0.070, memory: 11350, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0360, loss_cls: 0.1497, acc: 94.2988, loss_bbox: 0.2010, loss_mask: 0.2150, loss: 0.6136 2024-06-05 15:35:58,897 - mmdet - INFO - Epoch [9][750/7330] lr: 1.000e-05, eta: 7:01:37, time: 0.878, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0365, loss_cls: 0.1407, acc: 94.6521, loss_bbox: 0.1918, loss_mask: 0.2090, loss: 0.5899 2024-06-05 15:36:42,200 - mmdet - INFO - Epoch [9][800/7330] lr: 1.000e-05, eta: 7:00:52, time: 0.866, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0351, loss_cls: 0.1454, acc: 94.4556, loss_bbox: 0.2038, loss_mask: 0.2084, loss: 0.6040 2024-06-05 15:37:30,252 - mmdet - INFO - Epoch [9][850/7330] lr: 1.000e-05, eta: 7:00:10, time: 0.961, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0357, loss_cls: 0.1479, acc: 94.4111, loss_bbox: 0.1974, loss_mask: 0.2114, loss: 0.6048 2024-06-05 15:38:13,432 - mmdet - INFO - Epoch [9][900/7330] lr: 1.000e-05, eta: 6:59:25, time: 0.864, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0362, loss_cls: 0.1473, acc: 94.3972, loss_bbox: 0.2009, loss_mask: 0.2147, loss: 0.6119 2024-06-05 15:38:57,052 - mmdet - INFO - Epoch [9][950/7330] lr: 1.000e-05, eta: 6:58:41, time: 0.872, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0368, loss_cls: 0.1440, acc: 94.5737, loss_bbox: 0.1990, loss_mask: 0.2082, loss: 0.6006 2024-06-05 15:39:40,032 - mmdet - INFO - Epoch [9][1000/7330] lr: 1.000e-05, eta: 6:57:56, time: 0.860, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0347, loss_cls: 0.1452, acc: 94.4563, loss_bbox: 0.2011, loss_mask: 0.2143, loss: 0.6070 2024-06-05 15:40:25,815 - mmdet - INFO - Epoch [9][1050/7330] lr: 1.000e-05, eta: 6:57:12, time: 0.916, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0367, loss_cls: 0.1530, acc: 94.2146, loss_bbox: 0.2070, loss_mask: 0.2154, loss: 0.6245 2024-06-05 15:41:09,095 - mmdet - INFO - Epoch [9][1100/7330] lr: 1.000e-05, eta: 6:56:27, time: 0.866, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0346, loss_cls: 0.1387, acc: 94.7717, loss_bbox: 0.1883, loss_mask: 0.2034, loss: 0.5764 2024-06-05 15:41:53,632 - mmdet - INFO - Epoch [9][1150/7330] lr: 1.000e-05, eta: 6:55:43, time: 0.891, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0394, loss_cls: 0.1504, acc: 94.2473, loss_bbox: 0.2039, loss_mask: 0.2118, loss: 0.6186 2024-06-05 15:42:36,948 - mmdet - INFO - Epoch [9][1200/7330] lr: 1.000e-05, eta: 6:54:59, time: 0.866, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0367, loss_cls: 0.1427, acc: 94.5051, loss_bbox: 0.1954, loss_mask: 0.2097, loss: 0.5967 2024-06-05 15:43:22,556 - mmdet - INFO - Epoch [9][1250/7330] lr: 1.000e-05, eta: 6:54:15, time: 0.912, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0329, loss_cls: 0.1388, acc: 94.6660, loss_bbox: 0.1957, loss_mask: 0.2114, loss: 0.5896 2024-06-05 15:44:08,222 - mmdet - INFO - Epoch [9][1300/7330] lr: 1.000e-05, eta: 6:53:31, time: 0.913, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0378, loss_cls: 0.1509, acc: 94.2678, loss_bbox: 0.2032, loss_mask: 0.2137, loss: 0.6179 2024-06-05 15:44:51,531 - mmdet - INFO - Epoch [9][1350/7330] lr: 1.000e-05, eta: 6:52:47, time: 0.866, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0372, loss_cls: 0.1500, acc: 94.3020, loss_bbox: 0.2042, loss_mask: 0.2114, loss: 0.6150 2024-06-05 15:45:37,614 - mmdet - INFO - Epoch [9][1400/7330] lr: 1.000e-05, eta: 6:52:03, time: 0.922, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0369, loss_cls: 0.1451, acc: 94.5500, loss_bbox: 0.1982, loss_mask: 0.2119, loss: 0.6045 2024-06-05 15:46:20,867 - mmdet - INFO - Epoch [9][1450/7330] lr: 1.000e-05, eta: 6:51:18, time: 0.865, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0358, loss_cls: 0.1375, acc: 94.7822, loss_bbox: 0.1882, loss_mask: 0.2071, loss: 0.5798 2024-06-05 15:47:04,898 - mmdet - INFO - Epoch [9][1500/7330] lr: 1.000e-05, eta: 6:50:34, time: 0.881, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0388, loss_cls: 0.1463, acc: 94.4170, loss_bbox: 0.1999, loss_mask: 0.2133, loss: 0.6105 2024-06-05 15:47:48,151 - mmdet - INFO - Epoch [9][1550/7330] lr: 1.000e-05, eta: 6:49:49, time: 0.865, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0368, loss_cls: 0.1476, acc: 94.5183, loss_bbox: 0.1972, loss_mask: 0.2106, loss: 0.6049 2024-06-05 15:48:31,997 - mmdet - INFO - Epoch [9][1600/7330] lr: 1.000e-05, eta: 6:49:05, time: 0.877, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0389, loss_cls: 0.1521, acc: 94.2136, loss_bbox: 0.2045, loss_mask: 0.2104, loss: 0.6192 2024-06-05 15:49:15,088 - mmdet - INFO - Epoch [9][1650/7330] lr: 1.000e-05, eta: 6:48:20, time: 0.862, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0356, loss_cls: 0.1417, acc: 94.6091, loss_bbox: 0.1951, loss_mask: 0.2129, loss: 0.5969 2024-06-05 15:49:58,743 - mmdet - INFO - Epoch [9][1700/7330] lr: 1.000e-05, eta: 6:47:35, time: 0.873, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0360, loss_cls: 0.1397, acc: 94.6836, loss_bbox: 0.1912, loss_mask: 0.2114, loss: 0.5893 2024-06-05 15:50:45,359 - mmdet - INFO - Epoch [9][1750/7330] lr: 1.000e-05, eta: 6:46:52, time: 0.932, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0339, loss_cls: 0.1387, acc: 94.7188, loss_bbox: 0.1880, loss_mask: 0.2019, loss: 0.5731 2024-06-05 15:51:30,522 - mmdet - INFO - Epoch [9][1800/7330] lr: 1.000e-05, eta: 6:46:08, time: 0.903, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0333, loss_cls: 0.1449, acc: 94.4619, loss_bbox: 0.1975, loss_mask: 0.2072, loss: 0.5941 2024-06-05 15:52:14,288 - mmdet - INFO - Epoch [9][1850/7330] lr: 1.000e-05, eta: 6:45:24, time: 0.875, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0359, loss_cls: 0.1468, acc: 94.4124, loss_bbox: 0.2002, loss_mask: 0.2090, loss: 0.6030 2024-06-05 15:52:57,228 - mmdet - INFO - Epoch [9][1900/7330] lr: 1.000e-05, eta: 6:44:39, time: 0.859, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0334, loss_cls: 0.1379, acc: 94.7395, loss_bbox: 0.1904, loss_mask: 0.2020, loss: 0.5741 2024-06-05 15:53:40,277 - mmdet - INFO - Epoch [9][1950/7330] lr: 1.000e-05, eta: 6:43:54, time: 0.861, data_time: 0.037, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0321, loss_cls: 0.1423, acc: 94.5647, loss_bbox: 0.1956, loss_mask: 0.2052, loss: 0.5867 2024-06-05 15:54:23,915 - mmdet - INFO - Epoch [9][2000/7330] lr: 1.000e-05, eta: 6:43:10, time: 0.873, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0353, loss_cls: 0.1401, acc: 94.6106, loss_bbox: 0.1945, loss_mask: 0.2069, loss: 0.5875 2024-06-05 15:55:09,635 - mmdet - INFO - Epoch [9][2050/7330] lr: 1.000e-05, eta: 6:42:26, time: 0.914, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0368, loss_cls: 0.1413, acc: 94.6624, loss_bbox: 0.1949, loss_mask: 0.2082, loss: 0.5921 2024-06-05 15:55:54,924 - mmdet - INFO - Epoch [9][2100/7330] lr: 1.000e-05, eta: 6:41:42, time: 0.906, data_time: 0.041, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0338, loss_cls: 0.1374, acc: 94.7358, loss_bbox: 0.1889, loss_mask: 0.2010, loss: 0.5719 2024-06-05 15:56:38,091 - mmdet - INFO - Epoch [9][2150/7330] lr: 1.000e-05, eta: 6:40:57, time: 0.863, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0363, loss_cls: 0.1427, acc: 94.5312, loss_bbox: 0.1954, loss_mask: 0.2110, loss: 0.5963 2024-06-05 15:57:21,868 - mmdet - INFO - Epoch [9][2200/7330] lr: 1.000e-05, eta: 6:40:13, time: 0.875, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0363, loss_cls: 0.1480, acc: 94.4041, loss_bbox: 0.1997, loss_mask: 0.2091, loss: 0.6047 2024-06-05 15:58:05,563 - mmdet - INFO - Epoch [9][2250/7330] lr: 1.000e-05, eta: 6:39:28, time: 0.874, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0342, loss_cls: 0.1405, acc: 94.6777, loss_bbox: 0.1899, loss_mask: 0.2087, loss: 0.5847 2024-06-05 15:58:51,076 - mmdet - INFO - Epoch [9][2300/7330] lr: 1.000e-05, eta: 6:38:45, time: 0.910, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0354, loss_cls: 0.1403, acc: 94.7314, loss_bbox: 0.1963, loss_mask: 0.2085, loss: 0.5920 2024-06-05 15:59:34,631 - mmdet - INFO - Epoch [9][2350/7330] lr: 1.000e-05, eta: 6:38:00, time: 0.871, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0346, loss_cls: 0.1393, acc: 94.7090, loss_bbox: 0.1921, loss_mask: 0.2079, loss: 0.5847 2024-06-05 16:00:18,072 - mmdet - INFO - Epoch [9][2400/7330] lr: 1.000e-05, eta: 6:37:15, time: 0.869, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0370, loss_cls: 0.1532, acc: 94.2322, loss_bbox: 0.1996, loss_mask: 0.2069, loss: 0.6090 2024-06-05 16:01:01,707 - mmdet - INFO - Epoch [9][2450/7330] lr: 1.000e-05, eta: 6:36:31, time: 0.873, data_time: 0.036, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0349, loss_cls: 0.1441, acc: 94.5105, loss_bbox: 0.1958, loss_mask: 0.2076, loss: 0.5934 2024-06-05 16:01:47,066 - mmdet - INFO - Epoch [9][2500/7330] lr: 1.000e-05, eta: 6:35:47, time: 0.907, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0341, loss_cls: 0.1407, acc: 94.6035, loss_bbox: 0.1947, loss_mask: 0.2064, loss: 0.5875 2024-06-05 16:02:33,738 - mmdet - INFO - Epoch [9][2550/7330] lr: 1.000e-05, eta: 6:35:04, time: 0.934, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0347, loss_cls: 0.1418, acc: 94.6567, loss_bbox: 0.1934, loss_mask: 0.2059, loss: 0.5869 2024-06-05 16:03:17,790 - mmdet - INFO - Epoch [9][2600/7330] lr: 1.000e-05, eta: 6:34:19, time: 0.881, data_time: 0.083, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0368, loss_cls: 0.1482, acc: 94.3750, loss_bbox: 0.2029, loss_mask: 0.2107, loss: 0.6109 2024-06-05 16:04:03,654 - mmdet - INFO - Epoch [9][2650/7330] lr: 1.000e-05, eta: 6:33:36, time: 0.917, data_time: 0.069, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0382, loss_cls: 0.1517, acc: 94.1555, loss_bbox: 0.2080, loss_mask: 0.2142, loss: 0.6246 2024-06-05 16:04:47,089 - mmdet - INFO - Epoch [9][2700/7330] lr: 1.000e-05, eta: 6:32:51, time: 0.869, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0341, loss_cls: 0.1433, acc: 94.5327, loss_bbox: 0.1970, loss_mask: 0.2116, loss: 0.5977 2024-06-05 16:05:30,626 - mmdet - INFO - Epoch [9][2750/7330] lr: 1.000e-05, eta: 6:32:07, time: 0.871, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0356, loss_cls: 0.1444, acc: 94.5317, loss_bbox: 0.1911, loss_mask: 0.2034, loss: 0.5865 2024-06-05 16:06:14,218 - mmdet - INFO - Epoch [9][2800/7330] lr: 1.000e-05, eta: 6:31:22, time: 0.872, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0377, loss_cls: 0.1455, acc: 94.4385, loss_bbox: 0.2027, loss_mask: 0.2105, loss: 0.6078 2024-06-05 16:06:57,898 - mmdet - INFO - Epoch [9][2850/7330] lr: 1.000e-05, eta: 6:30:38, time: 0.874, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0366, loss_cls: 0.1421, acc: 94.5850, loss_bbox: 0.1949, loss_mask: 0.2077, loss: 0.5933 2024-06-05 16:07:41,010 - mmdet - INFO - Epoch [9][2900/7330] lr: 1.000e-05, eta: 6:29:53, time: 0.862, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0347, loss_cls: 0.1459, acc: 94.4866, loss_bbox: 0.1969, loss_mask: 0.2080, loss: 0.5979 2024-06-05 16:08:24,320 - mmdet - INFO - Epoch [9][2950/7330] lr: 1.000e-05, eta: 6:29:08, time: 0.866, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0374, loss_cls: 0.1461, acc: 94.4150, loss_bbox: 0.2038, loss_mask: 0.2115, loss: 0.6109 2024-06-05 16:09:11,559 - mmdet - INFO - Epoch [9][3000/7330] lr: 1.000e-05, eta: 6:28:25, time: 0.945, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0365, loss_cls: 0.1426, acc: 94.5830, loss_bbox: 0.1982, loss_mask: 0.2077, loss: 0.5967 2024-06-05 16:09:57,318 - mmdet - INFO - Epoch [9][3050/7330] lr: 1.000e-05, eta: 6:27:41, time: 0.915, data_time: 0.068, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0374, loss_cls: 0.1495, acc: 94.2539, loss_bbox: 0.2045, loss_mask: 0.2089, loss: 0.6130 2024-06-05 16:10:41,642 - mmdet - INFO - Epoch [9][3100/7330] lr: 1.000e-05, eta: 6:26:57, time: 0.887, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0381, loss_cls: 0.1521, acc: 94.1238, loss_bbox: 0.2088, loss_mask: 0.2109, loss: 0.6222 2024-06-05 16:11:24,920 - mmdet - INFO - Epoch [9][3150/7330] lr: 1.000e-05, eta: 6:26:12, time: 0.865, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0362, loss_cls: 0.1449, acc: 94.4963, loss_bbox: 0.2009, loss_mask: 0.2144, loss: 0.6073 2024-06-05 16:12:08,819 - mmdet - INFO - Epoch [9][3200/7330] lr: 1.000e-05, eta: 6:25:28, time: 0.878, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0381, loss_cls: 0.1507, acc: 94.2083, loss_bbox: 0.2062, loss_mask: 0.2135, loss: 0.6204 2024-06-05 16:12:52,463 - mmdet - INFO - Epoch [9][3250/7330] lr: 1.000e-05, eta: 6:24:43, time: 0.873, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0348, loss_cls: 0.1417, acc: 94.5974, loss_bbox: 0.1917, loss_mask: 0.2134, loss: 0.5930 2024-06-05 16:13:38,384 - mmdet - INFO - Epoch [9][3300/7330] lr: 1.000e-05, eta: 6:24:00, time: 0.918, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0389, loss_cls: 0.1482, acc: 94.2671, loss_bbox: 0.2037, loss_mask: 0.2153, loss: 0.6186 2024-06-05 16:14:23,876 - mmdet - INFO - Epoch [9][3350/7330] lr: 1.000e-05, eta: 6:23:16, time: 0.910, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0345, loss_cls: 0.1420, acc: 94.5837, loss_bbox: 0.1922, loss_mask: 0.2097, loss: 0.5894 2024-06-05 16:15:06,689 - mmdet - INFO - Epoch [9][3400/7330] lr: 1.000e-05, eta: 6:22:31, time: 0.856, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0345, loss_cls: 0.1418, acc: 94.5667, loss_bbox: 0.1990, loss_mask: 0.2118, loss: 0.5971 2024-06-05 16:15:50,531 - mmdet - INFO - Epoch [9][3450/7330] lr: 1.000e-05, eta: 6:21:47, time: 0.877, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0344, loss_cls: 0.1398, acc: 94.6316, loss_bbox: 0.1908, loss_mask: 0.2068, loss: 0.5827 2024-06-05 16:16:33,627 - mmdet - INFO - Epoch [9][3500/7330] lr: 1.000e-05, eta: 6:21:02, time: 0.862, data_time: 0.056, memory: 11350, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0366, loss_cls: 0.1408, acc: 94.6584, loss_bbox: 0.1964, loss_mask: 0.2092, loss: 0.5942 2024-06-05 16:17:19,452 - mmdet - INFO - Epoch [9][3550/7330] lr: 1.000e-05, eta: 6:20:18, time: 0.916, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0346, loss_cls: 0.1406, acc: 94.6040, loss_bbox: 0.1972, loss_mask: 0.2098, loss: 0.5931 2024-06-05 16:18:03,787 - mmdet - INFO - Epoch [9][3600/7330] lr: 1.000e-05, eta: 6:19:34, time: 0.887, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0393, loss_cls: 0.1469, acc: 94.4705, loss_bbox: 0.2002, loss_mask: 0.2123, loss: 0.6115 2024-06-05 16:18:47,793 - mmdet - INFO - Epoch [9][3650/7330] lr: 1.000e-05, eta: 6:18:50, time: 0.880, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0376, loss_cls: 0.1441, acc: 94.4651, loss_bbox: 0.2048, loss_mask: 0.2130, loss: 0.6110 2024-06-05 16:19:31,352 - mmdet - INFO - Epoch [9][3700/7330] lr: 1.000e-05, eta: 6:18:05, time: 0.871, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0366, loss_cls: 0.1443, acc: 94.5137, loss_bbox: 0.1974, loss_mask: 0.2115, loss: 0.6015 2024-06-05 16:20:17,315 - mmdet - INFO - Epoch [9][3750/7330] lr: 1.000e-05, eta: 6:17:22, time: 0.919, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0374, loss_cls: 0.1491, acc: 94.4150, loss_bbox: 0.2032, loss_mask: 0.2108, loss: 0.6127 2024-06-05 16:21:03,535 - mmdet - INFO - Epoch [9][3800/7330] lr: 1.000e-05, eta: 6:16:38, time: 0.924, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0380, loss_cls: 0.1456, acc: 94.5337, loss_bbox: 0.1964, loss_mask: 0.2121, loss: 0.6047 2024-06-05 16:21:46,913 - mmdet - INFO - Epoch [9][3850/7330] lr: 1.000e-05, eta: 6:15:54, time: 0.868, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0363, loss_cls: 0.1464, acc: 94.4294, loss_bbox: 0.2017, loss_mask: 0.2113, loss: 0.6084 2024-06-05 16:22:33,140 - mmdet - INFO - Epoch [9][3900/7330] lr: 1.000e-05, eta: 6:15:10, time: 0.925, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0384, loss_cls: 0.1487, acc: 94.2756, loss_bbox: 0.2104, loss_mask: 0.2153, loss: 0.6235 2024-06-05 16:23:16,431 - mmdet - INFO - Epoch [9][3950/7330] lr: 1.000e-05, eta: 6:14:25, time: 0.866, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0371, loss_cls: 0.1433, acc: 94.5662, loss_bbox: 0.2008, loss_mask: 0.2112, loss: 0.6032 2024-06-05 16:23:59,717 - mmdet - INFO - Epoch [9][4000/7330] lr: 1.000e-05, eta: 6:13:41, time: 0.866, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0325, loss_cls: 0.1367, acc: 94.7856, loss_bbox: 0.1891, loss_mask: 0.2059, loss: 0.5741 2024-06-05 16:24:43,019 - mmdet - INFO - Epoch [9][4050/7330] lr: 1.000e-05, eta: 6:12:56, time: 0.866, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0373, loss_cls: 0.1482, acc: 94.3850, loss_bbox: 0.2042, loss_mask: 0.2136, loss: 0.6156 2024-06-05 16:25:26,473 - mmdet - INFO - Epoch [9][4100/7330] lr: 1.000e-05, eta: 6:12:11, time: 0.869, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0356, loss_cls: 0.1428, acc: 94.5400, loss_bbox: 0.1967, loss_mask: 0.2104, loss: 0.5965 2024-06-05 16:26:09,672 - mmdet - INFO - Epoch [9][4150/7330] lr: 1.000e-05, eta: 6:11:27, time: 0.864, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0348, loss_cls: 0.1378, acc: 94.7012, loss_bbox: 0.1887, loss_mask: 0.1995, loss: 0.5717 2024-06-05 16:26:53,424 - mmdet - INFO - Epoch [9][4200/7330] lr: 1.000e-05, eta: 6:10:42, time: 0.875, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0351, loss_cls: 0.1352, acc: 94.9268, loss_bbox: 0.1842, loss_mask: 0.2031, loss: 0.5687 2024-06-05 16:27:42,035 - mmdet - INFO - Epoch [9][4250/7330] lr: 1.000e-05, eta: 6:10:00, time: 0.972, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0363, loss_cls: 0.1428, acc: 94.5872, loss_bbox: 0.1975, loss_mask: 0.2098, loss: 0.5989 2024-06-05 16:28:25,628 - mmdet - INFO - Epoch [9][4300/7330] lr: 1.000e-05, eta: 6:09:15, time: 0.872, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0352, loss_cls: 0.1382, acc: 94.7800, loss_bbox: 0.1880, loss_mask: 0.2036, loss: 0.5769 2024-06-05 16:29:09,008 - mmdet - INFO - Epoch [9][4350/7330] lr: 1.000e-05, eta: 6:08:30, time: 0.867, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0360, loss_cls: 0.1399, acc: 94.6262, loss_bbox: 0.2008, loss_mask: 0.2160, loss: 0.6044 2024-06-05 16:29:52,827 - mmdet - INFO - Epoch [9][4400/7330] lr: 1.000e-05, eta: 6:07:46, time: 0.877, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0375, loss_cls: 0.1447, acc: 94.4258, loss_bbox: 0.2025, loss_mask: 0.2136, loss: 0.6107 2024-06-05 16:30:36,659 - mmdet - INFO - Epoch [9][4450/7330] lr: 1.000e-05, eta: 6:07:02, time: 0.877, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0342, loss_cls: 0.1446, acc: 94.5417, loss_bbox: 0.1928, loss_mask: 0.2036, loss: 0.5867 2024-06-05 16:31:19,605 - mmdet - INFO - Epoch [9][4500/7330] lr: 1.000e-05, eta: 6:06:17, time: 0.859, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0347, loss_cls: 0.1367, acc: 94.8113, loss_bbox: 0.1897, loss_mask: 0.2055, loss: 0.5782 2024-06-05 16:32:05,295 - mmdet - INFO - Epoch [9][4550/7330] lr: 1.000e-05, eta: 6:05:33, time: 0.914, data_time: 0.062, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0392, loss_cls: 0.1452, acc: 94.4907, loss_bbox: 0.2000, loss_mask: 0.2128, loss: 0.6089 2024-06-05 16:32:50,887 - mmdet - INFO - Epoch [9][4600/7330] lr: 1.000e-05, eta: 6:04:49, time: 0.912, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0345, loss_cls: 0.1409, acc: 94.6494, loss_bbox: 0.1961, loss_mask: 0.2102, loss: 0.5935 2024-06-05 16:33:34,124 - mmdet - INFO - Epoch [9][4650/7330] lr: 1.000e-05, eta: 6:04:05, time: 0.865, data_time: 0.040, memory: 11350, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0362, loss_cls: 0.1403, acc: 94.6846, loss_bbox: 0.1905, loss_mask: 0.2051, loss: 0.5844 2024-06-05 16:34:17,176 - mmdet - INFO - Epoch [9][4700/7330] lr: 1.000e-05, eta: 6:03:20, time: 0.861, data_time: 0.039, memory: 11350, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0339, loss_cls: 0.1340, acc: 94.8784, loss_bbox: 0.1868, loss_mask: 0.2034, loss: 0.5701 2024-06-05 16:35:02,536 - mmdet - INFO - Epoch [9][4750/7330] lr: 1.000e-05, eta: 6:02:36, time: 0.907, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0362, loss_cls: 0.1390, acc: 94.6252, loss_bbox: 0.1911, loss_mask: 0.2085, loss: 0.5860 2024-06-05 16:35:45,783 - mmdet - INFO - Epoch [9][4800/7330] lr: 1.000e-05, eta: 6:01:51, time: 0.865, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0348, loss_cls: 0.1402, acc: 94.6187, loss_bbox: 0.1984, loss_mask: 0.2110, loss: 0.5944 2024-06-05 16:36:29,470 - mmdet - INFO - Epoch [9][4850/7330] lr: 1.000e-05, eta: 6:01:07, time: 0.874, data_time: 0.058, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0352, loss_cls: 0.1426, acc: 94.6218, loss_bbox: 0.1938, loss_mask: 0.2077, loss: 0.5910 2024-06-05 16:37:13,011 - mmdet - INFO - Epoch [9][4900/7330] lr: 1.000e-05, eta: 6:00:22, time: 0.871, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0384, loss_cls: 0.1508, acc: 94.1987, loss_bbox: 0.2056, loss_mask: 0.2149, loss: 0.6222 2024-06-05 16:37:56,221 - mmdet - INFO - Epoch [9][4950/7330] lr: 1.000e-05, eta: 5:59:38, time: 0.864, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0326, loss_cls: 0.1343, acc: 94.8879, loss_bbox: 0.1872, loss_mask: 0.2086, loss: 0.5740 2024-06-05 16:38:41,771 - mmdet - INFO - Epoch [9][5000/7330] lr: 1.000e-05, eta: 5:58:54, time: 0.911, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0358, loss_cls: 0.1388, acc: 94.7078, loss_bbox: 0.1924, loss_mask: 0.2074, loss: 0.5846 2024-06-05 16:39:27,371 - mmdet - INFO - Epoch [9][5050/7330] lr: 1.000e-05, eta: 5:58:10, time: 0.912, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0349, loss_cls: 0.1401, acc: 94.6682, loss_bbox: 0.1908, loss_mask: 0.2088, loss: 0.5855 2024-06-05 16:40:13,282 - mmdet - INFO - Epoch [9][5100/7330] lr: 1.000e-05, eta: 5:57:26, time: 0.918, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0346, loss_cls: 0.1339, acc: 94.8394, loss_bbox: 0.1869, loss_mask: 0.2048, loss: 0.5707 2024-06-05 16:40:57,161 - mmdet - INFO - Epoch [9][5150/7330] lr: 1.000e-05, eta: 5:56:42, time: 0.878, data_time: 0.055, memory: 11350, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0376, loss_cls: 0.1470, acc: 94.4631, loss_bbox: 0.2003, loss_mask: 0.2082, loss: 0.6054 2024-06-05 16:41:40,672 - mmdet - INFO - Epoch [9][5200/7330] lr: 1.000e-05, eta: 5:55:57, time: 0.870, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0358, loss_cls: 0.1477, acc: 94.5205, loss_bbox: 0.2013, loss_mask: 0.2115, loss: 0.6085 2024-06-05 16:42:24,334 - mmdet - INFO - Epoch [9][5250/7330] lr: 1.000e-05, eta: 5:55:13, time: 0.873, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0354, loss_cls: 0.1440, acc: 94.5508, loss_bbox: 0.1979, loss_mask: 0.2112, loss: 0.5997 2024-06-05 16:43:08,199 - mmdet - INFO - Epoch [9][5300/7330] lr: 1.000e-05, eta: 5:54:28, time: 0.877, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0382, loss_cls: 0.1403, acc: 94.6479, loss_bbox: 0.1972, loss_mask: 0.2141, loss: 0.6029 2024-06-05 16:43:51,321 - mmdet - INFO - Epoch [9][5350/7330] lr: 1.000e-05, eta: 5:53:44, time: 0.862, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0364, loss_cls: 0.1414, acc: 94.6108, loss_bbox: 0.1961, loss_mask: 0.2091, loss: 0.5954 2024-06-05 16:44:34,794 - mmdet - INFO - Epoch [9][5400/7330] lr: 1.000e-05, eta: 5:52:59, time: 0.869, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0342, loss_cls: 0.1427, acc: 94.5095, loss_bbox: 0.1980, loss_mask: 0.2117, loss: 0.5976 2024-06-05 16:45:17,930 - mmdet - INFO - Epoch [9][5450/7330] lr: 1.000e-05, eta: 5:52:15, time: 0.863, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0368, loss_cls: 0.1499, acc: 94.3230, loss_bbox: 0.2024, loss_mask: 0.2091, loss: 0.6095 2024-06-05 16:46:05,687 - mmdet - INFO - Epoch [9][5500/7330] lr: 1.000e-05, eta: 5:51:32, time: 0.955, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0363, loss_cls: 0.1421, acc: 94.5337, loss_bbox: 0.1950, loss_mask: 0.2074, loss: 0.5920 2024-06-05 16:46:48,656 - mmdet - INFO - Epoch [9][5550/7330] lr: 1.000e-05, eta: 5:50:47, time: 0.859, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0377, loss_cls: 0.1446, acc: 94.5063, loss_bbox: 0.1972, loss_mask: 0.2114, loss: 0.6025 2024-06-05 16:47:31,917 - mmdet - INFO - Epoch [9][5600/7330] lr: 1.000e-05, eta: 5:50:02, time: 0.865, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0365, loss_cls: 0.1435, acc: 94.5120, loss_bbox: 0.1986, loss_mask: 0.2053, loss: 0.5953 2024-06-05 16:48:15,897 - mmdet - INFO - Epoch [9][5650/7330] lr: 1.000e-05, eta: 5:49:18, time: 0.880, data_time: 0.048, memory: 11350, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0347, loss_cls: 0.1401, acc: 94.6458, loss_bbox: 0.1960, loss_mask: 0.2053, loss: 0.5865 2024-06-05 16:48:59,314 - mmdet - INFO - Epoch [9][5700/7330] lr: 1.000e-05, eta: 5:48:33, time: 0.868, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0371, loss_cls: 0.1448, acc: 94.4729, loss_bbox: 0.2009, loss_mask: 0.2140, loss: 0.6079 2024-06-05 16:49:45,471 - mmdet - INFO - Epoch [9][5750/7330] lr: 1.000e-05, eta: 5:47:50, time: 0.923, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0362, loss_cls: 0.1396, acc: 94.6899, loss_bbox: 0.1965, loss_mask: 0.2054, loss: 0.5896 2024-06-05 16:50:30,494 - mmdet - INFO - Epoch [9][5800/7330] lr: 1.000e-05, eta: 5:47:06, time: 0.901, data_time: 0.038, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0354, loss_cls: 0.1359, acc: 94.7964, loss_bbox: 0.1877, loss_mask: 0.2044, loss: 0.5748 2024-06-05 16:51:14,101 - mmdet - INFO - Epoch [9][5850/7330] lr: 1.000e-05, eta: 5:46:21, time: 0.872, data_time: 0.064, memory: 11350, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0355, loss_cls: 0.1384, acc: 94.7610, loss_bbox: 0.1943, loss_mask: 0.2058, loss: 0.5840 2024-06-05 16:51:57,910 - mmdet - INFO - Epoch [9][5900/7330] lr: 1.000e-05, eta: 5:45:37, time: 0.876, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0372, loss_cls: 0.1496, acc: 94.4375, loss_bbox: 0.2019, loss_mask: 0.2132, loss: 0.6135 2024-06-05 16:52:41,703 - mmdet - INFO - Epoch [9][5950/7330] lr: 1.000e-05, eta: 5:44:52, time: 0.876, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0366, loss_cls: 0.1452, acc: 94.4719, loss_bbox: 0.2017, loss_mask: 0.2109, loss: 0.6060 2024-06-05 16:53:27,271 - mmdet - INFO - Epoch [9][6000/7330] lr: 1.000e-05, eta: 5:44:08, time: 0.911, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0327, loss_cls: 0.1297, acc: 95.1619, loss_bbox: 0.1828, loss_mask: 0.2021, loss: 0.5571 2024-06-05 16:54:11,241 - mmdet - INFO - Epoch [9][6050/7330] lr: 1.000e-05, eta: 5:43:24, time: 0.879, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0352, loss_cls: 0.1388, acc: 94.6711, loss_bbox: 0.1940, loss_mask: 0.2071, loss: 0.5863 2024-06-05 16:54:54,749 - mmdet - INFO - Epoch [9][6100/7330] lr: 1.000e-05, eta: 5:42:39, time: 0.870, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0354, loss_cls: 0.1448, acc: 94.4417, loss_bbox: 0.1999, loss_mask: 0.2092, loss: 0.6001 2024-06-05 16:55:38,280 - mmdet - INFO - Epoch [9][6150/7330] lr: 1.000e-05, eta: 5:41:55, time: 0.871, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0347, loss_cls: 0.1379, acc: 94.7437, loss_bbox: 0.1929, loss_mask: 0.2070, loss: 0.5833 2024-06-05 16:56:22,001 - mmdet - INFO - Epoch [9][6200/7330] lr: 1.000e-05, eta: 5:41:10, time: 0.874, data_time: 0.054, memory: 11350, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0350, loss_cls: 0.1459, acc: 94.4790, loss_bbox: 0.1973, loss_mask: 0.2114, loss: 0.6008 2024-06-05 16:57:09,837 - mmdet - INFO - Epoch [9][6250/7330] lr: 1.000e-05, eta: 5:40:27, time: 0.957, data_time: 0.052, memory: 11350, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0348, loss_cls: 0.1367, acc: 94.8198, loss_bbox: 0.1890, loss_mask: 0.2030, loss: 0.5738 2024-06-05 16:57:53,273 - mmdet - INFO - Epoch [9][6300/7330] lr: 1.000e-05, eta: 5:39:43, time: 0.869, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0349, loss_cls: 0.1427, acc: 94.5671, loss_bbox: 0.1967, loss_mask: 0.2051, loss: 0.5901 2024-06-05 16:58:39,377 - mmdet - INFO - Epoch [9][6350/7330] lr: 1.000e-05, eta: 5:38:59, time: 0.922, data_time: 0.050, memory: 11350, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0347, loss_cls: 0.1411, acc: 94.7332, loss_bbox: 0.1924, loss_mask: 0.2038, loss: 0.5842 2024-06-05 16:59:23,152 - mmdet - INFO - Epoch [9][6400/7330] lr: 1.000e-05, eta: 5:38:15, time: 0.876, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0342, loss_cls: 0.1385, acc: 94.7073, loss_bbox: 0.1949, loss_mask: 0.2079, loss: 0.5861 2024-06-05 17:00:06,255 - mmdet - INFO - Epoch [9][6450/7330] lr: 1.000e-05, eta: 5:37:30, time: 0.862, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0344, loss_cls: 0.1387, acc: 94.6570, loss_bbox: 0.1913, loss_mask: 0.2103, loss: 0.5861 2024-06-05 17:00:49,399 - mmdet - INFO - Epoch [9][6500/7330] lr: 1.000e-05, eta: 5:36:45, time: 0.863, data_time: 0.045, memory: 11350, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0332, loss_cls: 0.1380, acc: 94.7068, loss_bbox: 0.1859, loss_mask: 0.2058, loss: 0.5728 2024-06-05 17:01:32,338 - mmdet - INFO - Epoch [9][6550/7330] lr: 1.000e-05, eta: 5:36:01, time: 0.859, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0332, loss_cls: 0.1382, acc: 94.6946, loss_bbox: 0.1926, loss_mask: 0.2091, loss: 0.5837 2024-06-05 17:02:16,207 - mmdet - INFO - Epoch [9][6600/7330] lr: 1.000e-05, eta: 5:35:16, time: 0.877, data_time: 0.057, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0374, loss_cls: 0.1423, acc: 94.5923, loss_bbox: 0.1927, loss_mask: 0.2057, loss: 0.5897 2024-06-05 17:02:59,582 - mmdet - INFO - Epoch [9][6650/7330] lr: 1.000e-05, eta: 5:34:32, time: 0.868, data_time: 0.047, memory: 11350, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0347, loss_cls: 0.1409, acc: 94.6372, loss_bbox: 0.1962, loss_mask: 0.2070, loss: 0.5903 2024-06-05 17:03:45,162 - mmdet - INFO - Epoch [9][6700/7330] lr: 1.000e-05, eta: 5:33:48, time: 0.912, data_time: 0.073, memory: 11350, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0351, loss_cls: 0.1421, acc: 94.5586, loss_bbox: 0.1934, loss_mask: 0.2050, loss: 0.5870 2024-06-05 17:04:31,021 - mmdet - INFO - Epoch [9][6750/7330] lr: 1.000e-05, eta: 5:33:04, time: 0.917, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0374, loss_cls: 0.1426, acc: 94.5774, loss_bbox: 0.1981, loss_mask: 0.2096, loss: 0.6008 2024-06-05 17:05:14,270 - mmdet - INFO - Epoch [9][6800/7330] lr: 1.000e-05, eta: 5:32:20, time: 0.865, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0368, loss_cls: 0.1449, acc: 94.5159, loss_bbox: 0.1977, loss_mask: 0.2093, loss: 0.5997 2024-06-05 17:05:57,969 - mmdet - INFO - Epoch [9][6850/7330] lr: 1.000e-05, eta: 5:31:35, time: 0.874, data_time: 0.044, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0351, loss_cls: 0.1423, acc: 94.6233, loss_bbox: 0.1961, loss_mask: 0.2089, loss: 0.5934 2024-06-05 17:06:41,238 - mmdet - INFO - Epoch [9][6900/7330] lr: 1.000e-05, eta: 5:30:50, time: 0.865, data_time: 0.061, memory: 11350, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0378, loss_cls: 0.1448, acc: 94.5139, loss_bbox: 0.2007, loss_mask: 0.2079, loss: 0.6033 2024-06-05 17:07:24,544 - mmdet - INFO - Epoch [9][6950/7330] lr: 1.000e-05, eta: 5:30:06, time: 0.866, data_time: 0.043, memory: 11350, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0351, loss_cls: 0.1479, acc: 94.3977, loss_bbox: 0.1971, loss_mask: 0.2126, loss: 0.6051 2024-06-05 17:08:10,569 - mmdet - INFO - Epoch [9][7000/7330] lr: 1.000e-05, eta: 5:29:22, time: 0.920, data_time: 0.051, memory: 11350, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0351, loss_cls: 0.1390, acc: 94.6558, loss_bbox: 0.1928, loss_mask: 0.2070, loss: 0.5850 2024-06-05 17:08:56,039 - mmdet - INFO - Epoch [9][7050/7330] lr: 1.000e-05, eta: 5:28:38, time: 0.910, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0376, loss_cls: 0.1464, acc: 94.4204, loss_bbox: 0.2029, loss_mask: 0.2136, loss: 0.6123 2024-06-05 17:09:39,390 - mmdet - INFO - Epoch [9][7100/7330] lr: 1.000e-05, eta: 5:27:54, time: 0.867, data_time: 0.046, memory: 11350, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0368, loss_cls: 0.1459, acc: 94.4578, loss_bbox: 0.2018, loss_mask: 0.2112, loss: 0.6063 2024-06-05 17:10:22,594 - mmdet - INFO - Epoch [9][7150/7330] lr: 1.000e-05, eta: 5:27:09, time: 0.864, data_time: 0.049, memory: 11350, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0349, loss_cls: 0.1410, acc: 94.6077, loss_bbox: 0.1903, loss_mask: 0.2035, loss: 0.5804 2024-06-05 17:11:05,906 - mmdet - INFO - Epoch [9][7200/7330] lr: 1.000e-05, eta: 5:26:25, time: 0.866, data_time: 0.060, memory: 11350, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0348, loss_cls: 0.1396, acc: 94.7317, loss_bbox: 0.1911, loss_mask: 0.2046, loss: 0.5817 2024-06-05 17:11:51,233 - mmdet - INFO - Epoch [9][7250/7330] lr: 1.000e-05, eta: 5:25:41, time: 0.906, data_time: 0.053, memory: 11350, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0359, loss_cls: 0.1377, acc: 94.6738, loss_bbox: 0.1941, loss_mask: 0.2103, loss: 0.5888 2024-06-05 17:12:34,603 - mmdet - INFO - Epoch [9][7300/7330] lr: 1.000e-05, eta: 5:24:56, time: 0.867, data_time: 0.042, memory: 11350, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0363, loss_cls: 0.1431, acc: 94.5359, loss_bbox: 0.1979, loss_mask: 0.2062, loss: 0.5945 2024-06-05 17:13:01,284 - mmdet - INFO - Saving checkpoint at 9 epochs 2024-06-05 17:14:46,435 - mmdet - INFO - Evaluating bbox... 2024-06-05 17:15:05,453 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.478 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.696 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.522 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.289 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.516 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.657 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.392 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.633 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.766 2024-06-05 17:15:05,453 - mmdet - INFO - Evaluating segm... 2024-06-05 17:15:27,185 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.423 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.660 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.450 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.207 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.455 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.640 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.530 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.530 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.530 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.319 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.574 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.719 2024-06-05 17:15:27,470 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-05 17:15:27,471 - mmdet - INFO - Epoch(val) [9][625] bbox_mAP: 0.4780, bbox_mAP_50: 0.6960, bbox_mAP_75: 0.5220, bbox_mAP_s: 0.2890, bbox_mAP_m: 0.5160, bbox_mAP_l: 0.6570, bbox_mAP_copypaste: 0.478 0.696 0.522 0.289 0.516 0.657, segm_mAP: 0.4230, segm_mAP_50: 0.6600, segm_mAP_75: 0.4500, segm_mAP_s: 0.2070, segm_mAP_m: 0.4550, segm_mAP_l: 0.6400, segm_mAP_copypaste: 0.423 0.660 0.450 0.207 0.455 0.640 2024-06-06 10:21:22,842 - mmdet - INFO - Epoch [10][50/7330] lr: 1.000e-05, eta: 6:35:55, time: 1.083, data_time: 0.138, memory: 11340, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0349, loss_cls: 0.1375, acc: 94.7991, loss_bbox: 0.1922, loss_mask: 0.2054, loss: 0.5819 2024-06-06 10:22:08,586 - mmdet - INFO - Epoch [10][100/7330] lr: 1.000e-05, eta: 6:04:23, time: 0.915, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0351, loss_cls: 0.1374, acc: 94.6826, loss_bbox: 0.1920, loss_mask: 0.2041, loss: 0.5796 2024-06-06 10:22:56,839 - mmdet - INFO - Epoch [10][150/7330] lr: 1.000e-05, eta: 5:59:28, time: 0.965, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0364, loss_cls: 0.1428, acc: 94.5518, loss_bbox: 0.2003, loss_mask: 0.2150, loss: 0.6050 2024-06-06 10:23:47,009 - mmdet - INFO - Epoch [10][200/7330] lr: 1.000e-05, eta: 6:00:05, time: 1.003, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0339, loss_cls: 0.1349, acc: 94.9038, loss_bbox: 0.1849, loss_mask: 0.2035, loss: 0.5678 2024-06-06 10:24:32,257 - mmdet - INFO - Epoch [10][250/7330] lr: 1.000e-05, eta: 5:52:59, time: 0.905, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0369, loss_cls: 0.1407, acc: 94.6523, loss_bbox: 0.1972, loss_mask: 0.2117, loss: 0.5980 2024-06-06 10:25:18,493 - mmdet - INFO - Epoch [10][300/7330] lr: 1.000e-05, eta: 5:49:11, time: 0.925, data_time: 0.103, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0352, loss_cls: 0.1379, acc: 94.7532, loss_bbox: 0.1946, loss_mask: 0.2065, loss: 0.5851 2024-06-06 10:26:03,543 - mmdet - INFO - Epoch [10][350/7330] lr: 1.000e-05, eta: 5:45:02, time: 0.901, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0350, loss_cls: 0.1390, acc: 94.7124, loss_bbox: 0.1948, loss_mask: 0.2084, loss: 0.5881 2024-06-06 10:26:48,259 - mmdet - INFO - Epoch [10][400/7330] lr: 1.000e-05, eta: 5:41:26, time: 0.894, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0340, loss_cls: 0.1339, acc: 94.8203, loss_bbox: 0.1903, loss_mask: 0.2050, loss: 0.5729 2024-06-06 10:27:33,297 - mmdet - INFO - Epoch [10][450/7330] lr: 1.000e-05, eta: 5:38:42, time: 0.900, data_time: 0.047, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0345, loss_cls: 0.1340, acc: 94.8669, loss_bbox: 0.1908, loss_mask: 0.2048, loss: 0.5751 2024-06-06 10:28:18,664 - mmdet - INFO - Epoch [10][500/7330] lr: 1.000e-05, eta: 5:36:38, time: 0.908, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0329, loss_cls: 0.1378, acc: 94.7654, loss_bbox: 0.1901, loss_mask: 0.2054, loss: 0.5765 2024-06-06 10:29:04,037 - mmdet - INFO - Epoch [10][550/7330] lr: 1.000e-05, eta: 5:34:48, time: 0.908, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0343, loss_cls: 0.1386, acc: 94.6685, loss_bbox: 0.1971, loss_mask: 0.2074, loss: 0.5877 2024-06-06 10:29:49,227 - mmdet - INFO - Epoch [10][600/7330] lr: 1.000e-05, eta: 5:33:02, time: 0.904, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0350, loss_cls: 0.1376, acc: 94.7795, loss_bbox: 0.1986, loss_mask: 0.2096, loss: 0.5919 2024-06-06 10:30:35,421 - mmdet - INFO - Epoch [10][650/7330] lr: 1.000e-05, eta: 5:31:58, time: 0.924, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0358, loss_cls: 0.1394, acc: 94.6377, loss_bbox: 0.1915, loss_mask: 0.2075, loss: 0.5851 2024-06-06 10:31:21,172 - mmdet - INFO - Epoch [10][700/7330] lr: 1.000e-05, eta: 5:30:43, time: 0.915, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0333, loss_cls: 0.1338, acc: 94.8586, loss_bbox: 0.1918, loss_mask: 0.2049, loss: 0.5740 2024-06-06 10:32:08,003 - mmdet - INFO - Epoch [10][750/7330] lr: 1.000e-05, eta: 5:30:03, time: 0.937, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0381, loss_cls: 0.1441, acc: 94.4600, loss_bbox: 0.2007, loss_mask: 0.2099, loss: 0.6045 2024-06-06 10:32:56,296 - mmdet - INFO - Epoch [10][800/7330] lr: 1.000e-05, eta: 5:30:01, time: 0.966, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0351, loss_cls: 0.1370, acc: 94.7734, loss_bbox: 0.1919, loss_mask: 0.2080, loss: 0.5832 2024-06-06 10:33:40,138 - mmdet - INFO - Epoch [10][850/7330] lr: 1.000e-05, eta: 5:28:03, time: 0.877, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0314, loss_cls: 0.1265, acc: 95.1672, loss_bbox: 0.1796, loss_mask: 0.1973, loss: 0.5448 2024-06-06 10:34:25,371 - mmdet - INFO - Epoch [10][900/7330] lr: 1.000e-05, eta: 5:26:45, time: 0.905, data_time: 0.060, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0350, loss_cls: 0.1383, acc: 94.7859, loss_bbox: 0.1945, loss_mask: 0.2028, loss: 0.5814 2024-06-06 10:35:10,751 - mmdet - INFO - Epoch [10][950/7330] lr: 1.000e-05, eta: 5:25:34, time: 0.908, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0362, loss_cls: 0.1386, acc: 94.6472, loss_bbox: 0.1901, loss_mask: 0.2051, loss: 0.5815 2024-06-06 10:35:57,268 - mmdet - INFO - Epoch [10][1000/7330] lr: 1.000e-05, eta: 5:24:50, time: 0.930, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0377, loss_cls: 0.1400, acc: 94.6118, loss_bbox: 0.1943, loss_mask: 0.2081, loss: 0.5909 2024-06-06 10:36:43,729 - mmdet - INFO - Epoch [10][1050/7330] lr: 1.000e-05, eta: 5:24:04, time: 0.929, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0353, loss_cls: 0.1432, acc: 94.4927, loss_bbox: 0.1982, loss_mask: 0.2056, loss: 0.5940 2024-06-06 10:37:28,613 - mmdet - INFO - Epoch [10][1100/7330] lr: 1.000e-05, eta: 5:22:48, time: 0.898, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0360, loss_cls: 0.1332, acc: 94.9407, loss_bbox: 0.1848, loss_mask: 0.2029, loss: 0.5677 2024-06-06 10:38:14,448 - mmdet - INFO - Epoch [10][1150/7330] lr: 1.000e-05, eta: 5:21:52, time: 0.917, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0385, loss_cls: 0.1490, acc: 94.2646, loss_bbox: 0.2035, loss_mask: 0.2121, loss: 0.6144 2024-06-06 10:38:59,388 - mmdet - INFO - Epoch [10][1200/7330] lr: 1.000e-05, eta: 5:20:42, time: 0.899, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0352, loss_cls: 0.1377, acc: 94.7039, loss_bbox: 0.1929, loss_mask: 0.2034, loss: 0.5794 2024-06-06 10:39:54,794 - mmdet - INFO - Epoch [10][1250/7330] lr: 1.000e-05, eta: 5:22:27, time: 1.108, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0374, loss_cls: 0.1426, acc: 94.5183, loss_bbox: 0.1998, loss_mask: 0.2089, loss: 0.5995 2024-06-06 10:40:40,067 - mmdet - INFO - Epoch [10][1300/7330] lr: 1.000e-05, eta: 5:21:19, time: 0.905, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0332, loss_cls: 0.1351, acc: 94.7620, loss_bbox: 0.1888, loss_mask: 0.2003, loss: 0.5677 2024-06-06 10:41:24,952 - mmdet - INFO - Epoch [10][1350/7330] lr: 1.000e-05, eta: 5:20:06, time: 0.898, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0316, loss_cls: 0.1312, acc: 94.9268, loss_bbox: 0.1866, loss_mask: 0.2015, loss: 0.5616 2024-06-06 10:42:10,851 - mmdet - INFO - Epoch [10][1400/7330] lr: 1.000e-05, eta: 5:19:10, time: 0.918, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0348, loss_cls: 0.1375, acc: 94.7227, loss_bbox: 0.1935, loss_mask: 0.2104, loss: 0.5874 2024-06-06 10:42:56,599 - mmdet - INFO - Epoch [10][1450/7330] lr: 1.000e-05, eta: 5:18:13, time: 0.915, data_time: 0.095, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0365, loss_cls: 0.1351, acc: 94.8655, loss_bbox: 0.1898, loss_mask: 0.2054, loss: 0.5785 2024-06-06 10:43:42,423 - mmdet - INFO - Epoch [10][1500/7330] lr: 1.000e-05, eta: 5:17:17, time: 0.916, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0353, loss_cls: 0.1401, acc: 94.6665, loss_bbox: 0.1915, loss_mask: 0.2042, loss: 0.5819 2024-06-06 10:44:27,240 - mmdet - INFO - Epoch [10][1550/7330] lr: 1.000e-05, eta: 5:16:09, time: 0.896, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0334, loss_cls: 0.1317, acc: 94.9795, loss_bbox: 0.1860, loss_mask: 0.2028, loss: 0.5639 2024-06-06 10:45:13,547 - mmdet - INFO - Epoch [10][1600/7330] lr: 1.000e-05, eta: 5:15:22, time: 0.926, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0371, loss_cls: 0.1440, acc: 94.4829, loss_bbox: 0.1994, loss_mask: 0.2148, loss: 0.6070 2024-06-06 10:45:58,631 - mmdet - INFO - Epoch [10][1650/7330] lr: 1.000e-05, eta: 5:14:19, time: 0.902, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0345, loss_cls: 0.1305, acc: 95.0266, loss_bbox: 0.1883, loss_mask: 0.2066, loss: 0.5707 2024-06-06 10:46:44,934 - mmdet - INFO - Epoch [10][1700/7330] lr: 1.000e-05, eta: 5:13:32, time: 0.926, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0344, loss_cls: 0.1314, acc: 94.9458, loss_bbox: 0.1865, loss_mask: 0.2025, loss: 0.5652 2024-06-06 10:47:29,689 - mmdet - INFO - Epoch [10][1750/7330] lr: 1.000e-05, eta: 5:12:27, time: 0.895, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0331, loss_cls: 0.1333, acc: 94.9126, loss_bbox: 0.1876, loss_mask: 0.2010, loss: 0.5648 2024-06-06 10:48:15,868 - mmdet - INFO - Epoch [10][1800/7330] lr: 1.000e-05, eta: 5:11:39, time: 0.924, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0372, loss_cls: 0.1470, acc: 94.3416, loss_bbox: 0.1998, loss_mask: 0.2129, loss: 0.6098 2024-06-06 10:49:03,024 - mmdet - INFO - Epoch [10][1850/7330] lr: 1.000e-05, eta: 5:11:02, time: 0.943, data_time: 0.060, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0320, loss_cls: 0.1288, acc: 95.1702, loss_bbox: 0.1787, loss_mask: 0.1994, loss: 0.5492 2024-06-06 10:49:47,586 - mmdet - INFO - Epoch [10][1900/7330] lr: 1.000e-05, eta: 5:09:57, time: 0.891, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0340, loss_cls: 0.1418, acc: 94.6409, loss_bbox: 0.1959, loss_mask: 0.2055, loss: 0.5874 2024-06-06 10:50:56,516 - mmdet - INFO - Epoch [10][1950/7330] lr: 1.000e-05, eta: 5:13:04, time: 1.379, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0339, loss_cls: 0.1352, acc: 94.8235, loss_bbox: 0.1888, loss_mask: 0.2020, loss: 0.5706 2024-06-06 10:51:43,684 - mmdet - INFO - Epoch [10][2000/7330] lr: 1.000e-05, eta: 5:12:20, time: 0.943, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0380, loss_cls: 0.1449, acc: 94.4473, loss_bbox: 0.2040, loss_mask: 0.2116, loss: 0.6104 2024-06-06 10:52:30,042 - mmdet - INFO - Epoch [10][2050/7330] lr: 1.000e-05, eta: 5:11:28, time: 0.927, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0364, loss_cls: 0.1440, acc: 94.5208, loss_bbox: 0.1951, loss_mask: 0.2093, loss: 0.5967 2024-06-06 10:53:16,560 - mmdet - INFO - Epoch [10][2100/7330] lr: 1.000e-05, eta: 5:10:38, time: 0.930, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0356, loss_cls: 0.1409, acc: 94.6094, loss_bbox: 0.1948, loss_mask: 0.2013, loss: 0.5835 2024-06-06 10:54:02,120 - mmdet - INFO - Epoch [10][2150/7330] lr: 1.000e-05, eta: 5:09:39, time: 0.911, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0343, loss_cls: 0.1319, acc: 94.9724, loss_bbox: 0.1869, loss_mask: 0.2020, loss: 0.5649 2024-06-06 10:54:46,208 - mmdet - INFO - Epoch [10][2200/7330] lr: 1.000e-05, eta: 5:08:27, time: 0.882, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0349, loss_cls: 0.1340, acc: 94.8452, loss_bbox: 0.1859, loss_mask: 0.2069, loss: 0.5721 2024-06-06 10:55:32,339 - mmdet - INFO - Epoch [10][2250/7330] lr: 1.000e-05, eta: 5:07:35, time: 0.923, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0388, loss_cls: 0.1504, acc: 94.2559, loss_bbox: 0.2097, loss_mask: 0.2125, loss: 0.6236 2024-06-06 10:56:30,563 - mmdet - INFO - Epoch [10][2300/7330] lr: 1.000e-05, eta: 5:08:27, time: 1.164, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0318, loss_cls: 0.1321, acc: 94.8977, loss_bbox: 0.1870, loss_mask: 0.2057, loss: 0.5668 2024-06-06 10:57:15,999 - mmdet - INFO - Epoch [10][2350/7330] lr: 1.000e-05, eta: 5:07:27, time: 0.909, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0327, loss_cls: 0.1339, acc: 94.9102, loss_bbox: 0.1871, loss_mask: 0.2004, loss: 0.5643 2024-06-06 10:58:01,611 - mmdet - INFO - Epoch [10][2400/7330] lr: 1.000e-05, eta: 5:06:29, time: 0.912, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0342, loss_cls: 0.1388, acc: 94.6667, loss_bbox: 0.1915, loss_mask: 0.2071, loss: 0.5827 2024-06-06 10:58:48,001 - mmdet - INFO - Epoch [10][2450/7330] lr: 1.000e-05, eta: 5:05:37, time: 0.928, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0360, loss_cls: 0.1433, acc: 94.5093, loss_bbox: 0.2018, loss_mask: 0.2134, loss: 0.6062 2024-06-06 10:59:33,544 - mmdet - INFO - Epoch [10][2500/7330] lr: 1.000e-05, eta: 5:04:40, time: 0.911, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0337, loss_cls: 0.1368, acc: 94.8018, loss_bbox: 0.1955, loss_mask: 0.2066, loss: 0.5830 2024-06-06 11:00:18,589 - mmdet - INFO - Epoch [10][2550/7330] lr: 1.000e-05, eta: 5:03:39, time: 0.901, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0347, loss_cls: 0.1317, acc: 94.9807, loss_bbox: 0.1843, loss_mask: 0.2014, loss: 0.5625 2024-06-06 11:01:04,101 - mmdet - INFO - Epoch [10][2600/7330] lr: 1.000e-05, eta: 5:02:42, time: 0.910, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0326, loss_cls: 0.1302, acc: 95.0022, loss_bbox: 0.1874, loss_mask: 0.2050, loss: 0.5646 2024-06-06 11:01:49,537 - mmdet - INFO - Epoch [10][2650/7330] lr: 1.000e-05, eta: 5:01:45, time: 0.909, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0347, loss_cls: 0.1314, acc: 94.9810, loss_bbox: 0.1862, loss_mask: 0.2068, loss: 0.5697 2024-06-06 11:02:34,692 - mmdet - INFO - Epoch [10][2700/7330] lr: 1.000e-05, eta: 5:00:46, time: 0.903, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0350, loss_cls: 0.1403, acc: 94.6172, loss_bbox: 0.1955, loss_mask: 0.2086, loss: 0.5903 2024-06-06 11:03:20,275 - mmdet - INFO - Epoch [10][2750/7330] lr: 1.000e-05, eta: 4:59:51, time: 0.912, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0349, loss_cls: 0.1347, acc: 94.8677, loss_bbox: 0.1868, loss_mask: 0.2027, loss: 0.5697 2024-06-06 11:04:05,400 - mmdet - INFO - Epoch [10][2800/7330] lr: 1.000e-05, eta: 4:58:53, time: 0.902, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0340, loss_cls: 0.1342, acc: 94.8254, loss_bbox: 0.1859, loss_mask: 0.2072, loss: 0.5718 2024-06-06 11:04:50,831 - mmdet - INFO - Epoch [10][2850/7330] lr: 1.000e-05, eta: 4:57:58, time: 0.909, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0349, loss_cls: 0.1370, acc: 94.8398, loss_bbox: 0.1912, loss_mask: 0.2070, loss: 0.5811 2024-06-06 11:05:35,851 - mmdet - INFO - Epoch [10][2900/7330] lr: 1.000e-05, eta: 4:57:00, time: 0.900, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0362, loss_cls: 0.1373, acc: 94.7585, loss_bbox: 0.1974, loss_mask: 0.2098, loss: 0.5914 2024-06-06 11:06:23,706 - mmdet - INFO - Epoch [10][2950/7330] lr: 1.000e-05, eta: 4:56:21, time: 0.957, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0353, loss_cls: 0.1408, acc: 94.6035, loss_bbox: 0.1948, loss_mask: 0.2114, loss: 0.5927 2024-06-06 11:07:08,866 - mmdet - INFO - Epoch [10][3000/7330] lr: 1.000e-05, eta: 4:55:24, time: 0.903, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0333, loss_cls: 0.1342, acc: 94.8027, loss_bbox: 0.1899, loss_mask: 0.2067, loss: 0.5741 2024-06-06 11:07:54,645 - mmdet - INFO - Epoch [10][3050/7330] lr: 1.000e-05, eta: 4:54:32, time: 0.916, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0328, loss_cls: 0.1355, acc: 94.7900, loss_bbox: 0.1857, loss_mask: 0.2030, loss: 0.5666 2024-06-06 11:08:39,765 - mmdet - INFO - Epoch [10][3100/7330] lr: 1.000e-05, eta: 4:53:36, time: 0.902, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0344, loss_cls: 0.1350, acc: 94.8430, loss_bbox: 0.1878, loss_mask: 0.2041, loss: 0.5712 2024-06-06 11:09:24,856 - mmdet - INFO - Epoch [10][3150/7330] lr: 1.000e-05, eta: 4:52:40, time: 0.902, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0363, loss_cls: 0.1383, acc: 94.7788, loss_bbox: 0.1961, loss_mask: 0.2060, loss: 0.5879 2024-06-06 11:10:09,831 - mmdet - INFO - Epoch [10][3200/7330] lr: 1.000e-05, eta: 4:51:44, time: 0.899, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0352, loss_cls: 0.1344, acc: 94.8418, loss_bbox: 0.1887, loss_mask: 0.2059, loss: 0.5753 2024-06-06 11:10:54,111 - mmdet - INFO - Epoch [10][3250/7330] lr: 1.000e-05, eta: 4:50:44, time: 0.886, data_time: 0.058, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0346, loss_cls: 0.1362, acc: 94.7769, loss_bbox: 0.1908, loss_mask: 0.2049, loss: 0.5774 2024-06-06 11:11:40,074 - mmdet - INFO - Epoch [10][3300/7330] lr: 1.000e-05, eta: 4:49:54, time: 0.919, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0329, loss_cls: 0.1317, acc: 94.9209, loss_bbox: 0.1854, loss_mask: 0.2021, loss: 0.5624 2024-06-06 11:12:35,930 - mmdet - INFO - Epoch [10][3350/7330] lr: 1.000e-05, eta: 4:50:00, time: 1.117, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0351, loss_cls: 0.1407, acc: 94.6147, loss_bbox: 0.1938, loss_mask: 0.2083, loss: 0.5894 2024-06-06 11:13:22,905 - mmdet - INFO - Epoch [10][3400/7330] lr: 1.000e-05, eta: 4:49:15, time: 0.939, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0331, loss_cls: 0.1281, acc: 95.1453, loss_bbox: 0.1809, loss_mask: 0.2013, loss: 0.5530 2024-06-06 11:14:08,783 - mmdet - INFO - Epoch [10][3450/7330] lr: 1.000e-05, eta: 4:48:24, time: 0.918, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0347, loss_cls: 0.1372, acc: 94.6470, loss_bbox: 0.1932, loss_mask: 0.2049, loss: 0.5805 2024-06-06 11:14:54,441 - mmdet - INFO - Epoch [10][3500/7330] lr: 1.000e-05, eta: 4:47:32, time: 0.913, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0346, loss_cls: 0.1367, acc: 94.7798, loss_bbox: 0.1943, loss_mask: 0.2072, loss: 0.5839 2024-06-06 11:15:39,869 - mmdet - INFO - Epoch [10][3550/7330] lr: 1.000e-05, eta: 4:46:39, time: 0.909, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0363, loss_cls: 0.1411, acc: 94.6528, loss_bbox: 0.1936, loss_mask: 0.2092, loss: 0.5914 2024-06-06 11:16:25,940 - mmdet - INFO - Epoch [10][3600/7330] lr: 1.000e-05, eta: 4:45:49, time: 0.921, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0344, loss_cls: 0.1378, acc: 94.6929, loss_bbox: 0.1893, loss_mask: 0.2048, loss: 0.5769 2024-06-06 11:17:11,937 - mmdet - INFO - Epoch [10][3650/7330] lr: 1.000e-05, eta: 4:44:59, time: 0.920, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0358, loss_cls: 0.1451, acc: 94.4268, loss_bbox: 0.2017, loss_mask: 0.2092, loss: 0.6031 2024-06-06 11:17:57,886 - mmdet - INFO - Epoch [10][3700/7330] lr: 1.000e-05, eta: 4:44:09, time: 0.919, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0343, loss_cls: 0.1353, acc: 94.8879, loss_bbox: 0.1876, loss_mask: 0.2041, loss: 0.5716 2024-06-06 11:18:43,533 - mmdet - INFO - Epoch [10][3750/7330] lr: 1.000e-05, eta: 4:43:18, time: 0.913, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0352, loss_cls: 0.1359, acc: 94.7661, loss_bbox: 0.1898, loss_mask: 0.2057, loss: 0.5766 2024-06-06 11:19:28,722 - mmdet - INFO - Epoch [10][3800/7330] lr: 1.000e-05, eta: 4:42:25, time: 0.904, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0334, loss_cls: 0.1299, acc: 95.0493, loss_bbox: 0.1825, loss_mask: 0.2016, loss: 0.5584 2024-06-06 11:20:13,614 - mmdet - INFO - Epoch [10][3850/7330] lr: 1.000e-05, eta: 4:41:30, time: 0.898, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0346, loss_cls: 0.1339, acc: 94.9436, loss_bbox: 0.1873, loss_mask: 0.2059, loss: 0.5727 2024-06-06 11:20:58,808 - mmdet - INFO - Epoch [10][3900/7330] lr: 1.000e-05, eta: 4:40:37, time: 0.904, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0342, loss_cls: 0.1345, acc: 94.8855, loss_bbox: 0.1870, loss_mask: 0.2073, loss: 0.5747 2024-06-06 11:21:43,961 - mmdet - INFO - Epoch [10][3950/7330] lr: 1.000e-05, eta: 4:39:45, time: 0.903, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0361, loss_cls: 0.1395, acc: 94.6248, loss_bbox: 0.1998, loss_mask: 0.2099, loss: 0.5971 2024-06-06 11:22:31,951 - mmdet - INFO - Epoch [10][4000/7330] lr: 1.000e-05, eta: 4:39:05, time: 0.960, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0363, loss_cls: 0.1348, acc: 94.8281, loss_bbox: 0.1918, loss_mask: 0.2016, loss: 0.5751 2024-06-06 11:23:17,115 - mmdet - INFO - Epoch [10][4050/7330] lr: 1.000e-05, eta: 4:38:12, time: 0.903, data_time: 0.051, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0371, loss_cls: 0.1435, acc: 94.5259, loss_bbox: 0.1973, loss_mask: 0.2111, loss: 0.5996 2024-06-06 11:24:01,947 - mmdet - INFO - Epoch [10][4100/7330] lr: 1.000e-05, eta: 4:37:18, time: 0.897, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0361, loss_cls: 0.1401, acc: 94.6357, loss_bbox: 0.1944, loss_mask: 0.2092, loss: 0.5910 2024-06-06 11:24:46,342 - mmdet - INFO - Epoch [10][4150/7330] lr: 1.000e-05, eta: 4:36:23, time: 0.888, data_time: 0.055, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0319, loss_cls: 0.1327, acc: 94.8882, loss_bbox: 0.1856, loss_mask: 0.2007, loss: 0.5609 2024-06-06 11:25:31,303 - mmdet - INFO - Epoch [10][4200/7330] lr: 1.000e-05, eta: 4:35:30, time: 0.899, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0367, loss_cls: 0.1404, acc: 94.6099, loss_bbox: 0.1940, loss_mask: 0.2107, loss: 0.5928 2024-06-06 11:26:17,253 - mmdet - INFO - Epoch [10][4250/7330] lr: 1.000e-05, eta: 4:34:41, time: 0.919, data_time: 0.060, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0353, loss_cls: 0.1414, acc: 94.5891, loss_bbox: 0.1961, loss_mask: 0.2040, loss: 0.5878 2024-06-06 11:27:01,817 - mmdet - INFO - Epoch [10][4300/7330] lr: 1.000e-05, eta: 4:33:47, time: 0.891, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0345, loss_cls: 0.1375, acc: 94.7271, loss_bbox: 0.1965, loss_mask: 0.2100, loss: 0.5890 2024-06-06 11:27:46,479 - mmdet - INFO - Epoch [10][4350/7330] lr: 1.000e-05, eta: 4:32:53, time: 0.893, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0338, loss_cls: 0.1328, acc: 94.9211, loss_bbox: 0.1853, loss_mask: 0.2013, loss: 0.5632 2024-06-06 11:28:32,283 - mmdet - INFO - Epoch [10][4400/7330] lr: 1.000e-05, eta: 4:32:04, time: 0.916, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0327, loss_cls: 0.1342, acc: 94.9004, loss_bbox: 0.1896, loss_mask: 0.2005, loss: 0.5676 2024-06-06 11:29:29,641 - mmdet - INFO - Epoch [10][4450/7330] lr: 1.000e-05, eta: 4:32:01, time: 1.147, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0384, loss_cls: 0.1422, acc: 94.5198, loss_bbox: 0.2012, loss_mask: 0.2090, loss: 0.6021 2024-06-06 11:30:14,752 - mmdet - INFO - Epoch [10][4500/7330] lr: 1.000e-05, eta: 4:31:09, time: 0.902, data_time: 0.060, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0363, loss_cls: 0.1416, acc: 94.6064, loss_bbox: 0.1993, loss_mask: 0.2082, loss: 0.5965 2024-06-06 11:30:59,799 - mmdet - INFO - Epoch [10][4550/7330] lr: 1.000e-05, eta: 4:30:17, time: 0.900, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0350, loss_cls: 0.1382, acc: 94.7256, loss_bbox: 0.1943, loss_mask: 0.2079, loss: 0.5868 2024-06-06 11:31:44,862 - mmdet - INFO - Epoch [10][4600/7330] lr: 1.000e-05, eta: 4:29:25, time: 0.902, data_time: 0.098, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0339, loss_cls: 0.1333, acc: 94.9941, loss_bbox: 0.1791, loss_mask: 0.2023, loss: 0.5590 2024-06-06 11:32:29,478 - mmdet - INFO - Epoch [10][4650/7330] lr: 1.000e-05, eta: 4:28:32, time: 0.892, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0332, loss_cls: 0.1356, acc: 94.8433, loss_bbox: 0.1867, loss_mask: 0.1973, loss: 0.5629 2024-06-06 11:33:13,871 - mmdet - INFO - Epoch [10][4700/7330] lr: 1.000e-05, eta: 4:27:38, time: 0.888, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0339, loss_cls: 0.1326, acc: 94.9058, loss_bbox: 0.1833, loss_mask: 0.2026, loss: 0.5618 2024-06-06 11:33:59,403 - mmdet - INFO - Epoch [10][4750/7330] lr: 1.000e-05, eta: 4:26:48, time: 0.911, data_time: 0.095, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0335, loss_cls: 0.1316, acc: 95.0232, loss_bbox: 0.1837, loss_mask: 0.2023, loss: 0.5614 2024-06-06 11:34:44,472 - mmdet - INFO - Epoch [10][4800/7330] lr: 1.000e-05, eta: 4:25:57, time: 0.901, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0328, loss_cls: 0.1319, acc: 94.9348, loss_bbox: 0.1836, loss_mask: 0.2040, loss: 0.5616 2024-06-06 11:35:30,045 - mmdet - INFO - Epoch [10][4850/7330] lr: 1.000e-05, eta: 4:25:07, time: 0.911, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0363, loss_cls: 0.1408, acc: 94.6621, loss_bbox: 0.1942, loss_mask: 0.2070, loss: 0.5897 2024-06-06 11:36:16,239 - mmdet - INFO - Epoch [10][4900/7330] lr: 1.000e-05, eta: 4:24:20, time: 0.924, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0362, loss_cls: 0.1373, acc: 94.7549, loss_bbox: 0.1916, loss_mask: 0.2058, loss: 0.5816 2024-06-06 11:37:01,745 - mmdet - INFO - Epoch [10][4950/7330] lr: 1.000e-05, eta: 4:23:31, time: 0.910, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0351, loss_cls: 0.1338, acc: 94.8020, loss_bbox: 0.1888, loss_mask: 0.2042, loss: 0.5725 2024-06-06 11:37:48,473 - mmdet - INFO - Epoch [10][5000/7330] lr: 1.000e-05, eta: 4:22:45, time: 0.935, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0391, loss_cls: 0.1490, acc: 94.3557, loss_bbox: 0.2059, loss_mask: 0.2178, loss: 0.6248 2024-06-06 11:38:33,749 - mmdet - INFO - Epoch [10][5050/7330] lr: 1.000e-05, eta: 4:21:55, time: 0.906, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0342, loss_cls: 0.1363, acc: 94.8230, loss_bbox: 0.1894, loss_mask: 0.1998, loss: 0.5696 2024-06-06 11:39:21,238 - mmdet - INFO - Epoch [10][5100/7330] lr: 1.000e-05, eta: 4:21:12, time: 0.950, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0326, loss_cls: 0.1318, acc: 94.9143, loss_bbox: 0.1877, loss_mask: 0.2043, loss: 0.5670 2024-06-06 11:40:06,042 - mmdet - INFO - Epoch [10][5150/7330] lr: 1.000e-05, eta: 4:20:21, time: 0.896, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0349, loss_cls: 0.1381, acc: 94.7405, loss_bbox: 0.1939, loss_mask: 0.2123, loss: 0.5894 2024-06-06 11:40:50,617 - mmdet - INFO - Epoch [10][5200/7330] lr: 1.000e-05, eta: 4:19:29, time: 0.891, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0339, loss_cls: 0.1365, acc: 94.7915, loss_bbox: 0.1902, loss_mask: 0.2044, loss: 0.5767 2024-06-06 11:41:36,597 - mmdet - INFO - Epoch [10][5250/7330] lr: 1.000e-05, eta: 4:18:41, time: 0.920, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0348, loss_cls: 0.1378, acc: 94.7476, loss_bbox: 0.1953, loss_mask: 0.2053, loss: 0.5842 2024-06-06 11:42:21,321 - mmdet - INFO - Epoch [10][5300/7330] lr: 1.000e-05, eta: 4:17:49, time: 0.895, data_time: 0.056, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0328, loss_cls: 0.1306, acc: 94.8706, loss_bbox: 0.1884, loss_mask: 0.2042, loss: 0.5653 2024-06-06 11:43:06,649 - mmdet - INFO - Epoch [10][5350/7330] lr: 1.000e-05, eta: 4:17:00, time: 0.907, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0352, loss_cls: 0.1341, acc: 94.8909, loss_bbox: 0.1897, loss_mask: 0.2036, loss: 0.5736 2024-06-06 11:43:51,267 - mmdet - INFO - Epoch [10][5400/7330] lr: 1.000e-05, eta: 4:16:08, time: 0.892, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0337, loss_cls: 0.1314, acc: 94.9856, loss_bbox: 0.1822, loss_mask: 0.2024, loss: 0.5601 2024-06-06 11:44:36,180 - mmdet - INFO - Epoch [10][5450/7330] lr: 1.000e-05, eta: 4:15:18, time: 0.898, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0356, loss_cls: 0.1405, acc: 94.6562, loss_bbox: 0.1935, loss_mask: 0.2043, loss: 0.5853 2024-06-06 11:45:37,520 - mmdet - INFO - Epoch [10][5500/7330] lr: 1.000e-05, eta: 4:15:17, time: 1.227, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0356, loss_cls: 0.1381, acc: 94.7378, loss_bbox: 0.1963, loss_mask: 0.2100, loss: 0.5910 2024-06-06 11:46:23,343 - mmdet - INFO - Epoch [10][5550/7330] lr: 1.000e-05, eta: 4:14:28, time: 0.916, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0354, loss_cls: 0.1408, acc: 94.5542, loss_bbox: 0.1932, loss_mask: 0.2077, loss: 0.5880 2024-06-06 11:47:08,950 - mmdet - INFO - Epoch [10][5600/7330] lr: 1.000e-05, eta: 4:13:39, time: 0.912, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0375, loss_cls: 0.1464, acc: 94.4922, loss_bbox: 0.1993, loss_mask: 0.2142, loss: 0.6099 2024-06-06 11:47:54,712 - mmdet - INFO - Epoch [10][5650/7330] lr: 1.000e-05, eta: 4:12:51, time: 0.915, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0364, loss_cls: 0.1404, acc: 94.6599, loss_bbox: 0.1982, loss_mask: 0.2118, loss: 0.5984 2024-06-06 11:48:40,605 - mmdet - INFO - Epoch [10][5700/7330] lr: 1.000e-05, eta: 4:12:03, time: 0.918, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0356, loss_cls: 0.1408, acc: 94.6006, loss_bbox: 0.1897, loss_mask: 0.2032, loss: 0.5801 2024-06-06 11:49:25,501 - mmdet - INFO - Epoch [10][5750/7330] lr: 1.000e-05, eta: 4:11:12, time: 0.898, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0346, loss_cls: 0.1332, acc: 94.8921, loss_bbox: 0.1890, loss_mask: 0.2037, loss: 0.5709 2024-06-06 11:50:10,186 - mmdet - INFO - Epoch [10][5800/7330] lr: 1.000e-05, eta: 4:10:21, time: 0.894, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0347, loss_cls: 0.1433, acc: 94.4773, loss_bbox: 0.1985, loss_mask: 0.2043, loss: 0.5927 2024-06-06 11:50:54,958 - mmdet - INFO - Epoch [10][5850/7330] lr: 1.000e-05, eta: 4:09:30, time: 0.895, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0328, loss_cls: 0.1277, acc: 95.0916, loss_bbox: 0.1786, loss_mask: 0.2043, loss: 0.5529 2024-06-06 11:51:40,015 - mmdet - INFO - Epoch [10][5900/7330] lr: 1.000e-05, eta: 4:08:40, time: 0.901, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0352, loss_cls: 0.1389, acc: 94.6382, loss_bbox: 0.1948, loss_mask: 0.2058, loss: 0.5859 2024-06-06 11:52:25,747 - mmdet - INFO - Epoch [10][5950/7330] lr: 1.000e-05, eta: 4:07:52, time: 0.915, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0358, loss_cls: 0.1327, acc: 94.8853, loss_bbox: 0.1881, loss_mask: 0.2070, loss: 0.5736 2024-06-06 11:53:09,832 - mmdet - INFO - Epoch [10][6000/7330] lr: 1.000e-05, eta: 4:07:00, time: 0.882, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0333, loss_cls: 0.1347, acc: 94.8406, loss_bbox: 0.1869, loss_mask: 0.1995, loss: 0.5652 2024-06-06 11:53:55,478 - mmdet - INFO - Epoch [10][6050/7330] lr: 1.000e-05, eta: 4:06:12, time: 0.913, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0359, loss_cls: 0.1405, acc: 94.6638, loss_bbox: 0.1994, loss_mask: 0.2099, loss: 0.5977 2024-06-06 11:54:40,231 - mmdet - INFO - Epoch [10][6100/7330] lr: 1.000e-05, eta: 4:05:21, time: 0.895, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0347, loss_cls: 0.1370, acc: 94.8403, loss_bbox: 0.1911, loss_mask: 0.2074, loss: 0.5808 2024-06-06 11:55:28,926 - mmdet - INFO - Epoch [10][6150/7330] lr: 1.000e-05, eta: 4:04:41, time: 0.974, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0353, loss_cls: 0.1359, acc: 94.7593, loss_bbox: 0.1911, loss_mask: 0.2050, loss: 0.5779 2024-06-06 11:56:14,210 - mmdet - INFO - Epoch [10][6200/7330] lr: 1.000e-05, eta: 4:03:52, time: 0.906, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0367, loss_cls: 0.1399, acc: 94.6262, loss_bbox: 0.1928, loss_mask: 0.2039, loss: 0.5850 2024-06-06 11:56:59,241 - mmdet - INFO - Epoch [10][6250/7330] lr: 1.000e-05, eta: 4:03:02, time: 0.901, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0362, loss_cls: 0.1395, acc: 94.6548, loss_bbox: 0.1935, loss_mask: 0.2055, loss: 0.5851 2024-06-06 11:57:44,197 - mmdet - INFO - Epoch [10][6300/7330] lr: 1.000e-05, eta: 4:02:13, time: 0.899, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0361, loss_cls: 0.1398, acc: 94.6738, loss_bbox: 0.1950, loss_mask: 0.2052, loss: 0.5857 2024-06-06 11:58:30,378 - mmdet - INFO - Epoch [10][6350/7330] lr: 1.000e-05, eta: 4:01:26, time: 0.924, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0374, loss_cls: 0.1454, acc: 94.4329, loss_bbox: 0.1991, loss_mask: 0.2103, loss: 0.6042 2024-06-06 11:59:16,559 - mmdet - INFO - Epoch [10][6400/7330] lr: 1.000e-05, eta: 4:00:39, time: 0.923, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0368, loss_cls: 0.1463, acc: 94.4248, loss_bbox: 0.1972, loss_mask: 0.2065, loss: 0.5990 2024-06-06 12:00:01,089 - mmdet - INFO - Epoch [10][6450/7330] lr: 1.000e-05, eta: 3:59:49, time: 0.891, data_time: 0.048, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0327, loss_cls: 0.1294, acc: 95.0388, loss_bbox: 0.1860, loss_mask: 0.2025, loss: 0.5601 2024-06-06 12:00:45,447 - mmdet - INFO - Epoch [10][6500/7330] lr: 1.000e-05, eta: 3:58:58, time: 0.887, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0328, loss_cls: 0.1315, acc: 94.9727, loss_bbox: 0.1897, loss_mask: 0.2077, loss: 0.5713 2024-06-06 12:01:37,035 - mmdet - INFO - Epoch [10][6550/7330] lr: 1.000e-05, eta: 3:58:24, time: 1.032, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0373, loss_cls: 0.1416, acc: 94.5596, loss_bbox: 0.1986, loss_mask: 0.2114, loss: 0.6007 2024-06-06 12:02:30,687 - mmdet - INFO - Epoch [10][6600/7330] lr: 1.000e-05, eta: 3:57:55, time: 1.073, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0352, loss_cls: 0.1405, acc: 94.5991, loss_bbox: 0.1952, loss_mask: 0.2084, loss: 0.5897 2024-06-06 12:03:16,364 - mmdet - INFO - Epoch [10][6650/7330] lr: 1.000e-05, eta: 3:57:07, time: 0.914, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0368, loss_cls: 0.1410, acc: 94.5605, loss_bbox: 0.1963, loss_mask: 0.2056, loss: 0.5902 2024-06-06 12:04:00,642 - mmdet - INFO - Epoch [10][6700/7330] lr: 1.000e-05, eta: 3:56:16, time: 0.886, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0375, loss_cls: 0.1403, acc: 94.7314, loss_bbox: 0.1971, loss_mask: 0.2087, loss: 0.5944 2024-06-06 12:04:45,548 - mmdet - INFO - Epoch [10][6750/7330] lr: 1.000e-05, eta: 3:55:26, time: 0.898, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0356, loss_cls: 0.1354, acc: 94.8528, loss_bbox: 0.1889, loss_mask: 0.2070, loss: 0.5789 2024-06-06 12:05:30,878 - mmdet - INFO - Epoch [10][6800/7330] lr: 1.000e-05, eta: 3:54:37, time: 0.907, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0365, loss_cls: 0.1390, acc: 94.6467, loss_bbox: 0.2001, loss_mask: 0.2108, loss: 0.5973 2024-06-06 12:06:16,399 - mmdet - INFO - Epoch [10][6850/7330] lr: 1.000e-05, eta: 3:53:49, time: 0.910, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0354, loss_cls: 0.1390, acc: 94.7549, loss_bbox: 0.1954, loss_mask: 0.2049, loss: 0.5859 2024-06-06 12:07:01,093 - mmdet - INFO - Epoch [10][6900/7330] lr: 1.000e-05, eta: 3:52:59, time: 0.894, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0372, loss_cls: 0.1431, acc: 94.4614, loss_bbox: 0.2003, loss_mask: 0.2111, loss: 0.6023 2024-06-06 12:07:47,101 - mmdet - INFO - Epoch [10][6950/7330] lr: 1.000e-05, eta: 3:52:12, time: 0.920, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0342, loss_cls: 0.1430, acc: 94.4592, loss_bbox: 0.2001, loss_mask: 0.2066, loss: 0.5937 2024-06-06 12:08:32,142 - mmdet - INFO - Epoch [10][7000/7330] lr: 1.000e-05, eta: 3:51:23, time: 0.901, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0364, loss_cls: 0.1356, acc: 94.7266, loss_bbox: 0.1920, loss_mask: 0.2024, loss: 0.5778 2024-06-06 12:09:17,601 - mmdet - INFO - Epoch [10][7050/7330] lr: 1.000e-05, eta: 3:50:35, time: 0.909, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0358, loss_cls: 0.1423, acc: 94.5056, loss_bbox: 0.2001, loss_mask: 0.2082, loss: 0.5972 2024-06-06 12:10:01,858 - mmdet - INFO - Epoch [10][7100/7330] lr: 1.000e-05, eta: 3:49:44, time: 0.885, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0349, loss_cls: 0.1379, acc: 94.6543, loss_bbox: 0.1974, loss_mask: 0.2065, loss: 0.5872 2024-06-06 12:10:47,415 - mmdet - INFO - Epoch [10][7150/7330] lr: 1.000e-05, eta: 3:48:57, time: 0.911, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0339, loss_cls: 0.1325, acc: 94.8784, loss_bbox: 0.1866, loss_mask: 0.2027, loss: 0.5660 2024-06-06 12:11:34,074 - mmdet - INFO - Epoch [10][7200/7330] lr: 1.000e-05, eta: 3:48:11, time: 0.933, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0375, loss_cls: 0.1422, acc: 94.5947, loss_bbox: 0.1925, loss_mask: 0.2056, loss: 0.5900 2024-06-06 12:12:19,699 - mmdet - INFO - Epoch [10][7250/7330] lr: 1.000e-05, eta: 3:47:24, time: 0.912, data_time: 0.095, memory: 11340, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0381, loss_cls: 0.1416, acc: 94.6289, loss_bbox: 0.1910, loss_mask: 0.2065, loss: 0.5898 2024-06-06 12:13:05,233 - mmdet - INFO - Epoch [10][7300/7330] lr: 1.000e-05, eta: 3:46:36, time: 0.911, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0348, loss_cls: 0.1392, acc: 94.6550, loss_bbox: 0.1942, loss_mask: 0.2082, loss: 0.5872 2024-06-06 12:13:33,477 - mmdet - INFO - Saving checkpoint at 10 epochs 2024-06-06 12:15:21,180 - mmdet - INFO - Evaluating bbox... 2024-06-06 12:15:42,303 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.479 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.697 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.524 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.290 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.517 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.659 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.391 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.631 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.764 2024-06-06 12:15:42,304 - mmdet - INFO - Evaluating segm... 2024-06-06 12:16:11,036 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.423 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.661 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.206 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.454 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.641 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.571 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.719 2024-06-06 12:16:11,520 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 12:16:11,521 - mmdet - INFO - Epoch(val) [10][625] bbox_mAP: 0.4790, bbox_mAP_50: 0.6970, bbox_mAP_75: 0.5240, bbox_mAP_s: 0.2900, bbox_mAP_m: 0.5170, bbox_mAP_l: 0.6590, bbox_mAP_copypaste: 0.479 0.697 0.524 0.290 0.517 0.659, segm_mAP: 0.4230, segm_mAP_50: 0.6610, segm_mAP_75: 0.4520, segm_mAP_s: 0.2060, segm_mAP_m: 0.4540, segm_mAP_l: 0.6410, segm_mAP_copypaste: 0.423 0.661 0.452 0.206 0.454 0.641 2024-06-06 12:17:00,695 - mmdet - INFO - Epoch [11][50/7330] lr: 1.000e-05, eta: 3:44:32, time: 0.983, data_time: 0.136, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0329, loss_cls: 0.1292, acc: 94.9758, loss_bbox: 0.1835, loss_mask: 0.1965, loss: 0.5525 2024-06-06 12:17:48,197 - mmdet - INFO - Epoch [11][100/7330] lr: 1.000e-05, eta: 3:43:49, time: 0.950, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0346, loss_cls: 0.1331, acc: 94.8596, loss_bbox: 0.1864, loss_mask: 0.2074, loss: 0.5716 2024-06-06 12:18:35,592 - mmdet - INFO - Epoch [11][150/7330] lr: 1.000e-05, eta: 3:43:05, time: 0.948, data_time: 0.061, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0355, loss_cls: 0.1398, acc: 94.5381, loss_bbox: 0.1978, loss_mask: 0.2095, loss: 0.5945 2024-06-06 12:19:20,684 - mmdet - INFO - Epoch [11][200/7330] lr: 1.000e-05, eta: 3:42:17, time: 0.902, data_time: 0.061, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0358, loss_cls: 0.1333, acc: 94.9248, loss_bbox: 0.1886, loss_mask: 0.2066, loss: 0.5756 2024-06-06 12:20:05,876 - mmdet - INFO - Epoch [11][250/7330] lr: 1.000e-05, eta: 3:41:29, time: 0.904, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0325, loss_cls: 0.1334, acc: 94.8257, loss_bbox: 0.1857, loss_mask: 0.1999, loss: 0.5614 2024-06-06 12:20:52,658 - mmdet - INFO - Epoch [11][300/7330] lr: 1.000e-05, eta: 3:40:45, time: 0.936, data_time: 0.098, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0362, loss_cls: 0.1386, acc: 94.6196, loss_bbox: 0.1948, loss_mask: 0.2073, loss: 0.5869 2024-06-06 12:21:42,332 - mmdet - INFO - Epoch [11][350/7330] lr: 1.000e-05, eta: 3:40:05, time: 0.994, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0375, loss_cls: 0.1433, acc: 94.4417, loss_bbox: 0.2007, loss_mask: 0.2108, loss: 0.6035 2024-06-06 12:22:38,508 - mmdet - INFO - Epoch [11][400/7330] lr: 1.000e-05, eta: 3:39:37, time: 1.123, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0355, loss_cls: 0.1361, acc: 94.7993, loss_bbox: 0.1960, loss_mask: 0.2055, loss: 0.5840 2024-06-06 12:23:29,026 - mmdet - INFO - Epoch [11][450/7330] lr: 1.000e-05, eta: 3:38:59, time: 1.010, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0363, loss_cls: 0.1387, acc: 94.6421, loss_bbox: 0.1946, loss_mask: 0.2017, loss: 0.5814 2024-06-06 12:24:14,910 - mmdet - INFO - Epoch [11][500/7330] lr: 1.000e-05, eta: 3:38:12, time: 0.918, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0370, loss_cls: 0.1358, acc: 94.8086, loss_bbox: 0.1924, loss_mask: 0.2019, loss: 0.5775 2024-06-06 12:25:01,476 - mmdet - INFO - Epoch [11][550/7330] lr: 1.000e-05, eta: 3:37:27, time: 0.931, data_time: 0.058, memory: 11340, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0356, loss_cls: 0.1394, acc: 94.5798, loss_bbox: 0.2000, loss_mask: 0.2108, loss: 0.5976 2024-06-06 12:25:48,437 - mmdet - INFO - Epoch [11][600/7330] lr: 1.000e-05, eta: 3:36:42, time: 0.939, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0354, loss_cls: 0.1336, acc: 94.8997, loss_bbox: 0.1891, loss_mask: 0.2066, loss: 0.5771 2024-06-06 12:26:35,161 - mmdet - INFO - Epoch [11][650/7330] lr: 1.000e-05, eta: 3:35:56, time: 0.934, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0365, loss_cls: 0.1388, acc: 94.7341, loss_bbox: 0.1935, loss_mask: 0.2065, loss: 0.5862 2024-06-06 12:27:21,829 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 12:27:21,829 - mmdet - INFO - Epoch [11][700/7330] lr: 1.000e-05, eta: 3:35:11, time: 0.933, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0344, loss_cls: 0.1305, acc: 94.8989, loss_bbox: 0.1875, loss_mask: 0.2053, loss: 0.5685 2024-06-06 12:28:09,219 - mmdet - INFO - Epoch [11][750/7330] lr: 1.000e-05, eta: 3:34:26, time: 0.948, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0335, loss_cls: 0.1268, acc: 95.1328, loss_bbox: 0.1801, loss_mask: 0.2011, loss: 0.5514 2024-06-06 12:28:55,414 - mmdet - INFO - Epoch [11][800/7330] lr: 1.000e-05, eta: 3:33:40, time: 0.924, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0328, loss_cls: 0.1323, acc: 94.9438, loss_bbox: 0.1887, loss_mask: 0.2017, loss: 0.5663 2024-06-06 12:29:42,643 - mmdet - INFO - Epoch [11][850/7330] lr: 1.000e-05, eta: 3:32:56, time: 0.945, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0356, loss_cls: 0.1366, acc: 94.7224, loss_bbox: 0.1939, loss_mask: 0.2067, loss: 0.5844 2024-06-06 12:30:28,426 - mmdet - INFO - Epoch [11][900/7330] lr: 1.000e-05, eta: 3:32:09, time: 0.916, data_time: 0.067, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0350, loss_cls: 0.1345, acc: 94.8469, loss_bbox: 0.1888, loss_mask: 0.2021, loss: 0.5708 2024-06-06 12:31:15,015 - mmdet - INFO - Epoch [11][950/7330] lr: 1.000e-05, eta: 3:31:23, time: 0.932, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0355, loss_cls: 0.1406, acc: 94.6152, loss_bbox: 0.1946, loss_mask: 0.2073, loss: 0.5889 2024-06-06 12:32:01,238 - mmdet - INFO - Epoch [11][1000/7330] lr: 1.000e-05, eta: 3:30:36, time: 0.924, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0323, loss_cls: 0.1330, acc: 94.9250, loss_bbox: 0.1852, loss_mask: 0.2016, loss: 0.5614 2024-06-06 12:32:47,365 - mmdet - INFO - Epoch [11][1050/7330] lr: 1.000e-05, eta: 3:29:50, time: 0.923, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0360, loss_cls: 0.1402, acc: 94.6006, loss_bbox: 0.2016, loss_mask: 0.2140, loss: 0.6021 2024-06-06 12:33:33,786 - mmdet - INFO - Epoch [11][1100/7330] lr: 1.000e-05, eta: 3:29:04, time: 0.928, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0366, loss_cls: 0.1387, acc: 94.5977, loss_bbox: 0.1937, loss_mask: 0.2049, loss: 0.5850 2024-06-06 12:34:19,588 - mmdet - INFO - Epoch [11][1150/7330] lr: 1.000e-05, eta: 3:28:17, time: 0.916, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0332, loss_cls: 0.1348, acc: 94.9385, loss_bbox: 0.1858, loss_mask: 0.2022, loss: 0.5663 2024-06-06 12:35:05,956 - mmdet - INFO - Epoch [11][1200/7330] lr: 1.000e-05, eta: 3:27:31, time: 0.927, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0334, loss_cls: 0.1351, acc: 94.7764, loss_bbox: 0.1886, loss_mask: 0.2065, loss: 0.5743 2024-06-06 12:35:50,841 - mmdet - INFO - Epoch [11][1250/7330] lr: 1.000e-05, eta: 3:26:43, time: 0.898, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0341, loss_cls: 0.1328, acc: 94.9609, loss_bbox: 0.1857, loss_mask: 0.1995, loss: 0.5616 2024-06-06 12:36:41,034 - mmdet - INFO - Epoch [11][1300/7330] lr: 1.000e-05, eta: 3:26:02, time: 1.004, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0357, loss_cls: 0.1346, acc: 94.8022, loss_bbox: 0.1905, loss_mask: 0.2023, loss: 0.5735 2024-06-06 12:37:27,351 - mmdet - INFO - Epoch [11][1350/7330] lr: 1.000e-05, eta: 3:25:16, time: 0.926, data_time: 0.094, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0344, loss_cls: 0.1407, acc: 94.5269, loss_bbox: 0.1916, loss_mask: 0.2073, loss: 0.5847 2024-06-06 12:38:13,373 - mmdet - INFO - Epoch [11][1400/7330] lr: 1.000e-05, eta: 3:24:30, time: 0.920, data_time: 0.061, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0341, loss_cls: 0.1348, acc: 94.7581, loss_bbox: 0.1885, loss_mask: 0.2001, loss: 0.5671 2024-06-06 12:39:00,205 - mmdet - INFO - Epoch [11][1450/7330] lr: 1.000e-05, eta: 3:23:44, time: 0.937, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0346, loss_cls: 0.1357, acc: 94.7212, loss_bbox: 0.1914, loss_mask: 0.2050, loss: 0.5768 2024-06-06 12:39:47,048 - mmdet - INFO - Epoch [11][1500/7330] lr: 1.000e-05, eta: 3:22:59, time: 0.937, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0330, loss_cls: 0.1268, acc: 95.1267, loss_bbox: 0.1779, loss_mask: 0.2003, loss: 0.5474 2024-06-06 12:40:33,686 - mmdet - INFO - Epoch [11][1550/7330] lr: 1.000e-05, eta: 3:22:13, time: 0.933, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0331, loss_cls: 0.1344, acc: 94.8545, loss_bbox: 0.1851, loss_mask: 0.1990, loss: 0.5611 2024-06-06 12:41:27,416 - mmdet - INFO - Epoch [11][1600/7330] lr: 1.000e-05, eta: 3:21:38, time: 1.075, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0378, loss_cls: 0.1384, acc: 94.7043, loss_bbox: 0.1938, loss_mask: 0.2067, loss: 0.5886 2024-06-06 12:42:22,964 - mmdet - INFO - Epoch [11][1650/7330] lr: 1.000e-05, eta: 3:21:05, time: 1.111, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0346, loss_cls: 0.1383, acc: 94.7336, loss_bbox: 0.1947, loss_mask: 0.2054, loss: 0.5829 2024-06-06 12:43:09,058 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 12:43:09,059 - mmdet - INFO - Epoch [11][1700/7330] lr: 1.000e-05, eta: 3:20:18, time: 0.922, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0334, loss_cls: 0.1341, acc: 94.8430, loss_bbox: 0.1878, loss_mask: 0.2054, loss: 0.5711 2024-06-06 12:43:54,637 - mmdet - INFO - Epoch [11][1750/7330] lr: 1.000e-05, eta: 3:19:30, time: 0.911, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0341, loss_cls: 0.1307, acc: 95.0107, loss_bbox: 0.1870, loss_mask: 0.2027, loss: 0.5642 2024-06-06 12:44:41,386 - mmdet - INFO - Epoch [11][1800/7330] lr: 1.000e-05, eta: 3:18:45, time: 0.935, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0374, loss_cls: 0.1374, acc: 94.7922, loss_bbox: 0.1950, loss_mask: 0.2042, loss: 0.5849 2024-06-06 12:45:27,818 - mmdet - INFO - Epoch [11][1850/7330] lr: 1.000e-05, eta: 3:17:58, time: 0.929, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0367, loss_cls: 0.1403, acc: 94.6907, loss_bbox: 0.1952, loss_mask: 0.2035, loss: 0.5868 2024-06-06 12:46:13,986 - mmdet - INFO - Epoch [11][1900/7330] lr: 1.000e-05, eta: 3:17:12, time: 0.923, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0343, loss_cls: 0.1333, acc: 94.8545, loss_bbox: 0.1913, loss_mask: 0.2024, loss: 0.5713 2024-06-06 12:46:59,983 - mmdet - INFO - Epoch [11][1950/7330] lr: 1.000e-05, eta: 3:16:25, time: 0.920, data_time: 0.061, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0335, loss_cls: 0.1290, acc: 95.0967, loss_bbox: 0.1844, loss_mask: 0.2000, loss: 0.5570 2024-06-06 12:47:45,996 - mmdet - INFO - Epoch [11][2000/7330] lr: 1.000e-05, eta: 3:15:38, time: 0.920, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0335, loss_cls: 0.1262, acc: 95.0771, loss_bbox: 0.1827, loss_mask: 0.1996, loss: 0.5515 2024-06-06 12:48:32,351 - mmdet - INFO - Epoch [11][2050/7330] lr: 1.000e-05, eta: 3:14:52, time: 0.927, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0354, loss_cls: 0.1368, acc: 94.7791, loss_bbox: 0.1922, loss_mask: 0.2053, loss: 0.5801 2024-06-06 12:49:17,449 - mmdet - INFO - Epoch [11][2100/7330] lr: 1.000e-05, eta: 3:14:04, time: 0.902, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0331, loss_cls: 0.1284, acc: 95.0925, loss_bbox: 0.1842, loss_mask: 0.2056, loss: 0.5605 2024-06-06 12:50:04,278 - mmdet - INFO - Epoch [11][2150/7330] lr: 1.000e-05, eta: 3:13:18, time: 0.937, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0350, loss_cls: 0.1411, acc: 94.5959, loss_bbox: 0.1964, loss_mask: 0.2046, loss: 0.5873 2024-06-06 12:50:52,342 - mmdet - INFO - Epoch [11][2200/7330] lr: 1.000e-05, eta: 3:12:34, time: 0.961, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0406, loss_cls: 0.1486, acc: 94.3528, loss_bbox: 0.2027, loss_mask: 0.2135, loss: 0.6173 2024-06-06 12:51:37,806 - mmdet - INFO - Epoch [11][2250/7330] lr: 1.000e-05, eta: 3:11:46, time: 0.909, data_time: 0.056, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0340, loss_cls: 0.1286, acc: 95.0247, loss_bbox: 0.1848, loss_mask: 0.2020, loss: 0.5593 2024-06-06 12:52:23,429 - mmdet - INFO - Epoch [11][2300/7330] lr: 1.000e-05, eta: 3:10:59, time: 0.912, data_time: 0.058, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0339, loss_cls: 0.1367, acc: 94.7671, loss_bbox: 0.1963, loss_mask: 0.2068, loss: 0.5838 2024-06-06 12:53:10,776 - mmdet - INFO - Epoch [11][2350/7330] lr: 1.000e-05, eta: 3:10:14, time: 0.947, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0353, loss_cls: 0.1295, acc: 95.0020, loss_bbox: 0.1818, loss_mask: 0.1990, loss: 0.5555 2024-06-06 12:53:56,146 - mmdet - INFO - Epoch [11][2400/7330] lr: 1.000e-05, eta: 3:09:26, time: 0.907, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0324, loss_cls: 0.1302, acc: 94.9470, loss_bbox: 0.1826, loss_mask: 0.2073, loss: 0.5619 2024-06-06 12:54:42,037 - mmdet - INFO - Epoch [11][2450/7330] lr: 1.000e-05, eta: 3:08:39, time: 0.918, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0331, loss_cls: 0.1314, acc: 94.9463, loss_bbox: 0.1866, loss_mask: 0.2024, loss: 0.5635 2024-06-06 12:55:29,892 - mmdet - INFO - Epoch [11][2500/7330] lr: 1.000e-05, eta: 3:07:55, time: 0.957, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0088, loss_rpn_bbox: 0.0325, loss_cls: 0.1282, acc: 95.1536, loss_bbox: 0.1834, loss_mask: 0.2024, loss: 0.5553 2024-06-06 12:56:15,799 - mmdet - INFO - Epoch [11][2550/7330] lr: 1.000e-05, eta: 3:07:08, time: 0.918, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0359, loss_cls: 0.1336, acc: 94.8518, loss_bbox: 0.1911, loss_mask: 0.2038, loss: 0.5752 2024-06-06 12:57:01,029 - mmdet - INFO - Epoch [11][2600/7330] lr: 1.000e-05, eta: 3:06:20, time: 0.904, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0363, loss_cls: 0.1434, acc: 94.4856, loss_bbox: 0.1981, loss_mask: 0.2065, loss: 0.5959 2024-06-06 12:57:47,525 - mmdet - INFO - Epoch [11][2650/7330] lr: 1.000e-05, eta: 3:05:34, time: 0.930, data_time: 0.090, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0344, loss_cls: 0.1270, acc: 95.1689, loss_bbox: 0.1836, loss_mask: 0.2016, loss: 0.5556 2024-06-06 12:58:34,266 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 12:58:34,266 - mmdet - INFO - Epoch [11][2700/7330] lr: 1.000e-05, eta: 3:04:48, time: 0.935, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0354, loss_cls: 0.1295, acc: 95.0120, loss_bbox: 0.1816, loss_mask: 0.2019, loss: 0.5582 2024-06-06 12:59:19,763 - mmdet - INFO - Epoch [11][2750/7330] lr: 1.000e-05, eta: 3:04:01, time: 0.910, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0344, loss_cls: 0.1356, acc: 94.8027, loss_bbox: 0.1886, loss_mask: 0.2071, loss: 0.5758 2024-06-06 13:00:07,775 - mmdet - INFO - Epoch [11][2800/7330] lr: 1.000e-05, eta: 3:03:16, time: 0.960, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0355, loss_cls: 0.1319, acc: 95.0264, loss_bbox: 0.1846, loss_mask: 0.2028, loss: 0.5653 2024-06-06 13:01:02,213 - mmdet - INFO - Epoch [11][2850/7330] lr: 1.000e-05, eta: 3:02:39, time: 1.089, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0088, loss_rpn_bbox: 0.0328, loss_cls: 0.1269, acc: 95.1296, loss_bbox: 0.1841, loss_mask: 0.2012, loss: 0.5540 2024-06-06 13:01:51,673 - mmdet - INFO - Epoch [11][2900/7330] lr: 1.000e-05, eta: 3:01:56, time: 0.989, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0354, loss_cls: 0.1378, acc: 94.6765, loss_bbox: 0.1946, loss_mask: 0.2031, loss: 0.5819 2024-06-06 13:02:37,623 - mmdet - INFO - Epoch [11][2950/7330] lr: 1.000e-05, eta: 3:01:09, time: 0.919, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0321, loss_cls: 0.1282, acc: 95.0706, loss_bbox: 0.1856, loss_mask: 0.2025, loss: 0.5589 2024-06-06 13:03:23,311 - mmdet - INFO - Epoch [11][3000/7330] lr: 1.000e-05, eta: 3:00:22, time: 0.914, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0338, loss_cls: 0.1305, acc: 94.9612, loss_bbox: 0.1879, loss_mask: 0.2044, loss: 0.5673 2024-06-06 13:04:08,808 - mmdet - INFO - Epoch [11][3050/7330] lr: 1.000e-05, eta: 2:59:35, time: 0.910, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0339, loss_cls: 0.1345, acc: 94.8391, loss_bbox: 0.1899, loss_mask: 0.2053, loss: 0.5739 2024-06-06 13:04:54,472 - mmdet - INFO - Epoch [11][3100/7330] lr: 1.000e-05, eta: 2:58:48, time: 0.913, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0337, loss_cls: 0.1316, acc: 95.0115, loss_bbox: 0.1891, loss_mask: 0.2071, loss: 0.5714 2024-06-06 13:05:40,449 - mmdet - INFO - Epoch [11][3150/7330] lr: 1.000e-05, eta: 2:58:01, time: 0.920, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0339, loss_cls: 0.1359, acc: 94.8003, loss_bbox: 0.1952, loss_mask: 0.2089, loss: 0.5840 2024-06-06 13:06:27,448 - mmdet - INFO - Epoch [11][3200/7330] lr: 1.000e-05, eta: 2:57:15, time: 0.940, data_time: 0.096, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0362, loss_cls: 0.1369, acc: 94.6497, loss_bbox: 0.1958, loss_mask: 0.2048, loss: 0.5851 2024-06-06 13:07:13,227 - mmdet - INFO - Epoch [11][3250/7330] lr: 1.000e-05, eta: 2:56:28, time: 0.916, data_time: 0.056, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0336, loss_cls: 0.1326, acc: 94.8679, loss_bbox: 0.1893, loss_mask: 0.2043, loss: 0.5696 2024-06-06 13:07:59,502 - mmdet - INFO - Epoch [11][3300/7330] lr: 1.000e-05, eta: 2:55:41, time: 0.925, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0342, loss_cls: 0.1345, acc: 94.8582, loss_bbox: 0.1867, loss_mask: 0.1981, loss: 0.5636 2024-06-06 13:08:45,449 - mmdet - INFO - Epoch [11][3350/7330] lr: 1.000e-05, eta: 2:54:54, time: 0.919, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0365, loss_cls: 0.1394, acc: 94.6379, loss_bbox: 0.1934, loss_mask: 0.2078, loss: 0.5877 2024-06-06 13:09:30,570 - mmdet - INFO - Epoch [11][3400/7330] lr: 1.000e-05, eta: 2:54:07, time: 0.902, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0345, loss_cls: 0.1334, acc: 94.8499, loss_bbox: 0.1900, loss_mask: 0.2069, loss: 0.5762 2024-06-06 13:10:15,980 - mmdet - INFO - Epoch [11][3450/7330] lr: 1.000e-05, eta: 2:53:19, time: 0.908, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0352, loss_cls: 0.1334, acc: 94.9143, loss_bbox: 0.1840, loss_mask: 0.2028, loss: 0.5671 2024-06-06 13:11:02,031 - mmdet - INFO - Epoch [11][3500/7330] lr: 1.000e-05, eta: 2:52:33, time: 0.921, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0344, loss_cls: 0.1315, acc: 94.9448, loss_bbox: 0.1841, loss_mask: 0.2023, loss: 0.5627 2024-06-06 13:11:48,527 - mmdet - INFO - Epoch [11][3550/7330] lr: 1.000e-05, eta: 2:51:46, time: 0.930, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0352, loss_cls: 0.1369, acc: 94.7620, loss_bbox: 0.1937, loss_mask: 0.2069, loss: 0.5824 2024-06-06 13:12:33,361 - mmdet - INFO - Epoch [11][3600/7330] lr: 1.000e-05, eta: 2:50:58, time: 0.897, data_time: 0.060, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0314, loss_cls: 0.1286, acc: 95.0806, loss_bbox: 0.1820, loss_mask: 0.1994, loss: 0.5512 2024-06-06 13:13:18,246 - mmdet - INFO - Epoch [11][3650/7330] lr: 1.000e-05, eta: 2:50:10, time: 0.898, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0335, loss_cls: 0.1290, acc: 95.1799, loss_bbox: 0.1800, loss_mask: 0.1991, loss: 0.5520 2024-06-06 13:14:03,742 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 13:14:03,743 - mmdet - INFO - Epoch [11][3700/7330] lr: 1.000e-05, eta: 2:49:23, time: 0.910, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0346, loss_cls: 0.1304, acc: 94.9878, loss_bbox: 0.1864, loss_mask: 0.2022, loss: 0.5636 2024-06-06 13:14:52,762 - mmdet - INFO - Epoch [11][3750/7330] lr: 1.000e-05, eta: 2:48:39, time: 0.980, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0348, loss_cls: 0.1322, acc: 94.8672, loss_bbox: 0.1889, loss_mask: 0.2011, loss: 0.5672 2024-06-06 13:15:38,642 - mmdet - INFO - Epoch [11][3800/7330] lr: 1.000e-05, eta: 2:47:53, time: 0.918, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0366, loss_cls: 0.1412, acc: 94.6389, loss_bbox: 0.1959, loss_mask: 0.2090, loss: 0.5926 2024-06-06 13:16:24,560 - mmdet - INFO - Epoch [11][3850/7330] lr: 1.000e-05, eta: 2:47:06, time: 0.918, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0350, loss_cls: 0.1389, acc: 94.7278, loss_bbox: 0.1935, loss_mask: 0.2050, loss: 0.5836 2024-06-06 13:17:09,809 - mmdet - INFO - Epoch [11][3900/7330] lr: 1.000e-05, eta: 2:46:18, time: 0.905, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0341, loss_cls: 0.1390, acc: 94.7004, loss_bbox: 0.1924, loss_mask: 0.2031, loss: 0.5788 2024-06-06 13:17:54,897 - mmdet - INFO - Epoch [11][3950/7330] lr: 1.000e-05, eta: 2:45:31, time: 0.902, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0332, loss_cls: 0.1276, acc: 95.0764, loss_bbox: 0.1822, loss_mask: 0.2033, loss: 0.5566 2024-06-06 13:18:40,036 - mmdet - INFO - Epoch [11][4000/7330] lr: 1.000e-05, eta: 2:44:43, time: 0.903, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0324, loss_cls: 0.1258, acc: 95.1638, loss_bbox: 0.1817, loss_mask: 0.1992, loss: 0.5482 2024-06-06 13:19:30,387 - mmdet - INFO - Epoch [11][4050/7330] lr: 1.000e-05, eta: 2:44:01, time: 1.007, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0329, loss_cls: 0.1295, acc: 94.9985, loss_bbox: 0.1838, loss_mask: 0.2035, loss: 0.5590 2024-06-06 13:20:28,200 - mmdet - INFO - Epoch [11][4100/7330] lr: 1.000e-05, eta: 2:43:25, time: 1.156, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0362, loss_cls: 0.1438, acc: 94.4932, loss_bbox: 0.1960, loss_mask: 0.2045, loss: 0.5916 2024-06-06 13:21:14,379 - mmdet - INFO - Epoch [11][4150/7330] lr: 1.000e-05, eta: 2:42:38, time: 0.924, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0340, loss_cls: 0.1306, acc: 95.0090, loss_bbox: 0.1825, loss_mask: 0.2017, loss: 0.5584 2024-06-06 13:22:00,394 - mmdet - INFO - Epoch [11][4200/7330] lr: 1.000e-05, eta: 2:41:51, time: 0.920, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0326, loss_cls: 0.1248, acc: 95.2725, loss_bbox: 0.1812, loss_mask: 0.1968, loss: 0.5451 2024-06-06 13:22:46,424 - mmdet - INFO - Epoch [11][4250/7330] lr: 1.000e-05, eta: 2:41:05, time: 0.921, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0364, loss_cls: 0.1387, acc: 94.6804, loss_bbox: 0.1948, loss_mask: 0.2078, loss: 0.5883 2024-06-06 13:23:31,094 - mmdet - INFO - Epoch [11][4300/7330] lr: 1.000e-05, eta: 2:40:17, time: 0.893, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0332, loss_cls: 0.1307, acc: 95.0688, loss_bbox: 0.1813, loss_mask: 0.2000, loss: 0.5556 2024-06-06 13:24:16,589 - mmdet - INFO - Epoch [11][4350/7330] lr: 1.000e-05, eta: 2:39:29, time: 0.910, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0340, loss_cls: 0.1376, acc: 94.6689, loss_bbox: 0.1945, loss_mask: 0.2070, loss: 0.5835 2024-06-06 13:25:02,585 - mmdet - INFO - Epoch [11][4400/7330] lr: 1.000e-05, eta: 2:38:43, time: 0.920, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0350, loss_cls: 0.1371, acc: 94.6956, loss_bbox: 0.1902, loss_mask: 0.2028, loss: 0.5753 2024-06-06 13:25:48,335 - mmdet - INFO - Epoch [11][4450/7330] lr: 1.000e-05, eta: 2:37:56, time: 0.915, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0315, loss_cls: 0.1293, acc: 94.9575, loss_bbox: 0.1865, loss_mask: 0.1967, loss: 0.5534 2024-06-06 13:26:36,321 - mmdet - INFO - Epoch [11][4500/7330] lr: 1.000e-05, eta: 2:37:11, time: 0.960, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0338, loss_cls: 0.1315, acc: 94.9629, loss_bbox: 0.1901, loss_mask: 0.2029, loss: 0.5685 2024-06-06 13:27:22,724 - mmdet - INFO - Epoch [11][4550/7330] lr: 1.000e-05, eta: 2:36:24, time: 0.928, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0339, loss_cls: 0.1341, acc: 94.8477, loss_bbox: 0.1812, loss_mask: 0.2010, loss: 0.5605 2024-06-06 13:28:07,892 - mmdet - INFO - Epoch [11][4600/7330] lr: 1.000e-05, eta: 2:35:37, time: 0.904, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0330, loss_cls: 0.1328, acc: 94.9658, loss_bbox: 0.1876, loss_mask: 0.2023, loss: 0.5649 2024-06-06 13:28:53,459 - mmdet - INFO - Epoch [11][4650/7330] lr: 1.000e-05, eta: 2:34:50, time: 0.911, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0343, loss_cls: 0.1299, acc: 94.9568, loss_bbox: 0.1871, loss_mask: 0.2060, loss: 0.5684 2024-06-06 13:29:38,613 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 13:29:38,614 - mmdet - INFO - Epoch [11][4700/7330] lr: 1.000e-05, eta: 2:34:02, time: 0.903, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0357, loss_cls: 0.1332, acc: 94.8149, loss_bbox: 0.1901, loss_mask: 0.2080, loss: 0.5775 2024-06-06 13:30:24,644 - mmdet - INFO - Epoch [11][4750/7330] lr: 1.000e-05, eta: 2:33:15, time: 0.921, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0323, loss_cls: 0.1271, acc: 95.1182, loss_bbox: 0.1830, loss_mask: 0.2046, loss: 0.5566 2024-06-06 13:31:12,132 - mmdet - INFO - Epoch [11][4800/7330] lr: 1.000e-05, eta: 2:32:30, time: 0.950, data_time: 0.052, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0326, loss_cls: 0.1280, acc: 95.0745, loss_bbox: 0.1813, loss_mask: 0.2020, loss: 0.5541 2024-06-06 13:31:57,409 - mmdet - INFO - Epoch [11][4850/7330] lr: 1.000e-05, eta: 2:31:43, time: 0.906, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0351, loss_cls: 0.1347, acc: 94.8965, loss_bbox: 0.1860, loss_mask: 0.1999, loss: 0.5659 2024-06-06 13:32:42,785 - mmdet - INFO - Epoch [11][4900/7330] lr: 1.000e-05, eta: 2:30:55, time: 0.907, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0320, loss_cls: 0.1300, acc: 95.0491, loss_bbox: 0.1830, loss_mask: 0.1998, loss: 0.5546 2024-06-06 13:33:30,665 - mmdet - INFO - Epoch [11][4950/7330] lr: 1.000e-05, eta: 2:30:10, time: 0.958, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0332, loss_cls: 0.1310, acc: 94.9619, loss_bbox: 0.1889, loss_mask: 0.2063, loss: 0.5697 2024-06-06 13:34:16,727 - mmdet - INFO - Epoch [11][5000/7330] lr: 1.000e-05, eta: 2:29:23, time: 0.921, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0333, loss_cls: 0.1347, acc: 94.8743, loss_bbox: 0.1867, loss_mask: 0.2044, loss: 0.5694 2024-06-06 13:35:02,062 - mmdet - INFO - Epoch [11][5050/7330] lr: 1.000e-05, eta: 2:28:36, time: 0.907, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0335, loss_cls: 0.1305, acc: 95.0278, loss_bbox: 0.1841, loss_mask: 0.2044, loss: 0.5618 2024-06-06 13:35:47,325 - mmdet - INFO - Epoch [11][5100/7330] lr: 1.000e-05, eta: 2:27:49, time: 0.905, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0375, loss_cls: 0.1400, acc: 94.5686, loss_bbox: 0.1991, loss_mask: 0.2104, loss: 0.5980 2024-06-06 13:36:33,028 - mmdet - INFO - Epoch [11][5150/7330] lr: 1.000e-05, eta: 2:27:02, time: 0.914, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0339, loss_cls: 0.1320, acc: 94.9216, loss_bbox: 0.1925, loss_mask: 0.2061, loss: 0.5749 2024-06-06 13:37:19,111 - mmdet - INFO - Epoch [11][5200/7330] lr: 1.000e-05, eta: 2:26:15, time: 0.922, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0353, loss_cls: 0.1347, acc: 94.7937, loss_bbox: 0.1888, loss_mask: 0.2033, loss: 0.5727 2024-06-06 13:38:08,426 - mmdet - INFO - Epoch [11][5250/7330] lr: 1.000e-05, eta: 2:25:31, time: 0.986, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0342, loss_cls: 0.1296, acc: 95.0525, loss_bbox: 0.1835, loss_mask: 0.1982, loss: 0.5564 2024-06-06 13:39:05,818 - mmdet - INFO - Epoch [11][5300/7330] lr: 1.000e-05, eta: 2:24:53, time: 1.148, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0335, loss_cls: 0.1323, acc: 94.8806, loss_bbox: 0.1862, loss_mask: 0.2013, loss: 0.5626 2024-06-06 13:39:53,394 - mmdet - INFO - Epoch [11][5350/7330] lr: 1.000e-05, eta: 2:24:07, time: 0.952, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0331, loss_cls: 0.1249, acc: 95.2336, loss_bbox: 0.1815, loss_mask: 0.2013, loss: 0.5504 2024-06-06 13:40:39,237 - mmdet - INFO - Epoch [11][5400/7330] lr: 1.000e-05, eta: 2:23:21, time: 0.917, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0348, loss_cls: 0.1413, acc: 94.6831, loss_bbox: 0.1941, loss_mask: 0.2085, loss: 0.5902 2024-06-06 13:41:24,763 - mmdet - INFO - Epoch [11][5450/7330] lr: 1.000e-05, eta: 2:22:33, time: 0.911, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0342, loss_cls: 0.1319, acc: 94.8970, loss_bbox: 0.1860, loss_mask: 0.1983, loss: 0.5601 2024-06-06 13:42:10,401 - mmdet - INFO - Epoch [11][5500/7330] lr: 1.000e-05, eta: 2:21:46, time: 0.913, data_time: 0.094, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0344, loss_cls: 0.1326, acc: 94.9690, loss_bbox: 0.1880, loss_mask: 0.2013, loss: 0.5675 2024-06-06 13:42:55,148 - mmdet - INFO - Epoch [11][5550/7330] lr: 1.000e-05, eta: 2:20:59, time: 0.895, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0354, loss_cls: 0.1355, acc: 94.7395, loss_bbox: 0.1926, loss_mask: 0.2068, loss: 0.5798 2024-06-06 13:43:40,934 - mmdet - INFO - Epoch [11][5600/7330] lr: 1.000e-05, eta: 2:20:12, time: 0.916, data_time: 0.090, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0336, loss_cls: 0.1305, acc: 95.0542, loss_bbox: 0.1814, loss_mask: 0.2024, loss: 0.5574 2024-06-06 13:44:26,731 - mmdet - INFO - Epoch [11][5650/7330] lr: 1.000e-05, eta: 2:19:25, time: 0.916, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0344, loss_cls: 0.1365, acc: 94.7524, loss_bbox: 0.1908, loss_mask: 0.2070, loss: 0.5784 2024-06-06 13:45:12,205 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 13:45:12,205 - mmdet - INFO - Epoch [11][5700/7330] lr: 1.000e-05, eta: 2:18:38, time: 0.910, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0329, loss_cls: 0.1352, acc: 94.8779, loss_bbox: 0.1906, loss_mask: 0.2016, loss: 0.5707 2024-06-06 13:45:58,103 - mmdet - INFO - Epoch [11][5750/7330] lr: 1.000e-05, eta: 2:17:51, time: 0.918, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0352, loss_cls: 0.1365, acc: 94.7551, loss_bbox: 0.1915, loss_mask: 0.2069, loss: 0.5809 2024-06-06 13:46:43,834 - mmdet - INFO - Epoch [11][5800/7330] lr: 1.000e-05, eta: 2:17:04, time: 0.915, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0336, loss_cls: 0.1308, acc: 94.9839, loss_bbox: 0.1855, loss_mask: 0.2030, loss: 0.5626 2024-06-06 13:47:29,890 - mmdet - INFO - Epoch [11][5850/7330] lr: 1.000e-05, eta: 2:16:18, time: 0.921, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0355, loss_cls: 0.1372, acc: 94.7454, loss_bbox: 0.1948, loss_mask: 0.2046, loss: 0.5817 2024-06-06 13:48:15,007 - mmdet - INFO - Epoch [11][5900/7330] lr: 1.000e-05, eta: 2:15:30, time: 0.902, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0343, loss_cls: 0.1347, acc: 94.8354, loss_bbox: 0.1898, loss_mask: 0.2043, loss: 0.5730 2024-06-06 13:49:00,191 - mmdet - INFO - Epoch [11][5950/7330] lr: 1.000e-05, eta: 2:14:43, time: 0.904, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0350, loss_cls: 0.1356, acc: 94.8098, loss_bbox: 0.1899, loss_mask: 0.2062, loss: 0.5765 2024-06-06 13:49:45,422 - mmdet - INFO - Epoch [11][6000/7330] lr: 1.000e-05, eta: 2:13:56, time: 0.905, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0336, loss_cls: 0.1278, acc: 95.1101, loss_bbox: 0.1830, loss_mask: 0.2002, loss: 0.5544 2024-06-06 13:50:30,763 - mmdet - INFO - Epoch [11][6050/7330] lr: 1.000e-05, eta: 2:13:09, time: 0.907, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0346, loss_cls: 0.1347, acc: 94.9182, loss_bbox: 0.1873, loss_mask: 0.2028, loss: 0.5699 2024-06-06 13:51:15,601 - mmdet - INFO - Epoch [11][6100/7330] lr: 1.000e-05, eta: 2:12:22, time: 0.897, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0343, loss_cls: 0.1305, acc: 95.0015, loss_bbox: 0.1849, loss_mask: 0.2043, loss: 0.5643 2024-06-06 13:52:01,509 - mmdet - INFO - Epoch [11][6150/7330] lr: 1.000e-05, eta: 2:11:35, time: 0.918, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0359, loss_cls: 0.1409, acc: 94.5593, loss_bbox: 0.1903, loss_mask: 0.2064, loss: 0.5839 2024-06-06 13:52:50,723 - mmdet - INFO - Epoch [11][6200/7330] lr: 1.000e-05, eta: 2:10:50, time: 0.984, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0362, loss_cls: 0.1420, acc: 94.5603, loss_bbox: 0.1988, loss_mask: 0.2099, loss: 0.5981 2024-06-06 13:53:36,042 - mmdet - INFO - Epoch [11][6250/7330] lr: 1.000e-05, eta: 2:10:03, time: 0.906, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0348, loss_cls: 0.1371, acc: 94.6814, loss_bbox: 0.1905, loss_mask: 0.2044, loss: 0.5771 2024-06-06 13:54:21,696 - mmdet - INFO - Epoch [11][6300/7330] lr: 1.000e-05, eta: 2:09:16, time: 0.913, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0372, loss_cls: 0.1428, acc: 94.4976, loss_bbox: 0.1983, loss_mask: 0.2079, loss: 0.5983 2024-06-06 13:55:08,542 - mmdet - INFO - Epoch [11][6350/7330] lr: 1.000e-05, eta: 2:08:30, time: 0.937, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0362, loss_cls: 0.1363, acc: 94.7668, loss_bbox: 0.1919, loss_mask: 0.2084, loss: 0.5851 2024-06-06 13:55:56,501 - mmdet - INFO - Epoch [11][6400/7330] lr: 1.000e-05, eta: 2:07:45, time: 0.959, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0357, loss_cls: 0.1378, acc: 94.6895, loss_bbox: 0.1917, loss_mask: 0.2044, loss: 0.5817 2024-06-06 13:56:42,338 - mmdet - INFO - Epoch [11][6450/7330] lr: 1.000e-05, eta: 2:06:58, time: 0.917, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0377, loss_cls: 0.1373, acc: 94.7454, loss_bbox: 0.1935, loss_mask: 0.2089, loss: 0.5893 2024-06-06 13:57:32,928 - mmdet - INFO - Epoch [11][6500/7330] lr: 1.000e-05, eta: 2:06:14, time: 1.012, data_time: 0.096, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0357, loss_cls: 0.1378, acc: 94.7339, loss_bbox: 0.1952, loss_mask: 0.2045, loss: 0.5846 2024-06-06 13:58:29,994 - mmdet - INFO - Epoch [11][6550/7330] lr: 1.000e-05, eta: 2:05:34, time: 1.141, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0363, loss_cls: 0.1377, acc: 94.7688, loss_bbox: 0.1970, loss_mask: 0.2079, loss: 0.5890 2024-06-06 13:59:16,174 - mmdet - INFO - Epoch [11][6600/7330] lr: 1.000e-05, eta: 2:04:47, time: 0.923, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0349, loss_cls: 0.1368, acc: 94.7844, loss_bbox: 0.1945, loss_mask: 0.2071, loss: 0.5832 2024-06-06 14:00:01,199 - mmdet - INFO - Epoch [11][6650/7330] lr: 1.000e-05, eta: 2:04:00, time: 0.901, data_time: 0.064, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0342, loss_cls: 0.1342, acc: 94.8467, loss_bbox: 0.1954, loss_mask: 0.2092, loss: 0.5837 2024-06-06 14:00:46,989 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 14:00:46,989 - mmdet - INFO - Epoch [11][6700/7330] lr: 1.000e-05, eta: 2:03:13, time: 0.916, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0338, loss_cls: 0.1318, acc: 95.0010, loss_bbox: 0.1831, loss_mask: 0.2004, loss: 0.5593 2024-06-06 14:01:32,052 - mmdet - INFO - Epoch [11][6750/7330] lr: 1.000e-05, eta: 2:02:26, time: 0.901, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0326, loss_cls: 0.1354, acc: 94.8035, loss_bbox: 0.1911, loss_mask: 0.2058, loss: 0.5755 2024-06-06 14:02:17,639 - mmdet - INFO - Epoch [11][6800/7330] lr: 1.000e-05, eta: 2:01:39, time: 0.912, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0350, loss_cls: 0.1370, acc: 94.7766, loss_bbox: 0.1927, loss_mask: 0.2083, loss: 0.5833 2024-06-06 14:03:04,342 - mmdet - INFO - Epoch [11][6850/7330] lr: 1.000e-05, eta: 2:00:53, time: 0.934, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0343, loss_cls: 0.1328, acc: 94.8521, loss_bbox: 0.1936, loss_mask: 0.2018, loss: 0.5726 2024-06-06 14:03:50,644 - mmdet - INFO - Epoch [11][6900/7330] lr: 1.000e-05, eta: 2:00:06, time: 0.926, data_time: 0.091, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0360, loss_cls: 0.1407, acc: 94.5869, loss_bbox: 0.1983, loss_mask: 0.2061, loss: 0.5921 2024-06-06 14:04:35,929 - mmdet - INFO - Epoch [11][6950/7330] lr: 1.000e-05, eta: 1:59:19, time: 0.906, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0340, loss_cls: 0.1321, acc: 94.8950, loss_bbox: 0.1828, loss_mask: 0.2058, loss: 0.5655 2024-06-06 14:05:22,917 - mmdet - INFO - Epoch [11][7000/7330] lr: 1.000e-05, eta: 1:58:33, time: 0.940, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0368, loss_cls: 0.1422, acc: 94.5334, loss_bbox: 0.2019, loss_mask: 0.2098, loss: 0.6021 2024-06-06 14:06:09,779 - mmdet - INFO - Epoch [11][7050/7330] lr: 1.000e-05, eta: 1:57:47, time: 0.937, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0343, loss_cls: 0.1344, acc: 94.8677, loss_bbox: 0.1871, loss_mask: 0.2038, loss: 0.5707 2024-06-06 14:06:55,837 - mmdet - INFO - Epoch [11][7100/7330] lr: 1.000e-05, eta: 1:57:00, time: 0.921, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0361, loss_cls: 0.1411, acc: 94.6780, loss_bbox: 0.1964, loss_mask: 0.2107, loss: 0.5953 2024-06-06 14:07:41,421 - mmdet - INFO - Epoch [11][7150/7330] lr: 1.000e-05, eta: 1:56:13, time: 0.912, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0338, loss_cls: 0.1301, acc: 94.9746, loss_bbox: 0.1871, loss_mask: 0.2041, loss: 0.5646 2024-06-06 14:08:27,020 - mmdet - INFO - Epoch [11][7200/7330] lr: 1.000e-05, eta: 1:55:27, time: 0.912, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0354, loss_cls: 0.1383, acc: 94.6711, loss_bbox: 0.1948, loss_mask: 0.2121, loss: 0.5915 2024-06-06 14:09:12,602 - mmdet - INFO - Epoch [11][7250/7330] lr: 1.000e-05, eta: 1:54:40, time: 0.912, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0318, loss_cls: 0.1269, acc: 95.1428, loss_bbox: 0.1778, loss_mask: 0.1989, loss: 0.5450 2024-06-06 14:09:59,485 - mmdet - INFO - Epoch [11][7300/7330] lr: 1.000e-05, eta: 1:53:53, time: 0.938, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0359, loss_cls: 0.1357, acc: 94.8438, loss_bbox: 0.1950, loss_mask: 0.2101, loss: 0.5865 2024-06-06 14:10:27,958 - mmdet - INFO - Saving checkpoint at 11 epochs 2024-06-06 14:12:15,584 - mmdet - INFO - Evaluating bbox... 2024-06-06 14:12:39,204 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.480 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.696 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.525 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.288 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.517 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.663 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.630 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.767 2024-06-06 14:12:39,204 - mmdet - INFO - Evaluating segm... 2024-06-06 14:13:02,629 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.424 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.661 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.453 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.207 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.643 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.320 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.570 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.720 2024-06-06 14:13:03,141 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 14:13:03,142 - mmdet - INFO - Epoch(val) [11][625] bbox_mAP: 0.4800, bbox_mAP_50: 0.6960, bbox_mAP_75: 0.5250, bbox_mAP_s: 0.2880, bbox_mAP_m: 0.5170, bbox_mAP_l: 0.6630, bbox_mAP_copypaste: 0.480 0.696 0.525 0.288 0.517 0.663, segm_mAP: 0.4240, segm_mAP_50: 0.6610, segm_mAP_75: 0.4530, segm_mAP_s: 0.2070, segm_mAP_m: 0.4520, segm_mAP_l: 0.6430, segm_mAP_copypaste: 0.424 0.661 0.453 0.207 0.452 0.643 2024-06-06 14:13:56,032 - mmdet - INFO - Epoch [12][50/7330] lr: 1.000e-06, eta: 1:52:29, time: 1.057, data_time: 0.151, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0357, loss_cls: 0.1337, acc: 94.8369, loss_bbox: 0.1899, loss_mask: 0.2065, loss: 0.5762 2024-06-06 14:14:41,695 - mmdet - INFO - Epoch [12][100/7330] lr: 1.000e-06, eta: 1:51:42, time: 0.913, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0338, loss_cls: 0.1309, acc: 94.9236, loss_bbox: 0.1868, loss_mask: 0.2048, loss: 0.5663 2024-06-06 14:15:28,189 - mmdet - INFO - Epoch [12][150/7330] lr: 1.000e-06, eta: 1:50:56, time: 0.930, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0337, loss_cls: 0.1320, acc: 94.9551, loss_bbox: 0.1893, loss_mask: 0.2015, loss: 0.5658 2024-06-06 14:16:13,698 - mmdet - INFO - Epoch [12][200/7330] lr: 1.000e-06, eta: 1:50:09, time: 0.910, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0344, loss_cls: 0.1285, acc: 95.0288, loss_bbox: 0.1870, loss_mask: 0.2033, loss: 0.5630 2024-06-06 14:17:00,338 - mmdet - INFO - Epoch [12][250/7330] lr: 1.000e-06, eta: 1:49:23, time: 0.933, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0353, loss_cls: 0.1350, acc: 94.7209, loss_bbox: 0.1938, loss_mask: 0.2014, loss: 0.5762 2024-06-06 14:17:50,616 - mmdet - INFO - Epoch [12][300/7330] lr: 1.000e-06, eta: 1:48:38, time: 1.006, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0357, loss_cls: 0.1375, acc: 94.7144, loss_bbox: 0.1914, loss_mask: 0.2009, loss: 0.5762 2024-06-06 14:18:36,484 - mmdet - INFO - Epoch [12][350/7330] lr: 1.000e-06, eta: 1:47:52, time: 0.917, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0336, loss_cls: 0.1263, acc: 95.1633, loss_bbox: 0.1860, loss_mask: 0.2035, loss: 0.5594 2024-06-06 14:19:22,316 - mmdet - INFO - Epoch [12][400/7330] lr: 1.000e-06, eta: 1:47:05, time: 0.917, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0348, loss_cls: 0.1264, acc: 95.1499, loss_bbox: 0.1813, loss_mask: 0.1978, loss: 0.5511 2024-06-06 14:20:08,156 - mmdet - INFO - Epoch [12][450/7330] lr: 1.000e-06, eta: 1:46:18, time: 0.917, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0344, loss_cls: 0.1331, acc: 94.9604, loss_bbox: 0.1849, loss_mask: 0.2013, loss: 0.5644 2024-06-06 14:20:53,915 - mmdet - INFO - Epoch [12][500/7330] lr: 1.000e-06, eta: 1:45:32, time: 0.915, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0329, loss_cls: 0.1257, acc: 95.1685, loss_bbox: 0.1826, loss_mask: 0.2017, loss: 0.5528 2024-06-06 14:21:39,515 - mmdet - INFO - Epoch [12][550/7330] lr: 1.000e-06, eta: 1:44:45, time: 0.912, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0318, loss_cls: 0.1217, acc: 95.3113, loss_bbox: 0.1772, loss_mask: 0.1964, loss: 0.5363 2024-06-06 14:22:25,446 - mmdet - INFO - Epoch [12][600/7330] lr: 1.000e-06, eta: 1:43:58, time: 0.919, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0344, loss_cls: 0.1300, acc: 94.9453, loss_bbox: 0.1861, loss_mask: 0.2031, loss: 0.5630 2024-06-06 14:23:10,689 - mmdet - INFO - Epoch [12][650/7330] lr: 1.000e-06, eta: 1:43:12, time: 0.905, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0320, loss_cls: 0.1257, acc: 95.2192, loss_bbox: 0.1802, loss_mask: 0.2015, loss: 0.5484 2024-06-06 14:23:56,198 - mmdet - INFO - Epoch [12][700/7330] lr: 1.000e-06, eta: 1:42:25, time: 0.910, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0330, loss_cls: 0.1254, acc: 95.2358, loss_bbox: 0.1771, loss_mask: 0.1986, loss: 0.5439 2024-06-06 14:24:42,114 - mmdet - INFO - Epoch [12][750/7330] lr: 1.000e-06, eta: 1:41:38, time: 0.919, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0342, loss_cls: 0.1325, acc: 94.9148, loss_bbox: 0.1854, loss_mask: 0.1983, loss: 0.5602 2024-06-06 14:25:28,780 - mmdet - INFO - Epoch [12][800/7330] lr: 1.000e-06, eta: 1:40:52, time: 0.933, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0344, loss_cls: 0.1332, acc: 94.9192, loss_bbox: 0.1875, loss_mask: 0.1997, loss: 0.5649 2024-06-06 14:26:16,145 - mmdet - INFO - Epoch [12][850/7330] lr: 1.000e-06, eta: 1:40:06, time: 0.947, data_time: 0.098, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0373, loss_cls: 0.1388, acc: 94.6345, loss_bbox: 0.1987, loss_mask: 0.2082, loss: 0.5944 2024-06-06 14:27:01,836 - mmdet - INFO - Epoch [12][900/7330] lr: 1.000e-06, eta: 1:39:20, time: 0.914, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0340, loss_cls: 0.1361, acc: 94.7095, loss_bbox: 0.1973, loss_mask: 0.2039, loss: 0.5812 2024-06-06 14:27:46,908 - mmdet - INFO - Epoch [12][950/7330] lr: 1.000e-06, eta: 1:38:33, time: 0.901, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0087, loss_rpn_bbox: 0.0333, loss_cls: 0.1297, acc: 95.0281, loss_bbox: 0.1894, loss_mask: 0.2072, loss: 0.5683 2024-06-06 14:28:35,726 - mmdet - INFO - Epoch [12][1000/7330] lr: 1.000e-06, eta: 1:37:47, time: 0.976, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0361, loss_cls: 0.1366, acc: 94.7161, loss_bbox: 0.1929, loss_mask: 0.2072, loss: 0.5834 2024-06-06 14:29:22,958 - mmdet - INFO - Epoch [12][1050/7330] lr: 1.000e-06, eta: 1:37:01, time: 0.945, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0326, loss_cls: 0.1255, acc: 95.1685, loss_bbox: 0.1790, loss_mask: 0.2026, loss: 0.5498 2024-06-06 14:30:11,859 - mmdet - INFO - Epoch [12][1100/7330] lr: 1.000e-06, eta: 1:36:16, time: 0.978, data_time: 0.100, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0347, loss_cls: 0.1316, acc: 94.9285, loss_bbox: 0.1898, loss_mask: 0.2036, loss: 0.5697 2024-06-06 14:31:03,743 - mmdet - INFO - Epoch [12][1150/7330] lr: 1.000e-06, eta: 1:35:32, time: 1.038, data_time: 0.102, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0332, loss_cls: 0.1332, acc: 94.8079, loss_bbox: 0.1897, loss_mask: 0.2027, loss: 0.5689 2024-06-06 14:31:58,178 - mmdet - INFO - Epoch [12][1200/7330] lr: 1.000e-06, eta: 1:34:49, time: 1.088, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0341, loss_cls: 0.1266, acc: 95.1238, loss_bbox: 0.1839, loss_mask: 0.2004, loss: 0.5549 2024-06-06 14:32:44,375 - mmdet - INFO - Epoch [12][1250/7330] lr: 1.000e-06, eta: 1:34:02, time: 0.924, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0339, loss_cls: 0.1324, acc: 94.9380, loss_bbox: 0.1876, loss_mask: 0.2070, loss: 0.5712 2024-06-06 14:33:30,310 - mmdet - INFO - Epoch [12][1300/7330] lr: 1.000e-06, eta: 1:33:16, time: 0.919, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0357, loss_cls: 0.1312, acc: 94.9690, loss_bbox: 0.1869, loss_mask: 0.2006, loss: 0.5644 2024-06-06 14:34:18,217 - mmdet - INFO - Epoch [12][1350/7330] lr: 1.000e-06, eta: 1:32:30, time: 0.958, data_time: 0.106, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0357, loss_cls: 0.1304, acc: 95.0308, loss_bbox: 0.1877, loss_mask: 0.2042, loss: 0.5680 2024-06-06 14:35:04,433 - mmdet - INFO - Epoch [12][1400/7330] lr: 1.000e-06, eta: 1:31:43, time: 0.924, data_time: 0.094, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0337, loss_cls: 0.1297, acc: 94.9587, loss_bbox: 0.1846, loss_mask: 0.2008, loss: 0.5586 2024-06-06 14:35:50,977 - mmdet - INFO - Epoch [12][1450/7330] lr: 1.000e-06, eta: 1:30:57, time: 0.931, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0365, loss_cls: 0.1333, acc: 94.9065, loss_bbox: 0.1837, loss_mask: 0.2018, loss: 0.5660 2024-06-06 14:36:38,498 - mmdet - INFO - Epoch [12][1500/7330] lr: 1.000e-06, eta: 1:30:11, time: 0.950, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0340, loss_cls: 0.1288, acc: 95.0144, loss_bbox: 0.1844, loss_mask: 0.2051, loss: 0.5629 2024-06-06 14:37:25,585 - mmdet - INFO - Epoch [12][1550/7330] lr: 1.000e-06, eta: 1:29:25, time: 0.942, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0340, loss_cls: 0.1344, acc: 94.8630, loss_bbox: 0.1908, loss_mask: 0.2060, loss: 0.5748 2024-06-06 14:38:11,641 - mmdet - INFO - Epoch [12][1600/7330] lr: 1.000e-06, eta: 1:28:38, time: 0.921, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0319, loss_cls: 0.1331, acc: 94.8557, loss_bbox: 0.1882, loss_mask: 0.2046, loss: 0.5680 2024-06-06 14:38:58,247 - mmdet - INFO - Epoch [12][1650/7330] lr: 1.000e-06, eta: 1:27:52, time: 0.932, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0357, loss_cls: 0.1315, acc: 94.9622, loss_bbox: 0.1866, loss_mask: 0.2012, loss: 0.5653 2024-06-06 14:39:45,315 - mmdet - INFO - Epoch [12][1700/7330] lr: 1.000e-06, eta: 1:27:06, time: 0.941, data_time: 0.099, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0327, loss_cls: 0.1300, acc: 94.9456, loss_bbox: 0.1836, loss_mask: 0.1975, loss: 0.5539 2024-06-06 14:40:31,740 - mmdet - INFO - Epoch [12][1750/7330] lr: 1.000e-06, eta: 1:26:19, time: 0.928, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0323, loss_cls: 0.1283, acc: 95.0891, loss_bbox: 0.1815, loss_mask: 0.2027, loss: 0.5549 2024-06-06 14:41:17,317 - mmdet - INFO - Epoch [12][1800/7330] lr: 1.000e-06, eta: 1:25:33, time: 0.911, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0337, loss_cls: 0.1245, acc: 95.2407, loss_bbox: 0.1816, loss_mask: 0.1979, loss: 0.5468 2024-06-06 14:42:03,290 - mmdet - INFO - Epoch [12][1850/7330] lr: 1.000e-06, eta: 1:24:46, time: 0.919, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0348, loss_cls: 0.1335, acc: 94.8225, loss_bbox: 0.1925, loss_mask: 0.2062, loss: 0.5775 2024-06-06 14:42:50,254 - mmdet - INFO - Epoch [12][1900/7330] lr: 1.000e-06, eta: 1:24:00, time: 0.939, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0349, loss_cls: 0.1362, acc: 94.7820, loss_bbox: 0.1888, loss_mask: 0.2070, loss: 0.5768 2024-06-06 14:43:37,142 - mmdet - INFO - Epoch [12][1950/7330] lr: 1.000e-06, eta: 1:23:14, time: 0.938, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0335, loss_cls: 0.1290, acc: 95.0847, loss_bbox: 0.1826, loss_mask: 0.2005, loss: 0.5557 2024-06-06 14:44:23,033 - mmdet - INFO - Epoch [12][2000/7330] lr: 1.000e-06, eta: 1:22:27, time: 0.918, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0324, loss_cls: 0.1252, acc: 95.1577, loss_bbox: 0.1832, loss_mask: 0.2035, loss: 0.5538 2024-06-06 14:45:09,056 - mmdet - INFO - Epoch [12][2050/7330] lr: 1.000e-06, eta: 1:21:40, time: 0.920, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0340, loss_cls: 0.1400, acc: 94.5308, loss_bbox: 0.1939, loss_mask: 0.2051, loss: 0.5823 2024-06-06 14:45:55,403 - mmdet - INFO - Epoch [12][2100/7330] lr: 1.000e-06, eta: 1:20:54, time: 0.927, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0343, loss_cls: 0.1306, acc: 95.0291, loss_bbox: 0.1872, loss_mask: 0.2038, loss: 0.5651 2024-06-06 14:46:40,414 - mmdet - INFO - Epoch [12][2150/7330] lr: 1.000e-06, eta: 1:20:07, time: 0.900, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0315, loss_cls: 0.1254, acc: 95.1917, loss_bbox: 0.1813, loss_mask: 0.2039, loss: 0.5521 2024-06-06 14:47:27,865 - mmdet - INFO - Epoch [12][2200/7330] lr: 1.000e-06, eta: 1:19:21, time: 0.949, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0340, loss_cls: 0.1299, acc: 95.0117, loss_bbox: 0.1835, loss_mask: 0.2014, loss: 0.5582 2024-06-06 14:48:16,755 - mmdet - INFO - Epoch [12][2250/7330] lr: 1.000e-06, eta: 1:18:35, time: 0.978, data_time: 0.095, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0350, loss_cls: 0.1303, acc: 95.0498, loss_bbox: 0.1833, loss_mask: 0.1964, loss: 0.5549 2024-06-06 14:49:03,250 - mmdet - INFO - Epoch [12][2300/7330] lr: 1.000e-06, eta: 1:17:49, time: 0.930, data_time: 0.103, memory: 11340, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0331, loss_cls: 0.1280, acc: 95.0657, loss_bbox: 0.1849, loss_mask: 0.2045, loss: 0.5600 2024-06-06 14:49:53,153 - mmdet - INFO - Epoch [12][2350/7330] lr: 1.000e-06, eta: 1:17:04, time: 0.998, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0321, loss_cls: 0.1257, acc: 95.1714, loss_bbox: 0.1811, loss_mask: 0.1982, loss: 0.5470 2024-06-06 14:50:47,104 - mmdet - INFO - Epoch [12][2400/7330] lr: 1.000e-06, eta: 1:16:19, time: 1.079, data_time: 0.101, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0355, loss_cls: 0.1344, acc: 94.8750, loss_bbox: 0.1916, loss_mask: 0.2079, loss: 0.5799 2024-06-06 14:51:35,751 - mmdet - INFO - Epoch [12][2450/7330] lr: 1.000e-06, eta: 1:15:34, time: 0.973, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0357, loss_cls: 0.1319, acc: 94.8967, loss_bbox: 0.1885, loss_mask: 0.2031, loss: 0.5691 2024-06-06 14:52:22,617 - mmdet - INFO - Epoch [12][2500/7330] lr: 1.000e-06, eta: 1:14:47, time: 0.937, data_time: 0.090, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0341, loss_cls: 0.1344, acc: 94.8418, loss_bbox: 0.1885, loss_mask: 0.2075, loss: 0.5741 2024-06-06 14:53:08,911 - mmdet - INFO - Epoch [12][2550/7330] lr: 1.000e-06, eta: 1:14:01, time: 0.926, data_time: 0.098, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0372, loss_cls: 0.1361, acc: 94.7246, loss_bbox: 0.1894, loss_mask: 0.2053, loss: 0.5794 2024-06-06 14:53:55,658 - mmdet - INFO - Epoch [12][2600/7330] lr: 1.000e-06, eta: 1:13:14, time: 0.935, data_time: 0.091, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0340, loss_cls: 0.1314, acc: 94.9373, loss_bbox: 0.1869, loss_mask: 0.2064, loss: 0.5689 2024-06-06 14:54:40,469 - mmdet - INFO - Epoch [12][2650/7330] lr: 1.000e-06, eta: 1:12:27, time: 0.896, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0312, loss_cls: 0.1249, acc: 95.1157, loss_bbox: 0.1826, loss_mask: 0.1989, loss: 0.5467 2024-06-06 14:55:26,506 - mmdet - INFO - Epoch [12][2700/7330] lr: 1.000e-06, eta: 1:11:41, time: 0.921, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0346, loss_cls: 0.1306, acc: 94.9817, loss_bbox: 0.1891, loss_mask: 0.2013, loss: 0.5666 2024-06-06 14:56:14,161 - mmdet - INFO - Epoch [12][2750/7330] lr: 1.000e-06, eta: 1:10:55, time: 0.953, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0332, loss_cls: 0.1273, acc: 95.1064, loss_bbox: 0.1848, loss_mask: 0.2057, loss: 0.5604 2024-06-06 14:57:00,248 - mmdet - INFO - Epoch [12][2800/7330] lr: 1.000e-06, eta: 1:10:08, time: 0.922, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0340, loss_cls: 0.1280, acc: 95.0693, loss_bbox: 0.1858, loss_mask: 0.2009, loss: 0.5585 2024-06-06 14:57:47,649 - mmdet - INFO - Epoch [12][2850/7330] lr: 1.000e-06, eta: 1:09:22, time: 0.948, data_time: 0.102, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0343, loss_cls: 0.1318, acc: 94.8743, loss_bbox: 0.1876, loss_mask: 0.2031, loss: 0.5669 2024-06-06 14:58:33,202 - mmdet - INFO - Epoch [12][2900/7330] lr: 1.000e-06, eta: 1:08:35, time: 0.911, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0347, loss_cls: 0.1305, acc: 94.9712, loss_bbox: 0.1878, loss_mask: 0.2011, loss: 0.5646 2024-06-06 14:59:19,094 - mmdet - INFO - Epoch [12][2950/7330] lr: 1.000e-06, eta: 1:07:49, time: 0.918, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0325, loss_cls: 0.1239, acc: 95.2397, loss_bbox: 0.1767, loss_mask: 0.1958, loss: 0.5386 2024-06-06 15:00:04,616 - mmdet - INFO - Epoch [12][3000/7330] lr: 1.000e-06, eta: 1:07:02, time: 0.910, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0334, loss_cls: 0.1264, acc: 95.1226, loss_bbox: 0.1853, loss_mask: 0.2009, loss: 0.5558 2024-06-06 15:00:51,816 - mmdet - INFO - Epoch [12][3050/7330] lr: 1.000e-06, eta: 1:06:16, time: 0.944, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0365, loss_cls: 0.1349, acc: 94.8423, loss_bbox: 0.1921, loss_mask: 0.2091, loss: 0.5841 2024-06-06 15:01:38,673 - mmdet - INFO - Epoch [12][3100/7330] lr: 1.000e-06, eta: 1:05:29, time: 0.937, data_time: 0.110, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0321, loss_cls: 0.1258, acc: 95.1672, loss_bbox: 0.1803, loss_mask: 0.2014, loss: 0.5485 2024-06-06 15:02:25,580 - mmdet - INFO - Epoch [12][3150/7330] lr: 1.000e-06, eta: 1:04:43, time: 0.938, data_time: 0.069, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0358, loss_cls: 0.1391, acc: 94.6443, loss_bbox: 0.1942, loss_mask: 0.2032, loss: 0.5821 2024-06-06 15:03:11,747 - mmdet - INFO - Epoch [12][3200/7330] lr: 1.000e-06, eta: 1:03:56, time: 0.923, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0331, loss_cls: 0.1325, acc: 94.8831, loss_bbox: 0.1893, loss_mask: 0.2048, loss: 0.5699 2024-06-06 15:03:58,704 - mmdet - INFO - Epoch [12][3250/7330] lr: 1.000e-06, eta: 1:03:10, time: 0.939, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0349, loss_cls: 0.1327, acc: 94.9304, loss_bbox: 0.1884, loss_mask: 0.2047, loss: 0.5716 2024-06-06 15:04:45,653 - mmdet - INFO - Epoch [12][3300/7330] lr: 1.000e-06, eta: 1:02:24, time: 0.939, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0333, loss_cls: 0.1348, acc: 94.8093, loss_bbox: 0.1915, loss_mask: 0.2022, loss: 0.5715 2024-06-06 15:05:31,603 - mmdet - INFO - Epoch [12][3350/7330] lr: 1.000e-06, eta: 1:01:37, time: 0.919, data_time: 0.103, memory: 11340, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0339, loss_cls: 0.1371, acc: 94.7251, loss_bbox: 0.1893, loss_mask: 0.2017, loss: 0.5729 2024-06-06 15:06:17,092 - mmdet - INFO - Epoch [12][3400/7330] lr: 1.000e-06, eta: 1:00:51, time: 0.910, data_time: 0.053, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0316, loss_cls: 0.1262, acc: 95.2209, loss_bbox: 0.1776, loss_mask: 0.1981, loss: 0.5432 2024-06-06 15:07:05,869 - mmdet - INFO - Epoch [12][3450/7330] lr: 1.000e-06, eta: 1:00:05, time: 0.976, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0335, loss_cls: 0.1336, acc: 94.8428, loss_bbox: 0.1897, loss_mask: 0.2029, loss: 0.5700 2024-06-06 15:07:51,859 - mmdet - INFO - Epoch [12][3500/7330] lr: 1.000e-06, eta: 0:59:18, time: 0.920, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0349, loss_cls: 0.1299, acc: 94.9958, loss_bbox: 0.1838, loss_mask: 0.2029, loss: 0.5611 2024-06-06 15:08:39,932 - mmdet - INFO - Epoch [12][3550/7330] lr: 1.000e-06, eta: 0:58:32, time: 0.961, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0333, loss_cls: 0.1277, acc: 95.0945, loss_bbox: 0.1852, loss_mask: 0.1981, loss: 0.5541 2024-06-06 15:09:30,838 - mmdet - INFO - Epoch [12][3600/7330] lr: 1.000e-06, eta: 0:57:46, time: 1.018, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0337, loss_cls: 0.1269, acc: 95.0859, loss_bbox: 0.1790, loss_mask: 0.1971, loss: 0.5471 2024-06-06 15:10:25,263 - mmdet - INFO - Epoch [12][3650/7330] lr: 1.000e-06, eta: 0:57:02, time: 1.089, data_time: 0.096, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0356, loss_cls: 0.1314, acc: 94.9392, loss_bbox: 0.1864, loss_mask: 0.2023, loss: 0.5657 2024-06-06 15:11:10,901 - mmdet - INFO - Epoch [12][3700/7330] lr: 1.000e-06, eta: 0:56:15, time: 0.912, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0084, loss_rpn_bbox: 0.0312, loss_cls: 0.1245, acc: 95.1584, loss_bbox: 0.1813, loss_mask: 0.1988, loss: 0.5442 2024-06-06 15:11:57,815 - mmdet - INFO - Epoch [12][3750/7330] lr: 1.000e-06, eta: 0:55:28, time: 0.939, data_time: 0.098, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0335, loss_cls: 0.1239, acc: 95.2195, loss_bbox: 0.1809, loss_mask: 0.1971, loss: 0.5445 2024-06-06 15:12:44,979 - mmdet - INFO - Epoch [12][3800/7330] lr: 1.000e-06, eta: 0:54:42, time: 0.943, data_time: 0.090, memory: 11340, loss_rpn_cls: 0.0088, loss_rpn_bbox: 0.0331, loss_cls: 0.1293, acc: 94.9985, loss_bbox: 0.1858, loss_mask: 0.2031, loss: 0.5600 2024-06-06 15:13:31,528 - mmdet - INFO - Epoch [12][3850/7330] lr: 1.000e-06, eta: 0:53:56, time: 0.931, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0348, loss_cls: 0.1304, acc: 94.9722, loss_bbox: 0.1887, loss_mask: 0.2030, loss: 0.5669 2024-06-06 15:14:17,286 - mmdet - INFO - Epoch [12][3900/7330] lr: 1.000e-06, eta: 0:53:09, time: 0.915, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0333, loss_cls: 0.1262, acc: 95.1982, loss_bbox: 0.1765, loss_mask: 0.1969, loss: 0.5426 2024-06-06 15:15:07,257 - mmdet - INFO - Epoch [12][3950/7330] lr: 1.000e-06, eta: 0:52:23, time: 0.999, data_time: 0.099, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0345, loss_cls: 0.1299, acc: 95.0212, loss_bbox: 0.1860, loss_mask: 0.2007, loss: 0.5604 2024-06-06 15:15:52,578 - mmdet - INFO - Epoch [12][4000/7330] lr: 1.000e-06, eta: 0:51:36, time: 0.906, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0319, loss_cls: 0.1309, acc: 95.0308, loss_bbox: 0.1814, loss_mask: 0.1993, loss: 0.5534 2024-06-06 15:16:39,003 - mmdet - INFO - Epoch [12][4050/7330] lr: 1.000e-06, eta: 0:50:50, time: 0.929, data_time: 0.072, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0352, loss_cls: 0.1345, acc: 94.7883, loss_bbox: 0.1933, loss_mask: 0.2065, loss: 0.5803 2024-06-06 15:17:24,313 - mmdet - INFO - Epoch [12][4100/7330] lr: 1.000e-06, eta: 0:50:03, time: 0.906, data_time: 0.059, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0311, loss_cls: 0.1243, acc: 95.1946, loss_bbox: 0.1782, loss_mask: 0.2008, loss: 0.5441 2024-06-06 15:18:10,101 - mmdet - INFO - Epoch [12][4150/7330] lr: 1.000e-06, eta: 0:49:17, time: 0.916, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0332, loss_cls: 0.1248, acc: 95.1836, loss_bbox: 0.1786, loss_mask: 0.2009, loss: 0.5483 2024-06-06 15:18:56,420 - mmdet - INFO - Epoch [12][4200/7330] lr: 1.000e-06, eta: 0:48:30, time: 0.926, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0336, loss_cls: 0.1247, acc: 95.1616, loss_bbox: 0.1788, loss_mask: 0.2003, loss: 0.5475 2024-06-06 15:19:42,589 - mmdet - INFO - Epoch [12][4250/7330] lr: 1.000e-06, eta: 0:47:43, time: 0.923, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0315, loss_cls: 0.1256, acc: 95.1860, loss_bbox: 0.1820, loss_mask: 0.1998, loss: 0.5480 2024-06-06 15:20:28,285 - mmdet - INFO - Epoch [12][4300/7330] lr: 1.000e-06, eta: 0:46:57, time: 0.914, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0085, loss_rpn_bbox: 0.0322, loss_cls: 0.1232, acc: 95.2395, loss_bbox: 0.1782, loss_mask: 0.2017, loss: 0.5438 2024-06-06 15:21:13,850 - mmdet - INFO - Epoch [12][4350/7330] lr: 1.000e-06, eta: 0:46:10, time: 0.911, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0351, loss_cls: 0.1316, acc: 94.9543, loss_bbox: 0.1872, loss_mask: 0.2040, loss: 0.5677 2024-06-06 15:21:59,624 - mmdet - INFO - Epoch [12][4400/7330] lr: 1.000e-06, eta: 0:45:24, time: 0.915, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0347, loss_cls: 0.1323, acc: 94.9490, loss_bbox: 0.1871, loss_mask: 0.2039, loss: 0.5685 2024-06-06 15:22:45,090 - mmdet - INFO - Epoch [12][4450/7330] lr: 1.000e-06, eta: 0:44:37, time: 0.909, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0329, loss_cls: 0.1286, acc: 95.0115, loss_bbox: 0.1839, loss_mask: 0.1999, loss: 0.5551 2024-06-06 15:23:32,847 - mmdet - INFO - Epoch [12][4500/7330] lr: 1.000e-06, eta: 0:43:51, time: 0.955, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0370, loss_cls: 0.1272, acc: 95.0247, loss_bbox: 0.1885, loss_mask: 0.2061, loss: 0.5690 2024-06-06 15:24:19,257 - mmdet - INFO - Epoch [12][4550/7330] lr: 1.000e-06, eta: 0:43:04, time: 0.928, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0318, loss_cls: 0.1255, acc: 95.1143, loss_bbox: 0.1795, loss_mask: 0.1978, loss: 0.5435 2024-06-06 15:25:06,424 - mmdet - INFO - Epoch [12][4600/7330] lr: 1.000e-06, eta: 0:42:18, time: 0.943, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0356, loss_cls: 0.1297, acc: 95.0032, loss_bbox: 0.1834, loss_mask: 0.1986, loss: 0.5577 2024-06-06 15:25:52,830 - mmdet - INFO - Epoch [12][4650/7330] lr: 1.000e-06, eta: 0:41:31, time: 0.928, data_time: 0.095, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0328, loss_cls: 0.1295, acc: 95.0049, loss_bbox: 0.1876, loss_mask: 0.2042, loss: 0.5632 2024-06-06 15:26:41,949 - mmdet - INFO - Epoch [12][4700/7330] lr: 1.000e-06, eta: 0:40:45, time: 0.982, data_time: 0.101, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0346, loss_cls: 0.1319, acc: 94.9297, loss_bbox: 0.1938, loss_mask: 0.2073, loss: 0.5775 2024-06-06 15:27:28,125 - mmdet - INFO - Epoch [12][4750/7330] lr: 1.000e-06, eta: 0:39:59, time: 0.924, data_time: 0.096, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0338, loss_cls: 0.1278, acc: 95.0942, loss_bbox: 0.1797, loss_mask: 0.2004, loss: 0.5509 2024-06-06 15:28:17,961 - mmdet - INFO - Epoch [12][4800/7330] lr: 1.000e-06, eta: 0:39:13, time: 0.997, data_time: 0.068, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0334, loss_cls: 0.1306, acc: 94.9585, loss_bbox: 0.1899, loss_mask: 0.2022, loss: 0.5657 2024-06-06 15:29:13,127 - mmdet - INFO - Epoch [12][4850/7330] lr: 1.000e-06, eta: 0:38:27, time: 1.103, data_time: 0.109, memory: 11340, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0340, loss_cls: 0.1372, acc: 94.7188, loss_bbox: 0.1892, loss_mask: 0.2078, loss: 0.5787 2024-06-06 15:30:01,376 - mmdet - INFO - Epoch [12][4900/7330] lr: 1.000e-06, eta: 0:37:41, time: 0.965, data_time: 0.077, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0337, loss_cls: 0.1285, acc: 95.1287, loss_bbox: 0.1848, loss_mask: 0.2071, loss: 0.5634 2024-06-06 15:30:47,487 - mmdet - INFO - Epoch [12][4950/7330] lr: 1.000e-06, eta: 0:36:54, time: 0.922, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0355, loss_cls: 0.1388, acc: 94.5657, loss_bbox: 0.1954, loss_mask: 0.2082, loss: 0.5888 2024-06-06 15:31:33,185 - mmdet - INFO - Epoch [12][5000/7330] lr: 1.000e-06, eta: 0:36:08, time: 0.914, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0334, loss_cls: 0.1305, acc: 95.0195, loss_bbox: 0.1849, loss_mask: 0.2025, loss: 0.5606 2024-06-06 15:32:19,958 - mmdet - INFO - Epoch [12][5050/7330] lr: 1.000e-06, eta: 0:35:21, time: 0.935, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0350, loss_cls: 0.1359, acc: 94.7754, loss_bbox: 0.1919, loss_mask: 0.2072, loss: 0.5804 2024-06-06 15:33:06,361 - mmdet - INFO - Epoch [12][5100/7330] lr: 1.000e-06, eta: 0:34:35, time: 0.928, data_time: 0.081, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0339, loss_cls: 0.1291, acc: 94.9797, loss_bbox: 0.1845, loss_mask: 0.2041, loss: 0.5613 2024-06-06 15:33:55,468 - mmdet - INFO - Epoch [12][5150/7330] lr: 1.000e-06, eta: 0:33:48, time: 0.982, data_time: 0.062, memory: 11340, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0351, loss_cls: 0.1344, acc: 94.8499, loss_bbox: 0.1925, loss_mask: 0.2079, loss: 0.5794 2024-06-06 15:34:41,967 - mmdet - INFO - Epoch [12][5200/7330] lr: 1.000e-06, eta: 0:33:02, time: 0.930, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0366, loss_cls: 0.1340, acc: 94.7576, loss_bbox: 0.1909, loss_mask: 0.2047, loss: 0.5770 2024-06-06 15:35:28,985 - mmdet - INFO - Epoch [12][5250/7330] lr: 1.000e-06, eta: 0:32:15, time: 0.940, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0356, loss_cls: 0.1353, acc: 94.7644, loss_bbox: 0.1881, loss_mask: 0.2040, loss: 0.5728 2024-06-06 15:36:16,457 - mmdet - INFO - Epoch [12][5300/7330] lr: 1.000e-06, eta: 0:31:29, time: 0.949, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0356, loss_cls: 0.1366, acc: 94.7273, loss_bbox: 0.1933, loss_mask: 0.2017, loss: 0.5777 2024-06-06 15:37:02,286 - mmdet - INFO - Epoch [12][5350/7330] lr: 1.000e-06, eta: 0:30:42, time: 0.917, data_time: 0.078, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0346, loss_cls: 0.1341, acc: 94.8020, loss_bbox: 0.1897, loss_mask: 0.2066, loss: 0.5751 2024-06-06 15:37:47,605 - mmdet - INFO - Epoch [12][5400/7330] lr: 1.000e-06, eta: 0:29:56, time: 0.906, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0327, loss_cls: 0.1305, acc: 94.9646, loss_bbox: 0.1841, loss_mask: 0.2025, loss: 0.5599 2024-06-06 15:38:33,610 - mmdet - INFO - Epoch [12][5450/7330] lr: 1.000e-06, eta: 0:29:09, time: 0.920, data_time: 0.088, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0349, loss_cls: 0.1323, acc: 94.9480, loss_bbox: 0.1879, loss_mask: 0.2025, loss: 0.5676 2024-06-06 15:39:19,808 - mmdet - INFO - Epoch [12][5500/7330] lr: 1.000e-06, eta: 0:28:23, time: 0.924, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0344, loss_cls: 0.1316, acc: 94.9285, loss_bbox: 0.1895, loss_mask: 0.2029, loss: 0.5677 2024-06-06 15:40:06,769 - mmdet - INFO - Epoch [12][5550/7330] lr: 1.000e-06, eta: 0:27:36, time: 0.939, data_time: 0.108, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0360, loss_cls: 0.1343, acc: 94.8562, loss_bbox: 0.1928, loss_mask: 0.2029, loss: 0.5764 2024-06-06 15:40:53,088 - mmdet - INFO - Epoch [12][5600/7330] lr: 1.000e-06, eta: 0:26:49, time: 0.926, data_time: 0.058, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0338, loss_cls: 0.1303, acc: 94.9863, loss_bbox: 0.1834, loss_mask: 0.2029, loss: 0.5604 2024-06-06 15:41:39,189 - mmdet - INFO - Epoch [12][5650/7330] lr: 1.000e-06, eta: 0:26:03, time: 0.922, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0093, loss_rpn_bbox: 0.0340, loss_cls: 0.1331, acc: 94.8264, loss_bbox: 0.1880, loss_mask: 0.2050, loss: 0.5694 2024-06-06 15:42:25,397 - mmdet - INFO - Epoch [12][5700/7330] lr: 1.000e-06, eta: 0:25:16, time: 0.924, data_time: 0.099, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0324, loss_cls: 0.1313, acc: 94.9714, loss_bbox: 0.1838, loss_mask: 0.2010, loss: 0.5582 2024-06-06 15:43:11,956 - mmdet - INFO - Epoch [12][5750/7330] lr: 1.000e-06, eta: 0:24:30, time: 0.931, data_time: 0.074, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0341, loss_cls: 0.1319, acc: 94.9661, loss_bbox: 0.1905, loss_mask: 0.2005, loss: 0.5675 2024-06-06 15:43:59,754 - mmdet - INFO - Epoch [12][5800/7330] lr: 1.000e-06, eta: 0:23:43, time: 0.956, data_time: 0.097, memory: 11340, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0361, loss_cls: 0.1273, acc: 95.0908, loss_bbox: 0.1826, loss_mask: 0.2015, loss: 0.5579 2024-06-06 15:44:44,879 - mmdet - INFO - Epoch [12][5850/7330] lr: 1.000e-06, eta: 0:22:57, time: 0.903, data_time: 0.076, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0335, loss_cls: 0.1317, acc: 94.9661, loss_bbox: 0.1869, loss_mask: 0.1974, loss: 0.5592 2024-06-06 15:45:33,252 - mmdet - INFO - Epoch [12][5900/7330] lr: 1.000e-06, eta: 0:22:10, time: 0.967, data_time: 0.087, memory: 11340, loss_rpn_cls: 0.0084, loss_rpn_bbox: 0.0324, loss_cls: 0.1240, acc: 95.1965, loss_bbox: 0.1794, loss_mask: 0.1969, loss: 0.5412 2024-06-06 15:46:20,118 - mmdet - INFO - Epoch [12][5950/7330] lr: 1.000e-06, eta: 0:21:24, time: 0.937, data_time: 0.105, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0350, loss_cls: 0.1375, acc: 94.6514, loss_bbox: 0.1929, loss_mask: 0.2055, loss: 0.5805 2024-06-06 15:47:07,543 - mmdet - INFO - Epoch [12][6000/7330] lr: 1.000e-06, eta: 0:20:37, time: 0.948, data_time: 0.070, memory: 11340, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0339, loss_cls: 0.1290, acc: 95.1003, loss_bbox: 0.1806, loss_mask: 0.2014, loss: 0.5561 2024-06-06 15:48:03,209 - mmdet - INFO - Epoch [12][6050/7330] lr: 1.000e-06, eta: 0:19:51, time: 1.113, data_time: 0.108, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0362, loss_cls: 0.1361, acc: 94.7698, loss_bbox: 0.1952, loss_mask: 0.2101, loss: 0.5879 2024-06-06 15:48:54,425 - mmdet - INFO - Epoch [12][6100/7330] lr: 1.000e-06, eta: 0:19:05, time: 1.024, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0339, loss_cls: 0.1317, acc: 94.9546, loss_bbox: 0.1851, loss_mask: 0.1968, loss: 0.5583 2024-06-06 15:49:41,786 - mmdet - INFO - Epoch [12][6150/7330] lr: 1.000e-06, eta: 0:18:19, time: 0.947, data_time: 0.094, memory: 11340, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0348, loss_cls: 0.1352, acc: 94.8184, loss_bbox: 0.1910, loss_mask: 0.2059, loss: 0.5785 2024-06-06 15:50:27,672 - mmdet - INFO - Epoch [12][6200/7330] lr: 1.000e-06, eta: 0:17:32, time: 0.918, data_time: 0.071, memory: 11340, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0377, loss_cls: 0.1399, acc: 94.6602, loss_bbox: 0.1950, loss_mask: 0.2094, loss: 0.5927 2024-06-06 15:51:13,094 - mmdet - INFO - Epoch [12][6250/7330] lr: 1.000e-06, eta: 0:16:45, time: 0.908, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0320, loss_cls: 0.1253, acc: 95.2053, loss_bbox: 0.1778, loss_mask: 0.1960, loss: 0.5401 2024-06-06 15:51:58,950 - mmdet - INFO - Epoch [12][6300/7330] lr: 1.000e-06, eta: 0:15:59, time: 0.917, data_time: 0.066, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0327, loss_cls: 0.1323, acc: 94.9045, loss_bbox: 0.1846, loss_mask: 0.1995, loss: 0.5591 2024-06-06 15:52:45,704 - mmdet - INFO - Epoch [12][6350/7330] lr: 1.000e-06, eta: 0:15:12, time: 0.935, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0084, loss_rpn_bbox: 0.0322, loss_cls: 0.1226, acc: 95.3420, loss_bbox: 0.1791, loss_mask: 0.1987, loss: 0.5410 2024-06-06 15:53:36,484 - mmdet - INFO - Epoch [12][6400/7330] lr: 1.000e-06, eta: 0:14:26, time: 1.016, data_time: 0.105, memory: 11340, loss_rpn_cls: 0.0089, loss_rpn_bbox: 0.0333, loss_cls: 0.1283, acc: 95.0420, loss_bbox: 0.1815, loss_mask: 0.2017, loss: 0.5538 2024-06-06 15:54:22,648 - mmdet - INFO - Epoch [12][6450/7330] lr: 1.000e-06, eta: 0:13:39, time: 0.923, data_time: 0.082, memory: 11340, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0356, loss_cls: 0.1317, acc: 94.9517, loss_bbox: 0.1883, loss_mask: 0.2009, loss: 0.5668 2024-06-06 15:55:08,793 - mmdet - INFO - Epoch [12][6500/7330] lr: 1.000e-06, eta: 0:12:53, time: 0.923, data_time: 0.093, memory: 11340, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0309, loss_cls: 0.1286, acc: 94.9888, loss_bbox: 0.1832, loss_mask: 0.1989, loss: 0.5507 2024-06-06 15:55:55,295 - mmdet - INFO - Epoch [12][6550/7330] lr: 1.000e-06, eta: 0:12:06, time: 0.930, data_time: 0.063, memory: 11340, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0336, loss_cls: 0.1305, acc: 94.9512, loss_bbox: 0.1851, loss_mask: 0.1990, loss: 0.5589 2024-06-06 15:56:41,021 - mmdet - INFO - Epoch [12][6600/7330] lr: 1.000e-06, eta: 0:11:19, time: 0.914, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0084, loss_rpn_bbox: 0.0293, loss_cls: 0.1227, acc: 95.3867, loss_bbox: 0.1761, loss_mask: 0.1902, loss: 0.5267 2024-06-06 15:57:27,168 - mmdet - INFO - Epoch [12][6650/7330] lr: 1.000e-06, eta: 0:10:33, time: 0.923, data_time: 0.075, memory: 11340, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0350, loss_cls: 0.1357, acc: 94.7664, loss_bbox: 0.1964, loss_mask: 0.2054, loss: 0.5838 2024-06-06 15:58:13,931 - mmdet - INFO - Epoch [12][6700/7330] lr: 1.000e-06, eta: 0:09:46, time: 0.935, data_time: 0.065, memory: 11340, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0343, loss_cls: 0.1335, acc: 94.8811, loss_bbox: 0.1877, loss_mask: 0.2001, loss: 0.5655 2024-06-06 15:59:00,289 - mmdet - INFO - Epoch [12][6750/7330] lr: 1.000e-06, eta: 0:09:00, time: 0.927, data_time: 0.090, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0339, loss_cls: 0.1359, acc: 94.7561, loss_bbox: 0.1930, loss_mask: 0.2037, loss: 0.5767 2024-06-06 15:59:47,101 - mmdet - INFO - Epoch [12][6800/7330] lr: 1.000e-06, eta: 0:08:13, time: 0.936, data_time: 0.083, memory: 11340, loss_rpn_cls: 0.0087, loss_rpn_bbox: 0.0337, loss_cls: 0.1307, acc: 94.9631, loss_bbox: 0.1858, loss_mask: 0.2027, loss: 0.5616 2024-06-06 16:00:32,459 - mmdet - INFO - Epoch [12][6850/7330] lr: 1.000e-06, eta: 0:07:27, time: 0.907, data_time: 0.073, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0328, loss_cls: 0.1296, acc: 94.9187, loss_bbox: 0.1839, loss_mask: 0.2008, loss: 0.5572 2024-06-06 16:01:19,084 - mmdet - INFO - Epoch [12][6900/7330] lr: 1.000e-06, eta: 0:06:40, time: 0.933, data_time: 0.092, memory: 11340, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0348, loss_cls: 0.1309, acc: 94.9143, loss_bbox: 0.1875, loss_mask: 0.2058, loss: 0.5693 2024-06-06 16:02:05,450 - mmdet - INFO - Epoch [12][6950/7330] lr: 1.000e-06, eta: 0:05:53, time: 0.927, data_time: 0.091, memory: 11340, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0359, loss_cls: 0.1324, acc: 94.8936, loss_bbox: 0.1899, loss_mask: 0.2064, loss: 0.5745 2024-06-06 16:02:52,494 - mmdet - INFO - Epoch [12][7000/7330] lr: 1.000e-06, eta: 0:05:07, time: 0.941, data_time: 0.089, memory: 11340, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0368, loss_cls: 0.1405, acc: 94.6045, loss_bbox: 0.1995, loss_mask: 0.2064, loss: 0.5946 2024-06-06 16:03:38,588 - mmdet - INFO - Epoch [12][7050/7330] lr: 1.000e-06, eta: 0:04:20, time: 0.922, data_time: 0.084, memory: 11340, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0331, loss_cls: 0.1279, acc: 95.1292, loss_bbox: 0.1835, loss_mask: 0.2010, loss: 0.5556 2024-06-06 16:04:24,971 - mmdet - INFO - Epoch [12][7100/7330] lr: 1.000e-06, eta: 0:03:34, time: 0.928, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0321, loss_cls: 0.1316, acc: 94.9873, loss_bbox: 0.1868, loss_mask: 0.2006, loss: 0.5603 2024-06-06 16:05:13,922 - mmdet - INFO - Epoch [12][7150/7330] lr: 1.000e-06, eta: 0:02:47, time: 0.979, data_time: 0.079, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0332, loss_cls: 0.1288, acc: 95.1165, loss_bbox: 0.1846, loss_mask: 0.2005, loss: 0.5572 2024-06-06 16:06:00,998 - mmdet - INFO - Epoch [12][7200/7330] lr: 1.000e-06, eta: 0:02:01, time: 0.941, data_time: 0.086, memory: 11340, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0347, loss_cls: 0.1324, acc: 94.8689, loss_bbox: 0.1863, loss_mask: 0.2050, loss: 0.5684 2024-06-06 16:06:51,593 - mmdet - INFO - Epoch [12][7250/7330] lr: 1.000e-06, eta: 0:01:14, time: 1.012, data_time: 0.080, memory: 11340, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0341, loss_cls: 0.1331, acc: 94.9587, loss_bbox: 0.1860, loss_mask: 0.1998, loss: 0.5625 2024-06-06 16:07:44,643 - mmdet - INFO - Epoch [12][7300/7330] lr: 1.000e-06, eta: 0:00:27, time: 1.061, data_time: 0.085, memory: 11340, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0351, loss_cls: 0.1277, acc: 95.0410, loss_bbox: 0.1808, loss_mask: 0.1972, loss: 0.5509 2024-06-06 16:08:15,215 - mmdet - INFO - Saving checkpoint at 12 epochs 2024-06-06 16:10:01,197 - mmdet - INFO - Evaluating bbox... 2024-06-06 16:10:25,647 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.481 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.697 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.525 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.297 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.517 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.663 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.404 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.631 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.766 2024-06-06 16:10:25,647 - mmdet - INFO - Evaluating segm... 2024-06-06 16:10:49,663 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.424 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.662 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.452 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.454 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.642 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.529 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.321 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.570 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.717 2024-06-06 16:10:50,285 - mmdet - INFO - Exp name: mask_rcnn_augreg_sbl_1568_1120_672_fpn_1x_coco_bs16_speedup.py 2024-06-06 16:10:50,287 - mmdet - INFO - Epoch(val) [12][625] bbox_mAP: 0.4810, bbox_mAP_50: 0.6970, bbox_mAP_75: 0.5250, bbox_mAP_s: 0.2970, bbox_mAP_m: 0.5170, bbox_mAP_l: 0.6630, bbox_mAP_copypaste: 0.481 0.697 0.525 0.297 0.517 0.663, segm_mAP: 0.4240, segm_mAP_50: 0.6620, segm_mAP_75: 0.4520, segm_mAP_s: 0.2080, segm_mAP_m: 0.4540, segm_mAP_l: 0.6420, segm_mAP_copypaste: 0.424 0.662 0.452 0.208 0.454 0.642