2023-11-13 16:22:29,595 - mmdet - INFO - Environment info: ------------------------------------------------------------ sys.platform: linux Python: 3.8.17 (default, Jul 5 2023, 21:04:15) [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-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 7.5.0 PyTorch: 1.12.0 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37 - 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 OpenCV: 4.8.0 MMCV: 1.5.0 MMCV Compiler: GCC 7.5 MMCV CUDA Compiler: 11.3 MMDetection: 2.28.1+a85a748 ------------------------------------------------------------ 2023-11-13 16:22:30,372 - mmdet - INFO - Distributed training: True 2023-11-13 16:22:31,032 - mmdet - INFO - Config: model = dict( type='MaskRCNN', backbone=dict( type='Flash_InternImage_nsmx', core_op='FlashDCNv3', channels=64, depths=[4, 4, 18, 4], groups=[4, 8, 16, 32], mlp_ratio=4.0, drop_path_rate=0.2, norm_layer='LN', layer_scale=1.0, offset_scale=1.0, post_norm=False, with_cp=True, op_bias=True, with_dw=False, out_indices=(0, 1, 2, 3), init_cfg=dict( type='Pretrained', checkpoint= '/mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_t_1k_224_nosmx/ckpt_epoch_ema_best.pth' )), neck=dict( type='FPN_vitdet', in_channels=[64, 128, 256, 512], out_channels=256, num_outs=5, norm_cfg=dict(type='LN', requires_grad=True), use_residual=True), 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=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True, with_mask=True), dict(type='Resize', img_scale=(1333, 800), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size_divisor=32), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']) ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size_divisor=32), 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=(1333, 800), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size_divisor=32), 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=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size_divisor=32), 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=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size_divisor=32), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ])) evaluation = dict(metric=['bbox', 'segm'], classwise=True, save_best='auto') optimizer = dict( type='AdamW', lr=0.0001, weight_decay=0.05, constructor='CustomLayerDecayOptimizerConstructor', paramwise_cfg=dict( num_layers=30, layer_decay_rate=1.0, depths=[4, 4, 18, 4])) 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, max_keep_ckpts=1, save_last=True) log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')]) custom_hooks = [dict(type='NumClassCheckHook')] dist_params = dict(backend='nccl') log_level = 'INFO' load_from = None resume_from = None workflow = [('train', 1)] pretrained = '/mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_t_1k_224_nosmx/ckpt_epoch_ema_best.pth' work_dir = './work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco' auto_resume = False gpu_ids = range(0, 8) 2023-11-13 16:22:37,120 - mmdet - INFO - Set random seed to 2045030018, deterministic: False 2023-11-13 16:22:37,121 - mmdet - INFO - using core type: FlashDCNv3 2023-11-13 16:22:37,121 - mmdet - INFO - using activation layer: GELU 2023-11-13 16:22:37,121 - mmdet - INFO - using main norm layer: LN 2023-11-13 16:22:37,121 - mmdet - INFO - using dpr: linear, 0.2 2023-11-13 16:22:37,121 - mmdet - INFO - level2_post_norm: False 2023-11-13 16:22:37,121 - mmdet - INFO - level2_post_norm_block_ids: None 2023-11-13 16:22:37,121 - mmdet - INFO - res_post_norm: False 2023-11-13 16:22:37,792 - mmdet - INFO - load checkpoint from local path: /mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_t_1k_224_nosmx/ckpt_epoch_ema_best.pth 2023-11-13 16:22:39,000 - mmdet - INFO - _IncompatibleKeys(missing_keys=['levels.0.blocks.0.gamma1', 'levels.0.blocks.0.gamma2', 'levels.0.blocks.1.gamma1', 'levels.0.blocks.1.gamma2', 'levels.0.blocks.2.gamma1', 'levels.0.blocks.2.gamma2', 'levels.0.blocks.3.gamma1', 'levels.0.blocks.3.gamma2', 'levels.1.blocks.0.gamma1', 'levels.1.blocks.0.gamma2', 'levels.1.blocks.1.gamma1', 'levels.1.blocks.1.gamma2', 'levels.1.blocks.2.gamma1', 'levels.1.blocks.2.gamma2', 'levels.1.blocks.3.gamma1', 'levels.1.blocks.3.gamma2', 'levels.2.blocks.0.gamma1', 'levels.2.blocks.0.gamma2', 'levels.2.blocks.1.gamma1', 'levels.2.blocks.1.gamma2', 'levels.2.blocks.2.gamma1', 'levels.2.blocks.2.gamma2', 'levels.2.blocks.3.gamma1', 'levels.2.blocks.3.gamma2', 'levels.2.blocks.4.gamma1', 'levels.2.blocks.4.gamma2', 'levels.2.blocks.5.gamma1', 'levels.2.blocks.5.gamma2', 'levels.2.blocks.6.gamma1', 'levels.2.blocks.6.gamma2', 'levels.2.blocks.7.gamma1', 'levels.2.blocks.7.gamma2', 'levels.2.blocks.8.gamma1', 'levels.2.blocks.8.gamma2', 'levels.2.blocks.9.gamma1', 'levels.2.blocks.9.gamma2', 'levels.2.blocks.10.gamma1', 'levels.2.blocks.10.gamma2', 'levels.2.blocks.11.gamma1', 'levels.2.blocks.11.gamma2', 'levels.2.blocks.12.gamma1', 'levels.2.blocks.12.gamma2', 'levels.2.blocks.13.gamma1', 'levels.2.blocks.13.gamma2', 'levels.2.blocks.14.gamma1', 'levels.2.blocks.14.gamma2', 'levels.2.blocks.15.gamma1', 'levels.2.blocks.15.gamma2', 'levels.2.blocks.16.gamma1', 'levels.2.blocks.16.gamma2', 'levels.2.blocks.17.gamma1', 'levels.2.blocks.17.gamma2', 'levels.3.blocks.0.gamma1', 'levels.3.blocks.0.gamma2', 'levels.3.blocks.1.gamma1', 'levels.3.blocks.1.gamma2', 'levels.3.blocks.2.gamma1', 'levels.3.blocks.2.gamma2', 'levels.3.blocks.3.gamma1', 'levels.3.blocks.3.gamma2'], unexpected_keys=['conv_head.0.weight', 'conv_head.1.0.weight', 'conv_head.1.0.bias', 'conv_head.1.0.running_mean', 'conv_head.1.0.running_var', 'conv_head.1.0.num_batches_tracked', 'head.weight', 'head.bias']) 2023-11-13 16:22:39,017 - mmdet - INFO - initialize FPN_vitdet with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'} 2023-11-13 16:22:39,033 - mmdet - INFO - initialize RPNHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01} 2023-11-13 16:22:39,037 - 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.patch_embed.conv1.weight - torch.Size([32, 3, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv1.bias - torch.Size([32]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.weight - torch.Size([32]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.bias - torch.Size([32]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.weight - torch.Size([64, 32, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.gamma1 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.0.gamma2 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.0.norm1.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm1.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.weight - torch.Size([108, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.bias - torch.Size([108]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.output_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.weight - torch.Size([256, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc2.weight - torch.Size([64, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.gamma1 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.1.gamma2 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.1.norm1.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm1.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.weight - torch.Size([108, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.bias - torch.Size([108]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.output_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.weight - torch.Size([256, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc2.weight - torch.Size([64, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.gamma1 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.2.gamma2 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.2.norm1.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm1.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.weight - torch.Size([108, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.bias - torch.Size([108]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.output_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.weight - torch.Size([256, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc2.weight - torch.Size([64, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.gamma1 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.3.gamma2 - torch.Size([64]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.0.blocks.3.norm1.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm1.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.weight - torch.Size([108, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.bias - torch.Size([108]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.output_proj.weight - torch.Size([64, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.weight - torch.Size([256, 64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc2.weight - torch.Size([64, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.norm.0.weight - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.norm.0.bias - torch.Size([64]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.conv.weight - torch.Size([128, 64, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.gamma1 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.0.gamma2 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.0.norm1.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm1.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.weight - torch.Size([216, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.bias - torch.Size([216]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.output_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.weight - torch.Size([512, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc2.weight - torch.Size([128, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.gamma1 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.1.gamma2 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.1.norm1.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm1.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.weight - torch.Size([216, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.bias - torch.Size([216]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.output_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.weight - torch.Size([512, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc2.weight - torch.Size([128, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.gamma1 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.2.gamma2 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.2.norm1.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm1.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.weight - torch.Size([216, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.bias - torch.Size([216]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.output_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.weight - torch.Size([512, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc2.weight - torch.Size([128, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.gamma1 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.3.gamma2 - torch.Size([128]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.1.blocks.3.norm1.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm1.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.weight - torch.Size([216, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.bias - torch.Size([216]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.output_proj.weight - torch.Size([128, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.weight - torch.Size([512, 128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc2.weight - torch.Size([128, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.norm.0.weight - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.norm.0.bias - torch.Size([128]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.conv.weight - torch.Size([256, 128, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.0.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.0.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.1.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.1.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.2.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.2.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.3.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.3.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.4.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.4.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.5.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.5.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.6.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.6.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.7.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.7.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.8.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.8.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.9.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.9.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.10.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.10.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.11.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.11.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.12.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.12.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.13.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.13.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.14.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.14.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.15.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.15.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.16.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.16.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.gamma1 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.17.gamma2 - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.2.blocks.17.norm1.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm1.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.weight - torch.Size([432, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.bias - torch.Size([432]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.output_proj.weight - torch.Size([256, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.weight - torch.Size([1024, 256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc2.weight - torch.Size([256, 1024]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.norm.0.weight - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.norm.0.bias - torch.Size([256]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.conv.weight - torch.Size([512, 256, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.gamma1 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.0.gamma2 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.0.norm1.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm1.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.weight - torch.Size([864, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.bias - torch.Size([864]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.output_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.weight - torch.Size([2048, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc2.weight - torch.Size([512, 2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.gamma1 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.1.gamma2 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.1.norm1.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm1.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.weight - torch.Size([864, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.bias - torch.Size([864]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.output_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.weight - torch.Size([2048, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc2.weight - torch.Size([512, 2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.gamma1 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.2.gamma2 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.2.norm1.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm1.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.weight - torch.Size([864, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.bias - torch.Size([864]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.output_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.weight - torch.Size([2048, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc2.weight - torch.Size([512, 2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.gamma1 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.3.gamma2 - torch.Size([512]): The value is the same before and after calling `init_weights` of MaskRCNN backbone.levels.3.blocks.3.norm1.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm1.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.weight - torch.Size([864, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.bias - torch.Size([864]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.output_proj.weight - torch.Size([512, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.weight - torch.Size([2048, 512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc2.weight - torch.Size([512, 2048]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.norm.0.weight - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.norm.0.bias - torch.Size([512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx neck.lateral_convs.0.conv.weight - torch.Size([256, 64, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.0.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.0.ln.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, 128, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.1.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.1.ln.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, 256, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.2.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.2.ln.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, 512, 1, 1]): XavierInit: gain=1, distribution=uniform, bias=0 neck.lateral_convs.3.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.lateral_convs.3.ln.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.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.0.ln.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.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.1.ln.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.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.2.ln.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.ln.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MaskRCNN neck.fpn_convs.3.ln.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 2023-11-13 16:22:57,911 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled. 2023-11-13 16:22:57,911 - mmdet - INFO - {'num_layers': 30, 'layer_decay_rate': 1.0, 'depths': [4, 4, 18, 4]} 2023-11-13 16:22:57,911 - mmdet - INFO - Build CustomLayerDecayOptimizerConstructor 1.000000 - 32 2023-11-13 16:22:57,914 - mmdet - INFO - Param groups = { "layer_0_decay": { "param_names": [ "backbone.patch_embed.conv1.weight", "backbone.patch_embed.conv2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_0_no_decay": { "param_names": [ "backbone.patch_embed.conv1.bias", "backbone.patch_embed.norm1.1.weight", "backbone.patch_embed.norm1.1.bias", "backbone.patch_embed.conv2.bias", "backbone.patch_embed.norm2.1.weight", "backbone.patch_embed.norm2.1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_1_no_decay": { "param_names": [ "backbone.levels.0.blocks.0.gamma1", "backbone.levels.0.blocks.0.gamma2", "backbone.levels.0.blocks.0.norm1.0.weight", "backbone.levels.0.blocks.0.norm1.0.bias", "backbone.levels.0.blocks.0.dcn.offset_mask.bias", "backbone.levels.0.blocks.0.dcn.value_proj.bias", "backbone.levels.0.blocks.0.norm2.0.weight", "backbone.levels.0.blocks.0.norm2.0.bias", "backbone.levels.0.blocks.0.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_1_decay": { "param_names": [ "backbone.levels.0.blocks.0.dcn.offset_mask.weight", "backbone.levels.0.blocks.0.dcn.value_proj.weight", "backbone.levels.0.blocks.0.dcn.output_proj.weight", "backbone.levels.0.blocks.0.mlp.fc1.weight", "backbone.levels.0.blocks.0.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_2_no_decay": { "param_names": [ "backbone.levels.0.blocks.1.gamma1", "backbone.levels.0.blocks.1.gamma2", "backbone.levels.0.blocks.1.norm1.0.weight", "backbone.levels.0.blocks.1.norm1.0.bias", "backbone.levels.0.blocks.1.dcn.offset_mask.bias", "backbone.levels.0.blocks.1.dcn.value_proj.bias", "backbone.levels.0.blocks.1.norm2.0.weight", "backbone.levels.0.blocks.1.norm2.0.bias", "backbone.levels.0.blocks.1.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_2_decay": { "param_names": [ "backbone.levels.0.blocks.1.dcn.offset_mask.weight", "backbone.levels.0.blocks.1.dcn.value_proj.weight", "backbone.levels.0.blocks.1.dcn.output_proj.weight", "backbone.levels.0.blocks.1.mlp.fc1.weight", "backbone.levels.0.blocks.1.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_3_no_decay": { "param_names": [ "backbone.levels.0.blocks.2.gamma1", "backbone.levels.0.blocks.2.gamma2", "backbone.levels.0.blocks.2.norm1.0.weight", "backbone.levels.0.blocks.2.norm1.0.bias", "backbone.levels.0.blocks.2.dcn.offset_mask.bias", "backbone.levels.0.blocks.2.dcn.value_proj.bias", "backbone.levels.0.blocks.2.norm2.0.weight", "backbone.levels.0.blocks.2.norm2.0.bias", "backbone.levels.0.blocks.2.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_3_decay": { "param_names": [ "backbone.levels.0.blocks.2.dcn.offset_mask.weight", "backbone.levels.0.blocks.2.dcn.value_proj.weight", "backbone.levels.0.blocks.2.dcn.output_proj.weight", "backbone.levels.0.blocks.2.mlp.fc1.weight", "backbone.levels.0.blocks.2.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_4_no_decay": { "param_names": [ "backbone.levels.0.blocks.3.gamma1", "backbone.levels.0.blocks.3.gamma2", "backbone.levels.0.blocks.3.norm1.0.weight", "backbone.levels.0.blocks.3.norm1.0.bias", "backbone.levels.0.blocks.3.dcn.offset_mask.bias", "backbone.levels.0.blocks.3.dcn.value_proj.bias", "backbone.levels.0.blocks.3.norm2.0.weight", "backbone.levels.0.blocks.3.norm2.0.bias", "backbone.levels.0.blocks.3.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_4_decay": { "param_names": [ "backbone.levels.0.blocks.3.dcn.offset_mask.weight", "backbone.levels.0.blocks.3.dcn.value_proj.weight", "backbone.levels.0.blocks.3.dcn.output_proj.weight", "backbone.levels.0.blocks.3.mlp.fc1.weight", "backbone.levels.0.blocks.3.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_5_no_decay": { "param_names": [ "backbone.levels.0.norm.0.weight", "backbone.levels.0.norm.0.bias", "backbone.levels.0.downsample.norm.1.weight", "backbone.levels.0.downsample.norm.1.bias", "backbone.levels.1.blocks.0.gamma1", "backbone.levels.1.blocks.0.gamma2", "backbone.levels.1.blocks.0.norm1.0.weight", "backbone.levels.1.blocks.0.norm1.0.bias", "backbone.levels.1.blocks.0.dcn.offset_mask.bias", "backbone.levels.1.blocks.0.dcn.value_proj.bias", "backbone.levels.1.blocks.0.norm2.0.weight", "backbone.levels.1.blocks.0.norm2.0.bias", "backbone.levels.1.blocks.0.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_5_decay": { "param_names": [ "backbone.levels.0.downsample.conv.weight", "backbone.levels.1.blocks.0.dcn.offset_mask.weight", "backbone.levels.1.blocks.0.dcn.value_proj.weight", "backbone.levels.1.blocks.0.dcn.output_proj.weight", "backbone.levels.1.blocks.0.mlp.fc1.weight", "backbone.levels.1.blocks.0.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_6_no_decay": { "param_names": [ "backbone.levels.1.blocks.1.gamma1", "backbone.levels.1.blocks.1.gamma2", "backbone.levels.1.blocks.1.norm1.0.weight", "backbone.levels.1.blocks.1.norm1.0.bias", "backbone.levels.1.blocks.1.dcn.offset_mask.bias", "backbone.levels.1.blocks.1.dcn.value_proj.bias", "backbone.levels.1.blocks.1.norm2.0.weight", "backbone.levels.1.blocks.1.norm2.0.bias", "backbone.levels.1.blocks.1.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_6_decay": { "param_names": [ "backbone.levels.1.blocks.1.dcn.offset_mask.weight", "backbone.levels.1.blocks.1.dcn.value_proj.weight", "backbone.levels.1.blocks.1.dcn.output_proj.weight", "backbone.levels.1.blocks.1.mlp.fc1.weight", "backbone.levels.1.blocks.1.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_7_no_decay": { "param_names": [ "backbone.levels.1.blocks.2.gamma1", "backbone.levels.1.blocks.2.gamma2", "backbone.levels.1.blocks.2.norm1.0.weight", "backbone.levels.1.blocks.2.norm1.0.bias", "backbone.levels.1.blocks.2.dcn.offset_mask.bias", "backbone.levels.1.blocks.2.dcn.value_proj.bias", "backbone.levels.1.blocks.2.norm2.0.weight", "backbone.levels.1.blocks.2.norm2.0.bias", "backbone.levels.1.blocks.2.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_7_decay": { "param_names": [ "backbone.levels.1.blocks.2.dcn.offset_mask.weight", "backbone.levels.1.blocks.2.dcn.value_proj.weight", "backbone.levels.1.blocks.2.dcn.output_proj.weight", "backbone.levels.1.blocks.2.mlp.fc1.weight", "backbone.levels.1.blocks.2.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_8_no_decay": { "param_names": [ "backbone.levels.1.blocks.3.gamma1", "backbone.levels.1.blocks.3.gamma2", "backbone.levels.1.blocks.3.norm1.0.weight", "backbone.levels.1.blocks.3.norm1.0.bias", 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{ "param_names": [ "backbone.levels.3.blocks.3.gamma1", "backbone.levels.3.blocks.3.gamma2", "backbone.levels.3.blocks.3.norm1.0.weight", "backbone.levels.3.blocks.3.norm1.0.bias", "backbone.levels.3.blocks.3.dcn.offset_mask.bias", "backbone.levels.3.blocks.3.dcn.value_proj.bias", "backbone.levels.3.blocks.3.norm2.0.weight", "backbone.levels.3.blocks.3.norm2.0.bias", "backbone.levels.3.blocks.3.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_30_decay": { "param_names": [ "backbone.levels.3.blocks.3.dcn.offset_mask.weight", "backbone.levels.3.blocks.3.dcn.value_proj.weight", "backbone.levels.3.blocks.3.dcn.output_proj.weight", "backbone.levels.3.blocks.3.mlp.fc1.weight", "backbone.levels.3.blocks.3.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_31_decay": { "param_names": [ "neck.lateral_convs.0.conv.weight", "neck.lateral_convs.1.conv.weight", "neck.lateral_convs.2.conv.weight", "neck.lateral_convs.3.conv.weight", "neck.fpn_convs.0.conv.weight", "neck.fpn_convs.1.conv.weight", "neck.fpn_convs.2.conv.weight", "neck.fpn_convs.3.conv.weight", "rpn_head.rpn_conv.weight", "rpn_head.rpn_cls.weight", "rpn_head.rpn_reg.weight", "roi_head.bbox_head.fc_cls.weight", "roi_head.bbox_head.fc_reg.weight", "roi_head.bbox_head.shared_fcs.0.weight", "roi_head.bbox_head.shared_fcs.1.weight", "roi_head.mask_head.convs.0.conv.weight", "roi_head.mask_head.convs.1.conv.weight", "roi_head.mask_head.convs.2.conv.weight", "roi_head.mask_head.convs.3.conv.weight", "roi_head.mask_head.upsample.weight", "roi_head.mask_head.conv_logits.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_31_no_decay": { "param_names": [ "neck.lateral_convs.0.ln.weight", "neck.lateral_convs.0.ln.bias", "neck.lateral_convs.1.ln.weight", "neck.lateral_convs.1.ln.bias", "neck.lateral_convs.2.ln.weight", "neck.lateral_convs.2.ln.bias", "neck.lateral_convs.3.ln.weight", "neck.lateral_convs.3.ln.bias", "neck.fpn_convs.0.ln.weight", "neck.fpn_convs.0.ln.bias", "neck.fpn_convs.1.ln.weight", "neck.fpn_convs.1.ln.bias", "neck.fpn_convs.2.ln.weight", "neck.fpn_convs.2.ln.bias", "neck.fpn_convs.3.ln.weight", "neck.fpn_convs.3.ln.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 } } 2023-11-13 16:22:58,423 - mmdet - INFO - Start running, host: lizhiqi@SH-IDC1-10-140-37-115, work_dir: /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco 2023-11-13 16:22:58,423 - mmdet - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) StepLrUpdaterHook (NORMAL ) CheckpointHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_epoch: (VERY_HIGH ) StepLrUpdaterHook (NORMAL ) NumClassCheckHook (NORMAL ) DistSamplerSeedHook (LOW ) IterTimerHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_iter: (VERY_HIGH ) StepLrUpdaterHook (LOW ) IterTimerHook (LOW ) DistEvalHook -------------------- after_train_iter: (ABOVE_NORMAL) OptimizerHook (NORMAL ) CheckpointHook (LOW ) IterTimerHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- after_train_epoch: (NORMAL ) CheckpointHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_val_epoch: (NORMAL ) NumClassCheckHook (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 -------------------- 2023-11-13 16:22:58,424 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs 2023-11-13 16:22:58,424 - mmdet - INFO - Checkpoints will be saved to /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco by HardDiskBackend. 2023-11-13 16:23:27,928 - mmdet - INFO - Epoch [1][50/7330] lr: 9.890e-06, eta: 14:24:21, time: 0.590, data_time: 0.083, memory: 3193, loss_rpn_cls: 0.6569, loss_rpn_bbox: 0.1060, loss_cls: 2.9206, acc: 74.2358, loss_bbox: 0.0347, loss_mask: 0.7849, loss: 4.5031 2023-11-13 16:23:44,706 - mmdet - INFO - Epoch [1][100/7330] lr: 1.988e-05, eta: 11:17:33, time: 0.335, data_time: 0.034, memory: 3453, loss_rpn_cls: 0.4788, loss_rpn_bbox: 0.1049, loss_cls: 0.4128, acc: 95.3284, loss_bbox: 0.1425, loss_mask: 0.7026, loss: 1.8416 2023-11-13 16:24:01,290 - mmdet - INFO - Epoch [1][150/7330] lr: 2.987e-05, eta: 10:13:15, time: 0.332, data_time: 0.030, memory: 3527, loss_rpn_cls: 0.2928, loss_rpn_bbox: 0.1030, loss_cls: 0.3895, acc: 94.4141, loss_bbox: 0.1837, loss_mask: 0.6751, loss: 1.6441 2023-11-13 16:24:17,867 - mmdet - INFO - Epoch [1][200/7330] lr: 3.986e-05, eta: 9:40:54, time: 0.332, data_time: 0.034, memory: 3652, loss_rpn_cls: 0.2208, loss_rpn_bbox: 0.0959, loss_cls: 0.4227, acc: 93.4265, loss_bbox: 0.2290, loss_mask: 0.6484, loss: 1.6168 2023-11-13 16:24:33,676 - mmdet - INFO - Epoch [1][250/7330] lr: 4.985e-05, eta: 9:16:53, time: 0.316, data_time: 0.028, memory: 3688, loss_rpn_cls: 0.1616, loss_rpn_bbox: 0.0932, loss_cls: 0.4430, acc: 92.7290, loss_bbox: 0.2602, loss_mask: 0.6207, loss: 1.5788 2023-11-13 16:24:50,761 - mmdet - INFO - Epoch [1][300/7330] lr: 5.984e-05, eta: 9:07:00, time: 0.342, data_time: 0.026, memory: 3741, loss_rpn_cls: 0.1166, loss_rpn_bbox: 0.0952, loss_cls: 0.4809, acc: 91.5679, loss_bbox: 0.3095, loss_mask: 0.5806, loss: 1.5829 2023-11-13 16:25:06,607 - mmdet - INFO - Epoch [1][350/7330] lr: 6.983e-05, eta: 8:54:42, time: 0.317, data_time: 0.030, memory: 3867, loss_rpn_cls: 0.0957, loss_rpn_bbox: 0.0870, loss_cls: 0.5350, acc: 90.4604, loss_bbox: 0.3631, loss_mask: 0.5466, loss: 1.6274 2023-11-13 16:25:22,566 - mmdet - INFO - Epoch [1][400/7330] lr: 7.982e-05, eta: 8:45:49, time: 0.319, data_time: 0.030, memory: 3867, loss_rpn_cls: 0.0874, loss_rpn_bbox: 0.0893, loss_cls: 0.5170, acc: 90.0815, loss_bbox: 0.3750, loss_mask: 0.4953, loss: 1.5639 2023-11-13 16:25:38,777 - mmdet - INFO - Epoch [1][450/7330] lr: 8.981e-05, eta: 8:39:39, time: 0.324, data_time: 0.029, memory: 3876, loss_rpn_cls: 0.0782, loss_rpn_bbox: 0.0882, loss_cls: 0.5107, acc: 89.6553, loss_bbox: 0.3889, loss_mask: 0.4693, loss: 1.5353 2023-11-13 16:25:54,366 - mmdet - INFO - Epoch [1][500/7330] lr: 9.980e-05, eta: 8:32:52, time: 0.312, data_time: 0.021, memory: 3899, loss_rpn_cls: 0.0817, loss_rpn_bbox: 0.0818, loss_cls: 0.4766, acc: 89.8367, loss_bbox: 0.3750, loss_mask: 0.4508, loss: 1.4660 2023-11-13 16:26:10,966 - mmdet - INFO - Epoch [1][550/7330] lr: 1.000e-04, eta: 8:29:57, time: 0.332, data_time: 0.027, memory: 3899, loss_rpn_cls: 0.0787, loss_rpn_bbox: 0.0867, loss_cls: 0.4587, acc: 89.3381, loss_bbox: 0.3791, loss_mask: 0.4286, loss: 1.4318 2023-11-13 16:26:26,732 - mmdet - INFO - Epoch [1][600/7330] lr: 1.000e-04, eta: 8:25:27, time: 0.315, data_time: 0.030, memory: 3899, loss_rpn_cls: 0.0732, loss_rpn_bbox: 0.0815, loss_cls: 0.4483, acc: 88.9304, loss_bbox: 0.3889, loss_mask: 0.4170, loss: 1.4090 2023-11-13 16:26:42,658 - mmdet - INFO - Epoch [1][650/7330] lr: 1.000e-04, eta: 8:21:57, time: 0.318, data_time: 0.027, memory: 3899, loss_rpn_cls: 0.0655, loss_rpn_bbox: 0.0786, loss_cls: 0.4119, acc: 89.4470, loss_bbox: 0.3705, loss_mask: 0.4018, loss: 1.3284 2023-11-13 16:26:57,851 - mmdet - INFO - Epoch [1][700/7330] lr: 1.000e-04, eta: 8:17:24, time: 0.304, data_time: 0.025, memory: 3899, loss_rpn_cls: 0.0650, loss_rpn_bbox: 0.0752, loss_cls: 0.3963, acc: 89.3887, loss_bbox: 0.3651, loss_mask: 0.3941, loss: 1.2958 2023-11-13 16:27:13,617 - mmdet - INFO - Epoch [1][750/7330] lr: 1.000e-04, eta: 8:14:31, time: 0.315, data_time: 0.026, memory: 3899, loss_rpn_cls: 0.0627, loss_rpn_bbox: 0.0743, loss_cls: 0.3853, acc: 89.4729, loss_bbox: 0.3675, loss_mask: 0.3827, loss: 1.2726 2023-11-13 16:27:29,061 - mmdet - INFO - Epoch [1][800/7330] lr: 1.000e-04, eta: 8:11:23, time: 0.309, data_time: 0.020, memory: 3899, loss_rpn_cls: 0.0629, loss_rpn_bbox: 0.0747, loss_cls: 0.3733, acc: 89.8008, loss_bbox: 0.3515, loss_mask: 0.3835, loss: 1.2459 2023-11-13 16:27:44,799 - mmdet - INFO - Epoch [1][850/7330] lr: 1.000e-04, eta: 8:09:06, time: 0.315, data_time: 0.024, memory: 3899, loss_rpn_cls: 0.0625, loss_rpn_bbox: 0.0701, loss_cls: 0.3692, acc: 89.4922, loss_bbox: 0.3681, loss_mask: 0.3777, loss: 1.2476 2023-11-13 16:28:01,291 - mmdet - INFO - Epoch [1][900/7330] lr: 1.000e-04, eta: 8:08:15, time: 0.330, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0591, loss_rpn_bbox: 0.0745, loss_cls: 0.3403, acc: 90.1621, loss_bbox: 0.3443, loss_mask: 0.3735, loss: 1.1916 2023-11-13 16:28:17,054 - mmdet - INFO - Epoch [1][950/7330] lr: 1.000e-04, eta: 8:06:21, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0630, loss_rpn_bbox: 0.0739, loss_cls: 0.3484, acc: 89.7002, loss_bbox: 0.3619, loss_mask: 0.3585, loss: 1.2057 2023-11-13 16:28:32,054 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:28:32,054 - mmdet - INFO - Epoch [1][1000/7330] lr: 1.000e-04, eta: 8:03:30, time: 0.300, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0585, loss_rpn_bbox: 0.0726, loss_cls: 0.3458, acc: 89.8040, loss_bbox: 0.3572, loss_mask: 0.3564, loss: 1.1904 2023-11-13 16:28:47,243 - mmdet - INFO - Epoch [1][1050/7330] lr: 1.000e-04, eta: 8:01:10, time: 0.304, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0553, loss_rpn_bbox: 0.0706, loss_cls: 0.3419, acc: 89.8857, loss_bbox: 0.3489, loss_mask: 0.3499, loss: 1.1665 2023-11-13 16:29:02,449 - mmdet - INFO - Epoch [1][1100/7330] lr: 1.000e-04, eta: 7:59:02, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0554, loss_rpn_bbox: 0.0705, loss_cls: 0.3276, acc: 90.2358, loss_bbox: 0.3396, loss_mask: 0.3417, loss: 1.1348 2023-11-13 16:29:18,110 - mmdet - INFO - Epoch [1][1150/7330] lr: 1.000e-04, eta: 7:57:39, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0589, loss_rpn_bbox: 0.0737, loss_cls: 0.3350, acc: 89.8560, loss_bbox: 0.3471, loss_mask: 0.3454, loss: 1.1600 2023-11-13 16:29:33,488 - mmdet - INFO - Epoch [1][1200/7330] lr: 1.000e-04, eta: 7:56:01, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0567, loss_rpn_bbox: 0.0694, loss_cls: 0.3295, acc: 89.9717, loss_bbox: 0.3429, loss_mask: 0.3401, loss: 1.1386 2023-11-13 16:29:49,019 - mmdet - INFO - Epoch [1][1250/7330] lr: 1.000e-04, eta: 7:54:40, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0517, loss_rpn_bbox: 0.0683, loss_cls: 0.3335, acc: 89.9402, loss_bbox: 0.3420, loss_mask: 0.3444, loss: 1.1399 2023-11-13 16:30:04,138 - mmdet - INFO - Epoch [1][1300/7330] lr: 1.000e-04, eta: 7:52:57, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0527, loss_rpn_bbox: 0.0677, loss_cls: 0.3186, acc: 90.1965, loss_bbox: 0.3359, loss_mask: 0.3367, loss: 1.1116 2023-11-13 16:30:19,379 - mmdet - INFO - Epoch [1][1350/7330] lr: 1.000e-04, eta: 7:51:28, time: 0.305, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0497, loss_rpn_bbox: 0.0685, loss_cls: 0.3119, acc: 90.3154, loss_bbox: 0.3310, loss_mask: 0.3299, loss: 1.0911 2023-11-13 16:30:35,468 - mmdet - INFO - Epoch [1][1400/7330] lr: 1.000e-04, eta: 7:50:56, time: 0.322, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0570, loss_rpn_bbox: 0.0704, loss_cls: 0.3144, acc: 90.1501, loss_bbox: 0.3317, loss_mask: 0.3362, loss: 1.1097 2023-11-13 16:30:50,795 - mmdet - INFO - Epoch [1][1450/7330] lr: 1.000e-04, eta: 7:49:41, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0554, loss_rpn_bbox: 0.0682, loss_cls: 0.3148, acc: 90.4282, loss_bbox: 0.3215, loss_mask: 0.3236, loss: 1.0835 2023-11-13 16:31:06,102 - mmdet - INFO - Epoch [1][1500/7330] lr: 1.000e-04, eta: 7:48:28, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0528, loss_rpn_bbox: 0.0649, loss_cls: 0.2997, acc: 90.5977, loss_bbox: 0.3244, loss_mask: 0.3225, loss: 1.0643 2023-11-13 16:31:21,755 - mmdet - INFO - Epoch [1][1550/7330] lr: 1.000e-04, eta: 7:47:38, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0555, loss_rpn_bbox: 0.0714, loss_cls: 0.3194, acc: 89.9380, loss_bbox: 0.3383, loss_mask: 0.3238, loss: 1.1084 2023-11-13 16:31:37,411 - mmdet - INFO - Epoch [1][1600/7330] lr: 1.000e-04, eta: 7:46:50, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0511, loss_rpn_bbox: 0.0648, loss_cls: 0.2992, acc: 90.6956, loss_bbox: 0.3143, loss_mask: 0.3233, loss: 1.0527 2023-11-13 16:31:52,596 - mmdet - INFO - Epoch [1][1650/7330] lr: 1.000e-04, eta: 7:45:40, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0499, loss_rpn_bbox: 0.0672, loss_cls: 0.2911, acc: 90.8850, loss_bbox: 0.3138, loss_mask: 0.3237, loss: 1.0457 2023-11-13 16:32:08,103 - mmdet - INFO - Epoch [1][1700/7330] lr: 1.000e-04, eta: 7:44:49, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0544, loss_rpn_bbox: 0.0691, loss_cls: 0.3018, acc: 90.2947, loss_bbox: 0.3357, loss_mask: 0.3238, loss: 1.0848 2023-11-13 16:32:23,625 - mmdet - INFO - Epoch [1][1750/7330] lr: 1.000e-04, eta: 7:44:01, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0571, loss_rpn_bbox: 0.0659, loss_cls: 0.3011, acc: 90.4272, loss_bbox: 0.3262, loss_mask: 0.3232, loss: 1.0735 2023-11-13 16:32:39,173 - mmdet - INFO - Epoch [1][1800/7330] lr: 1.000e-04, eta: 7:43:17, time: 0.311, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0559, loss_rpn_bbox: 0.0683, loss_cls: 0.2933, acc: 90.5415, loss_bbox: 0.3228, loss_mask: 0.3161, loss: 1.0565 2023-11-13 16:32:54,523 - mmdet - INFO - Epoch [1][1850/7330] lr: 1.000e-04, eta: 7:42:24, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0509, loss_rpn_bbox: 0.0668, loss_cls: 0.3010, acc: 90.4568, loss_bbox: 0.3256, loss_mask: 0.3148, loss: 1.0592 2023-11-13 16:33:09,902 - mmdet - INFO - Epoch [1][1900/7330] lr: 1.000e-04, eta: 7:41:35, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0510, loss_rpn_bbox: 0.0669, loss_cls: 0.3002, acc: 90.3875, loss_bbox: 0.3254, loss_mask: 0.3158, loss: 1.0593 2023-11-13 16:33:25,712 - mmdet - INFO - Epoch [1][1950/7330] lr: 1.000e-04, eta: 7:41:06, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0521, loss_rpn_bbox: 0.0667, loss_cls: 0.2896, acc: 90.5542, loss_bbox: 0.3189, loss_mask: 0.3169, loss: 1.0443 2023-11-13 16:33:41,073 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:33:41,074 - mmdet - INFO - Epoch [1][2000/7330] lr: 1.000e-04, eta: 7:40:19, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0482, loss_rpn_bbox: 0.0622, loss_cls: 0.2837, acc: 90.8025, loss_bbox: 0.3127, loss_mask: 0.3111, loss: 1.0179 2023-11-13 16:33:56,682 - mmdet - INFO - Epoch [1][2050/7330] lr: 1.000e-04, eta: 7:39:44, time: 0.312, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0455, loss_rpn_bbox: 0.0618, loss_cls: 0.2764, acc: 90.9202, loss_bbox: 0.3111, loss_mask: 0.3129, loss: 1.0077 2023-11-13 16:34:12,292 - mmdet - INFO - Epoch [1][2100/7330] lr: 1.000e-04, eta: 7:39:10, time: 0.312, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0481, loss_rpn_bbox: 0.0636, loss_cls: 0.2873, acc: 90.6436, loss_bbox: 0.3165, loss_mask: 0.3079, loss: 1.0234 2023-11-13 16:34:27,990 - mmdet - INFO - Epoch [1][2150/7330] lr: 1.000e-04, eta: 7:38:40, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0482, loss_rpn_bbox: 0.0655, loss_cls: 0.2935, acc: 90.3538, loss_bbox: 0.3254, loss_mask: 0.3128, loss: 1.0455 2023-11-13 16:34:43,288 - mmdet - INFO - Epoch [1][2200/7330] lr: 1.000e-04, eta: 7:37:55, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0498, loss_rpn_bbox: 0.0647, loss_cls: 0.3030, acc: 90.2581, loss_bbox: 0.3211, loss_mask: 0.3091, loss: 1.0478 2023-11-13 16:34:58,997 - mmdet - INFO - Epoch [1][2250/7330] lr: 1.000e-04, eta: 7:37:27, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0510, loss_rpn_bbox: 0.0697, loss_cls: 0.2972, acc: 90.4326, loss_bbox: 0.3245, loss_mask: 0.3125, loss: 1.0549 2023-11-13 16:35:14,495 - mmdet - INFO - Epoch [1][2300/7330] lr: 1.000e-04, eta: 7:36:52, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0491, loss_rpn_bbox: 0.0620, loss_cls: 0.2888, acc: 90.6838, loss_bbox: 0.3107, loss_mask: 0.3069, loss: 1.0175 2023-11-13 16:35:29,860 - mmdet - INFO - Epoch [1][2350/7330] lr: 1.000e-04, eta: 7:36:13, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0614, loss_cls: 0.2888, acc: 90.6655, loss_bbox: 0.3101, loss_mask: 0.3085, loss: 1.0173 2023-11-13 16:35:45,127 - mmdet - INFO - Epoch [1][2400/7330] lr: 1.000e-04, eta: 7:35:31, time: 0.305, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0472, loss_rpn_bbox: 0.0636, loss_cls: 0.2824, acc: 90.7603, loss_bbox: 0.3114, loss_mask: 0.3091, loss: 1.0137 2023-11-13 16:36:00,584 - mmdet - INFO - Epoch [1][2450/7330] lr: 1.000e-04, eta: 7:34:57, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0489, loss_rpn_bbox: 0.0630, loss_cls: 0.2878, acc: 90.6211, loss_bbox: 0.3156, loss_mask: 0.3064, loss: 1.0218 2023-11-13 16:36:16,006 - mmdet - INFO - Epoch [1][2500/7330] lr: 1.000e-04, eta: 7:34:23, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0469, loss_rpn_bbox: 0.0629, loss_cls: 0.2795, acc: 90.9521, loss_bbox: 0.3025, loss_mask: 0.3037, loss: 0.9956 2023-11-13 16:36:31,373 - mmdet - INFO - Epoch [1][2550/7330] lr: 1.000e-04, eta: 7:33:47, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0633, loss_cls: 0.2896, acc: 90.5435, loss_bbox: 0.3166, loss_mask: 0.3001, loss: 1.0184 2023-11-13 16:36:46,285 - mmdet - INFO - Epoch [1][2600/7330] lr: 1.000e-04, eta: 7:32:58, time: 0.298, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0620, loss_cls: 0.2769, acc: 90.9480, loss_bbox: 0.3070, loss_mask: 0.2961, loss: 0.9864 2023-11-13 16:37:01,462 - mmdet - INFO - Epoch [1][2650/7330] lr: 1.000e-04, eta: 7:32:18, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0462, loss_rpn_bbox: 0.0617, loss_cls: 0.2818, acc: 90.8008, loss_bbox: 0.3104, loss_mask: 0.3031, loss: 1.0032 2023-11-13 16:37:17,021 - mmdet - INFO - Epoch [1][2700/7330] lr: 1.000e-04, eta: 7:31:51, time: 0.311, data_time: 0.033, memory: 3904, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0647, loss_cls: 0.2840, acc: 90.6311, loss_bbox: 0.3167, loss_mask: 0.3032, loss: 1.0173 2023-11-13 16:37:31,954 - mmdet - INFO - Epoch [1][2750/7330] lr: 1.000e-04, eta: 7:31:05, time: 0.299, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0462, loss_rpn_bbox: 0.0629, loss_cls: 0.2786, acc: 90.9600, loss_bbox: 0.2982, loss_mask: 0.3011, loss: 0.9869 2023-11-13 16:37:47,054 - mmdet - INFO - Epoch [1][2800/7330] lr: 1.000e-04, eta: 7:30:25, time: 0.302, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0433, loss_rpn_bbox: 0.0596, loss_cls: 0.2765, acc: 90.9592, loss_bbox: 0.3083, loss_mask: 0.3007, loss: 0.9884 2023-11-13 16:38:02,541 - mmdet - INFO - Epoch [1][2850/7330] lr: 1.000e-04, eta: 7:29:58, time: 0.310, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0484, loss_rpn_bbox: 0.0594, loss_cls: 0.2692, acc: 91.1306, loss_bbox: 0.3011, loss_mask: 0.3008, loss: 0.9791 2023-11-13 16:38:17,896 - mmdet - INFO - Epoch [1][2900/7330] lr: 1.000e-04, eta: 7:29:27, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0497, loss_rpn_bbox: 0.0630, loss_cls: 0.2723, acc: 91.0078, loss_bbox: 0.3020, loss_mask: 0.3018, loss: 0.9888 2023-11-13 16:38:32,990 - mmdet - INFO - Epoch [1][2950/7330] lr: 1.000e-04, eta: 7:28:50, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0418, loss_rpn_bbox: 0.0606, loss_cls: 0.2787, acc: 90.6826, loss_bbox: 0.3132, loss_mask: 0.2893, loss: 0.9836 2023-11-13 16:38:48,278 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:38:48,278 - mmdet - INFO - Epoch [1][3000/7330] lr: 1.000e-04, eta: 7:28:18, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0466, loss_rpn_bbox: 0.0645, loss_cls: 0.2809, acc: 90.7371, loss_bbox: 0.3147, loss_mask: 0.2928, loss: 0.9995 2023-11-13 16:39:03,533 - mmdet - INFO - Epoch [1][3050/7330] lr: 1.000e-04, eta: 7:27:46, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0425, loss_rpn_bbox: 0.0602, loss_cls: 0.2690, acc: 90.8528, loss_bbox: 0.3052, loss_mask: 0.3015, loss: 0.9783 2023-11-13 16:39:19,023 - mmdet - INFO - Epoch [1][3100/7330] lr: 1.000e-04, eta: 7:27:22, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0439, loss_rpn_bbox: 0.0584, loss_cls: 0.2693, acc: 91.0076, loss_bbox: 0.3045, loss_mask: 0.3026, loss: 0.9787 2023-11-13 16:39:34,389 - mmdet - INFO - Epoch [1][3150/7330] lr: 1.000e-04, eta: 7:26:54, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0466, loss_rpn_bbox: 0.0600, loss_cls: 0.2635, acc: 91.2695, loss_bbox: 0.2924, loss_mask: 0.2917, loss: 0.9543 2023-11-13 16:39:49,273 - mmdet - INFO - Epoch [1][3200/7330] lr: 1.000e-04, eta: 7:26:13, time: 0.298, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0434, loss_rpn_bbox: 0.0569, loss_cls: 0.2622, acc: 91.3398, loss_bbox: 0.2920, loss_mask: 0.2904, loss: 0.9448 2023-11-13 16:40:04,638 - mmdet - INFO - Epoch [1][3250/7330] lr: 1.000e-04, eta: 7:25:46, time: 0.307, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0448, loss_rpn_bbox: 0.0558, loss_cls: 0.2691, acc: 91.0750, loss_bbox: 0.2985, loss_mask: 0.2903, loss: 0.9586 2023-11-13 16:40:20,245 - mmdet - INFO - Epoch [1][3300/7330] lr: 1.000e-04, eta: 7:25:26, time: 0.312, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0605, loss_cls: 0.2658, acc: 91.1313, loss_bbox: 0.2973, loss_mask: 0.2955, loss: 0.9635 2023-11-13 16:40:35,389 - mmdet - INFO - Epoch [1][3350/7330] lr: 1.000e-04, eta: 7:24:54, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0460, loss_rpn_bbox: 0.0615, loss_cls: 0.2748, acc: 90.9377, loss_bbox: 0.3008, loss_mask: 0.2948, loss: 0.9779 2023-11-13 16:40:51,565 - mmdet - INFO - Epoch [1][3400/7330] lr: 1.000e-04, eta: 7:24:48, time: 0.324, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0451, loss_rpn_bbox: 0.0621, loss_cls: 0.2811, acc: 90.7642, loss_bbox: 0.3082, loss_mask: 0.2994, loss: 0.9959 2023-11-13 16:41:07,247 - mmdet - INFO - Epoch [1][3450/7330] lr: 1.000e-04, eta: 7:24:30, time: 0.314, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0590, loss_cls: 0.2758, acc: 90.8777, loss_bbox: 0.3042, loss_mask: 0.2911, loss: 0.9716 2023-11-13 16:41:22,653 - mmdet - INFO - Epoch [1][3500/7330] lr: 1.000e-04, eta: 7:24:05, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0462, loss_rpn_bbox: 0.0594, loss_cls: 0.2712, acc: 90.9355, loss_bbox: 0.3074, loss_mask: 0.2896, loss: 0.9738 2023-11-13 16:41:38,028 - mmdet - INFO - Epoch [1][3550/7330] lr: 1.000e-04, eta: 7:23:40, time: 0.307, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0580, loss_cls: 0.2729, acc: 91.0203, loss_bbox: 0.3011, loss_mask: 0.2885, loss: 0.9621 2023-11-13 16:41:53,319 - mmdet - INFO - Epoch [1][3600/7330] lr: 1.000e-04, eta: 7:23:13, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0575, loss_cls: 0.2650, acc: 91.1306, loss_bbox: 0.2966, loss_mask: 0.2916, loss: 0.9537 2023-11-13 16:42:08,546 - mmdet - INFO - Epoch [1][3650/7330] lr: 1.000e-04, eta: 7:22:45, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0449, loss_rpn_bbox: 0.0601, loss_cls: 0.2587, acc: 91.2776, loss_bbox: 0.2911, loss_mask: 0.2852, loss: 0.9401 2023-11-13 16:42:23,569 - mmdet - INFO - Epoch [1][3700/7330] lr: 1.000e-04, eta: 7:22:12, time: 0.300, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0394, loss_rpn_bbox: 0.0564, loss_cls: 0.2538, acc: 91.4846, loss_bbox: 0.2865, loss_mask: 0.2817, loss: 0.9178 2023-11-13 16:42:39,035 - mmdet - INFO - Epoch [1][3750/7330] lr: 1.000e-04, eta: 7:21:50, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0447, loss_rpn_bbox: 0.0603, loss_cls: 0.2700, acc: 91.0271, loss_bbox: 0.3018, loss_mask: 0.2908, loss: 0.9676 2023-11-13 16:42:54,540 - mmdet - INFO - Epoch [1][3800/7330] lr: 1.000e-04, eta: 7:21:29, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0594, loss_cls: 0.2756, acc: 90.8970, loss_bbox: 0.3030, loss_mask: 0.2872, loss: 0.9688 2023-11-13 16:43:09,964 - mmdet - INFO - Epoch [1][3850/7330] lr: 1.000e-04, eta: 7:21:07, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0565, loss_cls: 0.2572, acc: 91.5493, loss_bbox: 0.2843, loss_mask: 0.2916, loss: 0.9322 2023-11-13 16:43:25,275 - mmdet - INFO - Epoch [1][3900/7330] lr: 1.000e-04, eta: 7:20:42, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0609, loss_cls: 0.2653, acc: 91.0081, loss_bbox: 0.3023, loss_mask: 0.2851, loss: 0.9541 2023-11-13 16:43:40,465 - mmdet - INFO - Epoch [1][3950/7330] lr: 1.000e-04, eta: 7:20:15, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0424, loss_rpn_bbox: 0.0566, loss_cls: 0.2572, acc: 91.5769, loss_bbox: 0.2805, loss_mask: 0.2782, loss: 0.9149 2023-11-13 16:43:56,143 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:43:56,143 - mmdet - INFO - Epoch [1][4000/7330] lr: 1.000e-04, eta: 7:19:58, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0437, loss_rpn_bbox: 0.0598, loss_cls: 0.2563, acc: 91.4514, loss_bbox: 0.2905, loss_mask: 0.2799, loss: 0.9302 2023-11-13 16:44:11,543 - mmdet - INFO - Epoch [1][4050/7330] lr: 1.000e-04, eta: 7:19:36, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0400, loss_rpn_bbox: 0.0545, loss_cls: 0.2477, acc: 91.6362, loss_bbox: 0.2823, loss_mask: 0.2856, loss: 0.9100 2023-11-13 16:44:27,053 - mmdet - INFO - Epoch [1][4100/7330] lr: 1.000e-04, eta: 7:19:16, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0596, loss_cls: 0.2658, acc: 91.1619, loss_bbox: 0.2956, loss_mask: 0.2870, loss: 0.9510 2023-11-13 16:44:42,936 - mmdet - INFO - Epoch [1][4150/7330] lr: 1.000e-04, eta: 7:19:03, time: 0.318, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0453, loss_rpn_bbox: 0.0614, loss_cls: 0.2734, acc: 90.8621, loss_bbox: 0.3100, loss_mask: 0.2942, loss: 0.9843 2023-11-13 16:44:57,866 - mmdet - INFO - Epoch [1][4200/7330] lr: 1.000e-04, eta: 7:18:32, time: 0.299, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0534, loss_cls: 0.2513, acc: 91.6401, loss_bbox: 0.2843, loss_mask: 0.2779, loss: 0.9071 2023-11-13 16:45:13,187 - mmdet - INFO - Epoch [1][4250/7330] lr: 1.000e-04, eta: 7:18:09, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0413, loss_rpn_bbox: 0.0534, loss_cls: 0.2544, acc: 91.7346, loss_bbox: 0.2824, loss_mask: 0.2813, loss: 0.9129 2023-11-13 16:45:28,157 - mmdet - INFO - Epoch [1][4300/7330] lr: 1.000e-04, eta: 7:17:39, time: 0.299, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0392, loss_rpn_bbox: 0.0553, loss_cls: 0.2511, acc: 91.6753, loss_bbox: 0.2841, loss_mask: 0.2828, loss: 0.9125 2023-11-13 16:45:43,572 - mmdet - INFO - Epoch [1][4350/7330] lr: 1.000e-04, eta: 7:17:18, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0428, loss_rpn_bbox: 0.0586, loss_cls: 0.2701, acc: 90.8906, loss_bbox: 0.3096, loss_mask: 0.2836, loss: 0.9648 2023-11-13 16:45:59,218 - mmdet - INFO - Epoch [1][4400/7330] lr: 1.000e-04, eta: 7:17:01, time: 0.313, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0601, loss_cls: 0.2789, acc: 90.8230, loss_bbox: 0.3017, loss_mask: 0.2878, loss: 0.9686 2023-11-13 16:46:14,220 - mmdet - INFO - Epoch [1][4450/7330] lr: 1.000e-04, eta: 7:16:33, time: 0.300, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0385, loss_rpn_bbox: 0.0569, loss_cls: 0.2573, acc: 91.3745, loss_bbox: 0.2858, loss_mask: 0.2835, loss: 0.9220 2023-11-13 16:46:29,499 - mmdet - INFO - Epoch [1][4500/7330] lr: 1.000e-04, eta: 7:16:09, time: 0.306, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0414, loss_rpn_bbox: 0.0583, loss_cls: 0.2536, acc: 91.5625, loss_bbox: 0.2871, loss_mask: 0.2814, loss: 0.9218 2023-11-13 16:46:44,967 - mmdet - INFO - Epoch [1][4550/7330] lr: 1.000e-04, eta: 7:15:50, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0425, loss_rpn_bbox: 0.0591, loss_cls: 0.2601, acc: 91.2480, loss_bbox: 0.2968, loss_mask: 0.2823, loss: 0.9407 2023-11-13 16:46:59,992 - mmdet - INFO - Epoch [1][4600/7330] lr: 1.000e-04, eta: 7:15:22, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0574, loss_cls: 0.2689, acc: 91.1030, loss_bbox: 0.2909, loss_mask: 0.2803, loss: 0.9405 2023-11-13 16:47:15,586 - mmdet - INFO - Epoch [1][4650/7330] lr: 1.000e-04, eta: 7:15:05, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0588, loss_cls: 0.2638, acc: 91.0955, loss_bbox: 0.3009, loss_mask: 0.2873, loss: 0.9537 2023-11-13 16:47:30,784 - mmdet - INFO - Epoch [1][4700/7330] lr: 1.000e-04, eta: 7:14:41, time: 0.304, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0394, loss_rpn_bbox: 0.0548, loss_cls: 0.2518, acc: 91.5859, loss_bbox: 0.2836, loss_mask: 0.2796, loss: 0.9092 2023-11-13 16:47:46,118 - mmdet - INFO - Epoch [1][4750/7330] lr: 1.000e-04, eta: 7:14:20, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0364, loss_rpn_bbox: 0.0540, loss_cls: 0.2449, acc: 91.7039, loss_bbox: 0.2751, loss_mask: 0.2754, loss: 0.8858 2023-11-13 16:48:01,938 - mmdet - INFO - Epoch [1][4800/7330] lr: 1.000e-04, eta: 7:14:07, time: 0.316, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0593, loss_cls: 0.2677, acc: 91.0801, loss_bbox: 0.2963, loss_mask: 0.2792, loss: 0.9439 2023-11-13 16:48:17,237 - mmdet - INFO - Epoch [1][4850/7330] lr: 1.000e-04, eta: 7:13:45, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0394, loss_rpn_bbox: 0.0574, loss_cls: 0.2570, acc: 91.4739, loss_bbox: 0.2877, loss_mask: 0.2805, loss: 0.9220 2023-11-13 16:48:32,678 - mmdet - INFO - Epoch [1][4900/7330] lr: 1.000e-04, eta: 7:13:26, time: 0.309, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0565, loss_cls: 0.2486, acc: 91.6917, loss_bbox: 0.2841, loss_mask: 0.2755, loss: 0.9060 2023-11-13 16:48:47,894 - mmdet - INFO - Epoch [1][4950/7330] lr: 1.000e-04, eta: 7:13:03, time: 0.304, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0408, loss_rpn_bbox: 0.0539, loss_cls: 0.2488, acc: 91.5930, loss_bbox: 0.2816, loss_mask: 0.2725, loss: 0.8976 2023-11-13 16:49:03,457 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:49:03,458 - mmdet - INFO - Epoch [1][5000/7330] lr: 1.000e-04, eta: 7:12:46, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0561, loss_cls: 0.2562, acc: 91.4692, loss_bbox: 0.2888, loss_mask: 0.2756, loss: 0.9182 2023-11-13 16:49:18,686 - mmdet - INFO - Epoch [1][5050/7330] lr: 1.000e-04, eta: 7:12:23, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0582, loss_cls: 0.2580, acc: 91.2698, loss_bbox: 0.2965, loss_mask: 0.2857, loss: 0.9365 2023-11-13 16:49:33,868 - mmdet - INFO - Epoch [1][5100/7330] lr: 1.000e-04, eta: 7:12:00, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0562, loss_cls: 0.2572, acc: 91.5571, loss_bbox: 0.2836, loss_mask: 0.2809, loss: 0.9193 2023-11-13 16:49:49,182 - mmdet - INFO - Epoch [1][5150/7330] lr: 1.000e-04, eta: 7:11:39, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0416, loss_rpn_bbox: 0.0569, loss_cls: 0.2509, acc: 91.5088, loss_bbox: 0.2851, loss_mask: 0.2827, loss: 0.9173 2023-11-13 16:50:04,183 - mmdet - INFO - Epoch [1][5200/7330] lr: 1.000e-04, eta: 7:11:13, time: 0.300, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0451, loss_rpn_bbox: 0.0574, loss_cls: 0.2548, acc: 91.4727, loss_bbox: 0.2899, loss_mask: 0.2735, loss: 0.9207 2023-11-13 16:50:19,128 - mmdet - INFO - Epoch [1][5250/7330] lr: 1.000e-04, eta: 7:10:47, time: 0.299, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0544, loss_cls: 0.2526, acc: 91.4888, loss_bbox: 0.2870, loss_mask: 0.2749, loss: 0.9109 2023-11-13 16:50:34,455 - mmdet - INFO - Epoch [1][5300/7330] lr: 1.000e-04, eta: 7:10:27, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0422, loss_rpn_bbox: 0.0559, loss_cls: 0.2542, acc: 91.3877, loss_bbox: 0.2930, loss_mask: 0.2770, loss: 0.9223 2023-11-13 16:50:49,986 - mmdet - INFO - Epoch [1][5350/7330] lr: 1.000e-04, eta: 7:10:09, time: 0.311, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0416, loss_rpn_bbox: 0.0573, loss_cls: 0.2534, acc: 91.3750, loss_bbox: 0.2915, loss_mask: 0.2787, loss: 0.9226 2023-11-13 16:51:04,656 - mmdet - INFO - Epoch [1][5400/7330] lr: 1.000e-04, eta: 7:09:39, time: 0.293, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0544, loss_cls: 0.2523, acc: 91.3279, loss_bbox: 0.2911, loss_mask: 0.2791, loss: 0.9148 2023-11-13 16:51:19,885 - mmdet - INFO - Epoch [1][5450/7330] lr: 1.000e-04, eta: 7:09:18, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0556, loss_cls: 0.2580, acc: 91.1262, loss_bbox: 0.2955, loss_mask: 0.2795, loss: 0.9267 2023-11-13 16:51:34,772 - mmdet - INFO - Epoch [1][5500/7330] lr: 1.000e-04, eta: 7:08:51, time: 0.298, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0536, loss_cls: 0.2441, acc: 91.7405, loss_bbox: 0.2828, loss_mask: 0.2685, loss: 0.8872 2023-11-13 16:51:49,819 - mmdet - INFO - Epoch [1][5550/7330] lr: 1.000e-04, eta: 7:08:28, time: 0.301, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0541, loss_cls: 0.2580, acc: 91.3281, loss_bbox: 0.2895, loss_mask: 0.2808, loss: 0.9237 2023-11-13 16:52:05,679 - mmdet - INFO - Epoch [1][5600/7330] lr: 1.000e-04, eta: 7:08:16, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0586, loss_cls: 0.2570, acc: 91.2053, loss_bbox: 0.2917, loss_mask: 0.2786, loss: 0.9275 2023-11-13 16:52:20,545 - mmdet - INFO - Epoch [1][5650/7330] lr: 1.000e-04, eta: 7:07:50, time: 0.297, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0539, loss_cls: 0.2475, acc: 91.6646, loss_bbox: 0.2796, loss_mask: 0.2769, loss: 0.8999 2023-11-13 16:52:35,702 - mmdet - INFO - Epoch [1][5700/7330] lr: 1.000e-04, eta: 7:07:28, time: 0.303, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0555, loss_cls: 0.2508, acc: 91.4041, loss_bbox: 0.2883, loss_mask: 0.2719, loss: 0.9080 2023-11-13 16:52:51,039 - mmdet - INFO - Epoch [1][5750/7330] lr: 1.000e-04, eta: 7:07:08, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0433, loss_rpn_bbox: 0.0568, loss_cls: 0.2535, acc: 91.5178, loss_bbox: 0.2834, loss_mask: 0.2741, loss: 0.9111 2023-11-13 16:53:05,507 - mmdet - INFO - Epoch [1][5800/7330] lr: 1.000e-04, eta: 7:06:37, time: 0.289, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0504, loss_cls: 0.2335, acc: 92.1123, loss_bbox: 0.2687, loss_mask: 0.2703, loss: 0.8564 2023-11-13 16:53:21,021 - mmdet - INFO - Epoch [1][5850/7330] lr: 1.000e-04, eta: 7:06:20, time: 0.310, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0552, loss_cls: 0.2433, acc: 91.8525, loss_bbox: 0.2761, loss_mask: 0.2823, loss: 0.8983 2023-11-13 16:53:36,212 - mmdet - INFO - Epoch [1][5900/7330] lr: 1.000e-04, eta: 7:06:00, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0535, loss_cls: 0.2397, acc: 91.8303, loss_bbox: 0.2768, loss_mask: 0.2673, loss: 0.8750 2023-11-13 16:53:51,082 - mmdet - INFO - Epoch [1][5950/7330] lr: 1.000e-04, eta: 7:05:34, time: 0.297, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0521, loss_cls: 0.2551, acc: 91.4778, loss_bbox: 0.2836, loss_mask: 0.2786, loss: 0.9096 2023-11-13 16:54:06,332 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:54:06,332 - mmdet - INFO - Epoch [1][6000/7330] lr: 1.000e-04, eta: 7:05:14, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0540, loss_cls: 0.2495, acc: 91.4143, loss_bbox: 0.2838, loss_mask: 0.2788, loss: 0.9040 2023-11-13 16:54:21,783 - mmdet - INFO - Epoch [1][6050/7330] lr: 1.000e-04, eta: 7:04:57, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0389, loss_rpn_bbox: 0.0577, loss_cls: 0.2605, acc: 91.1011, loss_bbox: 0.2984, loss_mask: 0.2778, loss: 0.9332 2023-11-13 16:54:36,891 - mmdet - INFO - Epoch [1][6100/7330] lr: 1.000e-04, eta: 7:04:36, time: 0.302, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0542, loss_cls: 0.2522, acc: 91.3591, loss_bbox: 0.2921, loss_mask: 0.2825, loss: 0.9215 2023-11-13 16:54:52,002 - mmdet - INFO - Epoch [1][6150/7330] lr: 1.000e-04, eta: 7:04:14, time: 0.302, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0552, loss_cls: 0.2443, acc: 91.5940, loss_bbox: 0.2862, loss_mask: 0.2743, loss: 0.9002 2023-11-13 16:55:07,252 - mmdet - INFO - Epoch [1][6200/7330] lr: 1.000e-04, eta: 7:03:54, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0533, loss_cls: 0.2445, acc: 91.7605, loss_bbox: 0.2819, loss_mask: 0.2759, loss: 0.8954 2023-11-13 16:55:22,499 - mmdet - INFO - Epoch [1][6250/7330] lr: 1.000e-04, eta: 7:03:35, time: 0.305, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0384, loss_rpn_bbox: 0.0528, loss_cls: 0.2439, acc: 91.5762, loss_bbox: 0.2823, loss_mask: 0.2732, loss: 0.8905 2023-11-13 16:55:37,643 - mmdet - INFO - Epoch [1][6300/7330] lr: 1.000e-04, eta: 7:03:14, time: 0.303, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0538, loss_cls: 0.2444, acc: 91.6045, loss_bbox: 0.2770, loss_mask: 0.2723, loss: 0.8842 2023-11-13 16:55:52,977 - mmdet - INFO - Epoch [1][6350/7330] lr: 1.000e-04, eta: 7:02:56, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0398, loss_rpn_bbox: 0.0538, loss_cls: 0.2426, acc: 91.9316, loss_bbox: 0.2692, loss_mask: 0.2714, loss: 0.8769 2023-11-13 16:56:08,503 - mmdet - INFO - Epoch [1][6400/7330] lr: 1.000e-04, eta: 7:02:40, time: 0.311, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0552, loss_cls: 0.2515, acc: 91.3931, loss_bbox: 0.2844, loss_mask: 0.2736, loss: 0.9045 2023-11-13 16:56:24,146 - mmdet - INFO - Epoch [1][6450/7330] lr: 1.000e-04, eta: 7:02:25, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0424, loss_rpn_bbox: 0.0578, loss_cls: 0.2459, acc: 91.5425, loss_bbox: 0.2836, loss_mask: 0.2759, loss: 0.9057 2023-11-13 16:56:39,679 - mmdet - INFO - Epoch [1][6500/7330] lr: 1.000e-04, eta: 7:02:10, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0419, loss_rpn_bbox: 0.0592, loss_cls: 0.2529, acc: 91.3215, loss_bbox: 0.2916, loss_mask: 0.2782, loss: 0.9238 2023-11-13 16:56:54,802 - mmdet - INFO - Epoch [1][6550/7330] lr: 1.000e-04, eta: 7:01:49, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0520, loss_cls: 0.2400, acc: 91.8728, loss_bbox: 0.2680, loss_mask: 0.2625, loss: 0.8604 2023-11-13 16:57:10,126 - mmdet - INFO - Epoch [1][6600/7330] lr: 1.000e-04, eta: 7:01:31, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0410, loss_rpn_bbox: 0.0546, loss_cls: 0.2479, acc: 91.5696, loss_bbox: 0.2825, loss_mask: 0.2718, loss: 0.8978 2023-11-13 16:57:25,377 - mmdet - INFO - Epoch [1][6650/7330] lr: 1.000e-04, eta: 7:01:12, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0550, loss_cls: 0.2462, acc: 91.7063, loss_bbox: 0.2784, loss_mask: 0.2722, loss: 0.8938 2023-11-13 16:57:40,288 - mmdet - INFO - Epoch [1][6700/7330] lr: 1.000e-04, eta: 7:00:48, time: 0.298, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0387, loss_rpn_bbox: 0.0511, loss_cls: 0.2324, acc: 92.2898, loss_bbox: 0.2569, loss_mask: 0.2635, loss: 0.8426 2023-11-13 16:57:55,331 - mmdet - INFO - Epoch [1][6750/7330] lr: 1.000e-04, eta: 7:00:27, time: 0.301, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0396, loss_rpn_bbox: 0.0527, loss_cls: 0.2389, acc: 91.7783, loss_bbox: 0.2739, loss_mask: 0.2730, loss: 0.8781 2023-11-13 16:58:10,819 - mmdet - INFO - Epoch [1][6800/7330] lr: 1.000e-04, eta: 7:00:11, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0547, loss_cls: 0.2436, acc: 91.7625, loss_bbox: 0.2796, loss_mask: 0.2708, loss: 0.8870 2023-11-13 16:58:26,094 - mmdet - INFO - Epoch [1][6850/7330] lr: 1.000e-04, eta: 6:59:52, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0356, loss_rpn_bbox: 0.0526, loss_cls: 0.2318, acc: 92.1194, loss_bbox: 0.2701, loss_mask: 0.2681, loss: 0.8582 2023-11-13 16:58:41,294 - mmdet - INFO - Epoch [1][6900/7330] lr: 1.000e-04, eta: 6:59:33, time: 0.304, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0542, loss_cls: 0.2495, acc: 91.6089, loss_bbox: 0.2768, loss_mask: 0.2734, loss: 0.8966 2023-11-13 16:58:56,574 - mmdet - INFO - Epoch [1][6950/7330] lr: 1.000e-04, eta: 6:59:14, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0541, loss_cls: 0.2433, acc: 91.5811, loss_bbox: 0.2801, loss_mask: 0.2721, loss: 0.8877 2023-11-13 16:59:11,357 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 16:59:11,357 - mmdet - INFO - Epoch [1][7000/7330] lr: 1.000e-04, eta: 6:58:50, time: 0.296, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0497, loss_cls: 0.2273, acc: 92.3652, loss_bbox: 0.2637, loss_mask: 0.2673, loss: 0.8427 2023-11-13 16:59:26,649 - mmdet - INFO - Epoch [1][7050/7330] lr: 1.000e-04, eta: 6:58:32, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0533, loss_cls: 0.2443, acc: 91.6497, loss_bbox: 0.2848, loss_mask: 0.2692, loss: 0.8900 2023-11-13 16:59:41,483 - mmdet - INFO - Epoch [1][7100/7330] lr: 1.000e-04, eta: 6:58:09, time: 0.297, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0518, loss_cls: 0.2359, acc: 92.2559, loss_bbox: 0.2652, loss_mask: 0.2685, loss: 0.8565 2023-11-13 16:59:57,337 - mmdet - INFO - Epoch [1][7150/7330] lr: 1.000e-04, eta: 6:57:57, time: 0.317, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0418, loss_rpn_bbox: 0.0563, loss_cls: 0.2422, acc: 91.7249, loss_bbox: 0.2767, loss_mask: 0.2706, loss: 0.8876 2023-11-13 17:00:12,742 - mmdet - INFO - Epoch [1][7200/7330] lr: 1.000e-04, eta: 6:57:40, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0388, loss_rpn_bbox: 0.0543, loss_cls: 0.2422, acc: 91.7002, loss_bbox: 0.2826, loss_mask: 0.2719, loss: 0.8899 2023-11-13 17:00:28,088 - mmdet - INFO - Epoch [1][7250/7330] lr: 1.000e-04, eta: 6:57:23, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0524, loss_cls: 0.2351, acc: 91.9697, loss_bbox: 0.2714, loss_mask: 0.2735, loss: 0.8696 2023-11-13 17:00:43,683 - mmdet - INFO - Epoch [1][7300/7330] lr: 1.000e-04, eta: 6:57:08, time: 0.312, data_time: 0.036, memory: 3904, loss_rpn_cls: 0.0406, loss_rpn_bbox: 0.0535, loss_cls: 0.2388, acc: 91.8345, loss_bbox: 0.2722, loss_mask: 0.2716, loss: 0.8767 2023-11-13 17:00:53,070 - mmdet - INFO - Saving checkpoint at 1 epochs 2023-11-13 17:01:44,104 - mmdet - INFO - Evaluating bbox... 2023-11-13 17:02:18,415 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.360 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.596 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.388 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.224 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.401 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.473 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.507 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.507 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.507 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.645 2023-11-13 17:02:18,418 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.510 | bicycle | 0.253 | car | 0.407 | | motorcycle | 0.363 | airplane | 0.544 | bus | 0.589 | | train | 0.559 | truck | 0.309 | boat | 0.234 | | traffic light | 0.245 | fire hydrant | 0.586 | stop sign | 0.562 | | parking meter | 0.401 | bench | 0.206 | bird | 0.343 | | cat | 0.629 | dog | 0.617 | horse | 0.517 | | sheep | 0.483 | cow | 0.535 | elephant | 0.593 | | bear | 0.665 | zebra | 0.588 | giraffe | 0.590 | | backpack | 0.120 | umbrella | 0.343 | handbag | 0.116 | | tie | 0.243 | suitcase | 0.299 | frisbee | 0.616 | | skis | 0.171 | snowboard | 0.213 | sports ball | 0.414 | | kite | 0.370 | baseball bat | 0.238 | baseball glove | 0.352 | | skateboard | 0.434 | surfboard | 0.290 | tennis racket | 0.406 | | bottle | 0.357 | wine glass | 0.286 | cup | 0.397 | | fork | 0.235 | knife | 0.146 | spoon | 0.130 | | bowl | 0.386 | banana | 0.204 | apple | 0.160 | | sandwich | 0.323 | orange | 0.292 | broccoli | 0.211 | | carrot | 0.193 | hot dog | 0.291 | pizza | 0.469 | | donut | 0.415 | cake | 0.338 | chair | 0.256 | | couch | 0.357 | potted plant | 0.200 | bed | 0.369 | | dining table | 0.204 | toilet | 0.511 | tv | 0.517 | | laptop | 0.527 | mouse | 0.541 | remote | 0.236 | | keyboard | 0.446 | cell phone | 0.338 | microwave | 0.516 | | oven | 0.282 | toaster | 0.207 | sink | 0.317 | | refrigerator | 0.501 | book | 0.120 | clock | 0.455 | | vase | 0.306 | scissors | 0.238 | teddy bear | 0.387 | | hair drier | 0.082 | toothbrush | 0.130 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:02:18,418 - mmdet - INFO - Evaluating segm... 2023-11-13 17:02:59,996 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.342 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.564 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.361 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.167 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.375 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.476 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.476 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.476 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.287 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 ] = 0.628 2023-11-13 17:02:59,999 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.443 | bicycle | 0.159 | car | 0.381 | | motorcycle | 0.284 | airplane | 0.455 | bus | 0.605 | | train | 0.578 | truck | 0.326 | boat | 0.213 | | traffic light | 0.238 | fire hydrant | 0.621 | stop sign | 0.607 | | parking meter | 0.456 | bench | 0.148 | bird | 0.300 | | cat | 0.667 | dog | 0.593 | horse | 0.376 | | sheep | 0.443 | cow | 0.448 | elephant | 0.518 | | bear | 0.691 | zebra | 0.507 | giraffe | 0.446 | | backpack | 0.137 | umbrella | 0.432 | handbag | 0.135 | | tie | 0.247 | suitcase | 0.345 | frisbee | 0.613 | | skis | 0.010 | snowboard | 0.164 | sports ball | 0.426 | | kite | 0.282 | baseball bat | 0.177 | baseball glove | 0.389 | | skateboard | 0.257 | surfboard | 0.255 | tennis racket | 0.507 | | bottle | 0.348 | wine glass | 0.271 | cup | 0.412 | | fork | 0.111 | knife | 0.091 | spoon | 0.088 | | bowl | 0.372 | banana | 0.157 | apple | 0.170 | | sandwich | 0.355 | orange | 0.308 | broccoli | 0.202 | | carrot | 0.165 | hot dog | 0.244 | pizza | 0.467 | | donut | 0.440 | cake | 0.358 | chair | 0.174 | | couch | 0.326 | potted plant | 0.184 | bed | 0.301 | | dining table | 0.102 | toilet | 0.550 | tv | 0.573 | | laptop | 0.562 | mouse | 0.568 | remote | 0.245 | | keyboard | 0.469 | cell phone | 0.342 | microwave | 0.541 | | oven | 0.274 | toaster | 0.308 | sink | 0.313 | | refrigerator | 0.510 | book | 0.088 | clock | 0.483 | | vase | 0.337 | scissors | 0.161 | teddy bear | 0.406 | | hair drier | 0.019 | toothbrush | 0.101 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:03:01,968 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_1.pth. 2023-11-13 17:03:01,968 - mmdet - INFO - Best bbox_mAP is 0.3604 at 1 epoch. 2023-11-13 17:03:01,968 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 17:03:01,968 - mmdet - INFO - Epoch(val) [1][625] bbox_mAP: 0.3604, bbox_mAP_50: 0.5963, bbox_mAP_75: 0.3879, bbox_mAP_s: 0.2242, bbox_mAP_m: 0.4010, bbox_mAP_l: 0.4728, bbox_mAP_copypaste: 0.3604 0.5963 0.3879 0.2242 0.4010 0.4728, segm_mAP: 0.3422, segm_mAP_50: 0.5642, segm_mAP_75: 0.3611, segm_mAP_s: 0.1666, segm_mAP_m: 0.3751, segm_mAP_l: 0.5024, segm_mAP_copypaste: 0.3422 0.5642 0.3611 0.1666 0.3751 0.5024 2023-11-13 17:03:21,420 - mmdet - INFO - Epoch [2][50/7330] lr: 1.000e-04, eta: 6:55:45, time: 0.389, data_time: 0.088, memory: 3904, loss_rpn_cls: 0.0353, loss_rpn_bbox: 0.0546, loss_cls: 0.2362, acc: 91.6465, loss_bbox: 0.2860, loss_mask: 0.2702, loss: 0.8824 2023-11-13 17:03:37,401 - mmdet - INFO - Epoch [2][100/7330] lr: 1.000e-04, eta: 6:55:35, time: 0.320, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0509, loss_cls: 0.2349, acc: 91.8616, loss_bbox: 0.2744, loss_mask: 0.2715, loss: 0.8660 2023-11-13 17:03:53,008 - mmdet - INFO - Epoch [2][150/7330] lr: 1.000e-04, eta: 6:55:21, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0499, loss_cls: 0.2289, acc: 92.0645, loss_bbox: 0.2684, loss_mask: 0.2626, loss: 0.8421 2023-11-13 17:04:08,373 - mmdet - INFO - Epoch [2][200/7330] lr: 1.000e-04, eta: 6:55:04, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0543, loss_cls: 0.2360, acc: 91.8616, loss_bbox: 0.2757, loss_mask: 0.2686, loss: 0.8714 2023-11-13 17:04:23,973 - mmdet - INFO - Epoch [2][250/7330] lr: 1.000e-04, eta: 6:54:50, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0543, loss_cls: 0.2332, acc: 91.8535, loss_bbox: 0.2730, loss_mask: 0.2583, loss: 0.8550 2023-11-13 17:04:39,371 - mmdet - INFO - Epoch [2][300/7330] lr: 1.000e-04, eta: 6:54:33, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0499, loss_cls: 0.2239, acc: 92.2283, loss_bbox: 0.2639, loss_mask: 0.2617, loss: 0.8309 2023-11-13 17:04:54,751 - mmdet - INFO - Epoch [2][350/7330] lr: 1.000e-04, eta: 6:54:17, time: 0.308, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0515, loss_cls: 0.2219, acc: 92.2876, loss_bbox: 0.2619, loss_mask: 0.2622, loss: 0.8299 2023-11-13 17:05:10,368 - mmdet - INFO - Epoch [2][400/7330] lr: 1.000e-04, eta: 6:54:03, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0350, loss_rpn_bbox: 0.0525, loss_cls: 0.2453, acc: 91.5742, loss_bbox: 0.2765, loss_mask: 0.2636, loss: 0.8728 2023-11-13 17:05:25,790 - mmdet - INFO - Epoch [2][450/7330] lr: 1.000e-04, eta: 6:53:46, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0339, loss_rpn_bbox: 0.0512, loss_cls: 0.2318, acc: 92.0547, loss_bbox: 0.2664, loss_mask: 0.2623, loss: 0.8457 2023-11-13 17:05:41,339 - mmdet - INFO - Epoch [2][500/7330] lr: 1.000e-04, eta: 6:53:32, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0529, loss_cls: 0.2324, acc: 91.9934, loss_bbox: 0.2709, loss_mask: 0.2644, loss: 0.8537 2023-11-13 17:05:56,652 - mmdet - INFO - Epoch [2][550/7330] lr: 1.000e-04, eta: 6:53:14, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0507, loss_cls: 0.2261, acc: 92.0957, loss_bbox: 0.2622, loss_mask: 0.2622, loss: 0.8346 2023-11-13 17:06:12,497 - mmdet - INFO - Epoch [2][600/7330] lr: 1.000e-04, eta: 6:53:03, time: 0.317, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0356, loss_rpn_bbox: 0.0551, loss_cls: 0.2373, acc: 91.7544, loss_bbox: 0.2789, loss_mask: 0.2660, loss: 0.8728 2023-11-13 17:06:27,868 - mmdet - INFO - Epoch [2][650/7330] lr: 1.000e-04, eta: 6:52:46, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0507, loss_cls: 0.2332, acc: 92.1106, loss_bbox: 0.2660, loss_mask: 0.2631, loss: 0.8478 2023-11-13 17:06:43,462 - mmdet - INFO - Epoch [2][700/7330] lr: 1.000e-04, eta: 6:52:32, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0503, loss_cls: 0.2266, acc: 92.1526, loss_bbox: 0.2636, loss_mask: 0.2634, loss: 0.8386 2023-11-13 17:06:58,639 - mmdet - INFO - Epoch [2][750/7330] lr: 1.000e-04, eta: 6:52:13, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0530, loss_cls: 0.2283, acc: 92.0720, loss_bbox: 0.2701, loss_mask: 0.2666, loss: 0.8525 2023-11-13 17:07:13,978 - mmdet - INFO - Epoch [2][800/7330] lr: 1.000e-04, eta: 6:51:56, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0357, loss_rpn_bbox: 0.0506, loss_cls: 0.2312, acc: 91.8677, loss_bbox: 0.2799, loss_mask: 0.2675, loss: 0.8649 2023-11-13 17:07:29,327 - mmdet - INFO - Epoch [2][850/7330] lr: 1.000e-04, eta: 6:51:39, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0510, loss_cls: 0.2265, acc: 92.0620, loss_bbox: 0.2664, loss_mask: 0.2614, loss: 0.8383 2023-11-13 17:07:44,768 - mmdet - INFO - Epoch [2][900/7330] lr: 1.000e-04, eta: 6:51:24, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0505, loss_cls: 0.2321, acc: 91.8584, loss_bbox: 0.2749, loss_mask: 0.2651, loss: 0.8564 2023-11-13 17:08:00,117 - mmdet - INFO - Epoch [2][950/7330] lr: 1.000e-04, eta: 6:51:07, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0510, loss_cls: 0.2273, acc: 92.0513, loss_bbox: 0.2690, loss_mask: 0.2561, loss: 0.8371 2023-11-13 17:08:15,442 - mmdet - INFO - Epoch [2][1000/7330] lr: 1.000e-04, eta: 6:50:50, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0507, loss_cls: 0.2257, acc: 92.1169, loss_bbox: 0.2660, loss_mask: 0.2629, loss: 0.8377 2023-11-13 17:08:31,098 - mmdet - INFO - Epoch [2][1050/7330] lr: 1.000e-04, eta: 6:50:36, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0537, loss_cls: 0.2378, acc: 91.7136, loss_bbox: 0.2820, loss_mask: 0.2702, loss: 0.8781 2023-11-13 17:08:46,588 - mmdet - INFO - Epoch [2][1100/7330] lr: 1.000e-04, eta: 6:50:21, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0535, loss_cls: 0.2363, acc: 91.7563, loss_bbox: 0.2791, loss_mask: 0.2644, loss: 0.8710 2023-11-13 17:09:01,954 - mmdet - INFO - Epoch [2][1150/7330] lr: 1.000e-04, eta: 6:50:04, time: 0.307, data_time: 0.017, memory: 3904, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0497, loss_cls: 0.2286, acc: 91.9673, loss_bbox: 0.2737, loss_mask: 0.2561, loss: 0.8390 2023-11-13 17:09:17,656 - mmdet - INFO - Epoch [2][1200/7330] lr: 1.000e-04, eta: 6:49:51, time: 0.314, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0349, loss_rpn_bbox: 0.0521, loss_cls: 0.2358, acc: 91.9597, loss_bbox: 0.2727, loss_mask: 0.2706, loss: 0.8661 2023-11-13 17:09:32,968 - mmdet - INFO - Epoch [2][1250/7330] lr: 1.000e-04, eta: 6:49:34, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0492, loss_cls: 0.2328, acc: 91.9636, loss_bbox: 0.2732, loss_mask: 0.2622, loss: 0.8492 2023-11-13 17:09:48,273 - mmdet - INFO - Epoch [2][1300/7330] lr: 1.000e-04, eta: 6:49:17, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0517, loss_cls: 0.2260, acc: 92.1055, loss_bbox: 0.2667, loss_mask: 0.2624, loss: 0.8407 2023-11-13 17:10:03,899 - mmdet - INFO - Epoch [2][1350/7330] lr: 1.000e-04, eta: 6:49:02, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0372, loss_rpn_bbox: 0.0547, loss_cls: 0.2319, acc: 91.8870, loss_bbox: 0.2749, loss_mask: 0.2629, loss: 0.8616 2023-11-13 17:10:19,673 - mmdet - INFO - Epoch [2][1400/7330] lr: 1.000e-04, eta: 6:48:50, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0538, loss_cls: 0.2292, acc: 92.0894, loss_bbox: 0.2636, loss_mask: 0.2604, loss: 0.8435 2023-11-13 17:10:35,052 - mmdet - INFO - Epoch [2][1450/7330] lr: 1.000e-04, eta: 6:48:33, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0357, loss_rpn_bbox: 0.0540, loss_cls: 0.2368, acc: 91.7805, loss_bbox: 0.2746, loss_mask: 0.2616, loss: 0.8627 2023-11-13 17:10:50,530 - mmdet - INFO - Epoch [2][1500/7330] lr: 1.000e-04, eta: 6:48:18, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0503, loss_cls: 0.2305, acc: 92.0588, loss_bbox: 0.2663, loss_mask: 0.2634, loss: 0.8467 2023-11-13 17:11:06,605 - mmdet - INFO - Epoch [2][1550/7330] lr: 1.000e-04, eta: 6:48:08, time: 0.321, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0536, loss_cls: 0.2315, acc: 91.9985, loss_bbox: 0.2670, loss_mask: 0.2628, loss: 0.8511 2023-11-13 17:11:22,002 - mmdet - INFO - Epoch [2][1600/7330] lr: 1.000e-04, eta: 6:47:51, time: 0.308, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0350, loss_rpn_bbox: 0.0514, loss_cls: 0.2265, acc: 92.0425, loss_bbox: 0.2709, loss_mask: 0.2577, loss: 0.8415 2023-11-13 17:11:37,749 - mmdet - INFO - Epoch [2][1650/7330] lr: 1.000e-04, eta: 6:47:38, time: 0.315, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0503, loss_cls: 0.2317, acc: 91.9509, loss_bbox: 0.2736, loss_mask: 0.2620, loss: 0.8525 2023-11-13 17:11:53,368 - mmdet - INFO - Epoch [2][1700/7330] lr: 1.000e-04, eta: 6:47:24, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0525, loss_cls: 0.2291, acc: 92.0024, loss_bbox: 0.2708, loss_mask: 0.2654, loss: 0.8521 2023-11-13 17:12:09,045 - mmdet - INFO - Epoch [2][1750/7330] lr: 1.000e-04, eta: 6:47:10, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0472, loss_cls: 0.2229, acc: 92.2078, loss_bbox: 0.2625, loss_mask: 0.2540, loss: 0.8158 2023-11-13 17:12:24,616 - mmdet - INFO - Epoch [2][1800/7330] lr: 1.000e-04, eta: 6:46:55, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0521, loss_cls: 0.2274, acc: 92.1055, loss_bbox: 0.2657, loss_mask: 0.2587, loss: 0.8399 2023-11-13 17:12:40,462 - mmdet - INFO - Epoch [2][1850/7330] lr: 1.000e-04, eta: 6:46:43, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0511, loss_cls: 0.2239, acc: 92.2710, loss_bbox: 0.2606, loss_mask: 0.2566, loss: 0.8244 2023-11-13 17:12:55,887 - mmdet - INFO - Epoch [2][1900/7330] lr: 1.000e-04, eta: 6:46:27, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0506, loss_cls: 0.2286, acc: 92.0542, loss_bbox: 0.2653, loss_mask: 0.2628, loss: 0.8422 2023-11-13 17:13:11,047 - mmdet - INFO - Epoch [2][1950/7330] lr: 1.000e-04, eta: 6:46:09, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0496, loss_cls: 0.2213, acc: 92.3269, loss_bbox: 0.2584, loss_mask: 0.2578, loss: 0.8213 2023-11-13 17:13:26,968 - mmdet - INFO - Epoch [2][2000/7330] lr: 1.000e-04, eta: 6:45:57, time: 0.318, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0369, loss_rpn_bbox: 0.0534, loss_cls: 0.2407, acc: 91.5447, loss_bbox: 0.2813, loss_mask: 0.2667, loss: 0.8789 2023-11-13 17:13:42,447 - mmdet - INFO - Epoch [2][2050/7330] lr: 1.000e-04, eta: 6:45:41, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0521, loss_cls: 0.2306, acc: 92.0466, loss_bbox: 0.2662, loss_mask: 0.2563, loss: 0.8374 2023-11-13 17:13:57,637 - mmdet - INFO - Epoch [2][2100/7330] lr: 1.000e-04, eta: 6:45:23, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0509, loss_cls: 0.2274, acc: 92.0449, loss_bbox: 0.2686, loss_mask: 0.2589, loss: 0.8387 2023-11-13 17:14:13,417 - mmdet - INFO - Epoch [2][2150/7330] lr: 1.000e-04, eta: 6:45:10, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0552, loss_cls: 0.2358, acc: 91.9370, loss_bbox: 0.2748, loss_mask: 0.2665, loss: 0.8689 2023-11-13 17:14:28,770 - mmdet - INFO - Epoch [2][2200/7330] lr: 1.000e-04, eta: 6:44:54, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0510, loss_cls: 0.2226, acc: 92.2405, loss_bbox: 0.2673, loss_mask: 0.2613, loss: 0.8351 2023-11-13 17:14:44,135 - mmdet - INFO - Epoch [2][2250/7330] lr: 1.000e-04, eta: 6:44:37, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0525, loss_cls: 0.2296, acc: 92.0100, loss_bbox: 0.2738, loss_mask: 0.2616, loss: 0.8505 2023-11-13 17:14:59,611 - mmdet - INFO - Epoch [2][2300/7330] lr: 1.000e-04, eta: 6:44:21, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0527, loss_cls: 0.2302, acc: 91.9883, loss_bbox: 0.2653, loss_mask: 0.2580, loss: 0.8386 2023-11-13 17:15:14,721 - mmdet - INFO - Epoch [2][2350/7330] lr: 1.000e-04, eta: 6:44:03, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0467, loss_cls: 0.2177, acc: 92.4475, loss_bbox: 0.2581, loss_mask: 0.2526, loss: 0.8047 2023-11-13 17:15:30,374 - mmdet - INFO - Epoch [2][2400/7330] lr: 1.000e-04, eta: 6:43:49, time: 0.313, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0544, loss_cls: 0.2430, acc: 91.5793, loss_bbox: 0.2774, loss_mask: 0.2627, loss: 0.8711 2023-11-13 17:15:46,018 - mmdet - INFO - Epoch [2][2450/7330] lr: 1.000e-04, eta: 6:43:35, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0497, loss_cls: 0.2179, acc: 92.4128, loss_bbox: 0.2552, loss_mask: 0.2601, loss: 0.8165 2023-11-13 17:16:01,094 - mmdet - INFO - Epoch [2][2500/7330] lr: 1.000e-04, eta: 6:43:16, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0487, loss_cls: 0.2118, acc: 92.6821, loss_bbox: 0.2507, loss_mask: 0.2605, loss: 0.8048 2023-11-13 17:16:16,409 - mmdet - INFO - Epoch [2][2550/7330] lr: 1.000e-04, eta: 6:42:59, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0500, loss_cls: 0.2272, acc: 92.1182, loss_bbox: 0.2671, loss_mask: 0.2579, loss: 0.8355 2023-11-13 17:16:32,135 - mmdet - INFO - Epoch [2][2600/7330] lr: 1.000e-04, eta: 6:42:45, time: 0.314, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0550, loss_cls: 0.2264, acc: 92.0339, loss_bbox: 0.2719, loss_mask: 0.2582, loss: 0.8440 2023-11-13 17:16:47,603 - mmdet - INFO - Epoch [2][2650/7330] lr: 1.000e-04, eta: 6:42:30, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0531, loss_cls: 0.2363, acc: 91.8945, loss_bbox: 0.2725, loss_mask: 0.2661, loss: 0.8617 2023-11-13 17:17:02,890 - mmdet - INFO - Epoch [2][2700/7330] lr: 1.000e-04, eta: 6:42:13, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0356, loss_rpn_bbox: 0.0549, loss_cls: 0.2297, acc: 91.9646, loss_bbox: 0.2665, loss_mask: 0.2658, loss: 0.8526 2023-11-13 17:17:18,361 - mmdet - INFO - Epoch [2][2750/7330] lr: 1.000e-04, eta: 6:41:57, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0525, loss_cls: 0.2307, acc: 92.0542, loss_bbox: 0.2703, loss_mask: 0.2606, loss: 0.8495 2023-11-13 17:17:33,856 - mmdet - INFO - Epoch [2][2800/7330] lr: 1.000e-04, eta: 6:41:42, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0528, loss_cls: 0.2332, acc: 91.9436, loss_bbox: 0.2705, loss_mask: 0.2597, loss: 0.8523 2023-11-13 17:17:49,199 - mmdet - INFO - Epoch [2][2850/7330] lr: 1.000e-04, eta: 6:41:25, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0521, loss_cls: 0.2372, acc: 91.8596, loss_bbox: 0.2698, loss_mask: 0.2621, loss: 0.8559 2023-11-13 17:18:04,670 - mmdet - INFO - Epoch [2][2900/7330] lr: 1.000e-04, eta: 6:41:10, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0481, loss_cls: 0.2190, acc: 92.3933, loss_bbox: 0.2562, loss_mask: 0.2532, loss: 0.8079 2023-11-13 17:18:20,599 - mmdet - INFO - Epoch [2][2950/7330] lr: 1.000e-04, eta: 6:40:57, time: 0.319, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0533, loss_cls: 0.2381, acc: 91.7600, loss_bbox: 0.2786, loss_mask: 0.2624, loss: 0.8655 2023-11-13 17:18:36,004 - mmdet - INFO - Epoch [2][3000/7330] lr: 1.000e-04, eta: 6:40:41, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0377, loss_rpn_bbox: 0.0532, loss_cls: 0.2296, acc: 92.0037, loss_bbox: 0.2694, loss_mask: 0.2608, loss: 0.8508 2023-11-13 17:18:51,699 - mmdet - INFO - Epoch [2][3050/7330] lr: 1.000e-04, eta: 6:40:27, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0520, loss_cls: 0.2232, acc: 92.3076, loss_bbox: 0.2629, loss_mask: 0.2560, loss: 0.8294 2023-11-13 17:19:07,316 - mmdet - INFO - Epoch [2][3100/7330] lr: 1.000e-04, eta: 6:40:13, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0339, loss_rpn_bbox: 0.0509, loss_cls: 0.2250, acc: 92.2207, loss_bbox: 0.2677, loss_mask: 0.2563, loss: 0.8338 2023-11-13 17:19:22,770 - mmdet - INFO - Epoch [2][3150/7330] lr: 1.000e-04, eta: 6:39:57, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0319, loss_rpn_bbox: 0.0506, loss_cls: 0.2286, acc: 91.9705, loss_bbox: 0.2702, loss_mask: 0.2576, loss: 0.8389 2023-11-13 17:19:38,191 - mmdet - INFO - Epoch [2][3200/7330] lr: 1.000e-04, eta: 6:39:41, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0486, loss_cls: 0.2292, acc: 92.1863, loss_bbox: 0.2703, loss_mask: 0.2638, loss: 0.8451 2023-11-13 17:19:53,565 - mmdet - INFO - Epoch [2][3250/7330] lr: 1.000e-04, eta: 6:39:25, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0477, loss_cls: 0.2233, acc: 92.2942, loss_bbox: 0.2601, loss_mask: 0.2535, loss: 0.8168 2023-11-13 17:20:08,911 - mmdet - INFO - Epoch [2][3300/7330] lr: 1.000e-04, eta: 6:39:08, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0499, loss_cls: 0.2262, acc: 92.2505, loss_bbox: 0.2594, loss_mask: 0.2554, loss: 0.8243 2023-11-13 17:20:24,329 - mmdet - INFO - Epoch [2][3350/7330] lr: 1.000e-04, eta: 6:38:52, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0514, loss_cls: 0.2289, acc: 91.9561, loss_bbox: 0.2703, loss_mask: 0.2602, loss: 0.8470 2023-11-13 17:20:40,130 - mmdet - INFO - Epoch [2][3400/7330] lr: 1.000e-04, eta: 6:38:39, time: 0.316, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0541, loss_cls: 0.2263, acc: 92.0366, loss_bbox: 0.2710, loss_mask: 0.2570, loss: 0.8446 2023-11-13 17:20:55,357 - mmdet - INFO - Epoch [2][3450/7330] lr: 1.000e-04, eta: 6:38:22, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0472, loss_cls: 0.2218, acc: 92.1912, loss_bbox: 0.2595, loss_mask: 0.2556, loss: 0.8179 2023-11-13 17:21:10,929 - mmdet - INFO - Epoch [2][3500/7330] lr: 1.000e-04, eta: 6:38:07, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0503, loss_cls: 0.2246, acc: 92.1062, loss_bbox: 0.2679, loss_mask: 0.2593, loss: 0.8362 2023-11-13 17:21:25,971 - mmdet - INFO - Epoch [2][3550/7330] lr: 1.000e-04, eta: 6:37:48, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0480, loss_cls: 0.2168, acc: 92.5720, loss_bbox: 0.2555, loss_mask: 0.2553, loss: 0.8093 2023-11-13 17:21:41,640 - mmdet - INFO - Epoch [2][3600/7330] lr: 1.000e-04, eta: 6:37:34, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0496, loss_cls: 0.2307, acc: 92.0029, loss_bbox: 0.2702, loss_mask: 0.2675, loss: 0.8509 2023-11-13 17:21:57,141 - mmdet - INFO - Epoch [2][3650/7330] lr: 1.000e-04, eta: 6:37:19, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0349, loss_rpn_bbox: 0.0520, loss_cls: 0.2311, acc: 91.9707, loss_bbox: 0.2711, loss_mask: 0.2629, loss: 0.8519 2023-11-13 17:22:12,583 - mmdet - INFO - Epoch [2][3700/7330] lr: 1.000e-04, eta: 6:37:03, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0501, loss_cls: 0.2195, acc: 92.2161, loss_bbox: 0.2636, loss_mask: 0.2508, loss: 0.8176 2023-11-13 17:22:28,082 - mmdet - INFO - Epoch [2][3750/7330] lr: 1.000e-04, eta: 6:36:48, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0463, loss_cls: 0.2112, acc: 92.6848, loss_bbox: 0.2448, loss_mask: 0.2427, loss: 0.7748 2023-11-13 17:22:43,437 - mmdet - INFO - Epoch [2][3800/7330] lr: 1.000e-04, eta: 6:36:31, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0487, loss_cls: 0.2254, acc: 92.3923, loss_bbox: 0.2567, loss_mask: 0.2559, loss: 0.8209 2023-11-13 17:22:59,083 - mmdet - INFO - Epoch [2][3850/7330] lr: 1.000e-04, eta: 6:36:17, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0485, loss_cls: 0.2288, acc: 92.0527, loss_bbox: 0.2654, loss_mask: 0.2579, loss: 0.8343 2023-11-13 17:23:14,593 - mmdet - INFO - Epoch [2][3900/7330] lr: 1.000e-04, eta: 6:36:02, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0492, loss_cls: 0.2233, acc: 92.3999, loss_bbox: 0.2577, loss_mask: 0.2539, loss: 0.8177 2023-11-13 17:23:30,412 - mmdet - INFO - Epoch [2][3950/7330] lr: 1.000e-04, eta: 6:35:48, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0512, loss_cls: 0.2276, acc: 92.1750, loss_bbox: 0.2590, loss_mask: 0.2574, loss: 0.8298 2023-11-13 17:23:45,856 - mmdet - INFO - Epoch [2][4000/7330] lr: 1.000e-04, eta: 6:35:33, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0486, loss_cls: 0.2220, acc: 92.2859, loss_bbox: 0.2591, loss_mask: 0.2495, loss: 0.8096 2023-11-13 17:24:01,730 - mmdet - INFO - Epoch [2][4050/7330] lr: 1.000e-04, eta: 6:35:20, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0516, loss_cls: 0.2310, acc: 92.1023, loss_bbox: 0.2651, loss_mask: 0.2560, loss: 0.8393 2023-11-13 17:24:17,301 - mmdet - INFO - Epoch [2][4100/7330] lr: 1.000e-04, eta: 6:35:05, time: 0.311, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0473, loss_cls: 0.2169, acc: 92.4807, loss_bbox: 0.2544, loss_mask: 0.2521, loss: 0.8040 2023-11-13 17:24:32,903 - mmdet - INFO - Epoch [2][4150/7330] lr: 1.000e-04, eta: 6:34:50, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0504, loss_cls: 0.2265, acc: 92.1765, loss_bbox: 0.2593, loss_mask: 0.2502, loss: 0.8188 2023-11-13 17:24:48,439 - mmdet - INFO - Epoch [2][4200/7330] lr: 1.000e-04, eta: 6:34:35, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0491, loss_cls: 0.2247, acc: 92.1553, loss_bbox: 0.2631, loss_mask: 0.2568, loss: 0.8239 2023-11-13 17:25:04,142 - mmdet - INFO - Epoch [2][4250/7330] lr: 1.000e-04, eta: 6:34:21, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0339, loss_rpn_bbox: 0.0533, loss_cls: 0.2356, acc: 91.7444, loss_bbox: 0.2774, loss_mask: 0.2634, loss: 0.8635 2023-11-13 17:25:19,766 - mmdet - INFO - Epoch [2][4300/7330] lr: 1.000e-04, eta: 6:34:06, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0523, loss_cls: 0.2266, acc: 92.1189, loss_bbox: 0.2644, loss_mask: 0.2518, loss: 0.8288 2023-11-13 17:25:34,946 - mmdet - INFO - Epoch [2][4350/7330] lr: 1.000e-04, eta: 6:33:49, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0478, loss_cls: 0.2179, acc: 92.4060, loss_bbox: 0.2564, loss_mask: 0.2540, loss: 0.8064 2023-11-13 17:25:49,821 - mmdet - INFO - Epoch [2][4400/7330] lr: 1.000e-04, eta: 6:33:29, time: 0.298, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0453, loss_cls: 0.2234, acc: 92.3430, loss_bbox: 0.2575, loss_mask: 0.2534, loss: 0.8110 2023-11-13 17:26:04,900 - mmdet - INFO - Epoch [2][4450/7330] lr: 1.000e-04, eta: 6:33:11, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0483, loss_cls: 0.2257, acc: 92.2214, loss_bbox: 0.2585, loss_mask: 0.2613, loss: 0.8253 2023-11-13 17:26:20,135 - mmdet - INFO - Epoch [2][4500/7330] lr: 1.000e-04, eta: 6:32:54, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0481, loss_cls: 0.2240, acc: 92.1953, loss_bbox: 0.2649, loss_mask: 0.2639, loss: 0.8323 2023-11-13 17:26:35,507 - mmdet - INFO - Epoch [2][4550/7330] lr: 1.000e-04, eta: 6:32:38, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0507, loss_cls: 0.2293, acc: 92.2339, loss_bbox: 0.2639, loss_mask: 0.2535, loss: 0.8318 2023-11-13 17:26:51,147 - mmdet - INFO - Epoch [2][4600/7330] lr: 1.000e-04, eta: 6:32:23, time: 0.313, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0497, loss_cls: 0.2192, acc: 92.2537, loss_bbox: 0.2590, loss_mask: 0.2577, loss: 0.8193 2023-11-13 17:27:06,574 - mmdet - INFO - Epoch [2][4650/7330] lr: 1.000e-04, eta: 6:32:08, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0517, loss_cls: 0.2162, acc: 92.3987, loss_bbox: 0.2560, loss_mask: 0.2586, loss: 0.8137 2023-11-13 17:27:21,730 - mmdet - INFO - Epoch [2][4700/7330] lr: 1.000e-04, eta: 6:31:50, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0478, loss_cls: 0.2108, acc: 92.5818, loss_bbox: 0.2497, loss_mask: 0.2591, loss: 0.8006 2023-11-13 17:27:37,259 - mmdet - INFO - Epoch [2][4750/7330] lr: 1.000e-04, eta: 6:31:35, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0484, loss_cls: 0.2242, acc: 92.1230, loss_bbox: 0.2658, loss_mask: 0.2540, loss: 0.8246 2023-11-13 17:27:52,696 - mmdet - INFO - Epoch [2][4800/7330] lr: 1.000e-04, eta: 6:31:19, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0500, loss_cls: 0.2152, acc: 92.4570, loss_bbox: 0.2621, loss_mask: 0.2584, loss: 0.8200 2023-11-13 17:28:08,146 - mmdet - INFO - Epoch [2][4850/7330] lr: 1.000e-04, eta: 6:31:03, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0496, loss_cls: 0.2243, acc: 92.0659, loss_bbox: 0.2668, loss_mask: 0.2530, loss: 0.8237 2023-11-13 17:28:23,926 - mmdet - INFO - Epoch [2][4900/7330] lr: 1.000e-04, eta: 6:30:50, time: 0.316, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0514, loss_cls: 0.2219, acc: 92.2515, loss_bbox: 0.2642, loss_mask: 0.2601, loss: 0.8323 2023-11-13 17:28:39,125 - mmdet - INFO - Epoch [2][4950/7330] lr: 1.000e-04, eta: 6:30:33, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0495, loss_cls: 0.2226, acc: 92.3577, loss_bbox: 0.2594, loss_mask: 0.2502, loss: 0.8150 2023-11-13 17:28:54,648 - mmdet - INFO - Epoch [2][5000/7330] lr: 1.000e-04, eta: 6:30:17, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0505, loss_cls: 0.2337, acc: 91.7871, loss_bbox: 0.2732, loss_mask: 0.2520, loss: 0.8417 2023-11-13 17:29:10,018 - mmdet - INFO - Epoch [2][5050/7330] lr: 1.000e-04, eta: 6:30:01, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0511, loss_cls: 0.2241, acc: 92.1748, loss_bbox: 0.2667, loss_mask: 0.2601, loss: 0.8366 2023-11-13 17:29:25,566 - mmdet - INFO - Epoch [2][5100/7330] lr: 1.000e-04, eta: 6:29:46, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0501, loss_cls: 0.2205, acc: 92.3643, loss_bbox: 0.2555, loss_mask: 0.2531, loss: 0.8122 2023-11-13 17:29:40,734 - mmdet - INFO - Epoch [2][5150/7330] lr: 1.000e-04, eta: 6:29:29, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0463, loss_cls: 0.2195, acc: 92.4597, loss_bbox: 0.2621, loss_mask: 0.2525, loss: 0.8130 2023-11-13 17:29:56,059 - mmdet - INFO - Epoch [2][5200/7330] lr: 1.000e-04, eta: 6:29:12, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0480, loss_cls: 0.2198, acc: 92.3030, loss_bbox: 0.2562, loss_mask: 0.2541, loss: 0.8104 2023-11-13 17:30:11,290 - mmdet - INFO - Epoch [2][5250/7330] lr: 1.000e-04, eta: 6:28:55, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0515, loss_cls: 0.2216, acc: 92.3870, loss_bbox: 0.2594, loss_mask: 0.2594, loss: 0.8267 2023-11-13 17:30:26,376 - mmdet - INFO - Epoch [2][5300/7330] lr: 1.000e-04, eta: 6:28:37, time: 0.302, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0451, loss_cls: 0.2145, acc: 92.5305, loss_bbox: 0.2520, loss_mask: 0.2551, loss: 0.7970 2023-11-13 17:30:41,413 - mmdet - INFO - Epoch [2][5350/7330] lr: 1.000e-04, eta: 6:28:19, time: 0.301, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0486, loss_cls: 0.2181, acc: 92.3711, loss_bbox: 0.2565, loss_mask: 0.2518, loss: 0.8065 2023-11-13 17:30:56,887 - mmdet - INFO - Epoch [2][5400/7330] lr: 1.000e-04, eta: 6:28:04, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0492, loss_cls: 0.2189, acc: 92.4346, loss_bbox: 0.2593, loss_mask: 0.2546, loss: 0.8156 2023-11-13 17:31:12,053 - mmdet - INFO - Epoch [2][5450/7330] lr: 1.000e-04, eta: 6:27:47, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0464, loss_cls: 0.2122, acc: 92.5139, loss_bbox: 0.2519, loss_mask: 0.2592, loss: 0.8000 2023-11-13 17:31:27,154 - mmdet - INFO - Epoch [2][5500/7330] lr: 1.000e-04, eta: 6:27:29, time: 0.302, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0472, loss_cls: 0.2178, acc: 92.4966, loss_bbox: 0.2569, loss_mask: 0.2483, loss: 0.8016 2023-11-13 17:31:42,409 - mmdet - INFO - Epoch [2][5550/7330] lr: 1.000e-04, eta: 6:27:12, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0493, loss_cls: 0.2150, acc: 92.4810, loss_bbox: 0.2551, loss_mask: 0.2585, loss: 0.8100 2023-11-13 17:31:57,841 - mmdet - INFO - Epoch [2][5600/7330] lr: 1.000e-04, eta: 6:26:56, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0491, loss_cls: 0.2232, acc: 92.1594, loss_bbox: 0.2563, loss_mask: 0.2502, loss: 0.8117 2023-11-13 17:32:12,903 - mmdet - INFO - Epoch [2][5650/7330] lr: 1.000e-04, eta: 6:26:39, time: 0.301, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0480, loss_cls: 0.2145, acc: 92.5374, loss_bbox: 0.2555, loss_mask: 0.2576, loss: 0.8064 2023-11-13 17:32:28,355 - mmdet - INFO - Epoch [2][5700/7330] lr: 1.000e-04, eta: 6:26:23, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0473, loss_cls: 0.2145, acc: 92.5166, loss_bbox: 0.2565, loss_mask: 0.2515, loss: 0.8012 2023-11-13 17:32:43,751 - mmdet - INFO - Epoch [2][5750/7330] lr: 1.000e-04, eta: 6:26:07, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0491, loss_cls: 0.2223, acc: 92.3792, loss_bbox: 0.2571, loss_mask: 0.2497, loss: 0.8104 2023-11-13 17:32:59,059 - mmdet - INFO - Epoch [2][5800/7330] lr: 1.000e-04, eta: 6:25:51, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0493, loss_cls: 0.2355, acc: 91.8064, loss_bbox: 0.2756, loss_mask: 0.2616, loss: 0.8537 2023-11-13 17:33:14,733 - mmdet - INFO - Epoch [2][5850/7330] lr: 1.000e-04, eta: 6:25:36, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0485, loss_cls: 0.2207, acc: 92.3530, loss_bbox: 0.2550, loss_mask: 0.2514, loss: 0.8087 2023-11-13 17:33:30,338 - mmdet - INFO - Epoch [2][5900/7330] lr: 1.000e-04, eta: 6:25:22, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0489, loss_cls: 0.2199, acc: 92.3542, loss_bbox: 0.2548, loss_mask: 0.2459, loss: 0.8008 2023-11-13 17:33:45,825 - mmdet - INFO - Epoch [2][5950/7330] lr: 1.000e-04, eta: 6:25:06, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0483, loss_cls: 0.2106, acc: 92.4956, loss_bbox: 0.2585, loss_mask: 0.2546, loss: 0.8032 2023-11-13 17:34:01,122 - mmdet - INFO - Epoch [2][6000/7330] lr: 1.000e-04, eta: 6:24:50, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0340, loss_rpn_bbox: 0.0498, loss_cls: 0.2226, acc: 92.3013, loss_bbox: 0.2629, loss_mask: 0.2643, loss: 0.8336 2023-11-13 17:34:16,547 - mmdet - INFO - Epoch [2][6050/7330] lr: 1.000e-04, eta: 6:24:34, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0456, loss_cls: 0.2179, acc: 92.5088, loss_bbox: 0.2481, loss_mask: 0.2573, loss: 0.7998 2023-11-13 17:34:31,749 - mmdet - INFO - Epoch [2][6100/7330] lr: 1.000e-04, eta: 6:24:17, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0486, loss_cls: 0.2092, acc: 92.6279, loss_bbox: 0.2478, loss_mask: 0.2512, loss: 0.7863 2023-11-13 17:34:46,973 - mmdet - INFO - Epoch [2][6150/7330] lr: 1.000e-04, eta: 6:24:00, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0493, loss_cls: 0.2153, acc: 92.4863, loss_bbox: 0.2548, loss_mask: 0.2501, loss: 0.8022 2023-11-13 17:35:02,142 - mmdet - INFO - Epoch [2][6200/7330] lr: 1.000e-04, eta: 6:23:43, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0489, loss_cls: 0.2176, acc: 92.3354, loss_bbox: 0.2517, loss_mask: 0.2535, loss: 0.8024 2023-11-13 17:35:17,481 - mmdet - INFO - Epoch [2][6250/7330] lr: 1.000e-04, eta: 6:23:27, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0306, loss_rpn_bbox: 0.0483, loss_cls: 0.2153, acc: 92.5364, loss_bbox: 0.2470, loss_mask: 0.2553, loss: 0.7964 2023-11-13 17:35:33,257 - mmdet - INFO - Epoch [2][6300/7330] lr: 1.000e-04, eta: 6:23:13, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0496, loss_cls: 0.2286, acc: 92.0972, loss_bbox: 0.2643, loss_mask: 0.2651, loss: 0.8402 2023-11-13 17:35:48,700 - mmdet - INFO - Epoch [2][6350/7330] lr: 1.000e-04, eta: 6:22:58, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0488, loss_cls: 0.2174, acc: 92.4072, loss_bbox: 0.2595, loss_mask: 0.2559, loss: 0.8130 2023-11-13 17:36:04,254 - mmdet - INFO - Epoch [2][6400/7330] lr: 1.000e-04, eta: 6:22:43, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0479, loss_cls: 0.2238, acc: 92.1277, loss_bbox: 0.2697, loss_mask: 0.2613, loss: 0.8326 2023-11-13 17:36:19,427 - mmdet - INFO - Epoch [2][6450/7330] lr: 1.000e-04, eta: 6:22:26, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0487, loss_cls: 0.2140, acc: 92.4729, loss_bbox: 0.2564, loss_mask: 0.2539, loss: 0.8013 2023-11-13 17:36:34,958 - mmdet - INFO - Epoch [2][6500/7330] lr: 1.000e-04, eta: 6:22:11, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0511, loss_cls: 0.2179, acc: 92.3340, loss_bbox: 0.2564, loss_mask: 0.2569, loss: 0.8160 2023-11-13 17:36:50,289 - mmdet - INFO - Epoch [2][6550/7330] lr: 1.000e-04, eta: 6:21:54, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0487, loss_cls: 0.2262, acc: 92.2053, loss_bbox: 0.2568, loss_mask: 0.2491, loss: 0.8143 2023-11-13 17:37:05,879 - mmdet - INFO - Epoch [2][6600/7330] lr: 1.000e-04, eta: 6:21:40, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0500, loss_cls: 0.2231, acc: 92.1841, loss_bbox: 0.2597, loss_mask: 0.2543, loss: 0.8222 2023-11-13 17:37:21,461 - mmdet - INFO - Epoch [2][6650/7330] lr: 1.000e-04, eta: 6:21:25, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0506, loss_cls: 0.2246, acc: 92.1697, loss_bbox: 0.2640, loss_mask: 0.2553, loss: 0.8261 2023-11-13 17:37:37,130 - mmdet - INFO - Epoch [2][6700/7330] lr: 1.000e-04, eta: 6:21:10, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0481, loss_cls: 0.2204, acc: 92.3694, loss_bbox: 0.2559, loss_mask: 0.2516, loss: 0.8101 2023-11-13 17:37:52,408 - mmdet - INFO - Epoch [2][6750/7330] lr: 1.000e-04, eta: 6:20:54, time: 0.306, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0467, loss_cls: 0.2140, acc: 92.4490, loss_bbox: 0.2545, loss_mask: 0.2539, loss: 0.8002 2023-11-13 17:38:08,270 - mmdet - INFO - Epoch [2][6800/7330] lr: 1.000e-04, eta: 6:20:40, time: 0.317, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0319, loss_rpn_bbox: 0.0483, loss_cls: 0.2133, acc: 92.5295, loss_bbox: 0.2497, loss_mask: 0.2483, loss: 0.7916 2023-11-13 17:38:23,908 - mmdet - INFO - Epoch [2][6850/7330] lr: 1.000e-04, eta: 6:20:26, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0488, loss_cls: 0.2097, acc: 92.5869, loss_bbox: 0.2491, loss_mask: 0.2443, loss: 0.7801 2023-11-13 17:38:39,398 - mmdet - INFO - Epoch [2][6900/7330] lr: 1.000e-04, eta: 6:20:10, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0481, loss_cls: 0.2137, acc: 92.4775, loss_bbox: 0.2525, loss_mask: 0.2483, loss: 0.7932 2023-11-13 17:38:54,724 - mmdet - INFO - Epoch [2][6950/7330] lr: 1.000e-04, eta: 6:19:54, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0486, loss_cls: 0.2161, acc: 92.3391, loss_bbox: 0.2598, loss_mask: 0.2546, loss: 0.8113 2023-11-13 17:39:10,362 - mmdet - INFO - Epoch [2][7000/7330] lr: 1.000e-04, eta: 6:19:40, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0499, loss_cls: 0.2163, acc: 92.5417, loss_bbox: 0.2593, loss_mask: 0.2559, loss: 0.8143 2023-11-13 17:39:25,891 - mmdet - INFO - Epoch [2][7050/7330] lr: 1.000e-04, eta: 6:19:24, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0485, loss_cls: 0.2190, acc: 92.4412, loss_bbox: 0.2542, loss_mask: 0.2613, loss: 0.8175 2023-11-13 17:39:41,259 - mmdet - INFO - Epoch [2][7100/7330] lr: 1.000e-04, eta: 6:19:08, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0468, loss_cls: 0.2145, acc: 92.7061, loss_bbox: 0.2485, loss_mask: 0.2542, loss: 0.7941 2023-11-13 17:39:56,853 - mmdet - INFO - Epoch [2][7150/7330] lr: 1.000e-04, eta: 6:18:54, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0491, loss_cls: 0.2248, acc: 92.0266, loss_bbox: 0.2649, loss_mask: 0.2586, loss: 0.8314 2023-11-13 17:40:12,207 - mmdet - INFO - Epoch [2][7200/7330] lr: 1.000e-04, eta: 6:18:38, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0453, loss_cls: 0.2047, acc: 92.9609, loss_bbox: 0.2446, loss_mask: 0.2510, loss: 0.7739 2023-11-13 17:40:27,513 - mmdet - INFO - Epoch [2][7250/7330] lr: 1.000e-04, eta: 6:18:21, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0479, loss_cls: 0.2176, acc: 92.3779, loss_bbox: 0.2551, loss_mask: 0.2503, loss: 0.8027 2023-11-13 17:40:43,172 - mmdet - INFO - Epoch [2][7300/7330] lr: 1.000e-04, eta: 6:18:07, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0511, loss_cls: 0.2290, acc: 91.9666, loss_bbox: 0.2651, loss_mask: 0.2504, loss: 0.8290 2023-11-13 17:40:52,742 - mmdet - INFO - Saving checkpoint at 2 epochs 2023-11-13 17:41:40,893 - mmdet - INFO - Evaluating bbox... 2023-11-13 17:42:13,449 - 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 ] = 0.444 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.249 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 ] = 0.526 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.536 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.536 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.536 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.678 2023-11-13 17:42:13,451 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.534 | bicycle | 0.284 | car | 0.435 | | motorcycle | 0.405 | airplane | 0.633 | bus | 0.621 | | train | 0.577 | truck | 0.349 | boat | 0.282 | | traffic light | 0.280 | fire hydrant | 0.635 | stop sign | 0.646 | | parking meter | 0.373 | bench | 0.237 | bird | 0.362 | | cat | 0.694 | dog | 0.613 | horse | 0.499 | | sheep | 0.540 | cow | 0.541 | elephant | 0.621 | | bear | 0.662 | zebra | 0.638 | giraffe | 0.647 | | backpack | 0.143 | umbrella | 0.400 | handbag | 0.154 | | tie | 0.300 | suitcase | 0.395 | frisbee | 0.654 | | skis | 0.206 | snowboard | 0.289 | sports ball | 0.437 | | kite | 0.419 | baseball bat | 0.260 | baseball glove | 0.381 | | skateboard | 0.486 | surfboard | 0.361 | tennis racket | 0.473 | | bottle | 0.389 | wine glass | 0.330 | cup | 0.441 | | fork | 0.308 | knife | 0.194 | spoon | 0.170 | | bowl | 0.411 | banana | 0.234 | apple | 0.189 | | sandwich | 0.343 | orange | 0.307 | broccoli | 0.231 | | carrot | 0.205 | hot dog | 0.340 | pizza | 0.491 | | donut | 0.492 | cake | 0.374 | chair | 0.297 | | couch | 0.410 | potted plant | 0.265 | bed | 0.389 | | dining table | 0.243 | toilet | 0.563 | tv | 0.565 | | laptop | 0.556 | mouse | 0.607 | remote | 0.302 | | keyboard | 0.466 | cell phone | 0.360 | microwave | 0.550 | | oven | 0.314 | toaster | 0.317 | sink | 0.354 | | refrigerator | 0.525 | book | 0.136 | clock | 0.498 | | vase | 0.394 | scissors | 0.291 | teddy bear | 0.439 | | hair drier | 0.115 | toothbrush | 0.219 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:42:13,451 - mmdet - INFO - Evaluating segm... 2023-11-13 17:42:51,954 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.375 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.606 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.405 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.186 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.408 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.546 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.502 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.314 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.545 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.655 2023-11-13 17:42:51,957 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.466 | bicycle | 0.168 | car | 0.407 | | motorcycle | 0.336 | airplane | 0.507 | bus | 0.625 | | train | 0.590 | truck | 0.356 | boat | 0.261 | | traffic light | 0.275 | fire hydrant | 0.635 | stop sign | 0.655 | | parking meter | 0.445 | bench | 0.177 | bird | 0.313 | | cat | 0.710 | dog | 0.598 | horse | 0.373 | | sheep | 0.464 | cow | 0.481 | elephant | 0.571 | | bear | 0.685 | zebra | 0.566 | giraffe | 0.496 | | backpack | 0.160 | umbrella | 0.484 | handbag | 0.153 | | tie | 0.288 | suitcase | 0.411 | frisbee | 0.647 | | skis | 0.028 | snowboard | 0.190 | sports ball | 0.451 | | kite | 0.305 | baseball bat | 0.232 | baseball glove | 0.410 | | skateboard | 0.293 | surfboard | 0.317 | tennis racket | 0.546 | | bottle | 0.382 | wine glass | 0.290 | cup | 0.459 | | fork | 0.145 | knife | 0.132 | spoon | 0.126 | | bowl | 0.391 | banana | 0.186 | apple | 0.200 | | sandwich | 0.398 | orange | 0.313 | broccoli | 0.223 | | carrot | 0.172 | hot dog | 0.266 | pizza | 0.503 | | donut | 0.511 | cake | 0.389 | chair | 0.211 | | couch | 0.369 | potted plant | 0.227 | bed | 0.331 | | dining table | 0.140 | toilet | 0.577 | tv | 0.599 | | laptop | 0.614 | mouse | 0.608 | remote | 0.293 | | keyboard | 0.492 | cell phone | 0.363 | microwave | 0.590 | | oven | 0.307 | toaster | 0.389 | sink | 0.352 | | refrigerator | 0.543 | book | 0.096 | clock | 0.501 | | vase | 0.399 | scissors | 0.231 | teddy bear | 0.446 | | hair drier | 0.049 | toothbrush | 0.132 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:42:52,506 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_1.pth was removed 2023-11-13 17:42:54,052 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_2.pth. 2023-11-13 17:42:54,052 - mmdet - INFO - Best bbox_mAP is 0.4011 at 2 epoch. 2023-11-13 17:42:54,052 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 17:42:54,052 - mmdet - INFO - Epoch(val) [2][625] bbox_mAP: 0.4011, bbox_mAP_50: 0.6370, bbox_mAP_75: 0.4442, bbox_mAP_s: 0.2489, bbox_mAP_m: 0.4424, bbox_mAP_l: 0.5258, bbox_mAP_copypaste: 0.4011 0.6370 0.4442 0.2489 0.4424 0.5258, segm_mAP: 0.3752, segm_mAP_50: 0.6060, segm_mAP_75: 0.4046, segm_mAP_s: 0.1859, segm_mAP_m: 0.4075, segm_mAP_l: 0.5461, segm_mAP_copypaste: 0.3752 0.6060 0.4046 0.1859 0.4075 0.5461 2023-11-13 17:43:13,310 - mmdet - INFO - Epoch [3][50/7330] lr: 1.000e-04, eta: 6:17:15, time: 0.385, data_time: 0.091, memory: 3904, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0494, loss_cls: 0.2081, acc: 92.5510, loss_bbox: 0.2508, loss_mask: 0.2468, loss: 0.7850 2023-11-13 17:43:29,033 - mmdet - INFO - Epoch [3][100/7330] lr: 1.000e-04, eta: 6:17:00, time: 0.314, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0454, loss_cls: 0.2022, acc: 92.7678, loss_bbox: 0.2449, loss_mask: 0.2486, loss: 0.7693 2023-11-13 17:43:45,433 - mmdet - INFO - Epoch [3][150/7330] lr: 1.000e-04, eta: 6:16:50, time: 0.328, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0491, loss_cls: 0.2163, acc: 92.1135, loss_bbox: 0.2650, loss_mask: 0.2498, loss: 0.8120 2023-11-13 17:44:01,516 - mmdet - INFO - Epoch [3][200/7330] lr: 1.000e-04, eta: 6:16:37, time: 0.322, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0455, loss_cls: 0.2008, acc: 92.8289, loss_bbox: 0.2444, loss_mask: 0.2474, loss: 0.7640 2023-11-13 17:44:17,261 - mmdet - INFO - Epoch [3][250/7330] lr: 1.000e-04, eta: 6:16:23, time: 0.315, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0490, loss_cls: 0.2070, acc: 92.6448, loss_bbox: 0.2486, loss_mask: 0.2479, loss: 0.7810 2023-11-13 17:44:33,292 - mmdet - INFO - Epoch [3][300/7330] lr: 1.000e-04, eta: 6:16:11, time: 0.321, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0487, loss_cls: 0.2143, acc: 92.3938, loss_bbox: 0.2625, loss_mask: 0.2490, loss: 0.8038 2023-11-13 17:44:49,268 - mmdet - INFO - Epoch [3][350/7330] lr: 1.000e-04, eta: 6:15:58, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0479, loss_cls: 0.2133, acc: 92.3762, loss_bbox: 0.2594, loss_mask: 0.2493, loss: 0.8001 2023-11-13 17:45:04,587 - mmdet - INFO - Epoch [3][400/7330] lr: 1.000e-04, eta: 6:15:42, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0479, loss_cls: 0.2061, acc: 92.7573, loss_bbox: 0.2462, loss_mask: 0.2419, loss: 0.7705 2023-11-13 17:45:20,231 - mmdet - INFO - Epoch [3][450/7330] lr: 1.000e-04, eta: 6:15:27, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0451, loss_cls: 0.2008, acc: 92.9036, loss_bbox: 0.2409, loss_mask: 0.2479, loss: 0.7640 2023-11-13 17:45:36,197 - mmdet - INFO - Epoch [3][500/7330] lr: 1.000e-04, eta: 6:15:14, time: 0.319, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0482, loss_cls: 0.2144, acc: 92.4136, loss_bbox: 0.2592, loss_mask: 0.2481, loss: 0.7996 2023-11-13 17:45:51,502 - mmdet - INFO - Epoch [3][550/7330] lr: 1.000e-04, eta: 6:14:58, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0475, loss_cls: 0.2099, acc: 92.5298, loss_bbox: 0.2532, loss_mask: 0.2507, loss: 0.7881 2023-11-13 17:46:06,689 - mmdet - INFO - Epoch [3][600/7330] lr: 1.000e-04, eta: 6:14:41, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0471, loss_cls: 0.2135, acc: 92.4148, loss_bbox: 0.2558, loss_mask: 0.2491, loss: 0.7944 2023-11-13 17:46:22,115 - mmdet - INFO - Epoch [3][650/7330] lr: 1.000e-04, eta: 6:14:25, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0469, loss_cls: 0.2064, acc: 92.6973, loss_bbox: 0.2484, loss_mask: 0.2489, loss: 0.7784 2023-11-13 17:46:37,227 - mmdet - INFO - Epoch [3][700/7330] lr: 1.000e-04, eta: 6:14:08, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0437, loss_cls: 0.1920, acc: 93.1504, loss_bbox: 0.2352, loss_mask: 0.2411, loss: 0.7392 2023-11-13 17:46:52,876 - mmdet - INFO - Epoch [3][750/7330] lr: 1.000e-04, eta: 6:13:54, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0479, loss_cls: 0.2080, acc: 92.6450, loss_bbox: 0.2496, loss_mask: 0.2490, loss: 0.7834 2023-11-13 17:47:08,390 - mmdet - INFO - Epoch [3][800/7330] lr: 1.000e-04, eta: 6:13:38, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0468, loss_cls: 0.2074, acc: 92.6277, loss_bbox: 0.2490, loss_mask: 0.2448, loss: 0.7788 2023-11-13 17:47:23,866 - mmdet - INFO - Epoch [3][850/7330] lr: 1.000e-04, eta: 6:13:23, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0459, loss_cls: 0.2100, acc: 92.5229, loss_bbox: 0.2562, loss_mask: 0.2535, loss: 0.7926 2023-11-13 17:47:39,563 - mmdet - INFO - Epoch [3][900/7330] lr: 1.000e-04, eta: 6:13:09, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0450, loss_cls: 0.2016, acc: 92.8245, loss_bbox: 0.2405, loss_mask: 0.2513, loss: 0.7675 2023-11-13 17:47:55,098 - mmdet - INFO - Epoch [3][950/7330] lr: 1.000e-04, eta: 6:12:53, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0490, loss_cls: 0.2123, acc: 92.4722, loss_bbox: 0.2587, loss_mask: 0.2512, loss: 0.7993 2023-11-13 17:48:10,729 - mmdet - INFO - Epoch [3][1000/7330] lr: 1.000e-04, eta: 6:12:39, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0501, loss_cls: 0.2154, acc: 92.3958, loss_bbox: 0.2609, loss_mask: 0.2521, loss: 0.8075 2023-11-13 17:48:26,109 - mmdet - INFO - Epoch [3][1050/7330] lr: 1.000e-04, eta: 6:12:23, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0501, loss_cls: 0.2066, acc: 92.5850, loss_bbox: 0.2514, loss_mask: 0.2508, loss: 0.7874 2023-11-13 17:48:41,293 - mmdet - INFO - Epoch [3][1100/7330] lr: 1.000e-04, eta: 6:12:06, time: 0.304, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0449, loss_cls: 0.1892, acc: 93.1677, loss_bbox: 0.2348, loss_mask: 0.2419, loss: 0.7376 2023-11-13 17:48:56,695 - mmdet - INFO - Epoch [3][1150/7330] lr: 1.000e-04, eta: 6:11:50, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0463, loss_cls: 0.2024, acc: 92.8975, loss_bbox: 0.2400, loss_mask: 0.2406, loss: 0.7565 2023-11-13 17:49:11,825 - mmdet - INFO - Epoch [3][1200/7330] lr: 1.000e-04, eta: 6:11:33, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0451, loss_cls: 0.2030, acc: 92.7307, loss_bbox: 0.2455, loss_mask: 0.2444, loss: 0.7660 2023-11-13 17:49:26,950 - mmdet - INFO - Epoch [3][1250/7330] lr: 1.000e-04, eta: 6:11:17, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0466, loss_cls: 0.2028, acc: 92.8276, loss_bbox: 0.2478, loss_mask: 0.2496, loss: 0.7751 2023-11-13 17:49:42,122 - mmdet - INFO - Epoch [3][1300/7330] lr: 1.000e-04, eta: 6:11:00, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0460, loss_cls: 0.2033, acc: 92.7063, loss_bbox: 0.2465, loss_mask: 0.2418, loss: 0.7634 2023-11-13 17:49:57,738 - mmdet - INFO - Epoch [3][1350/7330] lr: 1.000e-04, eta: 6:10:45, time: 0.312, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0501, loss_cls: 0.2173, acc: 92.3201, loss_bbox: 0.2601, loss_mask: 0.2518, loss: 0.8096 2023-11-13 17:50:12,954 - mmdet - INFO - Epoch [3][1400/7330] lr: 1.000e-04, eta: 6:10:28, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0467, loss_cls: 0.2071, acc: 92.6199, loss_bbox: 0.2566, loss_mask: 0.2513, loss: 0.7910 2023-11-13 17:50:28,207 - mmdet - INFO - Epoch [3][1450/7330] lr: 1.000e-04, eta: 6:10:12, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0483, loss_cls: 0.2091, acc: 92.5732, loss_bbox: 0.2503, loss_mask: 0.2497, loss: 0.7867 2023-11-13 17:50:43,908 - mmdet - INFO - Epoch [3][1500/7330] lr: 1.000e-04, eta: 6:09:58, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0485, loss_cls: 0.2086, acc: 92.4678, loss_bbox: 0.2509, loss_mask: 0.2416, loss: 0.7775 2023-11-13 17:50:59,386 - mmdet - INFO - Epoch [3][1550/7330] lr: 1.000e-04, eta: 6:09:42, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0457, loss_cls: 0.2007, acc: 92.7310, loss_bbox: 0.2481, loss_mask: 0.2402, loss: 0.7628 2023-11-13 17:51:14,800 - mmdet - INFO - Epoch [3][1600/7330] lr: 1.000e-04, eta: 6:09:27, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0486, loss_cls: 0.2058, acc: 92.7305, loss_bbox: 0.2475, loss_mask: 0.2449, loss: 0.7748 2023-11-13 17:51:30,118 - mmdet - INFO - Epoch [3][1650/7330] lr: 1.000e-04, eta: 6:09:11, time: 0.306, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0447, loss_cls: 0.1983, acc: 92.8987, loss_bbox: 0.2405, loss_mask: 0.2412, loss: 0.7519 2023-11-13 17:51:45,575 - mmdet - INFO - Epoch [3][1700/7330] lr: 1.000e-04, eta: 6:08:55, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0457, loss_cls: 0.2082, acc: 92.5471, loss_bbox: 0.2487, loss_mask: 0.2452, loss: 0.7746 2023-11-13 17:52:00,893 - mmdet - INFO - Epoch [3][1750/7330] lr: 1.000e-04, eta: 6:08:39, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0466, loss_cls: 0.2036, acc: 92.6853, loss_bbox: 0.2454, loss_mask: 0.2469, loss: 0.7694 2023-11-13 17:52:16,168 - mmdet - INFO - Epoch [3][1800/7330] lr: 1.000e-04, eta: 6:08:23, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0448, loss_cls: 0.1978, acc: 92.8999, loss_bbox: 0.2355, loss_mask: 0.2422, loss: 0.7473 2023-11-13 17:52:31,682 - mmdet - INFO - Epoch [3][1850/7330] lr: 1.000e-04, eta: 6:08:08, time: 0.310, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0486, loss_cls: 0.2071, acc: 92.6716, loss_bbox: 0.2495, loss_mask: 0.2463, loss: 0.7815 2023-11-13 17:52:47,362 - mmdet - INFO - Epoch [3][1900/7330] lr: 1.000e-04, eta: 6:07:53, time: 0.314, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0480, loss_cls: 0.2122, acc: 92.3496, loss_bbox: 0.2580, loss_mask: 0.2511, loss: 0.7976 2023-11-13 17:53:03,020 - mmdet - INFO - Epoch [3][1950/7330] lr: 1.000e-04, eta: 6:07:38, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0482, loss_cls: 0.2123, acc: 92.4827, loss_bbox: 0.2568, loss_mask: 0.2485, loss: 0.7964 2023-11-13 17:53:18,373 - mmdet - INFO - Epoch [3][2000/7330] lr: 1.000e-04, eta: 6:07:23, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0474, loss_cls: 0.2083, acc: 92.6985, loss_bbox: 0.2478, loss_mask: 0.2447, loss: 0.7763 2023-11-13 17:53:33,843 - mmdet - INFO - Epoch [3][2050/7330] lr: 1.000e-04, eta: 6:07:07, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0496, loss_cls: 0.2145, acc: 92.4856, loss_bbox: 0.2596, loss_mask: 0.2495, loss: 0.8034 2023-11-13 17:53:48,810 - mmdet - INFO - Epoch [3][2100/7330] lr: 1.000e-04, eta: 6:06:50, time: 0.299, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0501, loss_cls: 0.2105, acc: 92.5938, loss_bbox: 0.2535, loss_mask: 0.2595, loss: 0.8050 2023-11-13 17:54:03,909 - mmdet - INFO - Epoch [3][2150/7330] lr: 1.000e-04, eta: 6:06:33, time: 0.302, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0476, loss_cls: 0.2094, acc: 92.6003, loss_bbox: 0.2531, loss_mask: 0.2559, loss: 0.7953 2023-11-13 17:54:19,462 - mmdet - INFO - Epoch [3][2200/7330] lr: 1.000e-04, eta: 6:06:18, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0492, loss_cls: 0.2094, acc: 92.5476, loss_bbox: 0.2527, loss_mask: 0.2540, loss: 0.7941 2023-11-13 17:54:34,906 - mmdet - INFO - Epoch [3][2250/7330] lr: 1.000e-04, eta: 6:06:02, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0489, loss_cls: 0.2186, acc: 92.1895, loss_bbox: 0.2616, loss_mask: 0.2456, loss: 0.8029 2023-11-13 17:54:50,480 - mmdet - INFO - Epoch [3][2300/7330] lr: 1.000e-04, eta: 6:05:47, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0442, loss_cls: 0.2009, acc: 92.7771, loss_bbox: 0.2449, loss_mask: 0.2375, loss: 0.7542 2023-11-13 17:55:05,960 - mmdet - INFO - Epoch [3][2350/7330] lr: 1.000e-04, eta: 6:05:32, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0482, loss_cls: 0.2080, acc: 92.7322, loss_bbox: 0.2468, loss_mask: 0.2440, loss: 0.7765 2023-11-13 17:55:21,764 - mmdet - INFO - Epoch [3][2400/7330] lr: 1.000e-04, eta: 6:05:18, time: 0.316, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0483, loss_cls: 0.2031, acc: 92.6943, loss_bbox: 0.2480, loss_mask: 0.2434, loss: 0.7712 2023-11-13 17:55:37,128 - mmdet - INFO - Epoch [3][2450/7330] lr: 1.000e-04, eta: 6:05:02, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0450, loss_cls: 0.2109, acc: 92.5872, loss_bbox: 0.2553, loss_mask: 0.2465, loss: 0.7843 2023-11-13 17:55:52,127 - mmdet - INFO - Epoch [3][2500/7330] lr: 1.000e-04, eta: 6:04:45, time: 0.300, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0461, loss_cls: 0.2000, acc: 92.8396, loss_bbox: 0.2386, loss_mask: 0.2414, loss: 0.7518 2023-11-13 17:56:07,774 - mmdet - INFO - Epoch [3][2550/7330] lr: 1.000e-04, eta: 6:04:30, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0492, loss_cls: 0.2146, acc: 92.3423, loss_bbox: 0.2591, loss_mask: 0.2514, loss: 0.8019 2023-11-13 17:56:23,378 - mmdet - INFO - Epoch [3][2600/7330] lr: 1.000e-04, eta: 6:04:15, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0477, loss_cls: 0.2148, acc: 92.3225, loss_bbox: 0.2540, loss_mask: 0.2432, loss: 0.7896 2023-11-13 17:56:38,611 - mmdet - INFO - Epoch [3][2650/7330] lr: 1.000e-04, eta: 6:03:59, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0456, loss_cls: 0.2051, acc: 92.6409, loss_bbox: 0.2504, loss_mask: 0.2400, loss: 0.7666 2023-11-13 17:56:54,073 - mmdet - INFO - Epoch [3][2700/7330] lr: 1.000e-04, eta: 6:03:43, time: 0.309, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0473, loss_cls: 0.2072, acc: 92.5803, loss_bbox: 0.2519, loss_mask: 0.2485, loss: 0.7837 2023-11-13 17:57:09,291 - mmdet - INFO - Epoch [3][2750/7330] lr: 1.000e-04, eta: 6:03:27, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0453, loss_cls: 0.2034, acc: 92.6951, loss_bbox: 0.2498, loss_mask: 0.2415, loss: 0.7674 2023-11-13 17:57:24,883 - mmdet - INFO - Epoch [3][2800/7330] lr: 1.000e-04, eta: 6:03:12, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0457, loss_cls: 0.2021, acc: 92.8682, loss_bbox: 0.2488, loss_mask: 0.2504, loss: 0.7753 2023-11-13 17:57:39,813 - mmdet - INFO - Epoch [3][2850/7330] lr: 1.000e-04, eta: 6:02:54, time: 0.299, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0469, loss_cls: 0.2072, acc: 92.5840, loss_bbox: 0.2471, loss_mask: 0.2513, loss: 0.7801 2023-11-13 17:57:54,663 - mmdet - INFO - Epoch [3][2900/7330] lr: 1.000e-04, eta: 6:02:36, time: 0.297, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0430, loss_cls: 0.2027, acc: 92.7222, loss_bbox: 0.2413, loss_mask: 0.2412, loss: 0.7529 2023-11-13 17:58:09,800 - mmdet - INFO - Epoch [3][2950/7330] lr: 1.000e-04, eta: 6:02:20, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0464, loss_cls: 0.2056, acc: 92.7217, loss_bbox: 0.2460, loss_mask: 0.2447, loss: 0.7704 2023-11-13 17:58:24,994 - mmdet - INFO - Epoch [3][3000/7330] lr: 1.000e-04, eta: 6:02:03, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0464, loss_cls: 0.2087, acc: 92.5378, loss_bbox: 0.2539, loss_mask: 0.2462, loss: 0.7809 2023-11-13 17:58:40,301 - mmdet - INFO - Epoch [3][3050/7330] lr: 1.000e-04, eta: 6:01:47, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0473, loss_cls: 0.2058, acc: 92.5674, loss_bbox: 0.2534, loss_mask: 0.2477, loss: 0.7823 2023-11-13 17:58:55,653 - mmdet - INFO - Epoch [3][3100/7330] lr: 1.000e-04, eta: 6:01:31, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0449, loss_cls: 0.2022, acc: 92.7810, loss_bbox: 0.2445, loss_mask: 0.2426, loss: 0.7604 2023-11-13 17:59:11,195 - mmdet - INFO - Epoch [3][3150/7330] lr: 1.000e-04, eta: 6:01:16, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0502, loss_cls: 0.2056, acc: 92.6951, loss_bbox: 0.2477, loss_mask: 0.2454, loss: 0.7778 2023-11-13 17:59:27,019 - mmdet - INFO - Epoch [3][3200/7330] lr: 1.000e-04, eta: 6:01:02, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0467, loss_cls: 0.2062, acc: 92.7407, loss_bbox: 0.2444, loss_mask: 0.2427, loss: 0.7685 2023-11-13 17:59:42,532 - mmdet - INFO - Epoch [3][3250/7330] lr: 1.000e-04, eta: 6:00:47, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0494, loss_cls: 0.2027, acc: 92.8398, loss_bbox: 0.2468, loss_mask: 0.2488, loss: 0.7765 2023-11-13 17:59:58,088 - mmdet - INFO - Epoch [3][3300/7330] lr: 1.000e-04, eta: 6:00:32, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0465, loss_cls: 0.2086, acc: 92.3901, loss_bbox: 0.2507, loss_mask: 0.2455, loss: 0.7805 2023-11-13 18:00:13,623 - mmdet - INFO - Epoch [3][3350/7330] lr: 1.000e-04, eta: 6:00:17, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0482, loss_cls: 0.2098, acc: 92.4570, loss_bbox: 0.2522, loss_mask: 0.2402, loss: 0.7797 2023-11-13 18:00:28,514 - mmdet - INFO - Epoch [3][3400/7330] lr: 1.000e-04, eta: 5:59:59, time: 0.298, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0431, loss_cls: 0.1982, acc: 92.9067, loss_bbox: 0.2431, loss_mask: 0.2447, loss: 0.7548 2023-11-13 18:00:43,419 - mmdet - INFO - Epoch [3][3450/7330] lr: 1.000e-04, eta: 5:59:42, time: 0.298, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0450, loss_cls: 0.1999, acc: 92.8875, loss_bbox: 0.2458, loss_mask: 0.2439, loss: 0.7623 2023-11-13 18:00:58,830 - mmdet - INFO - Epoch [3][3500/7330] lr: 1.000e-04, eta: 5:59:26, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0477, loss_cls: 0.2016, acc: 92.8679, loss_bbox: 0.2434, loss_mask: 0.2454, loss: 0.7653 2023-11-13 18:01:13,973 - mmdet - INFO - Epoch [3][3550/7330] lr: 1.000e-04, eta: 5:59:10, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0468, loss_cls: 0.2047, acc: 92.7427, loss_bbox: 0.2488, loss_mask: 0.2424, loss: 0.7722 2023-11-13 18:01:29,508 - mmdet - INFO - Epoch [3][3600/7330] lr: 1.000e-04, eta: 5:58:54, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0485, loss_cls: 0.2191, acc: 92.1538, loss_bbox: 0.2618, loss_mask: 0.2513, loss: 0.8135 2023-11-13 18:01:44,833 - mmdet - INFO - Epoch [3][3650/7330] lr: 1.000e-04, eta: 5:58:39, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0467, loss_cls: 0.2061, acc: 92.5693, loss_bbox: 0.2518, loss_mask: 0.2440, loss: 0.7763 2023-11-13 18:02:00,442 - mmdet - INFO - Epoch [3][3700/7330] lr: 1.000e-04, eta: 5:58:24, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0505, loss_cls: 0.2139, acc: 92.2783, loss_bbox: 0.2582, loss_mask: 0.2527, loss: 0.8053 2023-11-13 18:02:15,738 - mmdet - INFO - Epoch [3][3750/7330] lr: 1.000e-04, eta: 5:58:08, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0462, loss_cls: 0.2048, acc: 92.7349, loss_bbox: 0.2487, loss_mask: 0.2529, loss: 0.7822 2023-11-13 18:02:31,030 - mmdet - INFO - Epoch [3][3800/7330] lr: 1.000e-04, eta: 5:57:52, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0466, loss_cls: 0.2000, acc: 92.6787, loss_bbox: 0.2494, loss_mask: 0.2482, loss: 0.7729 2023-11-13 18:02:46,524 - mmdet - INFO - Epoch [3][3850/7330] lr: 1.000e-04, eta: 5:57:36, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0484, loss_cls: 0.2117, acc: 92.3889, loss_bbox: 0.2499, loss_mask: 0.2448, loss: 0.7856 2023-11-13 18:03:01,793 - mmdet - INFO - Epoch [3][3900/7330] lr: 1.000e-04, eta: 5:57:20, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0442, loss_cls: 0.2015, acc: 92.9382, loss_bbox: 0.2402, loss_mask: 0.2455, loss: 0.7597 2023-11-13 18:03:17,331 - mmdet - INFO - Epoch [3][3950/7330] lr: 1.000e-04, eta: 5:57:05, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0467, loss_cls: 0.2032, acc: 92.7405, loss_bbox: 0.2440, loss_mask: 0.2446, loss: 0.7672 2023-11-13 18:03:33,297 - mmdet - INFO - Epoch [3][4000/7330] lr: 1.000e-04, eta: 5:56:52, time: 0.320, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0488, loss_cls: 0.2107, acc: 92.4839, loss_bbox: 0.2538, loss_mask: 0.2539, loss: 0.7975 2023-11-13 18:03:48,785 - mmdet - INFO - Epoch [3][4050/7330] lr: 1.000e-04, eta: 5:56:36, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0440, loss_cls: 0.2022, acc: 92.8105, loss_bbox: 0.2438, loss_mask: 0.2428, loss: 0.7603 2023-11-13 18:04:04,037 - mmdet - INFO - Epoch [3][4100/7330] lr: 1.000e-04, eta: 5:56:20, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0457, loss_cls: 0.2093, acc: 92.7830, loss_bbox: 0.2448, loss_mask: 0.2430, loss: 0.7715 2023-11-13 18:04:19,512 - mmdet - INFO - Epoch [3][4150/7330] lr: 1.000e-04, eta: 5:56:05, time: 0.310, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0457, loss_cls: 0.2071, acc: 92.6714, loss_bbox: 0.2518, loss_mask: 0.2457, loss: 0.7771 2023-11-13 18:04:34,667 - mmdet - INFO - Epoch [3][4200/7330] lr: 1.000e-04, eta: 5:55:48, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0461, loss_cls: 0.1987, acc: 92.9490, loss_bbox: 0.2394, loss_mask: 0.2382, loss: 0.7495 2023-11-13 18:04:49,806 - mmdet - INFO - Epoch [3][4250/7330] lr: 1.000e-04, eta: 5:55:32, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0462, loss_cls: 0.2045, acc: 92.8325, loss_bbox: 0.2455, loss_mask: 0.2479, loss: 0.7729 2023-11-13 18:05:05,109 - mmdet - INFO - Epoch [3][4300/7330] lr: 1.000e-04, eta: 5:55:16, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0451, loss_cls: 0.2046, acc: 92.7341, loss_bbox: 0.2471, loss_mask: 0.2465, loss: 0.7706 2023-11-13 18:05:20,689 - mmdet - INFO - Epoch [3][4350/7330] lr: 1.000e-04, eta: 5:55:01, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0478, loss_cls: 0.2033, acc: 92.7654, loss_bbox: 0.2442, loss_mask: 0.2426, loss: 0.7667 2023-11-13 18:05:36,242 - mmdet - INFO - Epoch [3][4400/7330] lr: 1.000e-04, eta: 5:54:46, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0455, loss_cls: 0.2025, acc: 92.8506, loss_bbox: 0.2439, loss_mask: 0.2409, loss: 0.7611 2023-11-13 18:05:51,613 - mmdet - INFO - Epoch [3][4450/7330] lr: 1.000e-04, eta: 5:54:30, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0473, loss_cls: 0.2053, acc: 92.6667, loss_bbox: 0.2484, loss_mask: 0.2439, loss: 0.7740 2023-11-13 18:06:07,248 - mmdet - INFO - Epoch [3][4500/7330] lr: 1.000e-04, eta: 5:54:15, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0461, loss_cls: 0.2073, acc: 92.5845, loss_bbox: 0.2462, loss_mask: 0.2419, loss: 0.7685 2023-11-13 18:06:22,572 - mmdet - INFO - Epoch [3][4550/7330] lr: 1.000e-04, eta: 5:53:59, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0469, loss_cls: 0.2036, acc: 92.7122, loss_bbox: 0.2435, loss_mask: 0.2384, loss: 0.7598 2023-11-13 18:06:37,833 - mmdet - INFO - Epoch [3][4600/7330] lr: 1.000e-04, eta: 5:53:43, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0429, loss_cls: 0.2026, acc: 92.7888, loss_bbox: 0.2406, loss_mask: 0.2433, loss: 0.7577 2023-11-13 18:06:53,416 - mmdet - INFO - Epoch [3][4650/7330] lr: 1.000e-04, eta: 5:53:28, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0463, loss_cls: 0.2101, acc: 92.6960, loss_bbox: 0.2450, loss_mask: 0.2458, loss: 0.7779 2023-11-13 18:07:08,867 - mmdet - INFO - Epoch [3][4700/7330] lr: 1.000e-04, eta: 5:53:13, time: 0.309, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0445, loss_cls: 0.1985, acc: 93.0046, loss_bbox: 0.2417, loss_mask: 0.2442, loss: 0.7565 2023-11-13 18:07:24,667 - mmdet - INFO - Epoch [3][4750/7330] lr: 1.000e-04, eta: 5:52:59, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0447, loss_cls: 0.1991, acc: 92.8911, loss_bbox: 0.2440, loss_mask: 0.2408, loss: 0.7569 2023-11-13 18:07:40,540 - mmdet - INFO - Epoch [3][4800/7330] lr: 1.000e-04, eta: 5:52:45, time: 0.317, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0517, loss_cls: 0.2204, acc: 92.1372, loss_bbox: 0.2688, loss_mask: 0.2505, loss: 0.8236 2023-11-13 18:07:56,032 - mmdet - INFO - Epoch [3][4850/7330] lr: 1.000e-04, eta: 5:52:29, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0439, loss_cls: 0.2097, acc: 92.5625, loss_bbox: 0.2458, loss_mask: 0.2472, loss: 0.7744 2023-11-13 18:08:11,304 - mmdet - INFO - Epoch [3][4900/7330] lr: 1.000e-04, eta: 5:52:13, time: 0.305, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0455, loss_cls: 0.2027, acc: 92.7102, loss_bbox: 0.2440, loss_mask: 0.2477, loss: 0.7683 2023-11-13 18:08:26,779 - mmdet - INFO - Epoch [3][4950/7330] lr: 1.000e-04, eta: 5:51:58, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0460, loss_cls: 0.2089, acc: 92.4924, loss_bbox: 0.2517, loss_mask: 0.2473, loss: 0.7804 2023-11-13 18:08:42,392 - mmdet - INFO - Epoch [3][5000/7330] lr: 1.000e-04, eta: 5:51:43, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0466, loss_cls: 0.2132, acc: 92.4038, loss_bbox: 0.2558, loss_mask: 0.2507, loss: 0.7938 2023-11-13 18:08:57,565 - mmdet - INFO - Epoch [3][5050/7330] lr: 1.000e-04, eta: 5:51:27, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0429, loss_cls: 0.1908, acc: 93.2295, loss_bbox: 0.2317, loss_mask: 0.2333, loss: 0.7263 2023-11-13 18:09:13,370 - mmdet - INFO - Epoch [3][5100/7330] lr: 1.000e-04, eta: 5:51:12, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0482, loss_cls: 0.2030, acc: 92.9150, loss_bbox: 0.2418, loss_mask: 0.2389, loss: 0.7604 2023-11-13 18:09:28,662 - mmdet - INFO - Epoch [3][5150/7330] lr: 1.000e-04, eta: 5:50:56, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0479, loss_cls: 0.2119, acc: 92.2656, loss_bbox: 0.2584, loss_mask: 0.2509, loss: 0.7995 2023-11-13 18:09:44,179 - mmdet - INFO - Epoch [3][5200/7330] lr: 1.000e-04, eta: 5:50:41, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0457, loss_cls: 0.2057, acc: 92.6130, loss_bbox: 0.2463, loss_mask: 0.2415, loss: 0.7669 2023-11-13 18:09:59,488 - mmdet - INFO - Epoch [3][5250/7330] lr: 1.000e-04, eta: 5:50:25, time: 0.306, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0440, loss_cls: 0.2035, acc: 92.7400, loss_bbox: 0.2509, loss_mask: 0.2431, loss: 0.7683 2023-11-13 18:10:14,927 - mmdet - INFO - Epoch [3][5300/7330] lr: 1.000e-04, eta: 5:50:10, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0477, loss_cls: 0.2092, acc: 92.5774, loss_bbox: 0.2509, loss_mask: 0.2484, loss: 0.7869 2023-11-13 18:10:30,327 - mmdet - INFO - Epoch [3][5350/7330] lr: 1.000e-04, eta: 5:49:54, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0460, loss_cls: 0.1908, acc: 93.1665, loss_bbox: 0.2333, loss_mask: 0.2338, loss: 0.7312 2023-11-13 18:10:45,677 - mmdet - INFO - Epoch [3][5400/7330] lr: 1.000e-04, eta: 5:49:38, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0443, loss_cls: 0.2015, acc: 92.6602, loss_bbox: 0.2474, loss_mask: 0.2440, loss: 0.7632 2023-11-13 18:11:01,066 - mmdet - INFO - Epoch [3][5450/7330] lr: 1.000e-04, eta: 5:49:23, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0454, loss_cls: 0.2125, acc: 92.4922, loss_bbox: 0.2542, loss_mask: 0.2480, loss: 0.7877 2023-11-13 18:11:16,603 - mmdet - INFO - Epoch [3][5500/7330] lr: 1.000e-04, eta: 5:49:08, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0483, loss_cls: 0.2182, acc: 92.2961, loss_bbox: 0.2587, loss_mask: 0.2500, loss: 0.8052 2023-11-13 18:11:32,158 - mmdet - INFO - Epoch [3][5550/7330] lr: 1.000e-04, eta: 5:48:52, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0464, loss_cls: 0.2077, acc: 92.6489, loss_bbox: 0.2431, loss_mask: 0.2427, loss: 0.7700 2023-11-13 18:11:47,448 - mmdet - INFO - Epoch [3][5600/7330] lr: 1.000e-04, eta: 5:48:36, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0456, loss_cls: 0.2039, acc: 92.7615, loss_bbox: 0.2453, loss_mask: 0.2445, loss: 0.7675 2023-11-13 18:12:02,842 - mmdet - INFO - Epoch [3][5650/7330] lr: 1.000e-04, eta: 5:48:21, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0482, loss_cls: 0.2130, acc: 92.2830, loss_bbox: 0.2545, loss_mask: 0.2488, loss: 0.7968 2023-11-13 18:12:18,415 - mmdet - INFO - Epoch [3][5700/7330] lr: 1.000e-04, eta: 5:48:06, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0472, loss_cls: 0.2057, acc: 92.6958, loss_bbox: 0.2528, loss_mask: 0.2446, loss: 0.7796 2023-11-13 18:12:33,716 - mmdet - INFO - Epoch [3][5750/7330] lr: 1.000e-04, eta: 5:47:50, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0450, loss_cls: 0.2015, acc: 92.8174, loss_bbox: 0.2450, loss_mask: 0.2399, loss: 0.7590 2023-11-13 18:12:49,226 - mmdet - INFO - Epoch [3][5800/7330] lr: 1.000e-04, eta: 5:47:35, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0463, loss_cls: 0.2222, acc: 92.2285, loss_bbox: 0.2541, loss_mask: 0.2455, loss: 0.7960 2023-11-13 18:13:04,453 - mmdet - INFO - Epoch [3][5850/7330] lr: 1.000e-04, eta: 5:47:18, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0458, loss_cls: 0.2095, acc: 92.6467, loss_bbox: 0.2439, loss_mask: 0.2394, loss: 0.7658 2023-11-13 18:13:19,523 - mmdet - INFO - Epoch [3][5900/7330] lr: 1.000e-04, eta: 5:47:02, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0433, loss_cls: 0.2033, acc: 92.8149, loss_bbox: 0.2406, loss_mask: 0.2407, loss: 0.7542 2023-11-13 18:13:34,684 - mmdet - INFO - Epoch [3][5950/7330] lr: 1.000e-04, eta: 5:46:45, time: 0.303, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0443, loss_cls: 0.2076, acc: 92.8252, loss_bbox: 0.2425, loss_mask: 0.2456, loss: 0.7670 2023-11-13 18:13:50,008 - mmdet - INFO - Epoch [3][6000/7330] lr: 1.000e-04, eta: 5:46:30, time: 0.306, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0423, loss_cls: 0.1912, acc: 93.2581, loss_bbox: 0.2307, loss_mask: 0.2413, loss: 0.7335 2023-11-13 18:14:05,488 - mmdet - INFO - Epoch [3][6050/7330] lr: 1.000e-04, eta: 5:46:14, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0446, loss_cls: 0.2005, acc: 92.9351, loss_bbox: 0.2401, loss_mask: 0.2412, loss: 0.7543 2023-11-13 18:14:20,755 - mmdet - INFO - Epoch [3][6100/7330] lr: 1.000e-04, eta: 5:45:58, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0481, loss_cls: 0.2053, acc: 92.6890, loss_bbox: 0.2435, loss_mask: 0.2471, loss: 0.7725 2023-11-13 18:14:36,197 - mmdet - INFO - Epoch [3][6150/7330] lr: 1.000e-04, eta: 5:45:43, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0438, loss_cls: 0.1979, acc: 92.8687, loss_bbox: 0.2371, loss_mask: 0.2402, loss: 0.7462 2023-11-13 18:14:51,403 - mmdet - INFO - Epoch [3][6200/7330] lr: 1.000e-04, eta: 5:45:27, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0470, loss_cls: 0.2035, acc: 92.7075, loss_bbox: 0.2467, loss_mask: 0.2419, loss: 0.7658 2023-11-13 18:15:07,086 - mmdet - INFO - Epoch [3][6250/7330] lr: 1.000e-04, eta: 5:45:12, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0499, loss_cls: 0.2142, acc: 92.4346, loss_bbox: 0.2502, loss_mask: 0.2509, loss: 0.7960 2023-11-13 18:15:22,602 - mmdet - INFO - Epoch [3][6300/7330] lr: 1.000e-04, eta: 5:44:57, time: 0.310, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0480, loss_cls: 0.2065, acc: 92.6475, loss_bbox: 0.2482, loss_mask: 0.2406, loss: 0.7716 2023-11-13 18:15:37,936 - mmdet - INFO - Epoch [3][6350/7330] lr: 1.000e-04, eta: 5:44:41, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0473, loss_cls: 0.2055, acc: 92.6799, loss_bbox: 0.2487, loss_mask: 0.2492, loss: 0.7769 2023-11-13 18:15:53,574 - mmdet - INFO - Epoch [3][6400/7330] lr: 1.000e-04, eta: 5:44:26, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0455, loss_cls: 0.2013, acc: 92.8184, loss_bbox: 0.2500, loss_mask: 0.2457, loss: 0.7705 2023-11-13 18:16:08,821 - mmdet - INFO - Epoch [3][6450/7330] lr: 1.000e-04, eta: 5:44:10, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0463, loss_cls: 0.2032, acc: 92.8228, loss_bbox: 0.2466, loss_mask: 0.2418, loss: 0.7645 2023-11-13 18:16:24,266 - mmdet - INFO - Epoch [3][6500/7330] lr: 1.000e-04, eta: 5:43:54, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0454, loss_cls: 0.1950, acc: 93.0479, loss_bbox: 0.2343, loss_mask: 0.2343, loss: 0.7369 2023-11-13 18:16:39,648 - mmdet - INFO - Epoch [3][6550/7330] lr: 1.000e-04, eta: 5:43:39, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0434, loss_cls: 0.2029, acc: 92.7964, loss_bbox: 0.2404, loss_mask: 0.2478, loss: 0.7605 2023-11-13 18:16:55,139 - mmdet - INFO - Epoch [3][6600/7330] lr: 1.000e-04, eta: 5:43:24, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0447, loss_cls: 0.2063, acc: 92.8054, loss_bbox: 0.2410, loss_mask: 0.2393, loss: 0.7576 2023-11-13 18:17:10,734 - mmdet - INFO - Epoch [3][6650/7330] lr: 1.000e-04, eta: 5:43:09, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0424, loss_cls: 0.1972, acc: 92.9883, loss_bbox: 0.2396, loss_mask: 0.2387, loss: 0.7427 2023-11-13 18:17:25,880 - mmdet - INFO - Epoch [3][6700/7330] lr: 1.000e-04, eta: 5:42:52, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0426, loss_cls: 0.2005, acc: 92.9648, loss_bbox: 0.2385, loss_mask: 0.2420, loss: 0.7491 2023-11-13 18:17:41,240 - mmdet - INFO - Epoch [3][6750/7330] lr: 1.000e-04, eta: 5:42:36, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0417, loss_cls: 0.2014, acc: 92.8406, loss_bbox: 0.2411, loss_mask: 0.2409, loss: 0.7500 2023-11-13 18:17:57,128 - mmdet - INFO - Epoch [3][6800/7330] lr: 1.000e-04, eta: 5:42:22, time: 0.318, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0475, loss_cls: 0.2112, acc: 92.5046, loss_bbox: 0.2529, loss_mask: 0.2427, loss: 0.7817 2023-11-13 18:18:12,272 - mmdet - INFO - Epoch [3][6850/7330] lr: 1.000e-04, eta: 5:42:06, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0457, loss_cls: 0.1974, acc: 92.9736, loss_bbox: 0.2345, loss_mask: 0.2411, loss: 0.7488 2023-11-13 18:18:27,538 - mmdet - INFO - Epoch [3][6900/7330] lr: 1.000e-04, eta: 5:41:50, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0445, loss_cls: 0.2003, acc: 92.8213, loss_bbox: 0.2451, loss_mask: 0.2454, loss: 0.7623 2023-11-13 18:18:43,481 - mmdet - INFO - Epoch [3][6950/7330] lr: 1.000e-04, eta: 5:41:36, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0483, loss_cls: 0.2131, acc: 92.4563, loss_bbox: 0.2570, loss_mask: 0.2473, loss: 0.7943 2023-11-13 18:18:58,827 - mmdet - INFO - Epoch [3][7000/7330] lr: 1.000e-04, eta: 5:41:20, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0483, loss_cls: 0.2077, acc: 92.6885, loss_bbox: 0.2484, loss_mask: 0.2396, loss: 0.7732 2023-11-13 18:19:13,527 - mmdet - INFO - Epoch [3][7050/7330] lr: 1.000e-04, eta: 5:41:03, time: 0.294, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0403, loss_cls: 0.1964, acc: 93.1438, loss_bbox: 0.2325, loss_mask: 0.2384, loss: 0.7325 2023-11-13 18:19:28,918 - mmdet - INFO - Epoch [3][7100/7330] lr: 1.000e-04, eta: 5:40:47, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0460, loss_cls: 0.2040, acc: 92.8801, loss_bbox: 0.2446, loss_mask: 0.2473, loss: 0.7694 2023-11-13 18:19:44,063 - mmdet - INFO - Epoch [3][7150/7330] lr: 1.000e-04, eta: 5:40:31, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0451, loss_cls: 0.2017, acc: 92.9495, loss_bbox: 0.2395, loss_mask: 0.2390, loss: 0.7527 2023-11-13 18:19:59,190 - mmdet - INFO - Epoch [3][7200/7330] lr: 1.000e-04, eta: 5:40:14, time: 0.302, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0464, loss_cls: 0.2008, acc: 92.8813, loss_bbox: 0.2391, loss_mask: 0.2388, loss: 0.7532 2023-11-13 18:20:14,587 - mmdet - INFO - Epoch [3][7250/7330] lr: 1.000e-04, eta: 5:39:59, time: 0.308, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0435, loss_cls: 0.2047, acc: 92.8494, loss_bbox: 0.2413, loss_mask: 0.2446, loss: 0.7617 2023-11-13 18:20:29,833 - mmdet - INFO - Epoch [3][7300/7330] lr: 1.000e-04, eta: 5:39:43, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0409, loss_cls: 0.1931, acc: 93.0356, loss_bbox: 0.2358, loss_mask: 0.2391, loss: 0.7344 2023-11-13 18:20:39,740 - mmdet - INFO - Saving checkpoint at 3 epochs 2023-11-13 18:21:26,793 - mmdet - INFO - Evaluating bbox... 2023-11-13 18:21:59,340 - 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 ] = 0.656 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.468 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.267 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.470 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.552 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 ] = 0.378 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 ] = 0.700 2023-11-13 18:21:59,343 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.545 | bicycle | 0.311 | car | 0.428 | | motorcycle | 0.439 | airplane | 0.649 | bus | 0.635 | | train | 0.622 | truck | 0.370 | boat | 0.296 | | traffic light | 0.288 | fire hydrant | 0.650 | stop sign | 0.654 | | parking meter | 0.462 | bench | 0.238 | bird | 0.383 | | cat | 0.678 | dog | 0.658 | horse | 0.578 | | sheep | 0.553 | cow | 0.594 | elephant | 0.629 | | bear | 0.724 | zebra | 0.654 | giraffe | 0.645 | | backpack | 0.170 | umbrella | 0.425 | handbag | 0.162 | | tie | 0.319 | suitcase | 0.390 | frisbee | 0.681 | | skis | 0.231 | snowboard | 0.363 | sports ball | 0.444 | | kite | 0.423 | baseball bat | 0.318 | baseball glove | 0.378 | | skateboard | 0.515 | surfboard | 0.399 | tennis racket | 0.476 | | bottle | 0.401 | wine glass | 0.364 | cup | 0.453 | | fork | 0.363 | knife | 0.231 | spoon | 0.197 | | bowl | 0.441 | banana | 0.267 | apple | 0.226 | | sandwich | 0.364 | orange | 0.332 | broccoli | 0.255 | | carrot | 0.233 | hot dog | 0.377 | pizza | 0.469 | | donut | 0.514 | cake | 0.386 | chair | 0.299 | | couch | 0.422 | potted plant | 0.273 | bed | 0.430 | | dining table | 0.267 | toilet | 0.558 | tv | 0.572 | | laptop | 0.595 | mouse | 0.615 | remote | 0.328 | | keyboard | 0.501 | cell phone | 0.358 | microwave | 0.569 | | oven | 0.332 | toaster | 0.429 | sink | 0.388 | | refrigerator | 0.548 | book | 0.166 | clock | 0.515 | | vase | 0.396 | scissors | 0.280 | teddy bear | 0.469 | | hair drier | 0.141 | toothbrush | 0.258 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:21:59,343 - mmdet - INFO - Evaluating segm... 2023-11-13 18:22:38,613 - 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 ] = 0.623 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.413 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.198 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.427 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.557 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.515 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.515 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.515 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.328 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.561 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.669 2023-11-13 18:22:38,615 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.476 | bicycle | 0.174 | car | 0.416 | | motorcycle | 0.338 | airplane | 0.513 | bus | 0.631 | | train | 0.624 | truck | 0.363 | boat | 0.258 | | traffic light | 0.282 | fire hydrant | 0.642 | stop sign | 0.662 | | parking meter | 0.487 | bench | 0.173 | bird | 0.319 | | cat | 0.705 | dog | 0.627 | horse | 0.427 | | sheep | 0.489 | cow | 0.496 | elephant | 0.567 | | bear | 0.723 | zebra | 0.556 | giraffe | 0.501 | | backpack | 0.180 | umbrella | 0.481 | handbag | 0.161 | | tie | 0.308 | suitcase | 0.407 | frisbee | 0.648 | | skis | 0.040 | snowboard | 0.258 | sports ball | 0.458 | | kite | 0.290 | baseball bat | 0.265 | baseball glove | 0.417 | | skateboard | 0.295 | surfboard | 0.338 | tennis racket | 0.552 | | bottle | 0.396 | wine glass | 0.320 | cup | 0.462 | | fork | 0.187 | knife | 0.151 | spoon | 0.141 | | bowl | 0.412 | banana | 0.220 | apple | 0.222 | | sandwich | 0.391 | orange | 0.342 | broccoli | 0.244 | | carrot | 0.210 | hot dog | 0.301 | pizza | 0.472 | | donut | 0.526 | cake | 0.397 | chair | 0.207 | | couch | 0.369 | potted plant | 0.232 | bed | 0.314 | | dining table | 0.158 | toilet | 0.563 | tv | 0.605 | | laptop | 0.621 | mouse | 0.622 | remote | 0.314 | | keyboard | 0.501 | cell phone | 0.337 | microwave | 0.602 | | oven | 0.325 | toaster | 0.463 | sink | 0.367 | | refrigerator | 0.557 | book | 0.118 | clock | 0.518 | | vase | 0.399 | scissors | 0.233 | teddy bear | 0.461 | | hair drier | 0.061 | toothbrush | 0.152 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:22:39,097 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_2.pth was removed 2023-11-13 18:22:40,678 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_3.pth. 2023-11-13 18:22:40,678 - mmdet - INFO - Best bbox_mAP is 0.4245 at 3 epoch. 2023-11-13 18:22:40,678 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 18:22:40,678 - mmdet - INFO - Epoch(val) [3][625] bbox_mAP: 0.4245, bbox_mAP_50: 0.6556, bbox_mAP_75: 0.4684, bbox_mAP_s: 0.2665, bbox_mAP_m: 0.4704, bbox_mAP_l: 0.5518, bbox_mAP_copypaste: 0.4245 0.6556 0.4684 0.2665 0.4704 0.5518, segm_mAP: 0.3880, segm_mAP_50: 0.6227, segm_mAP_75: 0.4134, segm_mAP_s: 0.1980, segm_mAP_m: 0.4268, segm_mAP_l: 0.5574, segm_mAP_copypaste: 0.3880 0.6227 0.4134 0.1980 0.4268 0.5574 2023-11-13 18:23:00,038 - mmdet - INFO - Epoch [4][50/7330] lr: 1.000e-04, eta: 5:39:02, time: 0.387, data_time: 0.089, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0423, loss_cls: 0.1812, acc: 93.4614, loss_bbox: 0.2300, loss_mask: 0.2332, loss: 0.7099 2023-11-13 18:23:16,048 - mmdet - INFO - Epoch [4][100/7330] lr: 1.000e-04, eta: 5:38:48, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0444, loss_cls: 0.1978, acc: 92.9360, loss_bbox: 0.2398, loss_mask: 0.2299, loss: 0.7380 2023-11-13 18:23:31,876 - mmdet - INFO - Epoch [4][150/7330] lr: 1.000e-04, eta: 5:38:34, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0441, loss_cls: 0.1840, acc: 93.2524, loss_bbox: 0.2340, loss_mask: 0.2407, loss: 0.7288 2023-11-13 18:23:47,638 - mmdet - INFO - Epoch [4][200/7330] lr: 1.000e-04, eta: 5:38:19, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0464, loss_cls: 0.1911, acc: 93.0840, loss_bbox: 0.2373, loss_mask: 0.2414, loss: 0.7421 2023-11-13 18:24:03,032 - mmdet - INFO - Epoch [4][250/7330] lr: 1.000e-04, eta: 5:38:04, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0424, loss_cls: 0.1967, acc: 92.8733, loss_bbox: 0.2436, loss_mask: 0.2381, loss: 0.7434 2023-11-13 18:24:18,618 - mmdet - INFO - Epoch [4][300/7330] lr: 1.000e-04, eta: 5:37:49, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0440, loss_cls: 0.1926, acc: 93.0862, loss_bbox: 0.2383, loss_mask: 0.2397, loss: 0.7386 2023-11-13 18:24:34,671 - mmdet - INFO - Epoch [4][350/7330] lr: 1.000e-04, eta: 5:37:35, time: 0.321, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0467, loss_cls: 0.1942, acc: 92.8765, loss_bbox: 0.2425, loss_mask: 0.2395, loss: 0.7476 2023-11-13 18:24:50,517 - mmdet - INFO - Epoch [4][400/7330] lr: 1.000e-04, eta: 5:37:21, time: 0.317, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0459, loss_cls: 0.2015, acc: 92.8000, loss_bbox: 0.2424, loss_mask: 0.2425, loss: 0.7601 2023-11-13 18:25:06,243 - mmdet - INFO - Epoch [4][450/7330] lr: 1.000e-04, eta: 5:37:07, time: 0.314, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0456, loss_cls: 0.1943, acc: 92.9182, loss_bbox: 0.2413, loss_mask: 0.2317, loss: 0.7397 2023-11-13 18:25:21,930 - mmdet - INFO - Epoch [4][500/7330] lr: 1.000e-04, eta: 5:36:52, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0459, loss_cls: 0.1898, acc: 93.1292, loss_bbox: 0.2381, loss_mask: 0.2364, loss: 0.7359 2023-11-13 18:25:37,240 - mmdet - INFO - Epoch [4][550/7330] lr: 1.000e-04, eta: 5:36:36, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0450, loss_cls: 0.1940, acc: 92.9587, loss_bbox: 0.2406, loss_mask: 0.2365, loss: 0.7408 2023-11-13 18:25:53,062 - mmdet - INFO - Epoch [4][600/7330] lr: 1.000e-04, eta: 5:36:22, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0443, loss_cls: 0.1966, acc: 92.8569, loss_bbox: 0.2442, loss_mask: 0.2399, loss: 0.7500 2023-11-13 18:26:08,931 - mmdet - INFO - Epoch [4][650/7330] lr: 1.000e-04, eta: 5:36:07, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0428, loss_cls: 0.1982, acc: 93.0081, loss_bbox: 0.2408, loss_mask: 0.2354, loss: 0.7425 2023-11-13 18:26:24,534 - mmdet - INFO - Epoch [4][700/7330] lr: 1.000e-04, eta: 5:35:53, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0445, loss_cls: 0.1902, acc: 93.1895, loss_bbox: 0.2336, loss_mask: 0.2352, loss: 0.7321 2023-11-13 18:26:40,123 - mmdet - INFO - Epoch [4][750/7330] lr: 1.000e-04, eta: 5:35:38, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0428, loss_cls: 0.1866, acc: 93.1887, loss_bbox: 0.2321, loss_mask: 0.2318, loss: 0.7163 2023-11-13 18:26:55,720 - mmdet - INFO - Epoch [4][800/7330] lr: 1.000e-04, eta: 5:35:23, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0451, loss_cls: 0.1991, acc: 92.8669, loss_bbox: 0.2428, loss_mask: 0.2366, loss: 0.7476 2023-11-13 18:27:11,207 - mmdet - INFO - Epoch [4][850/7330] lr: 1.000e-04, eta: 5:35:07, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0431, loss_cls: 0.1933, acc: 92.9702, loss_bbox: 0.2415, loss_mask: 0.2375, loss: 0.7394 2023-11-13 18:27:27,052 - mmdet - INFO - Epoch [4][900/7330] lr: 1.000e-04, eta: 5:34:53, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0443, loss_cls: 0.1910, acc: 92.9658, loss_bbox: 0.2432, loss_mask: 0.2367, loss: 0.7391 2023-11-13 18:27:42,312 - mmdet - INFO - Epoch [4][950/7330] lr: 1.000e-04, eta: 5:34:37, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0423, loss_cls: 0.1966, acc: 92.8276, loss_bbox: 0.2385, loss_mask: 0.2370, loss: 0.7390 2023-11-13 18:27:57,685 - mmdet - INFO - Epoch [4][1000/7330] lr: 1.000e-04, eta: 5:34:21, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0436, loss_cls: 0.1902, acc: 93.1379, loss_bbox: 0.2313, loss_mask: 0.2313, loss: 0.7227 2023-11-13 18:28:12,870 - mmdet - INFO - Epoch [4][1050/7330] lr: 1.000e-04, eta: 5:34:05, time: 0.304, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0438, loss_cls: 0.1925, acc: 93.0232, loss_bbox: 0.2375, loss_mask: 0.2378, loss: 0.7382 2023-11-13 18:28:28,238 - mmdet - INFO - Epoch [4][1100/7330] lr: 1.000e-04, eta: 5:33:50, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0441, loss_cls: 0.1959, acc: 93.0291, loss_bbox: 0.2390, loss_mask: 0.2411, loss: 0.7456 2023-11-13 18:28:43,514 - mmdet - INFO - Epoch [4][1150/7330] lr: 1.000e-04, eta: 5:33:34, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0445, loss_cls: 0.1921, acc: 93.0742, loss_bbox: 0.2376, loss_mask: 0.2367, loss: 0.7370 2023-11-13 18:28:59,220 - mmdet - INFO - Epoch [4][1200/7330] lr: 1.000e-04, eta: 5:33:19, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0454, loss_cls: 0.1972, acc: 92.7332, loss_bbox: 0.2398, loss_mask: 0.2426, loss: 0.7531 2023-11-13 18:29:14,144 - mmdet - INFO - Epoch [4][1250/7330] lr: 1.000e-04, eta: 5:33:02, time: 0.299, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0412, loss_cls: 0.1896, acc: 93.2017, loss_bbox: 0.2317, loss_mask: 0.2316, loss: 0.7192 2023-11-13 18:29:29,683 - mmdet - INFO - Epoch [4][1300/7330] lr: 1.000e-04, eta: 5:32:47, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0450, loss_cls: 0.1943, acc: 93.0627, loss_bbox: 0.2406, loss_mask: 0.2369, loss: 0.7427 2023-11-13 18:29:45,600 - mmdet - INFO - Epoch [4][1350/7330] lr: 1.000e-04, eta: 5:32:33, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0477, loss_cls: 0.2059, acc: 92.5615, loss_bbox: 0.2522, loss_mask: 0.2432, loss: 0.7758 2023-11-13 18:30:00,736 - mmdet - INFO - Epoch [4][1400/7330] lr: 1.000e-04, eta: 5:32:17, time: 0.303, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0418, loss_cls: 0.1876, acc: 93.1775, loss_bbox: 0.2348, loss_mask: 0.2367, loss: 0.7250 2023-11-13 18:30:16,394 - mmdet - INFO - Epoch [4][1450/7330] lr: 1.000e-04, eta: 5:32:02, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0452, loss_cls: 0.1958, acc: 92.8374, loss_bbox: 0.2467, loss_mask: 0.2344, loss: 0.7488 2023-11-13 18:30:31,880 - mmdet - INFO - Epoch [4][1500/7330] lr: 1.000e-04, eta: 5:31:46, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0459, loss_cls: 0.2017, acc: 92.7878, loss_bbox: 0.2423, loss_mask: 0.2366, loss: 0.7540 2023-11-13 18:30:47,262 - mmdet - INFO - Epoch [4][1550/7330] lr: 1.000e-04, eta: 5:31:31, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0457, loss_cls: 0.1955, acc: 92.9426, loss_bbox: 0.2400, loss_mask: 0.2322, loss: 0.7387 2023-11-13 18:31:02,952 - mmdet - INFO - Epoch [4][1600/7330] lr: 1.000e-04, eta: 5:31:16, time: 0.314, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0482, loss_cls: 0.2054, acc: 92.4050, loss_bbox: 0.2547, loss_mask: 0.2397, loss: 0.7746 2023-11-13 18:31:18,419 - mmdet - INFO - Epoch [4][1650/7330] lr: 1.000e-04, eta: 5:31:01, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0458, loss_cls: 0.1988, acc: 92.8667, loss_bbox: 0.2446, loss_mask: 0.2440, loss: 0.7578 2023-11-13 18:31:33,721 - mmdet - INFO - Epoch [4][1700/7330] lr: 1.000e-04, eta: 5:30:45, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0455, loss_cls: 0.1955, acc: 92.8411, loss_bbox: 0.2522, loss_mask: 0.2429, loss: 0.7600 2023-11-13 18:31:49,188 - mmdet - INFO - Epoch [4][1750/7330] lr: 1.000e-04, eta: 5:30:30, time: 0.309, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0444, loss_cls: 0.1937, acc: 92.9058, loss_bbox: 0.2411, loss_mask: 0.2349, loss: 0.7379 2023-11-13 18:32:04,580 - mmdet - INFO - Epoch [4][1800/7330] lr: 1.000e-04, eta: 5:30:14, time: 0.308, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0438, loss_cls: 0.1911, acc: 93.1118, loss_bbox: 0.2357, loss_mask: 0.2346, loss: 0.7320 2023-11-13 18:32:20,117 - mmdet - INFO - Epoch [4][1850/7330] lr: 1.000e-04, eta: 5:29:59, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0451, loss_cls: 0.1905, acc: 93.0569, loss_bbox: 0.2337, loss_mask: 0.2329, loss: 0.7264 2023-11-13 18:32:35,868 - mmdet - INFO - Epoch [4][1900/7330] lr: 1.000e-04, eta: 5:29:44, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0459, loss_cls: 0.1961, acc: 92.8525, loss_bbox: 0.2460, loss_mask: 0.2411, loss: 0.7549 2023-11-13 18:32:51,326 - mmdet - INFO - Epoch [4][1950/7330] lr: 1.000e-04, eta: 5:29:29, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0453, loss_cls: 0.1947, acc: 92.9556, loss_bbox: 0.2355, loss_mask: 0.2391, loss: 0.7405 2023-11-13 18:33:06,585 - mmdet - INFO - Epoch [4][2000/7330] lr: 1.000e-04, eta: 5:29:13, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0432, loss_cls: 0.1939, acc: 93.0747, loss_bbox: 0.2358, loss_mask: 0.2347, loss: 0.7326 2023-11-13 18:33:22,155 - mmdet - INFO - Epoch [4][2050/7330] lr: 1.000e-04, eta: 5:28:58, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0435, loss_cls: 0.1944, acc: 92.9014, loss_bbox: 0.2392, loss_mask: 0.2412, loss: 0.7425 2023-11-13 18:33:38,258 - mmdet - INFO - Epoch [4][2100/7330] lr: 1.000e-04, eta: 5:28:44, time: 0.322, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0467, loss_cls: 0.2012, acc: 92.7014, loss_bbox: 0.2454, loss_mask: 0.2414, loss: 0.7616 2023-11-13 18:33:53,697 - mmdet - INFO - Epoch [4][2150/7330] lr: 1.000e-04, eta: 5:28:29, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0451, loss_cls: 0.1914, acc: 92.9739, loss_bbox: 0.2358, loss_mask: 0.2387, loss: 0.7372 2023-11-13 18:34:09,110 - mmdet - INFO - Epoch [4][2200/7330] lr: 1.000e-04, eta: 5:28:13, time: 0.308, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0455, loss_cls: 0.1934, acc: 92.9563, loss_bbox: 0.2405, loss_mask: 0.2375, loss: 0.7429 2023-11-13 18:34:24,748 - mmdet - INFO - Epoch [4][2250/7330] lr: 1.000e-04, eta: 5:27:58, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0468, loss_cls: 0.1954, acc: 92.9431, loss_bbox: 0.2390, loss_mask: 0.2336, loss: 0.7391 2023-11-13 18:34:40,155 - mmdet - INFO - Epoch [4][2300/7330] lr: 1.000e-04, eta: 5:27:43, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0443, loss_cls: 0.1987, acc: 92.7451, loss_bbox: 0.2457, loss_mask: 0.2370, loss: 0.7524 2023-11-13 18:34:55,976 - mmdet - INFO - Epoch [4][2350/7330] lr: 1.000e-04, eta: 5:27:28, time: 0.316, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0459, loss_cls: 0.1981, acc: 92.8362, loss_bbox: 0.2409, loss_mask: 0.2353, loss: 0.7479 2023-11-13 18:35:11,466 - mmdet - INFO - Epoch [4][2400/7330] lr: 1.000e-04, eta: 5:27:13, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0449, loss_cls: 0.1980, acc: 92.8354, loss_bbox: 0.2374, loss_mask: 0.2318, loss: 0.7381 2023-11-13 18:35:27,083 - mmdet - INFO - Epoch [4][2450/7330] lr: 1.000e-04, eta: 5:26:58, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0459, loss_cls: 0.1936, acc: 92.8860, loss_bbox: 0.2386, loss_mask: 0.2373, loss: 0.7408 2023-11-13 18:35:42,321 - mmdet - INFO - Epoch [4][2500/7330] lr: 1.000e-04, eta: 5:26:42, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0447, loss_cls: 0.1929, acc: 93.0083, loss_bbox: 0.2336, loss_mask: 0.2304, loss: 0.7272 2023-11-13 18:35:57,650 - mmdet - INFO - Epoch [4][2550/7330] lr: 1.000e-04, eta: 5:26:26, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0430, loss_cls: 0.1890, acc: 93.1794, loss_bbox: 0.2285, loss_mask: 0.2373, loss: 0.7216 2023-11-13 18:36:12,994 - mmdet - INFO - Epoch [4][2600/7330] lr: 1.000e-04, eta: 5:26:10, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0424, loss_cls: 0.1913, acc: 93.0605, loss_bbox: 0.2402, loss_mask: 0.2390, loss: 0.7357 2023-11-13 18:36:29,006 - mmdet - INFO - Epoch [4][2650/7330] lr: 1.000e-04, eta: 5:25:57, time: 0.320, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0463, loss_cls: 0.1978, acc: 92.8950, loss_bbox: 0.2370, loss_mask: 0.2398, loss: 0.7473 2023-11-13 18:36:44,465 - mmdet - INFO - Epoch [4][2700/7330] lr: 1.000e-04, eta: 5:25:41, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0427, loss_cls: 0.1912, acc: 93.0771, loss_bbox: 0.2333, loss_mask: 0.2353, loss: 0.7265 2023-11-13 18:36:59,597 - mmdet - INFO - Epoch [4][2750/7330] lr: 1.000e-04, eta: 5:25:25, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0441, loss_cls: 0.1871, acc: 93.1370, loss_bbox: 0.2345, loss_mask: 0.2311, loss: 0.7188 2023-11-13 18:37:14,909 - mmdet - INFO - Epoch [4][2800/7330] lr: 1.000e-04, eta: 5:25:09, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0436, loss_cls: 0.1960, acc: 92.9929, loss_bbox: 0.2366, loss_mask: 0.2397, loss: 0.7421 2023-11-13 18:37:30,781 - mmdet - INFO - Epoch [4][2850/7330] lr: 1.000e-04, eta: 5:24:55, time: 0.317, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0442, loss_cls: 0.1964, acc: 92.9138, loss_bbox: 0.2390, loss_mask: 0.2360, loss: 0.7397 2023-11-13 18:37:46,081 - mmdet - INFO - Epoch [4][2900/7330] lr: 1.000e-04, eta: 5:24:39, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0413, loss_cls: 0.1913, acc: 93.1169, loss_bbox: 0.2359, loss_mask: 0.2335, loss: 0.7279 2023-11-13 18:38:01,686 - mmdet - INFO - Epoch [4][2950/7330] lr: 1.000e-04, eta: 5:24:24, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0459, loss_cls: 0.1979, acc: 92.8047, loss_bbox: 0.2476, loss_mask: 0.2415, loss: 0.7594 2023-11-13 18:38:16,703 - mmdet - INFO - Epoch [4][3000/7330] lr: 1.000e-04, eta: 5:24:07, time: 0.300, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0420, loss_cls: 0.1825, acc: 93.3699, loss_bbox: 0.2282, loss_mask: 0.2350, loss: 0.7131 2023-11-13 18:38:32,287 - mmdet - INFO - Epoch [4][3050/7330] lr: 1.000e-04, eta: 5:23:52, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0445, loss_cls: 0.1871, acc: 93.2881, loss_bbox: 0.2249, loss_mask: 0.2328, loss: 0.7140 2023-11-13 18:38:47,542 - mmdet - INFO - Epoch [4][3100/7330] lr: 1.000e-04, eta: 5:23:36, time: 0.305, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0435, loss_cls: 0.1869, acc: 93.1921, loss_bbox: 0.2277, loss_mask: 0.2329, loss: 0.7160 2023-11-13 18:39:03,232 - mmdet - INFO - Epoch [4][3150/7330] lr: 1.000e-04, eta: 5:23:22, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0446, loss_cls: 0.1963, acc: 92.8418, loss_bbox: 0.2411, loss_mask: 0.2352, loss: 0.7432 2023-11-13 18:39:18,701 - mmdet - INFO - Epoch [4][3200/7330] lr: 1.000e-04, eta: 5:23:06, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0443, loss_cls: 0.1950, acc: 92.9624, loss_bbox: 0.2397, loss_mask: 0.2368, loss: 0.7388 2023-11-13 18:39:33,945 - mmdet - INFO - Epoch [4][3250/7330] lr: 1.000e-04, eta: 5:22:50, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0463, loss_cls: 0.1938, acc: 92.9490, loss_bbox: 0.2381, loss_mask: 0.2377, loss: 0.7430 2023-11-13 18:39:49,367 - mmdet - INFO - Epoch [4][3300/7330] lr: 1.000e-04, eta: 5:22:35, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0488, loss_cls: 0.1995, acc: 92.7927, loss_bbox: 0.2483, loss_mask: 0.2411, loss: 0.7637 2023-11-13 18:40:05,029 - mmdet - INFO - Epoch [4][3350/7330] lr: 1.000e-04, eta: 5:22:20, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0482, loss_cls: 0.2035, acc: 92.6680, loss_bbox: 0.2497, loss_mask: 0.2450, loss: 0.7746 2023-11-13 18:40:20,259 - mmdet - INFO - Epoch [4][3400/7330] lr: 1.000e-04, eta: 5:22:04, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0427, loss_cls: 0.1897, acc: 93.2598, loss_bbox: 0.2249, loss_mask: 0.2342, loss: 0.7143 2023-11-13 18:40:35,382 - mmdet - INFO - Epoch [4][3450/7330] lr: 1.000e-04, eta: 5:21:48, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0426, loss_cls: 0.1843, acc: 93.4597, loss_bbox: 0.2234, loss_mask: 0.2354, loss: 0.7106 2023-11-13 18:40:50,779 - mmdet - INFO - Epoch [4][3500/7330] lr: 1.000e-04, eta: 5:21:32, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0438, loss_cls: 0.1944, acc: 92.9348, loss_bbox: 0.2371, loss_mask: 0.2382, loss: 0.7390 2023-11-13 18:41:06,216 - mmdet - INFO - Epoch [4][3550/7330] lr: 1.000e-04, eta: 5:21:17, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0471, loss_cls: 0.1978, acc: 92.8462, loss_bbox: 0.2456, loss_mask: 0.2386, loss: 0.7562 2023-11-13 18:41:21,188 - mmdet - INFO - Epoch [4][3600/7330] lr: 1.000e-04, eta: 5:21:00, time: 0.299, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0409, loss_cls: 0.1854, acc: 93.3193, loss_bbox: 0.2298, loss_mask: 0.2336, loss: 0.7120 2023-11-13 18:41:36,332 - mmdet - INFO - Epoch [4][3650/7330] lr: 1.000e-04, eta: 5:20:44, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0451, loss_cls: 0.1983, acc: 92.8169, loss_bbox: 0.2394, loss_mask: 0.2381, loss: 0.7468 2023-11-13 18:41:52,140 - mmdet - INFO - Epoch [4][3700/7330] lr: 1.000e-04, eta: 5:20:29, time: 0.316, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0470, loss_cls: 0.2004, acc: 92.7625, loss_bbox: 0.2480, loss_mask: 0.2408, loss: 0.7631 2023-11-13 18:42:07,891 - mmdet - INFO - Epoch [4][3750/7330] lr: 1.000e-04, eta: 5:20:15, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0445, loss_cls: 0.1987, acc: 92.9912, loss_bbox: 0.2344, loss_mask: 0.2415, loss: 0.7460 2023-11-13 18:42:23,048 - mmdet - INFO - Epoch [4][3800/7330] lr: 1.000e-04, eta: 5:19:59, time: 0.303, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0423, loss_cls: 0.1929, acc: 92.9971, loss_bbox: 0.2346, loss_mask: 0.2399, loss: 0.7341 2023-11-13 18:42:38,045 - mmdet - INFO - Epoch [4][3850/7330] lr: 1.000e-04, eta: 5:19:42, time: 0.300, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0438, loss_cls: 0.2001, acc: 92.7686, loss_bbox: 0.2465, loss_mask: 0.2421, loss: 0.7575 2023-11-13 18:42:53,235 - mmdet - INFO - Epoch [4][3900/7330] lr: 1.000e-04, eta: 5:19:26, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0432, loss_cls: 0.1858, acc: 93.3484, loss_bbox: 0.2265, loss_mask: 0.2364, loss: 0.7161 2023-11-13 18:43:08,811 - mmdet - INFO - Epoch [4][3950/7330] lr: 1.000e-04, eta: 5:19:11, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0418, loss_cls: 0.1872, acc: 93.1321, loss_bbox: 0.2315, loss_mask: 0.2344, loss: 0.7189 2023-11-13 18:43:23,897 - mmdet - INFO - Epoch [4][4000/7330] lr: 1.000e-04, eta: 5:18:55, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0421, loss_cls: 0.1873, acc: 93.2256, loss_bbox: 0.2276, loss_mask: 0.2337, loss: 0.7155 2023-11-13 18:43:39,435 - mmdet - INFO - Epoch [4][4050/7330] lr: 1.000e-04, eta: 5:18:39, time: 0.311, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0412, loss_cls: 0.1916, acc: 93.1079, loss_bbox: 0.2340, loss_mask: 0.2370, loss: 0.7277 2023-11-13 18:43:54,871 - mmdet - INFO - Epoch [4][4100/7330] lr: 1.000e-04, eta: 5:18:24, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0427, loss_cls: 0.1933, acc: 93.1370, loss_bbox: 0.2345, loss_mask: 0.2321, loss: 0.7282 2023-11-13 18:44:10,275 - mmdet - INFO - Epoch [4][4150/7330] lr: 1.000e-04, eta: 5:18:08, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0433, loss_cls: 0.1858, acc: 93.2354, loss_bbox: 0.2303, loss_mask: 0.2327, loss: 0.7174 2023-11-13 18:44:25,410 - mmdet - INFO - Epoch [4][4200/7330] lr: 1.000e-04, eta: 5:17:52, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0443, loss_cls: 0.2012, acc: 92.7004, loss_bbox: 0.2446, loss_mask: 0.2355, loss: 0.7522 2023-11-13 18:44:41,118 - mmdet - INFO - Epoch [4][4250/7330] lr: 1.000e-04, eta: 5:17:37, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0462, loss_cls: 0.1978, acc: 92.9060, loss_bbox: 0.2389, loss_mask: 0.2378, loss: 0.7463 2023-11-13 18:44:56,606 - mmdet - INFO - Epoch [4][4300/7330] lr: 1.000e-04, eta: 5:17:22, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0443, loss_cls: 0.1922, acc: 93.0112, loss_bbox: 0.2358, loss_mask: 0.2385, loss: 0.7367 2023-11-13 18:45:11,953 - mmdet - INFO - Epoch [4][4350/7330] lr: 1.000e-04, eta: 5:17:06, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0439, loss_cls: 0.1925, acc: 93.0669, loss_bbox: 0.2333, loss_mask: 0.2421, loss: 0.7365 2023-11-13 18:45:27,009 - mmdet - INFO - Epoch [4][4400/7330] lr: 1.000e-04, eta: 5:16:50, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0445, loss_cls: 0.1939, acc: 93.0979, loss_bbox: 0.2333, loss_mask: 0.2438, loss: 0.7405 2023-11-13 18:45:42,148 - mmdet - INFO - Epoch [4][4450/7330] lr: 1.000e-04, eta: 5:16:34, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0452, loss_cls: 0.1954, acc: 93.0291, loss_bbox: 0.2370, loss_mask: 0.2330, loss: 0.7362 2023-11-13 18:45:57,893 - mmdet - INFO - Epoch [4][4500/7330] lr: 1.000e-04, eta: 5:16:19, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0445, loss_cls: 0.1927, acc: 93.1238, loss_bbox: 0.2352, loss_mask: 0.2398, loss: 0.7384 2023-11-13 18:46:13,012 - mmdet - INFO - Epoch [4][4550/7330] lr: 1.000e-04, eta: 5:16:03, time: 0.302, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0436, loss_cls: 0.1800, acc: 93.4949, loss_bbox: 0.2222, loss_mask: 0.2279, loss: 0.6967 2023-11-13 18:46:28,480 - mmdet - INFO - Epoch [4][4600/7330] lr: 1.000e-04, eta: 5:15:48, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0441, loss_cls: 0.1992, acc: 92.7771, loss_bbox: 0.2431, loss_mask: 0.2401, loss: 0.7523 2023-11-13 18:46:44,138 - mmdet - INFO - Epoch [4][4650/7330] lr: 1.000e-04, eta: 5:15:33, time: 0.313, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0434, loss_cls: 0.1917, acc: 93.1355, loss_bbox: 0.2301, loss_mask: 0.2375, loss: 0.7290 2023-11-13 18:46:59,432 - mmdet - INFO - Epoch [4][4700/7330] lr: 1.000e-04, eta: 5:15:17, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0442, loss_cls: 0.2013, acc: 92.7996, loss_bbox: 0.2449, loss_mask: 0.2431, loss: 0.7598 2023-11-13 18:47:14,673 - mmdet - INFO - Epoch [4][4750/7330] lr: 1.000e-04, eta: 5:15:01, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0452, loss_cls: 0.1979, acc: 92.9543, loss_bbox: 0.2353, loss_mask: 0.2374, loss: 0.7409 2023-11-13 18:47:30,227 - mmdet - INFO - Epoch [4][4800/7330] lr: 1.000e-04, eta: 5:14:46, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0442, loss_cls: 0.1919, acc: 93.0867, loss_bbox: 0.2345, loss_mask: 0.2369, loss: 0.7320 2023-11-13 18:47:45,637 - mmdet - INFO - Epoch [4][4850/7330] lr: 1.000e-04, eta: 5:14:30, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0434, loss_cls: 0.1968, acc: 92.9419, loss_bbox: 0.2387, loss_mask: 0.2392, loss: 0.7416 2023-11-13 18:48:00,929 - mmdet - INFO - Epoch [4][4900/7330] lr: 1.000e-04, eta: 5:14:15, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0457, loss_cls: 0.2033, acc: 92.6069, loss_bbox: 0.2517, loss_mask: 0.2413, loss: 0.7679 2023-11-13 18:48:16,123 - mmdet - INFO - Epoch [4][4950/7330] lr: 1.000e-04, eta: 5:13:59, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0443, loss_cls: 0.1912, acc: 93.1895, loss_bbox: 0.2330, loss_mask: 0.2401, loss: 0.7337 2023-11-13 18:48:31,481 - mmdet - INFO - Epoch [4][5000/7330] lr: 1.000e-04, eta: 5:13:43, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0435, loss_cls: 0.1989, acc: 92.8120, loss_bbox: 0.2441, loss_mask: 0.2407, loss: 0.7518 2023-11-13 18:48:46,521 - mmdet - INFO - Epoch [4][5050/7330] lr: 1.000e-04, eta: 5:13:27, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0429, loss_cls: 0.1955, acc: 92.8757, loss_bbox: 0.2414, loss_mask: 0.2388, loss: 0.7422 2023-11-13 18:49:01,338 - mmdet - INFO - Epoch [4][5100/7330] lr: 1.000e-04, eta: 5:13:10, time: 0.296, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0398, loss_cls: 0.1847, acc: 93.3792, loss_bbox: 0.2285, loss_mask: 0.2329, loss: 0.7094 2023-11-13 18:49:16,249 - mmdet - INFO - Epoch [4][5150/7330] lr: 1.000e-04, eta: 5:12:53, time: 0.298, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0407, loss_cls: 0.1965, acc: 93.0225, loss_bbox: 0.2328, loss_mask: 0.2342, loss: 0.7289 2023-11-13 18:49:31,636 - mmdet - INFO - Epoch [4][5200/7330] lr: 1.000e-04, eta: 5:12:38, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0453, loss_cls: 0.2073, acc: 92.5278, loss_bbox: 0.2514, loss_mask: 0.2408, loss: 0.7712 2023-11-13 18:49:47,193 - mmdet - INFO - Epoch [4][5250/7330] lr: 1.000e-04, eta: 5:12:23, time: 0.311, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0447, loss_cls: 0.2011, acc: 92.8523, loss_bbox: 0.2429, loss_mask: 0.2412, loss: 0.7558 2023-11-13 18:50:02,382 - mmdet - INFO - Epoch [4][5300/7330] lr: 1.000e-04, eta: 5:12:07, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0412, loss_cls: 0.1843, acc: 93.3433, loss_bbox: 0.2241, loss_mask: 0.2365, loss: 0.7117 2023-11-13 18:50:17,748 - mmdet - INFO - Epoch [4][5350/7330] lr: 1.000e-04, eta: 5:11:51, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0480, loss_cls: 0.2055, acc: 92.5977, loss_bbox: 0.2477, loss_mask: 0.2429, loss: 0.7723 2023-11-13 18:50:32,863 - mmdet - INFO - Epoch [4][5400/7330] lr: 1.000e-04, eta: 5:11:35, time: 0.302, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0403, loss_cls: 0.1843, acc: 93.3354, loss_bbox: 0.2261, loss_mask: 0.2314, loss: 0.7061 2023-11-13 18:50:48,036 - mmdet - INFO - Epoch [4][5450/7330] lr: 1.000e-04, eta: 5:11:19, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0425, loss_cls: 0.1905, acc: 93.1362, loss_bbox: 0.2313, loss_mask: 0.2371, loss: 0.7260 2023-11-13 18:51:03,811 - mmdet - INFO - Epoch [4][5500/7330] lr: 1.000e-04, eta: 5:11:04, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0449, loss_cls: 0.1994, acc: 92.8889, loss_bbox: 0.2377, loss_mask: 0.2325, loss: 0.7416 2023-11-13 18:51:19,013 - mmdet - INFO - Epoch [4][5550/7330] lr: 1.000e-04, eta: 5:10:48, time: 0.304, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0414, loss_cls: 0.1898, acc: 93.0659, loss_bbox: 0.2325, loss_mask: 0.2329, loss: 0.7208 2023-11-13 18:51:34,451 - mmdet - INFO - Epoch [4][5600/7330] lr: 1.000e-04, eta: 5:10:33, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0440, loss_cls: 0.2034, acc: 92.7117, loss_bbox: 0.2437, loss_mask: 0.2416, loss: 0.7577 2023-11-13 18:51:49,975 - mmdet - INFO - Epoch [4][5650/7330] lr: 1.000e-04, eta: 5:10:18, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0413, loss_cls: 0.1908, acc: 93.1792, loss_bbox: 0.2316, loss_mask: 0.2337, loss: 0.7215 2023-11-13 18:52:05,369 - mmdet - INFO - Epoch [4][5700/7330] lr: 1.000e-04, eta: 5:10:02, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0451, loss_cls: 0.1997, acc: 92.8518, loss_bbox: 0.2405, loss_mask: 0.2317, loss: 0.7410 2023-11-13 18:52:20,950 - mmdet - INFO - Epoch [4][5750/7330] lr: 1.000e-04, eta: 5:09:47, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0447, loss_cls: 0.1911, acc: 93.1057, loss_bbox: 0.2351, loss_mask: 0.2347, loss: 0.7304 2023-11-13 18:52:36,403 - mmdet - INFO - Epoch [4][5800/7330] lr: 1.000e-04, eta: 5:09:32, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0462, loss_cls: 0.2006, acc: 92.7979, loss_bbox: 0.2435, loss_mask: 0.2349, loss: 0.7518 2023-11-13 18:52:51,652 - mmdet - INFO - Epoch [4][5850/7330] lr: 1.000e-04, eta: 5:09:16, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0429, loss_cls: 0.1859, acc: 93.3110, loss_bbox: 0.2317, loss_mask: 0.2344, loss: 0.7194 2023-11-13 18:53:07,165 - mmdet - INFO - Epoch [4][5900/7330] lr: 1.000e-04, eta: 5:09:01, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0443, loss_cls: 0.1910, acc: 93.0859, loss_bbox: 0.2340, loss_mask: 0.2371, loss: 0.7329 2023-11-13 18:53:22,461 - mmdet - INFO - Epoch [4][5950/7330] lr: 1.000e-04, eta: 5:08:45, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0435, loss_cls: 0.1849, acc: 93.2708, loss_bbox: 0.2237, loss_mask: 0.2392, loss: 0.7178 2023-11-13 18:53:37,711 - mmdet - INFO - Epoch [4][6000/7330] lr: 1.000e-04, eta: 5:08:29, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0438, loss_cls: 0.1955, acc: 92.9382, loss_bbox: 0.2395, loss_mask: 0.2400, loss: 0.7442 2023-11-13 18:53:53,040 - mmdet - INFO - Epoch [4][6050/7330] lr: 1.000e-04, eta: 5:08:13, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0414, loss_cls: 0.1755, acc: 93.5278, loss_bbox: 0.2221, loss_mask: 0.2262, loss: 0.6879 2023-11-13 18:54:08,383 - mmdet - INFO - Epoch [4][6100/7330] lr: 1.000e-04, eta: 5:07:58, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0455, loss_cls: 0.1959, acc: 92.8889, loss_bbox: 0.2352, loss_mask: 0.2388, loss: 0.7420 2023-11-13 18:54:23,873 - mmdet - INFO - Epoch [4][6150/7330] lr: 1.000e-04, eta: 5:07:42, time: 0.310, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0460, loss_cls: 0.1923, acc: 93.0674, loss_bbox: 0.2338, loss_mask: 0.2394, loss: 0.7368 2023-11-13 18:54:38,939 - mmdet - INFO - Epoch [4][6200/7330] lr: 1.000e-04, eta: 5:07:26, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0426, loss_cls: 0.1962, acc: 93.0398, loss_bbox: 0.2318, loss_mask: 0.2360, loss: 0.7289 2023-11-13 18:54:54,089 - mmdet - INFO - Epoch [4][6250/7330] lr: 1.000e-04, eta: 5:07:10, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0418, loss_cls: 0.1867, acc: 93.2019, loss_bbox: 0.2251, loss_mask: 0.2332, loss: 0.7094 2023-11-13 18:55:09,679 - mmdet - INFO - Epoch [4][6300/7330] lr: 1.000e-04, eta: 5:06:55, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0479, loss_cls: 0.2060, acc: 92.6160, loss_bbox: 0.2514, loss_mask: 0.2435, loss: 0.7773 2023-11-13 18:55:24,715 - mmdet - INFO - Epoch [4][6350/7330] lr: 1.000e-04, eta: 5:06:39, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0413, loss_cls: 0.1897, acc: 93.2539, loss_bbox: 0.2311, loss_mask: 0.2363, loss: 0.7226 2023-11-13 18:55:39,935 - mmdet - INFO - Epoch [4][6400/7330] lr: 1.000e-04, eta: 5:06:23, time: 0.304, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0445, loss_cls: 0.2010, acc: 92.7007, loss_bbox: 0.2425, loss_mask: 0.2327, loss: 0.7481 2023-11-13 18:55:54,912 - mmdet - INFO - Epoch [4][6450/7330] lr: 1.000e-04, eta: 5:06:07, time: 0.300, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0428, loss_cls: 0.1936, acc: 93.0327, loss_bbox: 0.2354, loss_mask: 0.2368, loss: 0.7319 2023-11-13 18:56:10,343 - mmdet - INFO - Epoch [4][6500/7330] lr: 1.000e-04, eta: 5:05:51, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0438, loss_cls: 0.2011, acc: 92.7539, loss_bbox: 0.2390, loss_mask: 0.2348, loss: 0.7434 2023-11-13 18:56:25,471 - mmdet - INFO - Epoch [4][6550/7330] lr: 1.000e-04, eta: 5:05:35, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0447, loss_cls: 0.1944, acc: 92.9663, loss_bbox: 0.2348, loss_mask: 0.2397, loss: 0.7393 2023-11-13 18:56:41,053 - mmdet - INFO - Epoch [4][6600/7330] lr: 1.000e-04, eta: 5:05:20, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0444, loss_cls: 0.1968, acc: 92.9238, loss_bbox: 0.2415, loss_mask: 0.2394, loss: 0.7481 2023-11-13 18:56:56,299 - mmdet - INFO - Epoch [4][6650/7330] lr: 1.000e-04, eta: 5:05:04, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0440, loss_cls: 0.2002, acc: 92.8069, loss_bbox: 0.2463, loss_mask: 0.2377, loss: 0.7554 2023-11-13 18:57:11,759 - mmdet - INFO - Epoch [4][6700/7330] lr: 1.000e-04, eta: 5:04:49, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0449, loss_cls: 0.2054, acc: 92.5449, loss_bbox: 0.2509, loss_mask: 0.2482, loss: 0.7744 2023-11-13 18:57:27,428 - mmdet - INFO - Epoch [4][6750/7330] lr: 1.000e-04, eta: 5:04:34, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0470, loss_cls: 0.1981, acc: 92.7908, loss_bbox: 0.2435, loss_mask: 0.2320, loss: 0.7477 2023-11-13 18:57:42,708 - mmdet - INFO - Epoch [4][6800/7330] lr: 1.000e-04, eta: 5:04:18, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0447, loss_cls: 0.1980, acc: 92.8682, loss_bbox: 0.2430, loss_mask: 0.2381, loss: 0.7494 2023-11-13 18:57:57,835 - mmdet - INFO - Epoch [4][6850/7330] lr: 1.000e-04, eta: 5:04:02, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0419, loss_cls: 0.1935, acc: 93.1384, loss_bbox: 0.2353, loss_mask: 0.2389, loss: 0.7338 2023-11-13 18:58:13,056 - mmdet - INFO - Epoch [4][6900/7330] lr: 1.000e-04, eta: 5:03:46, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0424, loss_cls: 0.1875, acc: 93.3643, loss_bbox: 0.2311, loss_mask: 0.2316, loss: 0.7199 2023-11-13 18:58:28,339 - mmdet - INFO - Epoch [4][6950/7330] lr: 1.000e-04, eta: 5:03:30, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0454, loss_cls: 0.1887, acc: 93.2405, loss_bbox: 0.2329, loss_mask: 0.2333, loss: 0.7283 2023-11-13 18:58:43,610 - mmdet - INFO - Epoch [4][7000/7330] lr: 1.000e-04, eta: 5:03:15, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0418, loss_cls: 0.1858, acc: 93.2649, loss_bbox: 0.2229, loss_mask: 0.2298, loss: 0.7046 2023-11-13 18:58:58,825 - mmdet - INFO - Epoch [4][7050/7330] lr: 1.000e-04, eta: 5:02:59, time: 0.304, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0398, loss_cls: 0.1906, acc: 93.2163, loss_bbox: 0.2324, loss_mask: 0.2333, loss: 0.7205 2023-11-13 18:59:14,284 - mmdet - INFO - Epoch [4][7100/7330] lr: 1.000e-04, eta: 5:02:44, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0457, loss_cls: 0.1981, acc: 92.8386, loss_bbox: 0.2384, loss_mask: 0.2330, loss: 0.7399 2023-11-13 18:59:29,450 - mmdet - INFO - Epoch [4][7150/7330] lr: 1.000e-04, eta: 5:02:28, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0436, loss_cls: 0.1966, acc: 92.9221, loss_bbox: 0.2438, loss_mask: 0.2372, loss: 0.7451 2023-11-13 18:59:44,757 - mmdet - INFO - Epoch [4][7200/7330] lr: 1.000e-04, eta: 5:02:12, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0445, loss_cls: 0.2060, acc: 92.6516, loss_bbox: 0.2470, loss_mask: 0.2344, loss: 0.7571 2023-11-13 18:59:59,738 - mmdet - INFO - Epoch [4][7250/7330] lr: 1.000e-04, eta: 5:01:56, time: 0.300, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0423, loss_cls: 0.1913, acc: 93.0042, loss_bbox: 0.2379, loss_mask: 0.2371, loss: 0.7327 2023-11-13 19:00:15,067 - mmdet - INFO - Epoch [4][7300/7330] lr: 1.000e-04, eta: 5:01:40, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0477, loss_cls: 0.1984, acc: 92.9119, loss_bbox: 0.2465, loss_mask: 0.2438, loss: 0.7640 2023-11-13 19:00:24,890 - mmdet - INFO - Saving checkpoint at 4 epochs 2023-11-13 19:01:09,004 - mmdet - INFO - Evaluating bbox... 2023-11-13 19:01:42,600 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.436 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.667 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.481 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.282 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.478 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.573 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.571 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.571 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.571 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.398 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.715 2023-11-13 19:01:42,602 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.558 | bicycle | 0.342 | car | 0.449 | | motorcycle | 0.452 | airplane | 0.673 | bus | 0.642 | | train | 0.645 | truck | 0.399 | boat | 0.311 | | traffic light | 0.294 | fire hydrant | 0.671 | stop sign | 0.657 | | parking meter | 0.464 | bench | 0.268 | bird | 0.391 | | cat | 0.720 | dog | 0.645 | horse | 0.560 | | sheep | 0.556 | cow | 0.596 | elephant | 0.630 | | bear | 0.754 | zebra | 0.678 | giraffe | 0.672 | | backpack | 0.175 | umbrella | 0.427 | handbag | 0.178 | | tie | 0.320 | suitcase | 0.424 | frisbee | 0.679 | | skis | 0.256 | snowboard | 0.333 | sports ball | 0.452 | | kite | 0.436 | baseball bat | 0.325 | baseball glove | 0.399 | | skateboard | 0.533 | surfboard | 0.409 | tennis racket | 0.498 | | bottle | 0.414 | wine glass | 0.369 | cup | 0.475 | | fork | 0.395 | knife | 0.233 | spoon | 0.199 | | bowl | 0.429 | banana | 0.280 | apple | 0.226 | | sandwich | 0.366 | orange | 0.341 | broccoli | 0.259 | | carrot | 0.231 | hot dog | 0.397 | pizza | 0.493 | | donut | 0.516 | cake | 0.383 | chair | 0.318 | | couch | 0.446 | potted plant | 0.286 | bed | 0.436 | | dining table | 0.275 | toilet | 0.603 | tv | 0.584 | | laptop | 0.614 | mouse | 0.607 | remote | 0.353 | | keyboard | 0.526 | cell phone | 0.403 | microwave | 0.594 | | oven | 0.359 | toaster | 0.408 | sink | 0.397 | | refrigerator | 0.589 | book | 0.166 | clock | 0.512 | | vase | 0.395 | scissors | 0.327 | teddy bear | 0.466 | | hair drier | 0.102 | toothbrush | 0.272 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:01:42,602 - mmdet - INFO - Evaluating segm... 2023-11-13 19:02:18,477 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.400 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.633 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.432 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.209 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 ] = 0.588 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.526 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.526 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.526 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.350 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.567 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.686 2023-11-13 19:02:18,479 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.488 | bicycle | 0.202 | car | 0.420 | | motorcycle | 0.338 | airplane | 0.532 | bus | 0.649 | | train | 0.634 | truck | 0.392 | boat | 0.280 | | traffic light | 0.283 | fire hydrant | 0.684 | stop sign | 0.672 | | parking meter | 0.474 | bench | 0.197 | bird | 0.323 | | cat | 0.722 | dog | 0.616 | horse | 0.420 | | sheep | 0.492 | cow | 0.502 | elephant | 0.593 | | bear | 0.733 | zebra | 0.595 | giraffe | 0.523 | | backpack | 0.188 | umbrella | 0.495 | handbag | 0.181 | | tie | 0.318 | suitcase | 0.446 | frisbee | 0.664 | | skis | 0.041 | snowboard | 0.231 | sports ball | 0.443 | | kite | 0.307 | baseball bat | 0.271 | baseball glove | 0.443 | | skateboard | 0.344 | surfboard | 0.339 | tennis racket | 0.573 | | bottle | 0.404 | wine glass | 0.328 | cup | 0.480 | | fork | 0.191 | knife | 0.148 | spoon | 0.133 | | bowl | 0.401 | banana | 0.230 | apple | 0.231 | | sandwich | 0.406 | orange | 0.353 | broccoli | 0.247 | | carrot | 0.203 | hot dog | 0.311 | pizza | 0.490 | | donut | 0.523 | cake | 0.399 | chair | 0.231 | | couch | 0.392 | potted plant | 0.252 | bed | 0.353 | | dining table | 0.164 | toilet | 0.620 | tv | 0.625 | | laptop | 0.629 | mouse | 0.613 | remote | 0.325 | | keyboard | 0.537 | cell phone | 0.374 | microwave | 0.615 | | oven | 0.339 | toaster | 0.439 | sink | 0.382 | | refrigerator | 0.618 | book | 0.118 | clock | 0.534 | | vase | 0.395 | scissors | 0.271 | teddy bear | 0.462 | | hair drier | 0.048 | toothbrush | 0.180 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:02:18,995 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_3.pth was removed 2023-11-13 19:02:20,597 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_4.pth. 2023-11-13 19:02:20,597 - mmdet - INFO - Best bbox_mAP is 0.4365 at 4 epoch. 2023-11-13 19:02:20,597 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:02:20,597 - mmdet - INFO - Epoch(val) [4][625] bbox_mAP: 0.4365, bbox_mAP_50: 0.6672, bbox_mAP_75: 0.4808, bbox_mAP_s: 0.2815, bbox_mAP_m: 0.4777, bbox_mAP_l: 0.5729, bbox_mAP_copypaste: 0.4365 0.6672 0.4808 0.2815 0.4777 0.5729, segm_mAP: 0.4005, segm_mAP_50: 0.6329, segm_mAP_75: 0.4325, segm_mAP_s: 0.2091, segm_mAP_m: 0.4309, segm_mAP_l: 0.5876, segm_mAP_copypaste: 0.4005 0.6329 0.4325 0.2091 0.4309 0.5876 2023-11-13 19:02:40,819 - mmdet - INFO - Epoch [5][50/7330] lr: 1.000e-04, eta: 5:01:06, time: 0.404, data_time: 0.090, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0449, loss_cls: 0.1898, acc: 93.0510, loss_bbox: 0.2350, loss_mask: 0.2327, loss: 0.7265 2023-11-13 19:02:57,501 - mmdet - INFO - Epoch [5][100/7330] lr: 1.000e-04, eta: 5:00:53, time: 0.334, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0436, loss_cls: 0.1888, acc: 92.9746, loss_bbox: 0.2332, loss_mask: 0.2320, loss: 0.7206 2023-11-13 19:03:13,983 - mmdet - INFO - Epoch [5][150/7330] lr: 1.000e-04, eta: 5:00:40, time: 0.330, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0417, loss_cls: 0.1866, acc: 93.2598, loss_bbox: 0.2327, loss_mask: 0.2418, loss: 0.7270 2023-11-13 19:03:30,776 - mmdet - INFO - Epoch [5][200/7330] lr: 1.000e-04, eta: 5:00:27, time: 0.336, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0436, loss_cls: 0.1897, acc: 92.9980, loss_bbox: 0.2401, loss_mask: 0.2303, loss: 0.7268 2023-11-13 19:03:47,052 - mmdet - INFO - Epoch [5][250/7330] lr: 1.000e-04, eta: 5:00:14, time: 0.325, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0431, loss_cls: 0.1858, acc: 93.0605, loss_bbox: 0.2326, loss_mask: 0.2263, loss: 0.7095 2023-11-13 19:04:03,108 - mmdet - INFO - Epoch [5][300/7330] lr: 1.000e-04, eta: 4:59:59, time: 0.321, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0418, loss_cls: 0.1829, acc: 93.1477, loss_bbox: 0.2307, loss_mask: 0.2304, loss: 0.7068 2023-11-13 19:04:19,578 - mmdet - INFO - Epoch [5][350/7330] lr: 1.000e-04, eta: 4:59:46, time: 0.329, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0431, loss_cls: 0.1863, acc: 93.1699, loss_bbox: 0.2290, loss_mask: 0.2308, loss: 0.7116 2023-11-13 19:04:35,999 - mmdet - INFO - Epoch [5][400/7330] lr: 1.000e-04, eta: 4:59:33, time: 0.328, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0442, loss_cls: 0.1837, acc: 93.3433, loss_bbox: 0.2316, loss_mask: 0.2312, loss: 0.7138 2023-11-13 19:04:52,278 - mmdet - INFO - Epoch [5][450/7330] lr: 1.000e-04, eta: 4:59:19, time: 0.326, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0417, loss_cls: 0.1812, acc: 93.3313, loss_bbox: 0.2278, loss_mask: 0.2340, loss: 0.7080 2023-11-13 19:05:08,410 - mmdet - INFO - Epoch [5][500/7330] lr: 1.000e-04, eta: 4:59:05, time: 0.323, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0464, loss_cls: 0.1844, acc: 93.3308, loss_bbox: 0.2316, loss_mask: 0.2306, loss: 0.7164 2023-11-13 19:05:24,592 - mmdet - INFO - Epoch [5][550/7330] lr: 1.000e-04, eta: 4:58:51, time: 0.324, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0441, loss_cls: 0.1848, acc: 93.1746, loss_bbox: 0.2377, loss_mask: 0.2307, loss: 0.7218 2023-11-13 19:05:40,471 - mmdet - INFO - Epoch [5][600/7330] lr: 1.000e-04, eta: 4:58:36, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0418, loss_cls: 0.1820, acc: 93.3433, loss_bbox: 0.2292, loss_mask: 0.2262, loss: 0.7015 2023-11-13 19:05:56,086 - mmdet - INFO - Epoch [5][650/7330] lr: 1.000e-04, eta: 4:58:21, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0401, loss_cls: 0.1836, acc: 93.3716, loss_bbox: 0.2255, loss_mask: 0.2269, loss: 0.6998 2023-11-13 19:06:12,217 - mmdet - INFO - Epoch [5][700/7330] lr: 1.000e-04, eta: 4:58:07, time: 0.323, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0450, loss_cls: 0.1967, acc: 92.9226, loss_bbox: 0.2380, loss_mask: 0.2349, loss: 0.7410 2023-11-13 19:06:28,805 - mmdet - INFO - Epoch [5][750/7330] lr: 1.000e-04, eta: 4:57:54, time: 0.332, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0434, loss_cls: 0.1881, acc: 93.0278, loss_bbox: 0.2364, loss_mask: 0.2321, loss: 0.7238 2023-11-13 19:06:44,738 - mmdet - INFO - Epoch [5][800/7330] lr: 1.000e-04, eta: 4:57:39, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0434, loss_cls: 0.1867, acc: 93.1765, loss_bbox: 0.2299, loss_mask: 0.2312, loss: 0.7148 2023-11-13 19:07:00,003 - mmdet - INFO - Epoch [5][850/7330] lr: 1.000e-04, eta: 4:57:24, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0400, loss_cls: 0.1844, acc: 93.3657, loss_bbox: 0.2249, loss_mask: 0.2292, loss: 0.7004 2023-11-13 19:07:15,219 - mmdet - INFO - Epoch [5][900/7330] lr: 1.000e-04, eta: 4:57:08, time: 0.304, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0417, loss_cls: 0.1843, acc: 93.2595, loss_bbox: 0.2311, loss_mask: 0.2323, loss: 0.7133 2023-11-13 19:07:30,867 - mmdet - INFO - Epoch [5][950/7330] lr: 1.000e-04, eta: 4:56:53, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0440, loss_cls: 0.1874, acc: 93.0801, loss_bbox: 0.2342, loss_mask: 0.2310, loss: 0.7199 2023-11-13 19:07:46,677 - mmdet - INFO - Epoch [5][1000/7330] lr: 1.000e-04, eta: 4:56:38, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0416, loss_cls: 0.1803, acc: 93.3240, loss_bbox: 0.2292, loss_mask: 0.2302, loss: 0.7054 2023-11-13 19:08:02,288 - mmdet - INFO - Epoch [5][1050/7330] lr: 1.000e-04, eta: 4:56:23, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0423, loss_cls: 0.1853, acc: 93.2646, loss_bbox: 0.2332, loss_mask: 0.2343, loss: 0.7193 2023-11-13 19:08:17,730 - mmdet - INFO - Epoch [5][1100/7330] lr: 1.000e-04, eta: 4:56:07, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0452, loss_cls: 0.1895, acc: 93.1255, loss_bbox: 0.2338, loss_mask: 0.2335, loss: 0.7265 2023-11-13 19:08:33,318 - mmdet - INFO - Epoch [5][1150/7330] lr: 1.000e-04, eta: 4:55:52, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0437, loss_cls: 0.1801, acc: 93.4019, loss_bbox: 0.2327, loss_mask: 0.2298, loss: 0.7113 2023-11-13 19:08:48,533 - mmdet - INFO - Epoch [5][1200/7330] lr: 1.000e-04, eta: 4:55:36, time: 0.304, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0409, loss_cls: 0.1775, acc: 93.5742, loss_bbox: 0.2187, loss_mask: 0.2247, loss: 0.6829 2023-11-13 19:09:04,092 - mmdet - INFO - Epoch [5][1250/7330] lr: 1.000e-04, eta: 4:55:21, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0408, loss_cls: 0.1839, acc: 93.3535, loss_bbox: 0.2287, loss_mask: 0.2288, loss: 0.7030 2023-11-13 19:09:19,778 - mmdet - INFO - Epoch [5][1300/7330] lr: 1.000e-04, eta: 4:55:06, time: 0.314, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0431, loss_cls: 0.1866, acc: 93.1626, loss_bbox: 0.2265, loss_mask: 0.2300, loss: 0.7079 2023-11-13 19:09:35,290 - mmdet - INFO - Epoch [5][1350/7330] lr: 1.000e-04, eta: 4:54:51, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0427, loss_cls: 0.1761, acc: 93.5476, loss_bbox: 0.2255, loss_mask: 0.2279, loss: 0.6942 2023-11-13 19:09:50,503 - mmdet - INFO - Epoch [5][1400/7330] lr: 1.000e-04, eta: 4:54:35, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0409, loss_cls: 0.1806, acc: 93.3855, loss_bbox: 0.2283, loss_mask: 0.2281, loss: 0.6996 2023-11-13 19:10:05,788 - mmdet - INFO - Epoch [5][1450/7330] lr: 1.000e-04, eta: 4:54:19, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0464, loss_cls: 0.1939, acc: 92.8330, loss_bbox: 0.2413, loss_mask: 0.2335, loss: 0.7392 2023-11-13 19:10:21,005 - mmdet - INFO - Epoch [5][1500/7330] lr: 1.000e-04, eta: 4:54:03, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0422, loss_cls: 0.1756, acc: 93.5833, loss_bbox: 0.2225, loss_mask: 0.2294, loss: 0.6922 2023-11-13 19:10:36,498 - mmdet - INFO - Epoch [5][1550/7330] lr: 1.000e-04, eta: 4:53:48, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0405, loss_cls: 0.1841, acc: 93.1865, loss_bbox: 0.2303, loss_mask: 0.2306, loss: 0.7062 2023-11-13 19:10:52,255 - mmdet - INFO - Epoch [5][1600/7330] lr: 1.000e-04, eta: 4:53:33, time: 0.315, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0421, loss_cls: 0.1897, acc: 93.0881, loss_bbox: 0.2304, loss_mask: 0.2320, loss: 0.7172 2023-11-13 19:11:07,860 - mmdet - INFO - Epoch [5][1650/7330] lr: 1.000e-04, eta: 4:53:18, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0457, loss_cls: 0.1905, acc: 93.0229, loss_bbox: 0.2353, loss_mask: 0.2380, loss: 0.7334 2023-11-13 19:11:23,353 - mmdet - INFO - Epoch [5][1700/7330] lr: 1.000e-04, eta: 4:53:03, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0419, loss_cls: 0.1793, acc: 93.4270, loss_bbox: 0.2268, loss_mask: 0.2330, loss: 0.7040 2023-11-13 19:11:41,875 - mmdet - INFO - Epoch [5][1750/7330] lr: 1.000e-04, eta: 4:52:53, time: 0.370, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0404, loss_cls: 0.1852, acc: 93.3567, loss_bbox: 0.2287, loss_mask: 0.2306, loss: 0.7076 2023-11-13 19:11:57,407 - mmdet - INFO - Epoch [5][1800/7330] lr: 1.000e-04, eta: 4:52:38, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0450, loss_cls: 0.1923, acc: 93.1042, loss_bbox: 0.2320, loss_mask: 0.2346, loss: 0.7287 2023-11-13 19:12:13,075 - mmdet - INFO - Epoch [5][1850/7330] lr: 1.000e-04, eta: 4:52:23, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0421, loss_cls: 0.1847, acc: 93.1575, loss_bbox: 0.2323, loss_mask: 0.2331, loss: 0.7153 2023-11-13 19:12:28,511 - mmdet - INFO - Epoch [5][1900/7330] lr: 1.000e-04, eta: 4:52:07, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0406, loss_cls: 0.1797, acc: 93.4817, loss_bbox: 0.2226, loss_mask: 0.2316, loss: 0.6971 2023-11-13 19:12:43,860 - mmdet - INFO - Epoch [5][1950/7330] lr: 1.000e-04, eta: 4:51:52, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0456, loss_cls: 0.1939, acc: 92.9880, loss_bbox: 0.2413, loss_mask: 0.2409, loss: 0.7464 2023-11-13 19:12:59,394 - mmdet - INFO - Epoch [5][2000/7330] lr: 1.000e-04, eta: 4:51:36, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0415, loss_cls: 0.1825, acc: 93.2717, loss_bbox: 0.2306, loss_mask: 0.2393, loss: 0.7168 2023-11-13 19:13:14,874 - mmdet - INFO - Epoch [5][2050/7330] lr: 1.000e-04, eta: 4:51:21, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0413, loss_cls: 0.1845, acc: 93.1604, loss_bbox: 0.2341, loss_mask: 0.2336, loss: 0.7167 2023-11-13 19:13:30,394 - mmdet - INFO - Epoch [5][2100/7330] lr: 1.000e-04, eta: 4:51:06, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0468, loss_cls: 0.1965, acc: 92.7993, loss_bbox: 0.2467, loss_mask: 0.2397, loss: 0.7537 2023-11-13 19:13:45,630 - mmdet - INFO - Epoch [5][2150/7330] lr: 1.000e-04, eta: 4:50:50, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0408, loss_cls: 0.1849, acc: 93.3274, loss_bbox: 0.2225, loss_mask: 0.2237, loss: 0.6945 2023-11-13 19:14:01,151 - mmdet - INFO - Epoch [5][2200/7330] lr: 1.000e-04, eta: 4:50:34, time: 0.310, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0416, loss_cls: 0.1894, acc: 93.1008, loss_bbox: 0.2374, loss_mask: 0.2320, loss: 0.7242 2023-11-13 19:14:16,558 - mmdet - INFO - Epoch [5][2250/7330] lr: 1.000e-04, eta: 4:50:19, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0453, loss_cls: 0.1878, acc: 93.1558, loss_bbox: 0.2343, loss_mask: 0.2310, loss: 0.7216 2023-11-13 19:14:31,914 - mmdet - INFO - Epoch [5][2300/7330] lr: 1.000e-04, eta: 4:50:03, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0430, loss_cls: 0.1877, acc: 93.1765, loss_bbox: 0.2329, loss_mask: 0.2333, loss: 0.7215 2023-11-13 19:14:47,152 - mmdet - INFO - Epoch [5][2350/7330] lr: 1.000e-04, eta: 4:49:47, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0432, loss_cls: 0.1794, acc: 93.3989, loss_bbox: 0.2312, loss_mask: 0.2304, loss: 0.7080 2023-11-13 19:15:02,228 - mmdet - INFO - Epoch [5][2400/7330] lr: 1.000e-04, eta: 4:49:31, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0433, loss_cls: 0.1842, acc: 93.2864, loss_bbox: 0.2299, loss_mask: 0.2310, loss: 0.7123 2023-11-13 19:15:17,830 - mmdet - INFO - Epoch [5][2450/7330] lr: 1.000e-04, eta: 4:49:16, time: 0.312, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0423, loss_cls: 0.1909, acc: 92.9468, loss_bbox: 0.2361, loss_mask: 0.2297, loss: 0.7223 2023-11-13 19:15:33,113 - mmdet - INFO - Epoch [5][2500/7330] lr: 1.000e-04, eta: 4:49:00, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0421, loss_cls: 0.1788, acc: 93.5000, loss_bbox: 0.2210, loss_mask: 0.2257, loss: 0.6904 2023-11-13 19:15:48,319 - mmdet - INFO - Epoch [5][2550/7330] lr: 1.000e-04, eta: 4:48:45, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0428, loss_cls: 0.1847, acc: 93.3118, loss_bbox: 0.2292, loss_mask: 0.2358, loss: 0.7158 2023-11-13 19:16:03,905 - mmdet - INFO - Epoch [5][2600/7330] lr: 1.000e-04, eta: 4:48:29, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0464, loss_cls: 0.1883, acc: 93.0891, loss_bbox: 0.2305, loss_mask: 0.2342, loss: 0.7251 2023-11-13 19:16:19,214 - mmdet - INFO - Epoch [5][2650/7330] lr: 1.000e-04, eta: 4:48:14, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0380, loss_cls: 0.1826, acc: 93.3574, loss_bbox: 0.2208, loss_mask: 0.2270, loss: 0.6877 2023-11-13 19:16:34,593 - mmdet - INFO - Epoch [5][2700/7330] lr: 1.000e-04, eta: 4:47:58, time: 0.308, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0409, loss_cls: 0.1944, acc: 92.8745, loss_bbox: 0.2408, loss_mask: 0.2364, loss: 0.7339 2023-11-13 19:16:50,559 - mmdet - INFO - Epoch [5][2750/7330] lr: 1.000e-04, eta: 4:47:44, time: 0.319, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0479, loss_cls: 0.1986, acc: 92.6995, loss_bbox: 0.2474, loss_mask: 0.2336, loss: 0.7527 2023-11-13 19:17:05,864 - mmdet - INFO - Epoch [5][2800/7330] lr: 1.000e-04, eta: 4:47:28, time: 0.306, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0464, loss_cls: 0.1937, acc: 92.9590, loss_bbox: 0.2409, loss_mask: 0.2357, loss: 0.7432 2023-11-13 19:17:21,281 - mmdet - INFO - Epoch [5][2850/7330] lr: 1.000e-04, eta: 4:47:12, time: 0.308, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0431, loss_cls: 0.1869, acc: 93.2063, loss_bbox: 0.2344, loss_mask: 0.2346, loss: 0.7220 2023-11-13 19:17:36,795 - mmdet - INFO - Epoch [5][2900/7330] lr: 1.000e-04, eta: 4:46:57, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0442, loss_cls: 0.1863, acc: 93.0969, loss_bbox: 0.2344, loss_mask: 0.2300, loss: 0.7180 2023-11-13 19:17:52,187 - mmdet - INFO - Epoch [5][2950/7330] lr: 1.000e-04, eta: 4:46:42, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0414, loss_cls: 0.1762, acc: 93.6472, loss_bbox: 0.2216, loss_mask: 0.2310, loss: 0.6936 2023-11-13 19:18:07,158 - mmdet - INFO - Epoch [5][3000/7330] lr: 1.000e-04, eta: 4:46:25, time: 0.299, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0423, loss_cls: 0.1867, acc: 93.1299, loss_bbox: 0.2288, loss_mask: 0.2334, loss: 0.7129 2023-11-13 19:18:22,335 - mmdet - INFO - Epoch [5][3050/7330] lr: 1.000e-04, eta: 4:46:09, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0416, loss_cls: 0.1843, acc: 93.3328, loss_bbox: 0.2264, loss_mask: 0.2275, loss: 0.7024 2023-11-13 19:18:37,673 - mmdet - INFO - Epoch [5][3100/7330] lr: 1.000e-04, eta: 4:45:54, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0405, loss_cls: 0.1790, acc: 93.5144, loss_bbox: 0.2229, loss_mask: 0.2277, loss: 0.6923 2023-11-13 19:18:53,290 - mmdet - INFO - Epoch [5][3150/7330] lr: 1.000e-04, eta: 4:45:39, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0439, loss_cls: 0.1937, acc: 92.8262, loss_bbox: 0.2388, loss_mask: 0.2350, loss: 0.7350 2023-11-13 19:19:08,588 - mmdet - INFO - Epoch [5][3200/7330] lr: 1.000e-04, eta: 4:45:23, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0434, loss_cls: 0.1848, acc: 93.3394, loss_bbox: 0.2308, loss_mask: 0.2347, loss: 0.7180 2023-11-13 19:19:23,627 - mmdet - INFO - Epoch [5][3250/7330] lr: 1.000e-04, eta: 4:45:07, time: 0.301, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0413, loss_cls: 0.1795, acc: 93.4526, loss_bbox: 0.2268, loss_mask: 0.2315, loss: 0.7014 2023-11-13 19:19:38,890 - mmdet - INFO - Epoch [5][3300/7330] lr: 1.000e-04, eta: 4:44:51, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0418, loss_cls: 0.1806, acc: 93.5383, loss_bbox: 0.2205, loss_mask: 0.2326, loss: 0.6982 2023-11-13 19:19:54,484 - mmdet - INFO - Epoch [5][3350/7330] lr: 1.000e-04, eta: 4:44:36, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0408, loss_cls: 0.1812, acc: 93.3860, loss_bbox: 0.2274, loss_mask: 0.2279, loss: 0.7004 2023-11-13 19:20:09,699 - mmdet - INFO - Epoch [5][3400/7330] lr: 1.000e-04, eta: 4:44:20, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0421, loss_cls: 0.1785, acc: 93.4966, loss_bbox: 0.2271, loss_mask: 0.2298, loss: 0.6991 2023-11-13 19:20:25,124 - mmdet - INFO - Epoch [5][3450/7330] lr: 1.000e-04, eta: 4:44:05, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0425, loss_cls: 0.1898, acc: 93.1240, loss_bbox: 0.2344, loss_mask: 0.2298, loss: 0.7220 2023-11-13 19:20:40,775 - mmdet - INFO - Epoch [5][3500/7330] lr: 1.000e-04, eta: 4:43:50, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0450, loss_cls: 0.1951, acc: 92.8333, loss_bbox: 0.2409, loss_mask: 0.2379, loss: 0.7428 2023-11-13 19:20:55,918 - mmdet - INFO - Epoch [5][3550/7330] lr: 1.000e-04, eta: 4:43:34, time: 0.303, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0412, loss_cls: 0.1724, acc: 93.6509, loss_bbox: 0.2195, loss_mask: 0.2255, loss: 0.6825 2023-11-13 19:21:11,896 - mmdet - INFO - Epoch [5][3600/7330] lr: 1.000e-04, eta: 4:43:19, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0463, loss_cls: 0.1872, acc: 93.0598, loss_bbox: 0.2359, loss_mask: 0.2310, loss: 0.7276 2023-11-13 19:21:26,875 - mmdet - INFO - Epoch [5][3650/7330] lr: 1.000e-04, eta: 4:43:03, time: 0.300, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0392, loss_cls: 0.1800, acc: 93.4988, loss_bbox: 0.2202, loss_mask: 0.2315, loss: 0.6911 2023-11-13 19:21:42,408 - mmdet - INFO - Epoch [5][3700/7330] lr: 1.000e-04, eta: 4:42:48, time: 0.311, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0433, loss_cls: 0.1894, acc: 93.1592, loss_bbox: 0.2361, loss_mask: 0.2325, loss: 0.7249 2023-11-13 19:21:57,404 - mmdet - INFO - Epoch [5][3750/7330] lr: 1.000e-04, eta: 4:42:31, time: 0.300, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0414, loss_cls: 0.1860, acc: 93.2397, loss_bbox: 0.2266, loss_mask: 0.2304, loss: 0.7079 2023-11-13 19:22:12,517 - mmdet - INFO - Epoch [5][3800/7330] lr: 1.000e-04, eta: 4:42:15, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0442, loss_cls: 0.1923, acc: 92.9790, loss_bbox: 0.2413, loss_mask: 0.2343, loss: 0.7358 2023-11-13 19:22:28,007 - mmdet - INFO - Epoch [5][3850/7330] lr: 1.000e-04, eta: 4:42:00, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0410, loss_cls: 0.1822, acc: 93.2483, loss_bbox: 0.2281, loss_mask: 0.2321, loss: 0.7079 2023-11-13 19:22:43,145 - mmdet - INFO - Epoch [5][3900/7330] lr: 1.000e-04, eta: 4:41:44, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0412, loss_cls: 0.1839, acc: 93.3213, loss_bbox: 0.2241, loss_mask: 0.2295, loss: 0.7013 2023-11-13 19:22:58,308 - mmdet - INFO - Epoch [5][3950/7330] lr: 1.000e-04, eta: 4:41:28, time: 0.303, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0417, loss_cls: 0.1855, acc: 93.1938, loss_bbox: 0.2296, loss_mask: 0.2308, loss: 0.7104 2023-11-13 19:23:13,801 - mmdet - INFO - Epoch [5][4000/7330] lr: 1.000e-04, eta: 4:41:13, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0469, loss_cls: 0.1875, acc: 93.1953, loss_bbox: 0.2390, loss_mask: 0.2333, loss: 0.7311 2023-11-13 19:23:28,953 - mmdet - INFO - Epoch [5][4050/7330] lr: 1.000e-04, eta: 4:40:57, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0410, loss_cls: 0.1832, acc: 93.2317, loss_bbox: 0.2302, loss_mask: 0.2315, loss: 0.7097 2023-11-13 19:23:44,372 - mmdet - INFO - Epoch [5][4100/7330] lr: 1.000e-04, eta: 4:40:41, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0426, loss_cls: 0.1882, acc: 93.1570, loss_bbox: 0.2317, loss_mask: 0.2292, loss: 0.7154 2023-11-13 19:23:59,848 - mmdet - INFO - Epoch [5][4150/7330] lr: 1.000e-04, eta: 4:40:26, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0425, loss_cls: 0.1861, acc: 93.3135, loss_bbox: 0.2284, loss_mask: 0.2315, loss: 0.7111 2023-11-13 19:24:15,292 - mmdet - INFO - Epoch [5][4200/7330] lr: 1.000e-04, eta: 4:40:11, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0415, loss_cls: 0.1820, acc: 93.3276, loss_bbox: 0.2253, loss_mask: 0.2275, loss: 0.7004 2023-11-13 19:24:31,384 - mmdet - INFO - Epoch [5][4250/7330] lr: 1.000e-04, eta: 4:39:56, time: 0.322, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0440, loss_cls: 0.1851, acc: 93.3604, loss_bbox: 0.2244, loss_mask: 0.2358, loss: 0.7114 2023-11-13 19:24:46,691 - mmdet - INFO - Epoch [5][4300/7330] lr: 1.000e-04, eta: 4:39:41, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0418, loss_cls: 0.1925, acc: 93.0354, loss_bbox: 0.2369, loss_mask: 0.2387, loss: 0.7335 2023-11-13 19:25:01,951 - mmdet - INFO - Epoch [5][4350/7330] lr: 1.000e-04, eta: 4:39:25, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0440, loss_cls: 0.1929, acc: 93.0559, loss_bbox: 0.2386, loss_mask: 0.2329, loss: 0.7337 2023-11-13 19:25:17,473 - mmdet - INFO - Epoch [5][4400/7330] lr: 1.000e-04, eta: 4:39:09, time: 0.310, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0424, loss_cls: 0.1823, acc: 93.4866, loss_bbox: 0.2234, loss_mask: 0.2289, loss: 0.7001 2023-11-13 19:25:33,031 - mmdet - INFO - Epoch [5][4450/7330] lr: 1.000e-04, eta: 4:38:54, time: 0.311, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0450, loss_cls: 0.1880, acc: 93.1438, loss_bbox: 0.2342, loss_mask: 0.2326, loss: 0.7237 2023-11-13 19:25:48,107 - mmdet - INFO - Epoch [5][4500/7330] lr: 1.000e-04, eta: 4:38:38, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0396, loss_cls: 0.1834, acc: 93.4326, loss_bbox: 0.2229, loss_mask: 0.2293, loss: 0.6964 2023-11-13 19:26:04,090 - mmdet - INFO - Epoch [5][4550/7330] lr: 1.000e-04, eta: 4:38:24, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0442, loss_cls: 0.1891, acc: 93.1006, loss_bbox: 0.2330, loss_mask: 0.2305, loss: 0.7217 2023-11-13 19:26:19,471 - mmdet - INFO - Epoch [5][4600/7330] lr: 1.000e-04, eta: 4:38:08, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0446, loss_cls: 0.1850, acc: 93.1768, loss_bbox: 0.2324, loss_mask: 0.2318, loss: 0.7193 2023-11-13 19:26:35,132 - mmdet - INFO - Epoch [5][4650/7330] lr: 1.000e-04, eta: 4:37:53, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0414, loss_cls: 0.1878, acc: 93.1868, loss_bbox: 0.2332, loss_mask: 0.2344, loss: 0.7190 2023-11-13 19:26:50,545 - mmdet - INFO - Epoch [5][4700/7330] lr: 1.000e-04, eta: 4:37:38, time: 0.308, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0458, loss_cls: 0.1969, acc: 92.8245, loss_bbox: 0.2390, loss_mask: 0.2346, loss: 0.7401 2023-11-13 19:27:05,661 - mmdet - INFO - Epoch [5][4750/7330] lr: 1.000e-04, eta: 4:37:22, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0415, loss_cls: 0.1844, acc: 93.3245, loss_bbox: 0.2309, loss_mask: 0.2319, loss: 0.7135 2023-11-13 19:27:20,754 - mmdet - INFO - Epoch [5][4800/7330] lr: 1.000e-04, eta: 4:37:06, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0402, loss_cls: 0.1900, acc: 93.1431, loss_bbox: 0.2320, loss_mask: 0.2324, loss: 0.7175 2023-11-13 19:27:36,336 - mmdet - INFO - Epoch [5][4850/7330] lr: 1.000e-04, eta: 4:36:50, time: 0.312, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0431, loss_cls: 0.1906, acc: 93.0903, loss_bbox: 0.2308, loss_mask: 0.2288, loss: 0.7184 2023-11-13 19:27:51,774 - mmdet - INFO - Epoch [5][4900/7330] lr: 1.000e-04, eta: 4:36:35, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0419, loss_cls: 0.1875, acc: 93.1746, loss_bbox: 0.2328, loss_mask: 0.2273, loss: 0.7103 2023-11-13 19:28:07,234 - mmdet - INFO - Epoch [5][4950/7330] lr: 1.000e-04, eta: 4:36:20, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0449, loss_cls: 0.1948, acc: 92.8777, loss_bbox: 0.2359, loss_mask: 0.2303, loss: 0.7301 2023-11-13 19:28:22,491 - mmdet - INFO - Epoch [5][5000/7330] lr: 1.000e-04, eta: 4:36:04, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0413, loss_cls: 0.1758, acc: 93.5547, loss_bbox: 0.2207, loss_mask: 0.2273, loss: 0.6856 2023-11-13 19:28:37,939 - mmdet - INFO - Epoch [5][5050/7330] lr: 1.000e-04, eta: 4:35:48, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0442, loss_cls: 0.1978, acc: 92.8896, loss_bbox: 0.2373, loss_mask: 0.2310, loss: 0.7343 2023-11-13 19:28:53,275 - mmdet - INFO - Epoch [5][5100/7330] lr: 1.000e-04, eta: 4:35:33, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0415, loss_cls: 0.1865, acc: 93.2756, loss_bbox: 0.2295, loss_mask: 0.2351, loss: 0.7162 2023-11-13 19:29:08,517 - mmdet - INFO - Epoch [5][5150/7330] lr: 1.000e-04, eta: 4:35:17, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0419, loss_cls: 0.1835, acc: 93.3533, loss_bbox: 0.2259, loss_mask: 0.2289, loss: 0.7045 2023-11-13 19:29:23,840 - mmdet - INFO - Epoch [5][5200/7330] lr: 1.000e-04, eta: 4:35:01, time: 0.306, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0431, loss_cls: 0.1795, acc: 93.5093, loss_bbox: 0.2239, loss_mask: 0.2296, loss: 0.7002 2023-11-13 19:29:39,006 - mmdet - INFO - Epoch [5][5250/7330] lr: 1.000e-04, eta: 4:34:46, time: 0.303, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0407, loss_cls: 0.1805, acc: 93.3425, loss_bbox: 0.2274, loss_mask: 0.2304, loss: 0.6998 2023-11-13 19:29:54,015 - mmdet - INFO - Epoch [5][5300/7330] lr: 1.000e-04, eta: 4:34:29, time: 0.300, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0392, loss_cls: 0.1795, acc: 93.5432, loss_bbox: 0.2178, loss_mask: 0.2279, loss: 0.6860 2023-11-13 19:30:09,421 - mmdet - INFO - Epoch [5][5350/7330] lr: 1.000e-04, eta: 4:34:14, time: 0.308, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0421, loss_cls: 0.1901, acc: 93.1287, loss_bbox: 0.2340, loss_mask: 0.2395, loss: 0.7302 2023-11-13 19:30:24,652 - mmdet - INFO - Epoch [5][5400/7330] lr: 1.000e-04, eta: 4:33:58, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0394, loss_cls: 0.1805, acc: 93.4084, loss_bbox: 0.2224, loss_mask: 0.2281, loss: 0.6951 2023-11-13 19:30:40,212 - mmdet - INFO - Epoch [5][5450/7330] lr: 1.000e-04, eta: 4:33:43, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0399, loss_cls: 0.1866, acc: 93.2292, loss_bbox: 0.2290, loss_mask: 0.2325, loss: 0.7120 2023-11-13 19:30:55,503 - mmdet - INFO - Epoch [5][5500/7330] lr: 1.000e-04, eta: 4:33:27, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0406, loss_cls: 0.1832, acc: 93.3599, loss_bbox: 0.2276, loss_mask: 0.2340, loss: 0.7082 2023-11-13 19:31:11,005 - mmdet - INFO - Epoch [5][5550/7330] lr: 1.000e-04, eta: 4:33:12, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0424, loss_cls: 0.1921, acc: 93.0281, loss_bbox: 0.2329, loss_mask: 0.2331, loss: 0.7252 2023-11-13 19:31:27,191 - mmdet - INFO - Epoch [5][5600/7330] lr: 1.000e-04, eta: 4:32:58, time: 0.324, data_time: 0.038, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0411, loss_cls: 0.1803, acc: 93.4216, loss_bbox: 0.2224, loss_mask: 0.2299, loss: 0.6943 2023-11-13 19:31:42,687 - mmdet - INFO - Epoch [5][5650/7330] lr: 1.000e-04, eta: 4:32:42, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0423, loss_cls: 0.1791, acc: 93.5000, loss_bbox: 0.2307, loss_mask: 0.2270, loss: 0.7019 2023-11-13 19:31:58,057 - mmdet - INFO - Epoch [5][5700/7330] lr: 1.000e-04, eta: 4:32:27, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0404, loss_cls: 0.1814, acc: 93.3926, loss_bbox: 0.2217, loss_mask: 0.2268, loss: 0.6934 2023-11-13 19:32:13,832 - mmdet - INFO - Epoch [5][5750/7330] lr: 1.000e-04, eta: 4:32:12, time: 0.315, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0460, loss_cls: 0.1961, acc: 92.8372, loss_bbox: 0.2427, loss_mask: 0.2363, loss: 0.7473 2023-11-13 19:32:29,515 - mmdet - INFO - Epoch [5][5800/7330] lr: 1.000e-04, eta: 4:31:57, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0418, loss_cls: 0.1786, acc: 93.5364, loss_bbox: 0.2224, loss_mask: 0.2267, loss: 0.6915 2023-11-13 19:32:45,216 - mmdet - INFO - Epoch [5][5850/7330] lr: 1.000e-04, eta: 4:31:42, time: 0.314, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0434, loss_cls: 0.1928, acc: 92.9756, loss_bbox: 0.2350, loss_mask: 0.2279, loss: 0.7233 2023-11-13 19:33:00,626 - mmdet - INFO - Epoch [5][5900/7330] lr: 1.000e-04, eta: 4:31:26, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0419, loss_cls: 0.1853, acc: 93.3025, loss_bbox: 0.2220, loss_mask: 0.2287, loss: 0.6997 2023-11-13 19:33:16,409 - mmdet - INFO - Epoch [5][5950/7330] lr: 1.000e-04, eta: 4:31:11, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0422, loss_cls: 0.1810, acc: 93.3723, loss_bbox: 0.2244, loss_mask: 0.2285, loss: 0.6998 2023-11-13 19:33:31,860 - mmdet - INFO - Epoch [5][6000/7330] lr: 1.000e-04, eta: 4:30:56, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0433, loss_cls: 0.1884, acc: 93.1052, loss_bbox: 0.2376, loss_mask: 0.2356, loss: 0.7311 2023-11-13 19:33:47,601 - mmdet - INFO - Epoch [5][6050/7330] lr: 1.000e-04, eta: 4:30:41, time: 0.315, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0421, loss_cls: 0.1841, acc: 93.1653, loss_bbox: 0.2271, loss_mask: 0.2251, loss: 0.7031 2023-11-13 19:34:02,701 - mmdet - INFO - Epoch [5][6100/7330] lr: 1.000e-04, eta: 4:30:25, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0414, loss_cls: 0.1832, acc: 93.2998, loss_bbox: 0.2331, loss_mask: 0.2281, loss: 0.7083 2023-11-13 19:34:17,863 - mmdet - INFO - Epoch [5][6150/7330] lr: 1.000e-04, eta: 4:30:09, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0403, loss_cls: 0.1797, acc: 93.3979, loss_bbox: 0.2299, loss_mask: 0.2331, loss: 0.7057 2023-11-13 19:34:33,230 - mmdet - INFO - Epoch [5][6200/7330] lr: 1.000e-04, eta: 4:29:53, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0427, loss_cls: 0.1908, acc: 93.1499, loss_bbox: 0.2402, loss_mask: 0.2354, loss: 0.7336 2023-11-13 19:34:48,474 - mmdet - INFO - Epoch [5][6250/7330] lr: 1.000e-04, eta: 4:29:38, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0424, loss_cls: 0.1915, acc: 93.0979, loss_bbox: 0.2297, loss_mask: 0.2297, loss: 0.7150 2023-11-13 19:35:03,922 - mmdet - INFO - Epoch [5][6300/7330] lr: 1.000e-04, eta: 4:29:22, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0435, loss_cls: 0.1930, acc: 92.9485, loss_bbox: 0.2367, loss_mask: 0.2334, loss: 0.7315 2023-11-13 19:35:19,932 - mmdet - INFO - Epoch [5][6350/7330] lr: 1.000e-04, eta: 4:29:08, time: 0.320, data_time: 0.042, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0405, loss_cls: 0.1852, acc: 93.3643, loss_bbox: 0.2240, loss_mask: 0.2249, loss: 0.6957 2023-11-13 19:35:35,351 - mmdet - INFO - Epoch [5][6400/7330] lr: 1.000e-04, eta: 4:28:52, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0419, loss_cls: 0.1825, acc: 93.2693, loss_bbox: 0.2276, loss_mask: 0.2314, loss: 0.7052 2023-11-13 19:35:50,933 - mmdet - INFO - Epoch [5][6450/7330] lr: 1.000e-04, eta: 4:28:37, time: 0.312, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0421, loss_cls: 0.1878, acc: 93.1235, loss_bbox: 0.2303, loss_mask: 0.2299, loss: 0.7142 2023-11-13 19:36:06,013 - mmdet - INFO - Epoch [5][6500/7330] lr: 1.000e-04, eta: 4:28:21, time: 0.302, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0414, loss_cls: 0.1910, acc: 93.1238, loss_bbox: 0.2286, loss_mask: 0.2290, loss: 0.7135 2023-11-13 19:36:21,793 - mmdet - INFO - Epoch [5][6550/7330] lr: 1.000e-04, eta: 4:28:06, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0430, loss_cls: 0.1872, acc: 93.2393, loss_bbox: 0.2239, loss_mask: 0.2291, loss: 0.7066 2023-11-13 19:36:37,317 - mmdet - INFO - Epoch [5][6600/7330] lr: 1.000e-04, eta: 4:27:51, time: 0.310, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0423, loss_cls: 0.1886, acc: 93.1609, loss_bbox: 0.2309, loss_mask: 0.2308, loss: 0.7155 2023-11-13 19:36:52,829 - mmdet - INFO - Epoch [5][6650/7330] lr: 1.000e-04, eta: 4:27:35, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0417, loss_cls: 0.1822, acc: 93.4258, loss_bbox: 0.2195, loss_mask: 0.2282, loss: 0.6970 2023-11-13 19:37:08,256 - mmdet - INFO - Epoch [5][6700/7330] lr: 1.000e-04, eta: 4:27:20, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0427, loss_cls: 0.1877, acc: 93.2271, loss_bbox: 0.2290, loss_mask: 0.2299, loss: 0.7122 2023-11-13 19:37:23,431 - mmdet - INFO - Epoch [5][6750/7330] lr: 1.000e-04, eta: 4:27:04, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0417, loss_cls: 0.1836, acc: 93.3845, loss_bbox: 0.2256, loss_mask: 0.2345, loss: 0.7099 2023-11-13 19:37:39,193 - mmdet - INFO - Epoch [5][6800/7330] lr: 1.000e-04, eta: 4:26:49, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0426, loss_cls: 0.1885, acc: 93.2109, loss_bbox: 0.2373, loss_mask: 0.2323, loss: 0.7236 2023-11-13 19:37:54,220 - mmdet - INFO - Epoch [5][6850/7330] lr: 1.000e-04, eta: 4:26:33, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0401, loss_cls: 0.1829, acc: 93.3979, loss_bbox: 0.2228, loss_mask: 0.2314, loss: 0.6988 2023-11-13 19:38:09,573 - mmdet - INFO - Epoch [5][6900/7330] lr: 1.000e-04, eta: 4:26:18, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0397, loss_cls: 0.1789, acc: 93.5479, loss_bbox: 0.2205, loss_mask: 0.2267, loss: 0.6881 2023-11-13 19:38:24,708 - mmdet - INFO - Epoch [5][6950/7330] lr: 1.000e-04, eta: 4:26:02, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0431, loss_cls: 0.1889, acc: 93.2712, loss_bbox: 0.2251, loss_mask: 0.2289, loss: 0.7098 2023-11-13 19:38:40,510 - mmdet - INFO - Epoch [5][7000/7330] lr: 1.000e-04, eta: 4:25:47, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0427, loss_cls: 0.1886, acc: 93.2078, loss_bbox: 0.2330, loss_mask: 0.2305, loss: 0.7197 2023-11-13 19:38:55,904 - mmdet - INFO - Epoch [5][7050/7330] lr: 1.000e-04, eta: 4:25:31, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0422, loss_cls: 0.1967, acc: 92.7598, loss_bbox: 0.2420, loss_mask: 0.2340, loss: 0.7392 2023-11-13 19:39:11,112 - mmdet - INFO - Epoch [5][7100/7330] lr: 1.000e-04, eta: 4:25:15, time: 0.304, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0413, loss_cls: 0.1782, acc: 93.5593, loss_bbox: 0.2205, loss_mask: 0.2291, loss: 0.6921 2023-11-13 19:39:26,691 - mmdet - INFO - Epoch [5][7150/7330] lr: 1.000e-04, eta: 4:25:00, time: 0.312, data_time: 0.032, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0430, loss_cls: 0.1818, acc: 93.4001, loss_bbox: 0.2259, loss_mask: 0.2241, loss: 0.6971 2023-11-13 19:39:41,602 - mmdet - INFO - Epoch [5][7200/7330] lr: 1.000e-04, eta: 4:24:44, time: 0.298, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0394, loss_cls: 0.1811, acc: 93.3652, loss_bbox: 0.2236, loss_mask: 0.2265, loss: 0.6910 2023-11-13 19:39:56,907 - mmdet - INFO - Epoch [5][7250/7330] lr: 1.000e-04, eta: 4:24:28, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0441, loss_cls: 0.1892, acc: 93.1201, loss_bbox: 0.2302, loss_mask: 0.2328, loss: 0.7206 2023-11-13 19:40:12,600 - mmdet - INFO - Epoch [5][7300/7330] lr: 1.000e-04, eta: 4:24:13, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0430, loss_cls: 0.1884, acc: 93.2112, loss_bbox: 0.2355, loss_mask: 0.2342, loss: 0.7250 2023-11-13 19:40:22,477 - mmdet - INFO - Saving checkpoint at 5 epochs 2023-11-13 19:41:08,430 - mmdet - INFO - Evaluating bbox... 2023-11-13 19:41:40,313 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.447 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.676 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.492 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.287 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.484 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.577 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.577 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.577 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.403 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.621 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.718 2023-11-13 19:41:40,316 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.565 | bicycle | 0.322 | car | 0.467 | | motorcycle | 0.441 | airplane | 0.681 | bus | 0.643 | | train | 0.658 | truck | 0.385 | boat | 0.323 | | traffic light | 0.302 | fire hydrant | 0.668 | stop sign | 0.662 | | parking meter | 0.474 | bench | 0.275 | bird | 0.386 | | cat | 0.706 | dog | 0.652 | horse | 0.603 | | sheep | 0.561 | cow | 0.599 | elephant | 0.651 | | bear | 0.746 | zebra | 0.681 | giraffe | 0.664 | | backpack | 0.196 | umbrella | 0.440 | handbag | 0.180 | | tie | 0.330 | suitcase | 0.453 | frisbee | 0.673 | | skis | 0.269 | snowboard | 0.401 | sports ball | 0.453 | | kite | 0.455 | baseball bat | 0.369 | baseball glove | 0.401 | | skateboard | 0.552 | surfboard | 0.427 | tennis racket | 0.497 | | bottle | 0.430 | wine glass | 0.391 | cup | 0.478 | | fork | 0.401 | knife | 0.245 | spoon | 0.226 | | bowl | 0.434 | banana | 0.274 | apple | 0.233 | | sandwich | 0.387 | orange | 0.334 | broccoli | 0.257 | | carrot | 0.229 | hot dog | 0.381 | pizza | 0.517 | | donut | 0.516 | cake | 0.392 | chair | 0.333 | | couch | 0.449 | potted plant | 0.302 | bed | 0.472 | | dining table | 0.286 | toilet | 0.639 | tv | 0.607 | | laptop | 0.631 | mouse | 0.619 | remote | 0.374 | | keyboard | 0.546 | cell phone | 0.380 | microwave | 0.617 | | oven | 0.378 | toaster | 0.349 | sink | 0.409 | | refrigerator | 0.574 | book | 0.181 | clock | 0.508 | | vase | 0.395 | scissors | 0.430 | teddy bear | 0.506 | | hair drier | 0.171 | toothbrush | 0.276 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:41:40,316 - mmdet - INFO - Evaluating segm... 2023-11-13 19:42:17,307 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.409 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.644 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.439 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.214 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 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.342 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.578 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.692 2023-11-13 19:42:17,309 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.485 | bicycle | 0.200 | car | 0.429 | | motorcycle | 0.363 | airplane | 0.540 | bus | 0.659 | | train | 0.646 | truck | 0.385 | boat | 0.281 | | traffic light | 0.289 | fire hydrant | 0.670 | stop sign | 0.681 | | parking meter | 0.499 | bench | 0.213 | bird | 0.322 | | cat | 0.710 | dog | 0.625 | horse | 0.438 | | sheep | 0.501 | cow | 0.507 | elephant | 0.602 | | bear | 0.743 | zebra | 0.592 | giraffe | 0.525 | | backpack | 0.203 | umbrella | 0.506 | handbag | 0.184 | | tie | 0.320 | suitcase | 0.463 | frisbee | 0.653 | | skis | 0.042 | snowboard | 0.271 | sports ball | 0.458 | | kite | 0.320 | baseball bat | 0.290 | baseball glove | 0.441 | | skateboard | 0.334 | surfboard | 0.353 | tennis racket | 0.577 | | bottle | 0.415 | wine glass | 0.344 | cup | 0.485 | | fork | 0.206 | knife | 0.160 | spoon | 0.153 | | bowl | 0.417 | banana | 0.222 | apple | 0.232 | | sandwich | 0.410 | orange | 0.341 | broccoli | 0.237 | | carrot | 0.207 | hot dog | 0.319 | pizza | 0.518 | | donut | 0.541 | cake | 0.408 | chair | 0.237 | | couch | 0.379 | potted plant | 0.258 | bed | 0.381 | | dining table | 0.164 | toilet | 0.625 | tv | 0.641 | | laptop | 0.647 | mouse | 0.633 | remote | 0.341 | | keyboard | 0.546 | cell phone | 0.373 | microwave | 0.647 | | oven | 0.354 | toaster | 0.442 | sink | 0.387 | | refrigerator | 0.597 | book | 0.131 | clock | 0.527 | | vase | 0.407 | scissors | 0.345 | teddy bear | 0.482 | | hair drier | 0.080 | toothbrush | 0.186 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:42:17,792 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_4.pth was removed 2023-11-13 19:42:19,431 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_5.pth. 2023-11-13 19:42:19,431 - mmdet - INFO - Best bbox_mAP is 0.4471 at 5 epoch. 2023-11-13 19:42:19,432 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:42:19,432 - mmdet - INFO - Epoch(val) [5][625] bbox_mAP: 0.4471, bbox_mAP_50: 0.6762, bbox_mAP_75: 0.4924, bbox_mAP_s: 0.2870, bbox_mAP_m: 0.4844, bbox_mAP_l: 0.5817, bbox_mAP_copypaste: 0.4471 0.6762 0.4924 0.2870 0.4844 0.5817, segm_mAP: 0.4094, segm_mAP_50: 0.6436, segm_mAP_75: 0.4395, segm_mAP_s: 0.2138, segm_mAP_m: 0.4418, segm_mAP_l: 0.5948, segm_mAP_copypaste: 0.4094 0.6436 0.4395 0.2138 0.4418 0.5948 2023-11-13 19:42:38,539 - mmdet - INFO - Epoch [6][50/7330] lr: 1.000e-04, eta: 4:23:41, time: 0.382, data_time: 0.089, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0409, loss_cls: 0.1762, acc: 93.5571, loss_bbox: 0.2217, loss_mask: 0.2221, loss: 0.6827 2023-11-13 19:42:54,915 - mmdet - INFO - Epoch [6][100/7330] lr: 1.000e-04, eta: 4:23:27, time: 0.328, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0416, loss_cls: 0.1743, acc: 93.4663, loss_bbox: 0.2235, loss_mask: 0.2275, loss: 0.6870 2023-11-13 19:43:10,772 - mmdet - INFO - Epoch [6][150/7330] lr: 1.000e-04, eta: 4:23:12, time: 0.317, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0394, loss_cls: 0.1719, acc: 93.7410, loss_bbox: 0.2165, loss_mask: 0.2275, loss: 0.6759 2023-11-13 19:43:26,680 - mmdet - INFO - Epoch [6][200/7330] lr: 1.000e-04, eta: 4:22:57, time: 0.318, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0413, loss_cls: 0.1744, acc: 93.4863, loss_bbox: 0.2268, loss_mask: 0.2274, loss: 0.6895 2023-11-13 19:43:42,624 - mmdet - INFO - Epoch [6][250/7330] lr: 1.000e-04, eta: 4:22:42, time: 0.319, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0412, loss_cls: 0.1727, acc: 93.6228, loss_bbox: 0.2197, loss_mask: 0.2296, loss: 0.6836 2023-11-13 19:43:58,760 - mmdet - INFO - Epoch [6][300/7330] lr: 1.000e-04, eta: 4:22:28, time: 0.323, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0426, loss_cls: 0.1798, acc: 93.3813, loss_bbox: 0.2277, loss_mask: 0.2322, loss: 0.7065 2023-11-13 19:44:14,526 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:44:14,526 - mmdet - INFO - Epoch [6][350/7330] lr: 1.000e-04, eta: 4:22:13, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0421, loss_cls: 0.1728, acc: 93.5769, loss_bbox: 0.2217, loss_mask: 0.2225, loss: 0.6800 2023-11-13 19:44:30,140 - mmdet - INFO - Epoch [6][400/7330] lr: 1.000e-04, eta: 4:21:58, time: 0.312, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0387, loss_cls: 0.1690, acc: 93.8071, loss_bbox: 0.2146, loss_mask: 0.2187, loss: 0.6634 2023-11-13 19:44:45,594 - mmdet - INFO - Epoch [6][450/7330] lr: 1.000e-04, eta: 4:21:42, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0411, loss_cls: 0.1749, acc: 93.4866, loss_bbox: 0.2192, loss_mask: 0.2221, loss: 0.6793 2023-11-13 19:45:01,188 - mmdet - INFO - Epoch [6][500/7330] lr: 1.000e-04, eta: 4:21:27, time: 0.312, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0420, loss_cls: 0.1799, acc: 93.2913, loss_bbox: 0.2255, loss_mask: 0.2264, loss: 0.6951 2023-11-13 19:45:16,419 - mmdet - INFO - Epoch [6][550/7330] lr: 1.000e-04, eta: 4:21:11, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0392, loss_cls: 0.1721, acc: 93.5693, loss_bbox: 0.2167, loss_mask: 0.2235, loss: 0.6714 2023-11-13 19:45:32,133 - mmdet - INFO - Epoch [6][600/7330] lr: 1.000e-04, eta: 4:20:56, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0443, loss_cls: 0.1821, acc: 93.3062, loss_bbox: 0.2274, loss_mask: 0.2309, loss: 0.7082 2023-11-13 19:45:47,476 - mmdet - INFO - Epoch [6][650/7330] lr: 1.000e-04, eta: 4:20:41, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0408, loss_cls: 0.1766, acc: 93.4729, loss_bbox: 0.2267, loss_mask: 0.2281, loss: 0.6939 2023-11-13 19:46:03,223 - mmdet - INFO - Epoch [6][700/7330] lr: 1.000e-04, eta: 4:20:26, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0414, loss_cls: 0.1823, acc: 93.2825, loss_bbox: 0.2271, loss_mask: 0.2271, loss: 0.7003 2023-11-13 19:46:18,745 - mmdet - INFO - Epoch [6][750/7330] lr: 1.000e-04, eta: 4:20:10, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0389, loss_cls: 0.1685, acc: 93.7546, loss_bbox: 0.2179, loss_mask: 0.2281, loss: 0.6730 2023-11-13 19:46:34,433 - mmdet - INFO - Epoch [6][800/7330] lr: 1.000e-04, eta: 4:19:55, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0429, loss_cls: 0.1862, acc: 93.1694, loss_bbox: 0.2335, loss_mask: 0.2291, loss: 0.7132 2023-11-13 19:46:50,160 - mmdet - INFO - Epoch [6][850/7330] lr: 1.000e-04, eta: 4:19:40, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0421, loss_cls: 0.1823, acc: 93.2803, loss_bbox: 0.2338, loss_mask: 0.2275, loss: 0.7096 2023-11-13 19:47:05,486 - mmdet - INFO - Epoch [6][900/7330] lr: 1.000e-04, eta: 4:19:25, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0380, loss_cls: 0.1724, acc: 93.6931, loss_bbox: 0.2172, loss_mask: 0.2228, loss: 0.6693 2023-11-13 19:47:20,620 - mmdet - INFO - Epoch [6][950/7330] lr: 1.000e-04, eta: 4:19:09, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0374, loss_cls: 0.1639, acc: 93.8845, loss_bbox: 0.2100, loss_mask: 0.2179, loss: 0.6491 2023-11-13 19:47:36,599 - mmdet - INFO - Epoch [6][1000/7330] lr: 1.000e-04, eta: 4:18:54, time: 0.320, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0416, loss_cls: 0.1840, acc: 93.1074, loss_bbox: 0.2274, loss_mask: 0.2231, loss: 0.6984 2023-11-13 19:47:52,540 - mmdet - INFO - Epoch [6][1050/7330] lr: 1.000e-04, eta: 4:18:39, time: 0.319, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0407, loss_cls: 0.1765, acc: 93.4888, loss_bbox: 0.2187, loss_mask: 0.2240, loss: 0.6817 2023-11-13 19:48:08,226 - mmdet - INFO - Epoch [6][1100/7330] lr: 1.000e-04, eta: 4:18:24, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0428, loss_cls: 0.1741, acc: 93.5520, loss_bbox: 0.2243, loss_mask: 0.2288, loss: 0.6935 2023-11-13 19:48:23,802 - mmdet - INFO - Epoch [6][1150/7330] lr: 1.000e-04, eta: 4:18:09, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0416, loss_cls: 0.1782, acc: 93.4104, loss_bbox: 0.2259, loss_mask: 0.2292, loss: 0.6956 2023-11-13 19:48:39,554 - mmdet - INFO - Epoch [6][1200/7330] lr: 1.000e-04, eta: 4:17:54, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0430, loss_cls: 0.1882, acc: 93.0261, loss_bbox: 0.2384, loss_mask: 0.2405, loss: 0.7322 2023-11-13 19:48:55,273 - mmdet - INFO - Epoch [6][1250/7330] lr: 1.000e-04, eta: 4:17:39, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0385, loss_cls: 0.1699, acc: 93.7173, loss_bbox: 0.2164, loss_mask: 0.2236, loss: 0.6679 2023-11-13 19:49:10,584 - mmdet - INFO - Epoch [6][1300/7330] lr: 1.000e-04, eta: 4:17:23, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0407, loss_cls: 0.1758, acc: 93.5056, loss_bbox: 0.2228, loss_mask: 0.2284, loss: 0.6876 2023-11-13 19:49:26,077 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:49:26,078 - mmdet - INFO - Epoch [6][1350/7330] lr: 1.000e-04, eta: 4:17:08, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0425, loss_cls: 0.1811, acc: 93.2891, loss_bbox: 0.2229, loss_mask: 0.2254, loss: 0.6941 2023-11-13 19:49:41,375 - mmdet - INFO - Epoch [6][1400/7330] lr: 1.000e-04, eta: 4:16:52, time: 0.306, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0384, loss_cls: 0.1749, acc: 93.5151, loss_bbox: 0.2211, loss_mask: 0.2271, loss: 0.6829 2023-11-13 19:49:56,880 - mmdet - INFO - Epoch [6][1450/7330] lr: 1.000e-04, eta: 4:16:37, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0424, loss_cls: 0.1834, acc: 93.1919, loss_bbox: 0.2315, loss_mask: 0.2307, loss: 0.7096 2023-11-13 19:50:12,650 - mmdet - INFO - Epoch [6][1500/7330] lr: 1.000e-04, eta: 4:16:22, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0389, loss_cls: 0.1718, acc: 93.7083, loss_bbox: 0.2156, loss_mask: 0.2278, loss: 0.6747 2023-11-13 19:50:28,094 - mmdet - INFO - Epoch [6][1550/7330] lr: 1.000e-04, eta: 4:16:06, time: 0.309, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0437, loss_cls: 0.1836, acc: 93.1990, loss_bbox: 0.2308, loss_mask: 0.2269, loss: 0.7064 2023-11-13 19:50:43,598 - mmdet - INFO - Epoch [6][1600/7330] lr: 1.000e-04, eta: 4:15:51, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0432, loss_cls: 0.1763, acc: 93.5149, loss_bbox: 0.2235, loss_mask: 0.2238, loss: 0.6879 2023-11-13 19:50:58,948 - mmdet - INFO - Epoch [6][1650/7330] lr: 1.000e-04, eta: 4:15:35, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0394, loss_cls: 0.1782, acc: 93.3413, loss_bbox: 0.2280, loss_mask: 0.2259, loss: 0.6929 2023-11-13 19:51:14,255 - mmdet - INFO - Epoch [6][1700/7330] lr: 1.000e-04, eta: 4:15:20, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0431, loss_cls: 0.1825, acc: 93.2820, loss_bbox: 0.2338, loss_mask: 0.2326, loss: 0.7148 2023-11-13 19:51:29,996 - mmdet - INFO - Epoch [6][1750/7330] lr: 1.000e-04, eta: 4:15:05, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0400, loss_cls: 0.1750, acc: 93.5432, loss_bbox: 0.2227, loss_mask: 0.2245, loss: 0.6831 2023-11-13 19:51:45,580 - mmdet - INFO - Epoch [6][1800/7330] lr: 1.000e-04, eta: 4:14:49, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0414, loss_cls: 0.1806, acc: 93.4150, loss_bbox: 0.2237, loss_mask: 0.2331, loss: 0.6999 2023-11-13 19:52:01,216 - mmdet - INFO - Epoch [6][1850/7330] lr: 1.000e-04, eta: 4:14:34, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0421, loss_cls: 0.1817, acc: 93.3660, loss_bbox: 0.2254, loss_mask: 0.2248, loss: 0.6959 2023-11-13 19:52:16,743 - mmdet - INFO - Epoch [6][1900/7330] lr: 1.000e-04, eta: 4:14:19, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0394, loss_cls: 0.1698, acc: 93.6880, loss_bbox: 0.2182, loss_mask: 0.2241, loss: 0.6707 2023-11-13 19:52:32,564 - mmdet - INFO - Epoch [6][1950/7330] lr: 1.000e-04, eta: 4:14:04, time: 0.316, data_time: 0.031, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0447, loss_cls: 0.1817, acc: 93.2673, loss_bbox: 0.2305, loss_mask: 0.2228, loss: 0.7012 2023-11-13 19:52:48,051 - mmdet - INFO - Epoch [6][2000/7330] lr: 1.000e-04, eta: 4:13:49, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0396, loss_cls: 0.1728, acc: 93.7002, loss_bbox: 0.2197, loss_mask: 0.2211, loss: 0.6729 2023-11-13 19:53:03,621 - mmdet - INFO - Epoch [6][2050/7330] lr: 1.000e-04, eta: 4:13:33, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0418, loss_cls: 0.1860, acc: 93.2349, loss_bbox: 0.2328, loss_mask: 0.2323, loss: 0.7163 2023-11-13 19:53:19,010 - mmdet - INFO - Epoch [6][2100/7330] lr: 1.000e-04, eta: 4:13:18, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0413, loss_cls: 0.1803, acc: 93.3071, loss_bbox: 0.2294, loss_mask: 0.2334, loss: 0.7062 2023-11-13 19:53:34,790 - mmdet - INFO - Epoch [6][2150/7330] lr: 1.000e-04, eta: 4:13:03, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0435, loss_cls: 0.1880, acc: 93.0657, loss_bbox: 0.2349, loss_mask: 0.2325, loss: 0.7239 2023-11-13 19:53:50,100 - mmdet - INFO - Epoch [6][2200/7330] lr: 1.000e-04, eta: 4:12:47, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0400, loss_cls: 0.1771, acc: 93.5259, loss_bbox: 0.2224, loss_mask: 0.2312, loss: 0.6916 2023-11-13 19:54:05,559 - mmdet - INFO - Epoch [6][2250/7330] lr: 1.000e-04, eta: 4:12:32, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0408, loss_cls: 0.1771, acc: 93.4495, loss_bbox: 0.2253, loss_mask: 0.2223, loss: 0.6854 2023-11-13 19:54:21,213 - mmdet - INFO - Epoch [6][2300/7330] lr: 1.000e-04, eta: 4:12:17, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0401, loss_cls: 0.1796, acc: 93.3071, loss_bbox: 0.2283, loss_mask: 0.2262, loss: 0.6948 2023-11-13 19:54:36,586 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:54:36,586 - mmdet - INFO - Epoch [6][2350/7330] lr: 1.000e-04, eta: 4:12:01, time: 0.307, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0417, loss_cls: 0.1762, acc: 93.4663, loss_bbox: 0.2207, loss_mask: 0.2268, loss: 0.6874 2023-11-13 19:54:52,314 - mmdet - INFO - Epoch [6][2400/7330] lr: 1.000e-04, eta: 4:11:46, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0409, loss_cls: 0.1761, acc: 93.4578, loss_bbox: 0.2204, loss_mask: 0.2280, loss: 0.6873 2023-11-13 19:55:07,838 - mmdet - INFO - Epoch [6][2450/7330] lr: 1.000e-04, eta: 4:11:31, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0413, loss_cls: 0.1797, acc: 93.3853, loss_bbox: 0.2259, loss_mask: 0.2259, loss: 0.6948 2023-11-13 19:55:23,492 - mmdet - INFO - Epoch [6][2500/7330] lr: 1.000e-04, eta: 4:11:15, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0385, loss_cls: 0.1726, acc: 93.7083, loss_bbox: 0.2143, loss_mask: 0.2232, loss: 0.6707 2023-11-13 19:55:38,936 - mmdet - INFO - Epoch [6][2550/7330] lr: 1.000e-04, eta: 4:11:00, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0435, loss_cls: 0.1788, acc: 93.3904, loss_bbox: 0.2260, loss_mask: 0.2235, loss: 0.6937 2023-11-13 19:55:54,740 - mmdet - INFO - Epoch [6][2600/7330] lr: 1.000e-04, eta: 4:10:45, time: 0.316, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0428, loss_cls: 0.1865, acc: 93.1514, loss_bbox: 0.2319, loss_mask: 0.2258, loss: 0.7103 2023-11-13 19:56:09,937 - mmdet - INFO - Epoch [6][2650/7330] lr: 1.000e-04, eta: 4:10:29, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0417, loss_cls: 0.1818, acc: 93.3896, loss_bbox: 0.2237, loss_mask: 0.2242, loss: 0.6935 2023-11-13 19:56:25,476 - mmdet - INFO - Epoch [6][2700/7330] lr: 1.000e-04, eta: 4:10:14, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0427, loss_cls: 0.1839, acc: 93.2046, loss_bbox: 0.2321, loss_mask: 0.2317, loss: 0.7125 2023-11-13 19:56:40,730 - mmdet - INFO - Epoch [6][2750/7330] lr: 1.000e-04, eta: 4:09:58, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0421, loss_cls: 0.1781, acc: 93.3411, loss_bbox: 0.2267, loss_mask: 0.2306, loss: 0.6995 2023-11-13 19:56:56,471 - mmdet - INFO - Epoch [6][2800/7330] lr: 1.000e-04, eta: 4:09:43, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0424, loss_cls: 0.1799, acc: 93.4373, loss_bbox: 0.2232, loss_mask: 0.2328, loss: 0.7011 2023-11-13 19:57:11,569 - mmdet - INFO - Epoch [6][2850/7330] lr: 1.000e-04, eta: 4:09:27, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0401, loss_cls: 0.1732, acc: 93.8071, loss_bbox: 0.2093, loss_mask: 0.2207, loss: 0.6646 2023-11-13 19:57:26,936 - mmdet - INFO - Epoch [6][2900/7330] lr: 1.000e-04, eta: 4:09:12, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0413, loss_cls: 0.1790, acc: 93.4827, loss_bbox: 0.2234, loss_mask: 0.2262, loss: 0.6927 2023-11-13 19:57:42,046 - mmdet - INFO - Epoch [6][2950/7330] lr: 1.000e-04, eta: 4:08:56, time: 0.302, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0413, loss_cls: 0.1822, acc: 93.3313, loss_bbox: 0.2272, loss_mask: 0.2302, loss: 0.7023 2023-11-13 19:57:57,488 - mmdet - INFO - Epoch [6][3000/7330] lr: 1.000e-04, eta: 4:08:40, time: 0.309, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0408, loss_cls: 0.1762, acc: 93.6494, loss_bbox: 0.2184, loss_mask: 0.2218, loss: 0.6789 2023-11-13 19:58:13,322 - mmdet - INFO - Epoch [6][3050/7330] lr: 1.000e-04, eta: 4:08:26, time: 0.317, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0442, loss_cls: 0.1865, acc: 93.0649, loss_bbox: 0.2372, loss_mask: 0.2295, loss: 0.7207 2023-11-13 19:58:28,739 - mmdet - INFO - Epoch [6][3100/7330] lr: 1.000e-04, eta: 4:08:10, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0402, loss_cls: 0.1793, acc: 93.4209, loss_bbox: 0.2290, loss_mask: 0.2248, loss: 0.6949 2023-11-13 19:58:44,178 - mmdet - INFO - Epoch [6][3150/7330] lr: 1.000e-04, eta: 4:07:55, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0399, loss_cls: 0.1747, acc: 93.6030, loss_bbox: 0.2191, loss_mask: 0.2283, loss: 0.6818 2023-11-13 19:58:59,995 - mmdet - INFO - Epoch [6][3200/7330] lr: 1.000e-04, eta: 4:07:40, time: 0.316, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0420, loss_cls: 0.1867, acc: 93.1206, loss_bbox: 0.2324, loss_mask: 0.2317, loss: 0.7146 2023-11-13 19:59:15,486 - mmdet - INFO - Epoch [6][3250/7330] lr: 1.000e-04, eta: 4:07:24, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0414, loss_cls: 0.1836, acc: 93.2295, loss_bbox: 0.2308, loss_mask: 0.2223, loss: 0.7015 2023-11-13 19:59:30,712 - mmdet - INFO - Epoch [6][3300/7330] lr: 1.000e-04, eta: 4:07:09, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0414, loss_cls: 0.1759, acc: 93.5674, loss_bbox: 0.2217, loss_mask: 0.2268, loss: 0.6881 2023-11-13 19:59:46,003 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 19:59:46,003 - mmdet - INFO - Epoch [6][3350/7330] lr: 1.000e-04, eta: 4:06:53, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0419, loss_cls: 0.1779, acc: 93.4858, loss_bbox: 0.2243, loss_mask: 0.2284, loss: 0.6953 2023-11-13 20:00:01,312 - mmdet - INFO - Epoch [6][3400/7330] lr: 1.000e-04, eta: 4:06:37, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0403, loss_cls: 0.1687, acc: 93.8594, loss_bbox: 0.2113, loss_mask: 0.2236, loss: 0.6645 2023-11-13 20:00:16,780 - mmdet - INFO - Epoch [6][3450/7330] lr: 1.000e-04, eta: 4:06:22, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0410, loss_cls: 0.1774, acc: 93.4697, loss_bbox: 0.2207, loss_mask: 0.2235, loss: 0.6843 2023-11-13 20:00:32,301 - mmdet - INFO - Epoch [6][3500/7330] lr: 1.000e-04, eta: 4:06:07, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0429, loss_cls: 0.1909, acc: 93.0183, loss_bbox: 0.2364, loss_mask: 0.2289, loss: 0.7203 2023-11-13 20:00:48,035 - mmdet - INFO - Epoch [6][3550/7330] lr: 1.000e-04, eta: 4:05:51, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0405, loss_cls: 0.1777, acc: 93.4180, loss_bbox: 0.2250, loss_mask: 0.2296, loss: 0.6954 2023-11-13 20:01:03,783 - mmdet - INFO - Epoch [6][3600/7330] lr: 1.000e-04, eta: 4:05:36, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0430, loss_cls: 0.1775, acc: 93.5032, loss_bbox: 0.2222, loss_mask: 0.2270, loss: 0.6928 2023-11-13 20:01:19,190 - mmdet - INFO - Epoch [6][3650/7330] lr: 1.000e-04, eta: 4:05:21, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0407, loss_cls: 0.1802, acc: 93.4109, loss_bbox: 0.2280, loss_mask: 0.2315, loss: 0.7019 2023-11-13 20:01:34,621 - mmdet - INFO - Epoch [6][3700/7330] lr: 1.000e-04, eta: 4:05:05, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0413, loss_cls: 0.1770, acc: 93.4219, loss_bbox: 0.2260, loss_mask: 0.2280, loss: 0.6938 2023-11-13 20:01:49,861 - mmdet - INFO - Epoch [6][3750/7330] lr: 1.000e-04, eta: 4:04:50, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0416, loss_cls: 0.1754, acc: 93.6150, loss_bbox: 0.2219, loss_mask: 0.2250, loss: 0.6867 2023-11-13 20:02:05,382 - mmdet - INFO - Epoch [6][3800/7330] lr: 1.000e-04, eta: 4:04:34, time: 0.310, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0464, loss_cls: 0.1883, acc: 92.9214, loss_bbox: 0.2393, loss_mask: 0.2325, loss: 0.7299 2023-11-13 20:02:20,400 - mmdet - INFO - Epoch [6][3850/7330] lr: 1.000e-04, eta: 4:04:18, time: 0.300, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0388, loss_cls: 0.1712, acc: 93.7568, loss_bbox: 0.2128, loss_mask: 0.2293, loss: 0.6724 2023-11-13 20:02:35,942 - mmdet - INFO - Epoch [6][3900/7330] lr: 1.000e-04, eta: 4:04:03, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0393, loss_cls: 0.1741, acc: 93.6838, loss_bbox: 0.2193, loss_mask: 0.2263, loss: 0.6782 2023-11-13 20:02:51,304 - mmdet - INFO - Epoch [6][3950/7330] lr: 1.000e-04, eta: 4:03:48, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0426, loss_cls: 0.1771, acc: 93.5078, loss_bbox: 0.2203, loss_mask: 0.2237, loss: 0.6858 2023-11-13 20:03:06,860 - mmdet - INFO - Epoch [6][4000/7330] lr: 1.000e-04, eta: 4:03:32, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0430, loss_cls: 0.1787, acc: 93.3547, loss_bbox: 0.2243, loss_mask: 0.2287, loss: 0.6968 2023-11-13 20:03:22,615 - mmdet - INFO - Epoch [6][4050/7330] lr: 1.000e-04, eta: 4:03:17, time: 0.315, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0460, loss_cls: 0.1896, acc: 92.9773, loss_bbox: 0.2401, loss_mask: 0.2333, loss: 0.7331 2023-11-13 20:03:38,045 - mmdet - INFO - Epoch [6][4100/7330] lr: 1.000e-04, eta: 4:03:02, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0394, loss_cls: 0.1727, acc: 93.5764, loss_bbox: 0.2207, loss_mask: 0.2230, loss: 0.6770 2023-11-13 20:03:55,186 - mmdet - INFO - Epoch [6][4150/7330] lr: 1.000e-04, eta: 4:02:48, time: 0.343, data_time: 0.050, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0400, loss_cls: 0.1788, acc: 93.5439, loss_bbox: 0.2187, loss_mask: 0.2221, loss: 0.6809 2023-11-13 20:04:10,654 - mmdet - INFO - Epoch [6][4200/7330] lr: 1.000e-04, eta: 4:02:33, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0406, loss_cls: 0.1758, acc: 93.5430, loss_bbox: 0.2225, loss_mask: 0.2264, loss: 0.6866 2023-11-13 20:04:26,325 - mmdet - INFO - Epoch [6][4250/7330] lr: 1.000e-04, eta: 4:02:18, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0414, loss_cls: 0.1757, acc: 93.5161, loss_bbox: 0.2225, loss_mask: 0.2249, loss: 0.6867 2023-11-13 20:04:41,821 - mmdet - INFO - Epoch [6][4300/7330] lr: 1.000e-04, eta: 4:02:02, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0396, loss_cls: 0.1805, acc: 93.4004, loss_bbox: 0.2244, loss_mask: 0.2261, loss: 0.6909 2023-11-13 20:04:57,194 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 20:04:57,194 - mmdet - INFO - Epoch [6][4350/7330] lr: 1.000e-04, eta: 4:01:47, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0381, loss_cls: 0.1748, acc: 93.5706, loss_bbox: 0.2192, loss_mask: 0.2211, loss: 0.6736 2023-11-13 20:05:13,150 - mmdet - INFO - Epoch [6][4400/7330] lr: 1.000e-04, eta: 4:01:32, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0396, loss_cls: 0.1725, acc: 93.7336, loss_bbox: 0.2184, loss_mask: 0.2217, loss: 0.6744 2023-11-13 20:05:28,595 - mmdet - INFO - Epoch [6][4450/7330] lr: 1.000e-04, eta: 4:01:16, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0419, loss_cls: 0.1736, acc: 93.6787, loss_bbox: 0.2145, loss_mask: 0.2279, loss: 0.6801 2023-11-13 20:05:44,321 - mmdet - INFO - Epoch [6][4500/7330] lr: 1.000e-04, eta: 4:01:01, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0421, loss_cls: 0.1782, acc: 93.4780, loss_bbox: 0.2240, loss_mask: 0.2324, loss: 0.6969 2023-11-13 20:05:59,558 - mmdet - INFO - Epoch [6][4550/7330] lr: 1.000e-04, eta: 4:00:46, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0418, loss_cls: 0.1803, acc: 93.4319, loss_bbox: 0.2225, loss_mask: 0.2249, loss: 0.6912 2023-11-13 20:06:15,061 - mmdet - INFO - Epoch [6][4600/7330] lr: 1.000e-04, eta: 4:00:30, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0426, loss_cls: 0.1844, acc: 93.2502, loss_bbox: 0.2291, loss_mask: 0.2315, loss: 0.7096 2023-11-13 20:06:31,233 - mmdet - INFO - Epoch [6][4650/7330] lr: 1.000e-04, eta: 4:00:16, time: 0.323, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0457, loss_cls: 0.1872, acc: 93.1777, loss_bbox: 0.2320, loss_mask: 0.2343, loss: 0.7219 2023-11-13 20:06:47,252 - mmdet - INFO - Epoch [6][4700/7330] lr: 1.000e-04, eta: 4:00:01, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0407, loss_cls: 0.1833, acc: 93.2490, loss_bbox: 0.2235, loss_mask: 0.2242, loss: 0.6935 2023-11-13 20:07:02,982 - mmdet - INFO - Epoch [6][4750/7330] lr: 1.000e-04, eta: 3:59:46, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0448, loss_cls: 0.1871, acc: 93.1458, loss_bbox: 0.2287, loss_mask: 0.2266, loss: 0.7119 2023-11-13 20:07:18,591 - mmdet - INFO - Epoch [6][4800/7330] lr: 1.000e-04, eta: 3:59:30, time: 0.312, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0410, loss_cls: 0.1769, acc: 93.6250, loss_bbox: 0.2184, loss_mask: 0.2255, loss: 0.6854 2023-11-13 20:07:34,804 - mmdet - INFO - Epoch [6][4850/7330] lr: 1.000e-04, eta: 3:59:16, time: 0.324, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0417, loss_cls: 0.1819, acc: 93.3188, loss_bbox: 0.2262, loss_mask: 0.2278, loss: 0.7010 2023-11-13 20:07:50,603 - mmdet - INFO - Epoch [6][4900/7330] lr: 1.000e-04, eta: 3:59:01, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0419, loss_cls: 0.1807, acc: 93.4353, loss_bbox: 0.2242, loss_mask: 0.2277, loss: 0.6988 2023-11-13 20:08:06,542 - mmdet - INFO - Epoch [6][4950/7330] lr: 1.000e-04, eta: 3:58:46, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0431, loss_cls: 0.1818, acc: 93.3528, loss_bbox: 0.2251, loss_mask: 0.2272, loss: 0.6992 2023-11-13 20:08:22,104 - mmdet - INFO - Epoch [6][5000/7330] lr: 1.000e-04, eta: 3:58:30, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0411, loss_cls: 0.1815, acc: 93.4353, loss_bbox: 0.2240, loss_mask: 0.2263, loss: 0.6945 2023-11-13 20:08:38,168 - mmdet - INFO - Epoch [6][5050/7330] lr: 1.000e-04, eta: 3:58:16, time: 0.321, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0419, loss_cls: 0.1806, acc: 93.3801, loss_bbox: 0.2269, loss_mask: 0.2295, loss: 0.6996 2023-11-13 20:08:53,917 - mmdet - INFO - Epoch [6][5100/7330] lr: 1.000e-04, eta: 3:58:01, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0419, loss_cls: 0.1803, acc: 93.4343, loss_bbox: 0.2268, loss_mask: 0.2265, loss: 0.6971 2023-11-13 20:09:09,400 - mmdet - INFO - Epoch [6][5150/7330] lr: 1.000e-04, eta: 3:57:45, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0404, loss_cls: 0.1732, acc: 93.6687, loss_bbox: 0.2188, loss_mask: 0.2199, loss: 0.6736 2023-11-13 20:09:25,159 - mmdet - INFO - Epoch [6][5200/7330] lr: 1.000e-04, eta: 3:57:30, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0414, loss_cls: 0.1797, acc: 93.4612, loss_bbox: 0.2189, loss_mask: 0.2224, loss: 0.6837 2023-11-13 20:09:40,687 - mmdet - INFO - Epoch [6][5250/7330] lr: 1.000e-04, eta: 3:57:15, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0405, loss_cls: 0.1776, acc: 93.5764, loss_bbox: 0.2156, loss_mask: 0.2251, loss: 0.6797 2023-11-13 20:09:56,329 - mmdet - INFO - Epoch [6][5300/7330] lr: 1.000e-04, eta: 3:56:59, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0429, loss_cls: 0.1765, acc: 93.4458, loss_bbox: 0.2261, loss_mask: 0.2342, loss: 0.7017 2023-11-13 20:10:11,921 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 20:10:11,922 - mmdet - INFO - Epoch [6][5350/7330] lr: 1.000e-04, eta: 3:56:44, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0407, loss_cls: 0.1746, acc: 93.5664, loss_bbox: 0.2169, loss_mask: 0.2237, loss: 0.6774 2023-11-13 20:10:27,571 - mmdet - INFO - Epoch [6][5400/7330] lr: 1.000e-04, eta: 3:56:29, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0438, loss_cls: 0.1815, acc: 93.4082, loss_bbox: 0.2235, loss_mask: 0.2315, loss: 0.7038 2023-11-13 20:10:43,584 - mmdet - INFO - Epoch [6][5450/7330] lr: 1.000e-04, eta: 3:56:14, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0423, loss_cls: 0.1806, acc: 93.3054, loss_bbox: 0.2259, loss_mask: 0.2322, loss: 0.7022 2023-11-13 20:10:59,060 - mmdet - INFO - Epoch [6][5500/7330] lr: 1.000e-04, eta: 3:55:59, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0402, loss_cls: 0.1825, acc: 93.3831, loss_bbox: 0.2241, loss_mask: 0.2324, loss: 0.6985 2023-11-13 20:11:14,713 - mmdet - INFO - Epoch [6][5550/7330] lr: 1.000e-04, eta: 3:55:43, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0419, loss_cls: 0.1756, acc: 93.6187, loss_bbox: 0.2198, loss_mask: 0.2236, loss: 0.6831 2023-11-13 20:11:30,162 - mmdet - INFO - Epoch [6][5600/7330] lr: 1.000e-04, eta: 3:55:28, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0400, loss_cls: 0.1822, acc: 93.2673, loss_bbox: 0.2331, loss_mask: 0.2284, loss: 0.7068 2023-11-13 20:11:45,810 - mmdet - INFO - Epoch [6][5650/7330] lr: 1.000e-04, eta: 3:55:13, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0401, loss_cls: 0.1772, acc: 93.4148, loss_bbox: 0.2266, loss_mask: 0.2255, loss: 0.6900 2023-11-13 20:12:01,693 - mmdet - INFO - Epoch [6][5700/7330] lr: 1.000e-04, eta: 3:54:58, time: 0.318, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0408, loss_cls: 0.1839, acc: 93.1580, loss_bbox: 0.2289, loss_mask: 0.2286, loss: 0.7038 2023-11-13 20:12:17,000 - mmdet - INFO - Epoch [6][5750/7330] lr: 1.000e-04, eta: 3:54:42, time: 0.306, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0388, loss_cls: 0.1696, acc: 93.8459, loss_bbox: 0.2129, loss_mask: 0.2231, loss: 0.6673 2023-11-13 20:12:32,709 - mmdet - INFO - Epoch [6][5800/7330] lr: 1.000e-04, eta: 3:54:27, time: 0.314, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0428, loss_cls: 0.1848, acc: 93.1731, loss_bbox: 0.2321, loss_mask: 0.2300, loss: 0.7144 2023-11-13 20:12:48,486 - mmdet - INFO - Epoch [6][5850/7330] lr: 1.000e-04, eta: 3:54:12, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0401, loss_cls: 0.1763, acc: 93.5740, loss_bbox: 0.2234, loss_mask: 0.2296, loss: 0.6918 2023-11-13 20:13:03,759 - mmdet - INFO - Epoch [6][5900/7330] lr: 1.000e-04, eta: 3:53:56, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0392, loss_cls: 0.1763, acc: 93.4724, loss_bbox: 0.2203, loss_mask: 0.2247, loss: 0.6805 2023-11-13 20:13:19,277 - mmdet - INFO - Epoch [6][5950/7330] lr: 1.000e-04, eta: 3:53:41, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0436, loss_cls: 0.1819, acc: 93.2729, loss_bbox: 0.2254, loss_mask: 0.2271, loss: 0.6996 2023-11-13 20:13:34,996 - mmdet - INFO - Epoch [6][6000/7330] lr: 1.000e-04, eta: 3:53:26, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0399, loss_cls: 0.1776, acc: 93.4661, loss_bbox: 0.2226, loss_mask: 0.2245, loss: 0.6860 2023-11-13 20:13:50,630 - mmdet - INFO - Epoch [6][6050/7330] lr: 1.000e-04, eta: 3:53:10, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0401, loss_cls: 0.1752, acc: 93.5525, loss_bbox: 0.2188, loss_mask: 0.2244, loss: 0.6789 2023-11-13 20:14:06,292 - mmdet - INFO - Epoch [6][6100/7330] lr: 1.000e-04, eta: 3:52:55, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0395, loss_cls: 0.1718, acc: 93.6562, loss_bbox: 0.2197, loss_mask: 0.2269, loss: 0.6800 2023-11-13 20:14:22,102 - mmdet - INFO - Epoch [6][6150/7330] lr: 1.000e-04, eta: 3:52:40, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0436, loss_cls: 0.1855, acc: 93.1235, loss_bbox: 0.2328, loss_mask: 0.2317, loss: 0.7182 2023-11-13 20:14:37,717 - mmdet - INFO - Epoch [6][6200/7330] lr: 1.000e-04, eta: 3:52:25, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0397, loss_cls: 0.1754, acc: 93.5923, loss_bbox: 0.2190, loss_mask: 0.2295, loss: 0.6863 2023-11-13 20:14:53,086 - mmdet - INFO - Epoch [6][6250/7330] lr: 1.000e-04, eta: 3:52:09, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0408, loss_cls: 0.1853, acc: 93.2322, loss_bbox: 0.2262, loss_mask: 0.2309, loss: 0.7040 2023-11-13 20:15:08,759 - mmdet - INFO - Epoch [6][6300/7330] lr: 1.000e-04, eta: 3:51:54, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0393, loss_cls: 0.1774, acc: 93.5076, loss_bbox: 0.2249, loss_mask: 0.2307, loss: 0.6932 2023-11-13 20:15:24,696 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 20:15:24,696 - mmdet - INFO - Epoch [6][6350/7330] lr: 1.000e-04, eta: 3:51:39, time: 0.319, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0417, loss_cls: 0.1823, acc: 93.3311, loss_bbox: 0.2260, loss_mask: 0.2324, loss: 0.7052 2023-11-13 20:15:40,319 - mmdet - INFO - Epoch [6][6400/7330] lr: 1.000e-04, eta: 3:51:24, time: 0.312, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0386, loss_cls: 0.1748, acc: 93.5342, loss_bbox: 0.2210, loss_mask: 0.2260, loss: 0.6811 2023-11-13 20:15:56,319 - mmdet - INFO - Epoch [6][6450/7330] lr: 1.000e-04, eta: 3:51:09, time: 0.320, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0447, loss_cls: 0.1907, acc: 93.1155, loss_bbox: 0.2388, loss_mask: 0.2364, loss: 0.7357 2023-11-13 20:16:12,278 - mmdet - INFO - Epoch [6][6500/7330] lr: 1.000e-04, eta: 3:50:54, time: 0.319, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0462, loss_cls: 0.1923, acc: 93.0515, loss_bbox: 0.2381, loss_mask: 0.2316, loss: 0.7332 2023-11-13 20:16:27,836 - mmdet - INFO - Epoch [6][6550/7330] lr: 1.000e-04, eta: 3:50:38, time: 0.311, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0391, loss_cls: 0.1711, acc: 93.7375, loss_bbox: 0.2148, loss_mask: 0.2230, loss: 0.6693 2023-11-13 20:16:43,437 - mmdet - INFO - Epoch [6][6600/7330] lr: 1.000e-04, eta: 3:50:23, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0385, loss_cls: 0.1819, acc: 93.4856, loss_bbox: 0.2218, loss_mask: 0.2273, loss: 0.6896 2023-11-13 20:16:59,164 - mmdet - INFO - Epoch [6][6650/7330] lr: 1.000e-04, eta: 3:50:08, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0409, loss_cls: 0.1890, acc: 93.0532, loss_bbox: 0.2375, loss_mask: 0.2304, loss: 0.7196 2023-11-13 20:17:14,924 - mmdet - INFO - Epoch [6][6700/7330] lr: 1.000e-04, eta: 3:49:53, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0407, loss_cls: 0.1739, acc: 93.6025, loss_bbox: 0.2183, loss_mask: 0.2248, loss: 0.6796 2023-11-13 20:17:30,162 - mmdet - INFO - Epoch [6][6750/7330] lr: 1.000e-04, eta: 3:49:37, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0405, loss_cls: 0.1832, acc: 93.2683, loss_bbox: 0.2251, loss_mask: 0.2272, loss: 0.6963 2023-11-13 20:17:45,640 - mmdet - INFO - Epoch [6][6800/7330] lr: 1.000e-04, eta: 3:49:22, time: 0.310, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0405, loss_cls: 0.1764, acc: 93.5210, loss_bbox: 0.2214, loss_mask: 0.2278, loss: 0.6861 2023-11-13 20:18:01,878 - mmdet - INFO - Epoch [6][6850/7330] lr: 1.000e-04, eta: 3:49:07, time: 0.325, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0419, loss_cls: 0.1832, acc: 93.3035, loss_bbox: 0.2239, loss_mask: 0.2312, loss: 0.7027 2023-11-13 20:18:18,091 - mmdet - INFO - Epoch [6][6900/7330] lr: 1.000e-04, eta: 3:48:52, time: 0.324, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0424, loss_cls: 0.1866, acc: 93.1797, loss_bbox: 0.2307, loss_mask: 0.2283, loss: 0.7119 2023-11-13 20:18:34,321 - mmdet - INFO - Epoch [6][6950/7330] lr: 1.000e-04, eta: 3:48:38, time: 0.325, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0396, loss_cls: 0.1749, acc: 93.5754, loss_bbox: 0.2161, loss_mask: 0.2230, loss: 0.6754 2023-11-13 20:18:50,170 - mmdet - INFO - Epoch [6][7000/7330] lr: 1.000e-04, eta: 3:48:23, time: 0.317, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0390, loss_cls: 0.1721, acc: 93.6855, loss_bbox: 0.2176, loss_mask: 0.2252, loss: 0.6764 2023-11-13 20:19:06,369 - mmdet - INFO - Epoch [6][7050/7330] lr: 1.000e-04, eta: 3:48:08, time: 0.324, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0402, loss_cls: 0.1813, acc: 93.4270, loss_bbox: 0.2210, loss_mask: 0.2269, loss: 0.6912 2023-11-13 20:19:22,232 - mmdet - INFO - Epoch [6][7100/7330] lr: 1.000e-04, eta: 3:47:53, time: 0.317, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0430, loss_cls: 0.1822, acc: 93.3340, loss_bbox: 0.2240, loss_mask: 0.2276, loss: 0.7011 2023-11-13 20:19:38,019 - mmdet - INFO - Epoch [6][7150/7330] lr: 1.000e-04, eta: 3:47:38, time: 0.316, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0386, loss_cls: 0.1736, acc: 93.6125, loss_bbox: 0.2181, loss_mask: 0.2246, loss: 0.6776 2023-11-13 20:19:53,859 - mmdet - INFO - Epoch [6][7200/7330] lr: 1.000e-04, eta: 3:47:23, time: 0.317, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0422, loss_cls: 0.1804, acc: 93.3352, loss_bbox: 0.2301, loss_mask: 0.2314, loss: 0.7065 2023-11-13 20:20:09,440 - mmdet - INFO - Epoch [6][7250/7330] lr: 1.000e-04, eta: 3:47:07, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0423, loss_cls: 0.1802, acc: 93.3569, loss_bbox: 0.2250, loss_mask: 0.2291, loss: 0.6989 2023-11-13 20:20:25,128 - mmdet - INFO - Epoch [6][7300/7330] lr: 1.000e-04, eta: 3:46:52, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0412, loss_cls: 0.1817, acc: 93.3425, loss_bbox: 0.2240, loss_mask: 0.2229, loss: 0.6903 2023-11-13 20:20:35,091 - mmdet - INFO - Saving checkpoint at 6 epochs 2023-11-13 20:21:18,035 - mmdet - INFO - Evaluating bbox... 2023-11-13 20:21:50,329 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.449 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.676 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.498 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.282 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 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.396 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.728 2023-11-13 20:21:50,332 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.567 | bicycle | 0.365 | car | 0.469 | | motorcycle | 0.468 | airplane | 0.692 | bus | 0.664 | | train | 0.654 | truck | 0.419 | boat | 0.315 | | traffic light | 0.296 | fire hydrant | 0.706 | stop sign | 0.656 | | parking meter | 0.478 | bench | 0.280 | bird | 0.393 | | cat | 0.701 | dog | 0.663 | horse | 0.595 | | sheep | 0.543 | cow | 0.596 | elephant | 0.669 | | bear | 0.737 | zebra | 0.684 | giraffe | 0.664 | | backpack | 0.171 | umbrella | 0.427 | handbag | 0.193 | | tie | 0.355 | suitcase | 0.422 | frisbee | 0.678 | | skis | 0.271 | snowboard | 0.409 | sports ball | 0.441 | | kite | 0.453 | baseball bat | 0.329 | baseball glove | 0.378 | | skateboard | 0.542 | surfboard | 0.428 | tennis racket | 0.492 | | bottle | 0.424 | wine glass | 0.397 | cup | 0.474 | | fork | 0.408 | knife | 0.257 | spoon | 0.233 | | bowl | 0.455 | banana | 0.275 | apple | 0.244 | | sandwich | 0.397 | orange | 0.342 | broccoli | 0.274 | | carrot | 0.231 | hot dog | 0.397 | pizza | 0.517 | | donut | 0.506 | cake | 0.401 | chair | 0.335 | | couch | 0.470 | potted plant | 0.314 | bed | 0.449 | | dining table | 0.286 | toilet | 0.623 | tv | 0.620 | | laptop | 0.655 | mouse | 0.624 | remote | 0.365 | | keyboard | 0.531 | cell phone | 0.411 | microwave | 0.612 | | oven | 0.369 | toaster | 0.370 | sink | 0.411 | | refrigerator | 0.587 | book | 0.164 | clock | 0.514 | | vase | 0.377 | scissors | 0.359 | teddy bear | 0.497 | | hair drier | 0.219 | toothbrush | 0.297 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:21:50,332 - mmdet - INFO - Evaluating segm... 2023-11-13 20:22:24,230 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.409 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.643 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.438 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.211 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.440 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.593 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.532 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.532 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.532 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.568 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.689 2023-11-13 20:22:24,233 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.487 | bicycle | 0.217 | car | 0.433 | | motorcycle | 0.380 | airplane | 0.557 | bus | 0.663 | | train | 0.643 | truck | 0.411 | boat | 0.291 | | traffic light | 0.285 | fire hydrant | 0.676 | stop sign | 0.669 | | parking meter | 0.482 | bench | 0.213 | bird | 0.332 | | cat | 0.699 | dog | 0.620 | horse | 0.440 | | sheep | 0.498 | cow | 0.531 | elephant | 0.607 | | bear | 0.740 | zebra | 0.580 | giraffe | 0.508 | | backpack | 0.178 | umbrella | 0.494 | handbag | 0.192 | | tie | 0.322 | suitcase | 0.440 | frisbee | 0.660 | | skis | 0.045 | snowboard | 0.251 | sports ball | 0.441 | | kite | 0.319 | baseball bat | 0.270 | baseball glove | 0.425 | | skateboard | 0.353 | surfboard | 0.359 | tennis racket | 0.580 | | bottle | 0.407 | wine glass | 0.352 | cup | 0.479 | | fork | 0.217 | knife | 0.167 | spoon | 0.165 | | bowl | 0.429 | banana | 0.222 | apple | 0.245 | | sandwich | 0.431 | orange | 0.348 | broccoli | 0.256 | | carrot | 0.209 | hot dog | 0.315 | pizza | 0.503 | | donut | 0.530 | cake | 0.411 | chair | 0.242 | | couch | 0.403 | potted plant | 0.264 | bed | 0.372 | | dining table | 0.166 | toilet | 0.607 | tv | 0.639 | | laptop | 0.659 | mouse | 0.624 | remote | 0.338 | | keyboard | 0.541 | cell phone | 0.390 | microwave | 0.646 | | oven | 0.360 | toaster | 0.403 | sink | 0.398 | | refrigerator | 0.610 | book | 0.130 | clock | 0.518 | | vase | 0.375 | scissors | 0.284 | teddy bear | 0.481 | | hair drier | 0.105 | toothbrush | 0.194 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:22:24,691 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_5.pth was removed 2023-11-13 20:22:26,262 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_6.pth. 2023-11-13 20:22:26,263 - mmdet - INFO - Best bbox_mAP is 0.4495 at 6 epoch. 2023-11-13 20:22:26,263 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 20:22:26,263 - mmdet - INFO - Epoch(val) [6][625] bbox_mAP: 0.4495, bbox_mAP_50: 0.6758, bbox_mAP_75: 0.4980, bbox_mAP_s: 0.2821, bbox_mAP_m: 0.4859, bbox_mAP_l: 0.5909, bbox_mAP_copypaste: 0.4495 0.6758 0.4980 0.2821 0.4859 0.5909, segm_mAP: 0.4091, segm_mAP_50: 0.6432, segm_mAP_75: 0.4381, segm_mAP_s: 0.2114, segm_mAP_m: 0.4395, segm_mAP_l: 0.5928, segm_mAP_copypaste: 0.4091 0.6432 0.4381 0.2114 0.4395 0.5928 2023-11-13 20:22:45,161 - mmdet - INFO - Epoch [7][50/7330] lr: 1.000e-04, eta: 3:46:21, time: 0.378, data_time: 0.093, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0393, loss_cls: 0.1627, acc: 93.9890, loss_bbox: 0.2085, loss_mask: 0.2233, loss: 0.6529 2023-11-13 20:23:01,385 - mmdet - INFO - Epoch [7][100/7330] lr: 1.000e-04, eta: 3:46:07, time: 0.324, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0447, loss_cls: 0.1722, acc: 93.5110, loss_bbox: 0.2233, loss_mask: 0.2205, loss: 0.6805 2023-11-13 20:23:17,264 - mmdet - INFO - Epoch [7][150/7330] lr: 1.000e-04, eta: 3:45:52, time: 0.318, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0401, loss_cls: 0.1722, acc: 93.5737, loss_bbox: 0.2185, loss_mask: 0.2199, loss: 0.6701 2023-11-13 20:23:33,105 - mmdet - INFO - Epoch [7][200/7330] lr: 1.000e-04, eta: 3:45:37, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0403, loss_cls: 0.1721, acc: 93.6370, loss_bbox: 0.2154, loss_mask: 0.2260, loss: 0.6746 2023-11-13 20:23:49,235 - mmdet - INFO - Epoch [7][250/7330] lr: 1.000e-04, eta: 3:45:22, time: 0.323, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0403, loss_cls: 0.1763, acc: 93.3933, loss_bbox: 0.2240, loss_mask: 0.2300, loss: 0.6909 2023-11-13 20:24:05,069 - mmdet - INFO - Epoch [7][300/7330] lr: 1.000e-04, eta: 3:45:07, time: 0.317, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0398, loss_cls: 0.1727, acc: 93.5706, loss_bbox: 0.2220, loss_mask: 0.2232, loss: 0.6795 2023-11-13 20:24:20,908 - mmdet - INFO - Epoch [7][350/7330] lr: 1.000e-04, eta: 3:44:52, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0420, loss_cls: 0.1705, acc: 93.6426, loss_bbox: 0.2172, loss_mask: 0.2214, loss: 0.6719 2023-11-13 20:24:36,729 - mmdet - INFO - Epoch [7][400/7330] lr: 1.000e-04, eta: 3:44:36, time: 0.316, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0419, loss_cls: 0.1801, acc: 93.2778, loss_bbox: 0.2325, loss_mask: 0.2296, loss: 0.7070 2023-11-13 20:24:52,398 - mmdet - INFO - Epoch [7][450/7330] lr: 1.000e-04, eta: 3:44:21, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0392, loss_cls: 0.1702, acc: 93.7620, loss_bbox: 0.2153, loss_mask: 0.2190, loss: 0.6629 2023-11-13 20:25:08,080 - mmdet - INFO - Epoch [7][500/7330] lr: 1.000e-04, eta: 3:44:06, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0378, loss_cls: 0.1613, acc: 94.0720, loss_bbox: 0.2052, loss_mask: 0.2217, loss: 0.6451 2023-11-13 20:25:23,916 - mmdet - INFO - Epoch [7][550/7330] lr: 1.000e-04, eta: 3:43:51, time: 0.317, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0388, loss_cls: 0.1700, acc: 93.6868, loss_bbox: 0.2152, loss_mask: 0.2175, loss: 0.6609 2023-11-13 20:25:39,983 - mmdet - INFO - Epoch [7][600/7330] lr: 1.000e-04, eta: 3:43:36, time: 0.321, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0395, loss_cls: 0.1706, acc: 93.7051, loss_bbox: 0.2170, loss_mask: 0.2299, loss: 0.6771 2023-11-13 20:25:55,767 - mmdet - INFO - Epoch [7][650/7330] lr: 1.000e-04, eta: 3:43:21, time: 0.316, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0415, loss_cls: 0.1634, acc: 93.9966, loss_bbox: 0.2115, loss_mask: 0.2216, loss: 0.6566 2023-11-13 20:26:12,051 - mmdet - INFO - Epoch [7][700/7330] lr: 1.000e-04, eta: 3:43:06, time: 0.326, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0425, loss_cls: 0.1696, acc: 93.7180, loss_bbox: 0.2213, loss_mask: 0.2272, loss: 0.6811 2023-11-13 20:26:27,989 - mmdet - INFO - Epoch [7][750/7330] lr: 1.000e-04, eta: 3:42:51, time: 0.319, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0397, loss_cls: 0.1729, acc: 93.5850, loss_bbox: 0.2202, loss_mask: 0.2225, loss: 0.6753 2023-11-13 20:26:43,425 - mmdet - INFO - Epoch [7][800/7330] lr: 1.000e-04, eta: 3:42:36, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0399, loss_cls: 0.1643, acc: 93.9229, loss_bbox: 0.2064, loss_mask: 0.2138, loss: 0.6432 2023-11-13 20:26:59,010 - mmdet - INFO - Epoch [7][850/7330] lr: 1.000e-04, eta: 3:42:20, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0374, loss_cls: 0.1646, acc: 93.8748, loss_bbox: 0.2146, loss_mask: 0.2154, loss: 0.6519 2023-11-13 20:27:14,612 - mmdet - INFO - Epoch [7][900/7330] lr: 1.000e-04, eta: 3:42:05, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0388, loss_cls: 0.1756, acc: 93.4365, loss_bbox: 0.2204, loss_mask: 0.2190, loss: 0.6721 2023-11-13 20:27:30,626 - mmdet - INFO - Epoch [7][950/7330] lr: 1.000e-04, eta: 3:41:50, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0415, loss_cls: 0.1759, acc: 93.4312, loss_bbox: 0.2289, loss_mask: 0.2234, loss: 0.6925 2023-11-13 20:27:46,531 - mmdet - INFO - Epoch [7][1000/7330] lr: 1.000e-04, eta: 3:41:35, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0386, loss_cls: 0.1685, acc: 93.8633, loss_bbox: 0.2120, loss_mask: 0.2230, loss: 0.6615 2023-11-13 20:28:02,301 - mmdet - INFO - Epoch [7][1050/7330] lr: 1.000e-04, eta: 3:41:20, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0411, loss_cls: 0.1729, acc: 93.5754, loss_bbox: 0.2123, loss_mask: 0.2215, loss: 0.6684 2023-11-13 20:28:17,820 - mmdet - INFO - Epoch [7][1100/7330] lr: 1.000e-04, eta: 3:41:04, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0393, loss_cls: 0.1716, acc: 93.5662, loss_bbox: 0.2211, loss_mask: 0.2202, loss: 0.6719 2023-11-13 20:28:33,649 - mmdet - INFO - Epoch [7][1150/7330] lr: 1.000e-04, eta: 3:40:49, time: 0.317, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0404, loss_cls: 0.1736, acc: 93.5823, loss_bbox: 0.2241, loss_mask: 0.2274, loss: 0.6861 2023-11-13 20:28:49,389 - mmdet - INFO - Epoch [7][1200/7330] lr: 1.000e-04, eta: 3:40:34, time: 0.315, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0422, loss_cls: 0.1766, acc: 93.3657, loss_bbox: 0.2263, loss_mask: 0.2294, loss: 0.6962 2023-11-13 20:29:05,149 - mmdet - INFO - Epoch [7][1250/7330] lr: 1.000e-04, eta: 3:40:19, time: 0.315, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0429, loss_cls: 0.1817, acc: 93.1770, loss_bbox: 0.2364, loss_mask: 0.2269, loss: 0.7104 2023-11-13 20:29:21,149 - mmdet - INFO - Epoch [7][1300/7330] lr: 1.000e-04, eta: 3:40:04, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0410, loss_cls: 0.1772, acc: 93.3728, loss_bbox: 0.2263, loss_mask: 0.2206, loss: 0.6855 2023-11-13 20:29:36,755 - mmdet - INFO - Epoch [7][1350/7330] lr: 1.000e-04, eta: 3:39:49, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0407, loss_cls: 0.1654, acc: 93.8335, loss_bbox: 0.2129, loss_mask: 0.2211, loss: 0.6581 2023-11-13 20:29:52,457 - mmdet - INFO - Epoch [7][1400/7330] lr: 1.000e-04, eta: 3:39:33, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0399, loss_cls: 0.1699, acc: 93.7556, loss_bbox: 0.2188, loss_mask: 0.2224, loss: 0.6708 2023-11-13 20:30:07,895 - mmdet - INFO - Epoch [7][1450/7330] lr: 1.000e-04, eta: 3:39:18, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0390, loss_cls: 0.1672, acc: 93.7966, loss_bbox: 0.2145, loss_mask: 0.2201, loss: 0.6589 2023-11-13 20:30:23,823 - mmdet - INFO - Epoch [7][1500/7330] lr: 1.000e-04, eta: 3:39:03, time: 0.319, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0403, loss_cls: 0.1732, acc: 93.5247, loss_bbox: 0.2214, loss_mask: 0.2231, loss: 0.6780 2023-11-13 20:30:39,479 - mmdet - INFO - Epoch [7][1550/7330] lr: 1.000e-04, eta: 3:38:47, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0392, loss_cls: 0.1739, acc: 93.6384, loss_bbox: 0.2197, loss_mask: 0.2228, loss: 0.6774 2023-11-13 20:30:54,745 - mmdet - INFO - Epoch [7][1600/7330] lr: 1.000e-04, eta: 3:38:32, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0406, loss_cls: 0.1670, acc: 93.7458, loss_bbox: 0.2214, loss_mask: 0.2294, loss: 0.6790 2023-11-13 20:31:10,191 - mmdet - INFO - Epoch [7][1650/7330] lr: 1.000e-04, eta: 3:38:16, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0414, loss_cls: 0.1815, acc: 93.2642, loss_bbox: 0.2277, loss_mask: 0.2274, loss: 0.7003 2023-11-13 20:31:26,137 - mmdet - INFO - Epoch [7][1700/7330] lr: 1.000e-04, eta: 3:38:01, time: 0.319, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0408, loss_cls: 0.1729, acc: 93.6340, loss_bbox: 0.2200, loss_mask: 0.2250, loss: 0.6790 2023-11-13 20:31:41,803 - mmdet - INFO - Epoch [7][1750/7330] lr: 1.000e-04, eta: 3:37:46, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0386, loss_cls: 0.1688, acc: 93.7947, loss_bbox: 0.2152, loss_mask: 0.2240, loss: 0.6661 2023-11-13 20:31:57,444 - mmdet - INFO - Epoch [7][1800/7330] lr: 1.000e-04, eta: 3:37:31, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0406, loss_cls: 0.1759, acc: 93.5310, loss_bbox: 0.2210, loss_mask: 0.2219, loss: 0.6803 2023-11-13 20:32:13,139 - mmdet - INFO - Epoch [7][1850/7330] lr: 1.000e-04, eta: 3:37:15, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0431, loss_cls: 0.1752, acc: 93.5022, loss_bbox: 0.2191, loss_mask: 0.2210, loss: 0.6806 2023-11-13 20:32:28,840 - mmdet - INFO - Epoch [7][1900/7330] lr: 1.000e-04, eta: 3:37:00, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0414, loss_cls: 0.1646, acc: 93.9080, loss_bbox: 0.2135, loss_mask: 0.2221, loss: 0.6637 2023-11-13 20:32:44,630 - mmdet - INFO - Epoch [7][1950/7330] lr: 1.000e-04, eta: 3:36:45, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0390, loss_cls: 0.1740, acc: 93.5449, loss_bbox: 0.2250, loss_mask: 0.2212, loss: 0.6805 2023-11-13 20:33:00,056 - mmdet - INFO - Epoch [7][2000/7330] lr: 1.000e-04, eta: 3:36:29, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0385, loss_cls: 0.1760, acc: 93.4539, loss_bbox: 0.2192, loss_mask: 0.2206, loss: 0.6733 2023-11-13 20:33:15,730 - mmdet - INFO - Epoch [7][2050/7330] lr: 1.000e-04, eta: 3:36:14, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0413, loss_cls: 0.1767, acc: 93.5479, loss_bbox: 0.2175, loss_mask: 0.2207, loss: 0.6777 2023-11-13 20:33:31,296 - mmdet - INFO - Epoch [7][2100/7330] lr: 1.000e-04, eta: 3:35:59, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0409, loss_cls: 0.1706, acc: 93.6514, loss_bbox: 0.2199, loss_mask: 0.2211, loss: 0.6738 2023-11-13 20:33:46,963 - mmdet - INFO - Epoch [7][2150/7330] lr: 1.000e-04, eta: 3:35:43, time: 0.313, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0418, loss_cls: 0.1746, acc: 93.5037, loss_bbox: 0.2267, loss_mask: 0.2239, loss: 0.6878 2023-11-13 20:34:02,399 - mmdet - INFO - Epoch [7][2200/7330] lr: 1.000e-04, eta: 3:35:28, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0409, loss_cls: 0.1712, acc: 93.5752, loss_bbox: 0.2178, loss_mask: 0.2213, loss: 0.6723 2023-11-13 20:34:17,809 - mmdet - INFO - Epoch [7][2250/7330] lr: 1.000e-04, eta: 3:35:12, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0442, loss_cls: 0.1767, acc: 93.4041, loss_bbox: 0.2251, loss_mask: 0.2231, loss: 0.6898 2023-11-13 20:34:33,224 - mmdet - INFO - Epoch [7][2300/7330] lr: 1.000e-04, eta: 3:34:57, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0384, loss_cls: 0.1763, acc: 93.4036, loss_bbox: 0.2220, loss_mask: 0.2212, loss: 0.6770 2023-11-13 20:34:48,657 - mmdet - INFO - Epoch [7][2350/7330] lr: 1.000e-04, eta: 3:34:41, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0389, loss_cls: 0.1721, acc: 93.6052, loss_bbox: 0.2186, loss_mask: 0.2215, loss: 0.6722 2023-11-13 20:35:04,095 - mmdet - INFO - Epoch [7][2400/7330] lr: 1.000e-04, eta: 3:34:26, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0408, loss_cls: 0.1792, acc: 93.4224, loss_bbox: 0.2252, loss_mask: 0.2233, loss: 0.6878 2023-11-13 20:35:19,789 - mmdet - INFO - Epoch [7][2450/7330] lr: 1.000e-04, eta: 3:34:11, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0406, loss_cls: 0.1770, acc: 93.4243, loss_bbox: 0.2271, loss_mask: 0.2247, loss: 0.6888 2023-11-13 20:35:34,679 - mmdet - INFO - Epoch [7][2500/7330] lr: 1.000e-04, eta: 3:33:55, time: 0.298, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0397, loss_cls: 0.1735, acc: 93.5808, loss_bbox: 0.2179, loss_mask: 0.2277, loss: 0.6786 2023-11-13 20:35:50,093 - mmdet - INFO - Epoch [7][2550/7330] lr: 1.000e-04, eta: 3:33:39, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0385, loss_cls: 0.1724, acc: 93.6843, loss_bbox: 0.2160, loss_mask: 0.2210, loss: 0.6671 2023-11-13 20:36:05,316 - mmdet - INFO - Epoch [7][2600/7330] lr: 1.000e-04, eta: 3:33:23, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0389, loss_cls: 0.1705, acc: 93.6995, loss_bbox: 0.2205, loss_mask: 0.2203, loss: 0.6691 2023-11-13 20:36:20,529 - mmdet - INFO - Epoch [7][2650/7330] lr: 1.000e-04, eta: 3:33:08, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0394, loss_cls: 0.1755, acc: 93.5693, loss_bbox: 0.2168, loss_mask: 0.2220, loss: 0.6724 2023-11-13 20:36:36,280 - mmdet - INFO - Epoch [7][2700/7330] lr: 1.000e-04, eta: 3:32:52, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0463, loss_cls: 0.1794, acc: 93.2878, loss_bbox: 0.2322, loss_mask: 0.2303, loss: 0.7106 2023-11-13 20:36:51,581 - mmdet - INFO - Epoch [7][2750/7330] lr: 1.000e-04, eta: 3:32:37, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0402, loss_cls: 0.1731, acc: 93.5654, loss_bbox: 0.2181, loss_mask: 0.2208, loss: 0.6729 2023-11-13 20:37:06,723 - mmdet - INFO - Epoch [7][2800/7330] lr: 1.000e-04, eta: 3:32:21, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0384, loss_cls: 0.1673, acc: 93.7874, loss_bbox: 0.2147, loss_mask: 0.2242, loss: 0.6648 2023-11-13 20:37:21,956 - mmdet - INFO - Epoch [7][2850/7330] lr: 1.000e-04, eta: 3:32:05, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0381, loss_cls: 0.1683, acc: 93.8213, loss_bbox: 0.2169, loss_mask: 0.2201, loss: 0.6636 2023-11-13 20:37:37,494 - mmdet - INFO - Epoch [7][2900/7330] lr: 1.000e-04, eta: 3:31:50, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0409, loss_cls: 0.1744, acc: 93.5715, loss_bbox: 0.2184, loss_mask: 0.2182, loss: 0.6745 2023-11-13 20:37:53,124 - mmdet - INFO - Epoch [7][2950/7330] lr: 1.000e-04, eta: 3:31:35, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0378, loss_cls: 0.1718, acc: 93.6462, loss_bbox: 0.2094, loss_mask: 0.2210, loss: 0.6599 2023-11-13 20:38:08,569 - mmdet - INFO - Epoch [7][3000/7330] lr: 1.000e-04, eta: 3:31:19, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0394, loss_cls: 0.1660, acc: 93.8347, loss_bbox: 0.2092, loss_mask: 0.2162, loss: 0.6511 2023-11-13 20:38:23,577 - mmdet - INFO - Epoch [7][3050/7330] lr: 1.000e-04, eta: 3:31:03, time: 0.300, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0370, loss_cls: 0.1647, acc: 93.8479, loss_bbox: 0.2104, loss_mask: 0.2205, loss: 0.6501 2023-11-13 20:38:38,790 - mmdet - INFO - Epoch [7][3100/7330] lr: 1.000e-04, eta: 3:30:48, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0399, loss_cls: 0.1743, acc: 93.6052, loss_bbox: 0.2204, loss_mask: 0.2260, loss: 0.6816 2023-11-13 20:38:53,870 - mmdet - INFO - Epoch [7][3150/7330] lr: 1.000e-04, eta: 3:30:32, time: 0.302, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0380, loss_cls: 0.1708, acc: 93.6809, loss_bbox: 0.2184, loss_mask: 0.2189, loss: 0.6643 2023-11-13 20:39:09,072 - mmdet - INFO - Epoch [7][3200/7330] lr: 1.000e-04, eta: 3:30:16, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0408, loss_cls: 0.1718, acc: 93.6338, loss_bbox: 0.2165, loss_mask: 0.2241, loss: 0.6751 2023-11-13 20:39:24,796 - mmdet - INFO - Epoch [7][3250/7330] lr: 1.000e-04, eta: 3:30:01, time: 0.314, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0394, loss_cls: 0.1746, acc: 93.5732, loss_bbox: 0.2212, loss_mask: 0.2191, loss: 0.6744 2023-11-13 20:39:40,358 - mmdet - INFO - Epoch [7][3300/7330] lr: 1.000e-04, eta: 3:29:45, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0374, loss_cls: 0.1672, acc: 93.8281, loss_bbox: 0.2113, loss_mask: 0.2185, loss: 0.6524 2023-11-13 20:39:55,762 - mmdet - INFO - Epoch [7][3350/7330] lr: 1.000e-04, eta: 3:29:30, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0411, loss_cls: 0.1686, acc: 93.7756, loss_bbox: 0.2132, loss_mask: 0.2217, loss: 0.6652 2023-11-13 20:40:10,835 - mmdet - INFO - Epoch [7][3400/7330] lr: 1.000e-04, eta: 3:29:14, time: 0.301, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0392, loss_cls: 0.1680, acc: 93.7502, loss_bbox: 0.2126, loss_mask: 0.2191, loss: 0.6585 2023-11-13 20:40:26,186 - mmdet - INFO - Epoch [7][3450/7330] lr: 1.000e-04, eta: 3:28:59, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0399, loss_cls: 0.1711, acc: 93.7051, loss_bbox: 0.2172, loss_mask: 0.2198, loss: 0.6689 2023-11-13 20:40:41,410 - mmdet - INFO - Epoch [7][3500/7330] lr: 1.000e-04, eta: 3:28:43, time: 0.304, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0433, loss_cls: 0.1735, acc: 93.6206, loss_bbox: 0.2235, loss_mask: 0.2334, loss: 0.6968 2023-11-13 20:40:57,055 - mmdet - INFO - Epoch [7][3550/7330] lr: 1.000e-04, eta: 3:28:28, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0404, loss_cls: 0.1699, acc: 93.6245, loss_bbox: 0.2222, loss_mask: 0.2228, loss: 0.6752 2023-11-13 20:41:12,305 - mmdet - INFO - Epoch [7][3600/7330] lr: 1.000e-04, eta: 3:28:12, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0391, loss_cls: 0.1701, acc: 93.5955, loss_bbox: 0.2186, loss_mask: 0.2258, loss: 0.6735 2023-11-13 20:41:27,360 - mmdet - INFO - Epoch [7][3650/7330] lr: 1.000e-04, eta: 3:27:56, time: 0.301, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0388, loss_cls: 0.1714, acc: 93.8357, loss_bbox: 0.2120, loss_mask: 0.2211, loss: 0.6631 2023-11-13 20:41:43,085 - mmdet - INFO - Epoch [7][3700/7330] lr: 1.000e-04, eta: 3:27:41, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0406, loss_cls: 0.1727, acc: 93.6362, loss_bbox: 0.2167, loss_mask: 0.2248, loss: 0.6763 2023-11-13 20:41:58,477 - mmdet - INFO - Epoch [7][3750/7330] lr: 1.000e-04, eta: 3:27:25, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0399, loss_cls: 0.1712, acc: 93.6929, loss_bbox: 0.2192, loss_mask: 0.2230, loss: 0.6744 2023-11-13 20:42:13,937 - mmdet - INFO - Epoch [7][3800/7330] lr: 1.000e-04, eta: 3:27:10, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0399, loss_cls: 0.1783, acc: 93.4568, loss_bbox: 0.2270, loss_mask: 0.2314, loss: 0.6976 2023-11-13 20:42:29,234 - mmdet - INFO - Epoch [7][3850/7330] lr: 1.000e-04, eta: 3:26:54, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0422, loss_cls: 0.1756, acc: 93.4854, loss_bbox: 0.2204, loss_mask: 0.2287, loss: 0.6891 2023-11-13 20:42:44,457 - mmdet - INFO - Epoch [7][3900/7330] lr: 1.000e-04, eta: 3:26:39, time: 0.304, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0401, loss_cls: 0.1802, acc: 93.4360, loss_bbox: 0.2267, loss_mask: 0.2290, loss: 0.6964 2023-11-13 20:42:59,838 - mmdet - INFO - Epoch [7][3950/7330] lr: 1.000e-04, eta: 3:26:23, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0413, loss_cls: 0.1707, acc: 93.7629, loss_bbox: 0.2137, loss_mask: 0.2218, loss: 0.6694 2023-11-13 20:43:14,941 - mmdet - INFO - Epoch [7][4000/7330] lr: 1.000e-04, eta: 3:26:07, time: 0.302, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0407, loss_cls: 0.1670, acc: 93.8223, loss_bbox: 0.2140, loss_mask: 0.2202, loss: 0.6637 2023-11-13 20:43:30,003 - mmdet - INFO - Epoch [7][4050/7330] lr: 1.000e-04, eta: 3:25:51, time: 0.301, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0399, loss_cls: 0.1673, acc: 93.8203, loss_bbox: 0.2174, loss_mask: 0.2311, loss: 0.6747 2023-11-13 20:43:45,641 - mmdet - INFO - Epoch [7][4100/7330] lr: 1.000e-04, eta: 3:25:36, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0402, loss_cls: 0.1767, acc: 93.5569, loss_bbox: 0.2206, loss_mask: 0.2216, loss: 0.6792 2023-11-13 20:44:01,191 - mmdet - INFO - Epoch [7][4150/7330] lr: 1.000e-04, eta: 3:25:21, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0396, loss_cls: 0.1657, acc: 93.8608, loss_bbox: 0.2080, loss_mask: 0.2257, loss: 0.6603 2023-11-13 20:44:16,874 - mmdet - INFO - Epoch [7][4200/7330] lr: 1.000e-04, eta: 3:25:05, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0378, loss_cls: 0.1693, acc: 93.7473, loss_bbox: 0.2133, loss_mask: 0.2211, loss: 0.6611 2023-11-13 20:44:32,330 - mmdet - INFO - Epoch [7][4250/7330] lr: 1.000e-04, eta: 3:24:50, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0405, loss_cls: 0.1700, acc: 93.7329, loss_bbox: 0.2171, loss_mask: 0.2181, loss: 0.6661 2023-11-13 20:44:48,032 - mmdet - INFO - Epoch [7][4300/7330] lr: 1.000e-04, eta: 3:24:35, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0410, loss_cls: 0.1766, acc: 93.3997, loss_bbox: 0.2223, loss_mask: 0.2287, loss: 0.6910 2023-11-13 20:45:03,953 - mmdet - INFO - Epoch [7][4350/7330] lr: 1.000e-04, eta: 3:24:20, time: 0.318, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0422, loss_cls: 0.1846, acc: 93.1750, loss_bbox: 0.2302, loss_mask: 0.2304, loss: 0.7107 2023-11-13 20:45:19,142 - mmdet - INFO - Epoch [7][4400/7330] lr: 1.000e-04, eta: 3:24:04, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0389, loss_cls: 0.1767, acc: 93.4392, loss_bbox: 0.2244, loss_mask: 0.2255, loss: 0.6856 2023-11-13 20:45:34,219 - mmdet - INFO - Epoch [7][4450/7330] lr: 1.000e-04, eta: 3:23:48, time: 0.302, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0380, loss_cls: 0.1658, acc: 93.8040, loss_bbox: 0.2143, loss_mask: 0.2204, loss: 0.6562 2023-11-13 20:45:49,306 - mmdet - INFO - Epoch [7][4500/7330] lr: 1.000e-04, eta: 3:23:32, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0413, loss_cls: 0.1795, acc: 93.3599, loss_bbox: 0.2224, loss_mask: 0.2295, loss: 0.6934 2023-11-13 20:46:04,569 - mmdet - INFO - Epoch [7][4550/7330] lr: 1.000e-04, eta: 3:23:17, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0422, loss_cls: 0.1798, acc: 93.3469, loss_bbox: 0.2270, loss_mask: 0.2266, loss: 0.6973 2023-11-13 20:46:19,865 - mmdet - INFO - Epoch [7][4600/7330] lr: 1.000e-04, eta: 3:23:01, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0408, loss_cls: 0.1758, acc: 93.4417, loss_bbox: 0.2219, loss_mask: 0.2249, loss: 0.6835 2023-11-13 20:46:35,253 - mmdet - INFO - Epoch [7][4650/7330] lr: 1.000e-04, eta: 3:22:46, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0430, loss_cls: 0.1822, acc: 93.2200, loss_bbox: 0.2276, loss_mask: 0.2273, loss: 0.7021 2023-11-13 20:46:50,593 - mmdet - INFO - Epoch [7][4700/7330] lr: 1.000e-04, eta: 3:22:30, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0385, loss_cls: 0.1717, acc: 93.6594, loss_bbox: 0.2167, loss_mask: 0.2215, loss: 0.6679 2023-11-13 20:47:06,126 - mmdet - INFO - Epoch [7][4750/7330] lr: 1.000e-04, eta: 3:22:15, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0409, loss_cls: 0.1819, acc: 93.2688, loss_bbox: 0.2262, loss_mask: 0.2240, loss: 0.6934 2023-11-13 20:47:21,411 - mmdet - INFO - Epoch [7][4800/7330] lr: 1.000e-04, eta: 3:21:59, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0394, loss_cls: 0.1735, acc: 93.5842, loss_bbox: 0.2193, loss_mask: 0.2239, loss: 0.6769 2023-11-13 20:47:36,953 - mmdet - INFO - Epoch [7][4850/7330] lr: 1.000e-04, eta: 3:21:44, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0433, loss_cls: 0.1781, acc: 93.4448, loss_bbox: 0.2204, loss_mask: 0.2229, loss: 0.6853 2023-11-13 20:47:52,377 - mmdet - INFO - Epoch [7][4900/7330] lr: 1.000e-04, eta: 3:21:28, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0417, loss_cls: 0.1800, acc: 93.2700, loss_bbox: 0.2251, loss_mask: 0.2227, loss: 0.6906 2023-11-13 20:48:07,773 - mmdet - INFO - Epoch [7][4950/7330] lr: 1.000e-04, eta: 3:21:12, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0401, loss_cls: 0.1742, acc: 93.5713, loss_bbox: 0.2192, loss_mask: 0.2284, loss: 0.6826 2023-11-13 20:48:22,866 - mmdet - INFO - Epoch [7][5000/7330] lr: 1.000e-04, eta: 3:20:57, time: 0.302, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0388, loss_cls: 0.1779, acc: 93.3958, loss_bbox: 0.2268, loss_mask: 0.2248, loss: 0.6896 2023-11-13 20:48:38,105 - mmdet - INFO - Epoch [7][5050/7330] lr: 1.000e-04, eta: 3:20:41, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0408, loss_cls: 0.1708, acc: 93.6938, loss_bbox: 0.2174, loss_mask: 0.2282, loss: 0.6781 2023-11-13 20:48:53,666 - mmdet - INFO - Epoch [7][5100/7330] lr: 1.000e-04, eta: 3:20:26, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0394, loss_cls: 0.1751, acc: 93.5093, loss_bbox: 0.2177, loss_mask: 0.2233, loss: 0.6753 2023-11-13 20:49:09,060 - mmdet - INFO - Epoch [7][5150/7330] lr: 1.000e-04, eta: 3:20:10, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0389, loss_cls: 0.1754, acc: 93.5132, loss_bbox: 0.2233, loss_mask: 0.2296, loss: 0.6886 2023-11-13 20:49:24,428 - mmdet - INFO - Epoch [7][5200/7330] lr: 1.000e-04, eta: 3:19:55, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0433, loss_cls: 0.1771, acc: 93.4456, loss_bbox: 0.2226, loss_mask: 0.2259, loss: 0.6919 2023-11-13 20:49:39,867 - mmdet - INFO - Epoch [7][5250/7330] lr: 1.000e-04, eta: 3:19:39, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0436, loss_cls: 0.1832, acc: 93.3140, loss_bbox: 0.2280, loss_mask: 0.2308, loss: 0.7076 2023-11-13 20:49:55,158 - mmdet - INFO - Epoch [7][5300/7330] lr: 1.000e-04, eta: 3:19:24, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0386, loss_cls: 0.1705, acc: 93.6611, loss_bbox: 0.2140, loss_mask: 0.2240, loss: 0.6672 2023-11-13 20:50:10,825 - mmdet - INFO - Epoch [7][5350/7330] lr: 1.000e-04, eta: 3:19:08, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0409, loss_cls: 0.1734, acc: 93.6042, loss_bbox: 0.2190, loss_mask: 0.2268, loss: 0.6818 2023-11-13 20:50:26,203 - mmdet - INFO - Epoch [7][5400/7330] lr: 1.000e-04, eta: 3:18:53, time: 0.308, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0415, loss_cls: 0.1727, acc: 93.6052, loss_bbox: 0.2182, loss_mask: 0.2248, loss: 0.6772 2023-11-13 20:50:41,292 - mmdet - INFO - Epoch [7][5450/7330] lr: 1.000e-04, eta: 3:18:37, time: 0.302, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0401, loss_cls: 0.1769, acc: 93.5481, loss_bbox: 0.2201, loss_mask: 0.2207, loss: 0.6780 2023-11-13 20:50:56,742 - mmdet - INFO - Epoch [7][5500/7330] lr: 1.000e-04, eta: 3:18:21, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0387, loss_cls: 0.1762, acc: 93.4885, loss_bbox: 0.2221, loss_mask: 0.2230, loss: 0.6797 2023-11-13 20:51:12,552 - mmdet - INFO - Epoch [7][5550/7330] lr: 1.000e-04, eta: 3:18:06, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0413, loss_cls: 0.1801, acc: 93.2834, loss_bbox: 0.2228, loss_mask: 0.2265, loss: 0.6912 2023-11-13 20:51:28,056 - mmdet - INFO - Epoch [7][5600/7330] lr: 1.000e-04, eta: 3:17:51, time: 0.310, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0403, loss_cls: 0.1745, acc: 93.5916, loss_bbox: 0.2248, loss_mask: 0.2224, loss: 0.6821 2023-11-13 20:51:43,385 - mmdet - INFO - Epoch [7][5650/7330] lr: 1.000e-04, eta: 3:17:35, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0407, loss_cls: 0.1696, acc: 93.8030, loss_bbox: 0.2085, loss_mask: 0.2198, loss: 0.6593 2023-11-13 20:51:58,713 - mmdet - INFO - Epoch [7][5700/7330] lr: 1.000e-04, eta: 3:17:20, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0408, loss_cls: 0.1724, acc: 93.6189, loss_bbox: 0.2248, loss_mask: 0.2295, loss: 0.6867 2023-11-13 20:52:14,066 - mmdet - INFO - Epoch [7][5750/7330] lr: 1.000e-04, eta: 3:17:04, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0408, loss_cls: 0.1781, acc: 93.4021, loss_bbox: 0.2226, loss_mask: 0.2273, loss: 0.6903 2023-11-13 20:52:29,071 - mmdet - INFO - Epoch [7][5800/7330] lr: 1.000e-04, eta: 3:16:48, time: 0.300, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0374, loss_cls: 0.1678, acc: 93.8689, loss_bbox: 0.2150, loss_mask: 0.2180, loss: 0.6570 2023-11-13 20:52:44,492 - mmdet - INFO - Epoch [7][5850/7330] lr: 1.000e-04, eta: 3:16:33, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0366, loss_cls: 0.1714, acc: 93.7676, loss_bbox: 0.2100, loss_mask: 0.2212, loss: 0.6628 2023-11-13 20:52:59,970 - mmdet - INFO - Epoch [7][5900/7330] lr: 1.000e-04, eta: 3:16:17, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0379, loss_cls: 0.1628, acc: 93.9883, loss_bbox: 0.2060, loss_mask: 0.2177, loss: 0.6446 2023-11-13 20:53:15,332 - mmdet - INFO - Epoch [7][5950/7330] lr: 1.000e-04, eta: 3:16:02, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0401, loss_cls: 0.1750, acc: 93.6187, loss_bbox: 0.2147, loss_mask: 0.2250, loss: 0.6756 2023-11-13 20:53:30,532 - mmdet - INFO - Epoch [7][6000/7330] lr: 1.000e-04, eta: 3:15:46, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0378, loss_cls: 0.1709, acc: 93.7844, loss_bbox: 0.2115, loss_mask: 0.2182, loss: 0.6579 2023-11-13 20:53:45,960 - mmdet - INFO - Epoch [7][6050/7330] lr: 1.000e-04, eta: 3:15:31, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0408, loss_cls: 0.1829, acc: 93.2805, loss_bbox: 0.2231, loss_mask: 0.2245, loss: 0.6919 2023-11-13 20:54:01,404 - mmdet - INFO - Epoch [7][6100/7330] lr: 1.000e-04, eta: 3:15:15, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0420, loss_cls: 0.1779, acc: 93.4785, loss_bbox: 0.2217, loss_mask: 0.2242, loss: 0.6870 2023-11-13 20:54:20,564 - mmdet - INFO - Epoch [7][6150/7330] lr: 1.000e-04, eta: 3:15:03, time: 0.383, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0428, loss_cls: 0.1760, acc: 93.5205, loss_bbox: 0.2200, loss_mask: 0.2229, loss: 0.6836 2023-11-13 20:54:36,108 - mmdet - INFO - Epoch [7][6200/7330] lr: 1.000e-04, eta: 3:14:47, time: 0.311, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0426, loss_cls: 0.1831, acc: 93.2339, loss_bbox: 0.2254, loss_mask: 0.2236, loss: 0.6977 2023-11-13 20:54:51,606 - mmdet - INFO - Epoch [7][6250/7330] lr: 1.000e-04, eta: 3:14:32, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0434, loss_cls: 0.1836, acc: 93.2483, loss_bbox: 0.2284, loss_mask: 0.2298, loss: 0.7072 2023-11-13 20:55:07,070 - mmdet - INFO - Epoch [7][6300/7330] lr: 1.000e-04, eta: 3:14:16, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0382, loss_cls: 0.1705, acc: 93.7261, loss_bbox: 0.2158, loss_mask: 0.2171, loss: 0.6622 2023-11-13 20:55:22,887 - mmdet - INFO - Epoch [7][6350/7330] lr: 1.000e-04, eta: 3:14:01, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0443, loss_cls: 0.1827, acc: 93.2412, loss_bbox: 0.2295, loss_mask: 0.2269, loss: 0.7056 2023-11-13 20:55:38,043 - mmdet - INFO - Epoch [7][6400/7330] lr: 1.000e-04, eta: 3:13:45, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0384, loss_cls: 0.1680, acc: 93.8523, loss_bbox: 0.2114, loss_mask: 0.2185, loss: 0.6552 2023-11-13 20:55:53,506 - mmdet - INFO - Epoch [7][6450/7330] lr: 1.000e-04, eta: 3:13:30, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0409, loss_cls: 0.1796, acc: 93.3401, loss_bbox: 0.2247, loss_mask: 0.2230, loss: 0.6885 2023-11-13 20:56:08,859 - mmdet - INFO - Epoch [7][6500/7330] lr: 1.000e-04, eta: 3:13:14, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0403, loss_cls: 0.1703, acc: 93.7344, loss_bbox: 0.2151, loss_mask: 0.2237, loss: 0.6699 2023-11-13 20:56:24,234 - mmdet - INFO - Epoch [7][6550/7330] lr: 1.000e-04, eta: 3:12:59, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0385, loss_cls: 0.1692, acc: 93.7847, loss_bbox: 0.2119, loss_mask: 0.2208, loss: 0.6592 2023-11-13 20:56:40,012 - mmdet - INFO - Epoch [7][6600/7330] lr: 1.000e-04, eta: 3:12:43, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0408, loss_cls: 0.1767, acc: 93.5376, loss_bbox: 0.2228, loss_mask: 0.2179, loss: 0.6796 2023-11-13 20:56:55,740 - mmdet - INFO - Epoch [7][6650/7330] lr: 1.000e-04, eta: 3:12:28, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0407, loss_cls: 0.1712, acc: 93.6418, loss_bbox: 0.2203, loss_mask: 0.2263, loss: 0.6793 2023-11-13 20:57:11,204 - mmdet - INFO - Epoch [7][6700/7330] lr: 1.000e-04, eta: 3:12:13, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0389, loss_cls: 0.1732, acc: 93.5210, loss_bbox: 0.2175, loss_mask: 0.2214, loss: 0.6711 2023-11-13 20:57:27,214 - mmdet - INFO - Epoch [7][6750/7330] lr: 1.000e-04, eta: 3:11:58, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0403, loss_cls: 0.1779, acc: 93.4429, loss_bbox: 0.2213, loss_mask: 0.2223, loss: 0.6823 2023-11-13 20:57:42,645 - mmdet - INFO - Epoch [7][6800/7330] lr: 1.000e-04, eta: 3:11:42, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0392, loss_cls: 0.1755, acc: 93.4128, loss_bbox: 0.2210, loss_mask: 0.2259, loss: 0.6819 2023-11-13 20:57:58,063 - mmdet - INFO - Epoch [7][6850/7330] lr: 1.000e-04, eta: 3:11:27, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0398, loss_cls: 0.1744, acc: 93.5483, loss_bbox: 0.2229, loss_mask: 0.2239, loss: 0.6811 2023-11-13 20:58:14,055 - mmdet - INFO - Epoch [7][6900/7330] lr: 1.000e-04, eta: 3:11:12, time: 0.320, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0428, loss_cls: 0.1791, acc: 93.4189, loss_bbox: 0.2239, loss_mask: 0.2274, loss: 0.6965 2023-11-13 20:58:29,358 - mmdet - INFO - Epoch [7][6950/7330] lr: 1.000e-04, eta: 3:10:56, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0403, loss_cls: 0.1747, acc: 93.5784, loss_bbox: 0.2213, loss_mask: 0.2201, loss: 0.6763 2023-11-13 20:58:44,839 - mmdet - INFO - Epoch [7][7000/7330] lr: 1.000e-04, eta: 3:10:41, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0384, loss_cls: 0.1693, acc: 93.7419, loss_bbox: 0.2110, loss_mask: 0.2167, loss: 0.6551 2023-11-13 20:59:00,202 - mmdet - INFO - Epoch [7][7050/7330] lr: 1.000e-04, eta: 3:10:25, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0410, loss_cls: 0.1779, acc: 93.3320, loss_bbox: 0.2229, loss_mask: 0.2289, loss: 0.6910 2023-11-13 20:59:15,485 - mmdet - INFO - Epoch [7][7100/7330] lr: 1.000e-04, eta: 3:10:09, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0386, loss_cls: 0.1709, acc: 93.6184, loss_bbox: 0.2152, loss_mask: 0.2227, loss: 0.6674 2023-11-13 20:59:30,699 - mmdet - INFO - Epoch [7][7150/7330] lr: 1.000e-04, eta: 3:09:54, time: 0.304, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0400, loss_cls: 0.1763, acc: 93.4526, loss_bbox: 0.2205, loss_mask: 0.2261, loss: 0.6825 2023-11-13 20:59:46,045 - mmdet - INFO - Epoch [7][7200/7330] lr: 1.000e-04, eta: 3:09:38, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0381, loss_cls: 0.1707, acc: 93.7021, loss_bbox: 0.2131, loss_mask: 0.2227, loss: 0.6645 2023-11-13 21:00:01,427 - mmdet - INFO - Epoch [7][7250/7330] lr: 1.000e-04, eta: 3:09:23, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0414, loss_cls: 0.1737, acc: 93.5745, loss_bbox: 0.2178, loss_mask: 0.2272, loss: 0.6800 2023-11-13 21:00:17,381 - mmdet - INFO - Epoch [7][7300/7330] lr: 1.000e-04, eta: 3:09:07, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0423, loss_cls: 0.1855, acc: 93.0999, loss_bbox: 0.2310, loss_mask: 0.2279, loss: 0.7085 2023-11-13 21:00:27,359 - mmdet - INFO - Saving checkpoint at 7 epochs 2023-11-13 21:01:15,398 - mmdet - INFO - Evaluating bbox... 2023-11-13 21:01:46,838 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.452 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.675 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.500 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 ] = 0.492 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 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.398 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 ] = 0.728 2023-11-13 21:01:46,841 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.566 | bicycle | 0.348 | car | 0.476 | | motorcycle | 0.460 | airplane | 0.692 | bus | 0.671 | | train | 0.640 | truck | 0.381 | boat | 0.314 | | traffic light | 0.291 | fire hydrant | 0.712 | stop sign | 0.689 | | parking meter | 0.480 | bench | 0.277 | bird | 0.390 | | cat | 0.719 | dog | 0.654 | horse | 0.602 | | sheep | 0.558 | cow | 0.613 | elephant | 0.672 | | bear | 0.731 | zebra | 0.678 | giraffe | 0.670 | | backpack | 0.190 | umbrella | 0.430 | handbag | 0.194 | | tie | 0.361 | suitcase | 0.441 | frisbee | 0.703 | | skis | 0.268 | snowboard | 0.445 | sports ball | 0.454 | | kite | 0.446 | baseball bat | 0.351 | baseball glove | 0.403 | | skateboard | 0.556 | surfboard | 0.440 | tennis racket | 0.525 | | bottle | 0.438 | wine glass | 0.390 | cup | 0.482 | | fork | 0.411 | knife | 0.259 | spoon | 0.216 | | bowl | 0.448 | banana | 0.282 | apple | 0.238 | | sandwich | 0.363 | orange | 0.354 | broccoli | 0.267 | | carrot | 0.236 | hot dog | 0.359 | pizza | 0.516 | | donut | 0.514 | cake | 0.384 | chair | 0.337 | | couch | 0.474 | potted plant | 0.311 | bed | 0.440 | | dining table | 0.298 | toilet | 0.623 | tv | 0.630 | | laptop | 0.659 | mouse | 0.621 | remote | 0.384 | | keyboard | 0.534 | cell phone | 0.412 | microwave | 0.631 | | oven | 0.365 | toaster | 0.457 | sink | 0.426 | | refrigerator | 0.606 | book | 0.186 | clock | 0.506 | | vase | 0.419 | scissors | 0.336 | teddy bear | 0.506 | | hair drier | 0.094 | toothbrush | 0.273 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:01:46,841 - mmdet - INFO - Evaluating segm... 2023-11-13 21:02:21,344 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.411 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.641 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.443 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.213 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.443 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.575 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.688 2023-11-13 21:02:21,347 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.495 | bicycle | 0.179 | car | 0.442 | | motorcycle | 0.357 | airplane | 0.534 | bus | 0.676 | | train | 0.638 | truck | 0.376 | boat | 0.285 | | traffic light | 0.288 | fire hydrant | 0.685 | stop sign | 0.684 | | parking meter | 0.497 | bench | 0.208 | bird | 0.327 | | cat | 0.708 | dog | 0.622 | horse | 0.440 | | sheep | 0.503 | cow | 0.523 | elephant | 0.623 | | bear | 0.738 | zebra | 0.607 | giraffe | 0.518 | | backpack | 0.200 | umbrella | 0.494 | handbag | 0.198 | | tie | 0.349 | suitcase | 0.469 | frisbee | 0.668 | | skis | 0.037 | snowboard | 0.261 | sports ball | 0.456 | | kite | 0.324 | baseball bat | 0.274 | baseball glove | 0.444 | | skateboard | 0.328 | surfboard | 0.361 | tennis racket | 0.566 | | bottle | 0.425 | wine glass | 0.346 | cup | 0.490 | | fork | 0.193 | knife | 0.169 | spoon | 0.143 | | bowl | 0.425 | banana | 0.233 | apple | 0.238 | | sandwich | 0.391 | orange | 0.362 | broccoli | 0.249 | | carrot | 0.206 | hot dog | 0.246 | pizza | 0.514 | | donut | 0.534 | cake | 0.402 | chair | 0.237 | | couch | 0.403 | potted plant | 0.268 | bed | 0.388 | | dining table | 0.190 | toilet | 0.621 | tv | 0.658 | | laptop | 0.657 | mouse | 0.640 | remote | 0.357 | | keyboard | 0.536 | cell phone | 0.384 | microwave | 0.649 | | oven | 0.351 | toaster | 0.462 | sink | 0.407 | | refrigerator | 0.617 | book | 0.132 | clock | 0.520 | | vase | 0.415 | scissors | 0.277 | teddy bear | 0.492 | | hair drier | 0.050 | toothbrush | 0.193 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:02:21,870 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_6.pth was removed 2023-11-13 21:02:23,403 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_7.pth. 2023-11-13 21:02:23,403 - mmdet - INFO - Best bbox_mAP is 0.4522 at 7 epoch. 2023-11-13 21:02:23,403 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 21:02:23,403 - mmdet - INFO - Epoch(val) [7][625] bbox_mAP: 0.4522, bbox_mAP_50: 0.6753, bbox_mAP_75: 0.4995, bbox_mAP_s: 0.2875, bbox_mAP_m: 0.4924, bbox_mAP_l: 0.5905, bbox_mAP_copypaste: 0.4522 0.6753 0.4995 0.2875 0.4924 0.5905, segm_mAP: 0.4106, segm_mAP_50: 0.6409, segm_mAP_75: 0.4430, segm_mAP_s: 0.2130, segm_mAP_m: 0.4427, segm_mAP_l: 0.5949, segm_mAP_copypaste: 0.4106 0.6409 0.4430 0.2130 0.4427 0.5949 2023-11-13 21:02:45,277 - mmdet - INFO - Epoch [8][50/7330] lr: 1.000e-04, eta: 3:08:41, time: 0.437, data_time: 0.140, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0408, loss_cls: 0.1637, acc: 93.9282, loss_bbox: 0.2129, loss_mask: 0.2200, loss: 0.6565 2023-11-13 21:03:01,487 - mmdet - INFO - Epoch [8][100/7330] lr: 1.000e-04, eta: 3:08:26, time: 0.324, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0413, loss_cls: 0.1707, acc: 93.5962, loss_bbox: 0.2205, loss_mask: 0.2219, loss: 0.6736 2023-11-13 21:03:17,695 - mmdet - INFO - Epoch [8][150/7330] lr: 1.000e-04, eta: 3:08:11, time: 0.324, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0378, loss_cls: 0.1685, acc: 93.6582, loss_bbox: 0.2134, loss_mask: 0.2231, loss: 0.6609 2023-11-13 21:03:33,897 - mmdet - INFO - Epoch [8][200/7330] lr: 1.000e-04, eta: 3:07:56, time: 0.324, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0405, loss_cls: 0.1706, acc: 93.7021, loss_bbox: 0.2169, loss_mask: 0.2246, loss: 0.6715 2023-11-13 21:03:49,866 - mmdet - INFO - Epoch [8][250/7330] lr: 1.000e-04, eta: 3:07:41, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0385, loss_cls: 0.1593, acc: 94.0393, loss_bbox: 0.2072, loss_mask: 0.2192, loss: 0.6417 2023-11-13 21:04:05,874 - mmdet - INFO - Epoch [8][300/7330] lr: 1.000e-04, eta: 3:07:26, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0404, loss_cls: 0.1668, acc: 93.7917, loss_bbox: 0.2166, loss_mask: 0.2156, loss: 0.6585 2023-11-13 21:04:21,549 - mmdet - INFO - Epoch [8][350/7330] lr: 1.000e-04, eta: 3:07:10, time: 0.314, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0369, loss_cls: 0.1620, acc: 93.9363, loss_bbox: 0.2082, loss_mask: 0.2181, loss: 0.6414 2023-11-13 21:04:37,533 - mmdet - INFO - Epoch [8][400/7330] lr: 1.000e-04, eta: 3:06:55, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0382, loss_cls: 0.1671, acc: 93.7771, loss_bbox: 0.2147, loss_mask: 0.2168, loss: 0.6540 2023-11-13 21:04:53,307 - mmdet - INFO - Epoch [8][450/7330] lr: 1.000e-04, eta: 3:06:40, time: 0.315, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0387, loss_cls: 0.1656, acc: 93.8420, loss_bbox: 0.2138, loss_mask: 0.2207, loss: 0.6571 2023-11-13 21:05:09,349 - mmdet - INFO - Epoch [8][500/7330] lr: 1.000e-04, eta: 3:06:25, time: 0.321, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0393, loss_cls: 0.1650, acc: 93.8328, loss_bbox: 0.2078, loss_mask: 0.2207, loss: 0.6515 2023-11-13 21:05:24,977 - mmdet - INFO - Epoch [8][550/7330] lr: 1.000e-04, eta: 3:06:10, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0382, loss_cls: 0.1651, acc: 93.7915, loss_bbox: 0.2172, loss_mask: 0.2205, loss: 0.6598 2023-11-13 21:05:41,013 - mmdet - INFO - Epoch [8][600/7330] lr: 1.000e-04, eta: 3:05:54, time: 0.321, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0385, loss_cls: 0.1685, acc: 93.7456, loss_bbox: 0.2193, loss_mask: 0.2204, loss: 0.6656 2023-11-13 21:05:56,957 - mmdet - INFO - Epoch [8][650/7330] lr: 1.000e-04, eta: 3:05:39, time: 0.319, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0389, loss_cls: 0.1658, acc: 93.6389, loss_bbox: 0.2151, loss_mask: 0.2165, loss: 0.6558 2023-11-13 21:06:12,409 - mmdet - INFO - Epoch [8][700/7330] lr: 1.000e-04, eta: 3:05:24, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0366, loss_cls: 0.1573, acc: 94.1843, loss_bbox: 0.2045, loss_mask: 0.2128, loss: 0.6275 2023-11-13 21:06:28,530 - mmdet - INFO - Epoch [8][750/7330] lr: 1.000e-04, eta: 3:05:09, time: 0.322, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0403, loss_cls: 0.1709, acc: 93.5867, loss_bbox: 0.2211, loss_mask: 0.2245, loss: 0.6780 2023-11-13 21:06:44,322 - mmdet - INFO - Epoch [8][800/7330] lr: 1.000e-04, eta: 3:04:54, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0380, loss_cls: 0.1677, acc: 93.7141, loss_bbox: 0.2151, loss_mask: 0.2187, loss: 0.6580 2023-11-13 21:07:00,134 - mmdet - INFO - Epoch [8][850/7330] lr: 1.000e-04, eta: 3:04:38, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0404, loss_cls: 0.1675, acc: 93.6812, loss_bbox: 0.2216, loss_mask: 0.2252, loss: 0.6747 2023-11-13 21:07:15,640 - mmdet - INFO - Epoch [8][900/7330] lr: 1.000e-04, eta: 3:04:23, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0419, loss_cls: 0.1729, acc: 93.5857, loss_bbox: 0.2216, loss_mask: 0.2232, loss: 0.6802 2023-11-13 21:07:31,534 - mmdet - INFO - Epoch [8][950/7330] lr: 1.000e-04, eta: 3:04:08, time: 0.318, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0393, loss_cls: 0.1630, acc: 93.9192, loss_bbox: 0.2109, loss_mask: 0.2179, loss: 0.6501 2023-11-13 21:07:47,110 - mmdet - INFO - Epoch [8][1000/7330] lr: 1.000e-04, eta: 3:03:52, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0389, loss_cls: 0.1686, acc: 93.6553, loss_bbox: 0.2163, loss_mask: 0.2141, loss: 0.6566 2023-11-13 21:08:02,752 - mmdet - INFO - Epoch [8][1050/7330] lr: 1.000e-04, eta: 3:03:37, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0382, loss_cls: 0.1627, acc: 93.8860, loss_bbox: 0.2154, loss_mask: 0.2190, loss: 0.6524 2023-11-13 21:08:18,628 - mmdet - INFO - Epoch [8][1100/7330] lr: 1.000e-04, eta: 3:03:22, time: 0.318, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0396, loss_cls: 0.1667, acc: 93.7087, loss_bbox: 0.2151, loss_mask: 0.2184, loss: 0.6576 2023-11-13 21:08:34,068 - mmdet - INFO - Epoch [8][1150/7330] lr: 1.000e-04, eta: 3:03:06, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0392, loss_cls: 0.1679, acc: 93.7200, loss_bbox: 0.2117, loss_mask: 0.2203, loss: 0.6599 2023-11-13 21:08:49,592 - mmdet - INFO - Epoch [8][1200/7330] lr: 1.000e-04, eta: 3:02:51, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0395, loss_cls: 0.1659, acc: 93.8279, loss_bbox: 0.2164, loss_mask: 0.2159, loss: 0.6563 2023-11-13 21:09:05,134 - mmdet - INFO - Epoch [8][1250/7330] lr: 1.000e-04, eta: 3:02:35, time: 0.311, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0389, loss_cls: 0.1688, acc: 93.6313, loss_bbox: 0.2111, loss_mask: 0.2199, loss: 0.6577 2023-11-13 21:09:20,767 - mmdet - INFO - Epoch [8][1300/7330] lr: 1.000e-04, eta: 3:02:20, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0394, loss_cls: 0.1676, acc: 93.7803, loss_bbox: 0.2163, loss_mask: 0.2253, loss: 0.6685 2023-11-13 21:09:36,797 - mmdet - INFO - Epoch [8][1350/7330] lr: 1.000e-04, eta: 3:02:05, time: 0.321, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0415, loss_cls: 0.1744, acc: 93.5059, loss_bbox: 0.2246, loss_mask: 0.2238, loss: 0.6850 2023-11-13 21:09:52,717 - mmdet - INFO - Epoch [8][1400/7330] lr: 1.000e-04, eta: 3:01:50, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0394, loss_cls: 0.1705, acc: 93.7458, loss_bbox: 0.2171, loss_mask: 0.2178, loss: 0.6629 2023-11-13 21:10:07,865 - mmdet - INFO - Epoch [8][1450/7330] lr: 1.000e-04, eta: 3:01:34, time: 0.303, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0397, loss_cls: 0.1724, acc: 93.6938, loss_bbox: 0.2226, loss_mask: 0.2242, loss: 0.6772 2023-11-13 21:10:23,490 - mmdet - INFO - Epoch [8][1500/7330] lr: 1.000e-04, eta: 3:01:19, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0394, loss_cls: 0.1701, acc: 93.6343, loss_bbox: 0.2164, loss_mask: 0.2190, loss: 0.6643 2023-11-13 21:10:39,243 - mmdet - INFO - Epoch [8][1550/7330] lr: 1.000e-04, eta: 3:01:03, time: 0.315, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0407, loss_cls: 0.1762, acc: 93.4604, loss_bbox: 0.2172, loss_mask: 0.2235, loss: 0.6795 2023-11-13 21:10:54,683 - mmdet - INFO - Epoch [8][1600/7330] lr: 1.000e-04, eta: 3:00:48, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0412, loss_cls: 0.1615, acc: 93.9773, loss_bbox: 0.2105, loss_mask: 0.2203, loss: 0.6542 2023-11-13 21:11:10,161 - mmdet - INFO - Epoch [8][1650/7330] lr: 1.000e-04, eta: 3:00:32, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0383, loss_cls: 0.1660, acc: 93.8784, loss_bbox: 0.2181, loss_mask: 0.2211, loss: 0.6624 2023-11-13 21:11:25,580 - mmdet - INFO - Epoch [8][1700/7330] lr: 1.000e-04, eta: 3:00:17, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0384, loss_cls: 0.1640, acc: 93.9055, loss_bbox: 0.2151, loss_mask: 0.2221, loss: 0.6585 2023-11-13 21:11:41,086 - mmdet - INFO - Epoch [8][1750/7330] lr: 1.000e-04, eta: 3:00:01, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0382, loss_cls: 0.1719, acc: 93.5193, loss_bbox: 0.2194, loss_mask: 0.2203, loss: 0.6694 2023-11-13 21:11:56,348 - mmdet - INFO - Epoch [8][1800/7330] lr: 1.000e-04, eta: 2:59:46, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0364, loss_cls: 0.1574, acc: 94.1980, loss_bbox: 0.2061, loss_mask: 0.2154, loss: 0.6328 2023-11-13 21:12:12,005 - mmdet - INFO - Epoch [8][1850/7330] lr: 1.000e-04, eta: 2:59:30, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0410, loss_cls: 0.1683, acc: 93.6833, loss_bbox: 0.2211, loss_mask: 0.2242, loss: 0.6733 2023-11-13 21:12:27,071 - mmdet - INFO - Epoch [8][1900/7330] lr: 1.000e-04, eta: 2:59:15, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0350, loss_cls: 0.1639, acc: 94.0083, loss_bbox: 0.2095, loss_mask: 0.2158, loss: 0.6422 2023-11-13 21:12:42,621 - mmdet - INFO - Epoch [8][1950/7330] lr: 1.000e-04, eta: 2:58:59, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0383, loss_cls: 0.1626, acc: 93.8325, loss_bbox: 0.2111, loss_mask: 0.2210, loss: 0.6525 2023-11-13 21:12:58,026 - mmdet - INFO - Epoch [8][2000/7330] lr: 1.000e-04, eta: 2:58:44, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0403, loss_cls: 0.1644, acc: 93.8882, loss_bbox: 0.2134, loss_mask: 0.2184, loss: 0.6555 2023-11-13 21:13:13,702 - mmdet - INFO - Epoch [8][2050/7330] lr: 1.000e-04, eta: 2:58:28, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0418, loss_cls: 0.1743, acc: 93.5146, loss_bbox: 0.2218, loss_mask: 0.2197, loss: 0.6776 2023-11-13 21:13:29,373 - mmdet - INFO - Epoch [8][2100/7330] lr: 1.000e-04, eta: 2:58:13, time: 0.313, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0417, loss_cls: 0.1712, acc: 93.6121, loss_bbox: 0.2180, loss_mask: 0.2247, loss: 0.6770 2023-11-13 21:13:45,173 - mmdet - INFO - Epoch [8][2150/7330] lr: 1.000e-04, eta: 2:57:58, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0392, loss_cls: 0.1734, acc: 93.5942, loss_bbox: 0.2167, loss_mask: 0.2233, loss: 0.6730 2023-11-13 21:14:00,817 - mmdet - INFO - Epoch [8][2200/7330] lr: 1.000e-04, eta: 2:57:42, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0385, loss_cls: 0.1672, acc: 93.8699, loss_bbox: 0.2126, loss_mask: 0.2230, loss: 0.6601 2023-11-13 21:14:16,624 - mmdet - INFO - Epoch [8][2250/7330] lr: 1.000e-04, eta: 2:57:27, time: 0.316, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0387, loss_cls: 0.1689, acc: 93.7981, loss_bbox: 0.2102, loss_mask: 0.2215, loss: 0.6576 2023-11-13 21:14:32,022 - mmdet - INFO - Epoch [8][2300/7330] lr: 1.000e-04, eta: 2:57:12, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0383, loss_cls: 0.1655, acc: 93.8943, loss_bbox: 0.2147, loss_mask: 0.2229, loss: 0.6587 2023-11-13 21:14:47,194 - mmdet - INFO - Epoch [8][2350/7330] lr: 1.000e-04, eta: 2:56:56, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0397, loss_cls: 0.1684, acc: 93.7480, loss_bbox: 0.2182, loss_mask: 0.2176, loss: 0.6650 2023-11-13 21:15:02,452 - mmdet - INFO - Epoch [8][2400/7330] lr: 1.000e-04, eta: 2:56:40, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0385, loss_cls: 0.1660, acc: 93.7451, loss_bbox: 0.2166, loss_mask: 0.2211, loss: 0.6599 2023-11-13 21:15:17,655 - mmdet - INFO - Epoch [8][2450/7330] lr: 1.000e-04, eta: 2:56:25, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0398, loss_cls: 0.1681, acc: 93.7681, loss_bbox: 0.2191, loss_mask: 0.2216, loss: 0.6682 2023-11-13 21:15:33,326 - mmdet - INFO - Epoch [8][2500/7330] lr: 1.000e-04, eta: 2:56:09, time: 0.313, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0418, loss_cls: 0.1747, acc: 93.4585, loss_bbox: 0.2211, loss_mask: 0.2266, loss: 0.6847 2023-11-13 21:15:48,799 - mmdet - INFO - Epoch [8][2550/7330] lr: 1.000e-04, eta: 2:55:54, time: 0.309, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0387, loss_cls: 0.1692, acc: 93.6597, loss_bbox: 0.2164, loss_mask: 0.2233, loss: 0.6671 2023-11-13 21:16:04,272 - mmdet - INFO - Epoch [8][2600/7330] lr: 1.000e-04, eta: 2:55:38, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0374, loss_cls: 0.1613, acc: 93.9890, loss_bbox: 0.2051, loss_mask: 0.2128, loss: 0.6344 2023-11-13 21:16:19,522 - mmdet - INFO - Epoch [8][2650/7330] lr: 1.000e-04, eta: 2:55:23, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0378, loss_cls: 0.1714, acc: 93.5872, loss_bbox: 0.2153, loss_mask: 0.2200, loss: 0.6621 2023-11-13 21:16:35,059 - mmdet - INFO - Epoch [8][2700/7330] lr: 1.000e-04, eta: 2:55:07, time: 0.311, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0417, loss_cls: 0.1732, acc: 93.6262, loss_bbox: 0.2186, loss_mask: 0.2221, loss: 0.6778 2023-11-13 21:16:50,846 - mmdet - INFO - Epoch [8][2750/7330] lr: 1.000e-04, eta: 2:54:52, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0391, loss_cls: 0.1686, acc: 93.6921, loss_bbox: 0.2111, loss_mask: 0.2171, loss: 0.6558 2023-11-13 21:17:06,256 - mmdet - INFO - Epoch [8][2800/7330] lr: 1.000e-04, eta: 2:54:36, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0395, loss_cls: 0.1691, acc: 93.6631, loss_bbox: 0.2153, loss_mask: 0.2170, loss: 0.6593 2023-11-13 21:17:21,806 - mmdet - INFO - Epoch [8][2850/7330] lr: 1.000e-04, eta: 2:54:21, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0411, loss_cls: 0.1715, acc: 93.5127, loss_bbox: 0.2249, loss_mask: 0.2256, loss: 0.6821 2023-11-13 21:17:37,343 - mmdet - INFO - Epoch [8][2900/7330] lr: 1.000e-04, eta: 2:54:06, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0413, loss_cls: 0.1720, acc: 93.6106, loss_bbox: 0.2220, loss_mask: 0.2243, loss: 0.6808 2023-11-13 21:17:52,834 - mmdet - INFO - Epoch [8][2950/7330] lr: 1.000e-04, eta: 2:53:50, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0377, loss_cls: 0.1620, acc: 94.0120, loss_bbox: 0.2065, loss_mask: 0.2161, loss: 0.6414 2023-11-13 21:18:08,253 - mmdet - INFO - Epoch [8][3000/7330] lr: 1.000e-04, eta: 2:53:35, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0401, loss_cls: 0.1713, acc: 93.5938, loss_bbox: 0.2158, loss_mask: 0.2198, loss: 0.6661 2023-11-13 21:18:23,794 - mmdet - INFO - Epoch [8][3050/7330] lr: 1.000e-04, eta: 2:53:19, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0376, loss_cls: 0.1686, acc: 93.6748, loss_bbox: 0.2153, loss_mask: 0.2175, loss: 0.6584 2023-11-13 21:18:39,405 - mmdet - INFO - Epoch [8][3100/7330] lr: 1.000e-04, eta: 2:53:04, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0384, loss_cls: 0.1729, acc: 93.5569, loss_bbox: 0.2204, loss_mask: 0.2204, loss: 0.6713 2023-11-13 21:18:54,799 - mmdet - INFO - Epoch [8][3150/7330] lr: 1.000e-04, eta: 2:52:48, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0394, loss_cls: 0.1656, acc: 93.9031, loss_bbox: 0.2096, loss_mask: 0.2184, loss: 0.6529 2023-11-13 21:19:10,110 - mmdet - INFO - Epoch [8][3200/7330] lr: 1.000e-04, eta: 2:52:33, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0388, loss_cls: 0.1729, acc: 93.5906, loss_bbox: 0.2166, loss_mask: 0.2250, loss: 0.6747 2023-11-13 21:19:25,505 - mmdet - INFO - Epoch [8][3250/7330] lr: 1.000e-04, eta: 2:52:17, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0400, loss_cls: 0.1688, acc: 93.8013, loss_bbox: 0.2136, loss_mask: 0.2270, loss: 0.6708 2023-11-13 21:19:40,906 - mmdet - INFO - Epoch [8][3300/7330] lr: 1.000e-04, eta: 2:52:02, time: 0.308, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0384, loss_cls: 0.1691, acc: 93.8230, loss_bbox: 0.2134, loss_mask: 0.2214, loss: 0.6612 2023-11-13 21:19:56,187 - mmdet - INFO - Epoch [8][3350/7330] lr: 1.000e-04, eta: 2:51:46, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0391, loss_cls: 0.1713, acc: 93.6462, loss_bbox: 0.2175, loss_mask: 0.2226, loss: 0.6703 2023-11-13 21:20:11,325 - mmdet - INFO - Epoch [8][3400/7330] lr: 1.000e-04, eta: 2:51:30, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0384, loss_cls: 0.1752, acc: 93.4561, loss_bbox: 0.2224, loss_mask: 0.2260, loss: 0.6818 2023-11-13 21:20:26,358 - mmdet - INFO - Epoch [8][3450/7330] lr: 1.000e-04, eta: 2:51:15, time: 0.301, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0377, loss_cls: 0.1643, acc: 93.8928, loss_bbox: 0.2095, loss_mask: 0.2181, loss: 0.6474 2023-11-13 21:20:41,944 - mmdet - INFO - Epoch [8][3500/7330] lr: 1.000e-04, eta: 2:50:59, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0407, loss_cls: 0.1726, acc: 93.6633, loss_bbox: 0.2195, loss_mask: 0.2232, loss: 0.6769 2023-11-13 21:20:57,328 - mmdet - INFO - Epoch [8][3550/7330] lr: 1.000e-04, eta: 2:50:44, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0389, loss_cls: 0.1631, acc: 93.9827, loss_bbox: 0.2092, loss_mask: 0.2209, loss: 0.6528 2023-11-13 21:21:12,700 - mmdet - INFO - Epoch [8][3600/7330] lr: 1.000e-04, eta: 2:50:28, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0403, loss_cls: 0.1674, acc: 93.8511, loss_bbox: 0.2148, loss_mask: 0.2196, loss: 0.6632 2023-11-13 21:21:27,931 - mmdet - INFO - Epoch [8][3650/7330] lr: 1.000e-04, eta: 2:50:13, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0363, loss_cls: 0.1663, acc: 93.8818, loss_bbox: 0.2106, loss_mask: 0.2170, loss: 0.6485 2023-11-13 21:21:43,605 - mmdet - INFO - Epoch [8][3700/7330] lr: 1.000e-04, eta: 2:49:57, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0389, loss_cls: 0.1683, acc: 93.6980, loss_bbox: 0.2137, loss_mask: 0.2217, loss: 0.6631 2023-11-13 21:21:59,040 - mmdet - INFO - Epoch [8][3750/7330] lr: 1.000e-04, eta: 2:49:42, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0395, loss_cls: 0.1707, acc: 93.7229, loss_bbox: 0.2149, loss_mask: 0.2223, loss: 0.6683 2023-11-13 21:22:14,456 - mmdet - INFO - Epoch [8][3800/7330] lr: 1.000e-04, eta: 2:49:26, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0411, loss_cls: 0.1715, acc: 93.6055, loss_bbox: 0.2161, loss_mask: 0.2218, loss: 0.6705 2023-11-13 21:22:29,909 - mmdet - INFO - Epoch [8][3850/7330] lr: 1.000e-04, eta: 2:49:11, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0393, loss_cls: 0.1709, acc: 93.6289, loss_bbox: 0.2176, loss_mask: 0.2228, loss: 0.6710 2023-11-13 21:22:45,921 - mmdet - INFO - Epoch [8][3900/7330] lr: 1.000e-04, eta: 2:48:56, time: 0.320, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0409, loss_cls: 0.1729, acc: 93.5161, loss_bbox: 0.2234, loss_mask: 0.2221, loss: 0.6787 2023-11-13 21:23:01,805 - mmdet - INFO - Epoch [8][3950/7330] lr: 1.000e-04, eta: 2:48:40, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0403, loss_cls: 0.1593, acc: 94.0713, loss_bbox: 0.2088, loss_mask: 0.2199, loss: 0.6505 2023-11-13 21:23:17,064 - mmdet - INFO - Epoch [8][4000/7330] lr: 1.000e-04, eta: 2:48:25, time: 0.305, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0398, loss_cls: 0.1717, acc: 93.5356, loss_bbox: 0.2178, loss_mask: 0.2229, loss: 0.6716 2023-11-13 21:23:32,446 - mmdet - INFO - Epoch [8][4050/7330] lr: 1.000e-04, eta: 2:48:09, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0401, loss_cls: 0.1708, acc: 93.6570, loss_bbox: 0.2138, loss_mask: 0.2218, loss: 0.6677 2023-11-13 21:23:48,077 - mmdet - INFO - Epoch [8][4100/7330] lr: 1.000e-04, eta: 2:47:54, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0389, loss_cls: 0.1635, acc: 93.9248, loss_bbox: 0.2114, loss_mask: 0.2215, loss: 0.6554 2023-11-13 21:24:03,606 - mmdet - INFO - Epoch [8][4150/7330] lr: 1.000e-04, eta: 2:47:38, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0402, loss_cls: 0.1690, acc: 93.6602, loss_bbox: 0.2137, loss_mask: 0.2203, loss: 0.6617 2023-11-13 21:24:19,123 - mmdet - INFO - Epoch [8][4200/7330] lr: 1.000e-04, eta: 2:47:23, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0418, loss_cls: 0.1751, acc: 93.5337, loss_bbox: 0.2177, loss_mask: 0.2231, loss: 0.6789 2023-11-13 21:24:34,670 - mmdet - INFO - Epoch [8][4250/7330] lr: 1.000e-04, eta: 2:47:07, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0399, loss_cls: 0.1694, acc: 93.7114, loss_bbox: 0.2185, loss_mask: 0.2206, loss: 0.6674 2023-11-13 21:24:50,002 - mmdet - INFO - Epoch [8][4300/7330] lr: 1.000e-04, eta: 2:46:52, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0395, loss_cls: 0.1667, acc: 93.7253, loss_bbox: 0.2159, loss_mask: 0.2210, loss: 0.6619 2023-11-13 21:25:05,473 - mmdet - INFO - Epoch [8][4350/7330] lr: 1.000e-04, eta: 2:46:36, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0394, loss_cls: 0.1693, acc: 93.8152, loss_bbox: 0.2124, loss_mask: 0.2185, loss: 0.6592 2023-11-13 21:25:21,172 - mmdet - INFO - Epoch [8][4400/7330] lr: 1.000e-04, eta: 2:46:21, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0400, loss_cls: 0.1698, acc: 93.7622, loss_bbox: 0.2143, loss_mask: 0.2195, loss: 0.6652 2023-11-13 21:25:36,708 - mmdet - INFO - Epoch [8][4450/7330] lr: 1.000e-04, eta: 2:46:06, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0375, loss_cls: 0.1651, acc: 93.8879, loss_bbox: 0.2070, loss_mask: 0.2184, loss: 0.6468 2023-11-13 21:25:51,976 - mmdet - INFO - Epoch [8][4500/7330] lr: 1.000e-04, eta: 2:45:50, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0399, loss_cls: 0.1652, acc: 93.8218, loss_bbox: 0.2053, loss_mask: 0.2145, loss: 0.6452 2023-11-13 21:26:07,388 - mmdet - INFO - Epoch [8][4550/7330] lr: 1.000e-04, eta: 2:45:35, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0380, loss_cls: 0.1679, acc: 93.7429, loss_bbox: 0.2150, loss_mask: 0.2171, loss: 0.6559 2023-11-13 21:26:23,280 - mmdet - INFO - Epoch [8][4600/7330] lr: 1.000e-04, eta: 2:45:19, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0416, loss_cls: 0.1666, acc: 93.7979, loss_bbox: 0.2141, loss_mask: 0.2184, loss: 0.6611 2023-11-13 21:26:38,536 - mmdet - INFO - Epoch [8][4650/7330] lr: 1.000e-04, eta: 2:45:04, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0393, loss_cls: 0.1641, acc: 93.9583, loss_bbox: 0.2089, loss_mask: 0.2218, loss: 0.6527 2023-11-13 21:26:53,960 - mmdet - INFO - Epoch [8][4700/7330] lr: 1.000e-04, eta: 2:44:48, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0401, loss_cls: 0.1767, acc: 93.5139, loss_bbox: 0.2214, loss_mask: 0.2227, loss: 0.6805 2023-11-13 21:27:09,372 - mmdet - INFO - Epoch [8][4750/7330] lr: 1.000e-04, eta: 2:44:33, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0370, loss_cls: 0.1642, acc: 93.9751, loss_bbox: 0.2057, loss_mask: 0.2167, loss: 0.6434 2023-11-13 21:27:24,528 - mmdet - INFO - Epoch [8][4800/7330] lr: 1.000e-04, eta: 2:44:17, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0383, loss_cls: 0.1660, acc: 93.9097, loss_bbox: 0.2105, loss_mask: 0.2149, loss: 0.6475 2023-11-13 21:27:39,864 - mmdet - INFO - Epoch [8][4850/7330] lr: 1.000e-04, eta: 2:44:01, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1734, acc: 93.5215, loss_bbox: 0.2196, loss_mask: 0.2197, loss: 0.6706 2023-11-13 21:27:55,524 - mmdet - INFO - Epoch [8][4900/7330] lr: 1.000e-04, eta: 2:43:46, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0384, loss_cls: 0.1764, acc: 93.4771, loss_bbox: 0.2189, loss_mask: 0.2208, loss: 0.6734 2023-11-13 21:28:10,762 - mmdet - INFO - Epoch [8][4950/7330] lr: 1.000e-04, eta: 2:43:31, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0381, loss_cls: 0.1620, acc: 93.9529, loss_bbox: 0.2056, loss_mask: 0.2146, loss: 0.6396 2023-11-13 21:28:26,156 - mmdet - INFO - Epoch [8][5000/7330] lr: 1.000e-04, eta: 2:43:15, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0392, loss_cls: 0.1653, acc: 93.8645, loss_bbox: 0.2138, loss_mask: 0.2162, loss: 0.6533 2023-11-13 21:28:41,403 - mmdet - INFO - Epoch [8][5050/7330] lr: 1.000e-04, eta: 2:42:59, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0385, loss_cls: 0.1744, acc: 93.4668, loss_bbox: 0.2221, loss_mask: 0.2186, loss: 0.6742 2023-11-13 21:28:56,986 - mmdet - INFO - Epoch [8][5100/7330] lr: 1.000e-04, eta: 2:42:44, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0423, loss_cls: 0.1772, acc: 93.3342, loss_bbox: 0.2251, loss_mask: 0.2251, loss: 0.6913 2023-11-13 21:29:12,135 - mmdet - INFO - Epoch [8][5150/7330] lr: 1.000e-04, eta: 2:42:28, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0378, loss_cls: 0.1649, acc: 93.8982, loss_bbox: 0.2067, loss_mask: 0.2113, loss: 0.6400 2023-11-13 21:29:28,134 - mmdet - INFO - Epoch [8][5200/7330] lr: 1.000e-04, eta: 2:42:13, time: 0.320, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0394, loss_cls: 0.1716, acc: 93.6448, loss_bbox: 0.2172, loss_mask: 0.2230, loss: 0.6724 2023-11-13 21:29:43,750 - mmdet - INFO - Epoch [8][5250/7330] lr: 1.000e-04, eta: 2:41:58, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0405, loss_cls: 0.1726, acc: 93.5686, loss_bbox: 0.2189, loss_mask: 0.2189, loss: 0.6709 2023-11-13 21:29:59,441 - mmdet - INFO - Epoch [8][5300/7330] lr: 1.000e-04, eta: 2:41:42, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0382, loss_cls: 0.1717, acc: 93.5764, loss_bbox: 0.2205, loss_mask: 0.2198, loss: 0.6709 2023-11-13 21:30:14,956 - mmdet - INFO - Epoch [8][5350/7330] lr: 1.000e-04, eta: 2:41:27, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0405, loss_cls: 0.1697, acc: 93.7451, loss_bbox: 0.2136, loss_mask: 0.2183, loss: 0.6616 2023-11-13 21:30:30,318 - mmdet - INFO - Epoch [8][5400/7330] lr: 1.000e-04, eta: 2:41:11, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0419, loss_cls: 0.1708, acc: 93.6860, loss_bbox: 0.2178, loss_mask: 0.2200, loss: 0.6702 2023-11-13 21:30:45,688 - mmdet - INFO - Epoch [8][5450/7330] lr: 1.000e-04, eta: 2:40:56, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0385, loss_cls: 0.1681, acc: 93.8591, loss_bbox: 0.2077, loss_mask: 0.2223, loss: 0.6561 2023-11-13 21:31:01,365 - mmdet - INFO - Epoch [8][5500/7330] lr: 1.000e-04, eta: 2:40:40, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0416, loss_cls: 0.1711, acc: 93.6672, loss_bbox: 0.2139, loss_mask: 0.2241, loss: 0.6712 2023-11-13 21:31:17,146 - mmdet - INFO - Epoch [8][5550/7330] lr: 1.000e-04, eta: 2:40:25, time: 0.316, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0421, loss_cls: 0.1711, acc: 93.5964, loss_bbox: 0.2208, loss_mask: 0.2197, loss: 0.6734 2023-11-13 21:31:32,731 - mmdet - INFO - Epoch [8][5600/7330] lr: 1.000e-04, eta: 2:40:10, time: 0.312, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0420, loss_cls: 0.1730, acc: 93.5078, loss_bbox: 0.2210, loss_mask: 0.2290, loss: 0.6866 2023-11-13 21:31:48,741 - mmdet - INFO - Epoch [8][5650/7330] lr: 1.000e-04, eta: 2:39:55, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0441, loss_cls: 0.1797, acc: 93.2454, loss_bbox: 0.2296, loss_mask: 0.2250, loss: 0.6986 2023-11-13 21:32:04,400 - mmdet - INFO - Epoch [8][5700/7330] lr: 1.000e-04, eta: 2:39:39, time: 0.313, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0404, loss_cls: 0.1717, acc: 93.5837, loss_bbox: 0.2185, loss_mask: 0.2237, loss: 0.6745 2023-11-13 21:32:20,235 - mmdet - INFO - Epoch [8][5750/7330] lr: 1.000e-04, eta: 2:39:24, time: 0.317, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0405, loss_cls: 0.1767, acc: 93.4832, loss_bbox: 0.2219, loss_mask: 0.2262, loss: 0.6878 2023-11-13 21:32:35,676 - mmdet - INFO - Epoch [8][5800/7330] lr: 1.000e-04, eta: 2:39:08, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0388, loss_cls: 0.1669, acc: 93.7893, loss_bbox: 0.2137, loss_mask: 0.2223, loss: 0.6628 2023-11-13 21:32:50,851 - mmdet - INFO - Epoch [8][5850/7330] lr: 1.000e-04, eta: 2:38:53, time: 0.304, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0376, loss_cls: 0.1625, acc: 93.8838, loss_bbox: 0.2068, loss_mask: 0.2163, loss: 0.6408 2023-11-13 21:33:06,073 - mmdet - INFO - Epoch [8][5900/7330] lr: 1.000e-04, eta: 2:38:37, time: 0.304, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0392, loss_cls: 0.1752, acc: 93.6340, loss_bbox: 0.2128, loss_mask: 0.2214, loss: 0.6676 2023-11-13 21:33:21,615 - mmdet - INFO - Epoch [8][5950/7330] lr: 1.000e-04, eta: 2:38:22, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0406, loss_cls: 0.1754, acc: 93.4939, loss_bbox: 0.2187, loss_mask: 0.2238, loss: 0.6793 2023-11-13 21:33:37,448 - mmdet - INFO - Epoch [8][6000/7330] lr: 1.000e-04, eta: 2:38:06, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0380, loss_cls: 0.1742, acc: 93.4490, loss_bbox: 0.2189, loss_mask: 0.2236, loss: 0.6744 2023-11-13 21:33:52,922 - mmdet - INFO - Epoch [8][6050/7330] lr: 1.000e-04, eta: 2:37:51, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0399, loss_cls: 0.1756, acc: 93.5273, loss_bbox: 0.2208, loss_mask: 0.2209, loss: 0.6784 2023-11-13 21:34:08,303 - mmdet - INFO - Epoch [8][6100/7330] lr: 1.000e-04, eta: 2:37:35, time: 0.308, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0394, loss_cls: 0.1709, acc: 93.5442, loss_bbox: 0.2138, loss_mask: 0.2204, loss: 0.6645 2023-11-13 21:34:23,787 - mmdet - INFO - Epoch [8][6150/7330] lr: 1.000e-04, eta: 2:37:20, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0392, loss_cls: 0.1723, acc: 93.7043, loss_bbox: 0.2166, loss_mask: 0.2235, loss: 0.6719 2023-11-13 21:34:38,982 - mmdet - INFO - Epoch [8][6200/7330] lr: 1.000e-04, eta: 2:37:04, time: 0.304, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0379, loss_cls: 0.1698, acc: 93.7844, loss_bbox: 0.2109, loss_mask: 0.2185, loss: 0.6559 2023-11-13 21:34:53,954 - mmdet - INFO - Epoch [8][6250/7330] lr: 1.000e-04, eta: 2:36:49, time: 0.299, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0361, loss_cls: 0.1665, acc: 93.8247, loss_bbox: 0.2135, loss_mask: 0.2163, loss: 0.6495 2023-11-13 21:35:09,351 - mmdet - INFO - Epoch [8][6300/7330] lr: 1.000e-04, eta: 2:36:33, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0379, loss_cls: 0.1658, acc: 93.9343, loss_bbox: 0.2103, loss_mask: 0.2221, loss: 0.6555 2023-11-13 21:35:24,768 - mmdet - INFO - Epoch [8][6350/7330] lr: 1.000e-04, eta: 2:36:18, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0414, loss_cls: 0.1825, acc: 93.2827, loss_bbox: 0.2313, loss_mask: 0.2255, loss: 0.7033 2023-11-13 21:35:39,994 - mmdet - INFO - Epoch [8][6400/7330] lr: 1.000e-04, eta: 2:36:02, time: 0.304, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0403, loss_cls: 0.1739, acc: 93.5752, loss_bbox: 0.2197, loss_mask: 0.2202, loss: 0.6736 2023-11-13 21:35:55,237 - mmdet - INFO - Epoch [8][6450/7330] lr: 1.000e-04, eta: 2:35:46, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0380, loss_cls: 0.1652, acc: 93.9851, loss_bbox: 0.2104, loss_mask: 0.2179, loss: 0.6498 2023-11-13 21:36:10,934 - mmdet - INFO - Epoch [8][6500/7330] lr: 1.000e-04, eta: 2:35:31, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0416, loss_cls: 0.1798, acc: 93.2458, loss_bbox: 0.2268, loss_mask: 0.2193, loss: 0.6884 2023-11-13 21:36:26,300 - mmdet - INFO - Epoch [8][6550/7330] lr: 1.000e-04, eta: 2:35:15, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0435, loss_cls: 0.1785, acc: 93.3003, loss_bbox: 0.2315, loss_mask: 0.2298, loss: 0.7032 2023-11-13 21:36:41,743 - mmdet - INFO - Epoch [8][6600/7330] lr: 1.000e-04, eta: 2:35:00, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0377, loss_cls: 0.1690, acc: 93.9333, loss_bbox: 0.2087, loss_mask: 0.2209, loss: 0.6553 2023-11-13 21:36:57,182 - mmdet - INFO - Epoch [8][6650/7330] lr: 1.000e-04, eta: 2:34:44, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0416, loss_cls: 0.1788, acc: 93.3491, loss_bbox: 0.2186, loss_mask: 0.2222, loss: 0.6836 2023-11-13 21:37:12,459 - mmdet - INFO - Epoch [8][6700/7330] lr: 1.000e-04, eta: 2:34:29, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0376, loss_cls: 0.1656, acc: 93.8091, loss_bbox: 0.2080, loss_mask: 0.2185, loss: 0.6482 2023-11-13 21:37:27,853 - mmdet - INFO - Epoch [8][6750/7330] lr: 1.000e-04, eta: 2:34:13, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0403, loss_cls: 0.1701, acc: 93.6262, loss_bbox: 0.2121, loss_mask: 0.2225, loss: 0.6646 2023-11-13 21:37:43,193 - mmdet - INFO - Epoch [8][6800/7330] lr: 1.000e-04, eta: 2:33:58, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0398, loss_cls: 0.1684, acc: 93.7275, loss_bbox: 0.2118, loss_mask: 0.2178, loss: 0.6582 2023-11-13 21:37:58,270 - mmdet - INFO - Epoch [8][6850/7330] lr: 1.000e-04, eta: 2:33:42, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0379, loss_cls: 0.1637, acc: 93.9622, loss_bbox: 0.2101, loss_mask: 0.2193, loss: 0.6502 2023-11-13 21:38:13,693 - mmdet - INFO - Epoch [8][6900/7330] lr: 1.000e-04, eta: 2:33:27, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0378, loss_cls: 0.1691, acc: 93.7043, loss_bbox: 0.2131, loss_mask: 0.2219, loss: 0.6598 2023-11-13 21:38:28,721 - mmdet - INFO - Epoch [8][6950/7330] lr: 1.000e-04, eta: 2:33:11, time: 0.301, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0365, loss_cls: 0.1621, acc: 93.9290, loss_bbox: 0.2128, loss_mask: 0.2212, loss: 0.6507 2023-11-13 21:38:44,090 - mmdet - INFO - Epoch [8][7000/7330] lr: 1.000e-04, eta: 2:32:55, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0398, loss_cls: 0.1748, acc: 93.5432, loss_bbox: 0.2168, loss_mask: 0.2193, loss: 0.6709 2023-11-13 21:38:59,444 - mmdet - INFO - Epoch [8][7050/7330] lr: 1.000e-04, eta: 2:32:40, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0386, loss_cls: 0.1673, acc: 93.8127, loss_bbox: 0.2112, loss_mask: 0.2221, loss: 0.6578 2023-11-13 21:39:14,763 - mmdet - INFO - Epoch [8][7100/7330] lr: 1.000e-04, eta: 2:32:24, time: 0.306, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0387, loss_cls: 0.1715, acc: 93.6282, loss_bbox: 0.2157, loss_mask: 0.2197, loss: 0.6655 2023-11-13 21:39:29,955 - mmdet - INFO - Epoch [8][7150/7330] lr: 1.000e-04, eta: 2:32:09, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0390, loss_cls: 0.1715, acc: 93.7388, loss_bbox: 0.2134, loss_mask: 0.2175, loss: 0.6604 2023-11-13 21:39:45,445 - mmdet - INFO - Epoch [8][7200/7330] lr: 1.000e-04, eta: 2:31:53, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0402, loss_cls: 0.1751, acc: 93.6543, loss_bbox: 0.2186, loss_mask: 0.2227, loss: 0.6779 2023-11-13 21:40:00,932 - mmdet - INFO - Epoch [8][7250/7330] lr: 1.000e-04, eta: 2:31:38, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0387, loss_cls: 0.1663, acc: 93.8828, loss_bbox: 0.2085, loss_mask: 0.2177, loss: 0.6518 2023-11-13 21:40:16,322 - mmdet - INFO - Epoch [8][7300/7330] lr: 1.000e-04, eta: 2:31:22, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0365, loss_cls: 0.1575, acc: 94.1379, loss_bbox: 0.2056, loss_mask: 0.2169, loss: 0.6338 2023-11-13 21:40:26,000 - mmdet - INFO - Saving checkpoint at 8 epochs 2023-11-13 21:41:10,567 - mmdet - INFO - Evaluating bbox... 2023-11-13 21:41:42,045 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.456 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.679 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.508 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.283 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 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.386 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.627 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.728 2023-11-13 21:41:42,048 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.568 | bicycle | 0.354 | car | 0.475 | | motorcycle | 0.470 | airplane | 0.703 | bus | 0.677 | | train | 0.640 | truck | 0.423 | boat | 0.296 | | traffic light | 0.312 | fire hydrant | 0.702 | stop sign | 0.646 | | parking meter | 0.484 | bench | 0.281 | bird | 0.400 | | cat | 0.701 | dog | 0.675 | horse | 0.590 | | sheep | 0.560 | cow | 0.604 | elephant | 0.654 | | bear | 0.730 | zebra | 0.671 | giraffe | 0.668 | | backpack | 0.205 | umbrella | 0.434 | handbag | 0.199 | | tie | 0.373 | suitcase | 0.433 | frisbee | 0.709 | | skis | 0.284 | snowboard | 0.403 | sports ball | 0.467 | | kite | 0.453 | baseball bat | 0.404 | baseball glove | 0.420 | | skateboard | 0.554 | surfboard | 0.447 | tennis racket | 0.502 | | bottle | 0.443 | wine glass | 0.402 | cup | 0.491 | | fork | 0.423 | knife | 0.258 | spoon | 0.238 | | bowl | 0.437 | banana | 0.268 | apple | 0.255 | | sandwich | 0.379 | orange | 0.318 | broccoli | 0.266 | | carrot | 0.249 | hot dog | 0.412 | pizza | 0.523 | | donut | 0.518 | cake | 0.395 | chair | 0.342 | | couch | 0.457 | potted plant | 0.327 | bed | 0.433 | | dining table | 0.302 | toilet | 0.647 | tv | 0.621 | | laptop | 0.647 | mouse | 0.633 | remote | 0.384 | | keyboard | 0.563 | cell phone | 0.434 | microwave | 0.582 | | oven | 0.372 | toaster | 0.404 | sink | 0.417 | | refrigerator | 0.622 | book | 0.179 | clock | 0.508 | | vase | 0.395 | scissors | 0.385 | teddy bear | 0.493 | | hair drier | 0.132 | toothbrush | 0.355 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:41:42,048 - mmdet - INFO - Evaluating segm... 2023-11-13 21:42:21,805 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.649 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.446 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.212 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.445 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.605 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 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.572 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.698 2023-11-13 21:42:21,808 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.496 | bicycle | 0.220 | car | 0.436 | | motorcycle | 0.381 | airplane | 0.564 | bus | 0.677 | | train | 0.648 | truck | 0.410 | boat | 0.273 | | traffic light | 0.304 | fire hydrant | 0.687 | stop sign | 0.660 | | parking meter | 0.490 | bench | 0.213 | bird | 0.343 | | cat | 0.709 | dog | 0.637 | horse | 0.442 | | sheep | 0.505 | cow | 0.534 | elephant | 0.602 | | bear | 0.722 | zebra | 0.573 | giraffe | 0.506 | | backpack | 0.220 | umbrella | 0.507 | handbag | 0.199 | | tie | 0.345 | suitcase | 0.467 | frisbee | 0.687 | | skis | 0.050 | snowboard | 0.269 | sports ball | 0.465 | | kite | 0.312 | baseball bat | 0.298 | baseball glove | 0.457 | | skateboard | 0.345 | surfboard | 0.376 | tennis racket | 0.571 | | bottle | 0.424 | wine glass | 0.358 | cup | 0.492 | | fork | 0.213 | knife | 0.170 | spoon | 0.164 | | bowl | 0.416 | banana | 0.228 | apple | 0.253 | | sandwich | 0.416 | orange | 0.319 | broccoli | 0.252 | | carrot | 0.233 | hot dog | 0.331 | pizza | 0.518 | | donut | 0.534 | cake | 0.406 | chair | 0.241 | | couch | 0.386 | potted plant | 0.286 | bed | 0.367 | | dining table | 0.188 | toilet | 0.629 | tv | 0.649 | | laptop | 0.656 | mouse | 0.633 | remote | 0.351 | | keyboard | 0.553 | cell phone | 0.401 | microwave | 0.625 | | oven | 0.353 | toaster | 0.442 | sink | 0.402 | | refrigerator | 0.634 | book | 0.135 | clock | 0.515 | | vase | 0.394 | scissors | 0.273 | teddy bear | 0.475 | | hair drier | 0.033 | toothbrush | 0.225 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:42:22,309 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_7.pth was removed 2023-11-13 21:42:23,819 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_8.pth. 2023-11-13 21:42:23,819 - mmdet - INFO - Best bbox_mAP is 0.4559 at 8 epoch. 2023-11-13 21:42:23,819 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 21:42:23,819 - mmdet - INFO - Epoch(val) [8][625] bbox_mAP: 0.4559, bbox_mAP_50: 0.6788, bbox_mAP_75: 0.5079, bbox_mAP_s: 0.2832, bbox_mAP_m: 0.4953, bbox_mAP_l: 0.5992, bbox_mAP_copypaste: 0.4559 0.6788 0.5079 0.2832 0.4953 0.5992, segm_mAP: 0.4146, segm_mAP_50: 0.6492, segm_mAP_75: 0.4459, segm_mAP_s: 0.2121, segm_mAP_m: 0.4449, segm_mAP_l: 0.6049, segm_mAP_copypaste: 0.4146 0.6492 0.4459 0.2121 0.4449 0.6049 2023-11-13 21:42:43,151 - mmdet - INFO - Epoch [9][50/7330] lr: 1.000e-05, eta: 2:30:55, time: 0.386, data_time: 0.090, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0377, loss_cls: 0.1517, acc: 94.3152, loss_bbox: 0.2014, loss_mask: 0.2142, loss: 0.6230 2023-11-13 21:42:58,837 - mmdet - INFO - Epoch [9][100/7330] lr: 1.000e-05, eta: 2:30:39, time: 0.314, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0379, loss_cls: 0.1527, acc: 94.2690, loss_bbox: 0.2017, loss_mask: 0.2121, loss: 0.6221 2023-11-13 21:43:14,502 - mmdet - INFO - Epoch [9][150/7330] lr: 1.000e-05, eta: 2:30:24, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0395, loss_cls: 0.1535, acc: 94.2380, loss_bbox: 0.2034, loss_mask: 0.2094, loss: 0.6247 2023-11-13 21:43:30,682 - mmdet - INFO - Epoch [9][200/7330] lr: 1.000e-05, eta: 2:30:09, time: 0.324, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0387, loss_cls: 0.1579, acc: 93.9497, loss_bbox: 0.2069, loss_mask: 0.2145, loss: 0.6356 2023-11-13 21:43:46,371 - mmdet - INFO - Epoch [9][250/7330] lr: 1.000e-05, eta: 2:29:54, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0382, loss_cls: 0.1597, acc: 94.1245, loss_bbox: 0.2046, loss_mask: 0.2139, loss: 0.6338 2023-11-13 21:44:02,647 - mmdet - INFO - Epoch [9][300/7330] lr: 1.000e-05, eta: 2:29:39, time: 0.326, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0371, loss_cls: 0.1520, acc: 94.2158, loss_bbox: 0.2046, loss_mask: 0.2136, loss: 0.6247 2023-11-13 21:44:18,470 - mmdet - INFO - Epoch [9][350/7330] lr: 1.000e-05, eta: 2:29:23, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0378, loss_cls: 0.1576, acc: 93.9824, loss_bbox: 0.2083, loss_mask: 0.2158, loss: 0.6361 2023-11-13 21:44:34,236 - mmdet - INFO - Epoch [9][400/7330] lr: 1.000e-05, eta: 2:29:08, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0348, loss_cls: 0.1484, acc: 94.4229, loss_bbox: 0.1946, loss_mask: 0.2056, loss: 0.5992 2023-11-13 21:44:49,888 - mmdet - INFO - Epoch [9][450/7330] lr: 1.000e-05, eta: 2:28:53, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0356, loss_cls: 0.1491, acc: 94.3293, loss_bbox: 0.1994, loss_mask: 0.2102, loss: 0.6106 2023-11-13 21:45:05,799 - mmdet - INFO - Epoch [9][500/7330] lr: 1.000e-05, eta: 2:28:37, time: 0.318, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0371, loss_cls: 0.1569, acc: 94.1128, loss_bbox: 0.2028, loss_mask: 0.2099, loss: 0.6247 2023-11-13 21:45:21,334 - mmdet - INFO - Epoch [9][550/7330] lr: 1.000e-05, eta: 2:28:22, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0373, loss_cls: 0.1584, acc: 94.0142, loss_bbox: 0.2072, loss_mask: 0.2108, loss: 0.6293 2023-11-13 21:45:37,205 - mmdet - INFO - Epoch [9][600/7330] lr: 1.000e-05, eta: 2:28:07, time: 0.317, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0367, loss_cls: 0.1599, acc: 94.0308, loss_bbox: 0.2058, loss_mask: 0.2156, loss: 0.6345 2023-11-13 21:45:52,957 - mmdet - INFO - Epoch [9][650/7330] lr: 1.000e-05, eta: 2:27:51, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0368, loss_cls: 0.1554, acc: 94.1233, loss_bbox: 0.2030, loss_mask: 0.2041, loss: 0.6161 2023-11-13 21:46:08,795 - mmdet - INFO - Epoch [9][700/7330] lr: 1.000e-05, eta: 2:27:36, time: 0.317, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0386, loss_cls: 0.1605, acc: 93.8499, loss_bbox: 0.2103, loss_mask: 0.2177, loss: 0.6449 2023-11-13 21:46:24,445 - mmdet - INFO - Epoch [9][750/7330] lr: 1.000e-05, eta: 2:27:21, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0362, loss_cls: 0.1548, acc: 94.0071, loss_bbox: 0.2065, loss_mask: 0.2117, loss: 0.6254 2023-11-13 21:46:40,370 - mmdet - INFO - Epoch [9][800/7330] lr: 1.000e-05, eta: 2:27:05, time: 0.318, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0366, loss_cls: 0.1531, acc: 94.1360, loss_bbox: 0.2025, loss_mask: 0.2151, loss: 0.6245 2023-11-13 21:46:56,086 - mmdet - INFO - Epoch [9][850/7330] lr: 1.000e-05, eta: 2:26:50, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0384, loss_cls: 0.1562, acc: 94.0955, loss_bbox: 0.2090, loss_mask: 0.2126, loss: 0.6346 2023-11-13 21:47:11,901 - mmdet - INFO - Epoch [9][900/7330] lr: 1.000e-05, eta: 2:26:35, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0359, loss_cls: 0.1545, acc: 94.1313, loss_bbox: 0.2017, loss_mask: 0.2115, loss: 0.6198 2023-11-13 21:47:27,075 - mmdet - INFO - Epoch [9][950/7330] lr: 1.000e-05, eta: 2:26:19, time: 0.303, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0368, loss_cls: 0.1556, acc: 94.1045, loss_bbox: 0.2008, loss_mask: 0.2134, loss: 0.6220 2023-11-13 21:47:42,949 - mmdet - INFO - Epoch [9][1000/7330] lr: 1.000e-05, eta: 2:26:04, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0384, loss_cls: 0.1568, acc: 94.0588, loss_bbox: 0.2074, loss_mask: 0.2130, loss: 0.6331 2023-11-13 21:47:58,615 - mmdet - INFO - Epoch [9][1050/7330] lr: 1.000e-05, eta: 2:25:48, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0375, loss_cls: 0.1558, acc: 94.0906, loss_bbox: 0.2044, loss_mask: 0.2123, loss: 0.6272 2023-11-13 21:48:14,177 - mmdet - INFO - Epoch [9][1100/7330] lr: 1.000e-05, eta: 2:25:33, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0372, loss_cls: 0.1516, acc: 94.2627, loss_bbox: 0.2006, loss_mask: 0.2069, loss: 0.6133 2023-11-13 21:48:29,830 - mmdet - INFO - Epoch [9][1150/7330] lr: 1.000e-05, eta: 2:25:18, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0371, loss_cls: 0.1511, acc: 94.2866, loss_bbox: 0.2003, loss_mask: 0.2089, loss: 0.6151 2023-11-13 21:48:45,281 - mmdet - INFO - Epoch [9][1200/7330] lr: 1.000e-05, eta: 2:25:02, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0345, loss_cls: 0.1459, acc: 94.4578, loss_bbox: 0.1994, loss_mask: 0.2124, loss: 0.6074 2023-11-13 21:49:01,192 - mmdet - INFO - Epoch [9][1250/7330] lr: 1.000e-05, eta: 2:24:47, time: 0.318, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0378, loss_cls: 0.1536, acc: 94.1167, loss_bbox: 0.2035, loss_mask: 0.2130, loss: 0.6247 2023-11-13 21:49:17,003 - mmdet - INFO - Epoch [9][1300/7330] lr: 1.000e-05, eta: 2:24:31, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0379, loss_cls: 0.1617, acc: 93.8555, loss_bbox: 0.2101, loss_mask: 0.2151, loss: 0.6419 2023-11-13 21:49:32,843 - mmdet - INFO - Epoch [9][1350/7330] lr: 1.000e-05, eta: 2:24:16, time: 0.317, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0402, loss_cls: 0.1635, acc: 93.7830, loss_bbox: 0.2163, loss_mask: 0.2209, loss: 0.6591 2023-11-13 21:49:48,209 - mmdet - INFO - Epoch [9][1400/7330] lr: 1.000e-05, eta: 2:24:01, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0366, loss_cls: 0.1549, acc: 94.1292, loss_bbox: 0.2009, loss_mask: 0.2113, loss: 0.6213 2023-11-13 21:50:03,801 - mmdet - INFO - Epoch [9][1450/7330] lr: 1.000e-05, eta: 2:23:45, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0383, loss_cls: 0.1610, acc: 93.8596, loss_bbox: 0.2094, loss_mask: 0.2143, loss: 0.6410 2023-11-13 21:50:19,333 - mmdet - INFO - Epoch [9][1500/7330] lr: 1.000e-05, eta: 2:23:30, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0370, loss_cls: 0.1533, acc: 94.2246, loss_bbox: 0.2045, loss_mask: 0.2130, loss: 0.6238 2023-11-13 21:50:34,967 - mmdet - INFO - Epoch [9][1550/7330] lr: 1.000e-05, eta: 2:23:14, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0377, loss_cls: 0.1529, acc: 94.1702, loss_bbox: 0.1987, loss_mask: 0.2085, loss: 0.6143 2023-11-13 21:50:50,218 - mmdet - INFO - Epoch [9][1600/7330] lr: 1.000e-05, eta: 2:22:59, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0350, loss_cls: 0.1488, acc: 94.3396, loss_bbox: 0.1945, loss_mask: 0.2110, loss: 0.6050 2023-11-13 21:51:05,831 - mmdet - INFO - Epoch [9][1650/7330] lr: 1.000e-05, eta: 2:22:43, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0354, loss_cls: 0.1475, acc: 94.3855, loss_bbox: 0.1989, loss_mask: 0.2133, loss: 0.6103 2023-11-13 21:51:21,656 - mmdet - INFO - Epoch [9][1700/7330] lr: 1.000e-05, eta: 2:22:28, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0389, loss_cls: 0.1545, acc: 94.0100, loss_bbox: 0.2049, loss_mask: 0.2101, loss: 0.6269 2023-11-13 21:51:37,420 - mmdet - INFO - Epoch [9][1750/7330] lr: 1.000e-05, eta: 2:22:13, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0388, loss_cls: 0.1548, acc: 94.0884, loss_bbox: 0.2017, loss_mask: 0.2039, loss: 0.6160 2023-11-13 21:51:52,999 - mmdet - INFO - Epoch [9][1800/7330] lr: 1.000e-05, eta: 2:21:57, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0376, loss_cls: 0.1580, acc: 93.9727, loss_bbox: 0.2062, loss_mask: 0.2128, loss: 0.6317 2023-11-13 21:52:08,640 - mmdet - INFO - Epoch [9][1850/7330] lr: 1.000e-05, eta: 2:21:42, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0366, loss_cls: 0.1543, acc: 94.0632, loss_bbox: 0.2065, loss_mask: 0.2118, loss: 0.6246 2023-11-13 21:52:24,091 - mmdet - INFO - Epoch [9][1900/7330] lr: 1.000e-05, eta: 2:21:26, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0362, loss_cls: 0.1546, acc: 94.1206, loss_bbox: 0.2023, loss_mask: 0.2114, loss: 0.6215 2023-11-13 21:52:39,444 - mmdet - INFO - Epoch [9][1950/7330] lr: 1.000e-05, eta: 2:21:11, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0345, loss_cls: 0.1484, acc: 94.3918, loss_bbox: 0.1993, loss_mask: 0.2092, loss: 0.6076 2023-11-13 21:52:55,088 - mmdet - INFO - Epoch [9][2000/7330] lr: 1.000e-05, eta: 2:20:55, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0366, loss_cls: 0.1531, acc: 94.1389, loss_bbox: 0.2005, loss_mask: 0.2139, loss: 0.6212 2023-11-13 21:53:10,846 - mmdet - INFO - Epoch [9][2050/7330] lr: 1.000e-05, eta: 2:20:40, time: 0.315, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0351, loss_cls: 0.1478, acc: 94.3657, loss_bbox: 0.1928, loss_mask: 0.2060, loss: 0.5972 2023-11-13 21:53:26,293 - mmdet - INFO - Epoch [9][2100/7330] lr: 1.000e-05, eta: 2:20:25, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0366, loss_cls: 0.1454, acc: 94.4231, loss_bbox: 0.1946, loss_mask: 0.2050, loss: 0.5982 2023-11-13 21:53:41,910 - mmdet - INFO - Epoch [9][2150/7330] lr: 1.000e-05, eta: 2:20:09, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0368, loss_cls: 0.1524, acc: 94.1362, loss_bbox: 0.2024, loss_mask: 0.2125, loss: 0.6198 2023-11-13 21:53:56,925 - mmdet - INFO - Epoch [9][2200/7330] lr: 1.000e-05, eta: 2:19:54, time: 0.300, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0349, loss_cls: 0.1488, acc: 94.3904, loss_bbox: 0.1963, loss_mask: 0.2088, loss: 0.6042 2023-11-13 21:54:12,608 - mmdet - INFO - Epoch [9][2250/7330] lr: 1.000e-05, eta: 2:19:38, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0365, loss_cls: 0.1477, acc: 94.2239, loss_bbox: 0.2002, loss_mask: 0.2104, loss: 0.6112 2023-11-13 21:54:28,287 - mmdet - INFO - Epoch [9][2300/7330] lr: 1.000e-05, eta: 2:19:23, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0368, loss_cls: 0.1487, acc: 94.3259, loss_bbox: 0.2006, loss_mask: 0.2121, loss: 0.6145 2023-11-13 21:54:43,943 - mmdet - INFO - Epoch [9][2350/7330] lr: 1.000e-05, eta: 2:19:07, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0364, loss_cls: 0.1480, acc: 94.3662, loss_bbox: 0.2001, loss_mask: 0.2096, loss: 0.6097 2023-11-13 21:54:59,321 - mmdet - INFO - Epoch [9][2400/7330] lr: 1.000e-05, eta: 2:18:52, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0344, loss_cls: 0.1430, acc: 94.4951, loss_bbox: 0.1950, loss_mask: 0.2053, loss: 0.5924 2023-11-13 21:55:15,139 - mmdet - INFO - Epoch [9][2450/7330] lr: 1.000e-05, eta: 2:18:36, time: 0.316, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0389, loss_cls: 0.1604, acc: 93.8630, loss_bbox: 0.2155, loss_mask: 0.2144, loss: 0.6469 2023-11-13 21:55:30,410 - mmdet - INFO - Epoch [9][2500/7330] lr: 1.000e-05, eta: 2:18:21, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0378, loss_cls: 0.1538, acc: 94.1401, loss_bbox: 0.2016, loss_mask: 0.2125, loss: 0.6231 2023-11-13 21:55:45,809 - mmdet - INFO - Epoch [9][2550/7330] lr: 1.000e-05, eta: 2:18:05, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0360, loss_cls: 0.1487, acc: 94.3884, loss_bbox: 0.1948, loss_mask: 0.2065, loss: 0.6034 2023-11-13 21:56:01,213 - mmdet - INFO - Epoch [9][2600/7330] lr: 1.000e-05, eta: 2:17:50, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0347, loss_cls: 0.1459, acc: 94.4016, loss_bbox: 0.1911, loss_mask: 0.2075, loss: 0.5950 2023-11-13 21:56:17,207 - mmdet - INFO - Epoch [9][2650/7330] lr: 1.000e-05, eta: 2:17:35, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0361, loss_cls: 0.1556, acc: 94.0479, loss_bbox: 0.2096, loss_mask: 0.2147, loss: 0.6329 2023-11-13 21:56:33,191 - mmdet - INFO - Epoch [9][2700/7330] lr: 1.000e-05, eta: 2:17:19, time: 0.320, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0361, loss_cls: 0.1495, acc: 94.3308, loss_bbox: 0.1979, loss_mask: 0.2120, loss: 0.6119 2023-11-13 21:56:48,530 - mmdet - INFO - Epoch [9][2750/7330] lr: 1.000e-05, eta: 2:17:04, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0365, loss_cls: 0.1504, acc: 94.3237, loss_bbox: 0.1982, loss_mask: 0.2079, loss: 0.6096 2023-11-13 21:57:03,946 - mmdet - INFO - Epoch [9][2800/7330] lr: 1.000e-05, eta: 2:16:48, time: 0.308, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0367, loss_cls: 0.1501, acc: 94.2122, loss_bbox: 0.2019, loss_mask: 0.2101, loss: 0.6131 2023-11-13 21:57:19,563 - mmdet - INFO - Epoch [9][2850/7330] lr: 1.000e-05, eta: 2:16:33, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0355, loss_cls: 0.1450, acc: 94.4541, loss_bbox: 0.1947, loss_mask: 0.2088, loss: 0.6020 2023-11-13 21:57:35,176 - mmdet - INFO - Epoch [9][2900/7330] lr: 1.000e-05, eta: 2:16:18, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0360, loss_cls: 0.1502, acc: 94.2839, loss_bbox: 0.2025, loss_mask: 0.2118, loss: 0.6159 2023-11-13 21:57:50,617 - mmdet - INFO - Epoch [9][2950/7330] lr: 1.000e-05, eta: 2:16:02, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0369, loss_cls: 0.1546, acc: 94.1162, loss_bbox: 0.2022, loss_mask: 0.2115, loss: 0.6224 2023-11-13 21:58:06,221 - mmdet - INFO - Epoch [9][3000/7330] lr: 1.000e-05, eta: 2:15:47, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0392, loss_cls: 0.1590, acc: 93.9668, loss_bbox: 0.2123, loss_mask: 0.2143, loss: 0.6427 2023-11-13 21:58:21,693 - mmdet - INFO - Epoch [9][3050/7330] lr: 1.000e-05, eta: 2:15:31, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0380, loss_cls: 0.1517, acc: 94.2573, loss_bbox: 0.1991, loss_mask: 0.2075, loss: 0.6133 2023-11-13 21:58:37,204 - mmdet - INFO - Epoch [9][3100/7330] lr: 1.000e-05, eta: 2:15:16, time: 0.310, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0362, loss_cls: 0.1508, acc: 94.2656, loss_bbox: 0.2003, loss_mask: 0.2102, loss: 0.6150 2023-11-13 21:58:52,528 - mmdet - INFO - Epoch [9][3150/7330] lr: 1.000e-05, eta: 2:15:00, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0357, loss_cls: 0.1519, acc: 94.1782, loss_bbox: 0.2017, loss_mask: 0.2099, loss: 0.6152 2023-11-13 21:59:07,956 - mmdet - INFO - Epoch [9][3200/7330] lr: 1.000e-05, eta: 2:14:45, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0365, loss_cls: 0.1541, acc: 94.2180, loss_bbox: 0.1995, loss_mask: 0.2069, loss: 0.6136 2023-11-13 21:59:23,253 - mmdet - INFO - Epoch [9][3250/7330] lr: 1.000e-05, eta: 2:14:29, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0365, loss_cls: 0.1516, acc: 94.2856, loss_bbox: 0.2009, loss_mask: 0.2093, loss: 0.6151 2023-11-13 21:59:38,330 - mmdet - INFO - Epoch [9][3300/7330] lr: 1.000e-05, eta: 2:14:13, time: 0.302, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0346, loss_cls: 0.1475, acc: 94.3606, loss_bbox: 0.1978, loss_mask: 0.2060, loss: 0.6019 2023-11-13 21:59:53,654 - mmdet - INFO - Epoch [9][3350/7330] lr: 1.000e-05, eta: 2:13:58, time: 0.306, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0351, loss_cls: 0.1516, acc: 94.2034, loss_bbox: 0.2012, loss_mask: 0.2114, loss: 0.6154 2023-11-13 22:00:08,902 - mmdet - INFO - Epoch [9][3400/7330] lr: 1.000e-05, eta: 2:13:42, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0351, loss_cls: 0.1479, acc: 94.4089, loss_bbox: 0.1983, loss_mask: 0.2093, loss: 0.6066 2023-11-13 22:00:24,234 - mmdet - INFO - Epoch [9][3450/7330] lr: 1.000e-05, eta: 2:13:27, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0351, loss_cls: 0.1511, acc: 94.2986, loss_bbox: 0.2019, loss_mask: 0.2122, loss: 0.6156 2023-11-13 22:00:39,361 - mmdet - INFO - Epoch [9][3500/7330] lr: 1.000e-05, eta: 2:13:11, time: 0.303, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0340, loss_cls: 0.1455, acc: 94.3733, loss_bbox: 0.1928, loss_mask: 0.2071, loss: 0.5940 2023-11-13 22:00:54,731 - mmdet - INFO - Epoch [9][3550/7330] lr: 1.000e-05, eta: 2:12:56, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0371, loss_cls: 0.1546, acc: 94.0962, loss_bbox: 0.2043, loss_mask: 0.2116, loss: 0.6243 2023-11-13 22:01:10,431 - mmdet - INFO - Epoch [9][3600/7330] lr: 1.000e-05, eta: 2:12:40, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0387, loss_cls: 0.1620, acc: 93.8518, loss_bbox: 0.2133, loss_mask: 0.2141, loss: 0.6458 2023-11-13 22:01:26,096 - mmdet - INFO - Epoch [9][3650/7330] lr: 1.000e-05, eta: 2:12:25, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0362, loss_cls: 0.1534, acc: 94.2061, loss_bbox: 0.2036, loss_mask: 0.2138, loss: 0.6234 2023-11-13 22:01:41,327 - mmdet - INFO - Epoch [9][3700/7330] lr: 1.000e-05, eta: 2:12:09, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0351, loss_cls: 0.1424, acc: 94.4778, loss_bbox: 0.1907, loss_mask: 0.2084, loss: 0.5913 2023-11-13 22:01:56,445 - mmdet - INFO - Epoch [9][3750/7330] lr: 1.000e-05, eta: 2:11:54, time: 0.302, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0322, loss_cls: 0.1348, acc: 94.8022, loss_bbox: 0.1842, loss_mask: 0.2056, loss: 0.5710 2023-11-13 22:02:11,745 - mmdet - INFO - Epoch [9][3800/7330] lr: 1.000e-05, eta: 2:11:38, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0366, loss_cls: 0.1532, acc: 94.2563, loss_bbox: 0.1975, loss_mask: 0.2145, loss: 0.6196 2023-11-13 22:02:27,213 - mmdet - INFO - Epoch [9][3850/7330] lr: 1.000e-05, eta: 2:11:23, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0371, loss_cls: 0.1498, acc: 94.2576, loss_bbox: 0.1984, loss_mask: 0.2090, loss: 0.6106 2023-11-13 22:02:42,458 - mmdet - INFO - Epoch [9][3900/7330] lr: 1.000e-05, eta: 2:11:07, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0356, loss_cls: 0.1492, acc: 94.3264, loss_bbox: 0.2025, loss_mask: 0.2088, loss: 0.6122 2023-11-13 22:02:57,791 - mmdet - INFO - Epoch [9][3950/7330] lr: 1.000e-05, eta: 2:10:52, time: 0.307, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0349, loss_cls: 0.1501, acc: 94.2959, loss_bbox: 0.2016, loss_mask: 0.2069, loss: 0.6095 2023-11-13 22:03:13,563 - mmdet - INFO - Epoch [9][4000/7330] lr: 1.000e-05, eta: 2:10:36, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0363, loss_cls: 0.1505, acc: 94.2454, loss_bbox: 0.1990, loss_mask: 0.2064, loss: 0.6089 2023-11-13 22:03:29,099 - mmdet - INFO - Epoch [9][4050/7330] lr: 1.000e-05, eta: 2:10:21, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0375, loss_cls: 0.1481, acc: 94.3042, loss_bbox: 0.1983, loss_mask: 0.2133, loss: 0.6143 2023-11-13 22:03:44,630 - mmdet - INFO - Epoch [9][4100/7330] lr: 1.000e-05, eta: 2:10:05, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0385, loss_cls: 0.1530, acc: 94.1843, loss_bbox: 0.1997, loss_mask: 0.2072, loss: 0.6153 2023-11-13 22:04:00,303 - mmdet - INFO - Epoch [9][4150/7330] lr: 1.000e-05, eta: 2:09:50, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0390, loss_cls: 0.1551, acc: 94.1011, loss_bbox: 0.2050, loss_mask: 0.2119, loss: 0.6279 2023-11-13 22:04:15,757 - mmdet - INFO - Epoch [9][4200/7330] lr: 1.000e-05, eta: 2:09:34, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0352, loss_cls: 0.1508, acc: 94.3367, loss_bbox: 0.1991, loss_mask: 0.2104, loss: 0.6121 2023-11-13 22:04:31,120 - mmdet - INFO - Epoch [9][4250/7330] lr: 1.000e-05, eta: 2:09:19, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0373, loss_cls: 0.1494, acc: 94.3083, loss_bbox: 0.2043, loss_mask: 0.2126, loss: 0.6200 2023-11-13 22:04:46,792 - mmdet - INFO - Epoch [9][4300/7330] lr: 1.000e-05, eta: 2:09:03, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0378, loss_cls: 0.1551, acc: 94.0339, loss_bbox: 0.2047, loss_mask: 0.2110, loss: 0.6279 2023-11-13 22:05:02,144 - mmdet - INFO - Epoch [9][4350/7330] lr: 1.000e-05, eta: 2:08:48, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0338, loss_cls: 0.1455, acc: 94.4968, loss_bbox: 0.1944, loss_mask: 0.2090, loss: 0.5978 2023-11-13 22:05:17,467 - mmdet - INFO - Epoch [9][4400/7330] lr: 1.000e-05, eta: 2:08:32, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0356, loss_cls: 0.1546, acc: 94.1150, loss_bbox: 0.2035, loss_mask: 0.2121, loss: 0.6218 2023-11-13 22:05:33,103 - mmdet - INFO - Epoch [9][4450/7330] lr: 1.000e-05, eta: 2:08:17, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0362, loss_cls: 0.1505, acc: 94.3472, loss_bbox: 0.1971, loss_mask: 0.2072, loss: 0.6075 2023-11-13 22:05:48,516 - mmdet - INFO - Epoch [9][4500/7330] lr: 1.000e-05, eta: 2:08:02, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0372, loss_cls: 0.1526, acc: 94.1487, loss_bbox: 0.2026, loss_mask: 0.2095, loss: 0.6194 2023-11-13 22:06:03,955 - mmdet - INFO - Epoch [9][4550/7330] lr: 1.000e-05, eta: 2:07:46, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0369, loss_cls: 0.1453, acc: 94.4148, loss_bbox: 0.1986, loss_mask: 0.2081, loss: 0.6048 2023-11-13 22:06:19,392 - mmdet - INFO - Epoch [9][4600/7330] lr: 1.000e-05, eta: 2:07:31, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0353, loss_cls: 0.1496, acc: 94.2944, loss_bbox: 0.2011, loss_mask: 0.2118, loss: 0.6126 2023-11-13 22:06:35,126 - mmdet - INFO - Epoch [9][4650/7330] lr: 1.000e-05, eta: 2:07:15, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0375, loss_cls: 0.1503, acc: 94.3193, loss_bbox: 0.2008, loss_mask: 0.2058, loss: 0.6114 2023-11-13 22:06:50,677 - mmdet - INFO - Epoch [9][4700/7330] lr: 1.000e-05, eta: 2:07:00, time: 0.311, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0369, loss_cls: 0.1515, acc: 94.1814, loss_bbox: 0.2028, loss_mask: 0.2126, loss: 0.6201 2023-11-13 22:07:06,467 - mmdet - INFO - Epoch [9][4750/7330] lr: 1.000e-05, eta: 2:06:44, time: 0.316, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0364, loss_cls: 0.1538, acc: 94.2310, loss_bbox: 0.2061, loss_mask: 0.2093, loss: 0.6221 2023-11-13 22:07:21,883 - mmdet - INFO - Epoch [9][4800/7330] lr: 1.000e-05, eta: 2:06:29, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0365, loss_cls: 0.1519, acc: 94.2510, loss_bbox: 0.1987, loss_mask: 0.2080, loss: 0.6108 2023-11-13 22:07:37,533 - mmdet - INFO - Epoch [9][4850/7330] lr: 1.000e-05, eta: 2:06:13, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0357, loss_cls: 0.1494, acc: 94.2983, loss_bbox: 0.1951, loss_mask: 0.2069, loss: 0.6053 2023-11-13 22:07:53,146 - mmdet - INFO - Epoch [9][4900/7330] lr: 1.000e-05, eta: 2:05:58, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0380, loss_cls: 0.1572, acc: 93.9463, loss_bbox: 0.2044, loss_mask: 0.2125, loss: 0.6294 2023-11-13 22:08:08,759 - mmdet - INFO - Epoch [9][4950/7330] lr: 1.000e-05, eta: 2:05:43, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0373, loss_cls: 0.1544, acc: 94.1531, loss_bbox: 0.2071, loss_mask: 0.2097, loss: 0.6251 2023-11-13 22:08:24,058 - mmdet - INFO - Epoch [9][5000/7330] lr: 1.000e-05, eta: 2:05:27, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0352, loss_cls: 0.1541, acc: 94.1057, loss_bbox: 0.2033, loss_mask: 0.2130, loss: 0.6213 2023-11-13 22:08:39,650 - mmdet - INFO - Epoch [9][5050/7330] lr: 1.000e-05, eta: 2:05:12, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0367, loss_cls: 0.1592, acc: 93.9258, loss_bbox: 0.2071, loss_mask: 0.2180, loss: 0.6370 2023-11-13 22:08:55,565 - mmdet - INFO - Epoch [9][5100/7330] lr: 1.000e-05, eta: 2:04:56, time: 0.318, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0400, loss_cls: 0.1642, acc: 93.6731, loss_bbox: 0.2176, loss_mask: 0.2176, loss: 0.6574 2023-11-13 22:09:10,964 - mmdet - INFO - Epoch [9][5150/7330] lr: 1.000e-05, eta: 2:04:41, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0351, loss_cls: 0.1494, acc: 94.2969, loss_bbox: 0.2000, loss_mask: 0.2121, loss: 0.6118 2023-11-13 22:09:26,335 - mmdet - INFO - Epoch [9][5200/7330] lr: 1.000e-05, eta: 2:04:25, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0344, loss_cls: 0.1466, acc: 94.5168, loss_bbox: 0.1945, loss_mask: 0.2061, loss: 0.5982 2023-11-13 22:09:41,510 - mmdet - INFO - Epoch [9][5250/7330] lr: 1.000e-05, eta: 2:04:10, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0357, loss_cls: 0.1471, acc: 94.3770, loss_bbox: 0.1967, loss_mask: 0.2091, loss: 0.6047 2023-11-13 22:09:56,828 - mmdet - INFO - Epoch [9][5300/7330] lr: 1.000e-05, eta: 2:03:54, time: 0.306, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0334, loss_cls: 0.1427, acc: 94.5574, loss_bbox: 0.1943, loss_mask: 0.2086, loss: 0.5930 2023-11-13 22:10:12,229 - mmdet - INFO - Epoch [9][5350/7330] lr: 1.000e-05, eta: 2:03:39, time: 0.308, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0348, loss_cls: 0.1408, acc: 94.5845, loss_bbox: 0.1921, loss_mask: 0.2109, loss: 0.5939 2023-11-13 22:10:27,597 - mmdet - INFO - Epoch [9][5400/7330] lr: 1.000e-05, eta: 2:03:23, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0364, loss_cls: 0.1535, acc: 94.1509, loss_bbox: 0.2020, loss_mask: 0.2065, loss: 0.6145 2023-11-13 22:10:43,370 - mmdet - INFO - Epoch [9][5450/7330] lr: 1.000e-05, eta: 2:03:08, time: 0.315, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0355, loss_cls: 0.1450, acc: 94.3884, loss_bbox: 0.1950, loss_mask: 0.2052, loss: 0.5963 2023-11-13 22:10:59,160 - mmdet - INFO - Epoch [9][5500/7330] lr: 1.000e-05, eta: 2:02:52, time: 0.316, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0361, loss_cls: 0.1576, acc: 93.9856, loss_bbox: 0.2051, loss_mask: 0.2138, loss: 0.6292 2023-11-13 22:11:14,357 - mmdet - INFO - Epoch [9][5550/7330] lr: 1.000e-05, eta: 2:02:37, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0374, loss_cls: 0.1472, acc: 94.3486, loss_bbox: 0.2023, loss_mask: 0.2149, loss: 0.6167 2023-11-13 22:11:29,902 - mmdet - INFO - Epoch [9][5600/7330] lr: 1.000e-05, eta: 2:02:21, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0402, loss_cls: 0.1566, acc: 94.0710, loss_bbox: 0.2076, loss_mask: 0.2087, loss: 0.6303 2023-11-13 22:11:45,245 - mmdet - INFO - Epoch [9][5650/7330] lr: 1.000e-05, eta: 2:02:06, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0369, loss_cls: 0.1521, acc: 94.2693, loss_bbox: 0.2062, loss_mask: 0.2132, loss: 0.6272 2023-11-13 22:12:00,609 - mmdet - INFO - Epoch [9][5700/7330] lr: 1.000e-05, eta: 2:01:50, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0370, loss_cls: 0.1514, acc: 94.3042, loss_bbox: 0.1981, loss_mask: 0.2060, loss: 0.6097 2023-11-13 22:12:16,410 - mmdet - INFO - Epoch [9][5750/7330] lr: 1.000e-05, eta: 2:01:35, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0391, loss_cls: 0.1518, acc: 94.2441, loss_bbox: 0.2025, loss_mask: 0.2135, loss: 0.6243 2023-11-13 22:12:31,868 - mmdet - INFO - Epoch [9][5800/7330] lr: 1.000e-05, eta: 2:01:20, time: 0.309, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0352, loss_cls: 0.1431, acc: 94.5278, loss_bbox: 0.1956, loss_mask: 0.2073, loss: 0.5986 2023-11-13 22:12:47,212 - mmdet - INFO - Epoch [9][5850/7330] lr: 1.000e-05, eta: 2:01:04, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0354, loss_cls: 0.1469, acc: 94.3186, loss_bbox: 0.1989, loss_mask: 0.2124, loss: 0.6100 2023-11-13 22:13:02,549 - mmdet - INFO - Epoch [9][5900/7330] lr: 1.000e-05, eta: 2:00:48, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0356, loss_cls: 0.1453, acc: 94.4917, loss_bbox: 0.1925, loss_mask: 0.1996, loss: 0.5895 2023-11-13 22:13:18,233 - mmdet - INFO - Epoch [9][5950/7330] lr: 1.000e-05, eta: 2:00:33, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0359, loss_cls: 0.1495, acc: 94.2263, loss_bbox: 0.2010, loss_mask: 0.2130, loss: 0.6157 2023-11-13 22:13:33,461 - mmdet - INFO - Epoch [9][6000/7330] lr: 1.000e-05, eta: 2:00:17, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0333, loss_cls: 0.1428, acc: 94.5947, loss_bbox: 0.1892, loss_mask: 0.2055, loss: 0.5867 2023-11-13 22:13:48,927 - mmdet - INFO - Epoch [9][6050/7330] lr: 1.000e-05, eta: 2:00:02, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0359, loss_cls: 0.1466, acc: 94.3630, loss_bbox: 0.1966, loss_mask: 0.2085, loss: 0.6040 2023-11-13 22:14:04,868 - mmdet - INFO - Epoch [9][6100/7330] lr: 1.000e-05, eta: 1:59:47, time: 0.319, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0382, loss_cls: 0.1534, acc: 94.0725, loss_bbox: 0.2041, loss_mask: 0.2115, loss: 0.6238 2023-11-13 22:14:20,144 - mmdet - INFO - Epoch [9][6150/7330] lr: 1.000e-05, eta: 1:59:31, time: 0.306, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0361, loss_cls: 0.1431, acc: 94.5464, loss_bbox: 0.1887, loss_mask: 0.2082, loss: 0.5914 2023-11-13 22:14:35,435 - mmdet - INFO - Epoch [9][6200/7330] lr: 1.000e-05, eta: 1:59:16, time: 0.306, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0343, loss_cls: 0.1444, acc: 94.4275, loss_bbox: 0.1962, loss_mask: 0.2082, loss: 0.5996 2023-11-13 22:14:50,967 - mmdet - INFO - Epoch [9][6250/7330] lr: 1.000e-05, eta: 1:59:00, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0343, loss_cls: 0.1426, acc: 94.6238, loss_bbox: 0.1908, loss_mask: 0.2051, loss: 0.5880 2023-11-13 22:15:06,140 - mmdet - INFO - Epoch [9][6300/7330] lr: 1.000e-05, eta: 1:58:45, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0357, loss_cls: 0.1473, acc: 94.4075, loss_bbox: 0.1953, loss_mask: 0.2085, loss: 0.6020 2023-11-13 22:15:21,541 - mmdet - INFO - Epoch [9][6350/7330] lr: 1.000e-05, eta: 1:58:29, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0375, loss_cls: 0.1569, acc: 93.9358, loss_bbox: 0.2087, loss_mask: 0.2132, loss: 0.6327 2023-11-13 22:15:37,172 - mmdet - INFO - Epoch [9][6400/7330] lr: 1.000e-05, eta: 1:58:14, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0369, loss_cls: 0.1519, acc: 94.2434, loss_bbox: 0.2039, loss_mask: 0.2096, loss: 0.6187 2023-11-13 22:15:52,405 - mmdet - INFO - Epoch [9][6450/7330] lr: 1.000e-05, eta: 1:57:58, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0336, loss_cls: 0.1424, acc: 94.5647, loss_bbox: 0.1957, loss_mask: 0.2081, loss: 0.5943 2023-11-13 22:16:08,480 - mmdet - INFO - Epoch [9][6500/7330] lr: 1.000e-05, eta: 1:57:43, time: 0.321, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0377, loss_cls: 0.1559, acc: 94.0117, loss_bbox: 0.2092, loss_mask: 0.2125, loss: 0.6317 2023-11-13 22:16:23,768 - mmdet - INFO - Epoch [9][6550/7330] lr: 1.000e-05, eta: 1:57:27, time: 0.306, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0324, loss_cls: 0.1420, acc: 94.5654, loss_bbox: 0.1889, loss_mask: 0.2018, loss: 0.5804 2023-11-13 22:16:39,077 - mmdet - INFO - Epoch [9][6600/7330] lr: 1.000e-05, eta: 1:57:12, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0356, loss_cls: 0.1453, acc: 94.4590, loss_bbox: 0.1921, loss_mask: 0.2070, loss: 0.5967 2023-11-13 22:16:54,373 - mmdet - INFO - Epoch [9][6650/7330] lr: 1.000e-05, eta: 1:56:56, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0357, loss_cls: 0.1481, acc: 94.2849, loss_bbox: 0.1963, loss_mask: 0.2072, loss: 0.6029 2023-11-13 22:17:09,671 - mmdet - INFO - Epoch [9][6700/7330] lr: 1.000e-05, eta: 1:56:41, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0345, loss_cls: 0.1524, acc: 94.2598, loss_bbox: 0.2000, loss_mask: 0.2133, loss: 0.6162 2023-11-13 22:17:25,167 - mmdet - INFO - Epoch [9][6750/7330] lr: 1.000e-05, eta: 1:56:25, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0367, loss_cls: 0.1534, acc: 94.1702, loss_bbox: 0.2062, loss_mask: 0.2105, loss: 0.6226 2023-11-13 22:17:41,097 - mmdet - INFO - Epoch [9][6800/7330] lr: 1.000e-05, eta: 1:56:10, time: 0.319, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0395, loss_cls: 0.1617, acc: 93.9080, loss_bbox: 0.2145, loss_mask: 0.2154, loss: 0.6484 2023-11-13 22:17:56,477 - mmdet - INFO - Epoch [9][6850/7330] lr: 1.000e-05, eta: 1:55:54, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0346, loss_cls: 0.1500, acc: 94.3875, loss_bbox: 0.1981, loss_mask: 0.2085, loss: 0.6065 2023-11-13 22:18:11,952 - mmdet - INFO - Epoch [9][6900/7330] lr: 1.000e-05, eta: 1:55:39, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0340, loss_cls: 0.1447, acc: 94.5156, loss_bbox: 0.1945, loss_mask: 0.2078, loss: 0.5955 2023-11-13 22:18:27,568 - mmdet - INFO - Epoch [9][6950/7330] lr: 1.000e-05, eta: 1:55:23, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0372, loss_cls: 0.1474, acc: 94.3733, loss_bbox: 0.1998, loss_mask: 0.2088, loss: 0.6097 2023-11-13 22:18:42,933 - mmdet - INFO - Epoch [9][7000/7330] lr: 1.000e-05, eta: 1:55:08, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0365, loss_cls: 0.1550, acc: 94.1323, loss_bbox: 0.2029, loss_mask: 0.2092, loss: 0.6205 2023-11-13 22:18:58,084 - mmdet - INFO - Epoch [9][7050/7330] lr: 1.000e-05, eta: 1:54:52, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0352, loss_cls: 0.1509, acc: 94.2212, loss_bbox: 0.2024, loss_mask: 0.2144, loss: 0.6180 2023-11-13 22:19:13,600 - mmdet - INFO - Epoch [9][7100/7330] lr: 1.000e-05, eta: 1:54:37, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0382, loss_cls: 0.1519, acc: 94.2000, loss_bbox: 0.2008, loss_mask: 0.2106, loss: 0.6183 2023-11-13 22:19:29,078 - mmdet - INFO - Epoch [9][7150/7330] lr: 1.000e-05, eta: 1:54:21, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0361, loss_cls: 0.1454, acc: 94.4231, loss_bbox: 0.1988, loss_mask: 0.2082, loss: 0.6049 2023-11-13 22:19:44,547 - mmdet - INFO - Epoch [9][7200/7330] lr: 1.000e-05, eta: 1:54:06, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0381, loss_cls: 0.1498, acc: 94.2600, loss_bbox: 0.2007, loss_mask: 0.2114, loss: 0.6159 2023-11-13 22:20:00,068 - mmdet - INFO - Epoch [9][7250/7330] lr: 1.000e-05, eta: 1:53:50, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0363, loss_cls: 0.1530, acc: 94.1877, loss_bbox: 0.2040, loss_mask: 0.2131, loss: 0.6228 2023-11-13 22:20:15,354 - mmdet - INFO - Epoch [9][7300/7330] lr: 1.000e-05, eta: 1:53:35, time: 0.306, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0340, loss_cls: 0.1407, acc: 94.5842, loss_bbox: 0.1877, loss_mask: 0.2081, loss: 0.5865 2023-11-13 22:20:25,065 - mmdet - INFO - Saving checkpoint at 9 epochs 2023-11-13 22:21:06,351 - mmdet - INFO - Evaluating bbox... 2023-11-13 22:21:36,412 - 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 ] = 0.694 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.525 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.303 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 ] = 0.629 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.409 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.641 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.748 2023-11-13 22:21:36,414 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.579 | bicycle | 0.369 | car | 0.482 | | motorcycle | 0.487 | airplane | 0.719 | bus | 0.691 | | train | 0.694 | truck | 0.432 | boat | 0.328 | | traffic light | 0.308 | fire hydrant | 0.744 | stop sign | 0.708 | | parking meter | 0.504 | bench | 0.301 | bird | 0.409 | | cat | 0.733 | dog | 0.694 | horse | 0.609 | | sheep | 0.573 | cow | 0.638 | elephant | 0.674 | | bear | 0.747 | zebra | 0.705 | giraffe | 0.704 | | backpack | 0.217 | umbrella | 0.459 | handbag | 0.219 | | tie | 0.378 | suitcase | 0.472 | frisbee | 0.712 | | skis | 0.310 | snowboard | 0.435 | sports ball | 0.484 | | kite | 0.467 | baseball bat | 0.401 | baseball glove | 0.427 | | skateboard | 0.580 | surfboard | 0.459 | tennis racket | 0.530 | | bottle | 0.459 | wine glass | 0.421 | cup | 0.505 | | fork | 0.445 | knife | 0.287 | spoon | 0.255 | | bowl | 0.458 | banana | 0.289 | apple | 0.276 | | sandwich | 0.421 | orange | 0.365 | broccoli | 0.270 | | carrot | 0.260 | hot dog | 0.450 | pizza | 0.543 | | donut | 0.563 | cake | 0.430 | chair | 0.351 | | couch | 0.478 | potted plant | 0.345 | bed | 0.479 | | dining table | 0.321 | toilet | 0.670 | tv | 0.633 | | laptop | 0.665 | mouse | 0.642 | remote | 0.409 | | keyboard | 0.598 | cell phone | 0.445 | microwave | 0.626 | | oven | 0.390 | toaster | 0.465 | sink | 0.441 | | refrigerator | 0.640 | book | 0.196 | clock | 0.529 | | vase | 0.426 | scissors | 0.415 | teddy bear | 0.516 | | hair drier | 0.180 | toothbrush | 0.331 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:21:36,414 - mmdet - INFO - Evaluating segm... 2023-11-13 22:22:07,206 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.430 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.667 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.463 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.461 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.621 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.545 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.545 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.545 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.354 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 ] = 0.705 2023-11-13 22:22:07,209 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.504 | bicycle | 0.226 | car | 0.444 | | motorcycle | 0.391 | airplane | 0.570 | bus | 0.675 | | train | 0.670 | truck | 0.417 | boat | 0.295 | | traffic light | 0.292 | fire hydrant | 0.709 | stop sign | 0.684 | | parking meter | 0.501 | bench | 0.225 | bird | 0.346 | | cat | 0.721 | dog | 0.642 | horse | 0.449 | | sheep | 0.520 | cow | 0.543 | elephant | 0.624 | | bear | 0.740 | zebra | 0.601 | giraffe | 0.548 | | backpack | 0.219 | umbrella | 0.515 | handbag | 0.217 | | tie | 0.352 | suitcase | 0.489 | frisbee | 0.682 | | skis | 0.060 | snowboard | 0.279 | sports ball | 0.479 | | kite | 0.330 | baseball bat | 0.307 | baseball glove | 0.458 | | skateboard | 0.364 | surfboard | 0.400 | tennis racket | 0.590 | | bottle | 0.438 | wine glass | 0.374 | cup | 0.502 | | fork | 0.234 | knife | 0.198 | spoon | 0.174 | | bowl | 0.430 | banana | 0.241 | apple | 0.267 | | sandwich | 0.446 | orange | 0.363 | broccoli | 0.251 | | carrot | 0.231 | hot dog | 0.343 | pizza | 0.531 | | donut | 0.558 | cake | 0.435 | chair | 0.249 | | couch | 0.406 | potted plant | 0.294 | bed | 0.407 | | dining table | 0.196 | toilet | 0.639 | tv | 0.661 | | laptop | 0.661 | mouse | 0.632 | remote | 0.380 | | keyboard | 0.574 | cell phone | 0.414 | microwave | 0.639 | | oven | 0.367 | toaster | 0.492 | sink | 0.414 | | refrigerator | 0.652 | book | 0.143 | clock | 0.533 | | vase | 0.416 | scissors | 0.326 | teddy bear | 0.493 | | hair drier | 0.085 | toothbrush | 0.240 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:22:07,658 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_8.pth was removed 2023-11-13 22:22:09,112 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_9.pth. 2023-11-13 22:22:09,112 - mmdet - INFO - Best bbox_mAP is 0.4784 at 9 epoch. 2023-11-13 22:22:09,112 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 22:22:09,113 - mmdet - INFO - Epoch(val) [9][625] bbox_mAP: 0.4784, bbox_mAP_50: 0.6938, bbox_mAP_75: 0.5252, bbox_mAP_s: 0.3027, bbox_mAP_m: 0.5172, bbox_mAP_l: 0.6292, bbox_mAP_copypaste: 0.4784 0.6938 0.5252 0.3027 0.5172 0.6292, segm_mAP: 0.4301, segm_mAP_50: 0.6668, segm_mAP_75: 0.4628, segm_mAP_s: 0.2246, segm_mAP_m: 0.4608, segm_mAP_l: 0.6205, segm_mAP_copypaste: 0.4301 0.6668 0.4628 0.2246 0.4608 0.6205 2023-11-13 22:22:29,286 - mmdet - INFO - Epoch [10][50/7330] lr: 1.000e-05, eta: 1:53:09, time: 0.403, data_time: 0.097, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0379, loss_cls: 0.1575, acc: 93.9878, loss_bbox: 0.2095, loss_mask: 0.2121, loss: 0.6342 2023-11-13 22:22:45,530 - mmdet - INFO - Epoch [10][100/7330] lr: 1.000e-05, eta: 1:52:53, time: 0.325, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0366, loss_cls: 0.1424, acc: 94.5928, loss_bbox: 0.1853, loss_mask: 0.2027, loss: 0.5838 2023-11-13 22:23:01,850 - mmdet - INFO - Epoch [10][150/7330] lr: 1.000e-05, eta: 1:52:38, time: 0.326, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0369, loss_cls: 0.1507, acc: 94.3066, loss_bbox: 0.2036, loss_mask: 0.2137, loss: 0.6222 2023-11-13 22:23:17,871 - mmdet - INFO - Epoch [10][200/7330] lr: 1.000e-05, eta: 1:52:23, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0368, loss_cls: 0.1503, acc: 94.2498, loss_bbox: 0.1981, loss_mask: 0.2118, loss: 0.6127 2023-11-13 22:23:33,675 - mmdet - INFO - Epoch [10][250/7330] lr: 1.000e-05, eta: 1:52:08, time: 0.316, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0353, loss_cls: 0.1469, acc: 94.3821, loss_bbox: 0.1988, loss_mask: 0.2103, loss: 0.6065 2023-11-13 22:23:49,408 - mmdet - INFO - Epoch [10][300/7330] lr: 1.000e-05, eta: 1:51:52, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0370, loss_cls: 0.1449, acc: 94.4783, loss_bbox: 0.1960, loss_mask: 0.2121, loss: 0.6067 2023-11-13 22:24:05,484 - mmdet - INFO - Epoch [10][350/7330] lr: 1.000e-05, eta: 1:51:37, time: 0.321, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0371, loss_cls: 0.1501, acc: 94.3333, loss_bbox: 0.1982, loss_mask: 0.2079, loss: 0.6111 2023-11-13 22:24:21,484 - mmdet - INFO - Epoch [10][400/7330] lr: 1.000e-05, eta: 1:51:22, time: 0.320, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0359, loss_cls: 0.1528, acc: 94.1926, loss_bbox: 0.2025, loss_mask: 0.2108, loss: 0.6185 2023-11-13 22:24:37,022 - mmdet - INFO - Epoch [10][450/7330] lr: 1.000e-05, eta: 1:51:06, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0317, loss_cls: 0.1365, acc: 94.7668, loss_bbox: 0.1864, loss_mask: 0.2026, loss: 0.5715 2023-11-13 22:24:52,710 - mmdet - INFO - Epoch [10][500/7330] lr: 1.000e-05, eta: 1:50:51, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0332, loss_cls: 0.1413, acc: 94.5779, loss_bbox: 0.1907, loss_mask: 0.2039, loss: 0.5839 2023-11-13 22:25:08,670 - mmdet - INFO - Epoch [10][550/7330] lr: 1.000e-05, eta: 1:50:35, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0334, loss_cls: 0.1400, acc: 94.6526, loss_bbox: 0.1927, loss_mask: 0.2077, loss: 0.5876 2023-11-13 22:25:24,276 - mmdet - INFO - Epoch [10][600/7330] lr: 1.000e-05, eta: 1:50:20, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0358, loss_cls: 0.1427, acc: 94.6089, loss_bbox: 0.1917, loss_mask: 0.2025, loss: 0.5875 2023-11-13 22:25:39,926 - mmdet - INFO - Epoch [10][650/7330] lr: 1.000e-05, eta: 1:50:05, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0350, loss_cls: 0.1465, acc: 94.3130, loss_bbox: 0.1994, loss_mask: 0.2111, loss: 0.6078 2023-11-13 22:25:55,921 - mmdet - INFO - Epoch [10][700/7330] lr: 1.000e-05, eta: 1:49:49, time: 0.320, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0370, loss_cls: 0.1444, acc: 94.5325, loss_bbox: 0.1948, loss_mask: 0.2091, loss: 0.6022 2023-11-13 22:26:11,815 - mmdet - INFO - Epoch [10][750/7330] lr: 1.000e-05, eta: 1:49:34, time: 0.318, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0348, loss_cls: 0.1414, acc: 94.7275, loss_bbox: 0.1919, loss_mask: 0.2067, loss: 0.5912 2023-11-13 22:26:27,578 - mmdet - INFO - Epoch [10][800/7330] lr: 1.000e-05, eta: 1:49:19, time: 0.315, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0358, loss_cls: 0.1410, acc: 94.6204, loss_bbox: 0.1900, loss_mask: 0.2089, loss: 0.5925 2023-11-13 22:26:43,208 - mmdet - INFO - Epoch [10][850/7330] lr: 1.000e-05, eta: 1:49:03, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0333, loss_cls: 0.1453, acc: 94.4355, loss_bbox: 0.1967, loss_mask: 0.2056, loss: 0.5960 2023-11-13 22:26:58,677 - mmdet - INFO - Epoch [10][900/7330] lr: 1.000e-05, eta: 1:48:48, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0356, loss_cls: 0.1497, acc: 94.3054, loss_bbox: 0.1978, loss_mask: 0.2071, loss: 0.6077 2023-11-13 22:27:14,351 - mmdet - INFO - Epoch [10][950/7330] lr: 1.000e-05, eta: 1:48:32, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0353, loss_cls: 0.1496, acc: 94.2239, loss_bbox: 0.2009, loss_mask: 0.2077, loss: 0.6084 2023-11-13 22:27:30,202 - mmdet - INFO - Epoch [10][1000/7330] lr: 1.000e-05, eta: 1:48:17, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0375, loss_cls: 0.1531, acc: 94.1653, loss_bbox: 0.2022, loss_mask: 0.2107, loss: 0.6208 2023-11-13 22:27:46,403 - mmdet - INFO - Epoch [10][1050/7330] lr: 1.000e-05, eta: 1:48:02, time: 0.324, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0359, loss_cls: 0.1475, acc: 94.3098, loss_bbox: 0.2010, loss_mask: 0.2075, loss: 0.6083 2023-11-13 22:28:01,910 - mmdet - INFO - Epoch [10][1100/7330] lr: 1.000e-05, eta: 1:47:46, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0352, loss_cls: 0.1491, acc: 94.3225, loss_bbox: 0.1969, loss_mask: 0.2051, loss: 0.6020 2023-11-13 22:28:17,351 - mmdet - INFO - Epoch [10][1150/7330] lr: 1.000e-05, eta: 1:47:31, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0360, loss_cls: 0.1468, acc: 94.4424, loss_bbox: 0.2001, loss_mask: 0.2113, loss: 0.6098 2023-11-13 22:28:32,888 - mmdet - INFO - Epoch [10][1200/7330] lr: 1.000e-05, eta: 1:47:15, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0338, loss_cls: 0.1428, acc: 94.5344, loss_bbox: 0.1891, loss_mask: 0.2070, loss: 0.5861 2023-11-13 22:28:48,344 - mmdet - INFO - Epoch [10][1250/7330] lr: 1.000e-05, eta: 1:47:00, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0339, loss_cls: 0.1378, acc: 94.7078, loss_bbox: 0.1914, loss_mask: 0.2064, loss: 0.5836 2023-11-13 22:29:03,610 - mmdet - INFO - Epoch [10][1300/7330] lr: 1.000e-05, eta: 1:46:44, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0348, loss_cls: 0.1499, acc: 94.2910, loss_bbox: 0.1989, loss_mask: 0.2127, loss: 0.6124 2023-11-13 22:29:19,591 - mmdet - INFO - Epoch [10][1350/7330] lr: 1.000e-05, eta: 1:46:29, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0371, loss_cls: 0.1497, acc: 94.3091, loss_bbox: 0.1964, loss_mask: 0.2081, loss: 0.6075 2023-11-13 22:29:35,405 - mmdet - INFO - Epoch [10][1400/7330] lr: 1.000e-05, eta: 1:46:13, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0356, loss_cls: 0.1464, acc: 94.4436, loss_bbox: 0.1952, loss_mask: 0.2062, loss: 0.5984 2023-11-13 22:29:50,993 - mmdet - INFO - Epoch [10][1450/7330] lr: 1.000e-05, eta: 1:45:58, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0356, loss_cls: 0.1477, acc: 94.2637, loss_bbox: 0.1983, loss_mask: 0.2047, loss: 0.6021 2023-11-13 22:30:06,385 - mmdet - INFO - Epoch [10][1500/7330] lr: 1.000e-05, eta: 1:45:43, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0368, loss_cls: 0.1508, acc: 94.1287, loss_bbox: 0.2018, loss_mask: 0.2060, loss: 0.6104 2023-11-13 22:30:22,006 - mmdet - INFO - Epoch [10][1550/7330] lr: 1.000e-05, eta: 1:45:27, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0367, loss_cls: 0.1498, acc: 94.2500, loss_bbox: 0.1999, loss_mask: 0.2080, loss: 0.6109 2023-11-13 22:30:37,079 - mmdet - INFO - Epoch [10][1600/7330] lr: 1.000e-05, eta: 1:45:11, time: 0.301, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0330, loss_cls: 0.1343, acc: 94.9268, loss_bbox: 0.1842, loss_mask: 0.2018, loss: 0.5669 2023-11-13 22:30:52,442 - mmdet - INFO - Epoch [10][1650/7330] lr: 1.000e-05, eta: 1:44:56, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0330, loss_cls: 0.1386, acc: 94.7197, loss_bbox: 0.1874, loss_mask: 0.2017, loss: 0.5754 2023-11-13 22:31:08,236 - mmdet - INFO - Epoch [10][1700/7330] lr: 1.000e-05, eta: 1:44:41, time: 0.316, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0353, loss_cls: 0.1419, acc: 94.5469, loss_bbox: 0.1910, loss_mask: 0.2064, loss: 0.5894 2023-11-13 22:31:23,516 - mmdet - INFO - Epoch [10][1750/7330] lr: 1.000e-05, eta: 1:44:25, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0370, loss_cls: 0.1463, acc: 94.3774, loss_bbox: 0.1986, loss_mask: 0.2107, loss: 0.6078 2023-11-13 22:31:39,104 - mmdet - INFO - Epoch [10][1800/7330] lr: 1.000e-05, eta: 1:44:10, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0364, loss_cls: 0.1487, acc: 94.3184, loss_bbox: 0.1949, loss_mask: 0.2072, loss: 0.6043 2023-11-13 22:31:54,712 - mmdet - INFO - Epoch [10][1850/7330] lr: 1.000e-05, eta: 1:43:54, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0356, loss_cls: 0.1455, acc: 94.4531, loss_bbox: 0.1956, loss_mask: 0.2092, loss: 0.6023 2023-11-13 22:32:09,951 - mmdet - INFO - Epoch [10][1900/7330] lr: 1.000e-05, eta: 1:43:39, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0343, loss_cls: 0.1419, acc: 94.6416, loss_bbox: 0.1888, loss_mask: 0.2057, loss: 0.5841 2023-11-13 22:32:25,176 - mmdet - INFO - Epoch [10][1950/7330] lr: 1.000e-05, eta: 1:43:23, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0335, loss_cls: 0.1427, acc: 94.5974, loss_bbox: 0.1928, loss_mask: 0.2051, loss: 0.5890 2023-11-13 22:32:40,603 - mmdet - INFO - Epoch [10][2000/7330] lr: 1.000e-05, eta: 1:43:08, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0338, loss_cls: 0.1443, acc: 94.4453, loss_bbox: 0.1928, loss_mask: 0.2092, loss: 0.5941 2023-11-13 22:32:56,136 - mmdet - INFO - Epoch [10][2050/7330] lr: 1.000e-05, eta: 1:42:52, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0345, loss_cls: 0.1452, acc: 94.4844, loss_bbox: 0.1944, loss_mask: 0.2091, loss: 0.5989 2023-11-13 22:33:11,750 - mmdet - INFO - Epoch [10][2100/7330] lr: 1.000e-05, eta: 1:42:37, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0368, loss_cls: 0.1500, acc: 94.3528, loss_bbox: 0.1959, loss_mask: 0.2095, loss: 0.6095 2023-11-13 22:33:27,088 - mmdet - INFO - Epoch [10][2150/7330] lr: 1.000e-05, eta: 1:42:21, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0378, loss_cls: 0.1513, acc: 94.2065, loss_bbox: 0.2041, loss_mask: 0.2097, loss: 0.6191 2023-11-13 22:33:42,645 - mmdet - INFO - Epoch [10][2200/7330] lr: 1.000e-05, eta: 1:42:06, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0364, loss_cls: 0.1468, acc: 94.4004, loss_bbox: 0.1988, loss_mask: 0.2080, loss: 0.6065 2023-11-13 22:33:58,394 - mmdet - INFO - Epoch [10][2250/7330] lr: 1.000e-05, eta: 1:41:50, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0382, loss_cls: 0.1570, acc: 93.9861, loss_bbox: 0.2050, loss_mask: 0.2125, loss: 0.6291 2023-11-13 22:34:13,683 - mmdet - INFO - Epoch [10][2300/7330] lr: 1.000e-05, eta: 1:41:35, time: 0.306, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0341, loss_cls: 0.1410, acc: 94.5786, loss_bbox: 0.1921, loss_mask: 0.2026, loss: 0.5841 2023-11-13 22:34:29,669 - mmdet - INFO - Epoch [10][2350/7330] lr: 1.000e-05, eta: 1:41:19, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0345, loss_cls: 0.1426, acc: 94.5513, loss_bbox: 0.1933, loss_mask: 0.2016, loss: 0.5875 2023-11-13 22:34:45,452 - mmdet - INFO - Epoch [10][2400/7330] lr: 1.000e-05, eta: 1:41:04, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0362, loss_cls: 0.1462, acc: 94.2937, loss_bbox: 0.1969, loss_mask: 0.2060, loss: 0.6015 2023-11-13 22:35:00,749 - mmdet - INFO - Epoch [10][2450/7330] lr: 1.000e-05, eta: 1:40:49, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0333, loss_cls: 0.1408, acc: 94.5007, loss_bbox: 0.1881, loss_mask: 0.2043, loss: 0.5807 2023-11-13 22:35:16,185 - mmdet - INFO - Epoch [10][2500/7330] lr: 1.000e-05, eta: 1:40:33, time: 0.309, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0363, loss_cls: 0.1485, acc: 94.2832, loss_bbox: 0.2054, loss_mask: 0.2123, loss: 0.6179 2023-11-13 22:35:31,694 - mmdet - INFO - Epoch [10][2550/7330] lr: 1.000e-05, eta: 1:40:18, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0362, loss_cls: 0.1472, acc: 94.2917, loss_bbox: 0.1963, loss_mask: 0.2089, loss: 0.6042 2023-11-13 22:35:47,382 - mmdet - INFO - Epoch [10][2600/7330] lr: 1.000e-05, eta: 1:40:02, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0359, loss_cls: 0.1453, acc: 94.4141, loss_bbox: 0.1975, loss_mask: 0.2054, loss: 0.5986 2023-11-13 22:36:03,033 - mmdet - INFO - Epoch [10][2650/7330] lr: 1.000e-05, eta: 1:39:47, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0368, loss_cls: 0.1469, acc: 94.3328, loss_bbox: 0.1963, loss_mask: 0.2103, loss: 0.6064 2023-11-13 22:36:18,166 - mmdet - INFO - Epoch [10][2700/7330] lr: 1.000e-05, eta: 1:39:31, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0346, loss_cls: 0.1442, acc: 94.5459, loss_bbox: 0.1946, loss_mask: 0.2070, loss: 0.5964 2023-11-13 22:36:33,891 - mmdet - INFO - Epoch [10][2750/7330] lr: 1.000e-05, eta: 1:39:16, time: 0.314, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0361, loss_cls: 0.1490, acc: 94.2456, loss_bbox: 0.2018, loss_mask: 0.2081, loss: 0.6105 2023-11-13 22:36:49,333 - mmdet - INFO - Epoch [10][2800/7330] lr: 1.000e-05, eta: 1:39:00, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0359, loss_cls: 0.1454, acc: 94.4634, loss_bbox: 0.1909, loss_mask: 0.2070, loss: 0.5943 2023-11-13 22:37:04,715 - mmdet - INFO - Epoch [10][2850/7330] lr: 1.000e-05, eta: 1:38:45, time: 0.308, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0349, loss_cls: 0.1459, acc: 94.4019, loss_bbox: 0.1964, loss_mask: 0.2107, loss: 0.6041 2023-11-13 22:37:20,288 - mmdet - INFO - Epoch [10][2900/7330] lr: 1.000e-05, eta: 1:38:29, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0369, loss_cls: 0.1506, acc: 94.2395, loss_bbox: 0.2016, loss_mask: 0.2163, loss: 0.6218 2023-11-13 22:37:35,620 - mmdet - INFO - Epoch [10][2950/7330] lr: 1.000e-05, eta: 1:38:14, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0371, loss_cls: 0.1455, acc: 94.3391, loss_bbox: 0.1996, loss_mask: 0.2089, loss: 0.6067 2023-11-13 22:37:50,964 - mmdet - INFO - Epoch [10][3000/7330] lr: 1.000e-05, eta: 1:37:58, time: 0.307, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0367, loss_cls: 0.1552, acc: 94.0681, loss_bbox: 0.2076, loss_mask: 0.2148, loss: 0.6309 2023-11-13 22:38:06,570 - mmdet - INFO - Epoch [10][3050/7330] lr: 1.000e-05, eta: 1:37:43, time: 0.312, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0368, loss_cls: 0.1547, acc: 94.1072, loss_bbox: 0.2047, loss_mask: 0.2098, loss: 0.6219 2023-11-13 22:38:21,962 - mmdet - INFO - Epoch [10][3100/7330] lr: 1.000e-05, eta: 1:37:27, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0357, loss_cls: 0.1446, acc: 94.4275, loss_bbox: 0.1983, loss_mask: 0.2095, loss: 0.6035 2023-11-13 22:38:37,532 - mmdet - INFO - Epoch [10][3150/7330] lr: 1.000e-05, eta: 1:37:12, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0361, loss_cls: 0.1430, acc: 94.5354, loss_bbox: 0.1979, loss_mask: 0.2076, loss: 0.5994 2023-11-13 22:38:52,895 - mmdet - INFO - Epoch [10][3200/7330] lr: 1.000e-05, eta: 1:36:56, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0345, loss_cls: 0.1422, acc: 94.5396, loss_bbox: 0.1880, loss_mask: 0.2090, loss: 0.5898 2023-11-13 22:39:08,277 - mmdet - INFO - Epoch [10][3250/7330] lr: 1.000e-05, eta: 1:36:41, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0359, loss_cls: 0.1442, acc: 94.4199, loss_bbox: 0.1941, loss_mask: 0.2065, loss: 0.5967 2023-11-13 22:39:24,234 - mmdet - INFO - Epoch [10][3300/7330] lr: 1.000e-05, eta: 1:36:25, time: 0.319, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0349, loss_cls: 0.1410, acc: 94.6814, loss_bbox: 0.1906, loss_mask: 0.2031, loss: 0.5846 2023-11-13 22:39:39,449 - mmdet - INFO - Epoch [10][3350/7330] lr: 1.000e-05, eta: 1:36:10, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0381, loss_cls: 0.1525, acc: 94.1641, loss_bbox: 0.2066, loss_mask: 0.2158, loss: 0.6289 2023-11-13 22:39:54,809 - mmdet - INFO - Epoch [10][3400/7330] lr: 1.000e-05, eta: 1:35:54, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0359, loss_cls: 0.1499, acc: 94.2969, loss_bbox: 0.2021, loss_mask: 0.2081, loss: 0.6124 2023-11-13 22:40:10,269 - mmdet - INFO - Epoch [10][3450/7330] lr: 1.000e-05, eta: 1:35:39, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0322, loss_cls: 0.1379, acc: 94.7256, loss_bbox: 0.1889, loss_mask: 0.2095, loss: 0.5817 2023-11-13 22:40:25,488 - mmdet - INFO - Epoch [10][3500/7330] lr: 1.000e-05, eta: 1:35:23, time: 0.304, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0366, loss_cls: 0.1493, acc: 94.3252, loss_bbox: 0.1999, loss_mask: 0.2058, loss: 0.6067 2023-11-13 22:40:41,465 - mmdet - INFO - Epoch [10][3550/7330] lr: 1.000e-05, eta: 1:35:08, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0374, loss_cls: 0.1518, acc: 94.2253, loss_bbox: 0.2061, loss_mask: 0.2110, loss: 0.6231 2023-11-13 22:40:56,940 - mmdet - INFO - Epoch [10][3600/7330] lr: 1.000e-05, eta: 1:34:53, time: 0.309, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0381, loss_cls: 0.1529, acc: 94.0825, loss_bbox: 0.2057, loss_mask: 0.2148, loss: 0.6284 2023-11-13 22:41:12,545 - mmdet - INFO - Epoch [10][3650/7330] lr: 1.000e-05, eta: 1:34:37, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0350, loss_cls: 0.1502, acc: 94.2607, loss_bbox: 0.2003, loss_mask: 0.2106, loss: 0.6116 2023-11-13 22:41:28,242 - mmdet - INFO - Epoch [10][3700/7330] lr: 1.000e-05, eta: 1:34:22, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0346, loss_cls: 0.1466, acc: 94.3713, loss_bbox: 0.1997, loss_mask: 0.2091, loss: 0.6064 2023-11-13 22:41:43,795 - mmdet - INFO - Epoch [10][3750/7330] lr: 1.000e-05, eta: 1:34:06, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0347, loss_cls: 0.1437, acc: 94.4995, loss_bbox: 0.1983, loss_mask: 0.2046, loss: 0.5967 2023-11-13 22:41:59,091 - mmdet - INFO - Epoch [10][3800/7330] lr: 1.000e-05, eta: 1:33:51, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0368, loss_cls: 0.1509, acc: 94.2080, loss_bbox: 0.2013, loss_mask: 0.2172, loss: 0.6240 2023-11-13 22:42:14,639 - mmdet - INFO - Epoch [10][3850/7330] lr: 1.000e-05, eta: 1:33:35, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0353, loss_cls: 0.1437, acc: 94.5068, loss_bbox: 0.1928, loss_mask: 0.2093, loss: 0.5966 2023-11-13 22:42:30,423 - mmdet - INFO - Epoch [10][3900/7330] lr: 1.000e-05, eta: 1:33:20, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0364, loss_cls: 0.1488, acc: 94.3894, loss_bbox: 0.1995, loss_mask: 0.2130, loss: 0.6145 2023-11-13 22:42:46,054 - mmdet - INFO - Epoch [10][3950/7330] lr: 1.000e-05, eta: 1:33:04, time: 0.313, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0387, loss_cls: 0.1539, acc: 94.1277, loss_bbox: 0.2073, loss_mask: 0.2122, loss: 0.6295 2023-11-13 22:43:01,375 - mmdet - INFO - Epoch [10][4000/7330] lr: 1.000e-05, eta: 1:32:49, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0344, loss_cls: 0.1484, acc: 94.2932, loss_bbox: 0.1942, loss_mask: 0.2087, loss: 0.6008 2023-11-13 22:43:16,866 - mmdet - INFO - Epoch [10][4050/7330] lr: 1.000e-05, eta: 1:32:33, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0346, loss_cls: 0.1463, acc: 94.3853, loss_bbox: 0.1963, loss_mask: 0.2069, loss: 0.6008 2023-11-13 22:43:32,388 - mmdet - INFO - Epoch [10][4100/7330] lr: 1.000e-05, eta: 1:32:18, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0347, loss_cls: 0.1413, acc: 94.6008, loss_bbox: 0.1941, loss_mask: 0.2069, loss: 0.5932 2023-11-13 22:43:47,716 - mmdet - INFO - Epoch [10][4150/7330] lr: 1.000e-05, eta: 1:32:02, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0344, loss_cls: 0.1452, acc: 94.3572, loss_bbox: 0.1965, loss_mask: 0.2073, loss: 0.5992 2023-11-13 22:44:03,051 - mmdet - INFO - Epoch [10][4200/7330] lr: 1.000e-05, eta: 1:31:47, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0359, loss_cls: 0.1484, acc: 94.4177, loss_bbox: 0.1971, loss_mask: 0.2043, loss: 0.6016 2023-11-13 22:44:18,130 - mmdet - INFO - Epoch [10][4250/7330] lr: 1.000e-05, eta: 1:31:31, time: 0.302, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0337, loss_cls: 0.1413, acc: 94.6331, loss_bbox: 0.1880, loss_mask: 0.2018, loss: 0.5795 2023-11-13 22:44:33,767 - mmdet - INFO - Epoch [10][4300/7330] lr: 1.000e-05, eta: 1:31:16, time: 0.313, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0392, loss_cls: 0.1547, acc: 94.0269, loss_bbox: 0.2085, loss_mask: 0.2100, loss: 0.6286 2023-11-13 22:44:48,904 - mmdet - INFO - Epoch [10][4350/7330] lr: 1.000e-05, eta: 1:31:00, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0344, loss_cls: 0.1434, acc: 94.5164, loss_bbox: 0.1926, loss_mask: 0.2062, loss: 0.5920 2023-11-13 22:45:04,636 - mmdet - INFO - Epoch [10][4400/7330] lr: 1.000e-05, eta: 1:30:45, time: 0.315, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0389, loss_cls: 0.1555, acc: 94.0818, loss_bbox: 0.2082, loss_mask: 0.2132, loss: 0.6339 2023-11-13 22:45:20,335 - mmdet - INFO - Epoch [10][4450/7330] lr: 1.000e-05, eta: 1:30:29, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0360, loss_cls: 0.1413, acc: 94.5862, loss_bbox: 0.1905, loss_mask: 0.2092, loss: 0.5925 2023-11-13 22:45:35,161 - mmdet - INFO - Epoch [10][4500/7330] lr: 1.000e-05, eta: 1:30:14, time: 0.297, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0337, loss_cls: 0.1389, acc: 94.6482, loss_bbox: 0.1896, loss_mask: 0.2043, loss: 0.5817 2023-11-13 22:45:50,527 - mmdet - INFO - Epoch [10][4550/7330] lr: 1.000e-05, eta: 1:29:58, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0370, loss_cls: 0.1454, acc: 94.4829, loss_bbox: 0.2006, loss_mask: 0.2115, loss: 0.6098 2023-11-13 22:46:05,935 - mmdet - INFO - Epoch [10][4600/7330] lr: 1.000e-05, eta: 1:29:43, time: 0.308, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0349, loss_cls: 0.1462, acc: 94.3757, loss_bbox: 0.1991, loss_mask: 0.2092, loss: 0.6043 2023-11-13 22:46:21,731 - mmdet - INFO - Epoch [10][4650/7330] lr: 1.000e-05, eta: 1:29:27, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0389, loss_cls: 0.1580, acc: 93.9141, loss_bbox: 0.2126, loss_mask: 0.2171, loss: 0.6438 2023-11-13 22:46:37,192 - mmdet - INFO - Epoch [10][4700/7330] lr: 1.000e-05, eta: 1:29:12, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0353, loss_cls: 0.1467, acc: 94.4045, loss_bbox: 0.1962, loss_mask: 0.2075, loss: 0.6021 2023-11-13 22:46:52,808 - mmdet - INFO - Epoch [10][4750/7330] lr: 1.000e-05, eta: 1:28:57, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0354, loss_cls: 0.1391, acc: 94.6848, loss_bbox: 0.1900, loss_mask: 0.2006, loss: 0.5819 2023-11-13 22:47:08,059 - mmdet - INFO - Epoch [10][4800/7330] lr: 1.000e-05, eta: 1:28:41, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0333, loss_cls: 0.1440, acc: 94.5295, loss_bbox: 0.1933, loss_mask: 0.2082, loss: 0.5930 2023-11-13 22:47:23,471 - mmdet - INFO - Epoch [10][4850/7330] lr: 1.000e-05, eta: 1:28:25, time: 0.308, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0344, loss_cls: 0.1436, acc: 94.4695, loss_bbox: 0.1924, loss_mask: 0.2091, loss: 0.5942 2023-11-13 22:47:38,879 - mmdet - INFO - Epoch [10][4900/7330] lr: 1.000e-05, eta: 1:28:10, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0375, loss_cls: 0.1478, acc: 94.4255, loss_bbox: 0.2016, loss_mask: 0.2111, loss: 0.6156 2023-11-13 22:47:54,491 - mmdet - INFO - Epoch [10][4950/7330] lr: 1.000e-05, eta: 1:27:55, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0380, loss_cls: 0.1528, acc: 94.0940, loss_bbox: 0.2102, loss_mask: 0.2144, loss: 0.6332 2023-11-13 22:48:09,944 - mmdet - INFO - Epoch [10][5000/7330] lr: 1.000e-05, eta: 1:27:39, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0367, loss_cls: 0.1395, acc: 94.7004, loss_bbox: 0.1907, loss_mask: 0.2042, loss: 0.5867 2023-11-13 22:48:25,609 - mmdet - INFO - Epoch [10][5050/7330] lr: 1.000e-05, eta: 1:27:24, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0365, loss_cls: 0.1464, acc: 94.3367, loss_bbox: 0.1981, loss_mask: 0.2049, loss: 0.6021 2023-11-13 22:48:41,516 - mmdet - INFO - Epoch [10][5100/7330] lr: 1.000e-05, eta: 1:27:08, time: 0.318, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0371, loss_cls: 0.1488, acc: 94.3203, loss_bbox: 0.1985, loss_mask: 0.2089, loss: 0.6104 2023-11-13 22:48:57,108 - mmdet - INFO - Epoch [10][5150/7330] lr: 1.000e-05, eta: 1:26:53, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0356, loss_cls: 0.1457, acc: 94.4387, loss_bbox: 0.1984, loss_mask: 0.2087, loss: 0.6042 2023-11-13 22:49:12,755 - mmdet - INFO - Epoch [10][5200/7330] lr: 1.000e-05, eta: 1:26:37, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0362, loss_cls: 0.1465, acc: 94.3650, loss_bbox: 0.1991, loss_mask: 0.2064, loss: 0.6048 2023-11-13 22:49:28,259 - mmdet - INFO - Epoch [10][5250/7330] lr: 1.000e-05, eta: 1:26:22, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0352, loss_cls: 0.1488, acc: 94.4097, loss_bbox: 0.1938, loss_mask: 0.2070, loss: 0.6017 2023-11-13 22:49:43,410 - mmdet - INFO - Epoch [10][5300/7330] lr: 1.000e-05, eta: 1:26:06, time: 0.303, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0366, loss_cls: 0.1482, acc: 94.3496, loss_bbox: 0.2001, loss_mask: 0.2111, loss: 0.6128 2023-11-13 22:49:58,855 - mmdet - INFO - Epoch [10][5350/7330] lr: 1.000e-05, eta: 1:25:51, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0370, loss_cls: 0.1556, acc: 94.0251, loss_bbox: 0.2116, loss_mask: 0.2125, loss: 0.6324 2023-11-13 22:50:14,411 - mmdet - INFO - Epoch [10][5400/7330] lr: 1.000e-05, eta: 1:25:35, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0352, loss_cls: 0.1448, acc: 94.4216, loss_bbox: 0.1983, loss_mask: 0.2071, loss: 0.5997 2023-11-13 22:50:29,783 - mmdet - INFO - Epoch [10][5450/7330] lr: 1.000e-05, eta: 1:25:20, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0360, loss_cls: 0.1559, acc: 94.0437, loss_bbox: 0.2053, loss_mask: 0.2094, loss: 0.6225 2023-11-13 22:50:45,020 - mmdet - INFO - Epoch [10][5500/7330] lr: 1.000e-05, eta: 1:25:04, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0356, loss_cls: 0.1482, acc: 94.3328, loss_bbox: 0.2013, loss_mask: 0.2090, loss: 0.6121 2023-11-13 22:51:00,408 - mmdet - INFO - Epoch [10][5550/7330] lr: 1.000e-05, eta: 1:24:49, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0347, loss_cls: 0.1435, acc: 94.4353, loss_bbox: 0.1944, loss_mask: 0.2049, loss: 0.5923 2023-11-13 22:51:15,851 - mmdet - INFO - Epoch [10][5600/7330] lr: 1.000e-05, eta: 1:24:33, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0355, loss_cls: 0.1461, acc: 94.5349, loss_bbox: 0.1918, loss_mask: 0.2092, loss: 0.5982 2023-11-13 22:51:31,303 - mmdet - INFO - Epoch [10][5650/7330] lr: 1.000e-05, eta: 1:24:18, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0359, loss_cls: 0.1461, acc: 94.4626, loss_bbox: 0.1994, loss_mask: 0.2102, loss: 0.6066 2023-11-13 22:51:47,009 - mmdet - INFO - Epoch [10][5700/7330] lr: 1.000e-05, eta: 1:24:02, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0365, loss_cls: 0.1470, acc: 94.3103, loss_bbox: 0.2002, loss_mask: 0.2081, loss: 0.6081 2023-11-13 22:52:02,833 - mmdet - INFO - Epoch [10][5750/7330] lr: 1.000e-05, eta: 1:23:47, time: 0.316, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0365, loss_cls: 0.1477, acc: 94.3232, loss_bbox: 0.1995, loss_mask: 0.2061, loss: 0.6054 2023-11-13 22:52:18,164 - mmdet - INFO - Epoch [10][5800/7330] lr: 1.000e-05, eta: 1:23:32, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0357, loss_cls: 0.1462, acc: 94.4287, loss_bbox: 0.1993, loss_mask: 0.2078, loss: 0.6044 2023-11-13 22:52:33,632 - mmdet - INFO - Epoch [10][5850/7330] lr: 1.000e-05, eta: 1:23:16, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0377, loss_cls: 0.1495, acc: 94.2266, loss_bbox: 0.2011, loss_mask: 0.2133, loss: 0.6178 2023-11-13 22:52:49,491 - mmdet - INFO - Epoch [10][5900/7330] lr: 1.000e-05, eta: 1:23:01, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0383, loss_cls: 0.1533, acc: 94.1431, loss_bbox: 0.2007, loss_mask: 0.2113, loss: 0.6204 2023-11-13 22:53:04,689 - mmdet - INFO - Epoch [10][5950/7330] lr: 1.000e-05, eta: 1:22:45, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0368, loss_cls: 0.1473, acc: 94.3694, loss_bbox: 0.2010, loss_mask: 0.2126, loss: 0.6139 2023-11-13 22:53:20,003 - mmdet - INFO - Epoch [10][6000/7330] lr: 1.000e-05, eta: 1:22:30, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0353, loss_cls: 0.1426, acc: 94.5176, loss_bbox: 0.1959, loss_mask: 0.2088, loss: 0.5968 2023-11-13 22:53:35,424 - mmdet - INFO - Epoch [10][6050/7330] lr: 1.000e-05, eta: 1:22:14, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0369, loss_cls: 0.1540, acc: 94.1406, loss_bbox: 0.2034, loss_mask: 0.2123, loss: 0.6239 2023-11-13 22:53:50,938 - mmdet - INFO - Epoch [10][6100/7330] lr: 1.000e-05, eta: 1:21:59, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0375, loss_cls: 0.1499, acc: 94.2776, loss_bbox: 0.2006, loss_mask: 0.2157, loss: 0.6201 2023-11-13 22:54:06,321 - mmdet - INFO - Epoch [10][6150/7330] lr: 1.000e-05, eta: 1:21:43, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0359, loss_cls: 0.1445, acc: 94.4719, loss_bbox: 0.1977, loss_mask: 0.2093, loss: 0.6032 2023-11-13 22:54:21,592 - mmdet - INFO - Epoch [10][6200/7330] lr: 1.000e-05, eta: 1:21:28, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0354, loss_cls: 0.1501, acc: 94.3525, loss_bbox: 0.1990, loss_mask: 0.2089, loss: 0.6096 2023-11-13 22:54:37,219 - mmdet - INFO - Epoch [10][6250/7330] lr: 1.000e-05, eta: 1:21:12, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0381, loss_cls: 0.1460, acc: 94.3752, loss_bbox: 0.1960, loss_mask: 0.2109, loss: 0.6078 2023-11-13 22:54:52,961 - mmdet - INFO - Epoch [10][6300/7330] lr: 1.000e-05, eta: 1:20:57, time: 0.315, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0368, loss_cls: 0.1458, acc: 94.3857, loss_bbox: 0.1993, loss_mask: 0.2079, loss: 0.6068 2023-11-13 22:55:08,746 - mmdet - INFO - Epoch [10][6350/7330] lr: 1.000e-05, eta: 1:20:41, time: 0.316, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0390, loss_cls: 0.1556, acc: 94.0793, loss_bbox: 0.2100, loss_mask: 0.2147, loss: 0.6363 2023-11-13 22:55:24,125 - mmdet - INFO - Epoch [10][6400/7330] lr: 1.000e-05, eta: 1:20:26, time: 0.308, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0347, loss_cls: 0.1450, acc: 94.5437, loss_bbox: 0.1983, loss_mask: 0.2114, loss: 0.6049 2023-11-13 22:55:39,498 - mmdet - INFO - Epoch [10][6450/7330] lr: 1.000e-05, eta: 1:20:10, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0349, loss_cls: 0.1404, acc: 94.7349, loss_bbox: 0.1899, loss_mask: 0.2037, loss: 0.5844 2023-11-13 22:55:55,047 - mmdet - INFO - Epoch [10][6500/7330] lr: 1.000e-05, eta: 1:19:55, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0363, loss_cls: 0.1510, acc: 94.2527, loss_bbox: 0.2015, loss_mask: 0.2115, loss: 0.6167 2023-11-13 22:56:10,102 - mmdet - INFO - Epoch [10][6550/7330] lr: 1.000e-05, eta: 1:19:39, time: 0.301, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0328, loss_cls: 0.1412, acc: 94.6614, loss_bbox: 0.1879, loss_mask: 0.2032, loss: 0.5797 2023-11-13 22:56:25,571 - mmdet - INFO - Epoch [10][6600/7330] lr: 1.000e-05, eta: 1:19:24, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0362, loss_cls: 0.1519, acc: 94.1750, loss_bbox: 0.2038, loss_mask: 0.2057, loss: 0.6132 2023-11-13 22:56:41,074 - mmdet - INFO - Epoch [10][6650/7330] lr: 1.000e-05, eta: 1:19:08, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0374, loss_cls: 0.1508, acc: 94.2695, loss_bbox: 0.2010, loss_mask: 0.2069, loss: 0.6118 2023-11-13 22:56:56,585 - mmdet - INFO - Epoch [10][6700/7330] lr: 1.000e-05, eta: 1:18:53, time: 0.310, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0368, loss_cls: 0.1498, acc: 94.2847, loss_bbox: 0.2051, loss_mask: 0.2118, loss: 0.6200 2023-11-13 22:57:12,305 - mmdet - INFO - Epoch [10][6750/7330] lr: 1.000e-05, eta: 1:18:37, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0375, loss_cls: 0.1484, acc: 94.3313, loss_bbox: 0.1977, loss_mask: 0.2139, loss: 0.6138 2023-11-13 22:57:27,485 - mmdet - INFO - Epoch [10][6800/7330] lr: 1.000e-05, eta: 1:18:22, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0342, loss_cls: 0.1386, acc: 94.6794, loss_bbox: 0.1890, loss_mask: 0.2049, loss: 0.5810 2023-11-13 22:57:42,787 - mmdet - INFO - Epoch [10][6850/7330] lr: 1.000e-05, eta: 1:18:06, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0367, loss_cls: 0.1483, acc: 94.3428, loss_bbox: 0.2014, loss_mask: 0.2091, loss: 0.6110 2023-11-13 22:57:58,587 - mmdet - INFO - Epoch [10][6900/7330] lr: 1.000e-05, eta: 1:17:51, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0384, loss_cls: 0.1536, acc: 94.0789, loss_bbox: 0.2037, loss_mask: 0.2123, loss: 0.6259 2023-11-13 22:58:13,882 - mmdet - INFO - Epoch [10][6950/7330] lr: 1.000e-05, eta: 1:17:35, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0340, loss_cls: 0.1417, acc: 94.4927, loss_bbox: 0.1924, loss_mask: 0.2042, loss: 0.5867 2023-11-13 22:58:29,541 - mmdet - INFO - Epoch [10][7000/7330] lr: 1.000e-05, eta: 1:17:20, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0349, loss_cls: 0.1443, acc: 94.4883, loss_bbox: 0.1916, loss_mask: 0.2087, loss: 0.5946 2023-11-13 22:58:44,803 - mmdet - INFO - Epoch [10][7050/7330] lr: 1.000e-05, eta: 1:17:04, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0337, loss_cls: 0.1431, acc: 94.6130, loss_bbox: 0.1880, loss_mask: 0.2018, loss: 0.5805 2023-11-13 22:59:00,645 - mmdet - INFO - Epoch [10][7100/7330] lr: 1.000e-05, eta: 1:16:49, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0356, loss_cls: 0.1497, acc: 94.2910, loss_bbox: 0.2022, loss_mask: 0.2107, loss: 0.6148 2023-11-13 22:59:16,146 - mmdet - INFO - Epoch [10][7150/7330] lr: 1.000e-05, eta: 1:16:34, time: 0.310, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0355, loss_cls: 0.1416, acc: 94.5376, loss_bbox: 0.1920, loss_mask: 0.2088, loss: 0.5944 2023-11-13 22:59:32,212 - mmdet - INFO - Epoch [10][7200/7330] lr: 1.000e-05, eta: 1:16:18, time: 0.321, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0350, loss_cls: 0.1431, acc: 94.5452, loss_bbox: 0.1923, loss_mask: 0.2049, loss: 0.5923 2023-11-13 22:59:47,890 - mmdet - INFO - Epoch [10][7250/7330] lr: 1.000e-05, eta: 1:16:03, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0351, loss_cls: 0.1512, acc: 94.1604, loss_bbox: 0.2020, loss_mask: 0.2095, loss: 0.6136 2023-11-13 23:00:03,775 - mmdet - INFO - Epoch [10][7300/7330] lr: 1.000e-05, eta: 1:15:47, time: 0.318, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0351, loss_cls: 0.1447, acc: 94.4380, loss_bbox: 0.1958, loss_mask: 0.2109, loss: 0.6030 2023-11-13 23:00:13,595 - mmdet - INFO - Saving checkpoint at 10 epochs 2023-11-13 23:00:56,349 - mmdet - INFO - Evaluating bbox... 2023-11-13 23:01:25,718 - 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 ] = 0.694 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.524 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.304 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.514 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 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.409 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.639 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.748 2023-11-13 23:01:25,721 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.580 | bicycle | 0.372 | car | 0.492 | | motorcycle | 0.487 | airplane | 0.716 | bus | 0.707 | | train | 0.686 | truck | 0.424 | boat | 0.329 | | traffic light | 0.309 | fire hydrant | 0.718 | stop sign | 0.708 | | parking meter | 0.517 | bench | 0.303 | bird | 0.413 | | cat | 0.731 | dog | 0.700 | horse | 0.607 | | sheep | 0.576 | cow | 0.634 | elephant | 0.681 | | bear | 0.752 | zebra | 0.696 | giraffe | 0.689 | | backpack | 0.220 | umbrella | 0.460 | handbag | 0.222 | | tie | 0.390 | suitcase | 0.479 | frisbee | 0.723 | | skis | 0.312 | snowboard | 0.447 | sports ball | 0.477 | | kite | 0.469 | baseball bat | 0.395 | baseball glove | 0.430 | | skateboard | 0.585 | surfboard | 0.463 | tennis racket | 0.532 | | bottle | 0.459 | wine glass | 0.424 | cup | 0.508 | | fork | 0.439 | knife | 0.287 | spoon | 0.251 | | bowl | 0.462 | banana | 0.290 | apple | 0.278 | | sandwich | 0.400 | orange | 0.367 | broccoli | 0.272 | | carrot | 0.260 | hot dog | 0.453 | pizza | 0.534 | | donut | 0.558 | cake | 0.429 | chair | 0.353 | | couch | 0.489 | potted plant | 0.343 | bed | 0.469 | | dining table | 0.318 | toilet | 0.667 | tv | 0.645 | | laptop | 0.674 | mouse | 0.650 | remote | 0.412 | | keyboard | 0.592 | cell phone | 0.446 | microwave | 0.628 | | oven | 0.398 | toaster | 0.437 | sink | 0.445 | | refrigerator | 0.630 | book | 0.199 | clock | 0.527 | | vase | 0.428 | scissors | 0.422 | teddy bear | 0.510 | | hair drier | 0.122 | toothbrush | 0.321 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:01:25,721 - mmdet - INFO - Evaluating segm... 2023-11-13 23:01:56,326 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.429 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.665 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.462 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.227 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.461 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.619 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.353 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.704 2023-11-13 23:01:56,328 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.505 | bicycle | 0.221 | car | 0.452 | | motorcycle | 0.392 | airplane | 0.561 | bus | 0.683 | | train | 0.670 | truck | 0.405 | boat | 0.301 | | traffic light | 0.295 | fire hydrant | 0.700 | stop sign | 0.685 | | parking meter | 0.506 | bench | 0.228 | bird | 0.345 | | cat | 0.719 | dog | 0.636 | horse | 0.450 | | sheep | 0.524 | cow | 0.542 | elephant | 0.621 | | bear | 0.756 | zebra | 0.601 | giraffe | 0.552 | | backpack | 0.226 | umbrella | 0.514 | handbag | 0.220 | | tie | 0.356 | suitcase | 0.496 | frisbee | 0.687 | | skis | 0.057 | snowboard | 0.282 | sports ball | 0.472 | | kite | 0.332 | baseball bat | 0.306 | baseball glove | 0.462 | | skateboard | 0.353 | surfboard | 0.395 | tennis racket | 0.588 | | bottle | 0.438 | wine glass | 0.373 | cup | 0.507 | | fork | 0.231 | knife | 0.200 | spoon | 0.177 | | bowl | 0.429 | banana | 0.236 | apple | 0.266 | | sandwich | 0.426 | orange | 0.362 | broccoli | 0.250 | | carrot | 0.230 | hot dog | 0.355 | pizza | 0.519 | | donut | 0.554 | cake | 0.435 | chair | 0.252 | | couch | 0.411 | potted plant | 0.292 | bed | 0.400 | | dining table | 0.193 | toilet | 0.640 | tv | 0.665 | | laptop | 0.665 | mouse | 0.634 | remote | 0.382 | | keyboard | 0.574 | cell phone | 0.416 | microwave | 0.639 | | oven | 0.373 | toaster | 0.460 | sink | 0.411 | | refrigerator | 0.644 | book | 0.148 | clock | 0.536 | | vase | 0.413 | scissors | 0.334 | teddy bear | 0.489 | | hair drier | 0.071 | toothbrush | 0.225 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:01:56,745 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:01:56,746 - mmdet - INFO - Epoch(val) [10][625] bbox_mAP: 0.4779, bbox_mAP_50: 0.6936, bbox_mAP_75: 0.5244, bbox_mAP_s: 0.3039, bbox_mAP_m: 0.5137, bbox_mAP_l: 0.6270, bbox_mAP_copypaste: 0.4779 0.6936 0.5244 0.3039 0.5137 0.6270, segm_mAP: 0.4294, segm_mAP_50: 0.6645, segm_mAP_75: 0.4617, segm_mAP_s: 0.2266, segm_mAP_m: 0.4611, segm_mAP_l: 0.6187, segm_mAP_copypaste: 0.4294 0.6645 0.4617 0.2266 0.4611 0.6187 2023-11-13 23:02:15,943 - mmdet - INFO - Epoch [11][50/7330] lr: 1.000e-05, eta: 1:15:22, time: 0.384, data_time: 0.093, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0353, loss_cls: 0.1398, acc: 94.6160, loss_bbox: 0.1899, loss_mask: 0.2073, loss: 0.5872 2023-11-13 23:02:31,690 - mmdet - INFO - Epoch [11][100/7330] lr: 1.000e-05, eta: 1:15:06, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0368, loss_cls: 0.1491, acc: 94.2866, loss_bbox: 0.2023, loss_mask: 0.2098, loss: 0.6133 2023-11-13 23:02:47,700 - mmdet - INFO - Epoch [11][150/7330] lr: 1.000e-05, eta: 1:14:51, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0351, loss_cls: 0.1433, acc: 94.5027, loss_bbox: 0.1935, loss_mask: 0.2006, loss: 0.5877 2023-11-13 23:03:03,700 - mmdet - INFO - Epoch [11][200/7330] lr: 1.000e-05, eta: 1:14:35, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0343, loss_cls: 0.1431, acc: 94.4275, loss_bbox: 0.1945, loss_mask: 0.2063, loss: 0.5934 2023-11-13 23:03:19,096 - mmdet - INFO - Epoch [11][250/7330] lr: 1.000e-05, eta: 1:14:20, time: 0.308, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0350, loss_cls: 0.1417, acc: 94.5774, loss_bbox: 0.1917, loss_mask: 0.2029, loss: 0.5852 2023-11-13 23:03:34,997 - mmdet - INFO - Epoch [11][300/7330] lr: 1.000e-05, eta: 1:14:04, time: 0.318, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0349, loss_cls: 0.1430, acc: 94.5217, loss_bbox: 0.1920, loss_mask: 0.2036, loss: 0.5878 2023-11-13 23:03:50,981 - mmdet - INFO - Epoch [11][350/7330] lr: 1.000e-05, eta: 1:13:49, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0356, loss_cls: 0.1471, acc: 94.3325, loss_bbox: 0.1963, loss_mask: 0.2098, loss: 0.6050 2023-11-13 23:04:06,608 - mmdet - INFO - Epoch [11][400/7330] lr: 1.000e-05, eta: 1:13:34, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0379, loss_cls: 0.1491, acc: 94.2856, loss_bbox: 0.2005, loss_mask: 0.2087, loss: 0.6122 2023-11-13 23:04:22,185 - mmdet - INFO - Epoch [11][450/7330] lr: 1.000e-05, eta: 1:13:18, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0360, loss_cls: 0.1442, acc: 94.4883, loss_bbox: 0.1969, loss_mask: 0.2077, loss: 0.6001 2023-11-13 23:04:38,176 - mmdet - INFO - Epoch [11][500/7330] lr: 1.000e-05, eta: 1:13:03, time: 0.320, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0363, loss_cls: 0.1448, acc: 94.4658, loss_bbox: 0.1957, loss_mask: 0.2095, loss: 0.6007 2023-11-13 23:04:54,175 - mmdet - INFO - Epoch [11][550/7330] lr: 1.000e-05, eta: 1:12:47, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0354, loss_cls: 0.1434, acc: 94.4998, loss_bbox: 0.1972, loss_mask: 0.2073, loss: 0.5973 2023-11-13 23:05:09,758 - mmdet - INFO - Epoch [11][600/7330] lr: 1.000e-05, eta: 1:12:32, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0345, loss_cls: 0.1355, acc: 94.7297, loss_bbox: 0.1839, loss_mask: 0.2035, loss: 0.5723 2023-11-13 23:05:25,717 - mmdet - INFO - Epoch [11][650/7330] lr: 1.000e-05, eta: 1:12:17, time: 0.319, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0360, loss_cls: 0.1479, acc: 94.3345, loss_bbox: 0.2020, loss_mask: 0.2135, loss: 0.6168 2023-11-13 23:05:41,644 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:05:41,645 - mmdet - INFO - Epoch [11][700/7330] lr: 1.000e-05, eta: 1:12:01, time: 0.319, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0363, loss_cls: 0.1467, acc: 94.4114, loss_bbox: 0.1998, loss_mask: 0.2087, loss: 0.6073 2023-11-13 23:05:57,147 - mmdet - INFO - Epoch [11][750/7330] lr: 1.000e-05, eta: 1:11:46, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0366, loss_cls: 0.1517, acc: 94.1689, loss_bbox: 0.2023, loss_mask: 0.2107, loss: 0.6189 2023-11-13 23:06:12,845 - mmdet - INFO - Epoch [11][800/7330] lr: 1.000e-05, eta: 1:11:30, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0357, loss_cls: 0.1416, acc: 94.4995, loss_bbox: 0.1950, loss_mask: 0.2054, loss: 0.5928 2023-11-13 23:06:28,967 - mmdet - INFO - Epoch [11][850/7330] lr: 1.000e-05, eta: 1:11:15, time: 0.322, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0354, loss_cls: 0.1450, acc: 94.4688, loss_bbox: 0.1952, loss_mask: 0.2093, loss: 0.6007 2023-11-13 23:06:45,695 - mmdet - INFO - Epoch [11][900/7330] lr: 1.000e-05, eta: 1:11:00, time: 0.335, data_time: 0.034, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0367, loss_cls: 0.1446, acc: 94.4578, loss_bbox: 0.1908, loss_mask: 0.2078, loss: 0.5967 2023-11-13 23:07:01,464 - mmdet - INFO - Epoch [11][950/7330] lr: 1.000e-05, eta: 1:10:44, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0347, loss_cls: 0.1422, acc: 94.5427, loss_bbox: 0.1950, loss_mask: 0.2055, loss: 0.5928 2023-11-13 23:07:17,224 - mmdet - INFO - Epoch [11][1000/7330] lr: 1.000e-05, eta: 1:10:29, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0358, loss_cls: 0.1373, acc: 94.8005, loss_bbox: 0.1911, loss_mask: 0.2032, loss: 0.5816 2023-11-13 23:07:33,094 - mmdet - INFO - Epoch [11][1050/7330] lr: 1.000e-05, eta: 1:10:13, time: 0.317, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0352, loss_cls: 0.1449, acc: 94.4121, loss_bbox: 0.1955, loss_mask: 0.2062, loss: 0.5973 2023-11-13 23:07:48,795 - mmdet - INFO - Epoch [11][1100/7330] lr: 1.000e-05, eta: 1:09:58, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0360, loss_cls: 0.1477, acc: 94.3359, loss_bbox: 0.1996, loss_mask: 0.2121, loss: 0.6097 2023-11-13 23:08:05,008 - mmdet - INFO - Epoch [11][1150/7330] lr: 1.000e-05, eta: 1:09:43, time: 0.324, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0361, loss_cls: 0.1504, acc: 94.2424, loss_bbox: 0.2025, loss_mask: 0.2127, loss: 0.6173 2023-11-13 23:08:20,567 - mmdet - INFO - Epoch [11][1200/7330] lr: 1.000e-05, eta: 1:09:27, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0347, loss_cls: 0.1410, acc: 94.6182, loss_bbox: 0.1869, loss_mask: 0.2045, loss: 0.5833 2023-11-13 23:08:36,313 - mmdet - INFO - Epoch [11][1250/7330] lr: 1.000e-05, eta: 1:09:12, time: 0.315, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0334, loss_cls: 0.1432, acc: 94.6072, loss_bbox: 0.1937, loss_mask: 0.2026, loss: 0.5873 2023-11-13 23:08:52,603 - mmdet - INFO - Epoch [11][1300/7330] lr: 1.000e-05, eta: 1:08:56, time: 0.326, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0382, loss_cls: 0.1487, acc: 94.3171, loss_bbox: 0.1963, loss_mask: 0.2074, loss: 0.6069 2023-11-13 23:09:08,431 - mmdet - INFO - Epoch [11][1350/7330] lr: 1.000e-05, eta: 1:08:41, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0367, loss_cls: 0.1525, acc: 94.2134, loss_bbox: 0.2001, loss_mask: 0.2091, loss: 0.6142 2023-11-13 23:09:23,874 - mmdet - INFO - Epoch [11][1400/7330] lr: 1.000e-05, eta: 1:08:25, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0349, loss_cls: 0.1422, acc: 94.5476, loss_bbox: 0.1913, loss_mask: 0.2034, loss: 0.5877 2023-11-13 23:09:39,937 - mmdet - INFO - Epoch [11][1450/7330] lr: 1.000e-05, eta: 1:08:10, time: 0.321, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0366, loss_cls: 0.1443, acc: 94.4185, loss_bbox: 0.1981, loss_mask: 0.2081, loss: 0.6030 2023-11-13 23:09:55,419 - mmdet - INFO - Epoch [11][1500/7330] lr: 1.000e-05, eta: 1:07:55, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0338, loss_cls: 0.1409, acc: 94.5779, loss_bbox: 0.1851, loss_mask: 0.2045, loss: 0.5796 2023-11-13 23:10:10,829 - mmdet - INFO - Epoch [11][1550/7330] lr: 1.000e-05, eta: 1:07:39, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0348, loss_cls: 0.1423, acc: 94.5374, loss_bbox: 0.1923, loss_mask: 0.2051, loss: 0.5904 2023-11-13 23:10:26,116 - mmdet - INFO - Epoch [11][1600/7330] lr: 1.000e-05, eta: 1:07:24, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0330, loss_cls: 0.1422, acc: 94.4922, loss_bbox: 0.1952, loss_mask: 0.2097, loss: 0.5940 2023-11-13 23:10:41,689 - mmdet - INFO - Epoch [11][1650/7330] lr: 1.000e-05, eta: 1:07:08, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0355, loss_cls: 0.1413, acc: 94.5571, loss_bbox: 0.1976, loss_mask: 0.2135, loss: 0.6025 2023-11-13 23:10:57,401 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:10:57,402 - mmdet - INFO - Epoch [11][1700/7330] lr: 1.000e-05, eta: 1:06:53, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0363, loss_cls: 0.1474, acc: 94.3083, loss_bbox: 0.2015, loss_mask: 0.2104, loss: 0.6115 2023-11-13 23:11:13,288 - mmdet - INFO - Epoch [11][1750/7330] lr: 1.000e-05, eta: 1:06:37, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0357, loss_cls: 0.1442, acc: 94.4553, loss_bbox: 0.1953, loss_mask: 0.2052, loss: 0.5965 2023-11-13 23:11:28,969 - mmdet - INFO - Epoch [11][1800/7330] lr: 1.000e-05, eta: 1:06:22, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0332, loss_cls: 0.1443, acc: 94.4863, loss_bbox: 0.1954, loss_mask: 0.2054, loss: 0.5925 2023-11-13 23:11:44,257 - mmdet - INFO - Epoch [11][1850/7330] lr: 1.000e-05, eta: 1:06:06, time: 0.306, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0332, loss_cls: 0.1492, acc: 94.2788, loss_bbox: 0.2009, loss_mask: 0.2061, loss: 0.6036 2023-11-13 23:11:59,505 - mmdet - INFO - Epoch [11][1900/7330] lr: 1.000e-05, eta: 1:05:51, time: 0.305, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0363, loss_cls: 0.1474, acc: 94.3755, loss_bbox: 0.2015, loss_mask: 0.2092, loss: 0.6099 2023-11-13 23:12:15,417 - mmdet - INFO - Epoch [11][1950/7330] lr: 1.000e-05, eta: 1:05:35, time: 0.318, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0382, loss_cls: 0.1459, acc: 94.4553, loss_bbox: 0.1994, loss_mask: 0.2111, loss: 0.6102 2023-11-13 23:12:30,749 - mmdet - INFO - Epoch [11][2000/7330] lr: 1.000e-05, eta: 1:05:20, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0336, loss_cls: 0.1425, acc: 94.5271, loss_bbox: 0.1949, loss_mask: 0.2048, loss: 0.5900 2023-11-13 23:12:46,077 - mmdet - INFO - Epoch [11][2050/7330] lr: 1.000e-05, eta: 1:05:04, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0331, loss_cls: 0.1333, acc: 94.9246, loss_bbox: 0.1831, loss_mask: 0.2052, loss: 0.5683 2023-11-13 23:13:01,715 - mmdet - INFO - Epoch [11][2100/7330] lr: 1.000e-05, eta: 1:04:49, time: 0.313, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0340, loss_cls: 0.1404, acc: 94.6267, loss_bbox: 0.1949, loss_mask: 0.2072, loss: 0.5921 2023-11-13 23:13:17,809 - mmdet - INFO - Epoch [11][2150/7330] lr: 1.000e-05, eta: 1:04:34, time: 0.322, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0378, loss_cls: 0.1496, acc: 94.2917, loss_bbox: 0.2021, loss_mask: 0.2118, loss: 0.6188 2023-11-13 23:13:33,573 - mmdet - INFO - Epoch [11][2200/7330] lr: 1.000e-05, eta: 1:04:18, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0352, loss_cls: 0.1466, acc: 94.3330, loss_bbox: 0.2002, loss_mask: 0.2060, loss: 0.6032 2023-11-13 23:13:49,209 - mmdet - INFO - Epoch [11][2250/7330] lr: 1.000e-05, eta: 1:04:03, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0341, loss_cls: 0.1426, acc: 94.5090, loss_bbox: 0.1965, loss_mask: 0.2071, loss: 0.5951 2023-11-13 23:14:04,940 - mmdet - INFO - Epoch [11][2300/7330] lr: 1.000e-05, eta: 1:03:47, time: 0.315, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0357, loss_cls: 0.1460, acc: 94.3787, loss_bbox: 0.1978, loss_mask: 0.2057, loss: 0.6019 2023-11-13 23:14:20,488 - mmdet - INFO - Epoch [11][2350/7330] lr: 1.000e-05, eta: 1:03:32, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0348, loss_cls: 0.1479, acc: 94.3003, loss_bbox: 0.1994, loss_mask: 0.2094, loss: 0.6068 2023-11-13 23:14:36,278 - mmdet - INFO - Epoch [11][2400/7330] lr: 1.000e-05, eta: 1:03:16, time: 0.316, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0351, loss_cls: 0.1452, acc: 94.3726, loss_bbox: 0.1961, loss_mask: 0.2072, loss: 0.5992 2023-11-13 23:14:51,981 - mmdet - INFO - Epoch [11][2450/7330] lr: 1.000e-05, eta: 1:03:01, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0362, loss_cls: 0.1474, acc: 94.3560, loss_bbox: 0.1949, loss_mask: 0.2099, loss: 0.6038 2023-11-13 23:15:07,685 - mmdet - INFO - Epoch [11][2500/7330] lr: 1.000e-05, eta: 1:02:45, time: 0.314, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0371, loss_cls: 0.1502, acc: 94.3647, loss_bbox: 0.1994, loss_mask: 0.2074, loss: 0.6098 2023-11-13 23:15:23,222 - mmdet - INFO - Epoch [11][2550/7330] lr: 1.000e-05, eta: 1:02:30, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0356, loss_cls: 0.1510, acc: 94.2529, loss_bbox: 0.2004, loss_mask: 0.2082, loss: 0.6108 2023-11-13 23:15:38,819 - mmdet - INFO - Epoch [11][2600/7330] lr: 1.000e-05, eta: 1:02:14, time: 0.312, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0383, loss_cls: 0.1542, acc: 94.1040, loss_bbox: 0.2095, loss_mask: 0.2155, loss: 0.6346 2023-11-13 23:15:54,082 - mmdet - INFO - Epoch [11][2650/7330] lr: 1.000e-05, eta: 1:01:59, time: 0.305, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0364, loss_cls: 0.1445, acc: 94.4451, loss_bbox: 0.1963, loss_mask: 0.2064, loss: 0.5992 2023-11-13 23:16:09,983 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:16:09,983 - mmdet - INFO - Epoch [11][2700/7330] lr: 1.000e-05, eta: 1:01:43, time: 0.318, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0356, loss_cls: 0.1453, acc: 94.4631, loss_bbox: 0.1930, loss_mask: 0.2072, loss: 0.5973 2023-11-13 23:16:25,413 - mmdet - INFO - Epoch [11][2750/7330] lr: 1.000e-05, eta: 1:01:28, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0348, loss_cls: 0.1458, acc: 94.4280, loss_bbox: 0.1933, loss_mask: 0.2076, loss: 0.5956 2023-11-13 23:16:41,087 - mmdet - INFO - Epoch [11][2800/7330] lr: 1.000e-05, eta: 1:01:13, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0356, loss_cls: 0.1462, acc: 94.4380, loss_bbox: 0.1977, loss_mask: 0.2115, loss: 0.6059 2023-11-13 23:16:56,543 - mmdet - INFO - Epoch [11][2850/7330] lr: 1.000e-05, eta: 1:00:57, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0347, loss_cls: 0.1404, acc: 94.6362, loss_bbox: 0.1906, loss_mask: 0.2019, loss: 0.5823 2023-11-13 23:17:12,143 - mmdet - INFO - Epoch [11][2900/7330] lr: 1.000e-05, eta: 1:00:42, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0362, loss_cls: 0.1435, acc: 94.5356, loss_bbox: 0.1909, loss_mask: 0.2026, loss: 0.5884 2023-11-13 23:17:28,010 - mmdet - INFO - Epoch [11][2950/7330] lr: 1.000e-05, eta: 1:00:26, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0345, loss_cls: 0.1416, acc: 94.5815, loss_bbox: 0.1936, loss_mask: 0.2041, loss: 0.5892 2023-11-13 23:17:43,289 - mmdet - INFO - Epoch [11][3000/7330] lr: 1.000e-05, eta: 1:00:11, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0365, loss_cls: 0.1467, acc: 94.3684, loss_bbox: 0.1978, loss_mask: 0.2126, loss: 0.6102 2023-11-13 23:17:58,815 - mmdet - INFO - Epoch [11][3050/7330] lr: 1.000e-05, eta: 0:59:55, time: 0.311, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0347, loss_cls: 0.1450, acc: 94.4441, loss_bbox: 0.1953, loss_mask: 0.2046, loss: 0.5965 2023-11-13 23:18:14,300 - mmdet - INFO - Epoch [11][3100/7330] lr: 1.000e-05, eta: 0:59:40, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0356, loss_cls: 0.1478, acc: 94.2917, loss_bbox: 0.1998, loss_mask: 0.2130, loss: 0.6132 2023-11-13 23:18:29,586 - mmdet - INFO - Epoch [11][3150/7330] lr: 1.000e-05, eta: 0:59:24, time: 0.306, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0328, loss_cls: 0.1429, acc: 94.5386, loss_bbox: 0.1922, loss_mask: 0.2043, loss: 0.5872 2023-11-13 23:18:44,897 - mmdet - INFO - Epoch [11][3200/7330] lr: 1.000e-05, eta: 0:59:09, time: 0.306, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0357, loss_cls: 0.1421, acc: 94.5645, loss_bbox: 0.1943, loss_mask: 0.2078, loss: 0.5944 2023-11-13 23:19:00,223 - mmdet - INFO - Epoch [11][3250/7330] lr: 1.000e-05, eta: 0:58:53, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0347, loss_cls: 0.1433, acc: 94.4863, loss_bbox: 0.1917, loss_mask: 0.2042, loss: 0.5892 2023-11-13 23:19:15,956 - mmdet - INFO - Epoch [11][3300/7330] lr: 1.000e-05, eta: 0:58:38, time: 0.315, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0383, loss_cls: 0.1519, acc: 94.1409, loss_bbox: 0.2056, loss_mask: 0.2109, loss: 0.6238 2023-11-13 23:19:31,443 - mmdet - INFO - Epoch [11][3350/7330] lr: 1.000e-05, eta: 0:58:22, time: 0.310, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0334, loss_cls: 0.1417, acc: 94.6001, loss_bbox: 0.1955, loss_mask: 0.2060, loss: 0.5912 2023-11-13 23:19:46,853 - mmdet - INFO - Epoch [11][3400/7330] lr: 1.000e-05, eta: 0:58:07, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0319, loss_cls: 0.1380, acc: 94.7832, loss_bbox: 0.1862, loss_mask: 0.2017, loss: 0.5731 2023-11-13 23:20:02,618 - mmdet - INFO - Epoch [11][3450/7330] lr: 1.000e-05, eta: 0:57:51, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0380, loss_cls: 0.1550, acc: 94.0950, loss_bbox: 0.2060, loss_mask: 0.2156, loss: 0.6317 2023-11-13 23:20:18,069 - mmdet - INFO - Epoch [11][3500/7330] lr: 1.000e-05, eta: 0:57:36, time: 0.309, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0347, loss_cls: 0.1401, acc: 94.6152, loss_bbox: 0.1893, loss_mask: 0.2079, loss: 0.5886 2023-11-13 23:20:33,767 - mmdet - INFO - Epoch [11][3550/7330] lr: 1.000e-05, eta: 0:57:20, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0359, loss_cls: 0.1440, acc: 94.5356, loss_bbox: 0.1891, loss_mask: 0.2020, loss: 0.5870 2023-11-13 23:20:49,593 - mmdet - INFO - Epoch [11][3600/7330] lr: 1.000e-05, eta: 0:57:05, time: 0.317, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0361, loss_cls: 0.1455, acc: 94.4644, loss_bbox: 0.1977, loss_mask: 0.2115, loss: 0.6067 2023-11-13 23:21:05,478 - mmdet - INFO - Epoch [11][3650/7330] lr: 1.000e-05, eta: 0:56:49, time: 0.318, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0386, loss_cls: 0.1492, acc: 94.2188, loss_bbox: 0.2021, loss_mask: 0.2136, loss: 0.6220 2023-11-13 23:21:20,806 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:21:20,806 - mmdet - INFO - Epoch [11][3700/7330] lr: 1.000e-05, eta: 0:56:34, time: 0.307, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0361, loss_cls: 0.1444, acc: 94.4846, loss_bbox: 0.1965, loss_mask: 0.2096, loss: 0.6014 2023-11-13 23:21:36,020 - mmdet - INFO - Epoch [11][3750/7330] lr: 1.000e-05, eta: 0:56:18, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0331, loss_cls: 0.1359, acc: 94.8286, loss_bbox: 0.1806, loss_mask: 0.2065, loss: 0.5701 2023-11-13 23:21:50,995 - mmdet - INFO - Epoch [11][3800/7330] lr: 1.000e-05, eta: 0:56:03, time: 0.299, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0336, loss_cls: 0.1385, acc: 94.6895, loss_bbox: 0.1901, loss_mask: 0.2049, loss: 0.5806 2023-11-13 23:22:06,716 - mmdet - INFO - Epoch [11][3850/7330] lr: 1.000e-05, eta: 0:55:47, time: 0.314, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0355, loss_cls: 0.1418, acc: 94.6057, loss_bbox: 0.1933, loss_mask: 0.2065, loss: 0.5926 2023-11-13 23:22:22,316 - mmdet - INFO - Epoch [11][3900/7330] lr: 1.000e-05, eta: 0:55:32, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0339, loss_cls: 0.1404, acc: 94.6843, loss_bbox: 0.1917, loss_mask: 0.2047, loss: 0.5844 2023-11-13 23:22:37,828 - mmdet - INFO - Epoch [11][3950/7330] lr: 1.000e-05, eta: 0:55:16, time: 0.310, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0385, loss_cls: 0.1522, acc: 94.2073, loss_bbox: 0.2067, loss_mask: 0.2121, loss: 0.6266 2023-11-13 23:22:53,662 - mmdet - INFO - Epoch [11][4000/7330] lr: 1.000e-05, eta: 0:55:01, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0389, loss_cls: 0.1578, acc: 93.9805, loss_bbox: 0.2115, loss_mask: 0.2149, loss: 0.6417 2023-11-13 23:23:09,177 - mmdet - INFO - Epoch [11][4050/7330] lr: 1.000e-05, eta: 0:54:46, time: 0.310, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0357, loss_cls: 0.1472, acc: 94.3481, loss_bbox: 0.2014, loss_mask: 0.2059, loss: 0.6053 2023-11-13 23:23:24,409 - mmdet - INFO - Epoch [11][4100/7330] lr: 1.000e-05, eta: 0:54:30, time: 0.305, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0369, loss_cls: 0.1478, acc: 94.2676, loss_bbox: 0.2051, loss_mask: 0.2138, loss: 0.6173 2023-11-13 23:23:40,264 - mmdet - INFO - Epoch [11][4150/7330] lr: 1.000e-05, eta: 0:54:15, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0378, loss_cls: 0.1489, acc: 94.3245, loss_bbox: 0.1970, loss_mask: 0.2087, loss: 0.6085 2023-11-13 23:23:55,726 - mmdet - INFO - Epoch [11][4200/7330] lr: 1.000e-05, eta: 0:53:59, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0344, loss_cls: 0.1431, acc: 94.5591, loss_bbox: 0.1903, loss_mask: 0.2046, loss: 0.5865 2023-11-13 23:24:10,694 - mmdet - INFO - Epoch [11][4250/7330] lr: 1.000e-05, eta: 0:53:44, time: 0.299, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0326, loss_cls: 0.1401, acc: 94.6003, loss_bbox: 0.1925, loss_mask: 0.2076, loss: 0.5866 2023-11-13 23:24:25,797 - mmdet - INFO - Epoch [11][4300/7330] lr: 1.000e-05, eta: 0:53:28, time: 0.302, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0321, loss_cls: 0.1324, acc: 94.9067, loss_bbox: 0.1806, loss_mask: 0.2000, loss: 0.5597 2023-11-13 23:24:40,956 - mmdet - INFO - Epoch [11][4350/7330] lr: 1.000e-05, eta: 0:53:12, time: 0.303, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0364, loss_cls: 0.1419, acc: 94.5867, loss_bbox: 0.1945, loss_mask: 0.2048, loss: 0.5933 2023-11-13 23:24:56,218 - mmdet - INFO - Epoch [11][4400/7330] lr: 1.000e-05, eta: 0:52:57, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0349, loss_cls: 0.1419, acc: 94.5938, loss_bbox: 0.1866, loss_mask: 0.2053, loss: 0.5837 2023-11-13 23:25:11,962 - mmdet - INFO - Epoch [11][4450/7330] lr: 1.000e-05, eta: 0:52:42, time: 0.315, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0361, loss_cls: 0.1493, acc: 94.3452, loss_bbox: 0.1995, loss_mask: 0.2083, loss: 0.6072 2023-11-13 23:25:27,426 - mmdet - INFO - Epoch [11][4500/7330] lr: 1.000e-05, eta: 0:52:26, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0328, loss_cls: 0.1451, acc: 94.4426, loss_bbox: 0.1911, loss_mask: 0.2094, loss: 0.5930 2023-11-13 23:25:43,278 - mmdet - INFO - Epoch [11][4550/7330] lr: 1.000e-05, eta: 0:52:11, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0369, loss_cls: 0.1475, acc: 94.3391, loss_bbox: 0.1990, loss_mask: 0.2059, loss: 0.6059 2023-11-13 23:25:58,753 - mmdet - INFO - Epoch [11][4600/7330] lr: 1.000e-05, eta: 0:51:55, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0344, loss_cls: 0.1435, acc: 94.5857, loss_bbox: 0.1916, loss_mask: 0.2086, loss: 0.5928 2023-11-13 23:26:14,098 - mmdet - INFO - Epoch [11][4650/7330] lr: 1.000e-05, eta: 0:51:40, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0340, loss_cls: 0.1420, acc: 94.5693, loss_bbox: 0.1876, loss_mask: 0.2039, loss: 0.5826 2023-11-13 23:26:29,529 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:26:29,529 - mmdet - INFO - Epoch [11][4700/7330] lr: 1.000e-05, eta: 0:51:24, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0352, loss_cls: 0.1464, acc: 94.3572, loss_bbox: 0.2004, loss_mask: 0.2082, loss: 0.6066 2023-11-13 23:26:44,985 - mmdet - INFO - Epoch [11][4750/7330] lr: 1.000e-05, eta: 0:51:09, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0357, loss_cls: 0.1427, acc: 94.5073, loss_bbox: 0.1912, loss_mask: 0.2090, loss: 0.5942 2023-11-13 23:27:00,530 - mmdet - INFO - Epoch [11][4800/7330] lr: 1.000e-05, eta: 0:50:53, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0369, loss_cls: 0.1494, acc: 94.2422, loss_bbox: 0.2027, loss_mask: 0.2078, loss: 0.6134 2023-11-13 23:27:15,813 - mmdet - INFO - Epoch [11][4850/7330] lr: 1.000e-05, eta: 0:50:38, time: 0.306, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0388, loss_cls: 0.1570, acc: 94.0115, loss_bbox: 0.2052, loss_mask: 0.2116, loss: 0.6299 2023-11-13 23:27:31,313 - mmdet - INFO - Epoch [11][4900/7330] lr: 1.000e-05, eta: 0:50:22, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0354, loss_cls: 0.1374, acc: 94.7578, loss_bbox: 0.1875, loss_mask: 0.2046, loss: 0.5812 2023-11-13 23:27:46,595 - mmdet - INFO - Epoch [11][4950/7330] lr: 1.000e-05, eta: 0:50:07, time: 0.306, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0335, loss_cls: 0.1388, acc: 94.7173, loss_bbox: 0.1951, loss_mask: 0.2081, loss: 0.5894 2023-11-13 23:28:02,264 - mmdet - INFO - Epoch [11][5000/7330] lr: 1.000e-05, eta: 0:49:51, time: 0.313, data_time: 0.030, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0349, loss_cls: 0.1423, acc: 94.4890, loss_bbox: 0.1941, loss_mask: 0.2095, loss: 0.5973 2023-11-13 23:28:17,602 - mmdet - INFO - Epoch [11][5050/7330] lr: 1.000e-05, eta: 0:49:36, time: 0.307, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0351, loss_cls: 0.1503, acc: 94.2275, loss_bbox: 0.1994, loss_mask: 0.2093, loss: 0.6111 2023-11-13 23:28:33,380 - mmdet - INFO - Epoch [11][5100/7330] lr: 1.000e-05, eta: 0:49:20, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0344, loss_cls: 0.1424, acc: 94.5000, loss_bbox: 0.1947, loss_mask: 0.2070, loss: 0.5941 2023-11-13 23:28:48,709 - mmdet - INFO - Epoch [11][5150/7330] lr: 1.000e-05, eta: 0:49:05, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0376, loss_cls: 0.1440, acc: 94.5020, loss_bbox: 0.1928, loss_mask: 0.2055, loss: 0.5977 2023-11-13 23:29:04,285 - mmdet - INFO - Epoch [11][5200/7330] lr: 1.000e-05, eta: 0:48:49, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0367, loss_cls: 0.1451, acc: 94.4302, loss_bbox: 0.1954, loss_mask: 0.2053, loss: 0.5990 2023-11-13 23:29:20,044 - mmdet - INFO - Epoch [11][5250/7330] lr: 1.000e-05, eta: 0:48:34, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0361, loss_cls: 0.1377, acc: 94.7275, loss_bbox: 0.1894, loss_mask: 0.2048, loss: 0.5826 2023-11-13 23:29:35,518 - mmdet - INFO - Epoch [11][5300/7330] lr: 1.000e-05, eta: 0:48:18, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0357, loss_cls: 0.1462, acc: 94.3701, loss_bbox: 0.1997, loss_mask: 0.2073, loss: 0.6055 2023-11-13 23:29:50,902 - mmdet - INFO - Epoch [11][5350/7330] lr: 1.000e-05, eta: 0:48:03, time: 0.308, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0397, loss_cls: 0.1575, acc: 93.9976, loss_bbox: 0.2151, loss_mask: 0.2223, loss: 0.6519 2023-11-13 23:30:06,131 - mmdet - INFO - Epoch [11][5400/7330] lr: 1.000e-05, eta: 0:47:47, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0334, loss_cls: 0.1399, acc: 94.6565, loss_bbox: 0.1880, loss_mask: 0.2044, loss: 0.5798 2023-11-13 23:30:21,450 - mmdet - INFO - Epoch [11][5450/7330] lr: 1.000e-05, eta: 0:47:32, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0344, loss_cls: 0.1380, acc: 94.6648, loss_bbox: 0.1928, loss_mask: 0.2028, loss: 0.5833 2023-11-13 23:30:36,882 - mmdet - INFO - Epoch [11][5500/7330] lr: 1.000e-05, eta: 0:47:16, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0340, loss_cls: 0.1421, acc: 94.5793, loss_bbox: 0.1937, loss_mask: 0.2079, loss: 0.5917 2023-11-13 23:30:52,257 - mmdet - INFO - Epoch [11][5550/7330] lr: 1.000e-05, eta: 0:47:01, time: 0.307, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0350, loss_cls: 0.1382, acc: 94.6875, loss_bbox: 0.1878, loss_mask: 0.2051, loss: 0.5811 2023-11-13 23:31:07,421 - mmdet - INFO - Epoch [11][5600/7330] lr: 1.000e-05, eta: 0:46:45, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0353, loss_cls: 0.1475, acc: 94.3633, loss_bbox: 0.2000, loss_mask: 0.2101, loss: 0.6093 2023-11-13 23:31:22,903 - mmdet - INFO - Epoch [11][5650/7330] lr: 1.000e-05, eta: 0:46:30, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0351, loss_cls: 0.1424, acc: 94.5515, loss_bbox: 0.1921, loss_mask: 0.2015, loss: 0.5865 2023-11-13 23:31:38,372 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:31:38,372 - mmdet - INFO - Epoch [11][5700/7330] lr: 1.000e-05, eta: 0:46:14, time: 0.309, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0348, loss_cls: 0.1393, acc: 94.7307, loss_bbox: 0.1899, loss_mask: 0.2052, loss: 0.5855 2023-11-13 23:31:53,714 - mmdet - INFO - Epoch [11][5750/7330] lr: 1.000e-05, eta: 0:45:59, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0347, loss_cls: 0.1445, acc: 94.4946, loss_bbox: 0.1973, loss_mask: 0.2060, loss: 0.5967 2023-11-13 23:32:08,910 - mmdet - INFO - Epoch [11][5800/7330] lr: 1.000e-05, eta: 0:45:43, time: 0.304, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0352, loss_cls: 0.1473, acc: 94.2952, loss_bbox: 0.1994, loss_mask: 0.2127, loss: 0.6095 2023-11-13 23:32:24,496 - mmdet - INFO - Epoch [11][5850/7330] lr: 1.000e-05, eta: 0:45:28, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0354, loss_cls: 0.1423, acc: 94.5754, loss_bbox: 0.1943, loss_mask: 0.2085, loss: 0.5972 2023-11-13 23:32:39,787 - mmdet - INFO - Epoch [11][5900/7330] lr: 1.000e-05, eta: 0:45:12, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0345, loss_cls: 0.1439, acc: 94.3401, loss_bbox: 0.1980, loss_mask: 0.2059, loss: 0.5970 2023-11-13 23:32:54,928 - mmdet - INFO - Epoch [11][5950/7330] lr: 1.000e-05, eta: 0:44:57, time: 0.303, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0348, loss_cls: 0.1452, acc: 94.4758, loss_bbox: 0.1954, loss_mask: 0.2084, loss: 0.5993 2023-11-13 23:33:10,357 - mmdet - INFO - Epoch [11][6000/7330] lr: 1.000e-05, eta: 0:44:41, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0346, loss_cls: 0.1420, acc: 94.6089, loss_bbox: 0.1938, loss_mask: 0.2086, loss: 0.5941 2023-11-13 23:33:25,639 - mmdet - INFO - Epoch [11][6050/7330] lr: 1.000e-05, eta: 0:44:26, time: 0.306, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0338, loss_cls: 0.1400, acc: 94.6135, loss_bbox: 0.1920, loss_mask: 0.2051, loss: 0.5855 2023-11-13 23:33:41,210 - mmdet - INFO - Epoch [11][6100/7330] lr: 1.000e-05, eta: 0:44:10, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0378, loss_cls: 0.1499, acc: 94.2578, loss_bbox: 0.2008, loss_mask: 0.2101, loss: 0.6145 2023-11-13 23:33:56,246 - mmdet - INFO - Epoch [11][6150/7330] lr: 1.000e-05, eta: 0:43:55, time: 0.301, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0327, loss_cls: 0.1380, acc: 94.7219, loss_bbox: 0.1827, loss_mask: 0.2020, loss: 0.5692 2023-11-13 23:34:11,723 - mmdet - INFO - Epoch [11][6200/7330] lr: 1.000e-05, eta: 0:43:39, time: 0.310, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0346, loss_cls: 0.1442, acc: 94.4458, loss_bbox: 0.1939, loss_mask: 0.2076, loss: 0.5955 2023-11-13 23:34:27,204 - mmdet - INFO - Epoch [11][6250/7330] lr: 1.000e-05, eta: 0:43:24, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0363, loss_cls: 0.1444, acc: 94.4822, loss_bbox: 0.1952, loss_mask: 0.2055, loss: 0.5966 2023-11-13 23:34:42,728 - mmdet - INFO - Epoch [11][6300/7330] lr: 1.000e-05, eta: 0:43:08, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0350, loss_cls: 0.1436, acc: 94.5085, loss_bbox: 0.1945, loss_mask: 0.2078, loss: 0.5958 2023-11-13 23:34:58,577 - mmdet - INFO - Epoch [11][6350/7330] lr: 1.000e-05, eta: 0:42:53, time: 0.317, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0363, loss_cls: 0.1437, acc: 94.4897, loss_bbox: 0.1903, loss_mask: 0.2107, loss: 0.5960 2023-11-13 23:35:14,471 - mmdet - INFO - Epoch [11][6400/7330] lr: 1.000e-05, eta: 0:42:37, time: 0.318, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0392, loss_cls: 0.1575, acc: 93.9734, loss_bbox: 0.2123, loss_mask: 0.2152, loss: 0.6419 2023-11-13 23:35:30,151 - mmdet - INFO - Epoch [11][6450/7330] lr: 1.000e-05, eta: 0:42:22, time: 0.314, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0373, loss_cls: 0.1448, acc: 94.4714, loss_bbox: 0.1937, loss_mask: 0.2093, loss: 0.6016 2023-11-13 23:35:45,390 - mmdet - INFO - Epoch [11][6500/7330] lr: 1.000e-05, eta: 0:42:06, time: 0.305, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0354, loss_cls: 0.1405, acc: 94.6746, loss_bbox: 0.1928, loss_mask: 0.2055, loss: 0.5889 2023-11-13 23:36:01,036 - mmdet - INFO - Epoch [11][6550/7330] lr: 1.000e-05, eta: 0:41:51, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0366, loss_cls: 0.1468, acc: 94.3416, loss_bbox: 0.2011, loss_mask: 0.2114, loss: 0.6121 2023-11-13 23:36:16,390 - mmdet - INFO - Epoch [11][6600/7330] lr: 1.000e-05, eta: 0:41:36, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0349, loss_cls: 0.1408, acc: 94.5808, loss_bbox: 0.1910, loss_mask: 0.2088, loss: 0.5903 2023-11-13 23:36:31,515 - mmdet - INFO - Epoch [11][6650/7330] lr: 1.000e-05, eta: 0:41:20, time: 0.303, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0342, loss_cls: 0.1408, acc: 94.6167, loss_bbox: 0.1933, loss_mask: 0.2030, loss: 0.5852 2023-11-13 23:36:47,086 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:36:47,086 - mmdet - INFO - Epoch [11][6700/7330] lr: 1.000e-05, eta: 0:41:05, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0352, loss_cls: 0.1445, acc: 94.4646, loss_bbox: 0.1996, loss_mask: 0.2093, loss: 0.6048 2023-11-13 23:37:03,184 - mmdet - INFO - Epoch [11][6750/7330] lr: 1.000e-05, eta: 0:40:49, time: 0.322, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0388, loss_cls: 0.1560, acc: 93.9705, loss_bbox: 0.2099, loss_mask: 0.2142, loss: 0.6357 2023-11-13 23:37:18,344 - mmdet - INFO - Epoch [11][6800/7330] lr: 1.000e-05, eta: 0:40:34, time: 0.303, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0343, loss_cls: 0.1409, acc: 94.5557, loss_bbox: 0.1869, loss_mask: 0.2061, loss: 0.5826 2023-11-13 23:37:33,836 - mmdet - INFO - Epoch [11][6850/7330] lr: 1.000e-05, eta: 0:40:18, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0360, loss_cls: 0.1476, acc: 94.3911, loss_bbox: 0.1952, loss_mask: 0.2093, loss: 0.6040 2023-11-13 23:37:49,162 - mmdet - INFO - Epoch [11][6900/7330] lr: 1.000e-05, eta: 0:40:03, time: 0.307, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0378, loss_cls: 0.1520, acc: 94.1655, loss_bbox: 0.2079, loss_mask: 0.2105, loss: 0.6240 2023-11-13 23:38:04,855 - mmdet - INFO - Epoch [11][6950/7330] lr: 1.000e-05, eta: 0:39:47, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0367, loss_cls: 0.1476, acc: 94.3735, loss_bbox: 0.1993, loss_mask: 0.2043, loss: 0.6037 2023-11-13 23:38:20,160 - mmdet - INFO - Epoch [11][7000/7330] lr: 1.000e-05, eta: 0:39:32, time: 0.306, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0349, loss_cls: 0.1427, acc: 94.5405, loss_bbox: 0.1943, loss_mask: 0.2035, loss: 0.5912 2023-11-13 23:38:35,241 - mmdet - INFO - Epoch [11][7050/7330] lr: 1.000e-05, eta: 0:39:16, time: 0.302, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0331, loss_cls: 0.1410, acc: 94.6572, loss_bbox: 0.1927, loss_mask: 0.2055, loss: 0.5873 2023-11-13 23:38:50,488 - mmdet - INFO - Epoch [11][7100/7330] lr: 1.000e-05, eta: 0:39:01, time: 0.305, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0336, loss_cls: 0.1451, acc: 94.4219, loss_bbox: 0.1936, loss_mask: 0.2070, loss: 0.5936 2023-11-13 23:39:05,716 - mmdet - INFO - Epoch [11][7150/7330] lr: 1.000e-05, eta: 0:38:45, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0349, loss_cls: 0.1422, acc: 94.5515, loss_bbox: 0.1924, loss_mask: 0.2053, loss: 0.5897 2023-11-13 23:39:21,547 - mmdet - INFO - Epoch [11][7200/7330] lr: 1.000e-05, eta: 0:38:30, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0381, loss_cls: 0.1509, acc: 94.2473, loss_bbox: 0.2024, loss_mask: 0.2089, loss: 0.6163 2023-11-13 23:39:36,680 - mmdet - INFO - Epoch [11][7250/7330] lr: 1.000e-05, eta: 0:38:14, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0358, loss_cls: 0.1436, acc: 94.4167, loss_bbox: 0.1914, loss_mask: 0.2096, loss: 0.5961 2023-11-13 23:39:52,228 - mmdet - INFO - Epoch [11][7300/7330] lr: 1.000e-05, eta: 0:37:59, time: 0.311, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0353, loss_cls: 0.1387, acc: 94.6453, loss_bbox: 0.1944, loss_mask: 0.2039, loss: 0.5880 2023-11-13 23:40:01,776 - mmdet - INFO - Saving checkpoint at 11 epochs 2023-11-13 23:40:45,540 - mmdet - INFO - Evaluating bbox... 2023-11-13 23:41:16,773 - 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 ] = 0.695 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.527 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.302 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 ] = 0.626 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.410 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.637 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.746 2023-11-13 23:41:16,776 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.581 | bicycle | 0.371 | car | 0.488 | | motorcycle | 0.490 | airplane | 0.717 | bus | 0.707 | | train | 0.686 | truck | 0.430 | boat | 0.327 | | traffic light | 0.309 | fire hydrant | 0.729 | stop sign | 0.712 | | parking meter | 0.515 | bench | 0.302 | bird | 0.410 | | cat | 0.740 | dog | 0.686 | horse | 0.624 | | sheep | 0.579 | cow | 0.633 | elephant | 0.680 | | bear | 0.758 | zebra | 0.708 | giraffe | 0.701 | | backpack | 0.221 | umbrella | 0.461 | handbag | 0.224 | | tie | 0.379 | suitcase | 0.479 | frisbee | 0.720 | | skis | 0.316 | snowboard | 0.427 | sports ball | 0.479 | | kite | 0.470 | baseball bat | 0.405 | baseball glove | 0.429 | | skateboard | 0.573 | surfboard | 0.466 | tennis racket | 0.534 | | bottle | 0.458 | wine glass | 0.418 | cup | 0.511 | | fork | 0.443 | knife | 0.292 | spoon | 0.255 | | bowl | 0.467 | banana | 0.290 | apple | 0.279 | | sandwich | 0.412 | orange | 0.371 | broccoli | 0.273 | | carrot | 0.264 | hot dog | 0.451 | pizza | 0.540 | | donut | 0.552 | cake | 0.430 | chair | 0.356 | | couch | 0.493 | potted plant | 0.343 | bed | 0.483 | | dining table | 0.314 | toilet | 0.661 | tv | 0.639 | | laptop | 0.671 | mouse | 0.649 | remote | 0.411 | | keyboard | 0.599 | cell phone | 0.456 | microwave | 0.620 | | oven | 0.393 | toaster | 0.451 | sink | 0.449 | | refrigerator | 0.630 | book | 0.200 | clock | 0.527 | | vase | 0.430 | scissors | 0.426 | teddy bear | 0.526 | | hair drier | 0.124 | toothbrush | 0.333 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:41:16,776 - mmdet - INFO - Evaluating segm... 2023-11-13 23:41:47,579 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.431 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.667 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.463 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.461 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.618 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.542 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.542 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.542 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.354 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.701 2023-11-13 23:41:47,582 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.503 | bicycle | 0.222 | car | 0.446 | | motorcycle | 0.394 | airplane | 0.566 | bus | 0.688 | | train | 0.669 | truck | 0.414 | boat | 0.298 | | traffic light | 0.293 | fire hydrant | 0.705 | stop sign | 0.688 | | parking meter | 0.507 | bench | 0.228 | bird | 0.344 | | cat | 0.716 | dog | 0.626 | horse | 0.460 | | sheep | 0.525 | cow | 0.540 | elephant | 0.624 | | bear | 0.756 | zebra | 0.606 | giraffe | 0.550 | | backpack | 0.229 | umbrella | 0.518 | handbag | 0.221 | | tie | 0.350 | suitcase | 0.490 | frisbee | 0.679 | | skis | 0.062 | snowboard | 0.286 | sports ball | 0.474 | | kite | 0.331 | baseball bat | 0.314 | baseball glove | 0.461 | | skateboard | 0.359 | surfboard | 0.394 | tennis racket | 0.594 | | bottle | 0.439 | wine glass | 0.374 | cup | 0.510 | | fork | 0.236 | knife | 0.197 | spoon | 0.183 | | bowl | 0.436 | banana | 0.240 | apple | 0.265 | | sandwich | 0.443 | orange | 0.367 | broccoli | 0.250 | | carrot | 0.230 | hot dog | 0.337 | pizza | 0.525 | | donut | 0.549 | cake | 0.429 | chair | 0.251 | | couch | 0.410 | potted plant | 0.293 | bed | 0.399 | | dining table | 0.191 | toilet | 0.636 | tv | 0.663 | | laptop | 0.670 | mouse | 0.636 | remote | 0.383 | | keyboard | 0.577 | cell phone | 0.419 | microwave | 0.639 | | oven | 0.370 | toaster | 0.457 | sink | 0.423 | | refrigerator | 0.651 | book | 0.149 | clock | 0.535 | | vase | 0.419 | scissors | 0.330 | teddy bear | 0.502 | | hair drier | 0.091 | toothbrush | 0.231 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:41:47,995 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_9.pth was removed 2023-11-13 23:41:49,597 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_11.pth. 2023-11-13 23:41:49,597 - mmdet - INFO - Best bbox_mAP is 0.4794 at 11 epoch. 2023-11-13 23:41:49,597 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-13 23:41:49,597 - mmdet - INFO - Epoch(val) [11][625] bbox_mAP: 0.4794, bbox_mAP_50: 0.6949, bbox_mAP_75: 0.5271, bbox_mAP_s: 0.3021, bbox_mAP_m: 0.5155, bbox_mAP_l: 0.6257, bbox_mAP_copypaste: 0.4794 0.6949 0.5271 0.3021 0.5155 0.6257, segm_mAP: 0.4308, segm_mAP_50: 0.6674, segm_mAP_75: 0.4633, segm_mAP_s: 0.2245, segm_mAP_m: 0.4611, segm_mAP_l: 0.6176, segm_mAP_copypaste: 0.4308 0.6674 0.4633 0.2245 0.4611 0.6176 2023-11-13 23:42:09,049 - mmdet - INFO - Epoch [12][50/7330] lr: 1.000e-06, eta: 0:37:33, time: 0.389, data_time: 0.086, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0355, loss_cls: 0.1425, acc: 94.5332, loss_bbox: 0.1931, loss_mask: 0.2054, loss: 0.5913 2023-11-13 23:42:25,014 - mmdet - INFO - Epoch [12][100/7330] lr: 1.000e-06, eta: 0:37:18, time: 0.319, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0343, loss_cls: 0.1441, acc: 94.3923, loss_bbox: 0.1958, loss_mask: 0.2056, loss: 0.5936 2023-11-13 23:42:41,479 - mmdet - INFO - Epoch [12][150/7330] lr: 1.000e-06, eta: 0:37:03, time: 0.329, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0380, loss_cls: 0.1411, acc: 94.5171, loss_bbox: 0.1995, loss_mask: 0.2089, loss: 0.6027 2023-11-13 23:42:58,005 - mmdet - INFO - Epoch [12][200/7330] lr: 1.000e-06, eta: 0:36:47, time: 0.330, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0377, loss_cls: 0.1508, acc: 94.1782, loss_bbox: 0.2035, loss_mask: 0.2107, loss: 0.6193 2023-11-13 23:43:14,186 - mmdet - INFO - Epoch [12][250/7330] lr: 1.000e-06, eta: 0:36:32, time: 0.324, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0359, loss_cls: 0.1431, acc: 94.5581, loss_bbox: 0.1930, loss_mask: 0.2073, loss: 0.5941 2023-11-13 23:43:29,753 - mmdet - INFO - Epoch [12][300/7330] lr: 1.000e-06, eta: 0:36:16, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0339, loss_cls: 0.1382, acc: 94.6221, loss_bbox: 0.1910, loss_mask: 0.2046, loss: 0.5818 2023-11-13 23:43:46,070 - mmdet - INFO - Epoch [12][350/7330] lr: 1.000e-06, eta: 0:36:01, time: 0.326, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0365, loss_cls: 0.1479, acc: 94.3425, loss_bbox: 0.2027, loss_mask: 0.2134, loss: 0.6160 2023-11-13 23:44:02,120 - mmdet - INFO - Epoch [12][400/7330] lr: 1.000e-06, eta: 0:35:45, time: 0.321, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0358, loss_cls: 0.1448, acc: 94.4653, loss_bbox: 0.1999, loss_mask: 0.2059, loss: 0.6026 2023-11-13 23:44:18,108 - mmdet - INFO - Epoch [12][450/7330] lr: 1.000e-06, eta: 0:35:30, time: 0.320, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0378, loss_cls: 0.1524, acc: 94.2229, loss_bbox: 0.2011, loss_mask: 0.2062, loss: 0.6152 2023-11-13 23:44:34,269 - mmdet - INFO - Epoch [12][500/7330] lr: 1.000e-06, eta: 0:35:15, time: 0.323, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0366, loss_cls: 0.1501, acc: 94.3105, loss_bbox: 0.2027, loss_mask: 0.2083, loss: 0.6135 2023-11-13 23:44:50,088 - mmdet - INFO - Epoch [12][550/7330] lr: 1.000e-06, eta: 0:34:59, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0341, loss_cls: 0.1396, acc: 94.6501, loss_bbox: 0.1933, loss_mask: 0.2097, loss: 0.5903 2023-11-13 23:45:06,440 - mmdet - INFO - Epoch [12][600/7330] lr: 1.000e-06, eta: 0:34:44, time: 0.327, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0366, loss_cls: 0.1467, acc: 94.3037, loss_bbox: 0.2006, loss_mask: 0.2110, loss: 0.6106 2023-11-13 23:45:22,650 - mmdet - INFO - Epoch [12][650/7330] lr: 1.000e-06, eta: 0:34:28, time: 0.324, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0353, loss_cls: 0.1443, acc: 94.4224, loss_bbox: 0.1968, loss_mask: 0.2092, loss: 0.6005 2023-11-13 23:45:38,822 - mmdet - INFO - Epoch [12][700/7330] lr: 1.000e-06, eta: 0:34:13, time: 0.323, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0355, loss_cls: 0.1441, acc: 94.4912, loss_bbox: 0.1987, loss_mask: 0.2086, loss: 0.6026 2023-11-13 23:45:54,456 - mmdet - INFO - Epoch [12][750/7330] lr: 1.000e-06, eta: 0:33:57, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0342, loss_cls: 0.1393, acc: 94.6868, loss_bbox: 0.1863, loss_mask: 0.1985, loss: 0.5743 2023-11-13 23:46:10,076 - mmdet - INFO - Epoch [12][800/7330] lr: 1.000e-06, eta: 0:33:42, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0348, loss_cls: 0.1390, acc: 94.6707, loss_bbox: 0.1883, loss_mask: 0.2047, loss: 0.5819 2023-11-13 23:46:26,045 - mmdet - INFO - Epoch [12][850/7330] lr: 1.000e-06, eta: 0:33:26, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0352, loss_cls: 0.1412, acc: 94.5586, loss_bbox: 0.1951, loss_mask: 0.2104, loss: 0.5964 2023-11-13 23:46:41,589 - mmdet - INFO - Epoch [12][900/7330] lr: 1.000e-06, eta: 0:33:11, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0353, loss_cls: 0.1468, acc: 94.4360, loss_bbox: 0.1910, loss_mask: 0.2100, loss: 0.5975 2023-11-13 23:46:56,929 - mmdet - INFO - Epoch [12][950/7330] lr: 1.000e-06, eta: 0:32:55, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0328, loss_cls: 0.1350, acc: 94.8015, loss_bbox: 0.1832, loss_mask: 0.2024, loss: 0.5660 2023-11-13 23:47:12,519 - mmdet - INFO - Epoch [12][1000/7330] lr: 1.000e-06, eta: 0:32:40, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0332, loss_cls: 0.1393, acc: 94.5779, loss_bbox: 0.1872, loss_mask: 0.2030, loss: 0.5761 2023-11-13 23:47:28,096 - mmdet - INFO - Epoch [12][1050/7330] lr: 1.000e-06, eta: 0:32:25, time: 0.312, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0337, loss_cls: 0.1355, acc: 94.8491, loss_bbox: 0.1844, loss_mask: 0.2009, loss: 0.5681 2023-11-13 23:47:44,021 - mmdet - INFO - Epoch [12][1100/7330] lr: 1.000e-06, eta: 0:32:09, time: 0.319, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0357, loss_cls: 0.1453, acc: 94.4929, loss_bbox: 0.1940, loss_mask: 0.2005, loss: 0.5908 2023-11-13 23:47:59,956 - mmdet - INFO - Epoch [12][1150/7330] lr: 1.000e-06, eta: 0:31:54, time: 0.319, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0369, loss_cls: 0.1452, acc: 94.3960, loss_bbox: 0.2003, loss_mask: 0.2075, loss: 0.6066 2023-11-13 23:48:15,942 - mmdet - INFO - Epoch [12][1200/7330] lr: 1.000e-06, eta: 0:31:38, time: 0.320, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0350, loss_cls: 0.1377, acc: 94.6702, loss_bbox: 0.1918, loss_mask: 0.2054, loss: 0.5854 2023-11-13 23:48:32,261 - mmdet - INFO - Epoch [12][1250/7330] lr: 1.000e-06, eta: 0:31:23, time: 0.326, data_time: 0.027, memory: 3904, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0368, loss_cls: 0.1454, acc: 94.4080, loss_bbox: 0.1946, loss_mask: 0.2078, loss: 0.6017 2023-11-13 23:48:47,848 - mmdet - INFO - Epoch [12][1300/7330] lr: 1.000e-06, eta: 0:31:07, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0355, loss_cls: 0.1501, acc: 94.2202, loss_bbox: 0.2032, loss_mask: 0.2072, loss: 0.6110 2023-11-13 23:49:03,620 - mmdet - INFO - Epoch [12][1350/7330] lr: 1.000e-06, eta: 0:30:52, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0354, loss_cls: 0.1423, acc: 94.5835, loss_bbox: 0.1939, loss_mask: 0.2040, loss: 0.5908 2023-11-13 23:49:19,392 - mmdet - INFO - Epoch [12][1400/7330] lr: 1.000e-06, eta: 0:30:36, time: 0.315, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0354, loss_cls: 0.1422, acc: 94.5886, loss_bbox: 0.1976, loss_mask: 0.2087, loss: 0.5989 2023-11-13 23:49:35,111 - mmdet - INFO - Epoch [12][1450/7330] lr: 1.000e-06, eta: 0:30:21, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0384, loss_cls: 0.1534, acc: 94.0166, loss_bbox: 0.2025, loss_mask: 0.2103, loss: 0.6215 2023-11-13 23:49:50,868 - mmdet - INFO - Epoch [12][1500/7330] lr: 1.000e-06, eta: 0:30:05, time: 0.315, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0345, loss_cls: 0.1409, acc: 94.5591, loss_bbox: 0.1927, loss_mask: 0.2064, loss: 0.5896 2023-11-13 23:50:06,536 - mmdet - INFO - Epoch [12][1550/7330] lr: 1.000e-06, eta: 0:29:50, time: 0.313, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0343, loss_cls: 0.1383, acc: 94.7031, loss_bbox: 0.1875, loss_mask: 0.2014, loss: 0.5773 2023-11-13 23:50:21,718 - mmdet - INFO - Epoch [12][1600/7330] lr: 1.000e-06, eta: 0:29:34, time: 0.304, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0355, loss_cls: 0.1422, acc: 94.5002, loss_bbox: 0.1979, loss_mask: 0.2120, loss: 0.6043 2023-11-13 23:50:37,661 - mmdet - INFO - Epoch [12][1650/7330] lr: 1.000e-06, eta: 0:29:19, time: 0.319, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0374, loss_cls: 0.1450, acc: 94.3142, loss_bbox: 0.2006, loss_mask: 0.2119, loss: 0.6098 2023-11-13 23:50:53,096 - mmdet - INFO - Epoch [12][1700/7330] lr: 1.000e-06, eta: 0:29:03, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0330, loss_cls: 0.1333, acc: 94.8838, loss_bbox: 0.1836, loss_mask: 0.1981, loss: 0.5619 2023-11-13 23:51:09,026 - mmdet - INFO - Epoch [12][1750/7330] lr: 1.000e-06, eta: 0:28:48, time: 0.319, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0370, loss_cls: 0.1522, acc: 94.1191, loss_bbox: 0.2061, loss_mask: 0.2110, loss: 0.6223 2023-11-13 23:51:24,624 - mmdet - INFO - Epoch [12][1800/7330] lr: 1.000e-06, eta: 0:28:33, time: 0.312, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0337, loss_cls: 0.1400, acc: 94.5615, loss_bbox: 0.1942, loss_mask: 0.2086, loss: 0.5897 2023-11-13 23:51:40,335 - mmdet - INFO - Epoch [12][1850/7330] lr: 1.000e-06, eta: 0:28:17, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0349, loss_cls: 0.1413, acc: 94.6028, loss_bbox: 0.1899, loss_mask: 0.2047, loss: 0.5866 2023-11-13 23:51:55,702 - mmdet - INFO - Epoch [12][1900/7330] lr: 1.000e-06, eta: 0:28:02, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0332, loss_cls: 0.1382, acc: 94.6797, loss_bbox: 0.1928, loss_mask: 0.2062, loss: 0.5838 2023-11-13 23:52:11,419 - mmdet - INFO - Epoch [12][1950/7330] lr: 1.000e-06, eta: 0:27:46, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0359, loss_cls: 0.1484, acc: 94.3254, loss_bbox: 0.2000, loss_mask: 0.2044, loss: 0.6038 2023-11-13 23:52:27,106 - mmdet - INFO - Epoch [12][2000/7330] lr: 1.000e-06, eta: 0:27:31, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0380, loss_cls: 0.1519, acc: 94.0886, loss_bbox: 0.2070, loss_mask: 0.2095, loss: 0.6228 2023-11-13 23:52:42,978 - mmdet - INFO - Epoch [12][2050/7330] lr: 1.000e-06, eta: 0:27:15, time: 0.317, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0373, loss_cls: 0.1468, acc: 94.3704, loss_bbox: 0.1939, loss_mask: 0.2071, loss: 0.5996 2023-11-13 23:52:58,450 - mmdet - INFO - Epoch [12][2100/7330] lr: 1.000e-06, eta: 0:27:00, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0357, loss_cls: 0.1439, acc: 94.4790, loss_bbox: 0.1941, loss_mask: 0.2085, loss: 0.5963 2023-11-13 23:53:14,476 - mmdet - INFO - Epoch [12][2150/7330] lr: 1.000e-06, eta: 0:26:44, time: 0.321, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0378, loss_cls: 0.1457, acc: 94.4072, loss_bbox: 0.1992, loss_mask: 0.2044, loss: 0.6031 2023-11-13 23:53:29,995 - mmdet - INFO - Epoch [12][2200/7330] lr: 1.000e-06, eta: 0:26:29, time: 0.310, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0352, loss_cls: 0.1431, acc: 94.5264, loss_bbox: 0.1953, loss_mask: 0.2057, loss: 0.5946 2023-11-13 23:53:45,954 - mmdet - INFO - Epoch [12][2250/7330] lr: 1.000e-06, eta: 0:26:13, time: 0.319, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0364, loss_cls: 0.1493, acc: 94.2253, loss_bbox: 0.2025, loss_mask: 0.2110, loss: 0.6173 2023-11-13 23:54:01,217 - mmdet - INFO - Epoch [12][2300/7330] lr: 1.000e-06, eta: 0:25:58, time: 0.305, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0347, loss_cls: 0.1399, acc: 94.6155, loss_bbox: 0.1946, loss_mask: 0.2063, loss: 0.5901 2023-11-13 23:54:16,972 - mmdet - INFO - Epoch [12][2350/7330] lr: 1.000e-06, eta: 0:25:42, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0365, loss_cls: 0.1460, acc: 94.3726, loss_bbox: 0.1999, loss_mask: 0.2064, loss: 0.6052 2023-11-13 23:54:32,288 - mmdet - INFO - Epoch [12][2400/7330] lr: 1.000e-06, eta: 0:25:27, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0328, loss_cls: 0.1451, acc: 94.3809, loss_bbox: 0.1994, loss_mask: 0.2043, loss: 0.5965 2023-11-13 23:54:47,996 - mmdet - INFO - Epoch [12][2450/7330] lr: 1.000e-06, eta: 0:25:11, time: 0.314, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0343, loss_cls: 0.1414, acc: 94.5508, loss_bbox: 0.1898, loss_mask: 0.2041, loss: 0.5843 2023-11-13 23:55:03,803 - mmdet - INFO - Epoch [12][2500/7330] lr: 1.000e-06, eta: 0:24:56, time: 0.316, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0357, loss_cls: 0.1487, acc: 94.2649, loss_bbox: 0.2002, loss_mask: 0.2078, loss: 0.6071 2023-11-13 23:55:19,445 - mmdet - INFO - Epoch [12][2550/7330] lr: 1.000e-06, eta: 0:24:40, time: 0.313, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0352, loss_cls: 0.1395, acc: 94.6184, loss_bbox: 0.1936, loss_mask: 0.2063, loss: 0.5893 2023-11-13 23:55:35,125 - mmdet - INFO - Epoch [12][2600/7330] lr: 1.000e-06, eta: 0:24:25, time: 0.314, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0361, loss_cls: 0.1410, acc: 94.5947, loss_bbox: 0.1896, loss_mask: 0.2044, loss: 0.5861 2023-11-13 23:55:50,797 - mmdet - INFO - Epoch [12][2650/7330] lr: 1.000e-06, eta: 0:24:09, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0339, loss_cls: 0.1393, acc: 94.5879, loss_bbox: 0.1912, loss_mask: 0.2048, loss: 0.5826 2023-11-13 23:56:06,618 - mmdet - INFO - Epoch [12][2700/7330] lr: 1.000e-06, eta: 0:23:54, time: 0.316, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0347, loss_cls: 0.1423, acc: 94.5522, loss_bbox: 0.1927, loss_mask: 0.2074, loss: 0.5917 2023-11-13 23:56:22,199 - mmdet - INFO - Epoch [12][2750/7330] lr: 1.000e-06, eta: 0:23:38, time: 0.312, data_time: 0.025, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0331, loss_cls: 0.1418, acc: 94.5610, loss_bbox: 0.1913, loss_mask: 0.2023, loss: 0.5831 2023-11-13 23:56:37,862 - mmdet - INFO - Epoch [12][2800/7330] lr: 1.000e-06, eta: 0:23:23, time: 0.313, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0352, loss_cls: 0.1423, acc: 94.5513, loss_bbox: 0.1908, loss_mask: 0.2065, loss: 0.5894 2023-11-13 23:56:53,718 - mmdet - INFO - Epoch [12][2850/7330] lr: 1.000e-06, eta: 0:23:07, time: 0.317, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0363, loss_cls: 0.1418, acc: 94.5173, loss_bbox: 0.1921, loss_mask: 0.2048, loss: 0.5906 2023-11-13 23:57:09,326 - mmdet - INFO - Epoch [12][2900/7330] lr: 1.000e-06, eta: 0:22:52, time: 0.312, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0335, loss_cls: 0.1365, acc: 94.6562, loss_bbox: 0.1855, loss_mask: 0.1990, loss: 0.5684 2023-11-13 23:57:24,568 - mmdet - INFO - Epoch [12][2950/7330] lr: 1.000e-06, eta: 0:22:36, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0355, loss_cls: 0.1492, acc: 94.2395, loss_bbox: 0.2025, loss_mask: 0.2143, loss: 0.6172 2023-11-13 23:57:40,388 - mmdet - INFO - Epoch [12][3000/7330] lr: 1.000e-06, eta: 0:22:21, time: 0.316, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0368, loss_cls: 0.1466, acc: 94.3120, loss_bbox: 0.2049, loss_mask: 0.2087, loss: 0.6135 2023-11-13 23:57:56,005 - mmdet - INFO - Epoch [12][3050/7330] lr: 1.000e-06, eta: 0:22:06, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0343, loss_cls: 0.1381, acc: 94.6487, loss_bbox: 0.1880, loss_mask: 0.2019, loss: 0.5769 2023-11-13 23:58:11,689 - mmdet - INFO - Epoch [12][3100/7330] lr: 1.000e-06, eta: 0:21:50, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0352, loss_cls: 0.1409, acc: 94.5920, loss_bbox: 0.1878, loss_mask: 0.2081, loss: 0.5872 2023-11-13 23:58:27,602 - mmdet - INFO - Epoch [12][3150/7330] lr: 1.000e-06, eta: 0:21:35, time: 0.318, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0365, loss_cls: 0.1452, acc: 94.4033, loss_bbox: 0.1980, loss_mask: 0.2015, loss: 0.5965 2023-11-13 23:58:42,866 - mmdet - INFO - Epoch [12][3200/7330] lr: 1.000e-06, eta: 0:21:19, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0340, loss_cls: 0.1424, acc: 94.5227, loss_bbox: 0.1974, loss_mask: 0.2052, loss: 0.5943 2023-11-13 23:58:58,330 - mmdet - INFO - Epoch [12][3250/7330] lr: 1.000e-06, eta: 0:21:04, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0346, loss_cls: 0.1403, acc: 94.6038, loss_bbox: 0.1948, loss_mask: 0.2106, loss: 0.5954 2023-11-13 23:59:13,703 - mmdet - INFO - Epoch [12][3300/7330] lr: 1.000e-06, eta: 0:20:48, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0343, loss_cls: 0.1394, acc: 94.6611, loss_bbox: 0.1892, loss_mask: 0.1949, loss: 0.5720 2023-11-13 23:59:29,512 - mmdet - INFO - Epoch [12][3350/7330] lr: 1.000e-06, eta: 0:20:33, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0352, loss_cls: 0.1361, acc: 94.7351, loss_bbox: 0.1877, loss_mask: 0.2025, loss: 0.5780 2023-11-13 23:59:45,056 - mmdet - INFO - Epoch [12][3400/7330] lr: 1.000e-06, eta: 0:20:17, time: 0.311, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0333, loss_cls: 0.1387, acc: 94.6797, loss_bbox: 0.1913, loss_mask: 0.2035, loss: 0.5822 2023-11-14 00:00:00,306 - mmdet - INFO - Epoch [12][3450/7330] lr: 1.000e-06, eta: 0:20:02, time: 0.305, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0345, loss_cls: 0.1401, acc: 94.6001, loss_bbox: 0.1903, loss_mask: 0.2093, loss: 0.5897 2023-11-14 00:00:15,963 - mmdet - INFO - Epoch [12][3500/7330] lr: 1.000e-06, eta: 0:19:46, time: 0.313, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0348, loss_cls: 0.1429, acc: 94.5105, loss_bbox: 0.1892, loss_mask: 0.2011, loss: 0.5827 2023-11-14 00:00:31,646 - mmdet - INFO - Epoch [12][3550/7330] lr: 1.000e-06, eta: 0:19:31, time: 0.314, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0353, loss_cls: 0.1441, acc: 94.4607, loss_bbox: 0.1974, loss_mask: 0.2067, loss: 0.5999 2023-11-14 00:00:47,180 - mmdet - INFO - Epoch [12][3600/7330] lr: 1.000e-06, eta: 0:19:15, time: 0.311, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0345, loss_cls: 0.1453, acc: 94.4902, loss_bbox: 0.1976, loss_mask: 0.2061, loss: 0.5993 2023-11-14 00:01:02,753 - mmdet - INFO - Epoch [12][3650/7330] lr: 1.000e-06, eta: 0:19:00, time: 0.311, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0347, loss_cls: 0.1431, acc: 94.5225, loss_bbox: 0.1929, loss_mask: 0.2070, loss: 0.5923 2023-11-14 00:01:18,207 - mmdet - INFO - Epoch [12][3700/7330] lr: 1.000e-06, eta: 0:18:44, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0326, loss_cls: 0.1412, acc: 94.5771, loss_bbox: 0.1897, loss_mask: 0.2033, loss: 0.5811 2023-11-14 00:01:33,749 - mmdet - INFO - Epoch [12][3750/7330] lr: 1.000e-06, eta: 0:18:29, time: 0.311, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0360, loss_cls: 0.1458, acc: 94.3271, loss_bbox: 0.1994, loss_mask: 0.2027, loss: 0.5986 2023-11-14 00:01:49,471 - mmdet - INFO - Epoch [12][3800/7330] lr: 1.000e-06, eta: 0:18:13, time: 0.314, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0341, loss_cls: 0.1413, acc: 94.5918, loss_bbox: 0.1890, loss_mask: 0.2015, loss: 0.5810 2023-11-14 00:02:05,271 - mmdet - INFO - Epoch [12][3850/7330] lr: 1.000e-06, eta: 0:17:58, time: 0.316, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0364, loss_cls: 0.1425, acc: 94.5027, loss_bbox: 0.1951, loss_mask: 0.2061, loss: 0.5954 2023-11-14 00:02:20,733 - mmdet - INFO - Epoch [12][3900/7330] lr: 1.000e-06, eta: 0:17:42, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0358, loss_cls: 0.1377, acc: 94.7014, loss_bbox: 0.1917, loss_mask: 0.2056, loss: 0.5849 2023-11-14 00:02:36,359 - mmdet - INFO - Epoch [12][3950/7330] lr: 1.000e-06, eta: 0:17:27, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0368, loss_cls: 0.1494, acc: 94.3315, loss_bbox: 0.2018, loss_mask: 0.2097, loss: 0.6128 2023-11-14 00:02:51,683 - mmdet - INFO - Epoch [12][4000/7330] lr: 1.000e-06, eta: 0:17:11, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0333, loss_cls: 0.1379, acc: 94.6841, loss_bbox: 0.1887, loss_mask: 0.2044, loss: 0.5794 2023-11-14 00:03:07,212 - mmdet - INFO - Epoch [12][4050/7330] lr: 1.000e-06, eta: 0:16:56, time: 0.311, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0336, loss_cls: 0.1363, acc: 94.7104, loss_bbox: 0.1842, loss_mask: 0.2025, loss: 0.5722 2023-11-14 00:03:22,584 - mmdet - INFO - Epoch [12][4100/7330] lr: 1.000e-06, eta: 0:16:40, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0354, loss_cls: 0.1423, acc: 94.5693, loss_bbox: 0.1918, loss_mask: 0.2034, loss: 0.5877 2023-11-14 00:03:38,260 - mmdet - INFO - Epoch [12][4150/7330] lr: 1.000e-06, eta: 0:16:25, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0388, loss_cls: 0.1531, acc: 94.1643, loss_bbox: 0.2053, loss_mask: 0.2147, loss: 0.6293 2023-11-14 00:03:53,797 - mmdet - INFO - Epoch [12][4200/7330] lr: 1.000e-06, eta: 0:16:09, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0356, loss_cls: 0.1425, acc: 94.5151, loss_bbox: 0.1970, loss_mask: 0.2060, loss: 0.5964 2023-11-14 00:04:09,526 - mmdet - INFO - Epoch [12][4250/7330] lr: 1.000e-06, eta: 0:15:54, time: 0.315, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0337, loss_cls: 0.1380, acc: 94.6663, loss_bbox: 0.1886, loss_mask: 0.2031, loss: 0.5783 2023-11-14 00:04:24,878 - mmdet - INFO - Epoch [12][4300/7330] lr: 1.000e-06, eta: 0:15:38, time: 0.307, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0350, loss_cls: 0.1432, acc: 94.5540, loss_bbox: 0.1979, loss_mask: 0.2057, loss: 0.5965 2023-11-14 00:04:40,474 - mmdet - INFO - Epoch [12][4350/7330] lr: 1.000e-06, eta: 0:15:23, time: 0.312, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0361, loss_cls: 0.1406, acc: 94.5889, loss_bbox: 0.1913, loss_mask: 0.2052, loss: 0.5879 2023-11-14 00:04:55,984 - mmdet - INFO - Epoch [12][4400/7330] lr: 1.000e-06, eta: 0:15:07, time: 0.310, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0349, loss_cls: 0.1371, acc: 94.7751, loss_bbox: 0.1849, loss_mask: 0.2036, loss: 0.5748 2023-11-14 00:05:11,433 - mmdet - INFO - Epoch [12][4450/7330] lr: 1.000e-06, eta: 0:14:52, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0357, loss_cls: 0.1424, acc: 94.5457, loss_bbox: 0.1984, loss_mask: 0.2075, loss: 0.6005 2023-11-14 00:05:26,627 - mmdet - INFO - Epoch [12][4500/7330] lr: 1.000e-06, eta: 0:14:36, time: 0.304, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0333, loss_cls: 0.1389, acc: 94.7122, loss_bbox: 0.1928, loss_mask: 0.2029, loss: 0.5830 2023-11-14 00:05:41,890 - mmdet - INFO - Epoch [12][4550/7330] lr: 1.000e-06, eta: 0:14:21, time: 0.305, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0342, loss_cls: 0.1354, acc: 94.8108, loss_bbox: 0.1865, loss_mask: 0.2065, loss: 0.5768 2023-11-14 00:05:57,151 - mmdet - INFO - Epoch [12][4600/7330] lr: 1.000e-06, eta: 0:14:05, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0358, loss_cls: 0.1479, acc: 94.3491, loss_bbox: 0.1997, loss_mask: 0.2084, loss: 0.6058 2023-11-14 00:06:12,593 - mmdet - INFO - Epoch [12][4650/7330] lr: 1.000e-06, eta: 0:13:50, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0340, loss_cls: 0.1375, acc: 94.5752, loss_bbox: 0.1909, loss_mask: 0.2048, loss: 0.5822 2023-11-14 00:06:27,963 - mmdet - INFO - Epoch [12][4700/7330] lr: 1.000e-06, eta: 0:13:34, time: 0.307, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0346, loss_cls: 0.1426, acc: 94.5637, loss_bbox: 0.1917, loss_mask: 0.2045, loss: 0.5880 2023-11-14 00:06:43,669 - mmdet - INFO - Epoch [12][4750/7330] lr: 1.000e-06, eta: 0:13:19, time: 0.314, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0375, loss_cls: 0.1442, acc: 94.4683, loss_bbox: 0.1969, loss_mask: 0.2120, loss: 0.6069 2023-11-14 00:06:59,218 - mmdet - INFO - Epoch [12][4800/7330] lr: 1.000e-06, eta: 0:13:03, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0374, loss_cls: 0.1483, acc: 94.3208, loss_bbox: 0.1966, loss_mask: 0.2028, loss: 0.6010 2023-11-14 00:07:14,752 - mmdet - INFO - Epoch [12][4850/7330] lr: 1.000e-06, eta: 0:12:48, time: 0.311, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0356, loss_cls: 0.1397, acc: 94.6631, loss_bbox: 0.1948, loss_mask: 0.2055, loss: 0.5921 2023-11-14 00:07:30,217 - mmdet - INFO - Epoch [12][4900/7330] lr: 1.000e-06, eta: 0:12:32, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0364, loss_cls: 0.1454, acc: 94.5037, loss_bbox: 0.1964, loss_mask: 0.2053, loss: 0.5987 2023-11-14 00:07:45,658 - mmdet - INFO - Epoch [12][4950/7330] lr: 1.000e-06, eta: 0:12:17, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0356, loss_cls: 0.1450, acc: 94.4058, loss_bbox: 0.1966, loss_mask: 0.2082, loss: 0.6019 2023-11-14 00:08:00,614 - mmdet - INFO - Epoch [12][5000/7330] lr: 1.000e-06, eta: 0:12:01, time: 0.299, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0310, loss_cls: 0.1377, acc: 94.6987, loss_bbox: 0.1857, loss_mask: 0.2053, loss: 0.5731 2023-11-14 00:08:15,967 - mmdet - INFO - Epoch [12][5050/7330] lr: 1.000e-06, eta: 0:11:46, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0340, loss_cls: 0.1424, acc: 94.5222, loss_bbox: 0.1942, loss_mask: 0.2030, loss: 0.5884 2023-11-14 00:08:32,033 - mmdet - INFO - Epoch [12][5100/7330] lr: 1.000e-06, eta: 0:11:30, time: 0.321, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0363, loss_cls: 0.1456, acc: 94.4409, loss_bbox: 0.1973, loss_mask: 0.2105, loss: 0.6043 2023-11-14 00:08:47,399 - mmdet - INFO - Epoch [12][5150/7330] lr: 1.000e-06, eta: 0:11:15, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0347, loss_cls: 0.1439, acc: 94.4780, loss_bbox: 0.1920, loss_mask: 0.2039, loss: 0.5894 2023-11-14 00:09:02,814 - mmdet - INFO - Epoch [12][5200/7330] lr: 1.000e-06, eta: 0:10:59, time: 0.308, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0335, loss_cls: 0.1413, acc: 94.5947, loss_bbox: 0.1904, loss_mask: 0.2032, loss: 0.5834 2023-11-14 00:09:18,642 - mmdet - INFO - Epoch [12][5250/7330] lr: 1.000e-06, eta: 0:10:44, time: 0.317, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0355, loss_cls: 0.1409, acc: 94.5967, loss_bbox: 0.1950, loss_mask: 0.2049, loss: 0.5911 2023-11-14 00:09:33,746 - mmdet - INFO - Epoch [12][5300/7330] lr: 1.000e-06, eta: 0:10:28, time: 0.302, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0330, loss_cls: 0.1338, acc: 94.7935, loss_bbox: 0.1836, loss_mask: 0.2057, loss: 0.5704 2023-11-14 00:09:49,105 - mmdet - INFO - Epoch [12][5350/7330] lr: 1.000e-06, eta: 0:10:13, time: 0.307, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0340, loss_cls: 0.1410, acc: 94.6021, loss_bbox: 0.1930, loss_mask: 0.2032, loss: 0.5858 2023-11-14 00:10:04,084 - mmdet - INFO - Epoch [12][5400/7330] lr: 1.000e-06, eta: 0:09:57, time: 0.300, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0350, loss_cls: 0.1377, acc: 94.6812, loss_bbox: 0.1877, loss_mask: 0.2066, loss: 0.5800 2023-11-14 00:10:19,250 - mmdet - INFO - Epoch [12][5450/7330] lr: 1.000e-06, eta: 0:09:42, time: 0.303, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0336, loss_cls: 0.1423, acc: 94.6521, loss_bbox: 0.1902, loss_mask: 0.2045, loss: 0.5850 2023-11-14 00:10:34,734 - mmdet - INFO - Epoch [12][5500/7330] lr: 1.000e-06, eta: 0:09:26, time: 0.310, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0354, loss_cls: 0.1367, acc: 94.7285, loss_bbox: 0.1857, loss_mask: 0.2042, loss: 0.5768 2023-11-14 00:10:50,204 - mmdet - INFO - Epoch [12][5550/7330] lr: 1.000e-06, eta: 0:09:11, time: 0.309, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0366, loss_cls: 0.1384, acc: 94.5791, loss_bbox: 0.1939, loss_mask: 0.2060, loss: 0.5889 2023-11-14 00:11:05,914 - mmdet - INFO - Epoch [12][5600/7330] lr: 1.000e-06, eta: 0:08:55, time: 0.314, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0361, loss_cls: 0.1461, acc: 94.4072, loss_bbox: 0.1991, loss_mask: 0.2076, loss: 0.6053 2023-11-14 00:11:21,087 - mmdet - INFO - Epoch [12][5650/7330] lr: 1.000e-06, eta: 0:08:40, time: 0.303, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0349, loss_cls: 0.1469, acc: 94.3450, loss_bbox: 0.1966, loss_mask: 0.2081, loss: 0.6023 2023-11-14 00:11:36,684 - mmdet - INFO - Epoch [12][5700/7330] lr: 1.000e-06, eta: 0:08:24, time: 0.312, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0370, loss_cls: 0.1471, acc: 94.2898, loss_bbox: 0.2001, loss_mask: 0.2072, loss: 0.6077 2023-11-14 00:11:52,120 - mmdet - INFO - Epoch [12][5750/7330] lr: 1.000e-06, eta: 0:08:09, time: 0.309, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0331, loss_cls: 0.1340, acc: 94.8286, loss_bbox: 0.1853, loss_mask: 0.2054, loss: 0.5714 2023-11-14 00:12:07,747 - mmdet - INFO - Epoch [12][5800/7330] lr: 1.000e-06, eta: 0:07:54, time: 0.313, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0348, loss_cls: 0.1444, acc: 94.4082, loss_bbox: 0.1946, loss_mask: 0.2100, loss: 0.5993 2023-11-14 00:12:23,187 - mmdet - INFO - Epoch [12][5850/7330] lr: 1.000e-06, eta: 0:07:38, time: 0.309, data_time: 0.026, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0331, loss_cls: 0.1379, acc: 94.7146, loss_bbox: 0.1842, loss_mask: 0.2010, loss: 0.5708 2023-11-14 00:12:38,431 - mmdet - INFO - Epoch [12][5900/7330] lr: 1.000e-06, eta: 0:07:23, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0357, loss_cls: 0.1463, acc: 94.4070, loss_bbox: 0.2022, loss_mask: 0.2140, loss: 0.6142 2023-11-14 00:12:53,330 - mmdet - INFO - Epoch [12][5950/7330] lr: 1.000e-06, eta: 0:07:07, time: 0.298, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0337, loss_cls: 0.1370, acc: 94.7627, loss_bbox: 0.1860, loss_mask: 0.2006, loss: 0.5716 2023-11-14 00:13:08,961 - mmdet - INFO - Epoch [12][6000/7330] lr: 1.000e-06, eta: 0:06:52, time: 0.313, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0334, loss_cls: 0.1385, acc: 94.5808, loss_bbox: 0.1882, loss_mask: 0.2024, loss: 0.5772 2023-11-14 00:13:24,148 - mmdet - INFO - Epoch [12][6050/7330] lr: 1.000e-06, eta: 0:06:36, time: 0.304, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0334, loss_cls: 0.1372, acc: 94.6875, loss_bbox: 0.1886, loss_mask: 0.1982, loss: 0.5708 2023-11-14 00:13:39,593 - mmdet - INFO - Epoch [12][6100/7330] lr: 1.000e-06, eta: 0:06:21, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0368, loss_cls: 0.1468, acc: 94.3867, loss_bbox: 0.1973, loss_mask: 0.2084, loss: 0.6048 2023-11-14 00:13:54,845 - mmdet - INFO - Epoch [12][6150/7330] lr: 1.000e-06, eta: 0:06:05, time: 0.305, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0364, loss_cls: 0.1430, acc: 94.4717, loss_bbox: 0.1949, loss_mask: 0.2068, loss: 0.5953 2023-11-14 00:14:09,847 - mmdet - INFO - Epoch [12][6200/7330] lr: 1.000e-06, eta: 0:05:50, time: 0.300, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0320, loss_cls: 0.1392, acc: 94.6897, loss_bbox: 0.1861, loss_mask: 0.2001, loss: 0.5718 2023-11-14 00:14:25,387 - mmdet - INFO - Epoch [12][6250/7330] lr: 1.000e-06, eta: 0:05:34, time: 0.311, data_time: 0.018, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0345, loss_cls: 0.1413, acc: 94.5662, loss_bbox: 0.1903, loss_mask: 0.2086, loss: 0.5901 2023-11-14 00:14:40,554 - mmdet - INFO - Epoch [12][6300/7330] lr: 1.000e-06, eta: 0:05:19, time: 0.303, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0317, loss_cls: 0.1349, acc: 94.8477, loss_bbox: 0.1861, loss_mask: 0.2055, loss: 0.5734 2023-11-14 00:14:56,023 - mmdet - INFO - Epoch [12][6350/7330] lr: 1.000e-06, eta: 0:05:03, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0355, loss_cls: 0.1432, acc: 94.4692, loss_bbox: 0.1943, loss_mask: 0.2086, loss: 0.5953 2023-11-14 00:15:11,300 - mmdet - INFO - Epoch [12][6400/7330] lr: 1.000e-06, eta: 0:04:48, time: 0.306, data_time: 0.021, memory: 3904, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0363, loss_cls: 0.1454, acc: 94.3899, loss_bbox: 0.2005, loss_mask: 0.2106, loss: 0.6091 2023-11-14 00:15:26,855 - mmdet - INFO - Epoch [12][6450/7330] lr: 1.000e-06, eta: 0:04:32, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0352, loss_cls: 0.1424, acc: 94.4961, loss_bbox: 0.1918, loss_mask: 0.2037, loss: 0.5888 2023-11-14 00:15:42,400 - mmdet - INFO - Epoch [12][6500/7330] lr: 1.000e-06, eta: 0:04:17, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0323, loss_cls: 0.1375, acc: 94.7632, loss_bbox: 0.1834, loss_mask: 0.2024, loss: 0.5697 2023-11-14 00:15:57,670 - mmdet - INFO - Epoch [12][6550/7330] lr: 1.000e-06, eta: 0:04:01, time: 0.305, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0345, loss_cls: 0.1415, acc: 94.6255, loss_bbox: 0.1923, loss_mask: 0.2044, loss: 0.5879 2023-11-14 00:16:12,953 - mmdet - INFO - Epoch [12][6600/7330] lr: 1.000e-06, eta: 0:03:46, time: 0.306, data_time: 0.029, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0341, loss_cls: 0.1411, acc: 94.5784, loss_bbox: 0.1947, loss_mask: 0.2095, loss: 0.5942 2023-11-14 00:16:28,240 - mmdet - INFO - Epoch [12][6650/7330] lr: 1.000e-06, eta: 0:03:30, time: 0.306, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0356, loss_cls: 0.1408, acc: 94.5703, loss_bbox: 0.1899, loss_mask: 0.2070, loss: 0.5879 2023-11-14 00:16:43,775 - mmdet - INFO - Epoch [12][6700/7330] lr: 1.000e-06, eta: 0:03:15, time: 0.311, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0351, loss_cls: 0.1421, acc: 94.6201, loss_bbox: 0.1929, loss_mask: 0.2090, loss: 0.5949 2023-11-14 00:16:59,293 - mmdet - INFO - Epoch [12][6750/7330] lr: 1.000e-06, eta: 0:02:59, time: 0.310, data_time: 0.028, memory: 3904, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0344, loss_cls: 0.1406, acc: 94.5215, loss_bbox: 0.1960, loss_mask: 0.2051, loss: 0.5906 2023-11-14 00:17:15,006 - mmdet - INFO - Epoch [12][6800/7330] lr: 1.000e-06, eta: 0:02:44, time: 0.314, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0343, loss_cls: 0.1430, acc: 94.4863, loss_bbox: 0.1967, loss_mask: 0.2057, loss: 0.5944 2023-11-14 00:17:30,650 - mmdet - INFO - Epoch [12][6850/7330] lr: 1.000e-06, eta: 0:02:28, time: 0.313, data_time: 0.024, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0351, loss_cls: 0.1437, acc: 94.4656, loss_bbox: 0.1930, loss_mask: 0.2085, loss: 0.5953 2023-11-14 00:17:46,326 - mmdet - INFO - Epoch [12][6900/7330] lr: 1.000e-06, eta: 0:02:13, time: 0.314, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0361, loss_cls: 0.1486, acc: 94.3372, loss_bbox: 0.1994, loss_mask: 0.2100, loss: 0.6102 2023-11-14 00:18:01,851 - mmdet - INFO - Epoch [12][6950/7330] lr: 1.000e-06, eta: 0:01:57, time: 0.310, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0363, loss_cls: 0.1423, acc: 94.5691, loss_bbox: 0.1937, loss_mask: 0.2056, loss: 0.5929 2023-11-14 00:18:17,407 - mmdet - INFO - Epoch [12][7000/7330] lr: 1.000e-06, eta: 0:01:42, time: 0.311, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0345, loss_cls: 0.1442, acc: 94.4539, loss_bbox: 0.1987, loss_mask: 0.2055, loss: 0.5979 2023-11-14 00:18:32,871 - mmdet - INFO - Epoch [12][7050/7330] lr: 1.000e-06, eta: 0:01:26, time: 0.309, data_time: 0.019, memory: 3904, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0351, loss_cls: 0.1416, acc: 94.5239, loss_bbox: 0.1930, loss_mask: 0.2051, loss: 0.5901 2023-11-14 00:18:48,309 - mmdet - INFO - Epoch [12][7100/7330] lr: 1.000e-06, eta: 0:01:11, time: 0.309, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0343, loss_cls: 0.1323, acc: 94.9124, loss_bbox: 0.1818, loss_mask: 0.2065, loss: 0.5700 2023-11-14 00:19:03,703 - mmdet - INFO - Epoch [12][7150/7330] lr: 1.000e-06, eta: 0:00:55, time: 0.308, data_time: 0.020, memory: 3904, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0362, loss_cls: 0.1468, acc: 94.3657, loss_bbox: 0.1957, loss_mask: 0.2061, loss: 0.6007 2023-11-14 00:19:19,164 - mmdet - INFO - Epoch [12][7200/7330] lr: 1.000e-06, eta: 0:00:40, time: 0.309, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0351, loss_cls: 0.1385, acc: 94.6880, loss_bbox: 0.1903, loss_mask: 0.2052, loss: 0.5846 2023-11-14 00:19:34,552 - mmdet - INFO - Epoch [12][7250/7330] lr: 1.000e-06, eta: 0:00:24, time: 0.308, data_time: 0.022, memory: 3904, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0344, loss_cls: 0.1368, acc: 94.7200, loss_bbox: 0.1900, loss_mask: 0.2014, loss: 0.5772 2023-11-14 00:19:49,913 - mmdet - INFO - Epoch [12][7300/7330] lr: 1.000e-06, eta: 0:00:09, time: 0.307, data_time: 0.023, memory: 3904, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0355, loss_cls: 0.1432, acc: 94.4995, loss_bbox: 0.1928, loss_mask: 0.2075, loss: 0.5941 2023-11-14 00:19:59,382 - mmdet - INFO - Saving checkpoint at 12 epochs 2023-11-14 00:20:43,394 - mmdet - INFO - Evaluating bbox... 2023-11-14 00:21:13,445 - 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 ] = 0.695 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.528 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.303 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 ] = 0.629 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.408 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.637 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.750 2023-11-14 00:21:13,447 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.580 | bicycle | 0.368 | car | 0.488 | | motorcycle | 0.490 | airplane | 0.710 | bus | 0.700 | | train | 0.689 | truck | 0.430 | boat | 0.328 | | traffic light | 0.312 | fire hydrant | 0.731 | stop sign | 0.711 | | parking meter | 0.512 | bench | 0.304 | bird | 0.411 | | cat | 0.741 | dog | 0.693 | horse | 0.623 | | sheep | 0.572 | cow | 0.638 | elephant | 0.684 | | bear | 0.765 | zebra | 0.702 | giraffe | 0.698 | | backpack | 0.221 | umbrella | 0.462 | handbag | 0.223 | | tie | 0.386 | suitcase | 0.479 | frisbee | 0.722 | | skis | 0.315 | snowboard | 0.440 | sports ball | 0.482 | | kite | 0.467 | baseball bat | 0.406 | baseball glove | 0.427 | | skateboard | 0.581 | surfboard | 0.457 | tennis racket | 0.540 | | bottle | 0.458 | wine glass | 0.424 | cup | 0.513 | | fork | 0.449 | knife | 0.292 | spoon | 0.260 | | bowl | 0.467 | banana | 0.289 | apple | 0.278 | | sandwich | 0.405 | orange | 0.368 | broccoli | 0.277 | | carrot | 0.261 | hot dog | 0.455 | pizza | 0.545 | | donut | 0.555 | cake | 0.436 | chair | 0.355 | | couch | 0.495 | potted plant | 0.345 | bed | 0.489 | | dining table | 0.319 | toilet | 0.658 | tv | 0.645 | | laptop | 0.672 | mouse | 0.650 | remote | 0.415 | | keyboard | 0.601 | cell phone | 0.454 | microwave | 0.632 | | oven | 0.389 | toaster | 0.448 | sink | 0.441 | | refrigerator | 0.632 | book | 0.196 | clock | 0.516 | | vase | 0.435 | scissors | 0.425 | teddy bear | 0.532 | | hair drier | 0.116 | toothbrush | 0.332 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:21:13,447 - mmdet - INFO - Evaluating segm... 2023-11-14 00:21:43,299 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.431 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.667 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.463 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.225 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.461 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.622 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.543 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.581 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.705 2023-11-14 00:21:43,302 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.505 | bicycle | 0.224 | car | 0.446 | | motorcycle | 0.393 | airplane | 0.566 | bus | 0.681 | | train | 0.667 | truck | 0.416 | boat | 0.300 | | traffic light | 0.296 | fire hydrant | 0.701 | stop sign | 0.689 | | parking meter | 0.506 | bench | 0.229 | bird | 0.347 | | cat | 0.716 | dog | 0.636 | horse | 0.458 | | sheep | 0.526 | cow | 0.545 | elephant | 0.625 | | bear | 0.749 | zebra | 0.601 | giraffe | 0.556 | | backpack | 0.224 | umbrella | 0.514 | handbag | 0.221 | | tie | 0.356 | suitcase | 0.489 | frisbee | 0.686 | | skis | 0.062 | snowboard | 0.280 | sports ball | 0.477 | | kite | 0.326 | baseball bat | 0.316 | baseball glove | 0.462 | | skateboard | 0.359 | surfboard | 0.397 | tennis racket | 0.594 | | bottle | 0.438 | wine glass | 0.380 | cup | 0.510 | | fork | 0.243 | knife | 0.201 | spoon | 0.183 | | bowl | 0.434 | banana | 0.240 | apple | 0.265 | | sandwich | 0.435 | orange | 0.367 | broccoli | 0.251 | | carrot | 0.227 | hot dog | 0.345 | pizza | 0.530 | | donut | 0.549 | cake | 0.437 | chair | 0.252 | | couch | 0.415 | potted plant | 0.295 | bed | 0.403 | | dining table | 0.192 | toilet | 0.634 | tv | 0.665 | | laptop | 0.671 | mouse | 0.639 | remote | 0.388 | | keyboard | 0.579 | cell phone | 0.414 | microwave | 0.643 | | oven | 0.367 | toaster | 0.460 | sink | 0.418 | | refrigerator | 0.653 | book | 0.147 | clock | 0.527 | | vase | 0.421 | scissors | 0.313 | teddy bear | 0.503 | | hair drier | 0.086 | toothbrush | 0.232 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:21:43,741 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_t_fpn_1x_coco/best_bbox_mAP_epoch_11.pth was removed 2023-11-14 00:21:45,374 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_12.pth. 2023-11-14 00:21:45,375 - mmdet - INFO - Best bbox_mAP is 0.4801 at 12 epoch. 2023-11-14 00:21:45,375 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_t_fpn_1x_coco.py 2023-11-14 00:21:45,375 - mmdet - INFO - Epoch(val) [12][625] bbox_mAP: 0.4801, bbox_mAP_50: 0.6948, bbox_mAP_75: 0.5283, bbox_mAP_s: 0.3026, bbox_mAP_m: 0.5155, bbox_mAP_l: 0.6292, bbox_mAP_copypaste: 0.4801 0.6948 0.5283 0.3026 0.5155 0.6292, segm_mAP: 0.4312, segm_mAP_50: 0.6672, segm_mAP_75: 0.4631, segm_mAP_s: 0.2250, segm_mAP_m: 0.4613, segm_mAP_l: 0.6216, segm_mAP_copypaste: 0.4312 0.6672 0.4631 0.2250 0.4613 0.6216