2023-11-13 16:22:37,391 - 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 16:22:38,160 - mmdet - INFO - Distributed training: True 2023-11-13 16:22:38,815 - mmdet - INFO - Config: model = dict( type='MaskRCNN', backbone=dict( type='Flash_InternImage_nsmx', core_op='FlashDCNv3', channels=80, depths=[4, 4, 21, 4], groups=[5, 10, 20, 40], mlp_ratio=4.0, drop_path_rate=0.3, norm_layer='LN', layer_scale=1.0, offset_scale=1.0, post_norm=True, with_cp=True, op_bias=True, out_indices=(0, 1, 2, 3), init_cfg=dict( type='Pretrained', checkpoint= '/mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_s_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth' )), neck=dict( type='FPN_vitdet', in_channels=[80, 160, 320, 640], 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=33, layer_decay_rate=1.0, depths=[4, 4, 21, 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_s_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth' work_dir = './work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco' auto_resume = False gpu_ids = range(0, 8) 2023-11-13 16:22:43,288 - mmdet - INFO - Set random seed to 1524754064, deterministic: False 2023-11-13 16:22:43,289 - mmdet - INFO - using core type: FlashDCNv3 2023-11-13 16:22:43,289 - mmdet - INFO - using activation layer: GELU 2023-11-13 16:22:43,289 - mmdet - INFO - using main norm layer: LN 2023-11-13 16:22:43,289 - mmdet - INFO - using dpr: linear, 0.3 2023-11-13 16:22:43,289 - mmdet - INFO - level2_post_norm: False 2023-11-13 16:22:43,289 - mmdet - INFO - level2_post_norm_block_ids: None 2023-11-13 16:22:43,289 - mmdet - INFO - res_post_norm: False 2023-11-13 16:22:44,240 - mmdet - INFO - load checkpoint from local path: /mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_s_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth 2023-11-13 16:22:46,017 - mmdet - INFO - _IncompatibleKeys(missing_keys=[], 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 16:22:46,042 - mmdet - INFO - initialize FPN_vitdet with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'} 2023-11-13 16:22:46,060 - mmdet - INFO - initialize RPNHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01} 2023-11-13 16:22:46,064 - 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([40, 3, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv1.bias - torch.Size([40]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.weight - torch.Size([40]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.bias - torch.Size([40]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.weight - torch.Size([80, 40, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.gamma1 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.gamma2 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm1.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm1.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask_dw.weight - torch.Size([80, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask_dw.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.weight - torch.Size([135, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.bias - torch.Size([135]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.output_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.weight - torch.Size([320, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc2.weight - torch.Size([80, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.gamma1 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.gamma2 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm1.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm1.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask_dw.weight - torch.Size([80, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask_dw.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.weight - torch.Size([135, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.bias - torch.Size([135]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.output_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.weight - torch.Size([320, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc2.weight - torch.Size([80, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.gamma1 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.gamma2 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm1.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm1.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask_dw.weight - torch.Size([80, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask_dw.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.weight - torch.Size([135, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.bias - torch.Size([135]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.output_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.weight - torch.Size([320, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc2.weight - torch.Size([80, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.gamma1 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.gamma2 - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm1.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm1.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask_dw.weight - torch.Size([80, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask_dw.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.weight - torch.Size([135, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.bias - torch.Size([135]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.output_proj.weight - torch.Size([80, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.weight - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.bias - torch.Size([80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.weight - torch.Size([320, 80]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc2.weight - torch.Size([80, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.conv.weight - torch.Size([160, 80, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.gamma1 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.gamma2 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm1.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm1.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask_dw.weight - torch.Size([160, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask_dw.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.weight - torch.Size([270, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.bias - torch.Size([270]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.output_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.weight - torch.Size([640, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc2.weight - torch.Size([160, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.gamma1 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.gamma2 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm1.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm1.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask_dw.weight - torch.Size([160, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask_dw.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.weight - torch.Size([270, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.bias - torch.Size([270]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.output_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.weight - torch.Size([640, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc2.weight - torch.Size([160, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.gamma1 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.gamma2 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm1.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm1.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask_dw.weight - torch.Size([160, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask_dw.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.weight - torch.Size([270, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.bias - torch.Size([270]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.output_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.weight - torch.Size([640, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc2.weight - torch.Size([160, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.gamma1 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.gamma2 - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm1.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm1.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask_dw.weight - torch.Size([160, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask_dw.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.weight - torch.Size([270, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.bias - torch.Size([270]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.output_proj.weight - torch.Size([160, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.weight - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.bias - torch.Size([160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.weight - torch.Size([640, 160]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc2.weight - torch.Size([160, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.conv.weight - torch.Size([320, 160, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.gamma1 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.gamma2 - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm1.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm1.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask_dw.weight - torch.Size([320, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask_dw.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask.weight - torch.Size([540, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask.bias - torch.Size([540]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.value_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.value_proj.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.output_proj.weight - torch.Size([320, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm2.0.weight - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm2.0.bias - torch.Size([320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc1.weight - torch.Size([1280, 320]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc1.bias - torch.Size([1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc2.weight - torch.Size([320, 1280]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.conv.weight - torch.Size([640, 320, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.gamma1 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.gamma2 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm1.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm1.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask_dw.weight - torch.Size([640, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask_dw.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.weight - torch.Size([1080, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.bias - torch.Size([1080]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.output_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.weight - torch.Size([2560, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.bias - torch.Size([2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc2.weight - torch.Size([640, 2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.gamma1 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.gamma2 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm1.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm1.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask_dw.weight - torch.Size([640, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask_dw.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.weight - torch.Size([1080, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.bias - torch.Size([1080]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.output_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.weight - torch.Size([2560, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.bias - torch.Size([2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc2.weight - torch.Size([640, 2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.gamma1 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.gamma2 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm1.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm1.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask_dw.weight - torch.Size([640, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask_dw.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.weight - torch.Size([1080, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.bias - torch.Size([1080]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.output_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.weight - torch.Size([2560, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.bias - torch.Size([2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc2.weight - torch.Size([640, 2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.gamma1 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.gamma2 - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm1.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm1.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask_dw.weight - torch.Size([640, 1, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask_dw.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.weight - torch.Size([1080, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.bias - torch.Size([1080]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.output_proj.weight - torch.Size([640, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.weight - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.bias - torch.Size([640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.weight - torch.Size([2560, 640]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.bias - torch.Size([2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc2.weight - torch.Size([640, 2560]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx neck.lateral_convs.0.conv.weight - torch.Size([256, 80, 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, 160, 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, 320, 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, 640, 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 16:23:05,445 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled. 2023-11-13 16:23:05,445 - mmdet - INFO - {'num_layers': 33, 'layer_decay_rate': 1.0, 'depths': [4, 4, 21, 4]} 2023-11-13 16:23:05,445 - mmdet - INFO - Build CustomLayerDecayOptimizerConstructor 1.000000 - 35 2023-11-13 16:23:05,449 - 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_dw.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_dw.weight", "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_dw.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_dw.weight", "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_dw.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_dw.weight", "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_dw.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_dw.weight", "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_decay": { "param_names": [ "backbone.levels.0.downsample.conv.weight", "backbone.levels.1.blocks.0.dcn.offset_mask_dw.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_5_no_decay": { "param_names": [ "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_dw.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_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_dw.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_dw.weight", "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_dw.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_dw.weight", "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", "backbone.levels.1.blocks.3.dcn.offset_mask_dw.bias", "backbone.levels.1.blocks.3.dcn.offset_mask.bias", "backbone.levels.1.blocks.3.dcn.value_proj.bias", "backbone.levels.1.blocks.3.norm2.0.weight", "backbone.levels.1.blocks.3.norm2.0.bias", "backbone.levels.1.blocks.3.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_8_decay": { "param_names": [ "backbone.levels.1.blocks.3.dcn.offset_mask_dw.weight", "backbone.levels.1.blocks.3.dcn.offset_mask.weight", "backbone.levels.1.blocks.3.dcn.value_proj.weight", "backbone.levels.1.blocks.3.dcn.output_proj.weight", "backbone.levels.1.blocks.3.mlp.fc1.weight", "backbone.levels.1.blocks.3.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_9_decay": { "param_names": [ "backbone.levels.1.downsample.conv.weight", "backbone.levels.2.blocks.0.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.0.dcn.offset_mask.weight", "backbone.levels.2.blocks.0.dcn.value_proj.weight", "backbone.levels.2.blocks.0.dcn.output_proj.weight", "backbone.levels.2.blocks.0.mlp.fc1.weight", "backbone.levels.2.blocks.0.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_9_no_decay": { "param_names": [ "backbone.levels.1.downsample.norm.1.weight", "backbone.levels.1.downsample.norm.1.bias", "backbone.levels.2.blocks.0.gamma1", "backbone.levels.2.blocks.0.gamma2", "backbone.levels.2.blocks.0.norm1.0.weight", "backbone.levels.2.blocks.0.norm1.0.bias", "backbone.levels.2.blocks.0.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.0.dcn.offset_mask.bias", "backbone.levels.2.blocks.0.dcn.value_proj.bias", "backbone.levels.2.blocks.0.norm2.0.weight", "backbone.levels.2.blocks.0.norm2.0.bias", "backbone.levels.2.blocks.0.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_10_no_decay": { "param_names": [ "backbone.levels.2.blocks.1.gamma1", "backbone.levels.2.blocks.1.gamma2", "backbone.levels.2.blocks.1.norm1.0.weight", "backbone.levels.2.blocks.1.norm1.0.bias", "backbone.levels.2.blocks.1.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.1.dcn.offset_mask.bias", "backbone.levels.2.blocks.1.dcn.value_proj.bias", "backbone.levels.2.blocks.1.norm2.0.weight", "backbone.levels.2.blocks.1.norm2.0.bias", "backbone.levels.2.blocks.1.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_10_decay": { "param_names": [ "backbone.levels.2.blocks.1.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.1.dcn.offset_mask.weight", "backbone.levels.2.blocks.1.dcn.value_proj.weight", "backbone.levels.2.blocks.1.dcn.output_proj.weight", "backbone.levels.2.blocks.1.mlp.fc1.weight", "backbone.levels.2.blocks.1.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_11_no_decay": { "param_names": [ "backbone.levels.2.blocks.2.gamma1", "backbone.levels.2.blocks.2.gamma2", "backbone.levels.2.blocks.2.norm1.0.weight", "backbone.levels.2.blocks.2.norm1.0.bias", "backbone.levels.2.blocks.2.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.2.dcn.offset_mask.bias", "backbone.levels.2.blocks.2.dcn.value_proj.bias", "backbone.levels.2.blocks.2.norm2.0.weight", "backbone.levels.2.blocks.2.norm2.0.bias", "backbone.levels.2.blocks.2.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_11_decay": { "param_names": [ "backbone.levels.2.blocks.2.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.2.dcn.offset_mask.weight", "backbone.levels.2.blocks.2.dcn.value_proj.weight", "backbone.levels.2.blocks.2.dcn.output_proj.weight", "backbone.levels.2.blocks.2.mlp.fc1.weight", "backbone.levels.2.blocks.2.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_12_no_decay": { "param_names": [ "backbone.levels.2.blocks.3.gamma1", "backbone.levels.2.blocks.3.gamma2", "backbone.levels.2.blocks.3.norm1.0.weight", "backbone.levels.2.blocks.3.norm1.0.bias", "backbone.levels.2.blocks.3.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.3.dcn.offset_mask.bias", "backbone.levels.2.blocks.3.dcn.value_proj.bias", "backbone.levels.2.blocks.3.norm2.0.weight", "backbone.levels.2.blocks.3.norm2.0.bias", "backbone.levels.2.blocks.3.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_12_decay": { "param_names": [ "backbone.levels.2.blocks.3.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.3.dcn.offset_mask.weight", "backbone.levels.2.blocks.3.dcn.value_proj.weight", "backbone.levels.2.blocks.3.dcn.output_proj.weight", "backbone.levels.2.blocks.3.mlp.fc1.weight", "backbone.levels.2.blocks.3.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_13_no_decay": { "param_names": [ "backbone.levels.2.blocks.4.gamma1", "backbone.levels.2.blocks.4.gamma2", "backbone.levels.2.blocks.4.norm1.0.weight", "backbone.levels.2.blocks.4.norm1.0.bias", "backbone.levels.2.blocks.4.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.4.dcn.offset_mask.bias", "backbone.levels.2.blocks.4.dcn.value_proj.bias", "backbone.levels.2.blocks.4.norm2.0.weight", "backbone.levels.2.blocks.4.norm2.0.bias", "backbone.levels.2.blocks.4.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_13_decay": { "param_names": [ "backbone.levels.2.blocks.4.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.4.dcn.offset_mask.weight", "backbone.levels.2.blocks.4.dcn.value_proj.weight", "backbone.levels.2.blocks.4.dcn.output_proj.weight", "backbone.levels.2.blocks.4.mlp.fc1.weight", "backbone.levels.2.blocks.4.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_14_no_decay": { "param_names": [ "backbone.levels.2.blocks.5.gamma1", "backbone.levels.2.blocks.5.gamma2", "backbone.levels.2.blocks.5.norm1.0.weight", "backbone.levels.2.blocks.5.norm1.0.bias", "backbone.levels.2.blocks.5.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.5.dcn.offset_mask.bias", "backbone.levels.2.blocks.5.dcn.value_proj.bias", "backbone.levels.2.blocks.5.norm2.0.weight", "backbone.levels.2.blocks.5.norm2.0.bias", "backbone.levels.2.blocks.5.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_14_decay": { "param_names": [ "backbone.levels.2.blocks.5.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.5.dcn.offset_mask.weight", "backbone.levels.2.blocks.5.dcn.value_proj.weight", "backbone.levels.2.blocks.5.dcn.output_proj.weight", "backbone.levels.2.blocks.5.mlp.fc1.weight", "backbone.levels.2.blocks.5.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_15_no_decay": { "param_names": [ "backbone.levels.2.blocks.6.gamma1", "backbone.levels.2.blocks.6.gamma2", "backbone.levels.2.blocks.6.norm1.0.weight", "backbone.levels.2.blocks.6.norm1.0.bias", "backbone.levels.2.blocks.6.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.6.dcn.offset_mask.bias", "backbone.levels.2.blocks.6.dcn.value_proj.bias", "backbone.levels.2.blocks.6.norm2.0.weight", "backbone.levels.2.blocks.6.norm2.0.bias", "backbone.levels.2.blocks.6.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_15_decay": { "param_names": [ "backbone.levels.2.blocks.6.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.6.dcn.offset_mask.weight", "backbone.levels.2.blocks.6.dcn.value_proj.weight", "backbone.levels.2.blocks.6.dcn.output_proj.weight", "backbone.levels.2.blocks.6.mlp.fc1.weight", "backbone.levels.2.blocks.6.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_16_no_decay": { "param_names": [ "backbone.levels.2.blocks.7.gamma1", "backbone.levels.2.blocks.7.gamma2", "backbone.levels.2.blocks.7.norm1.0.weight", "backbone.levels.2.blocks.7.norm1.0.bias", "backbone.levels.2.blocks.7.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.7.dcn.offset_mask.bias", "backbone.levels.2.blocks.7.dcn.value_proj.bias", "backbone.levels.2.blocks.7.norm2.0.weight", "backbone.levels.2.blocks.7.norm2.0.bias", "backbone.levels.2.blocks.7.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_16_decay": { "param_names": [ "backbone.levels.2.blocks.7.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.7.dcn.offset_mask.weight", "backbone.levels.2.blocks.7.dcn.value_proj.weight", "backbone.levels.2.blocks.7.dcn.output_proj.weight", "backbone.levels.2.blocks.7.mlp.fc1.weight", "backbone.levels.2.blocks.7.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_17_no_decay": { "param_names": [ "backbone.levels.2.blocks.8.gamma1", "backbone.levels.2.blocks.8.gamma2", "backbone.levels.2.blocks.8.norm1.0.weight", "backbone.levels.2.blocks.8.norm1.0.bias", "backbone.levels.2.blocks.8.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.8.dcn.offset_mask.bias", "backbone.levels.2.blocks.8.dcn.value_proj.bias", "backbone.levels.2.blocks.8.norm2.0.weight", "backbone.levels.2.blocks.8.norm2.0.bias", "backbone.levels.2.blocks.8.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_17_decay": { "param_names": [ "backbone.levels.2.blocks.8.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.8.dcn.offset_mask.weight", "backbone.levels.2.blocks.8.dcn.value_proj.weight", "backbone.levels.2.blocks.8.dcn.output_proj.weight", "backbone.levels.2.blocks.8.mlp.fc1.weight", "backbone.levels.2.blocks.8.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_18_no_decay": { "param_names": [ "backbone.levels.2.blocks.9.gamma1", "backbone.levels.2.blocks.9.gamma2", "backbone.levels.2.blocks.9.norm1.0.weight", "backbone.levels.2.blocks.9.norm1.0.bias", "backbone.levels.2.blocks.9.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.9.dcn.offset_mask.bias", "backbone.levels.2.blocks.9.dcn.value_proj.bias", "backbone.levels.2.blocks.9.norm2.0.weight", "backbone.levels.2.blocks.9.norm2.0.bias", "backbone.levels.2.blocks.9.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_18_decay": { "param_names": [ "backbone.levels.2.blocks.9.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.9.dcn.offset_mask.weight", "backbone.levels.2.blocks.9.dcn.value_proj.weight", "backbone.levels.2.blocks.9.dcn.output_proj.weight", "backbone.levels.2.blocks.9.mlp.fc1.weight", "backbone.levels.2.blocks.9.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_19_no_decay": { "param_names": [ "backbone.levels.2.blocks.10.gamma1", "backbone.levels.2.blocks.10.gamma2", "backbone.levels.2.blocks.10.norm1.0.weight", "backbone.levels.2.blocks.10.norm1.0.bias", "backbone.levels.2.blocks.10.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.10.dcn.offset_mask.bias", "backbone.levels.2.blocks.10.dcn.value_proj.bias", "backbone.levels.2.blocks.10.norm2.0.weight", "backbone.levels.2.blocks.10.norm2.0.bias", "backbone.levels.2.blocks.10.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_19_decay": { "param_names": [ "backbone.levels.2.blocks.10.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.10.dcn.offset_mask.weight", "backbone.levels.2.blocks.10.dcn.value_proj.weight", "backbone.levels.2.blocks.10.dcn.output_proj.weight", "backbone.levels.2.blocks.10.mlp.fc1.weight", "backbone.levels.2.blocks.10.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_20_no_decay": { "param_names": [ "backbone.levels.2.blocks.11.gamma1", "backbone.levels.2.blocks.11.gamma2", "backbone.levels.2.blocks.11.norm1.0.weight", "backbone.levels.2.blocks.11.norm1.0.bias", "backbone.levels.2.blocks.11.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.11.dcn.offset_mask.bias", "backbone.levels.2.blocks.11.dcn.value_proj.bias", "backbone.levels.2.blocks.11.norm2.0.weight", "backbone.levels.2.blocks.11.norm2.0.bias", "backbone.levels.2.blocks.11.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_20_decay": { "param_names": [ "backbone.levels.2.blocks.11.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.11.dcn.offset_mask.weight", "backbone.levels.2.blocks.11.dcn.value_proj.weight", "backbone.levels.2.blocks.11.dcn.output_proj.weight", "backbone.levels.2.blocks.11.mlp.fc1.weight", "backbone.levels.2.blocks.11.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_21_no_decay": { "param_names": [ "backbone.levels.2.blocks.12.gamma1", "backbone.levels.2.blocks.12.gamma2", "backbone.levels.2.blocks.12.norm1.0.weight", "backbone.levels.2.blocks.12.norm1.0.bias", "backbone.levels.2.blocks.12.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.12.dcn.offset_mask.bias", "backbone.levels.2.blocks.12.dcn.value_proj.bias", "backbone.levels.2.blocks.12.norm2.0.weight", "backbone.levels.2.blocks.12.norm2.0.bias", "backbone.levels.2.blocks.12.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_21_decay": { "param_names": [ "backbone.levels.2.blocks.12.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.12.dcn.offset_mask.weight", "backbone.levels.2.blocks.12.dcn.value_proj.weight", "backbone.levels.2.blocks.12.dcn.output_proj.weight", "backbone.levels.2.blocks.12.mlp.fc1.weight", "backbone.levels.2.blocks.12.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_22_no_decay": { "param_names": [ "backbone.levels.2.blocks.13.gamma1", "backbone.levels.2.blocks.13.gamma2", "backbone.levels.2.blocks.13.norm1.0.weight", "backbone.levels.2.blocks.13.norm1.0.bias", "backbone.levels.2.blocks.13.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.13.dcn.offset_mask.bias", "backbone.levels.2.blocks.13.dcn.value_proj.bias", "backbone.levels.2.blocks.13.norm2.0.weight", "backbone.levels.2.blocks.13.norm2.0.bias", "backbone.levels.2.blocks.13.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_22_decay": { "param_names": [ "backbone.levels.2.blocks.13.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.13.dcn.offset_mask.weight", "backbone.levels.2.blocks.13.dcn.value_proj.weight", "backbone.levels.2.blocks.13.dcn.output_proj.weight", "backbone.levels.2.blocks.13.mlp.fc1.weight", "backbone.levels.2.blocks.13.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_23_no_decay": { "param_names": [ "backbone.levels.2.blocks.14.gamma1", "backbone.levels.2.blocks.14.gamma2", "backbone.levels.2.blocks.14.norm1.0.weight", "backbone.levels.2.blocks.14.norm1.0.bias", "backbone.levels.2.blocks.14.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.14.dcn.offset_mask.bias", "backbone.levels.2.blocks.14.dcn.value_proj.bias", "backbone.levels.2.blocks.14.norm2.0.weight", "backbone.levels.2.blocks.14.norm2.0.bias", "backbone.levels.2.blocks.14.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_23_decay": { "param_names": [ "backbone.levels.2.blocks.14.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.14.dcn.offset_mask.weight", "backbone.levels.2.blocks.14.dcn.value_proj.weight", "backbone.levels.2.blocks.14.dcn.output_proj.weight", "backbone.levels.2.blocks.14.mlp.fc1.weight", "backbone.levels.2.blocks.14.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_24_no_decay": { "param_names": [ "backbone.levels.2.blocks.15.gamma1", "backbone.levels.2.blocks.15.gamma2", "backbone.levels.2.blocks.15.norm1.0.weight", "backbone.levels.2.blocks.15.norm1.0.bias", "backbone.levels.2.blocks.15.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.15.dcn.offset_mask.bias", "backbone.levels.2.blocks.15.dcn.value_proj.bias", "backbone.levels.2.blocks.15.norm2.0.weight", "backbone.levels.2.blocks.15.norm2.0.bias", "backbone.levels.2.blocks.15.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_24_decay": { "param_names": [ "backbone.levels.2.blocks.15.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.15.dcn.offset_mask.weight", "backbone.levels.2.blocks.15.dcn.value_proj.weight", "backbone.levels.2.blocks.15.dcn.output_proj.weight", "backbone.levels.2.blocks.15.mlp.fc1.weight", "backbone.levels.2.blocks.15.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_25_no_decay": { "param_names": [ "backbone.levels.2.blocks.16.gamma1", "backbone.levels.2.blocks.16.gamma2", "backbone.levels.2.blocks.16.norm1.0.weight", "backbone.levels.2.blocks.16.norm1.0.bias", "backbone.levels.2.blocks.16.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.16.dcn.offset_mask.bias", "backbone.levels.2.blocks.16.dcn.value_proj.bias", "backbone.levels.2.blocks.16.norm2.0.weight", "backbone.levels.2.blocks.16.norm2.0.bias", "backbone.levels.2.blocks.16.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_25_decay": { "param_names": [ "backbone.levels.2.blocks.16.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.16.dcn.offset_mask.weight", "backbone.levels.2.blocks.16.dcn.value_proj.weight", "backbone.levels.2.blocks.16.dcn.output_proj.weight", "backbone.levels.2.blocks.16.mlp.fc1.weight", "backbone.levels.2.blocks.16.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_26_no_decay": { "param_names": [ "backbone.levels.2.blocks.17.gamma1", "backbone.levels.2.blocks.17.gamma2", "backbone.levels.2.blocks.17.norm1.0.weight", "backbone.levels.2.blocks.17.norm1.0.bias", "backbone.levels.2.blocks.17.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.17.dcn.offset_mask.bias", "backbone.levels.2.blocks.17.dcn.value_proj.bias", "backbone.levels.2.blocks.17.norm2.0.weight", "backbone.levels.2.blocks.17.norm2.0.bias", "backbone.levels.2.blocks.17.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_26_decay": { "param_names": [ "backbone.levels.2.blocks.17.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.17.dcn.offset_mask.weight", "backbone.levels.2.blocks.17.dcn.value_proj.weight", "backbone.levels.2.blocks.17.dcn.output_proj.weight", "backbone.levels.2.blocks.17.mlp.fc1.weight", "backbone.levels.2.blocks.17.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_27_no_decay": { "param_names": [ "backbone.levels.2.blocks.18.gamma1", "backbone.levels.2.blocks.18.gamma2", "backbone.levels.2.blocks.18.norm1.0.weight", "backbone.levels.2.blocks.18.norm1.0.bias", "backbone.levels.2.blocks.18.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.18.dcn.offset_mask.bias", "backbone.levels.2.blocks.18.dcn.value_proj.bias", "backbone.levels.2.blocks.18.norm2.0.weight", "backbone.levels.2.blocks.18.norm2.0.bias", "backbone.levels.2.blocks.18.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_27_decay": { "param_names": [ "backbone.levels.2.blocks.18.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.18.dcn.offset_mask.weight", "backbone.levels.2.blocks.18.dcn.value_proj.weight", "backbone.levels.2.blocks.18.dcn.output_proj.weight", "backbone.levels.2.blocks.18.mlp.fc1.weight", "backbone.levels.2.blocks.18.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_28_no_decay": { "param_names": [ "backbone.levels.2.blocks.19.gamma1", "backbone.levels.2.blocks.19.gamma2", "backbone.levels.2.blocks.19.norm1.0.weight", "backbone.levels.2.blocks.19.norm1.0.bias", "backbone.levels.2.blocks.19.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.19.dcn.offset_mask.bias", "backbone.levels.2.blocks.19.dcn.value_proj.bias", "backbone.levels.2.blocks.19.norm2.0.weight", "backbone.levels.2.blocks.19.norm2.0.bias", "backbone.levels.2.blocks.19.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_28_decay": { "param_names": [ "backbone.levels.2.blocks.19.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.19.dcn.offset_mask.weight", "backbone.levels.2.blocks.19.dcn.value_proj.weight", "backbone.levels.2.blocks.19.dcn.output_proj.weight", "backbone.levels.2.blocks.19.mlp.fc1.weight", "backbone.levels.2.blocks.19.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_29_no_decay": { "param_names": [ "backbone.levels.2.blocks.20.gamma1", "backbone.levels.2.blocks.20.gamma2", "backbone.levels.2.blocks.20.norm1.0.weight", "backbone.levels.2.blocks.20.norm1.0.bias", "backbone.levels.2.blocks.20.dcn.offset_mask_dw.bias", "backbone.levels.2.blocks.20.dcn.offset_mask.bias", "backbone.levels.2.blocks.20.dcn.value_proj.bias", "backbone.levels.2.blocks.20.norm2.0.weight", "backbone.levels.2.blocks.20.norm2.0.bias", "backbone.levels.2.blocks.20.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_29_decay": { "param_names": [ "backbone.levels.2.blocks.20.dcn.offset_mask_dw.weight", "backbone.levels.2.blocks.20.dcn.offset_mask.weight", "backbone.levels.2.blocks.20.dcn.value_proj.weight", "backbone.levels.2.blocks.20.dcn.output_proj.weight", "backbone.levels.2.blocks.20.mlp.fc1.weight", "backbone.levels.2.blocks.20.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_30_decay": { "param_names": [ "backbone.levels.2.downsample.conv.weight", "backbone.levels.3.blocks.0.dcn.offset_mask_dw.weight", "backbone.levels.3.blocks.0.dcn.offset_mask.weight", "backbone.levels.3.blocks.0.dcn.value_proj.weight", "backbone.levels.3.blocks.0.dcn.output_proj.weight", "backbone.levels.3.blocks.0.mlp.fc1.weight", "backbone.levels.3.blocks.0.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_30_no_decay": { "param_names": [ "backbone.levels.2.downsample.norm.1.weight", "backbone.levels.2.downsample.norm.1.bias", "backbone.levels.3.blocks.0.gamma1", "backbone.levels.3.blocks.0.gamma2", "backbone.levels.3.blocks.0.norm1.0.weight", "backbone.levels.3.blocks.0.norm1.0.bias", "backbone.levels.3.blocks.0.dcn.offset_mask_dw.bias", "backbone.levels.3.blocks.0.dcn.offset_mask.bias", "backbone.levels.3.blocks.0.dcn.value_proj.bias", "backbone.levels.3.blocks.0.norm2.0.weight", "backbone.levels.3.blocks.0.norm2.0.bias", "backbone.levels.3.blocks.0.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_31_no_decay": { "param_names": [ "backbone.levels.3.blocks.1.gamma1", "backbone.levels.3.blocks.1.gamma2", "backbone.levels.3.blocks.1.norm1.0.weight", "backbone.levels.3.blocks.1.norm1.0.bias", "backbone.levels.3.blocks.1.dcn.offset_mask_dw.bias", "backbone.levels.3.blocks.1.dcn.offset_mask.bias", "backbone.levels.3.blocks.1.dcn.value_proj.bias", "backbone.levels.3.blocks.1.norm2.0.weight", "backbone.levels.3.blocks.1.norm2.0.bias", "backbone.levels.3.blocks.1.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_31_decay": { "param_names": [ "backbone.levels.3.blocks.1.dcn.offset_mask_dw.weight", "backbone.levels.3.blocks.1.dcn.offset_mask.weight", "backbone.levels.3.blocks.1.dcn.value_proj.weight", "backbone.levels.3.blocks.1.dcn.output_proj.weight", "backbone.levels.3.blocks.1.mlp.fc1.weight", "backbone.levels.3.blocks.1.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_32_no_decay": { "param_names": [ "backbone.levels.3.blocks.2.gamma1", "backbone.levels.3.blocks.2.gamma2", "backbone.levels.3.blocks.2.norm1.0.weight", "backbone.levels.3.blocks.2.norm1.0.bias", "backbone.levels.3.blocks.2.dcn.offset_mask_dw.bias", "backbone.levels.3.blocks.2.dcn.offset_mask.bias", "backbone.levels.3.blocks.2.dcn.value_proj.bias", "backbone.levels.3.blocks.2.norm2.0.weight", "backbone.levels.3.blocks.2.norm2.0.bias", "backbone.levels.3.blocks.2.mlp.fc1.bias" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.0 }, "layer_32_decay": { "param_names": [ "backbone.levels.3.blocks.2.dcn.offset_mask_dw.weight", "backbone.levels.3.blocks.2.dcn.offset_mask.weight", "backbone.levels.3.blocks.2.dcn.value_proj.weight", "backbone.levels.3.blocks.2.dcn.output_proj.weight", "backbone.levels.3.blocks.2.mlp.fc1.weight", "backbone.levels.3.blocks.2.mlp.fc2.weight" ], "lr_scale": 1.0, "lr": 0.0001, "weight_decay": 0.05 }, "layer_33_no_decay": { "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_dw.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_33_decay": { "param_names": [ "backbone.levels.3.blocks.3.dcn.offset_mask_dw.weight", "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_34_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_34_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 16:23:05,964 - mmdet - INFO - Start running, host: lizhiqi@SH-IDC1-10-140-37-135, work_dir: /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco 2023-11-13 16:23:05,964 - 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 16:23:05,964 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs 2023-11-13 16:23:05,964 - mmdet - INFO - Checkpoints will be saved to /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco by HardDiskBackend. 2023-11-13 16:23:31,316 - mmdet - INFO - Epoch [1][50/7330] lr: 9.890e-06, eta: 12:22:35, time: 0.507, data_time: 0.086, memory: 3732, loss_rpn_cls: 0.6901, loss_rpn_bbox: 0.1067, loss_cls: 3.4160, acc: 55.7131, loss_bbox: 0.0177, loss_mask: 0.7399, loss: 4.9704 2023-11-13 16:23:50,337 - mmdet - INFO - Epoch [1][100/7330] lr: 1.988e-05, eta: 10:49:33, time: 0.380, data_time: 0.033, memory: 3799, loss_rpn_cls: 0.5255, loss_rpn_bbox: 0.1092, loss_cls: 0.5348, acc: 95.6008, loss_bbox: 0.1320, loss_mask: 0.7050, loss: 2.0065 2023-11-13 16:24:09,920 - mmdet - INFO - Epoch [1][150/7330] lr: 2.987e-05, eta: 10:23:53, time: 0.392, data_time: 0.026, memory: 4118, loss_rpn_cls: 0.3004, loss_rpn_bbox: 0.1007, loss_cls: 0.4288, acc: 93.8142, loss_bbox: 0.2141, loss_mask: 0.6840, loss: 1.7280 2023-11-13 16:24:28,775 - mmdet - INFO - Epoch [1][200/7330] lr: 3.986e-05, eta: 10:05:30, time: 0.377, data_time: 0.024, memory: 4238, loss_rpn_cls: 0.2023, loss_rpn_bbox: 0.0909, loss_cls: 0.4529, acc: 92.8225, loss_bbox: 0.2582, loss_mask: 0.6541, loss: 1.6584 2023-11-13 16:24:47,889 - mmdet - INFO - Epoch [1][250/7330] lr: 4.985e-05, eta: 9:55:53, time: 0.382, data_time: 0.027, memory: 4238, loss_rpn_cls: 0.1563, loss_rpn_bbox: 0.0955, loss_cls: 0.4902, acc: 91.7537, loss_bbox: 0.3048, loss_mask: 0.6109, loss: 1.6577 2023-11-13 16:25:07,512 - mmdet - INFO - Epoch [1][300/7330] lr: 5.984e-05, eta: 9:51:51, time: 0.392, data_time: 0.030, memory: 4366, loss_rpn_cls: 0.1154, loss_rpn_bbox: 0.0969, loss_cls: 0.5024, acc: 90.8560, loss_bbox: 0.3454, loss_mask: 0.5737, loss: 1.6337 2023-11-13 16:25:26,648 - mmdet - INFO - Epoch [1][350/7330] lr: 6.983e-05, eta: 9:46:51, time: 0.383, data_time: 0.029, memory: 4366, loss_rpn_cls: 0.0937, loss_rpn_bbox: 0.0919, loss_cls: 0.4874, acc: 90.9875, loss_bbox: 0.3417, loss_mask: 0.5313, loss: 1.5460 2023-11-13 16:25:45,771 - mmdet - INFO - Epoch [1][400/7330] lr: 7.982e-05, eta: 9:42:58, time: 0.382, data_time: 0.028, memory: 4366, loss_rpn_cls: 0.0861, loss_rpn_bbox: 0.0908, loss_cls: 0.4872, acc: 90.1045, loss_bbox: 0.3787, loss_mask: 0.4957, loss: 1.5384 2023-11-13 16:26:05,113 - mmdet - INFO - Epoch [1][450/7330] lr: 8.981e-05, eta: 9:40:35, time: 0.387, data_time: 0.030, memory: 4398, loss_rpn_cls: 0.0849, loss_rpn_bbox: 0.0846, loss_cls: 0.4603, acc: 89.7754, loss_bbox: 0.3764, loss_mask: 0.4670, loss: 1.4731 2023-11-13 16:26:24,200 - mmdet - INFO - Epoch [1][500/7330] lr: 9.980e-05, eta: 9:37:52, time: 0.382, data_time: 0.028, memory: 4398, loss_rpn_cls: 0.0783, loss_rpn_bbox: 0.0832, loss_cls: 0.4404, acc: 89.4902, loss_bbox: 0.3863, loss_mask: 0.4395, loss: 1.4277 2023-11-13 16:26:43,406 - mmdet - INFO - Epoch [1][550/7330] lr: 1.000e-04, eta: 9:35:54, time: 0.384, data_time: 0.030, memory: 4416, loss_rpn_cls: 0.0727, loss_rpn_bbox: 0.0808, loss_cls: 0.4270, acc: 89.2622, loss_bbox: 0.3911, loss_mask: 0.4216, loss: 1.3932 2023-11-13 16:27:02,700 - mmdet - INFO - Epoch [1][600/7330] lr: 1.000e-04, eta: 9:34:25, time: 0.386, data_time: 0.028, memory: 4416, loss_rpn_cls: 0.0759, loss_rpn_bbox: 0.0824, loss_cls: 0.4111, acc: 88.9473, loss_bbox: 0.3989, loss_mask: 0.4123, loss: 1.3805 2023-11-13 16:27:21,565 - mmdet - INFO - Epoch [1][650/7330] lr: 1.000e-04, eta: 9:32:10, time: 0.377, data_time: 0.021, memory: 4416, loss_rpn_cls: 0.0669, loss_rpn_bbox: 0.0763, loss_cls: 0.3705, acc: 89.9434, loss_bbox: 0.3581, loss_mask: 0.3976, loss: 1.2695 2023-11-13 16:27:40,831 - mmdet - INFO - Epoch [1][700/7330] lr: 1.000e-04, eta: 9:31:01, time: 0.385, data_time: 0.028, memory: 4416, loss_rpn_cls: 0.0591, loss_rpn_bbox: 0.0752, loss_cls: 0.3595, acc: 89.5671, loss_bbox: 0.3740, loss_mask: 0.3844, loss: 1.2521 2023-11-13 16:27:59,965 - mmdet - INFO - Epoch [1][750/7330] lr: 1.000e-04, eta: 9:29:43, time: 0.383, data_time: 0.026, memory: 4416, loss_rpn_cls: 0.0600, loss_rpn_bbox: 0.0715, loss_cls: 0.3386, acc: 90.1082, loss_bbox: 0.3544, loss_mask: 0.3781, loss: 1.2028 2023-11-13 16:28:19,065 - mmdet - INFO - Epoch [1][800/7330] lr: 1.000e-04, eta: 9:28:29, time: 0.382, data_time: 0.023, memory: 4416, loss_rpn_cls: 0.0630, loss_rpn_bbox: 0.0759, loss_cls: 0.3409, acc: 89.6355, loss_bbox: 0.3641, loss_mask: 0.3641, loss: 1.2080 2023-11-13 16:28:38,334 - mmdet - INFO - Epoch [1][850/7330] lr: 1.000e-04, eta: 9:27:39, time: 0.385, data_time: 0.026, memory: 4416, loss_rpn_cls: 0.0640, loss_rpn_bbox: 0.0767, loss_cls: 0.3429, acc: 89.6848, loss_bbox: 0.3597, loss_mask: 0.3740, loss: 1.2173 2023-11-13 16:28:57,446 - mmdet - INFO - Epoch [1][900/7330] lr: 1.000e-04, eta: 9:26:38, time: 0.382, data_time: 0.022, memory: 4416, loss_rpn_cls: 0.0630, loss_rpn_bbox: 0.0777, loss_cls: 0.3343, acc: 89.9470, loss_bbox: 0.3523, loss_mask: 0.3600, loss: 1.1874 2023-11-13 16:29:16,309 - mmdet - INFO - Epoch [1][950/7330] lr: 1.000e-04, eta: 9:25:17, time: 0.377, data_time: 0.029, memory: 4426, loss_rpn_cls: 0.0585, loss_rpn_bbox: 0.0726, loss_cls: 0.3316, acc: 89.8467, loss_bbox: 0.3576, loss_mask: 0.3528, loss: 1.1732 2023-11-13 16:29:35,784 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 16:29:35,784 - mmdet - INFO - Epoch [1][1000/7330] lr: 1.000e-04, eta: 9:24:56, time: 0.390, data_time: 0.028, memory: 4426, loss_rpn_cls: 0.0570, loss_rpn_bbox: 0.0740, loss_cls: 0.3284, acc: 89.7253, loss_bbox: 0.3603, loss_mask: 0.3475, loss: 1.1673 2023-11-13 16:29:54,774 - mmdet - INFO - Epoch [1][1050/7330] lr: 1.000e-04, eta: 9:23:55, time: 0.380, data_time: 0.026, memory: 4442, loss_rpn_cls: 0.0610, loss_rpn_bbox: 0.0722, loss_cls: 0.3243, acc: 89.9734, loss_bbox: 0.3559, loss_mask: 0.3475, loss: 1.1608 2023-11-13 16:30:13,964 - mmdet - INFO - Epoch [1][1100/7330] lr: 1.000e-04, eta: 9:23:14, time: 0.384, data_time: 0.028, memory: 4442, loss_rpn_cls: 0.0591, loss_rpn_bbox: 0.0701, loss_cls: 0.3141, acc: 90.2219, loss_bbox: 0.3456, loss_mask: 0.3393, loss: 1.1283 2023-11-13 16:30:33,458 - mmdet - INFO - Epoch [1][1150/7330] lr: 1.000e-04, eta: 9:22:58, time: 0.390, data_time: 0.029, memory: 4442, loss_rpn_cls: 0.0584, loss_rpn_bbox: 0.0750, loss_cls: 0.3224, acc: 89.9268, loss_bbox: 0.3523, loss_mask: 0.3440, loss: 1.1521 2023-11-13 16:30:52,484 - mmdet - INFO - Epoch [1][1200/7330] lr: 1.000e-04, eta: 9:22:07, time: 0.381, data_time: 0.023, memory: 4442, loss_rpn_cls: 0.0538, loss_rpn_bbox: 0.0718, loss_cls: 0.3200, acc: 89.7288, loss_bbox: 0.3616, loss_mask: 0.3379, loss: 1.1452 2023-11-13 16:31:11,744 - mmdet - INFO - Epoch [1][1250/7330] lr: 1.000e-04, eta: 9:21:35, time: 0.385, data_time: 0.023, memory: 4442, loss_rpn_cls: 0.0563, loss_rpn_bbox: 0.0723, loss_cls: 0.3055, acc: 90.2219, loss_bbox: 0.3463, loss_mask: 0.3421, loss: 1.1225 2023-11-13 16:31:31,045 - mmdet - INFO - Epoch [1][1300/7330] lr: 1.000e-04, eta: 9:21:07, time: 0.386, data_time: 0.023, memory: 4442, loss_rpn_cls: 0.0545, loss_rpn_bbox: 0.0687, loss_cls: 0.3012, acc: 90.5884, loss_bbox: 0.3294, loss_mask: 0.3279, loss: 1.0817 2023-11-13 16:31:50,235 - mmdet - INFO - Epoch [1][1350/7330] lr: 1.000e-04, eta: 9:20:33, time: 0.384, data_time: 0.030, memory: 4443, loss_rpn_cls: 0.0547, loss_rpn_bbox: 0.0688, loss_cls: 0.2906, acc: 90.6562, loss_bbox: 0.3187, loss_mask: 0.3268, loss: 1.0595 2023-11-13 16:32:09,492 - mmdet - INFO - Epoch [1][1400/7330] lr: 1.000e-04, eta: 9:20:03, time: 0.385, data_time: 0.024, memory: 4443, loss_rpn_cls: 0.0534, loss_rpn_bbox: 0.0696, loss_cls: 0.2992, acc: 90.3176, loss_bbox: 0.3333, loss_mask: 0.3294, loss: 1.0850 2023-11-13 16:32:28,453 - mmdet - INFO - Epoch [1][1450/7330] lr: 1.000e-04, eta: 9:19:17, time: 0.379, data_time: 0.023, memory: 4443, loss_rpn_cls: 0.0490, loss_rpn_bbox: 0.0629, loss_cls: 0.2997, acc: 90.2593, loss_bbox: 0.3334, loss_mask: 0.3205, loss: 1.0655 2023-11-13 16:32:47,625 - mmdet - INFO - Epoch [1][1500/7330] lr: 1.000e-04, eta: 9:18:45, time: 0.383, data_time: 0.023, memory: 4443, loss_rpn_cls: 0.0503, loss_rpn_bbox: 0.0669, loss_cls: 0.3030, acc: 90.1099, loss_bbox: 0.3378, loss_mask: 0.3234, loss: 1.0814 2023-11-13 16:33:06,311 - mmdet - INFO - Epoch [1][1550/7330] lr: 1.000e-04, eta: 9:17:46, time: 0.374, data_time: 0.029, memory: 4443, loss_rpn_cls: 0.0459, loss_rpn_bbox: 0.0612, loss_cls: 0.2826, acc: 90.8945, loss_bbox: 0.3145, loss_mask: 0.3181, loss: 1.0222 2023-11-13 16:33:25,171 - mmdet - INFO - Epoch [1][1600/7330] lr: 1.000e-04, eta: 9:17:00, time: 0.377, data_time: 0.029, memory: 4443, loss_rpn_cls: 0.0507, loss_rpn_bbox: 0.0675, loss_cls: 0.2906, acc: 90.5166, loss_bbox: 0.3276, loss_mask: 0.3112, loss: 1.0476 2023-11-13 16:33:44,238 - mmdet - INFO - Epoch [1][1650/7330] lr: 1.000e-04, eta: 9:16:25, time: 0.381, data_time: 0.019, memory: 4443, loss_rpn_cls: 0.0491, loss_rpn_bbox: 0.0681, loss_cls: 0.2930, acc: 90.3594, loss_bbox: 0.3266, loss_mask: 0.3119, loss: 1.0487 2023-11-13 16:34:03,402 - mmdet - INFO - Epoch [1][1700/7330] lr: 1.000e-04, eta: 9:15:57, time: 0.383, data_time: 0.023, memory: 4443, loss_rpn_cls: 0.0512, loss_rpn_bbox: 0.0672, loss_cls: 0.2879, acc: 90.5415, loss_bbox: 0.3178, loss_mask: 0.3091, loss: 1.0333 2023-11-13 16:34:22,443 - mmdet - INFO - Epoch [1][1750/7330] lr: 1.000e-04, eta: 9:15:23, time: 0.381, data_time: 0.027, memory: 4443, loss_rpn_cls: 0.0533, loss_rpn_bbox: 0.0691, loss_cls: 0.2853, acc: 90.4758, loss_bbox: 0.3334, loss_mask: 0.3175, loss: 1.0585 2023-11-13 16:34:41,592 - mmdet - INFO - Epoch [1][1800/7330] lr: 1.000e-04, eta: 9:14:55, time: 0.383, data_time: 0.026, memory: 4443, loss_rpn_cls: 0.0497, loss_rpn_bbox: 0.0704, loss_cls: 0.2943, acc: 90.1099, loss_bbox: 0.3317, loss_mask: 0.3133, loss: 1.0594 2023-11-13 16:35:00,120 - mmdet - INFO - Epoch [1][1850/7330] lr: 1.000e-04, eta: 9:13:59, time: 0.371, data_time: 0.021, memory: 4443, loss_rpn_cls: 0.0462, loss_rpn_bbox: 0.0598, loss_cls: 0.2675, acc: 91.2717, loss_bbox: 0.3019, loss_mask: 0.3123, loss: 0.9878 2023-11-13 16:35:18,829 - mmdet - INFO - Epoch [1][1900/7330] lr: 1.000e-04, eta: 9:13:13, time: 0.374, data_time: 0.024, memory: 4443, loss_rpn_cls: 0.0493, loss_rpn_bbox: 0.0662, loss_cls: 0.2848, acc: 90.6169, loss_bbox: 0.3241, loss_mask: 0.3075, loss: 1.0320 2023-11-13 16:35:37,782 - mmdet - INFO - Epoch [1][1950/7330] lr: 1.000e-04, eta: 9:12:39, time: 0.379, data_time: 0.026, memory: 4443, loss_rpn_cls: 0.0448, loss_rpn_bbox: 0.0608, loss_cls: 0.2799, acc: 90.9175, loss_bbox: 0.3124, loss_mask: 0.3132, loss: 1.0111 2023-11-13 16:35:56,854 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 16:35:56,854 - mmdet - INFO - Epoch [1][2000/7330] lr: 1.000e-04, eta: 9:12:11, time: 0.381, data_time: 0.023, memory: 4443, loss_rpn_cls: 0.0489, loss_rpn_bbox: 0.0623, loss_cls: 0.2743, acc: 90.9658, loss_bbox: 0.3076, loss_mask: 0.3096, loss: 1.0026 2023-11-13 16:36:15,941 - mmdet - INFO - Epoch [1][2050/7330] lr: 1.000e-04, eta: 9:11:44, time: 0.382, data_time: 0.026, memory: 4443, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0615, loss_cls: 0.2744, acc: 90.9851, loss_bbox: 0.3049, loss_mask: 0.2965, loss: 0.9830 2023-11-13 16:36:34,992 - mmdet - INFO - Epoch [1][2100/7330] lr: 1.000e-04, eta: 9:11:16, time: 0.381, data_time: 0.025, memory: 4443, loss_rpn_cls: 0.0476, loss_rpn_bbox: 0.0618, loss_cls: 0.2855, acc: 90.6528, loss_bbox: 0.3145, loss_mask: 0.3044, loss: 1.0138 2023-11-13 16:36:54,047 - mmdet - INFO - Epoch [1][2150/7330] lr: 1.000e-04, eta: 9:10:48, time: 0.381, data_time: 0.025, memory: 4443, loss_rpn_cls: 0.0476, loss_rpn_bbox: 0.0637, loss_cls: 0.2820, acc: 90.8315, loss_bbox: 0.3136, loss_mask: 0.3067, loss: 1.0135 2023-11-13 16:37:12,760 - mmdet - INFO - Epoch [1][2200/7330] lr: 1.000e-04, eta: 9:10:08, time: 0.374, data_time: 0.024, memory: 4443, loss_rpn_cls: 0.0496, loss_rpn_bbox: 0.0620, loss_cls: 0.2715, acc: 90.9468, loss_bbox: 0.3108, loss_mask: 0.3093, loss: 1.0032 2023-11-13 16:37:31,868 - mmdet - INFO - Epoch [1][2250/7330] lr: 1.000e-04, eta: 9:09:43, time: 0.382, data_time: 0.024, memory: 4443, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0614, loss_cls: 0.2678, acc: 91.0186, loss_bbox: 0.3083, loss_mask: 0.2995, loss: 0.9826 2023-11-13 16:37:50,822 - mmdet - INFO - Epoch [1][2300/7330] lr: 1.000e-04, eta: 9:09:14, time: 0.379, data_time: 0.021, memory: 4443, loss_rpn_cls: 0.0437, loss_rpn_bbox: 0.0599, loss_cls: 0.2690, acc: 91.0684, loss_bbox: 0.3113, loss_mask: 0.3047, loss: 0.9885 2023-11-13 16:38:09,711 - mmdet - INFO - Epoch [1][2350/7330] lr: 1.000e-04, eta: 9:08:42, time: 0.378, data_time: 0.025, memory: 4443, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0596, loss_cls: 0.2647, acc: 91.2683, loss_bbox: 0.3043, loss_mask: 0.2877, loss: 0.9606 2023-11-13 16:38:28,554 - mmdet - INFO - Epoch [1][2400/7330] lr: 1.000e-04, eta: 9:08:09, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0614, loss_cls: 0.2686, acc: 91.1292, loss_bbox: 0.3051, loss_mask: 0.2985, loss: 0.9792 2023-11-13 16:38:47,424 - mmdet - INFO - Epoch [1][2450/7330] lr: 1.000e-04, eta: 9:07:37, time: 0.377, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0442, loss_rpn_bbox: 0.0585, loss_cls: 0.2700, acc: 90.9709, loss_bbox: 0.3113, loss_mask: 0.2971, loss: 0.9811 2023-11-13 16:39:06,800 - mmdet - INFO - Epoch [1][2500/7330] lr: 1.000e-04, eta: 9:07:23, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0623, loss_cls: 0.2656, acc: 91.0664, loss_bbox: 0.3019, loss_mask: 0.2948, loss: 0.9691 2023-11-13 16:39:25,584 - mmdet - INFO - Epoch [1][2550/7330] lr: 1.000e-04, eta: 9:06:50, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0466, loss_rpn_bbox: 0.0618, loss_cls: 0.2692, acc: 91.1035, loss_bbox: 0.3098, loss_mask: 0.2967, loss: 0.9840 2023-11-13 16:39:44,254 - mmdet - INFO - Epoch [1][2600/7330] lr: 1.000e-04, eta: 9:06:13, time: 0.373, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0467, loss_rpn_bbox: 0.0612, loss_cls: 0.2612, acc: 91.2720, loss_bbox: 0.3006, loss_mask: 0.2927, loss: 0.9624 2023-11-13 16:40:03,015 - mmdet - INFO - Epoch [1][2650/7330] lr: 1.000e-04, eta: 9:05:40, time: 0.375, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0451, loss_rpn_bbox: 0.0595, loss_cls: 0.2688, acc: 91.0754, loss_bbox: 0.2999, loss_mask: 0.2941, loss: 0.9674 2023-11-13 16:40:22,097 - mmdet - INFO - Epoch [1][2700/7330] lr: 1.000e-04, eta: 9:05:17, time: 0.382, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0465, loss_rpn_bbox: 0.0652, loss_cls: 0.2704, acc: 90.8521, loss_bbox: 0.3088, loss_mask: 0.2979, loss: 0.9888 2023-11-13 16:40:41,128 - mmdet - INFO - Epoch [1][2750/7330] lr: 1.000e-04, eta: 9:04:53, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0471, loss_rpn_bbox: 0.0605, loss_cls: 0.2563, acc: 91.3669, loss_bbox: 0.2950, loss_mask: 0.2937, loss: 0.9526 2023-11-13 16:41:00,259 - mmdet - INFO - Epoch [1][2800/7330] lr: 1.000e-04, eta: 9:04:32, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0458, loss_rpn_bbox: 0.0636, loss_cls: 0.2607, acc: 91.1038, loss_bbox: 0.3061, loss_mask: 0.2972, loss: 0.9734 2023-11-13 16:41:19,028 - mmdet - INFO - Epoch [1][2850/7330] lr: 1.000e-04, eta: 9:04:01, time: 0.375, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0579, loss_cls: 0.2541, acc: 91.3899, loss_bbox: 0.2972, loss_mask: 0.2882, loss: 0.9420 2023-11-13 16:41:37,592 - mmdet - INFO - Epoch [1][2900/7330] lr: 1.000e-04, eta: 9:03:24, time: 0.371, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0441, loss_rpn_bbox: 0.0597, loss_cls: 0.2688, acc: 90.9033, loss_bbox: 0.3112, loss_mask: 0.2940, loss: 0.9778 2023-11-13 16:41:56,475 - mmdet - INFO - Epoch [1][2950/7330] lr: 1.000e-04, eta: 9:02:56, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0418, loss_rpn_bbox: 0.0587, loss_cls: 0.2601, acc: 91.2434, loss_bbox: 0.3006, loss_mask: 0.2932, loss: 0.9544 2023-11-13 16:42:15,620 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 16:42:15,621 - mmdet - INFO - Epoch [1][3000/7330] lr: 1.000e-04, eta: 9:02:37, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0457, loss_rpn_bbox: 0.0588, loss_cls: 0.2689, acc: 90.8499, loss_bbox: 0.3156, loss_mask: 0.2877, loss: 0.9767 2023-11-13 16:42:34,213 - mmdet - INFO - Epoch [1][3050/7330] lr: 1.000e-04, eta: 9:02:02, time: 0.372, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0454, loss_rpn_bbox: 0.0585, loss_cls: 0.2591, acc: 91.2175, loss_bbox: 0.2922, loss_mask: 0.2886, loss: 0.9438 2023-11-13 16:42:53,216 - mmdet - INFO - Epoch [1][3100/7330] lr: 1.000e-04, eta: 9:01:38, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0476, loss_rpn_bbox: 0.0605, loss_cls: 0.2670, acc: 91.0613, loss_bbox: 0.3070, loss_mask: 0.2926, loss: 0.9746 2023-11-13 16:43:12,115 - mmdet - INFO - Epoch [1][3150/7330] lr: 1.000e-04, eta: 9:01:13, time: 0.378, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0612, loss_cls: 0.2673, acc: 91.0349, loss_bbox: 0.3065, loss_mask: 0.2911, loss: 0.9696 2023-11-13 16:43:31,355 - mmdet - INFO - Epoch [1][3200/7330] lr: 1.000e-04, eta: 9:00:56, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0422, loss_rpn_bbox: 0.0622, loss_cls: 0.2706, acc: 90.8201, loss_bbox: 0.3151, loss_mask: 0.2908, loss: 0.9809 2023-11-13 16:43:49,829 - mmdet - INFO - Epoch [1][3250/7330] lr: 1.000e-04, eta: 9:00:19, time: 0.370, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0573, loss_cls: 0.2495, acc: 91.6685, loss_bbox: 0.2851, loss_mask: 0.2823, loss: 0.9147 2023-11-13 16:44:08,434 - mmdet - INFO - Epoch [1][3300/7330] lr: 1.000e-04, eta: 8:59:47, time: 0.372, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0585, loss_cls: 0.2592, acc: 91.2676, loss_bbox: 0.2964, loss_mask: 0.2906, loss: 0.9473 2023-11-13 16:44:27,480 - mmdet - INFO - Epoch [1][3350/7330] lr: 1.000e-04, eta: 8:59:25, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0615, loss_cls: 0.2603, acc: 91.3076, loss_bbox: 0.2983, loss_mask: 0.2797, loss: 0.9427 2023-11-13 16:44:46,582 - mmdet - INFO - Epoch [1][3400/7330] lr: 1.000e-04, eta: 8:59:06, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0595, loss_cls: 0.2676, acc: 91.1008, loss_bbox: 0.3028, loss_mask: 0.2867, loss: 0.9609 2023-11-13 16:45:05,615 - mmdet - INFO - Epoch [1][3450/7330] lr: 1.000e-04, eta: 8:58:44, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0610, loss_cls: 0.2628, acc: 91.0623, loss_bbox: 0.3048, loss_mask: 0.2949, loss: 0.9664 2023-11-13 16:45:24,318 - mmdet - INFO - Epoch [1][3500/7330] lr: 1.000e-04, eta: 8:58:15, time: 0.374, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0562, loss_cls: 0.2415, acc: 91.8086, loss_bbox: 0.2876, loss_mask: 0.2786, loss: 0.9016 2023-11-13 16:45:43,086 - mmdet - INFO - Epoch [1][3550/7330] lr: 1.000e-04, eta: 8:57:47, time: 0.375, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0406, loss_rpn_bbox: 0.0574, loss_cls: 0.2603, acc: 91.1724, loss_bbox: 0.3039, loss_mask: 0.2898, loss: 0.9520 2023-11-13 16:46:02,164 - mmdet - INFO - Epoch [1][3600/7330] lr: 1.000e-04, eta: 8:57:27, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0424, loss_rpn_bbox: 0.0608, loss_cls: 0.2695, acc: 90.8992, loss_bbox: 0.3101, loss_mask: 0.2846, loss: 0.9674 2023-11-13 16:46:21,187 - mmdet - INFO - Epoch [1][3650/7330] lr: 1.000e-04, eta: 8:57:06, time: 0.380, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0575, loss_cls: 0.2570, acc: 91.3269, loss_bbox: 0.2990, loss_mask: 0.2802, loss: 0.9339 2023-11-13 16:46:40,404 - mmdet - INFO - Epoch [1][3700/7330] lr: 1.000e-04, eta: 8:56:50, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0598, loss_cls: 0.2631, acc: 91.1428, loss_bbox: 0.3007, loss_mask: 0.2831, loss: 0.9482 2023-11-13 16:46:59,493 - mmdet - INFO - Epoch [1][3750/7330] lr: 1.000e-04, eta: 8:56:30, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0446, loss_rpn_bbox: 0.0601, loss_cls: 0.2627, acc: 91.1992, loss_bbox: 0.2986, loss_mask: 0.2916, loss: 0.9576 2023-11-13 16:47:18,473 - mmdet - INFO - Epoch [1][3800/7330] lr: 1.000e-04, eta: 8:56:08, time: 0.380, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0590, loss_cls: 0.2493, acc: 91.5742, loss_bbox: 0.2930, loss_mask: 0.2846, loss: 0.9305 2023-11-13 16:47:37,573 - mmdet - INFO - Epoch [1][3850/7330] lr: 1.000e-04, eta: 8:55:48, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0410, loss_rpn_bbox: 0.0574, loss_cls: 0.2481, acc: 91.6006, loss_bbox: 0.2847, loss_mask: 0.2765, loss: 0.9076 2023-11-13 16:47:56,223 - mmdet - INFO - Epoch [1][3900/7330] lr: 1.000e-04, eta: 8:55:19, time: 0.373, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0391, loss_rpn_bbox: 0.0583, loss_cls: 0.2584, acc: 91.2258, loss_bbox: 0.2997, loss_mask: 0.2842, loss: 0.9398 2023-11-13 16:48:14,859 - mmdet - INFO - Epoch [1][3950/7330] lr: 1.000e-04, eta: 8:54:50, time: 0.373, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0411, loss_rpn_bbox: 0.0569, loss_cls: 0.2515, acc: 91.4294, loss_bbox: 0.2922, loss_mask: 0.2825, loss: 0.9241 2023-11-13 16:48:33,741 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 16:48:33,741 - mmdet - INFO - Epoch [1][4000/7330] lr: 1.000e-04, eta: 8:54:27, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0410, loss_rpn_bbox: 0.0575, loss_cls: 0.2578, acc: 91.1406, loss_bbox: 0.2935, loss_mask: 0.2841, loss: 0.9339 2023-11-13 16:48:52,607 - mmdet - INFO - Epoch [1][4050/7330] lr: 1.000e-04, eta: 8:54:03, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0388, loss_rpn_bbox: 0.0537, loss_cls: 0.2550, acc: 91.2300, loss_bbox: 0.3027, loss_mask: 0.2802, loss: 0.9305 2023-11-13 16:49:11,897 - mmdet - INFO - Epoch [1][4100/7330] lr: 1.000e-04, eta: 8:53:48, time: 0.386, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0583, loss_cls: 0.2626, acc: 91.1038, loss_bbox: 0.3014, loss_mask: 0.2857, loss: 0.9506 2023-11-13 16:49:30,591 - mmdet - INFO - Epoch [1][4150/7330] lr: 1.000e-04, eta: 8:53:20, time: 0.374, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0538, loss_cls: 0.2431, acc: 91.5933, loss_bbox: 0.2868, loss_mask: 0.2791, loss: 0.8990 2023-11-13 16:49:49,500 - mmdet - INFO - Epoch [1][4200/7330] lr: 1.000e-04, eta: 8:52:58, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0403, loss_rpn_bbox: 0.0542, loss_cls: 0.2514, acc: 91.6479, loss_bbox: 0.2851, loss_mask: 0.2769, loss: 0.9079 2023-11-13 16:50:08,524 - mmdet - INFO - Epoch [1][4250/7330] lr: 1.000e-04, eta: 8:52:37, time: 0.380, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0554, loss_cls: 0.2499, acc: 91.4319, loss_bbox: 0.2926, loss_mask: 0.2840, loss: 0.9235 2023-11-13 16:50:27,433 - mmdet - INFO - Epoch [1][4300/7330] lr: 1.000e-04, eta: 8:52:15, time: 0.378, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0573, loss_cls: 0.2572, acc: 91.2778, loss_bbox: 0.2963, loss_mask: 0.2788, loss: 0.9331 2023-11-13 16:50:46,257 - mmdet - INFO - Epoch [1][4350/7330] lr: 1.000e-04, eta: 8:51:51, time: 0.376, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0568, loss_cls: 0.2555, acc: 91.3694, loss_bbox: 0.2884, loss_mask: 0.2799, loss: 0.9204 2023-11-13 16:51:05,967 - mmdet - INFO - Epoch [1][4400/7330] lr: 1.000e-04, eta: 8:51:43, time: 0.394, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0612, loss_cls: 0.2630, acc: 90.9993, loss_bbox: 0.3027, loss_mask: 0.2839, loss: 0.9523 2023-11-13 16:51:25,179 - mmdet - INFO - Epoch [1][4450/7330] lr: 1.000e-04, eta: 8:51:27, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0418, loss_rpn_bbox: 0.0558, loss_cls: 0.2486, acc: 91.6965, loss_bbox: 0.2807, loss_mask: 0.2772, loss: 0.9041 2023-11-13 16:51:44,261 - mmdet - INFO - Epoch [1][4500/7330] lr: 1.000e-04, eta: 8:51:07, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0386, loss_rpn_bbox: 0.0542, loss_cls: 0.2552, acc: 91.3608, loss_bbox: 0.2865, loss_mask: 0.2748, loss: 0.9093 2023-11-13 16:52:03,733 - mmdet - INFO - Epoch [1][4550/7330] lr: 1.000e-04, eta: 8:50:55, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0396, loss_rpn_bbox: 0.0564, loss_cls: 0.2391, acc: 91.6523, loss_bbox: 0.2794, loss_mask: 0.2799, loss: 0.8944 2023-11-13 16:52:22,515 - mmdet - INFO - Epoch [1][4600/7330] lr: 1.000e-04, eta: 8:50:30, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0575, loss_cls: 0.2497, acc: 91.6101, loss_bbox: 0.2840, loss_mask: 0.2864, loss: 0.9187 2023-11-13 16:52:42,063 - mmdet - INFO - Epoch [1][4650/7330] lr: 1.000e-04, eta: 8:50:19, time: 0.391, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0572, loss_cls: 0.2451, acc: 91.6404, loss_bbox: 0.2880, loss_mask: 0.2706, loss: 0.9011 2023-11-13 16:53:00,595 - mmdet - INFO - Epoch [1][4700/7330] lr: 1.000e-04, eta: 8:49:50, time: 0.371, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0515, loss_cls: 0.2414, acc: 91.6021, loss_bbox: 0.2854, loss_mask: 0.2761, loss: 0.8910 2023-11-13 16:53:19,818 - mmdet - INFO - Epoch [1][4750/7330] lr: 1.000e-04, eta: 8:49:33, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0554, loss_cls: 0.2418, acc: 91.8384, loss_bbox: 0.2830, loss_mask: 0.2766, loss: 0.8969 2023-11-13 16:53:39,020 - mmdet - INFO - Epoch [1][4800/7330] lr: 1.000e-04, eta: 8:49:16, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0411, loss_rpn_bbox: 0.0589, loss_cls: 0.2450, acc: 91.6885, loss_bbox: 0.2811, loss_mask: 0.2747, loss: 0.9007 2023-11-13 16:53:58,176 - mmdet - INFO - Epoch [1][4850/7330] lr: 1.000e-04, eta: 8:48:58, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0527, loss_cls: 0.2387, acc: 91.8533, loss_bbox: 0.2803, loss_mask: 0.2758, loss: 0.8870 2023-11-13 16:54:17,294 - mmdet - INFO - Epoch [1][4900/7330] lr: 1.000e-04, eta: 8:48:40, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0422, loss_rpn_bbox: 0.0561, loss_cls: 0.2494, acc: 91.4790, loss_bbox: 0.2889, loss_mask: 0.2754, loss: 0.9119 2023-11-13 16:54:36,065 - mmdet - INFO - Epoch [1][4950/7330] lr: 1.000e-04, eta: 8:48:15, time: 0.375, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0432, loss_rpn_bbox: 0.0574, loss_cls: 0.2498, acc: 91.5120, loss_bbox: 0.2867, loss_mask: 0.2770, loss: 0.9142 2023-11-13 16:54:54,622 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 16:54:54,623 - mmdet - INFO - Epoch [1][5000/7330] lr: 1.000e-04, eta: 8:47:47, time: 0.371, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0404, loss_rpn_bbox: 0.0551, loss_cls: 0.2452, acc: 91.6602, loss_bbox: 0.2784, loss_mask: 0.2754, loss: 0.8944 2023-11-13 16:55:13,337 - mmdet - INFO - Epoch [1][5050/7330] lr: 1.000e-04, eta: 8:47:22, time: 0.374, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0350, loss_rpn_bbox: 0.0526, loss_cls: 0.2384, acc: 91.8088, loss_bbox: 0.2768, loss_mask: 0.2728, loss: 0.8756 2023-11-13 16:55:32,253 - mmdet - INFO - Epoch [1][5100/7330] lr: 1.000e-04, eta: 8:47:00, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0372, loss_rpn_bbox: 0.0560, loss_cls: 0.2397, acc: 91.8594, loss_bbox: 0.2799, loss_mask: 0.2720, loss: 0.8848 2023-11-13 16:55:51,273 - mmdet - INFO - Epoch [1][5150/7330] lr: 1.000e-04, eta: 8:46:40, time: 0.380, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0396, loss_rpn_bbox: 0.0583, loss_cls: 0.2457, acc: 91.6189, loss_bbox: 0.2857, loss_mask: 0.2725, loss: 0.9018 2023-11-13 16:56:10,401 - mmdet - INFO - Epoch [1][5200/7330] lr: 1.000e-04, eta: 8:46:22, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0419, loss_rpn_bbox: 0.0583, loss_cls: 0.2450, acc: 91.5410, loss_bbox: 0.2902, loss_mask: 0.2813, loss: 0.9167 2023-11-13 16:56:29,533 - mmdet - INFO - Epoch [1][5250/7330] lr: 1.000e-04, eta: 8:46:03, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0389, loss_rpn_bbox: 0.0568, loss_cls: 0.2421, acc: 91.8396, loss_bbox: 0.2839, loss_mask: 0.2705, loss: 0.8922 2023-11-13 16:56:48,587 - mmdet - INFO - Epoch [1][5300/7330] lr: 1.000e-04, eta: 8:45:44, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0428, loss_rpn_bbox: 0.0580, loss_cls: 0.2492, acc: 91.4480, loss_bbox: 0.2884, loss_mask: 0.2707, loss: 0.9092 2023-11-13 16:57:07,684 - mmdet - INFO - Epoch [1][5350/7330] lr: 1.000e-04, eta: 8:45:25, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0539, loss_cls: 0.2328, acc: 91.8799, loss_bbox: 0.2742, loss_mask: 0.2714, loss: 0.8728 2023-11-13 16:57:26,424 - mmdet - INFO - Epoch [1][5400/7330] lr: 1.000e-04, eta: 8:45:01, time: 0.375, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0539, loss_cls: 0.2375, acc: 91.8308, loss_bbox: 0.2827, loss_mask: 0.2716, loss: 0.8824 2023-11-13 16:57:45,161 - mmdet - INFO - Epoch [1][5450/7330] lr: 1.000e-04, eta: 8:44:37, time: 0.375, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0540, loss_cls: 0.2380, acc: 91.7939, loss_bbox: 0.2805, loss_mask: 0.2685, loss: 0.8773 2023-11-13 16:58:04,510 - mmdet - INFO - Epoch [1][5500/7330] lr: 1.000e-04, eta: 8:44:22, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0407, loss_rpn_bbox: 0.0573, loss_cls: 0.2405, acc: 91.7815, loss_bbox: 0.2806, loss_mask: 0.2771, loss: 0.8962 2023-11-13 16:58:22,950 - mmdet - INFO - Epoch [1][5550/7330] lr: 1.000e-04, eta: 8:43:53, time: 0.369, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0521, loss_cls: 0.2303, acc: 91.9983, loss_bbox: 0.2708, loss_mask: 0.2665, loss: 0.8552 2023-11-13 16:58:42,037 - mmdet - INFO - Epoch [1][5600/7330] lr: 1.000e-04, eta: 8:43:34, time: 0.382, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0358, loss_rpn_bbox: 0.0531, loss_cls: 0.2416, acc: 91.6553, loss_bbox: 0.2818, loss_mask: 0.2724, loss: 0.8847 2023-11-13 16:59:00,847 - mmdet - INFO - Epoch [1][5650/7330] lr: 1.000e-04, eta: 8:43:11, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0391, loss_rpn_bbox: 0.0572, loss_cls: 0.2399, acc: 91.8083, loss_bbox: 0.2813, loss_mask: 0.2700, loss: 0.8875 2023-11-13 16:59:20,019 - mmdet - INFO - Epoch [1][5700/7330] lr: 1.000e-04, eta: 8:42:54, time: 0.383, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0415, loss_rpn_bbox: 0.0562, loss_cls: 0.2482, acc: 91.5706, loss_bbox: 0.2823, loss_mask: 0.2749, loss: 0.9030 2023-11-13 16:59:39,002 - mmdet - INFO - Epoch [1][5750/7330] lr: 1.000e-04, eta: 8:42:33, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0515, loss_cls: 0.2337, acc: 91.9766, loss_bbox: 0.2730, loss_mask: 0.2641, loss: 0.8584 2023-11-13 16:59:58,107 - mmdet - INFO - Epoch [1][5800/7330] lr: 1.000e-04, eta: 8:42:15, time: 0.382, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0374, loss_rpn_bbox: 0.0526, loss_cls: 0.2405, acc: 91.6895, loss_bbox: 0.2770, loss_mask: 0.2649, loss: 0.8725 2023-11-13 17:00:17,239 - mmdet - INFO - Epoch [1][5850/7330] lr: 1.000e-04, eta: 8:41:57, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0551, loss_cls: 0.2470, acc: 91.5344, loss_bbox: 0.2827, loss_mask: 0.2692, loss: 0.8924 2023-11-13 17:00:36,464 - mmdet - INFO - Epoch [1][5900/7330] lr: 1.000e-04, eta: 8:41:40, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0375, loss_rpn_bbox: 0.0551, loss_cls: 0.2435, acc: 91.6863, loss_bbox: 0.2815, loss_mask: 0.2723, loss: 0.8900 2023-11-13 17:00:55,293 - mmdet - INFO - Epoch [1][5950/7330] lr: 1.000e-04, eta: 8:41:17, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0525, loss_cls: 0.2337, acc: 91.9343, loss_bbox: 0.2736, loss_mask: 0.2603, loss: 0.8562 2023-11-13 17:01:14,450 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 17:01:14,450 - mmdet - INFO - Epoch [1][6000/7330] lr: 1.000e-04, eta: 8:40:59, time: 0.383, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0557, loss_cls: 0.2400, acc: 91.7722, loss_bbox: 0.2848, loss_mask: 0.2729, loss: 0.8914 2023-11-13 17:01:33,352 - mmdet - INFO - Epoch [1][6050/7330] lr: 1.000e-04, eta: 8:40:38, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0518, loss_cls: 0.2278, acc: 92.1743, loss_bbox: 0.2711, loss_mask: 0.2664, loss: 0.8537 2023-11-13 17:01:51,962 - mmdet - INFO - Epoch [1][6100/7330] lr: 1.000e-04, eta: 8:40:13, time: 0.372, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0534, loss_cls: 0.2362, acc: 91.8486, loss_bbox: 0.2778, loss_mask: 0.2744, loss: 0.8823 2023-11-13 17:02:10,943 - mmdet - INFO - Epoch [1][6150/7330] lr: 1.000e-04, eta: 8:39:53, time: 0.380, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0397, loss_rpn_bbox: 0.0555, loss_cls: 0.2385, acc: 91.8572, loss_bbox: 0.2748, loss_mask: 0.2700, loss: 0.8786 2023-11-13 17:02:30,274 - mmdet - INFO - Epoch [1][6200/7330] lr: 1.000e-04, eta: 8:39:37, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0391, loss_rpn_bbox: 0.0578, loss_cls: 0.2351, acc: 91.8906, loss_bbox: 0.2784, loss_mask: 0.2704, loss: 0.8808 2023-11-13 17:02:48,719 - mmdet - INFO - Epoch [1][6250/7330] lr: 1.000e-04, eta: 8:39:10, time: 0.369, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0375, loss_rpn_bbox: 0.0546, loss_cls: 0.2299, acc: 92.0312, loss_bbox: 0.2735, loss_mask: 0.2697, loss: 0.8652 2023-11-13 17:03:07,838 - mmdet - INFO - Epoch [1][6300/7330] lr: 1.000e-04, eta: 8:38:52, time: 0.382, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0425, loss_rpn_bbox: 0.0560, loss_cls: 0.2340, acc: 92.0344, loss_bbox: 0.2690, loss_mask: 0.2666, loss: 0.8681 2023-11-13 17:03:27,074 - mmdet - INFO - Epoch [1][6350/7330] lr: 1.000e-04, eta: 8:38:35, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0526, loss_cls: 0.2290, acc: 92.1040, loss_bbox: 0.2681, loss_mask: 0.2725, loss: 0.8620 2023-11-13 17:03:45,974 - mmdet - INFO - Epoch [1][6400/7330] lr: 1.000e-04, eta: 8:38:14, time: 0.378, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0389, loss_rpn_bbox: 0.0537, loss_cls: 0.2364, acc: 91.8401, loss_bbox: 0.2790, loss_mask: 0.2716, loss: 0.8796 2023-11-13 17:04:05,616 - mmdet - INFO - Epoch [1][6450/7330] lr: 1.000e-04, eta: 8:38:02, time: 0.393, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0424, loss_rpn_bbox: 0.0571, loss_cls: 0.2524, acc: 91.3926, loss_bbox: 0.2883, loss_mask: 0.2740, loss: 0.9141 2023-11-13 17:04:24,532 - mmdet - INFO - Epoch [1][6500/7330] lr: 1.000e-04, eta: 8:37:41, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0349, loss_rpn_bbox: 0.0513, loss_cls: 0.2368, acc: 91.6941, loss_bbox: 0.2798, loss_mask: 0.2631, loss: 0.8659 2023-11-13 17:04:43,547 - mmdet - INFO - Epoch [1][6550/7330] lr: 1.000e-04, eta: 8:37:21, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0518, loss_cls: 0.2334, acc: 92.0828, loss_bbox: 0.2703, loss_mask: 0.2663, loss: 0.8580 2023-11-13 17:05:02,246 - mmdet - INFO - Epoch [1][6600/7330] lr: 1.000e-04, eta: 8:36:58, time: 0.374, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0538, loss_cls: 0.2358, acc: 91.8816, loss_bbox: 0.2737, loss_mask: 0.2661, loss: 0.8690 2023-11-13 17:05:21,426 - mmdet - INFO - Epoch [1][6650/7330] lr: 1.000e-04, eta: 8:36:40, time: 0.384, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0535, loss_cls: 0.2336, acc: 92.0237, loss_bbox: 0.2737, loss_mask: 0.2659, loss: 0.8617 2023-11-13 17:05:40,608 - mmdet - INFO - Epoch [1][6700/7330] lr: 1.000e-04, eta: 8:36:22, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0521, loss_cls: 0.2449, acc: 91.7134, loss_bbox: 0.2809, loss_mask: 0.2700, loss: 0.8842 2023-11-13 17:05:59,743 - mmdet - INFO - Epoch [1][6750/7330] lr: 1.000e-04, eta: 8:36:04, time: 0.383, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0371, loss_rpn_bbox: 0.0538, loss_cls: 0.2415, acc: 91.6189, loss_bbox: 0.2849, loss_mask: 0.2717, loss: 0.8889 2023-11-13 17:06:18,424 - mmdet - INFO - Epoch [1][6800/7330] lr: 1.000e-04, eta: 8:35:41, time: 0.374, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0528, loss_cls: 0.2261, acc: 91.9973, loss_bbox: 0.2734, loss_mask: 0.2634, loss: 0.8530 2023-11-13 17:06:37,895 - mmdet - INFO - Epoch [1][6850/7330] lr: 1.000e-04, eta: 8:35:26, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0519, loss_cls: 0.2345, acc: 91.8323, loss_bbox: 0.2763, loss_mask: 0.2645, loss: 0.8650 2023-11-13 17:06:56,802 - mmdet - INFO - Epoch [1][6900/7330] lr: 1.000e-04, eta: 8:35:05, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0400, loss_rpn_bbox: 0.0542, loss_cls: 0.2425, acc: 91.6460, loss_bbox: 0.2764, loss_mask: 0.2699, loss: 0.8830 2023-11-13 17:07:15,941 - mmdet - INFO - Epoch [1][6950/7330] lr: 1.000e-04, eta: 8:34:47, time: 0.383, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0536, loss_cls: 0.2341, acc: 91.8169, loss_bbox: 0.2795, loss_mask: 0.2700, loss: 0.8735 2023-11-13 17:07:35,250 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 17:07:35,250 - mmdet - INFO - Epoch [1][7000/7330] lr: 1.000e-04, eta: 8:34:31, time: 0.386, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0547, loss_cls: 0.2326, acc: 91.9104, loss_bbox: 0.2739, loss_mask: 0.2681, loss: 0.8674 2023-11-13 17:07:54,325 - mmdet - INFO - Epoch [1][7050/7330] lr: 1.000e-04, eta: 8:34:12, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0364, loss_rpn_bbox: 0.0521, loss_cls: 0.2341, acc: 91.8467, loss_bbox: 0.2784, loss_mask: 0.2639, loss: 0.8649 2023-11-13 17:08:13,424 - mmdet - INFO - Epoch [1][7100/7330] lr: 1.000e-04, eta: 8:33:53, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0539, loss_cls: 0.2265, acc: 92.2500, loss_bbox: 0.2602, loss_mask: 0.2591, loss: 0.8379 2023-11-13 17:08:32,834 - mmdet - INFO - Epoch [1][7150/7330] lr: 1.000e-04, eta: 8:33:38, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0534, loss_cls: 0.2421, acc: 91.7214, loss_bbox: 0.2793, loss_mask: 0.2697, loss: 0.8850 2023-11-13 17:08:51,537 - mmdet - INFO - Epoch [1][7200/7330] lr: 1.000e-04, eta: 8:33:15, time: 0.374, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0349, loss_rpn_bbox: 0.0498, loss_cls: 0.2328, acc: 92.0667, loss_bbox: 0.2680, loss_mask: 0.2616, loss: 0.8470 2023-11-13 17:09:10,835 - mmdet - INFO - Epoch [1][7250/7330] lr: 1.000e-04, eta: 8:32:58, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0540, loss_cls: 0.2315, acc: 92.1221, loss_bbox: 0.2692, loss_mask: 0.2602, loss: 0.8509 2023-11-13 17:09:30,045 - mmdet - INFO - Epoch [1][7300/7330] lr: 1.000e-04, eta: 8:32:41, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0545, loss_cls: 0.2363, acc: 91.7510, loss_bbox: 0.2756, loss_mask: 0.2684, loss: 0.8749 2023-11-13 17:09:41,985 - mmdet - INFO - Saving checkpoint at 1 epochs 2023-11-13 17:10:33,730 - mmdet - INFO - Evaluating bbox... 2023-11-13 17:11:07,511 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.618 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.407 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.228 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.416 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.489 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.511 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.511 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.511 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.331 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.648 2023-11-13 17:11:07,515 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.511 | bicycle | 0.304 | car | 0.397 | | motorcycle | 0.383 | airplane | 0.541 | bus | 0.622 | | train | 0.557 | truck | 0.316 | boat | 0.235 | | traffic light | 0.263 | fire hydrant | 0.597 | stop sign | 0.581 | | parking meter | 0.462 | bench | 0.213 | bird | 0.336 | | cat | 0.642 | dog | 0.574 | horse | 0.457 | | sheep | 0.487 | cow | 0.512 | elephant | 0.577 | | bear | 0.644 | zebra | 0.618 | giraffe | 0.607 | | backpack | 0.143 | umbrella | 0.354 | handbag | 0.129 | | tie | 0.271 | suitcase | 0.316 | frisbee | 0.595 | | skis | 0.164 | snowboard | 0.268 | sports ball | 0.419 | | kite | 0.342 | baseball bat | 0.241 | baseball glove | 0.374 | | skateboard | 0.431 | surfboard | 0.309 | tennis racket | 0.440 | | bottle | 0.394 | wine glass | 0.333 | cup | 0.436 | | fork | 0.293 | knife | 0.163 | spoon | 0.157 | | bowl | 0.401 | banana | 0.212 | apple | 0.196 | | sandwich | 0.350 | orange | 0.278 | broccoli | 0.211 | | carrot | 0.185 | hot dog | 0.287 | pizza | 0.473 | | donut | 0.394 | cake | 0.328 | chair | 0.271 | | couch | 0.368 | potted plant | 0.233 | bed | 0.402 | | dining table | 0.214 | toilet | 0.507 | tv | 0.527 | | laptop | 0.545 | mouse | 0.572 | remote | 0.294 | | keyboard | 0.444 | cell phone | 0.352 | microwave | 0.462 | | oven | 0.307 | toaster | 0.339 | sink | 0.322 | | refrigerator | 0.493 | book | 0.128 | clock | 0.497 | | vase | 0.350 | scissors | 0.219 | teddy bear | 0.383 | | hair drier | 0.117 | toothbrush | 0.141 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:11:07,515 - mmdet - INFO - Evaluating segm... 2023-11-13 17:11:48,420 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.353 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.584 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.376 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.171 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.387 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.517 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.480 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.480 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.480 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.294 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.527 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.632 2023-11-13 17:11:48,423 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.437 | bicycle | 0.178 | car | 0.378 | | motorcycle | 0.304 | airplane | 0.465 | bus | 0.624 | | train | 0.570 | truck | 0.325 | boat | 0.222 | | traffic light | 0.252 | fire hydrant | 0.621 | stop sign | 0.621 | | parking meter | 0.476 | bench | 0.163 | bird | 0.301 | | cat | 0.676 | dog | 0.584 | horse | 0.334 | | sheep | 0.428 | cow | 0.438 | elephant | 0.535 | | bear | 0.696 | zebra | 0.502 | giraffe | 0.442 | | backpack | 0.164 | umbrella | 0.450 | handbag | 0.139 | | tie | 0.280 | suitcase | 0.346 | frisbee | 0.611 | | skis | 0.011 | snowboard | 0.184 | sports ball | 0.428 | | kite | 0.277 | baseball bat | 0.209 | baseball glove | 0.418 | | skateboard | 0.244 | surfboard | 0.254 | tennis racket | 0.523 | | bottle | 0.376 | wine glass | 0.305 | cup | 0.445 | | fork | 0.117 | knife | 0.123 | spoon | 0.090 | | bowl | 0.383 | banana | 0.170 | apple | 0.191 | | sandwich | 0.405 | orange | 0.294 | broccoli | 0.211 | | carrot | 0.166 | hot dog | 0.277 | pizza | 0.482 | | donut | 0.435 | cake | 0.360 | chair | 0.194 | | couch | 0.341 | potted plant | 0.191 | bed | 0.302 | | dining table | 0.111 | toilet | 0.555 | tv | 0.567 | | laptop | 0.591 | mouse | 0.593 | remote | 0.280 | | keyboard | 0.478 | cell phone | 0.351 | microwave | 0.530 | | oven | 0.285 | toaster | 0.393 | sink | 0.330 | | refrigerator | 0.517 | book | 0.097 | clock | 0.513 | | vase | 0.354 | scissors | 0.161 | teddy bear | 0.412 | | hair drier | 0.028 | toothbrush | 0.090 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:11:50,911 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_1.pth. 2023-11-13 17:11:50,912 - mmdet - INFO - Best bbox_mAP is 0.3727 at 1 epoch. 2023-11-13 17:11:50,912 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 17:11:50,912 - mmdet - INFO - Epoch(val) [1][625] bbox_mAP: 0.3727, bbox_mAP_50: 0.6176, bbox_mAP_75: 0.4065, bbox_mAP_s: 0.2281, bbox_mAP_m: 0.4160, bbox_mAP_l: 0.4894, bbox_mAP_copypaste: 0.3727 0.6176 0.4065 0.2281 0.4160 0.4894, segm_mAP: 0.3526, segm_mAP_50: 0.5837, segm_mAP_75: 0.3757, segm_mAP_s: 0.1711, segm_mAP_m: 0.3869, segm_mAP_l: 0.5166, segm_mAP_copypaste: 0.3526 0.5837 0.3757 0.1711 0.3869 0.5166 2023-11-13 17:12:13,880 - mmdet - INFO - Epoch [2][50/7330] lr: 1.000e-04, eta: 8:30:48, time: 0.459, data_time: 0.090, memory: 4444, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0478, loss_cls: 0.2113, acc: 92.5515, loss_bbox: 0.2534, loss_mask: 0.2539, loss: 0.7967 2023-11-13 17:12:34,018 - mmdet - INFO - Epoch [2][100/7330] lr: 1.000e-04, eta: 8:30:41, time: 0.403, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0340, loss_rpn_bbox: 0.0511, loss_cls: 0.2276, acc: 91.8516, loss_bbox: 0.2747, loss_mask: 0.2680, loss: 0.8554 2023-11-13 17:12:53,515 - mmdet - INFO - Epoch [2][150/7330] lr: 1.000e-04, eta: 8:30:27, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0346, loss_rpn_bbox: 0.0514, loss_cls: 0.2194, acc: 92.2834, loss_bbox: 0.2658, loss_mask: 0.2617, loss: 0.8329 2023-11-13 17:13:13,304 - mmdet - INFO - Epoch [2][200/7330] lr: 1.000e-04, eta: 8:30:16, time: 0.396, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0498, loss_cls: 0.2241, acc: 92.0862, loss_bbox: 0.2701, loss_mask: 0.2647, loss: 0.8411 2023-11-13 17:13:32,808 - mmdet - INFO - Epoch [2][250/7330] lr: 1.000e-04, eta: 8:30:02, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0514, loss_cls: 0.2235, acc: 92.2429, loss_bbox: 0.2640, loss_mask: 0.2573, loss: 0.8303 2023-11-13 17:13:52,402 - mmdet - INFO - Epoch [2][300/7330] lr: 1.000e-04, eta: 8:29:49, time: 0.392, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0513, loss_cls: 0.2245, acc: 92.1353, loss_bbox: 0.2685, loss_mask: 0.2604, loss: 0.8361 2023-11-13 17:14:11,951 - mmdet - INFO - Epoch [2][350/7330] lr: 1.000e-04, eta: 8:29:35, time: 0.391, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0508, loss_cls: 0.2232, acc: 92.1157, loss_bbox: 0.2710, loss_mask: 0.2596, loss: 0.8371 2023-11-13 17:14:34,061 - mmdet - INFO - Epoch [2][400/7330] lr: 1.000e-04, eta: 8:29:48, time: 0.442, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0542, loss_cls: 0.2276, acc: 92.0598, loss_bbox: 0.2705, loss_mask: 0.2601, loss: 0.8474 2023-11-13 17:14:53,631 - mmdet - INFO - Epoch [2][450/7330] lr: 1.000e-04, eta: 8:29:34, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0518, loss_cls: 0.2240, acc: 91.9412, loss_bbox: 0.2694, loss_mask: 0.2629, loss: 0.8443 2023-11-13 17:15:13,243 - mmdet - INFO - Epoch [2][500/7330] lr: 1.000e-04, eta: 8:29:21, time: 0.392, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0499, loss_cls: 0.2223, acc: 92.1797, loss_bbox: 0.2681, loss_mask: 0.2563, loss: 0.8302 2023-11-13 17:15:34,457 - mmdet - INFO - Epoch [2][550/7330] lr: 1.000e-04, eta: 8:29:23, time: 0.424, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0496, loss_cls: 0.2345, acc: 91.8816, loss_bbox: 0.2701, loss_mask: 0.2609, loss: 0.8479 2023-11-13 17:15:53,704 - mmdet - INFO - Epoch [2][600/7330] lr: 1.000e-04, eta: 8:29:06, time: 0.385, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0526, loss_cls: 0.2249, acc: 92.2253, loss_bbox: 0.2710, loss_mask: 0.2623, loss: 0.8449 2023-11-13 17:16:14,908 - mmdet - INFO - Epoch [2][650/7330] lr: 1.000e-04, eta: 8:29:08, time: 0.424, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0497, loss_cls: 0.2313, acc: 91.8191, loss_bbox: 0.2734, loss_mask: 0.2614, loss: 0.8481 2023-11-13 17:16:34,532 - mmdet - INFO - Epoch [2][700/7330] lr: 1.000e-04, eta: 8:28:54, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0509, loss_cls: 0.2258, acc: 91.9792, loss_bbox: 0.2694, loss_mask: 0.2656, loss: 0.8437 2023-11-13 17:16:54,145 - mmdet - INFO - Epoch [2][750/7330] lr: 1.000e-04, eta: 8:28:40, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0519, loss_cls: 0.2285, acc: 92.0020, loss_bbox: 0.2748, loss_mask: 0.2603, loss: 0.8497 2023-11-13 17:17:13,450 - mmdet - INFO - Epoch [2][800/7330] lr: 1.000e-04, eta: 8:28:23, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0506, loss_cls: 0.2192, acc: 92.3823, loss_bbox: 0.2628, loss_mask: 0.2657, loss: 0.8315 2023-11-13 17:17:35,649 - mmdet - INFO - Epoch [2][850/7330] lr: 1.000e-04, eta: 8:28:34, time: 0.444, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0496, loss_cls: 0.2301, acc: 91.9072, loss_bbox: 0.2691, loss_mask: 0.2628, loss: 0.8430 2023-11-13 17:17:55,013 - mmdet - INFO - Epoch [2][900/7330] lr: 1.000e-04, eta: 8:28:17, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0508, loss_cls: 0.2254, acc: 92.1121, loss_bbox: 0.2671, loss_mask: 0.2605, loss: 0.8370 2023-11-13 17:18:14,469 - mmdet - INFO - Epoch [2][950/7330] lr: 1.000e-04, eta: 8:28:01, time: 0.389, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0477, loss_cls: 0.2132, acc: 92.5120, loss_bbox: 0.2550, loss_mask: 0.2621, loss: 0.8082 2023-11-13 17:18:34,446 - mmdet - INFO - Epoch [2][1000/7330] lr: 1.000e-04, eta: 8:27:50, time: 0.400, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0522, loss_cls: 0.2207, acc: 92.3010, loss_bbox: 0.2622, loss_mask: 0.2650, loss: 0.8333 2023-11-13 17:18:54,301 - mmdet - INFO - Epoch [2][1050/7330] lr: 1.000e-04, eta: 8:27:38, time: 0.397, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0518, loss_cls: 0.2208, acc: 92.2642, loss_bbox: 0.2635, loss_mask: 0.2648, loss: 0.8344 2023-11-13 17:19:13,776 - mmdet - INFO - Epoch [2][1100/7330] lr: 1.000e-04, eta: 8:27:22, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0535, loss_cls: 0.2281, acc: 91.9724, loss_bbox: 0.2784, loss_mask: 0.2620, loss: 0.8545 2023-11-13 17:19:33,485 - mmdet - INFO - Epoch [2][1150/7330] lr: 1.000e-04, eta: 8:27:08, time: 0.394, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0520, loss_cls: 0.2236, acc: 92.3169, loss_bbox: 0.2646, loss_mask: 0.2576, loss: 0.8339 2023-11-13 17:19:52,855 - mmdet - INFO - Epoch [2][1200/7330] lr: 1.000e-04, eta: 8:26:51, time: 0.387, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0500, loss_cls: 0.2243, acc: 92.0688, loss_bbox: 0.2668, loss_mask: 0.2580, loss: 0.8317 2023-11-13 17:20:12,579 - mmdet - INFO - Epoch [2][1250/7330] lr: 1.000e-04, eta: 8:26:38, time: 0.394, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0501, loss_cls: 0.2253, acc: 91.9834, loss_bbox: 0.2702, loss_mask: 0.2583, loss: 0.8368 2023-11-13 17:20:32,232 - mmdet - INFO - Epoch [2][1300/7330] lr: 1.000e-04, eta: 8:26:23, time: 0.393, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0522, loss_cls: 0.2290, acc: 92.0195, loss_bbox: 0.2704, loss_mask: 0.2642, loss: 0.8490 2023-11-13 17:20:53,942 - mmdet - INFO - Epoch [2][1350/7330] lr: 1.000e-04, eta: 8:26:27, time: 0.434, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0476, loss_cls: 0.2068, acc: 92.6772, loss_bbox: 0.2535, loss_mask: 0.2524, loss: 0.7918 2023-11-13 17:21:13,531 - mmdet - INFO - Epoch [2][1400/7330] lr: 1.000e-04, eta: 8:26:12, time: 0.392, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0340, loss_rpn_bbox: 0.0506, loss_cls: 0.2156, acc: 92.4409, loss_bbox: 0.2550, loss_mask: 0.2569, loss: 0.8121 2023-11-13 17:21:32,979 - mmdet - INFO - Epoch [2][1450/7330] lr: 1.000e-04, eta: 8:25:55, time: 0.389, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0467, loss_cls: 0.2177, acc: 92.4993, loss_bbox: 0.2522, loss_mask: 0.2514, loss: 0.7992 2023-11-13 17:21:52,236 - mmdet - INFO - Epoch [2][1500/7330] lr: 1.000e-04, eta: 8:25:37, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0481, loss_cls: 0.2201, acc: 92.2539, loss_bbox: 0.2636, loss_mask: 0.2552, loss: 0.8191 2023-11-13 17:22:11,732 - mmdet - INFO - Epoch [2][1550/7330] lr: 1.000e-04, eta: 8:25:21, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0343, loss_rpn_bbox: 0.0523, loss_cls: 0.2212, acc: 92.2947, loss_bbox: 0.2599, loss_mask: 0.2557, loss: 0.8234 2023-11-13 17:22:31,334 - mmdet - INFO - Epoch [2][1600/7330] lr: 1.000e-04, eta: 8:25:05, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0491, loss_cls: 0.2193, acc: 92.2136, loss_bbox: 0.2681, loss_mask: 0.2504, loss: 0.8203 2023-11-13 17:22:50,444 - mmdet - INFO - Epoch [2][1650/7330] lr: 1.000e-04, eta: 8:24:46, time: 0.382, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0475, loss_cls: 0.2232, acc: 92.2019, loss_bbox: 0.2622, loss_mask: 0.2533, loss: 0.8160 2023-11-13 17:23:10,062 - mmdet - INFO - Epoch [2][1700/7330] lr: 1.000e-04, eta: 8:24:30, time: 0.392, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0522, loss_cls: 0.2203, acc: 92.2083, loss_bbox: 0.2678, loss_mask: 0.2601, loss: 0.8340 2023-11-13 17:23:29,480 - mmdet - INFO - Epoch [2][1750/7330] lr: 1.000e-04, eta: 8:24:13, time: 0.388, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0508, loss_cls: 0.2187, acc: 92.2222, loss_bbox: 0.2603, loss_mask: 0.2591, loss: 0.8208 2023-11-13 17:23:48,789 - mmdet - INFO - Epoch [2][1800/7330] lr: 1.000e-04, eta: 8:23:55, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0485, loss_cls: 0.2097, acc: 92.5920, loss_bbox: 0.2577, loss_mask: 0.2583, loss: 0.8075 2023-11-13 17:24:08,050 - mmdet - INFO - Epoch [2][1850/7330] lr: 1.000e-04, eta: 8:23:37, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0512, loss_cls: 0.2268, acc: 91.8501, loss_bbox: 0.2747, loss_mask: 0.2592, loss: 0.8453 2023-11-13 17:24:27,475 - mmdet - INFO - Epoch [2][1900/7330] lr: 1.000e-04, eta: 8:23:20, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0499, loss_cls: 0.2283, acc: 92.1418, loss_bbox: 0.2631, loss_mask: 0.2526, loss: 0.8273 2023-11-13 17:24:46,760 - mmdet - INFO - Epoch [2][1950/7330] lr: 1.000e-04, eta: 8:23:01, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0526, loss_cls: 0.2275, acc: 92.1016, loss_bbox: 0.2664, loss_mask: 0.2614, loss: 0.8420 2023-11-13 17:25:06,408 - mmdet - INFO - Epoch [2][2000/7330] lr: 1.000e-04, eta: 8:22:46, time: 0.393, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0535, loss_cls: 0.2237, acc: 92.1917, loss_bbox: 0.2644, loss_mask: 0.2625, loss: 0.8390 2023-11-13 17:25:26,281 - mmdet - INFO - Epoch [2][2050/7330] lr: 1.000e-04, eta: 8:22:33, time: 0.398, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0525, loss_cls: 0.2292, acc: 91.8965, loss_bbox: 0.2697, loss_mask: 0.2644, loss: 0.8506 2023-11-13 17:25:45,866 - mmdet - INFO - Epoch [2][2100/7330] lr: 1.000e-04, eta: 8:22:17, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0333, loss_rpn_bbox: 0.0525, loss_cls: 0.2268, acc: 92.1179, loss_bbox: 0.2733, loss_mask: 0.2604, loss: 0.8464 2023-11-13 17:26:05,261 - mmdet - INFO - Epoch [2][2150/7330] lr: 1.000e-04, eta: 8:21:59, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0483, loss_cls: 0.2163, acc: 92.4543, loss_bbox: 0.2592, loss_mask: 0.2549, loss: 0.8067 2023-11-13 17:26:24,496 - mmdet - INFO - Epoch [2][2200/7330] lr: 1.000e-04, eta: 8:21:41, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0485, loss_cls: 0.2178, acc: 92.3591, loss_bbox: 0.2588, loss_mask: 0.2514, loss: 0.8083 2023-11-13 17:26:43,987 - mmdet - INFO - Epoch [2][2250/7330] lr: 1.000e-04, eta: 8:21:24, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0340, loss_rpn_bbox: 0.0521, loss_cls: 0.2244, acc: 92.0681, loss_bbox: 0.2642, loss_mask: 0.2582, loss: 0.8329 2023-11-13 17:27:03,131 - mmdet - INFO - Epoch [2][2300/7330] lr: 1.000e-04, eta: 8:21:04, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0515, loss_cls: 0.2175, acc: 92.1802, loss_bbox: 0.2693, loss_mask: 0.2588, loss: 0.8283 2023-11-13 17:27:22,654 - mmdet - INFO - Epoch [2][2350/7330] lr: 1.000e-04, eta: 8:20:48, time: 0.390, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0493, loss_cls: 0.2145, acc: 92.4846, loss_bbox: 0.2561, loss_mask: 0.2474, loss: 0.7988 2023-11-13 17:27:42,505 - mmdet - INFO - Epoch [2][2400/7330] lr: 1.000e-04, eta: 8:20:34, time: 0.397, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0501, loss_cls: 0.2149, acc: 92.3213, loss_bbox: 0.2628, loss_mask: 0.2553, loss: 0.8143 2023-11-13 17:28:01,833 - mmdet - INFO - Epoch [2][2450/7330] lr: 1.000e-04, eta: 8:20:16, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0513, loss_cls: 0.2214, acc: 92.2219, loss_bbox: 0.2646, loss_mask: 0.2547, loss: 0.8248 2023-11-13 17:28:21,233 - mmdet - INFO - Epoch [2][2500/7330] lr: 1.000e-04, eta: 8:19:58, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0494, loss_cls: 0.2207, acc: 92.2788, loss_bbox: 0.2646, loss_mask: 0.2606, loss: 0.8281 2023-11-13 17:28:40,298 - mmdet - INFO - Epoch [2][2550/7330] lr: 1.000e-04, eta: 8:19:38, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0480, loss_cls: 0.2092, acc: 92.5359, loss_bbox: 0.2589, loss_mask: 0.2475, loss: 0.7919 2023-11-13 17:28:59,493 - mmdet - INFO - Epoch [2][2600/7330] lr: 1.000e-04, eta: 8:19:19, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0354, loss_rpn_bbox: 0.0501, loss_cls: 0.2130, acc: 92.5210, loss_bbox: 0.2572, loss_mask: 0.2517, loss: 0.8074 2023-11-13 17:29:18,953 - mmdet - INFO - Epoch [2][2650/7330] lr: 1.000e-04, eta: 8:19:01, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0494, loss_cls: 0.2199, acc: 92.2412, loss_bbox: 0.2633, loss_mask: 0.2613, loss: 0.8255 2023-11-13 17:29:38,410 - mmdet - INFO - Epoch [2][2700/7330] lr: 1.000e-04, eta: 8:18:44, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0513, loss_cls: 0.2240, acc: 92.0032, loss_bbox: 0.2684, loss_mask: 0.2594, loss: 0.8364 2023-11-13 17:29:58,023 - mmdet - INFO - Epoch [2][2750/7330] lr: 1.000e-04, eta: 8:18:28, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0510, loss_cls: 0.2220, acc: 92.2375, loss_bbox: 0.2598, loss_mask: 0.2512, loss: 0.8182 2023-11-13 17:30:17,346 - mmdet - INFO - Epoch [2][2800/7330] lr: 1.000e-04, eta: 8:18:10, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0494, loss_cls: 0.2149, acc: 92.4014, loss_bbox: 0.2568, loss_mask: 0.2523, loss: 0.8071 2023-11-13 17:30:37,201 - mmdet - INFO - Epoch [2][2850/7330] lr: 1.000e-04, eta: 8:17:56, time: 0.397, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0530, loss_cls: 0.2294, acc: 91.8723, loss_bbox: 0.2740, loss_mask: 0.2573, loss: 0.8480 2023-11-13 17:30:56,786 - mmdet - INFO - Epoch [2][2900/7330] lr: 1.000e-04, eta: 8:17:39, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0505, loss_cls: 0.2229, acc: 92.1328, loss_bbox: 0.2660, loss_mask: 0.2557, loss: 0.8254 2023-11-13 17:31:16,555 - mmdet - INFO - Epoch [2][2950/7330] lr: 1.000e-04, eta: 8:17:24, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0498, loss_cls: 0.2239, acc: 92.0374, loss_bbox: 0.2651, loss_mask: 0.2589, loss: 0.8298 2023-11-13 17:31:35,798 - mmdet - INFO - Epoch [2][3000/7330] lr: 1.000e-04, eta: 8:17:05, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0483, loss_cls: 0.2236, acc: 92.1003, loss_bbox: 0.2629, loss_mask: 0.2486, loss: 0.8143 2023-11-13 17:31:55,264 - mmdet - INFO - Epoch [2][3050/7330] lr: 1.000e-04, eta: 8:16:48, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0521, loss_cls: 0.2280, acc: 91.9600, loss_bbox: 0.2723, loss_mask: 0.2590, loss: 0.8427 2023-11-13 17:32:14,767 - mmdet - INFO - Epoch [2][3100/7330] lr: 1.000e-04, eta: 8:16:31, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0478, loss_cls: 0.2201, acc: 92.3662, loss_bbox: 0.2587, loss_mask: 0.2541, loss: 0.8121 2023-11-13 17:32:34,374 - mmdet - INFO - Epoch [2][3150/7330] lr: 1.000e-04, eta: 8:16:15, time: 0.392, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0512, loss_cls: 0.2128, acc: 92.3430, loss_bbox: 0.2587, loss_mask: 0.2567, loss: 0.8104 2023-11-13 17:32:53,588 - mmdet - INFO - Epoch [2][3200/7330] lr: 1.000e-04, eta: 8:15:56, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0482, loss_cls: 0.2069, acc: 92.6631, loss_bbox: 0.2458, loss_mask: 0.2446, loss: 0.7782 2023-11-13 17:33:13,140 - mmdet - INFO - Epoch [2][3250/7330] lr: 1.000e-04, eta: 8:15:39, time: 0.391, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0505, loss_cls: 0.2200, acc: 92.2925, loss_bbox: 0.2592, loss_mask: 0.2501, loss: 0.8114 2023-11-13 17:33:32,648 - mmdet - INFO - Epoch [2][3300/7330] lr: 1.000e-04, eta: 8:15:22, time: 0.390, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0481, loss_cls: 0.2157, acc: 92.4590, loss_bbox: 0.2601, loss_mask: 0.2514, loss: 0.8052 2023-11-13 17:33:51,568 - mmdet - INFO - Epoch [2][3350/7330] lr: 1.000e-04, eta: 8:15:00, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0482, loss_cls: 0.2271, acc: 91.7920, loss_bbox: 0.2722, loss_mask: 0.2569, loss: 0.8373 2023-11-13 17:34:10,955 - mmdet - INFO - Epoch [2][3400/7330] lr: 1.000e-04, eta: 8:14:42, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0506, loss_cls: 0.2259, acc: 91.9766, loss_bbox: 0.2628, loss_mask: 0.2570, loss: 0.8290 2023-11-13 17:34:30,374 - mmdet - INFO - Epoch [2][3450/7330] lr: 1.000e-04, eta: 8:14:25, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0342, loss_rpn_bbox: 0.0546, loss_cls: 0.2323, acc: 91.8811, loss_bbox: 0.2726, loss_mask: 0.2577, loss: 0.8514 2023-11-13 17:34:50,062 - mmdet - INFO - Epoch [2][3500/7330] lr: 1.000e-04, eta: 8:14:09, time: 0.394, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0492, loss_cls: 0.2233, acc: 92.0334, loss_bbox: 0.2695, loss_mask: 0.2567, loss: 0.8305 2023-11-13 17:35:09,830 - mmdet - INFO - Epoch [2][3550/7330] lr: 1.000e-04, eta: 8:13:53, time: 0.395, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0483, loss_cls: 0.2093, acc: 92.5168, loss_bbox: 0.2485, loss_mask: 0.2472, loss: 0.7831 2023-11-13 17:35:29,182 - mmdet - INFO - Epoch [2][3600/7330] lr: 1.000e-04, eta: 8:13:35, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0452, loss_cls: 0.2077, acc: 92.7048, loss_bbox: 0.2541, loss_mask: 0.2510, loss: 0.7879 2023-11-13 17:35:48,361 - mmdet - INFO - Epoch [2][3650/7330] lr: 1.000e-04, eta: 8:13:16, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0464, loss_cls: 0.2076, acc: 92.5312, loss_bbox: 0.2565, loss_mask: 0.2501, loss: 0.7920 2023-11-13 17:36:07,864 - mmdet - INFO - Epoch [2][3700/7330] lr: 1.000e-04, eta: 8:12:58, time: 0.390, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0504, loss_cls: 0.2149, acc: 92.3760, loss_bbox: 0.2570, loss_mask: 0.2488, loss: 0.8046 2023-11-13 17:36:27,373 - mmdet - INFO - Epoch [2][3750/7330] lr: 1.000e-04, eta: 8:12:41, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0472, loss_cls: 0.2141, acc: 92.4961, loss_bbox: 0.2530, loss_mask: 0.2485, loss: 0.7942 2023-11-13 17:36:47,154 - mmdet - INFO - Epoch [2][3800/7330] lr: 1.000e-04, eta: 8:12:26, time: 0.396, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0504, loss_cls: 0.2154, acc: 92.3569, loss_bbox: 0.2604, loss_mask: 0.2474, loss: 0.8057 2023-11-13 17:37:06,703 - mmdet - INFO - Epoch [2][3850/7330] lr: 1.000e-04, eta: 8:12:09, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0493, loss_cls: 0.2105, acc: 92.5925, loss_bbox: 0.2538, loss_mask: 0.2515, loss: 0.7963 2023-11-13 17:37:26,539 - mmdet - INFO - Epoch [2][3900/7330] lr: 1.000e-04, eta: 8:11:54, time: 0.397, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0475, loss_cls: 0.2125, acc: 92.5120, loss_bbox: 0.2565, loss_mask: 0.2505, loss: 0.7987 2023-11-13 17:37:45,773 - mmdet - INFO - Epoch [2][3950/7330] lr: 1.000e-04, eta: 8:11:34, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0474, loss_cls: 0.2188, acc: 92.2839, loss_bbox: 0.2561, loss_mask: 0.2540, loss: 0.8077 2023-11-13 17:38:05,261 - mmdet - INFO - Epoch [2][4000/7330] lr: 1.000e-04, eta: 8:11:17, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0480, loss_cls: 0.2128, acc: 92.4072, loss_bbox: 0.2564, loss_mask: 0.2536, loss: 0.8002 2023-11-13 17:38:24,726 - mmdet - INFO - Epoch [2][4050/7330] lr: 1.000e-04, eta: 8:10:59, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0548, loss_cls: 0.2136, acc: 92.4646, loss_bbox: 0.2591, loss_mask: 0.2577, loss: 0.8190 2023-11-13 17:38:44,046 - mmdet - INFO - Epoch [2][4100/7330] lr: 1.000e-04, eta: 8:10:40, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0464, loss_cls: 0.2209, acc: 92.4299, loss_bbox: 0.2543, loss_mask: 0.2517, loss: 0.8037 2023-11-13 17:39:03,373 - mmdet - INFO - Epoch [2][4150/7330] lr: 1.000e-04, eta: 8:10:22, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0502, loss_cls: 0.2152, acc: 92.4541, loss_bbox: 0.2611, loss_mask: 0.2536, loss: 0.8125 2023-11-13 17:39:22,891 - mmdet - INFO - Epoch [2][4200/7330] lr: 1.000e-04, eta: 8:10:04, time: 0.390, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0511, loss_cls: 0.2174, acc: 92.4639, loss_bbox: 0.2549, loss_mask: 0.2584, loss: 0.8148 2023-11-13 17:39:42,063 - mmdet - INFO - Epoch [2][4250/7330] lr: 1.000e-04, eta: 8:09:45, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0477, loss_cls: 0.2166, acc: 92.3960, loss_bbox: 0.2568, loss_mask: 0.2532, loss: 0.8061 2023-11-13 17:40:00,892 - mmdet - INFO - Epoch [2][4300/7330] lr: 1.000e-04, eta: 8:09:23, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0465, loss_cls: 0.2078, acc: 92.6572, loss_bbox: 0.2457, loss_mask: 0.2476, loss: 0.7788 2023-11-13 17:40:20,640 - mmdet - INFO - Epoch [2][4350/7330] lr: 1.000e-04, eta: 8:09:07, time: 0.395, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0494, loss_cls: 0.2130, acc: 92.5037, loss_bbox: 0.2535, loss_mask: 0.2483, loss: 0.7946 2023-11-13 17:40:40,404 - mmdet - INFO - Epoch [2][4400/7330] lr: 1.000e-04, eta: 8:08:51, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0345, loss_rpn_bbox: 0.0522, loss_cls: 0.2176, acc: 92.4707, loss_bbox: 0.2556, loss_mask: 0.2533, loss: 0.8132 2023-11-13 17:40:59,984 - mmdet - INFO - Epoch [2][4450/7330] lr: 1.000e-04, eta: 8:08:34, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0489, loss_cls: 0.2211, acc: 92.2520, loss_bbox: 0.2586, loss_mask: 0.2502, loss: 0.8124 2023-11-13 17:41:19,863 - mmdet - INFO - Epoch [2][4500/7330] lr: 1.000e-04, eta: 8:08:19, time: 0.398, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0325, loss_rpn_bbox: 0.0520, loss_cls: 0.2215, acc: 92.1770, loss_bbox: 0.2658, loss_mask: 0.2562, loss: 0.8279 2023-11-13 17:41:39,543 - mmdet - INFO - Epoch [2][4550/7330] lr: 1.000e-04, eta: 8:08:03, time: 0.394, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0485, loss_cls: 0.2182, acc: 92.3030, loss_bbox: 0.2611, loss_mask: 0.2538, loss: 0.8137 2023-11-13 17:41:58,694 - mmdet - INFO - Epoch [2][4600/7330] lr: 1.000e-04, eta: 8:07:43, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0508, loss_cls: 0.2204, acc: 92.2546, loss_bbox: 0.2648, loss_mask: 0.2534, loss: 0.8226 2023-11-13 17:42:18,273 - mmdet - INFO - Epoch [2][4650/7330] lr: 1.000e-04, eta: 8:07:26, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0502, loss_cls: 0.2171, acc: 92.4023, loss_bbox: 0.2595, loss_mask: 0.2487, loss: 0.8077 2023-11-13 17:42:37,651 - mmdet - INFO - Epoch [2][4700/7330] lr: 1.000e-04, eta: 8:07:07, time: 0.388, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0472, loss_cls: 0.2149, acc: 92.4448, loss_bbox: 0.2529, loss_mask: 0.2483, loss: 0.7935 2023-11-13 17:42:57,283 - mmdet - INFO - Epoch [2][4750/7330] lr: 1.000e-04, eta: 8:06:50, time: 0.393, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0511, loss_cls: 0.2155, acc: 92.2280, loss_bbox: 0.2633, loss_mask: 0.2483, loss: 0.8097 2023-11-13 17:43:16,505 - mmdet - INFO - Epoch [2][4800/7330] lr: 1.000e-04, eta: 8:06:31, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0478, loss_cls: 0.2088, acc: 92.6802, loss_bbox: 0.2542, loss_mask: 0.2527, loss: 0.7940 2023-11-13 17:43:35,958 - mmdet - INFO - Epoch [2][4850/7330] lr: 1.000e-04, eta: 8:06:13, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0463, loss_cls: 0.2146, acc: 92.3899, loss_bbox: 0.2555, loss_mask: 0.2484, loss: 0.7934 2023-11-13 17:43:55,693 - mmdet - INFO - Epoch [2][4900/7330] lr: 1.000e-04, eta: 8:05:57, time: 0.395, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0483, loss_cls: 0.2223, acc: 92.0364, loss_bbox: 0.2645, loss_mask: 0.2558, loss: 0.8208 2023-11-13 17:44:15,261 - mmdet - INFO - Epoch [2][4950/7330] lr: 1.000e-04, eta: 8:05:39, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0501, loss_cls: 0.2187, acc: 92.2258, loss_bbox: 0.2601, loss_mask: 0.2498, loss: 0.8106 2023-11-13 17:44:34,652 - mmdet - INFO - Epoch [2][5000/7330] lr: 1.000e-04, eta: 8:05:21, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0321, loss_rpn_bbox: 0.0497, loss_cls: 0.2140, acc: 92.3447, loss_bbox: 0.2622, loss_mask: 0.2512, loss: 0.8093 2023-11-13 17:44:53,992 - mmdet - INFO - Epoch [2][5050/7330] lr: 1.000e-04, eta: 8:05:02, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0483, loss_cls: 0.2143, acc: 92.3950, loss_bbox: 0.2552, loss_mask: 0.2467, loss: 0.7933 2023-11-13 17:45:13,263 - mmdet - INFO - Epoch [2][5100/7330] lr: 1.000e-04, eta: 8:04:43, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0471, loss_cls: 0.2103, acc: 92.5442, loss_bbox: 0.2503, loss_mask: 0.2522, loss: 0.7894 2023-11-13 17:45:32,624 - mmdet - INFO - Epoch [2][5150/7330] lr: 1.000e-04, eta: 8:04:25, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0470, loss_cls: 0.2119, acc: 92.4553, loss_bbox: 0.2562, loss_mask: 0.2487, loss: 0.7930 2023-11-13 17:45:52,191 - mmdet - INFO - Epoch [2][5200/7330] lr: 1.000e-04, eta: 8:04:07, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0505, loss_cls: 0.2221, acc: 92.3293, loss_bbox: 0.2625, loss_mask: 0.2558, loss: 0.8237 2023-11-13 17:46:11,219 - mmdet - INFO - Epoch [2][5250/7330] lr: 1.000e-04, eta: 8:03:47, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0460, loss_cls: 0.2098, acc: 92.4524, loss_bbox: 0.2550, loss_mask: 0.2459, loss: 0.7853 2023-11-13 17:46:30,396 - mmdet - INFO - Epoch [2][5300/7330] lr: 1.000e-04, eta: 8:03:27, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0453, loss_cls: 0.2148, acc: 92.3655, loss_bbox: 0.2582, loss_mask: 0.2501, loss: 0.7994 2023-11-13 17:46:49,717 - mmdet - INFO - Epoch [2][5350/7330] lr: 1.000e-04, eta: 8:03:08, time: 0.386, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0495, loss_cls: 0.2128, acc: 92.5220, loss_bbox: 0.2543, loss_mask: 0.2565, loss: 0.8068 2023-11-13 17:47:09,271 - mmdet - INFO - Epoch [2][5400/7330] lr: 1.000e-04, eta: 8:02:51, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0481, loss_cls: 0.2119, acc: 92.6919, loss_bbox: 0.2436, loss_mask: 0.2499, loss: 0.7834 2023-11-13 17:47:29,213 - mmdet - INFO - Epoch [2][5450/7330] lr: 1.000e-04, eta: 8:02:35, time: 0.399, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0476, loss_cls: 0.2081, acc: 92.7485, loss_bbox: 0.2452, loss_mask: 0.2493, loss: 0.7784 2023-11-13 17:47:48,625 - mmdet - INFO - Epoch [2][5500/7330] lr: 1.000e-04, eta: 8:02:17, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0476, loss_cls: 0.2166, acc: 92.4944, loss_bbox: 0.2501, loss_mask: 0.2517, loss: 0.7942 2023-11-13 17:48:07,889 - mmdet - INFO - Epoch [2][5550/7330] lr: 1.000e-04, eta: 8:01:58, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0492, loss_cls: 0.2048, acc: 92.6792, loss_bbox: 0.2458, loss_mask: 0.2478, loss: 0.7786 2023-11-13 17:48:27,695 - mmdet - INFO - Epoch [2][5600/7330] lr: 1.000e-04, eta: 8:01:42, time: 0.396, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0492, loss_cls: 0.2154, acc: 92.3601, loss_bbox: 0.2531, loss_mask: 0.2487, loss: 0.7986 2023-11-13 17:48:47,493 - mmdet - INFO - Epoch [2][5650/7330] lr: 1.000e-04, eta: 8:01:25, time: 0.396, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0526, loss_cls: 0.2287, acc: 91.8372, loss_bbox: 0.2762, loss_mask: 0.2583, loss: 0.8474 2023-11-13 17:49:07,023 - mmdet - INFO - Epoch [2][5700/7330] lr: 1.000e-04, eta: 8:01:08, time: 0.391, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0324, loss_rpn_bbox: 0.0486, loss_cls: 0.2204, acc: 92.2268, loss_bbox: 0.2590, loss_mask: 0.2551, loss: 0.8155 2023-11-13 17:49:26,344 - mmdet - INFO - Epoch [2][5750/7330] lr: 1.000e-04, eta: 8:00:49, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0316, loss_rpn_bbox: 0.0496, loss_cls: 0.2181, acc: 92.1968, loss_bbox: 0.2630, loss_mask: 0.2539, loss: 0.8161 2023-11-13 17:49:45,662 - mmdet - INFO - Epoch [2][5800/7330] lr: 1.000e-04, eta: 8:00:30, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0501, loss_cls: 0.2220, acc: 92.2114, loss_bbox: 0.2634, loss_mask: 0.2495, loss: 0.8192 2023-11-13 17:50:04,651 - mmdet - INFO - Epoch [2][5850/7330] lr: 1.000e-04, eta: 8:00:09, time: 0.380, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0471, loss_cls: 0.2106, acc: 92.4758, loss_bbox: 0.2535, loss_mask: 0.2495, loss: 0.7881 2023-11-13 17:50:24,092 - mmdet - INFO - Epoch [2][5900/7330] lr: 1.000e-04, eta: 7:59:51, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0450, loss_cls: 0.2066, acc: 92.8096, loss_bbox: 0.2425, loss_mask: 0.2427, loss: 0.7646 2023-11-13 17:50:43,523 - mmdet - INFO - Epoch [2][5950/7330] lr: 1.000e-04, eta: 7:59:32, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0463, loss_cls: 0.2150, acc: 92.4607, loss_bbox: 0.2536, loss_mask: 0.2463, loss: 0.7892 2023-11-13 17:51:02,442 - mmdet - INFO - Epoch [2][6000/7330] lr: 1.000e-04, eta: 7:59:11, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0460, loss_cls: 0.2054, acc: 92.9287, loss_bbox: 0.2379, loss_mask: 0.2381, loss: 0.7555 2023-11-13 17:51:21,774 - mmdet - INFO - Epoch [2][6050/7330] lr: 1.000e-04, eta: 7:58:52, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0471, loss_cls: 0.2141, acc: 92.4104, loss_bbox: 0.2569, loss_mask: 0.2541, loss: 0.8004 2023-11-13 17:51:41,133 - mmdet - INFO - Epoch [2][6100/7330] lr: 1.000e-04, eta: 7:58:34, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0444, loss_cls: 0.2074, acc: 92.6453, loss_bbox: 0.2457, loss_mask: 0.2450, loss: 0.7729 2023-11-13 17:52:00,132 - mmdet - INFO - Epoch [2][6150/7330] lr: 1.000e-04, eta: 7:58:13, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0471, loss_cls: 0.2096, acc: 92.5515, loss_bbox: 0.2479, loss_mask: 0.2446, loss: 0.7790 2023-11-13 17:52:19,875 - mmdet - INFO - Epoch [2][6200/7330] lr: 1.000e-04, eta: 7:57:56, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0466, loss_cls: 0.2099, acc: 92.5469, loss_bbox: 0.2550, loss_mask: 0.2531, loss: 0.7948 2023-11-13 17:52:39,758 - mmdet - INFO - Epoch [2][6250/7330] lr: 1.000e-04, eta: 7:57:40, time: 0.398, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0510, loss_cls: 0.2162, acc: 92.4033, loss_bbox: 0.2592, loss_mask: 0.2567, loss: 0.8158 2023-11-13 17:52:59,238 - mmdet - INFO - Epoch [2][6300/7330] lr: 1.000e-04, eta: 7:57:22, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0483, loss_cls: 0.2132, acc: 92.3635, loss_bbox: 0.2566, loss_mask: 0.2542, loss: 0.8052 2023-11-13 17:53:18,207 - mmdet - INFO - Epoch [2][6350/7330] lr: 1.000e-04, eta: 7:57:01, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0445, loss_cls: 0.2038, acc: 92.7993, loss_bbox: 0.2438, loss_mask: 0.2431, loss: 0.7631 2023-11-13 17:53:37,647 - mmdet - INFO - Epoch [2][6400/7330] lr: 1.000e-04, eta: 7:56:43, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0501, loss_cls: 0.2093, acc: 92.6169, loss_bbox: 0.2543, loss_mask: 0.2532, loss: 0.7962 2023-11-13 17:53:57,432 - mmdet - INFO - Epoch [2][6450/7330] lr: 1.000e-04, eta: 7:56:27, time: 0.396, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0478, loss_cls: 0.2149, acc: 92.4700, loss_bbox: 0.2539, loss_mask: 0.2515, loss: 0.7993 2023-11-13 17:54:17,041 - mmdet - INFO - Epoch [2][6500/7330] lr: 1.000e-04, eta: 7:56:09, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0471, loss_cls: 0.2076, acc: 92.7466, loss_bbox: 0.2496, loss_mask: 0.2508, loss: 0.7838 2023-11-13 17:54:37,010 - mmdet - INFO - Epoch [2][6550/7330] lr: 1.000e-04, eta: 7:55:54, time: 0.399, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0497, loss_cls: 0.2219, acc: 92.0686, loss_bbox: 0.2665, loss_mask: 0.2517, loss: 0.8202 2023-11-13 17:54:56,135 - mmdet - INFO - Epoch [2][6600/7330] lr: 1.000e-04, eta: 7:55:34, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0429, loss_cls: 0.2031, acc: 92.9290, loss_bbox: 0.2425, loss_mask: 0.2512, loss: 0.7675 2023-11-13 17:55:15,570 - mmdet - INFO - Epoch [2][6650/7330] lr: 1.000e-04, eta: 7:55:15, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0474, loss_cls: 0.2085, acc: 92.5842, loss_bbox: 0.2507, loss_mask: 0.2453, loss: 0.7834 2023-11-13 17:55:34,831 - mmdet - INFO - Epoch [2][6700/7330] lr: 1.000e-04, eta: 7:54:56, time: 0.385, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0491, loss_cls: 0.2091, acc: 92.5991, loss_bbox: 0.2524, loss_mask: 0.2511, loss: 0.7934 2023-11-13 17:55:54,184 - mmdet - INFO - Epoch [2][6750/7330] lr: 1.000e-04, eta: 7:54:37, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0467, loss_cls: 0.2111, acc: 92.6228, loss_bbox: 0.2449, loss_mask: 0.2484, loss: 0.7809 2023-11-13 17:56:13,654 - mmdet - INFO - Epoch [2][6800/7330] lr: 1.000e-04, eta: 7:54:19, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0489, loss_cls: 0.2174, acc: 92.3364, loss_bbox: 0.2576, loss_mask: 0.2507, loss: 0.8062 2023-11-13 17:56:33,143 - mmdet - INFO - Epoch [2][6850/7330] lr: 1.000e-04, eta: 7:54:01, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0506, loss_cls: 0.2188, acc: 92.3049, loss_bbox: 0.2593, loss_mask: 0.2465, loss: 0.8052 2023-11-13 17:56:52,508 - mmdet - INFO - Epoch [2][6900/7330] lr: 1.000e-04, eta: 7:53:42, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0452, loss_cls: 0.2151, acc: 92.4761, loss_bbox: 0.2500, loss_mask: 0.2461, loss: 0.7872 2023-11-13 17:57:11,657 - mmdet - INFO - Epoch [2][6950/7330] lr: 1.000e-04, eta: 7:53:22, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0456, loss_cls: 0.2129, acc: 92.4502, loss_bbox: 0.2513, loss_mask: 0.2465, loss: 0.7859 2023-11-13 17:57:30,974 - mmdet - INFO - Epoch [2][7000/7330] lr: 1.000e-04, eta: 7:53:03, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0504, loss_cls: 0.2269, acc: 92.0190, loss_bbox: 0.2682, loss_mask: 0.2526, loss: 0.8289 2023-11-13 17:57:49,987 - mmdet - INFO - Epoch [2][7050/7330] lr: 1.000e-04, eta: 7:52:42, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0467, loss_cls: 0.2064, acc: 92.7163, loss_bbox: 0.2501, loss_mask: 0.2473, loss: 0.7811 2023-11-13 17:58:09,899 - mmdet - INFO - Epoch [2][7100/7330] lr: 1.000e-04, eta: 7:52:26, time: 0.398, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0534, loss_cls: 0.2212, acc: 92.1882, loss_bbox: 0.2621, loss_mask: 0.2495, loss: 0.8172 2023-11-13 17:58:29,254 - mmdet - INFO - Epoch [2][7150/7330] lr: 1.000e-04, eta: 7:52:07, time: 0.387, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0300, loss_rpn_bbox: 0.0475, loss_cls: 0.2128, acc: 92.4404, loss_bbox: 0.2513, loss_mask: 0.2460, loss: 0.7877 2023-11-13 17:58:48,113 - mmdet - INFO - Epoch [2][7200/7330] lr: 1.000e-04, eta: 7:51:46, time: 0.377, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0424, loss_cls: 0.1980, acc: 93.0374, loss_bbox: 0.2364, loss_mask: 0.2447, loss: 0.7486 2023-11-13 17:59:07,650 - mmdet - INFO - Epoch [2][7250/7330] lr: 1.000e-04, eta: 7:51:28, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0429, loss_cls: 0.2066, acc: 92.7292, loss_bbox: 0.2429, loss_mask: 0.2392, loss: 0.7579 2023-11-13 17:59:26,965 - mmdet - INFO - Epoch [2][7300/7330] lr: 1.000e-04, eta: 7:51:09, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0481, loss_cls: 0.2069, acc: 92.6929, loss_bbox: 0.2545, loss_mask: 0.2412, loss: 0.7796 2023-11-13 17:59:38,963 - mmdet - INFO - Saving checkpoint at 2 epochs 2023-11-13 18:00:28,864 - mmdet - INFO - Evaluating bbox... 2023-11-13 18:01:03,674 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.419 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.653 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.458 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.271 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.463 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.545 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.373 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.596 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.690 2023-11-13 18:01:03,677 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.542 | bicycle | 0.334 | car | 0.437 | | motorcycle | 0.428 | airplane | 0.645 | bus | 0.654 | | train | 0.635 | truck | 0.377 | boat | 0.295 | | traffic light | 0.291 | fire hydrant | 0.663 | stop sign | 0.631 | | parking meter | 0.484 | bench | 0.245 | bird | 0.384 | | cat | 0.686 | dog | 0.651 | horse | 0.573 | | sheep | 0.512 | cow | 0.563 | elephant | 0.640 | | bear | 0.719 | zebra | 0.664 | giraffe | 0.677 | | backpack | 0.179 | umbrella | 0.394 | handbag | 0.160 | | tie | 0.307 | suitcase | 0.381 | frisbee | 0.647 | | skis | 0.221 | snowboard | 0.368 | sports ball | 0.442 | | kite | 0.408 | baseball bat | 0.303 | baseball glove | 0.392 | | skateboard | 0.465 | surfboard | 0.375 | tennis racket | 0.475 | | bottle | 0.409 | wine glass | 0.352 | cup | 0.467 | | fork | 0.353 | knife | 0.217 | spoon | 0.197 | | bowl | 0.417 | banana | 0.245 | apple | 0.230 | | sandwich | 0.405 | orange | 0.294 | broccoli | 0.241 | | carrot | 0.234 | hot dog | 0.367 | pizza | 0.488 | | donut | 0.486 | cake | 0.358 | chair | 0.308 | | couch | 0.408 | potted plant | 0.291 | bed | 0.428 | | dining table | 0.266 | toilet | 0.581 | tv | 0.573 | | laptop | 0.610 | mouse | 0.635 | remote | 0.337 | | keyboard | 0.459 | cell phone | 0.368 | microwave | 0.596 | | oven | 0.345 | toaster | 0.284 | sink | 0.385 | | refrigerator | 0.532 | book | 0.149 | clock | 0.506 | | vase | 0.404 | scissors | 0.290 | teddy bear | 0.444 | | hair drier | 0.088 | toothbrush | 0.257 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:01:03,677 - mmdet - INFO - Evaluating segm... 2023-11-13 18:01:40,526 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.383 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.615 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.407 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.190 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.416 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.555 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.506 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.506 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.506 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.316 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.550 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.657 2023-11-13 18:01:40,529 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.464 | bicycle | 0.193 | car | 0.403 | | motorcycle | 0.340 | airplane | 0.484 | bus | 0.650 | | train | 0.635 | truck | 0.367 | boat | 0.265 | | traffic light | 0.276 | fire hydrant | 0.647 | stop sign | 0.644 | | parking meter | 0.504 | bench | 0.181 | bird | 0.323 | | cat | 0.705 | dog | 0.605 | horse | 0.414 | | sheep | 0.452 | cow | 0.475 | elephant | 0.590 | | bear | 0.718 | zebra | 0.558 | giraffe | 0.489 | | backpack | 0.189 | umbrella | 0.472 | handbag | 0.175 | | tie | 0.303 | suitcase | 0.406 | frisbee | 0.641 | | skis | 0.015 | snowboard | 0.217 | sports ball | 0.449 | | kite | 0.284 | baseball bat | 0.206 | baseball glove | 0.426 | | skateboard | 0.240 | surfboard | 0.322 | tennis racket | 0.544 | | bottle | 0.405 | wine glass | 0.307 | cup | 0.473 | | fork | 0.155 | knife | 0.145 | spoon | 0.129 | | bowl | 0.395 | banana | 0.200 | apple | 0.225 | | sandwich | 0.429 | orange | 0.315 | broccoli | 0.231 | | carrot | 0.209 | hot dog | 0.292 | pizza | 0.493 | | donut | 0.510 | cake | 0.396 | chair | 0.213 | | couch | 0.363 | potted plant | 0.219 | bed | 0.348 | | dining table | 0.143 | toilet | 0.611 | tv | 0.614 | | laptop | 0.629 | mouse | 0.628 | remote | 0.318 | | keyboard | 0.501 | cell phone | 0.347 | microwave | 0.625 | | oven | 0.346 | toaster | 0.370 | sink | 0.385 | | refrigerator | 0.551 | book | 0.108 | clock | 0.520 | | vase | 0.397 | scissors | 0.218 | teddy bear | 0.447 | | hair drier | 0.019 | toothbrush | 0.128 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:01:41,090 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_1.pth was removed 2023-11-13 18:01:43,187 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_2.pth. 2023-11-13 18:01:43,188 - mmdet - INFO - Best bbox_mAP is 0.4194 at 2 epoch. 2023-11-13 18:01:43,188 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 18:01:43,188 - mmdet - INFO - Epoch(val) [2][625] bbox_mAP: 0.4194, bbox_mAP_50: 0.6531, bbox_mAP_75: 0.4583, bbox_mAP_s: 0.2705, bbox_mAP_m: 0.4627, bbox_mAP_l: 0.5450, bbox_mAP_copypaste: 0.4194 0.6531 0.4583 0.2705 0.4627 0.5450, segm_mAP: 0.3828, segm_mAP_50: 0.6151, segm_mAP_75: 0.4072, segm_mAP_s: 0.1905, segm_mAP_m: 0.4160, segm_mAP_l: 0.5553, segm_mAP_copypaste: 0.3828 0.6151 0.4072 0.1905 0.4160 0.5553 2023-11-13 18:02:06,107 - mmdet - INFO - Epoch [3][50/7330] lr: 1.000e-04, eta: 7:49:59, time: 0.458, data_time: 0.092, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0447, loss_cls: 0.1997, acc: 92.7759, loss_bbox: 0.2425, loss_mask: 0.2421, loss: 0.7541 2023-11-13 18:02:26,187 - mmdet - INFO - Epoch [3][100/7330] lr: 1.000e-04, eta: 7:49:43, time: 0.402, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0448, loss_cls: 0.1992, acc: 92.8655, loss_bbox: 0.2399, loss_mask: 0.2422, loss: 0.7529 2023-11-13 18:02:45,900 - mmdet - INFO - Epoch [3][150/7330] lr: 1.000e-04, eta: 7:49:26, time: 0.394, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0467, loss_cls: 0.2077, acc: 92.4595, loss_bbox: 0.2557, loss_mask: 0.2513, loss: 0.7880 2023-11-13 18:03:05,596 - mmdet - INFO - Epoch [3][200/7330] lr: 1.000e-04, eta: 7:49:09, time: 0.394, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0449, loss_cls: 0.1999, acc: 92.8630, loss_bbox: 0.2392, loss_mask: 0.2402, loss: 0.7500 2023-11-13 18:03:25,374 - mmdet - INFO - Epoch [3][250/7330] lr: 1.000e-04, eta: 7:48:53, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0478, loss_cls: 0.2046, acc: 92.6067, loss_bbox: 0.2544, loss_mask: 0.2474, loss: 0.7813 2023-11-13 18:03:45,280 - mmdet - INFO - Epoch [3][300/7330] lr: 1.000e-04, eta: 7:48:37, time: 0.398, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0477, loss_cls: 0.2151, acc: 92.3552, loss_bbox: 0.2553, loss_mask: 0.2493, loss: 0.7966 2023-11-13 18:04:05,279 - mmdet - INFO - Epoch [3][350/7330] lr: 1.000e-04, eta: 7:48:21, time: 0.400, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0475, loss_cls: 0.2037, acc: 92.6304, loss_bbox: 0.2513, loss_mask: 0.2497, loss: 0.7785 2023-11-13 18:04:24,682 - mmdet - INFO - Epoch [3][400/7330] lr: 1.000e-04, eta: 7:48:02, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0442, loss_cls: 0.1996, acc: 92.8289, loss_bbox: 0.2423, loss_mask: 0.2367, loss: 0.7485 2023-11-13 18:04:44,350 - mmdet - INFO - Epoch [3][450/7330] lr: 1.000e-04, eta: 7:47:45, time: 0.393, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0447, loss_cls: 0.1974, acc: 92.8372, loss_bbox: 0.2473, loss_mask: 0.2409, loss: 0.7549 2023-11-13 18:05:04,065 - mmdet - INFO - Epoch [3][500/7330] lr: 1.000e-04, eta: 7:47:28, time: 0.394, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0487, loss_cls: 0.2049, acc: 92.6560, loss_bbox: 0.2479, loss_mask: 0.2409, loss: 0.7718 2023-11-13 18:05:24,187 - mmdet - INFO - Epoch [3][550/7330] lr: 1.000e-04, eta: 7:47:13, time: 0.402, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0474, loss_cls: 0.2132, acc: 92.4795, loss_bbox: 0.2553, loss_mask: 0.2467, loss: 0.7895 2023-11-13 18:05:44,081 - mmdet - INFO - Epoch [3][600/7330] lr: 1.000e-04, eta: 7:46:56, time: 0.398, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0476, loss_cls: 0.2027, acc: 92.6831, loss_bbox: 0.2475, loss_mask: 0.2448, loss: 0.7708 2023-11-13 18:06:03,907 - mmdet - INFO - Epoch [3][650/7330] lr: 1.000e-04, eta: 7:46:40, time: 0.396, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0454, loss_cls: 0.2019, acc: 92.7432, loss_bbox: 0.2473, loss_mask: 0.2382, loss: 0.7582 2023-11-13 18:06:23,576 - mmdet - INFO - Epoch [3][700/7330] lr: 1.000e-04, eta: 7:46:22, time: 0.393, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0455, loss_cls: 0.2011, acc: 92.7212, loss_bbox: 0.2434, loss_mask: 0.2373, loss: 0.7542 2023-11-13 18:06:43,001 - mmdet - INFO - Epoch [3][750/7330] lr: 1.000e-04, eta: 7:46:04, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0433, loss_cls: 0.1979, acc: 92.8232, loss_bbox: 0.2469, loss_mask: 0.2445, loss: 0.7567 2023-11-13 18:07:02,656 - mmdet - INFO - Epoch [3][800/7330] lr: 1.000e-04, eta: 7:45:46, time: 0.393, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0473, loss_cls: 0.2093, acc: 92.4534, loss_bbox: 0.2553, loss_mask: 0.2468, loss: 0.7863 2023-11-13 18:07:22,031 - mmdet - INFO - Epoch [3][850/7330] lr: 1.000e-04, eta: 7:45:28, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0443, loss_cls: 0.1975, acc: 92.8115, loss_bbox: 0.2431, loss_mask: 0.2389, loss: 0.7505 2023-11-13 18:07:41,391 - mmdet - INFO - Epoch [3][900/7330] lr: 1.000e-04, eta: 7:45:09, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0434, loss_cls: 0.1977, acc: 92.7361, loss_bbox: 0.2475, loss_mask: 0.2418, loss: 0.7563 2023-11-13 18:08:01,087 - mmdet - INFO - Epoch [3][950/7330] lr: 1.000e-04, eta: 7:44:51, time: 0.394, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0449, loss_cls: 0.1890, acc: 93.1343, loss_bbox: 0.2347, loss_mask: 0.2370, loss: 0.7323 2023-11-13 18:08:20,485 - mmdet - INFO - Epoch [3][1000/7330] lr: 1.000e-04, eta: 7:44:33, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0470, loss_cls: 0.2051, acc: 92.5986, loss_bbox: 0.2531, loss_mask: 0.2462, loss: 0.7779 2023-11-13 18:08:39,989 - mmdet - INFO - Epoch [3][1050/7330] lr: 1.000e-04, eta: 7:44:14, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0472, loss_cls: 0.2034, acc: 92.5718, loss_bbox: 0.2533, loss_mask: 0.2399, loss: 0.7719 2023-11-13 18:08:59,531 - mmdet - INFO - Epoch [3][1100/7330] lr: 1.000e-04, eta: 7:43:56, time: 0.391, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0451, loss_cls: 0.2045, acc: 92.6687, loss_bbox: 0.2479, loss_mask: 0.2361, loss: 0.7586 2023-11-13 18:09:18,749 - mmdet - INFO - Epoch [3][1150/7330] lr: 1.000e-04, eta: 7:43:37, time: 0.384, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0459, loss_cls: 0.1940, acc: 93.0239, loss_bbox: 0.2391, loss_mask: 0.2385, loss: 0.7440 2023-11-13 18:09:38,238 - mmdet - INFO - Epoch [3][1200/7330] lr: 1.000e-04, eta: 7:43:19, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0460, loss_cls: 0.2069, acc: 92.5786, loss_bbox: 0.2493, loss_mask: 0.2413, loss: 0.7715 2023-11-13 18:09:57,749 - mmdet - INFO - Epoch [3][1250/7330] lr: 1.000e-04, eta: 7:43:00, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0474, loss_cls: 0.1991, acc: 92.8308, loss_bbox: 0.2466, loss_mask: 0.2510, loss: 0.7714 2023-11-13 18:10:17,167 - mmdet - INFO - Epoch [3][1300/7330] lr: 1.000e-04, eta: 7:42:42, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0433, loss_cls: 0.2017, acc: 92.7717, loss_bbox: 0.2414, loss_mask: 0.2458, loss: 0.7571 2023-11-13 18:10:36,665 - mmdet - INFO - Epoch [3][1350/7330] lr: 1.000e-04, eta: 7:42:23, time: 0.390, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0447, loss_cls: 0.1999, acc: 92.7632, loss_bbox: 0.2446, loss_mask: 0.2386, loss: 0.7544 2023-11-13 18:10:56,150 - mmdet - INFO - Epoch [3][1400/7330] lr: 1.000e-04, eta: 7:42:05, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0441, loss_cls: 0.2019, acc: 92.8320, loss_bbox: 0.2476, loss_mask: 0.2437, loss: 0.7648 2023-11-13 18:11:15,902 - mmdet - INFO - Epoch [3][1450/7330] lr: 1.000e-04, eta: 7:41:48, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0467, loss_cls: 0.1960, acc: 92.9487, loss_bbox: 0.2387, loss_mask: 0.2427, loss: 0.7509 2023-11-13 18:11:35,080 - mmdet - INFO - Epoch [3][1500/7330] lr: 1.000e-04, eta: 7:41:28, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0474, loss_cls: 0.2014, acc: 92.7996, loss_bbox: 0.2441, loss_mask: 0.2431, loss: 0.7646 2023-11-13 18:11:54,800 - mmdet - INFO - Epoch [3][1550/7330] lr: 1.000e-04, eta: 7:41:11, time: 0.394, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0458, loss_cls: 0.1992, acc: 92.6814, loss_bbox: 0.2460, loss_mask: 0.2413, loss: 0.7580 2023-11-13 18:12:14,934 - mmdet - INFO - Epoch [3][1600/7330] lr: 1.000e-04, eta: 7:40:55, time: 0.403, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0479, loss_cls: 0.2118, acc: 92.4546, loss_bbox: 0.2574, loss_mask: 0.2466, loss: 0.7914 2023-11-13 18:12:34,982 - mmdet - INFO - Epoch [3][1650/7330] lr: 1.000e-04, eta: 7:40:39, time: 0.401, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0500, loss_cls: 0.2108, acc: 92.3198, loss_bbox: 0.2573, loss_mask: 0.2500, loss: 0.7966 2023-11-13 18:12:54,415 - mmdet - INFO - Epoch [3][1700/7330] lr: 1.000e-04, eta: 7:40:21, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0443, loss_cls: 0.1985, acc: 92.8735, loss_bbox: 0.2462, loss_mask: 0.2429, loss: 0.7602 2023-11-13 18:13:14,142 - mmdet - INFO - Epoch [3][1750/7330] lr: 1.000e-04, eta: 7:40:03, time: 0.394, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0481, loss_cls: 0.2086, acc: 92.5759, loss_bbox: 0.2580, loss_mask: 0.2470, loss: 0.7892 2023-11-13 18:13:33,377 - mmdet - INFO - Epoch [3][1800/7330] lr: 1.000e-04, eta: 7:39:44, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0470, loss_cls: 0.1887, acc: 93.2393, loss_bbox: 0.2313, loss_mask: 0.2423, loss: 0.7351 2023-11-13 18:13:52,834 - mmdet - INFO - Epoch [3][1850/7330] lr: 1.000e-04, eta: 7:39:25, time: 0.389, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0458, loss_cls: 0.1963, acc: 92.8855, loss_bbox: 0.2429, loss_mask: 0.2462, loss: 0.7569 2023-11-13 18:14:12,483 - mmdet - INFO - Epoch [3][1900/7330] lr: 1.000e-04, eta: 7:39:07, time: 0.393, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0478, loss_cls: 0.2099, acc: 92.3630, loss_bbox: 0.2593, loss_mask: 0.2501, loss: 0.7939 2023-11-13 18:14:31,803 - mmdet - INFO - Epoch [3][1950/7330] lr: 1.000e-04, eta: 7:38:48, time: 0.386, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0481, loss_cls: 0.2063, acc: 92.5723, loss_bbox: 0.2518, loss_mask: 0.2494, loss: 0.7836 2023-11-13 18:14:51,309 - mmdet - INFO - Epoch [3][2000/7330] lr: 1.000e-04, eta: 7:38:30, time: 0.390, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0474, loss_cls: 0.2028, acc: 92.6353, loss_bbox: 0.2537, loss_mask: 0.2408, loss: 0.7728 2023-11-13 18:15:10,803 - mmdet - INFO - Epoch [3][2050/7330] lr: 1.000e-04, eta: 7:38:11, time: 0.390, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0434, loss_cls: 0.1973, acc: 92.9280, loss_bbox: 0.2391, loss_mask: 0.2414, loss: 0.7481 2023-11-13 18:15:30,287 - mmdet - INFO - Epoch [3][2100/7330] lr: 1.000e-04, eta: 7:37:53, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0461, loss_cls: 0.2014, acc: 92.7957, loss_bbox: 0.2441, loss_mask: 0.2400, loss: 0.7583 2023-11-13 18:15:49,759 - mmdet - INFO - Epoch [3][2150/7330] lr: 1.000e-04, eta: 7:37:34, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0468, loss_cls: 0.2020, acc: 92.7058, loss_bbox: 0.2405, loss_mask: 0.2447, loss: 0.7619 2023-11-13 18:16:09,061 - mmdet - INFO - Epoch [3][2200/7330] lr: 1.000e-04, eta: 7:37:15, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0459, loss_cls: 0.2042, acc: 92.5635, loss_bbox: 0.2483, loss_mask: 0.2444, loss: 0.7697 2023-11-13 18:16:28,669 - mmdet - INFO - Epoch [3][2250/7330] lr: 1.000e-04, eta: 7:36:57, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0471, loss_cls: 0.2070, acc: 92.5312, loss_bbox: 0.2489, loss_mask: 0.2431, loss: 0.7756 2023-11-13 18:16:48,441 - mmdet - INFO - Epoch [3][2300/7330] lr: 1.000e-04, eta: 7:36:40, time: 0.395, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0459, loss_cls: 0.1937, acc: 93.0332, loss_bbox: 0.2403, loss_mask: 0.2336, loss: 0.7394 2023-11-13 18:17:07,482 - mmdet - INFO - Epoch [3][2350/7330] lr: 1.000e-04, eta: 7:36:19, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0466, loss_cls: 0.1922, acc: 93.1250, loss_bbox: 0.2310, loss_mask: 0.2422, loss: 0.7380 2023-11-13 18:17:26,642 - mmdet - INFO - Epoch [3][2400/7330] lr: 1.000e-04, eta: 7:36:00, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0451, loss_cls: 0.1975, acc: 92.9363, loss_bbox: 0.2430, loss_mask: 0.2376, loss: 0.7501 2023-11-13 18:17:46,095 - mmdet - INFO - Epoch [3][2450/7330] lr: 1.000e-04, eta: 7:35:41, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0447, loss_cls: 0.2008, acc: 92.7708, loss_bbox: 0.2476, loss_mask: 0.2440, loss: 0.7620 2023-11-13 18:18:05,059 - mmdet - INFO - Epoch [3][2500/7330] lr: 1.000e-04, eta: 7:35:20, time: 0.379, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0442, loss_cls: 0.1890, acc: 93.2642, loss_bbox: 0.2287, loss_mask: 0.2370, loss: 0.7236 2023-11-13 18:18:24,141 - mmdet - INFO - Epoch [3][2550/7330] lr: 1.000e-04, eta: 7:35:00, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0463, loss_cls: 0.1952, acc: 93.0542, loss_bbox: 0.2341, loss_mask: 0.2458, loss: 0.7483 2023-11-13 18:18:43,646 - mmdet - INFO - Epoch [3][2600/7330] lr: 1.000e-04, eta: 7:34:42, time: 0.390, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0471, loss_cls: 0.2043, acc: 92.7112, loss_bbox: 0.2449, loss_mask: 0.2380, loss: 0.7622 2023-11-13 18:19:02,898 - mmdet - INFO - Epoch [3][2650/7330] lr: 1.000e-04, eta: 7:34:22, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0444, loss_cls: 0.1989, acc: 92.8398, loss_bbox: 0.2424, loss_mask: 0.2356, loss: 0.7457 2023-11-13 18:19:21,776 - mmdet - INFO - Epoch [3][2700/7330] lr: 1.000e-04, eta: 7:34:01, time: 0.378, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0444, loss_cls: 0.1982, acc: 92.8318, loss_bbox: 0.2405, loss_mask: 0.2392, loss: 0.7477 2023-11-13 18:19:40,757 - mmdet - INFO - Epoch [3][2750/7330] lr: 1.000e-04, eta: 7:33:41, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0445, loss_cls: 0.2037, acc: 92.6482, loss_bbox: 0.2491, loss_mask: 0.2392, loss: 0.7629 2023-11-13 18:20:00,001 - mmdet - INFO - Epoch [3][2800/7330] lr: 1.000e-04, eta: 7:33:21, time: 0.385, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0455, loss_cls: 0.1985, acc: 92.8286, loss_bbox: 0.2400, loss_mask: 0.2400, loss: 0.7514 2023-11-13 18:20:19,316 - mmdet - INFO - Epoch [3][2850/7330] lr: 1.000e-04, eta: 7:33:02, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0482, loss_cls: 0.2067, acc: 92.5405, loss_bbox: 0.2480, loss_mask: 0.2434, loss: 0.7741 2023-11-13 18:20:38,655 - mmdet - INFO - Epoch [3][2900/7330] lr: 1.000e-04, eta: 7:32:43, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0443, loss_cls: 0.1964, acc: 92.9380, loss_bbox: 0.2430, loss_mask: 0.2429, loss: 0.7534 2023-11-13 18:20:58,103 - mmdet - INFO - Epoch [3][2950/7330] lr: 1.000e-04, eta: 7:32:24, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0479, loss_cls: 0.2105, acc: 92.4790, loss_bbox: 0.2526, loss_mask: 0.2418, loss: 0.7798 2023-11-13 18:21:17,541 - mmdet - INFO - Epoch [3][3000/7330] lr: 1.000e-04, eta: 7:32:06, time: 0.389, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0450, loss_cls: 0.1995, acc: 92.7998, loss_bbox: 0.2436, loss_mask: 0.2432, loss: 0.7587 2023-11-13 18:21:36,861 - mmdet - INFO - Epoch [3][3050/7330] lr: 1.000e-04, eta: 7:31:46, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0466, loss_cls: 0.2018, acc: 92.8518, loss_bbox: 0.2483, loss_mask: 0.2451, loss: 0.7701 2023-11-13 18:21:56,020 - mmdet - INFO - Epoch [3][3100/7330] lr: 1.000e-04, eta: 7:31:27, time: 0.383, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0468, loss_cls: 0.2047, acc: 92.6592, loss_bbox: 0.2489, loss_mask: 0.2369, loss: 0.7654 2023-11-13 18:22:15,369 - mmdet - INFO - Epoch [3][3150/7330] lr: 1.000e-04, eta: 7:31:07, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0459, loss_cls: 0.1995, acc: 92.9302, loss_bbox: 0.2387, loss_mask: 0.2361, loss: 0.7496 2023-11-13 18:22:34,470 - mmdet - INFO - Epoch [3][3200/7330] lr: 1.000e-04, eta: 7:30:47, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0435, loss_cls: 0.1962, acc: 92.9839, loss_bbox: 0.2412, loss_mask: 0.2423, loss: 0.7489 2023-11-13 18:22:53,390 - mmdet - INFO - Epoch [3][3250/7330] lr: 1.000e-04, eta: 7:30:27, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0445, loss_cls: 0.1972, acc: 92.7751, loss_bbox: 0.2447, loss_mask: 0.2439, loss: 0.7571 2023-11-13 18:23:12,297 - mmdet - INFO - Epoch [3][3300/7330] lr: 1.000e-04, eta: 7:30:06, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0461, loss_cls: 0.2029, acc: 92.8235, loss_bbox: 0.2415, loss_mask: 0.2357, loss: 0.7524 2023-11-13 18:23:31,182 - mmdet - INFO - Epoch [3][3350/7330] lr: 1.000e-04, eta: 7:29:45, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0433, loss_cls: 0.1884, acc: 93.1523, loss_bbox: 0.2323, loss_mask: 0.2367, loss: 0.7243 2023-11-13 18:23:50,582 - mmdet - INFO - Epoch [3][3400/7330] lr: 1.000e-04, eta: 7:29:26, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0465, loss_cls: 0.2013, acc: 92.8408, loss_bbox: 0.2447, loss_mask: 0.2451, loss: 0.7634 2023-11-13 18:24:09,959 - mmdet - INFO - Epoch [3][3450/7330] lr: 1.000e-04, eta: 7:29:07, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0444, loss_cls: 0.1928, acc: 93.0466, loss_bbox: 0.2399, loss_mask: 0.2341, loss: 0.7377 2023-11-13 18:24:29,308 - mmdet - INFO - Epoch [3][3500/7330] lr: 1.000e-04, eta: 7:28:48, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0463, loss_cls: 0.2033, acc: 92.6211, loss_bbox: 0.2490, loss_mask: 0.2465, loss: 0.7727 2023-11-13 18:24:48,868 - mmdet - INFO - Epoch [3][3550/7330] lr: 1.000e-04, eta: 7:28:30, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0455, loss_cls: 0.2038, acc: 92.6047, loss_bbox: 0.2495, loss_mask: 0.2416, loss: 0.7676 2023-11-13 18:25:08,249 - mmdet - INFO - Epoch [3][3600/7330] lr: 1.000e-04, eta: 7:28:11, time: 0.388, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0464, loss_cls: 0.2086, acc: 92.5120, loss_bbox: 0.2526, loss_mask: 0.2482, loss: 0.7831 2023-11-13 18:25:27,506 - mmdet - INFO - Epoch [3][3650/7330] lr: 1.000e-04, eta: 7:27:51, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0431, loss_cls: 0.2065, acc: 92.7603, loss_bbox: 0.2464, loss_mask: 0.2407, loss: 0.7634 2023-11-13 18:25:46,650 - mmdet - INFO - Epoch [3][3700/7330] lr: 1.000e-04, eta: 7:27:32, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0450, loss_cls: 0.2029, acc: 92.7607, loss_bbox: 0.2417, loss_mask: 0.2413, loss: 0.7577 2023-11-13 18:26:05,681 - mmdet - INFO - Epoch [3][3750/7330] lr: 1.000e-04, eta: 7:27:11, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0434, loss_cls: 0.2023, acc: 92.7053, loss_bbox: 0.2432, loss_mask: 0.2399, loss: 0.7553 2023-11-13 18:26:24,659 - mmdet - INFO - Epoch [3][3800/7330] lr: 1.000e-04, eta: 7:26:51, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0440, loss_cls: 0.1965, acc: 92.8408, loss_bbox: 0.2386, loss_mask: 0.2373, loss: 0.7418 2023-11-13 18:26:43,506 - mmdet - INFO - Epoch [3][3850/7330] lr: 1.000e-04, eta: 7:26:30, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0472, loss_cls: 0.2108, acc: 92.4250, loss_bbox: 0.2529, loss_mask: 0.2450, loss: 0.7833 2023-11-13 18:27:02,674 - mmdet - INFO - Epoch [3][3900/7330] lr: 1.000e-04, eta: 7:26:10, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0477, loss_cls: 0.2071, acc: 92.5393, loss_bbox: 0.2483, loss_mask: 0.2482, loss: 0.7810 2023-11-13 18:27:22,241 - mmdet - INFO - Epoch [3][3950/7330] lr: 1.000e-04, eta: 7:25:52, time: 0.391, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0440, loss_cls: 0.1981, acc: 92.8098, loss_bbox: 0.2392, loss_mask: 0.2384, loss: 0.7470 2023-11-13 18:27:41,373 - mmdet - INFO - Epoch [3][4000/7330] lr: 1.000e-04, eta: 7:25:32, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0471, loss_cls: 0.2029, acc: 92.7517, loss_bbox: 0.2483, loss_mask: 0.2433, loss: 0.7706 2023-11-13 18:28:00,715 - mmdet - INFO - Epoch [3][4050/7330] lr: 1.000e-04, eta: 7:25:13, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0461, loss_cls: 0.2040, acc: 92.7727, loss_bbox: 0.2473, loss_mask: 0.2387, loss: 0.7637 2023-11-13 18:28:19,725 - mmdet - INFO - Epoch [3][4100/7330] lr: 1.000e-04, eta: 7:24:53, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0449, loss_cls: 0.2050, acc: 92.6160, loss_bbox: 0.2482, loss_mask: 0.2422, loss: 0.7661 2023-11-13 18:28:38,921 - mmdet - INFO - Epoch [3][4150/7330] lr: 1.000e-04, eta: 7:24:33, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0452, loss_cls: 0.1979, acc: 92.8340, loss_bbox: 0.2419, loss_mask: 0.2401, loss: 0.7535 2023-11-13 18:28:57,955 - mmdet - INFO - Epoch [3][4200/7330] lr: 1.000e-04, eta: 7:24:13, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0466, loss_cls: 0.2004, acc: 92.9067, loss_bbox: 0.2400, loss_mask: 0.2400, loss: 0.7558 2023-11-13 18:29:17,129 - mmdet - INFO - Epoch [3][4250/7330] lr: 1.000e-04, eta: 7:23:53, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0454, loss_cls: 0.2066, acc: 92.6694, loss_bbox: 0.2425, loss_mask: 0.2397, loss: 0.7609 2023-11-13 18:29:36,304 - mmdet - INFO - Epoch [3][4300/7330] lr: 1.000e-04, eta: 7:23:33, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0460, loss_cls: 0.1960, acc: 92.9971, loss_bbox: 0.2426, loss_mask: 0.2403, loss: 0.7533 2023-11-13 18:29:55,836 - mmdet - INFO - Epoch [3][4350/7330] lr: 1.000e-04, eta: 7:23:15, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0441, loss_cls: 0.1929, acc: 93.1562, loss_bbox: 0.2369, loss_mask: 0.2389, loss: 0.7365 2023-11-13 18:30:15,204 - mmdet - INFO - Epoch [3][4400/7330] lr: 1.000e-04, eta: 7:22:56, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0480, loss_cls: 0.2048, acc: 92.5652, loss_bbox: 0.2517, loss_mask: 0.2496, loss: 0.7821 2023-11-13 18:30:34,792 - mmdet - INFO - Epoch [3][4450/7330] lr: 1.000e-04, eta: 7:22:38, time: 0.392, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0455, loss_cls: 0.1961, acc: 92.9321, loss_bbox: 0.2413, loss_mask: 0.2363, loss: 0.7466 2023-11-13 18:30:54,605 - mmdet - INFO - Epoch [3][4500/7330] lr: 1.000e-04, eta: 7:22:20, time: 0.396, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0458, loss_cls: 0.2061, acc: 92.5718, loss_bbox: 0.2433, loss_mask: 0.2343, loss: 0.7541 2023-11-13 18:31:13,718 - mmdet - INFO - Epoch [3][4550/7330] lr: 1.000e-04, eta: 7:22:01, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0451, loss_cls: 0.1950, acc: 93.0103, loss_bbox: 0.2379, loss_mask: 0.2369, loss: 0.7414 2023-11-13 18:31:33,085 - mmdet - INFO - Epoch [3][4600/7330] lr: 1.000e-04, eta: 7:21:42, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0475, loss_cls: 0.2042, acc: 92.6658, loss_bbox: 0.2485, loss_mask: 0.2438, loss: 0.7706 2023-11-13 18:31:52,246 - mmdet - INFO - Epoch [3][4650/7330] lr: 1.000e-04, eta: 7:21:22, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0473, loss_cls: 0.2075, acc: 92.5862, loss_bbox: 0.2503, loss_mask: 0.2443, loss: 0.7763 2023-11-13 18:32:11,028 - mmdet - INFO - Epoch [3][4700/7330] lr: 1.000e-04, eta: 7:21:01, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0456, loss_cls: 0.1971, acc: 92.9241, loss_bbox: 0.2402, loss_mask: 0.2362, loss: 0.7468 2023-11-13 18:32:30,082 - mmdet - INFO - Epoch [3][4750/7330] lr: 1.000e-04, eta: 7:20:41, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0470, loss_cls: 0.1938, acc: 93.0334, loss_bbox: 0.2397, loss_mask: 0.2407, loss: 0.7501 2023-11-13 18:32:48,992 - mmdet - INFO - Epoch [3][4800/7330] lr: 1.000e-04, eta: 7:20:20, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0275, loss_rpn_bbox: 0.0433, loss_cls: 0.1970, acc: 92.9958, loss_bbox: 0.2341, loss_mask: 0.2399, loss: 0.7419 2023-11-13 18:33:08,257 - mmdet - INFO - Epoch [3][4850/7330] lr: 1.000e-04, eta: 7:20:01, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0477, loss_cls: 0.1993, acc: 92.7263, loss_bbox: 0.2482, loss_mask: 0.2436, loss: 0.7663 2023-11-13 18:33:27,247 - mmdet - INFO - Epoch [3][4900/7330] lr: 1.000e-04, eta: 7:19:40, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0451, loss_cls: 0.1932, acc: 92.9932, loss_bbox: 0.2352, loss_mask: 0.2368, loss: 0.7369 2023-11-13 18:33:46,106 - mmdet - INFO - Epoch [3][4950/7330] lr: 1.000e-04, eta: 7:19:20, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0457, loss_cls: 0.2095, acc: 92.5791, loss_bbox: 0.2504, loss_mask: 0.2419, loss: 0.7756 2023-11-13 18:34:05,167 - mmdet - INFO - Epoch [3][5000/7330] lr: 1.000e-04, eta: 7:19:00, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0444, loss_cls: 0.2010, acc: 92.7080, loss_bbox: 0.2483, loss_mask: 0.2432, loss: 0.7629 2023-11-13 18:34:23,890 - mmdet - INFO - Epoch [3][5050/7330] lr: 1.000e-04, eta: 7:18:38, time: 0.375, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0405, loss_cls: 0.1923, acc: 93.0845, loss_bbox: 0.2333, loss_mask: 0.2431, loss: 0.7320 2023-11-13 18:34:42,954 - mmdet - INFO - Epoch [3][5100/7330] lr: 1.000e-04, eta: 7:18:18, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0465, loss_cls: 0.2074, acc: 92.5352, loss_bbox: 0.2498, loss_mask: 0.2393, loss: 0.7706 2023-11-13 18:35:02,165 - mmdet - INFO - Epoch [3][5150/7330] lr: 1.000e-04, eta: 7:17:59, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0448, loss_cls: 0.1911, acc: 93.0916, loss_bbox: 0.2356, loss_mask: 0.2396, loss: 0.7367 2023-11-13 18:35:21,301 - mmdet - INFO - Epoch [3][5200/7330] lr: 1.000e-04, eta: 7:17:39, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0465, loss_cls: 0.1965, acc: 92.8831, loss_bbox: 0.2447, loss_mask: 0.2354, loss: 0.7511 2023-11-13 18:35:40,074 - mmdet - INFO - Epoch [3][5250/7330] lr: 1.000e-04, eta: 7:17:18, time: 0.375, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0439, loss_cls: 0.1935, acc: 93.0151, loss_bbox: 0.2353, loss_mask: 0.2336, loss: 0.7298 2023-11-13 18:35:59,210 - mmdet - INFO - Epoch [3][5300/7330] lr: 1.000e-04, eta: 7:16:58, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0430, loss_cls: 0.1924, acc: 93.0701, loss_bbox: 0.2399, loss_mask: 0.2336, loss: 0.7323 2023-11-13 18:36:18,324 - mmdet - INFO - Epoch [3][5350/7330] lr: 1.000e-04, eta: 7:16:38, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0453, loss_cls: 0.1994, acc: 92.8542, loss_bbox: 0.2357, loss_mask: 0.2373, loss: 0.7449 2023-11-13 18:36:37,190 - mmdet - INFO - Epoch [3][5400/7330] lr: 1.000e-04, eta: 7:16:18, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0406, loss_cls: 0.1827, acc: 93.4326, loss_bbox: 0.2255, loss_mask: 0.2333, loss: 0.7069 2023-11-13 18:36:56,124 - mmdet - INFO - Epoch [3][5450/7330] lr: 1.000e-04, eta: 7:15:57, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0427, loss_cls: 0.1893, acc: 93.1804, loss_bbox: 0.2362, loss_mask: 0.2392, loss: 0.7316 2023-11-13 18:37:15,243 - mmdet - INFO - Epoch [3][5500/7330] lr: 1.000e-04, eta: 7:15:37, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0416, loss_cls: 0.1890, acc: 93.2344, loss_bbox: 0.2366, loss_mask: 0.2378, loss: 0.7296 2023-11-13 18:37:34,568 - mmdet - INFO - Epoch [3][5550/7330] lr: 1.000e-04, eta: 7:15:18, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0272, loss_rpn_bbox: 0.0430, loss_cls: 0.1983, acc: 92.8730, loss_bbox: 0.2419, loss_mask: 0.2422, loss: 0.7526 2023-11-13 18:37:53,632 - mmdet - INFO - Epoch [3][5600/7330] lr: 1.000e-04, eta: 7:14:58, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0271, loss_rpn_bbox: 0.0444, loss_cls: 0.1987, acc: 92.8962, loss_bbox: 0.2357, loss_mask: 0.2343, loss: 0.7402 2023-11-13 18:38:12,428 - mmdet - INFO - Epoch [3][5650/7330] lr: 1.000e-04, eta: 7:14:37, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0428, loss_cls: 0.1931, acc: 93.0037, loss_bbox: 0.2364, loss_mask: 0.2363, loss: 0.7323 2023-11-13 18:38:31,372 - mmdet - INFO - Epoch [3][5700/7330] lr: 1.000e-04, eta: 7:14:17, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0447, loss_cls: 0.2024, acc: 92.6887, loss_bbox: 0.2482, loss_mask: 0.2401, loss: 0.7613 2023-11-13 18:38:50,123 - mmdet - INFO - Epoch [3][5750/7330] lr: 1.000e-04, eta: 7:13:56, time: 0.375, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0433, loss_cls: 0.1937, acc: 93.1172, loss_bbox: 0.2338, loss_mask: 0.2377, loss: 0.7358 2023-11-13 18:39:08,831 - mmdet - INFO - Epoch [3][5800/7330] lr: 1.000e-04, eta: 7:13:35, time: 0.374, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0432, loss_cls: 0.1931, acc: 93.0391, loss_bbox: 0.2295, loss_mask: 0.2372, loss: 0.7292 2023-11-13 18:39:27,639 - mmdet - INFO - Epoch [3][5850/7330] lr: 1.000e-04, eta: 7:13:14, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0429, loss_cls: 0.1958, acc: 92.8972, loss_bbox: 0.2439, loss_mask: 0.2379, loss: 0.7455 2023-11-13 18:39:46,673 - mmdet - INFO - Epoch [3][5900/7330] lr: 1.000e-04, eta: 7:12:54, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0254, loss_rpn_bbox: 0.0442, loss_cls: 0.1966, acc: 92.8250, loss_bbox: 0.2390, loss_mask: 0.2404, loss: 0.7458 2023-11-13 18:40:05,861 - mmdet - INFO - Epoch [3][5950/7330] lr: 1.000e-04, eta: 7:12:35, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0461, loss_cls: 0.1997, acc: 92.9136, loss_bbox: 0.2408, loss_mask: 0.2362, loss: 0.7495 2023-11-13 18:40:25,271 - mmdet - INFO - Epoch [3][6000/7330] lr: 1.000e-04, eta: 7:12:16, time: 0.388, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0439, loss_cls: 0.1962, acc: 92.9041, loss_bbox: 0.2379, loss_mask: 0.2391, loss: 0.7444 2023-11-13 18:40:44,540 - mmdet - INFO - Epoch [3][6050/7330] lr: 1.000e-04, eta: 7:11:57, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0466, loss_cls: 0.2007, acc: 92.8928, loss_bbox: 0.2412, loss_mask: 0.2411, loss: 0.7555 2023-11-13 18:41:03,223 - mmdet - INFO - Epoch [3][6100/7330] lr: 1.000e-04, eta: 7:11:35, time: 0.374, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0425, loss_cls: 0.1867, acc: 93.2402, loss_bbox: 0.2308, loss_mask: 0.2377, loss: 0.7207 2023-11-13 18:41:22,355 - mmdet - INFO - Epoch [3][6150/7330] lr: 1.000e-04, eta: 7:11:16, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0439, loss_cls: 0.1930, acc: 93.0498, loss_bbox: 0.2375, loss_mask: 0.2341, loss: 0.7338 2023-11-13 18:41:41,101 - mmdet - INFO - Epoch [3][6200/7330] lr: 1.000e-04, eta: 7:10:55, time: 0.375, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0436, loss_cls: 0.1877, acc: 93.2878, loss_bbox: 0.2298, loss_mask: 0.2363, loss: 0.7238 2023-11-13 18:41:59,910 - mmdet - INFO - Epoch [3][6250/7330] lr: 1.000e-04, eta: 7:10:34, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0456, loss_cls: 0.2027, acc: 92.7202, loss_bbox: 0.2407, loss_mask: 0.2434, loss: 0.7591 2023-11-13 18:42:19,147 - mmdet - INFO - Epoch [3][6300/7330] lr: 1.000e-04, eta: 7:10:15, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0441, loss_cls: 0.1928, acc: 93.0269, loss_bbox: 0.2389, loss_mask: 0.2364, loss: 0.7373 2023-11-13 18:42:38,066 - mmdet - INFO - Epoch [3][6350/7330] lr: 1.000e-04, eta: 7:09:54, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0282, loss_rpn_bbox: 0.0462, loss_cls: 0.2040, acc: 92.6467, loss_bbox: 0.2448, loss_mask: 0.2400, loss: 0.7632 2023-11-13 18:42:57,018 - mmdet - INFO - Epoch [3][6400/7330] lr: 1.000e-04, eta: 7:09:34, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0450, loss_cls: 0.1998, acc: 92.7803, loss_bbox: 0.2421, loss_mask: 0.2399, loss: 0.7530 2023-11-13 18:43:15,817 - mmdet - INFO - Epoch [3][6450/7330] lr: 1.000e-04, eta: 7:09:13, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0431, loss_cls: 0.1947, acc: 92.9873, loss_bbox: 0.2332, loss_mask: 0.2388, loss: 0.7366 2023-11-13 18:43:34,987 - mmdet - INFO - Epoch [3][6500/7330] lr: 1.000e-04, eta: 7:08:54, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0448, loss_cls: 0.1949, acc: 93.0144, loss_bbox: 0.2364, loss_mask: 0.2421, loss: 0.7446 2023-11-13 18:43:54,129 - mmdet - INFO - Epoch [3][6550/7330] lr: 1.000e-04, eta: 7:08:34, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0454, loss_cls: 0.1990, acc: 92.8906, loss_bbox: 0.2394, loss_mask: 0.2379, loss: 0.7472 2023-11-13 18:44:14,080 - mmdet - INFO - Epoch [3][6600/7330] lr: 1.000e-04, eta: 7:08:17, time: 0.399, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0457, loss_cls: 0.1951, acc: 93.1018, loss_bbox: 0.2346, loss_mask: 0.2376, loss: 0.7393 2023-11-13 18:44:33,236 - mmdet - INFO - Epoch [3][6650/7330] lr: 1.000e-04, eta: 7:07:57, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0458, loss_cls: 0.1933, acc: 93.1238, loss_bbox: 0.2354, loss_mask: 0.2367, loss: 0.7365 2023-11-13 18:44:52,585 - mmdet - INFO - Epoch [3][6700/7330] lr: 1.000e-04, eta: 7:07:38, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0486, loss_cls: 0.1933, acc: 92.8618, loss_bbox: 0.2429, loss_mask: 0.2491, loss: 0.7620 2023-11-13 18:45:12,411 - mmdet - INFO - Epoch [3][6750/7330] lr: 1.000e-04, eta: 7:07:21, time: 0.396, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0447, loss_cls: 0.1988, acc: 92.7627, loss_bbox: 0.2440, loss_mask: 0.2391, loss: 0.7523 2023-11-13 18:45:31,312 - mmdet - INFO - Epoch [3][6800/7330] lr: 1.000e-04, eta: 7:07:00, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0427, loss_cls: 0.1945, acc: 93.1143, loss_bbox: 0.2327, loss_mask: 0.2373, loss: 0.7336 2023-11-13 18:45:50,199 - mmdet - INFO - Epoch [3][6850/7330] lr: 1.000e-04, eta: 7:06:40, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0453, loss_cls: 0.1916, acc: 93.0818, loss_bbox: 0.2374, loss_mask: 0.2365, loss: 0.7352 2023-11-13 18:46:09,181 - mmdet - INFO - Epoch [3][6900/7330] lr: 1.000e-04, eta: 7:06:20, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0423, loss_cls: 0.1974, acc: 92.8608, loss_bbox: 0.2375, loss_mask: 0.2343, loss: 0.7376 2023-11-13 18:46:28,560 - mmdet - INFO - Epoch [3][6950/7330] lr: 1.000e-04, eta: 7:06:01, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0468, loss_cls: 0.2064, acc: 92.6523, loss_bbox: 0.2486, loss_mask: 0.2432, loss: 0.7733 2023-11-13 18:46:47,889 - mmdet - INFO - Epoch [3][7000/7330] lr: 1.000e-04, eta: 7:05:42, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0449, loss_cls: 0.1976, acc: 92.8613, loss_bbox: 0.2413, loss_mask: 0.2368, loss: 0.7461 2023-11-13 18:47:06,750 - mmdet - INFO - Epoch [3][7050/7330] lr: 1.000e-04, eta: 7:05:21, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0441, loss_cls: 0.1900, acc: 93.2212, loss_bbox: 0.2332, loss_mask: 0.2361, loss: 0.7297 2023-11-13 18:47:25,961 - mmdet - INFO - Epoch [3][7100/7330] lr: 1.000e-04, eta: 7:05:02, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0451, loss_cls: 0.1978, acc: 92.8198, loss_bbox: 0.2436, loss_mask: 0.2336, loss: 0.7464 2023-11-13 18:47:44,742 - mmdet - INFO - Epoch [3][7150/7330] lr: 1.000e-04, eta: 7:04:41, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0478, loss_cls: 0.2074, acc: 92.5027, loss_bbox: 0.2482, loss_mask: 0.2456, loss: 0.7756 2023-11-13 18:48:04,310 - mmdet - INFO - Epoch [3][7200/7330] lr: 1.000e-04, eta: 7:04:23, time: 0.391, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0449, loss_cls: 0.1940, acc: 92.9446, loss_bbox: 0.2404, loss_mask: 0.2378, loss: 0.7429 2023-11-13 18:48:23,571 - mmdet - INFO - Epoch [3][7250/7330] lr: 1.000e-04, eta: 7:04:04, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0478, loss_cls: 0.2013, acc: 92.8806, loss_bbox: 0.2367, loss_mask: 0.2363, loss: 0.7519 2023-11-13 18:48:42,841 - mmdet - INFO - Epoch [3][7300/7330] lr: 1.000e-04, eta: 7:03:44, time: 0.385, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0439, loss_cls: 0.1927, acc: 93.0393, loss_bbox: 0.2416, loss_mask: 0.2420, loss: 0.7470 2023-11-13 18:48:54,902 - mmdet - INFO - Saving checkpoint at 3 epochs 2023-11-13 18:49:43,076 - mmdet - INFO - Evaluating bbox... 2023-11-13 18:50:14,693 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.439 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.672 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.484 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.281 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.483 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.572 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.568 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.568 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.568 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.387 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.612 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.717 2023-11-13 18:50:14,695 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.558 | bicycle | 0.344 | car | 0.462 | | motorcycle | 0.441 | airplane | 0.647 | bus | 0.662 | | train | 0.653 | truck | 0.367 | boat | 0.305 | | traffic light | 0.291 | fire hydrant | 0.699 | stop sign | 0.646 | | parking meter | 0.508 | bench | 0.271 | bird | 0.389 | | cat | 0.710 | dog | 0.668 | horse | 0.599 | | sheep | 0.555 | cow | 0.612 | elephant | 0.641 | | bear | 0.701 | zebra | 0.649 | giraffe | 0.678 | | backpack | 0.196 | umbrella | 0.413 | handbag | 0.179 | | tie | 0.342 | suitcase | 0.437 | frisbee | 0.675 | | skis | 0.259 | snowboard | 0.320 | sports ball | 0.451 | | kite | 0.443 | baseball bat | 0.351 | baseball glove | 0.406 | | skateboard | 0.489 | surfboard | 0.405 | tennis racket | 0.508 | | bottle | 0.418 | wine glass | 0.386 | cup | 0.471 | | fork | 0.396 | knife | 0.236 | spoon | 0.235 | | bowl | 0.437 | banana | 0.281 | apple | 0.231 | | sandwich | 0.416 | orange | 0.330 | broccoli | 0.249 | | carrot | 0.222 | hot dog | 0.416 | pizza | 0.518 | | donut | 0.507 | cake | 0.403 | chair | 0.315 | | couch | 0.456 | potted plant | 0.317 | bed | 0.403 | | dining table | 0.268 | toilet | 0.615 | tv | 0.589 | | laptop | 0.625 | mouse | 0.648 | remote | 0.361 | | keyboard | 0.480 | cell phone | 0.405 | microwave | 0.576 | | oven | 0.329 | toaster | 0.353 | sink | 0.413 | | refrigerator | 0.537 | book | 0.165 | clock | 0.524 | | vase | 0.407 | scissors | 0.324 | teddy bear | 0.463 | | hair drier | 0.149 | toothbrush | 0.285 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:50:14,696 - mmdet - INFO - Evaluating segm... 2023-11-13 18:50:50,300 - 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 ] = 0.636 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.429 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.434 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.584 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.524 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.524 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.524 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 ] = 0.567 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.683 2023-11-13 18:50:50,302 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.482 | bicycle | 0.197 | car | 0.429 | | motorcycle | 0.354 | airplane | 0.510 | bus | 0.662 | | train | 0.644 | truck | 0.367 | boat | 0.259 | | traffic light | 0.279 | fire hydrant | 0.678 | stop sign | 0.673 | | parking meter | 0.533 | bench | 0.195 | bird | 0.331 | | cat | 0.707 | dog | 0.628 | horse | 0.438 | | sheep | 0.491 | cow | 0.524 | elephant | 0.583 | | bear | 0.753 | zebra | 0.555 | giraffe | 0.519 | | backpack | 0.203 | umbrella | 0.488 | handbag | 0.189 | | tie | 0.330 | suitcase | 0.459 | frisbee | 0.650 | | skis | 0.039 | snowboard | 0.214 | sports ball | 0.443 | | kite | 0.321 | baseball bat | 0.268 | baseball glove | 0.445 | | skateboard | 0.313 | surfboard | 0.338 | tennis racket | 0.569 | | bottle | 0.401 | wine glass | 0.334 | cup | 0.483 | | fork | 0.200 | knife | 0.150 | spoon | 0.161 | | bowl | 0.419 | banana | 0.228 | apple | 0.226 | | sandwich | 0.439 | orange | 0.344 | broccoli | 0.232 | | carrot | 0.195 | hot dog | 0.330 | pizza | 0.504 | | donut | 0.516 | cake | 0.428 | chair | 0.222 | | couch | 0.404 | potted plant | 0.259 | bed | 0.338 | | dining table | 0.154 | toilet | 0.611 | tv | 0.620 | | laptop | 0.636 | mouse | 0.632 | remote | 0.322 | | keyboard | 0.485 | cell phone | 0.382 | microwave | 0.621 | | oven | 0.313 | toaster | 0.402 | sink | 0.390 | | refrigerator | 0.573 | book | 0.118 | clock | 0.533 | | vase | 0.397 | scissors | 0.242 | teddy bear | 0.454 | | hair drier | 0.058 | toothbrush | 0.185 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:50:50,763 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_2.pth was removed 2023-11-13 18:50:52,730 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_3.pth. 2023-11-13 18:50:52,731 - mmdet - INFO - Best bbox_mAP is 0.4386 at 3 epoch. 2023-11-13 18:50:52,731 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 18:50:52,731 - mmdet - INFO - Epoch(val) [3][625] bbox_mAP: 0.4386, bbox_mAP_50: 0.6723, bbox_mAP_75: 0.4838, bbox_mAP_s: 0.2807, bbox_mAP_m: 0.4833, bbox_mAP_l: 0.5720, bbox_mAP_copypaste: 0.4386 0.6723 0.4838 0.2807 0.4833 0.5720, segm_mAP: 0.4000, segm_mAP_50: 0.6358, segm_mAP_75: 0.4285, segm_mAP_s: 0.2084, segm_mAP_m: 0.4343, segm_mAP_l: 0.5837, segm_mAP_copypaste: 0.4000 0.6358 0.4285 0.2084 0.4343 0.5837 2023-11-13 18:51:15,789 - mmdet - INFO - Epoch [4][50/7330] lr: 1.000e-04, eta: 7:02:50, time: 0.461, data_time: 0.095, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0442, loss_cls: 0.1926, acc: 92.9202, loss_bbox: 0.2398, loss_mask: 0.2377, loss: 0.7390 2023-11-13 18:51:35,281 - mmdet - INFO - Epoch [4][100/7330] lr: 1.000e-04, eta: 7:02:32, time: 0.390, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0453, loss_cls: 0.1870, acc: 93.0579, loss_bbox: 0.2398, loss_mask: 0.2332, loss: 0.7300 2023-11-13 18:51:54,537 - mmdet - INFO - Epoch [4][150/7330] lr: 1.000e-04, eta: 7:02:13, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0441, loss_cls: 0.1864, acc: 93.1433, loss_bbox: 0.2366, loss_mask: 0.2371, loss: 0.7266 2023-11-13 18:52:14,145 - mmdet - INFO - Epoch [4][200/7330] lr: 1.000e-04, eta: 7:01:54, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0428, loss_cls: 0.1722, acc: 93.6069, loss_bbox: 0.2246, loss_mask: 0.2301, loss: 0.6916 2023-11-13 18:52:33,485 - mmdet - INFO - Epoch [4][250/7330] lr: 1.000e-04, eta: 7:01:36, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0413, loss_cls: 0.1850, acc: 93.2126, loss_bbox: 0.2289, loss_mask: 0.2335, loss: 0.7117 2023-11-13 18:52:52,844 - mmdet - INFO - Epoch [4][300/7330] lr: 1.000e-04, eta: 7:01:17, time: 0.387, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0437, loss_cls: 0.1812, acc: 93.3154, loss_bbox: 0.2274, loss_mask: 0.2307, loss: 0.7074 2023-11-13 18:53:12,073 - mmdet - INFO - Epoch [4][350/7330] lr: 1.000e-04, eta: 7:00:57, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0398, loss_cls: 0.1772, acc: 93.4351, loss_bbox: 0.2259, loss_mask: 0.2288, loss: 0.6930 2023-11-13 18:53:31,438 - mmdet - INFO - Epoch [4][400/7330] lr: 1.000e-04, eta: 7:00:38, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0412, loss_cls: 0.1813, acc: 93.3962, loss_bbox: 0.2239, loss_mask: 0.2256, loss: 0.6939 2023-11-13 18:53:50,527 - mmdet - INFO - Epoch [4][450/7330] lr: 1.000e-04, eta: 7:00:19, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0409, loss_cls: 0.1770, acc: 93.5835, loss_bbox: 0.2212, loss_mask: 0.2252, loss: 0.6866 2023-11-13 18:54:10,245 - mmdet - INFO - Epoch [4][500/7330] lr: 1.000e-04, eta: 7:00:01, time: 0.394, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0457, loss_cls: 0.1948, acc: 93.0081, loss_bbox: 0.2404, loss_mask: 0.2342, loss: 0.7411 2023-11-13 18:54:29,933 - mmdet - INFO - Epoch [4][550/7330] lr: 1.000e-04, eta: 6:59:43, time: 0.394, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0454, loss_cls: 0.1930, acc: 92.8850, loss_bbox: 0.2428, loss_mask: 0.2340, loss: 0.7404 2023-11-13 18:54:49,262 - mmdet - INFO - Epoch [4][600/7330] lr: 1.000e-04, eta: 6:59:24, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0435, loss_cls: 0.1876, acc: 93.1167, loss_bbox: 0.2313, loss_mask: 0.2382, loss: 0.7243 2023-11-13 18:55:08,635 - mmdet - INFO - Epoch [4][650/7330] lr: 1.000e-04, eta: 6:59:05, time: 0.387, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0458, loss_cls: 0.1956, acc: 92.8601, loss_bbox: 0.2409, loss_mask: 0.2379, loss: 0.7443 2023-11-13 18:55:27,912 - mmdet - INFO - Epoch [4][700/7330] lr: 1.000e-04, eta: 6:58:46, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0446, loss_cls: 0.1886, acc: 93.0454, loss_bbox: 0.2388, loss_mask: 0.2396, loss: 0.7354 2023-11-13 18:55:47,435 - mmdet - INFO - Epoch [4][750/7330] lr: 1.000e-04, eta: 6:58:27, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0440, loss_cls: 0.1861, acc: 93.1389, loss_bbox: 0.2317, loss_mask: 0.2307, loss: 0.7182 2023-11-13 18:56:06,861 - mmdet - INFO - Epoch [4][800/7330] lr: 1.000e-04, eta: 6:58:09, time: 0.389, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0446, loss_cls: 0.1843, acc: 93.2244, loss_bbox: 0.2316, loss_mask: 0.2347, loss: 0.7189 2023-11-13 18:56:25,897 - mmdet - INFO - Epoch [4][850/7330] lr: 1.000e-04, eta: 6:57:49, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0400, loss_cls: 0.1854, acc: 93.3345, loss_bbox: 0.2294, loss_mask: 0.2313, loss: 0.7092 2023-11-13 18:56:44,951 - mmdet - INFO - Epoch [4][900/7330] lr: 1.000e-04, eta: 6:57:29, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0433, loss_cls: 0.1834, acc: 93.4255, loss_bbox: 0.2299, loss_mask: 0.2346, loss: 0.7154 2023-11-13 18:57:04,177 - mmdet - INFO - Epoch [4][950/7330] lr: 1.000e-04, eta: 6:57:10, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0422, loss_cls: 0.1832, acc: 93.2695, loss_bbox: 0.2270, loss_mask: 0.2322, loss: 0.7085 2023-11-13 18:57:22,838 - mmdet - INFO - Epoch [4][1000/7330] lr: 1.000e-04, eta: 6:56:49, time: 0.373, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0435, loss_cls: 0.1845, acc: 93.2290, loss_bbox: 0.2328, loss_mask: 0.2345, loss: 0.7191 2023-11-13 18:57:42,334 - mmdet - INFO - Epoch [4][1050/7330] lr: 1.000e-04, eta: 6:56:30, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0454, loss_cls: 0.1924, acc: 92.8438, loss_bbox: 0.2454, loss_mask: 0.2420, loss: 0.7476 2023-11-13 18:58:01,609 - mmdet - INFO - Epoch [4][1100/7330] lr: 1.000e-04, eta: 6:56:11, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0414, loss_cls: 0.1896, acc: 93.0466, loss_bbox: 0.2320, loss_mask: 0.2330, loss: 0.7176 2023-11-13 18:58:21,065 - mmdet - INFO - Epoch [4][1150/7330] lr: 1.000e-04, eta: 6:55:52, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0443, loss_cls: 0.1864, acc: 93.1807, loss_bbox: 0.2331, loss_mask: 0.2277, loss: 0.7143 2023-11-13 18:58:40,359 - mmdet - INFO - Epoch [4][1200/7330] lr: 1.000e-04, eta: 6:55:33, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0442, loss_cls: 0.1878, acc: 93.1462, loss_bbox: 0.2313, loss_mask: 0.2341, loss: 0.7204 2023-11-13 18:58:59,664 - mmdet - INFO - Epoch [4][1250/7330] lr: 1.000e-04, eta: 6:55:14, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0429, loss_cls: 0.1915, acc: 93.0615, loss_bbox: 0.2327, loss_mask: 0.2322, loss: 0.7234 2023-11-13 18:59:18,935 - mmdet - INFO - Epoch [4][1300/7330] lr: 1.000e-04, eta: 6:54:55, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0468, loss_cls: 0.1989, acc: 92.7803, loss_bbox: 0.2465, loss_mask: 0.2380, loss: 0.7544 2023-11-13 18:59:37,959 - mmdet - INFO - Epoch [4][1350/7330] lr: 1.000e-04, eta: 6:54:35, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0443, loss_cls: 0.1876, acc: 93.1731, loss_bbox: 0.2326, loss_mask: 0.2384, loss: 0.7275 2023-11-13 18:59:57,042 - mmdet - INFO - Epoch [4][1400/7330] lr: 1.000e-04, eta: 6:54:15, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0436, loss_cls: 0.1861, acc: 93.1597, loss_bbox: 0.2292, loss_mask: 0.2308, loss: 0.7136 2023-11-13 19:00:16,124 - mmdet - INFO - Epoch [4][1450/7330] lr: 1.000e-04, eta: 6:53:56, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0416, loss_cls: 0.1832, acc: 93.2864, loss_bbox: 0.2244, loss_mask: 0.2284, loss: 0.7000 2023-11-13 19:00:35,343 - mmdet - INFO - Epoch [4][1500/7330] lr: 1.000e-04, eta: 6:53:36, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0440, loss_cls: 0.1869, acc: 93.1223, loss_bbox: 0.2366, loss_mask: 0.2384, loss: 0.7291 2023-11-13 19:00:54,485 - mmdet - INFO - Epoch [4][1550/7330] lr: 1.000e-04, eta: 6:53:17, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0435, loss_cls: 0.1892, acc: 93.1746, loss_bbox: 0.2316, loss_mask: 0.2310, loss: 0.7203 2023-11-13 19:01:13,741 - mmdet - INFO - Epoch [4][1600/7330] lr: 1.000e-04, eta: 6:52:58, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0398, loss_cls: 0.1791, acc: 93.4580, loss_bbox: 0.2221, loss_mask: 0.2284, loss: 0.6917 2023-11-13 19:01:32,906 - mmdet - INFO - Epoch [4][1650/7330] lr: 1.000e-04, eta: 6:52:38, time: 0.383, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0433, loss_cls: 0.1879, acc: 93.1250, loss_bbox: 0.2368, loss_mask: 0.2359, loss: 0.7279 2023-11-13 19:01:52,221 - mmdet - INFO - Epoch [4][1700/7330] lr: 1.000e-04, eta: 6:52:19, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0422, loss_cls: 0.1879, acc: 93.1582, loss_bbox: 0.2321, loss_mask: 0.2345, loss: 0.7215 2023-11-13 19:02:11,380 - mmdet - INFO - Epoch [4][1750/7330] lr: 1.000e-04, eta: 6:52:00, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0429, loss_cls: 0.1862, acc: 93.2437, loss_bbox: 0.2322, loss_mask: 0.2363, loss: 0.7210 2023-11-13 19:02:30,540 - mmdet - INFO - Epoch [4][1800/7330] lr: 1.000e-04, eta: 6:51:40, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0436, loss_cls: 0.1890, acc: 93.1831, loss_bbox: 0.2299, loss_mask: 0.2310, loss: 0.7172 2023-11-13 19:02:49,834 - mmdet - INFO - Epoch [4][1850/7330] lr: 1.000e-04, eta: 6:51:21, time: 0.386, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0435, loss_cls: 0.1897, acc: 93.1030, loss_bbox: 0.2359, loss_mask: 0.2334, loss: 0.7259 2023-11-13 19:03:09,010 - mmdet - INFO - Epoch [4][1900/7330] lr: 1.000e-04, eta: 6:51:02, time: 0.384, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0444, loss_cls: 0.1915, acc: 92.9780, loss_bbox: 0.2391, loss_mask: 0.2319, loss: 0.7330 2023-11-13 19:03:28,407 - mmdet - INFO - Epoch [4][1950/7330] lr: 1.000e-04, eta: 6:50:43, time: 0.388, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0440, loss_cls: 0.1842, acc: 93.2896, loss_bbox: 0.2287, loss_mask: 0.2233, loss: 0.7047 2023-11-13 19:03:47,212 - mmdet - INFO - Epoch [4][2000/7330] lr: 1.000e-04, eta: 6:50:22, time: 0.376, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0408, loss_cls: 0.1756, acc: 93.6582, loss_bbox: 0.2196, loss_mask: 0.2319, loss: 0.6912 2023-11-13 19:04:06,392 - mmdet - INFO - Epoch [4][2050/7330] lr: 1.000e-04, eta: 6:50:03, time: 0.384, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0435, loss_cls: 0.1890, acc: 93.1128, loss_bbox: 0.2352, loss_mask: 0.2330, loss: 0.7262 2023-11-13 19:04:25,637 - mmdet - INFO - Epoch [4][2100/7330] lr: 1.000e-04, eta: 6:49:44, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0451, loss_cls: 0.1931, acc: 93.0059, loss_bbox: 0.2399, loss_mask: 0.2350, loss: 0.7392 2023-11-13 19:04:44,574 - mmdet - INFO - Epoch [4][2150/7330] lr: 1.000e-04, eta: 6:49:24, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0407, loss_cls: 0.1811, acc: 93.3311, loss_bbox: 0.2293, loss_mask: 0.2308, loss: 0.7034 2023-11-13 19:05:04,319 - mmdet - INFO - Epoch [4][2200/7330] lr: 1.000e-04, eta: 6:49:06, time: 0.395, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0439, loss_cls: 0.1962, acc: 92.8618, loss_bbox: 0.2443, loss_mask: 0.2361, loss: 0.7457 2023-11-13 19:05:23,975 - mmdet - INFO - Epoch [4][2250/7330] lr: 1.000e-04, eta: 6:48:47, time: 0.393, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0436, loss_cls: 0.1952, acc: 92.8350, loss_bbox: 0.2377, loss_mask: 0.2349, loss: 0.7362 2023-11-13 19:05:43,136 - mmdet - INFO - Epoch [4][2300/7330] lr: 1.000e-04, eta: 6:48:28, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0430, loss_cls: 0.1835, acc: 93.3511, loss_bbox: 0.2271, loss_mask: 0.2346, loss: 0.7115 2023-11-13 19:06:02,177 - mmdet - INFO - Epoch [4][2350/7330] lr: 1.000e-04, eta: 6:48:08, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0434, loss_cls: 0.1936, acc: 92.8499, loss_bbox: 0.2360, loss_mask: 0.2341, loss: 0.7320 2023-11-13 19:06:21,296 - mmdet - INFO - Epoch [4][2400/7330] lr: 1.000e-04, eta: 6:47:49, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0437, loss_cls: 0.1871, acc: 93.1226, loss_bbox: 0.2338, loss_mask: 0.2346, loss: 0.7233 2023-11-13 19:06:40,447 - mmdet - INFO - Epoch [4][2450/7330] lr: 1.000e-04, eta: 6:47:29, time: 0.383, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0447, loss_cls: 0.1974, acc: 92.7744, loss_bbox: 0.2427, loss_mask: 0.2376, loss: 0.7477 2023-11-13 19:06:59,564 - mmdet - INFO - Epoch [4][2500/7330] lr: 1.000e-04, eta: 6:47:10, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0427, loss_cls: 0.1918, acc: 93.0505, loss_bbox: 0.2360, loss_mask: 0.2341, loss: 0.7296 2023-11-13 19:07:18,560 - mmdet - INFO - Epoch [4][2550/7330] lr: 1.000e-04, eta: 6:46:50, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0428, loss_cls: 0.1878, acc: 93.0898, loss_bbox: 0.2378, loss_mask: 0.2352, loss: 0.7265 2023-11-13 19:07:37,913 - mmdet - INFO - Epoch [4][2600/7330] lr: 1.000e-04, eta: 6:46:31, time: 0.387, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0458, loss_cls: 0.1905, acc: 93.1509, loss_bbox: 0.2355, loss_mask: 0.2355, loss: 0.7319 2023-11-13 19:07:56,921 - mmdet - INFO - Epoch [4][2650/7330] lr: 1.000e-04, eta: 6:46:11, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0420, loss_cls: 0.1818, acc: 93.4707, loss_bbox: 0.2219, loss_mask: 0.2327, loss: 0.7033 2023-11-13 19:08:16,196 - mmdet - INFO - Epoch [4][2700/7330] lr: 1.000e-04, eta: 6:45:52, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0434, loss_cls: 0.1845, acc: 93.1348, loss_bbox: 0.2308, loss_mask: 0.2352, loss: 0.7173 2023-11-13 19:08:35,229 - mmdet - INFO - Epoch [4][2750/7330] lr: 1.000e-04, eta: 6:45:32, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0452, loss_cls: 0.1972, acc: 92.8877, loss_bbox: 0.2399, loss_mask: 0.2341, loss: 0.7412 2023-11-13 19:08:54,717 - mmdet - INFO - Epoch [4][2800/7330] lr: 1.000e-04, eta: 6:45:13, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0460, loss_cls: 0.1904, acc: 92.8572, loss_bbox: 0.2412, loss_mask: 0.2369, loss: 0.7395 2023-11-13 19:09:13,655 - mmdet - INFO - Epoch [4][2850/7330] lr: 1.000e-04, eta: 6:44:53, time: 0.379, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0425, loss_cls: 0.1843, acc: 93.2275, loss_bbox: 0.2314, loss_mask: 0.2362, loss: 0.7170 2023-11-13 19:09:32,754 - mmdet - INFO - Epoch [4][2900/7330] lr: 1.000e-04, eta: 6:44:34, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0449, loss_cls: 0.1829, acc: 93.3235, loss_bbox: 0.2300, loss_mask: 0.2319, loss: 0.7162 2023-11-13 19:09:52,104 - mmdet - INFO - Epoch [4][2950/7330] lr: 1.000e-04, eta: 6:44:15, time: 0.387, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0423, loss_cls: 0.1821, acc: 93.3604, loss_bbox: 0.2295, loss_mask: 0.2282, loss: 0.7054 2023-11-13 19:10:11,197 - mmdet - INFO - Epoch [4][3000/7330] lr: 1.000e-04, eta: 6:43:55, time: 0.382, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0400, loss_cls: 0.1881, acc: 93.1743, loss_bbox: 0.2301, loss_mask: 0.2295, loss: 0.7093 2023-11-13 19:10:29,805 - mmdet - INFO - Epoch [4][3050/7330] lr: 1.000e-04, eta: 6:43:34, time: 0.372, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0421, loss_cls: 0.1811, acc: 93.3762, loss_bbox: 0.2265, loss_mask: 0.2315, loss: 0.7039 2023-11-13 19:10:49,190 - mmdet - INFO - Epoch [4][3100/7330] lr: 1.000e-04, eta: 6:43:15, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0450, loss_cls: 0.1889, acc: 93.1633, loss_bbox: 0.2375, loss_mask: 0.2372, loss: 0.7361 2023-11-13 19:11:08,187 - mmdet - INFO - Epoch [4][3150/7330] lr: 1.000e-04, eta: 6:42:55, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0414, loss_cls: 0.1910, acc: 93.0242, loss_bbox: 0.2321, loss_mask: 0.2326, loss: 0.7209 2023-11-13 19:11:27,578 - mmdet - INFO - Epoch [4][3200/7330] lr: 1.000e-04, eta: 6:42:37, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0426, loss_cls: 0.1842, acc: 93.3000, loss_bbox: 0.2244, loss_mask: 0.2279, loss: 0.7042 2023-11-13 19:11:46,592 - mmdet - INFO - Epoch [4][3250/7330] lr: 1.000e-04, eta: 6:42:17, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0439, loss_cls: 0.1899, acc: 93.1143, loss_bbox: 0.2355, loss_mask: 0.2365, loss: 0.7296 2023-11-13 19:12:05,980 - mmdet - INFO - Epoch [4][3300/7330] lr: 1.000e-04, eta: 6:41:58, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0451, loss_cls: 0.1949, acc: 92.8577, loss_bbox: 0.2375, loss_mask: 0.2385, loss: 0.7404 2023-11-13 19:12:24,940 - mmdet - INFO - Epoch [4][3350/7330] lr: 1.000e-04, eta: 6:41:38, time: 0.379, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0442, loss_cls: 0.1843, acc: 93.2681, loss_bbox: 0.2323, loss_mask: 0.2330, loss: 0.7161 2023-11-13 19:12:43,874 - mmdet - INFO - Epoch [4][3400/7330] lr: 1.000e-04, eta: 6:41:18, time: 0.379, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0425, loss_cls: 0.1827, acc: 93.3354, loss_bbox: 0.2229, loss_mask: 0.2280, loss: 0.7002 2023-11-13 19:13:02,941 - mmdet - INFO - Epoch [4][3450/7330] lr: 1.000e-04, eta: 6:40:58, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0398, loss_cls: 0.1808, acc: 93.3965, loss_bbox: 0.2265, loss_mask: 0.2272, loss: 0.6960 2023-11-13 19:13:22,118 - mmdet - INFO - Epoch [4][3500/7330] lr: 1.000e-04, eta: 6:40:39, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0420, loss_cls: 0.1809, acc: 93.3386, loss_bbox: 0.2285, loss_mask: 0.2291, loss: 0.7018 2023-11-13 19:13:41,358 - mmdet - INFO - Epoch [4][3550/7330] lr: 1.000e-04, eta: 6:40:20, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0418, loss_cls: 0.1900, acc: 93.0557, loss_bbox: 0.2299, loss_mask: 0.2278, loss: 0.7130 2023-11-13 19:14:00,703 - mmdet - INFO - Epoch [4][3600/7330] lr: 1.000e-04, eta: 6:40:01, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0431, loss_cls: 0.1874, acc: 93.1821, loss_bbox: 0.2316, loss_mask: 0.2282, loss: 0.7140 2023-11-13 19:14:20,126 - mmdet - INFO - Epoch [4][3650/7330] lr: 1.000e-04, eta: 6:39:42, time: 0.388, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0423, loss_cls: 0.1896, acc: 93.1155, loss_bbox: 0.2363, loss_mask: 0.2322, loss: 0.7229 2023-11-13 19:14:39,369 - mmdet - INFO - Epoch [4][3700/7330] lr: 1.000e-04, eta: 6:39:23, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0455, loss_cls: 0.1866, acc: 93.1003, loss_bbox: 0.2346, loss_mask: 0.2349, loss: 0.7261 2023-11-13 19:14:58,558 - mmdet - INFO - Epoch [4][3750/7330] lr: 1.000e-04, eta: 6:39:03, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0418, loss_cls: 0.1756, acc: 93.5703, loss_bbox: 0.2176, loss_mask: 0.2282, loss: 0.6849 2023-11-13 19:15:18,027 - mmdet - INFO - Epoch [4][3800/7330] lr: 1.000e-04, eta: 6:38:45, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0457, loss_cls: 0.1906, acc: 92.9849, loss_bbox: 0.2365, loss_mask: 0.2318, loss: 0.7294 2023-11-13 19:15:37,438 - mmdet - INFO - Epoch [4][3850/7330] lr: 1.000e-04, eta: 6:38:26, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0447, loss_cls: 0.1952, acc: 92.8074, loss_bbox: 0.2390, loss_mask: 0.2331, loss: 0.7367 2023-11-13 19:15:56,391 - mmdet - INFO - Epoch [4][3900/7330] lr: 1.000e-04, eta: 6:38:06, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0414, loss_cls: 0.1874, acc: 93.2148, loss_bbox: 0.2328, loss_mask: 0.2347, loss: 0.7195 2023-11-13 19:16:15,462 - mmdet - INFO - Epoch [4][3950/7330] lr: 1.000e-04, eta: 6:37:46, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0427, loss_cls: 0.1767, acc: 93.6035, loss_bbox: 0.2173, loss_mask: 0.2339, loss: 0.6945 2023-11-13 19:16:34,437 - mmdet - INFO - Epoch [4][4000/7330] lr: 1.000e-04, eta: 6:37:26, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0445, loss_cls: 0.1930, acc: 92.9297, loss_bbox: 0.2424, loss_mask: 0.2355, loss: 0.7396 2023-11-13 19:16:53,926 - mmdet - INFO - Epoch [4][4050/7330] lr: 1.000e-04, eta: 6:37:08, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0448, loss_cls: 0.1941, acc: 92.8064, loss_bbox: 0.2414, loss_mask: 0.2394, loss: 0.7453 2023-11-13 19:17:13,263 - mmdet - INFO - Epoch [4][4100/7330] lr: 1.000e-04, eta: 6:36:49, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0461, loss_cls: 0.1943, acc: 92.9761, loss_bbox: 0.2362, loss_mask: 0.2351, loss: 0.7374 2023-11-13 19:17:32,225 - mmdet - INFO - Epoch [4][4150/7330] lr: 1.000e-04, eta: 6:36:29, time: 0.379, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0439, loss_cls: 0.1939, acc: 92.9678, loss_bbox: 0.2379, loss_mask: 0.2341, loss: 0.7353 2023-11-13 19:17:51,361 - mmdet - INFO - Epoch [4][4200/7330] lr: 1.000e-04, eta: 6:36:09, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0422, loss_cls: 0.1874, acc: 93.2041, loss_bbox: 0.2298, loss_mask: 0.2303, loss: 0.7155 2023-11-13 19:18:10,946 - mmdet - INFO - Epoch [4][4250/7330] lr: 1.000e-04, eta: 6:35:51, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0432, loss_cls: 0.1907, acc: 93.0552, loss_bbox: 0.2365, loss_mask: 0.2326, loss: 0.7270 2023-11-13 19:18:29,823 - mmdet - INFO - Epoch [4][4300/7330] lr: 1.000e-04, eta: 6:35:31, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0425, loss_cls: 0.1837, acc: 93.3057, loss_bbox: 0.2272, loss_mask: 0.2289, loss: 0.7059 2023-11-13 19:18:48,901 - mmdet - INFO - Epoch [4][4350/7330] lr: 1.000e-04, eta: 6:35:11, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0429, loss_cls: 0.1869, acc: 93.0940, loss_bbox: 0.2325, loss_mask: 0.2346, loss: 0.7203 2023-11-13 19:19:08,024 - mmdet - INFO - Epoch [4][4400/7330] lr: 1.000e-04, eta: 6:34:51, time: 0.382, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0435, loss_cls: 0.1966, acc: 92.8611, loss_bbox: 0.2457, loss_mask: 0.2362, loss: 0.7470 2023-11-13 19:19:27,249 - mmdet - INFO - Epoch [4][4450/7330] lr: 1.000e-04, eta: 6:34:32, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0461, loss_cls: 0.1926, acc: 92.8625, loss_bbox: 0.2392, loss_mask: 0.2371, loss: 0.7388 2023-11-13 19:19:46,531 - mmdet - INFO - Epoch [4][4500/7330] lr: 1.000e-04, eta: 6:34:13, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0435, loss_cls: 0.1943, acc: 93.0244, loss_bbox: 0.2366, loss_mask: 0.2362, loss: 0.7370 2023-11-13 19:20:05,834 - mmdet - INFO - Epoch [4][4550/7330] lr: 1.000e-04, eta: 6:33:54, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0434, loss_cls: 0.1933, acc: 92.9470, loss_bbox: 0.2363, loss_mask: 0.2315, loss: 0.7287 2023-11-13 19:20:24,611 - mmdet - INFO - Epoch [4][4600/7330] lr: 1.000e-04, eta: 6:33:34, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0431, loss_cls: 0.1919, acc: 93.0840, loss_bbox: 0.2292, loss_mask: 0.2296, loss: 0.7183 2023-11-13 19:20:43,509 - mmdet - INFO - Epoch [4][4650/7330] lr: 1.000e-04, eta: 6:33:14, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0415, loss_cls: 0.1851, acc: 93.2881, loss_bbox: 0.2290, loss_mask: 0.2279, loss: 0.7062 2023-11-13 19:21:02,624 - mmdet - INFO - Epoch [4][4700/7330] lr: 1.000e-04, eta: 6:32:54, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0416, loss_cls: 0.1864, acc: 93.2537, loss_bbox: 0.2308, loss_mask: 0.2349, loss: 0.7166 2023-11-13 19:21:21,895 - mmdet - INFO - Epoch [4][4750/7330] lr: 1.000e-04, eta: 6:32:35, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0426, loss_cls: 0.1889, acc: 93.0200, loss_bbox: 0.2348, loss_mask: 0.2301, loss: 0.7182 2023-11-13 19:21:40,538 - mmdet - INFO - Epoch [4][4800/7330] lr: 1.000e-04, eta: 6:32:14, time: 0.373, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0396, loss_cls: 0.1784, acc: 93.5554, loss_bbox: 0.2219, loss_mask: 0.2286, loss: 0.6900 2023-11-13 19:21:59,609 - mmdet - INFO - Epoch [4][4850/7330] lr: 1.000e-04, eta: 6:31:55, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0445, loss_cls: 0.1912, acc: 93.1284, loss_bbox: 0.2312, loss_mask: 0.2313, loss: 0.7239 2023-11-13 19:22:18,592 - mmdet - INFO - Epoch [4][4900/7330] lr: 1.000e-04, eta: 6:31:35, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0428, loss_cls: 0.1882, acc: 93.2229, loss_bbox: 0.2316, loss_mask: 0.2331, loss: 0.7205 2023-11-13 19:22:37,653 - mmdet - INFO - Epoch [4][4950/7330] lr: 1.000e-04, eta: 6:31:15, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0452, loss_cls: 0.1884, acc: 93.1431, loss_bbox: 0.2316, loss_mask: 0.2308, loss: 0.7209 2023-11-13 19:22:56,709 - mmdet - INFO - Epoch [4][5000/7330] lr: 1.000e-04, eta: 6:30:56, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0418, loss_cls: 0.1855, acc: 93.2947, loss_bbox: 0.2272, loss_mask: 0.2276, loss: 0.7059 2023-11-13 19:23:15,905 - mmdet - INFO - Epoch [4][5050/7330] lr: 1.000e-04, eta: 6:30:36, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0437, loss_cls: 0.1978, acc: 92.7454, loss_bbox: 0.2380, loss_mask: 0.2347, loss: 0.7386 2023-11-13 19:23:35,070 - mmdet - INFO - Epoch [4][5100/7330] lr: 1.000e-04, eta: 6:30:17, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0457, loss_cls: 0.1943, acc: 92.8914, loss_bbox: 0.2375, loss_mask: 0.2258, loss: 0.7272 2023-11-13 19:23:53,961 - mmdet - INFO - Epoch [4][5150/7330] lr: 1.000e-04, eta: 6:29:57, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0404, loss_cls: 0.1812, acc: 93.3213, loss_bbox: 0.2265, loss_mask: 0.2343, loss: 0.7064 2023-11-13 19:24:12,787 - mmdet - INFO - Epoch [4][5200/7330] lr: 1.000e-04, eta: 6:29:37, time: 0.376, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0416, loss_cls: 0.1826, acc: 93.2478, loss_bbox: 0.2251, loss_mask: 0.2332, loss: 0.7056 2023-11-13 19:24:31,808 - mmdet - INFO - Epoch [4][5250/7330] lr: 1.000e-04, eta: 6:29:17, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0411, loss_cls: 0.1903, acc: 93.1121, loss_bbox: 0.2294, loss_mask: 0.2315, loss: 0.7163 2023-11-13 19:24:50,943 - mmdet - INFO - Epoch [4][5300/7330] lr: 1.000e-04, eta: 6:28:58, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0411, loss_cls: 0.1852, acc: 93.1985, loss_bbox: 0.2337, loss_mask: 0.2348, loss: 0.7166 2023-11-13 19:25:09,922 - mmdet - INFO - Epoch [4][5350/7330] lr: 1.000e-04, eta: 6:28:38, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0437, loss_cls: 0.1873, acc: 93.1750, loss_bbox: 0.2333, loss_mask: 0.2336, loss: 0.7226 2023-11-13 19:25:29,128 - mmdet - INFO - Epoch [4][5400/7330] lr: 1.000e-04, eta: 6:28:19, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0456, loss_cls: 0.1922, acc: 92.9714, loss_bbox: 0.2375, loss_mask: 0.2327, loss: 0.7345 2023-11-13 19:25:48,070 - mmdet - INFO - Epoch [4][5450/7330] lr: 1.000e-04, eta: 6:27:59, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0425, loss_cls: 0.1809, acc: 93.3833, loss_bbox: 0.2249, loss_mask: 0.2334, loss: 0.7062 2023-11-13 19:26:06,862 - mmdet - INFO - Epoch [4][5500/7330] lr: 1.000e-04, eta: 6:27:38, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0423, loss_cls: 0.1850, acc: 93.1396, loss_bbox: 0.2294, loss_mask: 0.2286, loss: 0.7074 2023-11-13 19:26:26,406 - mmdet - INFO - Epoch [4][5550/7330] lr: 1.000e-04, eta: 6:27:20, time: 0.391, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0423, loss_cls: 0.1950, acc: 92.9309, loss_bbox: 0.2397, loss_mask: 0.2365, loss: 0.7355 2023-11-13 19:26:45,591 - mmdet - INFO - Epoch [4][5600/7330] lr: 1.000e-04, eta: 6:27:01, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0446, loss_cls: 0.1853, acc: 93.2251, loss_bbox: 0.2287, loss_mask: 0.2307, loss: 0.7145 2023-11-13 19:27:04,386 - mmdet - INFO - Epoch [4][5650/7330] lr: 1.000e-04, eta: 6:26:40, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0432, loss_cls: 0.1863, acc: 93.1855, loss_bbox: 0.2271, loss_mask: 0.2342, loss: 0.7155 2023-11-13 19:27:23,656 - mmdet - INFO - Epoch [4][5700/7330] lr: 1.000e-04, eta: 6:26:21, time: 0.385, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0436, loss_cls: 0.1965, acc: 92.8933, loss_bbox: 0.2371, loss_mask: 0.2347, loss: 0.7367 2023-11-13 19:27:42,636 - mmdet - INFO - Epoch [4][5750/7330] lr: 1.000e-04, eta: 6:26:01, time: 0.380, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0442, loss_cls: 0.1958, acc: 92.9412, loss_bbox: 0.2377, loss_mask: 0.2295, loss: 0.7312 2023-11-13 19:28:01,574 - mmdet - INFO - Epoch [4][5800/7330] lr: 1.000e-04, eta: 6:25:42, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0392, loss_cls: 0.1810, acc: 93.4028, loss_bbox: 0.2207, loss_mask: 0.2293, loss: 0.6927 2023-11-13 19:28:20,585 - mmdet - INFO - Epoch [4][5850/7330] lr: 1.000e-04, eta: 6:25:22, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0427, loss_cls: 0.1936, acc: 92.9082, loss_bbox: 0.2419, loss_mask: 0.2317, loss: 0.7331 2023-11-13 19:28:39,727 - mmdet - INFO - Epoch [4][5900/7330] lr: 1.000e-04, eta: 6:25:02, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0446, loss_cls: 0.1903, acc: 93.1101, loss_bbox: 0.2348, loss_mask: 0.2332, loss: 0.7264 2023-11-13 19:28:58,966 - mmdet - INFO - Epoch [4][5950/7330] lr: 1.000e-04, eta: 6:24:43, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0427, loss_cls: 0.1907, acc: 93.0925, loss_bbox: 0.2331, loss_mask: 0.2346, loss: 0.7250 2023-11-13 19:29:18,243 - mmdet - INFO - Epoch [4][6000/7330] lr: 1.000e-04, eta: 6:24:24, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0441, loss_cls: 0.1997, acc: 92.7805, loss_bbox: 0.2411, loss_mask: 0.2365, loss: 0.7463 2023-11-13 19:29:37,062 - mmdet - INFO - Epoch [4][6050/7330] lr: 1.000e-04, eta: 6:24:04, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0429, loss_cls: 0.1898, acc: 93.0781, loss_bbox: 0.2350, loss_mask: 0.2359, loss: 0.7260 2023-11-13 19:29:55,827 - mmdet - INFO - Epoch [4][6100/7330] lr: 1.000e-04, eta: 6:23:44, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0417, loss_cls: 0.1837, acc: 93.3159, loss_bbox: 0.2279, loss_mask: 0.2312, loss: 0.7076 2023-11-13 19:30:14,871 - mmdet - INFO - Epoch [4][6150/7330] lr: 1.000e-04, eta: 6:23:24, time: 0.381, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0432, loss_cls: 0.1895, acc: 93.0308, loss_bbox: 0.2357, loss_mask: 0.2379, loss: 0.7304 2023-11-13 19:30:33,448 - mmdet - INFO - Epoch [4][6200/7330] lr: 1.000e-04, eta: 6:23:04, time: 0.372, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0413, loss_cls: 0.1881, acc: 93.2249, loss_bbox: 0.2324, loss_mask: 0.2382, loss: 0.7229 2023-11-13 19:30:52,284 - mmdet - INFO - Epoch [4][6250/7330] lr: 1.000e-04, eta: 6:22:43, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0409, loss_cls: 0.1851, acc: 93.2981, loss_bbox: 0.2294, loss_mask: 0.2337, loss: 0.7114 2023-11-13 19:31:11,330 - mmdet - INFO - Epoch [4][6300/7330] lr: 1.000e-04, eta: 6:22:24, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0441, loss_cls: 0.1906, acc: 93.0698, loss_bbox: 0.2406, loss_mask: 0.2371, loss: 0.7380 2023-11-13 19:31:30,461 - mmdet - INFO - Epoch [4][6350/7330] lr: 1.000e-04, eta: 6:22:04, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0388, loss_cls: 0.1809, acc: 93.4968, loss_bbox: 0.2212, loss_mask: 0.2259, loss: 0.6885 2023-11-13 19:31:49,527 - mmdet - INFO - Epoch [4][6400/7330] lr: 1.000e-04, eta: 6:21:45, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0430, loss_cls: 0.1942, acc: 92.9126, loss_bbox: 0.2354, loss_mask: 0.2355, loss: 0.7328 2023-11-13 19:32:08,720 - mmdet - INFO - Epoch [4][6450/7330] lr: 1.000e-04, eta: 6:21:26, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0400, loss_cls: 0.1781, acc: 93.4895, loss_bbox: 0.2236, loss_mask: 0.2279, loss: 0.6915 2023-11-13 19:32:27,677 - mmdet - INFO - Epoch [4][6500/7330] lr: 1.000e-04, eta: 6:21:06, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0427, loss_cls: 0.1830, acc: 93.3223, loss_bbox: 0.2297, loss_mask: 0.2300, loss: 0.7089 2023-11-13 19:32:46,715 - mmdet - INFO - Epoch [4][6550/7330] lr: 1.000e-04, eta: 6:20:46, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0434, loss_cls: 0.1887, acc: 93.0786, loss_bbox: 0.2332, loss_mask: 0.2310, loss: 0.7191 2023-11-13 19:33:06,075 - mmdet - INFO - Epoch [4][6600/7330] lr: 1.000e-04, eta: 6:20:27, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0412, loss_cls: 0.1823, acc: 93.3020, loss_bbox: 0.2263, loss_mask: 0.2310, loss: 0.7068 2023-11-13 19:33:25,239 - mmdet - INFO - Epoch [4][6650/7330] lr: 1.000e-04, eta: 6:20:08, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0404, loss_cls: 0.1850, acc: 93.1335, loss_bbox: 0.2314, loss_mask: 0.2307, loss: 0.7103 2023-11-13 19:33:44,638 - mmdet - INFO - Epoch [4][6700/7330] lr: 1.000e-04, eta: 6:19:49, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0435, loss_cls: 0.1871, acc: 93.2549, loss_bbox: 0.2266, loss_mask: 0.2415, loss: 0.7225 2023-11-13 19:34:03,723 - mmdet - INFO - Epoch [4][6750/7330] lr: 1.000e-04, eta: 6:19:30, time: 0.382, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0444, loss_cls: 0.1939, acc: 93.0359, loss_bbox: 0.2396, loss_mask: 0.2395, loss: 0.7433 2023-11-13 19:34:22,895 - mmdet - INFO - Epoch [4][6800/7330] lr: 1.000e-04, eta: 6:19:10, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0437, loss_cls: 0.1843, acc: 93.2710, loss_bbox: 0.2272, loss_mask: 0.2302, loss: 0.7090 2023-11-13 19:34:41,935 - mmdet - INFO - Epoch [4][6850/7330] lr: 1.000e-04, eta: 6:18:51, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0417, loss_cls: 0.1889, acc: 93.1194, loss_bbox: 0.2306, loss_mask: 0.2309, loss: 0.7150 2023-11-13 19:35:00,388 - mmdet - INFO - Epoch [4][6900/7330] lr: 1.000e-04, eta: 6:18:30, time: 0.369, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0403, loss_cls: 0.1839, acc: 93.4219, loss_bbox: 0.2243, loss_mask: 0.2323, loss: 0.7038 2023-11-13 19:35:20,068 - mmdet - INFO - Epoch [4][6950/7330] lr: 1.000e-04, eta: 6:18:11, time: 0.394, data_time: 0.035, memory: 4444, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0447, loss_cls: 0.1978, acc: 92.6455, loss_bbox: 0.2472, loss_mask: 0.2404, loss: 0.7551 2023-11-13 19:35:39,450 - mmdet - INFO - Epoch [4][7000/7330] lr: 1.000e-04, eta: 6:17:53, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0417, loss_cls: 0.1790, acc: 93.4851, loss_bbox: 0.2264, loss_mask: 0.2334, loss: 0.7052 2023-11-13 19:35:58,488 - mmdet - INFO - Epoch [4][7050/7330] lr: 1.000e-04, eta: 6:17:33, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0427, loss_cls: 0.1919, acc: 92.9492, loss_bbox: 0.2347, loss_mask: 0.2360, loss: 0.7282 2023-11-13 19:36:17,584 - mmdet - INFO - Epoch [4][7100/7330] lr: 1.000e-04, eta: 6:17:13, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0422, loss_cls: 0.1860, acc: 93.1777, loss_bbox: 0.2298, loss_mask: 0.2287, loss: 0.7115 2023-11-13 19:36:36,762 - mmdet - INFO - Epoch [4][7150/7330] lr: 1.000e-04, eta: 6:16:54, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0424, loss_cls: 0.1925, acc: 92.9414, loss_bbox: 0.2377, loss_mask: 0.2294, loss: 0.7250 2023-11-13 19:36:55,742 - mmdet - INFO - Epoch [4][7200/7330] lr: 1.000e-04, eta: 6:16:34, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0415, loss_cls: 0.1836, acc: 93.2263, loss_bbox: 0.2287, loss_mask: 0.2320, loss: 0.7087 2023-11-13 19:37:14,823 - mmdet - INFO - Epoch [4][7250/7330] lr: 1.000e-04, eta: 6:16:15, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0403, loss_cls: 0.1769, acc: 93.5649, loss_bbox: 0.2206, loss_mask: 0.2257, loss: 0.6849 2023-11-13 19:37:33,807 - mmdet - INFO - Epoch [4][7300/7330] lr: 1.000e-04, eta: 6:15:55, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0415, loss_cls: 0.1896, acc: 93.1104, loss_bbox: 0.2300, loss_mask: 0.2322, loss: 0.7167 2023-11-13 19:37:45,472 - mmdet - INFO - Saving checkpoint at 4 epochs 2023-11-13 19:38:36,777 - mmdet - INFO - Evaluating bbox... 2023-11-13 19:39:09,920 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.451 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.677 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.496 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 ] = 0.492 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 ] = 0.627 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.727 2023-11-13 19:39:09,923 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.559 | bicycle | 0.344 | car | 0.466 | | motorcycle | 0.451 | airplane | 0.681 | bus | 0.666 | | train | 0.663 | truck | 0.425 | boat | 0.324 | | traffic light | 0.296 | fire hydrant | 0.685 | stop sign | 0.662 | | parking meter | 0.485 | bench | 0.281 | bird | 0.390 | | cat | 0.709 | dog | 0.665 | horse | 0.613 | | sheep | 0.548 | cow | 0.609 | elephant | 0.663 | | bear | 0.741 | zebra | 0.664 | giraffe | 0.688 | | backpack | 0.196 | umbrella | 0.409 | handbag | 0.181 | | tie | 0.346 | suitcase | 0.428 | frisbee | 0.662 | | skis | 0.269 | snowboard | 0.416 | sports ball | 0.460 | | kite | 0.449 | baseball bat | 0.375 | baseball glove | 0.418 | | skateboard | 0.551 | surfboard | 0.416 | tennis racket | 0.528 | | bottle | 0.437 | wine glass | 0.394 | cup | 0.481 | | fork | 0.423 | knife | 0.243 | spoon | 0.267 | | bowl | 0.461 | banana | 0.288 | apple | 0.224 | | sandwich | 0.411 | orange | 0.346 | broccoli | 0.259 | | carrot | 0.228 | hot dog | 0.446 | pizza | 0.541 | | donut | 0.461 | cake | 0.415 | chair | 0.329 | | couch | 0.441 | potted plant | 0.329 | bed | 0.442 | | dining table | 0.289 | toilet | 0.615 | tv | 0.626 | | laptop | 0.644 | mouse | 0.630 | remote | 0.391 | | keyboard | 0.523 | cell phone | 0.385 | microwave | 0.635 | | oven | 0.359 | toaster | 0.342 | sink | 0.430 | | refrigerator | 0.576 | book | 0.176 | clock | 0.520 | | vase | 0.413 | scissors | 0.350 | teddy bear | 0.496 | | hair drier | 0.129 | toothbrush | 0.273 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:39:09,923 - mmdet - INFO - Evaluating segm... 2023-11-13 19:39:44,883 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.408 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 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.444 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.597 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 ] = 0.341 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.577 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.691 2023-11-13 19:39:44,885 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.489 | bicycle | 0.196 | car | 0.432 | | motorcycle | 0.381 | airplane | 0.536 | bus | 0.657 | | train | 0.651 | truck | 0.409 | boat | 0.277 | | traffic light | 0.283 | fire hydrant | 0.679 | stop sign | 0.669 | | parking meter | 0.507 | bench | 0.210 | bird | 0.330 | | cat | 0.717 | dog | 0.632 | horse | 0.452 | | sheep | 0.486 | cow | 0.514 | elephant | 0.604 | | bear | 0.746 | zebra | 0.578 | giraffe | 0.541 | | backpack | 0.199 | umbrella | 0.492 | handbag | 0.187 | | tie | 0.328 | suitcase | 0.456 | frisbee | 0.644 | | skis | 0.046 | snowboard | 0.245 | sports ball | 0.454 | | kite | 0.315 | baseball bat | 0.273 | baseball glove | 0.448 | | skateboard | 0.312 | surfboard | 0.329 | tennis racket | 0.576 | | bottle | 0.424 | wine glass | 0.329 | cup | 0.485 | | fork | 0.196 | knife | 0.163 | spoon | 0.162 | | bowl | 0.437 | banana | 0.250 | apple | 0.223 | | sandwich | 0.446 | orange | 0.350 | broccoli | 0.248 | | carrot | 0.217 | hot dog | 0.358 | pizza | 0.524 | | donut | 0.474 | cake | 0.437 | chair | 0.239 | | couch | 0.368 | potted plant | 0.270 | bed | 0.350 | | dining table | 0.162 | toilet | 0.604 | tv | 0.650 | | laptop | 0.645 | mouse | 0.617 | remote | 0.342 | | keyboard | 0.523 | cell phone | 0.363 | microwave | 0.642 | | oven | 0.347 | toaster | 0.366 | sink | 0.403 | | refrigerator | 0.601 | book | 0.137 | clock | 0.527 | | vase | 0.410 | scissors | 0.271 | teddy bear | 0.487 | | hair drier | 0.097 | toothbrush | 0.181 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:39:45,442 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_3.pth was removed 2023-11-13 19:39:47,615 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_4.pth. 2023-11-13 19:39:47,616 - mmdet - INFO - Best bbox_mAP is 0.4506 at 4 epoch. 2023-11-13 19:39:47,616 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 19:39:47,616 - mmdet - INFO - Epoch(val) [4][625] bbox_mAP: 0.4506, bbox_mAP_50: 0.6774, bbox_mAP_75: 0.4958, bbox_mAP_s: 0.2868, bbox_mAP_m: 0.4924, bbox_mAP_l: 0.5915, bbox_mAP_copypaste: 0.4506 0.6774 0.4958 0.2868 0.4924 0.5915, segm_mAP: 0.4076, segm_mAP_50: 0.6435, segm_mAP_75: 0.4383, segm_mAP_s: 0.2079, segm_mAP_m: 0.4435, segm_mAP_l: 0.5966, segm_mAP_copypaste: 0.4076 0.6435 0.4383 0.2079 0.4435 0.5966 2023-11-13 19:40:10,923 - mmdet - INFO - Epoch [5][50/7330] lr: 1.000e-04, eta: 6:15:10, time: 0.466, data_time: 0.088, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0421, loss_cls: 0.1795, acc: 93.3972, loss_bbox: 0.2229, loss_mask: 0.2291, loss: 0.6964 2023-11-13 19:40:30,665 - mmdet - INFO - Epoch [5][100/7330] lr: 1.000e-04, eta: 6:14:51, time: 0.395, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0401, loss_cls: 0.1698, acc: 93.7517, loss_bbox: 0.2188, loss_mask: 0.2292, loss: 0.6788 2023-11-13 19:40:50,718 - mmdet - INFO - Epoch [5][150/7330] lr: 1.000e-04, eta: 6:14:34, time: 0.401, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0431, loss_cls: 0.1813, acc: 93.4177, loss_bbox: 0.2257, loss_mask: 0.2259, loss: 0.6976 2023-11-13 19:41:10,530 - mmdet - INFO - Epoch [5][200/7330] lr: 1.000e-04, eta: 6:14:16, time: 0.396, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0428, loss_cls: 0.1822, acc: 93.1733, loss_bbox: 0.2327, loss_mask: 0.2325, loss: 0.7117 2023-11-13 19:41:30,114 - mmdet - INFO - Epoch [5][250/7330] lr: 1.000e-04, eta: 6:13:57, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0459, loss_cls: 0.1841, acc: 93.0896, loss_bbox: 0.2393, loss_mask: 0.2333, loss: 0.7266 2023-11-13 19:41:49,460 - mmdet - INFO - Epoch [5][300/7330] lr: 1.000e-04, eta: 6:13:38, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0414, loss_cls: 0.1779, acc: 93.3977, loss_bbox: 0.2244, loss_mask: 0.2261, loss: 0.6905 2023-11-13 19:42:08,856 - mmdet - INFO - Epoch [5][350/7330] lr: 1.000e-04, eta: 6:13:20, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0401, loss_cls: 0.1709, acc: 93.6809, loss_bbox: 0.2167, loss_mask: 0.2262, loss: 0.6736 2023-11-13 19:42:27,744 - mmdet - INFO - Epoch [5][400/7330] lr: 1.000e-04, eta: 6:13:00, time: 0.378, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0398, loss_cls: 0.1706, acc: 93.7397, loss_bbox: 0.2173, loss_mask: 0.2220, loss: 0.6681 2023-11-13 19:42:46,979 - mmdet - INFO - Epoch [5][450/7330] lr: 1.000e-04, eta: 6:12:41, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0400, loss_cls: 0.1691, acc: 93.6958, loss_bbox: 0.2148, loss_mask: 0.2260, loss: 0.6705 2023-11-13 19:43:06,141 - mmdet - INFO - Epoch [5][500/7330] lr: 1.000e-04, eta: 6:12:21, time: 0.383, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0397, loss_cls: 0.1726, acc: 93.6035, loss_bbox: 0.2199, loss_mask: 0.2217, loss: 0.6722 2023-11-13 19:43:25,422 - mmdet - INFO - Epoch [5][550/7330] lr: 1.000e-04, eta: 6:12:02, time: 0.386, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0408, loss_cls: 0.1748, acc: 93.6267, loss_bbox: 0.2151, loss_mask: 0.2232, loss: 0.6742 2023-11-13 19:43:44,940 - mmdet - INFO - Epoch [5][600/7330] lr: 1.000e-04, eta: 6:11:44, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0415, loss_cls: 0.1727, acc: 93.5718, loss_bbox: 0.2206, loss_mask: 0.2258, loss: 0.6808 2023-11-13 19:44:04,754 - mmdet - INFO - Epoch [5][650/7330] lr: 1.000e-04, eta: 6:11:25, time: 0.396, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0437, loss_cls: 0.1788, acc: 93.4346, loss_bbox: 0.2265, loss_mask: 0.2314, loss: 0.7040 2023-11-13 19:44:23,901 - mmdet - INFO - Epoch [5][700/7330] lr: 1.000e-04, eta: 6:11:06, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0408, loss_cls: 0.1692, acc: 93.6792, loss_bbox: 0.2152, loss_mask: 0.2261, loss: 0.6728 2023-11-13 19:44:43,136 - mmdet - INFO - Epoch [5][750/7330] lr: 1.000e-04, eta: 6:10:47, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0411, loss_cls: 0.1729, acc: 93.6462, loss_bbox: 0.2203, loss_mask: 0.2274, loss: 0.6830 2023-11-13 19:45:02,338 - mmdet - INFO - Epoch [5][800/7330] lr: 1.000e-04, eta: 6:10:28, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0403, loss_cls: 0.1803, acc: 93.3318, loss_bbox: 0.2291, loss_mask: 0.2317, loss: 0.7025 2023-11-13 19:45:21,230 - mmdet - INFO - Epoch [5][850/7330] lr: 1.000e-04, eta: 6:10:08, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0392, loss_cls: 0.1701, acc: 93.6440, loss_bbox: 0.2204, loss_mask: 0.2241, loss: 0.6744 2023-11-13 19:45:40,376 - mmdet - INFO - Epoch [5][900/7330] lr: 1.000e-04, eta: 6:09:49, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0396, loss_cls: 0.1742, acc: 93.5801, loss_bbox: 0.2198, loss_mask: 0.2241, loss: 0.6780 2023-11-13 19:45:59,803 - mmdet - INFO - Epoch [5][950/7330] lr: 1.000e-04, eta: 6:09:30, time: 0.389, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0438, loss_cls: 0.1836, acc: 93.2178, loss_bbox: 0.2294, loss_mask: 0.2303, loss: 0.7100 2023-11-13 19:46:19,513 - mmdet - INFO - Epoch [5][1000/7330] lr: 1.000e-04, eta: 6:09:11, time: 0.394, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0440, loss_cls: 0.1879, acc: 92.9590, loss_bbox: 0.2341, loss_mask: 0.2302, loss: 0.7188 2023-11-13 19:46:38,445 - mmdet - INFO - Epoch [5][1050/7330] lr: 1.000e-04, eta: 6:08:52, time: 0.379, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0396, loss_cls: 0.1804, acc: 93.3252, loss_bbox: 0.2322, loss_mask: 0.2285, loss: 0.7012 2023-11-13 19:46:57,693 - mmdet - INFO - Epoch [5][1100/7330] lr: 1.000e-04, eta: 6:08:33, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0385, loss_cls: 0.1701, acc: 93.8062, loss_bbox: 0.2161, loss_mask: 0.2234, loss: 0.6682 2023-11-13 19:47:16,720 - mmdet - INFO - Epoch [5][1150/7330] lr: 1.000e-04, eta: 6:08:13, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0425, loss_cls: 0.1790, acc: 93.4136, loss_bbox: 0.2272, loss_mask: 0.2323, loss: 0.7040 2023-11-13 19:47:36,008 - mmdet - INFO - Epoch [5][1200/7330] lr: 1.000e-04, eta: 6:07:54, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0406, loss_cls: 0.1766, acc: 93.5002, loss_bbox: 0.2253, loss_mask: 0.2267, loss: 0.6915 2023-11-13 19:47:55,443 - mmdet - INFO - Epoch [5][1250/7330] lr: 1.000e-04, eta: 6:07:35, time: 0.389, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0404, loss_cls: 0.1793, acc: 93.4011, loss_bbox: 0.2273, loss_mask: 0.2252, loss: 0.6934 2023-11-13 19:48:14,627 - mmdet - INFO - Epoch [5][1300/7330] lr: 1.000e-04, eta: 6:07:16, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0434, loss_cls: 0.1760, acc: 93.4917, loss_bbox: 0.2223, loss_mask: 0.2338, loss: 0.6972 2023-11-13 19:48:33,761 - mmdet - INFO - Epoch [5][1350/7330] lr: 1.000e-04, eta: 6:06:56, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0410, loss_cls: 0.1767, acc: 93.3606, loss_bbox: 0.2213, loss_mask: 0.2248, loss: 0.6848 2023-11-13 19:48:53,261 - mmdet - INFO - Epoch [5][1400/7330] lr: 1.000e-04, eta: 6:06:38, time: 0.390, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0436, loss_cls: 0.1856, acc: 93.1567, loss_bbox: 0.2337, loss_mask: 0.2286, loss: 0.7143 2023-11-13 19:49:12,941 - mmdet - INFO - Epoch [5][1450/7330] lr: 1.000e-04, eta: 6:06:19, time: 0.394, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0439, loss_cls: 0.1802, acc: 93.3472, loss_bbox: 0.2275, loss_mask: 0.2264, loss: 0.7013 2023-11-13 19:49:32,356 - mmdet - INFO - Epoch [5][1500/7330] lr: 1.000e-04, eta: 6:06:01, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0415, loss_cls: 0.1793, acc: 93.4224, loss_bbox: 0.2280, loss_mask: 0.2269, loss: 0.6970 2023-11-13 19:49:51,690 - mmdet - INFO - Epoch [5][1550/7330] lr: 1.000e-04, eta: 6:05:42, time: 0.387, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0433, loss_cls: 0.1806, acc: 93.4155, loss_bbox: 0.2255, loss_mask: 0.2256, loss: 0.6994 2023-11-13 19:50:11,198 - mmdet - INFO - Epoch [5][1600/7330] lr: 1.000e-04, eta: 6:05:23, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0439, loss_cls: 0.1804, acc: 93.3328, loss_bbox: 0.2286, loss_mask: 0.2299, loss: 0.7048 2023-11-13 19:50:30,605 - mmdet - INFO - Epoch [5][1650/7330] lr: 1.000e-04, eta: 6:05:04, time: 0.388, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0435, loss_cls: 0.1879, acc: 93.0750, loss_bbox: 0.2334, loss_mask: 0.2302, loss: 0.7187 2023-11-13 19:50:49,482 - mmdet - INFO - Epoch [5][1700/7330] lr: 1.000e-04, eta: 6:04:44, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0387, loss_cls: 0.1732, acc: 93.6665, loss_bbox: 0.2216, loss_mask: 0.2267, loss: 0.6796 2023-11-13 19:51:08,317 - mmdet - INFO - Epoch [5][1750/7330] lr: 1.000e-04, eta: 6:04:24, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0393, loss_cls: 0.1769, acc: 93.4719, loss_bbox: 0.2228, loss_mask: 0.2261, loss: 0.6857 2023-11-13 19:51:27,540 - mmdet - INFO - Epoch [5][1800/7330] lr: 1.000e-04, eta: 6:04:05, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0416, loss_cls: 0.1785, acc: 93.5188, loss_bbox: 0.2185, loss_mask: 0.2259, loss: 0.6855 2023-11-13 19:51:46,548 - mmdet - INFO - Epoch [5][1850/7330] lr: 1.000e-04, eta: 6:03:45, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0424, loss_cls: 0.1774, acc: 93.4482, loss_bbox: 0.2283, loss_mask: 0.2317, loss: 0.7006 2023-11-13 19:52:05,534 - mmdet - INFO - Epoch [5][1900/7330] lr: 1.000e-04, eta: 6:03:26, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0410, loss_cls: 0.1729, acc: 93.6174, loss_bbox: 0.2177, loss_mask: 0.2265, loss: 0.6801 2023-11-13 19:52:24,337 - mmdet - INFO - Epoch [5][1950/7330] lr: 1.000e-04, eta: 6:03:06, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0404, loss_cls: 0.1767, acc: 93.4924, loss_bbox: 0.2236, loss_mask: 0.2259, loss: 0.6881 2023-11-13 19:52:43,548 - mmdet - INFO - Epoch [5][2000/7330] lr: 1.000e-04, eta: 6:02:47, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0416, loss_cls: 0.1810, acc: 93.2708, loss_bbox: 0.2297, loss_mask: 0.2273, loss: 0.7020 2023-11-13 19:53:03,277 - mmdet - INFO - Epoch [5][2050/7330] lr: 1.000e-04, eta: 6:02:28, time: 0.395, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0414, loss_cls: 0.1822, acc: 93.2568, loss_bbox: 0.2281, loss_mask: 0.2288, loss: 0.7032 2023-11-13 19:53:22,148 - mmdet - INFO - Epoch [5][2100/7330] lr: 1.000e-04, eta: 6:02:08, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0414, loss_cls: 0.1865, acc: 93.2078, loss_bbox: 0.2294, loss_mask: 0.2299, loss: 0.7105 2023-11-13 19:53:41,821 - mmdet - INFO - Epoch [5][2150/7330] lr: 1.000e-04, eta: 6:01:50, time: 0.393, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0436, loss_cls: 0.1828, acc: 93.4199, loss_bbox: 0.2263, loss_mask: 0.2284, loss: 0.7049 2023-11-13 19:54:01,172 - mmdet - INFO - Epoch [5][2200/7330] lr: 1.000e-04, eta: 6:01:31, time: 0.387, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0406, loss_cls: 0.1803, acc: 93.3857, loss_bbox: 0.2250, loss_mask: 0.2211, loss: 0.6885 2023-11-13 19:54:20,034 - mmdet - INFO - Epoch [5][2250/7330] lr: 1.000e-04, eta: 6:01:11, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0401, loss_cls: 0.1743, acc: 93.5474, loss_bbox: 0.2196, loss_mask: 0.2253, loss: 0.6806 2023-11-13 19:54:39,281 - mmdet - INFO - Epoch [5][2300/7330] lr: 1.000e-04, eta: 6:00:52, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0413, loss_cls: 0.1819, acc: 93.3237, loss_bbox: 0.2270, loss_mask: 0.2266, loss: 0.6991 2023-11-13 19:54:58,549 - mmdet - INFO - Epoch [5][2350/7330] lr: 1.000e-04, eta: 6:00:33, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0438, loss_cls: 0.1875, acc: 93.1025, loss_bbox: 0.2311, loss_mask: 0.2299, loss: 0.7150 2023-11-13 19:55:17,396 - mmdet - INFO - Epoch [5][2400/7330] lr: 1.000e-04, eta: 6:00:13, time: 0.377, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0388, loss_cls: 0.1739, acc: 93.5266, loss_bbox: 0.2242, loss_mask: 0.2280, loss: 0.6848 2023-11-13 19:55:36,732 - mmdet - INFO - Epoch [5][2450/7330] lr: 1.000e-04, eta: 5:59:54, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0424, loss_cls: 0.1761, acc: 93.5310, loss_bbox: 0.2207, loss_mask: 0.2219, loss: 0.6838 2023-11-13 19:55:56,172 - mmdet - INFO - Epoch [5][2500/7330] lr: 1.000e-04, eta: 5:59:35, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0432, loss_cls: 0.1847, acc: 93.2461, loss_bbox: 0.2305, loss_mask: 0.2257, loss: 0.7082 2023-11-13 19:56:15,312 - mmdet - INFO - Epoch [5][2550/7330] lr: 1.000e-04, eta: 5:59:16, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0435, loss_cls: 0.1857, acc: 93.0498, loss_bbox: 0.2348, loss_mask: 0.2231, loss: 0.7092 2023-11-13 19:56:34,422 - mmdet - INFO - Epoch [5][2600/7330] lr: 1.000e-04, eta: 5:58:57, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0406, loss_cls: 0.1844, acc: 93.2791, loss_bbox: 0.2288, loss_mask: 0.2296, loss: 0.7056 2023-11-13 19:56:53,686 - mmdet - INFO - Epoch [5][2650/7330] lr: 1.000e-04, eta: 5:58:37, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0437, loss_cls: 0.1800, acc: 93.3923, loss_bbox: 0.2267, loss_mask: 0.2294, loss: 0.7031 2023-11-13 19:57:12,915 - mmdet - INFO - Epoch [5][2700/7330] lr: 1.000e-04, eta: 5:58:18, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0427, loss_cls: 0.1823, acc: 93.3616, loss_bbox: 0.2291, loss_mask: 0.2266, loss: 0.7034 2023-11-13 19:57:31,789 - mmdet - INFO - Epoch [5][2750/7330] lr: 1.000e-04, eta: 5:57:58, time: 0.377, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0425, loss_cls: 0.1818, acc: 93.2170, loss_bbox: 0.2324, loss_mask: 0.2288, loss: 0.7079 2023-11-13 19:57:50,610 - mmdet - INFO - Epoch [5][2800/7330] lr: 1.000e-04, eta: 5:57:38, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0407, loss_cls: 0.1804, acc: 93.3735, loss_bbox: 0.2230, loss_mask: 0.2288, loss: 0.6951 2023-11-13 19:58:09,853 - mmdet - INFO - Epoch [5][2850/7330] lr: 1.000e-04, eta: 5:57:19, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0398, loss_cls: 0.1761, acc: 93.4302, loss_bbox: 0.2241, loss_mask: 0.2237, loss: 0.6853 2023-11-13 19:58:28,593 - mmdet - INFO - Epoch [5][2900/7330] lr: 1.000e-04, eta: 5:56:59, time: 0.375, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0404, loss_cls: 0.1779, acc: 93.3650, loss_bbox: 0.2236, loss_mask: 0.2253, loss: 0.6885 2023-11-13 19:58:47,144 - mmdet - INFO - Epoch [5][2950/7330] lr: 1.000e-04, eta: 5:56:39, time: 0.371, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0394, loss_cls: 0.1730, acc: 93.6462, loss_bbox: 0.2150, loss_mask: 0.2186, loss: 0.6668 2023-11-13 19:59:06,438 - mmdet - INFO - Epoch [5][3000/7330] lr: 1.000e-04, eta: 5:56:20, time: 0.386, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0437, loss_cls: 0.1812, acc: 93.3879, loss_bbox: 0.2248, loss_mask: 0.2327, loss: 0.7057 2023-11-13 19:59:25,316 - mmdet - INFO - Epoch [5][3050/7330] lr: 1.000e-04, eta: 5:56:00, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0415, loss_cls: 0.1789, acc: 93.3616, loss_bbox: 0.2287, loss_mask: 0.2337, loss: 0.7051 2023-11-13 19:59:44,406 - mmdet - INFO - Epoch [5][3100/7330] lr: 1.000e-04, eta: 5:55:41, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0415, loss_cls: 0.1766, acc: 93.4011, loss_bbox: 0.2221, loss_mask: 0.2271, loss: 0.6881 2023-11-13 20:00:03,219 - mmdet - INFO - Epoch [5][3150/7330] lr: 1.000e-04, eta: 5:55:21, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0383, loss_cls: 0.1759, acc: 93.5457, loss_bbox: 0.2221, loss_mask: 0.2254, loss: 0.6814 2023-11-13 20:00:22,254 - mmdet - INFO - Epoch [5][3200/7330] lr: 1.000e-04, eta: 5:55:01, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0411, loss_cls: 0.1780, acc: 93.2600, loss_bbox: 0.2306, loss_mask: 0.2289, loss: 0.7000 2023-11-13 20:00:41,294 - mmdet - INFO - Epoch [5][3250/7330] lr: 1.000e-04, eta: 5:54:42, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0405, loss_cls: 0.1731, acc: 93.6602, loss_bbox: 0.2193, loss_mask: 0.2212, loss: 0.6748 2023-11-13 20:01:00,681 - mmdet - INFO - Epoch [5][3300/7330] lr: 1.000e-04, eta: 5:54:23, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0416, loss_cls: 0.1752, acc: 93.6182, loss_bbox: 0.2204, loss_mask: 0.2254, loss: 0.6846 2023-11-13 20:01:19,825 - mmdet - INFO - Epoch [5][3350/7330] lr: 1.000e-04, eta: 5:54:03, time: 0.383, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0423, loss_cls: 0.1794, acc: 93.3628, loss_bbox: 0.2252, loss_mask: 0.2282, loss: 0.6971 2023-11-13 20:01:38,809 - mmdet - INFO - Epoch [5][3400/7330] lr: 1.000e-04, eta: 5:53:44, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0412, loss_cls: 0.1819, acc: 93.4290, loss_bbox: 0.2263, loss_mask: 0.2284, loss: 0.7005 2023-11-13 20:01:58,447 - mmdet - INFO - Epoch [5][3450/7330] lr: 1.000e-04, eta: 5:53:25, time: 0.393, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0431, loss_cls: 0.1829, acc: 93.2241, loss_bbox: 0.2318, loss_mask: 0.2256, loss: 0.7067 2023-11-13 20:02:17,951 - mmdet - INFO - Epoch [5][3500/7330] lr: 1.000e-04, eta: 5:53:07, time: 0.390, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0413, loss_cls: 0.1820, acc: 93.2935, loss_bbox: 0.2295, loss_mask: 0.2308, loss: 0.7074 2023-11-13 20:02:36,874 - mmdet - INFO - Epoch [5][3550/7330] lr: 1.000e-04, eta: 5:52:47, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0416, loss_cls: 0.1724, acc: 93.6909, loss_bbox: 0.2160, loss_mask: 0.2270, loss: 0.6771 2023-11-13 20:02:55,700 - mmdet - INFO - Epoch [5][3600/7330] lr: 1.000e-04, eta: 5:52:27, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0416, loss_cls: 0.1776, acc: 93.4434, loss_bbox: 0.2175, loss_mask: 0.2285, loss: 0.6884 2023-11-13 20:03:14,765 - mmdet - INFO - Epoch [5][3650/7330] lr: 1.000e-04, eta: 5:52:08, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0404, loss_cls: 0.1741, acc: 93.4556, loss_bbox: 0.2249, loss_mask: 0.2292, loss: 0.6916 2023-11-13 20:03:33,669 - mmdet - INFO - Epoch [5][3700/7330] lr: 1.000e-04, eta: 5:51:48, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0400, loss_cls: 0.1749, acc: 93.5823, loss_bbox: 0.2224, loss_mask: 0.2247, loss: 0.6824 2023-11-13 20:03:53,455 - mmdet - INFO - Epoch [5][3750/7330] lr: 1.000e-04, eta: 5:51:30, time: 0.396, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0429, loss_cls: 0.1856, acc: 93.0952, loss_bbox: 0.2363, loss_mask: 0.2306, loss: 0.7165 2023-11-13 20:04:12,436 - mmdet - INFO - Epoch [5][3800/7330] lr: 1.000e-04, eta: 5:51:10, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0411, loss_cls: 0.1817, acc: 93.3694, loss_bbox: 0.2276, loss_mask: 0.2344, loss: 0.7070 2023-11-13 20:04:31,244 - mmdet - INFO - Epoch [5][3850/7330] lr: 1.000e-04, eta: 5:50:50, time: 0.376, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0400, loss_cls: 0.1758, acc: 93.6089, loss_bbox: 0.2167, loss_mask: 0.2245, loss: 0.6792 2023-11-13 20:04:50,095 - mmdet - INFO - Epoch [5][3900/7330] lr: 1.000e-04, eta: 5:50:30, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0413, loss_cls: 0.1807, acc: 93.3364, loss_bbox: 0.2266, loss_mask: 0.2271, loss: 0.6970 2023-11-13 20:05:09,532 - mmdet - INFO - Epoch [5][3950/7330] lr: 1.000e-04, eta: 5:50:12, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0416, loss_cls: 0.1857, acc: 93.2607, loss_bbox: 0.2304, loss_mask: 0.2340, loss: 0.7144 2023-11-13 20:05:28,368 - mmdet - INFO - Epoch [5][4000/7330] lr: 1.000e-04, eta: 5:49:52, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0398, loss_cls: 0.1810, acc: 93.3513, loss_bbox: 0.2242, loss_mask: 0.2251, loss: 0.6903 2023-11-13 20:05:48,029 - mmdet - INFO - Epoch [5][4050/7330] lr: 1.000e-04, eta: 5:49:33, time: 0.393, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0454, loss_cls: 0.1887, acc: 93.0435, loss_bbox: 0.2377, loss_mask: 0.2328, loss: 0.7290 2023-11-13 20:06:06,857 - mmdet - INFO - Epoch [5][4100/7330] lr: 1.000e-04, eta: 5:49:13, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0413, loss_cls: 0.1796, acc: 93.3101, loss_bbox: 0.2249, loss_mask: 0.2241, loss: 0.6908 2023-11-13 20:06:25,849 - mmdet - INFO - Epoch [5][4150/7330] lr: 1.000e-04, eta: 5:48:54, time: 0.380, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0419, loss_cls: 0.1776, acc: 93.5122, loss_bbox: 0.2216, loss_mask: 0.2285, loss: 0.6908 2023-11-13 20:06:45,282 - mmdet - INFO - Epoch [5][4200/7330] lr: 1.000e-04, eta: 5:48:35, time: 0.389, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0423, loss_cls: 0.1860, acc: 93.1763, loss_bbox: 0.2315, loss_mask: 0.2296, loss: 0.7121 2023-11-13 20:07:04,240 - mmdet - INFO - Epoch [5][4250/7330] lr: 1.000e-04, eta: 5:48:15, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0406, loss_cls: 0.1784, acc: 93.3159, loss_bbox: 0.2282, loss_mask: 0.2289, loss: 0.6972 2023-11-13 20:07:23,128 - mmdet - INFO - Epoch [5][4300/7330] lr: 1.000e-04, eta: 5:47:56, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0399, loss_cls: 0.1869, acc: 93.1152, loss_bbox: 0.2304, loss_mask: 0.2264, loss: 0.7048 2023-11-13 20:07:42,192 - mmdet - INFO - Epoch [5][4350/7330] lr: 1.000e-04, eta: 5:47:36, time: 0.381, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0421, loss_cls: 0.1772, acc: 93.4568, loss_bbox: 0.2257, loss_mask: 0.2301, loss: 0.6953 2023-11-13 20:08:01,322 - mmdet - INFO - Epoch [5][4400/7330] lr: 1.000e-04, eta: 5:47:17, time: 0.383, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0417, loss_cls: 0.1762, acc: 93.4238, loss_bbox: 0.2210, loss_mask: 0.2265, loss: 0.6865 2023-11-13 20:08:20,407 - mmdet - INFO - Epoch [5][4450/7330] lr: 1.000e-04, eta: 5:46:57, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0405, loss_cls: 0.1824, acc: 93.3535, loss_bbox: 0.2219, loss_mask: 0.2282, loss: 0.6943 2023-11-13 20:08:39,470 - mmdet - INFO - Epoch [5][4500/7330] lr: 1.000e-04, eta: 5:46:38, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0390, loss_cls: 0.1792, acc: 93.4729, loss_bbox: 0.2232, loss_mask: 0.2273, loss: 0.6901 2023-11-13 20:08:58,854 - mmdet - INFO - Epoch [5][4550/7330] lr: 1.000e-04, eta: 5:46:19, time: 0.388, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0417, loss_cls: 0.1839, acc: 93.3110, loss_bbox: 0.2280, loss_mask: 0.2318, loss: 0.7075 2023-11-13 20:09:18,201 - mmdet - INFO - Epoch [5][4600/7330] lr: 1.000e-04, eta: 5:46:00, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0427, loss_cls: 0.1812, acc: 93.2874, loss_bbox: 0.2261, loss_mask: 0.2314, loss: 0.7052 2023-11-13 20:09:37,268 - mmdet - INFO - Epoch [5][4650/7330] lr: 1.000e-04, eta: 5:45:41, time: 0.381, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0417, loss_cls: 0.1764, acc: 93.5088, loss_bbox: 0.2218, loss_mask: 0.2260, loss: 0.6868 2023-11-13 20:09:56,462 - mmdet - INFO - Epoch [5][4700/7330] lr: 1.000e-04, eta: 5:45:21, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0410, loss_cls: 0.1826, acc: 93.2083, loss_bbox: 0.2299, loss_mask: 0.2292, loss: 0.7064 2023-11-13 20:10:15,698 - mmdet - INFO - Epoch [5][4750/7330] lr: 1.000e-04, eta: 5:45:02, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0427, loss_cls: 0.1790, acc: 93.3262, loss_bbox: 0.2247, loss_mask: 0.2273, loss: 0.6951 2023-11-13 20:10:34,808 - mmdet - INFO - Epoch [5][4800/7330] lr: 1.000e-04, eta: 5:44:43, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0406, loss_cls: 0.1800, acc: 93.3716, loss_bbox: 0.2234, loss_mask: 0.2306, loss: 0.6957 2023-11-13 20:10:53,644 - mmdet - INFO - Epoch [5][4850/7330] lr: 1.000e-04, eta: 5:44:23, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0406, loss_cls: 0.1738, acc: 93.5991, loss_bbox: 0.2184, loss_mask: 0.2275, loss: 0.6809 2023-11-13 20:11:12,626 - mmdet - INFO - Epoch [5][4900/7330] lr: 1.000e-04, eta: 5:44:04, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0413, loss_cls: 0.1792, acc: 93.3481, loss_bbox: 0.2223, loss_mask: 0.2237, loss: 0.6906 2023-11-13 20:11:31,871 - mmdet - INFO - Epoch [5][4950/7330] lr: 1.000e-04, eta: 5:43:44, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0443, loss_cls: 0.1872, acc: 93.1775, loss_bbox: 0.2326, loss_mask: 0.2327, loss: 0.7210 2023-11-13 20:11:50,841 - mmdet - INFO - Epoch [5][5000/7330] lr: 1.000e-04, eta: 5:43:25, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0406, loss_cls: 0.1715, acc: 93.7585, loss_bbox: 0.2146, loss_mask: 0.2242, loss: 0.6702 2023-11-13 20:12:09,640 - mmdet - INFO - Epoch [5][5050/7330] lr: 1.000e-04, eta: 5:43:05, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0398, loss_cls: 0.1731, acc: 93.5898, loss_bbox: 0.2187, loss_mask: 0.2255, loss: 0.6766 2023-11-13 20:12:28,753 - mmdet - INFO - Epoch [5][5100/7330] lr: 1.000e-04, eta: 5:42:46, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0395, loss_cls: 0.1783, acc: 93.4480, loss_bbox: 0.2238, loss_mask: 0.2291, loss: 0.6919 2023-11-13 20:12:48,167 - mmdet - INFO - Epoch [5][5150/7330] lr: 1.000e-04, eta: 5:42:27, time: 0.388, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0435, loss_cls: 0.1873, acc: 93.1750, loss_bbox: 0.2330, loss_mask: 0.2308, loss: 0.7170 2023-11-13 20:13:07,357 - mmdet - INFO - Epoch [5][5200/7330] lr: 1.000e-04, eta: 5:42:08, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0415, loss_cls: 0.1790, acc: 93.4297, loss_bbox: 0.2285, loss_mask: 0.2299, loss: 0.7000 2023-11-13 20:13:26,484 - mmdet - INFO - Epoch [5][5250/7330] lr: 1.000e-04, eta: 5:41:48, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0405, loss_cls: 0.1827, acc: 93.2920, loss_bbox: 0.2264, loss_mask: 0.2336, loss: 0.7063 2023-11-13 20:13:45,678 - mmdet - INFO - Epoch [5][5300/7330] lr: 1.000e-04, eta: 5:41:29, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0403, loss_cls: 0.1753, acc: 93.6335, loss_bbox: 0.2169, loss_mask: 0.2202, loss: 0.6749 2023-11-13 20:14:04,743 - mmdet - INFO - Epoch [5][5350/7330] lr: 1.000e-04, eta: 5:41:10, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0409, loss_cls: 0.1883, acc: 93.0549, loss_bbox: 0.2344, loss_mask: 0.2302, loss: 0.7158 2023-11-13 20:14:24,012 - mmdet - INFO - Epoch [5][5400/7330] lr: 1.000e-04, eta: 5:40:50, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0414, loss_cls: 0.1839, acc: 93.1775, loss_bbox: 0.2288, loss_mask: 0.2300, loss: 0.7083 2023-11-13 20:14:43,716 - mmdet - INFO - Epoch [5][5450/7330] lr: 1.000e-04, eta: 5:40:32, time: 0.394, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0423, loss_cls: 0.1836, acc: 93.3406, loss_bbox: 0.2234, loss_mask: 0.2280, loss: 0.6987 2023-11-13 20:15:02,335 - mmdet - INFO - Epoch [5][5500/7330] lr: 1.000e-04, eta: 5:40:12, time: 0.372, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0394, loss_cls: 0.1847, acc: 93.3630, loss_bbox: 0.2253, loss_mask: 0.2288, loss: 0.7010 2023-11-13 20:15:21,763 - mmdet - INFO - Epoch [5][5550/7330] lr: 1.000e-04, eta: 5:39:53, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0417, loss_cls: 0.1810, acc: 93.4009, loss_bbox: 0.2231, loss_mask: 0.2276, loss: 0.6965 2023-11-13 20:15:40,591 - mmdet - INFO - Epoch [5][5600/7330] lr: 1.000e-04, eta: 5:39:33, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0411, loss_cls: 0.1828, acc: 93.3936, loss_bbox: 0.2257, loss_mask: 0.2257, loss: 0.6968 2023-11-13 20:15:59,758 - mmdet - INFO - Epoch [5][5650/7330] lr: 1.000e-04, eta: 5:39:14, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0392, loss_cls: 0.1656, acc: 93.9297, loss_bbox: 0.2118, loss_mask: 0.2226, loss: 0.6601 2023-11-13 20:16:19,159 - mmdet - INFO - Epoch [5][5700/7330] lr: 1.000e-04, eta: 5:38:55, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0423, loss_cls: 0.1864, acc: 93.1187, loss_bbox: 0.2334, loss_mask: 0.2268, loss: 0.7112 2023-11-13 20:16:38,023 - mmdet - INFO - Epoch [5][5750/7330] lr: 1.000e-04, eta: 5:38:35, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0383, loss_cls: 0.1701, acc: 93.7527, loss_bbox: 0.2194, loss_mask: 0.2223, loss: 0.6723 2023-11-13 20:16:57,339 - mmdet - INFO - Epoch [5][5800/7330] lr: 1.000e-04, eta: 5:38:16, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0409, loss_cls: 0.1848, acc: 93.2632, loss_bbox: 0.2301, loss_mask: 0.2274, loss: 0.7055 2023-11-13 20:17:16,212 - mmdet - INFO - Epoch [5][5850/7330] lr: 1.000e-04, eta: 5:37:57, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0406, loss_cls: 0.1820, acc: 93.3049, loss_bbox: 0.2300, loss_mask: 0.2252, loss: 0.6969 2023-11-13 20:17:35,146 - mmdet - INFO - Epoch [5][5900/7330] lr: 1.000e-04, eta: 5:37:37, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0394, loss_cls: 0.1784, acc: 93.4607, loss_bbox: 0.2178, loss_mask: 0.2312, loss: 0.6882 2023-11-13 20:17:54,363 - mmdet - INFO - Epoch [5][5950/7330] lr: 1.000e-04, eta: 5:37:18, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0417, loss_cls: 0.1843, acc: 93.1587, loss_bbox: 0.2290, loss_mask: 0.2335, loss: 0.7128 2023-11-13 20:18:13,637 - mmdet - INFO - Epoch [5][6000/7330] lr: 1.000e-04, eta: 5:36:59, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0401, loss_cls: 0.1767, acc: 93.4717, loss_bbox: 0.2262, loss_mask: 0.2298, loss: 0.6931 2023-11-13 20:18:32,874 - mmdet - INFO - Epoch [5][6050/7330] lr: 1.000e-04, eta: 5:36:40, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0384, loss_cls: 0.1777, acc: 93.4109, loss_bbox: 0.2190, loss_mask: 0.2272, loss: 0.6825 2023-11-13 20:18:51,836 - mmdet - INFO - Epoch [5][6100/7330] lr: 1.000e-04, eta: 5:36:20, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0383, loss_cls: 0.1770, acc: 93.5642, loss_bbox: 0.2207, loss_mask: 0.2218, loss: 0.6786 2023-11-13 20:19:11,125 - mmdet - INFO - Epoch [5][6150/7330] lr: 1.000e-04, eta: 5:36:01, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0423, loss_cls: 0.1774, acc: 93.3745, loss_bbox: 0.2293, loss_mask: 0.2303, loss: 0.7003 2023-11-13 20:19:30,534 - mmdet - INFO - Epoch [5][6200/7330] lr: 1.000e-04, eta: 5:35:42, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0424, loss_cls: 0.1859, acc: 93.2815, loss_bbox: 0.2290, loss_mask: 0.2277, loss: 0.7088 2023-11-13 20:19:49,891 - mmdet - INFO - Epoch [5][6250/7330] lr: 1.000e-04, eta: 5:35:23, time: 0.387, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0414, loss_cls: 0.1795, acc: 93.4248, loss_bbox: 0.2228, loss_mask: 0.2284, loss: 0.6935 2023-11-13 20:20:09,166 - mmdet - INFO - Epoch [5][6300/7330] lr: 1.000e-04, eta: 5:35:04, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0412, loss_cls: 0.1730, acc: 93.5903, loss_bbox: 0.2186, loss_mask: 0.2239, loss: 0.6801 2023-11-13 20:20:28,565 - mmdet - INFO - Epoch [5][6350/7330] lr: 1.000e-04, eta: 5:34:45, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0406, loss_cls: 0.1744, acc: 93.5737, loss_bbox: 0.2151, loss_mask: 0.2219, loss: 0.6722 2023-11-13 20:20:47,807 - mmdet - INFO - Epoch [5][6400/7330] lr: 1.000e-04, eta: 5:34:26, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0420, loss_cls: 0.1790, acc: 93.3469, loss_bbox: 0.2249, loss_mask: 0.2247, loss: 0.6920 2023-11-13 20:21:07,130 - mmdet - INFO - Epoch [5][6450/7330] lr: 1.000e-04, eta: 5:34:07, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0409, loss_cls: 0.1779, acc: 93.4919, loss_bbox: 0.2249, loss_mask: 0.2242, loss: 0.6876 2023-11-13 20:21:26,109 - mmdet - INFO - Epoch [5][6500/7330] lr: 1.000e-04, eta: 5:33:47, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0385, loss_cls: 0.1774, acc: 93.4673, loss_bbox: 0.2233, loss_mask: 0.2226, loss: 0.6813 2023-11-13 20:21:45,302 - mmdet - INFO - Epoch [5][6550/7330] lr: 1.000e-04, eta: 5:33:28, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0440, loss_cls: 0.1821, acc: 93.2710, loss_bbox: 0.2283, loss_mask: 0.2271, loss: 0.7057 2023-11-13 20:22:04,541 - mmdet - INFO - Epoch [5][6600/7330] lr: 1.000e-04, eta: 5:33:09, time: 0.385, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0398, loss_cls: 0.1783, acc: 93.5667, loss_bbox: 0.2165, loss_mask: 0.2268, loss: 0.6835 2023-11-13 20:22:23,837 - mmdet - INFO - Epoch [5][6650/7330] lr: 1.000e-04, eta: 5:32:50, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0420, loss_cls: 0.1793, acc: 93.4890, loss_bbox: 0.2256, loss_mask: 0.2305, loss: 0.6999 2023-11-13 20:22:42,254 - mmdet - INFO - Epoch [5][6700/7330] lr: 1.000e-04, eta: 5:32:29, time: 0.368, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0386, loss_cls: 0.1676, acc: 93.8542, loss_bbox: 0.2106, loss_mask: 0.2172, loss: 0.6534 2023-11-13 20:23:01,466 - mmdet - INFO - Epoch [5][6750/7330] lr: 1.000e-04, eta: 5:32:10, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0392, loss_cls: 0.1743, acc: 93.5857, loss_bbox: 0.2201, loss_mask: 0.2234, loss: 0.6771 2023-11-13 20:23:20,492 - mmdet - INFO - Epoch [5][6800/7330] lr: 1.000e-04, eta: 5:31:51, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0398, loss_cls: 0.1743, acc: 93.5942, loss_bbox: 0.2151, loss_mask: 0.2204, loss: 0.6699 2023-11-13 20:23:39,642 - mmdet - INFO - Epoch [5][6850/7330] lr: 1.000e-04, eta: 5:31:32, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0445, loss_cls: 0.1815, acc: 93.3389, loss_bbox: 0.2306, loss_mask: 0.2346, loss: 0.7143 2023-11-13 20:23:58,670 - mmdet - INFO - Epoch [5][6900/7330] lr: 1.000e-04, eta: 5:31:12, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0420, loss_cls: 0.1842, acc: 93.2996, loss_bbox: 0.2271, loss_mask: 0.2309, loss: 0.7058 2023-11-13 20:24:17,453 - mmdet - INFO - Epoch [5][6950/7330] lr: 1.000e-04, eta: 5:30:52, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0389, loss_cls: 0.1749, acc: 93.7615, loss_bbox: 0.2130, loss_mask: 0.2300, loss: 0.6778 2023-11-13 20:24:36,402 - mmdet - INFO - Epoch [5][7000/7330] lr: 1.000e-04, eta: 5:30:33, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0411, loss_cls: 0.1742, acc: 93.5881, loss_bbox: 0.2203, loss_mask: 0.2310, loss: 0.6872 2023-11-13 20:24:55,608 - mmdet - INFO - Epoch [5][7050/7330] lr: 1.000e-04, eta: 5:30:13, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0421, loss_cls: 0.1875, acc: 93.1106, loss_bbox: 0.2295, loss_mask: 0.2310, loss: 0.7130 2023-11-13 20:25:14,832 - mmdet - INFO - Epoch [5][7100/7330] lr: 1.000e-04, eta: 5:29:54, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0372, loss_cls: 0.1740, acc: 93.5356, loss_bbox: 0.2216, loss_mask: 0.2239, loss: 0.6762 2023-11-13 20:25:33,783 - mmdet - INFO - Epoch [5][7150/7330] lr: 1.000e-04, eta: 5:29:35, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0417, loss_cls: 0.1797, acc: 93.4556, loss_bbox: 0.2228, loss_mask: 0.2301, loss: 0.6967 2023-11-13 20:25:52,595 - mmdet - INFO - Epoch [5][7200/7330] lr: 1.000e-04, eta: 5:29:15, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0422, loss_cls: 0.1795, acc: 93.4856, loss_bbox: 0.2198, loss_mask: 0.2242, loss: 0.6882 2023-11-13 20:26:11,760 - mmdet - INFO - Epoch [5][7250/7330] lr: 1.000e-04, eta: 5:28:56, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0413, loss_cls: 0.1751, acc: 93.5781, loss_bbox: 0.2210, loss_mask: 0.2269, loss: 0.6872 2023-11-13 20:26:31,164 - mmdet - INFO - Epoch [5][7300/7330] lr: 1.000e-04, eta: 5:28:37, time: 0.388, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0440, loss_cls: 0.1882, acc: 93.1650, loss_bbox: 0.2255, loss_mask: 0.2298, loss: 0.7118 2023-11-13 20:26:43,156 - mmdet - INFO - Saving checkpoint at 5 epochs 2023-11-13 20:27:33,513 - mmdet - INFO - Evaluating bbox... 2023-11-13 20:28:02,566 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.451 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.679 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.500 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.300 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.496 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 ] = 0.583 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.583 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.583 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.412 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.631 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.725 2023-11-13 20:28:02,568 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.563 | bicycle | 0.348 | car | 0.471 | | motorcycle | 0.460 | airplane | 0.658 | bus | 0.641 | | train | 0.666 | truck | 0.393 | boat | 0.318 | | traffic light | 0.274 | fire hydrant | 0.691 | stop sign | 0.653 | | parking meter | 0.474 | bench | 0.272 | bird | 0.386 | | cat | 0.714 | dog | 0.663 | horse | 0.585 | | sheep | 0.526 | cow | 0.615 | elephant | 0.678 | | bear | 0.760 | zebra | 0.649 | giraffe | 0.684 | | backpack | 0.195 | umbrella | 0.439 | handbag | 0.209 | | tie | 0.364 | suitcase | 0.450 | frisbee | 0.675 | | skis | 0.274 | snowboard | 0.362 | sports ball | 0.442 | | kite | 0.433 | baseball bat | 0.375 | baseball glove | 0.405 | | skateboard | 0.559 | surfboard | 0.418 | tennis racket | 0.521 | | bottle | 0.440 | wine glass | 0.409 | cup | 0.480 | | fork | 0.435 | knife | 0.247 | spoon | 0.267 | | bowl | 0.454 | banana | 0.277 | apple | 0.258 | | sandwich | 0.438 | orange | 0.321 | broccoli | 0.255 | | carrot | 0.237 | hot dog | 0.408 | pizza | 0.533 | | donut | 0.510 | cake | 0.424 | chair | 0.344 | | couch | 0.454 | potted plant | 0.335 | bed | 0.454 | | dining table | 0.283 | toilet | 0.622 | tv | 0.620 | | laptop | 0.651 | mouse | 0.617 | remote | 0.399 | | keyboard | 0.496 | cell phone | 0.415 | microwave | 0.631 | | oven | 0.362 | toaster | 0.381 | sink | 0.418 | | refrigerator | 0.607 | book | 0.170 | clock | 0.526 | | vase | 0.431 | scissors | 0.349 | teddy bear | 0.489 | | hair drier | 0.114 | toothbrush | 0.279 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:28:02,568 - mmdet - INFO - Evaluating segm... 2023-11-13 20:28:35,375 - 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 ] = 0.649 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.439 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.216 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.446 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 ] = 0.531 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.531 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.531 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.358 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 ] = 0.684 2023-11-13 20:28:35,378 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.487 | bicycle | 0.197 | car | 0.428 | | motorcycle | 0.368 | airplane | 0.530 | bus | 0.648 | | train | 0.665 | truck | 0.376 | boat | 0.268 | | traffic light | 0.264 | fire hydrant | 0.692 | stop sign | 0.664 | | parking meter | 0.511 | bench | 0.203 | bird | 0.334 | | cat | 0.715 | dog | 0.622 | horse | 0.427 | | sheep | 0.490 | cow | 0.527 | elephant | 0.608 | | bear | 0.755 | zebra | 0.589 | giraffe | 0.530 | | backpack | 0.195 | umbrella | 0.508 | handbag | 0.197 | | tie | 0.343 | suitcase | 0.464 | frisbee | 0.653 | | skis | 0.045 | snowboard | 0.250 | sports ball | 0.450 | | kite | 0.321 | baseball bat | 0.287 | baseball glove | 0.442 | | skateboard | 0.317 | surfboard | 0.344 | tennis racket | 0.568 | | bottle | 0.417 | wine glass | 0.356 | cup | 0.485 | | fork | 0.227 | knife | 0.177 | spoon | 0.182 | | bowl | 0.427 | banana | 0.232 | apple | 0.254 | | sandwich | 0.453 | orange | 0.325 | broccoli | 0.241 | | carrot | 0.200 | hot dog | 0.309 | pizza | 0.516 | | donut | 0.521 | cake | 0.431 | chair | 0.242 | | couch | 0.357 | potted plant | 0.267 | bed | 0.365 | | dining table | 0.164 | toilet | 0.624 | tv | 0.640 | | laptop | 0.640 | mouse | 0.623 | remote | 0.351 | | keyboard | 0.516 | cell phone | 0.382 | microwave | 0.637 | | oven | 0.345 | toaster | 0.414 | sink | 0.391 | | refrigerator | 0.616 | book | 0.123 | clock | 0.528 | | vase | 0.437 | scissors | 0.271 | teddy bear | 0.474 | | hair drier | 0.096 | toothbrush | 0.191 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:28:35,833 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_4.pth was removed 2023-11-13 20:28:38,141 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_5.pth. 2023-11-13 20:28:38,141 - mmdet - INFO - Best bbox_mAP is 0.4513 at 5 epoch. 2023-11-13 20:28:38,141 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:28:38,141 - mmdet - INFO - Epoch(val) [5][625] bbox_mAP: 0.4513, bbox_mAP_50: 0.6793, bbox_mAP_75: 0.5000, bbox_mAP_s: 0.2997, bbox_mAP_m: 0.4956, bbox_mAP_l: 0.5907, bbox_mAP_copypaste: 0.4513 0.6793 0.5000 0.2997 0.4956 0.5907, segm_mAP: 0.4092, segm_mAP_50: 0.6485, segm_mAP_75: 0.4394, segm_mAP_s: 0.2162, segm_mAP_m: 0.4464, segm_mAP_l: 0.5948, segm_mAP_copypaste: 0.4092 0.6485 0.4394 0.2162 0.4464 0.5948 2023-11-13 20:29:00,788 - mmdet - INFO - Epoch [6][50/7330] lr: 1.000e-04, eta: 5:27:55, time: 0.453, data_time: 0.089, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0384, loss_cls: 0.1682, acc: 93.6780, loss_bbox: 0.2199, loss_mask: 0.2188, loss: 0.6639 2023-11-13 20:29:20,161 - mmdet - INFO - Epoch [6][100/7330] lr: 1.000e-04, eta: 5:27:36, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0403, loss_cls: 0.1686, acc: 93.6975, loss_bbox: 0.2162, loss_mask: 0.2214, loss: 0.6648 2023-11-13 20:29:40,164 - mmdet - INFO - Epoch [6][150/7330] lr: 1.000e-04, eta: 5:27:18, time: 0.400, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0388, loss_cls: 0.1679, acc: 93.6409, loss_bbox: 0.2160, loss_mask: 0.2264, loss: 0.6686 2023-11-13 20:29:59,495 - mmdet - INFO - Epoch [6][200/7330] lr: 1.000e-04, eta: 5:26:59, time: 0.387, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0402, loss_cls: 0.1727, acc: 93.6746, loss_bbox: 0.2183, loss_mask: 0.2267, loss: 0.6776 2023-11-13 20:30:18,933 - mmdet - INFO - Epoch [6][250/7330] lr: 1.000e-04, eta: 5:26:40, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0404, loss_cls: 0.1650, acc: 93.8635, loss_bbox: 0.2141, loss_mask: 0.2220, loss: 0.6615 2023-11-13 20:30:38,337 - mmdet - INFO - Epoch [6][300/7330] lr: 1.000e-04, eta: 5:26:21, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0396, loss_cls: 0.1696, acc: 93.5889, loss_bbox: 0.2186, loss_mask: 0.2188, loss: 0.6654 2023-11-13 20:30:57,920 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:30:57,920 - mmdet - INFO - Epoch [6][350/7330] lr: 1.000e-04, eta: 5:26:02, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0418, loss_cls: 0.1675, acc: 93.8066, loss_bbox: 0.2130, loss_mask: 0.2167, loss: 0.6591 2023-11-13 20:31:17,236 - mmdet - INFO - Epoch [6][400/7330] lr: 1.000e-04, eta: 5:25:43, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0424, loss_cls: 0.1719, acc: 93.5803, loss_bbox: 0.2228, loss_mask: 0.2240, loss: 0.6813 2023-11-13 20:31:36,482 - mmdet - INFO - Epoch [6][450/7330] lr: 1.000e-04, eta: 5:25:24, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0399, loss_cls: 0.1677, acc: 93.6021, loss_bbox: 0.2205, loss_mask: 0.2239, loss: 0.6711 2023-11-13 20:31:55,850 - mmdet - INFO - Epoch [6][500/7330] lr: 1.000e-04, eta: 5:25:05, time: 0.387, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0397, loss_cls: 0.1637, acc: 93.9146, loss_bbox: 0.2073, loss_mask: 0.2246, loss: 0.6558 2023-11-13 20:32:15,340 - mmdet - INFO - Epoch [6][550/7330] lr: 1.000e-04, eta: 5:24:46, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0392, loss_cls: 0.1688, acc: 93.6794, loss_bbox: 0.2157, loss_mask: 0.2159, loss: 0.6603 2023-11-13 20:32:34,982 - mmdet - INFO - Epoch [6][600/7330] lr: 1.000e-04, eta: 5:24:28, time: 0.393, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0397, loss_cls: 0.1696, acc: 93.7087, loss_bbox: 0.2180, loss_mask: 0.2226, loss: 0.6693 2023-11-13 20:32:54,464 - mmdet - INFO - Epoch [6][650/7330] lr: 1.000e-04, eta: 5:24:09, time: 0.390, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0391, loss_cls: 0.1727, acc: 93.6001, loss_bbox: 0.2195, loss_mask: 0.2250, loss: 0.6747 2023-11-13 20:33:13,980 - mmdet - INFO - Epoch [6][700/7330] lr: 1.000e-04, eta: 5:23:50, time: 0.390, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0394, loss_cls: 0.1716, acc: 93.6436, loss_bbox: 0.2154, loss_mask: 0.2224, loss: 0.6693 2023-11-13 20:33:32,876 - mmdet - INFO - Epoch [6][750/7330] lr: 1.000e-04, eta: 5:23:31, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0387, loss_cls: 0.1708, acc: 93.5989, loss_bbox: 0.2134, loss_mask: 0.2175, loss: 0.6591 2023-11-13 20:33:52,290 - mmdet - INFO - Epoch [6][800/7330] lr: 1.000e-04, eta: 5:23:12, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0412, loss_cls: 0.1694, acc: 93.6572, loss_bbox: 0.2219, loss_mask: 0.2229, loss: 0.6751 2023-11-13 20:34:11,508 - mmdet - INFO - Epoch [6][850/7330] lr: 1.000e-04, eta: 5:22:53, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0406, loss_cls: 0.1673, acc: 93.7883, loss_bbox: 0.2147, loss_mask: 0.2210, loss: 0.6636 2023-11-13 20:34:30,524 - mmdet - INFO - Epoch [6][900/7330] lr: 1.000e-04, eta: 5:22:33, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0411, loss_cls: 0.1674, acc: 93.7832, loss_bbox: 0.2140, loss_mask: 0.2187, loss: 0.6599 2023-11-13 20:34:49,673 - mmdet - INFO - Epoch [6][950/7330] lr: 1.000e-04, eta: 5:22:14, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0419, loss_cls: 0.1701, acc: 93.7571, loss_bbox: 0.2127, loss_mask: 0.2223, loss: 0.6687 2023-11-13 20:35:09,756 - mmdet - INFO - Epoch [6][1000/7330] lr: 1.000e-04, eta: 5:21:56, time: 0.402, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0421, loss_cls: 0.1759, acc: 93.4866, loss_bbox: 0.2213, loss_mask: 0.2205, loss: 0.6816 2023-11-13 20:35:28,781 - mmdet - INFO - Epoch [6][1050/7330] lr: 1.000e-04, eta: 5:21:36, time: 0.380, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0375, loss_cls: 0.1661, acc: 93.7458, loss_bbox: 0.2140, loss_mask: 0.2215, loss: 0.6569 2023-11-13 20:35:48,453 - mmdet - INFO - Epoch [6][1100/7330] lr: 1.000e-04, eta: 5:21:18, time: 0.393, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0404, loss_cls: 0.1667, acc: 93.7539, loss_bbox: 0.2168, loss_mask: 0.2261, loss: 0.6699 2023-11-13 20:36:07,874 - mmdet - INFO - Epoch [6][1150/7330] lr: 1.000e-04, eta: 5:20:59, time: 0.388, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0373, loss_cls: 0.1654, acc: 93.8206, loss_bbox: 0.2113, loss_mask: 0.2182, loss: 0.6510 2023-11-13 20:36:27,090 - mmdet - INFO - Epoch [6][1200/7330] lr: 1.000e-04, eta: 5:20:40, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0400, loss_cls: 0.1656, acc: 93.7869, loss_bbox: 0.2146, loss_mask: 0.2214, loss: 0.6625 2023-11-13 20:36:46,330 - mmdet - INFO - Epoch [6][1250/7330] lr: 1.000e-04, eta: 5:20:21, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0390, loss_cls: 0.1698, acc: 93.7124, loss_bbox: 0.2211, loss_mask: 0.2226, loss: 0.6731 2023-11-13 20:37:05,751 - mmdet - INFO - Epoch [6][1300/7330] lr: 1.000e-04, eta: 5:20:02, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0405, loss_cls: 0.1677, acc: 93.7969, loss_bbox: 0.2150, loss_mask: 0.2223, loss: 0.6648 2023-11-13 20:37:25,135 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:37:25,135 - mmdet - INFO - Epoch [6][1350/7330] lr: 1.000e-04, eta: 5:19:43, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0418, loss_cls: 0.1759, acc: 93.4839, loss_bbox: 0.2227, loss_mask: 0.2184, loss: 0.6786 2023-11-13 20:37:44,129 - mmdet - INFO - Epoch [6][1400/7330] lr: 1.000e-04, eta: 5:19:23, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0406, loss_cls: 0.1758, acc: 93.4102, loss_bbox: 0.2247, loss_mask: 0.2295, loss: 0.6904 2023-11-13 20:38:03,325 - mmdet - INFO - Epoch [6][1450/7330] lr: 1.000e-04, eta: 5:19:04, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0411, loss_cls: 0.1710, acc: 93.6067, loss_bbox: 0.2210, loss_mask: 0.2216, loss: 0.6750 2023-11-13 20:38:22,515 - mmdet - INFO - Epoch [6][1500/7330] lr: 1.000e-04, eta: 5:18:45, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0388, loss_cls: 0.1696, acc: 93.6633, loss_bbox: 0.2143, loss_mask: 0.2202, loss: 0.6622 2023-11-13 20:38:41,891 - mmdet - INFO - Epoch [6][1550/7330] lr: 1.000e-04, eta: 5:18:26, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0402, loss_cls: 0.1711, acc: 93.6201, loss_bbox: 0.2188, loss_mask: 0.2249, loss: 0.6745 2023-11-13 20:39:00,809 - mmdet - INFO - Epoch [6][1600/7330] lr: 1.000e-04, eta: 5:18:06, time: 0.378, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0374, loss_cls: 0.1655, acc: 93.8777, loss_bbox: 0.2103, loss_mask: 0.2170, loss: 0.6481 2023-11-13 20:39:20,453 - mmdet - INFO - Epoch [6][1650/7330] lr: 1.000e-04, eta: 5:17:48, time: 0.393, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0405, loss_cls: 0.1682, acc: 93.6731, loss_bbox: 0.2190, loss_mask: 0.2262, loss: 0.6750 2023-11-13 20:39:39,922 - mmdet - INFO - Epoch [6][1700/7330] lr: 1.000e-04, eta: 5:17:29, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0398, loss_cls: 0.1713, acc: 93.7297, loss_bbox: 0.2133, loss_mask: 0.2218, loss: 0.6647 2023-11-13 20:39:59,032 - mmdet - INFO - Epoch [6][1750/7330] lr: 1.000e-04, eta: 5:17:10, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0404, loss_cls: 0.1764, acc: 93.4592, loss_bbox: 0.2196, loss_mask: 0.2224, loss: 0.6786 2023-11-13 20:40:18,074 - mmdet - INFO - Epoch [6][1800/7330] lr: 1.000e-04, eta: 5:16:50, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0380, loss_cls: 0.1689, acc: 93.7192, loss_bbox: 0.2140, loss_mask: 0.2204, loss: 0.6602 2023-11-13 20:40:37,519 - mmdet - INFO - Epoch [6][1850/7330] lr: 1.000e-04, eta: 5:16:31, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0395, loss_cls: 0.1649, acc: 93.8579, loss_bbox: 0.2144, loss_mask: 0.2159, loss: 0.6547 2023-11-13 20:40:56,843 - mmdet - INFO - Epoch [6][1900/7330] lr: 1.000e-04, eta: 5:16:12, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0393, loss_cls: 0.1682, acc: 93.7039, loss_bbox: 0.2203, loss_mask: 0.2193, loss: 0.6663 2023-11-13 20:41:16,438 - mmdet - INFO - Epoch [6][1950/7330] lr: 1.000e-04, eta: 5:15:54, time: 0.392, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0409, loss_cls: 0.1762, acc: 93.5105, loss_bbox: 0.2199, loss_mask: 0.2240, loss: 0.6806 2023-11-13 20:41:35,834 - mmdet - INFO - Epoch [6][2000/7330] lr: 1.000e-04, eta: 5:15:35, time: 0.388, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0404, loss_cls: 0.1636, acc: 93.9036, loss_bbox: 0.2132, loss_mask: 0.2213, loss: 0.6596 2023-11-13 20:41:55,292 - mmdet - INFO - Epoch [6][2050/7330] lr: 1.000e-04, eta: 5:15:16, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0406, loss_cls: 0.1722, acc: 93.6050, loss_bbox: 0.2226, loss_mask: 0.2227, loss: 0.6784 2023-11-13 20:42:14,550 - mmdet - INFO - Epoch [6][2100/7330] lr: 1.000e-04, eta: 5:14:57, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0397, loss_cls: 0.1730, acc: 93.6235, loss_bbox: 0.2227, loss_mask: 0.2258, loss: 0.6826 2023-11-13 20:42:33,778 - mmdet - INFO - Epoch [6][2150/7330] lr: 1.000e-04, eta: 5:14:38, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0415, loss_cls: 0.1817, acc: 93.2234, loss_bbox: 0.2273, loss_mask: 0.2248, loss: 0.6967 2023-11-13 20:42:52,883 - mmdet - INFO - Epoch [6][2200/7330] lr: 1.000e-04, eta: 5:14:18, time: 0.382, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0386, loss_cls: 0.1716, acc: 93.6008, loss_bbox: 0.2151, loss_mask: 0.2201, loss: 0.6656 2023-11-13 20:43:12,170 - mmdet - INFO - Epoch [6][2250/7330] lr: 1.000e-04, eta: 5:13:59, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0404, loss_cls: 0.1742, acc: 93.4802, loss_bbox: 0.2253, loss_mask: 0.2250, loss: 0.6855 2023-11-13 20:43:31,681 - mmdet - INFO - Epoch [6][2300/7330] lr: 1.000e-04, eta: 5:13:40, time: 0.390, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0392, loss_cls: 0.1786, acc: 93.3606, loss_bbox: 0.2252, loss_mask: 0.2251, loss: 0.6905 2023-11-13 20:43:51,232 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:43:51,232 - mmdet - INFO - Epoch [6][2350/7330] lr: 1.000e-04, eta: 5:13:22, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0409, loss_cls: 0.1737, acc: 93.4817, loss_bbox: 0.2239, loss_mask: 0.2199, loss: 0.6790 2023-11-13 20:44:10,052 - mmdet - INFO - Epoch [6][2400/7330] lr: 1.000e-04, eta: 5:13:02, time: 0.376, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0364, loss_cls: 0.1623, acc: 93.9844, loss_bbox: 0.2086, loss_mask: 0.2213, loss: 0.6466 2023-11-13 20:44:29,096 - mmdet - INFO - Epoch [6][2450/7330] lr: 1.000e-04, eta: 5:12:42, time: 0.381, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0410, loss_cls: 0.1756, acc: 93.4976, loss_bbox: 0.2194, loss_mask: 0.2243, loss: 0.6823 2023-11-13 20:44:48,378 - mmdet - INFO - Epoch [6][2500/7330] lr: 1.000e-04, eta: 5:12:23, time: 0.386, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0409, loss_cls: 0.1696, acc: 93.6506, loss_bbox: 0.2221, loss_mask: 0.2241, loss: 0.6782 2023-11-13 20:45:07,796 - mmdet - INFO - Epoch [6][2550/7330] lr: 1.000e-04, eta: 5:12:04, time: 0.388, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0414, loss_cls: 0.1804, acc: 93.2883, loss_bbox: 0.2278, loss_mask: 0.2280, loss: 0.7013 2023-11-13 20:45:27,035 - mmdet - INFO - Epoch [6][2600/7330] lr: 1.000e-04, eta: 5:11:45, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0414, loss_cls: 0.1770, acc: 93.4702, loss_bbox: 0.2238, loss_mask: 0.2247, loss: 0.6877 2023-11-13 20:45:46,285 - mmdet - INFO - Epoch [6][2650/7330] lr: 1.000e-04, eta: 5:11:26, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0413, loss_cls: 0.1751, acc: 93.4956, loss_bbox: 0.2205, loss_mask: 0.2235, loss: 0.6815 2023-11-13 20:46:05,147 - mmdet - INFO - Epoch [6][2700/7330] lr: 1.000e-04, eta: 5:11:06, time: 0.377, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0397, loss_cls: 0.1703, acc: 93.6541, loss_bbox: 0.2189, loss_mask: 0.2163, loss: 0.6654 2023-11-13 20:46:23,651 - mmdet - INFO - Epoch [6][2750/7330] lr: 1.000e-04, eta: 5:10:46, time: 0.370, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0377, loss_cls: 0.1698, acc: 93.6726, loss_bbox: 0.2162, loss_mask: 0.2226, loss: 0.6658 2023-11-13 20:46:42,613 - mmdet - INFO - Epoch [6][2800/7330] lr: 1.000e-04, eta: 5:10:27, time: 0.379, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0395, loss_cls: 0.1700, acc: 93.6409, loss_bbox: 0.2167, loss_mask: 0.2202, loss: 0.6659 2023-11-13 20:47:01,936 - mmdet - INFO - Epoch [6][2850/7330] lr: 1.000e-04, eta: 5:10:08, time: 0.386, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0388, loss_cls: 0.1714, acc: 93.6211, loss_bbox: 0.2129, loss_mask: 0.2202, loss: 0.6627 2023-11-13 20:47:20,870 - mmdet - INFO - Epoch [6][2900/7330] lr: 1.000e-04, eta: 5:09:48, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0387, loss_cls: 0.1746, acc: 93.5608, loss_bbox: 0.2170, loss_mask: 0.2202, loss: 0.6704 2023-11-13 20:47:39,798 - mmdet - INFO - Epoch [6][2950/7330] lr: 1.000e-04, eta: 5:09:29, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0397, loss_cls: 0.1678, acc: 93.8330, loss_bbox: 0.2138, loss_mask: 0.2209, loss: 0.6635 2023-11-13 20:47:58,545 - mmdet - INFO - Epoch [6][3000/7330] lr: 1.000e-04, eta: 5:09:09, time: 0.375, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0390, loss_cls: 0.1709, acc: 93.6370, loss_bbox: 0.2192, loss_mask: 0.2203, loss: 0.6691 2023-11-13 20:48:17,306 - mmdet - INFO - Epoch [6][3050/7330] lr: 1.000e-04, eta: 5:08:49, time: 0.375, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0390, loss_cls: 0.1772, acc: 93.4497, loss_bbox: 0.2225, loss_mask: 0.2220, loss: 0.6810 2023-11-13 20:48:35,982 - mmdet - INFO - Epoch [6][3100/7330] lr: 1.000e-04, eta: 5:08:30, time: 0.374, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0401, loss_cls: 0.1707, acc: 93.6980, loss_bbox: 0.2172, loss_mask: 0.2186, loss: 0.6650 2023-11-13 20:48:54,838 - mmdet - INFO - Epoch [6][3150/7330] lr: 1.000e-04, eta: 5:08:10, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0375, loss_cls: 0.1684, acc: 93.6021, loss_bbox: 0.2148, loss_mask: 0.2198, loss: 0.6592 2023-11-13 20:49:13,856 - mmdet - INFO - Epoch [6][3200/7330] lr: 1.000e-04, eta: 5:07:51, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0394, loss_cls: 0.1727, acc: 93.6660, loss_bbox: 0.2220, loss_mask: 0.2272, loss: 0.6840 2023-11-13 20:49:32,845 - mmdet - INFO - Epoch [6][3250/7330] lr: 1.000e-04, eta: 5:07:31, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0398, loss_cls: 0.1656, acc: 93.8120, loss_bbox: 0.2171, loss_mask: 0.2197, loss: 0.6626 2023-11-13 20:49:51,848 - mmdet - INFO - Epoch [6][3300/7330] lr: 1.000e-04, eta: 5:07:12, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0438, loss_cls: 0.1746, acc: 93.4949, loss_bbox: 0.2219, loss_mask: 0.2249, loss: 0.6869 2023-11-13 20:50:11,008 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:50:11,008 - mmdet - INFO - Epoch [6][3350/7330] lr: 1.000e-04, eta: 5:06:52, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0418, loss_cls: 0.1729, acc: 93.6484, loss_bbox: 0.2194, loss_mask: 0.2225, loss: 0.6771 2023-11-13 20:50:30,211 - mmdet - INFO - Epoch [6][3400/7330] lr: 1.000e-04, eta: 5:06:33, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0397, loss_cls: 0.1724, acc: 93.6414, loss_bbox: 0.2194, loss_mask: 0.2204, loss: 0.6708 2023-11-13 20:50:49,107 - mmdet - INFO - Epoch [6][3450/7330] lr: 1.000e-04, eta: 5:06:14, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0417, loss_cls: 0.1786, acc: 93.4028, loss_bbox: 0.2232, loss_mask: 0.2266, loss: 0.6921 2023-11-13 20:51:08,024 - mmdet - INFO - Epoch [6][3500/7330] lr: 1.000e-04, eta: 5:05:54, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0433, loss_cls: 0.1850, acc: 93.1021, loss_bbox: 0.2225, loss_mask: 0.2301, loss: 0.7035 2023-11-13 20:51:26,571 - mmdet - INFO - Epoch [6][3550/7330] lr: 1.000e-04, eta: 5:05:34, time: 0.371, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0374, loss_cls: 0.1619, acc: 94.0222, loss_bbox: 0.2040, loss_mask: 0.2164, loss: 0.6399 2023-11-13 20:51:45,392 - mmdet - INFO - Epoch [6][3600/7330] lr: 1.000e-04, eta: 5:05:15, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0387, loss_cls: 0.1700, acc: 93.7424, loss_bbox: 0.2121, loss_mask: 0.2166, loss: 0.6562 2023-11-13 20:52:04,506 - mmdet - INFO - Epoch [6][3650/7330] lr: 1.000e-04, eta: 5:04:55, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0409, loss_cls: 0.1787, acc: 93.3906, loss_bbox: 0.2265, loss_mask: 0.2246, loss: 0.6913 2023-11-13 20:52:23,122 - mmdet - INFO - Epoch [6][3700/7330] lr: 1.000e-04, eta: 5:04:35, time: 0.372, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0385, loss_cls: 0.1675, acc: 93.7778, loss_bbox: 0.2164, loss_mask: 0.2257, loss: 0.6673 2023-11-13 20:52:41,885 - mmdet - INFO - Epoch [6][3750/7330] lr: 1.000e-04, eta: 5:04:16, time: 0.375, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0401, loss_cls: 0.1748, acc: 93.4365, loss_bbox: 0.2195, loss_mask: 0.2228, loss: 0.6782 2023-11-13 20:53:00,456 - mmdet - INFO - Epoch [6][3800/7330] lr: 1.000e-04, eta: 5:03:56, time: 0.371, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0381, loss_cls: 0.1690, acc: 93.7090, loss_bbox: 0.2122, loss_mask: 0.2213, loss: 0.6597 2023-11-13 20:53:19,211 - mmdet - INFO - Epoch [6][3850/7330] lr: 1.000e-04, eta: 5:03:36, time: 0.375, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0402, loss_cls: 0.1680, acc: 93.7434, loss_bbox: 0.2092, loss_mask: 0.2230, loss: 0.6598 2023-11-13 20:53:38,390 - mmdet - INFO - Epoch [6][3900/7330] lr: 1.000e-04, eta: 5:03:17, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0373, loss_cls: 0.1669, acc: 93.7910, loss_bbox: 0.2143, loss_mask: 0.2232, loss: 0.6608 2023-11-13 20:53:57,635 - mmdet - INFO - Epoch [6][3950/7330] lr: 1.000e-04, eta: 5:02:58, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0414, loss_cls: 0.1743, acc: 93.5081, loss_bbox: 0.2223, loss_mask: 0.2275, loss: 0.6864 2023-11-13 20:54:16,479 - mmdet - INFO - Epoch [6][4000/7330] lr: 1.000e-04, eta: 5:02:38, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0396, loss_cls: 0.1709, acc: 93.7002, loss_bbox: 0.2125, loss_mask: 0.2200, loss: 0.6622 2023-11-13 20:54:35,283 - mmdet - INFO - Epoch [6][4050/7330] lr: 1.000e-04, eta: 5:02:18, time: 0.376, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0375, loss_cls: 0.1737, acc: 93.6072, loss_bbox: 0.2167, loss_mask: 0.2211, loss: 0.6687 2023-11-13 20:54:54,109 - mmdet - INFO - Epoch [6][4100/7330] lr: 1.000e-04, eta: 5:01:59, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0389, loss_cls: 0.1694, acc: 93.7634, loss_bbox: 0.2172, loss_mask: 0.2157, loss: 0.6620 2023-11-13 20:55:12,814 - mmdet - INFO - Epoch [6][4150/7330] lr: 1.000e-04, eta: 5:01:39, time: 0.374, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0403, loss_cls: 0.1736, acc: 93.4995, loss_bbox: 0.2192, loss_mask: 0.2281, loss: 0.6821 2023-11-13 20:55:31,733 - mmdet - INFO - Epoch [6][4200/7330] lr: 1.000e-04, eta: 5:01:20, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0404, loss_cls: 0.1810, acc: 93.1877, loss_bbox: 0.2258, loss_mask: 0.2272, loss: 0.6946 2023-11-13 20:55:50,719 - mmdet - INFO - Epoch [6][4250/7330] lr: 1.000e-04, eta: 5:01:00, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0393, loss_cls: 0.1591, acc: 94.0442, loss_bbox: 0.2044, loss_mask: 0.2169, loss: 0.6399 2023-11-13 20:56:10,051 - mmdet - INFO - Epoch [6][4300/7330] lr: 1.000e-04, eta: 5:00:41, time: 0.387, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0422, loss_cls: 0.1659, acc: 93.8855, loss_bbox: 0.2121, loss_mask: 0.2228, loss: 0.6632 2023-11-13 20:56:29,096 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 20:56:29,097 - mmdet - INFO - Epoch [6][4350/7330] lr: 1.000e-04, eta: 5:00:22, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0416, loss_cls: 0.1755, acc: 93.4800, loss_bbox: 0.2240, loss_mask: 0.2222, loss: 0.6862 2023-11-13 20:56:48,132 - mmdet - INFO - Epoch [6][4400/7330] lr: 1.000e-04, eta: 5:00:02, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0399, loss_cls: 0.1693, acc: 93.6907, loss_bbox: 0.2136, loss_mask: 0.2239, loss: 0.6666 2023-11-13 20:57:07,279 - mmdet - INFO - Epoch [6][4450/7330] lr: 1.000e-04, eta: 4:59:43, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0400, loss_cls: 0.1790, acc: 93.4058, loss_bbox: 0.2259, loss_mask: 0.2242, loss: 0.6885 2023-11-13 20:57:26,459 - mmdet - INFO - Epoch [6][4500/7330] lr: 1.000e-04, eta: 4:59:24, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0416, loss_cls: 0.1759, acc: 93.4329, loss_bbox: 0.2225, loss_mask: 0.2238, loss: 0.6855 2023-11-13 20:57:45,893 - mmdet - INFO - Epoch [6][4550/7330] lr: 1.000e-04, eta: 4:59:05, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0431, loss_cls: 0.1774, acc: 93.4297, loss_bbox: 0.2255, loss_mask: 0.2340, loss: 0.7020 2023-11-13 20:58:04,621 - mmdet - INFO - Epoch [6][4600/7330] lr: 1.000e-04, eta: 4:58:45, time: 0.375, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0386, loss_cls: 0.1645, acc: 93.9885, loss_bbox: 0.2083, loss_mask: 0.2202, loss: 0.6501 2023-11-13 20:58:23,939 - mmdet - INFO - Epoch [6][4650/7330] lr: 1.000e-04, eta: 4:58:26, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0425, loss_cls: 0.1801, acc: 93.2788, loss_bbox: 0.2299, loss_mask: 0.2267, loss: 0.7005 2023-11-13 20:58:42,810 - mmdet - INFO - Epoch [6][4700/7330] lr: 1.000e-04, eta: 4:58:07, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0386, loss_cls: 0.1685, acc: 93.7495, loss_bbox: 0.2139, loss_mask: 0.2225, loss: 0.6628 2023-11-13 20:59:01,843 - mmdet - INFO - Epoch [6][4750/7330] lr: 1.000e-04, eta: 4:57:47, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0422, loss_cls: 0.1807, acc: 93.4485, loss_bbox: 0.2261, loss_mask: 0.2280, loss: 0.6983 2023-11-13 20:59:21,033 - mmdet - INFO - Epoch [6][4800/7330] lr: 1.000e-04, eta: 4:57:28, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0419, loss_cls: 0.1800, acc: 93.2966, loss_bbox: 0.2226, loss_mask: 0.2229, loss: 0.6882 2023-11-13 20:59:40,078 - mmdet - INFO - Epoch [6][4850/7330] lr: 1.000e-04, eta: 4:57:09, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0405, loss_cls: 0.1751, acc: 93.4880, loss_bbox: 0.2203, loss_mask: 0.2258, loss: 0.6817 2023-11-13 20:59:59,322 - mmdet - INFO - Epoch [6][4900/7330] lr: 1.000e-04, eta: 4:56:50, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0431, loss_cls: 0.1748, acc: 93.5618, loss_bbox: 0.2193, loss_mask: 0.2254, loss: 0.6852 2023-11-13 21:00:18,604 - mmdet - INFO - Epoch [6][4950/7330] lr: 1.000e-04, eta: 4:56:31, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0426, loss_cls: 0.1819, acc: 93.2522, loss_bbox: 0.2248, loss_mask: 0.2241, loss: 0.6958 2023-11-13 21:00:37,434 - mmdet - INFO - Epoch [6][5000/7330] lr: 1.000e-04, eta: 4:56:11, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0380, loss_cls: 0.1666, acc: 93.8682, loss_bbox: 0.2158, loss_mask: 0.2295, loss: 0.6703 2023-11-13 21:00:56,293 - mmdet - INFO - Epoch [6][5050/7330] lr: 1.000e-04, eta: 4:55:52, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0384, loss_cls: 0.1601, acc: 94.0281, loss_bbox: 0.2046, loss_mask: 0.2213, loss: 0.6424 2023-11-13 21:01:15,524 - mmdet - INFO - Epoch [6][5100/7330] lr: 1.000e-04, eta: 4:55:32, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0428, loss_cls: 0.1746, acc: 93.5408, loss_bbox: 0.2204, loss_mask: 0.2270, loss: 0.6846 2023-11-13 21:01:34,598 - mmdet - INFO - Epoch [6][5150/7330] lr: 1.000e-04, eta: 4:55:13, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0407, loss_cls: 0.1660, acc: 93.7991, loss_bbox: 0.2145, loss_mask: 0.2230, loss: 0.6652 2023-11-13 21:01:53,469 - mmdet - INFO - Epoch [6][5200/7330] lr: 1.000e-04, eta: 4:54:54, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0394, loss_cls: 0.1737, acc: 93.3972, loss_bbox: 0.2225, loss_mask: 0.2260, loss: 0.6816 2023-11-13 21:02:12,541 - mmdet - INFO - Epoch [6][5250/7330] lr: 1.000e-04, eta: 4:54:34, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0388, loss_cls: 0.1654, acc: 93.8977, loss_bbox: 0.2138, loss_mask: 0.2203, loss: 0.6569 2023-11-13 21:02:31,579 - mmdet - INFO - Epoch [6][5300/7330] lr: 1.000e-04, eta: 4:54:15, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0404, loss_cls: 0.1766, acc: 93.4702, loss_bbox: 0.2236, loss_mask: 0.2258, loss: 0.6875 2023-11-13 21:02:50,615 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 21:02:50,616 - mmdet - INFO - Epoch [6][5350/7330] lr: 1.000e-04, eta: 4:53:56, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0422, loss_cls: 0.1821, acc: 93.1960, loss_bbox: 0.2290, loss_mask: 0.2264, loss: 0.7007 2023-11-13 21:03:09,779 - mmdet - INFO - Epoch [6][5400/7330] lr: 1.000e-04, eta: 4:53:36, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0402, loss_cls: 0.1763, acc: 93.5681, loss_bbox: 0.2217, loss_mask: 0.2263, loss: 0.6847 2023-11-13 21:03:29,222 - mmdet - INFO - Epoch [6][5450/7330] lr: 1.000e-04, eta: 4:53:17, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0408, loss_cls: 0.1770, acc: 93.3989, loss_bbox: 0.2248, loss_mask: 0.2241, loss: 0.6876 2023-11-13 21:03:47,987 - mmdet - INFO - Epoch [6][5500/7330] lr: 1.000e-04, eta: 4:52:58, time: 0.375, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0406, loss_cls: 0.1743, acc: 93.5225, loss_bbox: 0.2215, loss_mask: 0.2235, loss: 0.6805 2023-11-13 21:04:06,700 - mmdet - INFO - Epoch [6][5550/7330] lr: 1.000e-04, eta: 4:52:38, time: 0.374, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0391, loss_cls: 0.1739, acc: 93.4854, loss_bbox: 0.2191, loss_mask: 0.2248, loss: 0.6777 2023-11-13 21:04:25,762 - mmdet - INFO - Epoch [6][5600/7330] lr: 1.000e-04, eta: 4:52:19, time: 0.381, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0384, loss_cls: 0.1717, acc: 93.7661, loss_bbox: 0.2122, loss_mask: 0.2171, loss: 0.6586 2023-11-13 21:04:44,561 - mmdet - INFO - Epoch [6][5650/7330] lr: 1.000e-04, eta: 4:51:59, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0388, loss_cls: 0.1692, acc: 93.6973, loss_bbox: 0.2153, loss_mask: 0.2216, loss: 0.6636 2023-11-13 21:05:03,364 - mmdet - INFO - Epoch [6][5700/7330] lr: 1.000e-04, eta: 4:51:40, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0416, loss_cls: 0.1704, acc: 93.7295, loss_bbox: 0.2144, loss_mask: 0.2196, loss: 0.6659 2023-11-13 21:05:22,588 - mmdet - INFO - Epoch [6][5750/7330] lr: 1.000e-04, eta: 4:51:20, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0396, loss_cls: 0.1753, acc: 93.4717, loss_bbox: 0.2213, loss_mask: 0.2219, loss: 0.6780 2023-11-13 21:05:41,686 - mmdet - INFO - Epoch [6][5800/7330] lr: 1.000e-04, eta: 4:51:01, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0385, loss_cls: 0.1732, acc: 93.6338, loss_bbox: 0.2165, loss_mask: 0.2272, loss: 0.6756 2023-11-13 21:06:00,316 - mmdet - INFO - Epoch [6][5850/7330] lr: 1.000e-04, eta: 4:50:41, time: 0.373, data_time: 0.016, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0402, loss_cls: 0.1679, acc: 93.8418, loss_bbox: 0.2113, loss_mask: 0.2223, loss: 0.6632 2023-11-13 21:06:19,197 - mmdet - INFO - Epoch [6][5900/7330] lr: 1.000e-04, eta: 4:50:22, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0391, loss_cls: 0.1712, acc: 93.7549, loss_bbox: 0.2149, loss_mask: 0.2227, loss: 0.6687 2023-11-13 21:06:38,410 - mmdet - INFO - Epoch [6][5950/7330] lr: 1.000e-04, eta: 4:50:03, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0411, loss_cls: 0.1788, acc: 93.5491, loss_bbox: 0.2192, loss_mask: 0.2217, loss: 0.6827 2023-11-13 21:06:57,979 - mmdet - INFO - Epoch [6][6000/7330] lr: 1.000e-04, eta: 4:49:44, time: 0.391, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0387, loss_cls: 0.1716, acc: 93.5925, loss_bbox: 0.2171, loss_mask: 0.2233, loss: 0.6712 2023-11-13 21:07:16,843 - mmdet - INFO - Epoch [6][6050/7330] lr: 1.000e-04, eta: 4:49:24, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0400, loss_cls: 0.1652, acc: 93.9360, loss_bbox: 0.2100, loss_mask: 0.2259, loss: 0.6628 2023-11-13 21:07:36,251 - mmdet - INFO - Epoch [6][6100/7330] lr: 1.000e-04, eta: 4:49:05, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0413, loss_cls: 0.1734, acc: 93.6218, loss_bbox: 0.2193, loss_mask: 0.2298, loss: 0.6858 2023-11-13 21:07:55,074 - mmdet - INFO - Epoch [6][6150/7330] lr: 1.000e-04, eta: 4:48:46, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0367, loss_cls: 0.1649, acc: 93.8147, loss_bbox: 0.2104, loss_mask: 0.2196, loss: 0.6517 2023-11-13 21:08:14,490 - mmdet - INFO - Epoch [6][6200/7330] lr: 1.000e-04, eta: 4:48:27, time: 0.388, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0420, loss_cls: 0.1783, acc: 93.4084, loss_bbox: 0.2277, loss_mask: 0.2280, loss: 0.6996 2023-11-13 21:08:33,143 - mmdet - INFO - Epoch [6][6250/7330] lr: 1.000e-04, eta: 4:48:07, time: 0.373, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0391, loss_cls: 0.1721, acc: 93.6929, loss_bbox: 0.2142, loss_mask: 0.2234, loss: 0.6674 2023-11-13 21:08:52,062 - mmdet - INFO - Epoch [6][6300/7330] lr: 1.000e-04, eta: 4:47:48, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0392, loss_cls: 0.1673, acc: 93.7483, loss_bbox: 0.2130, loss_mask: 0.2256, loss: 0.6659 2023-11-13 21:09:11,292 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 21:09:11,292 - mmdet - INFO - Epoch [6][6350/7330] lr: 1.000e-04, eta: 4:47:29, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0405, loss_cls: 0.1738, acc: 93.5884, loss_bbox: 0.2190, loss_mask: 0.2255, loss: 0.6818 2023-11-13 21:09:30,632 - mmdet - INFO - Epoch [6][6400/7330] lr: 1.000e-04, eta: 4:47:10, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0416, loss_cls: 0.1723, acc: 93.6091, loss_bbox: 0.2180, loss_mask: 0.2236, loss: 0.6761 2023-11-13 21:09:49,573 - mmdet - INFO - Epoch [6][6450/7330] lr: 1.000e-04, eta: 4:46:50, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0403, loss_cls: 0.1741, acc: 93.5737, loss_bbox: 0.2202, loss_mask: 0.2248, loss: 0.6796 2023-11-13 21:10:08,910 - mmdet - INFO - Epoch [6][6500/7330] lr: 1.000e-04, eta: 4:46:31, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0411, loss_cls: 0.1741, acc: 93.6035, loss_bbox: 0.2213, loss_mask: 0.2256, loss: 0.6856 2023-11-13 21:10:27,917 - mmdet - INFO - Epoch [6][6550/7330] lr: 1.000e-04, eta: 4:46:12, time: 0.380, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0383, loss_cls: 0.1690, acc: 93.7268, loss_bbox: 0.2148, loss_mask: 0.2212, loss: 0.6638 2023-11-13 21:10:46,873 - mmdet - INFO - Epoch [6][6600/7330] lr: 1.000e-04, eta: 4:45:52, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0380, loss_cls: 0.1640, acc: 93.9248, loss_bbox: 0.2073, loss_mask: 0.2152, loss: 0.6460 2023-11-13 21:11:05,861 - mmdet - INFO - Epoch [6][6650/7330] lr: 1.000e-04, eta: 4:45:33, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0385, loss_cls: 0.1669, acc: 93.7964, loss_bbox: 0.2172, loss_mask: 0.2224, loss: 0.6640 2023-11-13 21:11:24,650 - mmdet - INFO - Epoch [6][6700/7330] lr: 1.000e-04, eta: 4:45:13, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0374, loss_cls: 0.1699, acc: 93.7056, loss_bbox: 0.2124, loss_mask: 0.2185, loss: 0.6575 2023-11-13 21:11:43,376 - mmdet - INFO - Epoch [6][6750/7330] lr: 1.000e-04, eta: 4:44:54, time: 0.374, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0371, loss_cls: 0.1666, acc: 93.7820, loss_bbox: 0.2083, loss_mask: 0.2236, loss: 0.6555 2023-11-13 21:12:02,566 - mmdet - INFO - Epoch [6][6800/7330] lr: 1.000e-04, eta: 4:44:35, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0405, loss_cls: 0.1755, acc: 93.5940, loss_bbox: 0.2198, loss_mask: 0.2263, loss: 0.6831 2023-11-13 21:12:21,679 - mmdet - INFO - Epoch [6][6850/7330] lr: 1.000e-04, eta: 4:44:15, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0415, loss_cls: 0.1790, acc: 93.5078, loss_bbox: 0.2238, loss_mask: 0.2271, loss: 0.6930 2023-11-13 21:12:40,957 - mmdet - INFO - Epoch [6][6900/7330] lr: 1.000e-04, eta: 4:43:56, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0404, loss_cls: 0.1800, acc: 93.3015, loss_bbox: 0.2230, loss_mask: 0.2291, loss: 0.6933 2023-11-13 21:12:59,781 - mmdet - INFO - Epoch [6][6950/7330] lr: 1.000e-04, eta: 4:43:37, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0390, loss_cls: 0.1704, acc: 93.7625, loss_bbox: 0.2126, loss_mask: 0.2166, loss: 0.6584 2023-11-13 21:13:18,669 - mmdet - INFO - Epoch [6][7000/7330] lr: 1.000e-04, eta: 4:43:17, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0389, loss_cls: 0.1663, acc: 93.7671, loss_bbox: 0.2167, loss_mask: 0.2240, loss: 0.6661 2023-11-13 21:13:37,407 - mmdet - INFO - Epoch [6][7050/7330] lr: 1.000e-04, eta: 4:42:58, time: 0.375, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0392, loss_cls: 0.1711, acc: 93.7019, loss_bbox: 0.2130, loss_mask: 0.2184, loss: 0.6607 2023-11-13 21:13:56,512 - mmdet - INFO - Epoch [6][7100/7330] lr: 1.000e-04, eta: 4:42:38, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0394, loss_cls: 0.1717, acc: 93.6648, loss_bbox: 0.2182, loss_mask: 0.2249, loss: 0.6745 2023-11-13 21:14:15,244 - mmdet - INFO - Epoch [6][7150/7330] lr: 1.000e-04, eta: 4:42:19, time: 0.375, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0373, loss_cls: 0.1721, acc: 93.7695, loss_bbox: 0.2117, loss_mask: 0.2266, loss: 0.6666 2023-11-13 21:14:34,274 - mmdet - INFO - Epoch [6][7200/7330] lr: 1.000e-04, eta: 4:41:59, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0396, loss_cls: 0.1778, acc: 93.4775, loss_bbox: 0.2210, loss_mask: 0.2247, loss: 0.6833 2023-11-13 21:14:53,387 - mmdet - INFO - Epoch [6][7250/7330] lr: 1.000e-04, eta: 4:41:40, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0396, loss_cls: 0.1783, acc: 93.4514, loss_bbox: 0.2234, loss_mask: 0.2285, loss: 0.6905 2023-11-13 21:15:12,301 - mmdet - INFO - Epoch [6][7300/7330] lr: 1.000e-04, eta: 4:41:21, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0374, loss_cls: 0.1688, acc: 93.6982, loss_bbox: 0.2117, loss_mask: 0.2220, loss: 0.6611 2023-11-13 21:15:24,219 - mmdet - INFO - Saving checkpoint at 6 epochs 2023-11-13 21:16:14,059 - mmdet - INFO - Evaluating bbox... 2023-11-13 21:16:42,644 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.462 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.686 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.510 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 ] = 0.507 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.589 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.589 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.589 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.414 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.634 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.742 2023-11-13 21:16:42,646 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.573 | bicycle | 0.355 | car | 0.468 | | motorcycle | 0.467 | airplane | 0.668 | bus | 0.663 | | train | 0.639 | truck | 0.419 | boat | 0.337 | | traffic light | 0.303 | fire hydrant | 0.703 | stop sign | 0.688 | | parking meter | 0.542 | bench | 0.296 | bird | 0.406 | | cat | 0.730 | dog | 0.674 | horse | 0.630 | | sheep | 0.572 | cow | 0.621 | elephant | 0.679 | | bear | 0.755 | zebra | 0.686 | giraffe | 0.696 | | backpack | 0.210 | umbrella | 0.449 | handbag | 0.198 | | tie | 0.366 | suitcase | 0.448 | frisbee | 0.688 | | skis | 0.285 | snowboard | 0.422 | sports ball | 0.445 | | kite | 0.469 | baseball bat | 0.362 | baseball glove | 0.420 | | skateboard | 0.552 | surfboard | 0.453 | tennis racket | 0.521 | | bottle | 0.453 | wine glass | 0.402 | cup | 0.494 | | fork | 0.444 | knife | 0.273 | spoon | 0.273 | | bowl | 0.467 | banana | 0.294 | apple | 0.277 | | sandwich | 0.421 | orange | 0.353 | broccoli | 0.254 | | carrot | 0.222 | hot dog | 0.446 | pizza | 0.551 | | donut | 0.511 | cake | 0.439 | chair | 0.353 | | couch | 0.444 | potted plant | 0.324 | bed | 0.436 | | dining table | 0.311 | toilet | 0.613 | tv | 0.625 | | laptop | 0.660 | mouse | 0.622 | remote | 0.397 | | keyboard | 0.537 | cell phone | 0.403 | microwave | 0.615 | | oven | 0.376 | toaster | 0.379 | sink | 0.414 | | refrigerator | 0.618 | book | 0.195 | clock | 0.502 | | vase | 0.410 | scissors | 0.364 | teddy bear | 0.516 | | hair drier | 0.149 | toothbrush | 0.276 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:16:42,647 - mmdet - INFO - Evaluating segm... 2023-11-13 21:17:16,695 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.422 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.656 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.458 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.455 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.613 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.368 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.588 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.705 2023-11-13 21:17:16,697 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.500 | bicycle | 0.206 | car | 0.439 | | motorcycle | 0.382 | airplane | 0.544 | bus | 0.667 | | train | 0.645 | truck | 0.396 | boat | 0.304 | | traffic light | 0.293 | fire hydrant | 0.704 | stop sign | 0.678 | | parking meter | 0.549 | bench | 0.224 | bird | 0.342 | | cat | 0.727 | dog | 0.635 | horse | 0.462 | | sheep | 0.517 | cow | 0.537 | elephant | 0.628 | | bear | 0.760 | zebra | 0.602 | giraffe | 0.540 | | backpack | 0.221 | umbrella | 0.509 | handbag | 0.195 | | tie | 0.357 | suitcase | 0.464 | frisbee | 0.671 | | skis | 0.064 | snowboard | 0.298 | sports ball | 0.448 | | kite | 0.337 | baseball bat | 0.285 | baseball glove | 0.455 | | skateboard | 0.365 | surfboard | 0.383 | tennis racket | 0.570 | | bottle | 0.438 | wine glass | 0.362 | cup | 0.500 | | fork | 0.232 | knife | 0.194 | spoon | 0.182 | | bowl | 0.442 | banana | 0.249 | apple | 0.271 | | sandwich | 0.444 | orange | 0.356 | broccoli | 0.241 | | carrot | 0.204 | hot dog | 0.375 | pizza | 0.529 | | donut | 0.526 | cake | 0.445 | chair | 0.261 | | couch | 0.368 | potted plant | 0.265 | bed | 0.356 | | dining table | 0.179 | toilet | 0.622 | tv | 0.655 | | laptop | 0.655 | mouse | 0.632 | remote | 0.369 | | keyboard | 0.540 | cell phone | 0.393 | microwave | 0.666 | | oven | 0.346 | toaster | 0.401 | sink | 0.393 | | refrigerator | 0.632 | book | 0.149 | clock | 0.514 | | vase | 0.406 | scissors | 0.274 | teddy bear | 0.498 | | hair drier | 0.085 | toothbrush | 0.199 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:17:17,137 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_5.pth was removed 2023-11-13 21:17:19,263 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_6.pth. 2023-11-13 21:17:19,264 - mmdet - INFO - Best bbox_mAP is 0.4621 at 6 epoch. 2023-11-13 21:17:19,264 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 21:17:19,264 - mmdet - INFO - Epoch(val) [6][625] bbox_mAP: 0.4621, bbox_mAP_50: 0.6859, bbox_mAP_75: 0.5103, bbox_mAP_s: 0.3039, bbox_mAP_m: 0.5066, bbox_mAP_l: 0.6062, bbox_mAP_copypaste: 0.4621 0.6859 0.5103 0.3039 0.5066 0.6062, segm_mAP: 0.4219, segm_mAP_50: 0.6565, segm_mAP_75: 0.4578, segm_mAP_s: 0.2337, segm_mAP_m: 0.4550, segm_mAP_l: 0.6134, segm_mAP_copypaste: 0.4219 0.6565 0.4578 0.2337 0.4550 0.6134 2023-11-13 21:17:41,678 - mmdet - INFO - Epoch [7][50/7330] lr: 1.000e-04, eta: 4:40:42, time: 0.448, data_time: 0.091, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0376, loss_cls: 0.1647, acc: 93.8936, loss_bbox: 0.2122, loss_mask: 0.2166, loss: 0.6493 2023-11-13 21:18:01,216 - mmdet - INFO - Epoch [7][100/7330] lr: 1.000e-04, eta: 4:40:23, time: 0.391, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0370, loss_cls: 0.1615, acc: 93.9888, loss_bbox: 0.2078, loss_mask: 0.2158, loss: 0.6390 2023-11-13 21:18:21,250 - mmdet - INFO - Epoch [7][150/7330] lr: 1.000e-04, eta: 4:40:05, time: 0.401, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0415, loss_cls: 0.1680, acc: 93.6606, loss_bbox: 0.2201, loss_mask: 0.2221, loss: 0.6711 2023-11-13 21:18:40,675 - mmdet - INFO - Epoch [7][200/7330] lr: 1.000e-04, eta: 4:39:46, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0376, loss_cls: 0.1607, acc: 93.9495, loss_bbox: 0.2118, loss_mask: 0.2183, loss: 0.6468 2023-11-13 21:19:00,159 - mmdet - INFO - Epoch [7][250/7330] lr: 1.000e-04, eta: 4:39:27, time: 0.390, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0391, loss_cls: 0.1680, acc: 93.6511, loss_bbox: 0.2179, loss_mask: 0.2170, loss: 0.6606 2023-11-13 21:19:19,377 - mmdet - INFO - Epoch [7][300/7330] lr: 1.000e-04, eta: 4:39:08, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0380, loss_cls: 0.1632, acc: 93.8589, loss_bbox: 0.2108, loss_mask: 0.2172, loss: 0.6470 2023-11-13 21:19:38,651 - mmdet - INFO - Epoch [7][350/7330] lr: 1.000e-04, eta: 4:38:49, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0366, loss_cls: 0.1662, acc: 93.8674, loss_bbox: 0.2155, loss_mask: 0.2163, loss: 0.6523 2023-11-13 21:19:58,026 - mmdet - INFO - Epoch [7][400/7330] lr: 1.000e-04, eta: 4:38:30, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0404, loss_cls: 0.1715, acc: 93.5491, loss_bbox: 0.2223, loss_mask: 0.2167, loss: 0.6708 2023-11-13 21:20:17,302 - mmdet - INFO - Epoch [7][450/7330] lr: 1.000e-04, eta: 4:38:11, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0374, loss_cls: 0.1598, acc: 93.9900, loss_bbox: 0.2075, loss_mask: 0.2138, loss: 0.6365 2023-11-13 21:20:36,744 - mmdet - INFO - Epoch [7][500/7330] lr: 1.000e-04, eta: 4:37:52, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0387, loss_cls: 0.1626, acc: 93.9111, loss_bbox: 0.2115, loss_mask: 0.2145, loss: 0.6463 2023-11-13 21:20:56,740 - mmdet - INFO - Epoch [7][550/7330] lr: 1.000e-04, eta: 4:37:33, time: 0.400, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0407, loss_cls: 0.1698, acc: 93.6772, loss_bbox: 0.2248, loss_mask: 0.2178, loss: 0.6724 2023-11-13 21:21:16,204 - mmdet - INFO - Epoch [7][600/7330] lr: 1.000e-04, eta: 4:37:14, time: 0.389, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0397, loss_cls: 0.1643, acc: 93.8279, loss_bbox: 0.2154, loss_mask: 0.2165, loss: 0.6540 2023-11-13 21:21:35,947 - mmdet - INFO - Epoch [7][650/7330] lr: 1.000e-04, eta: 4:36:56, time: 0.395, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0391, loss_cls: 0.1679, acc: 93.7429, loss_bbox: 0.2194, loss_mask: 0.2232, loss: 0.6714 2023-11-13 21:21:55,322 - mmdet - INFO - Epoch [7][700/7330] lr: 1.000e-04, eta: 4:36:37, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0398, loss_cls: 0.1620, acc: 93.9106, loss_bbox: 0.2115, loss_mask: 0.2206, loss: 0.6514 2023-11-13 21:22:15,039 - mmdet - INFO - Epoch [7][750/7330] lr: 1.000e-04, eta: 4:36:18, time: 0.394, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0391, loss_cls: 0.1687, acc: 93.7197, loss_bbox: 0.2167, loss_mask: 0.2261, loss: 0.6708 2023-11-13 21:22:34,583 - mmdet - INFO - Epoch [7][800/7330] lr: 1.000e-04, eta: 4:35:59, time: 0.391, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0400, loss_cls: 0.1631, acc: 93.7739, loss_bbox: 0.2146, loss_mask: 0.2199, loss: 0.6558 2023-11-13 21:22:53,890 - mmdet - INFO - Epoch [7][850/7330] lr: 1.000e-04, eta: 4:35:40, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0414, loss_cls: 0.1682, acc: 93.5715, loss_bbox: 0.2153, loss_mask: 0.2213, loss: 0.6662 2023-11-13 21:23:13,405 - mmdet - INFO - Epoch [7][900/7330] lr: 1.000e-04, eta: 4:35:21, time: 0.390, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0393, loss_cls: 0.1716, acc: 93.6245, loss_bbox: 0.2184, loss_mask: 0.2208, loss: 0.6691 2023-11-13 21:23:32,673 - mmdet - INFO - Epoch [7][950/7330] lr: 1.000e-04, eta: 4:35:02, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0395, loss_cls: 0.1615, acc: 93.9434, loss_bbox: 0.2119, loss_mask: 0.2186, loss: 0.6497 2023-11-13 21:23:51,841 - mmdet - INFO - Epoch [7][1000/7330] lr: 1.000e-04, eta: 4:34:43, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0366, loss_cls: 0.1550, acc: 94.1841, loss_bbox: 0.2040, loss_mask: 0.2204, loss: 0.6326 2023-11-13 21:24:10,868 - mmdet - INFO - Epoch [7][1050/7330] lr: 1.000e-04, eta: 4:34:24, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0346, loss_cls: 0.1616, acc: 94.0806, loss_bbox: 0.2029, loss_mask: 0.2146, loss: 0.6313 2023-11-13 21:24:29,868 - mmdet - INFO - Epoch [7][1100/7330] lr: 1.000e-04, eta: 4:34:04, time: 0.380, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0387, loss_cls: 0.1612, acc: 93.9395, loss_bbox: 0.2068, loss_mask: 0.2175, loss: 0.6428 2023-11-13 21:24:49,029 - mmdet - INFO - Epoch [7][1150/7330] lr: 1.000e-04, eta: 4:33:45, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0380, loss_cls: 0.1603, acc: 94.0095, loss_bbox: 0.2073, loss_mask: 0.2134, loss: 0.6384 2023-11-13 21:25:08,660 - mmdet - INFO - Epoch [7][1200/7330] lr: 1.000e-04, eta: 4:33:27, time: 0.393, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0396, loss_cls: 0.1727, acc: 93.5269, loss_bbox: 0.2187, loss_mask: 0.2198, loss: 0.6701 2023-11-13 21:25:28,041 - mmdet - INFO - Epoch [7][1250/7330] lr: 1.000e-04, eta: 4:33:08, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0358, loss_cls: 0.1543, acc: 94.2522, loss_bbox: 0.2011, loss_mask: 0.2107, loss: 0.6185 2023-11-13 21:25:47,097 - mmdet - INFO - Epoch [7][1300/7330] lr: 1.000e-04, eta: 4:32:48, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0389, loss_cls: 0.1638, acc: 93.9270, loss_bbox: 0.2102, loss_mask: 0.2219, loss: 0.6546 2023-11-13 21:26:06,386 - mmdet - INFO - Epoch [7][1350/7330] lr: 1.000e-04, eta: 4:32:29, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0396, loss_cls: 0.1650, acc: 93.8682, loss_bbox: 0.2122, loss_mask: 0.2174, loss: 0.6537 2023-11-13 21:26:25,044 - mmdet - INFO - Epoch [7][1400/7330] lr: 1.000e-04, eta: 4:32:10, time: 0.373, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0364, loss_cls: 0.1556, acc: 94.1941, loss_bbox: 0.2029, loss_mask: 0.2141, loss: 0.6266 2023-11-13 21:26:44,386 - mmdet - INFO - Epoch [7][1450/7330] lr: 1.000e-04, eta: 4:31:51, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0402, loss_cls: 0.1688, acc: 93.7012, loss_bbox: 0.2180, loss_mask: 0.2206, loss: 0.6661 2023-11-13 21:27:03,297 - mmdet - INFO - Epoch [7][1500/7330] lr: 1.000e-04, eta: 4:31:31, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0384, loss_cls: 0.1612, acc: 93.8809, loss_bbox: 0.2200, loss_mask: 0.2209, loss: 0.6578 2023-11-13 21:27:22,070 - mmdet - INFO - Epoch [7][1550/7330] lr: 1.000e-04, eta: 4:31:12, time: 0.375, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0355, loss_cls: 0.1491, acc: 94.4143, loss_bbox: 0.1965, loss_mask: 0.2122, loss: 0.6096 2023-11-13 21:27:41,607 - mmdet - INFO - Epoch [7][1600/7330] lr: 1.000e-04, eta: 4:30:53, time: 0.391, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0407, loss_cls: 0.1690, acc: 93.6709, loss_bbox: 0.2186, loss_mask: 0.2262, loss: 0.6753 2023-11-13 21:28:01,203 - mmdet - INFO - Epoch [7][1650/7330] lr: 1.000e-04, eta: 4:30:34, time: 0.392, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0391, loss_cls: 0.1713, acc: 93.6182, loss_bbox: 0.2176, loss_mask: 0.2199, loss: 0.6669 2023-11-13 21:28:20,445 - mmdet - INFO - Epoch [7][1700/7330] lr: 1.000e-04, eta: 4:30:15, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0391, loss_cls: 0.1680, acc: 93.7610, loss_bbox: 0.2186, loss_mask: 0.2149, loss: 0.6601 2023-11-13 21:28:39,789 - mmdet - INFO - Epoch [7][1750/7330] lr: 1.000e-04, eta: 4:29:56, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1692, acc: 93.6582, loss_bbox: 0.2139, loss_mask: 0.2195, loss: 0.6603 2023-11-13 21:28:59,005 - mmdet - INFO - Epoch [7][1800/7330] lr: 1.000e-04, eta: 4:29:37, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1690, acc: 93.6274, loss_bbox: 0.2148, loss_mask: 0.2225, loss: 0.6641 2023-11-13 21:29:18,334 - mmdet - INFO - Epoch [7][1850/7330] lr: 1.000e-04, eta: 4:29:18, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0377, loss_cls: 0.1665, acc: 93.9543, loss_bbox: 0.2047, loss_mask: 0.2201, loss: 0.6475 2023-11-13 21:29:37,692 - mmdet - INFO - Epoch [7][1900/7330] lr: 1.000e-04, eta: 4:28:59, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0373, loss_cls: 0.1673, acc: 93.7700, loss_bbox: 0.2101, loss_mask: 0.2174, loss: 0.6523 2023-11-13 21:29:57,016 - mmdet - INFO - Epoch [7][1950/7330] lr: 1.000e-04, eta: 4:28:40, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0393, loss_cls: 0.1668, acc: 93.8169, loss_bbox: 0.2172, loss_mask: 0.2235, loss: 0.6659 2023-11-13 21:30:16,145 - mmdet - INFO - Epoch [7][2000/7330] lr: 1.000e-04, eta: 4:28:20, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0382, loss_cls: 0.1650, acc: 93.7676, loss_bbox: 0.2096, loss_mask: 0.2181, loss: 0.6494 2023-11-13 21:30:35,160 - mmdet - INFO - Epoch [7][2050/7330] lr: 1.000e-04, eta: 4:28:01, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0382, loss_cls: 0.1607, acc: 93.9521, loss_bbox: 0.2064, loss_mask: 0.2148, loss: 0.6377 2023-11-13 21:30:54,189 - mmdet - INFO - Epoch [7][2100/7330] lr: 1.000e-04, eta: 4:27:42, time: 0.381, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0379, loss_cls: 0.1585, acc: 94.0215, loss_bbox: 0.2046, loss_mask: 0.2173, loss: 0.6366 2023-11-13 21:31:13,311 - mmdet - INFO - Epoch [7][2150/7330] lr: 1.000e-04, eta: 4:27:22, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0369, loss_cls: 0.1587, acc: 93.9854, loss_bbox: 0.2024, loss_mask: 0.2155, loss: 0.6326 2023-11-13 21:31:32,155 - mmdet - INFO - Epoch [7][2200/7330] lr: 1.000e-04, eta: 4:27:03, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0387, loss_cls: 0.1592, acc: 94.0781, loss_bbox: 0.2058, loss_mask: 0.2220, loss: 0.6424 2023-11-13 21:31:51,687 - mmdet - INFO - Epoch [7][2250/7330] lr: 1.000e-04, eta: 4:26:44, time: 0.391, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0405, loss_cls: 0.1714, acc: 93.6458, loss_bbox: 0.2176, loss_mask: 0.2219, loss: 0.6704 2023-11-13 21:32:11,086 - mmdet - INFO - Epoch [7][2300/7330] lr: 1.000e-04, eta: 4:26:25, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0392, loss_cls: 0.1616, acc: 93.9343, loss_bbox: 0.2112, loss_mask: 0.2259, loss: 0.6569 2023-11-13 21:32:30,149 - mmdet - INFO - Epoch [7][2350/7330] lr: 1.000e-04, eta: 4:26:06, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0379, loss_cls: 0.1592, acc: 94.0632, loss_bbox: 0.2043, loss_mask: 0.2173, loss: 0.6365 2023-11-13 21:32:49,339 - mmdet - INFO - Epoch [7][2400/7330] lr: 1.000e-04, eta: 4:25:47, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0423, loss_cls: 0.1774, acc: 93.4253, loss_bbox: 0.2216, loss_mask: 0.2246, loss: 0.6861 2023-11-13 21:33:08,501 - mmdet - INFO - Epoch [7][2450/7330] lr: 1.000e-04, eta: 4:25:28, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0414, loss_cls: 0.1700, acc: 93.5986, loss_bbox: 0.2194, loss_mask: 0.2216, loss: 0.6719 2023-11-13 21:33:27,686 - mmdet - INFO - Epoch [7][2500/7330] lr: 1.000e-04, eta: 4:25:08, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0400, loss_cls: 0.1668, acc: 93.7122, loss_bbox: 0.2128, loss_mask: 0.2226, loss: 0.6615 2023-11-13 21:33:47,021 - mmdet - INFO - Epoch [7][2550/7330] lr: 1.000e-04, eta: 4:24:49, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0385, loss_cls: 0.1629, acc: 94.0139, loss_bbox: 0.2081, loss_mask: 0.2176, loss: 0.6457 2023-11-13 21:34:06,407 - mmdet - INFO - Epoch [7][2600/7330] lr: 1.000e-04, eta: 4:24:30, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1636, acc: 93.9421, loss_bbox: 0.2089, loss_mask: 0.2166, loss: 0.6470 2023-11-13 21:34:25,760 - mmdet - INFO - Epoch [7][2650/7330] lr: 1.000e-04, eta: 4:24:11, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0380, loss_cls: 0.1693, acc: 93.6892, loss_bbox: 0.2175, loss_mask: 0.2214, loss: 0.6659 2023-11-13 21:34:44,849 - mmdet - INFO - Epoch [7][2700/7330] lr: 1.000e-04, eta: 4:23:52, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0430, loss_cls: 0.1729, acc: 93.4922, loss_bbox: 0.2246, loss_mask: 0.2244, loss: 0.6852 2023-11-13 21:35:04,060 - mmdet - INFO - Epoch [7][2750/7330] lr: 1.000e-04, eta: 4:23:33, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0396, loss_cls: 0.1739, acc: 93.4956, loss_bbox: 0.2184, loss_mask: 0.2233, loss: 0.6744 2023-11-13 21:35:22,804 - mmdet - INFO - Epoch [7][2800/7330] lr: 1.000e-04, eta: 4:23:13, time: 0.375, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0380, loss_cls: 0.1643, acc: 93.9006, loss_bbox: 0.2062, loss_mask: 0.2213, loss: 0.6474 2023-11-13 21:35:41,803 - mmdet - INFO - Epoch [7][2850/7330] lr: 1.000e-04, eta: 4:22:54, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0400, loss_cls: 0.1689, acc: 93.6702, loss_bbox: 0.2134, loss_mask: 0.2227, loss: 0.6640 2023-11-13 21:36:01,326 - mmdet - INFO - Epoch [7][2900/7330] lr: 1.000e-04, eta: 4:22:35, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0384, loss_cls: 0.1648, acc: 93.8679, loss_bbox: 0.2096, loss_mask: 0.2175, loss: 0.6494 2023-11-13 21:36:20,476 - mmdet - INFO - Epoch [7][2950/7330] lr: 1.000e-04, eta: 4:22:16, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0390, loss_cls: 0.1646, acc: 93.7749, loss_bbox: 0.2147, loss_mask: 0.2223, loss: 0.6597 2023-11-13 21:36:39,783 - mmdet - INFO - Epoch [7][3000/7330] lr: 1.000e-04, eta: 4:21:57, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0402, loss_cls: 0.1660, acc: 93.7991, loss_bbox: 0.2147, loss_mask: 0.2218, loss: 0.6634 2023-11-13 21:36:58,664 - mmdet - INFO - Epoch [7][3050/7330] lr: 1.000e-04, eta: 4:21:37, time: 0.378, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0382, loss_cls: 0.1579, acc: 94.0942, loss_bbox: 0.2049, loss_mask: 0.2188, loss: 0.6380 2023-11-13 21:37:18,023 - mmdet - INFO - Epoch [7][3100/7330] lr: 1.000e-04, eta: 4:21:18, time: 0.387, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0414, loss_cls: 0.1642, acc: 93.8699, loss_bbox: 0.2165, loss_mask: 0.2216, loss: 0.6628 2023-11-13 21:37:37,088 - mmdet - INFO - Epoch [7][3150/7330] lr: 1.000e-04, eta: 4:20:59, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0381, loss_cls: 0.1597, acc: 93.9392, loss_bbox: 0.2089, loss_mask: 0.2158, loss: 0.6399 2023-11-13 21:37:56,066 - mmdet - INFO - Epoch [7][3200/7330] lr: 1.000e-04, eta: 4:20:40, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0368, loss_cls: 0.1593, acc: 94.0491, loss_bbox: 0.2033, loss_mask: 0.2177, loss: 0.6360 2023-11-13 21:38:15,185 - mmdet - INFO - Epoch [7][3250/7330] lr: 1.000e-04, eta: 4:20:21, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0395, loss_cls: 0.1657, acc: 93.7842, loss_bbox: 0.2157, loss_mask: 0.2221, loss: 0.6632 2023-11-13 21:38:34,324 - mmdet - INFO - Epoch [7][3300/7330] lr: 1.000e-04, eta: 4:20:01, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0362, loss_cls: 0.1590, acc: 94.0371, loss_bbox: 0.2048, loss_mask: 0.2209, loss: 0.6376 2023-11-13 21:38:53,877 - mmdet - INFO - Epoch [7][3350/7330] lr: 1.000e-04, eta: 4:19:43, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0405, loss_cls: 0.1718, acc: 93.6592, loss_bbox: 0.2208, loss_mask: 0.2254, loss: 0.6786 2023-11-13 21:39:13,346 - mmdet - INFO - Epoch [7][3400/7330] lr: 1.000e-04, eta: 4:19:24, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0409, loss_cls: 0.1667, acc: 93.7346, loss_bbox: 0.2147, loss_mask: 0.2208, loss: 0.6627 2023-11-13 21:39:32,015 - mmdet - INFO - Epoch [7][3450/7330] lr: 1.000e-04, eta: 4:19:04, time: 0.373, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0363, loss_cls: 0.1552, acc: 94.2041, loss_bbox: 0.2007, loss_mask: 0.2144, loss: 0.6236 2023-11-13 21:39:51,190 - mmdet - INFO - Epoch [7][3500/7330] lr: 1.000e-04, eta: 4:18:45, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0384, loss_cls: 0.1652, acc: 93.9185, loss_bbox: 0.2106, loss_mask: 0.2206, loss: 0.6541 2023-11-13 21:40:10,252 - mmdet - INFO - Epoch [7][3550/7330] lr: 1.000e-04, eta: 4:18:26, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0388, loss_cls: 0.1714, acc: 93.6116, loss_bbox: 0.2191, loss_mask: 0.2214, loss: 0.6699 2023-11-13 21:40:29,449 - mmdet - INFO - Epoch [7][3600/7330] lr: 1.000e-04, eta: 4:18:06, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0394, loss_cls: 0.1645, acc: 93.8860, loss_bbox: 0.2112, loss_mask: 0.2248, loss: 0.6595 2023-11-13 21:40:48,778 - mmdet - INFO - Epoch [7][3650/7330] lr: 1.000e-04, eta: 4:17:47, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0391, loss_cls: 0.1627, acc: 93.9290, loss_bbox: 0.2057, loss_mask: 0.2166, loss: 0.6440 2023-11-13 21:41:08,315 - mmdet - INFO - Epoch [7][3700/7330] lr: 1.000e-04, eta: 4:17:28, time: 0.391, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0383, loss_cls: 0.1673, acc: 93.7500, loss_bbox: 0.2140, loss_mask: 0.2155, loss: 0.6540 2023-11-13 21:41:27,674 - mmdet - INFO - Epoch [7][3750/7330] lr: 1.000e-04, eta: 4:17:09, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0392, loss_cls: 0.1641, acc: 93.8811, loss_bbox: 0.2096, loss_mask: 0.2151, loss: 0.6459 2023-11-13 21:41:46,668 - mmdet - INFO - Epoch [7][3800/7330] lr: 1.000e-04, eta: 4:16:50, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0370, loss_cls: 0.1593, acc: 94.0168, loss_bbox: 0.2037, loss_mask: 0.2142, loss: 0.6315 2023-11-13 21:42:05,590 - mmdet - INFO - Epoch [7][3850/7330] lr: 1.000e-04, eta: 4:16:31, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0381, loss_cls: 0.1639, acc: 93.9072, loss_bbox: 0.2148, loss_mask: 0.2227, loss: 0.6594 2023-11-13 21:42:24,242 - mmdet - INFO - Epoch [7][3900/7330] lr: 1.000e-04, eta: 4:16:11, time: 0.373, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0357, loss_cls: 0.1621, acc: 93.9810, loss_bbox: 0.2089, loss_mask: 0.2231, loss: 0.6468 2023-11-13 21:42:43,558 - mmdet - INFO - Epoch [7][3950/7330] lr: 1.000e-04, eta: 4:15:52, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0395, loss_cls: 0.1691, acc: 93.6843, loss_bbox: 0.2160, loss_mask: 0.2139, loss: 0.6582 2023-11-13 21:43:02,727 - mmdet - INFO - Epoch [7][4000/7330] lr: 1.000e-04, eta: 4:15:33, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0403, loss_cls: 0.1672, acc: 93.8684, loss_bbox: 0.2109, loss_mask: 0.2198, loss: 0.6590 2023-11-13 21:43:21,510 - mmdet - INFO - Epoch [7][4050/7330] lr: 1.000e-04, eta: 4:15:13, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0364, loss_cls: 0.1596, acc: 94.0774, loss_bbox: 0.2059, loss_mask: 0.2158, loss: 0.6348 2023-11-13 21:43:40,701 - mmdet - INFO - Epoch [7][4100/7330] lr: 1.000e-04, eta: 4:14:54, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0388, loss_cls: 0.1668, acc: 93.6772, loss_bbox: 0.2150, loss_mask: 0.2210, loss: 0.6605 2023-11-13 21:43:59,977 - mmdet - INFO - Epoch [7][4150/7330] lr: 1.000e-04, eta: 4:14:35, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0383, loss_cls: 0.1709, acc: 93.7065, loss_bbox: 0.2153, loss_mask: 0.2216, loss: 0.6655 2023-11-13 21:44:19,199 - mmdet - INFO - Epoch [7][4200/7330] lr: 1.000e-04, eta: 4:14:16, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0380, loss_cls: 0.1588, acc: 94.1384, loss_bbox: 0.2045, loss_mask: 0.2136, loss: 0.6329 2023-11-13 21:44:38,714 - mmdet - INFO - Epoch [7][4250/7330] lr: 1.000e-04, eta: 4:13:57, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0419, loss_cls: 0.1792, acc: 93.2358, loss_bbox: 0.2322, loss_mask: 0.2259, loss: 0.6985 2023-11-13 21:44:57,705 - mmdet - INFO - Epoch [7][4300/7330] lr: 1.000e-04, eta: 4:13:38, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0395, loss_cls: 0.1688, acc: 93.7827, loss_bbox: 0.2132, loss_mask: 0.2220, loss: 0.6624 2023-11-13 21:45:16,495 - mmdet - INFO - Epoch [7][4350/7330] lr: 1.000e-04, eta: 4:13:18, time: 0.376, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0376, loss_cls: 0.1619, acc: 94.0549, loss_bbox: 0.2076, loss_mask: 0.2174, loss: 0.6428 2023-11-13 21:45:35,661 - mmdet - INFO - Epoch [7][4400/7330] lr: 1.000e-04, eta: 4:12:59, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0400, loss_cls: 0.1646, acc: 93.7827, loss_bbox: 0.2120, loss_mask: 0.2212, loss: 0.6578 2023-11-13 21:45:54,878 - mmdet - INFO - Epoch [7][4450/7330] lr: 1.000e-04, eta: 4:12:40, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0384, loss_cls: 0.1684, acc: 93.7061, loss_bbox: 0.2152, loss_mask: 0.2194, loss: 0.6604 2023-11-13 21:46:14,129 - mmdet - INFO - Epoch [7][4500/7330] lr: 1.000e-04, eta: 4:12:21, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0404, loss_cls: 0.1726, acc: 93.5647, loss_bbox: 0.2216, loss_mask: 0.2248, loss: 0.6790 2023-11-13 21:46:33,348 - mmdet - INFO - Epoch [7][4550/7330] lr: 1.000e-04, eta: 4:12:02, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0378, loss_cls: 0.1618, acc: 93.9683, loss_bbox: 0.2088, loss_mask: 0.2232, loss: 0.6503 2023-11-13 21:46:52,506 - mmdet - INFO - Epoch [7][4600/7330] lr: 1.000e-04, eta: 4:11:42, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0393, loss_cls: 0.1668, acc: 93.7148, loss_bbox: 0.2150, loss_mask: 0.2204, loss: 0.6599 2023-11-13 21:47:11,489 - mmdet - INFO - Epoch [7][4650/7330] lr: 1.000e-04, eta: 4:11:23, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0388, loss_cls: 0.1677, acc: 93.7029, loss_bbox: 0.2142, loss_mask: 0.2241, loss: 0.6635 2023-11-13 21:47:30,846 - mmdet - INFO - Epoch [7][4700/7330] lr: 1.000e-04, eta: 4:11:04, time: 0.387, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0403, loss_cls: 0.1751, acc: 93.4512, loss_bbox: 0.2181, loss_mask: 0.2264, loss: 0.6791 2023-11-13 21:47:49,970 - mmdet - INFO - Epoch [7][4750/7330] lr: 1.000e-04, eta: 4:10:45, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0377, loss_cls: 0.1601, acc: 94.0496, loss_bbox: 0.2058, loss_mask: 0.2175, loss: 0.6400 2023-11-13 21:48:09,310 - mmdet - INFO - Epoch [7][4800/7330] lr: 1.000e-04, eta: 4:10:26, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0391, loss_cls: 0.1712, acc: 93.6462, loss_bbox: 0.2148, loss_mask: 0.2207, loss: 0.6668 2023-11-13 21:48:28,631 - mmdet - INFO - Epoch [7][4850/7330] lr: 1.000e-04, eta: 4:10:07, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0383, loss_cls: 0.1663, acc: 93.8171, loss_bbox: 0.2103, loss_mask: 0.2203, loss: 0.6553 2023-11-13 21:48:47,844 - mmdet - INFO - Epoch [7][4900/7330] lr: 1.000e-04, eta: 4:09:48, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0388, loss_cls: 0.1644, acc: 93.7874, loss_bbox: 0.2108, loss_mask: 0.2211, loss: 0.6540 2023-11-13 21:49:07,201 - mmdet - INFO - Epoch [7][4950/7330] lr: 1.000e-04, eta: 4:09:29, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0380, loss_cls: 0.1610, acc: 94.0051, loss_bbox: 0.2064, loss_mask: 0.2173, loss: 0.6411 2023-11-13 21:49:26,790 - mmdet - INFO - Epoch [7][5000/7330] lr: 1.000e-04, eta: 4:09:10, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0401, loss_cls: 0.1706, acc: 93.5818, loss_bbox: 0.2198, loss_mask: 0.2246, loss: 0.6745 2023-11-13 21:49:45,801 - mmdet - INFO - Epoch [7][5050/7330] lr: 1.000e-04, eta: 4:08:50, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0396, loss_cls: 0.1695, acc: 93.7556, loss_bbox: 0.2159, loss_mask: 0.2188, loss: 0.6634 2023-11-13 21:50:05,523 - mmdet - INFO - Epoch [7][5100/7330] lr: 1.000e-04, eta: 4:08:32, time: 0.394, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0392, loss_cls: 0.1650, acc: 93.8516, loss_bbox: 0.2110, loss_mask: 0.2168, loss: 0.6510 2023-11-13 21:50:24,785 - mmdet - INFO - Epoch [7][5150/7330] lr: 1.000e-04, eta: 4:08:13, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0395, loss_cls: 0.1705, acc: 93.6238, loss_bbox: 0.2159, loss_mask: 0.2180, loss: 0.6631 2023-11-13 21:50:43,916 - mmdet - INFO - Epoch [7][5200/7330] lr: 1.000e-04, eta: 4:07:53, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0395, loss_cls: 0.1632, acc: 93.9409, loss_bbox: 0.2088, loss_mask: 0.2190, loss: 0.6499 2023-11-13 21:51:03,523 - mmdet - INFO - Epoch [7][5250/7330] lr: 1.000e-04, eta: 4:07:35, time: 0.392, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0409, loss_cls: 0.1725, acc: 93.5398, loss_bbox: 0.2203, loss_mask: 0.2236, loss: 0.6770 2023-11-13 21:51:22,296 - mmdet - INFO - Epoch [7][5300/7330] lr: 1.000e-04, eta: 4:07:15, time: 0.375, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0384, loss_cls: 0.1655, acc: 93.8604, loss_bbox: 0.2079, loss_mask: 0.2138, loss: 0.6441 2023-11-13 21:51:41,355 - mmdet - INFO - Epoch [7][5350/7330] lr: 1.000e-04, eta: 4:06:56, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0405, loss_cls: 0.1665, acc: 93.7388, loss_bbox: 0.2118, loss_mask: 0.2197, loss: 0.6581 2023-11-13 21:52:00,506 - mmdet - INFO - Epoch [7][5400/7330] lr: 1.000e-04, eta: 4:06:37, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0378, loss_cls: 0.1638, acc: 93.8716, loss_bbox: 0.2129, loss_mask: 0.2176, loss: 0.6499 2023-11-13 21:52:19,426 - mmdet - INFO - Epoch [7][5450/7330] lr: 1.000e-04, eta: 4:06:17, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0403, loss_cls: 0.1744, acc: 93.3438, loss_bbox: 0.2186, loss_mask: 0.2229, loss: 0.6757 2023-11-13 21:52:38,624 - mmdet - INFO - Epoch [7][5500/7330] lr: 1.000e-04, eta: 4:05:58, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0407, loss_cls: 0.1702, acc: 93.7688, loss_bbox: 0.2108, loss_mask: 0.2182, loss: 0.6606 2023-11-13 21:52:57,729 - mmdet - INFO - Epoch [7][5550/7330] lr: 1.000e-04, eta: 4:05:39, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0387, loss_cls: 0.1617, acc: 93.9443, loss_bbox: 0.2067, loss_mask: 0.2209, loss: 0.6466 2023-11-13 21:53:16,553 - mmdet - INFO - Epoch [7][5600/7330] lr: 1.000e-04, eta: 4:05:19, time: 0.376, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0389, loss_cls: 0.1698, acc: 93.7473, loss_bbox: 0.2134, loss_mask: 0.2247, loss: 0.6669 2023-11-13 21:53:35,865 - mmdet - INFO - Epoch [7][5650/7330] lr: 1.000e-04, eta: 4:05:00, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0390, loss_cls: 0.1669, acc: 93.7930, loss_bbox: 0.2130, loss_mask: 0.2219, loss: 0.6591 2023-11-13 21:53:55,289 - mmdet - INFO - Epoch [7][5700/7330] lr: 1.000e-04, eta: 4:04:41, time: 0.388, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0391, loss_cls: 0.1765, acc: 93.3621, loss_bbox: 0.2243, loss_mask: 0.2226, loss: 0.6826 2023-11-13 21:54:14,619 - mmdet - INFO - Epoch [7][5750/7330] lr: 1.000e-04, eta: 4:04:22, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0385, loss_cls: 0.1682, acc: 93.5994, loss_bbox: 0.2136, loss_mask: 0.2176, loss: 0.6581 2023-11-13 21:54:33,761 - mmdet - INFO - Epoch [7][5800/7330] lr: 1.000e-04, eta: 4:04:03, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0366, loss_cls: 0.1611, acc: 93.9817, loss_bbox: 0.2067, loss_mask: 0.2149, loss: 0.6370 2023-11-13 21:54:53,110 - mmdet - INFO - Epoch [7][5850/7330] lr: 1.000e-04, eta: 4:03:44, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0393, loss_cls: 0.1673, acc: 93.7825, loss_bbox: 0.2125, loss_mask: 0.2216, loss: 0.6599 2023-11-13 21:55:11,987 - mmdet - INFO - Epoch [7][5900/7330] lr: 1.000e-04, eta: 4:03:25, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0359, loss_cls: 0.1653, acc: 93.7952, loss_bbox: 0.2125, loss_mask: 0.2173, loss: 0.6493 2023-11-13 21:55:31,290 - mmdet - INFO - Epoch [7][5950/7330] lr: 1.000e-04, eta: 4:03:05, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0377, loss_cls: 0.1665, acc: 93.6987, loss_bbox: 0.2177, loss_mask: 0.2240, loss: 0.6639 2023-11-13 21:55:50,712 - mmdet - INFO - Epoch [7][6000/7330] lr: 1.000e-04, eta: 4:02:46, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0373, loss_cls: 0.1699, acc: 93.7493, loss_bbox: 0.2115, loss_mask: 0.2148, loss: 0.6530 2023-11-13 21:56:09,944 - mmdet - INFO - Epoch [7][6050/7330] lr: 1.000e-04, eta: 4:02:27, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0397, loss_cls: 0.1706, acc: 93.6677, loss_bbox: 0.2133, loss_mask: 0.2155, loss: 0.6583 2023-11-13 21:56:28,848 - mmdet - INFO - Epoch [7][6100/7330] lr: 1.000e-04, eta: 4:02:08, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0376, loss_cls: 0.1637, acc: 93.8606, loss_bbox: 0.2064, loss_mask: 0.2139, loss: 0.6411 2023-11-13 21:56:48,035 - mmdet - INFO - Epoch [7][6150/7330] lr: 1.000e-04, eta: 4:01:49, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0410, loss_cls: 0.1744, acc: 93.5234, loss_bbox: 0.2163, loss_mask: 0.2222, loss: 0.6742 2023-11-13 21:57:06,946 - mmdet - INFO - Epoch [7][6200/7330] lr: 1.000e-04, eta: 4:01:29, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0380, loss_cls: 0.1640, acc: 93.8535, loss_bbox: 0.2084, loss_mask: 0.2241, loss: 0.6535 2023-11-13 21:57:26,206 - mmdet - INFO - Epoch [7][6250/7330] lr: 1.000e-04, eta: 4:01:10, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0424, loss_cls: 0.1765, acc: 93.4248, loss_bbox: 0.2196, loss_mask: 0.2246, loss: 0.6832 2023-11-13 21:57:45,090 - mmdet - INFO - Epoch [7][6300/7330] lr: 1.000e-04, eta: 4:00:51, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0371, loss_cls: 0.1628, acc: 93.8743, loss_bbox: 0.2085, loss_mask: 0.2172, loss: 0.6440 2023-11-13 21:58:04,414 - mmdet - INFO - Epoch [7][6350/7330] lr: 1.000e-04, eta: 4:00:32, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0382, loss_cls: 0.1656, acc: 93.8547, loss_bbox: 0.2131, loss_mask: 0.2117, loss: 0.6477 2023-11-13 21:58:23,820 - mmdet - INFO - Epoch [7][6400/7330] lr: 1.000e-04, eta: 4:00:13, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0387, loss_cls: 0.1713, acc: 93.5181, loss_bbox: 0.2175, loss_mask: 0.2157, loss: 0.6632 2023-11-13 21:58:43,036 - mmdet - INFO - Epoch [7][6450/7330] lr: 1.000e-04, eta: 3:59:54, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0341, loss_cls: 0.1559, acc: 94.2302, loss_bbox: 0.1981, loss_mask: 0.2092, loss: 0.6136 2023-11-13 21:59:01,897 - mmdet - INFO - Epoch [7][6500/7330] lr: 1.000e-04, eta: 3:59:34, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0382, loss_cls: 0.1649, acc: 93.8926, loss_bbox: 0.2116, loss_mask: 0.2124, loss: 0.6450 2023-11-13 21:59:21,828 - mmdet - INFO - Epoch [7][6550/7330] lr: 1.000e-04, eta: 3:59:16, time: 0.399, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0414, loss_cls: 0.1729, acc: 93.6328, loss_bbox: 0.2181, loss_mask: 0.2185, loss: 0.6712 2023-11-13 21:59:40,852 - mmdet - INFO - Epoch [7][6600/7330] lr: 1.000e-04, eta: 3:58:56, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0399, loss_cls: 0.1615, acc: 94.0415, loss_bbox: 0.2053, loss_mask: 0.2173, loss: 0.6457 2023-11-13 22:00:00,090 - mmdet - INFO - Epoch [7][6650/7330] lr: 1.000e-04, eta: 3:58:37, time: 0.385, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0402, loss_cls: 0.1669, acc: 93.7935, loss_bbox: 0.2135, loss_mask: 0.2189, loss: 0.6594 2023-11-13 22:00:18,799 - mmdet - INFO - Epoch [7][6700/7330] lr: 1.000e-04, eta: 3:58:18, time: 0.374, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0384, loss_cls: 0.1698, acc: 93.7439, loss_bbox: 0.2152, loss_mask: 0.2224, loss: 0.6670 2023-11-13 22:00:37,924 - mmdet - INFO - Epoch [7][6750/7330] lr: 1.000e-04, eta: 3:57:59, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0389, loss_cls: 0.1703, acc: 93.6987, loss_bbox: 0.2160, loss_mask: 0.2196, loss: 0.6648 2023-11-13 22:00:57,170 - mmdet - INFO - Epoch [7][6800/7330] lr: 1.000e-04, eta: 3:57:39, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0387, loss_cls: 0.1734, acc: 93.5898, loss_bbox: 0.2177, loss_mask: 0.2207, loss: 0.6701 2023-11-13 22:01:16,264 - mmdet - INFO - Epoch [7][6850/7330] lr: 1.000e-04, eta: 3:57:20, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0395, loss_cls: 0.1689, acc: 93.7390, loss_bbox: 0.2118, loss_mask: 0.2202, loss: 0.6598 2023-11-13 22:01:35,521 - mmdet - INFO - Epoch [7][6900/7330] lr: 1.000e-04, eta: 3:57:01, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0390, loss_cls: 0.1715, acc: 93.6172, loss_bbox: 0.2147, loss_mask: 0.2195, loss: 0.6661 2023-11-13 22:01:54,662 - mmdet - INFO - Epoch [7][6950/7330] lr: 1.000e-04, eta: 3:56:42, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0380, loss_cls: 0.1648, acc: 93.9148, loss_bbox: 0.2073, loss_mask: 0.2150, loss: 0.6455 2023-11-13 22:02:13,703 - mmdet - INFO - Epoch [7][7000/7330] lr: 1.000e-04, eta: 3:56:23, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0384, loss_cls: 0.1673, acc: 93.7725, loss_bbox: 0.2103, loss_mask: 0.2182, loss: 0.6537 2023-11-13 22:02:32,968 - mmdet - INFO - Epoch [7][7050/7330] lr: 1.000e-04, eta: 3:56:03, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0427, loss_cls: 0.1822, acc: 93.2361, loss_bbox: 0.2317, loss_mask: 0.2268, loss: 0.7023 2023-11-13 22:02:51,809 - mmdet - INFO - Epoch [7][7100/7330] lr: 1.000e-04, eta: 3:55:44, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0379, loss_cls: 0.1632, acc: 93.9050, loss_bbox: 0.2117, loss_mask: 0.2166, loss: 0.6481 2023-11-13 22:03:10,836 - mmdet - INFO - Epoch [7][7150/7330] lr: 1.000e-04, eta: 3:55:25, time: 0.380, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0391, loss_cls: 0.1692, acc: 93.7319, loss_bbox: 0.2122, loss_mask: 0.2201, loss: 0.6626 2023-11-13 22:03:29,952 - mmdet - INFO - Epoch [7][7200/7330] lr: 1.000e-04, eta: 3:55:06, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0412, loss_cls: 0.1798, acc: 93.3716, loss_bbox: 0.2244, loss_mask: 0.2222, loss: 0.6881 2023-11-13 22:03:48,884 - mmdet - INFO - Epoch [7][7250/7330] lr: 1.000e-04, eta: 3:54:46, time: 0.379, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0364, loss_cls: 0.1567, acc: 94.1948, loss_bbox: 0.1997, loss_mask: 0.2154, loss: 0.6260 2023-11-13 22:04:08,120 - mmdet - INFO - Epoch [7][7300/7330] lr: 1.000e-04, eta: 3:54:27, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0411, loss_cls: 0.1731, acc: 93.6406, loss_bbox: 0.2208, loss_mask: 0.2253, loss: 0.6798 2023-11-13 22:04:19,985 - mmdet - INFO - Saving checkpoint at 7 epochs 2023-11-13 22:05:10,292 - mmdet - INFO - Evaluating bbox... 2023-11-13 22:05:41,523 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.467 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.690 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.516 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.309 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.508 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.597 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.597 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.597 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.415 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.640 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.756 2023-11-13 22:05:41,526 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.575 | bicycle | 0.364 | car | 0.486 | | motorcycle | 0.474 | airplane | 0.683 | bus | 0.677 | | train | 0.682 | truck | 0.407 | boat | 0.327 | | traffic light | 0.308 | fire hydrant | 0.713 | stop sign | 0.668 | | parking meter | 0.513 | bench | 0.289 | bird | 0.412 | | cat | 0.719 | dog | 0.682 | horse | 0.628 | | sheep | 0.579 | cow | 0.588 | elephant | 0.648 | | bear | 0.745 | zebra | 0.687 | giraffe | 0.683 | | backpack | 0.207 | umbrella | 0.462 | handbag | 0.206 | | tie | 0.364 | suitcase | 0.448 | frisbee | 0.682 | | skis | 0.293 | snowboard | 0.447 | sports ball | 0.483 | | kite | 0.480 | baseball bat | 0.389 | baseball glove | 0.419 | | skateboard | 0.572 | surfboard | 0.441 | tennis racket | 0.531 | | bottle | 0.442 | wine glass | 0.401 | cup | 0.493 | | fork | 0.451 | knife | 0.264 | spoon | 0.280 | | bowl | 0.456 | banana | 0.287 | apple | 0.258 | | sandwich | 0.444 | orange | 0.363 | broccoli | 0.249 | | carrot | 0.256 | hot dog | 0.445 | pizza | 0.534 | | donut | 0.532 | cake | 0.439 | chair | 0.348 | | couch | 0.465 | potted plant | 0.349 | bed | 0.472 | | dining table | 0.308 | toilet | 0.646 | tv | 0.620 | | laptop | 0.650 | mouse | 0.651 | remote | 0.399 | | keyboard | 0.556 | cell phone | 0.432 | microwave | 0.601 | | oven | 0.376 | toaster | 0.421 | sink | 0.418 | | refrigerator | 0.639 | book | 0.189 | clock | 0.528 | | vase | 0.423 | scissors | 0.390 | teddy bear | 0.502 | | hair drier | 0.123 | toothbrush | 0.286 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:05:41,526 - mmdet - INFO - Evaluating segm... 2023-11-13 22:06:17,503 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.422 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.659 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.456 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.233 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.453 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.617 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 ] = 0.362 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.587 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.713 2023-11-13 22:06:17,506 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.501 | bicycle | 0.222 | car | 0.447 | | motorcycle | 0.395 | airplane | 0.543 | bus | 0.668 | | train | 0.670 | truck | 0.393 | boat | 0.293 | | traffic light | 0.290 | fire hydrant | 0.698 | stop sign | 0.673 | | parking meter | 0.537 | bench | 0.224 | bird | 0.349 | | cat | 0.718 | dog | 0.646 | horse | 0.452 | | sheep | 0.505 | cow | 0.503 | elephant | 0.611 | | bear | 0.723 | zebra | 0.604 | giraffe | 0.535 | | backpack | 0.216 | umbrella | 0.507 | handbag | 0.212 | | tie | 0.355 | suitcase | 0.473 | frisbee | 0.654 | | skis | 0.057 | snowboard | 0.258 | sports ball | 0.478 | | kite | 0.338 | baseball bat | 0.306 | baseball glove | 0.450 | | skateboard | 0.355 | surfboard | 0.353 | tennis racket | 0.567 | | bottle | 0.430 | wine glass | 0.369 | cup | 0.496 | | fork | 0.239 | knife | 0.184 | spoon | 0.191 | | bowl | 0.425 | banana | 0.242 | apple | 0.251 | | sandwich | 0.461 | orange | 0.366 | broccoli | 0.237 | | carrot | 0.228 | hot dog | 0.349 | pizza | 0.520 | | donut | 0.530 | cake | 0.445 | chair | 0.252 | | couch | 0.384 | potted plant | 0.299 | bed | 0.370 | | dining table | 0.180 | toilet | 0.633 | tv | 0.649 | | laptop | 0.652 | mouse | 0.637 | remote | 0.359 | | keyboard | 0.549 | cell phone | 0.417 | microwave | 0.631 | | oven | 0.373 | toaster | 0.438 | sink | 0.386 | | refrigerator | 0.631 | book | 0.138 | clock | 0.538 | | vase | 0.424 | scissors | 0.288 | teddy bear | 0.483 | | hair drier | 0.086 | toothbrush | 0.185 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:06:18,037 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_6.pth was removed 2023-11-13 22:06:20,188 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_7.pth. 2023-11-13 22:06:20,189 - mmdet - INFO - Best bbox_mAP is 0.4669 at 7 epoch. 2023-11-13 22:06:20,189 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 22:06:20,189 - mmdet - INFO - Epoch(val) [7][625] bbox_mAP: 0.4669, bbox_mAP_50: 0.6896, bbox_mAP_75: 0.5164, bbox_mAP_s: 0.3091, bbox_mAP_m: 0.5081, bbox_mAP_l: 0.6143, bbox_mAP_copypaste: 0.4669 0.6896 0.5164 0.3091 0.5081 0.6143, segm_mAP: 0.4216, segm_mAP_50: 0.6591, segm_mAP_75: 0.4562, segm_mAP_s: 0.2328, segm_mAP_m: 0.4526, segm_mAP_l: 0.6172, segm_mAP_copypaste: 0.4216 0.6591 0.4562 0.2328 0.4526 0.6172 2023-11-13 22:06:43,265 - mmdet - INFO - Epoch [8][50/7330] lr: 1.000e-04, eta: 3:53:51, time: 0.461, data_time: 0.094, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0377, loss_cls: 0.1562, acc: 94.1162, loss_bbox: 0.2036, loss_mask: 0.2172, loss: 0.6335 2023-11-13 22:07:03,137 - mmdet - INFO - Epoch [8][100/7330] lr: 1.000e-04, eta: 3:53:32, time: 0.397, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0380, loss_cls: 0.1597, acc: 94.0696, loss_bbox: 0.2047, loss_mask: 0.2125, loss: 0.6322 2023-11-13 22:07:23,247 - mmdet - INFO - Epoch [8][150/7330] lr: 1.000e-04, eta: 3:53:14, time: 0.402, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0377, loss_cls: 0.1617, acc: 93.9211, loss_bbox: 0.2114, loss_mask: 0.2179, loss: 0.6447 2023-11-13 22:07:42,568 - mmdet - INFO - Epoch [8][200/7330] lr: 1.000e-04, eta: 3:52:55, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0366, loss_cls: 0.1573, acc: 94.0398, loss_bbox: 0.2027, loss_mask: 0.2161, loss: 0.6294 2023-11-13 22:08:02,118 - mmdet - INFO - Epoch [8][250/7330] lr: 1.000e-04, eta: 3:52:36, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0388, loss_cls: 0.1610, acc: 93.9460, loss_bbox: 0.2122, loss_mask: 0.2154, loss: 0.6452 2023-11-13 22:08:22,003 - mmdet - INFO - Epoch [8][300/7330] lr: 1.000e-04, eta: 3:52:17, time: 0.398, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0382, loss_cls: 0.1574, acc: 94.0425, loss_bbox: 0.2122, loss_mask: 0.2159, loss: 0.6418 2023-11-13 22:08:41,532 - mmdet - INFO - Epoch [8][350/7330] lr: 1.000e-04, eta: 3:51:58, time: 0.391, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0370, loss_cls: 0.1506, acc: 94.3589, loss_bbox: 0.1979, loss_mask: 0.2137, loss: 0.6151 2023-11-13 22:09:01,336 - mmdet - INFO - Epoch [8][400/7330] lr: 1.000e-04, eta: 3:51:39, time: 0.396, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0395, loss_cls: 0.1658, acc: 93.7568, loss_bbox: 0.2154, loss_mask: 0.2197, loss: 0.6596 2023-11-13 22:09:20,641 - mmdet - INFO - Epoch [8][450/7330] lr: 1.000e-04, eta: 3:51:20, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0370, loss_cls: 0.1627, acc: 93.8591, loss_bbox: 0.2092, loss_mask: 0.2174, loss: 0.6423 2023-11-13 22:09:40,027 - mmdet - INFO - Epoch [8][500/7330] lr: 1.000e-04, eta: 3:51:01, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0391, loss_cls: 0.1629, acc: 93.8254, loss_bbox: 0.2089, loss_mask: 0.2125, loss: 0.6416 2023-11-13 22:09:59,257 - mmdet - INFO - Epoch [8][550/7330] lr: 1.000e-04, eta: 3:50:42, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0361, loss_cls: 0.1540, acc: 94.2322, loss_bbox: 0.2058, loss_mask: 0.2179, loss: 0.6306 2023-11-13 22:10:18,789 - mmdet - INFO - Epoch [8][600/7330] lr: 1.000e-04, eta: 3:50:23, time: 0.391, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0361, loss_cls: 0.1578, acc: 94.0654, loss_bbox: 0.2024, loss_mask: 0.2087, loss: 0.6231 2023-11-13 22:10:38,111 - mmdet - INFO - Epoch [8][650/7330] lr: 1.000e-04, eta: 3:50:04, time: 0.386, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0365, loss_cls: 0.1557, acc: 94.0271, loss_bbox: 0.2053, loss_mask: 0.2091, loss: 0.6238 2023-11-13 22:10:57,387 - mmdet - INFO - Epoch [8][700/7330] lr: 1.000e-04, eta: 3:49:45, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0380, loss_cls: 0.1608, acc: 94.2756, loss_bbox: 0.1981, loss_mask: 0.2148, loss: 0.6280 2023-11-13 22:11:17,100 - mmdet - INFO - Epoch [8][750/7330] lr: 1.000e-04, eta: 3:49:26, time: 0.394, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0397, loss_cls: 0.1665, acc: 93.8130, loss_bbox: 0.2124, loss_mask: 0.2232, loss: 0.6603 2023-11-13 22:11:36,658 - mmdet - INFO - Epoch [8][800/7330] lr: 1.000e-04, eta: 3:49:07, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0392, loss_cls: 0.1596, acc: 94.0469, loss_bbox: 0.2098, loss_mask: 0.2130, loss: 0.6388 2023-11-13 22:11:56,189 - mmdet - INFO - Epoch [8][850/7330] lr: 1.000e-04, eta: 3:48:48, time: 0.391, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0373, loss_cls: 0.1549, acc: 94.2019, loss_bbox: 0.2049, loss_mask: 0.2116, loss: 0.6263 2023-11-13 22:12:15,372 - mmdet - INFO - Epoch [8][900/7330] lr: 1.000e-04, eta: 3:48:29, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0392, loss_cls: 0.1606, acc: 93.9231, loss_bbox: 0.2084, loss_mask: 0.2193, loss: 0.6454 2023-11-13 22:12:34,960 - mmdet - INFO - Epoch [8][950/7330] lr: 1.000e-04, eta: 3:48:10, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0397, loss_cls: 0.1647, acc: 93.7666, loss_bbox: 0.2132, loss_mask: 0.2149, loss: 0.6527 2023-11-13 22:12:54,219 - mmdet - INFO - Epoch [8][1000/7330] lr: 1.000e-04, eta: 3:47:51, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0383, loss_cls: 0.1568, acc: 94.0315, loss_bbox: 0.2054, loss_mask: 0.2210, loss: 0.6402 2023-11-13 22:13:13,831 - mmdet - INFO - Epoch [8][1050/7330] lr: 1.000e-04, eta: 3:47:32, time: 0.392, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0396, loss_cls: 0.1540, acc: 94.2798, loss_bbox: 0.2038, loss_mask: 0.2092, loss: 0.6257 2023-11-13 22:13:33,094 - mmdet - INFO - Epoch [8][1100/7330] lr: 1.000e-04, eta: 3:47:13, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0362, loss_cls: 0.1613, acc: 94.0676, loss_bbox: 0.2086, loss_mask: 0.2144, loss: 0.6385 2023-11-13 22:13:52,450 - mmdet - INFO - Epoch [8][1150/7330] lr: 1.000e-04, eta: 3:46:54, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0368, loss_cls: 0.1617, acc: 93.9490, loss_bbox: 0.2109, loss_mask: 0.2162, loss: 0.6433 2023-11-13 22:14:11,648 - mmdet - INFO - Epoch [8][1200/7330] lr: 1.000e-04, eta: 3:46:35, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0370, loss_cls: 0.1630, acc: 93.9678, loss_bbox: 0.2141, loss_mask: 0.2108, loss: 0.6417 2023-11-13 22:14:31,018 - mmdet - INFO - Epoch [8][1250/7330] lr: 1.000e-04, eta: 3:46:16, time: 0.387, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0384, loss_cls: 0.1622, acc: 93.8967, loss_bbox: 0.2146, loss_mask: 0.2171, loss: 0.6502 2023-11-13 22:14:50,458 - mmdet - INFO - Epoch [8][1300/7330] lr: 1.000e-04, eta: 3:45:57, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0408, loss_cls: 0.1590, acc: 94.0015, loss_bbox: 0.2094, loss_mask: 0.2167, loss: 0.6449 2023-11-13 22:15:09,384 - mmdet - INFO - Epoch [8][1350/7330] lr: 1.000e-04, eta: 3:45:38, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0379, loss_cls: 0.1561, acc: 94.1038, loss_bbox: 0.2098, loss_mask: 0.2166, loss: 0.6367 2023-11-13 22:15:28,475 - mmdet - INFO - Epoch [8][1400/7330] lr: 1.000e-04, eta: 3:45:18, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0393, loss_cls: 0.1644, acc: 93.7551, loss_bbox: 0.2191, loss_mask: 0.2270, loss: 0.6675 2023-11-13 22:15:47,726 - mmdet - INFO - Epoch [8][1450/7330] lr: 1.000e-04, eta: 3:44:59, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0372, loss_cls: 0.1616, acc: 93.7869, loss_bbox: 0.2169, loss_mask: 0.2186, loss: 0.6509 2023-11-13 22:16:06,872 - mmdet - INFO - Epoch [8][1500/7330] lr: 1.000e-04, eta: 3:44:40, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0370, loss_cls: 0.1533, acc: 94.2261, loss_bbox: 0.2031, loss_mask: 0.2120, loss: 0.6218 2023-11-13 22:16:25,975 - mmdet - INFO - Epoch [8][1550/7330] lr: 1.000e-04, eta: 3:44:21, time: 0.382, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0381, loss_cls: 0.1557, acc: 94.0986, loss_bbox: 0.2003, loss_mask: 0.2147, loss: 0.6255 2023-11-13 22:16:45,070 - mmdet - INFO - Epoch [8][1600/7330] lr: 1.000e-04, eta: 3:44:02, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0373, loss_cls: 0.1571, acc: 94.0288, loss_bbox: 0.2057, loss_mask: 0.2126, loss: 0.6296 2023-11-13 22:17:04,279 - mmdet - INFO - Epoch [8][1650/7330] lr: 1.000e-04, eta: 3:43:43, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0407, loss_cls: 0.1611, acc: 93.8904, loss_bbox: 0.2129, loss_mask: 0.2161, loss: 0.6497 2023-11-13 22:17:23,281 - mmdet - INFO - Epoch [8][1700/7330] lr: 1.000e-04, eta: 3:43:23, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0361, loss_cls: 0.1593, acc: 94.0151, loss_bbox: 0.2088, loss_mask: 0.2159, loss: 0.6377 2023-11-13 22:17:42,386 - mmdet - INFO - Epoch [8][1750/7330] lr: 1.000e-04, eta: 3:43:04, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0374, loss_cls: 0.1620, acc: 93.9194, loss_bbox: 0.2083, loss_mask: 0.2202, loss: 0.6444 2023-11-13 22:18:01,868 - mmdet - INFO - Epoch [8][1800/7330] lr: 1.000e-04, eta: 3:42:45, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0376, loss_cls: 0.1603, acc: 94.0720, loss_bbox: 0.2064, loss_mask: 0.2135, loss: 0.6364 2023-11-13 22:18:21,224 - mmdet - INFO - Epoch [8][1850/7330] lr: 1.000e-04, eta: 3:42:26, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0412, loss_cls: 0.1649, acc: 93.8088, loss_bbox: 0.2103, loss_mask: 0.2183, loss: 0.6543 2023-11-13 22:18:40,221 - mmdet - INFO - Epoch [8][1900/7330] lr: 1.000e-04, eta: 3:42:07, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0403, loss_cls: 0.1620, acc: 93.8999, loss_bbox: 0.2052, loss_mask: 0.2194, loss: 0.6467 2023-11-13 22:18:59,501 - mmdet - INFO - Epoch [8][1950/7330] lr: 1.000e-04, eta: 3:41:48, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0411, loss_cls: 0.1623, acc: 93.9236, loss_bbox: 0.2174, loss_mask: 0.2210, loss: 0.6615 2023-11-13 22:19:18,418 - mmdet - INFO - Epoch [8][2000/7330] lr: 1.000e-04, eta: 3:41:28, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0373, loss_cls: 0.1579, acc: 94.2236, loss_bbox: 0.2029, loss_mask: 0.2147, loss: 0.6293 2023-11-13 22:19:37,524 - mmdet - INFO - Epoch [8][2050/7330] lr: 1.000e-04, eta: 3:41:09, time: 0.382, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0370, loss_cls: 0.1671, acc: 93.6653, loss_bbox: 0.2119, loss_mask: 0.2132, loss: 0.6478 2023-11-13 22:19:56,968 - mmdet - INFO - Epoch [8][2100/7330] lr: 1.000e-04, eta: 3:40:50, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0392, loss_cls: 0.1668, acc: 93.6973, loss_bbox: 0.2121, loss_mask: 0.2141, loss: 0.6508 2023-11-13 22:20:15,941 - mmdet - INFO - Epoch [8][2150/7330] lr: 1.000e-04, eta: 3:40:31, time: 0.379, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0379, loss_cls: 0.1608, acc: 93.9443, loss_bbox: 0.2118, loss_mask: 0.2181, loss: 0.6465 2023-11-13 22:20:35,472 - mmdet - INFO - Epoch [8][2200/7330] lr: 1.000e-04, eta: 3:40:12, time: 0.391, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0377, loss_cls: 0.1627, acc: 93.8232, loss_bbox: 0.2123, loss_mask: 0.2157, loss: 0.6458 2023-11-13 22:20:54,752 - mmdet - INFO - Epoch [8][2250/7330] lr: 1.000e-04, eta: 3:39:53, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0371, loss_cls: 0.1572, acc: 94.1462, loss_bbox: 0.2045, loss_mask: 0.2151, loss: 0.6308 2023-11-13 22:21:13,960 - mmdet - INFO - Epoch [8][2300/7330] lr: 1.000e-04, eta: 3:39:33, time: 0.384, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0371, loss_cls: 0.1593, acc: 93.9885, loss_bbox: 0.2070, loss_mask: 0.2131, loss: 0.6328 2023-11-13 22:21:33,180 - mmdet - INFO - Epoch [8][2350/7330] lr: 1.000e-04, eta: 3:39:14, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0394, loss_cls: 0.1672, acc: 93.7014, loss_bbox: 0.2161, loss_mask: 0.2168, loss: 0.6585 2023-11-13 22:21:51,990 - mmdet - INFO - Epoch [8][2400/7330] lr: 1.000e-04, eta: 3:38:55, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0367, loss_cls: 0.1624, acc: 93.9639, loss_bbox: 0.2103, loss_mask: 0.2168, loss: 0.6429 2023-11-13 22:22:11,446 - mmdet - INFO - Epoch [8][2450/7330] lr: 1.000e-04, eta: 3:38:36, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0375, loss_cls: 0.1601, acc: 93.9500, loss_bbox: 0.2113, loss_mask: 0.2144, loss: 0.6410 2023-11-13 22:22:30,681 - mmdet - INFO - Epoch [8][2500/7330] lr: 1.000e-04, eta: 3:38:17, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0376, loss_cls: 0.1640, acc: 93.9692, loss_bbox: 0.2084, loss_mask: 0.2132, loss: 0.6400 2023-11-13 22:22:50,088 - mmdet - INFO - Epoch [8][2550/7330] lr: 1.000e-04, eta: 3:37:58, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0361, loss_cls: 0.1573, acc: 94.0920, loss_bbox: 0.2050, loss_mask: 0.2145, loss: 0.6301 2023-11-13 22:23:09,297 - mmdet - INFO - Epoch [8][2600/7330] lr: 1.000e-04, eta: 3:37:39, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0398, loss_cls: 0.1640, acc: 93.9788, loss_bbox: 0.2084, loss_mask: 0.2209, loss: 0.6523 2023-11-13 22:23:28,511 - mmdet - INFO - Epoch [8][2650/7330] lr: 1.000e-04, eta: 3:37:19, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0386, loss_cls: 0.1634, acc: 93.8708, loss_bbox: 0.2130, loss_mask: 0.2130, loss: 0.6462 2023-11-13 22:23:47,848 - mmdet - INFO - Epoch [8][2700/7330] lr: 1.000e-04, eta: 3:37:00, time: 0.387, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0365, loss_cls: 0.1558, acc: 94.1489, loss_bbox: 0.1996, loss_mask: 0.2148, loss: 0.6258 2023-11-13 22:24:07,027 - mmdet - INFO - Epoch [8][2750/7330] lr: 1.000e-04, eta: 3:36:41, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0363, loss_cls: 0.1583, acc: 94.0730, loss_bbox: 0.2057, loss_mask: 0.2145, loss: 0.6317 2023-11-13 22:24:26,169 - mmdet - INFO - Epoch [8][2800/7330] lr: 1.000e-04, eta: 3:36:22, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0362, loss_cls: 0.1497, acc: 94.3508, loss_bbox: 0.1958, loss_mask: 0.2189, loss: 0.6161 2023-11-13 22:24:45,145 - mmdet - INFO - Epoch [8][2850/7330] lr: 1.000e-04, eta: 3:36:03, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0374, loss_cls: 0.1614, acc: 93.9128, loss_bbox: 0.2093, loss_mask: 0.2190, loss: 0.6450 2023-11-13 22:25:04,300 - mmdet - INFO - Epoch [8][2900/7330] lr: 1.000e-04, eta: 3:35:44, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0384, loss_cls: 0.1635, acc: 93.9026, loss_bbox: 0.2050, loss_mask: 0.2149, loss: 0.6399 2023-11-13 22:25:23,347 - mmdet - INFO - Epoch [8][2950/7330] lr: 1.000e-04, eta: 3:35:24, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0375, loss_cls: 0.1600, acc: 94.0605, loss_bbox: 0.2101, loss_mask: 0.2203, loss: 0.6464 2023-11-13 22:25:42,498 - mmdet - INFO - Epoch [8][3000/7330] lr: 1.000e-04, eta: 3:35:05, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0355, loss_cls: 0.1558, acc: 94.1433, loss_bbox: 0.2009, loss_mask: 0.2135, loss: 0.6228 2023-11-13 22:26:01,651 - mmdet - INFO - Epoch [8][3050/7330] lr: 1.000e-04, eta: 3:34:46, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0388, loss_cls: 0.1641, acc: 93.8250, loss_bbox: 0.2144, loss_mask: 0.2164, loss: 0.6512 2023-11-13 22:26:21,252 - mmdet - INFO - Epoch [8][3100/7330] lr: 1.000e-04, eta: 3:34:27, time: 0.392, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0391, loss_cls: 0.1632, acc: 93.9165, loss_bbox: 0.2132, loss_mask: 0.2175, loss: 0.6526 2023-11-13 22:26:40,153 - mmdet - INFO - Epoch [8][3150/7330] lr: 1.000e-04, eta: 3:34:08, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0379, loss_cls: 0.1628, acc: 93.8284, loss_bbox: 0.2141, loss_mask: 0.2184, loss: 0.6519 2023-11-13 22:26:59,825 - mmdet - INFO - Epoch [8][3200/7330] lr: 1.000e-04, eta: 3:33:49, time: 0.393, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0409, loss_cls: 0.1719, acc: 93.3884, loss_bbox: 0.2243, loss_mask: 0.2271, loss: 0.6833 2023-11-13 22:27:18,563 - mmdet - INFO - Epoch [8][3250/7330] lr: 1.000e-04, eta: 3:33:29, time: 0.375, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0374, loss_cls: 0.1586, acc: 94.0420, loss_bbox: 0.2045, loss_mask: 0.2123, loss: 0.6300 2023-11-13 22:27:37,722 - mmdet - INFO - Epoch [8][3300/7330] lr: 1.000e-04, eta: 3:33:10, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0382, loss_cls: 0.1653, acc: 93.7483, loss_bbox: 0.2096, loss_mask: 0.2190, loss: 0.6498 2023-11-13 22:27:56,680 - mmdet - INFO - Epoch [8][3350/7330] lr: 1.000e-04, eta: 3:32:51, time: 0.379, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0370, loss_cls: 0.1578, acc: 94.1333, loss_bbox: 0.2051, loss_mask: 0.2215, loss: 0.6388 2023-11-13 22:28:15,819 - mmdet - INFO - Epoch [8][3400/7330] lr: 1.000e-04, eta: 3:32:32, time: 0.383, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0369, loss_cls: 0.1621, acc: 93.9526, loss_bbox: 0.2083, loss_mask: 0.2150, loss: 0.6397 2023-11-13 22:28:35,364 - mmdet - INFO - Epoch [8][3450/7330] lr: 1.000e-04, eta: 3:32:13, time: 0.391, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0383, loss_cls: 0.1602, acc: 93.9167, loss_bbox: 0.2103, loss_mask: 0.2188, loss: 0.6449 2023-11-13 22:28:54,430 - mmdet - INFO - Epoch [8][3500/7330] lr: 1.000e-04, eta: 3:31:53, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0379, loss_cls: 0.1610, acc: 94.0046, loss_bbox: 0.2076, loss_mask: 0.2128, loss: 0.6372 2023-11-13 22:29:13,530 - mmdet - INFO - Epoch [8][3550/7330] lr: 1.000e-04, eta: 3:31:34, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0366, loss_cls: 0.1596, acc: 94.0237, loss_bbox: 0.2058, loss_mask: 0.2131, loss: 0.6323 2023-11-13 22:29:32,710 - mmdet - INFO - Epoch [8][3600/7330] lr: 1.000e-04, eta: 3:31:15, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0386, loss_cls: 0.1671, acc: 93.6663, loss_bbox: 0.2135, loss_mask: 0.2166, loss: 0.6538 2023-11-13 22:29:51,567 - mmdet - INFO - Epoch [8][3650/7330] lr: 1.000e-04, eta: 3:30:56, time: 0.377, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0369, loss_cls: 0.1614, acc: 93.9578, loss_bbox: 0.2097, loss_mask: 0.2157, loss: 0.6411 2023-11-13 22:30:10,635 - mmdet - INFO - Epoch [8][3700/7330] lr: 1.000e-04, eta: 3:30:36, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0380, loss_cls: 0.1590, acc: 94.0457, loss_bbox: 0.2073, loss_mask: 0.2185, loss: 0.6418 2023-11-13 22:30:29,625 - mmdet - INFO - Epoch [8][3750/7330] lr: 1.000e-04, eta: 3:30:17, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0380, loss_cls: 0.1628, acc: 93.9832, loss_bbox: 0.2098, loss_mask: 0.2179, loss: 0.6456 2023-11-13 22:30:48,709 - mmdet - INFO - Epoch [8][3800/7330] lr: 1.000e-04, eta: 3:29:58, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0357, loss_cls: 0.1630, acc: 93.8962, loss_bbox: 0.2059, loss_mask: 0.2160, loss: 0.6390 2023-11-13 22:31:08,072 - mmdet - INFO - Epoch [8][3850/7330] lr: 1.000e-04, eta: 3:29:39, time: 0.387, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0409, loss_cls: 0.1625, acc: 93.8428, loss_bbox: 0.2136, loss_mask: 0.2162, loss: 0.6527 2023-11-13 22:31:27,474 - mmdet - INFO - Epoch [8][3900/7330] lr: 1.000e-04, eta: 3:29:20, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0415, loss_cls: 0.1675, acc: 93.7957, loss_bbox: 0.2178, loss_mask: 0.2242, loss: 0.6710 2023-11-13 22:31:46,201 - mmdet - INFO - Epoch [8][3950/7330] lr: 1.000e-04, eta: 3:29:00, time: 0.375, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0355, loss_cls: 0.1537, acc: 94.2388, loss_bbox: 0.1978, loss_mask: 0.2095, loss: 0.6135 2023-11-13 22:32:05,394 - mmdet - INFO - Epoch [8][4000/7330] lr: 1.000e-04, eta: 3:28:41, time: 0.384, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0357, loss_cls: 0.1601, acc: 93.9573, loss_bbox: 0.2115, loss_mask: 0.2172, loss: 0.6422 2023-11-13 22:32:24,596 - mmdet - INFO - Epoch [8][4050/7330] lr: 1.000e-04, eta: 3:28:22, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0383, loss_cls: 0.1611, acc: 93.8992, loss_bbox: 0.2060, loss_mask: 0.2116, loss: 0.6354 2023-11-13 22:32:43,513 - mmdet - INFO - Epoch [8][4100/7330] lr: 1.000e-04, eta: 3:28:03, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0368, loss_cls: 0.1591, acc: 94.0100, loss_bbox: 0.2011, loss_mask: 0.2131, loss: 0.6269 2023-11-13 22:33:03,007 - mmdet - INFO - Epoch [8][4150/7330] lr: 1.000e-04, eta: 3:27:44, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0400, loss_cls: 0.1671, acc: 93.8311, loss_bbox: 0.2098, loss_mask: 0.2197, loss: 0.6575 2023-11-13 22:33:22,228 - mmdet - INFO - Epoch [8][4200/7330] lr: 1.000e-04, eta: 3:27:25, time: 0.384, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0373, loss_cls: 0.1601, acc: 94.0039, loss_bbox: 0.2055, loss_mask: 0.2134, loss: 0.6341 2023-11-13 22:33:41,305 - mmdet - INFO - Epoch [8][4250/7330] lr: 1.000e-04, eta: 3:27:05, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0371, loss_cls: 0.1596, acc: 94.0034, loss_bbox: 0.2050, loss_mask: 0.2148, loss: 0.6345 2023-11-13 22:34:00,689 - mmdet - INFO - Epoch [8][4300/7330] lr: 1.000e-04, eta: 3:26:46, time: 0.388, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0363, loss_cls: 0.1577, acc: 94.0959, loss_bbox: 0.2080, loss_mask: 0.2161, loss: 0.6363 2023-11-13 22:34:19,861 - mmdet - INFO - Epoch [8][4350/7330] lr: 1.000e-04, eta: 3:26:27, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0389, loss_cls: 0.1610, acc: 93.9763, loss_bbox: 0.2070, loss_mask: 0.2195, loss: 0.6444 2023-11-13 22:34:39,623 - mmdet - INFO - Epoch [8][4400/7330] lr: 1.000e-04, eta: 3:26:08, time: 0.395, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0412, loss_cls: 0.1659, acc: 93.8560, loss_bbox: 0.2074, loss_mask: 0.2180, loss: 0.6527 2023-11-13 22:34:58,889 - mmdet - INFO - Epoch [8][4450/7330] lr: 1.000e-04, eta: 3:25:49, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0398, loss_cls: 0.1690, acc: 93.6421, loss_bbox: 0.2195, loss_mask: 0.2224, loss: 0.6696 2023-11-13 22:35:18,051 - mmdet - INFO - Epoch [8][4500/7330] lr: 1.000e-04, eta: 3:25:30, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0378, loss_cls: 0.1668, acc: 93.7488, loss_bbox: 0.2103, loss_mask: 0.2164, loss: 0.6497 2023-11-13 22:35:37,043 - mmdet - INFO - Epoch [8][4550/7330] lr: 1.000e-04, eta: 3:25:11, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0373, loss_cls: 0.1597, acc: 94.0371, loss_bbox: 0.2040, loss_mask: 0.2149, loss: 0.6347 2023-11-13 22:35:56,292 - mmdet - INFO - Epoch [8][4600/7330] lr: 1.000e-04, eta: 3:24:52, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0396, loss_cls: 0.1607, acc: 93.9978, loss_bbox: 0.2079, loss_mask: 0.2148, loss: 0.6412 2023-11-13 22:36:15,156 - mmdet - INFO - Epoch [8][4650/7330] lr: 1.000e-04, eta: 3:24:32, time: 0.377, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0364, loss_cls: 0.1568, acc: 94.1436, loss_bbox: 0.2034, loss_mask: 0.2095, loss: 0.6219 2023-11-13 22:36:34,289 - mmdet - INFO - Epoch [8][4700/7330] lr: 1.000e-04, eta: 3:24:13, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0388, loss_cls: 0.1659, acc: 93.8628, loss_bbox: 0.2132, loss_mask: 0.2235, loss: 0.6614 2023-11-13 22:36:53,495 - mmdet - INFO - Epoch [8][4750/7330] lr: 1.000e-04, eta: 3:23:54, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0377, loss_cls: 0.1631, acc: 93.9607, loss_bbox: 0.2044, loss_mask: 0.2116, loss: 0.6351 2023-11-13 22:37:12,561 - mmdet - INFO - Epoch [8][4800/7330] lr: 1.000e-04, eta: 3:23:35, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0376, loss_cls: 0.1622, acc: 93.9231, loss_bbox: 0.2095, loss_mask: 0.2152, loss: 0.6411 2023-11-13 22:37:31,531 - mmdet - INFO - Epoch [8][4850/7330] lr: 1.000e-04, eta: 3:23:15, time: 0.379, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0378, loss_cls: 0.1584, acc: 94.1145, loss_bbox: 0.2030, loss_mask: 0.2170, loss: 0.6350 2023-11-13 22:37:50,367 - mmdet - INFO - Epoch [8][4900/7330] lr: 1.000e-04, eta: 3:22:56, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0396, loss_cls: 0.1634, acc: 93.8757, loss_bbox: 0.2117, loss_mask: 0.2186, loss: 0.6527 2023-11-13 22:38:09,204 - mmdet - INFO - Epoch [8][4950/7330] lr: 1.000e-04, eta: 3:22:37, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0371, loss_cls: 0.1561, acc: 94.1750, loss_bbox: 0.2055, loss_mask: 0.2154, loss: 0.6325 2023-11-13 22:38:28,031 - mmdet - INFO - Epoch [8][5000/7330] lr: 1.000e-04, eta: 3:22:17, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0366, loss_cls: 0.1531, acc: 94.3772, loss_bbox: 0.2016, loss_mask: 0.2180, loss: 0.6264 2023-11-13 22:38:46,935 - mmdet - INFO - Epoch [8][5050/7330] lr: 1.000e-04, eta: 3:21:58, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0381, loss_cls: 0.1601, acc: 94.0532, loss_bbox: 0.2063, loss_mask: 0.2197, loss: 0.6417 2023-11-13 22:39:05,856 - mmdet - INFO - Epoch [8][5100/7330] lr: 1.000e-04, eta: 3:21:39, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0356, loss_cls: 0.1569, acc: 94.1365, loss_bbox: 0.1998, loss_mask: 0.2148, loss: 0.6235 2023-11-13 22:39:24,999 - mmdet - INFO - Epoch [8][5150/7330] lr: 1.000e-04, eta: 3:21:19, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0387, loss_cls: 0.1689, acc: 93.7371, loss_bbox: 0.2166, loss_mask: 0.2204, loss: 0.6647 2023-11-13 22:39:44,123 - mmdet - INFO - Epoch [8][5200/7330] lr: 1.000e-04, eta: 3:21:00, time: 0.383, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0382, loss_cls: 0.1682, acc: 93.7131, loss_bbox: 0.2150, loss_mask: 0.2174, loss: 0.6585 2023-11-13 22:40:03,168 - mmdet - INFO - Epoch [8][5250/7330] lr: 1.000e-04, eta: 3:20:41, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0371, loss_cls: 0.1613, acc: 93.9634, loss_bbox: 0.2081, loss_mask: 0.2141, loss: 0.6385 2023-11-13 22:40:21,990 - mmdet - INFO - Epoch [8][5300/7330] lr: 1.000e-04, eta: 3:20:22, time: 0.376, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0363, loss_cls: 0.1582, acc: 94.0371, loss_bbox: 0.2051, loss_mask: 0.2122, loss: 0.6296 2023-11-13 22:40:40,932 - mmdet - INFO - Epoch [8][5350/7330] lr: 1.000e-04, eta: 3:20:02, time: 0.379, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0375, loss_cls: 0.1662, acc: 93.8367, loss_bbox: 0.2142, loss_mask: 0.2173, loss: 0.6547 2023-11-13 22:41:00,063 - mmdet - INFO - Epoch [8][5400/7330] lr: 1.000e-04, eta: 3:19:43, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0422, loss_cls: 0.1680, acc: 93.7285, loss_bbox: 0.2161, loss_mask: 0.2201, loss: 0.6652 2023-11-13 22:41:18,919 - mmdet - INFO - Epoch [8][5450/7330] lr: 1.000e-04, eta: 3:19:24, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0372, loss_cls: 0.1620, acc: 93.9221, loss_bbox: 0.2045, loss_mask: 0.2160, loss: 0.6375 2023-11-13 22:41:38,051 - mmdet - INFO - Epoch [8][5500/7330] lr: 1.000e-04, eta: 3:19:04, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0350, loss_cls: 0.1572, acc: 94.1814, loss_bbox: 0.1990, loss_mask: 0.2152, loss: 0.6232 2023-11-13 22:41:56,966 - mmdet - INFO - Epoch [8][5550/7330] lr: 1.000e-04, eta: 3:18:45, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0355, loss_cls: 0.1572, acc: 94.2258, loss_bbox: 0.1973, loss_mask: 0.2120, loss: 0.6191 2023-11-13 22:42:15,744 - mmdet - INFO - Epoch [8][5600/7330] lr: 1.000e-04, eta: 3:18:26, time: 0.376, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0377, loss_cls: 0.1609, acc: 93.9568, loss_bbox: 0.2110, loss_mask: 0.2160, loss: 0.6448 2023-11-13 22:42:34,452 - mmdet - INFO - Epoch [8][5650/7330] lr: 1.000e-04, eta: 3:18:06, time: 0.374, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0352, loss_cls: 0.1510, acc: 94.3813, loss_bbox: 0.1984, loss_mask: 0.2082, loss: 0.6090 2023-11-13 22:42:53,470 - mmdet - INFO - Epoch [8][5700/7330] lr: 1.000e-04, eta: 3:17:47, time: 0.380, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0388, loss_cls: 0.1681, acc: 93.7271, loss_bbox: 0.2149, loss_mask: 0.2167, loss: 0.6572 2023-11-13 22:43:12,762 - mmdet - INFO - Epoch [8][5750/7330] lr: 1.000e-04, eta: 3:17:28, time: 0.386, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0391, loss_cls: 0.1579, acc: 94.1282, loss_bbox: 0.2015, loss_mask: 0.2163, loss: 0.6333 2023-11-13 22:43:31,866 - mmdet - INFO - Epoch [8][5800/7330] lr: 1.000e-04, eta: 3:17:09, time: 0.382, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0369, loss_cls: 0.1573, acc: 94.1614, loss_bbox: 0.1997, loss_mask: 0.2103, loss: 0.6223 2023-11-13 22:43:50,587 - mmdet - INFO - Epoch [8][5850/7330] lr: 1.000e-04, eta: 3:16:49, time: 0.374, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0380, loss_cls: 0.1580, acc: 94.0544, loss_bbox: 0.2045, loss_mask: 0.2140, loss: 0.6314 2023-11-13 22:44:09,592 - mmdet - INFO - Epoch [8][5900/7330] lr: 1.000e-04, eta: 3:16:30, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0408, loss_cls: 0.1638, acc: 93.8247, loss_bbox: 0.2110, loss_mask: 0.2151, loss: 0.6489 2023-11-13 22:44:28,763 - mmdet - INFO - Epoch [8][5950/7330] lr: 1.000e-04, eta: 3:16:11, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0384, loss_cls: 0.1656, acc: 93.7954, loss_bbox: 0.2125, loss_mask: 0.2165, loss: 0.6510 2023-11-13 22:44:48,136 - mmdet - INFO - Epoch [8][6000/7330] lr: 1.000e-04, eta: 3:15:52, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0376, loss_cls: 0.1594, acc: 94.0308, loss_bbox: 0.2007, loss_mask: 0.2177, loss: 0.6338 2023-11-13 22:45:06,601 - mmdet - INFO - Epoch [8][6050/7330] lr: 1.000e-04, eta: 3:15:32, time: 0.369, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0348, loss_cls: 0.1568, acc: 94.1633, loss_bbox: 0.2030, loss_mask: 0.2140, loss: 0.6245 2023-11-13 22:45:25,661 - mmdet - INFO - Epoch [8][6100/7330] lr: 1.000e-04, eta: 3:15:13, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0398, loss_cls: 0.1709, acc: 93.6035, loss_bbox: 0.2103, loss_mask: 0.2180, loss: 0.6586 2023-11-13 22:45:44,473 - mmdet - INFO - Epoch [8][6150/7330] lr: 1.000e-04, eta: 3:14:54, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0371, loss_cls: 0.1590, acc: 93.9470, loss_bbox: 0.2032, loss_mask: 0.2159, loss: 0.6334 2023-11-13 22:46:03,601 - mmdet - INFO - Epoch [8][6200/7330] lr: 1.000e-04, eta: 3:14:35, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0386, loss_cls: 0.1684, acc: 93.7446, loss_bbox: 0.2126, loss_mask: 0.2158, loss: 0.6551 2023-11-13 22:46:22,754 - mmdet - INFO - Epoch [8][6250/7330] lr: 1.000e-04, eta: 3:14:15, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0395, loss_cls: 0.1721, acc: 93.6963, loss_bbox: 0.2145, loss_mask: 0.2209, loss: 0.6657 2023-11-13 22:46:42,129 - mmdet - INFO - Epoch [8][6300/7330] lr: 1.000e-04, eta: 3:13:56, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0410, loss_cls: 0.1686, acc: 93.5991, loss_bbox: 0.2195, loss_mask: 0.2175, loss: 0.6656 2023-11-13 22:47:01,024 - mmdet - INFO - Epoch [8][6350/7330] lr: 1.000e-04, eta: 3:13:37, time: 0.378, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0371, loss_cls: 0.1582, acc: 94.0771, loss_bbox: 0.2045, loss_mask: 0.2211, loss: 0.6389 2023-11-13 22:47:19,739 - mmdet - INFO - Epoch [8][6400/7330] lr: 1.000e-04, eta: 3:13:18, time: 0.374, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0373, loss_cls: 0.1579, acc: 94.0481, loss_bbox: 0.2078, loss_mask: 0.2173, loss: 0.6366 2023-11-13 22:47:38,668 - mmdet - INFO - Epoch [8][6450/7330] lr: 1.000e-04, eta: 3:12:58, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0359, loss_cls: 0.1584, acc: 93.9788, loss_bbox: 0.2078, loss_mask: 0.2184, loss: 0.6367 2023-11-13 22:47:57,502 - mmdet - INFO - Epoch [8][6500/7330] lr: 1.000e-04, eta: 3:12:39, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0371, loss_cls: 0.1636, acc: 93.8901, loss_bbox: 0.2084, loss_mask: 0.2190, loss: 0.6471 2023-11-13 22:48:16,211 - mmdet - INFO - Epoch [8][6550/7330] lr: 1.000e-04, eta: 3:12:19, time: 0.374, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0367, loss_cls: 0.1564, acc: 94.1343, loss_bbox: 0.2019, loss_mask: 0.2130, loss: 0.6249 2023-11-13 22:48:35,202 - mmdet - INFO - Epoch [8][6600/7330] lr: 1.000e-04, eta: 3:12:00, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0355, loss_cls: 0.1595, acc: 94.0591, loss_bbox: 0.2028, loss_mask: 0.2101, loss: 0.6250 2023-11-13 22:48:54,401 - mmdet - INFO - Epoch [8][6650/7330] lr: 1.000e-04, eta: 3:11:41, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0390, loss_cls: 0.1648, acc: 93.8691, loss_bbox: 0.2108, loss_mask: 0.2166, loss: 0.6502 2023-11-13 22:49:13,299 - mmdet - INFO - Epoch [8][6700/7330] lr: 1.000e-04, eta: 3:11:22, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0366, loss_cls: 0.1545, acc: 94.1909, loss_bbox: 0.1994, loss_mask: 0.2125, loss: 0.6201 2023-11-13 22:49:32,451 - mmdet - INFO - Epoch [8][6750/7330] lr: 1.000e-04, eta: 3:11:03, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0392, loss_cls: 0.1624, acc: 93.8357, loss_bbox: 0.2104, loss_mask: 0.2171, loss: 0.6490 2023-11-13 22:49:51,156 - mmdet - INFO - Epoch [8][6800/7330] lr: 1.000e-04, eta: 3:10:43, time: 0.374, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0371, loss_cls: 0.1617, acc: 94.0327, loss_bbox: 0.2089, loss_mask: 0.2173, loss: 0.6445 2023-11-13 22:50:10,231 - mmdet - INFO - Epoch [8][6850/7330] lr: 1.000e-04, eta: 3:10:24, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0396, loss_cls: 0.1562, acc: 94.1289, loss_bbox: 0.2035, loss_mask: 0.2134, loss: 0.6312 2023-11-13 22:50:29,273 - mmdet - INFO - Epoch [8][6900/7330] lr: 1.000e-04, eta: 3:10:05, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0374, loss_cls: 0.1700, acc: 93.6965, loss_bbox: 0.2183, loss_mask: 0.2184, loss: 0.6618 2023-11-13 22:50:48,351 - mmdet - INFO - Epoch [8][6950/7330] lr: 1.000e-04, eta: 3:09:46, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0407, loss_cls: 0.1695, acc: 93.7002, loss_bbox: 0.2143, loss_mask: 0.2168, loss: 0.6609 2023-11-13 22:51:07,467 - mmdet - INFO - Epoch [8][7000/7330] lr: 1.000e-04, eta: 3:09:26, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0392, loss_cls: 0.1607, acc: 93.9912, loss_bbox: 0.2090, loss_mask: 0.2170, loss: 0.6458 2023-11-13 22:51:26,381 - mmdet - INFO - Epoch [8][7050/7330] lr: 1.000e-04, eta: 3:09:07, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0386, loss_cls: 0.1626, acc: 93.9167, loss_bbox: 0.2100, loss_mask: 0.2137, loss: 0.6432 2023-11-13 22:51:45,146 - mmdet - INFO - Epoch [8][7100/7330] lr: 1.000e-04, eta: 3:08:48, time: 0.375, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0382, loss_cls: 0.1607, acc: 93.9695, loss_bbox: 0.2067, loss_mask: 0.2167, loss: 0.6403 2023-11-13 22:52:04,667 - mmdet - INFO - Epoch [8][7150/7330] lr: 1.000e-04, eta: 3:08:29, time: 0.390, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0402, loss_cls: 0.1693, acc: 93.6658, loss_bbox: 0.2214, loss_mask: 0.2216, loss: 0.6729 2023-11-13 22:52:23,892 - mmdet - INFO - Epoch [8][7200/7330] lr: 1.000e-04, eta: 3:08:10, time: 0.385, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0349, loss_cls: 0.1532, acc: 94.2595, loss_bbox: 0.1980, loss_mask: 0.2165, loss: 0.6186 2023-11-13 22:52:42,779 - mmdet - INFO - Epoch [8][7250/7330] lr: 1.000e-04, eta: 3:07:50, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0419, loss_cls: 0.1674, acc: 93.7266, loss_bbox: 0.2077, loss_mask: 0.2217, loss: 0.6573 2023-11-13 22:53:01,825 - mmdet - INFO - Epoch [8][7300/7330] lr: 1.000e-04, eta: 3:07:31, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0388, loss_cls: 0.1584, acc: 94.0854, loss_bbox: 0.2086, loss_mask: 0.2205, loss: 0.6441 2023-11-13 22:53:13,717 - mmdet - INFO - Saving checkpoint at 8 epochs 2023-11-13 22:54:01,314 - mmdet - INFO - Evaluating bbox... 2023-11-13 22:54:30,267 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.467 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.690 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.517 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.305 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.509 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.613 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 ] = 0.418 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.640 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.751 2023-11-13 22:54:30,270 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.570 | bicycle | 0.359 | car | 0.471 | | motorcycle | 0.459 | airplane | 0.690 | bus | 0.667 | | train | 0.686 | truck | 0.430 | boat | 0.317 | | traffic light | 0.309 | fire hydrant | 0.694 | stop sign | 0.654 | | parking meter | 0.491 | bench | 0.298 | bird | 0.408 | | cat | 0.726 | dog | 0.701 | horse | 0.608 | | sheep | 0.549 | cow | 0.593 | elephant | 0.668 | | bear | 0.767 | zebra | 0.686 | giraffe | 0.707 | | backpack | 0.220 | umbrella | 0.460 | handbag | 0.216 | | tie | 0.379 | suitcase | 0.451 | frisbee | 0.689 | | skis | 0.290 | snowboard | 0.442 | sports ball | 0.476 | | kite | 0.464 | baseball bat | 0.380 | baseball glove | 0.433 | | skateboard | 0.581 | surfboard | 0.436 | tennis racket | 0.541 | | bottle | 0.437 | wine glass | 0.423 | cup | 0.490 | | fork | 0.461 | knife | 0.274 | spoon | 0.272 | | bowl | 0.436 | banana | 0.295 | apple | 0.249 | | sandwich | 0.426 | orange | 0.339 | broccoli | 0.249 | | carrot | 0.256 | hot dog | 0.442 | pizza | 0.542 | | donut | 0.541 | cake | 0.431 | chair | 0.352 | | couch | 0.449 | potted plant | 0.339 | bed | 0.477 | | dining table | 0.316 | toilet | 0.652 | tv | 0.612 | | laptop | 0.659 | mouse | 0.636 | remote | 0.405 | | keyboard | 0.527 | cell phone | 0.435 | microwave | 0.658 | | oven | 0.383 | toaster | 0.404 | sink | 0.432 | | refrigerator | 0.590 | book | 0.185 | clock | 0.530 | | vase | 0.422 | scissors | 0.382 | teddy bear | 0.518 | | hair drier | 0.185 | toothbrush | 0.295 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:54:30,270 - mmdet - INFO - Evaluating segm... 2023-11-13 22:55:03,110 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.421 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.660 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.453 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.453 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.611 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.361 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.587 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.703 2023-11-13 22:55:03,112 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.498 | bicycle | 0.205 | car | 0.438 | | motorcycle | 0.383 | airplane | 0.533 | bus | 0.656 | | train | 0.672 | truck | 0.409 | boat | 0.291 | | traffic light | 0.301 | fire hydrant | 0.693 | stop sign | 0.667 | | parking meter | 0.519 | bench | 0.223 | bird | 0.341 | | cat | 0.729 | dog | 0.651 | horse | 0.452 | | sheep | 0.491 | cow | 0.503 | elephant | 0.611 | | bear | 0.747 | zebra | 0.626 | giraffe | 0.548 | | backpack | 0.218 | umbrella | 0.509 | handbag | 0.201 | | tie | 0.354 | suitcase | 0.462 | frisbee | 0.662 | | skis | 0.053 | snowboard | 0.264 | sports ball | 0.469 | | kite | 0.330 | baseball bat | 0.307 | baseball glove | 0.451 | | skateboard | 0.353 | surfboard | 0.359 | tennis racket | 0.577 | | bottle | 0.422 | wine glass | 0.373 | cup | 0.495 | | fork | 0.230 | knife | 0.189 | spoon | 0.187 | | bowl | 0.413 | banana | 0.241 | apple | 0.251 | | sandwich | 0.449 | orange | 0.339 | broccoli | 0.231 | | carrot | 0.220 | hot dog | 0.339 | pizza | 0.518 | | donut | 0.547 | cake | 0.437 | chair | 0.253 | | couch | 0.371 | potted plant | 0.283 | bed | 0.371 | | dining table | 0.190 | toilet | 0.625 | tv | 0.638 | | laptop | 0.656 | mouse | 0.633 | remote | 0.369 | | keyboard | 0.533 | cell phone | 0.407 | microwave | 0.677 | | oven | 0.354 | toaster | 0.437 | sink | 0.396 | | refrigerator | 0.627 | book | 0.143 | clock | 0.537 | | vase | 0.420 | scissors | 0.290 | teddy bear | 0.500 | | hair drier | 0.092 | toothbrush | 0.234 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:55:03,604 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_7.pth was removed 2023-11-13 22:55:05,760 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_8.pth. 2023-11-13 22:55:05,761 - mmdet - INFO - Best bbox_mAP is 0.4671 at 8 epoch. 2023-11-13 22:55:05,761 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 22:55:05,761 - mmdet - INFO - Epoch(val) [8][625] bbox_mAP: 0.4671, bbox_mAP_50: 0.6903, bbox_mAP_75: 0.5171, bbox_mAP_s: 0.3045, bbox_mAP_m: 0.5089, bbox_mAP_l: 0.6125, bbox_mAP_copypaste: 0.4671 0.6903 0.5171 0.3045 0.5089 0.6125, segm_mAP: 0.4209, segm_mAP_50: 0.6597, segm_mAP_75: 0.4529, segm_mAP_s: 0.2298, segm_mAP_m: 0.4532, segm_mAP_l: 0.6115, segm_mAP_copypaste: 0.4209 0.6597 0.4529 0.2298 0.4532 0.6115 2023-11-13 22:55:28,991 - mmdet - INFO - Epoch [9][50/7330] lr: 1.000e-05, eta: 3:06:57, time: 0.464, data_time: 0.088, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0351, loss_cls: 0.1550, acc: 94.1711, loss_bbox: 0.2001, loss_mask: 0.2105, loss: 0.6170 2023-11-13 22:55:48,645 - mmdet - INFO - Epoch [9][100/7330] lr: 1.000e-05, eta: 3:06:38, time: 0.393, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0365, loss_cls: 0.1568, acc: 94.1089, loss_bbox: 0.2039, loss_mask: 0.2078, loss: 0.6195 2023-11-13 22:56:08,166 - mmdet - INFO - Epoch [9][150/7330] lr: 1.000e-05, eta: 3:06:19, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0351, loss_cls: 0.1518, acc: 94.2312, loss_bbox: 0.2004, loss_mask: 0.2096, loss: 0.6122 2023-11-13 22:56:27,658 - mmdet - INFO - Epoch [9][200/7330] lr: 1.000e-05, eta: 3:06:00, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0346, loss_cls: 0.1498, acc: 94.2571, loss_bbox: 0.1961, loss_mask: 0.2092, loss: 0.6061 2023-11-13 22:56:47,237 - mmdet - INFO - Epoch [9][250/7330] lr: 1.000e-05, eta: 3:05:41, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0385, loss_cls: 0.1592, acc: 93.9214, loss_bbox: 0.2090, loss_mask: 0.2105, loss: 0.6338 2023-11-13 22:57:07,065 - mmdet - INFO - Epoch [9][300/7330] lr: 1.000e-05, eta: 3:05:22, time: 0.397, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0367, loss_cls: 0.1523, acc: 94.1763, loss_bbox: 0.2050, loss_mask: 0.2108, loss: 0.6212 2023-11-13 22:57:26,687 - mmdet - INFO - Epoch [9][350/7330] lr: 1.000e-05, eta: 3:05:03, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0375, loss_cls: 0.1544, acc: 94.2178, loss_bbox: 0.2025, loss_mask: 0.2100, loss: 0.6210 2023-11-13 22:57:46,271 - mmdet - INFO - Epoch [9][400/7330] lr: 1.000e-05, eta: 3:04:44, time: 0.392, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0349, loss_cls: 0.1395, acc: 94.6809, loss_bbox: 0.1907, loss_mask: 0.2081, loss: 0.5879 2023-11-13 22:58:06,130 - mmdet - INFO - Epoch [9][450/7330] lr: 1.000e-05, eta: 3:04:25, time: 0.397, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0364, loss_cls: 0.1494, acc: 94.3616, loss_bbox: 0.1988, loss_mask: 0.2088, loss: 0.6093 2023-11-13 22:58:25,481 - mmdet - INFO - Epoch [9][500/7330] lr: 1.000e-05, eta: 3:04:06, time: 0.387, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0379, loss_cls: 0.1504, acc: 94.1907, loss_bbox: 0.2054, loss_mask: 0.2127, loss: 0.6232 2023-11-13 22:58:45,061 - mmdet - INFO - Epoch [9][550/7330] lr: 1.000e-05, eta: 3:03:47, time: 0.392, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0362, loss_cls: 0.1523, acc: 94.2178, loss_bbox: 0.1957, loss_mask: 0.2083, loss: 0.6086 2023-11-13 22:59:04,642 - mmdet - INFO - Epoch [9][600/7330] lr: 1.000e-05, eta: 3:03:28, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0369, loss_cls: 0.1550, acc: 94.1167, loss_bbox: 0.2050, loss_mask: 0.2106, loss: 0.6233 2023-11-13 22:59:23,919 - mmdet - INFO - Epoch [9][650/7330] lr: 1.000e-05, eta: 3:03:09, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0352, loss_cls: 0.1470, acc: 94.3821, loss_bbox: 0.1960, loss_mask: 0.2064, loss: 0.6000 2023-11-13 22:59:43,127 - mmdet - INFO - Epoch [9][700/7330] lr: 1.000e-05, eta: 3:02:50, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0353, loss_cls: 0.1470, acc: 94.4167, loss_bbox: 0.1943, loss_mask: 0.2013, loss: 0.5920 2023-11-13 23:00:02,676 - mmdet - INFO - Epoch [9][750/7330] lr: 1.000e-05, eta: 3:02:31, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0359, loss_cls: 0.1525, acc: 94.1526, loss_bbox: 0.2013, loss_mask: 0.2118, loss: 0.6172 2023-11-13 23:00:21,841 - mmdet - INFO - Epoch [9][800/7330] lr: 1.000e-05, eta: 3:02:12, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0330, loss_cls: 0.1387, acc: 94.7402, loss_bbox: 0.1896, loss_mask: 0.2025, loss: 0.5790 2023-11-13 23:00:41,323 - mmdet - INFO - Epoch [9][850/7330] lr: 1.000e-05, eta: 3:01:53, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0368, loss_cls: 0.1488, acc: 94.2698, loss_bbox: 0.1998, loss_mask: 0.2106, loss: 0.6123 2023-11-13 23:01:00,446 - mmdet - INFO - Epoch [9][900/7330] lr: 1.000e-05, eta: 3:01:34, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0365, loss_cls: 0.1522, acc: 94.1953, loss_bbox: 0.2029, loss_mask: 0.2110, loss: 0.6175 2023-11-13 23:01:19,832 - mmdet - INFO - Epoch [9][950/7330] lr: 1.000e-05, eta: 3:01:15, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0351, loss_cls: 0.1425, acc: 94.5183, loss_bbox: 0.1920, loss_mask: 0.2052, loss: 0.5899 2023-11-13 23:01:38,969 - mmdet - INFO - Epoch [9][1000/7330] lr: 1.000e-05, eta: 3:00:55, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0355, loss_cls: 0.1554, acc: 94.0361, loss_bbox: 0.2074, loss_mask: 0.2142, loss: 0.6281 2023-11-13 23:01:58,411 - mmdet - INFO - Epoch [9][1050/7330] lr: 1.000e-05, eta: 3:00:36, time: 0.389, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0378, loss_cls: 0.1530, acc: 94.1692, loss_bbox: 0.2021, loss_mask: 0.2093, loss: 0.6191 2023-11-13 23:02:17,588 - mmdet - INFO - Epoch [9][1100/7330] lr: 1.000e-05, eta: 3:00:17, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0342, loss_cls: 0.1444, acc: 94.5151, loss_bbox: 0.1913, loss_mask: 0.2016, loss: 0.5861 2023-11-13 23:02:36,730 - mmdet - INFO - Epoch [9][1150/7330] lr: 1.000e-05, eta: 2:59:58, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0348, loss_cls: 0.1448, acc: 94.5574, loss_bbox: 0.1963, loss_mask: 0.2047, loss: 0.5936 2023-11-13 23:02:56,291 - mmdet - INFO - Epoch [9][1200/7330] lr: 1.000e-05, eta: 2:59:39, time: 0.391, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0370, loss_cls: 0.1444, acc: 94.4534, loss_bbox: 0.1942, loss_mask: 0.2087, loss: 0.6010 2023-11-13 23:03:15,244 - mmdet - INFO - Epoch [9][1250/7330] lr: 1.000e-05, eta: 2:59:20, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0334, loss_cls: 0.1417, acc: 94.6711, loss_bbox: 0.1895, loss_mask: 0.2011, loss: 0.5811 2023-11-13 23:03:34,472 - mmdet - INFO - Epoch [9][1300/7330] lr: 1.000e-05, eta: 2:59:01, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0335, loss_cls: 0.1424, acc: 94.5283, loss_bbox: 0.1898, loss_mask: 0.2052, loss: 0.5843 2023-11-13 23:03:53,844 - mmdet - INFO - Epoch [9][1350/7330] lr: 1.000e-05, eta: 2:58:41, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0333, loss_cls: 0.1438, acc: 94.5928, loss_bbox: 0.1915, loss_mask: 0.2048, loss: 0.5885 2023-11-13 23:04:13,123 - mmdet - INFO - Epoch [9][1400/7330] lr: 1.000e-05, eta: 2:58:22, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0367, loss_cls: 0.1503, acc: 94.3472, loss_bbox: 0.2002, loss_mask: 0.2115, loss: 0.6129 2023-11-13 23:04:32,350 - mmdet - INFO - Epoch [9][1450/7330] lr: 1.000e-05, eta: 2:58:03, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0361, loss_cls: 0.1496, acc: 94.2686, loss_bbox: 0.2006, loss_mask: 0.2077, loss: 0.6091 2023-11-13 23:04:51,765 - mmdet - INFO - Epoch [9][1500/7330] lr: 1.000e-05, eta: 2:57:44, time: 0.388, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0360, loss_cls: 0.1499, acc: 94.2131, loss_bbox: 0.2046, loss_mask: 0.2104, loss: 0.6169 2023-11-13 23:05:11,359 - mmdet - INFO - Epoch [9][1550/7330] lr: 1.000e-05, eta: 2:57:25, time: 0.392, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0366, loss_cls: 0.1484, acc: 94.3401, loss_bbox: 0.1955, loss_mask: 0.2035, loss: 0.6010 2023-11-13 23:05:31,067 - mmdet - INFO - Epoch [9][1600/7330] lr: 1.000e-05, eta: 2:57:06, time: 0.394, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0354, loss_cls: 0.1397, acc: 94.6006, loss_bbox: 0.1898, loss_mask: 0.2037, loss: 0.5835 2023-11-13 23:05:50,378 - mmdet - INFO - Epoch [9][1650/7330] lr: 1.000e-05, eta: 2:56:47, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0325, loss_cls: 0.1376, acc: 94.7427, loss_bbox: 0.1861, loss_mask: 0.2029, loss: 0.5727 2023-11-13 23:06:09,939 - mmdet - INFO - Epoch [9][1700/7330] lr: 1.000e-05, eta: 2:56:28, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0348, loss_cls: 0.1485, acc: 94.3472, loss_bbox: 0.1900, loss_mask: 0.2017, loss: 0.5910 2023-11-13 23:06:29,135 - mmdet - INFO - Epoch [9][1750/7330] lr: 1.000e-05, eta: 2:56:09, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0341, loss_cls: 0.1419, acc: 94.5261, loss_bbox: 0.1922, loss_mask: 0.2048, loss: 0.5873 2023-11-13 23:06:48,357 - mmdet - INFO - Epoch [9][1800/7330] lr: 1.000e-05, eta: 2:55:50, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0368, loss_cls: 0.1491, acc: 94.2854, loss_bbox: 0.1989, loss_mask: 0.2093, loss: 0.6105 2023-11-13 23:07:07,751 - mmdet - INFO - Epoch [9][1850/7330] lr: 1.000e-05, eta: 2:55:31, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0353, loss_cls: 0.1443, acc: 94.5166, loss_bbox: 0.1938, loss_mask: 0.2057, loss: 0.5952 2023-11-13 23:07:27,390 - mmdet - INFO - Epoch [9][1900/7330] lr: 1.000e-05, eta: 2:55:12, time: 0.393, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0376, loss_cls: 0.1526, acc: 94.0647, loss_bbox: 0.2006, loss_mask: 0.2065, loss: 0.6143 2023-11-13 23:07:46,624 - mmdet - INFO - Epoch [9][1950/7330] lr: 1.000e-05, eta: 2:54:53, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0352, loss_cls: 0.1446, acc: 94.4622, loss_bbox: 0.1956, loss_mask: 0.2103, loss: 0.6008 2023-11-13 23:08:05,902 - mmdet - INFO - Epoch [9][2000/7330] lr: 1.000e-05, eta: 2:54:34, time: 0.386, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0359, loss_cls: 0.1464, acc: 94.3640, loss_bbox: 0.2032, loss_mask: 0.2104, loss: 0.6119 2023-11-13 23:08:25,132 - mmdet - INFO - Epoch [9][2050/7330] lr: 1.000e-05, eta: 2:54:14, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0364, loss_cls: 0.1486, acc: 94.2930, loss_bbox: 0.1952, loss_mask: 0.2045, loss: 0.6005 2023-11-13 23:08:44,344 - mmdet - INFO - Epoch [9][2100/7330] lr: 1.000e-05, eta: 2:53:55, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0332, loss_cls: 0.1392, acc: 94.6340, loss_bbox: 0.1855, loss_mask: 0.2007, loss: 0.5719 2023-11-13 23:09:03,484 - mmdet - INFO - Epoch [9][2150/7330] lr: 1.000e-05, eta: 2:53:36, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0354, loss_cls: 0.1506, acc: 94.2141, loss_bbox: 0.1999, loss_mask: 0.2105, loss: 0.6117 2023-11-13 23:09:23,154 - mmdet - INFO - Epoch [9][2200/7330] lr: 1.000e-05, eta: 2:53:17, time: 0.393, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0375, loss_cls: 0.1562, acc: 93.9836, loss_bbox: 0.1990, loss_mask: 0.2100, loss: 0.6185 2023-11-13 23:09:42,178 - mmdet - INFO - Epoch [9][2250/7330] lr: 1.000e-05, eta: 2:52:58, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0360, loss_cls: 0.1522, acc: 94.1777, loss_bbox: 0.2029, loss_mask: 0.2130, loss: 0.6190 2023-11-13 23:10:01,061 - mmdet - INFO - Epoch [9][2300/7330] lr: 1.000e-05, eta: 2:52:39, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0357, loss_cls: 0.1451, acc: 94.4456, loss_bbox: 0.1926, loss_mask: 0.2047, loss: 0.5945 2023-11-13 23:10:20,186 - mmdet - INFO - Epoch [9][2350/7330] lr: 1.000e-05, eta: 2:52:19, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0365, loss_cls: 0.1470, acc: 94.4070, loss_bbox: 0.1917, loss_mask: 0.2072, loss: 0.5976 2023-11-13 23:10:39,620 - mmdet - INFO - Epoch [9][2400/7330] lr: 1.000e-05, eta: 2:52:00, time: 0.389, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0336, loss_cls: 0.1419, acc: 94.5986, loss_bbox: 0.1882, loss_mask: 0.2024, loss: 0.5803 2023-11-13 23:10:58,719 - mmdet - INFO - Epoch [9][2450/7330] lr: 1.000e-05, eta: 2:51:41, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0330, loss_cls: 0.1402, acc: 94.6694, loss_bbox: 0.1907, loss_mask: 0.2032, loss: 0.5819 2023-11-13 23:11:17,821 - mmdet - INFO - Epoch [9][2500/7330] lr: 1.000e-05, eta: 2:51:22, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0332, loss_cls: 0.1395, acc: 94.7666, loss_bbox: 0.1855, loss_mask: 0.2031, loss: 0.5751 2023-11-13 23:11:37,021 - mmdet - INFO - Epoch [9][2550/7330] lr: 1.000e-05, eta: 2:51:03, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0347, loss_cls: 0.1456, acc: 94.3699, loss_bbox: 0.1946, loss_mask: 0.2087, loss: 0.5980 2023-11-13 23:11:56,327 - mmdet - INFO - Epoch [9][2600/7330] lr: 1.000e-05, eta: 2:50:44, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0340, loss_cls: 0.1409, acc: 94.5505, loss_bbox: 0.1905, loss_mask: 0.2023, loss: 0.5824 2023-11-13 23:12:15,336 - mmdet - INFO - Epoch [9][2650/7330] lr: 1.000e-05, eta: 2:50:25, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0345, loss_cls: 0.1438, acc: 94.4707, loss_bbox: 0.1936, loss_mask: 0.2022, loss: 0.5885 2023-11-13 23:12:34,434 - mmdet - INFO - Epoch [9][2700/7330] lr: 1.000e-05, eta: 2:50:05, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0353, loss_cls: 0.1435, acc: 94.4587, loss_bbox: 0.1935, loss_mask: 0.2078, loss: 0.5937 2023-11-13 23:12:53,960 - mmdet - INFO - Epoch [9][2750/7330] lr: 1.000e-05, eta: 2:49:46, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0358, loss_cls: 0.1447, acc: 94.4268, loss_bbox: 0.1937, loss_mask: 0.2067, loss: 0.5955 2023-11-13 23:13:13,126 - mmdet - INFO - Epoch [9][2800/7330] lr: 1.000e-05, eta: 2:49:27, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0342, loss_cls: 0.1439, acc: 94.5115, loss_bbox: 0.1851, loss_mask: 0.2010, loss: 0.5792 2023-11-13 23:13:32,467 - mmdet - INFO - Epoch [9][2850/7330] lr: 1.000e-05, eta: 2:49:08, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0347, loss_cls: 0.1490, acc: 94.3308, loss_bbox: 0.1988, loss_mask: 0.2061, loss: 0.6046 2023-11-13 23:13:51,741 - mmdet - INFO - Epoch [9][2900/7330] lr: 1.000e-05, eta: 2:48:49, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0339, loss_cls: 0.1392, acc: 94.6382, loss_bbox: 0.1858, loss_mask: 0.2035, loss: 0.5770 2023-11-13 23:14:11,229 - mmdet - INFO - Epoch [9][2950/7330] lr: 1.000e-05, eta: 2:48:30, time: 0.390, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0329, loss_cls: 0.1425, acc: 94.5625, loss_bbox: 0.1903, loss_mask: 0.2060, loss: 0.5860 2023-11-13 23:14:30,493 - mmdet - INFO - Epoch [9][3000/7330] lr: 1.000e-05, eta: 2:48:11, time: 0.385, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0353, loss_cls: 0.1441, acc: 94.4338, loss_bbox: 0.1952, loss_mask: 0.2074, loss: 0.5979 2023-11-13 23:14:49,734 - mmdet - INFO - Epoch [9][3050/7330] lr: 1.000e-05, eta: 2:47:52, time: 0.385, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0360, loss_cls: 0.1480, acc: 94.3027, loss_bbox: 0.1953, loss_mask: 0.2096, loss: 0.6048 2023-11-13 23:15:08,705 - mmdet - INFO - Epoch [9][3100/7330] lr: 1.000e-05, eta: 2:47:32, time: 0.379, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0342, loss_cls: 0.1402, acc: 94.5696, loss_bbox: 0.1935, loss_mask: 0.2090, loss: 0.5906 2023-11-13 23:15:28,378 - mmdet - INFO - Epoch [9][3150/7330] lr: 1.000e-05, eta: 2:47:13, time: 0.393, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0363, loss_cls: 0.1498, acc: 94.3115, loss_bbox: 0.2044, loss_mask: 0.2104, loss: 0.6159 2023-11-13 23:15:47,120 - mmdet - INFO - Epoch [9][3200/7330] lr: 1.000e-05, eta: 2:46:54, time: 0.375, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0340, loss_cls: 0.1453, acc: 94.4480, loss_bbox: 0.1937, loss_mask: 0.2052, loss: 0.5929 2023-11-13 23:16:06,263 - mmdet - INFO - Epoch [9][3250/7330] lr: 1.000e-05, eta: 2:46:35, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0328, loss_cls: 0.1420, acc: 94.5015, loss_bbox: 0.1893, loss_mask: 0.2021, loss: 0.5800 2023-11-13 23:16:25,799 - mmdet - INFO - Epoch [9][3300/7330] lr: 1.000e-05, eta: 2:46:16, time: 0.391, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0378, loss_cls: 0.1515, acc: 94.2559, loss_bbox: 0.2022, loss_mask: 0.2022, loss: 0.6103 2023-11-13 23:16:45,076 - mmdet - INFO - Epoch [9][3350/7330] lr: 1.000e-05, eta: 2:45:57, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0358, loss_cls: 0.1448, acc: 94.4165, loss_bbox: 0.1922, loss_mask: 0.2063, loss: 0.5948 2023-11-13 23:17:04,335 - mmdet - INFO - Epoch [9][3400/7330] lr: 1.000e-05, eta: 2:45:38, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0356, loss_cls: 0.1426, acc: 94.5518, loss_bbox: 0.1925, loss_mask: 0.2026, loss: 0.5887 2023-11-13 23:17:23,211 - mmdet - INFO - Epoch [9][3450/7330] lr: 1.000e-05, eta: 2:45:18, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0346, loss_cls: 0.1417, acc: 94.6021, loss_bbox: 0.1874, loss_mask: 0.2070, loss: 0.5854 2023-11-13 23:17:42,120 - mmdet - INFO - Epoch [9][3500/7330] lr: 1.000e-05, eta: 2:44:59, time: 0.378, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0334, loss_cls: 0.1446, acc: 94.4668, loss_bbox: 0.1909, loss_mask: 0.2085, loss: 0.5921 2023-11-13 23:18:01,727 - mmdet - INFO - Epoch [9][3550/7330] lr: 1.000e-05, eta: 2:44:40, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0353, loss_cls: 0.1469, acc: 94.3857, loss_bbox: 0.2002, loss_mask: 0.2088, loss: 0.6066 2023-11-13 23:18:21,178 - mmdet - INFO - Epoch [9][3600/7330] lr: 1.000e-05, eta: 2:44:21, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0356, loss_cls: 0.1461, acc: 94.3555, loss_bbox: 0.1962, loss_mask: 0.2068, loss: 0.5996 2023-11-13 23:18:40,450 - mmdet - INFO - Epoch [9][3650/7330] lr: 1.000e-05, eta: 2:44:02, time: 0.386, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0352, loss_cls: 0.1394, acc: 94.6638, loss_bbox: 0.1876, loss_mask: 0.2055, loss: 0.5823 2023-11-13 23:19:00,229 - mmdet - INFO - Epoch [9][3700/7330] lr: 1.000e-05, eta: 2:43:43, time: 0.396, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0357, loss_cls: 0.1434, acc: 94.5242, loss_bbox: 0.1905, loss_mask: 0.2032, loss: 0.5884 2023-11-13 23:19:19,527 - mmdet - INFO - Epoch [9][3750/7330] lr: 1.000e-05, eta: 2:43:24, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0352, loss_cls: 0.1474, acc: 94.4260, loss_bbox: 0.1992, loss_mask: 0.2025, loss: 0.6014 2023-11-13 23:19:38,523 - mmdet - INFO - Epoch [9][3800/7330] lr: 1.000e-05, eta: 2:43:05, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0349, loss_cls: 0.1435, acc: 94.5437, loss_bbox: 0.1928, loss_mask: 0.2060, loss: 0.5932 2023-11-13 23:19:57,834 - mmdet - INFO - Epoch [9][3850/7330] lr: 1.000e-05, eta: 2:42:45, time: 0.386, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0354, loss_cls: 0.1460, acc: 94.3860, loss_bbox: 0.2003, loss_mask: 0.2102, loss: 0.6063 2023-11-13 23:20:17,015 - mmdet - INFO - Epoch [9][3900/7330] lr: 1.000e-05, eta: 2:42:26, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0354, loss_cls: 0.1439, acc: 94.3787, loss_bbox: 0.1957, loss_mask: 0.2119, loss: 0.6013 2023-11-13 23:20:36,463 - mmdet - INFO - Epoch [9][3950/7330] lr: 1.000e-05, eta: 2:42:07, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0376, loss_cls: 0.1506, acc: 94.1567, loss_bbox: 0.2053, loss_mask: 0.2108, loss: 0.6197 2023-11-13 23:20:55,239 - mmdet - INFO - Epoch [9][4000/7330] lr: 1.000e-05, eta: 2:41:48, time: 0.375, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0346, loss_cls: 0.1428, acc: 94.5627, loss_bbox: 0.1946, loss_mask: 0.2117, loss: 0.5991 2023-11-13 23:21:14,348 - mmdet - INFO - Epoch [9][4050/7330] lr: 1.000e-05, eta: 2:41:29, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0345, loss_cls: 0.1406, acc: 94.6255, loss_bbox: 0.1911, loss_mask: 0.2010, loss: 0.5808 2023-11-13 23:21:33,310 - mmdet - INFO - Epoch [9][4100/7330] lr: 1.000e-05, eta: 2:41:09, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0322, loss_cls: 0.1375, acc: 94.7380, loss_bbox: 0.1846, loss_mask: 0.2020, loss: 0.5706 2023-11-13 23:21:52,828 - mmdet - INFO - Epoch [9][4150/7330] lr: 1.000e-05, eta: 2:40:50, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0373, loss_cls: 0.1516, acc: 94.2463, loss_bbox: 0.2017, loss_mask: 0.2111, loss: 0.6175 2023-11-13 23:22:12,244 - mmdet - INFO - Epoch [9][4200/7330] lr: 1.000e-05, eta: 2:40:31, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0375, loss_cls: 0.1479, acc: 94.3276, loss_bbox: 0.1992, loss_mask: 0.2109, loss: 0.6125 2023-11-13 23:22:31,729 - mmdet - INFO - Epoch [9][4250/7330] lr: 1.000e-05, eta: 2:40:12, time: 0.390, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0382, loss_cls: 0.1545, acc: 94.0862, loss_bbox: 0.2077, loss_mask: 0.2115, loss: 0.6292 2023-11-13 23:22:51,462 - mmdet - INFO - Epoch [9][4300/7330] lr: 1.000e-05, eta: 2:39:53, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0348, loss_cls: 0.1407, acc: 94.5847, loss_bbox: 0.1878, loss_mask: 0.2033, loss: 0.5820 2023-11-13 23:23:10,441 - mmdet - INFO - Epoch [9][4350/7330] lr: 1.000e-05, eta: 2:39:34, time: 0.380, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0335, loss_cls: 0.1401, acc: 94.6062, loss_bbox: 0.1930, loss_mask: 0.2053, loss: 0.5862 2023-11-13 23:23:29,736 - mmdet - INFO - Epoch [9][4400/7330] lr: 1.000e-05, eta: 2:39:15, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0336, loss_cls: 0.1408, acc: 94.6277, loss_bbox: 0.1838, loss_mask: 0.2049, loss: 0.5780 2023-11-13 23:23:49,057 - mmdet - INFO - Epoch [9][4450/7330] lr: 1.000e-05, eta: 2:38:56, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0362, loss_cls: 0.1485, acc: 94.2524, loss_bbox: 0.2020, loss_mask: 0.2150, loss: 0.6168 2023-11-13 23:24:08,373 - mmdet - INFO - Epoch [9][4500/7330] lr: 1.000e-05, eta: 2:38:37, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0358, loss_cls: 0.1424, acc: 94.5698, loss_bbox: 0.1906, loss_mask: 0.2091, loss: 0.5912 2023-11-13 23:24:27,841 - mmdet - INFO - Epoch [9][4550/7330] lr: 1.000e-05, eta: 2:38:18, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0357, loss_cls: 0.1432, acc: 94.5134, loss_bbox: 0.1868, loss_mask: 0.2053, loss: 0.5861 2023-11-13 23:24:46,999 - mmdet - INFO - Epoch [9][4600/7330] lr: 1.000e-05, eta: 2:37:58, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0321, loss_cls: 0.1405, acc: 94.6494, loss_bbox: 0.1865, loss_mask: 0.2022, loss: 0.5757 2023-11-13 23:25:05,933 - mmdet - INFO - Epoch [9][4650/7330] lr: 1.000e-05, eta: 2:37:39, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0339, loss_cls: 0.1388, acc: 94.7837, loss_bbox: 0.1860, loss_mask: 0.2043, loss: 0.5772 2023-11-13 23:25:25,294 - mmdet - INFO - Epoch [9][4700/7330] lr: 1.000e-05, eta: 2:37:20, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0356, loss_cls: 0.1429, acc: 94.5913, loss_bbox: 0.1920, loss_mask: 0.2018, loss: 0.5878 2023-11-13 23:25:44,328 - mmdet - INFO - Epoch [9][4750/7330] lr: 1.000e-05, eta: 2:37:01, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0333, loss_cls: 0.1375, acc: 94.7756, loss_bbox: 0.1878, loss_mask: 0.2021, loss: 0.5750 2023-11-13 23:26:03,681 - mmdet - INFO - Epoch [9][4800/7330] lr: 1.000e-05, eta: 2:36:42, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0352, loss_cls: 0.1409, acc: 94.5859, loss_bbox: 0.1917, loss_mask: 0.2017, loss: 0.5830 2023-11-13 23:26:22,785 - mmdet - INFO - Epoch [9][4850/7330] lr: 1.000e-05, eta: 2:36:23, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0353, loss_cls: 0.1374, acc: 94.7073, loss_bbox: 0.1869, loss_mask: 0.2029, loss: 0.5764 2023-11-13 23:26:42,208 - mmdet - INFO - Epoch [9][4900/7330] lr: 1.000e-05, eta: 2:36:04, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0332, loss_cls: 0.1414, acc: 94.5974, loss_bbox: 0.1943, loss_mask: 0.2057, loss: 0.5901 2023-11-13 23:27:01,181 - mmdet - INFO - Epoch [9][4950/7330] lr: 1.000e-05, eta: 2:35:44, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0360, loss_cls: 0.1450, acc: 94.4382, loss_bbox: 0.1941, loss_mask: 0.2029, loss: 0.5946 2023-11-13 23:27:20,202 - mmdet - INFO - Epoch [9][5000/7330] lr: 1.000e-05, eta: 2:35:25, time: 0.380, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0335, loss_cls: 0.1400, acc: 94.6914, loss_bbox: 0.1918, loss_mask: 0.2065, loss: 0.5862 2023-11-13 23:27:39,338 - mmdet - INFO - Epoch [9][5050/7330] lr: 1.000e-05, eta: 2:35:06, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0351, loss_cls: 0.1425, acc: 94.5862, loss_bbox: 0.1953, loss_mask: 0.2058, loss: 0.5938 2023-11-13 23:27:58,702 - mmdet - INFO - Epoch [9][5100/7330] lr: 1.000e-05, eta: 2:34:47, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0360, loss_cls: 0.1433, acc: 94.5117, loss_bbox: 0.1945, loss_mask: 0.2038, loss: 0.5922 2023-11-13 23:28:17,859 - mmdet - INFO - Epoch [9][5150/7330] lr: 1.000e-05, eta: 2:34:28, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0366, loss_cls: 0.1500, acc: 94.3035, loss_bbox: 0.1987, loss_mask: 0.2119, loss: 0.6142 2023-11-13 23:28:37,057 - mmdet - INFO - Epoch [9][5200/7330] lr: 1.000e-05, eta: 2:34:08, time: 0.384, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0348, loss_cls: 0.1454, acc: 94.4355, loss_bbox: 0.1975, loss_mask: 0.2072, loss: 0.5997 2023-11-13 23:28:56,047 - mmdet - INFO - Epoch [9][5250/7330] lr: 1.000e-05, eta: 2:33:49, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0348, loss_cls: 0.1382, acc: 94.7944, loss_bbox: 0.1835, loss_mask: 0.2007, loss: 0.5704 2023-11-13 23:29:15,416 - mmdet - INFO - Epoch [9][5300/7330] lr: 1.000e-05, eta: 2:33:30, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0356, loss_cls: 0.1515, acc: 94.1528, loss_bbox: 0.2055, loss_mask: 0.2092, loss: 0.6171 2023-11-13 23:29:34,593 - mmdet - INFO - Epoch [9][5350/7330] lr: 1.000e-05, eta: 2:33:11, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0348, loss_cls: 0.1420, acc: 94.5552, loss_bbox: 0.1910, loss_mask: 0.2029, loss: 0.5851 2023-11-13 23:29:53,804 - mmdet - INFO - Epoch [9][5400/7330] lr: 1.000e-05, eta: 2:32:52, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0342, loss_cls: 0.1401, acc: 94.6611, loss_bbox: 0.1875, loss_mask: 0.2010, loss: 0.5782 2023-11-13 23:30:12,769 - mmdet - INFO - Epoch [9][5450/7330] lr: 1.000e-05, eta: 2:32:32, time: 0.379, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0337, loss_cls: 0.1384, acc: 94.6509, loss_bbox: 0.1883, loss_mask: 0.2040, loss: 0.5785 2023-11-13 23:30:31,802 - mmdet - INFO - Epoch [9][5500/7330] lr: 1.000e-05, eta: 2:32:13, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0333, loss_cls: 0.1386, acc: 94.6672, loss_bbox: 0.1826, loss_mask: 0.2028, loss: 0.5714 2023-11-13 23:30:50,736 - mmdet - INFO - Epoch [9][5550/7330] lr: 1.000e-05, eta: 2:31:54, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0336, loss_cls: 0.1377, acc: 94.7129, loss_bbox: 0.1857, loss_mask: 0.2015, loss: 0.5723 2023-11-13 23:31:09,868 - mmdet - INFO - Epoch [9][5600/7330] lr: 1.000e-05, eta: 2:31:35, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0336, loss_cls: 0.1401, acc: 94.6204, loss_bbox: 0.1953, loss_mask: 0.2078, loss: 0.5900 2023-11-13 23:31:29,687 - mmdet - INFO - Epoch [9][5650/7330] lr: 1.000e-05, eta: 2:31:16, time: 0.396, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0358, loss_cls: 0.1439, acc: 94.4421, loss_bbox: 0.1958, loss_mask: 0.2064, loss: 0.5963 2023-11-13 23:31:48,940 - mmdet - INFO - Epoch [9][5700/7330] lr: 1.000e-05, eta: 2:30:57, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0381, loss_cls: 0.1451, acc: 94.5134, loss_bbox: 0.1938, loss_mask: 0.2053, loss: 0.5989 2023-11-13 23:32:08,318 - mmdet - INFO - Epoch [9][5750/7330] lr: 1.000e-05, eta: 2:30:38, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0348, loss_cls: 0.1414, acc: 94.5505, loss_bbox: 0.1976, loss_mask: 0.2069, loss: 0.5960 2023-11-13 23:32:27,554 - mmdet - INFO - Epoch [9][5800/7330] lr: 1.000e-05, eta: 2:30:18, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0343, loss_cls: 0.1476, acc: 94.3572, loss_bbox: 0.1994, loss_mask: 0.2107, loss: 0.6065 2023-11-13 23:32:46,398 - mmdet - INFO - Epoch [9][5850/7330] lr: 1.000e-05, eta: 2:29:59, time: 0.377, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0342, loss_cls: 0.1382, acc: 94.7004, loss_bbox: 0.1875, loss_mask: 0.2069, loss: 0.5804 2023-11-13 23:33:05,457 - mmdet - INFO - Epoch [9][5900/7330] lr: 1.000e-05, eta: 2:29:40, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0333, loss_cls: 0.1405, acc: 94.6365, loss_bbox: 0.1898, loss_mask: 0.2042, loss: 0.5827 2023-11-13 23:33:24,633 - mmdet - INFO - Epoch [9][5950/7330] lr: 1.000e-05, eta: 2:29:21, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0377, loss_cls: 0.1360, acc: 94.7922, loss_bbox: 0.1881, loss_mask: 0.2044, loss: 0.5816 2023-11-13 23:33:43,802 - mmdet - INFO - Epoch [9][6000/7330] lr: 1.000e-05, eta: 2:29:02, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0334, loss_cls: 0.1367, acc: 94.7861, loss_bbox: 0.1857, loss_mask: 0.2031, loss: 0.5729 2023-11-13 23:34:03,155 - mmdet - INFO - Epoch [9][6050/7330] lr: 1.000e-05, eta: 2:28:43, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0344, loss_cls: 0.1390, acc: 94.6797, loss_bbox: 0.1868, loss_mask: 0.2024, loss: 0.5767 2023-11-13 23:34:22,165 - mmdet - INFO - Epoch [9][6100/7330] lr: 1.000e-05, eta: 2:28:23, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0319, loss_cls: 0.1374, acc: 94.6492, loss_bbox: 0.1876, loss_mask: 0.2053, loss: 0.5762 2023-11-13 23:34:41,500 - mmdet - INFO - Epoch [9][6150/7330] lr: 1.000e-05, eta: 2:28:04, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0376, loss_cls: 0.1477, acc: 94.3389, loss_bbox: 0.1961, loss_mask: 0.2079, loss: 0.6043 2023-11-13 23:35:00,679 - mmdet - INFO - Epoch [9][6200/7330] lr: 1.000e-05, eta: 2:27:45, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0347, loss_cls: 0.1441, acc: 94.3926, loss_bbox: 0.1939, loss_mask: 0.2052, loss: 0.5942 2023-11-13 23:35:19,680 - mmdet - INFO - Epoch [9][6250/7330] lr: 1.000e-05, eta: 2:27:26, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0345, loss_cls: 0.1486, acc: 94.3826, loss_bbox: 0.1971, loss_mask: 0.2076, loss: 0.6016 2023-11-13 23:35:38,721 - mmdet - INFO - Epoch [9][6300/7330] lr: 1.000e-05, eta: 2:27:07, time: 0.381, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0345, loss_cls: 0.1429, acc: 94.4485, loss_bbox: 0.1960, loss_mask: 0.2076, loss: 0.5950 2023-11-13 23:35:57,508 - mmdet - INFO - Epoch [9][6350/7330] lr: 1.000e-05, eta: 2:26:47, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0324, loss_cls: 0.1359, acc: 94.8281, loss_bbox: 0.1885, loss_mask: 0.2038, loss: 0.5749 2023-11-13 23:36:16,677 - mmdet - INFO - Epoch [9][6400/7330] lr: 1.000e-05, eta: 2:26:28, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0349, loss_cls: 0.1433, acc: 94.4858, loss_bbox: 0.1950, loss_mask: 0.2082, loss: 0.5959 2023-11-13 23:36:36,073 - mmdet - INFO - Epoch [9][6450/7330] lr: 1.000e-05, eta: 2:26:09, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0343, loss_cls: 0.1403, acc: 94.6387, loss_bbox: 0.1927, loss_mask: 0.2044, loss: 0.5875 2023-11-13 23:36:55,376 - mmdet - INFO - Epoch [9][6500/7330] lr: 1.000e-05, eta: 2:25:50, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0340, loss_cls: 0.1379, acc: 94.7063, loss_bbox: 0.1881, loss_mask: 0.2013, loss: 0.5759 2023-11-13 23:37:14,196 - mmdet - INFO - Epoch [9][6550/7330] lr: 1.000e-05, eta: 2:25:31, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0336, loss_cls: 0.1407, acc: 94.6470, loss_bbox: 0.1911, loss_mask: 0.2042, loss: 0.5838 2023-11-13 23:37:33,654 - mmdet - INFO - Epoch [9][6600/7330] lr: 1.000e-05, eta: 2:25:11, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0346, loss_cls: 0.1402, acc: 94.5745, loss_bbox: 0.1883, loss_mask: 0.2039, loss: 0.5823 2023-11-13 23:37:52,864 - mmdet - INFO - Epoch [9][6650/7330] lr: 1.000e-05, eta: 2:24:52, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0333, loss_cls: 0.1391, acc: 94.6809, loss_bbox: 0.1877, loss_mask: 0.2002, loss: 0.5743 2023-11-13 23:38:12,130 - mmdet - INFO - Epoch [9][6700/7330] lr: 1.000e-05, eta: 2:24:33, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0366, loss_cls: 0.1461, acc: 94.3237, loss_bbox: 0.1958, loss_mask: 0.2103, loss: 0.6044 2023-11-13 23:38:31,456 - mmdet - INFO - Epoch [9][6750/7330] lr: 1.000e-05, eta: 2:24:14, time: 0.387, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0366, loss_cls: 0.1463, acc: 94.3696, loss_bbox: 0.2011, loss_mask: 0.2175, loss: 0.6167 2023-11-13 23:38:50,798 - mmdet - INFO - Epoch [9][6800/7330] lr: 1.000e-05, eta: 2:23:55, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0352, loss_cls: 0.1418, acc: 94.5205, loss_bbox: 0.1931, loss_mask: 0.2067, loss: 0.5917 2023-11-13 23:39:10,689 - mmdet - INFO - Epoch [9][6850/7330] lr: 1.000e-05, eta: 2:23:36, time: 0.398, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0362, loss_cls: 0.1445, acc: 94.3936, loss_bbox: 0.1954, loss_mask: 0.2043, loss: 0.5951 2023-11-13 23:39:29,729 - mmdet - INFO - Epoch [9][6900/7330] lr: 1.000e-05, eta: 2:23:17, time: 0.381, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0345, loss_cls: 0.1461, acc: 94.4343, loss_bbox: 0.1988, loss_mask: 0.2105, loss: 0.6031 2023-11-13 23:39:48,969 - mmdet - INFO - Epoch [9][6950/7330] lr: 1.000e-05, eta: 2:22:58, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0351, loss_cls: 0.1443, acc: 94.4465, loss_bbox: 0.1923, loss_mask: 0.2086, loss: 0.5953 2023-11-13 23:40:07,838 - mmdet - INFO - Epoch [9][7000/7330] lr: 1.000e-05, eta: 2:22:38, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0342, loss_cls: 0.1423, acc: 94.5671, loss_bbox: 0.1902, loss_mask: 0.2033, loss: 0.5845 2023-11-13 23:40:26,829 - mmdet - INFO - Epoch [9][7050/7330] lr: 1.000e-05, eta: 2:22:19, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0318, loss_cls: 0.1375, acc: 94.7075, loss_bbox: 0.1879, loss_mask: 0.2064, loss: 0.5770 2023-11-13 23:40:45,983 - mmdet - INFO - Epoch [9][7100/7330] lr: 1.000e-05, eta: 2:22:00, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0361, loss_cls: 0.1423, acc: 94.5752, loss_bbox: 0.1889, loss_mask: 0.2032, loss: 0.5850 2023-11-13 23:41:04,941 - mmdet - INFO - Epoch [9][7150/7330] lr: 1.000e-05, eta: 2:21:41, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0345, loss_cls: 0.1424, acc: 94.5764, loss_bbox: 0.1912, loss_mask: 0.2062, loss: 0.5892 2023-11-13 23:41:24,101 - mmdet - INFO - Epoch [9][7200/7330] lr: 1.000e-05, eta: 2:21:22, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0330, loss_cls: 0.1375, acc: 94.7488, loss_bbox: 0.1885, loss_mask: 0.2000, loss: 0.5735 2023-11-13 23:41:43,464 - mmdet - INFO - Epoch [9][7250/7330] lr: 1.000e-05, eta: 2:21:02, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0340, loss_cls: 0.1426, acc: 94.4736, loss_bbox: 0.1934, loss_mask: 0.2059, loss: 0.5905 2023-11-13 23:42:02,554 - mmdet - INFO - Epoch [9][7300/7330] lr: 1.000e-05, eta: 2:20:43, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0316, loss_cls: 0.1328, acc: 94.8591, loss_bbox: 0.1832, loss_mask: 0.2019, loss: 0.5628 2023-11-13 23:42:14,388 - mmdet - INFO - Saving checkpoint at 9 epochs 2023-11-13 23:43:02,150 - mmdet - INFO - Evaluating bbox... 2023-11-13 23:43:32,230 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.489 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.705 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.538 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.323 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.531 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.640 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.607 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.607 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.607 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.427 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.651 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.764 2023-11-13 23:43:32,233 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.584 | bicycle | 0.384 | car | 0.492 | | motorcycle | 0.488 | airplane | 0.721 | bus | 0.700 | | train | 0.692 | truck | 0.435 | boat | 0.343 | | traffic light | 0.312 | fire hydrant | 0.739 | stop sign | 0.682 | | parking meter | 0.514 | bench | 0.321 | bird | 0.428 | | cat | 0.754 | dog | 0.709 | horse | 0.629 | | sheep | 0.596 | cow | 0.629 | elephant | 0.699 | | bear | 0.766 | zebra | 0.706 | giraffe | 0.729 | | backpack | 0.218 | umbrella | 0.471 | handbag | 0.232 | | tie | 0.401 | suitcase | 0.475 | frisbee | 0.705 | | skis | 0.314 | snowboard | 0.484 | sports ball | 0.479 | | kite | 0.479 | baseball bat | 0.408 | baseball glove | 0.436 | | skateboard | 0.608 | surfboard | 0.460 | tennis racket | 0.562 | | bottle | 0.461 | wine glass | 0.430 | cup | 0.503 | | fork | 0.468 | knife | 0.291 | spoon | 0.298 | | bowl | 0.477 | banana | 0.299 | apple | 0.269 | | sandwich | 0.464 | orange | 0.365 | broccoli | 0.258 | | carrot | 0.274 | hot dog | 0.475 | pizza | 0.545 | | donut | 0.559 | cake | 0.443 | chair | 0.364 | | couch | 0.483 | potted plant | 0.357 | bed | 0.477 | | dining table | 0.326 | toilet | 0.674 | tv | 0.630 | | laptop | 0.688 | mouse | 0.669 | remote | 0.428 | | keyboard | 0.565 | cell phone | 0.455 | microwave | 0.674 | | oven | 0.410 | toaster | 0.456 | sink | 0.449 | | refrigerator | 0.654 | book | 0.202 | clock | 0.540 | | vase | 0.432 | scissors | 0.417 | teddy bear | 0.549 | | hair drier | 0.213 | toothbrush | 0.331 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:43:32,233 - mmdet - INFO - Evaluating segm... 2023-11-13 23:44:04,690 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.677 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.474 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.238 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 ] = 0.629 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.371 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.713 2023-11-13 23:44:04,693 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.508 | bicycle | 0.224 | car | 0.455 | | motorcycle | 0.402 | airplane | 0.542 | bus | 0.689 | | train | 0.686 | truck | 0.415 | boat | 0.308 | | traffic light | 0.303 | fire hydrant | 0.710 | stop sign | 0.663 | | parking meter | 0.531 | bench | 0.246 | bird | 0.351 | | cat | 0.739 | dog | 0.664 | horse | 0.471 | | sheep | 0.521 | cow | 0.528 | elephant | 0.638 | | bear | 0.753 | zebra | 0.622 | giraffe | 0.561 | | backpack | 0.218 | umbrella | 0.517 | handbag | 0.220 | | tie | 0.368 | suitcase | 0.489 | frisbee | 0.676 | | skis | 0.066 | snowboard | 0.285 | sports ball | 0.481 | | kite | 0.342 | baseball bat | 0.315 | baseball glove | 0.465 | | skateboard | 0.376 | surfboard | 0.380 | tennis racket | 0.597 | | bottle | 0.444 | wine glass | 0.385 | cup | 0.505 | | fork | 0.246 | knife | 0.202 | spoon | 0.207 | | bowl | 0.446 | banana | 0.254 | apple | 0.262 | | sandwich | 0.470 | orange | 0.363 | broccoli | 0.238 | | carrot | 0.236 | hot dog | 0.374 | pizza | 0.528 | | donut | 0.555 | cake | 0.453 | chair | 0.262 | | couch | 0.399 | potted plant | 0.303 | bed | 0.396 | | dining table | 0.193 | toilet | 0.656 | tv | 0.656 | | laptop | 0.674 | mouse | 0.647 | remote | 0.383 | | keyboard | 0.556 | cell phone | 0.417 | microwave | 0.679 | | oven | 0.375 | toaster | 0.513 | sink | 0.411 | | refrigerator | 0.659 | book | 0.155 | clock | 0.541 | | vase | 0.428 | scissors | 0.311 | teddy bear | 0.526 | | hair drier | 0.147 | toothbrush | 0.234 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:44:05,111 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_8.pth was removed 2023-11-13 23:44:07,166 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_9.pth. 2023-11-13 23:44:07,166 - mmdet - INFO - Best bbox_mAP is 0.4888 at 9 epoch. 2023-11-13 23:44:07,167 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-13 23:44:07,167 - mmdet - INFO - Epoch(val) [9][625] bbox_mAP: 0.4888, bbox_mAP_50: 0.7048, bbox_mAP_75: 0.5383, bbox_mAP_s: 0.3227, bbox_mAP_m: 0.5309, bbox_mAP_l: 0.6400, bbox_mAP_copypaste: 0.4888 0.7048 0.5383 0.3227 0.5309 0.6400, segm_mAP: 0.4377, segm_mAP_50: 0.6774, segm_mAP_75: 0.4738, segm_mAP_s: 0.2379, segm_mAP_m: 0.4695, segm_mAP_l: 0.6294, segm_mAP_copypaste: 0.4377 0.6774 0.4738 0.2379 0.4695 0.6294 2023-11-13 23:44:30,065 - mmdet - INFO - Epoch [10][50/7330] lr: 1.000e-05, eta: 2:20:10, time: 0.458, data_time: 0.087, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0361, loss_cls: 0.1390, acc: 94.6763, loss_bbox: 0.1880, loss_mask: 0.2027, loss: 0.5793 2023-11-13 23:44:49,250 - mmdet - INFO - Epoch [10][100/7330] lr: 1.000e-05, eta: 2:19:51, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0326, loss_cls: 0.1407, acc: 94.5713, loss_bbox: 0.1851, loss_mask: 0.2031, loss: 0.5754 2023-11-13 23:45:08,592 - mmdet - INFO - Epoch [10][150/7330] lr: 1.000e-05, eta: 2:19:32, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0342, loss_cls: 0.1394, acc: 94.6907, loss_bbox: 0.1905, loss_mask: 0.2035, loss: 0.5815 2023-11-13 23:45:27,937 - mmdet - INFO - Epoch [10][200/7330] lr: 1.000e-05, eta: 2:19:13, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0342, loss_cls: 0.1432, acc: 94.5657, loss_bbox: 0.1911, loss_mask: 0.2037, loss: 0.5865 2023-11-13 23:45:47,313 - mmdet - INFO - Epoch [10][250/7330] lr: 1.000e-05, eta: 2:18:53, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0342, loss_cls: 0.1365, acc: 94.6733, loss_bbox: 0.1892, loss_mask: 0.2049, loss: 0.5795 2023-11-13 23:46:06,577 - mmdet - INFO - Epoch [10][300/7330] lr: 1.000e-05, eta: 2:18:34, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0351, loss_cls: 0.1437, acc: 94.5056, loss_bbox: 0.1949, loss_mask: 0.2086, loss: 0.5977 2023-11-13 23:46:25,913 - mmdet - INFO - Epoch [10][350/7330] lr: 1.000e-05, eta: 2:18:15, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0341, loss_cls: 0.1424, acc: 94.4521, loss_bbox: 0.1939, loss_mask: 0.2057, loss: 0.5922 2023-11-13 23:46:45,382 - mmdet - INFO - Epoch [10][400/7330] lr: 1.000e-05, eta: 2:17:56, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0340, loss_cls: 0.1381, acc: 94.7209, loss_bbox: 0.1909, loss_mask: 0.2048, loss: 0.5839 2023-11-13 23:47:05,016 - mmdet - INFO - Epoch [10][450/7330] lr: 1.000e-05, eta: 2:17:37, time: 0.393, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0370, loss_cls: 0.1500, acc: 94.2285, loss_bbox: 0.2014, loss_mask: 0.2148, loss: 0.6184 2023-11-13 23:47:24,441 - mmdet - INFO - Epoch [10][500/7330] lr: 1.000e-05, eta: 2:17:18, time: 0.388, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0360, loss_cls: 0.1442, acc: 94.4629, loss_bbox: 0.1937, loss_mask: 0.2065, loss: 0.5946 2023-11-13 23:47:43,719 - mmdet - INFO - Epoch [10][550/7330] lr: 1.000e-05, eta: 2:16:59, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0353, loss_cls: 0.1439, acc: 94.4722, loss_bbox: 0.1933, loss_mask: 0.2102, loss: 0.5971 2023-11-13 23:48:02,727 - mmdet - INFO - Epoch [10][600/7330] lr: 1.000e-05, eta: 2:16:40, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0348, loss_cls: 0.1414, acc: 94.5305, loss_bbox: 0.1933, loss_mask: 0.2060, loss: 0.5898 2023-11-13 23:48:21,880 - mmdet - INFO - Epoch [10][650/7330] lr: 1.000e-05, eta: 2:16:21, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0322, loss_cls: 0.1363, acc: 94.8125, loss_bbox: 0.1886, loss_mask: 0.2054, loss: 0.5764 2023-11-13 23:48:41,608 - mmdet - INFO - Epoch [10][700/7330] lr: 1.000e-05, eta: 2:16:02, time: 0.395, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0354, loss_cls: 0.1444, acc: 94.3853, loss_bbox: 0.1978, loss_mask: 0.2030, loss: 0.5953 2023-11-13 23:49:00,898 - mmdet - INFO - Epoch [10][750/7330] lr: 1.000e-05, eta: 2:15:42, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0342, loss_cls: 0.1416, acc: 94.5813, loss_bbox: 0.1900, loss_mask: 0.2005, loss: 0.5822 2023-11-13 23:49:20,013 - mmdet - INFO - Epoch [10][800/7330] lr: 1.000e-05, eta: 2:15:23, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0339, loss_cls: 0.1359, acc: 94.7883, loss_bbox: 0.1844, loss_mask: 0.2017, loss: 0.5689 2023-11-13 23:49:39,334 - mmdet - INFO - Epoch [10][850/7330] lr: 1.000e-05, eta: 2:15:04, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0354, loss_cls: 0.1413, acc: 94.5713, loss_bbox: 0.1928, loss_mask: 0.2034, loss: 0.5874 2023-11-13 23:49:58,196 - mmdet - INFO - Epoch [10][900/7330] lr: 1.000e-05, eta: 2:14:45, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0336, loss_cls: 0.1368, acc: 94.7148, loss_bbox: 0.1931, loss_mask: 0.2050, loss: 0.5822 2023-11-13 23:50:17,696 - mmdet - INFO - Epoch [10][950/7330] lr: 1.000e-05, eta: 2:14:26, time: 0.390, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0340, loss_cls: 0.1407, acc: 94.5774, loss_bbox: 0.1935, loss_mask: 0.2058, loss: 0.5893 2023-11-13 23:50:36,866 - mmdet - INFO - Epoch [10][1000/7330] lr: 1.000e-05, eta: 2:14:07, time: 0.383, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0340, loss_cls: 0.1387, acc: 94.6008, loss_bbox: 0.1946, loss_mask: 0.2031, loss: 0.5850 2023-11-13 23:50:56,113 - mmdet - INFO - Epoch [10][1050/7330] lr: 1.000e-05, eta: 2:13:47, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0348, loss_cls: 0.1456, acc: 94.4167, loss_bbox: 0.1917, loss_mask: 0.2035, loss: 0.5912 2023-11-13 23:51:15,126 - mmdet - INFO - Epoch [10][1100/7330] lr: 1.000e-05, eta: 2:13:28, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0323, loss_cls: 0.1336, acc: 94.8198, loss_bbox: 0.1842, loss_mask: 0.2032, loss: 0.5659 2023-11-13 23:51:34,193 - mmdet - INFO - Epoch [10][1150/7330] lr: 1.000e-05, eta: 2:13:09, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0349, loss_cls: 0.1436, acc: 94.4734, loss_bbox: 0.1935, loss_mask: 0.2050, loss: 0.5918 2023-11-13 23:51:53,483 - mmdet - INFO - Epoch [10][1200/7330] lr: 1.000e-05, eta: 2:12:50, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0344, loss_cls: 0.1346, acc: 94.8296, loss_bbox: 0.1835, loss_mask: 0.2054, loss: 0.5724 2023-11-13 23:52:12,703 - mmdet - INFO - Epoch [10][1250/7330] lr: 1.000e-05, eta: 2:12:31, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0355, loss_cls: 0.1391, acc: 94.5796, loss_bbox: 0.1878, loss_mask: 0.2036, loss: 0.5800 2023-11-13 23:52:31,778 - mmdet - INFO - Epoch [10][1300/7330] lr: 1.000e-05, eta: 2:12:12, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0351, loss_cls: 0.1385, acc: 94.6033, loss_bbox: 0.1909, loss_mask: 0.2006, loss: 0.5791 2023-11-13 23:52:50,718 - mmdet - INFO - Epoch [10][1350/7330] lr: 1.000e-05, eta: 2:11:52, time: 0.379, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0305, loss_cls: 0.1346, acc: 94.8105, loss_bbox: 0.1816, loss_mask: 0.1994, loss: 0.5595 2023-11-13 23:53:09,978 - mmdet - INFO - Epoch [10][1400/7330] lr: 1.000e-05, eta: 2:11:33, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0367, loss_cls: 0.1453, acc: 94.3950, loss_bbox: 0.1979, loss_mask: 0.2071, loss: 0.6016 2023-11-13 23:53:29,483 - mmdet - INFO - Epoch [10][1450/7330] lr: 1.000e-05, eta: 2:11:14, time: 0.390, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0320, loss_cls: 0.1323, acc: 94.8933, loss_bbox: 0.1840, loss_mask: 0.2004, loss: 0.5637 2023-11-13 23:53:48,933 - mmdet - INFO - Epoch [10][1500/7330] lr: 1.000e-05, eta: 2:10:55, time: 0.389, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0346, loss_cls: 0.1438, acc: 94.5435, loss_bbox: 0.1920, loss_mask: 0.2068, loss: 0.5926 2023-11-13 23:54:08,012 - mmdet - INFO - Epoch [10][1550/7330] lr: 1.000e-05, eta: 2:10:36, time: 0.382, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0348, loss_cls: 0.1422, acc: 94.5591, loss_bbox: 0.1935, loss_mask: 0.2036, loss: 0.5889 2023-11-13 23:54:26,883 - mmdet - INFO - Epoch [10][1600/7330] lr: 1.000e-05, eta: 2:10:17, time: 0.377, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0329, loss_cls: 0.1318, acc: 94.8955, loss_bbox: 0.1834, loss_mask: 0.2019, loss: 0.5629 2023-11-13 23:54:45,971 - mmdet - INFO - Epoch [10][1650/7330] lr: 1.000e-05, eta: 2:09:57, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0333, loss_cls: 0.1415, acc: 94.5435, loss_bbox: 0.1890, loss_mask: 0.2047, loss: 0.5839 2023-11-13 23:55:05,224 - mmdet - INFO - Epoch [10][1700/7330] lr: 1.000e-05, eta: 2:09:38, time: 0.385, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0335, loss_cls: 0.1348, acc: 94.9446, loss_bbox: 0.1841, loss_mask: 0.2002, loss: 0.5647 2023-11-13 23:55:24,463 - mmdet - INFO - Epoch [10][1750/7330] lr: 1.000e-05, eta: 2:09:19, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0353, loss_cls: 0.1446, acc: 94.4592, loss_bbox: 0.1967, loss_mask: 0.2043, loss: 0.5957 2023-11-13 23:55:43,695 - mmdet - INFO - Epoch [10][1800/7330] lr: 1.000e-05, eta: 2:09:00, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0354, loss_cls: 0.1440, acc: 94.4429, loss_bbox: 0.1976, loss_mask: 0.2079, loss: 0.5998 2023-11-13 23:56:03,365 - mmdet - INFO - Epoch [10][1850/7330] lr: 1.000e-05, eta: 2:08:41, time: 0.393, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0351, loss_cls: 0.1420, acc: 94.6108, loss_bbox: 0.1901, loss_mask: 0.2052, loss: 0.5870 2023-11-13 23:56:22,505 - mmdet - INFO - Epoch [10][1900/7330] lr: 1.000e-05, eta: 2:08:22, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0345, loss_cls: 0.1414, acc: 94.5913, loss_bbox: 0.1938, loss_mask: 0.2041, loss: 0.5893 2023-11-13 23:56:41,454 - mmdet - INFO - Epoch [10][1950/7330] lr: 1.000e-05, eta: 2:08:03, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0340, loss_cls: 0.1350, acc: 94.8440, loss_bbox: 0.1839, loss_mask: 0.1963, loss: 0.5619 2023-11-13 23:57:00,510 - mmdet - INFO - Epoch [10][2000/7330] lr: 1.000e-05, eta: 2:07:43, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0330, loss_cls: 0.1378, acc: 94.7366, loss_bbox: 0.1875, loss_mask: 0.1998, loss: 0.5721 2023-11-13 23:57:19,808 - mmdet - INFO - Epoch [10][2050/7330] lr: 1.000e-05, eta: 2:07:24, time: 0.386, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0340, loss_cls: 0.1408, acc: 94.5820, loss_bbox: 0.1941, loss_mask: 0.2004, loss: 0.5834 2023-11-13 23:57:38,936 - mmdet - INFO - Epoch [10][2100/7330] lr: 1.000e-05, eta: 2:07:05, time: 0.383, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0334, loss_cls: 0.1350, acc: 94.9153, loss_bbox: 0.1801, loss_mask: 0.1998, loss: 0.5615 2023-11-13 23:57:58,510 - mmdet - INFO - Epoch [10][2150/7330] lr: 1.000e-05, eta: 2:06:46, time: 0.391, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0383, loss_cls: 0.1474, acc: 94.2766, loss_bbox: 0.2012, loss_mask: 0.2086, loss: 0.6115 2023-11-13 23:58:18,254 - mmdet - INFO - Epoch [10][2200/7330] lr: 1.000e-05, eta: 2:06:27, time: 0.395, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0363, loss_cls: 0.1458, acc: 94.4260, loss_bbox: 0.1997, loss_mask: 0.2115, loss: 0.6079 2023-11-13 23:58:37,561 - mmdet - INFO - Epoch [10][2250/7330] lr: 1.000e-05, eta: 2:06:08, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0331, loss_cls: 0.1331, acc: 94.8938, loss_bbox: 0.1850, loss_mask: 0.1988, loss: 0.5635 2023-11-13 23:58:56,604 - mmdet - INFO - Epoch [10][2300/7330] lr: 1.000e-05, eta: 2:05:49, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0337, loss_cls: 0.1390, acc: 94.6270, loss_bbox: 0.1916, loss_mask: 0.2014, loss: 0.5785 2023-11-13 23:59:15,796 - mmdet - INFO - Epoch [10][2350/7330] lr: 1.000e-05, eta: 2:05:29, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0338, loss_cls: 0.1401, acc: 94.6472, loss_bbox: 0.1875, loss_mask: 0.2050, loss: 0.5808 2023-11-13 23:59:34,582 - mmdet - INFO - Epoch [10][2400/7330] lr: 1.000e-05, eta: 2:05:10, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0329, loss_cls: 0.1349, acc: 94.8445, loss_bbox: 0.1839, loss_mask: 0.2040, loss: 0.5697 2023-11-13 23:59:53,641 - mmdet - INFO - Epoch [10][2450/7330] lr: 1.000e-05, eta: 2:04:51, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0330, loss_cls: 0.1375, acc: 94.7034, loss_bbox: 0.1854, loss_mask: 0.2043, loss: 0.5749 2023-11-14 00:00:12,764 - mmdet - INFO - Epoch [10][2500/7330] lr: 1.000e-05, eta: 2:04:32, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0332, loss_cls: 0.1396, acc: 94.6101, loss_bbox: 0.1936, loss_mask: 0.2016, loss: 0.5827 2023-11-14 00:00:32,238 - mmdet - INFO - Epoch [10][2550/7330] lr: 1.000e-05, eta: 2:04:13, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0333, loss_cls: 0.1369, acc: 94.7649, loss_bbox: 0.1840, loss_mask: 0.2019, loss: 0.5705 2023-11-14 00:00:51,275 - mmdet - INFO - Epoch [10][2600/7330] lr: 1.000e-05, eta: 2:03:53, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0349, loss_cls: 0.1451, acc: 94.4534, loss_bbox: 0.1985, loss_mask: 0.2096, loss: 0.6014 2023-11-14 00:01:10,213 - mmdet - INFO - Epoch [10][2650/7330] lr: 1.000e-05, eta: 2:03:34, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0327, loss_cls: 0.1322, acc: 94.8894, loss_bbox: 0.1792, loss_mask: 0.2012, loss: 0.5584 2023-11-14 00:01:29,357 - mmdet - INFO - Epoch [10][2700/7330] lr: 1.000e-05, eta: 2:03:15, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0336, loss_cls: 0.1367, acc: 94.6697, loss_bbox: 0.1889, loss_mask: 0.2023, loss: 0.5757 2023-11-14 00:01:48,877 - mmdet - INFO - Epoch [10][2750/7330] lr: 1.000e-05, eta: 2:02:56, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0355, loss_cls: 0.1430, acc: 94.5127, loss_bbox: 0.1908, loss_mask: 0.2012, loss: 0.5860 2023-11-14 00:02:08,644 - mmdet - INFO - Epoch [10][2800/7330] lr: 1.000e-05, eta: 2:02:37, time: 0.395, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0365, loss_cls: 0.1408, acc: 94.5715, loss_bbox: 0.1906, loss_mask: 0.2071, loss: 0.5900 2023-11-14 00:02:27,797 - mmdet - INFO - Epoch [10][2850/7330] lr: 1.000e-05, eta: 2:02:18, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0344, loss_cls: 0.1418, acc: 94.5356, loss_bbox: 0.1951, loss_mask: 0.2083, loss: 0.5947 2023-11-14 00:02:46,832 - mmdet - INFO - Epoch [10][2900/7330] lr: 1.000e-05, eta: 2:01:59, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0343, loss_cls: 0.1400, acc: 94.5210, loss_bbox: 0.1949, loss_mask: 0.2122, loss: 0.5955 2023-11-14 00:03:05,672 - mmdet - INFO - Epoch [10][2950/7330] lr: 1.000e-05, eta: 2:01:39, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0326, loss_cls: 0.1393, acc: 94.6501, loss_bbox: 0.1916, loss_mask: 0.2019, loss: 0.5796 2023-11-14 00:03:24,766 - mmdet - INFO - Epoch [10][3000/7330] lr: 1.000e-05, eta: 2:01:20, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0353, loss_cls: 0.1448, acc: 94.4229, loss_bbox: 0.1982, loss_mask: 0.2122, loss: 0.6051 2023-11-14 00:03:43,809 - mmdet - INFO - Epoch [10][3050/7330] lr: 1.000e-05, eta: 2:01:01, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0347, loss_cls: 0.1385, acc: 94.5840, loss_bbox: 0.1899, loss_mask: 0.2084, loss: 0.5855 2023-11-14 00:04:03,172 - mmdet - INFO - Epoch [10][3100/7330] lr: 1.000e-05, eta: 2:00:42, time: 0.387, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0347, loss_cls: 0.1380, acc: 94.7253, loss_bbox: 0.1887, loss_mask: 0.2013, loss: 0.5774 2023-11-14 00:04:22,339 - mmdet - INFO - Epoch [10][3150/7330] lr: 1.000e-05, eta: 2:00:23, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0335, loss_cls: 0.1334, acc: 94.9089, loss_bbox: 0.1815, loss_mask: 0.2020, loss: 0.5635 2023-11-14 00:04:41,215 - mmdet - INFO - Epoch [10][3200/7330] lr: 1.000e-05, eta: 2:00:03, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0335, loss_cls: 0.1321, acc: 94.9412, loss_bbox: 0.1795, loss_mask: 0.2033, loss: 0.5612 2023-11-14 00:05:00,070 - mmdet - INFO - Epoch [10][3250/7330] lr: 1.000e-05, eta: 1:59:44, time: 0.377, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0336, loss_cls: 0.1435, acc: 94.5051, loss_bbox: 0.1904, loss_mask: 0.2074, loss: 0.5891 2023-11-14 00:05:19,415 - mmdet - INFO - Epoch [10][3300/7330] lr: 1.000e-05, eta: 1:59:25, time: 0.387, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0372, loss_cls: 0.1491, acc: 94.2400, loss_bbox: 0.2020, loss_mask: 0.2101, loss: 0.6158 2023-11-14 00:05:38,924 - mmdet - INFO - Epoch [10][3350/7330] lr: 1.000e-05, eta: 1:59:06, time: 0.390, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0366, loss_cls: 0.1431, acc: 94.4832, loss_bbox: 0.1956, loss_mask: 0.2033, loss: 0.5934 2023-11-14 00:05:58,220 - mmdet - INFO - Epoch [10][3400/7330] lr: 1.000e-05, eta: 1:58:47, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0362, loss_cls: 0.1451, acc: 94.4136, loss_bbox: 0.2014, loss_mask: 0.2098, loss: 0.6071 2023-11-14 00:06:17,495 - mmdet - INFO - Epoch [10][3450/7330] lr: 1.000e-05, eta: 1:58:28, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0358, loss_cls: 0.1392, acc: 94.6372, loss_bbox: 0.1897, loss_mask: 0.2043, loss: 0.5833 2023-11-14 00:06:36,907 - mmdet - INFO - Epoch [10][3500/7330] lr: 1.000e-05, eta: 1:58:09, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0345, loss_cls: 0.1351, acc: 94.7644, loss_bbox: 0.1846, loss_mask: 0.2021, loss: 0.5698 2023-11-14 00:06:55,772 - mmdet - INFO - Epoch [10][3550/7330] lr: 1.000e-05, eta: 1:57:49, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0361, loss_cls: 0.1406, acc: 94.5925, loss_bbox: 0.1939, loss_mask: 0.2058, loss: 0.5904 2023-11-14 00:07:15,058 - mmdet - INFO - Epoch [10][3600/7330] lr: 1.000e-05, eta: 1:57:30, time: 0.386, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0317, loss_cls: 0.1306, acc: 94.9189, loss_bbox: 0.1788, loss_mask: 0.1948, loss: 0.5492 2023-11-14 00:07:34,428 - mmdet - INFO - Epoch [10][3650/7330] lr: 1.000e-05, eta: 1:57:11, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0341, loss_cls: 0.1415, acc: 94.5684, loss_bbox: 0.1918, loss_mask: 0.2041, loss: 0.5865 2023-11-14 00:07:53,789 - mmdet - INFO - Epoch [10][3700/7330] lr: 1.000e-05, eta: 1:56:52, time: 0.387, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0337, loss_cls: 0.1344, acc: 94.8252, loss_bbox: 0.1819, loss_mask: 0.1982, loss: 0.5623 2023-11-14 00:08:13,031 - mmdet - INFO - Epoch [10][3750/7330] lr: 1.000e-05, eta: 1:56:33, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0359, loss_cls: 0.1379, acc: 94.7019, loss_bbox: 0.1892, loss_mask: 0.2035, loss: 0.5803 2023-11-14 00:08:32,641 - mmdet - INFO - Epoch [10][3800/7330] lr: 1.000e-05, eta: 1:56:14, time: 0.392, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0354, loss_cls: 0.1412, acc: 94.5308, loss_bbox: 0.1905, loss_mask: 0.2013, loss: 0.5828 2023-11-14 00:08:51,449 - mmdet - INFO - Epoch [10][3850/7330] lr: 1.000e-05, eta: 1:55:54, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0320, loss_cls: 0.1306, acc: 94.9673, loss_bbox: 0.1790, loss_mask: 0.1969, loss: 0.5517 2023-11-14 00:09:10,675 - mmdet - INFO - Epoch [10][3900/7330] lr: 1.000e-05, eta: 1:55:35, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0358, loss_cls: 0.1464, acc: 94.3716, loss_bbox: 0.1970, loss_mask: 0.2033, loss: 0.5984 2023-11-14 00:09:29,823 - mmdet - INFO - Epoch [10][3950/7330] lr: 1.000e-05, eta: 1:55:16, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0347, loss_cls: 0.1389, acc: 94.7263, loss_bbox: 0.1917, loss_mask: 0.2046, loss: 0.5833 2023-11-14 00:09:48,857 - mmdet - INFO - Epoch [10][4000/7330] lr: 1.000e-05, eta: 1:54:57, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0360, loss_cls: 0.1427, acc: 94.4802, loss_bbox: 0.1941, loss_mask: 0.2042, loss: 0.5910 2023-11-14 00:10:08,297 - mmdet - INFO - Epoch [10][4050/7330] lr: 1.000e-05, eta: 1:54:38, time: 0.389, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0348, loss_cls: 0.1395, acc: 94.6057, loss_bbox: 0.1883, loss_mask: 0.2033, loss: 0.5808 2023-11-14 00:10:27,687 - mmdet - INFO - Epoch [10][4100/7330] lr: 1.000e-05, eta: 1:54:19, time: 0.388, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0370, loss_cls: 0.1486, acc: 94.2583, loss_bbox: 0.1979, loss_mask: 0.2009, loss: 0.5995 2023-11-14 00:10:46,674 - mmdet - INFO - Epoch [10][4150/7330] lr: 1.000e-05, eta: 1:54:00, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0356, loss_cls: 0.1375, acc: 94.7039, loss_bbox: 0.1864, loss_mask: 0.2006, loss: 0.5743 2023-11-14 00:11:05,779 - mmdet - INFO - Epoch [10][4200/7330] lr: 1.000e-05, eta: 1:53:40, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0345, loss_cls: 0.1447, acc: 94.5315, loss_bbox: 0.1950, loss_mask: 0.2059, loss: 0.5941 2023-11-14 00:11:24,806 - mmdet - INFO - Epoch [10][4250/7330] lr: 1.000e-05, eta: 1:53:21, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0360, loss_cls: 0.1503, acc: 94.2317, loss_bbox: 0.2008, loss_mask: 0.2103, loss: 0.6137 2023-11-14 00:11:44,073 - mmdet - INFO - Epoch [10][4300/7330] lr: 1.000e-05, eta: 1:53:02, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0341, loss_cls: 0.1373, acc: 94.7104, loss_bbox: 0.1884, loss_mask: 0.2017, loss: 0.5760 2023-11-14 00:12:03,217 - mmdet - INFO - Epoch [10][4350/7330] lr: 1.000e-05, eta: 1:52:43, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0347, loss_cls: 0.1421, acc: 94.5027, loss_bbox: 0.1934, loss_mask: 0.2084, loss: 0.5934 2023-11-14 00:12:22,325 - mmdet - INFO - Epoch [10][4400/7330] lr: 1.000e-05, eta: 1:52:24, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0345, loss_cls: 0.1389, acc: 94.7441, loss_bbox: 0.1862, loss_mask: 0.2013, loss: 0.5751 2023-11-14 00:12:41,403 - mmdet - INFO - Epoch [10][4450/7330] lr: 1.000e-05, eta: 1:52:04, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0352, loss_cls: 0.1454, acc: 94.4878, loss_bbox: 0.1954, loss_mask: 0.2107, loss: 0.6014 2023-11-14 00:13:00,995 - mmdet - INFO - Epoch [10][4500/7330] lr: 1.000e-05, eta: 1:51:45, time: 0.392, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0355, loss_cls: 0.1467, acc: 94.3992, loss_bbox: 0.2006, loss_mask: 0.2060, loss: 0.6030 2023-11-14 00:13:19,954 - mmdet - INFO - Epoch [10][4550/7330] lr: 1.000e-05, eta: 1:51:26, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0341, loss_cls: 0.1408, acc: 94.5220, loss_bbox: 0.1913, loss_mask: 0.2006, loss: 0.5803 2023-11-14 00:13:38,841 - mmdet - INFO - Epoch [10][4600/7330] lr: 1.000e-05, eta: 1:51:07, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0344, loss_cls: 0.1363, acc: 94.7734, loss_bbox: 0.1890, loss_mask: 0.2042, loss: 0.5781 2023-11-14 00:13:58,219 - mmdet - INFO - Epoch [10][4650/7330] lr: 1.000e-05, eta: 1:50:48, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0356, loss_cls: 0.1433, acc: 94.4331, loss_bbox: 0.1964, loss_mask: 0.2080, loss: 0.5996 2023-11-14 00:14:17,904 - mmdet - INFO - Epoch [10][4700/7330] lr: 1.000e-05, eta: 1:50:29, time: 0.394, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0364, loss_cls: 0.1481, acc: 94.2925, loss_bbox: 0.1986, loss_mask: 0.2099, loss: 0.6088 2023-11-14 00:14:36,929 - mmdet - INFO - Epoch [10][4750/7330] lr: 1.000e-05, eta: 1:50:10, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0331, loss_cls: 0.1377, acc: 94.6853, loss_bbox: 0.1875, loss_mask: 0.2023, loss: 0.5750 2023-11-14 00:14:55,968 - mmdet - INFO - Epoch [10][4800/7330] lr: 1.000e-05, eta: 1:49:50, time: 0.381, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0332, loss_cls: 0.1410, acc: 94.5562, loss_bbox: 0.1906, loss_mask: 0.2025, loss: 0.5814 2023-11-14 00:15:15,052 - mmdet - INFO - Epoch [10][4850/7330] lr: 1.000e-05, eta: 1:49:31, time: 0.382, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0328, loss_cls: 0.1343, acc: 94.8938, loss_bbox: 0.1817, loss_mask: 0.2026, loss: 0.5643 2023-11-14 00:15:34,294 - mmdet - INFO - Epoch [10][4900/7330] lr: 1.000e-05, eta: 1:49:12, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0342, loss_cls: 0.1382, acc: 94.7410, loss_bbox: 0.1902, loss_mask: 0.2037, loss: 0.5801 2023-11-14 00:15:53,583 - mmdet - INFO - Epoch [10][4950/7330] lr: 1.000e-05, eta: 1:48:53, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0355, loss_cls: 0.1383, acc: 94.7285, loss_bbox: 0.1887, loss_mask: 0.2067, loss: 0.5832 2023-11-14 00:16:13,078 - mmdet - INFO - Epoch [10][5000/7330] lr: 1.000e-05, eta: 1:48:34, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0355, loss_cls: 0.1446, acc: 94.5208, loss_bbox: 0.1900, loss_mask: 0.2035, loss: 0.5901 2023-11-14 00:16:32,053 - mmdet - INFO - Epoch [10][5050/7330] lr: 1.000e-05, eta: 1:48:15, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0341, loss_cls: 0.1399, acc: 94.6675, loss_bbox: 0.1921, loss_mask: 0.2020, loss: 0.5830 2023-11-14 00:16:51,190 - mmdet - INFO - Epoch [10][5100/7330] lr: 1.000e-05, eta: 1:47:55, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0313, loss_cls: 0.1329, acc: 94.8962, loss_bbox: 0.1823, loss_mask: 0.2029, loss: 0.5624 2023-11-14 00:17:09,963 - mmdet - INFO - Epoch [10][5150/7330] lr: 1.000e-05, eta: 1:47:36, time: 0.376, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0325, loss_cls: 0.1365, acc: 94.7275, loss_bbox: 0.1838, loss_mask: 0.1998, loss: 0.5667 2023-11-14 00:17:29,254 - mmdet - INFO - Epoch [10][5200/7330] lr: 1.000e-05, eta: 1:47:17, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0341, loss_cls: 0.1335, acc: 94.8521, loss_bbox: 0.1798, loss_mask: 0.1992, loss: 0.5609 2023-11-14 00:17:48,438 - mmdet - INFO - Epoch [10][5250/7330] lr: 1.000e-05, eta: 1:46:58, time: 0.384, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0358, loss_cls: 0.1356, acc: 94.7556, loss_bbox: 0.1868, loss_mask: 0.2018, loss: 0.5744 2023-11-14 00:18:07,662 - mmdet - INFO - Epoch [10][5300/7330] lr: 1.000e-05, eta: 1:46:39, time: 0.384, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0365, loss_cls: 0.1370, acc: 94.6536, loss_bbox: 0.1904, loss_mask: 0.2041, loss: 0.5818 2023-11-14 00:18:26,791 - mmdet - INFO - Epoch [10][5350/7330] lr: 1.000e-05, eta: 1:46:19, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0331, loss_cls: 0.1428, acc: 94.5967, loss_bbox: 0.1906, loss_mask: 0.2015, loss: 0.5820 2023-11-14 00:18:45,940 - mmdet - INFO - Epoch [10][5400/7330] lr: 1.000e-05, eta: 1:46:00, time: 0.383, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0348, loss_cls: 0.1390, acc: 94.6536, loss_bbox: 0.1880, loss_mask: 0.2053, loss: 0.5811 2023-11-14 00:19:05,252 - mmdet - INFO - Epoch [10][5450/7330] lr: 1.000e-05, eta: 1:45:41, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0345, loss_cls: 0.1356, acc: 94.8237, loss_bbox: 0.1854, loss_mask: 0.2008, loss: 0.5704 2023-11-14 00:19:24,936 - mmdet - INFO - Epoch [10][5500/7330] lr: 1.000e-05, eta: 1:45:22, time: 0.394, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0365, loss_cls: 0.1458, acc: 94.4231, loss_bbox: 0.1990, loss_mask: 0.2099, loss: 0.6076 2023-11-14 00:19:43,993 - mmdet - INFO - Epoch [10][5550/7330] lr: 1.000e-05, eta: 1:45:03, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0362, loss_cls: 0.1472, acc: 94.3376, loss_bbox: 0.1976, loss_mask: 0.2099, loss: 0.6068 2023-11-14 00:20:02,988 - mmdet - INFO - Epoch [10][5600/7330] lr: 1.000e-05, eta: 1:44:44, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0317, loss_cls: 0.1304, acc: 94.9111, loss_bbox: 0.1797, loss_mask: 0.2002, loss: 0.5542 2023-11-14 00:20:22,255 - mmdet - INFO - Epoch [10][5650/7330] lr: 1.000e-05, eta: 1:44:25, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0361, loss_cls: 0.1429, acc: 94.4438, loss_bbox: 0.1907, loss_mask: 0.2051, loss: 0.5906 2023-11-14 00:20:41,396 - mmdet - INFO - Epoch [10][5700/7330] lr: 1.000e-05, eta: 1:44:05, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0338, loss_cls: 0.1342, acc: 94.7773, loss_bbox: 0.1826, loss_mask: 0.2037, loss: 0.5678 2023-11-14 00:21:00,694 - mmdet - INFO - Epoch [10][5750/7330] lr: 1.000e-05, eta: 1:43:46, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0344, loss_cls: 0.1385, acc: 94.6653, loss_bbox: 0.1897, loss_mask: 0.2045, loss: 0.5808 2023-11-14 00:21:20,233 - mmdet - INFO - Epoch [10][5800/7330] lr: 1.000e-05, eta: 1:43:27, time: 0.391, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0337, loss_cls: 0.1406, acc: 94.5828, loss_bbox: 0.1919, loss_mask: 0.2012, loss: 0.5811 2023-11-14 00:21:39,154 - mmdet - INFO - Epoch [10][5850/7330] lr: 1.000e-05, eta: 1:43:08, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0343, loss_cls: 0.1378, acc: 94.6826, loss_bbox: 0.1876, loss_mask: 0.2008, loss: 0.5736 2023-11-14 00:21:58,245 - mmdet - INFO - Epoch [10][5900/7330] lr: 1.000e-05, eta: 1:42:49, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0310, loss_cls: 0.1339, acc: 94.8904, loss_bbox: 0.1864, loss_mask: 0.2033, loss: 0.5672 2023-11-14 00:22:17,629 - mmdet - INFO - Epoch [10][5950/7330] lr: 1.000e-05, eta: 1:42:30, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0362, loss_cls: 0.1395, acc: 94.5581, loss_bbox: 0.1936, loss_mask: 0.2056, loss: 0.5906 2023-11-14 00:22:37,070 - mmdet - INFO - Epoch [10][6000/7330] lr: 1.000e-05, eta: 1:42:10, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0349, loss_cls: 0.1439, acc: 94.4714, loss_bbox: 0.1941, loss_mask: 0.2058, loss: 0.5939 2023-11-14 00:22:56,445 - mmdet - INFO - Epoch [10][6050/7330] lr: 1.000e-05, eta: 1:41:51, time: 0.388, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0343, loss_cls: 0.1378, acc: 94.7141, loss_bbox: 0.1886, loss_mask: 0.2028, loss: 0.5785 2023-11-14 00:23:15,646 - mmdet - INFO - Epoch [10][6100/7330] lr: 1.000e-05, eta: 1:41:32, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0324, loss_cls: 0.1335, acc: 94.8181, loss_bbox: 0.1821, loss_mask: 0.1986, loss: 0.5606 2023-11-14 00:23:35,006 - mmdet - INFO - Epoch [10][6150/7330] lr: 1.000e-05, eta: 1:41:13, time: 0.387, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0340, loss_cls: 0.1396, acc: 94.6135, loss_bbox: 0.1898, loss_mask: 0.2021, loss: 0.5792 2023-11-14 00:23:53,812 - mmdet - INFO - Epoch [10][6200/7330] lr: 1.000e-05, eta: 1:40:54, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0325, loss_cls: 0.1372, acc: 94.7424, loss_bbox: 0.1885, loss_mask: 0.2065, loss: 0.5781 2023-11-14 00:24:12,832 - mmdet - INFO - Epoch [10][6250/7330] lr: 1.000e-05, eta: 1:40:35, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0351, loss_cls: 0.1414, acc: 94.4895, loss_bbox: 0.1978, loss_mask: 0.2083, loss: 0.5961 2023-11-14 00:24:31,965 - mmdet - INFO - Epoch [10][6300/7330] lr: 1.000e-05, eta: 1:40:15, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0331, loss_cls: 0.1353, acc: 94.8452, loss_bbox: 0.1862, loss_mask: 0.2069, loss: 0.5767 2023-11-14 00:24:50,887 - mmdet - INFO - Epoch [10][6350/7330] lr: 1.000e-05, eta: 1:39:56, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0335, loss_cls: 0.1380, acc: 94.6213, loss_bbox: 0.1915, loss_mask: 0.2043, loss: 0.5803 2023-11-14 00:25:10,061 - mmdet - INFO - Epoch [10][6400/7330] lr: 1.000e-05, eta: 1:39:37, time: 0.383, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0333, loss_cls: 0.1384, acc: 94.6777, loss_bbox: 0.1881, loss_mask: 0.1983, loss: 0.5719 2023-11-14 00:25:29,069 - mmdet - INFO - Epoch [10][6450/7330] lr: 1.000e-05, eta: 1:39:18, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0346, loss_cls: 0.1351, acc: 94.8477, loss_bbox: 0.1873, loss_mask: 0.2000, loss: 0.5703 2023-11-14 00:25:48,329 - mmdet - INFO - Epoch [10][6500/7330] lr: 1.000e-05, eta: 1:38:59, time: 0.385, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0370, loss_cls: 0.1488, acc: 94.3274, loss_bbox: 0.2013, loss_mask: 0.2091, loss: 0.6119 2023-11-14 00:26:07,249 - mmdet - INFO - Epoch [10][6550/7330] lr: 1.000e-05, eta: 1:38:39, time: 0.378, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0321, loss_cls: 0.1331, acc: 94.9414, loss_bbox: 0.1796, loss_mask: 0.1992, loss: 0.5571 2023-11-14 00:26:26,373 - mmdet - INFO - Epoch [10][6600/7330] lr: 1.000e-05, eta: 1:38:20, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0348, loss_cls: 0.1424, acc: 94.5574, loss_bbox: 0.1956, loss_mask: 0.2065, loss: 0.5940 2023-11-14 00:26:45,441 - mmdet - INFO - Epoch [10][6650/7330] lr: 1.000e-05, eta: 1:38:01, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0332, loss_cls: 0.1389, acc: 94.7195, loss_bbox: 0.1904, loss_mask: 0.2044, loss: 0.5807 2023-11-14 00:27:04,809 - mmdet - INFO - Epoch [10][6700/7330] lr: 1.000e-05, eta: 1:37:42, time: 0.387, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0354, loss_cls: 0.1457, acc: 94.3811, loss_bbox: 0.1953, loss_mask: 0.2055, loss: 0.5963 2023-11-14 00:27:23,949 - mmdet - INFO - Epoch [10][6750/7330] lr: 1.000e-05, eta: 1:37:23, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0322, loss_cls: 0.1361, acc: 94.7642, loss_bbox: 0.1859, loss_mask: 0.2029, loss: 0.5704 2023-11-14 00:27:42,889 - mmdet - INFO - Epoch [10][6800/7330] lr: 1.000e-05, eta: 1:37:04, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0324, loss_cls: 0.1361, acc: 94.7817, loss_bbox: 0.1845, loss_mask: 0.2000, loss: 0.5659 2023-11-14 00:28:01,432 - mmdet - INFO - Epoch [10][6850/7330] lr: 1.000e-05, eta: 1:36:44, time: 0.371, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0339, loss_cls: 0.1371, acc: 94.6921, loss_bbox: 0.1839, loss_mask: 0.2010, loss: 0.5695 2023-11-14 00:28:20,597 - mmdet - INFO - Epoch [10][6900/7330] lr: 1.000e-05, eta: 1:36:25, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0323, loss_cls: 0.1405, acc: 94.5903, loss_bbox: 0.1870, loss_mask: 0.2079, loss: 0.5822 2023-11-14 00:28:39,642 - mmdet - INFO - Epoch [10][6950/7330] lr: 1.000e-05, eta: 1:36:06, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0343, loss_cls: 0.1380, acc: 94.7581, loss_bbox: 0.1825, loss_mask: 0.2011, loss: 0.5698 2023-11-14 00:28:58,754 - mmdet - INFO - Epoch [10][7000/7330] lr: 1.000e-05, eta: 1:35:47, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0348, loss_cls: 0.1421, acc: 94.4541, loss_bbox: 0.1936, loss_mask: 0.2057, loss: 0.5909 2023-11-14 00:29:18,056 - mmdet - INFO - Epoch [10][7050/7330] lr: 1.000e-05, eta: 1:35:28, time: 0.386, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0328, loss_cls: 0.1333, acc: 94.9080, loss_bbox: 0.1814, loss_mask: 0.1964, loss: 0.5580 2023-11-14 00:29:37,208 - mmdet - INFO - Epoch [10][7100/7330] lr: 1.000e-05, eta: 1:35:08, time: 0.383, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0348, loss_cls: 0.1435, acc: 94.4905, loss_bbox: 0.1943, loss_mask: 0.2091, loss: 0.5957 2023-11-14 00:29:56,492 - mmdet - INFO - Epoch [10][7150/7330] lr: 1.000e-05, eta: 1:34:49, time: 0.386, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0325, loss_cls: 0.1357, acc: 94.8176, loss_bbox: 0.1863, loss_mask: 0.2012, loss: 0.5695 2023-11-14 00:30:15,500 - mmdet - INFO - Epoch [10][7200/7330] lr: 1.000e-05, eta: 1:34:30, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0320, loss_cls: 0.1331, acc: 94.9355, loss_bbox: 0.1815, loss_mask: 0.1993, loss: 0.5606 2023-11-14 00:30:34,791 - mmdet - INFO - Epoch [10][7250/7330] lr: 1.000e-05, eta: 1:34:11, time: 0.386, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0330, loss_cls: 0.1326, acc: 94.9312, loss_bbox: 0.1787, loss_mask: 0.1972, loss: 0.5539 2023-11-14 00:30:54,444 - mmdet - INFO - Epoch [10][7300/7330] lr: 1.000e-05, eta: 1:33:52, time: 0.393, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0356, loss_cls: 0.1411, acc: 94.5627, loss_bbox: 0.1937, loss_mask: 0.2037, loss: 0.5880 2023-11-14 00:31:06,555 - mmdet - INFO - Saving checkpoint at 10 epochs 2023-11-14 00:31:49,649 - mmdet - INFO - Evaluating bbox... 2023-11-14 00:32:18,730 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.492 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.708 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.541 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.327 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.532 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.643 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.611 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.611 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.611 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.433 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.653 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.771 2023-11-14 00:32:18,733 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.585 | bicycle | 0.379 | car | 0.490 | | motorcycle | 0.496 | airplane | 0.701 | bus | 0.695 | | train | 0.693 | truck | 0.445 | boat | 0.349 | | traffic light | 0.308 | fire hydrant | 0.735 | stop sign | 0.688 | | parking meter | 0.532 | bench | 0.321 | bird | 0.427 | | cat | 0.746 | dog | 0.718 | horse | 0.642 | | sheep | 0.597 | cow | 0.635 | elephant | 0.697 | | bear | 0.772 | zebra | 0.712 | giraffe | 0.724 | | backpack | 0.214 | umbrella | 0.475 | handbag | 0.237 | | tie | 0.405 | suitcase | 0.484 | frisbee | 0.707 | | skis | 0.322 | snowboard | 0.478 | sports ball | 0.485 | | kite | 0.482 | baseball bat | 0.418 | baseball glove | 0.441 | | skateboard | 0.614 | surfboard | 0.466 | tennis racket | 0.570 | | bottle | 0.456 | wine glass | 0.430 | cup | 0.500 | | fork | 0.464 | knife | 0.299 | spoon | 0.303 | | bowl | 0.482 | banana | 0.305 | apple | 0.269 | | sandwich | 0.473 | orange | 0.369 | broccoli | 0.263 | | carrot | 0.267 | hot dog | 0.497 | pizza | 0.551 | | donut | 0.568 | cake | 0.461 | chair | 0.367 | | couch | 0.487 | potted plant | 0.359 | bed | 0.490 | | dining table | 0.333 | toilet | 0.685 | tv | 0.635 | | laptop | 0.682 | mouse | 0.666 | remote | 0.429 | | keyboard | 0.561 | cell phone | 0.440 | microwave | 0.680 | | oven | 0.418 | toaster | 0.469 | sink | 0.443 | | refrigerator | 0.650 | book | 0.210 | clock | 0.539 | | vase | 0.433 | scissors | 0.418 | teddy bear | 0.554 | | hair drier | 0.239 | toothbrush | 0.313 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:32:18,733 - mmdet - INFO - Evaluating segm... 2023-11-14 00:32:48,357 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.440 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.681 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.478 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.245 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.473 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.635 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.555 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.555 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.555 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.375 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.597 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.718 2023-11-14 00:32:48,360 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.510 | bicycle | 0.218 | car | 0.455 | | motorcycle | 0.401 | airplane | 0.537 | bus | 0.689 | | train | 0.686 | truck | 0.420 | boat | 0.310 | | traffic light | 0.300 | fire hydrant | 0.709 | stop sign | 0.675 | | parking meter | 0.537 | bench | 0.245 | bird | 0.353 | | cat | 0.739 | dog | 0.666 | horse | 0.474 | | sheep | 0.520 | cow | 0.534 | elephant | 0.646 | | bear | 0.743 | zebra | 0.626 | giraffe | 0.556 | | backpack | 0.219 | umbrella | 0.513 | handbag | 0.228 | | tie | 0.370 | suitcase | 0.500 | frisbee | 0.679 | | skis | 0.067 | snowboard | 0.280 | sports ball | 0.488 | | kite | 0.344 | baseball bat | 0.325 | baseball glove | 0.470 | | skateboard | 0.390 | surfboard | 0.381 | tennis racket | 0.602 | | bottle | 0.442 | wine glass | 0.392 | cup | 0.506 | | fork | 0.252 | knife | 0.206 | spoon | 0.207 | | bowl | 0.450 | banana | 0.262 | apple | 0.264 | | sandwich | 0.483 | orange | 0.365 | broccoli | 0.244 | | carrot | 0.231 | hot dog | 0.404 | pizza | 0.529 | | donut | 0.564 | cake | 0.467 | chair | 0.264 | | couch | 0.404 | potted plant | 0.300 | bed | 0.402 | | dining table | 0.198 | toilet | 0.654 | tv | 0.657 | | laptop | 0.675 | mouse | 0.650 | remote | 0.383 | | keyboard | 0.562 | cell phone | 0.416 | microwave | 0.686 | | oven | 0.385 | toaster | 0.516 | sink | 0.408 | | refrigerator | 0.663 | book | 0.162 | clock | 0.544 | | vase | 0.427 | scissors | 0.302 | teddy bear | 0.532 | | hair drier | 0.149 | toothbrush | 0.227 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:32:48,739 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_9.pth was removed 2023-11-14 00:32:50,750 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_10.pth. 2023-11-14 00:32:50,750 - mmdet - INFO - Best bbox_mAP is 0.4918 at 10 epoch. 2023-11-14 00:32:50,750 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 00:32:50,750 - mmdet - INFO - Epoch(val) [10][625] bbox_mAP: 0.4918, bbox_mAP_50: 0.7078, bbox_mAP_75: 0.5413, bbox_mAP_s: 0.3273, bbox_mAP_m: 0.5324, bbox_mAP_l: 0.6430, bbox_mAP_copypaste: 0.4918 0.7078 0.5413 0.3273 0.5324 0.6430, segm_mAP: 0.4405, segm_mAP_50: 0.6805, segm_mAP_75: 0.4778, segm_mAP_s: 0.2449, segm_mAP_m: 0.4726, segm_mAP_l: 0.6352, segm_mAP_copypaste: 0.4405 0.6805 0.4778 0.2449 0.4726 0.6352 2023-11-14 00:33:15,875 - mmdet - INFO - Epoch [11][50/7330] lr: 1.000e-05, eta: 1:33:20, time: 0.502, data_time: 0.107, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0324, loss_cls: 0.1362, acc: 94.7825, loss_bbox: 0.1859, loss_mask: 0.2040, loss: 0.5729 2023-11-14 00:33:36,135 - mmdet - INFO - Epoch [11][100/7330] lr: 1.000e-05, eta: 1:33:01, time: 0.405, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0349, loss_cls: 0.1399, acc: 94.5701, loss_bbox: 0.1951, loss_mask: 0.2072, loss: 0.5932 2023-11-14 00:33:59,780 - mmdet - INFO - Epoch [11][150/7330] lr: 1.000e-05, eta: 1:32:43, time: 0.473, data_time: 0.058, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0345, loss_cls: 0.1407, acc: 94.6152, loss_bbox: 0.1887, loss_mask: 0.1996, loss: 0.5783 2023-11-14 00:34:19,802 - mmdet - INFO - Epoch [11][200/7330] lr: 1.000e-05, eta: 1:32:24, time: 0.400, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0330, loss_cls: 0.1314, acc: 94.9333, loss_bbox: 0.1839, loss_mask: 0.1999, loss: 0.5614 2023-11-14 00:34:40,959 - mmdet - INFO - Epoch [11][250/7330] lr: 1.000e-05, eta: 1:32:05, time: 0.423, data_time: 0.041, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0346, loss_cls: 0.1388, acc: 94.6506, loss_bbox: 0.1886, loss_mask: 0.2021, loss: 0.5782 2023-11-14 00:35:00,793 - mmdet - INFO - Epoch [11][300/7330] lr: 1.000e-05, eta: 1:31:46, time: 0.397, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0374, loss_cls: 0.1474, acc: 94.3193, loss_bbox: 0.1985, loss_mask: 0.2099, loss: 0.6090 2023-11-14 00:35:20,066 - mmdet - INFO - Epoch [11][350/7330] lr: 1.000e-05, eta: 1:31:27, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0324, loss_cls: 0.1356, acc: 94.6802, loss_bbox: 0.1839, loss_mask: 0.2041, loss: 0.5690 2023-11-14 00:35:39,621 - mmdet - INFO - Epoch [11][400/7330] lr: 1.000e-05, eta: 1:31:08, time: 0.391, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0342, loss_cls: 0.1389, acc: 94.6072, loss_bbox: 0.1900, loss_mask: 0.2019, loss: 0.5788 2023-11-14 00:35:59,327 - mmdet - INFO - Epoch [11][450/7330] lr: 1.000e-05, eta: 1:30:49, time: 0.394, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0332, loss_cls: 0.1344, acc: 94.7898, loss_bbox: 0.1839, loss_mask: 0.2048, loss: 0.5706 2023-11-14 00:36:19,187 - mmdet - INFO - Epoch [11][500/7330] lr: 1.000e-05, eta: 1:30:30, time: 0.397, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0340, loss_cls: 0.1405, acc: 94.5356, loss_bbox: 0.1895, loss_mask: 0.2057, loss: 0.5841 2023-11-14 00:36:38,743 - mmdet - INFO - Epoch [11][550/7330] lr: 1.000e-05, eta: 1:30:10, time: 0.391, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0319, loss_cls: 0.1342, acc: 94.8496, loss_bbox: 0.1830, loss_mask: 0.2021, loss: 0.5656 2023-11-14 00:36:58,148 - mmdet - INFO - Epoch [11][600/7330] lr: 1.000e-05, eta: 1:29:51, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0336, loss_cls: 0.1398, acc: 94.5803, loss_bbox: 0.1915, loss_mask: 0.2039, loss: 0.5828 2023-11-14 00:37:17,413 - mmdet - INFO - Epoch [11][650/7330] lr: 1.000e-05, eta: 1:29:32, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0331, loss_cls: 0.1355, acc: 94.7822, loss_bbox: 0.1867, loss_mask: 0.2026, loss: 0.5717 2023-11-14 00:37:37,138 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 00:37:37,138 - mmdet - INFO - Epoch [11][700/7330] lr: 1.000e-05, eta: 1:29:13, time: 0.394, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0360, loss_cls: 0.1421, acc: 94.4990, loss_bbox: 0.1938, loss_mask: 0.2020, loss: 0.5899 2023-11-14 00:37:56,589 - mmdet - INFO - Epoch [11][750/7330] lr: 1.000e-05, eta: 1:28:54, time: 0.389, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0336, loss_cls: 0.1367, acc: 94.7085, loss_bbox: 0.1934, loss_mask: 0.2091, loss: 0.5861 2023-11-14 00:38:15,886 - mmdet - INFO - Epoch [11][800/7330] lr: 1.000e-05, eta: 1:28:35, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0354, loss_cls: 0.1355, acc: 94.8179, loss_bbox: 0.1838, loss_mask: 0.2001, loss: 0.5686 2023-11-14 00:38:35,521 - mmdet - INFO - Epoch [11][850/7330] lr: 1.000e-05, eta: 1:28:16, time: 0.393, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0358, loss_cls: 0.1416, acc: 94.4880, loss_bbox: 0.1928, loss_mask: 0.2047, loss: 0.5891 2023-11-14 00:38:55,023 - mmdet - INFO - Epoch [11][900/7330] lr: 1.000e-05, eta: 1:27:57, time: 0.390, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0363, loss_cls: 0.1469, acc: 94.2896, loss_bbox: 0.2010, loss_mask: 0.2064, loss: 0.6054 2023-11-14 00:39:14,004 - mmdet - INFO - Epoch [11][950/7330] lr: 1.000e-05, eta: 1:27:37, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0323, loss_cls: 0.1330, acc: 94.8706, loss_bbox: 0.1817, loss_mask: 0.2033, loss: 0.5634 2023-11-14 00:39:33,392 - mmdet - INFO - Epoch [11][1000/7330] lr: 1.000e-05, eta: 1:27:18, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0335, loss_cls: 0.1385, acc: 94.5779, loss_bbox: 0.1909, loss_mask: 0.2036, loss: 0.5801 2023-11-14 00:39:52,542 - mmdet - INFO - Epoch [11][1050/7330] lr: 1.000e-05, eta: 1:26:59, time: 0.383, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0328, loss_cls: 0.1318, acc: 94.9358, loss_bbox: 0.1778, loss_mask: 0.1993, loss: 0.5543 2023-11-14 00:40:11,742 - mmdet - INFO - Epoch [11][1100/7330] lr: 1.000e-05, eta: 1:26:40, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0332, loss_cls: 0.1361, acc: 94.7700, loss_bbox: 0.1890, loss_mask: 0.2028, loss: 0.5741 2023-11-14 00:40:31,021 - mmdet - INFO - Epoch [11][1150/7330] lr: 1.000e-05, eta: 1:26:21, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0343, loss_cls: 0.1394, acc: 94.6475, loss_bbox: 0.1869, loss_mask: 0.2038, loss: 0.5778 2023-11-14 00:40:50,315 - mmdet - INFO - Epoch [11][1200/7330] lr: 1.000e-05, eta: 1:26:02, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0325, loss_cls: 0.1336, acc: 94.8438, loss_bbox: 0.1777, loss_mask: 0.1986, loss: 0.5556 2023-11-14 00:41:09,560 - mmdet - INFO - Epoch [11][1250/7330] lr: 1.000e-05, eta: 1:25:42, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0349, loss_cls: 0.1439, acc: 94.4675, loss_bbox: 0.1963, loss_mask: 0.2041, loss: 0.5922 2023-11-14 00:41:28,850 - mmdet - INFO - Epoch [11][1300/7330] lr: 1.000e-05, eta: 1:25:23, time: 0.386, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0344, loss_cls: 0.1365, acc: 94.7285, loss_bbox: 0.1890, loss_mask: 0.2044, loss: 0.5777 2023-11-14 00:41:48,176 - mmdet - INFO - Epoch [11][1350/7330] lr: 1.000e-05, eta: 1:25:04, time: 0.386, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0335, loss_cls: 0.1339, acc: 94.8564, loss_bbox: 0.1862, loss_mask: 0.2009, loss: 0.5680 2023-11-14 00:42:07,372 - mmdet - INFO - Epoch [11][1400/7330] lr: 1.000e-05, eta: 1:24:45, time: 0.384, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0368, loss_cls: 0.1452, acc: 94.3982, loss_bbox: 0.1974, loss_mask: 0.2058, loss: 0.6003 2023-11-14 00:42:26,155 - mmdet - INFO - Epoch [11][1450/7330] lr: 1.000e-05, eta: 1:24:26, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0338, loss_cls: 0.1378, acc: 94.7617, loss_bbox: 0.1906, loss_mask: 0.1976, loss: 0.5744 2023-11-14 00:42:45,556 - mmdet - INFO - Epoch [11][1500/7330] lr: 1.000e-05, eta: 1:24:07, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0358, loss_cls: 0.1468, acc: 94.3176, loss_bbox: 0.1992, loss_mask: 0.2070, loss: 0.6051 2023-11-14 00:43:05,140 - mmdet - INFO - Epoch [11][1550/7330] lr: 1.000e-05, eta: 1:23:47, time: 0.392, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0356, loss_cls: 0.1409, acc: 94.5984, loss_bbox: 0.1932, loss_mask: 0.2079, loss: 0.5921 2023-11-14 00:43:24,366 - mmdet - INFO - Epoch [11][1600/7330] lr: 1.000e-05, eta: 1:23:28, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0334, loss_cls: 0.1412, acc: 94.5625, loss_bbox: 0.1918, loss_mask: 0.2014, loss: 0.5815 2023-11-14 00:43:43,381 - mmdet - INFO - Epoch [11][1650/7330] lr: 1.000e-05, eta: 1:23:09, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0329, loss_cls: 0.1338, acc: 94.8489, loss_bbox: 0.1856, loss_mask: 0.2067, loss: 0.5732 2023-11-14 00:44:02,443 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 00:44:02,443 - mmdet - INFO - Epoch [11][1700/7330] lr: 1.000e-05, eta: 1:22:50, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0361, loss_cls: 0.1412, acc: 94.5967, loss_bbox: 0.1927, loss_mask: 0.2030, loss: 0.5876 2023-11-14 00:44:21,424 - mmdet - INFO - Epoch [11][1750/7330] lr: 1.000e-05, eta: 1:22:31, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0316, loss_cls: 0.1322, acc: 94.8484, loss_bbox: 0.1835, loss_mask: 0.2036, loss: 0.5644 2023-11-14 00:44:40,321 - mmdet - INFO - Epoch [11][1800/7330] lr: 1.000e-05, eta: 1:22:11, time: 0.378, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0343, loss_cls: 0.1332, acc: 94.8420, loss_bbox: 0.1851, loss_mask: 0.2012, loss: 0.5672 2023-11-14 00:44:59,487 - mmdet - INFO - Epoch [11][1850/7330] lr: 1.000e-05, eta: 1:21:52, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0351, loss_cls: 0.1385, acc: 94.6418, loss_bbox: 0.1893, loss_mask: 0.2048, loss: 0.5818 2023-11-14 00:45:18,622 - mmdet - INFO - Epoch [11][1900/7330] lr: 1.000e-05, eta: 1:21:33, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0329, loss_cls: 0.1352, acc: 94.7607, loss_bbox: 0.1869, loss_mask: 0.2026, loss: 0.5703 2023-11-14 00:45:37,854 - mmdet - INFO - Epoch [11][1950/7330] lr: 1.000e-05, eta: 1:21:14, time: 0.385, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0328, loss_cls: 0.1340, acc: 94.8862, loss_bbox: 0.1829, loss_mask: 0.2012, loss: 0.5651 2023-11-14 00:45:56,858 - mmdet - INFO - Epoch [11][2000/7330] lr: 1.000e-05, eta: 1:20:55, time: 0.380, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0333, loss_cls: 0.1375, acc: 94.7241, loss_bbox: 0.1873, loss_mask: 0.2023, loss: 0.5744 2023-11-14 00:46:15,893 - mmdet - INFO - Epoch [11][2050/7330] lr: 1.000e-05, eta: 1:20:36, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0342, loss_cls: 0.1389, acc: 94.5923, loss_bbox: 0.1932, loss_mask: 0.2058, loss: 0.5859 2023-11-14 00:46:35,148 - mmdet - INFO - Epoch [11][2100/7330] lr: 1.000e-05, eta: 1:20:16, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0352, loss_cls: 0.1440, acc: 94.4504, loss_bbox: 0.1935, loss_mask: 0.2084, loss: 0.5965 2023-11-14 00:46:53,818 - mmdet - INFO - Epoch [11][2150/7330] lr: 1.000e-05, eta: 1:19:57, time: 0.373, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0331, loss_cls: 0.1357, acc: 94.7522, loss_bbox: 0.1878, loss_mask: 0.2034, loss: 0.5729 2023-11-14 00:47:12,719 - mmdet - INFO - Epoch [11][2200/7330] lr: 1.000e-05, eta: 1:19:38, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0329, loss_cls: 0.1354, acc: 94.7939, loss_bbox: 0.1856, loss_mask: 0.2011, loss: 0.5677 2023-11-14 00:47:31,364 - mmdet - INFO - Epoch [11][2250/7330] lr: 1.000e-05, eta: 1:19:19, time: 0.373, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0338, loss_cls: 0.1325, acc: 94.9355, loss_bbox: 0.1809, loss_mask: 0.2027, loss: 0.5617 2023-11-14 00:47:50,563 - mmdet - INFO - Epoch [11][2300/7330] lr: 1.000e-05, eta: 1:18:59, time: 0.384, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0335, loss_cls: 0.1396, acc: 94.5684, loss_bbox: 0.1878, loss_mask: 0.1984, loss: 0.5738 2023-11-14 00:48:09,564 - mmdet - INFO - Epoch [11][2350/7330] lr: 1.000e-05, eta: 1:18:40, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0350, loss_cls: 0.1405, acc: 94.6243, loss_bbox: 0.1958, loss_mask: 0.2091, loss: 0.5950 2023-11-14 00:48:28,542 - mmdet - INFO - Epoch [11][2400/7330] lr: 1.000e-05, eta: 1:18:21, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0336, loss_cls: 0.1356, acc: 94.7688, loss_bbox: 0.1891, loss_mask: 0.1996, loss: 0.5721 2023-11-14 00:48:47,811 - mmdet - INFO - Epoch [11][2450/7330] lr: 1.000e-05, eta: 1:18:02, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0361, loss_cls: 0.1472, acc: 94.3601, loss_bbox: 0.1981, loss_mask: 0.2028, loss: 0.5989 2023-11-14 00:49:06,430 - mmdet - INFO - Epoch [11][2500/7330] lr: 1.000e-05, eta: 1:17:43, time: 0.372, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0351, loss_cls: 0.1342, acc: 94.7957, loss_bbox: 0.1905, loss_mask: 0.2039, loss: 0.5767 2023-11-14 00:49:25,365 - mmdet - INFO - Epoch [11][2550/7330] lr: 1.000e-05, eta: 1:17:23, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0337, loss_cls: 0.1349, acc: 94.8672, loss_bbox: 0.1854, loss_mask: 0.2014, loss: 0.5685 2023-11-14 00:49:44,316 - mmdet - INFO - Epoch [11][2600/7330] lr: 1.000e-05, eta: 1:17:04, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0326, loss_cls: 0.1352, acc: 94.7961, loss_bbox: 0.1866, loss_mask: 0.2040, loss: 0.5725 2023-11-14 00:50:03,146 - mmdet - INFO - Epoch [11][2650/7330] lr: 1.000e-05, eta: 1:16:45, time: 0.377, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0336, loss_cls: 0.1380, acc: 94.7351, loss_bbox: 0.1892, loss_mask: 0.2059, loss: 0.5810 2023-11-14 00:50:21,715 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 00:50:21,716 - mmdet - INFO - Epoch [11][2700/7330] lr: 1.000e-05, eta: 1:16:26, time: 0.371, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0335, loss_cls: 0.1359, acc: 94.7930, loss_bbox: 0.1848, loss_mask: 0.2011, loss: 0.5685 2023-11-14 00:50:40,867 - mmdet - INFO - Epoch [11][2750/7330] lr: 1.000e-05, eta: 1:16:07, time: 0.383, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0338, loss_cls: 0.1353, acc: 94.7129, loss_bbox: 0.1909, loss_mask: 0.2055, loss: 0.5797 2023-11-14 00:50:59,749 - mmdet - INFO - Epoch [11][2800/7330] lr: 1.000e-05, eta: 1:15:47, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0342, loss_cls: 0.1357, acc: 94.8286, loss_bbox: 0.1840, loss_mask: 0.1995, loss: 0.5663 2023-11-14 00:51:18,875 - mmdet - INFO - Epoch [11][2850/7330] lr: 1.000e-05, eta: 1:15:28, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0346, loss_cls: 0.1388, acc: 94.6631, loss_bbox: 0.1901, loss_mask: 0.2026, loss: 0.5796 2023-11-14 00:51:37,664 - mmdet - INFO - Epoch [11][2900/7330] lr: 1.000e-05, eta: 1:15:09, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0352, loss_cls: 0.1383, acc: 94.6404, loss_bbox: 0.1898, loss_mask: 0.2061, loss: 0.5827 2023-11-14 00:51:56,805 - mmdet - INFO - Epoch [11][2950/7330] lr: 1.000e-05, eta: 1:14:50, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0354, loss_cls: 0.1446, acc: 94.4390, loss_bbox: 0.1938, loss_mask: 0.2028, loss: 0.5911 2023-11-14 00:52:15,730 - mmdet - INFO - Epoch [11][3000/7330] lr: 1.000e-05, eta: 1:14:31, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0340, loss_cls: 0.1404, acc: 94.5571, loss_bbox: 0.1881, loss_mask: 0.2063, loss: 0.5826 2023-11-14 00:52:34,801 - mmdet - INFO - Epoch [11][3050/7330] lr: 1.000e-05, eta: 1:14:11, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0323, loss_cls: 0.1358, acc: 94.8503, loss_bbox: 0.1850, loss_mask: 0.2013, loss: 0.5673 2023-11-14 00:52:53,859 - mmdet - INFO - Epoch [11][3100/7330] lr: 1.000e-05, eta: 1:13:52, time: 0.381, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0357, loss_cls: 0.1377, acc: 94.6558, loss_bbox: 0.1898, loss_mask: 0.2031, loss: 0.5799 2023-11-14 00:53:12,719 - mmdet - INFO - Epoch [11][3150/7330] lr: 1.000e-05, eta: 1:13:33, time: 0.377, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0355, loss_cls: 0.1355, acc: 94.8533, loss_bbox: 0.1863, loss_mask: 0.2018, loss: 0.5739 2023-11-14 00:53:31,707 - mmdet - INFO - Epoch [11][3200/7330] lr: 1.000e-05, eta: 1:13:14, time: 0.380, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0350, loss_cls: 0.1391, acc: 94.6948, loss_bbox: 0.1855, loss_mask: 0.2037, loss: 0.5780 2023-11-14 00:53:50,770 - mmdet - INFO - Epoch [11][3250/7330] lr: 1.000e-05, eta: 1:12:55, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0341, loss_cls: 0.1407, acc: 94.5593, loss_bbox: 0.1894, loss_mask: 0.2057, loss: 0.5846 2023-11-14 00:54:09,596 - mmdet - INFO - Epoch [11][3300/7330] lr: 1.000e-05, eta: 1:12:35, time: 0.376, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0333, loss_cls: 0.1323, acc: 94.9778, loss_bbox: 0.1856, loss_mask: 0.2000, loss: 0.5638 2023-11-14 00:54:28,766 - mmdet - INFO - Epoch [11][3350/7330] lr: 1.000e-05, eta: 1:12:16, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0347, loss_cls: 0.1384, acc: 94.6938, loss_bbox: 0.1875, loss_mask: 0.1989, loss: 0.5744 2023-11-14 00:54:47,755 - mmdet - INFO - Epoch [11][3400/7330] lr: 1.000e-05, eta: 1:11:57, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0359, loss_cls: 0.1410, acc: 94.6685, loss_bbox: 0.1931, loss_mask: 0.2067, loss: 0.5910 2023-11-14 00:55:06,818 - mmdet - INFO - Epoch [11][3450/7330] lr: 1.000e-05, eta: 1:11:38, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0338, loss_cls: 0.1360, acc: 94.8069, loss_bbox: 0.1902, loss_mask: 0.1992, loss: 0.5739 2023-11-14 00:55:25,908 - mmdet - INFO - Epoch [11][3500/7330] lr: 1.000e-05, eta: 1:11:19, time: 0.382, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0366, loss_cls: 0.1419, acc: 94.5269, loss_bbox: 0.1926, loss_mask: 0.2059, loss: 0.5911 2023-11-14 00:55:45,066 - mmdet - INFO - Epoch [11][3550/7330] lr: 1.000e-05, eta: 1:10:59, time: 0.383, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0345, loss_cls: 0.1391, acc: 94.6343, loss_bbox: 0.1894, loss_mask: 0.2037, loss: 0.5811 2023-11-14 00:56:04,107 - mmdet - INFO - Epoch [11][3600/7330] lr: 1.000e-05, eta: 1:10:40, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0322, loss_cls: 0.1318, acc: 94.9695, loss_bbox: 0.1829, loss_mask: 0.1994, loss: 0.5605 2023-11-14 00:56:23,306 - mmdet - INFO - Epoch [11][3650/7330] lr: 1.000e-05, eta: 1:10:21, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0357, loss_cls: 0.1423, acc: 94.4500, loss_bbox: 0.1904, loss_mask: 0.2045, loss: 0.5871 2023-11-14 00:56:42,266 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 00:56:42,267 - mmdet - INFO - Epoch [11][3700/7330] lr: 1.000e-05, eta: 1:10:02, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0330, loss_cls: 0.1373, acc: 94.7222, loss_bbox: 0.1904, loss_mask: 0.2051, loss: 0.5794 2023-11-14 00:57:01,113 - mmdet - INFO - Epoch [11][3750/7330] lr: 1.000e-05, eta: 1:09:43, time: 0.377, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0313, loss_cls: 0.1357, acc: 94.8098, loss_bbox: 0.1845, loss_mask: 0.2031, loss: 0.5672 2023-11-14 00:57:20,228 - mmdet - INFO - Epoch [11][3800/7330] lr: 1.000e-05, eta: 1:09:23, time: 0.382, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0323, loss_cls: 0.1278, acc: 95.1306, loss_bbox: 0.1735, loss_mask: 0.1960, loss: 0.5425 2023-11-14 00:57:39,294 - mmdet - INFO - Epoch [11][3850/7330] lr: 1.000e-05, eta: 1:09:04, time: 0.381, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0333, loss_cls: 0.1308, acc: 94.9795, loss_bbox: 0.1775, loss_mask: 0.1959, loss: 0.5515 2023-11-14 00:57:58,252 - mmdet - INFO - Epoch [11][3900/7330] lr: 1.000e-05, eta: 1:08:45, time: 0.379, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0357, loss_cls: 0.1374, acc: 94.6787, loss_bbox: 0.1954, loss_mask: 0.2083, loss: 0.5900 2023-11-14 00:58:17,213 - mmdet - INFO - Epoch [11][3950/7330] lr: 1.000e-05, eta: 1:08:26, time: 0.379, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0344, loss_cls: 0.1361, acc: 94.7996, loss_bbox: 0.1856, loss_mask: 0.2020, loss: 0.5714 2023-11-14 00:58:36,004 - mmdet - INFO - Epoch [11][4000/7330] lr: 1.000e-05, eta: 1:08:07, time: 0.376, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0333, loss_cls: 0.1338, acc: 94.7869, loss_bbox: 0.1835, loss_mask: 0.1997, loss: 0.5635 2023-11-14 00:58:55,057 - mmdet - INFO - Epoch [11][4050/7330] lr: 1.000e-05, eta: 1:07:47, time: 0.381, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0328, loss_cls: 0.1345, acc: 94.8423, loss_bbox: 0.1817, loss_mask: 0.1977, loss: 0.5598 2023-11-14 00:59:16,443 - mmdet - INFO - Epoch [11][4100/7330] lr: 1.000e-05, eta: 1:07:29, time: 0.428, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0360, loss_cls: 0.1400, acc: 94.6443, loss_bbox: 0.1926, loss_mask: 0.2086, loss: 0.5926 2023-11-14 00:59:35,580 - mmdet - INFO - Epoch [11][4150/7330] lr: 1.000e-05, eta: 1:07:09, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0347, loss_cls: 0.1416, acc: 94.6406, loss_bbox: 0.1926, loss_mask: 0.2074, loss: 0.5912 2023-11-14 00:59:54,572 - mmdet - INFO - Epoch [11][4200/7330] lr: 1.000e-05, eta: 1:06:50, time: 0.380, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0365, loss_cls: 0.1395, acc: 94.6775, loss_bbox: 0.1897, loss_mask: 0.2059, loss: 0.5864 2023-11-14 01:00:13,718 - mmdet - INFO - Epoch [11][4250/7330] lr: 1.000e-05, eta: 1:06:31, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0338, loss_cls: 0.1430, acc: 94.4761, loss_bbox: 0.1956, loss_mask: 0.2051, loss: 0.5906 2023-11-14 01:00:32,518 - mmdet - INFO - Epoch [11][4300/7330] lr: 1.000e-05, eta: 1:06:12, time: 0.376, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0337, loss_cls: 0.1319, acc: 94.8855, loss_bbox: 0.1804, loss_mask: 0.1985, loss: 0.5567 2023-11-14 01:00:51,322 - mmdet - INFO - Epoch [11][4350/7330] lr: 1.000e-05, eta: 1:05:53, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0330, loss_cls: 0.1332, acc: 94.8777, loss_bbox: 0.1808, loss_mask: 0.2010, loss: 0.5619 2023-11-14 01:01:09,956 - mmdet - INFO - Epoch [11][4400/7330] lr: 1.000e-05, eta: 1:05:33, time: 0.373, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0313, loss_cls: 0.1310, acc: 95.0129, loss_bbox: 0.1831, loss_mask: 0.1969, loss: 0.5553 2023-11-14 01:01:28,958 - mmdet - INFO - Epoch [11][4450/7330] lr: 1.000e-05, eta: 1:05:14, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0310, loss_cls: 0.1315, acc: 95.0146, loss_bbox: 0.1788, loss_mask: 0.1986, loss: 0.5540 2023-11-14 01:01:48,132 - mmdet - INFO - Epoch [11][4500/7330] lr: 1.000e-05, eta: 1:04:55, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0353, loss_cls: 0.1354, acc: 94.7900, loss_bbox: 0.1861, loss_mask: 0.2019, loss: 0.5723 2023-11-14 01:02:07,561 - mmdet - INFO - Epoch [11][4550/7330] lr: 1.000e-05, eta: 1:04:36, time: 0.389, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0375, loss_cls: 0.1413, acc: 94.6379, loss_bbox: 0.1912, loss_mask: 0.2046, loss: 0.5893 2023-11-14 01:02:26,957 - mmdet - INFO - Epoch [11][4600/7330] lr: 1.000e-05, eta: 1:04:17, time: 0.388, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0340, loss_cls: 0.1373, acc: 94.7043, loss_bbox: 0.1892, loss_mask: 0.2079, loss: 0.5828 2023-11-14 01:02:45,910 - mmdet - INFO - Epoch [11][4650/7330] lr: 1.000e-05, eta: 1:03:58, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0355, loss_cls: 0.1365, acc: 94.7520, loss_bbox: 0.1877, loss_mask: 0.2021, loss: 0.5753 2023-11-14 01:03:05,036 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 01:03:05,036 - mmdet - INFO - Epoch [11][4700/7330] lr: 1.000e-05, eta: 1:03:38, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0336, loss_cls: 0.1397, acc: 94.6309, loss_bbox: 0.1891, loss_mask: 0.2008, loss: 0.5773 2023-11-14 01:03:23,991 - mmdet - INFO - Epoch [11][4750/7330] lr: 1.000e-05, eta: 1:03:19, time: 0.379, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0361, loss_cls: 0.1451, acc: 94.4570, loss_bbox: 0.1969, loss_mask: 0.2052, loss: 0.5988 2023-11-14 01:03:42,981 - mmdet - INFO - Epoch [11][4800/7330] lr: 1.000e-05, eta: 1:03:00, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0342, loss_cls: 0.1349, acc: 94.8494, loss_bbox: 0.1860, loss_mask: 0.2046, loss: 0.5736 2023-11-14 01:04:01,987 - mmdet - INFO - Epoch [11][4850/7330] lr: 1.000e-05, eta: 1:02:41, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0344, loss_cls: 0.1365, acc: 94.7654, loss_bbox: 0.1857, loss_mask: 0.2008, loss: 0.5709 2023-11-14 01:04:21,387 - mmdet - INFO - Epoch [11][4900/7330] lr: 1.000e-05, eta: 1:02:22, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0362, loss_cls: 0.1400, acc: 94.6321, loss_bbox: 0.1928, loss_mask: 0.2015, loss: 0.5849 2023-11-14 01:04:40,206 - mmdet - INFO - Epoch [11][4950/7330] lr: 1.000e-05, eta: 1:02:02, time: 0.376, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0306, loss_cls: 0.1268, acc: 95.2402, loss_bbox: 0.1762, loss_mask: 0.1987, loss: 0.5438 2023-11-14 01:04:58,986 - mmdet - INFO - Epoch [11][5000/7330] lr: 1.000e-05, eta: 1:01:43, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0335, loss_cls: 0.1346, acc: 94.7820, loss_bbox: 0.1865, loss_mask: 0.2048, loss: 0.5727 2023-11-14 01:05:17,889 - mmdet - INFO - Epoch [11][5050/7330] lr: 1.000e-05, eta: 1:01:24, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0335, loss_cls: 0.1310, acc: 94.9719, loss_bbox: 0.1809, loss_mask: 0.2017, loss: 0.5609 2023-11-14 01:05:36,918 - mmdet - INFO - Epoch [11][5100/7330] lr: 1.000e-05, eta: 1:01:05, time: 0.381, data_time: 0.018, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0308, loss_cls: 0.1285, acc: 95.0479, loss_bbox: 0.1797, loss_mask: 0.1956, loss: 0.5476 2023-11-14 01:05:55,908 - mmdet - INFO - Epoch [11][5150/7330] lr: 1.000e-05, eta: 1:00:46, time: 0.380, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0324, loss_cls: 0.1362, acc: 94.7493, loss_bbox: 0.1839, loss_mask: 0.2007, loss: 0.5658 2023-11-14 01:06:14,681 - mmdet - INFO - Epoch [11][5200/7330] lr: 1.000e-05, eta: 1:00:26, time: 0.375, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0332, loss_cls: 0.1417, acc: 94.5571, loss_bbox: 0.1940, loss_mask: 0.2095, loss: 0.5924 2023-11-14 01:06:33,388 - mmdet - INFO - Epoch [11][5250/7330] lr: 1.000e-05, eta: 1:00:07, time: 0.374, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0329, loss_cls: 0.1374, acc: 94.6843, loss_bbox: 0.1910, loss_mask: 0.2047, loss: 0.5805 2023-11-14 01:06:52,206 - mmdet - INFO - Epoch [11][5300/7330] lr: 1.000e-05, eta: 0:59:48, time: 0.376, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0352, loss_cls: 0.1407, acc: 94.6199, loss_bbox: 0.1900, loss_mask: 0.2058, loss: 0.5863 2023-11-14 01:07:11,290 - mmdet - INFO - Epoch [11][5350/7330] lr: 1.000e-05, eta: 0:59:29, time: 0.382, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0347, loss_cls: 0.1406, acc: 94.6235, loss_bbox: 0.1904, loss_mask: 0.2040, loss: 0.5844 2023-11-14 01:07:30,353 - mmdet - INFO - Epoch [11][5400/7330] lr: 1.000e-05, eta: 0:59:10, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0359, loss_cls: 0.1412, acc: 94.6169, loss_bbox: 0.1914, loss_mask: 0.2084, loss: 0.5912 2023-11-14 01:07:49,301 - mmdet - INFO - Epoch [11][5450/7330] lr: 1.000e-05, eta: 0:58:50, time: 0.379, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0338, loss_cls: 0.1334, acc: 94.8586, loss_bbox: 0.1831, loss_mask: 0.2009, loss: 0.5650 2023-11-14 01:08:08,178 - mmdet - INFO - Epoch [11][5500/7330] lr: 1.000e-05, eta: 0:58:31, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0340, loss_cls: 0.1346, acc: 94.7717, loss_bbox: 0.1852, loss_mask: 0.2019, loss: 0.5677 2023-11-14 01:08:27,263 - mmdet - INFO - Epoch [11][5550/7330] lr: 1.000e-05, eta: 0:58:12, time: 0.382, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0345, loss_cls: 0.1359, acc: 94.7947, loss_bbox: 0.1828, loss_mask: 0.1986, loss: 0.5663 2023-11-14 01:08:46,043 - mmdet - INFO - Epoch [11][5600/7330] lr: 1.000e-05, eta: 0:57:53, time: 0.376, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0324, loss_cls: 0.1398, acc: 94.5928, loss_bbox: 0.1909, loss_mask: 0.2051, loss: 0.5820 2023-11-14 01:09:05,190 - mmdet - INFO - Epoch [11][5650/7330] lr: 1.000e-05, eta: 0:57:34, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0322, loss_cls: 0.1267, acc: 95.1187, loss_bbox: 0.1789, loss_mask: 0.1972, loss: 0.5471 2023-11-14 01:09:24,043 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 01:09:24,043 - mmdet - INFO - Epoch [11][5700/7330] lr: 1.000e-05, eta: 0:57:14, time: 0.377, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0360, loss_cls: 0.1450, acc: 94.4697, loss_bbox: 0.1932, loss_mask: 0.2054, loss: 0.5956 2023-11-14 01:09:43,033 - mmdet - INFO - Epoch [11][5750/7330] lr: 1.000e-05, eta: 0:56:55, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0360, loss_cls: 0.1419, acc: 94.5659, loss_bbox: 0.1943, loss_mask: 0.2060, loss: 0.5924 2023-11-14 01:10:01,933 - mmdet - INFO - Epoch [11][5800/7330] lr: 1.000e-05, eta: 0:56:36, time: 0.378, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0328, loss_cls: 0.1347, acc: 94.7012, loss_bbox: 0.1880, loss_mask: 0.2017, loss: 0.5711 2023-11-14 01:10:20,356 - mmdet - INFO - Epoch [11][5850/7330] lr: 1.000e-05, eta: 0:56:17, time: 0.369, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0327, loss_cls: 0.1376, acc: 94.6196, loss_bbox: 0.1898, loss_mask: 0.2057, loss: 0.5801 2023-11-14 01:10:39,147 - mmdet - INFO - Epoch [11][5900/7330] lr: 1.000e-05, eta: 0:55:58, time: 0.376, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0329, loss_cls: 0.1395, acc: 94.6250, loss_bbox: 0.1885, loss_mask: 0.2003, loss: 0.5750 2023-11-14 01:10:58,045 - mmdet - INFO - Epoch [11][5950/7330] lr: 1.000e-05, eta: 0:55:38, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0321, loss_cls: 0.1322, acc: 94.9614, loss_bbox: 0.1826, loss_mask: 0.2021, loss: 0.5623 2023-11-14 01:11:17,185 - mmdet - INFO - Epoch [11][6000/7330] lr: 1.000e-05, eta: 0:55:19, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0345, loss_cls: 0.1388, acc: 94.6841, loss_bbox: 0.1935, loss_mask: 0.2055, loss: 0.5858 2023-11-14 01:11:36,149 - mmdet - INFO - Epoch [11][6050/7330] lr: 1.000e-05, eta: 0:55:00, time: 0.379, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0344, loss_cls: 0.1400, acc: 94.5913, loss_bbox: 0.1924, loss_mask: 0.2030, loss: 0.5834 2023-11-14 01:11:55,427 - mmdet - INFO - Epoch [11][6100/7330] lr: 1.000e-05, eta: 0:54:41, time: 0.386, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0339, loss_cls: 0.1392, acc: 94.5671, loss_bbox: 0.1933, loss_mask: 0.2007, loss: 0.5811 2023-11-14 01:12:17,030 - mmdet - INFO - Epoch [11][6150/7330] lr: 1.000e-05, eta: 0:54:22, time: 0.432, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0333, loss_cls: 0.1395, acc: 94.6157, loss_bbox: 0.1911, loss_mask: 0.2032, loss: 0.5807 2023-11-14 01:12:35,792 - mmdet - INFO - Epoch [11][6200/7330] lr: 1.000e-05, eta: 0:54:03, time: 0.375, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0328, loss_cls: 0.1298, acc: 95.0078, loss_bbox: 0.1759, loss_mask: 0.1983, loss: 0.5499 2023-11-14 01:12:54,698 - mmdet - INFO - Epoch [11][6250/7330] lr: 1.000e-05, eta: 0:53:44, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0325, loss_cls: 0.1322, acc: 94.8074, loss_bbox: 0.1845, loss_mask: 0.2036, loss: 0.5669 2023-11-14 01:13:13,751 - mmdet - INFO - Epoch [11][6300/7330] lr: 1.000e-05, eta: 0:53:24, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0344, loss_cls: 0.1419, acc: 94.4590, loss_bbox: 0.1959, loss_mask: 0.2051, loss: 0.5922 2023-11-14 01:13:32,814 - mmdet - INFO - Epoch [11][6350/7330] lr: 1.000e-05, eta: 0:53:05, time: 0.381, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0314, loss_cls: 0.1316, acc: 94.9170, loss_bbox: 0.1812, loss_mask: 0.1948, loss: 0.5511 2023-11-14 01:13:51,906 - mmdet - INFO - Epoch [11][6400/7330] lr: 1.000e-05, eta: 0:52:46, time: 0.382, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0352, loss_cls: 0.1468, acc: 94.2820, loss_bbox: 0.1987, loss_mask: 0.2094, loss: 0.6051 2023-11-14 01:14:10,803 - mmdet - INFO - Epoch [11][6450/7330] lr: 1.000e-05, eta: 0:52:27, time: 0.378, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0334, loss_cls: 0.1353, acc: 94.7542, loss_bbox: 0.1871, loss_mask: 0.2031, loss: 0.5725 2023-11-14 01:14:29,975 - mmdet - INFO - Epoch [11][6500/7330] lr: 1.000e-05, eta: 0:52:08, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0350, loss_cls: 0.1478, acc: 94.3118, loss_bbox: 0.1995, loss_mask: 0.2095, loss: 0.6069 2023-11-14 01:14:48,944 - mmdet - INFO - Epoch [11][6550/7330] lr: 1.000e-05, eta: 0:51:48, time: 0.379, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0359, loss_cls: 0.1386, acc: 94.7339, loss_bbox: 0.1892, loss_mask: 0.2046, loss: 0.5838 2023-11-14 01:15:07,925 - mmdet - INFO - Epoch [11][6600/7330] lr: 1.000e-05, eta: 0:51:29, time: 0.380, data_time: 0.019, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0339, loss_cls: 0.1364, acc: 94.7388, loss_bbox: 0.1906, loss_mask: 0.2061, loss: 0.5814 2023-11-14 01:15:26,802 - mmdet - INFO - Epoch [11][6650/7330] lr: 1.000e-05, eta: 0:51:10, time: 0.377, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0335, loss_cls: 0.1361, acc: 94.7761, loss_bbox: 0.1857, loss_mask: 0.1997, loss: 0.5684 2023-11-14 01:15:45,877 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 01:15:45,877 - mmdet - INFO - Epoch [11][6700/7330] lr: 1.000e-05, eta: 0:50:51, time: 0.382, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0346, loss_cls: 0.1395, acc: 94.6077, loss_bbox: 0.1960, loss_mask: 0.2113, loss: 0.5962 2023-11-14 01:16:04,525 - mmdet - INFO - Epoch [11][6750/7330] lr: 1.000e-05, eta: 0:50:32, time: 0.373, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0346, loss_cls: 0.1385, acc: 94.6611, loss_bbox: 0.1876, loss_mask: 0.2043, loss: 0.5788 2023-11-14 01:16:23,406 - mmdet - INFO - Epoch [11][6800/7330] lr: 1.000e-05, eta: 0:50:12, time: 0.378, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0309, loss_cls: 0.1334, acc: 94.9099, loss_bbox: 0.1839, loss_mask: 0.2023, loss: 0.5638 2023-11-14 01:16:42,303 - mmdet - INFO - Epoch [11][6850/7330] lr: 1.000e-05, eta: 0:49:53, time: 0.378, data_time: 0.017, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0323, loss_cls: 0.1346, acc: 94.8037, loss_bbox: 0.1800, loss_mask: 0.1963, loss: 0.5563 2023-11-14 01:17:04,055 - mmdet - INFO - Epoch [11][6900/7330] lr: 1.000e-05, eta: 0:49:34, time: 0.435, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0350, loss_cls: 0.1431, acc: 94.5471, loss_bbox: 0.1953, loss_mask: 0.2093, loss: 0.5984 2023-11-14 01:17:23,238 - mmdet - INFO - Epoch [11][6950/7330] lr: 1.000e-05, eta: 0:49:15, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0322, loss_cls: 0.1345, acc: 94.8357, loss_bbox: 0.1851, loss_mask: 0.2027, loss: 0.5672 2023-11-14 01:17:42,144 - mmdet - INFO - Epoch [11][7000/7330] lr: 1.000e-05, eta: 0:48:56, time: 0.378, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0349, loss_cls: 0.1408, acc: 94.6133, loss_bbox: 0.1890, loss_mask: 0.2033, loss: 0.5818 2023-11-14 01:18:01,233 - mmdet - INFO - Epoch [11][7050/7330] lr: 1.000e-05, eta: 0:48:37, time: 0.382, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0342, loss_cls: 0.1429, acc: 94.4978, loss_bbox: 0.1893, loss_mask: 0.2046, loss: 0.5852 2023-11-14 01:18:20,457 - mmdet - INFO - Epoch [11][7100/7330] lr: 1.000e-05, eta: 0:48:18, time: 0.385, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0358, loss_cls: 0.1385, acc: 94.5898, loss_bbox: 0.1932, loss_mask: 0.2020, loss: 0.5838 2023-11-14 01:18:39,171 - mmdet - INFO - Epoch [11][7150/7330] lr: 1.000e-05, eta: 0:47:58, time: 0.374, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0325, loss_cls: 0.1318, acc: 94.8926, loss_bbox: 0.1845, loss_mask: 0.1997, loss: 0.5608 2023-11-14 01:18:58,546 - mmdet - INFO - Epoch [11][7200/7330] lr: 1.000e-05, eta: 0:47:39, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0378, loss_cls: 0.1395, acc: 94.5940, loss_bbox: 0.1909, loss_mask: 0.2043, loss: 0.5882 2023-11-14 01:19:17,860 - mmdet - INFO - Epoch [11][7250/7330] lr: 1.000e-05, eta: 0:47:20, time: 0.386, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0338, loss_cls: 0.1308, acc: 94.9321, loss_bbox: 0.1862, loss_mask: 0.2035, loss: 0.5672 2023-11-14 01:19:36,742 - mmdet - INFO - Epoch [11][7300/7330] lr: 1.000e-05, eta: 0:47:01, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0344, loss_cls: 0.1375, acc: 94.6326, loss_bbox: 0.1893, loss_mask: 0.2098, loss: 0.5844 2023-11-14 01:19:48,984 - mmdet - INFO - Saving checkpoint at 11 epochs 2023-11-14 01:20:34,985 - mmdet - INFO - Evaluating bbox... 2023-11-14 01:21:03,474 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.492 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.708 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.539 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.328 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.531 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.646 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.430 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.651 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.769 2023-11-14 01:21:03,476 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.584 | bicycle | 0.383 | car | 0.497 | | motorcycle | 0.492 | airplane | 0.705 | bus | 0.698 | | train | 0.692 | truck | 0.441 | boat | 0.352 | | traffic light | 0.312 | fire hydrant | 0.732 | stop sign | 0.699 | | parking meter | 0.532 | bench | 0.323 | bird | 0.430 | | cat | 0.760 | dog | 0.720 | horse | 0.631 | | sheep | 0.595 | cow | 0.629 | elephant | 0.700 | | bear | 0.773 | zebra | 0.707 | giraffe | 0.720 | | backpack | 0.218 | umbrella | 0.480 | handbag | 0.236 | | tie | 0.410 | suitcase | 0.476 | frisbee | 0.699 | | skis | 0.316 | snowboard | 0.491 | sports ball | 0.485 | | kite | 0.485 | baseball bat | 0.410 | baseball glove | 0.450 | | skateboard | 0.618 | surfboard | 0.465 | tennis racket | 0.566 | | bottle | 0.455 | wine glass | 0.427 | cup | 0.509 | | fork | 0.470 | knife | 0.294 | spoon | 0.296 | | bowl | 0.473 | banana | 0.303 | apple | 0.281 | | sandwich | 0.481 | orange | 0.365 | broccoli | 0.260 | | carrot | 0.264 | hot dog | 0.484 | pizza | 0.552 | | donut | 0.561 | cake | 0.451 | chair | 0.368 | | couch | 0.487 | potted plant | 0.358 | bed | 0.488 | | dining table | 0.335 | toilet | 0.685 | tv | 0.634 | | laptop | 0.683 | mouse | 0.662 | remote | 0.424 | | keyboard | 0.566 | cell phone | 0.448 | microwave | 0.675 | | oven | 0.413 | toaster | 0.482 | sink | 0.450 | | refrigerator | 0.661 | book | 0.211 | clock | 0.540 | | vase | 0.437 | scissors | 0.407 | teddy bear | 0.548 | | hair drier | 0.227 | toothbrush | 0.317 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 01:21:03,476 - mmdet - INFO - Evaluating segm... 2023-11-14 01:21:32,818 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.440 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.679 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.477 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.472 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.632 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.552 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.373 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.593 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.716 2023-11-14 01:21:32,821 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.510 | bicycle | 0.222 | car | 0.458 | | motorcycle | 0.399 | airplane | 0.540 | bus | 0.689 | | train | 0.684 | truck | 0.413 | boat | 0.318 | | traffic light | 0.304 | fire hydrant | 0.707 | stop sign | 0.683 | | parking meter | 0.537 | bench | 0.241 | bird | 0.357 | | cat | 0.737 | dog | 0.665 | horse | 0.466 | | sheep | 0.517 | cow | 0.532 | elephant | 0.640 | | bear | 0.752 | zebra | 0.629 | giraffe | 0.555 | | backpack | 0.225 | umbrella | 0.514 | handbag | 0.224 | | tie | 0.370 | suitcase | 0.493 | frisbee | 0.679 | | skis | 0.067 | snowboard | 0.287 | sports ball | 0.483 | | kite | 0.340 | baseball bat | 0.324 | baseball glove | 0.477 | | skateboard | 0.391 | surfboard | 0.384 | tennis racket | 0.603 | | bottle | 0.440 | wine glass | 0.389 | cup | 0.512 | | fork | 0.256 | knife | 0.202 | spoon | 0.207 | | bowl | 0.441 | banana | 0.260 | apple | 0.267 | | sandwich | 0.488 | orange | 0.359 | broccoli | 0.242 | | carrot | 0.229 | hot dog | 0.388 | pizza | 0.532 | | donut | 0.558 | cake | 0.453 | chair | 0.263 | | couch | 0.407 | potted plant | 0.299 | bed | 0.403 | | dining table | 0.198 | toilet | 0.651 | tv | 0.658 | | laptop | 0.675 | mouse | 0.645 | remote | 0.380 | | keyboard | 0.560 | cell phone | 0.416 | microwave | 0.687 | | oven | 0.372 | toaster | 0.501 | sink | 0.407 | | refrigerator | 0.666 | book | 0.160 | clock | 0.542 | | vase | 0.432 | scissors | 0.309 | teddy bear | 0.522 | | hair drier | 0.142 | toothbrush | 0.241 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 01:21:33,212 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 01:21:33,213 - mmdet - INFO - Epoch(val) [11][625] bbox_mAP: 0.4918, bbox_mAP_50: 0.7079, bbox_mAP_75: 0.5391, bbox_mAP_s: 0.3277, bbox_mAP_m: 0.5310, bbox_mAP_l: 0.6460, bbox_mAP_copypaste: 0.4918 0.7079 0.5391 0.3277 0.5310 0.6460, segm_mAP: 0.4397, segm_mAP_50: 0.6789, segm_mAP_75: 0.4765, segm_mAP_s: 0.2458, segm_mAP_m: 0.4722, segm_mAP_l: 0.6317, segm_mAP_copypaste: 0.4397 0.6789 0.4765 0.2458 0.4722 0.6317 2023-11-14 01:21:57,217 - mmdet - INFO - Epoch [12][50/7330] lr: 1.000e-06, eta: 0:46:30, time: 0.480, data_time: 0.092, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0341, loss_cls: 0.1382, acc: 94.6118, loss_bbox: 0.1887, loss_mask: 0.1985, loss: 0.5728 2023-11-14 01:22:17,608 - mmdet - INFO - Epoch [12][100/7330] lr: 1.000e-06, eta: 0:46:11, time: 0.408, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0345, loss_cls: 0.1343, acc: 94.8376, loss_bbox: 0.1829, loss_mask: 0.1982, loss: 0.5630 2023-11-14 01:22:37,531 - mmdet - INFO - Epoch [12][150/7330] lr: 1.000e-06, eta: 0:45:52, time: 0.398, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0337, loss_cls: 0.1359, acc: 94.7922, loss_bbox: 0.1840, loss_mask: 0.1988, loss: 0.5663 2023-11-14 01:22:57,275 - mmdet - INFO - Epoch [12][200/7330] lr: 1.000e-06, eta: 0:45:32, time: 0.395, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0350, loss_cls: 0.1390, acc: 94.6057, loss_bbox: 0.1915, loss_mask: 0.2026, loss: 0.5822 2023-11-14 01:23:16,912 - mmdet - INFO - Epoch [12][250/7330] lr: 1.000e-06, eta: 0:45:13, time: 0.393, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0325, loss_cls: 0.1347, acc: 94.7952, loss_bbox: 0.1847, loss_mask: 0.2051, loss: 0.5694 2023-11-14 01:23:36,856 - mmdet - INFO - Epoch [12][300/7330] lr: 1.000e-06, eta: 0:44:54, time: 0.399, data_time: 0.035, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0340, loss_cls: 0.1329, acc: 94.8936, loss_bbox: 0.1847, loss_mask: 0.1974, loss: 0.5625 2023-11-14 01:23:57,042 - mmdet - INFO - Epoch [12][350/7330] lr: 1.000e-06, eta: 0:44:35, time: 0.404, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0348, loss_cls: 0.1369, acc: 94.7444, loss_bbox: 0.1872, loss_mask: 0.1977, loss: 0.5706 2023-11-14 01:24:16,628 - mmdet - INFO - Epoch [12][400/7330] lr: 1.000e-06, eta: 0:44:16, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0337, loss_cls: 0.1333, acc: 94.8809, loss_bbox: 0.1810, loss_mask: 0.1980, loss: 0.5591 2023-11-14 01:24:36,002 - mmdet - INFO - Epoch [12][450/7330] lr: 1.000e-06, eta: 0:43:57, time: 0.387, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0342, loss_cls: 0.1360, acc: 94.7397, loss_bbox: 0.1886, loss_mask: 0.1990, loss: 0.5723 2023-11-14 01:24:55,751 - mmdet - INFO - Epoch [12][500/7330] lr: 1.000e-06, eta: 0:43:38, time: 0.395, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0324, loss_cls: 0.1326, acc: 94.9297, loss_bbox: 0.1823, loss_mask: 0.1992, loss: 0.5591 2023-11-14 01:25:15,676 - mmdet - INFO - Epoch [12][550/7330] lr: 1.000e-06, eta: 0:43:19, time: 0.398, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0351, loss_cls: 0.1341, acc: 94.7896, loss_bbox: 0.1843, loss_mask: 0.2008, loss: 0.5678 2023-11-14 01:25:35,875 - mmdet - INFO - Epoch [12][600/7330] lr: 1.000e-06, eta: 0:43:00, time: 0.404, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0345, loss_cls: 0.1324, acc: 94.8481, loss_bbox: 0.1902, loss_mask: 0.2041, loss: 0.5736 2023-11-14 01:25:55,766 - mmdet - INFO - Epoch [12][650/7330] lr: 1.000e-06, eta: 0:42:40, time: 0.398, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0335, loss_cls: 0.1341, acc: 94.8008, loss_bbox: 0.1833, loss_mask: 0.1988, loss: 0.5628 2023-11-14 01:26:15,558 - mmdet - INFO - Epoch [12][700/7330] lr: 1.000e-06, eta: 0:42:21, time: 0.396, data_time: 0.035, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0339, loss_cls: 0.1354, acc: 94.7471, loss_bbox: 0.1883, loss_mask: 0.1977, loss: 0.5683 2023-11-14 01:26:35,026 - mmdet - INFO - Epoch [12][750/7330] lr: 1.000e-06, eta: 0:42:02, time: 0.389, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0330, loss_cls: 0.1340, acc: 94.7856, loss_bbox: 0.1808, loss_mask: 0.1965, loss: 0.5567 2023-11-14 01:26:54,857 - mmdet - INFO - Epoch [12][800/7330] lr: 1.000e-06, eta: 0:41:43, time: 0.397, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0346, loss_cls: 0.1380, acc: 94.6545, loss_bbox: 0.1920, loss_mask: 0.2074, loss: 0.5860 2023-11-14 01:27:14,665 - mmdet - INFO - Epoch [12][850/7330] lr: 1.000e-06, eta: 0:41:24, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0349, loss_cls: 0.1332, acc: 94.8259, loss_bbox: 0.1846, loss_mask: 0.2019, loss: 0.5673 2023-11-14 01:27:34,149 - mmdet - INFO - Epoch [12][900/7330] lr: 1.000e-06, eta: 0:41:05, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0314, loss_cls: 0.1319, acc: 94.9482, loss_bbox: 0.1827, loss_mask: 0.1968, loss: 0.5554 2023-11-14 01:27:53,440 - mmdet - INFO - Epoch [12][950/7330] lr: 1.000e-06, eta: 0:40:46, time: 0.386, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0313, loss_cls: 0.1277, acc: 94.9714, loss_bbox: 0.1781, loss_mask: 0.1971, loss: 0.5463 2023-11-14 01:28:13,379 - mmdet - INFO - Epoch [12][1000/7330] lr: 1.000e-06, eta: 0:40:27, time: 0.399, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0335, loss_cls: 0.1392, acc: 94.6238, loss_bbox: 0.1916, loss_mask: 0.2025, loss: 0.5802 2023-11-14 01:28:33,215 - mmdet - INFO - Epoch [12][1050/7330] lr: 1.000e-06, eta: 0:40:07, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0338, loss_cls: 0.1359, acc: 94.8047, loss_bbox: 0.1877, loss_mask: 0.2001, loss: 0.5711 2023-11-14 01:28:53,411 - mmdet - INFO - Epoch [12][1100/7330] lr: 1.000e-06, eta: 0:39:48, time: 0.404, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0370, loss_cls: 0.1426, acc: 94.5037, loss_bbox: 0.2006, loss_mask: 0.2122, loss: 0.6086 2023-11-14 01:29:13,006 - mmdet - INFO - Epoch [12][1150/7330] lr: 1.000e-06, eta: 0:39:29, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0324, loss_cls: 0.1332, acc: 94.8696, loss_bbox: 0.1818, loss_mask: 0.2015, loss: 0.5612 2023-11-14 01:29:32,987 - mmdet - INFO - Epoch [12][1200/7330] lr: 1.000e-06, eta: 0:39:10, time: 0.400, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0342, loss_cls: 0.1376, acc: 94.6646, loss_bbox: 0.1872, loss_mask: 0.2000, loss: 0.5731 2023-11-14 01:29:52,952 - mmdet - INFO - Epoch [12][1250/7330] lr: 1.000e-06, eta: 0:38:51, time: 0.399, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0337, loss_cls: 0.1417, acc: 94.4927, loss_bbox: 0.1972, loss_mask: 0.2043, loss: 0.5906 2023-11-14 01:30:12,725 - mmdet - INFO - Epoch [12][1300/7330] lr: 1.000e-06, eta: 0:38:32, time: 0.395, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0317, loss_cls: 0.1269, acc: 95.1013, loss_bbox: 0.1800, loss_mask: 0.1973, loss: 0.5490 2023-11-14 01:30:32,582 - mmdet - INFO - Epoch [12][1350/7330] lr: 1.000e-06, eta: 0:38:13, time: 0.397, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0345, loss_cls: 0.1364, acc: 94.7524, loss_bbox: 0.1861, loss_mask: 0.1979, loss: 0.5694 2023-11-14 01:30:52,173 - mmdet - INFO - Epoch [12][1400/7330] lr: 1.000e-06, eta: 0:37:54, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0325, loss_cls: 0.1350, acc: 94.7698, loss_bbox: 0.1894, loss_mask: 0.2018, loss: 0.5729 2023-11-14 01:31:11,881 - mmdet - INFO - Epoch [12][1450/7330] lr: 1.000e-06, eta: 0:37:34, time: 0.394, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0343, loss_cls: 0.1395, acc: 94.6040, loss_bbox: 0.1920, loss_mask: 0.2066, loss: 0.5875 2023-11-14 01:31:32,000 - mmdet - INFO - Epoch [12][1500/7330] lr: 1.000e-06, eta: 0:37:15, time: 0.402, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0346, loss_cls: 0.1308, acc: 94.8796, loss_bbox: 0.1864, loss_mask: 0.1998, loss: 0.5657 2023-11-14 01:31:51,576 - mmdet - INFO - Epoch [12][1550/7330] lr: 1.000e-06, eta: 0:36:56, time: 0.392, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0324, loss_cls: 0.1289, acc: 94.9404, loss_bbox: 0.1801, loss_mask: 0.1949, loss: 0.5489 2023-11-14 01:32:11,378 - mmdet - INFO - Epoch [12][1600/7330] lr: 1.000e-06, eta: 0:36:37, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0345, loss_cls: 0.1330, acc: 94.8455, loss_bbox: 0.1850, loss_mask: 0.2012, loss: 0.5666 2023-11-14 01:32:30,544 - mmdet - INFO - Epoch [12][1650/7330] lr: 1.000e-06, eta: 0:36:18, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0337, loss_cls: 0.1306, acc: 94.9607, loss_bbox: 0.1817, loss_mask: 0.2002, loss: 0.5590 2023-11-14 01:32:50,255 - mmdet - INFO - Epoch [12][1700/7330] lr: 1.000e-06, eta: 0:35:59, time: 0.394, data_time: 0.033, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0332, loss_cls: 0.1333, acc: 94.8660, loss_bbox: 0.1809, loss_mask: 0.1958, loss: 0.5562 2023-11-14 01:33:10,038 - mmdet - INFO - Epoch [12][1750/7330] lr: 1.000e-06, eta: 0:35:40, time: 0.396, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0341, loss_cls: 0.1367, acc: 94.6667, loss_bbox: 0.1899, loss_mask: 0.2045, loss: 0.5795 2023-11-14 01:33:29,445 - mmdet - INFO - Epoch [12][1800/7330] lr: 1.000e-06, eta: 0:35:20, time: 0.388, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0348, loss_cls: 0.1362, acc: 94.7632, loss_bbox: 0.1844, loss_mask: 0.2041, loss: 0.5742 2023-11-14 01:33:48,836 - mmdet - INFO - Epoch [12][1850/7330] lr: 1.000e-06, eta: 0:35:01, time: 0.388, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0335, loss_cls: 0.1347, acc: 94.7595, loss_bbox: 0.1845, loss_mask: 0.2036, loss: 0.5699 2023-11-14 01:34:08,707 - mmdet - INFO - Epoch [12][1900/7330] lr: 1.000e-06, eta: 0:34:42, time: 0.397, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0328, loss_cls: 0.1355, acc: 94.8474, loss_bbox: 0.1886, loss_mask: 0.2053, loss: 0.5746 2023-11-14 01:34:28,156 - mmdet - INFO - Epoch [12][1950/7330] lr: 1.000e-06, eta: 0:34:23, time: 0.389, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0317, loss_cls: 0.1332, acc: 94.9260, loss_bbox: 0.1847, loss_mask: 0.2027, loss: 0.5655 2023-11-14 01:34:48,192 - mmdet - INFO - Epoch [12][2000/7330] lr: 1.000e-06, eta: 0:34:04, time: 0.401, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0342, loss_cls: 0.1392, acc: 94.5708, loss_bbox: 0.1941, loss_mask: 0.2061, loss: 0.5870 2023-11-14 01:35:07,933 - mmdet - INFO - Epoch [12][2050/7330] lr: 1.000e-06, eta: 0:33:45, time: 0.395, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0339, loss_cls: 0.1383, acc: 94.6230, loss_bbox: 0.1882, loss_mask: 0.2068, loss: 0.5808 2023-11-14 01:35:27,236 - mmdet - INFO - Epoch [12][2100/7330] lr: 1.000e-06, eta: 0:33:26, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0323, loss_cls: 0.1342, acc: 94.8281, loss_bbox: 0.1848, loss_mask: 0.1987, loss: 0.5633 2023-11-14 01:35:46,935 - mmdet - INFO - Epoch [12][2150/7330] lr: 1.000e-06, eta: 0:33:06, time: 0.394, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0348, loss_cls: 0.1352, acc: 94.7346, loss_bbox: 0.1835, loss_mask: 0.1966, loss: 0.5643 2023-11-14 01:36:06,978 - mmdet - INFO - Epoch [12][2200/7330] lr: 1.000e-06, eta: 0:32:47, time: 0.401, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0345, loss_cls: 0.1410, acc: 94.5854, loss_bbox: 0.1903, loss_mask: 0.2020, loss: 0.5819 2023-11-14 01:36:26,899 - mmdet - INFO - Epoch [12][2250/7330] lr: 1.000e-06, eta: 0:32:28, time: 0.398, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0331, loss_cls: 0.1373, acc: 94.6191, loss_bbox: 0.1859, loss_mask: 0.2040, loss: 0.5740 2023-11-14 01:36:46,754 - mmdet - INFO - Epoch [12][2300/7330] lr: 1.000e-06, eta: 0:32:09, time: 0.397, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0350, loss_cls: 0.1365, acc: 94.7502, loss_bbox: 0.1871, loss_mask: 0.1999, loss: 0.5721 2023-11-14 01:37:06,606 - mmdet - INFO - Epoch [12][2350/7330] lr: 1.000e-06, eta: 0:31:50, time: 0.397, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0333, loss_cls: 0.1307, acc: 94.9282, loss_bbox: 0.1815, loss_mask: 0.1959, loss: 0.5536 2023-11-14 01:37:26,161 - mmdet - INFO - Epoch [12][2400/7330] lr: 1.000e-06, eta: 0:31:31, time: 0.391, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0334, loss_cls: 0.1345, acc: 94.7522, loss_bbox: 0.1893, loss_mask: 0.2026, loss: 0.5723 2023-11-14 01:37:45,887 - mmdet - INFO - Epoch [12][2450/7330] lr: 1.000e-06, eta: 0:31:12, time: 0.395, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0334, loss_cls: 0.1375, acc: 94.7266, loss_bbox: 0.1872, loss_mask: 0.2032, loss: 0.5745 2023-11-14 01:38:05,393 - mmdet - INFO - Epoch [12][2500/7330] lr: 1.000e-06, eta: 0:30:52, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0324, loss_cls: 0.1353, acc: 94.8660, loss_bbox: 0.1837, loss_mask: 0.2049, loss: 0.5705 2023-11-14 01:38:25,197 - mmdet - INFO - Epoch [12][2550/7330] lr: 1.000e-06, eta: 0:30:33, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0325, loss_cls: 0.1329, acc: 94.8645, loss_bbox: 0.1852, loss_mask: 0.2007, loss: 0.5640 2023-11-14 01:38:44,740 - mmdet - INFO - Epoch [12][2600/7330] lr: 1.000e-06, eta: 0:30:14, time: 0.391, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0343, loss_cls: 0.1342, acc: 94.8022, loss_bbox: 0.1874, loss_mask: 0.2029, loss: 0.5725 2023-11-14 01:39:04,206 - mmdet - INFO - Epoch [12][2650/7330] lr: 1.000e-06, eta: 0:29:55, time: 0.389, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0337, loss_cls: 0.1363, acc: 94.7229, loss_bbox: 0.1889, loss_mask: 0.2033, loss: 0.5769 2023-11-14 01:39:23,650 - mmdet - INFO - Epoch [12][2700/7330] lr: 1.000e-06, eta: 0:29:36, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0326, loss_cls: 0.1323, acc: 94.9343, loss_bbox: 0.1828, loss_mask: 0.1992, loss: 0.5601 2023-11-14 01:39:43,184 - mmdet - INFO - Epoch [12][2750/7330] lr: 1.000e-06, eta: 0:29:17, time: 0.391, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0323, loss_cls: 0.1356, acc: 94.8118, loss_bbox: 0.1859, loss_mask: 0.1974, loss: 0.5651 2023-11-14 01:40:02,954 - mmdet - INFO - Epoch [12][2800/7330] lr: 1.000e-06, eta: 0:28:57, time: 0.395, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0336, loss_cls: 0.1360, acc: 94.7705, loss_bbox: 0.1870, loss_mask: 0.1965, loss: 0.5669 2023-11-14 01:40:23,070 - mmdet - INFO - Epoch [12][2850/7330] lr: 1.000e-06, eta: 0:28:38, time: 0.402, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0363, loss_cls: 0.1430, acc: 94.5125, loss_bbox: 0.1957, loss_mask: 0.2041, loss: 0.5940 2023-11-14 01:40:42,697 - mmdet - INFO - Epoch [12][2900/7330] lr: 1.000e-06, eta: 0:28:19, time: 0.393, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0317, loss_cls: 0.1341, acc: 94.7898, loss_bbox: 0.1853, loss_mask: 0.1995, loss: 0.5637 2023-11-14 01:41:01,849 - mmdet - INFO - Epoch [12][2950/7330] lr: 1.000e-06, eta: 0:28:00, time: 0.383, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0331, loss_cls: 0.1345, acc: 94.8613, loss_bbox: 0.1832, loss_mask: 0.1983, loss: 0.5623 2023-11-14 01:41:21,007 - mmdet - INFO - Epoch [12][3000/7330] lr: 1.000e-06, eta: 0:27:41, time: 0.383, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0321, loss_cls: 0.1315, acc: 94.9648, loss_bbox: 0.1805, loss_mask: 0.1980, loss: 0.5551 2023-11-14 01:41:40,677 - mmdet - INFO - Epoch [12][3050/7330] lr: 1.000e-06, eta: 0:27:22, time: 0.393, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0332, loss_cls: 0.1376, acc: 94.6987, loss_bbox: 0.1918, loss_mask: 0.2077, loss: 0.5830 2023-11-14 01:42:00,193 - mmdet - INFO - Epoch [12][3100/7330] lr: 1.000e-06, eta: 0:27:02, time: 0.390, data_time: 0.030, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0331, loss_cls: 0.1319, acc: 94.8931, loss_bbox: 0.1790, loss_mask: 0.1964, loss: 0.5538 2023-11-14 01:42:19,789 - mmdet - INFO - Epoch [12][3150/7330] lr: 1.000e-06, eta: 0:26:43, time: 0.392, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0347, loss_cls: 0.1399, acc: 94.5825, loss_bbox: 0.1918, loss_mask: 0.1993, loss: 0.5798 2023-11-14 01:42:39,097 - mmdet - INFO - Epoch [12][3200/7330] lr: 1.000e-06, eta: 0:26:24, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0304, loss_cls: 0.1213, acc: 95.2993, loss_bbox: 0.1677, loss_mask: 0.1925, loss: 0.5242 2023-11-14 01:42:58,752 - mmdet - INFO - Epoch [12][3250/7330] lr: 1.000e-06, eta: 0:26:05, time: 0.393, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0323, loss_cls: 0.1306, acc: 94.9980, loss_bbox: 0.1791, loss_mask: 0.1994, loss: 0.5539 2023-11-14 01:43:18,242 - mmdet - INFO - Epoch [12][3300/7330] lr: 1.000e-06, eta: 0:25:46, time: 0.390, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0325, loss_cls: 0.1277, acc: 95.1396, loss_bbox: 0.1762, loss_mask: 0.1940, loss: 0.5432 2023-11-14 01:43:37,948 - mmdet - INFO - Epoch [12][3350/7330] lr: 1.000e-06, eta: 0:25:27, time: 0.394, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0350, loss_cls: 0.1347, acc: 94.7905, loss_bbox: 0.1847, loss_mask: 0.1960, loss: 0.5642 2023-11-14 01:43:57,215 - mmdet - INFO - Epoch [12][3400/7330] lr: 1.000e-06, eta: 0:25:07, time: 0.385, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0323, loss_cls: 0.1313, acc: 94.9744, loss_bbox: 0.1803, loss_mask: 0.1998, loss: 0.5568 2023-11-14 01:44:17,417 - mmdet - INFO - Epoch [12][3450/7330] lr: 1.000e-06, eta: 0:24:48, time: 0.404, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0347, loss_cls: 0.1423, acc: 94.4924, loss_bbox: 0.1916, loss_mask: 0.2069, loss: 0.5898 2023-11-14 01:44:37,359 - mmdet - INFO - Epoch [12][3500/7330] lr: 1.000e-06, eta: 0:24:29, time: 0.399, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0347, loss_cls: 0.1406, acc: 94.4663, loss_bbox: 0.1911, loss_mask: 0.2083, loss: 0.5891 2023-11-14 01:44:56,627 - mmdet - INFO - Epoch [12][3550/7330] lr: 1.000e-06, eta: 0:24:10, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0330, loss_cls: 0.1331, acc: 94.8535, loss_bbox: 0.1849, loss_mask: 0.2021, loss: 0.5661 2023-11-14 01:45:16,133 - mmdet - INFO - Epoch [12][3600/7330] lr: 1.000e-06, eta: 0:23:51, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0339, loss_cls: 0.1331, acc: 94.8711, loss_bbox: 0.1839, loss_mask: 0.2012, loss: 0.5658 2023-11-14 01:45:35,400 - mmdet - INFO - Epoch [12][3650/7330] lr: 1.000e-06, eta: 0:23:32, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0313, loss_cls: 0.1298, acc: 94.9995, loss_bbox: 0.1809, loss_mask: 0.2042, loss: 0.5588 2023-11-14 01:45:55,063 - mmdet - INFO - Epoch [12][3700/7330] lr: 1.000e-06, eta: 0:23:12, time: 0.393, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0353, loss_cls: 0.1428, acc: 94.4836, loss_bbox: 0.1911, loss_mask: 0.2009, loss: 0.5857 2023-11-14 01:46:14,299 - mmdet - INFO - Epoch [12][3750/7330] lr: 1.000e-06, eta: 0:22:53, time: 0.385, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0331, loss_cls: 0.1300, acc: 94.9702, loss_bbox: 0.1836, loss_mask: 0.2051, loss: 0.5638 2023-11-14 01:46:33,551 - mmdet - INFO - Epoch [12][3800/7330] lr: 1.000e-06, eta: 0:22:34, time: 0.385, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0354, loss_cls: 0.1322, acc: 94.8303, loss_bbox: 0.1818, loss_mask: 0.1965, loss: 0.5594 2023-11-14 01:46:52,945 - mmdet - INFO - Epoch [12][3850/7330] lr: 1.000e-06, eta: 0:22:15, time: 0.388, data_time: 0.020, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0319, loss_cls: 0.1311, acc: 94.8804, loss_bbox: 0.1830, loss_mask: 0.2048, loss: 0.5638 2023-11-14 01:47:12,414 - mmdet - INFO - Epoch [12][3900/7330] lr: 1.000e-06, eta: 0:21:56, time: 0.389, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0321, loss_cls: 0.1265, acc: 95.0862, loss_bbox: 0.1793, loss_mask: 0.1956, loss: 0.5455 2023-11-14 01:47:31,925 - mmdet - INFO - Epoch [12][3950/7330] lr: 1.000e-06, eta: 0:21:37, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0356, loss_cls: 0.1400, acc: 94.6262, loss_bbox: 0.1871, loss_mask: 0.2034, loss: 0.5793 2023-11-14 01:47:51,108 - mmdet - INFO - Epoch [12][4000/7330] lr: 1.000e-06, eta: 0:21:17, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0308, loss_cls: 0.1234, acc: 95.2043, loss_bbox: 0.1763, loss_mask: 0.1962, loss: 0.5379 2023-11-14 01:48:10,498 - mmdet - INFO - Epoch [12][4050/7330] lr: 1.000e-06, eta: 0:20:58, time: 0.388, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0328, loss_cls: 0.1296, acc: 95.0737, loss_bbox: 0.1810, loss_mask: 0.1945, loss: 0.5499 2023-11-14 01:48:30,408 - mmdet - INFO - Epoch [12][4100/7330] lr: 1.000e-06, eta: 0:20:39, time: 0.398, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0355, loss_cls: 0.1420, acc: 94.5327, loss_bbox: 0.1922, loss_mask: 0.2072, loss: 0.5920 2023-11-14 01:48:49,660 - mmdet - INFO - Epoch [12][4150/7330] lr: 1.000e-06, eta: 0:20:20, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0333, loss_cls: 0.1373, acc: 94.6763, loss_bbox: 0.1879, loss_mask: 0.2020, loss: 0.5741 2023-11-14 01:49:09,096 - mmdet - INFO - Epoch [12][4200/7330] lr: 1.000e-06, eta: 0:20:01, time: 0.389, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0340, loss_cls: 0.1404, acc: 94.5979, loss_bbox: 0.1961, loss_mask: 0.2105, loss: 0.5945 2023-11-14 01:49:28,378 - mmdet - INFO - Epoch [12][4250/7330] lr: 1.000e-06, eta: 0:19:41, time: 0.386, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0325, loss_cls: 0.1326, acc: 94.8604, loss_bbox: 0.1814, loss_mask: 0.2027, loss: 0.5619 2023-11-14 01:49:47,731 - mmdet - INFO - Epoch [12][4300/7330] lr: 1.000e-06, eta: 0:19:22, time: 0.387, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0333, loss_cls: 0.1325, acc: 94.9148, loss_bbox: 0.1796, loss_mask: 0.1994, loss: 0.5579 2023-11-14 01:50:07,072 - mmdet - INFO - Epoch [12][4350/7330] lr: 1.000e-06, eta: 0:19:03, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0339, loss_cls: 0.1388, acc: 94.6829, loss_bbox: 0.1875, loss_mask: 0.2016, loss: 0.5759 2023-11-14 01:50:27,456 - mmdet - INFO - Epoch [12][4400/7330] lr: 1.000e-06, eta: 0:18:44, time: 0.408, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0370, loss_cls: 0.1444, acc: 94.5283, loss_bbox: 0.1933, loss_mask: 0.2014, loss: 0.5908 2023-11-14 01:50:47,231 - mmdet - INFO - Epoch [12][4450/7330] lr: 1.000e-06, eta: 0:18:25, time: 0.396, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0367, loss_cls: 0.1399, acc: 94.5527, loss_bbox: 0.1942, loss_mask: 0.2043, loss: 0.5891 2023-11-14 01:51:06,932 - mmdet - INFO - Epoch [12][4500/7330] lr: 1.000e-06, eta: 0:18:06, time: 0.394, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0353, loss_cls: 0.1408, acc: 94.5151, loss_bbox: 0.1913, loss_mask: 0.2039, loss: 0.5847 2023-11-14 01:51:25,855 - mmdet - INFO - Epoch [12][4550/7330] lr: 1.000e-06, eta: 0:17:46, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0330, loss_cls: 0.1311, acc: 94.8943, loss_bbox: 0.1822, loss_mask: 0.2033, loss: 0.5633 2023-11-14 01:51:44,855 - mmdet - INFO - Epoch [12][4600/7330] lr: 1.000e-06, eta: 0:17:27, time: 0.380, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0339, loss_cls: 0.1288, acc: 95.0088, loss_bbox: 0.1814, loss_mask: 0.1971, loss: 0.5531 2023-11-14 01:52:04,263 - mmdet - INFO - Epoch [12][4650/7330] lr: 1.000e-06, eta: 0:17:08, time: 0.388, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0360, loss_cls: 0.1434, acc: 94.4563, loss_bbox: 0.1914, loss_mask: 0.2047, loss: 0.5908 2023-11-14 01:52:23,422 - mmdet - INFO - Epoch [12][4700/7330] lr: 1.000e-06, eta: 0:16:49, time: 0.383, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0328, loss_cls: 0.1395, acc: 94.6230, loss_bbox: 0.1879, loss_mask: 0.2000, loss: 0.5739 2023-11-14 01:52:42,256 - mmdet - INFO - Epoch [12][4750/7330] lr: 1.000e-06, eta: 0:16:30, time: 0.377, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0335, loss_cls: 0.1366, acc: 94.6570, loss_bbox: 0.1942, loss_mask: 0.2074, loss: 0.5844 2023-11-14 01:53:01,263 - mmdet - INFO - Epoch [12][4800/7330] lr: 1.000e-06, eta: 0:16:10, time: 0.380, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0334, loss_cls: 0.1333, acc: 94.8584, loss_bbox: 0.1837, loss_mask: 0.1984, loss: 0.5627 2023-11-14 01:53:20,311 - mmdet - INFO - Epoch [12][4850/7330] lr: 1.000e-06, eta: 0:15:51, time: 0.381, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0318, loss_cls: 0.1351, acc: 94.8271, loss_bbox: 0.1873, loss_mask: 0.2034, loss: 0.5707 2023-11-14 01:53:39,458 - mmdet - INFO - Epoch [12][4900/7330] lr: 1.000e-06, eta: 0:15:32, time: 0.383, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0321, loss_cls: 0.1321, acc: 94.8604, loss_bbox: 0.1854, loss_mask: 0.2037, loss: 0.5663 2023-11-14 01:53:58,133 - mmdet - INFO - Epoch [12][4950/7330] lr: 1.000e-06, eta: 0:15:13, time: 0.373, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0333, loss_cls: 0.1336, acc: 94.8245, loss_bbox: 0.1882, loss_mask: 0.2031, loss: 0.5717 2023-11-14 01:54:17,698 - mmdet - INFO - Epoch [12][5000/7330] lr: 1.000e-06, eta: 0:14:54, time: 0.391, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0337, loss_cls: 0.1356, acc: 94.7812, loss_bbox: 0.1883, loss_mask: 0.2017, loss: 0.5733 2023-11-14 01:54:37,039 - mmdet - INFO - Epoch [12][5050/7330] lr: 1.000e-06, eta: 0:14:35, time: 0.387, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0335, loss_cls: 0.1355, acc: 94.8193, loss_bbox: 0.1830, loss_mask: 0.2010, loss: 0.5670 2023-11-14 01:54:56,482 - mmdet - INFO - Epoch [12][5100/7330] lr: 1.000e-06, eta: 0:14:15, time: 0.389, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0368, loss_cls: 0.1424, acc: 94.4739, loss_bbox: 0.1955, loss_mask: 0.2057, loss: 0.5946 2023-11-14 01:55:15,540 - mmdet - INFO - Epoch [12][5150/7330] lr: 1.000e-06, eta: 0:13:56, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0333, loss_cls: 0.1382, acc: 94.5466, loss_bbox: 0.1921, loss_mask: 0.2039, loss: 0.5817 2023-11-14 01:55:35,078 - mmdet - INFO - Epoch [12][5200/7330] lr: 1.000e-06, eta: 0:13:37, time: 0.391, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0361, loss_cls: 0.1411, acc: 94.4368, loss_bbox: 0.1955, loss_mask: 0.2074, loss: 0.5953 2023-11-14 01:55:53,768 - mmdet - INFO - Epoch [12][5250/7330] lr: 1.000e-06, eta: 0:13:18, time: 0.374, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0317, loss_cls: 0.1309, acc: 94.8994, loss_bbox: 0.1785, loss_mask: 0.2015, loss: 0.5549 2023-11-14 01:56:12,887 - mmdet - INFO - Epoch [12][5300/7330] lr: 1.000e-06, eta: 0:12:59, time: 0.382, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0320, loss_cls: 0.1302, acc: 94.9399, loss_bbox: 0.1812, loss_mask: 0.2026, loss: 0.5591 2023-11-14 01:56:32,134 - mmdet - INFO - Epoch [12][5350/7330] lr: 1.000e-06, eta: 0:12:39, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0318, loss_cls: 0.1243, acc: 95.2048, loss_bbox: 0.1738, loss_mask: 0.1953, loss: 0.5386 2023-11-14 01:56:51,482 - mmdet - INFO - Epoch [12][5400/7330] lr: 1.000e-06, eta: 0:12:20, time: 0.387, data_time: 0.031, memory: 4444, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0360, loss_cls: 0.1438, acc: 94.4431, loss_bbox: 0.1954, loss_mask: 0.2043, loss: 0.5935 2023-11-14 01:57:10,732 - mmdet - INFO - Epoch [12][5450/7330] lr: 1.000e-06, eta: 0:12:01, time: 0.385, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0354, loss_cls: 0.1351, acc: 94.7759, loss_bbox: 0.1878, loss_mask: 0.2030, loss: 0.5750 2023-11-14 01:57:29,745 - mmdet - INFO - Epoch [12][5500/7330] lr: 1.000e-06, eta: 0:11:42, time: 0.380, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0345, loss_cls: 0.1375, acc: 94.7078, loss_bbox: 0.1881, loss_mask: 0.2048, loss: 0.5782 2023-11-14 01:57:48,779 - mmdet - INFO - Epoch [12][5550/7330] lr: 1.000e-06, eta: 0:11:23, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0319, loss_cls: 0.1279, acc: 95.0261, loss_bbox: 0.1801, loss_mask: 0.1978, loss: 0.5497 2023-11-14 01:58:07,950 - mmdet - INFO - Epoch [12][5600/7330] lr: 1.000e-06, eta: 0:11:03, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0356, loss_cls: 0.1410, acc: 94.5430, loss_bbox: 0.1926, loss_mask: 0.2048, loss: 0.5881 2023-11-14 01:58:27,106 - mmdet - INFO - Epoch [12][5650/7330] lr: 1.000e-06, eta: 0:10:44, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0347, loss_cls: 0.1378, acc: 94.6416, loss_bbox: 0.1903, loss_mask: 0.2035, loss: 0.5800 2023-11-14 01:58:46,596 - mmdet - INFO - Epoch [12][5700/7330] lr: 1.000e-06, eta: 0:10:25, time: 0.390, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0349, loss_cls: 0.1337, acc: 94.8232, loss_bbox: 0.1870, loss_mask: 0.2036, loss: 0.5732 2023-11-14 01:59:06,175 - mmdet - INFO - Epoch [12][5750/7330] lr: 1.000e-06, eta: 0:10:06, time: 0.392, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0339, loss_cls: 0.1304, acc: 94.9094, loss_bbox: 0.1803, loss_mask: 0.2024, loss: 0.5600 2023-11-14 01:59:25,759 - mmdet - INFO - Epoch [12][5800/7330] lr: 1.000e-06, eta: 0:09:47, time: 0.392, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0340, loss_cls: 0.1362, acc: 94.7444, loss_bbox: 0.1860, loss_mask: 0.2028, loss: 0.5738 2023-11-14 01:59:44,932 - mmdet - INFO - Epoch [12][5850/7330] lr: 1.000e-06, eta: 0:09:28, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0346, loss_cls: 0.1415, acc: 94.6267, loss_bbox: 0.1866, loss_mask: 0.2036, loss: 0.5818 2023-11-14 02:00:04,045 - mmdet - INFO - Epoch [12][5900/7330] lr: 1.000e-06, eta: 0:09:08, time: 0.382, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0334, loss_cls: 0.1351, acc: 94.8035, loss_bbox: 0.1873, loss_mask: 0.2071, loss: 0.5763 2023-11-14 02:00:23,095 - mmdet - INFO - Epoch [12][5950/7330] lr: 1.000e-06, eta: 0:08:49, time: 0.381, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0331, loss_cls: 0.1347, acc: 94.7495, loss_bbox: 0.1890, loss_mask: 0.2028, loss: 0.5731 2023-11-14 02:00:42,163 - mmdet - INFO - Epoch [12][6000/7330] lr: 1.000e-06, eta: 0:08:30, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0325, loss_cls: 0.1324, acc: 94.8604, loss_bbox: 0.1881, loss_mask: 0.2019, loss: 0.5677 2023-11-14 02:01:01,350 - mmdet - INFO - Epoch [12][6050/7330] lr: 1.000e-06, eta: 0:08:11, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0317, loss_cls: 0.1335, acc: 94.8206, loss_bbox: 0.1866, loss_mask: 0.2008, loss: 0.5657 2023-11-14 02:01:20,569 - mmdet - INFO - Epoch [12][6100/7330] lr: 1.000e-06, eta: 0:07:52, time: 0.384, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0330, loss_cls: 0.1344, acc: 94.8286, loss_bbox: 0.1859, loss_mask: 0.1989, loss: 0.5651 2023-11-14 02:01:40,400 - mmdet - INFO - Epoch [12][6150/7330] lr: 1.000e-06, eta: 0:07:32, time: 0.397, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0345, loss_cls: 0.1399, acc: 94.6060, loss_bbox: 0.1921, loss_mask: 0.2044, loss: 0.5856 2023-11-14 02:01:59,586 - mmdet - INFO - Epoch [12][6200/7330] lr: 1.000e-06, eta: 0:07:13, time: 0.384, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0321, loss_cls: 0.1319, acc: 94.8889, loss_bbox: 0.1831, loss_mask: 0.1961, loss: 0.5570 2023-11-14 02:02:18,803 - mmdet - INFO - Epoch [12][6250/7330] lr: 1.000e-06, eta: 0:06:54, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0326, loss_cls: 0.1314, acc: 94.9026, loss_bbox: 0.1844, loss_mask: 0.2026, loss: 0.5640 2023-11-14 02:02:38,415 - mmdet - INFO - Epoch [12][6300/7330] lr: 1.000e-06, eta: 0:06:35, time: 0.392, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0339, loss_cls: 0.1336, acc: 94.8611, loss_bbox: 0.1852, loss_mask: 0.1984, loss: 0.5644 2023-11-14 02:02:57,708 - mmdet - INFO - Epoch [12][6350/7330] lr: 1.000e-06, eta: 0:06:16, time: 0.386, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0351, loss_cls: 0.1380, acc: 94.7168, loss_bbox: 0.1895, loss_mask: 0.2005, loss: 0.5773 2023-11-14 02:03:16,962 - mmdet - INFO - Epoch [12][6400/7330] lr: 1.000e-06, eta: 0:05:56, time: 0.385, data_time: 0.028, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0328, loss_cls: 0.1304, acc: 95.0083, loss_bbox: 0.1832, loss_mask: 0.1958, loss: 0.5556 2023-11-14 02:03:36,019 - mmdet - INFO - Epoch [12][6450/7330] lr: 1.000e-06, eta: 0:05:37, time: 0.381, data_time: 0.032, memory: 4444, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0331, loss_cls: 0.1363, acc: 94.7595, loss_bbox: 0.1852, loss_mask: 0.1976, loss: 0.5648 2023-11-14 02:03:55,399 - mmdet - INFO - Epoch [12][6500/7330] lr: 1.000e-06, eta: 0:05:18, time: 0.388, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0347, loss_cls: 0.1371, acc: 94.6226, loss_bbox: 0.1869, loss_mask: 0.1979, loss: 0.5696 2023-11-14 02:04:14,633 - mmdet - INFO - Epoch [12][6550/7330] lr: 1.000e-06, eta: 0:04:59, time: 0.385, data_time: 0.021, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0333, loss_cls: 0.1324, acc: 94.9307, loss_bbox: 0.1834, loss_mask: 0.2012, loss: 0.5637 2023-11-14 02:04:33,681 - mmdet - INFO - Epoch [12][6600/7330] lr: 1.000e-06, eta: 0:04:40, time: 0.381, data_time: 0.023, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0339, loss_cls: 0.1412, acc: 94.5811, loss_bbox: 0.1936, loss_mask: 0.2042, loss: 0.5865 2023-11-14 02:04:53,013 - mmdet - INFO - Epoch [12][6650/7330] lr: 1.000e-06, eta: 0:04:20, time: 0.387, data_time: 0.027, memory: 4444, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0360, loss_cls: 0.1398, acc: 94.5461, loss_bbox: 0.1907, loss_mask: 0.2018, loss: 0.5824 2023-11-14 02:05:12,534 - mmdet - INFO - Epoch [12][6700/7330] lr: 1.000e-06, eta: 0:04:01, time: 0.390, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0356, loss_cls: 0.1381, acc: 94.7227, loss_bbox: 0.1894, loss_mask: 0.2035, loss: 0.5808 2023-11-14 02:05:31,712 - mmdet - INFO - Epoch [12][6750/7330] lr: 1.000e-06, eta: 0:03:42, time: 0.384, data_time: 0.022, memory: 4444, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0325, loss_cls: 0.1343, acc: 94.8047, loss_bbox: 0.1865, loss_mask: 0.2002, loss: 0.5670 2023-11-14 02:05:51,197 - mmdet - INFO - Epoch [12][6800/7330] lr: 1.000e-06, eta: 0:03:23, time: 0.390, data_time: 0.029, memory: 4444, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0328, loss_cls: 0.1342, acc: 94.8259, loss_bbox: 0.1814, loss_mask: 0.1990, loss: 0.5608 2023-11-14 02:06:10,359 - mmdet - INFO - Epoch [12][6850/7330] lr: 1.000e-06, eta: 0:03:04, time: 0.383, data_time: 0.026, memory: 4444, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0336, loss_cls: 0.1319, acc: 94.8911, loss_bbox: 0.1825, loss_mask: 0.2001, loss: 0.5618 2023-11-14 02:06:29,572 - mmdet - INFO - Epoch [12][6900/7330] lr: 1.000e-06, eta: 0:02:45, time: 0.384, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0336, loss_cls: 0.1296, acc: 94.9773, loss_bbox: 0.1845, loss_mask: 0.1999, loss: 0.5601 2023-11-14 02:06:48,468 - mmdet - INFO - Epoch [12][6950/7330] lr: 1.000e-06, eta: 0:02:25, time: 0.378, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0318, loss_cls: 0.1314, acc: 94.9417, loss_bbox: 0.1798, loss_mask: 0.2009, loss: 0.5573 2023-11-14 02:07:07,521 - mmdet - INFO - Epoch [12][7000/7330] lr: 1.000e-06, eta: 0:02:06, time: 0.381, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0316, loss_cls: 0.1325, acc: 94.9060, loss_bbox: 0.1857, loss_mask: 0.1985, loss: 0.5608 2023-11-14 02:07:27,026 - mmdet - INFO - Epoch [12][7050/7330] lr: 1.000e-06, eta: 0:01:47, time: 0.390, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0375, loss_cls: 0.1412, acc: 94.4807, loss_bbox: 0.1927, loss_mask: 0.2082, loss: 0.5956 2023-11-14 02:07:46,164 - mmdet - INFO - Epoch [12][7100/7330] lr: 1.000e-06, eta: 0:01:28, time: 0.383, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0328, loss_cls: 0.1333, acc: 94.8403, loss_bbox: 0.1839, loss_mask: 0.2002, loss: 0.5633 2023-11-14 02:08:04,996 - mmdet - INFO - Epoch [12][7150/7330] lr: 1.000e-06, eta: 0:01:09, time: 0.377, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0309, loss_cls: 0.1260, acc: 95.1602, loss_bbox: 0.1744, loss_mask: 0.1942, loss: 0.5378 2023-11-14 02:08:23,797 - mmdet - INFO - Epoch [12][7200/7330] lr: 1.000e-06, eta: 0:00:49, time: 0.376, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0311, loss_cls: 0.1287, acc: 94.9514, loss_bbox: 0.1776, loss_mask: 0.1968, loss: 0.5469 2023-11-14 02:08:43,056 - mmdet - INFO - Epoch [12][7250/7330] lr: 1.000e-06, eta: 0:00:30, time: 0.385, data_time: 0.025, memory: 4444, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0355, loss_cls: 0.1364, acc: 94.7471, loss_bbox: 0.1837, loss_mask: 0.2034, loss: 0.5740 2023-11-14 02:09:02,234 - mmdet - INFO - Epoch [12][7300/7330] lr: 1.000e-06, eta: 0:00:11, time: 0.384, data_time: 0.024, memory: 4444, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0357, loss_cls: 0.1384, acc: 94.6748, loss_bbox: 0.1888, loss_mask: 0.2013, loss: 0.5789 2023-11-14 02:09:14,189 - mmdet - INFO - Saving checkpoint at 12 epochs 2023-11-14 02:10:00,760 - mmdet - INFO - Evaluating bbox... 2023-11-14 02:10:30,825 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.492 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.707 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.539 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.328 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.531 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.647 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.431 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.651 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.768 2023-11-14 02:10:30,828 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.586 | bicycle | 0.387 | car | 0.494 | | motorcycle | 0.493 | airplane | 0.705 | bus | 0.701 | | train | 0.694 | truck | 0.441 | boat | 0.351 | | traffic light | 0.313 | fire hydrant | 0.736 | stop sign | 0.692 | | parking meter | 0.524 | bench | 0.323 | bird | 0.431 | | cat | 0.758 | dog | 0.721 | horse | 0.634 | | sheep | 0.594 | cow | 0.632 | elephant | 0.705 | | bear | 0.777 | zebra | 0.717 | giraffe | 0.721 | | backpack | 0.216 | umbrella | 0.474 | handbag | 0.239 | | tie | 0.413 | suitcase | 0.476 | frisbee | 0.698 | | skis | 0.322 | snowboard | 0.491 | sports ball | 0.486 | | kite | 0.476 | baseball bat | 0.415 | baseball glove | 0.445 | | skateboard | 0.614 | surfboard | 0.466 | tennis racket | 0.569 | | bottle | 0.457 | wine glass | 0.431 | cup | 0.507 | | fork | 0.472 | knife | 0.297 | spoon | 0.301 | | bowl | 0.479 | banana | 0.307 | apple | 0.275 | | sandwich | 0.485 | orange | 0.365 | broccoli | 0.260 | | carrot | 0.270 | hot dog | 0.493 | pizza | 0.558 | | donut | 0.562 | cake | 0.450 | chair | 0.369 | | couch | 0.493 | potted plant | 0.354 | bed | 0.479 | | dining table | 0.333 | toilet | 0.688 | tv | 0.636 | | laptop | 0.687 | mouse | 0.663 | remote | 0.423 | | keyboard | 0.567 | cell phone | 0.451 | microwave | 0.684 | | oven | 0.413 | toaster | 0.453 | sink | 0.446 | | refrigerator | 0.665 | book | 0.210 | clock | 0.539 | | vase | 0.435 | scissors | 0.407 | teddy bear | 0.552 | | hair drier | 0.218 | toothbrush | 0.327 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 02:10:30,828 - mmdet - INFO - Evaluating segm... 2023-11-14 02:11:00,346 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.440 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.678 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.476 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.470 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.633 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.372 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.591 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.714 2023-11-14 02:11:00,348 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.511 | bicycle | 0.223 | car | 0.457 | | motorcycle | 0.402 | airplane | 0.539 | bus | 0.688 | | train | 0.691 | truck | 0.414 | boat | 0.313 | | traffic light | 0.302 | fire hydrant | 0.705 | stop sign | 0.679 | | parking meter | 0.537 | bench | 0.247 | bird | 0.358 | | cat | 0.736 | dog | 0.667 | horse | 0.469 | | sheep | 0.519 | cow | 0.534 | elephant | 0.641 | | bear | 0.752 | zebra | 0.627 | giraffe | 0.551 | | backpack | 0.222 | umbrella | 0.513 | handbag | 0.224 | | tie | 0.370 | suitcase | 0.490 | frisbee | 0.679 | | skis | 0.067 | snowboard | 0.288 | sports ball | 0.485 | | kite | 0.339 | baseball bat | 0.326 | baseball glove | 0.471 | | skateboard | 0.390 | surfboard | 0.379 | tennis racket | 0.606 | | bottle | 0.439 | wine glass | 0.391 | cup | 0.510 | | fork | 0.250 | knife | 0.206 | spoon | 0.207 | | bowl | 0.445 | banana | 0.260 | apple | 0.264 | | sandwich | 0.489 | orange | 0.359 | broccoli | 0.240 | | carrot | 0.232 | hot dog | 0.395 | pizza | 0.534 | | donut | 0.556 | cake | 0.454 | chair | 0.265 | | couch | 0.407 | potted plant | 0.296 | bed | 0.396 | | dining table | 0.200 | toilet | 0.656 | tv | 0.663 | | laptop | 0.676 | mouse | 0.642 | remote | 0.380 | | keyboard | 0.560 | cell phone | 0.424 | microwave | 0.691 | | oven | 0.376 | toaster | 0.486 | sink | 0.404 | | refrigerator | 0.670 | book | 0.161 | clock | 0.545 | | vase | 0.431 | scissors | 0.302 | teddy bear | 0.528 | | hair drier | 0.129 | toothbrush | 0.247 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 02:11:00,744 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_s_fpn_1x_coco/best_bbox_mAP_epoch_10.pth was removed 2023-11-14 02:11:02,778 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_12.pth. 2023-11-14 02:11:02,779 - mmdet - INFO - Best bbox_mAP is 0.4923 at 12 epoch. 2023-11-14 02:11:02,779 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_s_fpn_1x_coco.py 2023-11-14 02:11:02,779 - mmdet - INFO - Epoch(val) [12][625] bbox_mAP: 0.4923, bbox_mAP_50: 0.7072, bbox_mAP_75: 0.5391, bbox_mAP_s: 0.3282, bbox_mAP_m: 0.5313, bbox_mAP_l: 0.6475, bbox_mAP_copypaste: 0.4923 0.7072 0.5391 0.3282 0.5313 0.6475, segm_mAP: 0.4397, segm_mAP_50: 0.6781, segm_mAP_75: 0.4761, segm_mAP_s: 0.2456, segm_mAP_m: 0.4698, segm_mAP_l: 0.6329, segm_mAP_copypaste: 0.4397 0.6781 0.4761 0.2456 0.4698 0.6329