2023-11-13 16:22:50,879 - 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 16:22:51,656 - mmdet - INFO - Distributed training: True 2023-11-13 16:22:52,316 - mmdet - INFO - Config: model = dict( type='MaskRCNN', backbone=dict( type='Flash_InternImage_nsmx', core_op='FlashDCNv3', channels=112, depths=[4, 4, 21, 4], groups=[7, 14, 28, 56], mlp_ratio=4.0, drop_path_rate=0.3, norm_layer='LN', layer_scale=1.0, offset_scale=0.5, 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_b_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth' )), neck=dict( type='FPN_vitdet', in_channels=[112, 224, 448, 896], 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_b_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth' norm_cfg = dict(type='LN', requires_grad=True) work_dir = './work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco' auto_resume = False gpu_ids = range(0, 8) 2023-11-13 16:22:56,829 - mmdet - INFO - Set random seed to 726810153, deterministic: False 2023-11-13 16:22:56,830 - mmdet - INFO - using core type: FlashDCNv3 2023-11-13 16:22:56,830 - mmdet - INFO - using activation layer: GELU 2023-11-13 16:22:56,830 - mmdet - INFO - using main norm layer: LN 2023-11-13 16:22:56,831 - mmdet - INFO - using dpr: linear, 0.3 2023-11-13 16:22:56,831 - mmdet - INFO - level2_post_norm: False 2023-11-13 16:22:56,831 - mmdet - INFO - level2_post_norm_block_ids: None 2023-11-13 16:22:56,831 - mmdet - INFO - res_post_norm: False 2023-11-13 16:22:58,625 - mmdet - INFO - load checkpoint from local path: /mnt/petrelfs/share_data/xiongyuwen/checkpoint/flash_internimage_b_1k_224_nosmx_dw/ckpt_epoch_ema_best.pth 2023-11-13 16:23:01,454 - 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 16:23:01,492 - mmdet - INFO - initialize FPN_vitdet with init_cfg {'type': 'Xavier', 'layer': 'Conv2d', 'distribution': 'uniform'} 2023-11-13 16:23:01,509 - mmdet - INFO - initialize RPNHead with init_cfg {'type': 'Normal', 'layer': 'Conv2d', 'std': 0.01} 2023-11-13 16:23:01,512 - 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([56, 3, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv1.bias - torch.Size([56]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.weight - torch.Size([56]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm1.1.bias - torch.Size([56]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.weight - torch.Size([112, 56, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.conv2.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.patch_embed.norm2.1.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.gamma1 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.gamma2 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm1.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm1.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask_dw.weight - torch.Size([112, 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([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.weight - torch.Size([189, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.offset_mask.bias - torch.Size([189]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.value_proj.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.dcn.output_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.norm2.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.weight - torch.Size([448, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc1.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.0.mlp.fc2.weight - torch.Size([112, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.gamma1 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.gamma2 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm1.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm1.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask_dw.weight - torch.Size([112, 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([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.weight - torch.Size([189, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.offset_mask.bias - torch.Size([189]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.value_proj.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.dcn.output_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.norm2.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.weight - torch.Size([448, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc1.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.1.mlp.fc2.weight - torch.Size([112, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.gamma1 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.gamma2 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm1.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm1.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask_dw.weight - torch.Size([112, 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([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.weight - torch.Size([189, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.offset_mask.bias - torch.Size([189]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.value_proj.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.dcn.output_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.norm2.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.weight - torch.Size([448, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc1.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.2.mlp.fc2.weight - torch.Size([112, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.gamma1 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.gamma2 - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm1.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm1.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask_dw.weight - torch.Size([112, 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([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.weight - torch.Size([189, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.offset_mask.bias - torch.Size([189]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.value_proj.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.dcn.output_proj.weight - torch.Size([112, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.weight - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.norm2.0.bias - torch.Size([112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.weight - torch.Size([448, 112]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc1.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.blocks.3.mlp.fc2.weight - torch.Size([112, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.conv.weight - torch.Size([224, 112, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.0.downsample.norm.1.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.gamma1 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.gamma2 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm1.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm1.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask_dw.weight - torch.Size([224, 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([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.weight - torch.Size([378, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.offset_mask.bias - torch.Size([378]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.value_proj.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.dcn.output_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.norm2.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.weight - torch.Size([896, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc1.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.0.mlp.fc2.weight - torch.Size([224, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.gamma1 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.gamma2 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm1.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm1.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask_dw.weight - torch.Size([224, 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([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.weight - torch.Size([378, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.offset_mask.bias - torch.Size([378]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.value_proj.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.dcn.output_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.norm2.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.weight - torch.Size([896, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc1.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.1.mlp.fc2.weight - torch.Size([224, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.gamma1 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.gamma2 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm1.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm1.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask_dw.weight - torch.Size([224, 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([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.weight - torch.Size([378, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.offset_mask.bias - torch.Size([378]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.value_proj.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.dcn.output_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.norm2.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.weight - torch.Size([896, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc1.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.2.mlp.fc2.weight - torch.Size([224, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.gamma1 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.gamma2 - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm1.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm1.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask_dw.weight - torch.Size([224, 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([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.weight - torch.Size([378, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.offset_mask.bias - torch.Size([378]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.value_proj.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.dcn.output_proj.weight - torch.Size([224, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.weight - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.norm2.0.bias - torch.Size([224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.weight - torch.Size([896, 224]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc1.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.blocks.3.mlp.fc2.weight - torch.Size([224, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.conv.weight - torch.Size([448, 224, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.1.downsample.norm.1.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.0.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.1.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.2.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.3.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.4.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.5.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.6.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.7.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.8.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.9.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.10.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.11.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.12.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.13.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.14.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.15.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.16.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.17.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.18.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.19.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.gamma1 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.gamma2 - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm1.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm1.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask_dw.weight - torch.Size([448, 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([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask.weight - torch.Size([756, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.offset_mask.bias - torch.Size([756]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.value_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.value_proj.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.dcn.output_proj.weight - torch.Size([448, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm2.0.weight - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.norm2.0.bias - torch.Size([448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc1.weight - torch.Size([1792, 448]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc1.bias - torch.Size([1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.blocks.20.mlp.fc2.weight - torch.Size([448, 1792]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.conv.weight - torch.Size([896, 448, 3, 3]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.2.downsample.norm.1.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.gamma1 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.gamma2 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm1.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm1.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask_dw.weight - torch.Size([896, 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([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.weight - torch.Size([1512, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.offset_mask.bias - torch.Size([1512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.value_proj.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.dcn.output_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.norm2.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.weight - torch.Size([3584, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc1.bias - torch.Size([3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.0.mlp.fc2.weight - torch.Size([896, 3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.gamma1 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.gamma2 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm1.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm1.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask_dw.weight - torch.Size([896, 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([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.weight - torch.Size([1512, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.offset_mask.bias - torch.Size([1512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.value_proj.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.dcn.output_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.norm2.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.weight - torch.Size([3584, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc1.bias - torch.Size([3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.1.mlp.fc2.weight - torch.Size([896, 3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.gamma1 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.gamma2 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm1.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm1.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask_dw.weight - torch.Size([896, 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([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.weight - torch.Size([1512, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.offset_mask.bias - torch.Size([1512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.value_proj.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.dcn.output_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.norm2.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.weight - torch.Size([3584, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc1.bias - torch.Size([3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.2.mlp.fc2.weight - torch.Size([896, 3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.gamma1 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.gamma2 - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm1.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm1.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask_dw.weight - torch.Size([896, 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([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.weight - torch.Size([1512, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.offset_mask.bias - torch.Size([1512]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.value_proj.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.dcn.output_proj.weight - torch.Size([896, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.weight - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.norm2.0.bias - torch.Size([896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.weight - torch.Size([3584, 896]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc1.bias - torch.Size([3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx backbone.levels.3.blocks.3.mlp.fc2.weight - torch.Size([896, 3584]): Initialized by user-defined `init_weights` in Flash_InternImage_nsmx neck.lateral_convs.0.conv.weight - torch.Size([256, 112, 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, 224, 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, 448, 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, 896, 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 16:23:19,269 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled. 2023-11-13 16:23:19,269 - mmdet - INFO - {'num_layers': 33, 'layer_decay_rate': 1.0, 'depths': [4, 4, 21, 4]} 2023-11-13 16:23:19,269 - mmdet - INFO - Build CustomLayerDecayOptimizerConstructor 1.000000 - 35 2023-11-13 16:23:19,273 - 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", 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"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": [ 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"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 16:23:19,861 - mmdet - INFO - Start running, host: lizhiqi@SH-IDC1-10-140-37-151, work_dir: /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco 2023-11-13 16:23:19,861 - 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 16:23:19,862 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs 2023-11-13 16:23:19,862 - mmdet - INFO - Checkpoints will be saved to /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco by HardDiskBackend. 2023-11-13 16:23:49,128 - mmdet - INFO - Epoch [1][50/7330] lr: 9.890e-06, eta: 14:17:11, time: 0.585, data_time: 0.093, memory: 5019, loss_rpn_cls: 0.6719, loss_rpn_bbox: 0.1110, loss_cls: 3.4393, acc: 59.9302, loss_bbox: 0.0216, loss_mask: 0.7884, loss: 5.0321 2023-11-13 16:24:11,417 - mmdet - INFO - Epoch [1][100/7330] lr: 1.988e-05, eta: 12:34:39, time: 0.446, data_time: 0.025, memory: 5299, loss_rpn_cls: 0.4951, loss_rpn_bbox: 0.1056, loss_cls: 0.6136, acc: 94.9905, loss_bbox: 0.1614, loss_mask: 0.7124, loss: 2.0882 2023-11-13 16:24:33,623 - mmdet - INFO - Epoch [1][150/7330] lr: 2.987e-05, eta: 11:59:32, time: 0.444, data_time: 0.025, memory: 5467, loss_rpn_cls: 0.2757, loss_rpn_bbox: 0.0954, loss_cls: 0.4436, acc: 93.6079, loss_bbox: 0.2243, loss_mask: 0.6905, loss: 1.7295 2023-11-13 16:24:55,874 - mmdet - INFO - Epoch [1][200/7330] lr: 3.986e-05, eta: 11:42:02, time: 0.445, data_time: 0.028, memory: 5548, loss_rpn_cls: 0.2056, loss_rpn_bbox: 0.0982, loss_cls: 0.4672, acc: 92.6521, loss_bbox: 0.2616, loss_mask: 0.6622, loss: 1.6947 2023-11-13 16:25:18,158 - mmdet - INFO - Epoch [1][250/7330] lr: 4.985e-05, eta: 11:31:37, time: 0.446, data_time: 0.023, memory: 5576, loss_rpn_cls: 0.1472, loss_rpn_bbox: 0.0902, loss_cls: 0.4847, acc: 91.6523, loss_bbox: 0.3053, loss_mask: 0.6215, loss: 1.6488 2023-11-13 16:25:40,274 - mmdet - INFO - Epoch [1][300/7330] lr: 5.984e-05, eta: 11:23:42, time: 0.442, data_time: 0.032, memory: 5576, loss_rpn_cls: 0.1046, loss_rpn_bbox: 0.0886, loss_cls: 0.4753, acc: 91.2432, loss_bbox: 0.3307, loss_mask: 0.5779, loss: 1.5772 2023-11-13 16:26:02,378 - mmdet - INFO - Epoch [1][350/7330] lr: 6.983e-05, eta: 11:17:55, time: 0.442, data_time: 0.023, memory: 5625, loss_rpn_cls: 0.0902, loss_rpn_bbox: 0.0860, loss_cls: 0.4922, acc: 90.6848, loss_bbox: 0.3513, loss_mask: 0.5476, loss: 1.5674 2023-11-13 16:26:24,364 - mmdet - INFO - Epoch [1][400/7330] lr: 7.982e-05, eta: 11:13:03, time: 0.440, data_time: 0.027, memory: 5681, loss_rpn_cls: 0.0838, loss_rpn_bbox: 0.0859, loss_cls: 0.4515, acc: 90.5410, loss_bbox: 0.3568, loss_mask: 0.5013, loss: 1.4793 2023-11-13 16:26:46,356 - mmdet - INFO - Epoch [1][450/7330] lr: 8.981e-05, eta: 11:09:12, time: 0.440, data_time: 0.034, memory: 5681, loss_rpn_cls: 0.0794, loss_rpn_bbox: 0.0807, loss_cls: 0.4497, acc: 89.8914, loss_bbox: 0.3741, loss_mask: 0.4683, loss: 1.4522 2023-11-13 16:27:08,135 - mmdet - INFO - Epoch [1][500/7330] lr: 9.980e-05, eta: 11:05:26, time: 0.436, data_time: 0.029, memory: 5681, loss_rpn_cls: 0.0774, loss_rpn_bbox: 0.0807, loss_cls: 0.4307, acc: 89.8345, loss_bbox: 0.3702, loss_mask: 0.4437, loss: 1.4027 2023-11-13 16:27:30,604 - mmdet - INFO - Epoch [1][550/7330] lr: 1.000e-04, eta: 11:04:05, time: 0.449, data_time: 0.031, memory: 5686, loss_rpn_cls: 0.0733, loss_rpn_bbox: 0.0799, loss_cls: 0.4231, acc: 89.2791, loss_bbox: 0.3876, loss_mask: 0.4176, loss: 1.3815 2023-11-13 16:27:53,014 - mmdet - INFO - Epoch [1][600/7330] lr: 1.000e-04, eta: 11:02:48, time: 0.448, data_time: 0.023, memory: 5686, loss_rpn_cls: 0.0692, loss_rpn_bbox: 0.0822, loss_cls: 0.3997, acc: 89.1858, loss_bbox: 0.3870, loss_mask: 0.4075, loss: 1.3457 2023-11-13 16:28:15,094 - mmdet - INFO - Epoch [1][650/7330] lr: 1.000e-04, eta: 11:00:53, time: 0.442, data_time: 0.026, memory: 5686, loss_rpn_cls: 0.0653, loss_rpn_bbox: 0.0762, loss_cls: 0.3660, acc: 89.6746, loss_bbox: 0.3789, loss_mask: 0.4038, loss: 1.2902 2023-11-13 16:28:37,011 - mmdet - INFO - Epoch [1][700/7330] lr: 1.000e-04, eta: 10:58:52, time: 0.438, data_time: 0.028, memory: 5686, loss_rpn_cls: 0.0595, loss_rpn_bbox: 0.0723, loss_cls: 0.3700, acc: 89.3958, loss_bbox: 0.3786, loss_mask: 0.3888, loss: 1.2692 2023-11-13 16:28:59,028 - mmdet - INFO - Epoch [1][750/7330] lr: 1.000e-04, eta: 10:57:15, time: 0.440, data_time: 0.026, memory: 5686, loss_rpn_cls: 0.0594, loss_rpn_bbox: 0.0763, loss_cls: 0.3398, acc: 89.6470, loss_bbox: 0.3707, loss_mask: 0.3828, loss: 1.2290 2023-11-13 16:29:21,080 - mmdet - INFO - Epoch [1][800/7330] lr: 1.000e-04, eta: 10:55:52, time: 0.441, data_time: 0.027, memory: 5688, loss_rpn_cls: 0.0584, loss_rpn_bbox: 0.0756, loss_cls: 0.3342, acc: 89.8130, loss_bbox: 0.3637, loss_mask: 0.3739, loss: 1.2059 2023-11-13 16:29:43,690 - mmdet - INFO - Epoch [1][850/7330] lr: 1.000e-04, eta: 10:55:33, time: 0.452, data_time: 0.030, memory: 5690, loss_rpn_cls: 0.0607, loss_rpn_bbox: 0.0766, loss_cls: 0.3360, acc: 89.7017, loss_bbox: 0.3647, loss_mask: 0.3672, loss: 1.2052 2023-11-13 16:30:05,654 - mmdet - INFO - Epoch [1][900/7330] lr: 1.000e-04, eta: 10:54:11, time: 0.439, data_time: 0.026, memory: 5713, loss_rpn_cls: 0.0597, loss_rpn_bbox: 0.0737, loss_cls: 0.3280, acc: 89.9490, loss_bbox: 0.3613, loss_mask: 0.3580, loss: 1.1807 2023-11-13 16:30:28,038 - mmdet - INFO - Epoch [1][950/7330] lr: 1.000e-04, eta: 10:53:34, time: 0.448, data_time: 0.031, memory: 5713, loss_rpn_cls: 0.0525, loss_rpn_bbox: 0.0717, loss_cls: 0.3168, acc: 90.1533, loss_bbox: 0.3524, loss_mask: 0.3532, loss: 1.1466 2023-11-13 16:30:49,709 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 16:30:49,710 - mmdet - INFO - Epoch [1][1000/7330] lr: 1.000e-04, eta: 10:51:56, time: 0.433, data_time: 0.029, memory: 5713, loss_rpn_cls: 0.0536, loss_rpn_bbox: 0.0706, loss_cls: 0.3101, acc: 90.2485, loss_bbox: 0.3414, loss_mask: 0.3549, loss: 1.1306 2023-11-13 16:31:11,636 - mmdet - INFO - Epoch [1][1050/7330] lr: 1.000e-04, eta: 10:50:47, time: 0.439, data_time: 0.025, memory: 5713, loss_rpn_cls: 0.0561, loss_rpn_bbox: 0.0703, loss_cls: 0.3107, acc: 90.2300, loss_bbox: 0.3458, loss_mask: 0.3431, loss: 1.1259 2023-11-13 16:31:33,645 - mmdet - INFO - Epoch [1][1100/7330] lr: 1.000e-04, eta: 10:49:48, time: 0.440, data_time: 0.023, memory: 5713, loss_rpn_cls: 0.0562, loss_rpn_bbox: 0.0736, loss_cls: 0.3130, acc: 90.0210, loss_bbox: 0.3518, loss_mask: 0.3397, loss: 1.1343 2023-11-13 16:31:55,764 - mmdet - INFO - Epoch [1][1150/7330] lr: 1.000e-04, eta: 10:49:02, time: 0.442, data_time: 0.025, memory: 5713, loss_rpn_cls: 0.0584, loss_rpn_bbox: 0.0709, loss_cls: 0.3014, acc: 90.2463, loss_bbox: 0.3417, loss_mask: 0.3390, loss: 1.1114 2023-11-13 16:32:17,930 - mmdet - INFO - Epoch [1][1200/7330] lr: 1.000e-04, eta: 10:48:20, time: 0.443, data_time: 0.027, memory: 5714, loss_rpn_cls: 0.0578, loss_rpn_bbox: 0.0727, loss_cls: 0.3169, acc: 89.8738, loss_bbox: 0.3499, loss_mask: 0.3378, loss: 1.1350 2023-11-13 16:32:40,228 - mmdet - INFO - Epoch [1][1250/7330] lr: 1.000e-04, eta: 10:47:49, time: 0.446, data_time: 0.029, memory: 5714, loss_rpn_cls: 0.0492, loss_rpn_bbox: 0.0718, loss_cls: 0.3023, acc: 90.0471, loss_bbox: 0.3430, loss_mask: 0.3344, loss: 1.1007 2023-11-13 16:33:02,793 - mmdet - INFO - Epoch [1][1300/7330] lr: 1.000e-04, eta: 10:47:37, time: 0.451, data_time: 0.027, memory: 5718, loss_rpn_cls: 0.0495, loss_rpn_bbox: 0.0690, loss_cls: 0.2957, acc: 90.2808, loss_bbox: 0.3373, loss_mask: 0.3281, loss: 1.0796 2023-11-13 16:33:24,656 - mmdet - INFO - Epoch [1][1350/7330] lr: 1.000e-04, eta: 10:46:39, time: 0.437, data_time: 0.025, memory: 5718, loss_rpn_cls: 0.0581, loss_rpn_bbox: 0.0700, loss_cls: 0.2901, acc: 90.5664, loss_bbox: 0.3305, loss_mask: 0.3278, loss: 1.0764 2023-11-13 16:33:46,704 - mmdet - INFO - Epoch [1][1400/7330] lr: 1.000e-04, eta: 10:45:55, time: 0.441, data_time: 0.031, memory: 5718, loss_rpn_cls: 0.0497, loss_rpn_bbox: 0.0677, loss_cls: 0.2873, acc: 90.5083, loss_bbox: 0.3365, loss_mask: 0.3244, loss: 1.0656 2023-11-13 16:34:08,868 - mmdet - INFO - Epoch [1][1450/7330] lr: 1.000e-04, eta: 10:45:19, time: 0.443, data_time: 0.025, memory: 5730, loss_rpn_cls: 0.0541, loss_rpn_bbox: 0.0678, loss_cls: 0.2958, acc: 90.2666, loss_bbox: 0.3388, loss_mask: 0.3197, loss: 1.0762 2023-11-13 16:34:31,047 - mmdet - INFO - Epoch [1][1500/7330] lr: 1.000e-04, eta: 10:44:45, time: 0.444, data_time: 0.023, memory: 5730, loss_rpn_cls: 0.0517, loss_rpn_bbox: 0.0669, loss_cls: 0.2824, acc: 90.7036, loss_bbox: 0.3245, loss_mask: 0.3206, loss: 1.0461 2023-11-13 16:34:53,244 - mmdet - INFO - Epoch [1][1550/7330] lr: 1.000e-04, eta: 10:44:13, time: 0.444, data_time: 0.024, memory: 5730, loss_rpn_cls: 0.0501, loss_rpn_bbox: 0.0688, loss_cls: 0.2843, acc: 90.5168, loss_bbox: 0.3296, loss_mask: 0.3186, loss: 1.0514 2023-11-13 16:35:15,522 - mmdet - INFO - Epoch [1][1600/7330] lr: 1.000e-04, eta: 10:43:46, time: 0.446, data_time: 0.022, memory: 5730, loss_rpn_cls: 0.0472, loss_rpn_bbox: 0.0659, loss_cls: 0.2781, acc: 90.7253, loss_bbox: 0.3202, loss_mask: 0.3186, loss: 1.0299 2023-11-13 16:35:37,812 - mmdet - INFO - Epoch [1][1650/7330] lr: 1.000e-04, eta: 10:43:20, time: 0.446, data_time: 0.022, memory: 5730, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0644, loss_cls: 0.2889, acc: 90.4790, loss_bbox: 0.3234, loss_mask: 0.3179, loss: 1.0392 2023-11-13 16:36:00,278 - mmdet - INFO - Epoch [1][1700/7330] lr: 1.000e-04, eta: 10:43:02, time: 0.449, data_time: 0.021, memory: 5730, loss_rpn_cls: 0.0484, loss_rpn_bbox: 0.0685, loss_cls: 0.2858, acc: 90.5903, loss_bbox: 0.3302, loss_mask: 0.3201, loss: 1.0530 2023-11-13 16:36:22,400 - mmdet - INFO - Epoch [1][1750/7330] lr: 1.000e-04, eta: 10:42:28, time: 0.443, data_time: 0.023, memory: 5730, loss_rpn_cls: 0.0489, loss_rpn_bbox: 0.0635, loss_cls: 0.2739, acc: 90.8718, loss_bbox: 0.3156, loss_mask: 0.3122, loss: 1.0141 2023-11-13 16:36:44,112 - mmdet - INFO - Epoch [1][1800/7330] lr: 1.000e-04, eta: 10:41:35, time: 0.434, data_time: 0.023, memory: 5730, loss_rpn_cls: 0.0441, loss_rpn_bbox: 0.0632, loss_cls: 0.2731, acc: 90.9241, loss_bbox: 0.3138, loss_mask: 0.3001, loss: 0.9944 2023-11-13 16:37:05,859 - mmdet - INFO - Epoch [1][1850/7330] lr: 1.000e-04, eta: 10:40:45, time: 0.435, data_time: 0.023, memory: 5730, loss_rpn_cls: 0.0503, loss_rpn_bbox: 0.0672, loss_cls: 0.2786, acc: 90.7219, loss_bbox: 0.3217, loss_mask: 0.3048, loss: 1.0227 2023-11-13 16:37:28,066 - mmdet - INFO - Epoch [1][1900/7330] lr: 1.000e-04, eta: 10:40:17, time: 0.444, data_time: 0.025, memory: 5730, loss_rpn_cls: 0.0466, loss_rpn_bbox: 0.0650, loss_cls: 0.2830, acc: 90.6526, loss_bbox: 0.3235, loss_mask: 0.3161, loss: 1.0342 2023-11-13 16:37:49,854 - mmdet - INFO - Epoch [1][1950/7330] lr: 1.000e-04, eta: 10:39:32, time: 0.436, data_time: 0.023, memory: 5730, loss_rpn_cls: 0.0446, loss_rpn_bbox: 0.0614, loss_cls: 0.2739, acc: 90.9553, loss_bbox: 0.3112, loss_mask: 0.3031, loss: 0.9941 2023-11-13 16:38:12,119 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 16:38:12,119 - mmdet - INFO - Epoch [1][2000/7330] lr: 1.000e-04, eta: 10:39:07, time: 0.445, data_time: 0.021, memory: 5730, loss_rpn_cls: 0.0476, loss_rpn_bbox: 0.0678, loss_cls: 0.2698, acc: 91.0154, loss_bbox: 0.3152, loss_mask: 0.3079, loss: 1.0082 2023-11-13 16:38:34,180 - mmdet - INFO - Epoch [1][2050/7330] lr: 1.000e-04, eta: 10:38:35, time: 0.441, data_time: 0.021, memory: 5730, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0661, loss_cls: 0.2762, acc: 90.8350, loss_bbox: 0.3161, loss_mask: 0.3034, loss: 1.0104 2023-11-13 16:38:56,035 - mmdet - INFO - Epoch [1][2100/7330] lr: 1.000e-04, eta: 10:37:54, time: 0.437, data_time: 0.024, memory: 5730, loss_rpn_cls: 0.0460, loss_rpn_bbox: 0.0613, loss_cls: 0.2732, acc: 91.0542, loss_bbox: 0.3123, loss_mask: 0.3032, loss: 0.9960 2023-11-13 16:39:18,086 - mmdet - INFO - Epoch [1][2150/7330] lr: 1.000e-04, eta: 10:37:22, time: 0.441, data_time: 0.022, memory: 5730, loss_rpn_cls: 0.0465, loss_rpn_bbox: 0.0623, loss_cls: 0.2699, acc: 90.8506, loss_bbox: 0.3177, loss_mask: 0.2996, loss: 0.9960 2023-11-13 16:39:39,897 - mmdet - INFO - Epoch [1][2200/7330] lr: 1.000e-04, eta: 10:36:42, time: 0.436, data_time: 0.030, memory: 5730, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0632, loss_cls: 0.2759, acc: 90.8079, loss_bbox: 0.3196, loss_mask: 0.3021, loss: 1.0051 2023-11-13 16:40:01,793 - mmdet - INFO - Epoch [1][2250/7330] lr: 1.000e-04, eta: 10:36:05, time: 0.438, data_time: 0.026, memory: 5730, loss_rpn_cls: 0.0442, loss_rpn_bbox: 0.0604, loss_cls: 0.2652, acc: 91.0500, loss_bbox: 0.3140, loss_mask: 0.2980, loss: 0.9819 2023-11-13 16:40:23,685 - mmdet - INFO - Epoch [1][2300/7330] lr: 1.000e-04, eta: 10:35:29, time: 0.438, data_time: 0.027, memory: 5730, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0585, loss_cls: 0.2633, acc: 91.0999, loss_bbox: 0.3097, loss_mask: 0.2953, loss: 0.9712 2023-11-13 16:40:45,950 - mmdet - INFO - Epoch [1][2350/7330] lr: 1.000e-04, eta: 10:35:07, time: 0.445, data_time: 0.026, memory: 5730, loss_rpn_cls: 0.0473, loss_rpn_bbox: 0.0619, loss_cls: 0.2719, acc: 90.7231, loss_bbox: 0.3178, loss_mask: 0.2986, loss: 0.9974 2023-11-13 16:41:09,067 - mmdet - INFO - Epoch [1][2400/7330] lr: 1.000e-04, eta: 10:35:16, time: 0.462, data_time: 0.022, memory: 5730, loss_rpn_cls: 0.0458, loss_rpn_bbox: 0.0622, loss_cls: 0.2647, acc: 90.9983, loss_bbox: 0.3121, loss_mask: 0.3017, loss: 0.9864 2023-11-13 16:41:30,670 - mmdet - INFO - Epoch [1][2450/7330] lr: 1.000e-04, eta: 10:34:30, time: 0.432, data_time: 0.025, memory: 5730, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0598, loss_cls: 0.2633, acc: 91.0137, loss_bbox: 0.3115, loss_mask: 0.2945, loss: 0.9734 2023-11-13 16:41:52,518 - mmdet - INFO - Epoch [1][2500/7330] lr: 1.000e-04, eta: 10:33:53, time: 0.437, data_time: 0.025, memory: 5730, loss_rpn_cls: 0.0473, loss_rpn_bbox: 0.0651, loss_cls: 0.2702, acc: 90.8967, loss_bbox: 0.3150, loss_mask: 0.2974, loss: 0.9950 2023-11-13 16:42:14,397 - mmdet - INFO - Epoch [1][2550/7330] lr: 1.000e-04, eta: 10:33:19, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0411, loss_rpn_bbox: 0.0606, loss_cls: 0.2639, acc: 91.1541, loss_bbox: 0.3068, loss_mask: 0.2954, loss: 0.9678 2023-11-13 16:42:36,488 - mmdet - INFO - Epoch [1][2600/7330] lr: 1.000e-04, eta: 10:32:51, time: 0.442, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0460, loss_rpn_bbox: 0.0628, loss_cls: 0.2647, acc: 91.0593, loss_bbox: 0.3107, loss_mask: 0.2955, loss: 0.9796 2023-11-13 16:42:58,634 - mmdet - INFO - Epoch [1][2650/7330] lr: 1.000e-04, eta: 10:32:26, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0602, loss_cls: 0.2665, acc: 90.9888, loss_bbox: 0.3088, loss_mask: 0.2963, loss: 0.9747 2023-11-13 16:43:20,683 - mmdet - INFO - Epoch [1][2700/7330] lr: 1.000e-04, eta: 10:31:58, time: 0.441, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0452, loss_rpn_bbox: 0.0625, loss_cls: 0.2613, acc: 91.3037, loss_bbox: 0.3017, loss_mask: 0.2898, loss: 0.9604 2023-11-13 16:43:43,099 - mmdet - INFO - Epoch [1][2750/7330] lr: 1.000e-04, eta: 10:31:41, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0592, loss_cls: 0.2453, acc: 91.5620, loss_bbox: 0.2922, loss_mask: 0.2897, loss: 0.9268 2023-11-13 16:44:05,201 - mmdet - INFO - Epoch [1][2800/7330] lr: 1.000e-04, eta: 10:31:14, time: 0.442, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0610, loss_cls: 0.2645, acc: 91.0281, loss_bbox: 0.3148, loss_mask: 0.2916, loss: 0.9763 2023-11-13 16:44:27,124 - mmdet - INFO - Epoch [1][2850/7330] lr: 1.000e-04, eta: 10:30:43, time: 0.438, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0472, loss_rpn_bbox: 0.0609, loss_cls: 0.2668, acc: 91.1672, loss_bbox: 0.3006, loss_mask: 0.2942, loss: 0.9697 2023-11-13 16:44:48,783 - mmdet - INFO - Epoch [1][2900/7330] lr: 1.000e-04, eta: 10:30:04, time: 0.433, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0428, loss_rpn_bbox: 0.0606, loss_cls: 0.2596, acc: 91.2107, loss_bbox: 0.3007, loss_mask: 0.2916, loss: 0.9552 2023-11-13 16:45:11,536 - mmdet - INFO - Epoch [1][2950/7330] lr: 1.000e-04, eta: 10:29:57, time: 0.455, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0450, loss_rpn_bbox: 0.0624, loss_cls: 0.2611, acc: 91.0872, loss_bbox: 0.3100, loss_mask: 0.2880, loss: 0.9664 2023-11-13 16:45:33,573 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 16:45:33,573 - mmdet - INFO - Epoch [1][3000/7330] lr: 1.000e-04, eta: 10:29:29, time: 0.441, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0555, loss_cls: 0.2494, acc: 91.5891, loss_bbox: 0.2929, loss_mask: 0.2797, loss: 0.9156 2023-11-13 16:45:55,590 - mmdet - INFO - Epoch [1][3050/7330] lr: 1.000e-04, eta: 10:29:01, time: 0.440, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0388, loss_rpn_bbox: 0.0564, loss_cls: 0.2523, acc: 91.4480, loss_bbox: 0.2883, loss_mask: 0.2862, loss: 0.9220 2023-11-13 16:46:17,396 - mmdet - INFO - Epoch [1][3100/7330] lr: 1.000e-04, eta: 10:28:27, time: 0.436, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0406, loss_rpn_bbox: 0.0597, loss_cls: 0.2597, acc: 91.2644, loss_bbox: 0.2966, loss_mask: 0.2912, loss: 0.9479 2023-11-13 16:46:39,134 - mmdet - INFO - Epoch [1][3150/7330] lr: 1.000e-04, eta: 10:27:52, time: 0.435, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0575, loss_cls: 0.2535, acc: 91.4673, loss_bbox: 0.2948, loss_mask: 0.2828, loss: 0.9299 2023-11-13 16:47:01,040 - mmdet - INFO - Epoch [1][3200/7330] lr: 1.000e-04, eta: 10:27:22, time: 0.438, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0620, loss_cls: 0.2599, acc: 91.0972, loss_bbox: 0.3024, loss_mask: 0.2842, loss: 0.9520 2023-11-13 16:47:23,212 - mmdet - INFO - Epoch [1][3250/7330] lr: 1.000e-04, eta: 10:26:59, time: 0.443, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0434, loss_rpn_bbox: 0.0580, loss_cls: 0.2556, acc: 91.4102, loss_bbox: 0.2924, loss_mask: 0.2859, loss: 0.9353 2023-11-13 16:47:45,042 - mmdet - INFO - Epoch [1][3300/7330] lr: 1.000e-04, eta: 10:26:27, time: 0.437, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0410, loss_rpn_bbox: 0.0585, loss_cls: 0.2465, acc: 91.5085, loss_bbox: 0.2949, loss_mask: 0.2844, loss: 0.9252 2023-11-13 16:48:06,427 - mmdet - INFO - Epoch [1][3350/7330] lr: 1.000e-04, eta: 10:25:44, time: 0.428, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0446, loss_rpn_bbox: 0.0610, loss_cls: 0.2505, acc: 91.5217, loss_bbox: 0.2898, loss_mask: 0.2872, loss: 0.9332 2023-11-13 16:48:28,280 - mmdet - INFO - Epoch [1][3400/7330] lr: 1.000e-04, eta: 10:25:14, time: 0.437, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0427, loss_rpn_bbox: 0.0575, loss_cls: 0.2558, acc: 91.2407, loss_bbox: 0.2996, loss_mask: 0.2812, loss: 0.9368 2023-11-13 16:48:50,491 - mmdet - INFO - Epoch [1][3450/7330] lr: 1.000e-04, eta: 10:24:52, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0575, loss_cls: 0.2520, acc: 91.4648, loss_bbox: 0.2975, loss_mask: 0.2755, loss: 0.9238 2023-11-13 16:49:12,477 - mmdet - INFO - Epoch [1][3500/7330] lr: 1.000e-04, eta: 10:24:25, time: 0.440, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0554, loss_cls: 0.2468, acc: 91.4697, loss_bbox: 0.2916, loss_mask: 0.2795, loss: 0.9135 2023-11-13 16:49:34,963 - mmdet - INFO - Epoch [1][3550/7330] lr: 1.000e-04, eta: 10:24:10, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0584, loss_cls: 0.2528, acc: 91.3240, loss_bbox: 0.3013, loss_mask: 0.2836, loss: 0.9382 2023-11-13 16:49:57,188 - mmdet - INFO - Epoch [1][3600/7330] lr: 1.000e-04, eta: 10:23:49, time: 0.445, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0440, loss_rpn_bbox: 0.0606, loss_cls: 0.2573, acc: 91.1475, loss_bbox: 0.3069, loss_mask: 0.2822, loss: 0.9510 2023-11-13 16:50:19,284 - mmdet - INFO - Epoch [1][3650/7330] lr: 1.000e-04, eta: 10:23:25, time: 0.442, data_time: 0.017, memory: 5731, loss_rpn_cls: 0.0394, loss_rpn_bbox: 0.0560, loss_cls: 0.2478, acc: 91.3057, loss_bbox: 0.3025, loss_mask: 0.2821, loss: 0.9278 2023-11-13 16:50:41,323 - mmdet - INFO - Epoch [1][3700/7330] lr: 1.000e-04, eta: 10:22:59, time: 0.441, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0413, loss_rpn_bbox: 0.0584, loss_cls: 0.2506, acc: 91.3896, loss_bbox: 0.2935, loss_mask: 0.2826, loss: 0.9263 2023-11-13 16:51:03,330 - mmdet - INFO - Epoch [1][3750/7330] lr: 1.000e-04, eta: 10:22:33, time: 0.440, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0583, loss_cls: 0.2542, acc: 91.2949, loss_bbox: 0.3015, loss_mask: 0.2817, loss: 0.9383 2023-11-13 16:51:25,358 - mmdet - INFO - Epoch [1][3800/7330] lr: 1.000e-04, eta: 10:22:08, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0529, loss_cls: 0.2454, acc: 91.6335, loss_bbox: 0.2904, loss_mask: 0.2744, loss: 0.9003 2023-11-13 16:51:47,390 - mmdet - INFO - Epoch [1][3850/7330] lr: 1.000e-04, eta: 10:21:42, time: 0.441, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0393, loss_rpn_bbox: 0.0546, loss_cls: 0.2435, acc: 91.6162, loss_bbox: 0.2869, loss_mask: 0.2800, loss: 0.9043 2023-11-13 16:52:09,408 - mmdet - INFO - Epoch [1][3900/7330] lr: 1.000e-04, eta: 10:21:17, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0390, loss_rpn_bbox: 0.0547, loss_cls: 0.2429, acc: 91.5100, loss_bbox: 0.2850, loss_mask: 0.2807, loss: 0.9023 2023-11-13 16:52:31,572 - mmdet - INFO - Epoch [1][3950/7330] lr: 1.000e-04, eta: 10:20:55, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0578, loss_cls: 0.2472, acc: 91.3523, loss_bbox: 0.2900, loss_mask: 0.2731, loss: 0.9086 2023-11-13 16:52:53,497 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 16:52:53,497 - mmdet - INFO - Epoch [1][4000/7330] lr: 1.000e-04, eta: 10:20:27, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0408, loss_rpn_bbox: 0.0555, loss_cls: 0.2432, acc: 91.5901, loss_bbox: 0.2833, loss_mask: 0.2721, loss: 0.8949 2023-11-13 16:53:16,179 - mmdet - INFO - Epoch [1][4050/7330] lr: 1.000e-04, eta: 10:20:16, time: 0.454, data_time: 0.036, memory: 5731, loss_rpn_cls: 0.0393, loss_rpn_bbox: 0.0586, loss_cls: 0.2440, acc: 91.4856, loss_bbox: 0.2923, loss_mask: 0.2730, loss: 0.9071 2023-11-13 16:53:37,988 - mmdet - INFO - Epoch [1][4100/7330] lr: 1.000e-04, eta: 10:19:46, time: 0.436, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0387, loss_rpn_bbox: 0.0529, loss_cls: 0.2456, acc: 91.7058, loss_bbox: 0.2824, loss_mask: 0.2795, loss: 0.8991 2023-11-13 16:54:00,070 - mmdet - INFO - Epoch [1][4150/7330] lr: 1.000e-04, eta: 10:19:22, time: 0.442, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0395, loss_rpn_bbox: 0.0558, loss_cls: 0.2425, acc: 91.5908, loss_bbox: 0.2863, loss_mask: 0.2811, loss: 0.9052 2023-11-13 16:54:22,068 - mmdet - INFO - Epoch [1][4200/7330] lr: 1.000e-04, eta: 10:18:56, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0426, loss_rpn_bbox: 0.0587, loss_cls: 0.2430, acc: 91.6506, loss_bbox: 0.2864, loss_mask: 0.2742, loss: 0.9049 2023-11-13 16:54:43,818 - mmdet - INFO - Epoch [1][4250/7330] lr: 1.000e-04, eta: 10:18:26, time: 0.435, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0382, loss_rpn_bbox: 0.0525, loss_cls: 0.2496, acc: 91.3643, loss_bbox: 0.2952, loss_mask: 0.2762, loss: 0.9116 2023-11-13 16:55:06,040 - mmdet - INFO - Epoch [1][4300/7330] lr: 1.000e-04, eta: 10:18:05, time: 0.444, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0413, loss_rpn_bbox: 0.0602, loss_cls: 0.2448, acc: 91.5752, loss_bbox: 0.2896, loss_mask: 0.2809, loss: 0.9168 2023-11-13 16:55:27,597 - mmdet - INFO - Epoch [1][4350/7330] lr: 1.000e-04, eta: 10:17:31, time: 0.431, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0544, loss_cls: 0.2340, acc: 92.0071, loss_bbox: 0.2772, loss_mask: 0.2706, loss: 0.8783 2023-11-13 16:55:49,678 - mmdet - INFO - Epoch [1][4400/7330] lr: 1.000e-04, eta: 10:17:07, time: 0.442, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0376, loss_rpn_bbox: 0.0551, loss_cls: 0.2401, acc: 91.9053, loss_bbox: 0.2782, loss_mask: 0.2718, loss: 0.8828 2023-11-13 16:56:11,774 - mmdet - INFO - Epoch [1][4450/7330] lr: 1.000e-04, eta: 10:16:44, time: 0.442, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0400, loss_rpn_bbox: 0.0558, loss_cls: 0.2502, acc: 91.4534, loss_bbox: 0.2894, loss_mask: 0.2792, loss: 0.9146 2023-11-13 16:56:34,107 - mmdet - INFO - Epoch [1][4500/7330] lr: 1.000e-04, eta: 10:16:25, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0403, loss_rpn_bbox: 0.0551, loss_cls: 0.2383, acc: 91.7969, loss_bbox: 0.2761, loss_mask: 0.2689, loss: 0.8788 2023-11-13 16:56:56,111 - mmdet - INFO - Epoch [1][4550/7330] lr: 1.000e-04, eta: 10:16:00, time: 0.440, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0533, loss_cls: 0.2385, acc: 91.7825, loss_bbox: 0.2836, loss_mask: 0.2758, loss: 0.8890 2023-11-13 16:57:18,180 - mmdet - INFO - Epoch [1][4600/7330] lr: 1.000e-04, eta: 10:15:36, time: 0.441, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0545, loss_cls: 0.2431, acc: 91.5278, loss_bbox: 0.2891, loss_mask: 0.2724, loss: 0.8964 2023-11-13 16:57:40,081 - mmdet - INFO - Epoch [1][4650/7330] lr: 1.000e-04, eta: 10:15:10, time: 0.438, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0578, loss_cls: 0.2455, acc: 91.4104, loss_bbox: 0.2952, loss_mask: 0.2760, loss: 0.9108 2023-11-13 16:58:01,922 - mmdet - INFO - Epoch [1][4700/7330] lr: 1.000e-04, eta: 10:14:42, time: 0.437, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0392, loss_rpn_bbox: 0.0548, loss_cls: 0.2439, acc: 91.5188, loss_bbox: 0.2844, loss_mask: 0.2720, loss: 0.8943 2023-11-13 16:58:24,023 - mmdet - INFO - Epoch [1][4750/7330] lr: 1.000e-04, eta: 10:14:19, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0405, loss_rpn_bbox: 0.0567, loss_cls: 0.2454, acc: 91.6477, loss_bbox: 0.2865, loss_mask: 0.2739, loss: 0.9030 2023-11-13 16:58:46,410 - mmdet - INFO - Epoch [1][4800/7330] lr: 1.000e-04, eta: 10:14:01, time: 0.448, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0541, loss_cls: 0.2459, acc: 91.5024, loss_bbox: 0.2910, loss_mask: 0.2706, loss: 0.8990 2023-11-13 16:59:08,072 - mmdet - INFO - Epoch [1][4850/7330] lr: 1.000e-04, eta: 10:13:31, time: 0.433, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0529, loss_cls: 0.2377, acc: 91.8916, loss_bbox: 0.2793, loss_mask: 0.2761, loss: 0.8814 2023-11-13 16:59:30,285 - mmdet - INFO - Epoch [1][4900/7330] lr: 1.000e-04, eta: 10:13:09, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0515, loss_cls: 0.2443, acc: 91.5393, loss_bbox: 0.2904, loss_mask: 0.2741, loss: 0.8970 2023-11-13 16:59:52,518 - mmdet - INFO - Epoch [1][4950/7330] lr: 1.000e-04, eta: 10:12:49, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0412, loss_rpn_bbox: 0.0562, loss_cls: 0.2497, acc: 91.4861, loss_bbox: 0.2869, loss_mask: 0.2772, loss: 0.9112 2023-11-13 17:00:14,278 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 17:00:14,278 - mmdet - INFO - Epoch [1][5000/7330] lr: 1.000e-04, eta: 10:12:20, time: 0.435, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0516, loss_cls: 0.2167, acc: 92.4695, loss_bbox: 0.2639, loss_mask: 0.2640, loss: 0.8325 2023-11-13 17:00:36,607 - mmdet - INFO - Epoch [1][5050/7330] lr: 1.000e-04, eta: 10:12:01, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0376, loss_rpn_bbox: 0.0562, loss_cls: 0.2523, acc: 91.2490, loss_bbox: 0.2964, loss_mask: 0.2783, loss: 0.9208 2023-11-13 17:00:58,777 - mmdet - INFO - Epoch [1][5100/7330] lr: 1.000e-04, eta: 10:11:39, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0375, loss_rpn_bbox: 0.0569, loss_cls: 0.2369, acc: 91.7026, loss_bbox: 0.2805, loss_mask: 0.2699, loss: 0.8817 2023-11-13 17:01:20,441 - mmdet - INFO - Epoch [1][5150/7330] lr: 1.000e-04, eta: 10:11:10, time: 0.433, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0513, loss_cls: 0.2331, acc: 91.9529, loss_bbox: 0.2734, loss_mask: 0.2650, loss: 0.8568 2023-11-13 17:01:41,872 - mmdet - INFO - Epoch [1][5200/7330] lr: 1.000e-04, eta: 10:10:36, time: 0.429, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0502, loss_cls: 0.2334, acc: 91.8555, loss_bbox: 0.2753, loss_mask: 0.2676, loss: 0.8594 2023-11-13 17:02:03,720 - mmdet - INFO - Epoch [1][5250/7330] lr: 1.000e-04, eta: 10:10:09, time: 0.437, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0373, loss_rpn_bbox: 0.0550, loss_cls: 0.2455, acc: 91.5757, loss_bbox: 0.2845, loss_mask: 0.2684, loss: 0.8906 2023-11-13 17:02:25,865 - mmdet - INFO - Epoch [1][5300/7330] lr: 1.000e-04, eta: 10:09:47, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0502, loss_cls: 0.2226, acc: 92.2407, loss_bbox: 0.2712, loss_mask: 0.2596, loss: 0.8380 2023-11-13 17:02:47,311 - mmdet - INFO - Epoch [1][5350/7330] lr: 1.000e-04, eta: 10:09:15, time: 0.429, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0499, loss_cls: 0.2284, acc: 91.9995, loss_bbox: 0.2692, loss_mask: 0.2621, loss: 0.8430 2023-11-13 17:03:08,709 - mmdet - INFO - Epoch [1][5400/7330] lr: 1.000e-04, eta: 10:08:42, time: 0.428, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0496, loss_cls: 0.2296, acc: 92.1562, loss_bbox: 0.2682, loss_mask: 0.2570, loss: 0.8380 2023-11-13 17:03:31,411 - mmdet - INFO - Epoch [1][5450/7330] lr: 1.000e-04, eta: 10:08:28, time: 0.454, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0599, loss_cls: 0.2527, acc: 91.3501, loss_bbox: 0.2909, loss_mask: 0.2720, loss: 0.9184 2023-11-13 17:03:53,501 - mmdet - INFO - Epoch [1][5500/7330] lr: 1.000e-04, eta: 10:08:06, time: 0.442, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0390, loss_rpn_bbox: 0.0568, loss_cls: 0.2451, acc: 91.5112, loss_bbox: 0.2869, loss_mask: 0.2704, loss: 0.8982 2023-11-13 17:04:15,646 - mmdet - INFO - Epoch [1][5550/7330] lr: 1.000e-04, eta: 10:07:44, time: 0.443, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0369, loss_rpn_bbox: 0.0544, loss_cls: 0.2454, acc: 91.5076, loss_bbox: 0.2883, loss_mask: 0.2780, loss: 0.9030 2023-11-13 17:04:37,781 - mmdet - INFO - Epoch [1][5600/7330] lr: 1.000e-04, eta: 10:07:22, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0369, loss_rpn_bbox: 0.0532, loss_cls: 0.2392, acc: 91.6953, loss_bbox: 0.2800, loss_mask: 0.2739, loss: 0.8832 2023-11-13 17:04:59,528 - mmdet - INFO - Epoch [1][5650/7330] lr: 1.000e-04, eta: 10:06:54, time: 0.435, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0376, loss_rpn_bbox: 0.0539, loss_cls: 0.2333, acc: 91.9680, loss_bbox: 0.2737, loss_mask: 0.2694, loss: 0.8679 2023-11-13 17:05:21,453 - mmdet - INFO - Epoch [1][5700/7330] lr: 1.000e-04, eta: 10:06:29, time: 0.439, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0377, loss_rpn_bbox: 0.0534, loss_cls: 0.2432, acc: 91.5928, loss_bbox: 0.2842, loss_mask: 0.2660, loss: 0.8845 2023-11-13 17:05:43,485 - mmdet - INFO - Epoch [1][5750/7330] lr: 1.000e-04, eta: 10:06:06, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0521, loss_cls: 0.2458, acc: 91.4524, loss_bbox: 0.2851, loss_mask: 0.2703, loss: 0.8884 2023-11-13 17:06:05,661 - mmdet - INFO - Epoch [1][5800/7330] lr: 1.000e-04, eta: 10:05:45, time: 0.444, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0561, loss_cls: 0.2391, acc: 91.7222, loss_bbox: 0.2808, loss_mask: 0.2610, loss: 0.8773 2023-11-13 17:06:27,557 - mmdet - INFO - Epoch [1][5850/7330] lr: 1.000e-04, eta: 10:05:19, time: 0.438, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0387, loss_rpn_bbox: 0.0554, loss_cls: 0.2473, acc: 91.4465, loss_bbox: 0.2852, loss_mask: 0.2781, loss: 0.9047 2023-11-13 17:06:49,497 - mmdet - INFO - Epoch [1][5900/7330] lr: 1.000e-04, eta: 10:04:55, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0522, loss_cls: 0.2286, acc: 92.1650, loss_bbox: 0.2654, loss_mask: 0.2653, loss: 0.8463 2023-11-13 17:07:11,295 - mmdet - INFO - Epoch [1][5950/7330] lr: 1.000e-04, eta: 10:04:28, time: 0.436, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0529, loss_cls: 0.2343, acc: 91.8936, loss_bbox: 0.2758, loss_mask: 0.2655, loss: 0.8619 2023-11-13 17:07:33,063 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 17:07:33,064 - mmdet - INFO - Epoch [1][6000/7330] lr: 1.000e-04, eta: 10:04:01, time: 0.435, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0350, loss_rpn_bbox: 0.0538, loss_cls: 0.2332, acc: 91.9426, loss_bbox: 0.2733, loss_mask: 0.2632, loss: 0.8584 2023-11-13 17:07:55,172 - mmdet - INFO - Epoch [1][6050/7330] lr: 1.000e-04, eta: 10:03:39, time: 0.442, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0388, loss_rpn_bbox: 0.0531, loss_cls: 0.2356, acc: 91.6875, loss_bbox: 0.2799, loss_mask: 0.2643, loss: 0.8718 2023-11-13 17:08:17,242 - mmdet - INFO - Epoch [1][6100/7330] lr: 1.000e-04, eta: 10:03:17, time: 0.441, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0547, loss_cls: 0.2383, acc: 91.6521, loss_bbox: 0.2801, loss_mask: 0.2633, loss: 0.8733 2023-11-13 17:08:39,450 - mmdet - INFO - Epoch [1][6150/7330] lr: 1.000e-04, eta: 10:02:56, time: 0.444, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0538, loss_cls: 0.2294, acc: 91.9695, loss_bbox: 0.2760, loss_mask: 0.2673, loss: 0.8612 2023-11-13 17:09:01,122 - mmdet - INFO - Epoch [1][6200/7330] lr: 1.000e-04, eta: 10:02:28, time: 0.433, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0337, loss_rpn_bbox: 0.0537, loss_cls: 0.2286, acc: 91.8806, loss_bbox: 0.2790, loss_mask: 0.2654, loss: 0.8603 2023-11-13 17:09:23,166 - mmdet - INFO - Epoch [1][6250/7330] lr: 1.000e-04, eta: 10:02:05, time: 0.441, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0359, loss_rpn_bbox: 0.0534, loss_cls: 0.2346, acc: 91.8840, loss_bbox: 0.2766, loss_mask: 0.2679, loss: 0.8684 2023-11-13 17:09:44,783 - mmdet - INFO - Epoch [1][6300/7330] lr: 1.000e-04, eta: 10:01:37, time: 0.432, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0528, loss_cls: 0.2342, acc: 91.9587, loss_bbox: 0.2727, loss_mask: 0.2642, loss: 0.8594 2023-11-13 17:10:07,146 - mmdet - INFO - Epoch [1][6350/7330] lr: 1.000e-04, eta: 10:01:18, time: 0.447, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0548, loss_cls: 0.2385, acc: 91.7888, loss_bbox: 0.2814, loss_mask: 0.2623, loss: 0.8730 2023-11-13 17:10:28,655 - mmdet - INFO - Epoch [1][6400/7330] lr: 1.000e-04, eta: 10:00:48, time: 0.430, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0513, loss_cls: 0.2322, acc: 91.9517, loss_bbox: 0.2752, loss_mask: 0.2598, loss: 0.8532 2023-11-13 17:10:50,709 - mmdet - INFO - Epoch [1][6450/7330] lr: 1.000e-04, eta: 10:00:25, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0526, loss_cls: 0.2268, acc: 92.0208, loss_bbox: 0.2712, loss_mask: 0.2664, loss: 0.8517 2023-11-13 17:11:12,681 - mmdet - INFO - Epoch [1][6500/7330] lr: 1.000e-04, eta: 10:00:02, time: 0.439, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0359, loss_rpn_bbox: 0.0551, loss_cls: 0.2321, acc: 91.9075, loss_bbox: 0.2763, loss_mask: 0.2700, loss: 0.8695 2023-11-13 17:11:34,835 - mmdet - INFO - Epoch [1][6550/7330] lr: 1.000e-04, eta: 9:59:40, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0517, loss_cls: 0.2264, acc: 92.0962, loss_bbox: 0.2744, loss_mask: 0.2668, loss: 0.8554 2023-11-13 17:11:56,708 - mmdet - INFO - Epoch [1][6600/7330] lr: 1.000e-04, eta: 9:59:16, time: 0.437, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0354, loss_rpn_bbox: 0.0535, loss_cls: 0.2329, acc: 91.9185, loss_bbox: 0.2759, loss_mask: 0.2719, loss: 0.8696 2023-11-13 17:12:18,551 - mmdet - INFO - Epoch [1][6650/7330] lr: 1.000e-04, eta: 9:58:50, time: 0.437, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0511, loss_cls: 0.2325, acc: 91.8552, loss_bbox: 0.2735, loss_mask: 0.2623, loss: 0.8540 2023-11-13 17:12:40,883 - mmdet - INFO - Epoch [1][6700/7330] lr: 1.000e-04, eta: 9:58:31, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0501, loss_cls: 0.2307, acc: 91.8638, loss_bbox: 0.2727, loss_mask: 0.2619, loss: 0.8489 2023-11-13 17:13:02,864 - mmdet - INFO - Epoch [1][6750/7330] lr: 1.000e-04, eta: 9:58:08, time: 0.440, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0377, loss_rpn_bbox: 0.0528, loss_cls: 0.2324, acc: 91.8479, loss_bbox: 0.2797, loss_mask: 0.2685, loss: 0.8710 2023-11-13 17:13:24,526 - mmdet - INFO - Epoch [1][6800/7330] lr: 1.000e-04, eta: 9:57:40, time: 0.433, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0526, loss_cls: 0.2192, acc: 92.4138, loss_bbox: 0.2647, loss_mask: 0.2583, loss: 0.8284 2023-11-13 17:13:46,396 - mmdet - INFO - Epoch [1][6850/7330] lr: 1.000e-04, eta: 9:57:16, time: 0.437, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0356, loss_rpn_bbox: 0.0515, loss_cls: 0.2288, acc: 92.0469, loss_bbox: 0.2688, loss_mask: 0.2616, loss: 0.8463 2023-11-13 17:14:08,342 - mmdet - INFO - Epoch [1][6900/7330] lr: 1.000e-04, eta: 9:56:52, time: 0.439, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0339, loss_rpn_bbox: 0.0503, loss_cls: 0.2225, acc: 92.3062, loss_bbox: 0.2696, loss_mask: 0.2668, loss: 0.8431 2023-11-13 17:14:30,766 - mmdet - INFO - Epoch [1][6950/7330] lr: 1.000e-04, eta: 9:56:34, time: 0.448, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0565, loss_cls: 0.2465, acc: 91.4050, loss_bbox: 0.2839, loss_mask: 0.2747, loss: 0.8986 2023-11-13 17:14:52,602 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 17:14:52,602 - mmdet - INFO - Epoch [1][7000/7330] lr: 1.000e-04, eta: 9:56:09, time: 0.437, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0358, loss_rpn_bbox: 0.0514, loss_cls: 0.2241, acc: 92.2297, loss_bbox: 0.2645, loss_mask: 0.2570, loss: 0.8329 2023-11-13 17:15:14,257 - mmdet - INFO - Epoch [1][7050/7330] lr: 1.000e-04, eta: 9:55:41, time: 0.433, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0503, loss_cls: 0.2213, acc: 92.1797, loss_bbox: 0.2661, loss_mask: 0.2523, loss: 0.8223 2023-11-13 17:15:36,476 - mmdet - INFO - Epoch [1][7100/7330] lr: 1.000e-04, eta: 9:55:21, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0327, loss_rpn_bbox: 0.0509, loss_cls: 0.2309, acc: 92.0198, loss_bbox: 0.2733, loss_mask: 0.2644, loss: 0.8523 2023-11-13 17:15:58,482 - mmdet - INFO - Epoch [1][7150/7330] lr: 1.000e-04, eta: 9:54:58, time: 0.440, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0534, loss_cls: 0.2295, acc: 91.9907, loss_bbox: 0.2690, loss_mask: 0.2632, loss: 0.8502 2023-11-13 17:16:20,539 - mmdet - INFO - Epoch [1][7200/7330] lr: 1.000e-04, eta: 9:54:35, time: 0.441, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0363, loss_rpn_bbox: 0.0558, loss_cls: 0.2355, acc: 91.8198, loss_bbox: 0.2757, loss_mask: 0.2538, loss: 0.8571 2023-11-13 17:16:42,993 - mmdet - INFO - Epoch [1][7250/7330] lr: 1.000e-04, eta: 9:54:17, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0350, loss_rpn_bbox: 0.0509, loss_cls: 0.2272, acc: 91.9541, loss_bbox: 0.2758, loss_mask: 0.2620, loss: 0.8509 2023-11-13 17:17:05,130 - mmdet - INFO - Epoch [1][7300/7330] lr: 1.000e-04, eta: 9:53:56, time: 0.443, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0335, loss_rpn_bbox: 0.0502, loss_cls: 0.2225, acc: 92.2588, loss_bbox: 0.2653, loss_mask: 0.2509, loss: 0.8225 2023-11-13 17:17:18,770 - mmdet - INFO - Saving checkpoint at 1 epochs 2023-11-13 17:18:14,823 - mmdet - INFO - Evaluating bbox... 2023-11-13 17:18:50,525 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.387 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.630 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.424 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.252 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.422 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.504 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.521 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.521 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.521 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.352 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.565 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.658 2023-11-13 17:18:50,528 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.518 | bicycle | 0.311 | car | 0.417 | | motorcycle | 0.390 | airplane | 0.576 | bus | 0.636 | | train | 0.601 | truck | 0.367 | boat | 0.241 | | traffic light | 0.265 | fire hydrant | 0.628 | stop sign | 0.601 | | parking meter | 0.448 | bench | 0.212 | bird | 0.356 | | cat | 0.634 | dog | 0.614 | horse | 0.537 | | sheep | 0.506 | cow | 0.542 | elephant | 0.624 | | bear | 0.634 | zebra | 0.613 | giraffe | 0.615 | | backpack | 0.162 | umbrella | 0.356 | handbag | 0.153 | | tie | 0.276 | suitcase | 0.336 | frisbee | 0.622 | | skis | 0.183 | snowboard | 0.264 | sports ball | 0.446 | | kite | 0.377 | baseball bat | 0.271 | baseball glove | 0.372 | | skateboard | 0.454 | surfboard | 0.329 | tennis racket | 0.445 | | bottle | 0.386 | wine glass | 0.309 | cup | 0.450 | | fork | 0.273 | knife | 0.187 | spoon | 0.188 | | bowl | 0.405 | banana | 0.236 | apple | 0.183 | | sandwich | 0.364 | orange | 0.312 | broccoli | 0.232 | | carrot | 0.202 | hot dog | 0.281 | pizza | 0.497 | | donut | 0.437 | cake | 0.361 | chair | 0.278 | | couch | 0.372 | potted plant | 0.240 | bed | 0.422 | | dining table | 0.231 | toilet | 0.510 | tv | 0.560 | | laptop | 0.569 | mouse | 0.583 | remote | 0.304 | | keyboard | 0.452 | cell phone | 0.367 | microwave | 0.567 | | oven | 0.311 | toaster | 0.197 | sink | 0.328 | | refrigerator | 0.522 | book | 0.136 | clock | 0.476 | | vase | 0.371 | scissors | 0.253 | teddy bear | 0.416 | | hair drier | 0.097 | toothbrush | 0.138 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:18:50,528 - mmdet - INFO - Evaluating segm... 2023-11-13 17:19:33,060 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.365 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.600 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.385 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.189 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.398 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.489 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.489 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.489 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.535 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.640 2023-11-13 17:19:33,063 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.453 | bicycle | 0.192 | car | 0.389 | | motorcycle | 0.317 | airplane | 0.481 | bus | 0.637 | | train | 0.597 | truck | 0.370 | boat | 0.237 | | traffic light | 0.261 | fire hydrant | 0.632 | stop sign | 0.631 | | parking meter | 0.484 | bench | 0.170 | bird | 0.311 | | cat | 0.681 | dog | 0.605 | horse | 0.411 | | sheep | 0.456 | cow | 0.446 | elephant | 0.570 | | bear | 0.697 | zebra | 0.511 | giraffe | 0.461 | | backpack | 0.181 | umbrella | 0.463 | handbag | 0.166 | | tie | 0.272 | suitcase | 0.365 | frisbee | 0.627 | | skis | 0.020 | snowboard | 0.187 | sports ball | 0.448 | | kite | 0.275 | baseball bat | 0.205 | baseball glove | 0.409 | | skateboard | 0.279 | surfboard | 0.276 | tennis racket | 0.527 | | bottle | 0.384 | wine glass | 0.309 | cup | 0.468 | | fork | 0.129 | knife | 0.136 | spoon | 0.126 | | bowl | 0.386 | banana | 0.189 | apple | 0.182 | | sandwich | 0.419 | orange | 0.321 | broccoli | 0.219 | | carrot | 0.179 | hot dog | 0.238 | pizza | 0.502 | | donut | 0.468 | cake | 0.389 | chair | 0.196 | | couch | 0.329 | potted plant | 0.208 | bed | 0.331 | | dining table | 0.129 | toilet | 0.541 | tv | 0.590 | | laptop | 0.605 | mouse | 0.596 | remote | 0.274 | | keyboard | 0.477 | cell phone | 0.352 | microwave | 0.616 | | oven | 0.310 | toaster | 0.294 | sink | 0.344 | | refrigerator | 0.540 | book | 0.094 | clock | 0.501 | | vase | 0.376 | scissors | 0.195 | teddy bear | 0.409 | | hair drier | 0.035 | toothbrush | 0.086 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 17:19:36,846 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_1.pth. 2023-11-13 17:19:36,847 - mmdet - INFO - Best bbox_mAP is 0.3867 at 1 epoch. 2023-11-13 17:19:36,847 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 17:19:36,847 - mmdet - INFO - Epoch(val) [1][625] bbox_mAP: 0.3867, bbox_mAP_50: 0.6296, bbox_mAP_75: 0.4244, bbox_mAP_s: 0.2516, bbox_mAP_m: 0.4216, bbox_mAP_l: 0.5039, bbox_mAP_copypaste: 0.3867 0.6296 0.4244 0.2516 0.4216 0.5039, segm_mAP: 0.3647, segm_mAP_50: 0.6001, segm_mAP_75: 0.3853, segm_mAP_s: 0.1894, segm_mAP_m: 0.3975, segm_mAP_l: 0.5334, segm_mAP_copypaste: 0.3647 0.6001 0.3853 0.1894 0.3975 0.5334 2023-11-13 17:20:03,232 - mmdet - INFO - Epoch [2][50/7330] lr: 1.000e-04, eta: 9:51:43, time: 0.527, data_time: 0.089, memory: 5731, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0511, loss_cls: 0.2217, acc: 92.2388, loss_bbox: 0.2626, loss_mask: 0.2547, loss: 0.8249 2023-11-13 17:20:26,201 - mmdet - INFO - Epoch [2][100/7330] lr: 1.000e-04, eta: 9:51:31, time: 0.459, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0329, loss_rpn_bbox: 0.0523, loss_cls: 0.2248, acc: 92.0203, loss_bbox: 0.2744, loss_mask: 0.2596, loss: 0.8440 2023-11-13 17:20:49,041 - mmdet - INFO - Epoch [2][150/7330] lr: 1.000e-04, eta: 9:51:17, time: 0.457, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0480, loss_cls: 0.2143, acc: 92.2756, loss_bbox: 0.2635, loss_mask: 0.2575, loss: 0.8128 2023-11-13 17:21:12,037 - mmdet - INFO - Epoch [2][200/7330] lr: 1.000e-04, eta: 9:51:05, time: 0.460, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0354, loss_rpn_bbox: 0.0504, loss_cls: 0.2132, acc: 92.4314, loss_bbox: 0.2583, loss_mask: 0.2532, loss: 0.8105 2023-11-13 17:21:37,224 - mmdet - INFO - Epoch [2][250/7330] lr: 1.000e-04, eta: 9:51:17, time: 0.503, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0323, loss_rpn_bbox: 0.0500, loss_cls: 0.2224, acc: 92.1536, loss_bbox: 0.2697, loss_mask: 0.2547, loss: 0.8291 2023-11-13 17:22:00,601 - mmdet - INFO - Epoch [2][300/7330] lr: 1.000e-04, eta: 9:51:08, time: 0.468, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0511, loss_cls: 0.2188, acc: 92.1650, loss_bbox: 0.2719, loss_mask: 0.2531, loss: 0.8269 2023-11-13 17:22:23,364 - mmdet - INFO - Epoch [2][350/7330] lr: 1.000e-04, eta: 9:50:53, time: 0.455, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0504, loss_cls: 0.2181, acc: 92.1919, loss_bbox: 0.2685, loss_mask: 0.2502, loss: 0.8194 2023-11-13 17:22:46,128 - mmdet - INFO - Epoch [2][400/7330] lr: 1.000e-04, eta: 9:50:38, time: 0.455, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0491, loss_cls: 0.2099, acc: 92.6199, loss_bbox: 0.2549, loss_mask: 0.2485, loss: 0.7939 2023-11-13 17:23:09,043 - mmdet - INFO - Epoch [2][450/7330] lr: 1.000e-04, eta: 9:50:25, time: 0.458, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0513, loss_cls: 0.2215, acc: 92.1685, loss_bbox: 0.2676, loss_mask: 0.2576, loss: 0.8318 2023-11-13 17:23:31,733 - mmdet - INFO - Epoch [2][500/7330] lr: 1.000e-04, eta: 9:50:09, time: 0.454, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0510, loss_cls: 0.2213, acc: 92.2014, loss_bbox: 0.2659, loss_mask: 0.2542, loss: 0.8241 2023-11-13 17:23:54,643 - mmdet - INFO - Epoch [2][550/7330] lr: 1.000e-04, eta: 9:49:55, time: 0.458, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0506, loss_cls: 0.2177, acc: 92.2703, loss_bbox: 0.2670, loss_mask: 0.2560, loss: 0.8241 2023-11-13 17:24:17,709 - mmdet - INFO - Epoch [2][600/7330] lr: 1.000e-04, eta: 9:49:43, time: 0.461, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0336, loss_rpn_bbox: 0.0485, loss_cls: 0.2162, acc: 92.3315, loss_bbox: 0.2631, loss_mask: 0.2508, loss: 0.8122 2023-11-13 17:24:40,562 - mmdet - INFO - Epoch [2][650/7330] lr: 1.000e-04, eta: 9:49:28, time: 0.457, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0485, loss_cls: 0.2077, acc: 92.5908, loss_bbox: 0.2579, loss_mask: 0.2489, loss: 0.7928 2023-11-13 17:25:03,028 - mmdet - INFO - Epoch [2][700/7330] lr: 1.000e-04, eta: 9:49:10, time: 0.449, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0482, loss_cls: 0.2105, acc: 92.4680, loss_bbox: 0.2592, loss_mask: 0.2560, loss: 0.8040 2023-11-13 17:25:30,153 - mmdet - INFO - Epoch [2][750/7330] lr: 1.000e-04, eta: 9:49:37, time: 0.542, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0310, loss_rpn_bbox: 0.0496, loss_cls: 0.2102, acc: 92.4658, loss_bbox: 0.2623, loss_mask: 0.2550, loss: 0.8081 2023-11-13 17:25:53,128 - mmdet - INFO - Epoch [2][800/7330] lr: 1.000e-04, eta: 9:49:23, time: 0.460, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0508, loss_cls: 0.2218, acc: 92.0557, loss_bbox: 0.2691, loss_mask: 0.2587, loss: 0.8317 2023-11-13 17:26:20,847 - mmdet - INFO - Epoch [2][850/7330] lr: 1.000e-04, eta: 9:49:55, time: 0.554, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0328, loss_rpn_bbox: 0.0500, loss_cls: 0.2220, acc: 92.1604, loss_bbox: 0.2682, loss_mask: 0.2544, loss: 0.8273 2023-11-13 17:26:44,083 - mmdet - INFO - Epoch [2][900/7330] lr: 1.000e-04, eta: 9:49:43, time: 0.465, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0506, loss_cls: 0.2192, acc: 92.2510, loss_bbox: 0.2624, loss_mask: 0.2577, loss: 0.8190 2023-11-13 17:27:07,097 - mmdet - INFO - Epoch [2][950/7330] lr: 1.000e-04, eta: 9:49:29, time: 0.460, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0503, loss_cls: 0.2163, acc: 92.3508, loss_bbox: 0.2634, loss_mask: 0.2534, loss: 0.8138 2023-11-13 17:27:30,069 - mmdet - INFO - Epoch [2][1000/7330] lr: 1.000e-04, eta: 9:49:14, time: 0.460, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0330, loss_rpn_bbox: 0.0521, loss_cls: 0.2187, acc: 92.2798, loss_bbox: 0.2595, loss_mask: 0.2562, loss: 0.8194 2023-11-13 17:27:52,994 - mmdet - INFO - Epoch [2][1050/7330] lr: 1.000e-04, eta: 9:48:59, time: 0.458, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0485, loss_cls: 0.2124, acc: 92.4102, loss_bbox: 0.2604, loss_mask: 0.2547, loss: 0.8070 2023-11-13 17:28:15,348 - mmdet - INFO - Epoch [2][1100/7330] lr: 1.000e-04, eta: 9:48:38, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0431, loss_cls: 0.2035, acc: 92.7114, loss_bbox: 0.2503, loss_mask: 0.2443, loss: 0.7701 2023-11-13 17:28:37,764 - mmdet - INFO - Epoch [2][1150/7330] lr: 1.000e-04, eta: 9:48:18, time: 0.448, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0494, loss_cls: 0.2075, acc: 92.5808, loss_bbox: 0.2520, loss_mask: 0.2543, loss: 0.7924 2023-11-13 17:29:00,452 - mmdet - INFO - Epoch [2][1200/7330] lr: 1.000e-04, eta: 9:48:00, time: 0.454, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0471, loss_cls: 0.2053, acc: 92.6218, loss_bbox: 0.2479, loss_mask: 0.2489, loss: 0.7793 2023-11-13 17:29:23,761 - mmdet - INFO - Epoch [2][1250/7330] lr: 1.000e-04, eta: 9:47:48, time: 0.466, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0344, loss_rpn_bbox: 0.0542, loss_cls: 0.2302, acc: 91.8015, loss_bbox: 0.2805, loss_mask: 0.2562, loss: 0.8556 2023-11-13 17:29:46,385 - mmdet - INFO - Epoch [2][1300/7330] lr: 1.000e-04, eta: 9:47:30, time: 0.452, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0511, loss_cls: 0.2207, acc: 92.0513, loss_bbox: 0.2729, loss_mask: 0.2608, loss: 0.8370 2023-11-13 17:30:09,299 - mmdet - INFO - Epoch [2][1350/7330] lr: 1.000e-04, eta: 9:47:14, time: 0.458, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0317, loss_rpn_bbox: 0.0498, loss_cls: 0.2140, acc: 92.4043, loss_bbox: 0.2650, loss_mask: 0.2577, loss: 0.8182 2023-11-13 17:30:31,814 - mmdet - INFO - Epoch [2][1400/7330] lr: 1.000e-04, eta: 9:46:54, time: 0.450, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0283, loss_rpn_bbox: 0.0452, loss_cls: 0.1960, acc: 93.0793, loss_bbox: 0.2375, loss_mask: 0.2426, loss: 0.7496 2023-11-13 17:30:54,297 - mmdet - INFO - Epoch [2][1450/7330] lr: 1.000e-04, eta: 9:46:34, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0312, loss_rpn_bbox: 0.0501, loss_cls: 0.2175, acc: 92.3958, loss_bbox: 0.2629, loss_mask: 0.2552, loss: 0.8168 2023-11-13 17:31:17,241 - mmdet - INFO - Epoch [2][1500/7330] lr: 1.000e-04, eta: 9:46:18, time: 0.459, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0334, loss_rpn_bbox: 0.0503, loss_cls: 0.2116, acc: 92.6089, loss_bbox: 0.2586, loss_mask: 0.2525, loss: 0.8064 2023-11-13 17:31:40,132 - mmdet - INFO - Epoch [2][1550/7330] lr: 1.000e-04, eta: 9:46:02, time: 0.458, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0498, loss_cls: 0.2044, acc: 92.7151, loss_bbox: 0.2552, loss_mask: 0.2452, loss: 0.7851 2023-11-13 17:32:02,713 - mmdet - INFO - Epoch [2][1600/7330] lr: 1.000e-04, eta: 9:45:43, time: 0.452, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0508, loss_cls: 0.2068, acc: 92.5969, loss_bbox: 0.2543, loss_mask: 0.2505, loss: 0.7922 2023-11-13 17:32:25,279 - mmdet - INFO - Epoch [2][1650/7330] lr: 1.000e-04, eta: 9:45:24, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0313, loss_rpn_bbox: 0.0482, loss_cls: 0.2155, acc: 92.4915, loss_bbox: 0.2560, loss_mask: 0.2456, loss: 0.7966 2023-11-13 17:32:47,579 - mmdet - INFO - Epoch [2][1700/7330] lr: 1.000e-04, eta: 9:45:02, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0494, loss_cls: 0.2125, acc: 92.4502, loss_bbox: 0.2612, loss_mask: 0.2526, loss: 0.8075 2023-11-13 17:33:10,528 - mmdet - INFO - Epoch [2][1750/7330] lr: 1.000e-04, eta: 9:44:46, time: 0.459, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0493, loss_cls: 0.2105, acc: 92.5215, loss_bbox: 0.2539, loss_mask: 0.2526, loss: 0.7954 2023-11-13 17:33:32,861 - mmdet - INFO - Epoch [2][1800/7330] lr: 1.000e-04, eta: 9:44:24, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0469, loss_cls: 0.2129, acc: 92.4866, loss_bbox: 0.2627, loss_mask: 0.2499, loss: 0.8012 2023-11-13 17:33:55,317 - mmdet - INFO - Epoch [2][1850/7330] lr: 1.000e-04, eta: 9:44:04, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0303, loss_rpn_bbox: 0.0508, loss_cls: 0.2122, acc: 92.5452, loss_bbox: 0.2589, loss_mask: 0.2502, loss: 0.8024 2023-11-13 17:34:18,499 - mmdet - INFO - Epoch [2][1900/7330] lr: 1.000e-04, eta: 9:43:50, time: 0.464, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0518, loss_cls: 0.2204, acc: 92.1667, loss_bbox: 0.2694, loss_mask: 0.2515, loss: 0.8249 2023-11-13 17:34:41,519 - mmdet - INFO - Epoch [2][1950/7330] lr: 1.000e-04, eta: 9:43:34, time: 0.460, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0503, loss_cls: 0.2150, acc: 92.3330, loss_bbox: 0.2662, loss_mask: 0.2523, loss: 0.8133 2023-11-13 17:35:04,371 - mmdet - INFO - Epoch [2][2000/7330] lr: 1.000e-04, eta: 9:43:17, time: 0.457, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0500, loss_cls: 0.2215, acc: 92.1624, loss_bbox: 0.2666, loss_mask: 0.2530, loss: 0.8207 2023-11-13 17:35:27,085 - mmdet - INFO - Epoch [2][2050/7330] lr: 1.000e-04, eta: 9:42:59, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0489, loss_cls: 0.2111, acc: 92.3843, loss_bbox: 0.2650, loss_mask: 0.2473, loss: 0.8017 2023-11-13 17:35:49,899 - mmdet - INFO - Epoch [2][2100/7330] lr: 1.000e-04, eta: 9:42:41, time: 0.456, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0341, loss_rpn_bbox: 0.0515, loss_cls: 0.2212, acc: 92.0386, loss_bbox: 0.2688, loss_mask: 0.2492, loss: 0.8249 2023-11-13 17:36:12,276 - mmdet - INFO - Epoch [2][2150/7330] lr: 1.000e-04, eta: 9:42:20, time: 0.448, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0459, loss_cls: 0.2099, acc: 92.5237, loss_bbox: 0.2595, loss_mask: 0.2425, loss: 0.7877 2023-11-13 17:36:34,953 - mmdet - INFO - Epoch [2][2200/7330] lr: 1.000e-04, eta: 9:42:01, time: 0.454, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0485, loss_cls: 0.2203, acc: 92.1045, loss_bbox: 0.2673, loss_mask: 0.2568, loss: 0.8233 2023-11-13 17:36:57,447 - mmdet - INFO - Epoch [2][2250/7330] lr: 1.000e-04, eta: 9:41:40, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0484, loss_cls: 0.2200, acc: 92.1223, loss_bbox: 0.2713, loss_mask: 0.2498, loss: 0.8210 2023-11-13 17:37:20,070 - mmdet - INFO - Epoch [2][2300/7330] lr: 1.000e-04, eta: 9:41:21, time: 0.453, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0504, loss_cls: 0.2160, acc: 92.3528, loss_bbox: 0.2620, loss_mask: 0.2499, loss: 0.8101 2023-11-13 17:37:42,935 - mmdet - INFO - Epoch [2][2350/7330] lr: 1.000e-04, eta: 9:41:04, time: 0.457, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0509, loss_cls: 0.2168, acc: 92.2258, loss_bbox: 0.2698, loss_mask: 0.2599, loss: 0.8300 2023-11-13 17:38:05,501 - mmdet - INFO - Epoch [2][2400/7330] lr: 1.000e-04, eta: 9:40:44, time: 0.451, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0479, loss_cls: 0.2091, acc: 92.6221, loss_bbox: 0.2515, loss_mask: 0.2504, loss: 0.7878 2023-11-13 17:38:27,713 - mmdet - INFO - Epoch [2][2450/7330] lr: 1.000e-04, eta: 9:40:21, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0319, loss_rpn_bbox: 0.0481, loss_cls: 0.2162, acc: 92.4265, loss_bbox: 0.2538, loss_mask: 0.2552, loss: 0.8051 2023-11-13 17:38:50,183 - mmdet - INFO - Epoch [2][2500/7330] lr: 1.000e-04, eta: 9:40:00, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0484, loss_cls: 0.2172, acc: 92.1365, loss_bbox: 0.2701, loss_mask: 0.2571, loss: 0.8224 2023-11-13 17:39:12,677 - mmdet - INFO - Epoch [2][2550/7330] lr: 1.000e-04, eta: 9:39:40, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0479, loss_cls: 0.2091, acc: 92.4524, loss_bbox: 0.2614, loss_mask: 0.2523, loss: 0.8012 2023-11-13 17:39:34,958 - mmdet - INFO - Epoch [2][2600/7330] lr: 1.000e-04, eta: 9:39:18, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0508, loss_cls: 0.2143, acc: 92.2732, loss_bbox: 0.2588, loss_mask: 0.2527, loss: 0.8068 2023-11-13 17:39:57,328 - mmdet - INFO - Epoch [2][2650/7330] lr: 1.000e-04, eta: 9:38:56, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0315, loss_rpn_bbox: 0.0490, loss_cls: 0.2072, acc: 92.5356, loss_bbox: 0.2597, loss_mask: 0.2463, loss: 0.7938 2023-11-13 17:40:19,428 - mmdet - INFO - Epoch [2][2700/7330] lr: 1.000e-04, eta: 9:38:33, time: 0.442, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0438, loss_cls: 0.2060, acc: 92.5608, loss_bbox: 0.2490, loss_mask: 0.2475, loss: 0.7725 2023-11-13 17:40:41,589 - mmdet - INFO - Epoch [2][2750/7330] lr: 1.000e-04, eta: 9:38:09, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0456, loss_cls: 0.2070, acc: 92.6936, loss_bbox: 0.2494, loss_mask: 0.2444, loss: 0.7745 2023-11-13 17:41:04,298 - mmdet - INFO - Epoch [2][2800/7330] lr: 1.000e-04, eta: 9:37:50, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0466, loss_cls: 0.2107, acc: 92.5276, loss_bbox: 0.2523, loss_mask: 0.2538, loss: 0.7906 2023-11-13 17:41:26,970 - mmdet - INFO - Epoch [2][2850/7330] lr: 1.000e-04, eta: 9:37:31, time: 0.453, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0489, loss_cls: 0.2126, acc: 92.2522, loss_bbox: 0.2625, loss_mask: 0.2495, loss: 0.8049 2023-11-13 17:41:49,386 - mmdet - INFO - Epoch [2][2900/7330] lr: 1.000e-04, eta: 9:37:10, time: 0.448, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0304, loss_rpn_bbox: 0.0485, loss_cls: 0.2165, acc: 92.3381, loss_bbox: 0.2647, loss_mask: 0.2551, loss: 0.8151 2023-11-13 17:42:11,685 - mmdet - INFO - Epoch [2][2950/7330] lr: 1.000e-04, eta: 9:36:48, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0299, loss_rpn_bbox: 0.0490, loss_cls: 0.2182, acc: 92.4011, loss_bbox: 0.2591, loss_mask: 0.2567, loss: 0.8129 2023-11-13 17:42:34,174 - mmdet - INFO - Epoch [2][3000/7330] lr: 1.000e-04, eta: 9:36:27, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0442, loss_cls: 0.1999, acc: 92.7600, loss_bbox: 0.2486, loss_mask: 0.2487, loss: 0.7682 2023-11-13 17:42:57,058 - mmdet - INFO - Epoch [2][3050/7330] lr: 1.000e-04, eta: 9:36:10, time: 0.458, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0332, loss_rpn_bbox: 0.0510, loss_cls: 0.2110, acc: 92.5896, loss_bbox: 0.2610, loss_mask: 0.2495, loss: 0.8058 2023-11-13 17:43:19,569 - mmdet - INFO - Epoch [2][3100/7330] lr: 1.000e-04, eta: 9:35:49, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0318, loss_rpn_bbox: 0.0479, loss_cls: 0.2105, acc: 92.5278, loss_bbox: 0.2529, loss_mask: 0.2523, loss: 0.7954 2023-11-13 17:43:42,002 - mmdet - INFO - Epoch [2][3150/7330] lr: 1.000e-04, eta: 9:35:28, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0471, loss_cls: 0.2040, acc: 92.6238, loss_bbox: 0.2533, loss_mask: 0.2478, loss: 0.7809 2023-11-13 17:44:04,181 - mmdet - INFO - Epoch [2][3200/7330] lr: 1.000e-04, eta: 9:35:05, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0496, loss_cls: 0.2183, acc: 92.3362, loss_bbox: 0.2546, loss_mask: 0.2475, loss: 0.8009 2023-11-13 17:44:26,917 - mmdet - INFO - Epoch [2][3250/7330] lr: 1.000e-04, eta: 9:34:46, time: 0.455, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0322, loss_rpn_bbox: 0.0522, loss_cls: 0.2262, acc: 92.0879, loss_bbox: 0.2721, loss_mask: 0.2542, loss: 0.8369 2023-11-13 17:44:49,506 - mmdet - INFO - Epoch [2][3300/7330] lr: 1.000e-04, eta: 9:34:26, time: 0.452, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0492, loss_cls: 0.2131, acc: 92.4070, loss_bbox: 0.2526, loss_mask: 0.2494, loss: 0.7944 2023-11-13 17:45:11,667 - mmdet - INFO - Epoch [2][3350/7330] lr: 1.000e-04, eta: 9:34:03, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0474, loss_cls: 0.2044, acc: 92.7705, loss_bbox: 0.2482, loss_mask: 0.2476, loss: 0.7762 2023-11-13 17:45:34,033 - mmdet - INFO - Epoch [2][3400/7330] lr: 1.000e-04, eta: 9:33:41, time: 0.447, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0309, loss_rpn_bbox: 0.0489, loss_cls: 0.2128, acc: 92.4976, loss_bbox: 0.2567, loss_mask: 0.2466, loss: 0.7959 2023-11-13 17:45:56,747 - mmdet - INFO - Epoch [2][3450/7330] lr: 1.000e-04, eta: 9:33:22, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0474, loss_cls: 0.2051, acc: 92.6091, loss_bbox: 0.2532, loss_mask: 0.2504, loss: 0.7871 2023-11-13 17:46:19,274 - mmdet - INFO - Epoch [2][3500/7330] lr: 1.000e-04, eta: 9:33:01, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0470, loss_cls: 0.2115, acc: 92.6123, loss_bbox: 0.2526, loss_mask: 0.2499, loss: 0.7907 2023-11-13 17:46:41,805 - mmdet - INFO - Epoch [2][3550/7330] lr: 1.000e-04, eta: 9:32:40, time: 0.451, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0305, loss_rpn_bbox: 0.0485, loss_cls: 0.2161, acc: 92.4204, loss_bbox: 0.2573, loss_mask: 0.2493, loss: 0.8018 2023-11-13 17:47:04,175 - mmdet - INFO - Epoch [2][3600/7330] lr: 1.000e-04, eta: 9:32:19, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0467, loss_cls: 0.2060, acc: 92.6514, loss_bbox: 0.2475, loss_mask: 0.2450, loss: 0.7744 2023-11-13 17:47:26,616 - mmdet - INFO - Epoch [2][3650/7330] lr: 1.000e-04, eta: 9:31:58, time: 0.449, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0298, loss_rpn_bbox: 0.0461, loss_cls: 0.2130, acc: 92.4912, loss_bbox: 0.2621, loss_mask: 0.2517, loss: 0.8027 2023-11-13 17:47:48,986 - mmdet - INFO - Epoch [2][3700/7330] lr: 1.000e-04, eta: 9:31:36, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0492, loss_cls: 0.2068, acc: 92.7075, loss_bbox: 0.2459, loss_mask: 0.2506, loss: 0.7820 2023-11-13 17:48:11,709 - mmdet - INFO - Epoch [2][3750/7330] lr: 1.000e-04, eta: 9:31:16, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0499, loss_cls: 0.2104, acc: 92.5918, loss_bbox: 0.2471, loss_mask: 0.2487, loss: 0.7888 2023-11-13 17:48:34,507 - mmdet - INFO - Epoch [2][3800/7330] lr: 1.000e-04, eta: 9:30:58, time: 0.456, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0480, loss_cls: 0.2118, acc: 92.4397, loss_bbox: 0.2602, loss_mask: 0.2463, loss: 0.7958 2023-11-13 17:48:56,708 - mmdet - INFO - Epoch [2][3850/7330] lr: 1.000e-04, eta: 9:30:35, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0445, loss_cls: 0.2015, acc: 92.8633, loss_bbox: 0.2466, loss_mask: 0.2441, loss: 0.7634 2023-11-13 17:49:19,106 - mmdet - INFO - Epoch [2][3900/7330] lr: 1.000e-04, eta: 9:30:13, time: 0.448, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0457, loss_cls: 0.2107, acc: 92.6406, loss_bbox: 0.2489, loss_mask: 0.2469, loss: 0.7854 2023-11-13 17:49:41,621 - mmdet - INFO - Epoch [2][3950/7330] lr: 1.000e-04, eta: 9:29:52, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0311, loss_rpn_bbox: 0.0499, loss_cls: 0.2074, acc: 92.6343, loss_bbox: 0.2554, loss_mask: 0.2525, loss: 0.7962 2023-11-13 17:50:04,346 - mmdet - INFO - Epoch [2][4000/7330] lr: 1.000e-04, eta: 9:29:33, time: 0.454, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0475, loss_cls: 0.2010, acc: 92.8357, loss_bbox: 0.2452, loss_mask: 0.2463, loss: 0.7677 2023-11-13 17:50:26,905 - mmdet - INFO - Epoch [2][4050/7330] lr: 1.000e-04, eta: 9:29:12, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0469, loss_cls: 0.2105, acc: 92.4670, loss_bbox: 0.2515, loss_mask: 0.2440, loss: 0.7804 2023-11-13 17:50:49,448 - mmdet - INFO - Epoch [2][4100/7330] lr: 1.000e-04, eta: 9:28:52, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0307, loss_rpn_bbox: 0.0479, loss_cls: 0.2054, acc: 92.6421, loss_bbox: 0.2462, loss_mask: 0.2515, loss: 0.7818 2023-11-13 17:51:11,658 - mmdet - INFO - Epoch [2][4150/7330] lr: 1.000e-04, eta: 9:28:29, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0495, loss_cls: 0.2125, acc: 92.4316, loss_bbox: 0.2606, loss_mask: 0.2490, loss: 0.7991 2023-11-13 17:51:33,954 - mmdet - INFO - Epoch [2][4200/7330] lr: 1.000e-04, eta: 9:28:07, time: 0.446, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0490, loss_cls: 0.2081, acc: 92.4600, loss_bbox: 0.2581, loss_mask: 0.2514, loss: 0.7960 2023-11-13 17:51:56,706 - mmdet - INFO - Epoch [2][4250/7330] lr: 1.000e-04, eta: 9:27:47, time: 0.455, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0484, loss_cls: 0.2052, acc: 92.5481, loss_bbox: 0.2508, loss_mask: 0.2444, loss: 0.7769 2023-11-13 17:52:19,477 - mmdet - INFO - Epoch [2][4300/7330] lr: 1.000e-04, eta: 9:27:28, time: 0.455, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0497, loss_cls: 0.2119, acc: 92.4268, loss_bbox: 0.2607, loss_mask: 0.2514, loss: 0.8038 2023-11-13 17:52:41,759 - mmdet - INFO - Epoch [2][4350/7330] lr: 1.000e-04, eta: 9:27:06, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0488, loss_cls: 0.2149, acc: 92.3848, loss_bbox: 0.2580, loss_mask: 0.2464, loss: 0.7977 2023-11-13 17:53:04,249 - mmdet - INFO - Epoch [2][4400/7330] lr: 1.000e-04, eta: 9:26:44, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0473, loss_cls: 0.2078, acc: 92.5300, loss_bbox: 0.2581, loss_mask: 0.2510, loss: 0.7934 2023-11-13 17:53:26,698 - mmdet - INFO - Epoch [2][4450/7330] lr: 1.000e-04, eta: 9:26:23, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0497, loss_cls: 0.2182, acc: 92.2793, loss_bbox: 0.2617, loss_mask: 0.2522, loss: 0.8095 2023-11-13 17:53:49,462 - mmdet - INFO - Epoch [2][4500/7330] lr: 1.000e-04, eta: 9:26:04, time: 0.455, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0320, loss_rpn_bbox: 0.0502, loss_cls: 0.2170, acc: 92.3284, loss_bbox: 0.2576, loss_mask: 0.2533, loss: 0.8102 2023-11-13 17:54:12,391 - mmdet - INFO - Epoch [2][4550/7330] lr: 1.000e-04, eta: 9:25:45, time: 0.459, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0507, loss_cls: 0.2135, acc: 92.3882, loss_bbox: 0.2624, loss_mask: 0.2546, loss: 0.8107 2023-11-13 17:54:34,827 - mmdet - INFO - Epoch [2][4600/7330] lr: 1.000e-04, eta: 9:25:24, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0288, loss_rpn_bbox: 0.0482, loss_cls: 0.2117, acc: 92.4612, loss_bbox: 0.2537, loss_mask: 0.2451, loss: 0.7874 2023-11-13 17:54:57,204 - mmdet - INFO - Epoch [2][4650/7330] lr: 1.000e-04, eta: 9:25:02, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0492, loss_cls: 0.2065, acc: 92.5876, loss_bbox: 0.2565, loss_mask: 0.2487, loss: 0.7904 2023-11-13 17:55:19,463 - mmdet - INFO - Epoch [2][4700/7330] lr: 1.000e-04, eta: 9:24:39, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0453, loss_cls: 0.2109, acc: 92.4834, loss_bbox: 0.2549, loss_mask: 0.2543, loss: 0.7923 2023-11-13 17:55:41,915 - mmdet - INFO - Epoch [2][4750/7330] lr: 1.000e-04, eta: 9:24:18, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0314, loss_rpn_bbox: 0.0494, loss_cls: 0.2143, acc: 92.1538, loss_bbox: 0.2588, loss_mask: 0.2525, loss: 0.8063 2023-11-13 17:56:04,093 - mmdet - INFO - Epoch [2][4800/7330] lr: 1.000e-04, eta: 9:23:55, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0290, loss_rpn_bbox: 0.0473, loss_cls: 0.2110, acc: 92.5508, loss_bbox: 0.2485, loss_mask: 0.2442, loss: 0.7800 2023-11-13 17:56:26,294 - mmdet - INFO - Epoch [2][4850/7330] lr: 1.000e-04, eta: 9:23:32, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0445, loss_cls: 0.2114, acc: 92.5312, loss_bbox: 0.2551, loss_mask: 0.2494, loss: 0.7881 2023-11-13 17:56:48,478 - mmdet - INFO - Epoch [2][4900/7330] lr: 1.000e-04, eta: 9:23:09, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0446, loss_cls: 0.2024, acc: 92.7791, loss_bbox: 0.2443, loss_mask: 0.2426, loss: 0.7611 2023-11-13 17:57:10,790 - mmdet - INFO - Epoch [2][4950/7330] lr: 1.000e-04, eta: 9:22:46, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0458, loss_cls: 0.2049, acc: 92.6362, loss_bbox: 0.2505, loss_mask: 0.2428, loss: 0.7736 2023-11-13 17:57:33,247 - mmdet - INFO - Epoch [2][5000/7330] lr: 1.000e-04, eta: 9:22:25, time: 0.449, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0452, loss_cls: 0.2111, acc: 92.6113, loss_bbox: 0.2485, loss_mask: 0.2387, loss: 0.7711 2023-11-13 17:57:55,477 - mmdet - INFO - Epoch [2][5050/7330] lr: 1.000e-04, eta: 9:22:02, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0464, loss_cls: 0.2033, acc: 92.7104, loss_bbox: 0.2505, loss_mask: 0.2487, loss: 0.7781 2023-11-13 17:58:18,061 - mmdet - INFO - Epoch [2][5100/7330] lr: 1.000e-04, eta: 9:21:42, time: 0.452, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0301, loss_rpn_bbox: 0.0482, loss_cls: 0.2113, acc: 92.3262, loss_bbox: 0.2604, loss_mask: 0.2510, loss: 0.8010 2023-11-13 17:58:40,065 - mmdet - INFO - Epoch [2][5150/7330] lr: 1.000e-04, eta: 9:21:17, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0453, loss_cls: 0.2121, acc: 92.4951, loss_bbox: 0.2523, loss_mask: 0.2439, loss: 0.7810 2023-11-13 17:59:02,151 - mmdet - INFO - Epoch [2][5200/7330] lr: 1.000e-04, eta: 9:20:54, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0295, loss_rpn_bbox: 0.0449, loss_cls: 0.2050, acc: 92.5537, loss_bbox: 0.2532, loss_mask: 0.2419, loss: 0.7745 2023-11-13 17:59:24,485 - mmdet - INFO - Epoch [2][5250/7330] lr: 1.000e-04, eta: 9:20:32, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0490, loss_cls: 0.2145, acc: 92.3691, loss_bbox: 0.2658, loss_mask: 0.2507, loss: 0.8084 2023-11-13 17:59:46,879 - mmdet - INFO - Epoch [2][5300/7330] lr: 1.000e-04, eta: 9:20:10, time: 0.448, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0308, loss_rpn_bbox: 0.0506, loss_cls: 0.2221, acc: 92.1174, loss_bbox: 0.2597, loss_mask: 0.2475, loss: 0.8107 2023-11-13 18:00:08,902 - mmdet - INFO - Epoch [2][5350/7330] lr: 1.000e-04, eta: 9:19:46, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0457, loss_cls: 0.2132, acc: 92.4097, loss_bbox: 0.2609, loss_mask: 0.2486, loss: 0.7971 2023-11-13 18:00:30,809 - mmdet - INFO - Epoch [2][5400/7330] lr: 1.000e-04, eta: 9:19:21, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0255, loss_rpn_bbox: 0.0430, loss_cls: 0.1957, acc: 92.9922, loss_bbox: 0.2432, loss_mask: 0.2390, loss: 0.7464 2023-11-13 18:00:53,796 - mmdet - INFO - Epoch [2][5450/7330] lr: 1.000e-04, eta: 9:19:03, time: 0.460, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0481, loss_cls: 0.2099, acc: 92.5513, loss_bbox: 0.2514, loss_mask: 0.2432, loss: 0.7806 2023-11-13 18:01:16,224 - mmdet - INFO - Epoch [2][5500/7330] lr: 1.000e-04, eta: 9:18:41, time: 0.449, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0287, loss_rpn_bbox: 0.0474, loss_cls: 0.2058, acc: 92.7510, loss_bbox: 0.2477, loss_mask: 0.2443, loss: 0.7739 2023-11-13 18:01:37,974 - mmdet - INFO - Epoch [2][5550/7330] lr: 1.000e-04, eta: 9:18:16, time: 0.435, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0440, loss_cls: 0.1969, acc: 92.9644, loss_bbox: 0.2428, loss_mask: 0.2433, loss: 0.7537 2023-11-13 18:02:00,305 - mmdet - INFO - Epoch [2][5600/7330] lr: 1.000e-04, eta: 9:17:53, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0452, loss_cls: 0.1996, acc: 92.7629, loss_bbox: 0.2474, loss_mask: 0.2369, loss: 0.7587 2023-11-13 18:02:22,726 - mmdet - INFO - Epoch [2][5650/7330] lr: 1.000e-04, eta: 9:17:32, time: 0.448, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0473, loss_cls: 0.2157, acc: 92.3035, loss_bbox: 0.2628, loss_mask: 0.2560, loss: 0.8103 2023-11-13 18:02:45,245 - mmdet - INFO - Epoch [2][5700/7330] lr: 1.000e-04, eta: 9:17:11, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0289, loss_rpn_bbox: 0.0470, loss_cls: 0.2106, acc: 92.5400, loss_bbox: 0.2478, loss_mask: 0.2467, loss: 0.7810 2023-11-13 18:03:07,320 - mmdet - INFO - Epoch [2][5750/7330] lr: 1.000e-04, eta: 9:16:47, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0446, loss_cls: 0.1974, acc: 92.9983, loss_bbox: 0.2374, loss_mask: 0.2434, loss: 0.7497 2023-11-13 18:03:29,583 - mmdet - INFO - Epoch [2][5800/7330] lr: 1.000e-04, eta: 9:16:25, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0285, loss_rpn_bbox: 0.0452, loss_cls: 0.2026, acc: 92.7966, loss_bbox: 0.2500, loss_mask: 0.2414, loss: 0.7677 2023-11-13 18:03:51,742 - mmdet - INFO - Epoch [2][5850/7330] lr: 1.000e-04, eta: 9:16:01, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0474, loss_cls: 0.2071, acc: 92.6411, loss_bbox: 0.2510, loss_mask: 0.2492, loss: 0.7827 2023-11-13 18:04:14,067 - mmdet - INFO - Epoch [2][5900/7330] lr: 1.000e-04, eta: 9:15:39, time: 0.447, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0294, loss_rpn_bbox: 0.0477, loss_cls: 0.2049, acc: 92.7542, loss_bbox: 0.2504, loss_mask: 0.2475, loss: 0.7799 2023-11-13 18:04:36,473 - mmdet - INFO - Epoch [2][5950/7330] lr: 1.000e-04, eta: 9:15:17, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0292, loss_rpn_bbox: 0.0471, loss_cls: 0.2064, acc: 92.6719, loss_bbox: 0.2482, loss_mask: 0.2501, loss: 0.7811 2023-11-13 18:04:58,941 - mmdet - INFO - Epoch [2][6000/7330] lr: 1.000e-04, eta: 9:14:56, time: 0.449, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0448, loss_cls: 0.2123, acc: 92.4937, loss_bbox: 0.2530, loss_mask: 0.2451, loss: 0.7818 2023-11-13 18:05:21,362 - mmdet - INFO - Epoch [2][6050/7330] lr: 1.000e-04, eta: 9:14:34, time: 0.448, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0296, loss_rpn_bbox: 0.0459, loss_cls: 0.1990, acc: 92.9604, loss_bbox: 0.2368, loss_mask: 0.2429, loss: 0.7542 2023-11-13 18:05:43,654 - mmdet - INFO - Epoch [2][6100/7330] lr: 1.000e-04, eta: 9:14:12, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0468, loss_cls: 0.2016, acc: 92.7742, loss_bbox: 0.2462, loss_mask: 0.2461, loss: 0.7686 2023-11-13 18:06:05,882 - mmdet - INFO - Epoch [2][6150/7330] lr: 1.000e-04, eta: 9:13:49, time: 0.444, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0297, loss_rpn_bbox: 0.0464, loss_cls: 0.2038, acc: 92.7612, loss_bbox: 0.2450, loss_mask: 0.2454, loss: 0.7702 2023-11-13 18:06:27,990 - mmdet - INFO - Epoch [2][6200/7330] lr: 1.000e-04, eta: 9:13:26, time: 0.442, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0457, loss_cls: 0.2112, acc: 92.3865, loss_bbox: 0.2550, loss_mask: 0.2435, loss: 0.7834 2023-11-13 18:06:50,143 - mmdet - INFO - Epoch [2][6250/7330] lr: 1.000e-04, eta: 9:13:03, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0291, loss_rpn_bbox: 0.0473, loss_cls: 0.2042, acc: 92.6057, loss_bbox: 0.2487, loss_mask: 0.2437, loss: 0.7730 2023-11-13 18:07:12,390 - mmdet - INFO - Epoch [2][6300/7330] lr: 1.000e-04, eta: 9:12:40, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0455, loss_cls: 0.2044, acc: 92.7141, loss_bbox: 0.2531, loss_mask: 0.2441, loss: 0.7740 2023-11-13 18:07:34,505 - mmdet - INFO - Epoch [2][6350/7330] lr: 1.000e-04, eta: 9:12:17, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0273, loss_rpn_bbox: 0.0463, loss_cls: 0.2187, acc: 92.2578, loss_bbox: 0.2594, loss_mask: 0.2495, loss: 0.8013 2023-11-13 18:07:57,036 - mmdet - INFO - Epoch [2][6400/7330] lr: 1.000e-04, eta: 9:11:56, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0293, loss_rpn_bbox: 0.0480, loss_cls: 0.2069, acc: 92.5930, loss_bbox: 0.2536, loss_mask: 0.2527, loss: 0.7905 2023-11-13 18:08:19,212 - mmdet - INFO - Epoch [2][6450/7330] lr: 1.000e-04, eta: 9:11:33, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0438, loss_cls: 0.2011, acc: 92.7913, loss_bbox: 0.2469, loss_mask: 0.2415, loss: 0.7610 2023-11-13 18:08:41,570 - mmdet - INFO - Epoch [2][6500/7330] lr: 1.000e-04, eta: 9:11:10, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0451, loss_cls: 0.2080, acc: 92.5151, loss_bbox: 0.2509, loss_mask: 0.2427, loss: 0.7753 2023-11-13 18:09:03,906 - mmdet - INFO - Epoch [2][6550/7330] lr: 1.000e-04, eta: 9:10:48, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0280, loss_rpn_bbox: 0.0482, loss_cls: 0.2052, acc: 92.6599, loss_bbox: 0.2430, loss_mask: 0.2421, loss: 0.7664 2023-11-13 18:09:26,239 - mmdet - INFO - Epoch [2][6600/7330] lr: 1.000e-04, eta: 9:10:26, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0286, loss_rpn_bbox: 0.0456, loss_cls: 0.2075, acc: 92.6079, loss_bbox: 0.2473, loss_mask: 0.2448, loss: 0.7737 2023-11-13 18:09:48,279 - mmdet - INFO - Epoch [2][6650/7330] lr: 1.000e-04, eta: 9:10:02, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0326, loss_rpn_bbox: 0.0477, loss_cls: 0.2102, acc: 92.4006, loss_bbox: 0.2585, loss_mask: 0.2507, loss: 0.7999 2023-11-13 18:10:10,449 - mmdet - INFO - Epoch [2][6700/7330] lr: 1.000e-04, eta: 9:09:39, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0444, loss_cls: 0.1995, acc: 92.8870, loss_bbox: 0.2338, loss_mask: 0.2392, loss: 0.7445 2023-11-13 18:10:32,680 - mmdet - INFO - Epoch [2][6750/7330] lr: 1.000e-04, eta: 9:09:17, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0284, loss_rpn_bbox: 0.0447, loss_cls: 0.2184, acc: 92.3093, loss_bbox: 0.2496, loss_mask: 0.2416, loss: 0.7827 2023-11-13 18:10:54,571 - mmdet - INFO - Epoch [2][6800/7330] lr: 1.000e-04, eta: 9:08:52, time: 0.438, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0281, loss_rpn_bbox: 0.0472, loss_cls: 0.2087, acc: 92.5630, loss_bbox: 0.2508, loss_mask: 0.2462, loss: 0.7811 2023-11-13 18:11:17,661 - mmdet - INFO - Epoch [2][6850/7330] lr: 1.000e-04, eta: 9:08:34, time: 0.462, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0279, loss_rpn_bbox: 0.0469, loss_cls: 0.2164, acc: 92.3130, loss_bbox: 0.2548, loss_mask: 0.2476, loss: 0.7936 2023-11-13 18:11:39,939 - mmdet - INFO - Epoch [2][6900/7330] lr: 1.000e-04, eta: 9:08:12, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0475, loss_cls: 0.1964, acc: 93.0076, loss_bbox: 0.2395, loss_mask: 0.2415, loss: 0.7512 2023-11-13 18:12:02,128 - mmdet - INFO - Epoch [2][6950/7330] lr: 1.000e-04, eta: 9:07:49, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0460, loss_cls: 0.2031, acc: 92.7761, loss_bbox: 0.2478, loss_mask: 0.2502, loss: 0.7740 2023-11-13 18:12:24,530 - mmdet - INFO - Epoch [2][7000/7330] lr: 1.000e-04, eta: 9:07:27, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0460, loss_cls: 0.2035, acc: 92.7229, loss_bbox: 0.2466, loss_mask: 0.2490, loss: 0.7752 2023-11-13 18:12:46,885 - mmdet - INFO - Epoch [2][7050/7330] lr: 1.000e-04, eta: 9:07:05, time: 0.447, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0467, loss_cls: 0.2034, acc: 92.7603, loss_bbox: 0.2441, loss_mask: 0.2390, loss: 0.7601 2023-11-13 18:13:09,399 - mmdet - INFO - Epoch [2][7100/7330] lr: 1.000e-04, eta: 9:06:44, time: 0.450, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0459, loss_cls: 0.2051, acc: 92.6506, loss_bbox: 0.2466, loss_mask: 0.2437, loss: 0.7678 2023-11-13 18:13:31,795 - mmdet - INFO - Epoch [2][7150/7330] lr: 1.000e-04, eta: 9:06:22, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0302, loss_rpn_bbox: 0.0450, loss_cls: 0.2052, acc: 92.7202, loss_bbox: 0.2483, loss_mask: 0.2464, loss: 0.7752 2023-11-13 18:13:54,501 - mmdet - INFO - Epoch [2][7200/7330] lr: 1.000e-04, eta: 9:06:01, time: 0.454, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0476, loss_cls: 0.2088, acc: 92.4570, loss_bbox: 0.2572, loss_mask: 0.2468, loss: 0.7864 2023-11-13 18:14:16,361 - mmdet - INFO - Epoch [2][7250/7330] lr: 1.000e-04, eta: 9:05:37, time: 0.437, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0445, loss_cls: 0.2071, acc: 92.5469, loss_bbox: 0.2559, loss_mask: 0.2486, loss: 0.7826 2023-11-13 18:14:38,375 - mmdet - INFO - Epoch [2][7300/7330] lr: 1.000e-04, eta: 9:05:13, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0443, loss_cls: 0.1982, acc: 92.9392, loss_bbox: 0.2388, loss_mask: 0.2414, loss: 0.7476 2023-11-13 18:14:52,286 - mmdet - INFO - Saving checkpoint at 2 epochs 2023-11-13 18:15:45,648 - mmdet - INFO - Evaluating bbox... 2023-11-13 18:16:18,784 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.430 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.664 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.476 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.275 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.471 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.564 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.560 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.560 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.560 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.602 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.706 2023-11-13 18:16:18,787 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.545 | bicycle | 0.330 | car | 0.444 | | motorcycle | 0.432 | airplane | 0.680 | bus | 0.634 | | train | 0.658 | truck | 0.407 | boat | 0.285 | | traffic light | 0.290 | fire hydrant | 0.661 | stop sign | 0.646 | | parking meter | 0.456 | bench | 0.236 | bird | 0.384 | | cat | 0.678 | dog | 0.650 | horse | 0.573 | | sheep | 0.511 | cow | 0.581 | elephant | 0.673 | | bear | 0.707 | zebra | 0.631 | giraffe | 0.654 | | backpack | 0.191 | umbrella | 0.412 | handbag | 0.193 | | tie | 0.313 | suitcase | 0.406 | frisbee | 0.680 | | skis | 0.244 | snowboard | 0.372 | sports ball | 0.443 | | kite | 0.422 | baseball bat | 0.351 | baseball glove | 0.386 | | skateboard | 0.516 | surfboard | 0.401 | tennis racket | 0.508 | | bottle | 0.428 | wine glass | 0.376 | cup | 0.461 | | fork | 0.360 | knife | 0.202 | spoon | 0.231 | | bowl | 0.432 | banana | 0.252 | apple | 0.226 | | sandwich | 0.385 | orange | 0.326 | broccoli | 0.237 | | carrot | 0.228 | hot dog | 0.384 | pizza | 0.516 | | donut | 0.506 | cake | 0.400 | chair | 0.317 | | couch | 0.375 | potted plant | 0.312 | bed | 0.464 | | dining table | 0.277 | toilet | 0.578 | tv | 0.591 | | laptop | 0.610 | mouse | 0.594 | remote | 0.348 | | keyboard | 0.482 | cell phone | 0.420 | microwave | 0.551 | | oven | 0.345 | toaster | 0.347 | sink | 0.368 | | refrigerator | 0.556 | book | 0.157 | clock | 0.513 | | vase | 0.405 | scissors | 0.341 | teddy bear | 0.510 | | hair drier | 0.152 | toothbrush | 0.235 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:16:18,787 - mmdet - INFO - Evaluating segm... 2023-11-13 18:16:53,774 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.394 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.630 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.423 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.207 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.430 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.571 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.516 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.516 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.516 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.330 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.560 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.670 2023-11-13 18:16:53,776 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.472 | bicycle | 0.199 | car | 0.411 | | motorcycle | 0.345 | airplane | 0.532 | bus | 0.640 | | train | 0.648 | truck | 0.406 | boat | 0.264 | | traffic light | 0.286 | fire hydrant | 0.653 | stop sign | 0.664 | | parking meter | 0.488 | bench | 0.189 | bird | 0.328 | | cat | 0.697 | dog | 0.611 | horse | 0.417 | | sheep | 0.465 | cow | 0.484 | elephant | 0.603 | | bear | 0.705 | zebra | 0.537 | giraffe | 0.502 | | backpack | 0.197 | umbrella | 0.487 | handbag | 0.199 | | tie | 0.308 | suitcase | 0.433 | frisbee | 0.664 | | skis | 0.031 | snowboard | 0.247 | sports ball | 0.455 | | kite | 0.302 | baseball bat | 0.258 | baseball glove | 0.435 | | skateboard | 0.329 | surfboard | 0.341 | tennis racket | 0.565 | | bottle | 0.418 | wine glass | 0.338 | cup | 0.466 | | fork | 0.161 | knife | 0.140 | spoon | 0.161 | | bowl | 0.409 | banana | 0.187 | apple | 0.221 | | sandwich | 0.421 | orange | 0.330 | broccoli | 0.215 | | carrot | 0.188 | hot dog | 0.326 | pizza | 0.498 | | donut | 0.518 | cake | 0.424 | chair | 0.229 | | couch | 0.320 | potted plant | 0.257 | bed | 0.367 | | dining table | 0.159 | toilet | 0.585 | tv | 0.620 | | laptop | 0.619 | mouse | 0.616 | remote | 0.304 | | keyboard | 0.496 | cell phone | 0.396 | microwave | 0.617 | | oven | 0.337 | toaster | 0.394 | sink | 0.390 | | refrigerator | 0.581 | book | 0.108 | clock | 0.520 | | vase | 0.400 | scissors | 0.251 | teddy bear | 0.477 | | hair drier | 0.110 | toothbrush | 0.140 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 18:16:54,265 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_1.pth was removed 2023-11-13 18:16:57,591 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_2.pth. 2023-11-13 18:16:57,591 - mmdet - INFO - Best bbox_mAP is 0.4297 at 2 epoch. 2023-11-13 18:16:57,592 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 18:16:57,592 - mmdet - INFO - Epoch(val) [2][625] bbox_mAP: 0.4297, bbox_mAP_50: 0.6642, bbox_mAP_75: 0.4755, bbox_mAP_s: 0.2752, bbox_mAP_m: 0.4709, bbox_mAP_l: 0.5639, bbox_mAP_copypaste: 0.4297 0.6642 0.4755 0.2752 0.4709 0.5639, segm_mAP: 0.3939, segm_mAP_50: 0.6296, segm_mAP_75: 0.4228, segm_mAP_s: 0.2069, segm_mAP_m: 0.4295, segm_mAP_l: 0.5711, segm_mAP_copypaste: 0.3939 0.6296 0.4228 0.2069 0.4295 0.5711 2023-11-13 18:17:23,867 - mmdet - INFO - Epoch [3][50/7330] lr: 1.000e-04, eta: 9:03:50, time: 0.525, data_time: 0.089, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0458, loss_cls: 0.1983, acc: 92.7234, loss_bbox: 0.2489, loss_mask: 0.2425, loss: 0.7626 2023-11-13 18:17:46,655 - mmdet - INFO - Epoch [3][100/7330] lr: 1.000e-04, eta: 9:03:31, time: 0.456, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0470, loss_cls: 0.2069, acc: 92.4084, loss_bbox: 0.2562, loss_mask: 0.2435, loss: 0.7788 2023-11-13 18:18:09,508 - mmdet - INFO - Epoch [3][150/7330] lr: 1.000e-04, eta: 9:03:11, time: 0.457, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0457, loss_cls: 0.1953, acc: 92.9907, loss_bbox: 0.2390, loss_mask: 0.2362, loss: 0.7428 2023-11-13 18:18:32,291 - mmdet - INFO - Epoch [3][200/7330] lr: 1.000e-04, eta: 9:02:52, time: 0.456, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0467, loss_cls: 0.1956, acc: 92.8489, loss_bbox: 0.2420, loss_mask: 0.2383, loss: 0.7471 2023-11-13 18:18:54,877 - mmdet - INFO - Epoch [3][250/7330] lr: 1.000e-04, eta: 9:02:31, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0451, loss_cls: 0.1927, acc: 93.0674, loss_bbox: 0.2373, loss_mask: 0.2378, loss: 0.7386 2023-11-13 18:19:17,657 - mmdet - INFO - Epoch [3][300/7330] lr: 1.000e-04, eta: 9:02:11, time: 0.456, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0471, loss_cls: 0.1975, acc: 92.6421, loss_bbox: 0.2487, loss_mask: 0.2404, loss: 0.7584 2023-11-13 18:19:40,114 - mmdet - INFO - Epoch [3][350/7330] lr: 1.000e-04, eta: 9:01:49, time: 0.449, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0451, loss_cls: 0.1909, acc: 93.0791, loss_bbox: 0.2366, loss_mask: 0.2400, loss: 0.7376 2023-11-13 18:20:02,360 - mmdet - INFO - Epoch [3][400/7330] lr: 1.000e-04, eta: 9:01:27, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0444, loss_cls: 0.1881, acc: 93.0938, loss_bbox: 0.2438, loss_mask: 0.2403, loss: 0.7414 2023-11-13 18:20:24,771 - mmdet - INFO - Epoch [3][450/7330] lr: 1.000e-04, eta: 9:01:05, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0440, loss_cls: 0.1874, acc: 93.1960, loss_bbox: 0.2401, loss_mask: 0.2409, loss: 0.7374 2023-11-13 18:20:47,057 - mmdet - INFO - Epoch [3][500/7330] lr: 1.000e-04, eta: 9:00:43, time: 0.446, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0439, loss_cls: 0.1876, acc: 93.1484, loss_bbox: 0.2341, loss_mask: 0.2364, loss: 0.7265 2023-11-13 18:21:09,369 - mmdet - INFO - Epoch [3][550/7330] lr: 1.000e-04, eta: 9:00:21, time: 0.446, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0460, loss_cls: 0.1924, acc: 92.9443, loss_bbox: 0.2428, loss_mask: 0.2461, loss: 0.7539 2023-11-13 18:21:31,787 - mmdet - INFO - Epoch [3][600/7330] lr: 1.000e-04, eta: 8:59:59, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0454, loss_cls: 0.1979, acc: 92.8188, loss_bbox: 0.2431, loss_mask: 0.2376, loss: 0.7484 2023-11-13 18:21:54,480 - mmdet - INFO - Epoch [3][650/7330] lr: 1.000e-04, eta: 8:59:39, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0475, loss_cls: 0.2002, acc: 92.7539, loss_bbox: 0.2439, loss_mask: 0.2441, loss: 0.7620 2023-11-13 18:22:17,052 - mmdet - INFO - Epoch [3][700/7330] lr: 1.000e-04, eta: 8:59:18, time: 0.451, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0459, loss_cls: 0.1951, acc: 92.8135, loss_bbox: 0.2465, loss_mask: 0.2418, loss: 0.7560 2023-11-13 18:22:38,975 - mmdet - INFO - Epoch [3][750/7330] lr: 1.000e-04, eta: 8:58:54, time: 0.438, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0402, loss_cls: 0.1769, acc: 93.4612, loss_bbox: 0.2211, loss_mask: 0.2308, loss: 0.6926 2023-11-13 18:23:01,661 - mmdet - INFO - Epoch [3][800/7330] lr: 1.000e-04, eta: 8:58:34, time: 0.454, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0468, loss_cls: 0.1926, acc: 93.0005, loss_bbox: 0.2450, loss_mask: 0.2445, loss: 0.7554 2023-11-13 18:23:23,990 - mmdet - INFO - Epoch [3][850/7330] lr: 1.000e-04, eta: 8:58:12, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0419, loss_cls: 0.1857, acc: 93.2251, loss_bbox: 0.2334, loss_mask: 0.2310, loss: 0.7151 2023-11-13 18:23:46,632 - mmdet - INFO - Epoch [3][900/7330] lr: 1.000e-04, eta: 8:57:51, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0445, loss_cls: 0.1883, acc: 93.1482, loss_bbox: 0.2381, loss_mask: 0.2282, loss: 0.7239 2023-11-13 18:24:09,018 - mmdet - INFO - Epoch [3][950/7330] lr: 1.000e-04, eta: 8:57:29, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0434, loss_cls: 0.1903, acc: 92.9153, loss_bbox: 0.2380, loss_mask: 0.2363, loss: 0.7309 2023-11-13 18:24:32,005 - mmdet - INFO - Epoch [3][1000/7330] lr: 1.000e-04, eta: 8:57:10, time: 0.460, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0484, loss_cls: 0.2006, acc: 92.7683, loss_bbox: 0.2533, loss_mask: 0.2400, loss: 0.7675 2023-11-13 18:24:54,437 - mmdet - INFO - Epoch [3][1050/7330] lr: 1.000e-04, eta: 8:56:48, time: 0.449, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0274, loss_rpn_bbox: 0.0460, loss_cls: 0.1984, acc: 92.7539, loss_bbox: 0.2521, loss_mask: 0.2439, loss: 0.7678 2023-11-13 18:25:16,985 - mmdet - INFO - Epoch [3][1100/7330] lr: 1.000e-04, eta: 8:56:27, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0469, loss_cls: 0.1972, acc: 92.7805, loss_bbox: 0.2479, loss_mask: 0.2375, loss: 0.7565 2023-11-13 18:25:39,177 - mmdet - INFO - Epoch [3][1150/7330] lr: 1.000e-04, eta: 8:56:05, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0453, loss_cls: 0.1989, acc: 92.7610, loss_bbox: 0.2481, loss_mask: 0.2427, loss: 0.7615 2023-11-13 18:26:01,475 - mmdet - INFO - Epoch [3][1200/7330] lr: 1.000e-04, eta: 8:55:42, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0461, loss_cls: 0.1901, acc: 93.0244, loss_bbox: 0.2402, loss_mask: 0.2371, loss: 0.7387 2023-11-13 18:26:23,773 - mmdet - INFO - Epoch [3][1250/7330] lr: 1.000e-04, eta: 8:55:20, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0463, loss_cls: 0.1975, acc: 92.7747, loss_bbox: 0.2455, loss_mask: 0.2384, loss: 0.7542 2023-11-13 18:26:46,112 - mmdet - INFO - Epoch [3][1300/7330] lr: 1.000e-04, eta: 8:54:58, time: 0.447, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0438, loss_cls: 0.1948, acc: 92.9375, loss_bbox: 0.2447, loss_mask: 0.2342, loss: 0.7411 2023-11-13 18:27:08,561 - mmdet - INFO - Epoch [3][1350/7330] lr: 1.000e-04, eta: 8:54:36, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0448, loss_cls: 0.1925, acc: 92.9631, loss_bbox: 0.2459, loss_mask: 0.2345, loss: 0.7434 2023-11-13 18:27:30,723 - mmdet - INFO - Epoch [3][1400/7330] lr: 1.000e-04, eta: 8:54:13, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0456, loss_cls: 0.1938, acc: 93.0156, loss_bbox: 0.2415, loss_mask: 0.2363, loss: 0.7424 2023-11-13 18:27:52,921 - mmdet - INFO - Epoch [3][1450/7330] lr: 1.000e-04, eta: 8:53:51, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0432, loss_cls: 0.1961, acc: 92.8682, loss_bbox: 0.2407, loss_mask: 0.2363, loss: 0.7406 2023-11-13 18:28:15,421 - mmdet - INFO - Epoch [3][1500/7330] lr: 1.000e-04, eta: 8:53:29, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0432, loss_cls: 0.1875, acc: 93.2163, loss_bbox: 0.2344, loss_mask: 0.2387, loss: 0.7289 2023-11-13 18:28:37,635 - mmdet - INFO - Epoch [3][1550/7330] lr: 1.000e-04, eta: 8:53:07, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0451, loss_cls: 0.1986, acc: 92.7163, loss_bbox: 0.2474, loss_mask: 0.2428, loss: 0.7588 2023-11-13 18:29:00,362 - mmdet - INFO - Epoch [3][1600/7330] lr: 1.000e-04, eta: 8:52:46, time: 0.454, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0259, loss_rpn_bbox: 0.0435, loss_cls: 0.1876, acc: 93.1433, loss_bbox: 0.2324, loss_mask: 0.2367, loss: 0.7262 2023-11-13 18:29:22,719 - mmdet - INFO - Epoch [3][1650/7330] lr: 1.000e-04, eta: 8:52:24, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0437, loss_cls: 0.1962, acc: 92.8850, loss_bbox: 0.2457, loss_mask: 0.2375, loss: 0.7493 2023-11-13 18:29:45,122 - mmdet - INFO - Epoch [3][1700/7330] lr: 1.000e-04, eta: 8:52:03, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0440, loss_cls: 0.1907, acc: 93.0745, loss_bbox: 0.2374, loss_mask: 0.2312, loss: 0.7268 2023-11-13 18:30:07,321 - mmdet - INFO - Epoch [3][1750/7330] lr: 1.000e-04, eta: 8:51:40, time: 0.444, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0434, loss_cls: 0.1901, acc: 93.1045, loss_bbox: 0.2386, loss_mask: 0.2342, loss: 0.7331 2023-11-13 18:30:29,593 - mmdet - INFO - Epoch [3][1800/7330] lr: 1.000e-04, eta: 8:51:17, time: 0.445, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0418, loss_cls: 0.1876, acc: 93.1865, loss_bbox: 0.2287, loss_mask: 0.2291, loss: 0.7110 2023-11-13 18:30:51,907 - mmdet - INFO - Epoch [3][1850/7330] lr: 1.000e-04, eta: 8:50:55, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0431, loss_cls: 0.1910, acc: 93.0750, loss_bbox: 0.2325, loss_mask: 0.2412, loss: 0.7306 2023-11-13 18:31:14,285 - mmdet - INFO - Epoch [3][1900/7330] lr: 1.000e-04, eta: 8:50:33, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0268, loss_rpn_bbox: 0.0471, loss_cls: 0.1977, acc: 92.8018, loss_bbox: 0.2470, loss_mask: 0.2389, loss: 0.7576 2023-11-13 18:31:36,635 - mmdet - INFO - Epoch [3][1950/7330] lr: 1.000e-04, eta: 8:50:11, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0452, loss_cls: 0.1881, acc: 93.1699, loss_bbox: 0.2332, loss_mask: 0.2408, loss: 0.7306 2023-11-13 18:31:59,154 - mmdet - INFO - Epoch [3][2000/7330] lr: 1.000e-04, eta: 8:49:50, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0253, loss_rpn_bbox: 0.0448, loss_cls: 0.1867, acc: 93.2832, loss_bbox: 0.2327, loss_mask: 0.2356, loss: 0.7251 2023-11-13 18:32:21,642 - mmdet - INFO - Epoch [3][2050/7330] lr: 1.000e-04, eta: 8:49:29, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0446, loss_cls: 0.2046, acc: 92.6125, loss_bbox: 0.2510, loss_mask: 0.2423, loss: 0.7682 2023-11-13 18:32:43,994 - mmdet - INFO - Epoch [3][2100/7330] lr: 1.000e-04, eta: 8:49:06, time: 0.447, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0426, loss_cls: 0.1875, acc: 93.0881, loss_bbox: 0.2389, loss_mask: 0.2383, loss: 0.7316 2023-11-13 18:33:06,415 - mmdet - INFO - Epoch [3][2150/7330] lr: 1.000e-04, eta: 8:48:45, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0474, loss_cls: 0.1902, acc: 93.0530, loss_bbox: 0.2503, loss_mask: 0.2433, loss: 0.7563 2023-11-13 18:33:28,537 - mmdet - INFO - Epoch [3][2200/7330] lr: 1.000e-04, eta: 8:48:22, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0436, loss_cls: 0.1978, acc: 92.7686, loss_bbox: 0.2452, loss_mask: 0.2375, loss: 0.7481 2023-11-13 18:33:50,946 - mmdet - INFO - Epoch [3][2250/7330] lr: 1.000e-04, eta: 8:48:00, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0450, loss_cls: 0.1900, acc: 93.1055, loss_bbox: 0.2374, loss_mask: 0.2349, loss: 0.7321 2023-11-13 18:34:13,627 - mmdet - INFO - Epoch [3][2300/7330] lr: 1.000e-04, eta: 8:47:39, time: 0.454, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0454, loss_cls: 0.1919, acc: 92.9436, loss_bbox: 0.2414, loss_mask: 0.2425, loss: 0.7464 2023-11-13 18:34:36,021 - mmdet - INFO - Epoch [3][2350/7330] lr: 1.000e-04, eta: 8:47:17, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0444, loss_cls: 0.1911, acc: 93.1025, loss_bbox: 0.2370, loss_mask: 0.2484, loss: 0.7452 2023-11-13 18:34:58,581 - mmdet - INFO - Epoch [3][2400/7330] lr: 1.000e-04, eta: 8:46:56, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0459, loss_cls: 0.1982, acc: 92.6658, loss_bbox: 0.2450, loss_mask: 0.2397, loss: 0.7552 2023-11-13 18:35:20,445 - mmdet - INFO - Epoch [3][2450/7330] lr: 1.000e-04, eta: 8:46:32, time: 0.437, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0433, loss_cls: 0.1861, acc: 93.2695, loss_bbox: 0.2347, loss_mask: 0.2342, loss: 0.7216 2023-11-13 18:35:42,726 - mmdet - INFO - Epoch [3][2500/7330] lr: 1.000e-04, eta: 8:46:10, time: 0.446, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0443, loss_cls: 0.1898, acc: 93.0920, loss_bbox: 0.2376, loss_mask: 0.2372, loss: 0.7347 2023-11-13 18:36:05,190 - mmdet - INFO - Epoch [3][2550/7330] lr: 1.000e-04, eta: 8:45:48, time: 0.449, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0458, loss_cls: 0.1877, acc: 93.0708, loss_bbox: 0.2409, loss_mask: 0.2364, loss: 0.7371 2023-11-13 18:36:27,508 - mmdet - INFO - Epoch [3][2600/7330] lr: 1.000e-04, eta: 8:45:26, time: 0.446, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0427, loss_cls: 0.1973, acc: 92.7874, loss_bbox: 0.2466, loss_mask: 0.2390, loss: 0.7504 2023-11-13 18:36:49,906 - mmdet - INFO - Epoch [3][2650/7330] lr: 1.000e-04, eta: 8:45:04, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0448, loss_cls: 0.1840, acc: 93.2556, loss_bbox: 0.2372, loss_mask: 0.2424, loss: 0.7330 2023-11-13 18:37:12,550 - mmdet - INFO - Epoch [3][2700/7330] lr: 1.000e-04, eta: 8:44:43, time: 0.453, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0481, loss_cls: 0.2035, acc: 92.5769, loss_bbox: 0.2465, loss_mask: 0.2440, loss: 0.7698 2023-11-13 18:37:34,788 - mmdet - INFO - Epoch [3][2750/7330] lr: 1.000e-04, eta: 8:44:21, time: 0.445, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0266, loss_rpn_bbox: 0.0428, loss_cls: 0.1898, acc: 93.0369, loss_bbox: 0.2352, loss_mask: 0.2383, loss: 0.7327 2023-11-13 18:37:57,054 - mmdet - INFO - Epoch [3][2800/7330] lr: 1.000e-04, eta: 8:43:58, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0423, loss_cls: 0.1870, acc: 93.0674, loss_bbox: 0.2396, loss_mask: 0.2357, loss: 0.7276 2023-11-13 18:38:19,219 - mmdet - INFO - Epoch [3][2850/7330] lr: 1.000e-04, eta: 8:43:35, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0262, loss_rpn_bbox: 0.0452, loss_cls: 0.1898, acc: 93.1008, loss_bbox: 0.2392, loss_mask: 0.2424, loss: 0.7427 2023-11-13 18:38:41,598 - mmdet - INFO - Epoch [3][2900/7330] lr: 1.000e-04, eta: 8:43:13, time: 0.448, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0407, loss_cls: 0.1780, acc: 93.4832, loss_bbox: 0.2249, loss_mask: 0.2347, loss: 0.7012 2023-11-13 18:39:03,633 - mmdet - INFO - Epoch [3][2950/7330] lr: 1.000e-04, eta: 8:42:50, time: 0.441, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0408, loss_cls: 0.1858, acc: 93.2769, loss_bbox: 0.2313, loss_mask: 0.2343, loss: 0.7146 2023-11-13 18:39:26,151 - mmdet - INFO - Epoch [3][3000/7330] lr: 1.000e-04, eta: 8:42:29, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0263, loss_rpn_bbox: 0.0435, loss_cls: 0.1962, acc: 92.9001, loss_bbox: 0.2431, loss_mask: 0.2428, loss: 0.7519 2023-11-13 18:39:48,258 - mmdet - INFO - Epoch [3][3050/7330] lr: 1.000e-04, eta: 8:42:06, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0435, loss_cls: 0.1884, acc: 93.1682, loss_bbox: 0.2300, loss_mask: 0.2306, loss: 0.7163 2023-11-13 18:40:10,936 - mmdet - INFO - Epoch [3][3100/7330] lr: 1.000e-04, eta: 8:41:45, time: 0.454, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0246, loss_rpn_bbox: 0.0444, loss_cls: 0.1861, acc: 93.4160, loss_bbox: 0.2243, loss_mask: 0.2265, loss: 0.7060 2023-11-13 18:40:33,224 - mmdet - INFO - Epoch [3][3150/7330] lr: 1.000e-04, eta: 8:41:22, time: 0.446, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0456, loss_cls: 0.1940, acc: 92.9924, loss_bbox: 0.2373, loss_mask: 0.2334, loss: 0.7359 2023-11-13 18:40:55,487 - mmdet - INFO - Epoch [3][3200/7330] lr: 1.000e-04, eta: 8:41:00, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0269, loss_rpn_bbox: 0.0459, loss_cls: 0.1994, acc: 92.5752, loss_bbox: 0.2477, loss_mask: 0.2423, loss: 0.7623 2023-11-13 18:41:17,782 - mmdet - INFO - Epoch [3][3250/7330] lr: 1.000e-04, eta: 8:40:38, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0439, loss_cls: 0.1906, acc: 93.1909, loss_bbox: 0.2317, loss_mask: 0.2391, loss: 0.7313 2023-11-13 18:41:39,949 - mmdet - INFO - Epoch [3][3300/7330] lr: 1.000e-04, eta: 8:40:15, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0233, loss_rpn_bbox: 0.0421, loss_cls: 0.1804, acc: 93.4309, loss_bbox: 0.2266, loss_mask: 0.2374, loss: 0.7098 2023-11-13 18:42:02,300 - mmdet - INFO - Epoch [3][3350/7330] lr: 1.000e-04, eta: 8:39:53, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0472, loss_cls: 0.1977, acc: 92.8257, loss_bbox: 0.2433, loss_mask: 0.2387, loss: 0.7520 2023-11-13 18:42:24,999 - mmdet - INFO - Epoch [3][3400/7330] lr: 1.000e-04, eta: 8:39:32, time: 0.454, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0472, loss_cls: 0.2025, acc: 92.6799, loss_bbox: 0.2492, loss_mask: 0.2362, loss: 0.7612 2023-11-13 18:42:47,478 - mmdet - INFO - Epoch [3][3450/7330] lr: 1.000e-04, eta: 8:39:10, time: 0.450, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0244, loss_rpn_bbox: 0.0456, loss_cls: 0.1961, acc: 92.8914, loss_bbox: 0.2403, loss_mask: 0.2324, loss: 0.7387 2023-11-13 18:43:10,071 - mmdet - INFO - Epoch [3][3500/7330] lr: 1.000e-04, eta: 8:38:49, time: 0.452, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0471, loss_cls: 0.1944, acc: 92.9839, loss_bbox: 0.2376, loss_mask: 0.2380, loss: 0.7421 2023-11-13 18:43:32,200 - mmdet - INFO - Epoch [3][3550/7330] lr: 1.000e-04, eta: 8:38:26, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0443, loss_cls: 0.1963, acc: 92.9246, loss_bbox: 0.2419, loss_mask: 0.2314, loss: 0.7395 2023-11-13 18:43:54,193 - mmdet - INFO - Epoch [3][3600/7330] lr: 1.000e-04, eta: 8:38:03, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0414, loss_cls: 0.1907, acc: 93.1299, loss_bbox: 0.2357, loss_mask: 0.2335, loss: 0.7256 2023-11-13 18:44:16,884 - mmdet - INFO - Epoch [3][3650/7330] lr: 1.000e-04, eta: 8:37:42, time: 0.454, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0450, loss_cls: 0.2045, acc: 92.6428, loss_bbox: 0.2463, loss_mask: 0.2419, loss: 0.7619 2023-11-13 18:44:38,963 - mmdet - INFO - Epoch [3][3700/7330] lr: 1.000e-04, eta: 8:37:19, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0437, loss_cls: 0.1915, acc: 93.1516, loss_bbox: 0.2363, loss_mask: 0.2332, loss: 0.7285 2023-11-13 18:45:01,497 - mmdet - INFO - Epoch [3][3750/7330] lr: 1.000e-04, eta: 8:36:57, time: 0.451, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0455, loss_cls: 0.1932, acc: 92.8982, loss_bbox: 0.2471, loss_mask: 0.2345, loss: 0.7462 2023-11-13 18:45:23,661 - mmdet - INFO - Epoch [3][3800/7330] lr: 1.000e-04, eta: 8:36:35, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0383, loss_cls: 0.1812, acc: 93.5356, loss_bbox: 0.2204, loss_mask: 0.2254, loss: 0.6867 2023-11-13 18:45:45,631 - mmdet - INFO - Epoch [3][3850/7330] lr: 1.000e-04, eta: 8:36:11, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0447, loss_cls: 0.1924, acc: 93.0344, loss_bbox: 0.2387, loss_mask: 0.2369, loss: 0.7375 2023-11-13 18:46:08,214 - mmdet - INFO - Epoch [3][3900/7330] lr: 1.000e-04, eta: 8:35:50, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0443, loss_cls: 0.1914, acc: 93.0227, loss_bbox: 0.2394, loss_mask: 0.2372, loss: 0.7372 2023-11-13 18:46:30,460 - mmdet - INFO - Epoch [3][3950/7330] lr: 1.000e-04, eta: 8:35:27, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0452, loss_cls: 0.1925, acc: 92.8640, loss_bbox: 0.2426, loss_mask: 0.2407, loss: 0.7447 2023-11-13 18:46:52,721 - mmdet - INFO - Epoch [3][4000/7330] lr: 1.000e-04, eta: 8:35:05, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0424, loss_cls: 0.1973, acc: 92.7688, loss_bbox: 0.2455, loss_mask: 0.2372, loss: 0.7464 2023-11-13 18:47:14,932 - mmdet - INFO - Epoch [3][4050/7330] lr: 1.000e-04, eta: 8:34:42, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0446, loss_cls: 0.1937, acc: 93.0286, loss_bbox: 0.2397, loss_mask: 0.2434, loss: 0.7449 2023-11-13 18:47:37,097 - mmdet - INFO - Epoch [3][4100/7330] lr: 1.000e-04, eta: 8:34:20, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0419, loss_cls: 0.1835, acc: 93.3213, loss_bbox: 0.2250, loss_mask: 0.2317, loss: 0.7058 2023-11-13 18:47:59,381 - mmdet - INFO - Epoch [3][4150/7330] lr: 1.000e-04, eta: 8:33:57, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0449, loss_cls: 0.1914, acc: 93.1274, loss_bbox: 0.2325, loss_mask: 0.2333, loss: 0.7298 2023-11-13 18:48:21,256 - mmdet - INFO - Epoch [3][4200/7330] lr: 1.000e-04, eta: 8:33:33, time: 0.437, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0410, loss_cls: 0.1880, acc: 93.2781, loss_bbox: 0.2347, loss_mask: 0.2302, loss: 0.7176 2023-11-13 18:48:43,352 - mmdet - INFO - Epoch [3][4250/7330] lr: 1.000e-04, eta: 8:33:10, time: 0.442, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0447, loss_cls: 0.1962, acc: 92.8538, loss_bbox: 0.2409, loss_mask: 0.2315, loss: 0.7384 2023-11-13 18:49:05,582 - mmdet - INFO - Epoch [3][4300/7330] lr: 1.000e-04, eta: 8:32:48, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0264, loss_rpn_bbox: 0.0452, loss_cls: 0.1976, acc: 92.8086, loss_bbox: 0.2491, loss_mask: 0.2427, loss: 0.7610 2023-11-13 18:49:27,995 - mmdet - INFO - Epoch [3][4350/7330] lr: 1.000e-04, eta: 8:32:26, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0432, loss_cls: 0.1970, acc: 92.9426, loss_bbox: 0.2386, loss_mask: 0.2301, loss: 0.7337 2023-11-13 18:49:50,473 - mmdet - INFO - Epoch [3][4400/7330] lr: 1.000e-04, eta: 8:32:04, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0276, loss_rpn_bbox: 0.0449, loss_cls: 0.1913, acc: 93.0698, loss_bbox: 0.2378, loss_mask: 0.2360, loss: 0.7376 2023-11-13 18:50:12,888 - mmdet - INFO - Epoch [3][4450/7330] lr: 1.000e-04, eta: 8:31:42, time: 0.448, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0458, loss_cls: 0.1987, acc: 92.7083, loss_bbox: 0.2474, loss_mask: 0.2338, loss: 0.7506 2023-11-13 18:50:35,181 - mmdet - INFO - Epoch [3][4500/7330] lr: 1.000e-04, eta: 8:31:20, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0432, loss_cls: 0.1922, acc: 93.0364, loss_bbox: 0.2375, loss_mask: 0.2307, loss: 0.7286 2023-11-13 18:50:57,252 - mmdet - INFO - Epoch [3][4550/7330] lr: 1.000e-04, eta: 8:30:57, time: 0.441, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0436, loss_cls: 0.1834, acc: 93.3616, loss_bbox: 0.2290, loss_mask: 0.2309, loss: 0.7106 2023-11-13 18:51:19,487 - mmdet - INFO - Epoch [3][4600/7330] lr: 1.000e-04, eta: 8:30:34, time: 0.445, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0450, loss_cls: 0.1918, acc: 93.0881, loss_bbox: 0.2295, loss_mask: 0.2333, loss: 0.7247 2023-11-13 18:51:41,395 - mmdet - INFO - Epoch [3][4650/7330] lr: 1.000e-04, eta: 8:30:11, time: 0.438, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0424, loss_cls: 0.1876, acc: 93.1904, loss_bbox: 0.2295, loss_mask: 0.2278, loss: 0.7110 2023-11-13 18:52:03,316 - mmdet - INFO - Epoch [3][4700/7330] lr: 1.000e-04, eta: 8:29:47, time: 0.438, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0411, loss_cls: 0.1838, acc: 93.3379, loss_bbox: 0.2325, loss_mask: 0.2381, loss: 0.7190 2023-11-13 18:52:25,389 - mmdet - INFO - Epoch [3][4750/7330] lr: 1.000e-04, eta: 8:29:24, time: 0.442, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0419, loss_cls: 0.1868, acc: 93.2402, loss_bbox: 0.2365, loss_mask: 0.2302, loss: 0.7178 2023-11-13 18:52:47,597 - mmdet - INFO - Epoch [3][4800/7330] lr: 1.000e-04, eta: 8:29:02, time: 0.444, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0403, loss_cls: 0.1864, acc: 93.2429, loss_bbox: 0.2314, loss_mask: 0.2366, loss: 0.7199 2023-11-13 18:53:09,679 - mmdet - INFO - Epoch [3][4850/7330] lr: 1.000e-04, eta: 8:28:38, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0428, loss_cls: 0.1864, acc: 93.2671, loss_bbox: 0.2288, loss_mask: 0.2354, loss: 0.7172 2023-11-13 18:53:31,769 - mmdet - INFO - Epoch [3][4900/7330] lr: 1.000e-04, eta: 8:28:15, time: 0.442, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0265, loss_rpn_bbox: 0.0461, loss_cls: 0.1992, acc: 92.6782, loss_bbox: 0.2467, loss_mask: 0.2399, loss: 0.7582 2023-11-13 18:53:54,400 - mmdet - INFO - Epoch [3][4950/7330] lr: 1.000e-04, eta: 8:27:54, time: 0.453, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0465, loss_cls: 0.1946, acc: 92.8599, loss_bbox: 0.2432, loss_mask: 0.2334, loss: 0.7417 2023-11-13 18:54:16,672 - mmdet - INFO - Epoch [3][5000/7330] lr: 1.000e-04, eta: 8:27:32, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0423, loss_cls: 0.1889, acc: 93.1614, loss_bbox: 0.2318, loss_mask: 0.2374, loss: 0.7247 2023-11-13 18:54:39,198 - mmdet - INFO - Epoch [3][5050/7330] lr: 1.000e-04, eta: 8:27:10, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0436, loss_cls: 0.1925, acc: 92.9395, loss_bbox: 0.2386, loss_mask: 0.2325, loss: 0.7330 2023-11-13 18:55:01,482 - mmdet - INFO - Epoch [3][5100/7330] lr: 1.000e-04, eta: 8:26:48, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0425, loss_cls: 0.1821, acc: 93.2461, loss_bbox: 0.2289, loss_mask: 0.2333, loss: 0.7085 2023-11-13 18:55:23,794 - mmdet - INFO - Epoch [3][5150/7330] lr: 1.000e-04, eta: 8:26:26, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0439, loss_cls: 0.1895, acc: 93.0571, loss_bbox: 0.2373, loss_mask: 0.2460, loss: 0.7406 2023-11-13 18:55:46,269 - mmdet - INFO - Epoch [3][5200/7330] lr: 1.000e-04, eta: 8:26:04, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0241, loss_rpn_bbox: 0.0444, loss_cls: 0.1919, acc: 92.9490, loss_bbox: 0.2404, loss_mask: 0.2397, loss: 0.7405 2023-11-13 18:56:08,524 - mmdet - INFO - Epoch [3][5250/7330] lr: 1.000e-04, eta: 8:25:42, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0250, loss_rpn_bbox: 0.0423, loss_cls: 0.1903, acc: 93.1555, loss_bbox: 0.2353, loss_mask: 0.2294, loss: 0.7222 2023-11-13 18:56:30,808 - mmdet - INFO - Epoch [3][5300/7330] lr: 1.000e-04, eta: 8:25:20, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0277, loss_rpn_bbox: 0.0468, loss_cls: 0.1914, acc: 93.0833, loss_bbox: 0.2374, loss_mask: 0.2411, loss: 0.7443 2023-11-13 18:56:53,024 - mmdet - INFO - Epoch [3][5350/7330] lr: 1.000e-04, eta: 8:24:57, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0436, loss_cls: 0.1889, acc: 93.0876, loss_bbox: 0.2305, loss_mask: 0.2308, loss: 0.7181 2023-11-13 18:57:15,497 - mmdet - INFO - Epoch [3][5400/7330] lr: 1.000e-04, eta: 8:24:35, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0434, loss_cls: 0.1919, acc: 93.0852, loss_bbox: 0.2346, loss_mask: 0.2340, loss: 0.7292 2023-11-13 18:57:38,012 - mmdet - INFO - Epoch [3][5450/7330] lr: 1.000e-04, eta: 8:24:14, time: 0.450, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0261, loss_rpn_bbox: 0.0440, loss_cls: 0.1910, acc: 92.9648, loss_bbox: 0.2373, loss_mask: 0.2360, loss: 0.7344 2023-11-13 18:57:59,977 - mmdet - INFO - Epoch [3][5500/7330] lr: 1.000e-04, eta: 8:23:50, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0427, loss_cls: 0.1832, acc: 93.3630, loss_bbox: 0.2281, loss_mask: 0.2390, loss: 0.7154 2023-11-13 18:58:22,336 - mmdet - INFO - Epoch [3][5550/7330] lr: 1.000e-04, eta: 8:23:28, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0423, loss_cls: 0.1886, acc: 93.1433, loss_bbox: 0.2347, loss_mask: 0.2354, loss: 0.7235 2023-11-13 18:58:45,008 - mmdet - INFO - Epoch [3][5600/7330] lr: 1.000e-04, eta: 8:23:07, time: 0.453, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0458, loss_cls: 0.1983, acc: 92.7124, loss_bbox: 0.2449, loss_mask: 0.2342, loss: 0.7491 2023-11-13 18:59:07,022 - mmdet - INFO - Epoch [3][5650/7330] lr: 1.000e-04, eta: 8:22:44, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0417, loss_cls: 0.1930, acc: 93.0298, loss_bbox: 0.2351, loss_mask: 0.2319, loss: 0.7242 2023-11-13 18:59:29,109 - mmdet - INFO - Epoch [3][5700/7330] lr: 1.000e-04, eta: 8:22:21, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0419, loss_cls: 0.1866, acc: 93.2700, loss_bbox: 0.2294, loss_mask: 0.2354, loss: 0.7169 2023-11-13 18:59:51,549 - mmdet - INFO - Epoch [3][5750/7330] lr: 1.000e-04, eta: 8:21:59, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0461, loss_cls: 0.1907, acc: 93.0029, loss_bbox: 0.2373, loss_mask: 0.2398, loss: 0.7386 2023-11-13 19:00:13,610 - mmdet - INFO - Epoch [3][5800/7330] lr: 1.000e-04, eta: 8:21:36, time: 0.441, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0427, loss_cls: 0.1925, acc: 92.9514, loss_bbox: 0.2396, loss_mask: 0.2334, loss: 0.7319 2023-11-13 19:00:36,186 - mmdet - INFO - Epoch [3][5850/7330] lr: 1.000e-04, eta: 8:21:15, time: 0.451, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0429, loss_cls: 0.1968, acc: 92.9819, loss_bbox: 0.2455, loss_mask: 0.2373, loss: 0.7483 2023-11-13 19:00:58,686 - mmdet - INFO - Epoch [3][5900/7330] lr: 1.000e-04, eta: 8:20:53, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0270, loss_rpn_bbox: 0.0460, loss_cls: 0.1951, acc: 92.8833, loss_bbox: 0.2396, loss_mask: 0.2349, loss: 0.7426 2023-11-13 19:01:20,709 - mmdet - INFO - Epoch [3][5950/7330] lr: 1.000e-04, eta: 8:20:30, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0419, loss_cls: 0.1853, acc: 93.2234, loss_bbox: 0.2331, loss_mask: 0.2308, loss: 0.7149 2023-11-13 19:01:43,095 - mmdet - INFO - Epoch [3][6000/7330] lr: 1.000e-04, eta: 8:20:08, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0252, loss_rpn_bbox: 0.0417, loss_cls: 0.1931, acc: 92.9451, loss_bbox: 0.2376, loss_mask: 0.2309, loss: 0.7285 2023-11-13 19:02:05,241 - mmdet - INFO - Epoch [3][6050/7330] lr: 1.000e-04, eta: 8:19:45, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0251, loss_rpn_bbox: 0.0421, loss_cls: 0.1936, acc: 93.0447, loss_bbox: 0.2328, loss_mask: 0.2285, loss: 0.7221 2023-11-13 19:02:27,438 - mmdet - INFO - Epoch [3][6100/7330] lr: 1.000e-04, eta: 8:19:23, time: 0.444, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0278, loss_rpn_bbox: 0.0455, loss_cls: 0.1947, acc: 92.9546, loss_bbox: 0.2384, loss_mask: 0.2415, loss: 0.7479 2023-11-13 19:02:49,459 - mmdet - INFO - Epoch [3][6150/7330] lr: 1.000e-04, eta: 8:18:59, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0434, loss_cls: 0.1876, acc: 93.1819, loss_bbox: 0.2368, loss_mask: 0.2295, loss: 0.7205 2023-11-13 19:03:11,870 - mmdet - INFO - Epoch [3][6200/7330] lr: 1.000e-04, eta: 8:18:37, time: 0.448, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0430, loss_cls: 0.1842, acc: 93.2878, loss_bbox: 0.2284, loss_mask: 0.2253, loss: 0.7046 2023-11-13 19:03:34,364 - mmdet - INFO - Epoch [3][6250/7330] lr: 1.000e-04, eta: 8:18:16, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0443, loss_cls: 0.2007, acc: 92.7498, loss_bbox: 0.2399, loss_mask: 0.2326, loss: 0.7431 2023-11-13 19:03:56,630 - mmdet - INFO - Epoch [3][6300/7330] lr: 1.000e-04, eta: 8:17:53, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0260, loss_rpn_bbox: 0.0442, loss_cls: 0.1936, acc: 92.8926, loss_bbox: 0.2401, loss_mask: 0.2345, loss: 0.7384 2023-11-13 19:04:18,598 - mmdet - INFO - Epoch [3][6350/7330] lr: 1.000e-04, eta: 8:17:30, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0434, loss_cls: 0.2053, acc: 92.5645, loss_bbox: 0.2512, loss_mask: 0.2393, loss: 0.7624 2023-11-13 19:04:40,510 - mmdet - INFO - Epoch [3][6400/7330] lr: 1.000e-04, eta: 8:17:07, time: 0.438, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0403, loss_cls: 0.1824, acc: 93.4299, loss_bbox: 0.2280, loss_mask: 0.2298, loss: 0.7041 2023-11-13 19:05:02,868 - mmdet - INFO - Epoch [3][6450/7330] lr: 1.000e-04, eta: 8:16:44, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0267, loss_rpn_bbox: 0.0428, loss_cls: 0.1849, acc: 93.3540, loss_bbox: 0.2322, loss_mask: 0.2312, loss: 0.7179 2023-11-13 19:05:25,029 - mmdet - INFO - Epoch [3][6500/7330] lr: 1.000e-04, eta: 8:16:22, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0427, loss_cls: 0.1898, acc: 93.0923, loss_bbox: 0.2363, loss_mask: 0.2360, loss: 0.7278 2023-11-13 19:05:46,886 - mmdet - INFO - Epoch [3][6550/7330] lr: 1.000e-04, eta: 8:15:58, time: 0.437, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0411, loss_cls: 0.1903, acc: 93.1985, loss_bbox: 0.2329, loss_mask: 0.2374, loss: 0.7248 2023-11-13 19:06:09,051 - mmdet - INFO - Epoch [3][6600/7330] lr: 1.000e-04, eta: 8:15:35, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0429, loss_cls: 0.1962, acc: 92.8623, loss_bbox: 0.2420, loss_mask: 0.2344, loss: 0.7379 2023-11-13 19:06:31,402 - mmdet - INFO - Epoch [3][6650/7330] lr: 1.000e-04, eta: 8:15:13, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0257, loss_rpn_bbox: 0.0434, loss_cls: 0.1949, acc: 92.9707, loss_bbox: 0.2382, loss_mask: 0.2373, loss: 0.7394 2023-11-13 19:06:53,611 - mmdet - INFO - Epoch [3][6700/7330] lr: 1.000e-04, eta: 8:14:51, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0412, loss_cls: 0.1846, acc: 93.1863, loss_bbox: 0.2333, loss_mask: 0.2356, loss: 0.7195 2023-11-13 19:07:15,614 - mmdet - INFO - Epoch [3][6750/7330] lr: 1.000e-04, eta: 8:14:28, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0423, loss_cls: 0.1869, acc: 93.2566, loss_bbox: 0.2296, loss_mask: 0.2323, loss: 0.7138 2023-11-13 19:07:38,051 - mmdet - INFO - Epoch [3][6800/7330] lr: 1.000e-04, eta: 8:14:06, time: 0.449, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0406, loss_cls: 0.1932, acc: 93.0271, loss_bbox: 0.2307, loss_mask: 0.2252, loss: 0.7134 2023-11-13 19:07:59,928 - mmdet - INFO - Epoch [3][6850/7330] lr: 1.000e-04, eta: 8:13:42, time: 0.437, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0420, loss_cls: 0.1874, acc: 93.2163, loss_bbox: 0.2346, loss_mask: 0.2297, loss: 0.7194 2023-11-13 19:08:21,922 - mmdet - INFO - Epoch [3][6900/7330] lr: 1.000e-04, eta: 8:13:19, time: 0.440, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0403, loss_cls: 0.1894, acc: 93.1431, loss_bbox: 0.2318, loss_mask: 0.2340, loss: 0.7177 2023-11-13 19:08:43,577 - mmdet - INFO - Epoch [3][6950/7330] lr: 1.000e-04, eta: 8:12:55, time: 0.433, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0423, loss_cls: 0.1878, acc: 93.2258, loss_bbox: 0.2285, loss_mask: 0.2308, loss: 0.7126 2023-11-13 19:09:05,549 - mmdet - INFO - Epoch [3][7000/7330] lr: 1.000e-04, eta: 8:12:31, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0421, loss_cls: 0.1908, acc: 93.2441, loss_bbox: 0.2298, loss_mask: 0.2287, loss: 0.7161 2023-11-13 19:09:27,893 - mmdet - INFO - Epoch [3][7050/7330] lr: 1.000e-04, eta: 8:12:09, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0407, loss_cls: 0.1870, acc: 93.2314, loss_bbox: 0.2309, loss_mask: 0.2362, loss: 0.7187 2023-11-13 19:09:49,877 - mmdet - INFO - Epoch [3][7100/7330] lr: 1.000e-04, eta: 8:11:46, time: 0.440, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0421, loss_cls: 0.1871, acc: 93.1243, loss_bbox: 0.2288, loss_mask: 0.2290, loss: 0.7102 2023-11-13 19:10:12,240 - mmdet - INFO - Epoch [3][7150/7330] lr: 1.000e-04, eta: 8:11:24, time: 0.447, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0439, loss_cls: 0.1852, acc: 93.3826, loss_bbox: 0.2262, loss_mask: 0.2376, loss: 0.7172 2023-11-13 19:10:34,364 - mmdet - INFO - Epoch [3][7200/7330] lr: 1.000e-04, eta: 8:11:01, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0258, loss_rpn_bbox: 0.0428, loss_cls: 0.1837, acc: 93.3091, loss_bbox: 0.2276, loss_mask: 0.2327, loss: 0.7125 2023-11-13 19:10:56,715 - mmdet - INFO - Epoch [3][7250/7330] lr: 1.000e-04, eta: 8:10:39, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0435, loss_cls: 0.1807, acc: 93.4397, loss_bbox: 0.2291, loss_mask: 0.2327, loss: 0.7097 2023-11-13 19:11:19,652 - mmdet - INFO - Epoch [3][7300/7330] lr: 1.000e-04, eta: 8:10:19, time: 0.459, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0249, loss_rpn_bbox: 0.0446, loss_cls: 0.1895, acc: 93.1506, loss_bbox: 0.2360, loss_mask: 0.2339, loss: 0.7289 2023-11-13 19:11:33,440 - mmdet - INFO - Saving checkpoint at 3 epochs 2023-11-13 19:12:26,138 - mmdet - INFO - Evaluating bbox... 2023-11-13 19:12:58,866 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.453 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.684 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.504 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 ] = 0.494 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.580 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.580 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.580 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.580 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 ] = 0.630 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.715 2023-11-13 19:12:58,868 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.569 | bicycle | 0.347 | car | 0.464 | | motorcycle | 0.463 | airplane | 0.684 | bus | 0.652 | | train | 0.659 | truck | 0.415 | boat | 0.305 | | traffic light | 0.295 | fire hydrant | 0.683 | stop sign | 0.647 | | parking meter | 0.474 | bench | 0.276 | bird | 0.381 | | cat | 0.721 | dog | 0.659 | horse | 0.609 | | sheep | 0.566 | cow | 0.610 | elephant | 0.685 | | bear | 0.742 | zebra | 0.658 | giraffe | 0.685 | | backpack | 0.202 | umbrella | 0.430 | handbag | 0.208 | | tie | 0.350 | suitcase | 0.446 | frisbee | 0.660 | | skis | 0.268 | snowboard | 0.398 | sports ball | 0.459 | | kite | 0.444 | baseball bat | 0.386 | baseball glove | 0.420 | | skateboard | 0.565 | surfboard | 0.424 | tennis racket | 0.540 | | bottle | 0.448 | wine glass | 0.374 | cup | 0.491 | | fork | 0.418 | knife | 0.264 | spoon | 0.232 | | bowl | 0.448 | banana | 0.264 | apple | 0.222 | | sandwich | 0.408 | orange | 0.358 | broccoli | 0.235 | | carrot | 0.256 | hot dog | 0.408 | pizza | 0.516 | | donut | 0.524 | cake | 0.425 | chair | 0.332 | | couch | 0.437 | potted plant | 0.326 | bed | 0.448 | | dining table | 0.289 | toilet | 0.629 | tv | 0.582 | | laptop | 0.644 | mouse | 0.615 | remote | 0.386 | | keyboard | 0.509 | cell phone | 0.411 | microwave | 0.631 | | oven | 0.379 | toaster | 0.488 | sink | 0.425 | | refrigerator | 0.599 | book | 0.182 | clock | 0.529 | | vase | 0.414 | scissors | 0.334 | teddy bear | 0.506 | | hair drier | 0.092 | toothbrush | 0.274 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:12:58,868 - mmdet - INFO - Evaluating segm... 2023-11-13 19:13:32,906 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.412 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.650 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.446 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.228 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 ] = 0.594 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.576 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.689 2023-11-13 19:13:32,908 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.492 | bicycle | 0.196 | car | 0.423 | | motorcycle | 0.362 | airplane | 0.544 | bus | 0.661 | | train | 0.642 | truck | 0.408 | boat | 0.279 | | traffic light | 0.283 | fire hydrant | 0.675 | stop sign | 0.665 | | parking meter | 0.496 | bench | 0.207 | bird | 0.335 | | cat | 0.725 | dog | 0.629 | horse | 0.453 | | sheep | 0.502 | cow | 0.530 | elephant | 0.622 | | bear | 0.740 | zebra | 0.569 | giraffe | 0.535 | | backpack | 0.210 | umbrella | 0.501 | handbag | 0.196 | | tie | 0.334 | suitcase | 0.488 | frisbee | 0.653 | | skis | 0.038 | snowboard | 0.233 | sports ball | 0.459 | | kite | 0.314 | baseball bat | 0.286 | baseball glove | 0.447 | | skateboard | 0.345 | surfboard | 0.350 | tennis racket | 0.566 | | bottle | 0.427 | wine glass | 0.342 | cup | 0.494 | | fork | 0.208 | knife | 0.190 | spoon | 0.169 | | bowl | 0.419 | banana | 0.220 | apple | 0.216 | | sandwich | 0.455 | orange | 0.355 | broccoli | 0.236 | | carrot | 0.227 | hot dog | 0.298 | pizza | 0.507 | | donut | 0.542 | cake | 0.450 | chair | 0.234 | | couch | 0.368 | potted plant | 0.278 | bed | 0.346 | | dining table | 0.173 | toilet | 0.617 | tv | 0.613 | | laptop | 0.654 | mouse | 0.621 | remote | 0.340 | | keyboard | 0.516 | cell phone | 0.392 | microwave | 0.664 | | oven | 0.368 | toaster | 0.554 | sink | 0.418 | | refrigerator | 0.613 | book | 0.137 | clock | 0.536 | | vase | 0.424 | scissors | 0.257 | teddy bear | 0.488 | | hair drier | 0.050 | toothbrush | 0.173 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 19:13:33,399 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_2.pth was removed 2023-11-13 19:13:36,828 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_3.pth. 2023-11-13 19:13:36,828 - mmdet - INFO - Best bbox_mAP is 0.4525 at 3 epoch. 2023-11-13 19:13:36,829 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 19:13:36,829 - mmdet - INFO - Epoch(val) [3][625] bbox_mAP: 0.4525, bbox_mAP_50: 0.6839, bbox_mAP_75: 0.5036, bbox_mAP_s: 0.3036, bbox_mAP_m: 0.4943, bbox_mAP_l: 0.5798, bbox_mAP_copypaste: 0.4525 0.6839 0.5036 0.3036 0.4943 0.5798, segm_mAP: 0.4123, segm_mAP_50: 0.6501, segm_mAP_75: 0.4462, segm_mAP_s: 0.2284, segm_mAP_m: 0.4456, segm_mAP_l: 0.5940, segm_mAP_copypaste: 0.4123 0.6501 0.4462 0.2284 0.4456 0.5940 2023-11-13 19:14:03,478 - mmdet - INFO - Epoch [4][50/7330] lr: 1.000e-04, eta: 8:09:16, time: 0.533, data_time: 0.091, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0432, loss_cls: 0.1799, acc: 93.3743, loss_bbox: 0.2282, loss_mask: 0.2333, loss: 0.7083 2023-11-13 19:14:26,330 - mmdet - INFO - Epoch [4][100/7330] lr: 1.000e-04, eta: 8:08:56, time: 0.457, data_time: 0.036, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0412, loss_cls: 0.1762, acc: 93.5137, loss_bbox: 0.2285, loss_mask: 0.2339, loss: 0.7005 2023-11-13 19:14:48,803 - mmdet - INFO - Epoch [4][150/7330] lr: 1.000e-04, eta: 8:08:34, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0437, loss_cls: 0.1723, acc: 93.5579, loss_bbox: 0.2229, loss_mask: 0.2296, loss: 0.6914 2023-11-13 19:15:11,349 - mmdet - INFO - Epoch [4][200/7330] lr: 1.000e-04, eta: 8:08:13, time: 0.451, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0439, loss_cls: 0.1740, acc: 93.5283, loss_bbox: 0.2271, loss_mask: 0.2277, loss: 0.6940 2023-11-13 19:15:33,684 - mmdet - INFO - Epoch [4][250/7330] lr: 1.000e-04, eta: 8:07:51, time: 0.447, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0406, loss_cls: 0.1746, acc: 93.5784, loss_bbox: 0.2213, loss_mask: 0.2248, loss: 0.6813 2023-11-13 19:15:55,772 - mmdet - INFO - Epoch [4][300/7330] lr: 1.000e-04, eta: 8:07:28, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0399, loss_cls: 0.1760, acc: 93.5317, loss_bbox: 0.2218, loss_mask: 0.2243, loss: 0.6827 2023-11-13 19:16:18,123 - mmdet - INFO - Epoch [4][350/7330] lr: 1.000e-04, eta: 8:07:06, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0437, loss_cls: 0.1799, acc: 93.3513, loss_bbox: 0.2314, loss_mask: 0.2297, loss: 0.7064 2023-11-13 19:16:40,476 - mmdet - INFO - Epoch [4][400/7330] lr: 1.000e-04, eta: 8:06:44, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0416, loss_cls: 0.1762, acc: 93.4436, loss_bbox: 0.2280, loss_mask: 0.2284, loss: 0.6956 2023-11-13 19:17:02,651 - mmdet - INFO - Epoch [4][450/7330] lr: 1.000e-04, eta: 8:06:21, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0412, loss_cls: 0.1800, acc: 93.3721, loss_bbox: 0.2281, loss_mask: 0.2344, loss: 0.7058 2023-11-13 19:17:25,391 - mmdet - INFO - Epoch [4][500/7330] lr: 1.000e-04, eta: 8:06:00, time: 0.455, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0428, loss_cls: 0.1814, acc: 93.3264, loss_bbox: 0.2276, loss_mask: 0.2279, loss: 0.7004 2023-11-13 19:17:47,587 - mmdet - INFO - Epoch [4][550/7330] lr: 1.000e-04, eta: 8:05:38, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0397, loss_cls: 0.1751, acc: 93.5225, loss_bbox: 0.2206, loss_mask: 0.2248, loss: 0.6794 2023-11-13 19:18:10,068 - mmdet - INFO - Epoch [4][600/7330] lr: 1.000e-04, eta: 8:05:16, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0403, loss_cls: 0.1759, acc: 93.4768, loss_bbox: 0.2222, loss_mask: 0.2233, loss: 0.6822 2023-11-13 19:18:32,433 - mmdet - INFO - Epoch [4][650/7330] lr: 1.000e-04, eta: 8:04:54, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0415, loss_cls: 0.1701, acc: 93.6519, loss_bbox: 0.2221, loss_mask: 0.2271, loss: 0.6810 2023-11-13 19:18:54,797 - mmdet - INFO - Epoch [4][700/7330] lr: 1.000e-04, eta: 8:04:32, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0436, loss_cls: 0.1892, acc: 92.8728, loss_bbox: 0.2389, loss_mask: 0.2303, loss: 0.7247 2023-11-13 19:19:17,353 - mmdet - INFO - Epoch [4][750/7330] lr: 1.000e-04, eta: 8:04:11, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0437, loss_cls: 0.1797, acc: 93.3206, loss_bbox: 0.2261, loss_mask: 0.2317, loss: 0.7026 2023-11-13 19:19:39,403 - mmdet - INFO - Epoch [4][800/7330] lr: 1.000e-04, eta: 8:03:48, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0402, loss_cls: 0.1802, acc: 93.3154, loss_bbox: 0.2317, loss_mask: 0.2316, loss: 0.7043 2023-11-13 19:20:01,788 - mmdet - INFO - Epoch [4][850/7330] lr: 1.000e-04, eta: 8:03:26, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0411, loss_cls: 0.1829, acc: 93.2319, loss_bbox: 0.2263, loss_mask: 0.2262, loss: 0.6986 2023-11-13 19:20:23,840 - mmdet - INFO - Epoch [4][900/7330] lr: 1.000e-04, eta: 8:03:03, time: 0.441, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0387, loss_cls: 0.1743, acc: 93.5498, loss_bbox: 0.2239, loss_mask: 0.2258, loss: 0.6829 2023-11-13 19:20:46,404 - mmdet - INFO - Epoch [4][950/7330] lr: 1.000e-04, eta: 8:02:41, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0427, loss_cls: 0.1807, acc: 93.3335, loss_bbox: 0.2290, loss_mask: 0.2319, loss: 0.7065 2023-11-13 19:21:08,626 - mmdet - INFO - Epoch [4][1000/7330] lr: 1.000e-04, eta: 8:02:19, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0403, loss_cls: 0.1770, acc: 93.5735, loss_bbox: 0.2226, loss_mask: 0.2253, loss: 0.6853 2023-11-13 19:21:31,168 - mmdet - INFO - Epoch [4][1050/7330] lr: 1.000e-04, eta: 8:01:58, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0400, loss_cls: 0.1692, acc: 93.6833, loss_bbox: 0.2229, loss_mask: 0.2234, loss: 0.6755 2023-11-13 19:21:53,634 - mmdet - INFO - Epoch [4][1100/7330] lr: 1.000e-04, eta: 8:01:36, time: 0.449, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0399, loss_cls: 0.1730, acc: 93.6133, loss_bbox: 0.2225, loss_mask: 0.2249, loss: 0.6805 2023-11-13 19:22:16,193 - mmdet - INFO - Epoch [4][1150/7330] lr: 1.000e-04, eta: 8:01:14, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0437, loss_cls: 0.1824, acc: 93.3557, loss_bbox: 0.2305, loss_mask: 0.2289, loss: 0.7084 2023-11-13 19:22:38,459 - mmdet - INFO - Epoch [4][1200/7330] lr: 1.000e-04, eta: 8:00:52, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0426, loss_cls: 0.1735, acc: 93.7527, loss_bbox: 0.2193, loss_mask: 0.2222, loss: 0.6793 2023-11-13 19:23:00,768 - mmdet - INFO - Epoch [4][1250/7330] lr: 1.000e-04, eta: 8:00:30, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0449, loss_cls: 0.1788, acc: 93.3955, loss_bbox: 0.2233, loss_mask: 0.2276, loss: 0.6970 2023-11-13 19:23:23,299 - mmdet - INFO - Epoch [4][1300/7330] lr: 1.000e-04, eta: 8:00:08, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0429, loss_cls: 0.1793, acc: 93.3611, loss_bbox: 0.2303, loss_mask: 0.2272, loss: 0.7021 2023-11-13 19:23:45,466 - mmdet - INFO - Epoch [4][1350/7330] lr: 1.000e-04, eta: 7:59:46, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0425, loss_cls: 0.1713, acc: 93.7402, loss_bbox: 0.2219, loss_mask: 0.2293, loss: 0.6892 2023-11-13 19:24:07,637 - mmdet - INFO - Epoch [4][1400/7330] lr: 1.000e-04, eta: 7:59:23, time: 0.443, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0411, loss_cls: 0.1759, acc: 93.3389, loss_bbox: 0.2298, loss_mask: 0.2239, loss: 0.6929 2023-11-13 19:24:29,795 - mmdet - INFO - Epoch [4][1450/7330] lr: 1.000e-04, eta: 7:59:01, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0404, loss_cls: 0.1751, acc: 93.4839, loss_bbox: 0.2221, loss_mask: 0.2237, loss: 0.6811 2023-11-13 19:24:52,118 - mmdet - INFO - Epoch [4][1500/7330] lr: 1.000e-04, eta: 7:58:38, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0434, loss_cls: 0.1895, acc: 92.9985, loss_bbox: 0.2364, loss_mask: 0.2318, loss: 0.7225 2023-11-13 19:25:14,274 - mmdet - INFO - Epoch [4][1550/7330] lr: 1.000e-04, eta: 7:58:16, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0424, loss_cls: 0.1831, acc: 93.1160, loss_bbox: 0.2318, loss_mask: 0.2296, loss: 0.7097 2023-11-13 19:25:36,421 - mmdet - INFO - Epoch [4][1600/7330] lr: 1.000e-04, eta: 7:57:53, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0399, loss_cls: 0.1752, acc: 93.5376, loss_bbox: 0.2197, loss_mask: 0.2225, loss: 0.6776 2023-11-13 19:25:58,339 - mmdet - INFO - Epoch [4][1650/7330] lr: 1.000e-04, eta: 7:57:30, time: 0.438, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0401, loss_cls: 0.1772, acc: 93.4521, loss_bbox: 0.2292, loss_mask: 0.2257, loss: 0.6932 2023-11-13 19:26:20,288 - mmdet - INFO - Epoch [4][1700/7330] lr: 1.000e-04, eta: 7:57:07, time: 0.439, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0405, loss_cls: 0.1732, acc: 93.6987, loss_bbox: 0.2231, loss_mask: 0.2334, loss: 0.6915 2023-11-13 19:26:42,815 - mmdet - INFO - Epoch [4][1750/7330] lr: 1.000e-04, eta: 7:56:45, time: 0.451, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0428, loss_cls: 0.1843, acc: 93.1794, loss_bbox: 0.2285, loss_mask: 0.2262, loss: 0.7055 2023-11-13 19:27:04,832 - mmdet - INFO - Epoch [4][1800/7330] lr: 1.000e-04, eta: 7:56:22, time: 0.440, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0393, loss_cls: 0.1701, acc: 93.7146, loss_bbox: 0.2128, loss_mask: 0.2210, loss: 0.6628 2023-11-13 19:27:26,831 - mmdet - INFO - Epoch [4][1850/7330] lr: 1.000e-04, eta: 7:55:59, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0416, loss_cls: 0.1731, acc: 93.5835, loss_bbox: 0.2256, loss_mask: 0.2282, loss: 0.6893 2023-11-13 19:27:48,928 - mmdet - INFO - Epoch [4][1900/7330] lr: 1.000e-04, eta: 7:55:37, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0416, loss_cls: 0.1767, acc: 93.4749, loss_bbox: 0.2280, loss_mask: 0.2319, loss: 0.7001 2023-11-13 19:28:11,142 - mmdet - INFO - Epoch [4][1950/7330] lr: 1.000e-04, eta: 7:55:14, time: 0.444, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0240, loss_rpn_bbox: 0.0438, loss_cls: 0.1884, acc: 92.9971, loss_bbox: 0.2366, loss_mask: 0.2349, loss: 0.7277 2023-11-13 19:28:33,111 - mmdet - INFO - Epoch [4][2000/7330] lr: 1.000e-04, eta: 7:54:51, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0379, loss_cls: 0.1699, acc: 93.6895, loss_bbox: 0.2201, loss_mask: 0.2268, loss: 0.6735 2023-11-13 19:28:55,401 - mmdet - INFO - Epoch [4][2050/7330] lr: 1.000e-04, eta: 7:54:29, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0417, loss_cls: 0.1784, acc: 93.4341, loss_bbox: 0.2255, loss_mask: 0.2244, loss: 0.6912 2023-11-13 19:29:17,560 - mmdet - INFO - Epoch [4][2100/7330] lr: 1.000e-04, eta: 7:54:06, time: 0.443, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0228, loss_rpn_bbox: 0.0430, loss_cls: 0.1801, acc: 93.3469, loss_bbox: 0.2310, loss_mask: 0.2275, loss: 0.7043 2023-11-13 19:29:39,305 - mmdet - INFO - Epoch [4][2150/7330] lr: 1.000e-04, eta: 7:53:43, time: 0.435, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0425, loss_cls: 0.1810, acc: 93.3438, loss_bbox: 0.2330, loss_mask: 0.2312, loss: 0.7103 2023-11-13 19:30:00,732 - mmdet - INFO - Epoch [4][2200/7330] lr: 1.000e-04, eta: 7:53:18, time: 0.428, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0395, loss_cls: 0.1662, acc: 93.9536, loss_bbox: 0.2117, loss_mask: 0.2207, loss: 0.6577 2023-11-13 19:30:23,103 - mmdet - INFO - Epoch [4][2250/7330] lr: 1.000e-04, eta: 7:52:56, time: 0.447, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0435, loss_cls: 0.1890, acc: 92.9380, loss_bbox: 0.2353, loss_mask: 0.2315, loss: 0.7213 2023-11-13 19:30:45,357 - mmdet - INFO - Epoch [4][2300/7330] lr: 1.000e-04, eta: 7:52:34, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0410, loss_cls: 0.1845, acc: 93.1970, loss_bbox: 0.2293, loss_mask: 0.2340, loss: 0.7110 2023-11-13 19:31:07,371 - mmdet - INFO - Epoch [4][2350/7330] lr: 1.000e-04, eta: 7:52:11, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0402, loss_cls: 0.1720, acc: 93.7119, loss_bbox: 0.2183, loss_mask: 0.2250, loss: 0.6758 2023-11-13 19:31:29,278 - mmdet - INFO - Epoch [4][2400/7330] lr: 1.000e-04, eta: 7:51:48, time: 0.438, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0386, loss_cls: 0.1736, acc: 93.6895, loss_bbox: 0.2163, loss_mask: 0.2235, loss: 0.6722 2023-11-13 19:31:51,884 - mmdet - INFO - Epoch [4][2450/7330] lr: 1.000e-04, eta: 7:51:26, time: 0.452, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0430, loss_cls: 0.1731, acc: 93.6233, loss_bbox: 0.2217, loss_mask: 0.2240, loss: 0.6850 2023-11-13 19:32:13,732 - mmdet - INFO - Epoch [4][2500/7330] lr: 1.000e-04, eta: 7:51:03, time: 0.437, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0382, loss_cls: 0.1724, acc: 93.5579, loss_bbox: 0.2206, loss_mask: 0.2281, loss: 0.6798 2023-11-13 19:32:36,191 - mmdet - INFO - Epoch [4][2550/7330] lr: 1.000e-04, eta: 7:50:41, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0428, loss_cls: 0.1805, acc: 93.3503, loss_bbox: 0.2295, loss_mask: 0.2261, loss: 0.7019 2023-11-13 19:32:58,398 - mmdet - INFO - Epoch [4][2600/7330] lr: 1.000e-04, eta: 7:50:19, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0422, loss_cls: 0.1771, acc: 93.4368, loss_bbox: 0.2213, loss_mask: 0.2263, loss: 0.6880 2023-11-13 19:33:20,787 - mmdet - INFO - Epoch [4][2650/7330] lr: 1.000e-04, eta: 7:49:57, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0423, loss_cls: 0.1791, acc: 93.3418, loss_bbox: 0.2278, loss_mask: 0.2300, loss: 0.7019 2023-11-13 19:33:42,669 - mmdet - INFO - Epoch [4][2700/7330] lr: 1.000e-04, eta: 7:49:34, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0396, loss_cls: 0.1769, acc: 93.4595, loss_bbox: 0.2250, loss_mask: 0.2226, loss: 0.6856 2023-11-13 19:34:04,800 - mmdet - INFO - Epoch [4][2750/7330] lr: 1.000e-04, eta: 7:49:11, time: 0.443, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0406, loss_cls: 0.1744, acc: 93.6897, loss_bbox: 0.2237, loss_mask: 0.2288, loss: 0.6906 2023-11-13 19:34:26,601 - mmdet - INFO - Epoch [4][2800/7330] lr: 1.000e-04, eta: 7:48:48, time: 0.436, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0400, loss_cls: 0.1712, acc: 93.5657, loss_bbox: 0.2238, loss_mask: 0.2278, loss: 0.6836 2023-11-13 19:34:48,534 - mmdet - INFO - Epoch [4][2850/7330] lr: 1.000e-04, eta: 7:48:24, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0394, loss_cls: 0.1730, acc: 93.6499, loss_bbox: 0.2225, loss_mask: 0.2263, loss: 0.6813 2023-11-13 19:35:10,592 - mmdet - INFO - Epoch [4][2900/7330] lr: 1.000e-04, eta: 7:48:02, time: 0.441, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0420, loss_cls: 0.1795, acc: 93.3616, loss_bbox: 0.2249, loss_mask: 0.2273, loss: 0.6957 2023-11-13 19:35:32,889 - mmdet - INFO - Epoch [4][2950/7330] lr: 1.000e-04, eta: 7:47:39, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0245, loss_rpn_bbox: 0.0449, loss_cls: 0.1884, acc: 93.0405, loss_bbox: 0.2361, loss_mask: 0.2312, loss: 0.7252 2023-11-13 19:35:55,240 - mmdet - INFO - Epoch [4][3000/7330] lr: 1.000e-04, eta: 7:47:17, time: 0.447, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0432, loss_cls: 0.1830, acc: 93.4082, loss_bbox: 0.2277, loss_mask: 0.2306, loss: 0.7066 2023-11-13 19:36:17,555 - mmdet - INFO - Epoch [4][3050/7330] lr: 1.000e-04, eta: 7:46:55, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0427, loss_cls: 0.1790, acc: 93.4683, loss_bbox: 0.2247, loss_mask: 0.2297, loss: 0.6974 2023-11-13 19:36:39,634 - mmdet - INFO - Epoch [4][3100/7330] lr: 1.000e-04, eta: 7:46:33, time: 0.442, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0412, loss_cls: 0.1806, acc: 93.3079, loss_bbox: 0.2309, loss_mask: 0.2309, loss: 0.7048 2023-11-13 19:37:02,213 - mmdet - INFO - Epoch [4][3150/7330] lr: 1.000e-04, eta: 7:46:11, time: 0.452, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0421, loss_cls: 0.1842, acc: 93.1125, loss_bbox: 0.2300, loss_mask: 0.2320, loss: 0.7095 2023-11-13 19:37:24,486 - mmdet - INFO - Epoch [4][3200/7330] lr: 1.000e-04, eta: 7:45:49, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0432, loss_cls: 0.1811, acc: 93.2942, loss_bbox: 0.2287, loss_mask: 0.2300, loss: 0.7062 2023-11-13 19:37:46,200 - mmdet - INFO - Epoch [4][3250/7330] lr: 1.000e-04, eta: 7:45:25, time: 0.434, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0400, loss_cls: 0.1779, acc: 93.3569, loss_bbox: 0.2282, loss_mask: 0.2326, loss: 0.6997 2023-11-13 19:38:08,286 - mmdet - INFO - Epoch [4][3300/7330] lr: 1.000e-04, eta: 7:45:03, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0408, loss_cls: 0.1817, acc: 93.3174, loss_bbox: 0.2289, loss_mask: 0.2275, loss: 0.7011 2023-11-13 19:38:30,305 - mmdet - INFO - Epoch [4][3350/7330] lr: 1.000e-04, eta: 7:44:40, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0422, loss_cls: 0.1794, acc: 93.4709, loss_bbox: 0.2198, loss_mask: 0.2281, loss: 0.6920 2023-11-13 19:38:52,900 - mmdet - INFO - Epoch [4][3400/7330] lr: 1.000e-04, eta: 7:44:18, time: 0.452, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0423, loss_cls: 0.1821, acc: 93.2485, loss_bbox: 0.2346, loss_mask: 0.2302, loss: 0.7112 2023-11-13 19:39:15,283 - mmdet - INFO - Epoch [4][3450/7330] lr: 1.000e-04, eta: 7:43:56, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0404, loss_cls: 0.1794, acc: 93.3359, loss_bbox: 0.2273, loss_mask: 0.2258, loss: 0.6944 2023-11-13 19:39:37,718 - mmdet - INFO - Epoch [4][3500/7330] lr: 1.000e-04, eta: 7:43:34, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0248, loss_rpn_bbox: 0.0437, loss_cls: 0.1850, acc: 93.2126, loss_bbox: 0.2295, loss_mask: 0.2274, loss: 0.7105 2023-11-13 19:40:00,296 - mmdet - INFO - Epoch [4][3550/7330] lr: 1.000e-04, eta: 7:43:13, time: 0.452, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0418, loss_cls: 0.1854, acc: 93.1755, loss_bbox: 0.2343, loss_mask: 0.2288, loss: 0.7121 2023-11-13 19:40:22,979 - mmdet - INFO - Epoch [4][3600/7330] lr: 1.000e-04, eta: 7:42:52, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0394, loss_cls: 0.1789, acc: 93.4556, loss_bbox: 0.2266, loss_mask: 0.2265, loss: 0.6948 2023-11-13 19:40:45,422 - mmdet - INFO - Epoch [4][3650/7330] lr: 1.000e-04, eta: 7:42:30, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0234, loss_rpn_bbox: 0.0429, loss_cls: 0.1752, acc: 93.6431, loss_bbox: 0.2230, loss_mask: 0.2287, loss: 0.6931 2023-11-13 19:41:07,304 - mmdet - INFO - Epoch [4][3700/7330] lr: 1.000e-04, eta: 7:42:07, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0413, loss_cls: 0.1775, acc: 93.5105, loss_bbox: 0.2238, loss_mask: 0.2286, loss: 0.6910 2023-11-13 19:41:29,435 - mmdet - INFO - Epoch [4][3750/7330] lr: 1.000e-04, eta: 7:41:44, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0408, loss_cls: 0.1812, acc: 93.2749, loss_bbox: 0.2342, loss_mask: 0.2288, loss: 0.7076 2023-11-13 19:41:51,399 - mmdet - INFO - Epoch [4][3800/7330] lr: 1.000e-04, eta: 7:41:21, time: 0.439, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0424, loss_cls: 0.1831, acc: 93.3484, loss_bbox: 0.2252, loss_mask: 0.2282, loss: 0.7015 2023-11-13 19:42:13,535 - mmdet - INFO - Epoch [4][3850/7330] lr: 1.000e-04, eta: 7:40:59, time: 0.443, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0398, loss_cls: 0.1769, acc: 93.5046, loss_bbox: 0.2274, loss_mask: 0.2281, loss: 0.6945 2023-11-13 19:42:35,614 - mmdet - INFO - Epoch [4][3900/7330] lr: 1.000e-04, eta: 7:40:36, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0403, loss_cls: 0.1802, acc: 93.3250, loss_bbox: 0.2225, loss_mask: 0.2300, loss: 0.6942 2023-11-13 19:42:57,956 - mmdet - INFO - Epoch [4][3950/7330] lr: 1.000e-04, eta: 7:40:14, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0239, loss_rpn_bbox: 0.0438, loss_cls: 0.1844, acc: 93.1765, loss_bbox: 0.2267, loss_mask: 0.2249, loss: 0.7037 2023-11-13 19:43:19,985 - mmdet - INFO - Epoch [4][4000/7330] lr: 1.000e-04, eta: 7:39:51, time: 0.441, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0388, loss_cls: 0.1744, acc: 93.5845, loss_bbox: 0.2167, loss_mask: 0.2261, loss: 0.6758 2023-11-13 19:43:42,141 - mmdet - INFO - Epoch [4][4050/7330] lr: 1.000e-04, eta: 7:39:28, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0422, loss_cls: 0.1776, acc: 93.3657, loss_bbox: 0.2306, loss_mask: 0.2278, loss: 0.6990 2023-11-13 19:44:04,641 - mmdet - INFO - Epoch [4][4100/7330] lr: 1.000e-04, eta: 7:39:07, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0422, loss_cls: 0.1836, acc: 93.2690, loss_bbox: 0.2284, loss_mask: 0.2300, loss: 0.7053 2023-11-13 19:44:27,079 - mmdet - INFO - Epoch [4][4150/7330] lr: 1.000e-04, eta: 7:38:45, time: 0.449, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0236, loss_rpn_bbox: 0.0433, loss_cls: 0.1858, acc: 93.1538, loss_bbox: 0.2353, loss_mask: 0.2314, loss: 0.7194 2023-11-13 19:44:49,213 - mmdet - INFO - Epoch [4][4200/7330] lr: 1.000e-04, eta: 7:38:22, time: 0.443, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0416, loss_cls: 0.1770, acc: 93.5413, loss_bbox: 0.2248, loss_mask: 0.2320, loss: 0.6954 2023-11-13 19:45:11,842 - mmdet - INFO - Epoch [4][4250/7330] lr: 1.000e-04, eta: 7:38:01, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0426, loss_cls: 0.1797, acc: 93.3809, loss_bbox: 0.2286, loss_mask: 0.2318, loss: 0.7055 2023-11-13 19:45:34,533 - mmdet - INFO - Epoch [4][4300/7330] lr: 1.000e-04, eta: 7:37:40, time: 0.454, data_time: 0.034, memory: 5731, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0434, loss_cls: 0.1893, acc: 93.0742, loss_bbox: 0.2403, loss_mask: 0.2331, loss: 0.7288 2023-11-13 19:45:56,965 - mmdet - INFO - Epoch [4][4350/7330] lr: 1.000e-04, eta: 7:37:18, time: 0.449, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0224, loss_rpn_bbox: 0.0440, loss_cls: 0.1851, acc: 93.1599, loss_bbox: 0.2332, loss_mask: 0.2339, loss: 0.7186 2023-11-13 19:46:19,411 - mmdet - INFO - Epoch [4][4400/7330] lr: 1.000e-04, eta: 7:36:56, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0235, loss_rpn_bbox: 0.0432, loss_cls: 0.1814, acc: 93.3672, loss_bbox: 0.2243, loss_mask: 0.2283, loss: 0.7008 2023-11-13 19:46:42,131 - mmdet - INFO - Epoch [4][4450/7330] lr: 1.000e-04, eta: 7:36:35, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0412, loss_cls: 0.1859, acc: 93.2183, loss_bbox: 0.2257, loss_mask: 0.2277, loss: 0.7035 2023-11-13 19:47:04,276 - mmdet - INFO - Epoch [4][4500/7330] lr: 1.000e-04, eta: 7:36:12, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0396, loss_cls: 0.1757, acc: 93.6421, loss_bbox: 0.2171, loss_mask: 0.2252, loss: 0.6779 2023-11-13 19:47:26,356 - mmdet - INFO - Epoch [4][4550/7330] lr: 1.000e-04, eta: 7:35:49, time: 0.442, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0410, loss_cls: 0.1730, acc: 93.7454, loss_bbox: 0.2190, loss_mask: 0.2250, loss: 0.6793 2023-11-13 19:47:48,901 - mmdet - INFO - Epoch [4][4600/7330] lr: 1.000e-04, eta: 7:35:28, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0392, loss_cls: 0.1765, acc: 93.5171, loss_bbox: 0.2176, loss_mask: 0.2239, loss: 0.6792 2023-11-13 19:48:11,226 - mmdet - INFO - Epoch [4][4650/7330] lr: 1.000e-04, eta: 7:35:06, time: 0.446, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0397, loss_cls: 0.1765, acc: 93.4441, loss_bbox: 0.2276, loss_mask: 0.2282, loss: 0.6923 2023-11-13 19:48:33,842 - mmdet - INFO - Epoch [4][4700/7330] lr: 1.000e-04, eta: 7:34:44, time: 0.452, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0420, loss_cls: 0.1822, acc: 93.2920, loss_bbox: 0.2284, loss_mask: 0.2320, loss: 0.7052 2023-11-13 19:48:56,230 - mmdet - INFO - Epoch [4][4750/7330] lr: 1.000e-04, eta: 7:34:22, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0395, loss_cls: 0.1765, acc: 93.4780, loss_bbox: 0.2225, loss_mask: 0.2286, loss: 0.6870 2023-11-13 19:49:18,437 - mmdet - INFO - Epoch [4][4800/7330] lr: 1.000e-04, eta: 7:34:00, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0406, loss_cls: 0.1820, acc: 93.3582, loss_bbox: 0.2261, loss_mask: 0.2247, loss: 0.6943 2023-11-13 19:49:41,084 - mmdet - INFO - Epoch [4][4850/7330] lr: 1.000e-04, eta: 7:33:38, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0417, loss_cls: 0.1872, acc: 93.1729, loss_bbox: 0.2270, loss_mask: 0.2238, loss: 0.7039 2023-11-13 19:50:03,527 - mmdet - INFO - Epoch [4][4900/7330] lr: 1.000e-04, eta: 7:33:17, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0231, loss_rpn_bbox: 0.0427, loss_cls: 0.1807, acc: 93.3618, loss_bbox: 0.2258, loss_mask: 0.2271, loss: 0.6994 2023-11-13 19:50:25,966 - mmdet - INFO - Epoch [4][4950/7330] lr: 1.000e-04, eta: 7:32:55, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0400, loss_cls: 0.1833, acc: 93.3181, loss_bbox: 0.2271, loss_mask: 0.2267, loss: 0.6980 2023-11-13 19:50:48,404 - mmdet - INFO - Epoch [4][5000/7330] lr: 1.000e-04, eta: 7:32:33, time: 0.449, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0424, loss_cls: 0.1789, acc: 93.4175, loss_bbox: 0.2267, loss_mask: 0.2314, loss: 0.7005 2023-11-13 19:51:10,619 - mmdet - INFO - Epoch [4][5050/7330] lr: 1.000e-04, eta: 7:32:10, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0376, loss_cls: 0.1771, acc: 93.6580, loss_bbox: 0.2202, loss_mask: 0.2287, loss: 0.6859 2023-11-13 19:51:33,290 - mmdet - INFO - Epoch [4][5100/7330] lr: 1.000e-04, eta: 7:31:49, time: 0.453, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0256, loss_rpn_bbox: 0.0441, loss_cls: 0.1858, acc: 93.2292, loss_bbox: 0.2285, loss_mask: 0.2282, loss: 0.7122 2023-11-13 19:51:55,583 - mmdet - INFO - Epoch [4][5150/7330] lr: 1.000e-04, eta: 7:31:27, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0401, loss_cls: 0.1741, acc: 93.6738, loss_bbox: 0.2142, loss_mask: 0.2291, loss: 0.6786 2023-11-13 19:52:17,663 - mmdet - INFO - Epoch [4][5200/7330] lr: 1.000e-04, eta: 7:31:04, time: 0.442, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0386, loss_cls: 0.1712, acc: 93.6716, loss_bbox: 0.2221, loss_mask: 0.2225, loss: 0.6765 2023-11-13 19:52:39,929 - mmdet - INFO - Epoch [4][5250/7330] lr: 1.000e-04, eta: 7:30:42, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0392, loss_cls: 0.1747, acc: 93.5789, loss_bbox: 0.2284, loss_mask: 0.2315, loss: 0.6937 2023-11-13 19:53:02,289 - mmdet - INFO - Epoch [4][5300/7330] lr: 1.000e-04, eta: 7:30:20, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0400, loss_cls: 0.1745, acc: 93.6948, loss_bbox: 0.2196, loss_mask: 0.2240, loss: 0.6778 2023-11-13 19:53:24,215 - mmdet - INFO - Epoch [4][5350/7330] lr: 1.000e-04, eta: 7:29:57, time: 0.439, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0386, loss_cls: 0.1666, acc: 93.8274, loss_bbox: 0.2200, loss_mask: 0.2204, loss: 0.6649 2023-11-13 19:53:46,563 - mmdet - INFO - Epoch [4][5400/7330] lr: 1.000e-04, eta: 7:29:35, time: 0.447, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0209, loss_rpn_bbox: 0.0408, loss_cls: 0.1824, acc: 93.2373, loss_bbox: 0.2242, loss_mask: 0.2216, loss: 0.6899 2023-11-13 19:54:08,804 - mmdet - INFO - Epoch [4][5450/7330] lr: 1.000e-04, eta: 7:29:12, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0404, loss_cls: 0.1795, acc: 93.3516, loss_bbox: 0.2207, loss_mask: 0.2282, loss: 0.6906 2023-11-13 19:54:31,660 - mmdet - INFO - Epoch [4][5500/7330] lr: 1.000e-04, eta: 7:28:51, time: 0.457, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0418, loss_cls: 0.1845, acc: 93.1870, loss_bbox: 0.2295, loss_mask: 0.2228, loss: 0.7004 2023-11-13 19:54:53,945 - mmdet - INFO - Epoch [4][5550/7330] lr: 1.000e-04, eta: 7:28:29, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0396, loss_cls: 0.1790, acc: 93.3618, loss_bbox: 0.2284, loss_mask: 0.2301, loss: 0.6974 2023-11-13 19:55:16,513 - mmdet - INFO - Epoch [4][5600/7330] lr: 1.000e-04, eta: 7:28:08, time: 0.451, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0416, loss_cls: 0.1829, acc: 93.2832, loss_bbox: 0.2302, loss_mask: 0.2291, loss: 0.7058 2023-11-13 19:55:38,727 - mmdet - INFO - Epoch [4][5650/7330] lr: 1.000e-04, eta: 7:27:45, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0237, loss_rpn_bbox: 0.0417, loss_cls: 0.1798, acc: 93.3740, loss_bbox: 0.2247, loss_mask: 0.2304, loss: 0.7003 2023-11-13 19:56:00,832 - mmdet - INFO - Epoch [4][5700/7330] lr: 1.000e-04, eta: 7:27:23, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0402, loss_cls: 0.1816, acc: 93.2795, loss_bbox: 0.2246, loss_mask: 0.2316, loss: 0.6999 2023-11-13 19:56:22,989 - mmdet - INFO - Epoch [4][5750/7330] lr: 1.000e-04, eta: 7:27:00, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0387, loss_cls: 0.1703, acc: 93.6592, loss_bbox: 0.2166, loss_mask: 0.2237, loss: 0.6710 2023-11-13 19:56:45,850 - mmdet - INFO - Epoch [4][5800/7330] lr: 1.000e-04, eta: 7:26:39, time: 0.457, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0242, loss_rpn_bbox: 0.0408, loss_cls: 0.1790, acc: 93.3875, loss_bbox: 0.2254, loss_mask: 0.2262, loss: 0.6955 2023-11-13 19:57:08,008 - mmdet - INFO - Epoch [4][5850/7330] lr: 1.000e-04, eta: 7:26:17, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0424, loss_cls: 0.1794, acc: 93.4543, loss_bbox: 0.2253, loss_mask: 0.2299, loss: 0.6987 2023-11-13 19:57:30,436 - mmdet - INFO - Epoch [4][5900/7330] lr: 1.000e-04, eta: 7:25:55, time: 0.449, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0219, loss_rpn_bbox: 0.0418, loss_cls: 0.1805, acc: 93.2893, loss_bbox: 0.2234, loss_mask: 0.2316, loss: 0.6992 2023-11-13 19:57:52,428 - mmdet - INFO - Epoch [4][5950/7330] lr: 1.000e-04, eta: 7:25:32, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0408, loss_cls: 0.1738, acc: 93.5889, loss_bbox: 0.2241, loss_mask: 0.2293, loss: 0.6892 2023-11-13 19:58:14,696 - mmdet - INFO - Epoch [4][6000/7330] lr: 1.000e-04, eta: 7:25:09, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0221, loss_rpn_bbox: 0.0415, loss_cls: 0.1824, acc: 93.2964, loss_bbox: 0.2351, loss_mask: 0.2306, loss: 0.7115 2023-11-13 19:58:37,087 - mmdet - INFO - Epoch [4][6050/7330] lr: 1.000e-04, eta: 7:24:47, time: 0.448, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0389, loss_cls: 0.1758, acc: 93.5271, loss_bbox: 0.2241, loss_mask: 0.2288, loss: 0.6873 2023-11-13 19:58:59,206 - mmdet - INFO - Epoch [4][6100/7330] lr: 1.000e-04, eta: 7:24:25, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0393, loss_cls: 0.1783, acc: 93.4380, loss_bbox: 0.2261, loss_mask: 0.2265, loss: 0.6903 2023-11-13 19:59:21,267 - mmdet - INFO - Epoch [4][6150/7330] lr: 1.000e-04, eta: 7:24:02, time: 0.441, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0417, loss_cls: 0.1786, acc: 93.4854, loss_bbox: 0.2243, loss_mask: 0.2245, loss: 0.6909 2023-11-13 19:59:43,569 - mmdet - INFO - Epoch [4][6200/7330] lr: 1.000e-04, eta: 7:23:40, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0393, loss_cls: 0.1779, acc: 93.5967, loss_bbox: 0.2203, loss_mask: 0.2266, loss: 0.6852 2023-11-13 20:00:06,042 - mmdet - INFO - Epoch [4][6250/7330] lr: 1.000e-04, eta: 7:23:18, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0426, loss_cls: 0.1863, acc: 93.1555, loss_bbox: 0.2357, loss_mask: 0.2282, loss: 0.7148 2023-11-13 20:00:28,537 - mmdet - INFO - Epoch [4][6300/7330] lr: 1.000e-04, eta: 7:22:56, time: 0.450, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0407, loss_cls: 0.1780, acc: 93.4944, loss_bbox: 0.2189, loss_mask: 0.2274, loss: 0.6856 2023-11-13 20:00:50,794 - mmdet - INFO - Epoch [4][6350/7330] lr: 1.000e-04, eta: 7:22:34, time: 0.445, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0411, loss_cls: 0.1831, acc: 93.3147, loss_bbox: 0.2262, loss_mask: 0.2278, loss: 0.6989 2023-11-13 20:01:13,565 - mmdet - INFO - Epoch [4][6400/7330] lr: 1.000e-04, eta: 7:22:13, time: 0.455, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0227, loss_rpn_bbox: 0.0431, loss_cls: 0.1849, acc: 93.2148, loss_bbox: 0.2342, loss_mask: 0.2340, loss: 0.7190 2023-11-13 20:01:35,937 - mmdet - INFO - Epoch [4][6450/7330] lr: 1.000e-04, eta: 7:21:51, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0403, loss_cls: 0.1738, acc: 93.6951, loss_bbox: 0.2180, loss_mask: 0.2234, loss: 0.6778 2023-11-13 20:01:58,339 - mmdet - INFO - Epoch [4][6500/7330] lr: 1.000e-04, eta: 7:21:29, time: 0.448, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0429, loss_cls: 0.1780, acc: 93.3916, loss_bbox: 0.2311, loss_mask: 0.2306, loss: 0.7048 2023-11-13 20:02:20,291 - mmdet - INFO - Epoch [4][6550/7330] lr: 1.000e-04, eta: 7:21:06, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0409, loss_cls: 0.1705, acc: 93.6680, loss_bbox: 0.2185, loss_mask: 0.2216, loss: 0.6730 2023-11-13 20:02:42,441 - mmdet - INFO - Epoch [4][6600/7330] lr: 1.000e-04, eta: 7:20:43, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0232, loss_rpn_bbox: 0.0411, loss_cls: 0.1770, acc: 93.4839, loss_bbox: 0.2211, loss_mask: 0.2305, loss: 0.6928 2023-11-13 20:03:05,049 - mmdet - INFO - Epoch [4][6650/7330] lr: 1.000e-04, eta: 7:20:22, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0243, loss_rpn_bbox: 0.0448, loss_cls: 0.1866, acc: 93.2024, loss_bbox: 0.2289, loss_mask: 0.2331, loss: 0.7178 2023-11-13 20:03:27,732 - mmdet - INFO - Epoch [4][6700/7330] lr: 1.000e-04, eta: 7:20:00, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0238, loss_rpn_bbox: 0.0428, loss_cls: 0.1856, acc: 93.2234, loss_bbox: 0.2306, loss_mask: 0.2311, loss: 0.7139 2023-11-13 20:03:50,943 - mmdet - INFO - Epoch [4][6750/7330] lr: 1.000e-04, eta: 7:19:40, time: 0.464, data_time: 0.033, memory: 5731, loss_rpn_cls: 0.0247, loss_rpn_bbox: 0.0449, loss_cls: 0.1931, acc: 92.9504, loss_bbox: 0.2389, loss_mask: 0.2349, loss: 0.7364 2023-11-13 20:04:13,057 - mmdet - INFO - Epoch [4][6800/7330] lr: 1.000e-04, eta: 7:19:17, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0220, loss_rpn_bbox: 0.0409, loss_cls: 0.1784, acc: 93.4229, loss_bbox: 0.2247, loss_mask: 0.2239, loss: 0.6898 2023-11-13 20:04:35,686 - mmdet - INFO - Epoch [4][6850/7330] lr: 1.000e-04, eta: 7:18:56, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0451, loss_cls: 0.1867, acc: 93.2439, loss_bbox: 0.2298, loss_mask: 0.2288, loss: 0.7127 2023-11-13 20:04:57,828 - mmdet - INFO - Epoch [4][6900/7330] lr: 1.000e-04, eta: 7:18:33, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0440, loss_cls: 0.1833, acc: 93.1443, loss_bbox: 0.2402, loss_mask: 0.2389, loss: 0.7292 2023-11-13 20:05:19,961 - mmdet - INFO - Epoch [4][6950/7330] lr: 1.000e-04, eta: 7:18:11, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0223, loss_rpn_bbox: 0.0418, loss_cls: 0.1812, acc: 93.3047, loss_bbox: 0.2252, loss_mask: 0.2277, loss: 0.6983 2023-11-13 20:05:42,331 - mmdet - INFO - Epoch [4][7000/7330] lr: 1.000e-04, eta: 7:17:49, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0416, loss_cls: 0.1775, acc: 93.3462, loss_bbox: 0.2296, loss_mask: 0.2290, loss: 0.6992 2023-11-13 20:06:04,322 - mmdet - INFO - Epoch [4][7050/7330] lr: 1.000e-04, eta: 7:17:26, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0404, loss_cls: 0.1822, acc: 93.2224, loss_bbox: 0.2280, loss_mask: 0.2210, loss: 0.6919 2023-11-13 20:06:25,895 - mmdet - INFO - Epoch [4][7100/7330] lr: 1.000e-04, eta: 7:17:02, time: 0.432, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0375, loss_cls: 0.1705, acc: 93.7273, loss_bbox: 0.2097, loss_mask: 0.2201, loss: 0.6586 2023-11-13 20:06:47,931 - mmdet - INFO - Epoch [4][7150/7330] lr: 1.000e-04, eta: 7:16:39, time: 0.441, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0230, loss_rpn_bbox: 0.0417, loss_cls: 0.1851, acc: 93.2290, loss_bbox: 0.2227, loss_mask: 0.2283, loss: 0.7008 2023-11-13 20:07:09,892 - mmdet - INFO - Epoch [4][7200/7330] lr: 1.000e-04, eta: 7:16:16, time: 0.439, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0419, loss_cls: 0.1796, acc: 93.3164, loss_bbox: 0.2299, loss_mask: 0.2281, loss: 0.7012 2023-11-13 20:07:32,623 - mmdet - INFO - Epoch [4][7250/7330] lr: 1.000e-04, eta: 7:15:55, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0229, loss_rpn_bbox: 0.0427, loss_cls: 0.1880, acc: 93.1067, loss_bbox: 0.2344, loss_mask: 0.2309, loss: 0.7189 2023-11-13 20:07:54,665 - mmdet - INFO - Epoch [4][7300/7330] lr: 1.000e-04, eta: 7:15:32, time: 0.441, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0406, loss_cls: 0.1854, acc: 93.2339, loss_bbox: 0.2217, loss_mask: 0.2263, loss: 0.6946 2023-11-13 20:08:08,303 - mmdet - INFO - Saving checkpoint at 4 epochs 2023-11-13 20:09:00,088 - mmdet - INFO - Evaluating bbox... 2023-11-13 20:09:34,200 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.464 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.694 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.512 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.312 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.504 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 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.449 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.635 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.735 2023-11-13 20:09:34,203 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.578 | bicycle | 0.360 | car | 0.466 | | motorcycle | 0.458 | airplane | 0.687 | bus | 0.658 | | train | 0.654 | truck | 0.439 | boat | 0.323 | | traffic light | 0.313 | fire hydrant | 0.711 | stop sign | 0.661 | | parking meter | 0.512 | bench | 0.284 | bird | 0.392 | | cat | 0.717 | dog | 0.668 | horse | 0.601 | | sheep | 0.567 | cow | 0.613 | elephant | 0.685 | | bear | 0.720 | zebra | 0.677 | giraffe | 0.682 | | backpack | 0.208 | umbrella | 0.440 | handbag | 0.227 | | tie | 0.361 | suitcase | 0.467 | frisbee | 0.701 | | skis | 0.294 | snowboard | 0.383 | sports ball | 0.473 | | kite | 0.450 | baseball bat | 0.374 | baseball glove | 0.421 | | skateboard | 0.572 | surfboard | 0.454 | tennis racket | 0.531 | | bottle | 0.454 | wine glass | 0.393 | cup | 0.497 | | fork | 0.430 | knife | 0.256 | spoon | 0.257 | | bowl | 0.470 | banana | 0.286 | apple | 0.239 | | sandwich | 0.410 | orange | 0.364 | broccoli | 0.271 | | carrot | 0.250 | hot dog | 0.423 | pizza | 0.530 | | donut | 0.549 | cake | 0.421 | chair | 0.358 | | couch | 0.442 | potted plant | 0.331 | bed | 0.453 | | dining table | 0.300 | toilet | 0.646 | tv | 0.613 | | laptop | 0.643 | mouse | 0.601 | remote | 0.405 | | keyboard | 0.542 | cell phone | 0.425 | microwave | 0.637 | | oven | 0.390 | toaster | 0.474 | sink | 0.429 | | refrigerator | 0.627 | book | 0.177 | clock | 0.533 | | vase | 0.422 | scissors | 0.402 | teddy bear | 0.526 | | hair drier | 0.164 | toothbrush | 0.305 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:09:34,203 - mmdet - INFO - Evaluating segm... 2023-11-13 20:10:07,782 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.423 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.664 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.455 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.236 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.458 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.610 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.547 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.547 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.547 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.381 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 ] = 0.703 2023-11-13 20:10:07,784 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.499 | bicycle | 0.210 | car | 0.427 | | motorcycle | 0.359 | airplane | 0.535 | bus | 0.664 | | train | 0.652 | truck | 0.426 | boat | 0.295 | | traffic light | 0.306 | fire hydrant | 0.693 | stop sign | 0.664 | | parking meter | 0.529 | bench | 0.214 | bird | 0.338 | | cat | 0.726 | dog | 0.631 | horse | 0.449 | | sheep | 0.512 | cow | 0.528 | elephant | 0.611 | | bear | 0.726 | zebra | 0.587 | giraffe | 0.524 | | backpack | 0.221 | umbrella | 0.526 | handbag | 0.222 | | tie | 0.356 | suitcase | 0.475 | frisbee | 0.673 | | skis | 0.043 | snowboard | 0.249 | sports ball | 0.471 | | kite | 0.314 | baseball bat | 0.277 | baseball glove | 0.449 | | skateboard | 0.362 | surfboard | 0.365 | tennis racket | 0.568 | | bottle | 0.440 | wine glass | 0.353 | cup | 0.500 | | fork | 0.227 | knife | 0.180 | spoon | 0.189 | | bowl | 0.444 | banana | 0.240 | apple | 0.239 | | sandwich | 0.431 | orange | 0.371 | broccoli | 0.254 | | carrot | 0.211 | hot dog | 0.353 | pizza | 0.527 | | donut | 0.556 | cake | 0.442 | chair | 0.258 | | couch | 0.372 | potted plant | 0.278 | bed | 0.368 | | dining table | 0.175 | toilet | 0.632 | tv | 0.655 | | laptop | 0.660 | mouse | 0.613 | remote | 0.352 | | keyboard | 0.533 | cell phone | 0.406 | microwave | 0.655 | | oven | 0.374 | toaster | 0.527 | sink | 0.409 | | refrigerator | 0.643 | book | 0.133 | clock | 0.543 | | vase | 0.422 | scissors | 0.331 | teddy bear | 0.510 | | hair drier | 0.131 | toothbrush | 0.203 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 20:10:08,378 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_3.pth was removed 2023-11-13 20:10:11,878 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_4.pth. 2023-11-13 20:10:11,879 - mmdet - INFO - Best bbox_mAP is 0.4641 at 4 epoch. 2023-11-13 20:10:11,879 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 20:10:11,879 - mmdet - INFO - Epoch(val) [4][625] bbox_mAP: 0.4641, bbox_mAP_50: 0.6943, bbox_mAP_75: 0.5124, bbox_mAP_s: 0.3117, bbox_mAP_m: 0.5038, bbox_mAP_l: 0.5968, bbox_mAP_copypaste: 0.4641 0.6943 0.5124 0.3117 0.5038 0.5968, segm_mAP: 0.4227, segm_mAP_50: 0.6639, segm_mAP_75: 0.4550, segm_mAP_s: 0.2357, segm_mAP_m: 0.4582, segm_mAP_l: 0.6100, segm_mAP_copypaste: 0.4227 0.6639 0.4550 0.2357 0.4582 0.6100 2023-11-13 20:10:37,967 - mmdet - INFO - Epoch [5][50/7330] lr: 1.000e-04, eta: 7:14:38, time: 0.521, data_time: 0.093, memory: 5731, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0404, loss_cls: 0.1665, acc: 93.7881, loss_bbox: 0.2176, loss_mask: 0.2225, loss: 0.6665 2023-11-13 20:11:00,432 - mmdet - INFO - Epoch [5][100/7330] lr: 1.000e-04, eta: 7:14:16, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0366, loss_cls: 0.1592, acc: 94.1108, loss_bbox: 0.2093, loss_mask: 0.2154, loss: 0.6381 2023-11-13 20:11:23,340 - mmdet - INFO - Epoch [5][150/7330] lr: 1.000e-04, eta: 7:13:55, time: 0.458, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0411, loss_cls: 0.1706, acc: 93.6677, loss_bbox: 0.2200, loss_mask: 0.2205, loss: 0.6717 2023-11-13 20:11:45,942 - mmdet - INFO - Epoch [5][200/7330] lr: 1.000e-04, eta: 7:13:33, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0391, loss_cls: 0.1674, acc: 93.7476, loss_bbox: 0.2140, loss_mask: 0.2234, loss: 0.6647 2023-11-13 20:12:08,629 - mmdet - INFO - Epoch [5][250/7330] lr: 1.000e-04, eta: 7:13:12, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0392, loss_cls: 0.1699, acc: 93.5725, loss_bbox: 0.2202, loss_mask: 0.2177, loss: 0.6653 2023-11-13 20:12:31,005 - mmdet - INFO - Epoch [5][300/7330] lr: 1.000e-04, eta: 7:12:50, time: 0.448, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0344, loss_cls: 0.1606, acc: 93.9834, loss_bbox: 0.2088, loss_mask: 0.2202, loss: 0.6402 2023-11-13 20:12:53,155 - mmdet - INFO - Epoch [5][350/7330] lr: 1.000e-04, eta: 7:12:27, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0398, loss_cls: 0.1656, acc: 93.8804, loss_bbox: 0.2091, loss_mask: 0.2189, loss: 0.6530 2023-11-13 20:13:15,625 - mmdet - INFO - Epoch [5][400/7330] lr: 1.000e-04, eta: 7:12:06, time: 0.449, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0393, loss_cls: 0.1635, acc: 93.9331, loss_bbox: 0.2162, loss_mask: 0.2255, loss: 0.6644 2023-11-13 20:13:38,068 - mmdet - INFO - Epoch [5][450/7330] lr: 1.000e-04, eta: 7:11:44, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0411, loss_cls: 0.1659, acc: 93.7627, loss_bbox: 0.2194, loss_mask: 0.2214, loss: 0.6663 2023-11-13 20:14:00,746 - mmdet - INFO - Epoch [5][500/7330] lr: 1.000e-04, eta: 7:11:22, time: 0.454, data_time: 0.034, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0427, loss_cls: 0.1734, acc: 93.5107, loss_bbox: 0.2293, loss_mask: 0.2243, loss: 0.6896 2023-11-13 20:14:23,797 - mmdet - INFO - Epoch [5][550/7330] lr: 1.000e-04, eta: 7:11:01, time: 0.461, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0404, loss_cls: 0.1649, acc: 93.8972, loss_bbox: 0.2126, loss_mask: 0.2198, loss: 0.6580 2023-11-13 20:14:46,642 - mmdet - INFO - Epoch [5][600/7330] lr: 1.000e-04, eta: 7:10:40, time: 0.457, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0402, loss_cls: 0.1755, acc: 93.4446, loss_bbox: 0.2290, loss_mask: 0.2231, loss: 0.6866 2023-11-13 20:15:09,307 - mmdet - INFO - Epoch [5][650/7330] lr: 1.000e-04, eta: 7:10:19, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0404, loss_cls: 0.1676, acc: 93.8071, loss_bbox: 0.2137, loss_mask: 0.2212, loss: 0.6636 2023-11-13 20:15:31,792 - mmdet - INFO - Epoch [5][700/7330] lr: 1.000e-04, eta: 7:09:57, time: 0.450, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0406, loss_cls: 0.1741, acc: 93.4788, loss_bbox: 0.2210, loss_mask: 0.2234, loss: 0.6774 2023-11-13 20:15:54,677 - mmdet - INFO - Epoch [5][750/7330] lr: 1.000e-04, eta: 7:09:36, time: 0.458, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0398, loss_cls: 0.1677, acc: 93.7576, loss_bbox: 0.2166, loss_mask: 0.2214, loss: 0.6657 2023-11-13 20:16:16,731 - mmdet - INFO - Epoch [5][800/7330] lr: 1.000e-04, eta: 7:09:13, time: 0.441, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0379, loss_cls: 0.1572, acc: 94.0293, loss_bbox: 0.2058, loss_mask: 0.2147, loss: 0.6341 2023-11-13 20:16:38,920 - mmdet - INFO - Epoch [5][850/7330] lr: 1.000e-04, eta: 7:08:51, time: 0.444, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0354, loss_cls: 0.1542, acc: 94.3372, loss_bbox: 0.2027, loss_mask: 0.2153, loss: 0.6249 2023-11-13 20:17:01,556 - mmdet - INFO - Epoch [5][900/7330] lr: 1.000e-04, eta: 7:08:29, time: 0.453, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0402, loss_cls: 0.1676, acc: 93.6541, loss_bbox: 0.2183, loss_mask: 0.2238, loss: 0.6706 2023-11-13 20:17:24,412 - mmdet - INFO - Epoch [5][950/7330] lr: 1.000e-04, eta: 7:08:08, time: 0.457, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0398, loss_cls: 0.1692, acc: 93.6682, loss_bbox: 0.2172, loss_mask: 0.2158, loss: 0.6620 2023-11-13 20:17:47,514 - mmdet - INFO - Epoch [5][1000/7330] lr: 1.000e-04, eta: 7:07:48, time: 0.462, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0407, loss_cls: 0.1745, acc: 93.4790, loss_bbox: 0.2234, loss_mask: 0.2266, loss: 0.6864 2023-11-13 20:18:09,853 - mmdet - INFO - Epoch [5][1050/7330] lr: 1.000e-04, eta: 7:07:25, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0394, loss_cls: 0.1689, acc: 93.7046, loss_bbox: 0.2147, loss_mask: 0.2256, loss: 0.6670 2023-11-13 20:18:32,498 - mmdet - INFO - Epoch [5][1100/7330] lr: 1.000e-04, eta: 7:07:04, time: 0.453, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0393, loss_cls: 0.1650, acc: 93.8313, loss_bbox: 0.2188, loss_mask: 0.2180, loss: 0.6602 2023-11-13 20:18:54,727 - mmdet - INFO - Epoch [5][1150/7330] lr: 1.000e-04, eta: 7:06:42, time: 0.445, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0399, loss_cls: 0.1657, acc: 93.8120, loss_bbox: 0.2189, loss_mask: 0.2210, loss: 0.6655 2023-11-13 20:19:17,287 - mmdet - INFO - Epoch [5][1200/7330] lr: 1.000e-04, eta: 7:06:20, time: 0.451, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0400, loss_cls: 0.1695, acc: 93.6958, loss_bbox: 0.2187, loss_mask: 0.2177, loss: 0.6648 2023-11-13 20:19:39,876 - mmdet - INFO - Epoch [5][1250/7330] lr: 1.000e-04, eta: 7:05:58, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0390, loss_cls: 0.1737, acc: 93.5742, loss_bbox: 0.2225, loss_mask: 0.2271, loss: 0.6808 2023-11-13 20:20:02,630 - mmdet - INFO - Epoch [5][1300/7330] lr: 1.000e-04, eta: 7:05:37, time: 0.455, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0411, loss_cls: 0.1746, acc: 93.6265, loss_bbox: 0.2220, loss_mask: 0.2212, loss: 0.6795 2023-11-13 20:20:25,227 - mmdet - INFO - Epoch [5][1350/7330] lr: 1.000e-04, eta: 7:05:15, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0406, loss_cls: 0.1675, acc: 93.7036, loss_bbox: 0.2162, loss_mask: 0.2199, loss: 0.6639 2023-11-13 20:20:47,793 - mmdet - INFO - Epoch [5][1400/7330] lr: 1.000e-04, eta: 7:04:53, time: 0.451, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0405, loss_cls: 0.1743, acc: 93.4570, loss_bbox: 0.2230, loss_mask: 0.2274, loss: 0.6855 2023-11-13 20:21:10,612 - mmdet - INFO - Epoch [5][1450/7330] lr: 1.000e-04, eta: 7:04:32, time: 0.456, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0402, loss_cls: 0.1718, acc: 93.5066, loss_bbox: 0.2243, loss_mask: 0.2286, loss: 0.6854 2023-11-13 20:21:32,916 - mmdet - INFO - Epoch [5][1500/7330] lr: 1.000e-04, eta: 7:04:10, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0379, loss_cls: 0.1718, acc: 93.5630, loss_bbox: 0.2254, loss_mask: 0.2255, loss: 0.6791 2023-11-13 20:21:55,671 - mmdet - INFO - Epoch [5][1550/7330] lr: 1.000e-04, eta: 7:03:49, time: 0.455, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0414, loss_cls: 0.1785, acc: 93.2585, loss_bbox: 0.2275, loss_mask: 0.2247, loss: 0.6925 2023-11-13 20:22:17,974 - mmdet - INFO - Epoch [5][1600/7330] lr: 1.000e-04, eta: 7:03:26, time: 0.446, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0400, loss_cls: 0.1705, acc: 93.6682, loss_bbox: 0.2195, loss_mask: 0.2223, loss: 0.6716 2023-11-13 20:22:40,231 - mmdet - INFO - Epoch [5][1650/7330] lr: 1.000e-04, eta: 7:03:04, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0393, loss_cls: 0.1656, acc: 93.8301, loss_bbox: 0.2119, loss_mask: 0.2222, loss: 0.6592 2023-11-13 20:23:02,218 - mmdet - INFO - Epoch [5][1700/7330] lr: 1.000e-04, eta: 7:02:41, time: 0.440, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0356, loss_cls: 0.1559, acc: 94.1597, loss_bbox: 0.2056, loss_mask: 0.2197, loss: 0.6337 2023-11-13 20:23:24,667 - mmdet - INFO - Epoch [5][1750/7330] lr: 1.000e-04, eta: 7:02:19, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0409, loss_cls: 0.1742, acc: 93.5269, loss_bbox: 0.2262, loss_mask: 0.2214, loss: 0.6820 2023-11-13 20:23:47,009 - mmdet - INFO - Epoch [5][1800/7330] lr: 1.000e-04, eta: 7:01:57, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0382, loss_cls: 0.1720, acc: 93.6348, loss_bbox: 0.2187, loss_mask: 0.2241, loss: 0.6723 2023-11-13 20:24:09,345 - mmdet - INFO - Epoch [5][1850/7330] lr: 1.000e-04, eta: 7:01:35, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0208, loss_rpn_bbox: 0.0412, loss_cls: 0.1670, acc: 93.7544, loss_bbox: 0.2191, loss_mask: 0.2235, loss: 0.6717 2023-11-13 20:24:31,509 - mmdet - INFO - Epoch [5][1900/7330] lr: 1.000e-04, eta: 7:01:13, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0402, loss_cls: 0.1703, acc: 93.6218, loss_bbox: 0.2212, loss_mask: 0.2244, loss: 0.6760 2023-11-13 20:24:54,109 - mmdet - INFO - Epoch [5][1950/7330] lr: 1.000e-04, eta: 7:00:51, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0398, loss_cls: 0.1725, acc: 93.5830, loss_bbox: 0.2221, loss_mask: 0.2240, loss: 0.6776 2023-11-13 20:25:16,375 - mmdet - INFO - Epoch [5][2000/7330] lr: 1.000e-04, eta: 7:00:29, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1697, acc: 93.6763, loss_bbox: 0.2160, loss_mask: 0.2225, loss: 0.6660 2023-11-13 20:25:38,784 - mmdet - INFO - Epoch [5][2050/7330] lr: 1.000e-04, eta: 7:00:07, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0367, loss_cls: 0.1648, acc: 93.7878, loss_bbox: 0.2074, loss_mask: 0.2138, loss: 0.6412 2023-11-13 20:26:01,032 - mmdet - INFO - Epoch [5][2100/7330] lr: 1.000e-04, eta: 6:59:44, time: 0.445, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0390, loss_cls: 0.1690, acc: 93.7651, loss_bbox: 0.2137, loss_mask: 0.2223, loss: 0.6623 2023-11-13 20:26:23,769 - mmdet - INFO - Epoch [5][2150/7330] lr: 1.000e-04, eta: 6:59:23, time: 0.455, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0394, loss_cls: 0.1669, acc: 93.7944, loss_bbox: 0.2215, loss_mask: 0.2292, loss: 0.6771 2023-11-13 20:26:46,619 - mmdet - INFO - Epoch [5][2200/7330] lr: 1.000e-04, eta: 6:59:02, time: 0.457, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0384, loss_cls: 0.1719, acc: 93.6951, loss_bbox: 0.2181, loss_mask: 0.2225, loss: 0.6706 2023-11-13 20:27:08,937 - mmdet - INFO - Epoch [5][2250/7330] lr: 1.000e-04, eta: 6:58:39, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0408, loss_cls: 0.1767, acc: 93.3591, loss_bbox: 0.2238, loss_mask: 0.2259, loss: 0.6869 2023-11-13 20:27:31,558 - mmdet - INFO - Epoch [5][2300/7330] lr: 1.000e-04, eta: 6:58:18, time: 0.452, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0401, loss_cls: 0.1726, acc: 93.6221, loss_bbox: 0.2184, loss_mask: 0.2228, loss: 0.6735 2023-11-13 20:27:54,428 - mmdet - INFO - Epoch [5][2350/7330] lr: 1.000e-04, eta: 6:57:57, time: 0.457, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0225, loss_rpn_bbox: 0.0404, loss_cls: 0.1726, acc: 93.6450, loss_bbox: 0.2172, loss_mask: 0.2234, loss: 0.6761 2023-11-13 20:28:16,601 - mmdet - INFO - Epoch [5][2400/7330] lr: 1.000e-04, eta: 6:57:34, time: 0.443, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0391, loss_cls: 0.1655, acc: 93.8154, loss_bbox: 0.2136, loss_mask: 0.2256, loss: 0.6626 2023-11-13 20:28:39,065 - mmdet - INFO - Epoch [5][2450/7330] lr: 1.000e-04, eta: 6:57:12, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0396, loss_cls: 0.1652, acc: 93.9795, loss_bbox: 0.2111, loss_mask: 0.2182, loss: 0.6529 2023-11-13 20:29:01,739 - mmdet - INFO - Epoch [5][2500/7330] lr: 1.000e-04, eta: 6:56:51, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0401, loss_cls: 0.1759, acc: 93.4990, loss_bbox: 0.2234, loss_mask: 0.2232, loss: 0.6830 2023-11-13 20:29:24,107 - mmdet - INFO - Epoch [5][2550/7330] lr: 1.000e-04, eta: 6:56:28, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0383, loss_cls: 0.1631, acc: 93.8633, loss_bbox: 0.2124, loss_mask: 0.2173, loss: 0.6497 2023-11-13 20:29:46,482 - mmdet - INFO - Epoch [5][2600/7330] lr: 1.000e-04, eta: 6:56:06, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0402, loss_cls: 0.1620, acc: 93.8411, loss_bbox: 0.2157, loss_mask: 0.2186, loss: 0.6531 2023-11-13 20:30:09,007 - mmdet - INFO - Epoch [5][2650/7330] lr: 1.000e-04, eta: 6:55:45, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0390, loss_cls: 0.1618, acc: 93.9128, loss_bbox: 0.2109, loss_mask: 0.2172, loss: 0.6496 2023-11-13 20:30:31,563 - mmdet - INFO - Epoch [5][2700/7330] lr: 1.000e-04, eta: 6:55:23, time: 0.451, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0405, loss_cls: 0.1722, acc: 93.6399, loss_bbox: 0.2167, loss_mask: 0.2263, loss: 0.6775 2023-11-13 20:30:53,817 - mmdet - INFO - Epoch [5][2750/7330] lr: 1.000e-04, eta: 6:55:00, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0396, loss_cls: 0.1684, acc: 93.7192, loss_bbox: 0.2213, loss_mask: 0.2266, loss: 0.6749 2023-11-13 20:31:16,143 - mmdet - INFO - Epoch [5][2800/7330] lr: 1.000e-04, eta: 6:54:38, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0411, loss_cls: 0.1710, acc: 93.5933, loss_bbox: 0.2201, loss_mask: 0.2231, loss: 0.6751 2023-11-13 20:31:38,791 - mmdet - INFO - Epoch [5][2850/7330] lr: 1.000e-04, eta: 6:54:17, time: 0.453, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0409, loss_cls: 0.1667, acc: 93.7844, loss_bbox: 0.2128, loss_mask: 0.2230, loss: 0.6635 2023-11-13 20:32:01,911 - mmdet - INFO - Epoch [5][2900/7330] lr: 1.000e-04, eta: 6:53:56, time: 0.462, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0424, loss_cls: 0.1685, acc: 93.6636, loss_bbox: 0.2216, loss_mask: 0.2224, loss: 0.6756 2023-11-13 20:32:24,535 - mmdet - INFO - Epoch [5][2950/7330] lr: 1.000e-04, eta: 6:53:34, time: 0.452, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0211, loss_rpn_bbox: 0.0419, loss_cls: 0.1759, acc: 93.4651, loss_bbox: 0.2239, loss_mask: 0.2282, loss: 0.6910 2023-11-13 20:32:47,411 - mmdet - INFO - Epoch [5][3000/7330] lr: 1.000e-04, eta: 6:53:13, time: 0.457, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0413, loss_cls: 0.1690, acc: 93.6787, loss_bbox: 0.2199, loss_mask: 0.2246, loss: 0.6732 2023-11-13 20:33:09,560 - mmdet - INFO - Epoch [5][3050/7330] lr: 1.000e-04, eta: 6:52:50, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0390, loss_cls: 0.1707, acc: 93.6975, loss_bbox: 0.2115, loss_mask: 0.2186, loss: 0.6581 2023-11-13 20:33:32,342 - mmdet - INFO - Epoch [5][3100/7330] lr: 1.000e-04, eta: 6:52:29, time: 0.456, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0420, loss_cls: 0.1759, acc: 93.5159, loss_bbox: 0.2241, loss_mask: 0.2253, loss: 0.6879 2023-11-13 20:33:54,763 - mmdet - INFO - Epoch [5][3150/7330] lr: 1.000e-04, eta: 6:52:07, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0411, loss_cls: 0.1674, acc: 93.6938, loss_bbox: 0.2173, loss_mask: 0.2212, loss: 0.6658 2023-11-13 20:34:16,660 - mmdet - INFO - Epoch [5][3200/7330] lr: 1.000e-04, eta: 6:51:44, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0404, loss_cls: 0.1642, acc: 93.9880, loss_bbox: 0.2136, loss_mask: 0.2220, loss: 0.6580 2023-11-13 20:34:39,190 - mmdet - INFO - Epoch [5][3250/7330] lr: 1.000e-04, eta: 6:51:22, time: 0.451, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0419, loss_cls: 0.1802, acc: 93.2595, loss_bbox: 0.2282, loss_mask: 0.2248, loss: 0.6962 2023-11-13 20:35:01,373 - mmdet - INFO - Epoch [5][3300/7330] lr: 1.000e-04, eta: 6:51:00, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0393, loss_cls: 0.1647, acc: 93.7695, loss_bbox: 0.2143, loss_mask: 0.2194, loss: 0.6571 2023-11-13 20:35:23,786 - mmdet - INFO - Epoch [5][3350/7330] lr: 1.000e-04, eta: 6:50:38, time: 0.448, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0386, loss_cls: 0.1699, acc: 93.7378, loss_bbox: 0.2142, loss_mask: 0.2179, loss: 0.6600 2023-11-13 20:35:46,125 - mmdet - INFO - Epoch [5][3400/7330] lr: 1.000e-04, eta: 6:50:15, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0391, loss_cls: 0.1718, acc: 93.6101, loss_bbox: 0.2178, loss_mask: 0.2204, loss: 0.6679 2023-11-13 20:36:08,496 - mmdet - INFO - Epoch [5][3450/7330] lr: 1.000e-04, eta: 6:49:53, time: 0.447, data_time: 0.034, memory: 5731, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0397, loss_cls: 0.1698, acc: 93.6804, loss_bbox: 0.2214, loss_mask: 0.2198, loss: 0.6717 2023-11-13 20:36:30,627 - mmdet - INFO - Epoch [5][3500/7330] lr: 1.000e-04, eta: 6:49:31, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0391, loss_cls: 0.1671, acc: 93.8015, loss_bbox: 0.2108, loss_mask: 0.2174, loss: 0.6535 2023-11-13 20:36:53,330 - mmdet - INFO - Epoch [5][3550/7330] lr: 1.000e-04, eta: 6:49:09, time: 0.454, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0401, loss_cls: 0.1613, acc: 94.0276, loss_bbox: 0.2065, loss_mask: 0.2182, loss: 0.6458 2023-11-13 20:37:15,618 - mmdet - INFO - Epoch [5][3600/7330] lr: 1.000e-04, eta: 6:48:47, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0397, loss_cls: 0.1673, acc: 93.7114, loss_bbox: 0.2144, loss_mask: 0.2254, loss: 0.6666 2023-11-13 20:37:38,170 - mmdet - INFO - Epoch [5][3650/7330] lr: 1.000e-04, eta: 6:48:25, time: 0.451, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0405, loss_cls: 0.1716, acc: 93.5986, loss_bbox: 0.2214, loss_mask: 0.2199, loss: 0.6746 2023-11-13 20:38:00,675 - mmdet - INFO - Epoch [5][3700/7330] lr: 1.000e-04, eta: 6:48:03, time: 0.450, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0400, loss_cls: 0.1680, acc: 93.7839, loss_bbox: 0.2156, loss_mask: 0.2239, loss: 0.6671 2023-11-13 20:38:22,791 - mmdet - INFO - Epoch [5][3750/7330] lr: 1.000e-04, eta: 6:47:41, time: 0.442, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0396, loss_cls: 0.1702, acc: 93.6265, loss_bbox: 0.2139, loss_mask: 0.2201, loss: 0.6634 2023-11-13 20:38:45,587 - mmdet - INFO - Epoch [5][3800/7330] lr: 1.000e-04, eta: 6:47:19, time: 0.456, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0373, loss_cls: 0.1596, acc: 93.9949, loss_bbox: 0.2116, loss_mask: 0.2232, loss: 0.6497 2023-11-13 20:39:08,080 - mmdet - INFO - Epoch [5][3850/7330] lr: 1.000e-04, eta: 6:46:57, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0401, loss_cls: 0.1756, acc: 93.4424, loss_bbox: 0.2220, loss_mask: 0.2250, loss: 0.6819 2023-11-13 20:39:30,466 - mmdet - INFO - Epoch [5][3900/7330] lr: 1.000e-04, eta: 6:46:35, time: 0.448, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0376, loss_cls: 0.1638, acc: 93.9377, loss_bbox: 0.2094, loss_mask: 0.2266, loss: 0.6575 2023-11-13 20:39:52,869 - mmdet - INFO - Epoch [5][3950/7330] lr: 1.000e-04, eta: 6:46:13, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0215, loss_rpn_bbox: 0.0418, loss_cls: 0.1744, acc: 93.5056, loss_bbox: 0.2226, loss_mask: 0.2229, loss: 0.6833 2023-11-13 20:40:15,225 - mmdet - INFO - Epoch [5][4000/7330] lr: 1.000e-04, eta: 6:45:51, time: 0.447, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0403, loss_cls: 0.1715, acc: 93.5999, loss_bbox: 0.2214, loss_mask: 0.2188, loss: 0.6697 2023-11-13 20:40:37,760 - mmdet - INFO - Epoch [5][4050/7330] lr: 1.000e-04, eta: 6:45:29, time: 0.451, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0373, loss_cls: 0.1663, acc: 93.8154, loss_bbox: 0.2182, loss_mask: 0.2198, loss: 0.6595 2023-11-13 20:41:00,594 - mmdet - INFO - Epoch [5][4100/7330] lr: 1.000e-04, eta: 6:45:08, time: 0.457, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0428, loss_cls: 0.1763, acc: 93.5259, loss_bbox: 0.2228, loss_mask: 0.2260, loss: 0.6896 2023-11-13 20:41:22,754 - mmdet - INFO - Epoch [5][4150/7330] lr: 1.000e-04, eta: 6:44:45, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0395, loss_cls: 0.1670, acc: 93.8833, loss_bbox: 0.2128, loss_mask: 0.2224, loss: 0.6614 2023-11-13 20:41:45,306 - mmdet - INFO - Epoch [5][4200/7330] lr: 1.000e-04, eta: 6:44:23, time: 0.451, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0226, loss_rpn_bbox: 0.0414, loss_cls: 0.1686, acc: 93.7410, loss_bbox: 0.2186, loss_mask: 0.2223, loss: 0.6734 2023-11-13 20:42:08,172 - mmdet - INFO - Epoch [5][4250/7330] lr: 1.000e-04, eta: 6:44:02, time: 0.457, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0201, loss_rpn_bbox: 0.0395, loss_cls: 0.1783, acc: 93.3074, loss_bbox: 0.2277, loss_mask: 0.2262, loss: 0.6917 2023-11-13 20:42:30,545 - mmdet - INFO - Epoch [5][4300/7330] lr: 1.000e-04, eta: 6:43:40, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0384, loss_cls: 0.1646, acc: 93.9358, loss_bbox: 0.2150, loss_mask: 0.2178, loss: 0.6562 2023-11-13 20:42:52,849 - mmdet - INFO - Epoch [5][4350/7330] lr: 1.000e-04, eta: 6:43:17, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0394, loss_cls: 0.1680, acc: 93.6367, loss_bbox: 0.2160, loss_mask: 0.2243, loss: 0.6657 2023-11-13 20:43:15,282 - mmdet - INFO - Epoch [5][4400/7330] lr: 1.000e-04, eta: 6:42:55, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0412, loss_cls: 0.1723, acc: 93.5320, loss_bbox: 0.2217, loss_mask: 0.2250, loss: 0.6789 2023-11-13 20:43:37,857 - mmdet - INFO - Epoch [5][4450/7330] lr: 1.000e-04, eta: 6:42:34, time: 0.451, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0375, loss_cls: 0.1644, acc: 94.0188, loss_bbox: 0.2099, loss_mask: 0.2218, loss: 0.6538 2023-11-13 20:44:00,340 - mmdet - INFO - Epoch [5][4500/7330] lr: 1.000e-04, eta: 6:42:12, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0400, loss_cls: 0.1630, acc: 93.9429, loss_bbox: 0.2101, loss_mask: 0.2166, loss: 0.6482 2023-11-13 20:44:22,826 - mmdet - INFO - Epoch [5][4550/7330] lr: 1.000e-04, eta: 6:41:50, time: 0.450, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0406, loss_cls: 0.1737, acc: 93.5774, loss_bbox: 0.2213, loss_mask: 0.2246, loss: 0.6816 2023-11-13 20:44:45,228 - mmdet - INFO - Epoch [5][4600/7330] lr: 1.000e-04, eta: 6:41:28, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0383, loss_cls: 0.1664, acc: 93.8083, loss_bbox: 0.2148, loss_mask: 0.2226, loss: 0.6599 2023-11-13 20:45:07,729 - mmdet - INFO - Epoch [5][4650/7330] lr: 1.000e-04, eta: 6:41:06, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0384, loss_cls: 0.1708, acc: 93.7058, loss_bbox: 0.2150, loss_mask: 0.2203, loss: 0.6643 2023-11-13 20:45:30,246 - mmdet - INFO - Epoch [5][4700/7330] lr: 1.000e-04, eta: 6:40:44, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0377, loss_cls: 0.1653, acc: 93.9248, loss_bbox: 0.2077, loss_mask: 0.2129, loss: 0.6422 2023-11-13 20:45:52,597 - mmdet - INFO - Epoch [5][4750/7330] lr: 1.000e-04, eta: 6:40:22, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0402, loss_cls: 0.1729, acc: 93.6790, loss_bbox: 0.2185, loss_mask: 0.2228, loss: 0.6749 2023-11-13 20:46:14,609 - mmdet - INFO - Epoch [5][4800/7330] lr: 1.000e-04, eta: 6:39:59, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0400, loss_cls: 0.1701, acc: 93.6611, loss_bbox: 0.2181, loss_mask: 0.2210, loss: 0.6680 2023-11-13 20:46:37,612 - mmdet - INFO - Epoch [5][4850/7330] lr: 1.000e-04, eta: 6:39:38, time: 0.460, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0424, loss_cls: 0.1758, acc: 93.4417, loss_bbox: 0.2231, loss_mask: 0.2208, loss: 0.6837 2023-11-13 20:47:00,191 - mmdet - INFO - Epoch [5][4900/7330] lr: 1.000e-04, eta: 6:39:16, time: 0.452, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0394, loss_cls: 0.1690, acc: 93.7773, loss_bbox: 0.2135, loss_mask: 0.2181, loss: 0.6596 2023-11-13 20:47:22,805 - mmdet - INFO - Epoch [5][4950/7330] lr: 1.000e-04, eta: 6:38:54, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0390, loss_cls: 0.1685, acc: 93.6599, loss_bbox: 0.2118, loss_mask: 0.2196, loss: 0.6576 2023-11-13 20:47:45,558 - mmdet - INFO - Epoch [5][5000/7330] lr: 1.000e-04, eta: 6:38:32, time: 0.455, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0210, loss_rpn_bbox: 0.0391, loss_cls: 0.1699, acc: 93.6655, loss_bbox: 0.2198, loss_mask: 0.2221, loss: 0.6720 2023-11-13 20:48:08,135 - mmdet - INFO - Epoch [5][5050/7330] lr: 1.000e-04, eta: 6:38:11, time: 0.451, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0388, loss_cls: 0.1659, acc: 93.8674, loss_bbox: 0.2148, loss_mask: 0.2207, loss: 0.6601 2023-11-13 20:48:30,651 - mmdet - INFO - Epoch [5][5100/7330] lr: 1.000e-04, eta: 6:37:49, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0416, loss_cls: 0.1722, acc: 93.6204, loss_bbox: 0.2209, loss_mask: 0.2252, loss: 0.6787 2023-11-13 20:48:52,934 - mmdet - INFO - Epoch [5][5150/7330] lr: 1.000e-04, eta: 6:37:26, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0385, loss_cls: 0.1711, acc: 93.6748, loss_bbox: 0.2171, loss_mask: 0.2239, loss: 0.6705 2023-11-13 20:49:15,303 - mmdet - INFO - Epoch [5][5200/7330] lr: 1.000e-04, eta: 6:37:04, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0383, loss_cls: 0.1627, acc: 93.8826, loss_bbox: 0.2118, loss_mask: 0.2200, loss: 0.6514 2023-11-13 20:49:37,725 - mmdet - INFO - Epoch [5][5250/7330] lr: 1.000e-04, eta: 6:36:42, time: 0.448, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0388, loss_cls: 0.1691, acc: 93.7239, loss_bbox: 0.2186, loss_mask: 0.2248, loss: 0.6697 2023-11-13 20:50:00,322 - mmdet - INFO - Epoch [5][5300/7330] lr: 1.000e-04, eta: 6:36:20, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0212, loss_rpn_bbox: 0.0400, loss_cls: 0.1740, acc: 93.5710, loss_bbox: 0.2187, loss_mask: 0.2251, loss: 0.6791 2023-11-13 20:50:23,242 - mmdet - INFO - Epoch [5][5350/7330] lr: 1.000e-04, eta: 6:35:59, time: 0.458, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0423, loss_cls: 0.1725, acc: 93.6140, loss_bbox: 0.2237, loss_mask: 0.2273, loss: 0.6860 2023-11-13 20:50:45,607 - mmdet - INFO - Epoch [5][5400/7330] lr: 1.000e-04, eta: 6:35:37, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0400, loss_cls: 0.1752, acc: 93.5347, loss_bbox: 0.2245, loss_mask: 0.2234, loss: 0.6829 2023-11-13 20:51:08,248 - mmdet - INFO - Epoch [5][5450/7330] lr: 1.000e-04, eta: 6:35:15, time: 0.453, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0217, loss_rpn_bbox: 0.0410, loss_cls: 0.1855, acc: 93.1836, loss_bbox: 0.2284, loss_mask: 0.2274, loss: 0.7039 2023-11-13 20:51:30,637 - mmdet - INFO - Epoch [5][5500/7330] lr: 1.000e-04, eta: 6:34:53, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0401, loss_cls: 0.1700, acc: 93.6401, loss_bbox: 0.2145, loss_mask: 0.2195, loss: 0.6640 2023-11-13 20:51:53,260 - mmdet - INFO - Epoch [5][5550/7330] lr: 1.000e-04, eta: 6:34:31, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0216, loss_rpn_bbox: 0.0427, loss_cls: 0.1803, acc: 93.2810, loss_bbox: 0.2257, loss_mask: 0.2312, loss: 0.7015 2023-11-13 20:52:15,466 - mmdet - INFO - Epoch [5][5600/7330] lr: 1.000e-04, eta: 6:34:09, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0206, loss_rpn_bbox: 0.0380, loss_cls: 0.1683, acc: 93.7000, loss_bbox: 0.2119, loss_mask: 0.2156, loss: 0.6542 2023-11-13 20:52:37,931 - mmdet - INFO - Epoch [5][5650/7330] lr: 1.000e-04, eta: 6:33:47, time: 0.449, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0387, loss_cls: 0.1674, acc: 93.8691, loss_bbox: 0.2137, loss_mask: 0.2178, loss: 0.6565 2023-11-13 20:52:59,952 - mmdet - INFO - Epoch [5][5700/7330] lr: 1.000e-04, eta: 6:33:24, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0392, loss_cls: 0.1760, acc: 93.4514, loss_bbox: 0.2282, loss_mask: 0.2268, loss: 0.6894 2023-11-13 20:53:22,365 - mmdet - INFO - Epoch [5][5750/7330] lr: 1.000e-04, eta: 6:33:02, time: 0.448, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0389, loss_cls: 0.1663, acc: 93.8274, loss_bbox: 0.2131, loss_mask: 0.2181, loss: 0.6559 2023-11-13 20:53:44,997 - mmdet - INFO - Epoch [5][5800/7330] lr: 1.000e-04, eta: 6:32:40, time: 0.453, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0218, loss_rpn_bbox: 0.0404, loss_cls: 0.1766, acc: 93.4500, loss_bbox: 0.2200, loss_mask: 0.2223, loss: 0.6811 2023-11-13 20:54:07,479 - mmdet - INFO - Epoch [5][5850/7330] lr: 1.000e-04, eta: 6:32:18, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0404, loss_cls: 0.1759, acc: 93.3904, loss_bbox: 0.2194, loss_mask: 0.2225, loss: 0.6795 2023-11-13 20:54:29,997 - mmdet - INFO - Epoch [5][5900/7330] lr: 1.000e-04, eta: 6:31:56, time: 0.450, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0407, loss_cls: 0.1701, acc: 93.6389, loss_bbox: 0.2169, loss_mask: 0.2214, loss: 0.6696 2023-11-13 20:54:52,331 - mmdet - INFO - Epoch [5][5950/7330] lr: 1.000e-04, eta: 6:31:34, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0401, loss_cls: 0.1720, acc: 93.6956, loss_bbox: 0.2176, loss_mask: 0.2230, loss: 0.6717 2023-11-13 20:55:14,265 - mmdet - INFO - Epoch [5][6000/7330] lr: 1.000e-04, eta: 6:31:11, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0407, loss_cls: 0.1672, acc: 93.8337, loss_bbox: 0.2089, loss_mask: 0.2198, loss: 0.6545 2023-11-13 20:55:36,976 - mmdet - INFO - Epoch [5][6050/7330] lr: 1.000e-04, eta: 6:30:49, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0203, loss_rpn_bbox: 0.0393, loss_cls: 0.1663, acc: 93.8086, loss_bbox: 0.2124, loss_mask: 0.2204, loss: 0.6587 2023-11-13 20:55:59,167 - mmdet - INFO - Epoch [5][6100/7330] lr: 1.000e-04, eta: 6:30:27, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0381, loss_cls: 0.1665, acc: 93.8804, loss_bbox: 0.2120, loss_mask: 0.2217, loss: 0.6574 2023-11-13 20:56:22,213 - mmdet - INFO - Epoch [5][6150/7330] lr: 1.000e-04, eta: 6:30:06, time: 0.461, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0390, loss_cls: 0.1672, acc: 93.8218, loss_bbox: 0.2122, loss_mask: 0.2215, loss: 0.6587 2023-11-13 20:56:45,059 - mmdet - INFO - Epoch [5][6200/7330] lr: 1.000e-04, eta: 6:29:44, time: 0.457, data_time: 0.035, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0414, loss_cls: 0.1721, acc: 93.6211, loss_bbox: 0.2233, loss_mask: 0.2212, loss: 0.6782 2023-11-13 20:57:07,281 - mmdet - INFO - Epoch [5][6250/7330] lr: 1.000e-04, eta: 6:29:22, time: 0.444, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0385, loss_cls: 0.1713, acc: 93.6167, loss_bbox: 0.2228, loss_mask: 0.2224, loss: 0.6727 2023-11-13 20:57:29,602 - mmdet - INFO - Epoch [5][6300/7330] lr: 1.000e-04, eta: 6:28:59, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0381, loss_cls: 0.1765, acc: 93.5022, loss_bbox: 0.2218, loss_mask: 0.2208, loss: 0.6762 2023-11-13 20:57:52,358 - mmdet - INFO - Epoch [5][6350/7330] lr: 1.000e-04, eta: 6:28:38, time: 0.455, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0411, loss_cls: 0.1767, acc: 93.5103, loss_bbox: 0.2270, loss_mask: 0.2211, loss: 0.6859 2023-11-13 20:58:14,996 - mmdet - INFO - Epoch [5][6400/7330] lr: 1.000e-04, eta: 6:28:16, time: 0.453, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0392, loss_cls: 0.1689, acc: 93.6814, loss_bbox: 0.2179, loss_mask: 0.2210, loss: 0.6668 2023-11-13 20:58:37,211 - mmdet - INFO - Epoch [5][6450/7330] lr: 1.000e-04, eta: 6:27:54, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0387, loss_cls: 0.1632, acc: 93.9302, loss_bbox: 0.2120, loss_mask: 0.2150, loss: 0.6485 2023-11-13 20:58:59,389 - mmdet - INFO - Epoch [5][6500/7330] lr: 1.000e-04, eta: 6:27:31, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0366, loss_cls: 0.1598, acc: 94.1394, loss_bbox: 0.2026, loss_mask: 0.2152, loss: 0.6336 2023-11-13 20:59:22,014 - mmdet - INFO - Epoch [5][6550/7330] lr: 1.000e-04, eta: 6:27:09, time: 0.453, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0399, loss_cls: 0.1662, acc: 93.8923, loss_bbox: 0.2074, loss_mask: 0.2202, loss: 0.6533 2023-11-13 20:59:44,483 - mmdet - INFO - Epoch [5][6600/7330] lr: 1.000e-04, eta: 6:26:47, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0383, loss_cls: 0.1668, acc: 93.8777, loss_bbox: 0.2147, loss_mask: 0.2182, loss: 0.6570 2023-11-13 21:00:07,189 - mmdet - INFO - Epoch [5][6650/7330] lr: 1.000e-04, eta: 6:26:26, time: 0.454, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0373, loss_cls: 0.1640, acc: 93.9045, loss_bbox: 0.2074, loss_mask: 0.2263, loss: 0.6531 2023-11-13 21:00:29,789 - mmdet - INFO - Epoch [5][6700/7330] lr: 1.000e-04, eta: 6:26:04, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0395, loss_cls: 0.1691, acc: 93.7456, loss_bbox: 0.2143, loss_mask: 0.2157, loss: 0.6584 2023-11-13 21:00:52,909 - mmdet - INFO - Epoch [5][6750/7330] lr: 1.000e-04, eta: 6:25:43, time: 0.462, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0403, loss_cls: 0.1716, acc: 93.5991, loss_bbox: 0.2185, loss_mask: 0.2226, loss: 0.6742 2023-11-13 21:01:15,872 - mmdet - INFO - Epoch [5][6800/7330] lr: 1.000e-04, eta: 6:25:21, time: 0.459, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0205, loss_rpn_bbox: 0.0416, loss_cls: 0.1789, acc: 93.4741, loss_bbox: 0.2205, loss_mask: 0.2227, loss: 0.6842 2023-11-13 21:01:38,217 - mmdet - INFO - Epoch [5][6850/7330] lr: 1.000e-04, eta: 6:24:59, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0213, loss_rpn_bbox: 0.0396, loss_cls: 0.1754, acc: 93.6697, loss_bbox: 0.2117, loss_mask: 0.2177, loss: 0.6657 2023-11-13 21:02:00,588 - mmdet - INFO - Epoch [5][6900/7330] lr: 1.000e-04, eta: 6:24:37, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0383, loss_cls: 0.1716, acc: 93.6138, loss_bbox: 0.2186, loss_mask: 0.2227, loss: 0.6704 2023-11-13 21:02:23,493 - mmdet - INFO - Epoch [5][6950/7330] lr: 1.000e-04, eta: 6:24:15, time: 0.458, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0405, loss_cls: 0.1792, acc: 93.3203, loss_bbox: 0.2252, loss_mask: 0.2279, loss: 0.6949 2023-11-13 21:02:46,164 - mmdet - INFO - Epoch [5][7000/7330] lr: 1.000e-04, eta: 6:23:54, time: 0.453, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0222, loss_rpn_bbox: 0.0422, loss_cls: 0.1778, acc: 93.2961, loss_bbox: 0.2228, loss_mask: 0.2279, loss: 0.6930 2023-11-13 21:03:08,093 - mmdet - INFO - Epoch [5][7050/7330] lr: 1.000e-04, eta: 6:23:31, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0371, loss_cls: 0.1657, acc: 93.9114, loss_bbox: 0.2084, loss_mask: 0.2208, loss: 0.6506 2023-11-13 21:03:30,301 - mmdet - INFO - Epoch [5][7100/7330] lr: 1.000e-04, eta: 6:23:08, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0199, loss_rpn_bbox: 0.0389, loss_cls: 0.1704, acc: 93.7283, loss_bbox: 0.2197, loss_mask: 0.2206, loss: 0.6696 2023-11-13 21:03:53,019 - mmdet - INFO - Epoch [5][7150/7330] lr: 1.000e-04, eta: 6:22:47, time: 0.454, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0398, loss_cls: 0.1705, acc: 93.6323, loss_bbox: 0.2236, loss_mask: 0.2252, loss: 0.6805 2023-11-13 21:04:15,474 - mmdet - INFO - Epoch [5][7200/7330] lr: 1.000e-04, eta: 6:22:25, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0408, loss_cls: 0.1706, acc: 93.5579, loss_bbox: 0.2185, loss_mask: 0.2221, loss: 0.6717 2023-11-13 21:04:37,958 - mmdet - INFO - Epoch [5][7250/7330] lr: 1.000e-04, eta: 6:22:02, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0392, loss_cls: 0.1680, acc: 93.8037, loss_bbox: 0.2128, loss_mask: 0.2163, loss: 0.6558 2023-11-13 21:05:00,301 - mmdet - INFO - Epoch [5][7300/7330] lr: 1.000e-04, eta: 6:21:40, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0394, loss_cls: 0.1729, acc: 93.6189, loss_bbox: 0.2135, loss_mask: 0.2142, loss: 0.6597 2023-11-13 21:05:14,592 - mmdet - INFO - Saving checkpoint at 5 epochs 2023-11-13 21:06:06,802 - mmdet - INFO - Evaluating bbox... 2023-11-13 21:06:38,908 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.470 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.696 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.520 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.310 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.516 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.607 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 ] = 0.430 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.645 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.736 2023-11-13 21:06:38,911 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.574 | bicycle | 0.365 | car | 0.487 | | motorcycle | 0.451 | airplane | 0.696 | bus | 0.685 | | train | 0.674 | truck | 0.424 | boat | 0.323 | | traffic light | 0.308 | fire hydrant | 0.703 | stop sign | 0.667 | | parking meter | 0.492 | bench | 0.285 | bird | 0.416 | | cat | 0.730 | dog | 0.662 | horse | 0.608 | | sheep | 0.577 | cow | 0.621 | elephant | 0.698 | | bear | 0.760 | zebra | 0.670 | giraffe | 0.701 | | backpack | 0.214 | umbrella | 0.444 | handbag | 0.222 | | tie | 0.365 | suitcase | 0.471 | frisbee | 0.681 | | skis | 0.267 | snowboard | 0.418 | sports ball | 0.463 | | kite | 0.433 | baseball bat | 0.431 | baseball glove | 0.423 | | skateboard | 0.564 | surfboard | 0.462 | tennis racket | 0.552 | | bottle | 0.451 | wine glass | 0.401 | cup | 0.496 | | fork | 0.444 | knife | 0.282 | spoon | 0.273 | | bowl | 0.464 | banana | 0.278 | apple | 0.248 | | sandwich | 0.461 | orange | 0.351 | broccoli | 0.255 | | carrot | 0.254 | hot dog | 0.415 | pizza | 0.527 | | donut | 0.559 | cake | 0.433 | chair | 0.354 | | couch | 0.443 | potted plant | 0.346 | bed | 0.465 | | dining table | 0.318 | toilet | 0.641 | tv | 0.616 | | laptop | 0.657 | mouse | 0.634 | remote | 0.400 | | keyboard | 0.548 | cell phone | 0.437 | microwave | 0.651 | | oven | 0.391 | toaster | 0.488 | sink | 0.432 | | refrigerator | 0.642 | book | 0.184 | clock | 0.532 | | vase | 0.422 | scissors | 0.457 | teddy bear | 0.522 | | hair drier | 0.161 | toothbrush | 0.277 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:06:38,911 - mmdet - INFO - Evaluating segm... 2023-11-13 21:07:11,564 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.426 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.668 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 ] = 0.462 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 ] = 0.549 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.549 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.549 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.594 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.706 2023-11-13 21:07:11,566 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.501 | bicycle | 0.222 | car | 0.448 | | motorcycle | 0.374 | airplane | 0.550 | bus | 0.674 | | train | 0.671 | truck | 0.414 | boat | 0.299 | | traffic light | 0.300 | fire hydrant | 0.688 | stop sign | 0.664 | | parking meter | 0.519 | bench | 0.222 | bird | 0.347 | | cat | 0.731 | dog | 0.626 | horse | 0.455 | | sheep | 0.520 | cow | 0.525 | elephant | 0.629 | | bear | 0.740 | zebra | 0.581 | giraffe | 0.548 | | backpack | 0.225 | umbrella | 0.523 | handbag | 0.215 | | tie | 0.353 | suitcase | 0.491 | frisbee | 0.652 | | skis | 0.052 | snowboard | 0.279 | sports ball | 0.478 | | kite | 0.329 | baseball bat | 0.325 | baseball glove | 0.450 | | skateboard | 0.356 | surfboard | 0.374 | tennis racket | 0.568 | | bottle | 0.436 | wine glass | 0.361 | cup | 0.493 | | fork | 0.238 | knife | 0.203 | spoon | 0.192 | | bowl | 0.441 | banana | 0.225 | apple | 0.243 | | sandwich | 0.485 | orange | 0.358 | broccoli | 0.227 | | carrot | 0.225 | hot dog | 0.315 | pizza | 0.508 | | donut | 0.561 | cake | 0.452 | chair | 0.256 | | couch | 0.367 | potted plant | 0.285 | bed | 0.363 | | dining table | 0.181 | toilet | 0.621 | tv | 0.644 | | laptop | 0.663 | mouse | 0.634 | remote | 0.370 | | keyboard | 0.539 | cell phone | 0.415 | microwave | 0.669 | | oven | 0.361 | toaster | 0.532 | sink | 0.403 | | refrigerator | 0.656 | book | 0.143 | clock | 0.536 | | vase | 0.420 | scissors | 0.333 | teddy bear | 0.492 | | hair drier | 0.108 | toothbrush | 0.197 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 21:07:12,083 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_4.pth was removed 2023-11-13 21:07:15,535 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_5.pth. 2023-11-13 21:07:15,536 - mmdet - INFO - Best bbox_mAP is 0.4700 at 5 epoch. 2023-11-13 21:07:15,536 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:07:15,536 - mmdet - INFO - Epoch(val) [5][625] bbox_mAP: 0.4700, bbox_mAP_50: 0.6961, bbox_mAP_75: 0.5198, bbox_mAP_s: 0.3099, bbox_mAP_m: 0.5160, bbox_mAP_l: 0.6071, bbox_mAP_copypaste: 0.4700 0.6961 0.5198 0.3099 0.5160 0.6071, segm_mAP: 0.4258, segm_mAP_50: 0.6683, segm_mAP_75: 0.4565, segm_mAP_s: 0.2326, segm_mAP_m: 0.4623, segm_mAP_l: 0.6139, segm_mAP_copypaste: 0.4258 0.6683 0.4565 0.2326 0.4623 0.6139 2023-11-13 21:07:41,675 - mmdet - INFO - Epoch [6][50/7330] lr: 1.000e-04, eta: 6:20:51, time: 0.523, data_time: 0.088, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0381, loss_cls: 0.1616, acc: 93.7820, loss_bbox: 0.2163, loss_mask: 0.2186, loss: 0.6513 2023-11-13 21:08:04,601 - mmdet - INFO - Epoch [6][100/7330] lr: 1.000e-04, eta: 6:20:30, time: 0.458, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0390, loss_cls: 0.1593, acc: 93.9604, loss_bbox: 0.2123, loss_mask: 0.2178, loss: 0.6465 2023-11-13 21:08:27,170 - mmdet - INFO - Epoch [6][150/7330] lr: 1.000e-04, eta: 6:20:08, time: 0.451, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0373, loss_cls: 0.1574, acc: 94.0879, loss_bbox: 0.2047, loss_mask: 0.2173, loss: 0.6343 2023-11-13 21:08:49,874 - mmdet - INFO - Epoch [6][200/7330] lr: 1.000e-04, eta: 6:19:46, time: 0.454, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0387, loss_cls: 0.1587, acc: 94.0188, loss_bbox: 0.2133, loss_mask: 0.2164, loss: 0.6453 2023-11-13 21:09:12,132 - mmdet - INFO - Epoch [6][250/7330] lr: 1.000e-04, eta: 6:19:24, time: 0.445, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0362, loss_cls: 0.1571, acc: 94.0627, loss_bbox: 0.2044, loss_mask: 0.2094, loss: 0.6223 2023-11-13 21:09:34,306 - mmdet - INFO - Epoch [6][300/7330] lr: 1.000e-04, eta: 6:19:01, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0340, loss_cls: 0.1582, acc: 94.0679, loss_bbox: 0.2067, loss_mask: 0.2162, loss: 0.6314 2023-11-13 21:09:56,824 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:09:56,824 - mmdet - INFO - Epoch [6][350/7330] lr: 1.000e-04, eta: 6:18:39, time: 0.450, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0368, loss_cls: 0.1552, acc: 94.2026, loss_bbox: 0.2094, loss_mask: 0.2135, loss: 0.6317 2023-11-13 21:10:18,835 - mmdet - INFO - Epoch [6][400/7330] lr: 1.000e-04, eta: 6:18:17, time: 0.440, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0336, loss_cls: 0.1508, acc: 94.2883, loss_bbox: 0.2046, loss_mask: 0.2160, loss: 0.6200 2023-11-13 21:10:41,443 - mmdet - INFO - Epoch [6][450/7330] lr: 1.000e-04, eta: 6:17:55, time: 0.452, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0371, loss_cls: 0.1645, acc: 93.8066, loss_bbox: 0.2172, loss_mask: 0.2197, loss: 0.6559 2023-11-13 21:11:03,910 - mmdet - INFO - Epoch [6][500/7330] lr: 1.000e-04, eta: 6:17:33, time: 0.449, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0387, loss_cls: 0.1588, acc: 94.0820, loss_bbox: 0.2092, loss_mask: 0.2139, loss: 0.6378 2023-11-13 21:11:26,392 - mmdet - INFO - Epoch [6][550/7330] lr: 1.000e-04, eta: 6:17:11, time: 0.450, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0411, loss_cls: 0.1711, acc: 93.6213, loss_bbox: 0.2196, loss_mask: 0.2165, loss: 0.6663 2023-11-13 21:11:49,284 - mmdet - INFO - Epoch [6][600/7330] lr: 1.000e-04, eta: 6:16:49, time: 0.458, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0196, loss_rpn_bbox: 0.0403, loss_cls: 0.1700, acc: 93.5640, loss_bbox: 0.2181, loss_mask: 0.2144, loss: 0.6623 2023-11-13 21:12:11,363 - mmdet - INFO - Epoch [6][650/7330] lr: 1.000e-04, eta: 6:16:27, time: 0.442, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0360, loss_cls: 0.1565, acc: 94.1592, loss_bbox: 0.2035, loss_mask: 0.2106, loss: 0.6231 2023-11-13 21:12:34,029 - mmdet - INFO - Epoch [6][700/7330] lr: 1.000e-04, eta: 6:16:05, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0393, loss_cls: 0.1630, acc: 93.8442, loss_bbox: 0.2155, loss_mask: 0.2196, loss: 0.6558 2023-11-13 21:12:56,503 - mmdet - INFO - Epoch [6][750/7330] lr: 1.000e-04, eta: 6:15:43, time: 0.450, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0400, loss_cls: 0.1684, acc: 93.6021, loss_bbox: 0.2219, loss_mask: 0.2213, loss: 0.6699 2023-11-13 21:13:18,807 - mmdet - INFO - Epoch [6][800/7330] lr: 1.000e-04, eta: 6:15:21, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0375, loss_cls: 0.1616, acc: 93.9575, loss_bbox: 0.2130, loss_mask: 0.2135, loss: 0.6439 2023-11-13 21:13:41,786 - mmdet - INFO - Epoch [6][850/7330] lr: 1.000e-04, eta: 6:14:59, time: 0.460, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0378, loss_cls: 0.1542, acc: 94.1899, loss_bbox: 0.2031, loss_mask: 0.2091, loss: 0.6209 2023-11-13 21:14:04,185 - mmdet - INFO - Epoch [6][900/7330] lr: 1.000e-04, eta: 6:14:37, time: 0.448, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0375, loss_cls: 0.1524, acc: 94.3401, loss_bbox: 0.2011, loss_mask: 0.2152, loss: 0.6234 2023-11-13 21:14:26,402 - mmdet - INFO - Epoch [6][950/7330] lr: 1.000e-04, eta: 6:14:15, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0366, loss_cls: 0.1579, acc: 94.0486, loss_bbox: 0.2063, loss_mask: 0.2152, loss: 0.6335 2023-11-13 21:14:48,667 - mmdet - INFO - Epoch [6][1000/7330] lr: 1.000e-04, eta: 6:13:52, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0356, loss_cls: 0.1538, acc: 94.2788, loss_bbox: 0.2013, loss_mask: 0.2139, loss: 0.6214 2023-11-13 21:15:11,105 - mmdet - INFO - Epoch [6][1050/7330] lr: 1.000e-04, eta: 6:13:30, time: 0.449, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0366, loss_cls: 0.1549, acc: 94.2280, loss_bbox: 0.2014, loss_mask: 0.2127, loss: 0.6232 2023-11-13 21:15:33,640 - mmdet - INFO - Epoch [6][1100/7330] lr: 1.000e-04, eta: 6:13:08, time: 0.451, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0390, loss_cls: 0.1685, acc: 93.6816, loss_bbox: 0.2188, loss_mask: 0.2234, loss: 0.6667 2023-11-13 21:15:56,221 - mmdet - INFO - Epoch [6][1150/7330] lr: 1.000e-04, eta: 6:12:46, time: 0.452, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0405, loss_cls: 0.1686, acc: 93.6165, loss_bbox: 0.2179, loss_mask: 0.2186, loss: 0.6643 2023-11-13 21:16:18,815 - mmdet - INFO - Epoch [6][1200/7330] lr: 1.000e-04, eta: 6:12:24, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0392, loss_cls: 0.1677, acc: 93.7144, loss_bbox: 0.2196, loss_mask: 0.2200, loss: 0.6635 2023-11-13 21:16:40,904 - mmdet - INFO - Epoch [6][1250/7330] lr: 1.000e-04, eta: 6:12:02, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0374, loss_cls: 0.1560, acc: 94.1411, loss_bbox: 0.2056, loss_mask: 0.2194, loss: 0.6348 2023-11-13 21:17:03,331 - mmdet - INFO - Epoch [6][1300/7330] lr: 1.000e-04, eta: 6:11:40, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0379, loss_cls: 0.1650, acc: 93.7368, loss_bbox: 0.2162, loss_mask: 0.2154, loss: 0.6508 2023-11-13 21:17:26,030 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:17:26,030 - mmdet - INFO - Epoch [6][1350/7330] lr: 1.000e-04, eta: 6:11:18, time: 0.454, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0420, loss_cls: 0.1714, acc: 93.6001, loss_bbox: 0.2206, loss_mask: 0.2229, loss: 0.6771 2023-11-13 21:17:48,499 - mmdet - INFO - Epoch [6][1400/7330] lr: 1.000e-04, eta: 6:10:56, time: 0.449, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0379, loss_cls: 0.1618, acc: 93.8699, loss_bbox: 0.2138, loss_mask: 0.2168, loss: 0.6487 2023-11-13 21:18:11,024 - mmdet - INFO - Epoch [6][1450/7330] lr: 1.000e-04, eta: 6:10:34, time: 0.450, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0398, loss_cls: 0.1643, acc: 93.9150, loss_bbox: 0.2130, loss_mask: 0.2183, loss: 0.6533 2023-11-13 21:18:33,633 - mmdet - INFO - Epoch [6][1500/7330] lr: 1.000e-04, eta: 6:10:12, time: 0.452, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0390, loss_cls: 0.1665, acc: 93.6611, loss_bbox: 0.2164, loss_mask: 0.2192, loss: 0.6591 2023-11-13 21:18:55,603 - mmdet - INFO - Epoch [6][1550/7330] lr: 1.000e-04, eta: 6:09:49, time: 0.439, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0369, loss_cls: 0.1520, acc: 94.2148, loss_bbox: 0.2016, loss_mask: 0.2155, loss: 0.6231 2023-11-13 21:19:18,246 - mmdet - INFO - Epoch [6][1600/7330] lr: 1.000e-04, eta: 6:09:27, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0402, loss_cls: 0.1696, acc: 93.7712, loss_bbox: 0.2111, loss_mask: 0.2214, loss: 0.6620 2023-11-13 21:19:40,704 - mmdet - INFO - Epoch [6][1650/7330] lr: 1.000e-04, eta: 6:09:05, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0198, loss_rpn_bbox: 0.0403, loss_cls: 0.1600, acc: 93.9932, loss_bbox: 0.2151, loss_mask: 0.2235, loss: 0.6587 2023-11-13 21:20:03,262 - mmdet - INFO - Epoch [6][1700/7330] lr: 1.000e-04, eta: 6:08:43, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0397, loss_cls: 0.1610, acc: 93.9692, loss_bbox: 0.2116, loss_mask: 0.2192, loss: 0.6507 2023-11-13 21:20:25,481 - mmdet - INFO - Epoch [6][1750/7330] lr: 1.000e-04, eta: 6:08:21, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0373, loss_cls: 0.1605, acc: 93.8906, loss_bbox: 0.2109, loss_mask: 0.2167, loss: 0.6420 2023-11-13 21:20:48,090 - mmdet - INFO - Epoch [6][1800/7330] lr: 1.000e-04, eta: 6:07:59, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0380, loss_cls: 0.1614, acc: 93.9014, loss_bbox: 0.2145, loss_mask: 0.2164, loss: 0.6479 2023-11-13 21:21:10,589 - mmdet - INFO - Epoch [6][1850/7330] lr: 1.000e-04, eta: 6:07:37, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0402, loss_cls: 0.1655, acc: 93.7922, loss_bbox: 0.2131, loss_mask: 0.2152, loss: 0.6526 2023-11-13 21:21:33,064 - mmdet - INFO - Epoch [6][1900/7330] lr: 1.000e-04, eta: 6:07:15, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0406, loss_cls: 0.1701, acc: 93.6782, loss_bbox: 0.2190, loss_mask: 0.2198, loss: 0.6675 2023-11-13 21:21:55,010 - mmdet - INFO - Epoch [6][1950/7330] lr: 1.000e-04, eta: 6:06:52, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0362, loss_cls: 0.1593, acc: 94.0515, loss_bbox: 0.2047, loss_mask: 0.2148, loss: 0.6321 2023-11-13 21:22:17,129 - mmdet - INFO - Epoch [6][2000/7330] lr: 1.000e-04, eta: 6:06:30, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0376, loss_cls: 0.1616, acc: 93.9246, loss_bbox: 0.2109, loss_mask: 0.2172, loss: 0.6451 2023-11-13 21:22:39,091 - mmdet - INFO - Epoch [6][2050/7330] lr: 1.000e-04, eta: 6:06:07, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0363, loss_cls: 0.1566, acc: 94.0979, loss_bbox: 0.2018, loss_mask: 0.2132, loss: 0.6226 2023-11-13 21:23:01,299 - mmdet - INFO - Epoch [6][2100/7330] lr: 1.000e-04, eta: 6:05:45, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0352, loss_cls: 0.1565, acc: 94.1484, loss_bbox: 0.2034, loss_mask: 0.2157, loss: 0.6268 2023-11-13 21:23:23,600 - mmdet - INFO - Epoch [6][2150/7330] lr: 1.000e-04, eta: 6:05:22, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0369, loss_cls: 0.1623, acc: 93.9006, loss_bbox: 0.2129, loss_mask: 0.2171, loss: 0.6469 2023-11-13 21:23:46,207 - mmdet - INFO - Epoch [6][2200/7330] lr: 1.000e-04, eta: 6:05:00, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0386, loss_cls: 0.1637, acc: 93.9150, loss_bbox: 0.2107, loss_mask: 0.2114, loss: 0.6424 2023-11-13 21:24:08,357 - mmdet - INFO - Epoch [6][2250/7330] lr: 1.000e-04, eta: 6:04:38, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0376, loss_cls: 0.1624, acc: 93.8804, loss_bbox: 0.2083, loss_mask: 0.2145, loss: 0.6419 2023-11-13 21:24:30,606 - mmdet - INFO - Epoch [6][2300/7330] lr: 1.000e-04, eta: 6:04:16, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0409, loss_cls: 0.1670, acc: 93.6785, loss_bbox: 0.2186, loss_mask: 0.2205, loss: 0.6662 2023-11-13 21:24:52,792 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:24:52,792 - mmdet - INFO - Epoch [6][2350/7330] lr: 1.000e-04, eta: 6:03:53, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0386, loss_cls: 0.1603, acc: 93.9619, loss_bbox: 0.2087, loss_mask: 0.2177, loss: 0.6443 2023-11-13 21:25:15,009 - mmdet - INFO - Epoch [6][2400/7330] lr: 1.000e-04, eta: 6:03:31, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0370, loss_cls: 0.1630, acc: 93.9548, loss_bbox: 0.2106, loss_mask: 0.2134, loss: 0.6416 2023-11-13 21:25:37,542 - mmdet - INFO - Epoch [6][2450/7330] lr: 1.000e-04, eta: 6:03:09, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0398, loss_cls: 0.1708, acc: 93.6406, loss_bbox: 0.2169, loss_mask: 0.2198, loss: 0.6661 2023-11-13 21:25:59,711 - mmdet - INFO - Epoch [6][2500/7330] lr: 1.000e-04, eta: 6:02:46, time: 0.443, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0374, loss_cls: 0.1604, acc: 93.9102, loss_bbox: 0.2096, loss_mask: 0.2138, loss: 0.6380 2023-11-13 21:26:22,016 - mmdet - INFO - Epoch [6][2550/7330] lr: 1.000e-04, eta: 6:02:24, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0411, loss_cls: 0.1698, acc: 93.6152, loss_bbox: 0.2175, loss_mask: 0.2202, loss: 0.6677 2023-11-13 21:26:44,607 - mmdet - INFO - Epoch [6][2600/7330] lr: 1.000e-04, eta: 6:02:02, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0400, loss_cls: 0.1592, acc: 94.0938, loss_bbox: 0.2030, loss_mask: 0.2151, loss: 0.6355 2023-11-13 21:27:07,093 - mmdet - INFO - Epoch [6][2650/7330] lr: 1.000e-04, eta: 6:01:40, time: 0.450, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0369, loss_cls: 0.1566, acc: 94.0500, loss_bbox: 0.2075, loss_mask: 0.2197, loss: 0.6375 2023-11-13 21:27:29,741 - mmdet - INFO - Epoch [6][2700/7330] lr: 1.000e-04, eta: 6:01:18, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0401, loss_cls: 0.1640, acc: 93.8584, loss_bbox: 0.2144, loss_mask: 0.2199, loss: 0.6570 2023-11-13 21:27:51,726 - mmdet - INFO - Epoch [6][2750/7330] lr: 1.000e-04, eta: 6:00:55, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0366, loss_cls: 0.1549, acc: 94.2029, loss_bbox: 0.2031, loss_mask: 0.2118, loss: 0.6240 2023-11-13 21:28:14,162 - mmdet - INFO - Epoch [6][2800/7330] lr: 1.000e-04, eta: 6:00:33, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0405, loss_cls: 0.1653, acc: 93.8516, loss_bbox: 0.2100, loss_mask: 0.2187, loss: 0.6537 2023-11-13 21:28:36,440 - mmdet - INFO - Epoch [6][2850/7330] lr: 1.000e-04, eta: 6:00:11, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0357, loss_cls: 0.1485, acc: 94.4731, loss_bbox: 0.1974, loss_mask: 0.2127, loss: 0.6114 2023-11-13 21:28:58,442 - mmdet - INFO - Epoch [6][2900/7330] lr: 1.000e-04, eta: 5:59:48, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0365, loss_cls: 0.1586, acc: 94.1042, loss_bbox: 0.2075, loss_mask: 0.2165, loss: 0.6368 2023-11-13 21:29:20,463 - mmdet - INFO - Epoch [6][2950/7330] lr: 1.000e-04, eta: 5:59:26, time: 0.440, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0372, loss_cls: 0.1603, acc: 94.0037, loss_bbox: 0.2064, loss_mask: 0.2087, loss: 0.6296 2023-11-13 21:29:42,742 - mmdet - INFO - Epoch [6][3000/7330] lr: 1.000e-04, eta: 5:59:03, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0403, loss_cls: 0.1679, acc: 93.7063, loss_bbox: 0.2160, loss_mask: 0.2213, loss: 0.6646 2023-11-13 21:30:05,485 - mmdet - INFO - Epoch [6][3050/7330] lr: 1.000e-04, eta: 5:58:42, time: 0.455, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0411, loss_cls: 0.1633, acc: 93.8611, loss_bbox: 0.2091, loss_mask: 0.2163, loss: 0.6484 2023-11-13 21:30:27,672 - mmdet - INFO - Epoch [6][3100/7330] lr: 1.000e-04, eta: 5:58:19, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0358, loss_cls: 0.1582, acc: 94.0776, loss_bbox: 0.2081, loss_mask: 0.2158, loss: 0.6350 2023-11-13 21:30:49,883 - mmdet - INFO - Epoch [6][3150/7330] lr: 1.000e-04, eta: 5:57:57, time: 0.444, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0377, loss_cls: 0.1625, acc: 93.9558, loss_bbox: 0.2091, loss_mask: 0.2152, loss: 0.6427 2023-11-13 21:31:12,016 - mmdet - INFO - Epoch [6][3200/7330] lr: 1.000e-04, eta: 5:57:34, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0352, loss_cls: 0.1532, acc: 94.3154, loss_bbox: 0.2001, loss_mask: 0.2120, loss: 0.6175 2023-11-13 21:31:34,722 - mmdet - INFO - Epoch [6][3250/7330] lr: 1.000e-04, eta: 5:57:12, time: 0.454, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0409, loss_cls: 0.1660, acc: 93.8538, loss_bbox: 0.2139, loss_mask: 0.2192, loss: 0.6582 2023-11-13 21:31:57,314 - mmdet - INFO - Epoch [6][3300/7330] lr: 1.000e-04, eta: 5:56:50, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0386, loss_cls: 0.1638, acc: 93.8818, loss_bbox: 0.2104, loss_mask: 0.2171, loss: 0.6471 2023-11-13 21:32:20,052 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:32:20,052 - mmdet - INFO - Epoch [6][3350/7330] lr: 1.000e-04, eta: 5:56:29, time: 0.455, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0408, loss_cls: 0.1692, acc: 93.6206, loss_bbox: 0.2214, loss_mask: 0.2156, loss: 0.6654 2023-11-13 21:32:42,236 - mmdet - INFO - Epoch [6][3400/7330] lr: 1.000e-04, eta: 5:56:06, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0368, loss_cls: 0.1630, acc: 93.9583, loss_bbox: 0.2093, loss_mask: 0.2169, loss: 0.6428 2023-11-13 21:33:04,644 - mmdet - INFO - Epoch [6][3450/7330] lr: 1.000e-04, eta: 5:55:44, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0381, loss_cls: 0.1638, acc: 93.9390, loss_bbox: 0.2070, loss_mask: 0.2135, loss: 0.6409 2023-11-13 21:33:26,767 - mmdet - INFO - Epoch [6][3500/7330] lr: 1.000e-04, eta: 5:55:22, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0373, loss_cls: 0.1649, acc: 93.8540, loss_bbox: 0.2124, loss_mask: 0.2152, loss: 0.6480 2023-11-13 21:33:48,800 - mmdet - INFO - Epoch [6][3550/7330] lr: 1.000e-04, eta: 5:54:59, time: 0.441, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0387, loss_cls: 0.1618, acc: 93.8586, loss_bbox: 0.2147, loss_mask: 0.2229, loss: 0.6561 2023-11-13 21:34:10,572 - mmdet - INFO - Epoch [6][3600/7330] lr: 1.000e-04, eta: 5:54:36, time: 0.436, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0364, loss_cls: 0.1524, acc: 94.3228, loss_bbox: 0.2043, loss_mask: 0.2102, loss: 0.6210 2023-11-13 21:34:32,448 - mmdet - INFO - Epoch [6][3650/7330] lr: 1.000e-04, eta: 5:54:13, time: 0.437, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0371, loss_cls: 0.1674, acc: 93.6611, loss_bbox: 0.2230, loss_mask: 0.2269, loss: 0.6719 2023-11-13 21:34:55,009 - mmdet - INFO - Epoch [6][3700/7330] lr: 1.000e-04, eta: 5:53:51, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0398, loss_cls: 0.1572, acc: 94.0491, loss_bbox: 0.2072, loss_mask: 0.2165, loss: 0.6382 2023-11-13 21:35:17,271 - mmdet - INFO - Epoch [6][3750/7330] lr: 1.000e-04, eta: 5:53:29, time: 0.445, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0390, loss_cls: 0.1655, acc: 93.8203, loss_bbox: 0.2099, loss_mask: 0.2220, loss: 0.6546 2023-11-13 21:35:39,689 - mmdet - INFO - Epoch [6][3800/7330] lr: 1.000e-04, eta: 5:53:07, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0384, loss_cls: 0.1640, acc: 93.8596, loss_bbox: 0.2120, loss_mask: 0.2192, loss: 0.6514 2023-11-13 21:36:01,622 - mmdet - INFO - Epoch [6][3850/7330] lr: 1.000e-04, eta: 5:52:44, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0370, loss_cls: 0.1597, acc: 94.0112, loss_bbox: 0.2093, loss_mask: 0.2190, loss: 0.6421 2023-11-13 21:36:23,531 - mmdet - INFO - Epoch [6][3900/7330] lr: 1.000e-04, eta: 5:52:21, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0414, loss_cls: 0.1626, acc: 93.9443, loss_bbox: 0.2105, loss_mask: 0.2161, loss: 0.6482 2023-11-13 21:36:45,756 - mmdet - INFO - Epoch [6][3950/7330] lr: 1.000e-04, eta: 5:51:59, time: 0.444, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0353, loss_cls: 0.1560, acc: 94.0171, loss_bbox: 0.2048, loss_mask: 0.2150, loss: 0.6256 2023-11-13 21:37:08,587 - mmdet - INFO - Epoch [6][4000/7330] lr: 1.000e-04, eta: 5:51:37, time: 0.457, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0384, loss_cls: 0.1567, acc: 94.1099, loss_bbox: 0.2032, loss_mask: 0.2148, loss: 0.6319 2023-11-13 21:37:30,699 - mmdet - INFO - Epoch [6][4050/7330] lr: 1.000e-04, eta: 5:51:15, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0357, loss_cls: 0.1539, acc: 94.3198, loss_bbox: 0.1991, loss_mask: 0.2125, loss: 0.6172 2023-11-13 21:37:52,962 - mmdet - INFO - Epoch [6][4100/7330] lr: 1.000e-04, eta: 5:50:52, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0400, loss_cls: 0.1681, acc: 93.6655, loss_bbox: 0.2126, loss_mask: 0.2177, loss: 0.6572 2023-11-13 21:38:14,964 - mmdet - INFO - Epoch [6][4150/7330] lr: 1.000e-04, eta: 5:50:30, time: 0.440, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0373, loss_cls: 0.1596, acc: 94.0117, loss_bbox: 0.2085, loss_mask: 0.2198, loss: 0.6424 2023-11-13 21:38:37,070 - mmdet - INFO - Epoch [6][4200/7330] lr: 1.000e-04, eta: 5:50:07, time: 0.442, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0394, loss_cls: 0.1611, acc: 93.9058, loss_bbox: 0.2099, loss_mask: 0.2225, loss: 0.6523 2023-11-13 21:38:58,831 - mmdet - INFO - Epoch [6][4250/7330] lr: 1.000e-04, eta: 5:49:44, time: 0.435, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0357, loss_cls: 0.1595, acc: 94.0559, loss_bbox: 0.2039, loss_mask: 0.2193, loss: 0.6359 2023-11-13 21:39:21,021 - mmdet - INFO - Epoch [6][4300/7330] lr: 1.000e-04, eta: 5:49:22, time: 0.444, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0366, loss_cls: 0.1576, acc: 94.1599, loss_bbox: 0.2061, loss_mask: 0.2148, loss: 0.6300 2023-11-13 21:39:43,114 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:39:43,114 - mmdet - INFO - Epoch [6][4350/7330] lr: 1.000e-04, eta: 5:48:59, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0382, loss_cls: 0.1580, acc: 93.9924, loss_bbox: 0.2071, loss_mask: 0.2162, loss: 0.6375 2023-11-13 21:40:05,157 - mmdet - INFO - Epoch [6][4400/7330] lr: 1.000e-04, eta: 5:48:37, time: 0.441, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0207, loss_rpn_bbox: 0.0395, loss_cls: 0.1658, acc: 93.8169, loss_bbox: 0.2167, loss_mask: 0.2200, loss: 0.6627 2023-11-13 21:40:27,256 - mmdet - INFO - Epoch [6][4450/7330] lr: 1.000e-04, eta: 5:48:14, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0364, loss_cls: 0.1575, acc: 94.0161, loss_bbox: 0.2052, loss_mask: 0.2172, loss: 0.6345 2023-11-13 21:40:49,474 - mmdet - INFO - Epoch [6][4500/7330] lr: 1.000e-04, eta: 5:47:52, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0416, loss_cls: 0.1648, acc: 93.8398, loss_bbox: 0.2094, loss_mask: 0.2118, loss: 0.6473 2023-11-13 21:41:11,719 - mmdet - INFO - Epoch [6][4550/7330] lr: 1.000e-04, eta: 5:47:30, time: 0.445, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0180, loss_rpn_bbox: 0.0388, loss_cls: 0.1677, acc: 93.7068, loss_bbox: 0.2167, loss_mask: 0.2187, loss: 0.6598 2023-11-13 21:41:33,863 - mmdet - INFO - Epoch [6][4600/7330] lr: 1.000e-04, eta: 5:47:07, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0380, loss_cls: 0.1683, acc: 93.6340, loss_bbox: 0.2165, loss_mask: 0.2160, loss: 0.6574 2023-11-13 21:41:55,976 - mmdet - INFO - Epoch [6][4650/7330] lr: 1.000e-04, eta: 5:46:45, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0406, loss_cls: 0.1710, acc: 93.7146, loss_bbox: 0.2173, loss_mask: 0.2243, loss: 0.6718 2023-11-13 21:42:18,174 - mmdet - INFO - Epoch [6][4700/7330] lr: 1.000e-04, eta: 5:46:22, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0408, loss_cls: 0.1676, acc: 93.7759, loss_bbox: 0.2124, loss_mask: 0.2233, loss: 0.6625 2023-11-13 21:42:40,122 - mmdet - INFO - Epoch [6][4750/7330] lr: 1.000e-04, eta: 5:45:59, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0381, loss_cls: 0.1631, acc: 93.8350, loss_bbox: 0.2122, loss_mask: 0.2202, loss: 0.6526 2023-11-13 21:43:02,315 - mmdet - INFO - Epoch [6][4800/7330] lr: 1.000e-04, eta: 5:45:37, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0376, loss_cls: 0.1585, acc: 94.0515, loss_bbox: 0.2056, loss_mask: 0.2142, loss: 0.6341 2023-11-13 21:43:24,530 - mmdet - INFO - Epoch [6][4850/7330] lr: 1.000e-04, eta: 5:45:15, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0366, loss_cls: 0.1600, acc: 94.0132, loss_bbox: 0.2037, loss_mask: 0.2117, loss: 0.6285 2023-11-13 21:43:46,677 - mmdet - INFO - Epoch [6][4900/7330] lr: 1.000e-04, eta: 5:44:52, time: 0.443, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0378, loss_cls: 0.1647, acc: 93.8145, loss_bbox: 0.2144, loss_mask: 0.2166, loss: 0.6503 2023-11-13 21:44:09,301 - mmdet - INFO - Epoch [6][4950/7330] lr: 1.000e-04, eta: 5:44:30, time: 0.452, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0202, loss_rpn_bbox: 0.0398, loss_cls: 0.1703, acc: 93.6331, loss_bbox: 0.2183, loss_mask: 0.2201, loss: 0.6687 2023-11-13 21:44:31,369 - mmdet - INFO - Epoch [6][5000/7330] lr: 1.000e-04, eta: 5:44:08, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0385, loss_cls: 0.1667, acc: 93.7163, loss_bbox: 0.2145, loss_mask: 0.2174, loss: 0.6552 2023-11-13 21:44:53,346 - mmdet - INFO - Epoch [6][5050/7330] lr: 1.000e-04, eta: 5:43:45, time: 0.439, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0361, loss_cls: 0.1545, acc: 94.2852, loss_bbox: 0.2015, loss_mask: 0.2138, loss: 0.6234 2023-11-13 21:45:15,646 - mmdet - INFO - Epoch [6][5100/7330] lr: 1.000e-04, eta: 5:43:23, time: 0.446, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0370, loss_cls: 0.1594, acc: 93.8735, loss_bbox: 0.2142, loss_mask: 0.2170, loss: 0.6439 2023-11-13 21:45:37,695 - mmdet - INFO - Epoch [6][5150/7330] lr: 1.000e-04, eta: 5:43:00, time: 0.441, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0367, loss_cls: 0.1640, acc: 93.7944, loss_bbox: 0.2115, loss_mask: 0.2201, loss: 0.6502 2023-11-13 21:45:59,890 - mmdet - INFO - Epoch [6][5200/7330] lr: 1.000e-04, eta: 5:42:38, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0192, loss_rpn_bbox: 0.0360, loss_cls: 0.1613, acc: 93.9856, loss_bbox: 0.2031, loss_mask: 0.2145, loss: 0.6340 2023-11-13 21:46:21,897 - mmdet - INFO - Epoch [6][5250/7330] lr: 1.000e-04, eta: 5:42:15, time: 0.440, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0388, loss_cls: 0.1633, acc: 93.8162, loss_bbox: 0.2117, loss_mask: 0.2161, loss: 0.6485 2023-11-13 21:46:44,040 - mmdet - INFO - Epoch [6][5300/7330] lr: 1.000e-04, eta: 5:41:53, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0366, loss_cls: 0.1590, acc: 94.0637, loss_bbox: 0.2051, loss_mask: 0.2159, loss: 0.6334 2023-11-13 21:47:06,085 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:47:06,085 - mmdet - INFO - Epoch [6][5350/7330] lr: 1.000e-04, eta: 5:41:30, time: 0.441, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0399, loss_cls: 0.1663, acc: 93.7378, loss_bbox: 0.2134, loss_mask: 0.2228, loss: 0.6598 2023-11-13 21:47:28,048 - mmdet - INFO - Epoch [6][5400/7330] lr: 1.000e-04, eta: 5:41:08, time: 0.439, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0374, loss_cls: 0.1578, acc: 94.0334, loss_bbox: 0.2063, loss_mask: 0.2175, loss: 0.6361 2023-11-13 21:47:50,388 - mmdet - INFO - Epoch [6][5450/7330] lr: 1.000e-04, eta: 5:40:45, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0393, loss_cls: 0.1630, acc: 93.8948, loss_bbox: 0.2132, loss_mask: 0.2193, loss: 0.6521 2023-11-13 21:48:12,684 - mmdet - INFO - Epoch [6][5500/7330] lr: 1.000e-04, eta: 5:40:23, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0389, loss_cls: 0.1628, acc: 93.9482, loss_bbox: 0.2110, loss_mask: 0.2161, loss: 0.6478 2023-11-13 21:48:34,949 - mmdet - INFO - Epoch [6][5550/7330] lr: 1.000e-04, eta: 5:40:01, time: 0.445, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0388, loss_cls: 0.1604, acc: 94.0605, loss_bbox: 0.2082, loss_mask: 0.2180, loss: 0.6425 2023-11-13 21:48:57,204 - mmdet - INFO - Epoch [6][5600/7330] lr: 1.000e-04, eta: 5:39:38, time: 0.445, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0359, loss_cls: 0.1595, acc: 94.0728, loss_bbox: 0.2031, loss_mask: 0.2121, loss: 0.6269 2023-11-13 21:49:19,696 - mmdet - INFO - Epoch [6][5650/7330] lr: 1.000e-04, eta: 5:39:16, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0387, loss_cls: 0.1641, acc: 93.9390, loss_bbox: 0.2063, loss_mask: 0.2184, loss: 0.6466 2023-11-13 21:49:41,963 - mmdet - INFO - Epoch [6][5700/7330] lr: 1.000e-04, eta: 5:38:54, time: 0.445, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0388, loss_cls: 0.1641, acc: 93.8364, loss_bbox: 0.2139, loss_mask: 0.2187, loss: 0.6543 2023-11-13 21:50:04,398 - mmdet - INFO - Epoch [6][5750/7330] lr: 1.000e-04, eta: 5:38:32, time: 0.449, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0181, loss_rpn_bbox: 0.0403, loss_cls: 0.1627, acc: 93.8860, loss_bbox: 0.2181, loss_mask: 0.2256, loss: 0.6647 2023-11-13 21:50:26,484 - mmdet - INFO - Epoch [6][5800/7330] lr: 1.000e-04, eta: 5:38:09, time: 0.442, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0378, loss_cls: 0.1616, acc: 94.0122, loss_bbox: 0.2046, loss_mask: 0.2228, loss: 0.6452 2023-11-13 21:50:48,708 - mmdet - INFO - Epoch [6][5850/7330] lr: 1.000e-04, eta: 5:37:47, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0400, loss_cls: 0.1650, acc: 93.7268, loss_bbox: 0.2113, loss_mask: 0.2181, loss: 0.6539 2023-11-13 21:51:11,159 - mmdet - INFO - Epoch [6][5900/7330] lr: 1.000e-04, eta: 5:37:25, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0391, loss_cls: 0.1628, acc: 93.8857, loss_bbox: 0.2135, loss_mask: 0.2150, loss: 0.6490 2023-11-13 21:51:32,952 - mmdet - INFO - Epoch [6][5950/7330] lr: 1.000e-04, eta: 5:37:02, time: 0.436, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0372, loss_cls: 0.1594, acc: 94.0898, loss_bbox: 0.2012, loss_mask: 0.2151, loss: 0.6302 2023-11-13 21:51:55,393 - mmdet - INFO - Epoch [6][6000/7330] lr: 1.000e-04, eta: 5:36:40, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0402, loss_cls: 0.1667, acc: 93.7747, loss_bbox: 0.2137, loss_mask: 0.2166, loss: 0.6549 2023-11-13 21:52:17,447 - mmdet - INFO - Epoch [6][6050/7330] lr: 1.000e-04, eta: 5:36:17, time: 0.441, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0400, loss_cls: 0.1692, acc: 93.7227, loss_bbox: 0.2154, loss_mask: 0.2190, loss: 0.6632 2023-11-13 21:52:39,429 - mmdet - INFO - Epoch [6][6100/7330] lr: 1.000e-04, eta: 5:35:55, time: 0.440, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0397, loss_cls: 0.1634, acc: 93.8469, loss_bbox: 0.2160, loss_mask: 0.2187, loss: 0.6563 2023-11-13 21:53:02,008 - mmdet - INFO - Epoch [6][6150/7330] lr: 1.000e-04, eta: 5:35:33, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0197, loss_rpn_bbox: 0.0390, loss_cls: 0.1695, acc: 93.7405, loss_bbox: 0.2204, loss_mask: 0.2217, loss: 0.6703 2023-11-13 21:53:24,199 - mmdet - INFO - Epoch [6][6200/7330] lr: 1.000e-04, eta: 5:35:10, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0395, loss_cls: 0.1652, acc: 93.8142, loss_bbox: 0.2189, loss_mask: 0.2181, loss: 0.6594 2023-11-13 21:53:46,941 - mmdet - INFO - Epoch [6][6250/7330] lr: 1.000e-04, eta: 5:34:49, time: 0.455, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0383, loss_cls: 0.1653, acc: 93.7629, loss_bbox: 0.2143, loss_mask: 0.2199, loss: 0.6564 2023-11-13 21:54:09,212 - mmdet - INFO - Epoch [6][6300/7330] lr: 1.000e-04, eta: 5:34:26, time: 0.445, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0190, loss_rpn_bbox: 0.0382, loss_cls: 0.1667, acc: 93.8811, loss_bbox: 0.2133, loss_mask: 0.2176, loss: 0.6548 2023-11-13 21:54:31,511 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 21:54:31,512 - mmdet - INFO - Epoch [6][6350/7330] lr: 1.000e-04, eta: 5:34:04, time: 0.446, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0395, loss_cls: 0.1654, acc: 93.7964, loss_bbox: 0.2100, loss_mask: 0.2175, loss: 0.6496 2023-11-13 21:54:53,816 - mmdet - INFO - Epoch [6][6400/7330] lr: 1.000e-04, eta: 5:33:42, time: 0.446, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0388, loss_cls: 0.1683, acc: 93.7007, loss_bbox: 0.2142, loss_mask: 0.2162, loss: 0.6553 2023-11-13 21:55:16,359 - mmdet - INFO - Epoch [6][6450/7330] lr: 1.000e-04, eta: 5:33:20, time: 0.451, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0429, loss_cls: 0.1677, acc: 93.8188, loss_bbox: 0.2162, loss_mask: 0.2211, loss: 0.6665 2023-11-13 21:55:38,315 - mmdet - INFO - Epoch [6][6500/7330] lr: 1.000e-04, eta: 5:32:57, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0366, loss_cls: 0.1552, acc: 94.2749, loss_bbox: 0.2002, loss_mask: 0.2093, loss: 0.6195 2023-11-13 21:56:00,701 - mmdet - INFO - Epoch [6][6550/7330] lr: 1.000e-04, eta: 5:32:35, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0405, loss_cls: 0.1689, acc: 93.6206, loss_bbox: 0.2208, loss_mask: 0.2227, loss: 0.6713 2023-11-13 21:56:23,384 - mmdet - INFO - Epoch [6][6600/7330] lr: 1.000e-04, eta: 5:32:13, time: 0.454, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0214, loss_rpn_bbox: 0.0398, loss_cls: 0.1645, acc: 93.8552, loss_bbox: 0.2127, loss_mask: 0.2183, loss: 0.6567 2023-11-13 21:56:45,727 - mmdet - INFO - Epoch [6][6650/7330] lr: 1.000e-04, eta: 5:31:51, time: 0.447, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0392, loss_cls: 0.1661, acc: 93.8181, loss_bbox: 0.2183, loss_mask: 0.2210, loss: 0.6638 2023-11-13 21:57:08,220 - mmdet - INFO - Epoch [6][6700/7330] lr: 1.000e-04, eta: 5:31:29, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0374, loss_cls: 0.1703, acc: 93.6404, loss_bbox: 0.2195, loss_mask: 0.2157, loss: 0.6613 2023-11-13 21:57:30,356 - mmdet - INFO - Epoch [6][6750/7330] lr: 1.000e-04, eta: 5:31:06, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0374, loss_cls: 0.1654, acc: 93.8340, loss_bbox: 0.2108, loss_mask: 0.2191, loss: 0.6512 2023-11-13 21:57:52,715 - mmdet - INFO - Epoch [6][6800/7330] lr: 1.000e-04, eta: 5:30:44, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0200, loss_rpn_bbox: 0.0379, loss_cls: 0.1586, acc: 94.0874, loss_bbox: 0.2068, loss_mask: 0.2189, loss: 0.6422 2023-11-13 21:58:14,918 - mmdet - INFO - Epoch [6][6850/7330] lr: 1.000e-04, eta: 5:30:22, time: 0.444, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0381, loss_cls: 0.1655, acc: 93.8657, loss_bbox: 0.2119, loss_mask: 0.2168, loss: 0.6508 2023-11-13 21:58:37,221 - mmdet - INFO - Epoch [6][6900/7330] lr: 1.000e-04, eta: 5:29:59, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0204, loss_rpn_bbox: 0.0406, loss_cls: 0.1711, acc: 93.5789, loss_bbox: 0.2209, loss_mask: 0.2175, loss: 0.6705 2023-11-13 21:58:59,140 - mmdet - INFO - Epoch [6][6950/7330] lr: 1.000e-04, eta: 5:29:37, time: 0.438, data_time: 0.031, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0360, loss_cls: 0.1562, acc: 94.1885, loss_bbox: 0.2026, loss_mask: 0.2141, loss: 0.6266 2023-11-13 21:59:21,487 - mmdet - INFO - Epoch [6][7000/7330] lr: 1.000e-04, eta: 5:29:14, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0381, loss_cls: 0.1612, acc: 93.9993, loss_bbox: 0.2067, loss_mask: 0.2174, loss: 0.6422 2023-11-13 21:59:43,348 - mmdet - INFO - Epoch [6][7050/7330] lr: 1.000e-04, eta: 5:28:52, time: 0.437, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0372, loss_cls: 0.1606, acc: 93.9785, loss_bbox: 0.2052, loss_mask: 0.2146, loss: 0.6348 2023-11-13 22:00:06,013 - mmdet - INFO - Epoch [6][7100/7330] lr: 1.000e-04, eta: 5:28:30, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0406, loss_cls: 0.1627, acc: 93.8865, loss_bbox: 0.2166, loss_mask: 0.2210, loss: 0.6603 2023-11-13 22:00:28,234 - mmdet - INFO - Epoch [6][7150/7330] lr: 1.000e-04, eta: 5:28:07, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0399, loss_cls: 0.1678, acc: 93.7305, loss_bbox: 0.2205, loss_mask: 0.2196, loss: 0.6660 2023-11-13 22:00:50,357 - mmdet - INFO - Epoch [6][7200/7330] lr: 1.000e-04, eta: 5:27:45, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0195, loss_rpn_bbox: 0.0378, loss_cls: 0.1603, acc: 94.0305, loss_bbox: 0.2043, loss_mask: 0.2157, loss: 0.6375 2023-11-13 22:01:12,344 - mmdet - INFO - Epoch [6][7250/7330] lr: 1.000e-04, eta: 5:27:22, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0360, loss_cls: 0.1586, acc: 94.0586, loss_bbox: 0.1982, loss_mask: 0.2099, loss: 0.6198 2023-11-13 22:01:34,695 - mmdet - INFO - Epoch [6][7300/7330] lr: 1.000e-04, eta: 5:27:00, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0194, loss_rpn_bbox: 0.0373, loss_cls: 0.1646, acc: 93.8438, loss_bbox: 0.2093, loss_mask: 0.2150, loss: 0.6455 2023-11-13 22:01:48,810 - mmdet - INFO - Saving checkpoint at 6 epochs 2023-11-13 22:02:40,025 - mmdet - INFO - Evaluating bbox... 2023-11-13 22:03:08,267 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.476 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.702 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.526 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.313 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.517 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.443 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.648 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.752 2023-11-13 22:03:08,269 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.578 | bicycle | 0.360 | car | 0.494 | | motorcycle | 0.485 | airplane | 0.686 | bus | 0.683 | | train | 0.672 | truck | 0.427 | boat | 0.313 | | traffic light | 0.318 | fire hydrant | 0.742 | stop sign | 0.669 | | parking meter | 0.502 | bench | 0.297 | bird | 0.407 | | cat | 0.730 | dog | 0.676 | horse | 0.621 | | sheep | 0.582 | cow | 0.630 | elephant | 0.675 | | bear | 0.746 | zebra | 0.705 | giraffe | 0.707 | | backpack | 0.223 | umbrella | 0.452 | handbag | 0.237 | | tie | 0.391 | suitcase | 0.481 | frisbee | 0.656 | | skis | 0.277 | snowboard | 0.430 | sports ball | 0.476 | | kite | 0.442 | baseball bat | 0.384 | baseball glove | 0.429 | | skateboard | 0.592 | surfboard | 0.454 | tennis racket | 0.557 | | bottle | 0.459 | wine glass | 0.417 | cup | 0.497 | | fork | 0.439 | knife | 0.286 | spoon | 0.266 | | bowl | 0.477 | banana | 0.279 | apple | 0.258 | | sandwich | 0.468 | orange | 0.362 | broccoli | 0.271 | | carrot | 0.250 | hot dog | 0.422 | pizza | 0.548 | | donut | 0.554 | cake | 0.421 | chair | 0.348 | | couch | 0.470 | potted plant | 0.342 | bed | 0.475 | | dining table | 0.314 | toilet | 0.650 | tv | 0.625 | | laptop | 0.673 | mouse | 0.640 | remote | 0.416 | | keyboard | 0.556 | cell phone | 0.445 | microwave | 0.677 | | oven | 0.402 | toaster | 0.531 | sink | 0.438 | | refrigerator | 0.648 | book | 0.198 | clock | 0.527 | | vase | 0.431 | scissors | 0.417 | teddy bear | 0.526 | | hair drier | 0.168 | toothbrush | 0.301 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:03:08,270 - mmdet - INFO - Evaluating segm... 2023-11-13 22:03:42,115 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.428 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.671 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.460 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.231 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.464 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.621 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.550 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.550 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.550 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 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.712 2023-11-13 22:03:42,117 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.501 | bicycle | 0.217 | car | 0.449 | | motorcycle | 0.379 | airplane | 0.523 | bus | 0.669 | | train | 0.666 | truck | 0.411 | boat | 0.301 | | traffic light | 0.301 | fire hydrant | 0.708 | stop sign | 0.666 | | parking meter | 0.526 | bench | 0.225 | bird | 0.341 | | cat | 0.718 | dog | 0.632 | horse | 0.458 | | sheep | 0.516 | cow | 0.532 | elephant | 0.620 | | bear | 0.742 | zebra | 0.594 | giraffe | 0.552 | | backpack | 0.225 | umbrella | 0.512 | handbag | 0.218 | | tie | 0.362 | suitcase | 0.498 | frisbee | 0.637 | | skis | 0.046 | snowboard | 0.298 | sports ball | 0.478 | | kite | 0.317 | baseball bat | 0.288 | baseball glove | 0.451 | | skateboard | 0.360 | surfboard | 0.372 | tennis racket | 0.569 | | bottle | 0.446 | wine glass | 0.373 | cup | 0.495 | | fork | 0.231 | knife | 0.197 | spoon | 0.182 | | bowl | 0.440 | banana | 0.243 | apple | 0.257 | | sandwich | 0.481 | orange | 0.363 | broccoli | 0.249 | | carrot | 0.224 | hot dog | 0.320 | pizza | 0.528 | | donut | 0.567 | cake | 0.442 | chair | 0.245 | | couch | 0.394 | potted plant | 0.288 | bed | 0.360 | | dining table | 0.186 | toilet | 0.622 | tv | 0.647 | | laptop | 0.664 | mouse | 0.626 | remote | 0.385 | | keyboard | 0.540 | cell phone | 0.416 | microwave | 0.670 | | oven | 0.367 | toaster | 0.554 | sink | 0.411 | | refrigerator | 0.666 | book | 0.146 | clock | 0.526 | | vase | 0.425 | scissors | 0.313 | teddy bear | 0.508 | | hair drier | 0.130 | toothbrush | 0.233 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:03:42,542 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_5.pth was removed 2023-11-13 22:03:46,187 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_6.pth. 2023-11-13 22:03:46,188 - mmdet - INFO - Best bbox_mAP is 0.4760 at 6 epoch. 2023-11-13 22:03:46,188 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 22:03:46,188 - mmdet - INFO - Epoch(val) [6][625] bbox_mAP: 0.4760, bbox_mAP_50: 0.7022, bbox_mAP_75: 0.5264, bbox_mAP_s: 0.3125, bbox_mAP_m: 0.5174, bbox_mAP_l: 0.6166, bbox_mAP_copypaste: 0.4760 0.7022 0.5264 0.3125 0.5174 0.6166, segm_mAP: 0.4280, segm_mAP_50: 0.6707, segm_mAP_75: 0.4595, segm_mAP_s: 0.2313, segm_mAP_m: 0.4642, segm_mAP_l: 0.6207, segm_mAP_copypaste: 0.4280 0.6707 0.4595 0.2313 0.4642 0.6207 2023-11-13 22:04:12,153 - mmdet - INFO - Epoch [7][50/7330] lr: 1.000e-04, eta: 5:26:15, time: 0.519, data_time: 0.089, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0377, loss_cls: 0.1534, acc: 94.1855, loss_bbox: 0.2065, loss_mask: 0.2163, loss: 0.6312 2023-11-13 22:04:34,758 - mmdet - INFO - Epoch [7][100/7330] lr: 1.000e-04, eta: 5:25:53, time: 0.452, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0348, loss_cls: 0.1510, acc: 94.3613, loss_bbox: 0.1958, loss_mask: 0.2100, loss: 0.6075 2023-11-13 22:04:57,584 - mmdet - INFO - Epoch [7][150/7330] lr: 1.000e-04, eta: 5:25:31, time: 0.457, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0381, loss_cls: 0.1559, acc: 94.1423, loss_bbox: 0.2034, loss_mask: 0.2142, loss: 0.6280 2023-11-13 22:05:20,010 - mmdet - INFO - Epoch [7][200/7330] lr: 1.000e-04, eta: 5:25:09, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0384, loss_cls: 0.1582, acc: 94.0261, loss_bbox: 0.2079, loss_mask: 0.2191, loss: 0.6398 2023-11-13 22:05:42,603 - mmdet - INFO - Epoch [7][250/7330] lr: 1.000e-04, eta: 5:24:47, time: 0.452, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0373, loss_cls: 0.1584, acc: 94.0159, loss_bbox: 0.2106, loss_mask: 0.2168, loss: 0.6405 2023-11-13 22:06:05,457 - mmdet - INFO - Epoch [7][300/7330] lr: 1.000e-04, eta: 5:24:25, time: 0.457, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0389, loss_cls: 0.1579, acc: 94.1116, loss_bbox: 0.2083, loss_mask: 0.2115, loss: 0.6332 2023-11-13 22:06:27,727 - mmdet - INFO - Epoch [7][350/7330] lr: 1.000e-04, eta: 5:24:03, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0377, loss_cls: 0.1512, acc: 94.3274, loss_bbox: 0.1982, loss_mask: 0.2131, loss: 0.6161 2023-11-13 22:06:49,865 - mmdet - INFO - Epoch [7][400/7330] lr: 1.000e-04, eta: 5:23:40, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0348, loss_cls: 0.1519, acc: 94.2427, loss_bbox: 0.2032, loss_mask: 0.2086, loss: 0.6138 2023-11-13 22:07:12,357 - mmdet - INFO - Epoch [7][450/7330] lr: 1.000e-04, eta: 5:23:18, time: 0.450, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0379, loss_cls: 0.1504, acc: 94.2449, loss_bbox: 0.2070, loss_mask: 0.2120, loss: 0.6251 2023-11-13 22:07:34,835 - mmdet - INFO - Epoch [7][500/7330] lr: 1.000e-04, eta: 5:22:56, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0364, loss_cls: 0.1487, acc: 94.3528, loss_bbox: 0.1988, loss_mask: 0.2069, loss: 0.6072 2023-11-13 22:07:57,195 - mmdet - INFO - Epoch [7][550/7330] lr: 1.000e-04, eta: 5:22:34, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0366, loss_cls: 0.1483, acc: 94.4097, loss_bbox: 0.2011, loss_mask: 0.2084, loss: 0.6093 2023-11-13 22:08:19,679 - mmdet - INFO - Epoch [7][600/7330] lr: 1.000e-04, eta: 5:22:12, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0344, loss_cls: 0.1492, acc: 94.3406, loss_bbox: 0.2010, loss_mask: 0.2095, loss: 0.6091 2023-11-13 22:08:41,844 - mmdet - INFO - Epoch [7][650/7330] lr: 1.000e-04, eta: 5:21:50, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0395, loss_cls: 0.1593, acc: 93.9143, loss_bbox: 0.2137, loss_mask: 0.2153, loss: 0.6437 2023-11-13 22:09:04,639 - mmdet - INFO - Epoch [7][700/7330] lr: 1.000e-04, eta: 5:21:28, time: 0.456, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0381, loss_cls: 0.1568, acc: 94.0789, loss_bbox: 0.2082, loss_mask: 0.2131, loss: 0.6321 2023-11-13 22:09:26,962 - mmdet - INFO - Epoch [7][750/7330] lr: 1.000e-04, eta: 5:21:06, time: 0.447, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0375, loss_cls: 0.1521, acc: 94.1851, loss_bbox: 0.2015, loss_mask: 0.2138, loss: 0.6215 2023-11-13 22:09:49,540 - mmdet - INFO - Epoch [7][800/7330] lr: 1.000e-04, eta: 5:20:44, time: 0.451, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0188, loss_rpn_bbox: 0.0400, loss_cls: 0.1618, acc: 93.8828, loss_bbox: 0.2135, loss_mask: 0.2187, loss: 0.6528 2023-11-13 22:10:11,624 - mmdet - INFO - Epoch [7][850/7330] lr: 1.000e-04, eta: 5:20:21, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0351, loss_cls: 0.1508, acc: 94.3567, loss_bbox: 0.2007, loss_mask: 0.2098, loss: 0.6126 2023-11-13 22:10:33,985 - mmdet - INFO - Epoch [7][900/7330] lr: 1.000e-04, eta: 5:19:59, time: 0.447, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0385, loss_cls: 0.1553, acc: 94.1174, loss_bbox: 0.2054, loss_mask: 0.2179, loss: 0.6339 2023-11-13 22:10:56,157 - mmdet - INFO - Epoch [7][950/7330] lr: 1.000e-04, eta: 5:19:36, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0367, loss_cls: 0.1545, acc: 94.1941, loss_bbox: 0.2056, loss_mask: 0.2125, loss: 0.6255 2023-11-13 22:11:18,888 - mmdet - INFO - Epoch [7][1000/7330] lr: 1.000e-04, eta: 5:19:15, time: 0.455, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0391, loss_cls: 0.1649, acc: 93.8459, loss_bbox: 0.2120, loss_mask: 0.2124, loss: 0.6463 2023-11-13 22:11:41,334 - mmdet - INFO - Epoch [7][1050/7330] lr: 1.000e-04, eta: 5:18:53, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0370, loss_cls: 0.1520, acc: 94.1780, loss_bbox: 0.2032, loss_mask: 0.2137, loss: 0.6224 2023-11-13 22:12:04,012 - mmdet - INFO - Epoch [7][1100/7330] lr: 1.000e-04, eta: 5:18:31, time: 0.453, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0406, loss_cls: 0.1639, acc: 93.8276, loss_bbox: 0.2137, loss_mask: 0.2168, loss: 0.6532 2023-11-13 22:12:26,320 - mmdet - INFO - Epoch [7][1150/7330] lr: 1.000e-04, eta: 5:18:08, time: 0.446, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0362, loss_cls: 0.1546, acc: 94.1277, loss_bbox: 0.2042, loss_mask: 0.2097, loss: 0.6216 2023-11-13 22:12:48,415 - mmdet - INFO - Epoch [7][1200/7330] lr: 1.000e-04, eta: 5:17:46, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0377, loss_cls: 0.1549, acc: 94.1807, loss_bbox: 0.2011, loss_mask: 0.2117, loss: 0.6223 2023-11-13 22:13:11,193 - mmdet - INFO - Epoch [7][1250/7330] lr: 1.000e-04, eta: 5:17:24, time: 0.456, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0385, loss_cls: 0.1592, acc: 93.9329, loss_bbox: 0.2099, loss_mask: 0.2200, loss: 0.6451 2023-11-13 22:13:33,776 - mmdet - INFO - Epoch [7][1300/7330] lr: 1.000e-04, eta: 5:17:02, time: 0.452, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0363, loss_cls: 0.1539, acc: 94.2368, loss_bbox: 0.2018, loss_mask: 0.2137, loss: 0.6210 2023-11-13 22:13:56,486 - mmdet - INFO - Epoch [7][1350/7330] lr: 1.000e-04, eta: 5:16:40, time: 0.454, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0384, loss_cls: 0.1583, acc: 94.0349, loss_bbox: 0.2088, loss_mask: 0.2110, loss: 0.6343 2023-11-13 22:14:18,877 - mmdet - INFO - Epoch [7][1400/7330] lr: 1.000e-04, eta: 5:16:18, time: 0.448, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0386, loss_cls: 0.1604, acc: 93.8633, loss_bbox: 0.2123, loss_mask: 0.2123, loss: 0.6412 2023-11-13 22:14:40,998 - mmdet - INFO - Epoch [7][1450/7330] lr: 1.000e-04, eta: 5:15:56, time: 0.442, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0346, loss_cls: 0.1546, acc: 94.2595, loss_bbox: 0.2001, loss_mask: 0.2109, loss: 0.6171 2023-11-13 22:15:03,143 - mmdet - INFO - Epoch [7][1500/7330] lr: 1.000e-04, eta: 5:15:33, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0367, loss_cls: 0.1552, acc: 94.1375, loss_bbox: 0.2028, loss_mask: 0.2116, loss: 0.6218 2023-11-13 22:15:25,605 - mmdet - INFO - Epoch [7][1550/7330] lr: 1.000e-04, eta: 5:15:11, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0391, loss_cls: 0.1555, acc: 94.1182, loss_bbox: 0.2041, loss_mask: 0.2120, loss: 0.6272 2023-11-13 22:15:47,603 - mmdet - INFO - Epoch [7][1600/7330] lr: 1.000e-04, eta: 5:14:48, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0350, loss_cls: 0.1513, acc: 94.2476, loss_bbox: 0.2024, loss_mask: 0.2098, loss: 0.6128 2023-11-13 22:16:09,716 - mmdet - INFO - Epoch [7][1650/7330] lr: 1.000e-04, eta: 5:14:26, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0358, loss_cls: 0.1529, acc: 94.2302, loss_bbox: 0.2021, loss_mask: 0.2091, loss: 0.6156 2023-11-13 22:16:32,186 - mmdet - INFO - Epoch [7][1700/7330] lr: 1.000e-04, eta: 5:14:04, time: 0.449, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0407, loss_cls: 0.1601, acc: 93.9951, loss_bbox: 0.2120, loss_mask: 0.2142, loss: 0.6454 2023-11-13 22:16:54,598 - mmdet - INFO - Epoch [7][1750/7330] lr: 1.000e-04, eta: 5:13:42, time: 0.448, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0360, loss_cls: 0.1485, acc: 94.3547, loss_bbox: 0.2002, loss_mask: 0.2129, loss: 0.6141 2023-11-13 22:17:16,892 - mmdet - INFO - Epoch [7][1800/7330] lr: 1.000e-04, eta: 5:13:19, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0365, loss_cls: 0.1558, acc: 94.0925, loss_bbox: 0.2045, loss_mask: 0.2145, loss: 0.6274 2023-11-13 22:17:38,988 - mmdet - INFO - Epoch [7][1850/7330] lr: 1.000e-04, eta: 5:12:57, time: 0.442, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0364, loss_cls: 0.1490, acc: 94.4172, loss_bbox: 0.1994, loss_mask: 0.2108, loss: 0.6112 2023-11-13 22:18:00,952 - mmdet - INFO - Epoch [7][1900/7330] lr: 1.000e-04, eta: 5:12:34, time: 0.439, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0358, loss_cls: 0.1542, acc: 94.1516, loss_bbox: 0.2037, loss_mask: 0.2131, loss: 0.6232 2023-11-13 22:18:22,794 - mmdet - INFO - Epoch [7][1950/7330] lr: 1.000e-04, eta: 5:12:12, time: 0.437, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0343, loss_cls: 0.1511, acc: 94.3621, loss_bbox: 0.2004, loss_mask: 0.2062, loss: 0.6076 2023-11-13 22:18:45,455 - mmdet - INFO - Epoch [7][2000/7330] lr: 1.000e-04, eta: 5:11:50, time: 0.453, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0393, loss_cls: 0.1618, acc: 93.9080, loss_bbox: 0.2114, loss_mask: 0.2110, loss: 0.6394 2023-11-13 22:19:07,768 - mmdet - INFO - Epoch [7][2050/7330] lr: 1.000e-04, eta: 5:11:28, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0346, loss_cls: 0.1474, acc: 94.4177, loss_bbox: 0.1969, loss_mask: 0.2084, loss: 0.6012 2023-11-13 22:19:29,809 - mmdet - INFO - Epoch [7][2100/7330] lr: 1.000e-04, eta: 5:11:05, time: 0.441, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0353, loss_cls: 0.1502, acc: 94.3489, loss_bbox: 0.2026, loss_mask: 0.2108, loss: 0.6161 2023-11-13 22:19:52,196 - mmdet - INFO - Epoch [7][2150/7330] lr: 1.000e-04, eta: 5:10:43, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0376, loss_cls: 0.1531, acc: 94.1101, loss_bbox: 0.2086, loss_mask: 0.2124, loss: 0.6274 2023-11-13 22:20:14,978 - mmdet - INFO - Epoch [7][2200/7330] lr: 1.000e-04, eta: 5:10:21, time: 0.456, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0384, loss_cls: 0.1567, acc: 94.0710, loss_bbox: 0.2017, loss_mask: 0.2106, loss: 0.6244 2023-11-13 22:20:37,809 - mmdet - INFO - Epoch [7][2250/7330] lr: 1.000e-04, eta: 5:09:59, time: 0.457, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0382, loss_cls: 0.1532, acc: 94.2756, loss_bbox: 0.2030, loss_mask: 0.2066, loss: 0.6181 2023-11-13 22:21:00,257 - mmdet - INFO - Epoch [7][2300/7330] lr: 1.000e-04, eta: 5:09:37, time: 0.449, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0373, loss_cls: 0.1595, acc: 94.0640, loss_bbox: 0.2123, loss_mask: 0.2177, loss: 0.6440 2023-11-13 22:21:22,921 - mmdet - INFO - Epoch [7][2350/7330] lr: 1.000e-04, eta: 5:09:15, time: 0.453, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0383, loss_cls: 0.1632, acc: 93.9045, loss_bbox: 0.2097, loss_mask: 0.2178, loss: 0.6459 2023-11-13 22:21:45,120 - mmdet - INFO - Epoch [7][2400/7330] lr: 1.000e-04, eta: 5:08:53, time: 0.444, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0355, loss_cls: 0.1493, acc: 94.4238, loss_bbox: 0.1984, loss_mask: 0.2100, loss: 0.6094 2023-11-13 22:22:07,814 - mmdet - INFO - Epoch [7][2450/7330] lr: 1.000e-04, eta: 5:08:31, time: 0.454, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0371, loss_cls: 0.1619, acc: 93.8652, loss_bbox: 0.2114, loss_mask: 0.2154, loss: 0.6420 2023-11-13 22:22:30,506 - mmdet - INFO - Epoch [7][2500/7330] lr: 1.000e-04, eta: 5:08:09, time: 0.454, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0397, loss_cls: 0.1621, acc: 93.8950, loss_bbox: 0.2141, loss_mask: 0.2195, loss: 0.6528 2023-11-13 22:22:52,793 - mmdet - INFO - Epoch [7][2550/7330] lr: 1.000e-04, eta: 5:07:47, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0360, loss_cls: 0.1565, acc: 94.0686, loss_bbox: 0.2061, loss_mask: 0.2135, loss: 0.6289 2023-11-13 22:23:14,796 - mmdet - INFO - Epoch [7][2600/7330] lr: 1.000e-04, eta: 5:07:24, time: 0.440, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0365, loss_cls: 0.1563, acc: 94.0601, loss_bbox: 0.2024, loss_mask: 0.2138, loss: 0.6248 2023-11-13 22:23:36,863 - mmdet - INFO - Epoch [7][2650/7330] lr: 1.000e-04, eta: 5:07:02, time: 0.441, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0366, loss_cls: 0.1607, acc: 93.8604, loss_bbox: 0.2095, loss_mask: 0.2134, loss: 0.6359 2023-11-13 22:23:59,232 - mmdet - INFO - Epoch [7][2700/7330] lr: 1.000e-04, eta: 5:06:39, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0353, loss_cls: 0.1548, acc: 94.1531, loss_bbox: 0.2060, loss_mask: 0.2105, loss: 0.6222 2023-11-13 22:24:21,511 - mmdet - INFO - Epoch [7][2750/7330] lr: 1.000e-04, eta: 5:06:17, time: 0.446, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0360, loss_cls: 0.1492, acc: 94.4109, loss_bbox: 0.2003, loss_mask: 0.2118, loss: 0.6145 2023-11-13 22:24:43,753 - mmdet - INFO - Epoch [7][2800/7330] lr: 1.000e-04, eta: 5:05:55, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0364, loss_cls: 0.1529, acc: 94.2795, loss_bbox: 0.1969, loss_mask: 0.2103, loss: 0.6134 2023-11-13 22:25:06,197 - mmdet - INFO - Epoch [7][2850/7330] lr: 1.000e-04, eta: 5:05:33, time: 0.449, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0408, loss_cls: 0.1563, acc: 94.1917, loss_bbox: 0.2045, loss_mask: 0.2160, loss: 0.6346 2023-11-13 22:25:28,268 - mmdet - INFO - Epoch [7][2900/7330] lr: 1.000e-04, eta: 5:05:10, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0342, loss_cls: 0.1493, acc: 94.4351, loss_bbox: 0.1956, loss_mask: 0.2122, loss: 0.6060 2023-11-13 22:25:50,839 - mmdet - INFO - Epoch [7][2950/7330] lr: 1.000e-04, eta: 5:04:48, time: 0.451, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0371, loss_cls: 0.1559, acc: 94.1646, loss_bbox: 0.2009, loss_mask: 0.2078, loss: 0.6187 2023-11-13 22:26:12,897 - mmdet - INFO - Epoch [7][3000/7330] lr: 1.000e-04, eta: 5:04:26, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0351, loss_cls: 0.1520, acc: 94.1995, loss_bbox: 0.1981, loss_mask: 0.2110, loss: 0.6128 2023-11-13 22:26:35,075 - mmdet - INFO - Epoch [7][3050/7330] lr: 1.000e-04, eta: 5:04:03, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0352, loss_cls: 0.1509, acc: 94.3123, loss_bbox: 0.1956, loss_mask: 0.2118, loss: 0.6093 2023-11-13 22:26:57,883 - mmdet - INFO - Epoch [7][3100/7330] lr: 1.000e-04, eta: 5:03:41, time: 0.456, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0366, loss_cls: 0.1619, acc: 93.9141, loss_bbox: 0.2100, loss_mask: 0.2124, loss: 0.6384 2023-11-13 22:27:20,223 - mmdet - INFO - Epoch [7][3150/7330] lr: 1.000e-04, eta: 5:03:19, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0186, loss_rpn_bbox: 0.0395, loss_cls: 0.1625, acc: 93.9053, loss_bbox: 0.2129, loss_mask: 0.2161, loss: 0.6495 2023-11-13 22:27:42,462 - mmdet - INFO - Epoch [7][3200/7330] lr: 1.000e-04, eta: 5:02:57, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0355, loss_cls: 0.1471, acc: 94.4543, loss_bbox: 0.1969, loss_mask: 0.2100, loss: 0.6059 2023-11-13 22:28:04,768 - mmdet - INFO - Epoch [7][3250/7330] lr: 1.000e-04, eta: 5:02:35, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0370, loss_cls: 0.1526, acc: 94.3335, loss_bbox: 0.1962, loss_mask: 0.2128, loss: 0.6154 2023-11-13 22:28:27,282 - mmdet - INFO - Epoch [7][3300/7330] lr: 1.000e-04, eta: 5:02:12, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0366, loss_cls: 0.1552, acc: 94.1982, loss_bbox: 0.2050, loss_mask: 0.2122, loss: 0.6254 2023-11-13 22:28:49,839 - mmdet - INFO - Epoch [7][3350/7330] lr: 1.000e-04, eta: 5:01:50, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0374, loss_cls: 0.1519, acc: 94.3005, loss_bbox: 0.2029, loss_mask: 0.2116, loss: 0.6215 2023-11-13 22:29:11,912 - mmdet - INFO - Epoch [7][3400/7330] lr: 1.000e-04, eta: 5:01:28, time: 0.441, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0358, loss_cls: 0.1500, acc: 94.3301, loss_bbox: 0.1993, loss_mask: 0.2077, loss: 0.6091 2023-11-13 22:29:33,959 - mmdet - INFO - Epoch [7][3450/7330] lr: 1.000e-04, eta: 5:01:05, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0355, loss_cls: 0.1554, acc: 94.1550, loss_bbox: 0.2039, loss_mask: 0.2119, loss: 0.6220 2023-11-13 22:29:56,118 - mmdet - INFO - Epoch [7][3500/7330] lr: 1.000e-04, eta: 5:00:43, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0388, loss_cls: 0.1563, acc: 94.0645, loss_bbox: 0.2066, loss_mask: 0.2135, loss: 0.6323 2023-11-13 22:30:18,424 - mmdet - INFO - Epoch [7][3550/7330] lr: 1.000e-04, eta: 5:00:21, time: 0.446, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0386, loss_cls: 0.1592, acc: 94.0750, loss_bbox: 0.2065, loss_mask: 0.2135, loss: 0.6343 2023-11-13 22:30:40,286 - mmdet - INFO - Epoch [7][3600/7330] lr: 1.000e-04, eta: 4:59:58, time: 0.437, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0345, loss_cls: 0.1478, acc: 94.4255, loss_bbox: 0.1963, loss_mask: 0.2069, loss: 0.6017 2023-11-13 22:31:02,528 - mmdet - INFO - Epoch [7][3650/7330] lr: 1.000e-04, eta: 4:59:36, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0357, loss_cls: 0.1529, acc: 94.1641, loss_bbox: 0.2029, loss_mask: 0.2126, loss: 0.6196 2023-11-13 22:31:24,908 - mmdet - INFO - Epoch [7][3700/7330] lr: 1.000e-04, eta: 4:59:14, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0377, loss_cls: 0.1529, acc: 94.2292, loss_bbox: 0.2021, loss_mask: 0.2168, loss: 0.6262 2023-11-13 22:31:47,303 - mmdet - INFO - Epoch [7][3750/7330] lr: 1.000e-04, eta: 4:58:51, time: 0.448, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0390, loss_cls: 0.1604, acc: 93.8303, loss_bbox: 0.2166, loss_mask: 0.2207, loss: 0.6535 2023-11-13 22:32:09,224 - mmdet - INFO - Epoch [7][3800/7330] lr: 1.000e-04, eta: 4:58:29, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0374, loss_cls: 0.1495, acc: 94.3108, loss_bbox: 0.2021, loss_mask: 0.2123, loss: 0.6183 2023-11-13 22:32:31,533 - mmdet - INFO - Epoch [7][3850/7330] lr: 1.000e-04, eta: 4:58:07, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0373, loss_cls: 0.1584, acc: 93.9087, loss_bbox: 0.2105, loss_mask: 0.2162, loss: 0.6383 2023-11-13 22:32:54,049 - mmdet - INFO - Epoch [7][3900/7330] lr: 1.000e-04, eta: 4:57:44, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0367, loss_cls: 0.1544, acc: 94.1899, loss_bbox: 0.2043, loss_mask: 0.2123, loss: 0.6242 2023-11-13 22:33:16,460 - mmdet - INFO - Epoch [7][3950/7330] lr: 1.000e-04, eta: 4:57:22, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0367, loss_cls: 0.1550, acc: 94.0938, loss_bbox: 0.2082, loss_mask: 0.2144, loss: 0.6306 2023-11-13 22:33:38,571 - mmdet - INFO - Epoch [7][4000/7330] lr: 1.000e-04, eta: 4:57:00, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0364, loss_cls: 0.1566, acc: 94.0857, loss_bbox: 0.2028, loss_mask: 0.2075, loss: 0.6205 2023-11-13 22:34:00,855 - mmdet - INFO - Epoch [7][4050/7330] lr: 1.000e-04, eta: 4:56:38, time: 0.446, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0387, loss_cls: 0.1570, acc: 94.1750, loss_bbox: 0.2095, loss_mask: 0.2173, loss: 0.6408 2023-11-13 22:34:22,770 - mmdet - INFO - Epoch [7][4100/7330] lr: 1.000e-04, eta: 4:56:15, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0366, loss_cls: 0.1546, acc: 94.1848, loss_bbox: 0.2019, loss_mask: 0.2174, loss: 0.6279 2023-11-13 22:34:45,196 - mmdet - INFO - Epoch [7][4150/7330] lr: 1.000e-04, eta: 4:55:53, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0383, loss_cls: 0.1568, acc: 94.1482, loss_bbox: 0.2017, loss_mask: 0.2104, loss: 0.6232 2023-11-13 22:35:07,425 - mmdet - INFO - Epoch [7][4200/7330] lr: 1.000e-04, eta: 4:55:30, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0360, loss_cls: 0.1557, acc: 94.1494, loss_bbox: 0.2024, loss_mask: 0.2127, loss: 0.6230 2023-11-13 22:35:30,063 - mmdet - INFO - Epoch [7][4250/7330] lr: 1.000e-04, eta: 4:55:08, time: 0.453, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0373, loss_cls: 0.1578, acc: 94.0850, loss_bbox: 0.2067, loss_mask: 0.2146, loss: 0.6336 2023-11-13 22:35:52,286 - mmdet - INFO - Epoch [7][4300/7330] lr: 1.000e-04, eta: 4:54:46, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0356, loss_cls: 0.1499, acc: 94.2878, loss_bbox: 0.2012, loss_mask: 0.2150, loss: 0.6177 2023-11-13 22:36:14,824 - mmdet - INFO - Epoch [7][4350/7330] lr: 1.000e-04, eta: 4:54:24, time: 0.451, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0373, loss_cls: 0.1553, acc: 94.1501, loss_bbox: 0.2105, loss_mask: 0.2130, loss: 0.6328 2023-11-13 22:36:37,533 - mmdet - INFO - Epoch [7][4400/7330] lr: 1.000e-04, eta: 4:54:02, time: 0.454, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0381, loss_cls: 0.1569, acc: 94.0725, loss_bbox: 0.2035, loss_mask: 0.2129, loss: 0.6271 2023-11-13 22:36:59,772 - mmdet - INFO - Epoch [7][4450/7330] lr: 1.000e-04, eta: 4:53:40, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0384, loss_cls: 0.1628, acc: 93.9041, loss_bbox: 0.2132, loss_mask: 0.2192, loss: 0.6502 2023-11-13 22:37:21,983 - mmdet - INFO - Epoch [7][4500/7330] lr: 1.000e-04, eta: 4:53:17, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0368, loss_cls: 0.1543, acc: 94.1533, loss_bbox: 0.2023, loss_mask: 0.2131, loss: 0.6232 2023-11-13 22:37:44,711 - mmdet - INFO - Epoch [7][4550/7330] lr: 1.000e-04, eta: 4:52:55, time: 0.455, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0388, loss_cls: 0.1632, acc: 93.8550, loss_bbox: 0.2105, loss_mask: 0.2101, loss: 0.6391 2023-11-13 22:38:06,891 - mmdet - INFO - Epoch [7][4600/7330] lr: 1.000e-04, eta: 4:52:33, time: 0.444, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0380, loss_cls: 0.1610, acc: 93.9351, loss_bbox: 0.2084, loss_mask: 0.2212, loss: 0.6454 2023-11-13 22:38:29,040 - mmdet - INFO - Epoch [7][4650/7330] lr: 1.000e-04, eta: 4:52:11, time: 0.443, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0375, loss_cls: 0.1540, acc: 94.1987, loss_bbox: 0.2041, loss_mask: 0.2140, loss: 0.6261 2023-11-13 22:38:51,295 - mmdet - INFO - Epoch [7][4700/7330] lr: 1.000e-04, eta: 4:51:48, time: 0.445, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0187, loss_rpn_bbox: 0.0382, loss_cls: 0.1639, acc: 93.7178, loss_bbox: 0.2149, loss_mask: 0.2213, loss: 0.6570 2023-11-13 22:39:13,079 - mmdet - INFO - Epoch [7][4750/7330] lr: 1.000e-04, eta: 4:51:26, time: 0.436, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0372, loss_cls: 0.1528, acc: 94.3101, loss_bbox: 0.1986, loss_mask: 0.2139, loss: 0.6198 2023-11-13 22:39:35,076 - mmdet - INFO - Epoch [7][4800/7330] lr: 1.000e-04, eta: 4:51:03, time: 0.440, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0363, loss_cls: 0.1589, acc: 94.0173, loss_bbox: 0.2092, loss_mask: 0.2143, loss: 0.6346 2023-11-13 22:39:57,038 - mmdet - INFO - Epoch [7][4850/7330] lr: 1.000e-04, eta: 4:50:41, time: 0.439, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0339, loss_cls: 0.1513, acc: 94.4280, loss_bbox: 0.1972, loss_mask: 0.2146, loss: 0.6111 2023-11-13 22:40:20,086 - mmdet - INFO - Epoch [7][4900/7330] lr: 1.000e-04, eta: 4:50:19, time: 0.461, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0398, loss_cls: 0.1646, acc: 93.8555, loss_bbox: 0.2143, loss_mask: 0.2150, loss: 0.6519 2023-11-13 22:40:42,114 - mmdet - INFO - Epoch [7][4950/7330] lr: 1.000e-04, eta: 4:49:56, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0369, loss_cls: 0.1555, acc: 94.1663, loss_bbox: 0.2022, loss_mask: 0.2115, loss: 0.6224 2023-11-13 22:41:04,546 - mmdet - INFO - Epoch [7][5000/7330] lr: 1.000e-04, eta: 4:49:34, time: 0.449, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0355, loss_cls: 0.1541, acc: 94.1907, loss_bbox: 0.1999, loss_mask: 0.2084, loss: 0.6141 2023-11-13 22:41:26,839 - mmdet - INFO - Epoch [7][5050/7330] lr: 1.000e-04, eta: 4:49:12, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0383, loss_cls: 0.1586, acc: 94.0520, loss_bbox: 0.2078, loss_mask: 0.2165, loss: 0.6388 2023-11-13 22:41:49,513 - mmdet - INFO - Epoch [7][5100/7330] lr: 1.000e-04, eta: 4:48:50, time: 0.453, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0382, loss_cls: 0.1647, acc: 93.8442, loss_bbox: 0.2163, loss_mask: 0.2172, loss: 0.6557 2023-11-13 22:42:12,176 - mmdet - INFO - Epoch [7][5150/7330] lr: 1.000e-04, eta: 4:48:28, time: 0.453, data_time: 0.017, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0390, loss_cls: 0.1592, acc: 93.9470, loss_bbox: 0.2081, loss_mask: 0.2155, loss: 0.6394 2023-11-13 22:42:34,545 - mmdet - INFO - Epoch [7][5200/7330] lr: 1.000e-04, eta: 4:48:06, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0393, loss_cls: 0.1645, acc: 93.7871, loss_bbox: 0.2172, loss_mask: 0.2189, loss: 0.6585 2023-11-13 22:42:57,193 - mmdet - INFO - Epoch [7][5250/7330] lr: 1.000e-04, eta: 4:47:44, time: 0.453, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0390, loss_cls: 0.1669, acc: 93.6306, loss_bbox: 0.2128, loss_mask: 0.2149, loss: 0.6505 2023-11-13 22:43:19,456 - mmdet - INFO - Epoch [7][5300/7330] lr: 1.000e-04, eta: 4:47:21, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0366, loss_cls: 0.1542, acc: 94.2891, loss_bbox: 0.2033, loss_mask: 0.2105, loss: 0.6214 2023-11-13 22:43:41,723 - mmdet - INFO - Epoch [7][5350/7330] lr: 1.000e-04, eta: 4:46:59, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0369, loss_cls: 0.1508, acc: 94.3218, loss_bbox: 0.1960, loss_mask: 0.2159, loss: 0.6165 2023-11-13 22:44:03,805 - mmdet - INFO - Epoch [7][5400/7330] lr: 1.000e-04, eta: 4:46:37, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0361, loss_cls: 0.1550, acc: 94.1387, loss_bbox: 0.2071, loss_mask: 0.2163, loss: 0.6294 2023-11-13 22:44:26,086 - mmdet - INFO - Epoch [7][5450/7330] lr: 1.000e-04, eta: 4:46:14, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0387, loss_cls: 0.1583, acc: 94.0222, loss_bbox: 0.2120, loss_mask: 0.2173, loss: 0.6426 2023-11-13 22:44:48,457 - mmdet - INFO - Epoch [7][5500/7330] lr: 1.000e-04, eta: 4:45:52, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0402, loss_cls: 0.1567, acc: 94.1006, loss_bbox: 0.2062, loss_mask: 0.2131, loss: 0.6332 2023-11-13 22:45:10,705 - mmdet - INFO - Epoch [7][5550/7330] lr: 1.000e-04, eta: 4:45:30, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0359, loss_cls: 0.1597, acc: 94.0859, loss_bbox: 0.2086, loss_mask: 0.2136, loss: 0.6343 2023-11-13 22:45:32,718 - mmdet - INFO - Epoch [7][5600/7330] lr: 1.000e-04, eta: 4:45:07, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0373, loss_cls: 0.1589, acc: 94.0142, loss_bbox: 0.2063, loss_mask: 0.2155, loss: 0.6346 2023-11-13 22:45:54,977 - mmdet - INFO - Epoch [7][5650/7330] lr: 1.000e-04, eta: 4:44:45, time: 0.445, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0183, loss_rpn_bbox: 0.0381, loss_cls: 0.1620, acc: 93.8591, loss_bbox: 0.2127, loss_mask: 0.2186, loss: 0.6498 2023-11-13 22:46:17,195 - mmdet - INFO - Epoch [7][5700/7330] lr: 1.000e-04, eta: 4:44:23, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0370, loss_cls: 0.1519, acc: 94.1968, loss_bbox: 0.2032, loss_mask: 0.2114, loss: 0.6200 2023-11-13 22:46:39,047 - mmdet - INFO - Epoch [7][5750/7330] lr: 1.000e-04, eta: 4:44:00, time: 0.437, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0360, loss_cls: 0.1540, acc: 94.1907, loss_bbox: 0.2023, loss_mask: 0.2159, loss: 0.6247 2023-11-13 22:47:01,430 - mmdet - INFO - Epoch [7][5800/7330] lr: 1.000e-04, eta: 4:43:38, time: 0.448, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0184, loss_rpn_bbox: 0.0377, loss_cls: 0.1562, acc: 94.0754, loss_bbox: 0.2026, loss_mask: 0.2138, loss: 0.6287 2023-11-13 22:47:23,622 - mmdet - INFO - Epoch [7][5850/7330] lr: 1.000e-04, eta: 4:43:16, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0182, loss_rpn_bbox: 0.0371, loss_cls: 0.1584, acc: 94.0149, loss_bbox: 0.2056, loss_mask: 0.2128, loss: 0.6322 2023-11-13 22:47:46,121 - mmdet - INFO - Epoch [7][5900/7330] lr: 1.000e-04, eta: 4:42:53, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0398, loss_cls: 0.1594, acc: 94.0073, loss_bbox: 0.2076, loss_mask: 0.2062, loss: 0.6300 2023-11-13 22:48:08,324 - mmdet - INFO - Epoch [7][5950/7330] lr: 1.000e-04, eta: 4:42:31, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0359, loss_cls: 0.1531, acc: 94.2241, loss_bbox: 0.2043, loss_mask: 0.2147, loss: 0.6249 2023-11-13 22:48:30,895 - mmdet - INFO - Epoch [7][6000/7330] lr: 1.000e-04, eta: 4:42:09, time: 0.451, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0379, loss_cls: 0.1605, acc: 93.9160, loss_bbox: 0.2072, loss_mask: 0.2095, loss: 0.6312 2023-11-13 22:48:53,057 - mmdet - INFO - Epoch [7][6050/7330] lr: 1.000e-04, eta: 4:41:47, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0376, loss_cls: 0.1546, acc: 94.1401, loss_bbox: 0.2093, loss_mask: 0.2118, loss: 0.6303 2023-11-13 22:49:15,287 - mmdet - INFO - Epoch [7][6100/7330] lr: 1.000e-04, eta: 4:41:24, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0356, loss_cls: 0.1490, acc: 94.4512, loss_bbox: 0.1953, loss_mask: 0.2062, loss: 0.6028 2023-11-13 22:49:37,289 - mmdet - INFO - Epoch [7][6150/7330] lr: 1.000e-04, eta: 4:41:02, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0371, loss_cls: 0.1536, acc: 94.3108, loss_bbox: 0.2011, loss_mask: 0.2110, loss: 0.6201 2023-11-13 22:49:59,681 - mmdet - INFO - Epoch [7][6200/7330] lr: 1.000e-04, eta: 4:40:40, time: 0.448, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0372, loss_cls: 0.1518, acc: 94.2744, loss_bbox: 0.1966, loss_mask: 0.2083, loss: 0.6105 2023-11-13 22:50:21,679 - mmdet - INFO - Epoch [7][6250/7330] lr: 1.000e-04, eta: 4:40:17, time: 0.440, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0335, loss_cls: 0.1480, acc: 94.3198, loss_bbox: 0.1944, loss_mask: 0.2111, loss: 0.6013 2023-11-13 22:50:43,994 - mmdet - INFO - Epoch [7][6300/7330] lr: 1.000e-04, eta: 4:39:55, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0340, loss_cls: 0.1508, acc: 94.3630, loss_bbox: 0.1913, loss_mask: 0.2070, loss: 0.5986 2023-11-13 22:51:06,306 - mmdet - INFO - Epoch [7][6350/7330] lr: 1.000e-04, eta: 4:39:33, time: 0.446, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0339, loss_cls: 0.1534, acc: 94.2405, loss_bbox: 0.2003, loss_mask: 0.2095, loss: 0.6138 2023-11-13 22:51:28,945 - mmdet - INFO - Epoch [7][6400/7330] lr: 1.000e-04, eta: 4:39:10, time: 0.453, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0365, loss_cls: 0.1607, acc: 93.9072, loss_bbox: 0.2048, loss_mask: 0.2122, loss: 0.6314 2023-11-13 22:51:51,345 - mmdet - INFO - Epoch [7][6450/7330] lr: 1.000e-04, eta: 4:38:48, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0366, loss_cls: 0.1536, acc: 94.1191, loss_bbox: 0.2044, loss_mask: 0.2154, loss: 0.6263 2023-11-13 22:52:13,390 - mmdet - INFO - Epoch [7][6500/7330] lr: 1.000e-04, eta: 4:38:26, time: 0.441, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0382, loss_cls: 0.1592, acc: 94.0991, loss_bbox: 0.2045, loss_mask: 0.2140, loss: 0.6328 2023-11-13 22:52:35,911 - mmdet - INFO - Epoch [7][6550/7330] lr: 1.000e-04, eta: 4:38:04, time: 0.450, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0364, loss_cls: 0.1550, acc: 94.2231, loss_bbox: 0.2037, loss_mask: 0.2151, loss: 0.6269 2023-11-13 22:52:58,432 - mmdet - INFO - Epoch [7][6600/7330] lr: 1.000e-04, eta: 4:37:42, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0380, loss_cls: 0.1579, acc: 94.0374, loss_bbox: 0.2077, loss_mask: 0.2160, loss: 0.6369 2023-11-13 22:53:21,239 - mmdet - INFO - Epoch [7][6650/7330] lr: 1.000e-04, eta: 4:37:20, time: 0.456, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0189, loss_rpn_bbox: 0.0381, loss_cls: 0.1618, acc: 93.9565, loss_bbox: 0.2097, loss_mask: 0.2117, loss: 0.6402 2023-11-13 22:53:43,464 - mmdet - INFO - Epoch [7][6700/7330] lr: 1.000e-04, eta: 4:36:57, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0376, loss_cls: 0.1535, acc: 94.2422, loss_bbox: 0.2029, loss_mask: 0.2141, loss: 0.6249 2023-11-13 22:54:05,423 - mmdet - INFO - Epoch [7][6750/7330] lr: 1.000e-04, eta: 4:36:35, time: 0.439, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0353, loss_cls: 0.1491, acc: 94.4150, loss_bbox: 0.2015, loss_mask: 0.2138, loss: 0.6153 2023-11-13 22:54:27,586 - mmdet - INFO - Epoch [7][6800/7330] lr: 1.000e-04, eta: 4:36:12, time: 0.443, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0370, loss_cls: 0.1561, acc: 94.1458, loss_bbox: 0.2022, loss_mask: 0.2153, loss: 0.6267 2023-11-13 22:54:50,121 - mmdet - INFO - Epoch [7][6850/7330] lr: 1.000e-04, eta: 4:35:50, time: 0.451, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0185, loss_rpn_bbox: 0.0413, loss_cls: 0.1589, acc: 94.0371, loss_bbox: 0.2086, loss_mask: 0.2186, loss: 0.6458 2023-11-13 22:55:12,257 - mmdet - INFO - Epoch [7][6900/7330] lr: 1.000e-04, eta: 4:35:28, time: 0.443, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0345, loss_cls: 0.1440, acc: 94.5713, loss_bbox: 0.1950, loss_mask: 0.2095, loss: 0.5985 2023-11-13 22:55:34,869 - mmdet - INFO - Epoch [7][6950/7330] lr: 1.000e-04, eta: 4:35:06, time: 0.452, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0396, loss_cls: 0.1546, acc: 94.2385, loss_bbox: 0.2037, loss_mask: 0.2132, loss: 0.6290 2023-11-13 22:55:57,054 - mmdet - INFO - Epoch [7][7000/7330] lr: 1.000e-04, eta: 4:34:44, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0336, loss_cls: 0.1509, acc: 94.3142, loss_bbox: 0.2010, loss_mask: 0.2112, loss: 0.6124 2023-11-13 22:56:19,354 - mmdet - INFO - Epoch [7][7050/7330] lr: 1.000e-04, eta: 4:34:21, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0399, loss_cls: 0.1608, acc: 93.9114, loss_bbox: 0.2103, loss_mask: 0.2152, loss: 0.6440 2023-11-13 22:56:41,727 - mmdet - INFO - Epoch [7][7100/7330] lr: 1.000e-04, eta: 4:33:59, time: 0.448, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0353, loss_cls: 0.1520, acc: 94.2083, loss_bbox: 0.1991, loss_mask: 0.2085, loss: 0.6111 2023-11-13 22:57:04,211 - mmdet - INFO - Epoch [7][7150/7330] lr: 1.000e-04, eta: 4:33:37, time: 0.450, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0377, loss_cls: 0.1634, acc: 93.8804, loss_bbox: 0.2106, loss_mask: 0.2172, loss: 0.6458 2023-11-13 22:57:26,321 - mmdet - INFO - Epoch [7][7200/7330] lr: 1.000e-04, eta: 4:33:14, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0374, loss_cls: 0.1572, acc: 94.1169, loss_bbox: 0.2057, loss_mask: 0.2122, loss: 0.6295 2023-11-13 22:57:48,755 - mmdet - INFO - Epoch [7][7250/7330] lr: 1.000e-04, eta: 4:32:52, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0178, loss_rpn_bbox: 0.0383, loss_cls: 0.1611, acc: 93.8872, loss_bbox: 0.2103, loss_mask: 0.2138, loss: 0.6413 2023-11-13 22:58:10,916 - mmdet - INFO - Epoch [7][7300/7330] lr: 1.000e-04, eta: 4:32:30, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0373, loss_cls: 0.1576, acc: 94.0620, loss_bbox: 0.2085, loss_mask: 0.2140, loss: 0.6351 2023-11-13 22:58:24,653 - mmdet - INFO - Saving checkpoint at 7 epochs 2023-11-13 22:59:15,356 - mmdet - INFO - Evaluating bbox... 2023-11-13 22:59:47,212 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.477 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.700 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.527 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.308 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.518 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.620 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.606 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.441 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.649 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.755 2023-11-13 22:59:47,215 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.578 | bicycle | 0.380 | car | 0.483 | | motorcycle | 0.478 | airplane | 0.728 | bus | 0.713 | | train | 0.691 | truck | 0.432 | boat | 0.333 | | traffic light | 0.316 | fire hydrant | 0.713 | stop sign | 0.650 | | parking meter | 0.509 | bench | 0.299 | bird | 0.414 | | cat | 0.724 | dog | 0.653 | horse | 0.644 | | sheep | 0.587 | cow | 0.624 | elephant | 0.708 | | bear | 0.723 | zebra | 0.683 | giraffe | 0.681 | | backpack | 0.222 | umbrella | 0.450 | handbag | 0.239 | | tie | 0.385 | suitcase | 0.477 | frisbee | 0.707 | | skis | 0.296 | snowboard | 0.454 | sports ball | 0.476 | | kite | 0.453 | baseball bat | 0.418 | baseball glove | 0.439 | | skateboard | 0.559 | surfboard | 0.465 | tennis racket | 0.550 | | bottle | 0.449 | wine glass | 0.423 | cup | 0.503 | | fork | 0.456 | knife | 0.297 | spoon | 0.269 | | bowl | 0.472 | banana | 0.285 | apple | 0.275 | | sandwich | 0.438 | orange | 0.331 | broccoli | 0.261 | | carrot | 0.258 | hot dog | 0.428 | pizza | 0.543 | | donut | 0.546 | cake | 0.430 | chair | 0.357 | | couch | 0.470 | potted plant | 0.349 | bed | 0.486 | | dining table | 0.305 | toilet | 0.671 | tv | 0.630 | | laptop | 0.677 | mouse | 0.663 | remote | 0.413 | | keyboard | 0.561 | cell phone | 0.424 | microwave | 0.562 | | oven | 0.405 | toaster | 0.509 | sink | 0.432 | | refrigerator | 0.637 | book | 0.180 | clock | 0.531 | | vase | 0.428 | scissors | 0.444 | teddy bear | 0.528 | | hair drier | 0.207 | toothbrush | 0.323 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 22:59:47,215 - mmdet - INFO - Evaluating segm... 2023-11-13 23:00:22,483 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.431 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.671 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.466 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.231 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.467 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.623 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.376 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 ] = 0.715 2023-11-13 23:00:22,485 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.506 | bicycle | 0.236 | car | 0.441 | | motorcycle | 0.384 | airplane | 0.561 | bus | 0.694 | | train | 0.670 | truck | 0.423 | boat | 0.302 | | traffic light | 0.302 | fire hydrant | 0.691 | stop sign | 0.657 | | parking meter | 0.530 | bench | 0.227 | bird | 0.347 | | cat | 0.724 | dog | 0.617 | horse | 0.472 | | sheep | 0.507 | cow | 0.535 | elephant | 0.644 | | bear | 0.709 | zebra | 0.583 | giraffe | 0.527 | | backpack | 0.229 | umbrella | 0.517 | handbag | 0.241 | | tie | 0.361 | suitcase | 0.495 | frisbee | 0.670 | | skis | 0.053 | snowboard | 0.299 | sports ball | 0.485 | | kite | 0.334 | baseball bat | 0.330 | baseball glove | 0.459 | | skateboard | 0.368 | surfboard | 0.384 | tennis racket | 0.573 | | bottle | 0.444 | wine glass | 0.384 | cup | 0.500 | | fork | 0.223 | knife | 0.194 | spoon | 0.199 | | bowl | 0.444 | banana | 0.232 | apple | 0.264 | | sandwich | 0.475 | orange | 0.337 | broccoli | 0.237 | | carrot | 0.223 | hot dog | 0.351 | pizza | 0.531 | | donut | 0.550 | cake | 0.448 | chair | 0.260 | | couch | 0.394 | potted plant | 0.297 | bed | 0.388 | | dining table | 0.181 | toilet | 0.629 | tv | 0.658 | | laptop | 0.672 | mouse | 0.641 | remote | 0.368 | | keyboard | 0.542 | cell phone | 0.407 | microwave | 0.606 | | oven | 0.376 | toaster | 0.550 | sink | 0.401 | | refrigerator | 0.662 | book | 0.135 | clock | 0.542 | | vase | 0.418 | scissors | 0.331 | teddy bear | 0.499 | | hair drier | 0.202 | toothbrush | 0.231 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:00:22,914 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_6.pth was removed 2023-11-13 23:00:26,523 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_7.pth. 2023-11-13 23:00:26,524 - mmdet - INFO - Best bbox_mAP is 0.4774 at 7 epoch. 2023-11-13 23:00:26,524 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 23:00:26,524 - mmdet - INFO - Epoch(val) [7][625] bbox_mAP: 0.4774, bbox_mAP_50: 0.6996, bbox_mAP_75: 0.5274, bbox_mAP_s: 0.3080, bbox_mAP_m: 0.5185, bbox_mAP_l: 0.6202, bbox_mAP_copypaste: 0.4774 0.6996 0.5274 0.3080 0.5185 0.6202, segm_mAP: 0.4314, segm_mAP_50: 0.6711, segm_mAP_75: 0.4657, segm_mAP_s: 0.2308, segm_mAP_m: 0.4674, segm_mAP_l: 0.6232, segm_mAP_copypaste: 0.4314 0.6711 0.4657 0.2308 0.4674 0.6232 2023-11-13 23:00:52,183 - mmdet - INFO - Epoch [8][50/7330] lr: 1.000e-04, eta: 4:31:47, time: 0.513, data_time: 0.085, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0363, loss_cls: 0.1495, acc: 94.3115, loss_bbox: 0.2013, loss_mask: 0.2073, loss: 0.6099 2023-11-13 23:01:14,864 - mmdet - INFO - Epoch [8][100/7330] lr: 1.000e-04, eta: 4:31:25, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0360, loss_cls: 0.1487, acc: 94.3071, loss_bbox: 0.2005, loss_mask: 0.2087, loss: 0.6079 2023-11-13 23:01:37,317 - mmdet - INFO - Epoch [8][150/7330] lr: 1.000e-04, eta: 4:31:03, time: 0.449, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0381, loss_cls: 0.1499, acc: 94.2605, loss_bbox: 0.2012, loss_mask: 0.2106, loss: 0.6144 2023-11-13 23:01:59,827 - mmdet - INFO - Epoch [8][200/7330] lr: 1.000e-04, eta: 4:30:41, time: 0.450, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0359, loss_cls: 0.1507, acc: 94.2966, loss_bbox: 0.2001, loss_mask: 0.2062, loss: 0.6094 2023-11-13 23:02:21,996 - mmdet - INFO - Epoch [8][250/7330] lr: 1.000e-04, eta: 4:30:18, time: 0.443, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0349, loss_cls: 0.1459, acc: 94.4641, loss_bbox: 0.2000, loss_mask: 0.2052, loss: 0.6004 2023-11-13 23:02:44,444 - mmdet - INFO - Epoch [8][300/7330] lr: 1.000e-04, eta: 4:29:56, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0374, loss_cls: 0.1517, acc: 94.3293, loss_bbox: 0.2038, loss_mask: 0.2153, loss: 0.6232 2023-11-13 23:03:06,612 - mmdet - INFO - Epoch [8][350/7330] lr: 1.000e-04, eta: 4:29:34, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0362, loss_cls: 0.1475, acc: 94.4531, loss_bbox: 0.2003, loss_mask: 0.2042, loss: 0.6041 2023-11-13 23:03:28,760 - mmdet - INFO - Epoch [8][400/7330] lr: 1.000e-04, eta: 4:29:12, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0361, loss_cls: 0.1484, acc: 94.4370, loss_bbox: 0.1944, loss_mask: 0.2027, loss: 0.5960 2023-11-13 23:03:51,367 - mmdet - INFO - Epoch [8][450/7330] lr: 1.000e-04, eta: 4:28:50, time: 0.452, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0363, loss_cls: 0.1538, acc: 94.1021, loss_bbox: 0.2055, loss_mask: 0.2064, loss: 0.6176 2023-11-13 23:04:13,894 - mmdet - INFO - Epoch [8][500/7330] lr: 1.000e-04, eta: 4:28:27, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0375, loss_cls: 0.1544, acc: 94.1355, loss_bbox: 0.2055, loss_mask: 0.2102, loss: 0.6241 2023-11-13 23:04:35,755 - mmdet - INFO - Epoch [8][550/7330] lr: 1.000e-04, eta: 4:28:05, time: 0.437, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0337, loss_cls: 0.1453, acc: 94.4685, loss_bbox: 0.1937, loss_mask: 0.2062, loss: 0.5944 2023-11-13 23:04:57,860 - mmdet - INFO - Epoch [8][600/7330] lr: 1.000e-04, eta: 4:27:42, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0400, loss_cls: 0.1565, acc: 94.0623, loss_bbox: 0.2068, loss_mask: 0.2081, loss: 0.6288 2023-11-13 23:05:19,952 - mmdet - INFO - Epoch [8][650/7330] lr: 1.000e-04, eta: 4:27:20, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0353, loss_cls: 0.1512, acc: 94.3247, loss_bbox: 0.2030, loss_mask: 0.2123, loss: 0.6168 2023-11-13 23:05:42,096 - mmdet - INFO - Epoch [8][700/7330] lr: 1.000e-04, eta: 4:26:58, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0372, loss_cls: 0.1512, acc: 94.2896, loss_bbox: 0.1969, loss_mask: 0.2068, loss: 0.6082 2023-11-13 23:06:03,957 - mmdet - INFO - Epoch [8][750/7330] lr: 1.000e-04, eta: 4:26:35, time: 0.437, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0154, loss_rpn_bbox: 0.0363, loss_cls: 0.1486, acc: 94.3105, loss_bbox: 0.2016, loss_mask: 0.2126, loss: 0.6146 2023-11-13 23:06:26,052 - mmdet - INFO - Epoch [8][800/7330] lr: 1.000e-04, eta: 4:26:13, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0370, loss_cls: 0.1536, acc: 94.1965, loss_bbox: 0.2063, loss_mask: 0.2104, loss: 0.6234 2023-11-13 23:06:47,961 - mmdet - INFO - Epoch [8][850/7330] lr: 1.000e-04, eta: 4:25:50, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0357, loss_cls: 0.1458, acc: 94.4810, loss_bbox: 0.1972, loss_mask: 0.2055, loss: 0.5989 2023-11-13 23:07:09,768 - mmdet - INFO - Epoch [8][900/7330] lr: 1.000e-04, eta: 4:25:28, time: 0.436, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0349, loss_cls: 0.1432, acc: 94.5674, loss_bbox: 0.1960, loss_mask: 0.2080, loss: 0.5962 2023-11-13 23:07:32,038 - mmdet - INFO - Epoch [8][950/7330] lr: 1.000e-04, eta: 4:25:05, time: 0.445, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0393, loss_cls: 0.1596, acc: 93.8899, loss_bbox: 0.2131, loss_mask: 0.2132, loss: 0.6416 2023-11-13 23:07:54,653 - mmdet - INFO - Epoch [8][1000/7330] lr: 1.000e-04, eta: 4:24:43, time: 0.452, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0375, loss_cls: 0.1466, acc: 94.4377, loss_bbox: 0.2012, loss_mask: 0.2058, loss: 0.6079 2023-11-13 23:08:16,851 - mmdet - INFO - Epoch [8][1050/7330] lr: 1.000e-04, eta: 4:24:21, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0368, loss_cls: 0.1530, acc: 94.1401, loss_bbox: 0.2025, loss_mask: 0.2119, loss: 0.6188 2023-11-13 23:08:39,074 - mmdet - INFO - Epoch [8][1100/7330] lr: 1.000e-04, eta: 4:23:59, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0375, loss_cls: 0.1546, acc: 94.0972, loss_bbox: 0.2050, loss_mask: 0.2122, loss: 0.6258 2023-11-13 23:09:01,529 - mmdet - INFO - Epoch [8][1150/7330] lr: 1.000e-04, eta: 4:23:36, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0363, loss_cls: 0.1479, acc: 94.3757, loss_bbox: 0.1992, loss_mask: 0.2121, loss: 0.6117 2023-11-13 23:09:23,990 - mmdet - INFO - Epoch [8][1200/7330] lr: 1.000e-04, eta: 4:23:14, time: 0.449, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0381, loss_cls: 0.1567, acc: 94.1311, loss_bbox: 0.2037, loss_mask: 0.2076, loss: 0.6223 2023-11-13 23:09:46,475 - mmdet - INFO - Epoch [8][1250/7330] lr: 1.000e-04, eta: 4:22:52, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0397, loss_cls: 0.1559, acc: 94.1011, loss_bbox: 0.2096, loss_mask: 0.2143, loss: 0.6369 2023-11-13 23:10:08,466 - mmdet - INFO - Epoch [8][1300/7330] lr: 1.000e-04, eta: 4:22:30, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0356, loss_cls: 0.1474, acc: 94.4768, loss_bbox: 0.2033, loss_mask: 0.2079, loss: 0.6093 2023-11-13 23:10:31,028 - mmdet - INFO - Epoch [8][1350/7330] lr: 1.000e-04, eta: 4:22:08, time: 0.451, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0175, loss_rpn_bbox: 0.0394, loss_cls: 0.1590, acc: 93.9426, loss_bbox: 0.2118, loss_mask: 0.2162, loss: 0.6439 2023-11-13 23:10:53,086 - mmdet - INFO - Epoch [8][1400/7330] lr: 1.000e-04, eta: 4:21:45, time: 0.441, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0357, loss_cls: 0.1527, acc: 94.2224, loss_bbox: 0.2061, loss_mask: 0.2136, loss: 0.6239 2023-11-13 23:11:15,476 - mmdet - INFO - Epoch [8][1450/7330] lr: 1.000e-04, eta: 4:21:23, time: 0.448, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0365, loss_cls: 0.1489, acc: 94.3022, loss_bbox: 0.1969, loss_mask: 0.2050, loss: 0.6016 2023-11-13 23:11:37,830 - mmdet - INFO - Epoch [8][1500/7330] lr: 1.000e-04, eta: 4:21:01, time: 0.447, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0382, loss_cls: 0.1566, acc: 93.8796, loss_bbox: 0.2114, loss_mask: 0.2165, loss: 0.6390 2023-11-13 23:11:59,804 - mmdet - INFO - Epoch [8][1550/7330] lr: 1.000e-04, eta: 4:20:38, time: 0.440, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0356, loss_cls: 0.1481, acc: 94.4097, loss_bbox: 0.1966, loss_mask: 0.2073, loss: 0.6022 2023-11-13 23:12:21,432 - mmdet - INFO - Epoch [8][1600/7330] lr: 1.000e-04, eta: 4:20:16, time: 0.433, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0339, loss_cls: 0.1459, acc: 94.4673, loss_bbox: 0.1938, loss_mask: 0.2067, loss: 0.5929 2023-11-13 23:12:43,561 - mmdet - INFO - Epoch [8][1650/7330] lr: 1.000e-04, eta: 4:19:53, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0358, loss_cls: 0.1487, acc: 94.3843, loss_bbox: 0.1952, loss_mask: 0.2030, loss: 0.5975 2023-11-13 23:13:05,789 - mmdet - INFO - Epoch [8][1700/7330] lr: 1.000e-04, eta: 4:19:31, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0351, loss_cls: 0.1454, acc: 94.5444, loss_bbox: 0.1941, loss_mask: 0.2066, loss: 0.5961 2023-11-13 23:13:28,124 - mmdet - INFO - Epoch [8][1750/7330] lr: 1.000e-04, eta: 4:19:09, time: 0.447, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0359, loss_cls: 0.1508, acc: 94.3110, loss_bbox: 0.2014, loss_mask: 0.2072, loss: 0.6115 2023-11-13 23:13:50,275 - mmdet - INFO - Epoch [8][1800/7330] lr: 1.000e-04, eta: 4:18:46, time: 0.443, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0354, loss_cls: 0.1510, acc: 94.2751, loss_bbox: 0.2015, loss_mask: 0.2125, loss: 0.6144 2023-11-13 23:14:12,418 - mmdet - INFO - Epoch [8][1850/7330] lr: 1.000e-04, eta: 4:18:24, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0378, loss_cls: 0.1500, acc: 94.2827, loss_bbox: 0.2017, loss_mask: 0.2144, loss: 0.6187 2023-11-13 23:14:34,472 - mmdet - INFO - Epoch [8][1900/7330] lr: 1.000e-04, eta: 4:18:01, time: 0.441, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0342, loss_cls: 0.1442, acc: 94.5139, loss_bbox: 0.1882, loss_mask: 0.2072, loss: 0.5876 2023-11-13 23:14:56,718 - mmdet - INFO - Epoch [8][1950/7330] lr: 1.000e-04, eta: 4:17:39, time: 0.445, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0384, loss_cls: 0.1540, acc: 94.2170, loss_bbox: 0.2062, loss_mask: 0.2122, loss: 0.6273 2023-11-13 23:15:18,566 - mmdet - INFO - Epoch [8][2000/7330] lr: 1.000e-04, eta: 4:17:17, time: 0.437, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0359, loss_cls: 0.1521, acc: 94.2224, loss_bbox: 0.2003, loss_mask: 0.2147, loss: 0.6176 2023-11-13 23:15:40,408 - mmdet - INFO - Epoch [8][2050/7330] lr: 1.000e-04, eta: 4:16:54, time: 0.437, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0338, loss_cls: 0.1424, acc: 94.6228, loss_bbox: 0.1894, loss_mask: 0.2049, loss: 0.5851 2023-11-13 23:16:02,371 - mmdet - INFO - Epoch [8][2100/7330] lr: 1.000e-04, eta: 4:16:32, time: 0.439, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0369, loss_cls: 0.1454, acc: 94.5259, loss_bbox: 0.1940, loss_mask: 0.2087, loss: 0.6011 2023-11-13 23:16:24,467 - mmdet - INFO - Epoch [8][2150/7330] lr: 1.000e-04, eta: 4:16:09, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0336, loss_cls: 0.1407, acc: 94.6624, loss_bbox: 0.1922, loss_mask: 0.2060, loss: 0.5874 2023-11-13 23:16:46,568 - mmdet - INFO - Epoch [8][2200/7330] lr: 1.000e-04, eta: 4:15:47, time: 0.442, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0380, loss_cls: 0.1597, acc: 93.8850, loss_bbox: 0.2074, loss_mask: 0.2141, loss: 0.6360 2023-11-13 23:17:08,665 - mmdet - INFO - Epoch [8][2250/7330] lr: 1.000e-04, eta: 4:15:24, time: 0.442, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0372, loss_cls: 0.1453, acc: 94.4534, loss_bbox: 0.1983, loss_mask: 0.2093, loss: 0.6047 2023-11-13 23:17:30,615 - mmdet - INFO - Epoch [8][2300/7330] lr: 1.000e-04, eta: 4:15:02, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0341, loss_cls: 0.1452, acc: 94.4607, loss_bbox: 0.1957, loss_mask: 0.2073, loss: 0.5969 2023-11-13 23:17:52,494 - mmdet - INFO - Epoch [8][2350/7330] lr: 1.000e-04, eta: 4:14:39, time: 0.438, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0352, loss_cls: 0.1409, acc: 94.7053, loss_bbox: 0.1915, loss_mask: 0.2054, loss: 0.5870 2023-11-13 23:18:14,687 - mmdet - INFO - Epoch [8][2400/7330] lr: 1.000e-04, eta: 4:14:17, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0350, loss_cls: 0.1486, acc: 94.4111, loss_bbox: 0.1983, loss_mask: 0.2093, loss: 0.6058 2023-11-13 23:18:36,874 - mmdet - INFO - Epoch [8][2450/7330] lr: 1.000e-04, eta: 4:13:55, time: 0.444, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0372, loss_cls: 0.1498, acc: 94.2896, loss_bbox: 0.2020, loss_mask: 0.2102, loss: 0.6155 2023-11-13 23:18:58,812 - mmdet - INFO - Epoch [8][2500/7330] lr: 1.000e-04, eta: 4:13:32, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0353, loss_cls: 0.1450, acc: 94.5940, loss_bbox: 0.2001, loss_mask: 0.2089, loss: 0.6050 2023-11-13 23:19:20,753 - mmdet - INFO - Epoch [8][2550/7330] lr: 1.000e-04, eta: 4:13:10, time: 0.439, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0354, loss_cls: 0.1531, acc: 94.2488, loss_bbox: 0.2051, loss_mask: 0.2085, loss: 0.6178 2023-11-13 23:19:42,982 - mmdet - INFO - Epoch [8][2600/7330] lr: 1.000e-04, eta: 4:12:47, time: 0.445, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0384, loss_cls: 0.1579, acc: 94.0002, loss_bbox: 0.2082, loss_mask: 0.2119, loss: 0.6327 2023-11-13 23:20:05,303 - mmdet - INFO - Epoch [8][2650/7330] lr: 1.000e-04, eta: 4:12:25, time: 0.446, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0367, loss_cls: 0.1531, acc: 94.1921, loss_bbox: 0.2038, loss_mask: 0.2054, loss: 0.6150 2023-11-13 23:20:26,826 - mmdet - INFO - Epoch [8][2700/7330] lr: 1.000e-04, eta: 4:12:03, time: 0.430, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0329, loss_cls: 0.1388, acc: 94.7461, loss_bbox: 0.1852, loss_mask: 0.1991, loss: 0.5704 2023-11-13 23:20:48,817 - mmdet - INFO - Epoch [8][2750/7330] lr: 1.000e-04, eta: 4:11:40, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0345, loss_cls: 0.1493, acc: 94.2834, loss_bbox: 0.2021, loss_mask: 0.2096, loss: 0.6103 2023-11-13 23:21:10,939 - mmdet - INFO - Epoch [8][2800/7330] lr: 1.000e-04, eta: 4:11:18, time: 0.442, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0173, loss_rpn_bbox: 0.0377, loss_cls: 0.1520, acc: 94.2493, loss_bbox: 0.1998, loss_mask: 0.2166, loss: 0.6234 2023-11-13 23:21:33,015 - mmdet - INFO - Epoch [8][2850/7330] lr: 1.000e-04, eta: 4:10:55, time: 0.441, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0365, loss_cls: 0.1526, acc: 94.2332, loss_bbox: 0.2021, loss_mask: 0.2090, loss: 0.6160 2023-11-13 23:21:55,308 - mmdet - INFO - Epoch [8][2900/7330] lr: 1.000e-04, eta: 4:10:33, time: 0.446, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0375, loss_cls: 0.1552, acc: 94.0659, loss_bbox: 0.2074, loss_mask: 0.2131, loss: 0.6303 2023-11-13 23:22:17,383 - mmdet - INFO - Epoch [8][2950/7330] lr: 1.000e-04, eta: 4:10:11, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0363, loss_cls: 0.1514, acc: 94.1387, loss_bbox: 0.2036, loss_mask: 0.2076, loss: 0.6135 2023-11-13 23:22:39,485 - mmdet - INFO - Epoch [8][3000/7330] lr: 1.000e-04, eta: 4:09:48, time: 0.442, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0346, loss_cls: 0.1449, acc: 94.4673, loss_bbox: 0.1935, loss_mask: 0.2077, loss: 0.5969 2023-11-13 23:23:01,288 - mmdet - INFO - Epoch [8][3050/7330] lr: 1.000e-04, eta: 4:09:26, time: 0.436, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0355, loss_cls: 0.1475, acc: 94.4031, loss_bbox: 0.1980, loss_mask: 0.2081, loss: 0.6038 2023-11-13 23:23:23,238 - mmdet - INFO - Epoch [8][3100/7330] lr: 1.000e-04, eta: 4:09:03, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0365, loss_cls: 0.1501, acc: 94.3137, loss_bbox: 0.2031, loss_mask: 0.2118, loss: 0.6174 2023-11-13 23:23:45,150 - mmdet - INFO - Epoch [8][3150/7330] lr: 1.000e-04, eta: 4:08:41, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0344, loss_cls: 0.1452, acc: 94.6338, loss_bbox: 0.1954, loss_mask: 0.2036, loss: 0.5932 2023-11-13 23:24:07,339 - mmdet - INFO - Epoch [8][3200/7330] lr: 1.000e-04, eta: 4:08:18, time: 0.444, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0381, loss_cls: 0.1557, acc: 94.1038, loss_bbox: 0.2031, loss_mask: 0.2083, loss: 0.6210 2023-11-13 23:24:29,269 - mmdet - INFO - Epoch [8][3250/7330] lr: 1.000e-04, eta: 4:07:56, time: 0.439, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0345, loss_cls: 0.1470, acc: 94.3594, loss_bbox: 0.2003, loss_mask: 0.2087, loss: 0.6051 2023-11-13 23:24:51,659 - mmdet - INFO - Epoch [8][3300/7330] lr: 1.000e-04, eta: 4:07:34, time: 0.448, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0371, loss_cls: 0.1591, acc: 93.9692, loss_bbox: 0.2112, loss_mask: 0.2143, loss: 0.6385 2023-11-13 23:25:14,073 - mmdet - INFO - Epoch [8][3350/7330] lr: 1.000e-04, eta: 4:07:12, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0177, loss_rpn_bbox: 0.0371, loss_cls: 0.1539, acc: 94.2834, loss_bbox: 0.2011, loss_mask: 0.2075, loss: 0.6173 2023-11-13 23:25:36,060 - mmdet - INFO - Epoch [8][3400/7330] lr: 1.000e-04, eta: 4:06:49, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0357, loss_cls: 0.1464, acc: 94.4802, loss_bbox: 0.1976, loss_mask: 0.2096, loss: 0.6055 2023-11-13 23:25:57,734 - mmdet - INFO - Epoch [8][3450/7330] lr: 1.000e-04, eta: 4:06:26, time: 0.433, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0334, loss_cls: 0.1436, acc: 94.6235, loss_bbox: 0.1924, loss_mask: 0.2085, loss: 0.5922 2023-11-13 23:26:19,702 - mmdet - INFO - Epoch [8][3500/7330] lr: 1.000e-04, eta: 4:06:04, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0346, loss_cls: 0.1466, acc: 94.4810, loss_bbox: 0.1973, loss_mask: 0.2076, loss: 0.6012 2023-11-13 23:26:41,875 - mmdet - INFO - Epoch [8][3550/7330] lr: 1.000e-04, eta: 4:05:42, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0368, loss_cls: 0.1570, acc: 94.1228, loss_bbox: 0.2094, loss_mask: 0.2166, loss: 0.6347 2023-11-13 23:27:03,786 - mmdet - INFO - Epoch [8][3600/7330] lr: 1.000e-04, eta: 4:05:19, time: 0.438, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0349, loss_cls: 0.1420, acc: 94.6692, loss_bbox: 0.1885, loss_mask: 0.2032, loss: 0.5830 2023-11-13 23:27:25,641 - mmdet - INFO - Epoch [8][3650/7330] lr: 1.000e-04, eta: 4:04:57, time: 0.437, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0367, loss_cls: 0.1533, acc: 94.1936, loss_bbox: 0.2012, loss_mask: 0.2112, loss: 0.6191 2023-11-13 23:27:47,595 - mmdet - INFO - Epoch [8][3700/7330] lr: 1.000e-04, eta: 4:04:34, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0358, loss_cls: 0.1483, acc: 94.4077, loss_bbox: 0.1952, loss_mask: 0.2136, loss: 0.6080 2023-11-13 23:28:09,632 - mmdet - INFO - Epoch [8][3750/7330] lr: 1.000e-04, eta: 4:04:12, time: 0.441, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0353, loss_cls: 0.1482, acc: 94.3325, loss_bbox: 0.1991, loss_mask: 0.2091, loss: 0.6064 2023-11-13 23:28:31,720 - mmdet - INFO - Epoch [8][3800/7330] lr: 1.000e-04, eta: 4:03:49, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0372, loss_cls: 0.1532, acc: 94.1787, loss_bbox: 0.2024, loss_mask: 0.2116, loss: 0.6202 2023-11-13 23:28:53,619 - mmdet - INFO - Epoch [8][3850/7330] lr: 1.000e-04, eta: 4:03:27, time: 0.438, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0389, loss_cls: 0.1502, acc: 94.2671, loss_bbox: 0.1995, loss_mask: 0.2123, loss: 0.6167 2023-11-13 23:29:15,865 - mmdet - INFO - Epoch [8][3900/7330] lr: 1.000e-04, eta: 4:03:05, time: 0.445, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0163, loss_rpn_bbox: 0.0366, loss_cls: 0.1521, acc: 94.2695, loss_bbox: 0.2022, loss_mask: 0.2101, loss: 0.6173 2023-11-13 23:29:37,947 - mmdet - INFO - Epoch [8][3950/7330] lr: 1.000e-04, eta: 4:02:42, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0381, loss_cls: 0.1501, acc: 94.3333, loss_bbox: 0.1981, loss_mask: 0.2127, loss: 0.6137 2023-11-13 23:30:00,202 - mmdet - INFO - Epoch [8][4000/7330] lr: 1.000e-04, eta: 4:02:20, time: 0.445, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0333, loss_cls: 0.1457, acc: 94.5510, loss_bbox: 0.1916, loss_mask: 0.2020, loss: 0.5868 2023-11-13 23:30:22,661 - mmdet - INFO - Epoch [8][4050/7330] lr: 1.000e-04, eta: 4:01:58, time: 0.449, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0373, loss_cls: 0.1604, acc: 93.9636, loss_bbox: 0.2103, loss_mask: 0.2138, loss: 0.6376 2023-11-13 23:30:45,210 - mmdet - INFO - Epoch [8][4100/7330] lr: 1.000e-04, eta: 4:01:36, time: 0.451, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0193, loss_rpn_bbox: 0.0390, loss_cls: 0.1541, acc: 94.2678, loss_bbox: 0.2067, loss_mask: 0.2112, loss: 0.6302 2023-11-13 23:31:07,132 - mmdet - INFO - Epoch [8][4150/7330] lr: 1.000e-04, eta: 4:01:13, time: 0.438, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0153, loss_rpn_bbox: 0.0348, loss_cls: 0.1503, acc: 94.3540, loss_bbox: 0.2017, loss_mask: 0.2092, loss: 0.6114 2023-11-13 23:31:29,150 - mmdet - INFO - Epoch [8][4200/7330] lr: 1.000e-04, eta: 4:00:51, time: 0.440, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0330, loss_cls: 0.1411, acc: 94.6660, loss_bbox: 0.1887, loss_mask: 0.1999, loss: 0.5771 2023-11-13 23:31:51,374 - mmdet - INFO - Epoch [8][4250/7330] lr: 1.000e-04, eta: 4:00:29, time: 0.445, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0348, loss_cls: 0.1501, acc: 94.3386, loss_bbox: 0.1979, loss_mask: 0.2081, loss: 0.6069 2023-11-13 23:32:13,484 - mmdet - INFO - Epoch [8][4300/7330] lr: 1.000e-04, eta: 4:00:06, time: 0.442, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0339, loss_cls: 0.1439, acc: 94.4668, loss_bbox: 0.1951, loss_mask: 0.2131, loss: 0.6015 2023-11-13 23:32:35,326 - mmdet - INFO - Epoch [8][4350/7330] lr: 1.000e-04, eta: 3:59:44, time: 0.437, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0368, loss_cls: 0.1511, acc: 94.3694, loss_bbox: 0.1999, loss_mask: 0.2039, loss: 0.6066 2023-11-13 23:32:57,129 - mmdet - INFO - Epoch [8][4400/7330] lr: 1.000e-04, eta: 3:59:21, time: 0.436, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0377, loss_cls: 0.1572, acc: 94.0364, loss_bbox: 0.2069, loss_mask: 0.2105, loss: 0.6291 2023-11-13 23:33:19,266 - mmdet - INFO - Epoch [8][4450/7330] lr: 1.000e-04, eta: 3:58:59, time: 0.443, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0356, loss_cls: 0.1541, acc: 94.2334, loss_bbox: 0.2005, loss_mask: 0.2071, loss: 0.6132 2023-11-13 23:33:41,405 - mmdet - INFO - Epoch [8][4500/7330] lr: 1.000e-04, eta: 3:58:37, time: 0.443, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0352, loss_cls: 0.1493, acc: 94.3289, loss_bbox: 0.1961, loss_mask: 0.2090, loss: 0.6056 2023-11-13 23:34:03,582 - mmdet - INFO - Epoch [8][4550/7330] lr: 1.000e-04, eta: 3:58:14, time: 0.444, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0365, loss_cls: 0.1485, acc: 94.3269, loss_bbox: 0.1981, loss_mask: 0.2022, loss: 0.5997 2023-11-13 23:34:25,545 - mmdet - INFO - Epoch [8][4600/7330] lr: 1.000e-04, eta: 3:57:52, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0168, loss_rpn_bbox: 0.0360, loss_cls: 0.1512, acc: 94.3103, loss_bbox: 0.2010, loss_mask: 0.2090, loss: 0.6140 2023-11-13 23:34:47,556 - mmdet - INFO - Epoch [8][4650/7330] lr: 1.000e-04, eta: 3:57:29, time: 0.440, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0167, loss_rpn_bbox: 0.0367, loss_cls: 0.1479, acc: 94.4404, loss_bbox: 0.1957, loss_mask: 0.2036, loss: 0.6007 2023-11-13 23:35:09,653 - mmdet - INFO - Epoch [8][4700/7330] lr: 1.000e-04, eta: 3:57:07, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0372, loss_cls: 0.1564, acc: 94.0703, loss_bbox: 0.2064, loss_mask: 0.2060, loss: 0.6232 2023-11-13 23:35:31,605 - mmdet - INFO - Epoch [8][4750/7330] lr: 1.000e-04, eta: 3:56:45, time: 0.439, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0364, loss_cls: 0.1532, acc: 94.2439, loss_bbox: 0.1982, loss_mask: 0.2096, loss: 0.6126 2023-11-13 23:35:53,258 - mmdet - INFO - Epoch [8][4800/7330] lr: 1.000e-04, eta: 3:56:22, time: 0.433, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0343, loss_cls: 0.1432, acc: 94.5828, loss_bbox: 0.1906, loss_mask: 0.2075, loss: 0.5900 2023-11-13 23:36:15,194 - mmdet - INFO - Epoch [8][4850/7330] lr: 1.000e-04, eta: 3:55:59, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0324, loss_cls: 0.1415, acc: 94.6750, loss_bbox: 0.1857, loss_mask: 0.2023, loss: 0.5766 2023-11-13 23:36:37,484 - mmdet - INFO - Epoch [8][4900/7330] lr: 1.000e-04, eta: 3:55:37, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0363, loss_cls: 0.1476, acc: 94.4890, loss_bbox: 0.1968, loss_mask: 0.2080, loss: 0.6032 2023-11-13 23:36:59,272 - mmdet - INFO - Epoch [8][4950/7330] lr: 1.000e-04, eta: 3:55:15, time: 0.436, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0363, loss_cls: 0.1502, acc: 94.3176, loss_bbox: 0.2003, loss_mask: 0.2116, loss: 0.6133 2023-11-13 23:37:21,484 - mmdet - INFO - Epoch [8][5000/7330] lr: 1.000e-04, eta: 3:54:52, time: 0.444, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0352, loss_cls: 0.1510, acc: 94.2979, loss_bbox: 0.2008, loss_mask: 0.2120, loss: 0.6131 2023-11-13 23:37:43,654 - mmdet - INFO - Epoch [8][5050/7330] lr: 1.000e-04, eta: 3:54:30, time: 0.443, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0368, loss_cls: 0.1513, acc: 94.2920, loss_bbox: 0.1966, loss_mask: 0.2092, loss: 0.6100 2023-11-13 23:38:05,582 - mmdet - INFO - Epoch [8][5100/7330] lr: 1.000e-04, eta: 3:54:08, time: 0.438, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0368, loss_cls: 0.1561, acc: 94.0803, loss_bbox: 0.2047, loss_mask: 0.2142, loss: 0.6278 2023-11-13 23:38:27,395 - mmdet - INFO - Epoch [8][5150/7330] lr: 1.000e-04, eta: 3:53:45, time: 0.436, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0357, loss_cls: 0.1495, acc: 94.3950, loss_bbox: 0.1976, loss_mask: 0.2117, loss: 0.6100 2023-11-13 23:38:49,347 - mmdet - INFO - Epoch [8][5200/7330] lr: 1.000e-04, eta: 3:53:23, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0348, loss_cls: 0.1467, acc: 94.4451, loss_bbox: 0.1949, loss_mask: 0.2110, loss: 0.6012 2023-11-13 23:39:11,452 - mmdet - INFO - Epoch [8][5250/7330] lr: 1.000e-04, eta: 3:53:00, time: 0.442, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0172, loss_rpn_bbox: 0.0385, loss_cls: 0.1590, acc: 94.0393, loss_bbox: 0.2085, loss_mask: 0.2138, loss: 0.6371 2023-11-13 23:39:33,242 - mmdet - INFO - Epoch [8][5300/7330] lr: 1.000e-04, eta: 3:52:38, time: 0.436, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0353, loss_cls: 0.1494, acc: 94.3752, loss_bbox: 0.1936, loss_mask: 0.2109, loss: 0.6040 2023-11-13 23:39:55,451 - mmdet - INFO - Epoch [8][5350/7330] lr: 1.000e-04, eta: 3:52:16, time: 0.444, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0380, loss_cls: 0.1518, acc: 94.2373, loss_bbox: 0.2032, loss_mask: 0.2113, loss: 0.6206 2023-11-13 23:40:17,310 - mmdet - INFO - Epoch [8][5400/7330] lr: 1.000e-04, eta: 3:51:53, time: 0.437, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0338, loss_cls: 0.1498, acc: 94.3149, loss_bbox: 0.1995, loss_mask: 0.2066, loss: 0.6066 2023-11-13 23:40:39,389 - mmdet - INFO - Epoch [8][5450/7330] lr: 1.000e-04, eta: 3:51:31, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0376, loss_cls: 0.1566, acc: 94.0505, loss_bbox: 0.2030, loss_mask: 0.2113, loss: 0.6249 2023-11-13 23:41:01,304 - mmdet - INFO - Epoch [8][5500/7330] lr: 1.000e-04, eta: 3:51:08, time: 0.438, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0150, loss_rpn_bbox: 0.0339, loss_cls: 0.1462, acc: 94.4419, loss_bbox: 0.1939, loss_mask: 0.2041, loss: 0.5931 2023-11-13 23:41:23,218 - mmdet - INFO - Epoch [8][5550/7330] lr: 1.000e-04, eta: 3:50:46, time: 0.438, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0164, loss_rpn_bbox: 0.0361, loss_cls: 0.1482, acc: 94.4294, loss_bbox: 0.1916, loss_mask: 0.2093, loss: 0.6017 2023-11-13 23:41:45,244 - mmdet - INFO - Epoch [8][5600/7330] lr: 1.000e-04, eta: 3:50:23, time: 0.441, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0373, loss_cls: 0.1537, acc: 94.3059, loss_bbox: 0.2019, loss_mask: 0.2151, loss: 0.6240 2023-11-13 23:42:07,407 - mmdet - INFO - Epoch [8][5650/7330] lr: 1.000e-04, eta: 3:50:01, time: 0.443, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0356, loss_cls: 0.1456, acc: 94.4319, loss_bbox: 0.1972, loss_mask: 0.2091, loss: 0.6033 2023-11-13 23:42:29,915 - mmdet - INFO - Epoch [8][5700/7330] lr: 1.000e-04, eta: 3:49:39, time: 0.450, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0364, loss_cls: 0.1533, acc: 94.1890, loss_bbox: 0.1956, loss_mask: 0.2075, loss: 0.6088 2023-11-13 23:42:52,166 - mmdet - INFO - Epoch [8][5750/7330] lr: 1.000e-04, eta: 3:49:17, time: 0.445, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0373, loss_cls: 0.1567, acc: 94.0730, loss_bbox: 0.2050, loss_mask: 0.2121, loss: 0.6276 2023-11-13 23:43:13,717 - mmdet - INFO - Epoch [8][5800/7330] lr: 1.000e-04, eta: 3:48:54, time: 0.431, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0334, loss_cls: 0.1465, acc: 94.5173, loss_bbox: 0.1914, loss_mask: 0.2098, loss: 0.5962 2023-11-13 23:43:36,004 - mmdet - INFO - Epoch [8][5850/7330] lr: 1.000e-04, eta: 3:48:32, time: 0.446, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0171, loss_rpn_bbox: 0.0376, loss_cls: 0.1604, acc: 93.9592, loss_bbox: 0.2137, loss_mask: 0.2111, loss: 0.6398 2023-11-13 23:43:57,887 - mmdet - INFO - Epoch [8][5900/7330] lr: 1.000e-04, eta: 3:48:09, time: 0.438, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0148, loss_rpn_bbox: 0.0371, loss_cls: 0.1506, acc: 94.3008, loss_bbox: 0.2040, loss_mask: 0.2104, loss: 0.6170 2023-11-13 23:44:20,233 - mmdet - INFO - Epoch [8][5950/7330] lr: 1.000e-04, eta: 3:47:47, time: 0.447, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0365, loss_cls: 0.1559, acc: 94.1257, loss_bbox: 0.2054, loss_mask: 0.2138, loss: 0.6271 2023-11-13 23:44:42,034 - mmdet - INFO - Epoch [8][6000/7330] lr: 1.000e-04, eta: 3:47:25, time: 0.436, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0157, loss_rpn_bbox: 0.0350, loss_cls: 0.1476, acc: 94.4778, loss_bbox: 0.1940, loss_mask: 0.2099, loss: 0.6022 2023-11-13 23:45:03,835 - mmdet - INFO - Epoch [8][6050/7330] lr: 1.000e-04, eta: 3:47:02, time: 0.436, data_time: 0.018, memory: 5731, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0362, loss_cls: 0.1500, acc: 94.2832, loss_bbox: 0.1955, loss_mask: 0.2093, loss: 0.6060 2023-11-13 23:45:25,842 - mmdet - INFO - Epoch [8][6100/7330] lr: 1.000e-04, eta: 3:46:40, time: 0.440, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0348, loss_cls: 0.1475, acc: 94.3818, loss_bbox: 0.1967, loss_mask: 0.2054, loss: 0.5991 2023-11-13 23:45:47,544 - mmdet - INFO - Epoch [8][6150/7330] lr: 1.000e-04, eta: 3:46:17, time: 0.434, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0352, loss_cls: 0.1480, acc: 94.4058, loss_bbox: 0.1960, loss_mask: 0.2090, loss: 0.6040 2023-11-13 23:46:09,475 - mmdet - INFO - Epoch [8][6200/7330] lr: 1.000e-04, eta: 3:45:55, time: 0.439, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0366, loss_cls: 0.1547, acc: 94.1460, loss_bbox: 0.1998, loss_mask: 0.2110, loss: 0.6181 2023-11-13 23:46:31,593 - mmdet - INFO - Epoch [8][6250/7330] lr: 1.000e-04, eta: 3:45:32, time: 0.442, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0380, loss_cls: 0.1523, acc: 94.2715, loss_bbox: 0.1991, loss_mask: 0.2133, loss: 0.6179 2023-11-13 23:46:53,274 - mmdet - INFO - Epoch [8][6300/7330] lr: 1.000e-04, eta: 3:45:10, time: 0.434, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0344, loss_cls: 0.1527, acc: 94.2375, loss_bbox: 0.2041, loss_mask: 0.2151, loss: 0.6225 2023-11-13 23:47:15,443 - mmdet - INFO - Epoch [8][6350/7330] lr: 1.000e-04, eta: 3:44:48, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0377, loss_cls: 0.1583, acc: 93.9417, loss_bbox: 0.2063, loss_mask: 0.2168, loss: 0.6369 2023-11-13 23:47:37,249 - mmdet - INFO - Epoch [8][6400/7330] lr: 1.000e-04, eta: 3:44:25, time: 0.436, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0162, loss_rpn_bbox: 0.0352, loss_cls: 0.1466, acc: 94.4795, loss_bbox: 0.1937, loss_mask: 0.2081, loss: 0.5997 2023-11-13 23:47:59,493 - mmdet - INFO - Epoch [8][6450/7330] lr: 1.000e-04, eta: 3:44:03, time: 0.445, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0191, loss_rpn_bbox: 0.0381, loss_cls: 0.1557, acc: 94.0942, loss_bbox: 0.2012, loss_mask: 0.2109, loss: 0.6250 2023-11-13 23:48:21,375 - mmdet - INFO - Epoch [8][6500/7330] lr: 1.000e-04, eta: 3:43:40, time: 0.438, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0358, loss_cls: 0.1505, acc: 94.2900, loss_bbox: 0.1998, loss_mask: 0.2098, loss: 0.6117 2023-11-13 23:48:42,983 - mmdet - INFO - Epoch [8][6550/7330] lr: 1.000e-04, eta: 3:43:18, time: 0.432, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0371, loss_cls: 0.1537, acc: 94.2346, loss_bbox: 0.1996, loss_mask: 0.2123, loss: 0.6196 2023-11-13 23:49:05,751 - mmdet - INFO - Epoch [8][6600/7330] lr: 1.000e-04, eta: 3:42:56, time: 0.455, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0169, loss_rpn_bbox: 0.0375, loss_cls: 0.1514, acc: 94.2544, loss_bbox: 0.1969, loss_mask: 0.2087, loss: 0.6114 2023-11-13 23:49:27,965 - mmdet - INFO - Epoch [8][6650/7330] lr: 1.000e-04, eta: 3:42:33, time: 0.444, data_time: 0.021, memory: 5731, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0349, loss_cls: 0.1519, acc: 94.2024, loss_bbox: 0.2053, loss_mask: 0.2151, loss: 0.6230 2023-11-13 23:49:49,973 - mmdet - INFO - Epoch [8][6700/7330] lr: 1.000e-04, eta: 3:42:11, time: 0.440, data_time: 0.020, memory: 5731, loss_rpn_cls: 0.0159, loss_rpn_bbox: 0.0363, loss_cls: 0.1503, acc: 94.3552, loss_bbox: 0.1936, loss_mask: 0.2093, loss: 0.6053 2023-11-13 23:50:12,330 - mmdet - INFO - Epoch [8][6750/7330] lr: 1.000e-04, eta: 3:41:49, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0176, loss_rpn_bbox: 0.0386, loss_cls: 0.1551, acc: 94.1553, loss_bbox: 0.2025, loss_mask: 0.2129, loss: 0.6268 2023-11-13 23:50:34,715 - mmdet - INFO - Epoch [8][6800/7330] lr: 1.000e-04, eta: 3:41:27, time: 0.448, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0174, loss_rpn_bbox: 0.0377, loss_cls: 0.1548, acc: 94.2058, loss_bbox: 0.1996, loss_mask: 0.2096, loss: 0.6191 2023-11-13 23:50:56,688 - mmdet - INFO - Epoch [8][6850/7330] lr: 1.000e-04, eta: 3:41:04, time: 0.439, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0348, loss_cls: 0.1522, acc: 94.3062, loss_bbox: 0.2007, loss_mask: 0.2071, loss: 0.6096 2023-11-13 23:51:18,499 - mmdet - INFO - Epoch [8][6900/7330] lr: 1.000e-04, eta: 3:40:42, time: 0.436, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0350, loss_cls: 0.1489, acc: 94.3984, loss_bbox: 0.2002, loss_mask: 0.2099, loss: 0.6089 2023-11-13 23:51:40,124 - mmdet - INFO - Epoch [8][6950/7330] lr: 1.000e-04, eta: 3:40:19, time: 0.433, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0327, loss_cls: 0.1432, acc: 94.5510, loss_bbox: 0.1900, loss_mask: 0.2099, loss: 0.5902 2023-11-13 23:52:02,220 - mmdet - INFO - Epoch [8][7000/7330] lr: 1.000e-04, eta: 3:39:57, time: 0.442, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0160, loss_rpn_bbox: 0.0374, loss_cls: 0.1584, acc: 94.0261, loss_bbox: 0.2079, loss_mask: 0.2146, loss: 0.6343 2023-11-13 23:52:24,223 - mmdet - INFO - Epoch [8][7050/7330] lr: 1.000e-04, eta: 3:39:34, time: 0.440, data_time: 0.019, memory: 5731, loss_rpn_cls: 0.0170, loss_rpn_bbox: 0.0370, loss_cls: 0.1593, acc: 93.8940, loss_bbox: 0.2054, loss_mask: 0.2135, loss: 0.6322 2023-11-13 23:52:46,112 - mmdet - INFO - Epoch [8][7100/7330] lr: 1.000e-04, eta: 3:39:12, time: 0.438, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0166, loss_rpn_bbox: 0.0355, loss_cls: 0.1533, acc: 94.2529, loss_bbox: 0.2038, loss_mask: 0.2124, loss: 0.6216 2023-11-13 23:53:08,183 - mmdet - INFO - Epoch [8][7150/7330] lr: 1.000e-04, eta: 3:38:50, time: 0.441, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0352, loss_cls: 0.1508, acc: 94.2759, loss_bbox: 0.2046, loss_mask: 0.2100, loss: 0.6157 2023-11-13 23:53:30,385 - mmdet - INFO - Epoch [8][7200/7330] lr: 1.000e-04, eta: 3:38:27, time: 0.444, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0179, loss_rpn_bbox: 0.0368, loss_cls: 0.1555, acc: 94.2791, loss_bbox: 0.1986, loss_mask: 0.2124, loss: 0.6212 2023-11-13 23:53:52,181 - mmdet - INFO - Epoch [8][7250/7330] lr: 1.000e-04, eta: 3:38:05, time: 0.436, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0165, loss_rpn_bbox: 0.0360, loss_cls: 0.1539, acc: 94.2583, loss_bbox: 0.1994, loss_mask: 0.2049, loss: 0.6108 2023-11-13 23:54:14,296 - mmdet - INFO - Epoch [8][7300/7330] lr: 1.000e-04, eta: 3:37:43, time: 0.442, data_time: 0.022, memory: 5731, loss_rpn_cls: 0.0161, loss_rpn_bbox: 0.0364, loss_cls: 0.1512, acc: 94.3257, loss_bbox: 0.1976, loss_mask: 0.2050, loss: 0.6063 2023-11-13 23:54:28,020 - mmdet - INFO - Saving checkpoint at 8 epochs 2023-11-13 23:55:19,829 - mmdet - INFO - Evaluating bbox... 2023-11-13 23:55:48,510 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.477 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.701 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.524 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.311 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.522 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 ] = 0.604 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.604 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.604 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.423 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.649 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.749 2023-11-13 23:55:48,513 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.580 | bicycle | 0.369 | car | 0.493 | | motorcycle | 0.487 | airplane | 0.702 | bus | 0.667 | | train | 0.681 | truck | 0.451 | boat | 0.315 | | traffic light | 0.311 | fire hydrant | 0.726 | stop sign | 0.678 | | parking meter | 0.495 | bench | 0.297 | bird | 0.415 | | cat | 0.735 | dog | 0.688 | horse | 0.628 | | sheep | 0.586 | cow | 0.639 | elephant | 0.695 | | bear | 0.779 | zebra | 0.691 | giraffe | 0.709 | | backpack | 0.203 | umbrella | 0.443 | handbag | 0.252 | | tie | 0.398 | suitcase | 0.463 | frisbee | 0.704 | | skis | 0.295 | snowboard | 0.464 | sports ball | 0.475 | | kite | 0.464 | baseball bat | 0.416 | baseball glove | 0.453 | | skateboard | 0.592 | surfboard | 0.470 | tennis racket | 0.576 | | bottle | 0.468 | wine glass | 0.412 | cup | 0.491 | | fork | 0.454 | knife | 0.281 | spoon | 0.270 | | bowl | 0.465 | banana | 0.274 | apple | 0.263 | | sandwich | 0.463 | orange | 0.352 | broccoli | 0.259 | | carrot | 0.239 | hot dog | 0.409 | pizza | 0.548 | | donut | 0.554 | cake | 0.423 | chair | 0.362 | | couch | 0.448 | potted plant | 0.335 | bed | 0.499 | | dining table | 0.304 | toilet | 0.659 | tv | 0.626 | | laptop | 0.675 | mouse | 0.650 | remote | 0.414 | | keyboard | 0.555 | cell phone | 0.440 | microwave | 0.616 | | oven | 0.401 | toaster | 0.375 | sink | 0.446 | | refrigerator | 0.672 | book | 0.198 | clock | 0.537 | | vase | 0.406 | scissors | 0.399 | teddy bear | 0.522 | | hair drier | 0.185 | toothbrush | 0.359 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:55:48,513 - mmdet - INFO - Evaluating segm... 2023-11-13 23:56:22,616 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.432 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.672 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.466 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 ] = 0.465 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.619 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.370 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.596 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.708 2023-11-13 23:56:22,618 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.509 | bicycle | 0.230 | car | 0.456 | | motorcycle | 0.392 | airplane | 0.547 | bus | 0.659 | | train | 0.683 | truck | 0.433 | boat | 0.297 | | traffic light | 0.297 | fire hydrant | 0.703 | stop sign | 0.673 | | parking meter | 0.513 | bench | 0.231 | bird | 0.357 | | cat | 0.728 | dog | 0.646 | horse | 0.471 | | sheep | 0.526 | cow | 0.553 | elephant | 0.618 | | bear | 0.763 | zebra | 0.607 | giraffe | 0.533 | | backpack | 0.209 | umbrella | 0.500 | handbag | 0.228 | | tie | 0.369 | suitcase | 0.481 | frisbee | 0.671 | | skis | 0.060 | snowboard | 0.303 | sports ball | 0.475 | | kite | 0.344 | baseball bat | 0.309 | baseball glove | 0.472 | | skateboard | 0.362 | surfboard | 0.400 | tennis racket | 0.584 | | bottle | 0.453 | wine glass | 0.363 | cup | 0.496 | | fork | 0.252 | knife | 0.205 | spoon | 0.200 | | bowl | 0.439 | banana | 0.229 | apple | 0.257 | | sandwich | 0.485 | orange | 0.360 | broccoli | 0.240 | | carrot | 0.220 | hot dog | 0.318 | pizza | 0.530 | | donut | 0.559 | cake | 0.436 | chair | 0.252 | | couch | 0.393 | potted plant | 0.289 | bed | 0.382 | | dining table | 0.159 | toilet | 0.641 | tv | 0.646 | | laptop | 0.664 | mouse | 0.642 | remote | 0.379 | | keyboard | 0.546 | cell phone | 0.418 | microwave | 0.644 | | oven | 0.367 | toaster | 0.470 | sink | 0.416 | | refrigerator | 0.696 | book | 0.152 | clock | 0.538 | | vase | 0.397 | scissors | 0.298 | teddy bear | 0.508 | | hair drier | 0.216 | toothbrush | 0.239 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-13 23:56:23,015 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-13 23:56:23,015 - mmdet - INFO - Epoch(val) [8][625] bbox_mAP: 0.4774, bbox_mAP_50: 0.7007, bbox_mAP_75: 0.5244, bbox_mAP_s: 0.3112, bbox_mAP_m: 0.5224, bbox_mAP_l: 0.6172, bbox_mAP_copypaste: 0.4774 0.7007 0.5244 0.3112 0.5224 0.6172, segm_mAP: 0.4323, segm_mAP_50: 0.6719, segm_mAP_75: 0.4655, segm_mAP_s: 0.2380, segm_mAP_m: 0.4648, segm_mAP_l: 0.6188, segm_mAP_copypaste: 0.4323 0.6719 0.4655 0.2380 0.4648 0.6188 2023-11-13 23:56:49,087 - mmdet - INFO - Epoch [9][50/7330] lr: 1.000e-05, eta: 3:37:02, time: 0.521, data_time: 0.089, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0358, loss_cls: 0.1450, acc: 94.4399, loss_bbox: 0.1953, loss_mask: 0.2069, loss: 0.5979 2023-11-13 23:57:11,646 - mmdet - INFO - Epoch [9][100/7330] lr: 1.000e-05, eta: 3:36:40, time: 0.451, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0331, loss_cls: 0.1364, acc: 94.8301, loss_bbox: 0.1845, loss_mask: 0.2003, loss: 0.5681 2023-11-13 23:57:34,230 - mmdet - INFO - Epoch [9][150/7330] lr: 1.000e-05, eta: 3:36:18, time: 0.452, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0152, loss_rpn_bbox: 0.0344, loss_cls: 0.1410, acc: 94.6670, loss_bbox: 0.1959, loss_mask: 0.2066, loss: 0.5930 2023-11-13 23:57:56,814 - mmdet - INFO - Epoch [9][200/7330] lr: 1.000e-05, eta: 3:35:56, time: 0.452, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0325, loss_cls: 0.1352, acc: 94.8718, loss_bbox: 0.1865, loss_mask: 0.2024, loss: 0.5692 2023-11-13 23:58:19,337 - mmdet - INFO - Epoch [9][250/7330] lr: 1.000e-05, eta: 3:35:34, time: 0.450, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0333, loss_cls: 0.1405, acc: 94.6433, loss_bbox: 0.1916, loss_mask: 0.2056, loss: 0.5853 2023-11-13 23:58:41,918 - mmdet - INFO - Epoch [9][300/7330] lr: 1.000e-05, eta: 3:35:12, time: 0.452, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0339, loss_cls: 0.1429, acc: 94.6284, loss_bbox: 0.1930, loss_mask: 0.2052, loss: 0.5880 2023-11-13 23:59:04,844 - mmdet - INFO - Epoch [9][350/7330] lr: 1.000e-05, eta: 3:34:50, time: 0.459, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0330, loss_cls: 0.1384, acc: 94.6929, loss_bbox: 0.1890, loss_mask: 0.2013, loss: 0.5760 2023-11-13 23:59:27,212 - mmdet - INFO - Epoch [9][400/7330] lr: 1.000e-05, eta: 3:34:28, time: 0.447, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0334, loss_cls: 0.1357, acc: 94.8215, loss_bbox: 0.1825, loss_mask: 0.2020, loss: 0.5673 2023-11-13 23:59:49,774 - mmdet - INFO - Epoch [9][450/7330] lr: 1.000e-05, eta: 3:34:06, time: 0.451, data_time: 0.032, memory: 5731, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0339, loss_cls: 0.1368, acc: 94.7517, loss_bbox: 0.1874, loss_mask: 0.1992, loss: 0.5715 2023-11-14 00:00:12,004 - mmdet - INFO - Epoch [9][500/7330] lr: 1.000e-05, eta: 3:33:43, time: 0.445, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0318, loss_cls: 0.1319, acc: 94.9500, loss_bbox: 0.1756, loss_mask: 0.1958, loss: 0.5481 2023-11-14 00:00:34,330 - mmdet - INFO - Epoch [9][550/7330] lr: 1.000e-05, eta: 3:33:21, time: 0.446, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0319, loss_cls: 0.1348, acc: 94.8547, loss_bbox: 0.1805, loss_mask: 0.1994, loss: 0.5603 2023-11-14 00:00:56,766 - mmdet - INFO - Epoch [9][600/7330] lr: 1.000e-05, eta: 3:32:59, time: 0.449, data_time: 0.030, memory: 5731, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0332, loss_cls: 0.1355, acc: 94.7585, loss_bbox: 0.1863, loss_mask: 0.1988, loss: 0.5665 2023-11-14 00:01:19,086 - mmdet - INFO - Epoch [9][650/7330] lr: 1.000e-05, eta: 3:32:37, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0329, loss_cls: 0.1321, acc: 94.9268, loss_bbox: 0.1836, loss_mask: 0.1988, loss: 0.5590 2023-11-14 00:01:41,508 - mmdet - INFO - Epoch [9][700/7330] lr: 1.000e-05, eta: 3:32:15, time: 0.448, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0341, loss_cls: 0.1387, acc: 94.7007, loss_bbox: 0.1880, loss_mask: 0.2024, loss: 0.5766 2023-11-14 00:02:03,914 - mmdet - INFO - Epoch [9][750/7330] lr: 1.000e-05, eta: 3:31:52, time: 0.448, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0338, loss_cls: 0.1372, acc: 94.7495, loss_bbox: 0.1864, loss_mask: 0.2037, loss: 0.5752 2023-11-14 00:02:26,544 - mmdet - INFO - Epoch [9][800/7330] lr: 1.000e-05, eta: 3:31:30, time: 0.453, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0149, loss_rpn_bbox: 0.0361, loss_cls: 0.1376, acc: 94.7126, loss_bbox: 0.1846, loss_mask: 0.2006, loss: 0.5738 2023-11-14 00:02:49,229 - mmdet - INFO - Epoch [9][850/7330] lr: 1.000e-05, eta: 3:31:08, time: 0.454, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0337, loss_cls: 0.1315, acc: 94.9634, loss_bbox: 0.1854, loss_mask: 0.2002, loss: 0.5641 2023-11-14 00:03:11,683 - mmdet - INFO - Epoch [9][900/7330] lr: 1.000e-05, eta: 3:30:46, time: 0.449, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0336, loss_cls: 0.1400, acc: 94.5857, loss_bbox: 0.1942, loss_mask: 0.2049, loss: 0.5853 2023-11-14 00:03:34,360 - mmdet - INFO - Epoch [9][950/7330] lr: 1.000e-05, eta: 3:30:24, time: 0.454, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0365, loss_cls: 0.1412, acc: 94.5898, loss_bbox: 0.1935, loss_mask: 0.2023, loss: 0.5875 2023-11-14 00:03:56,743 - mmdet - INFO - Epoch [9][1000/7330] lr: 1.000e-05, eta: 3:30:02, time: 0.448, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0327, loss_cls: 0.1332, acc: 94.8342, loss_bbox: 0.1872, loss_mask: 0.1989, loss: 0.5654 2023-11-14 00:04:19,046 - mmdet - INFO - Epoch [9][1050/7330] lr: 1.000e-05, eta: 3:29:40, time: 0.446, data_time: 0.023, memory: 5731, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0324, loss_cls: 0.1337, acc: 94.8691, loss_bbox: 0.1797, loss_mask: 0.1998, loss: 0.5589 2023-11-14 00:04:41,838 - mmdet - INFO - Epoch [9][1100/7330] lr: 1.000e-05, eta: 3:29:18, time: 0.456, data_time: 0.028, memory: 5731, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0355, loss_cls: 0.1364, acc: 94.7681, loss_bbox: 0.1862, loss_mask: 0.1976, loss: 0.5679 2023-11-14 00:05:04,200 - mmdet - INFO - Epoch [9][1150/7330] lr: 1.000e-05, eta: 3:28:56, time: 0.447, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0351, loss_cls: 0.1359, acc: 94.8174, loss_bbox: 0.1854, loss_mask: 0.2051, loss: 0.5744 2023-11-14 00:05:26,530 - mmdet - INFO - Epoch [9][1200/7330] lr: 1.000e-05, eta: 3:28:33, time: 0.447, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0324, loss_cls: 0.1325, acc: 94.8347, loss_bbox: 0.1851, loss_mask: 0.2004, loss: 0.5635 2023-11-14 00:05:48,686 - mmdet - INFO - Epoch [9][1250/7330] lr: 1.000e-05, eta: 3:28:11, time: 0.443, data_time: 0.027, memory: 5731, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0350, loss_cls: 0.1403, acc: 94.6340, loss_bbox: 0.1896, loss_mask: 0.2021, loss: 0.5824 2023-11-14 00:06:10,841 - mmdet - INFO - Epoch [9][1300/7330] lr: 1.000e-05, eta: 3:27:49, time: 0.443, data_time: 0.024, memory: 5731, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1318, acc: 94.9316, loss_bbox: 0.1826, loss_mask: 0.1986, loss: 0.5580 2023-11-14 00:06:33,198 - mmdet - INFO - Epoch [9][1350/7330] lr: 1.000e-05, eta: 3:27:26, time: 0.447, data_time: 0.026, memory: 5731, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0322, loss_cls: 0.1376, acc: 94.7510, loss_bbox: 0.1874, loss_mask: 0.2053, loss: 0.5755 2023-11-14 00:06:55,660 - mmdet - INFO - Epoch [9][1400/7330] lr: 1.000e-05, eta: 3:27:04, time: 0.449, data_time: 0.029, memory: 5731, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0334, loss_cls: 0.1366, acc: 94.8296, loss_bbox: 0.1858, loss_mask: 0.1963, loss: 0.5650 2023-11-14 00:07:17,731 - mmdet - INFO - Epoch [9][1450/7330] lr: 1.000e-05, eta: 3:26:42, time: 0.441, data_time: 0.025, memory: 5731, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0323, loss_cls: 0.1279, acc: 95.0750, loss_bbox: 0.1767, loss_mask: 0.1963, loss: 0.5458 2023-11-14 00:07:40,193 - mmdet - INFO - Epoch [9][1500/7330] lr: 1.000e-05, eta: 3:26:20, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0331, loss_cls: 0.1334, acc: 94.9238, loss_bbox: 0.1816, loss_mask: 0.2008, loss: 0.5613 2023-11-14 00:08:02,658 - mmdet - INFO - Epoch [9][1550/7330] lr: 1.000e-05, eta: 3:25:58, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0327, loss_cls: 0.1369, acc: 94.7969, loss_bbox: 0.1843, loss_mask: 0.2013, loss: 0.5690 2023-11-14 00:08:24,984 - mmdet - INFO - Epoch [9][1600/7330] lr: 1.000e-05, eta: 3:25:35, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0336, loss_cls: 0.1293, acc: 94.9973, loss_bbox: 0.1810, loss_mask: 0.1970, loss: 0.5538 2023-11-14 00:08:47,534 - mmdet - INFO - Epoch [9][1650/7330] lr: 1.000e-05, eta: 3:25:13, time: 0.451, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0341, loss_cls: 0.1379, acc: 94.7061, loss_bbox: 0.1858, loss_mask: 0.2018, loss: 0.5743 2023-11-14 00:09:09,741 - mmdet - INFO - Epoch [9][1700/7330] lr: 1.000e-05, eta: 3:24:51, time: 0.444, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0330, loss_cls: 0.1278, acc: 95.0002, loss_bbox: 0.1778, loss_mask: 0.1974, loss: 0.5481 2023-11-14 00:09:32,055 - mmdet - INFO - Epoch [9][1750/7330] lr: 1.000e-05, eta: 3:24:29, time: 0.446, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0311, loss_cls: 0.1284, acc: 95.0403, loss_bbox: 0.1814, loss_mask: 0.1951, loss: 0.5478 2023-11-14 00:09:54,255 - mmdet - INFO - Epoch [9][1800/7330] lr: 1.000e-05, eta: 3:24:07, time: 0.444, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0334, loss_cls: 0.1375, acc: 94.6455, loss_bbox: 0.1899, loss_mask: 0.2041, loss: 0.5788 2023-11-14 00:10:16,481 - mmdet - INFO - Epoch [9][1850/7330] lr: 1.000e-05, eta: 3:23:44, time: 0.444, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0353, loss_cls: 0.1383, acc: 94.6790, loss_bbox: 0.1919, loss_mask: 0.2021, loss: 0.5814 2023-11-14 00:10:38,573 - mmdet - INFO - Epoch [9][1900/7330] lr: 1.000e-05, eta: 3:23:22, time: 0.442, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0308, loss_cls: 0.1311, acc: 94.9236, loss_bbox: 0.1781, loss_mask: 0.1979, loss: 0.5514 2023-11-14 00:11:00,680 - mmdet - INFO - Epoch [9][1950/7330] lr: 1.000e-05, eta: 3:23:00, time: 0.442, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0323, loss_cls: 0.1345, acc: 94.8503, loss_bbox: 0.1873, loss_mask: 0.1978, loss: 0.5645 2023-11-14 00:11:22,891 - mmdet - INFO - Epoch [9][2000/7330] lr: 1.000e-05, eta: 3:22:37, time: 0.444, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0339, loss_cls: 0.1312, acc: 94.9519, loss_bbox: 0.1850, loss_mask: 0.2000, loss: 0.5642 2023-11-14 00:11:45,189 - mmdet - INFO - Epoch [9][2050/7330] lr: 1.000e-05, eta: 3:22:15, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0335, loss_cls: 0.1344, acc: 94.8364, loss_bbox: 0.1902, loss_mask: 0.2025, loss: 0.5735 2023-11-14 00:12:07,686 - mmdet - INFO - Epoch [9][2100/7330] lr: 1.000e-05, eta: 3:21:53, time: 0.450, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0332, loss_cls: 0.1390, acc: 94.7275, loss_bbox: 0.1895, loss_mask: 0.2055, loss: 0.5805 2023-11-14 00:12:30,374 - mmdet - INFO - Epoch [9][2150/7330] lr: 1.000e-05, eta: 3:21:31, time: 0.454, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0348, loss_cls: 0.1425, acc: 94.4604, loss_bbox: 0.1915, loss_mask: 0.2035, loss: 0.5862 2023-11-14 00:12:52,973 - mmdet - INFO - Epoch [9][2200/7330] lr: 1.000e-05, eta: 3:21:09, time: 0.452, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0327, loss_cls: 0.1313, acc: 94.8914, loss_bbox: 0.1814, loss_mask: 0.1971, loss: 0.5552 2023-11-14 00:13:15,314 - mmdet - INFO - Epoch [9][2250/7330] lr: 1.000e-05, eta: 3:20:47, time: 0.447, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0344, loss_cls: 0.1384, acc: 94.6301, loss_bbox: 0.1884, loss_mask: 0.2048, loss: 0.5791 2023-11-14 00:13:38,061 - mmdet - INFO - Epoch [9][2300/7330] lr: 1.000e-05, eta: 3:20:25, time: 0.455, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0323, loss_cls: 0.1306, acc: 94.9087, loss_bbox: 0.1839, loss_mask: 0.1983, loss: 0.5581 2023-11-14 00:14:00,222 - mmdet - INFO - Epoch [9][2350/7330] lr: 1.000e-05, eta: 3:20:02, time: 0.443, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0331, loss_cls: 0.1348, acc: 94.7742, loss_bbox: 0.1840, loss_mask: 0.2039, loss: 0.5691 2023-11-14 00:14:22,319 - mmdet - INFO - Epoch [9][2400/7330] lr: 1.000e-05, eta: 3:19:40, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0328, loss_cls: 0.1310, acc: 94.9985, loss_bbox: 0.1851, loss_mask: 0.2017, loss: 0.5639 2023-11-14 00:14:44,605 - mmdet - INFO - Epoch [9][2450/7330] lr: 1.000e-05, eta: 3:19:18, time: 0.446, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0338, loss_cls: 0.1333, acc: 94.7773, loss_bbox: 0.1854, loss_mask: 0.1989, loss: 0.5650 2023-11-14 00:15:07,168 - mmdet - INFO - Epoch [9][2500/7330] lr: 1.000e-05, eta: 3:18:56, time: 0.451, data_time: 0.031, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0333, loss_cls: 0.1335, acc: 94.8535, loss_bbox: 0.1856, loss_mask: 0.2035, loss: 0.5688 2023-11-14 00:15:29,290 - mmdet - INFO - Epoch [9][2550/7330] lr: 1.000e-05, eta: 3:18:33, time: 0.442, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0312, loss_cls: 0.1293, acc: 95.0203, loss_bbox: 0.1769, loss_mask: 0.1959, loss: 0.5461 2023-11-14 00:15:51,912 - mmdet - INFO - Epoch [9][2600/7330] lr: 1.000e-05, eta: 3:18:11, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0342, loss_cls: 0.1346, acc: 94.8105, loss_bbox: 0.1911, loss_mask: 0.2011, loss: 0.5741 2023-11-14 00:16:14,150 - mmdet - INFO - Epoch [9][2650/7330] lr: 1.000e-05, eta: 3:17:49, time: 0.445, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0320, loss_cls: 0.1371, acc: 94.7620, loss_bbox: 0.1869, loss_mask: 0.2032, loss: 0.5713 2023-11-14 00:16:36,548 - mmdet - INFO - Epoch [9][2700/7330] lr: 1.000e-05, eta: 3:17:27, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0353, loss_cls: 0.1426, acc: 94.5415, loss_bbox: 0.1931, loss_mask: 0.2044, loss: 0.5887 2023-11-14 00:16:59,126 - mmdet - INFO - Epoch [9][2750/7330] lr: 1.000e-05, eta: 3:17:05, time: 0.452, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0320, loss_cls: 0.1267, acc: 95.0391, loss_bbox: 0.1755, loss_mask: 0.1981, loss: 0.5438 2023-11-14 00:17:21,619 - mmdet - INFO - Epoch [9][2800/7330] lr: 1.000e-05, eta: 3:16:43, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0353, loss_cls: 0.1414, acc: 94.5608, loss_bbox: 0.1928, loss_mask: 0.2012, loss: 0.5850 2023-11-14 00:17:44,124 - mmdet - INFO - Epoch [9][2850/7330] lr: 1.000e-05, eta: 3:16:20, time: 0.450, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0327, loss_cls: 0.1334, acc: 94.9600, loss_bbox: 0.1811, loss_mask: 0.2049, loss: 0.5656 2023-11-14 00:18:06,418 - mmdet - INFO - Epoch [9][2900/7330] lr: 1.000e-05, eta: 3:15:58, time: 0.446, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0309, loss_cls: 0.1302, acc: 95.0256, loss_bbox: 0.1793, loss_mask: 0.1961, loss: 0.5494 2023-11-14 00:18:28,566 - mmdet - INFO - Epoch [9][2950/7330] lr: 1.000e-05, eta: 3:15:36, time: 0.443, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0317, loss_cls: 0.1332, acc: 94.8142, loss_bbox: 0.1883, loss_mask: 0.2013, loss: 0.5674 2023-11-14 00:18:50,746 - mmdet - INFO - Epoch [9][3000/7330] lr: 1.000e-05, eta: 3:15:14, time: 0.444, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0341, loss_cls: 0.1360, acc: 94.8757, loss_bbox: 0.1836, loss_mask: 0.1966, loss: 0.5632 2023-11-14 00:19:12,956 - mmdet - INFO - Epoch [9][3050/7330] lr: 1.000e-05, eta: 3:14:51, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0335, loss_cls: 0.1330, acc: 94.8884, loss_bbox: 0.1826, loss_mask: 0.1989, loss: 0.5613 2023-11-14 00:19:35,160 - mmdet - INFO - Epoch [9][3100/7330] lr: 1.000e-05, eta: 3:14:29, time: 0.444, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0343, loss_cls: 0.1353, acc: 94.8132, loss_bbox: 0.1853, loss_mask: 0.1955, loss: 0.5641 2023-11-14 00:19:57,631 - mmdet - INFO - Epoch [9][3150/7330] lr: 1.000e-05, eta: 3:14:07, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0346, loss_cls: 0.1366, acc: 94.7356, loss_bbox: 0.1925, loss_mask: 0.2008, loss: 0.5783 2023-11-14 00:20:19,926 - mmdet - INFO - Epoch [9][3200/7330] lr: 1.000e-05, eta: 3:13:45, time: 0.446, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0320, loss_cls: 0.1285, acc: 95.0959, loss_bbox: 0.1789, loss_mask: 0.1966, loss: 0.5489 2023-11-14 00:20:42,142 - mmdet - INFO - Epoch [9][3250/7330] lr: 1.000e-05, eta: 3:13:22, time: 0.444, data_time: 0.019, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0322, loss_cls: 0.1332, acc: 94.8926, loss_bbox: 0.1801, loss_mask: 0.1993, loss: 0.5585 2023-11-14 00:21:04,546 - mmdet - INFO - Epoch [9][3300/7330] lr: 1.000e-05, eta: 3:13:00, time: 0.448, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0151, loss_rpn_bbox: 0.0366, loss_cls: 0.1370, acc: 94.7158, loss_bbox: 0.1896, loss_mask: 0.2037, loss: 0.5819 2023-11-14 00:21:26,568 - mmdet - INFO - Epoch [9][3350/7330] lr: 1.000e-05, eta: 3:12:38, time: 0.440, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0328, loss_cls: 0.1340, acc: 94.9153, loss_bbox: 0.1831, loss_mask: 0.1971, loss: 0.5595 2023-11-14 00:21:49,160 - mmdet - INFO - Epoch [9][3400/7330] lr: 1.000e-05, eta: 3:12:16, time: 0.452, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0341, loss_cls: 0.1405, acc: 94.5288, loss_bbox: 0.1892, loss_mask: 0.1957, loss: 0.5739 2023-11-14 00:22:11,495 - mmdet - INFO - Epoch [9][3450/7330] lr: 1.000e-05, eta: 3:11:54, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0318, loss_cls: 0.1284, acc: 95.0513, loss_bbox: 0.1805, loss_mask: 0.1979, loss: 0.5509 2023-11-14 00:22:33,930 - mmdet - INFO - Epoch [9][3500/7330] lr: 1.000e-05, eta: 3:11:31, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0348, loss_cls: 0.1378, acc: 94.6897, loss_bbox: 0.1857, loss_mask: 0.2016, loss: 0.5729 2023-11-14 00:22:56,049 - mmdet - INFO - Epoch [9][3550/7330] lr: 1.000e-05, eta: 3:11:09, time: 0.442, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0339, loss_cls: 0.1351, acc: 94.8430, loss_bbox: 0.1856, loss_mask: 0.1992, loss: 0.5674 2023-11-14 00:23:18,107 - mmdet - INFO - Epoch [9][3600/7330] lr: 1.000e-05, eta: 3:10:47, time: 0.441, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0336, loss_cls: 0.1329, acc: 94.8660, loss_bbox: 0.1857, loss_mask: 0.2025, loss: 0.5673 2023-11-14 00:23:40,879 - mmdet - INFO - Epoch [9][3650/7330] lr: 1.000e-05, eta: 3:10:25, time: 0.455, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0363, loss_cls: 0.1382, acc: 94.6726, loss_bbox: 0.1925, loss_mask: 0.1997, loss: 0.5806 2023-11-14 00:24:03,790 - mmdet - INFO - Epoch [9][3700/7330] lr: 1.000e-05, eta: 3:10:03, time: 0.458, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0361, loss_cls: 0.1390, acc: 94.6807, loss_bbox: 0.1891, loss_mask: 0.2002, loss: 0.5778 2023-11-14 00:24:25,815 - mmdet - INFO - Epoch [9][3750/7330] lr: 1.000e-05, eta: 3:09:40, time: 0.441, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0331, loss_cls: 0.1299, acc: 94.9651, loss_bbox: 0.1809, loss_mask: 0.1990, loss: 0.5549 2023-11-14 00:24:48,344 - mmdet - INFO - Epoch [9][3800/7330] lr: 1.000e-05, eta: 3:09:18, time: 0.450, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0353, loss_cls: 0.1397, acc: 94.5886, loss_bbox: 0.1909, loss_mask: 0.2029, loss: 0.5825 2023-11-14 00:25:10,785 - mmdet - INFO - Epoch [9][3850/7330] lr: 1.000e-05, eta: 3:08:56, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0346, loss_cls: 0.1442, acc: 94.4202, loss_bbox: 0.1962, loss_mask: 0.2018, loss: 0.5893 2023-11-14 00:25:33,057 - mmdet - INFO - Epoch [9][3900/7330] lr: 1.000e-05, eta: 3:08:34, time: 0.445, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0340, loss_cls: 0.1327, acc: 94.9019, loss_bbox: 0.1854, loss_mask: 0.2006, loss: 0.5643 2023-11-14 00:25:55,614 - mmdet - INFO - Epoch [9][3950/7330] lr: 1.000e-05, eta: 3:08:12, time: 0.451, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0315, loss_cls: 0.1357, acc: 94.8784, loss_bbox: 0.1799, loss_mask: 0.1941, loss: 0.5545 2023-11-14 00:26:17,844 - mmdet - INFO - Epoch [9][4000/7330] lr: 1.000e-05, eta: 3:07:49, time: 0.445, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0318, loss_cls: 0.1297, acc: 94.9761, loss_bbox: 0.1822, loss_mask: 0.2024, loss: 0.5583 2023-11-14 00:26:40,107 - mmdet - INFO - Epoch [9][4050/7330] lr: 1.000e-05, eta: 3:07:27, time: 0.445, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0338, loss_cls: 0.1294, acc: 94.9766, loss_bbox: 0.1816, loss_mask: 0.1997, loss: 0.5573 2023-11-14 00:27:02,289 - mmdet - INFO - Epoch [9][4100/7330] lr: 1.000e-05, eta: 3:07:05, time: 0.444, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0315, loss_cls: 0.1310, acc: 94.9678, loss_bbox: 0.1819, loss_mask: 0.1962, loss: 0.5516 2023-11-14 00:27:24,387 - mmdet - INFO - Epoch [9][4150/7330] lr: 1.000e-05, eta: 3:06:43, time: 0.442, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0327, loss_cls: 0.1332, acc: 94.8589, loss_bbox: 0.1843, loss_mask: 0.2017, loss: 0.5649 2023-11-14 00:27:47,090 - mmdet - INFO - Epoch [9][4200/7330] lr: 1.000e-05, eta: 3:06:20, time: 0.454, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0321, loss_cls: 0.1331, acc: 94.9211, loss_bbox: 0.1822, loss_mask: 0.2031, loss: 0.5630 2023-11-14 00:28:09,014 - mmdet - INFO - Epoch [9][4250/7330] lr: 1.000e-05, eta: 3:05:58, time: 0.438, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0315, loss_cls: 0.1364, acc: 94.8601, loss_bbox: 0.1788, loss_mask: 0.1980, loss: 0.5582 2023-11-14 00:28:31,454 - mmdet - INFO - Epoch [9][4300/7330] lr: 1.000e-05, eta: 3:05:36, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0318, loss_cls: 0.1264, acc: 95.0774, loss_bbox: 0.1748, loss_mask: 0.1933, loss: 0.5380 2023-11-14 00:28:53,734 - mmdet - INFO - Epoch [9][4350/7330] lr: 1.000e-05, eta: 3:05:14, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0318, loss_cls: 0.1311, acc: 94.9597, loss_bbox: 0.1782, loss_mask: 0.1974, loss: 0.5505 2023-11-14 00:29:16,233 - mmdet - INFO - Epoch [9][4400/7330] lr: 1.000e-05, eta: 3:04:51, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0349, loss_cls: 0.1356, acc: 94.7930, loss_bbox: 0.1899, loss_mask: 0.1997, loss: 0.5731 2023-11-14 00:29:38,382 - mmdet - INFO - Epoch [9][4450/7330] lr: 1.000e-05, eta: 3:04:29, time: 0.443, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0322, loss_cls: 0.1319, acc: 94.9011, loss_bbox: 0.1845, loss_mask: 0.2003, loss: 0.5611 2023-11-14 00:30:00,314 - mmdet - INFO - Epoch [9][4500/7330] lr: 1.000e-05, eta: 3:04:07, time: 0.439, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0339, loss_cls: 0.1327, acc: 94.8894, loss_bbox: 0.1917, loss_mask: 0.2002, loss: 0.5710 2023-11-14 00:30:22,414 - mmdet - INFO - Epoch [9][4550/7330] lr: 1.000e-05, eta: 3:03:44, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0333, loss_cls: 0.1359, acc: 94.8066, loss_bbox: 0.1882, loss_mask: 0.2021, loss: 0.5724 2023-11-14 00:30:44,701 - mmdet - INFO - Epoch [9][4600/7330] lr: 1.000e-05, eta: 3:03:22, time: 0.446, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0320, loss_cls: 0.1267, acc: 95.0862, loss_bbox: 0.1770, loss_mask: 0.1905, loss: 0.5393 2023-11-14 00:31:06,991 - mmdet - INFO - Epoch [9][4650/7330] lr: 1.000e-05, eta: 3:03:00, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0335, loss_cls: 0.1331, acc: 94.8167, loss_bbox: 0.1886, loss_mask: 0.2009, loss: 0.5692 2023-11-14 00:31:29,578 - mmdet - INFO - Epoch [9][4700/7330] lr: 1.000e-05, eta: 3:02:38, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0346, loss_cls: 0.1381, acc: 94.7097, loss_bbox: 0.1931, loss_mask: 0.2052, loss: 0.5843 2023-11-14 00:31:51,930 - mmdet - INFO - Epoch [9][4750/7330] lr: 1.000e-05, eta: 3:02:16, time: 0.447, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0359, loss_cls: 0.1373, acc: 94.7109, loss_bbox: 0.1923, loss_mask: 0.2027, loss: 0.5814 2023-11-14 00:32:14,492 - mmdet - INFO - Epoch [9][4800/7330] lr: 1.000e-05, eta: 3:01:54, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0322, loss_cls: 0.1286, acc: 95.0813, loss_bbox: 0.1830, loss_mask: 0.2005, loss: 0.5564 2023-11-14 00:32:36,885 - mmdet - INFO - Epoch [9][4850/7330] lr: 1.000e-05, eta: 3:01:31, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0327, loss_cls: 0.1345, acc: 94.8384, loss_bbox: 0.1836, loss_mask: 0.1970, loss: 0.5603 2023-11-14 00:32:59,176 - mmdet - INFO - Epoch [9][4900/7330] lr: 1.000e-05, eta: 3:01:09, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0338, loss_cls: 0.1346, acc: 94.8210, loss_bbox: 0.1848, loss_mask: 0.2000, loss: 0.5661 2023-11-14 00:33:22,671 - mmdet - INFO - Epoch [9][4950/7330] lr: 1.000e-05, eta: 3:00:47, time: 0.470, data_time: 0.034, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0319, loss_cls: 0.1294, acc: 95.0090, loss_bbox: 0.1789, loss_mask: 0.1961, loss: 0.5487 2023-11-14 00:33:47,043 - mmdet - INFO - Epoch [9][5000/7330] lr: 1.000e-05, eta: 3:00:26, time: 0.487, data_time: 0.042, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0313, loss_cls: 0.1270, acc: 95.1213, loss_bbox: 0.1805, loss_mask: 0.1945, loss: 0.5443 2023-11-14 00:34:09,533 - mmdet - INFO - Epoch [9][5050/7330] lr: 1.000e-05, eta: 3:00:04, time: 0.450, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0318, loss_cls: 0.1302, acc: 94.9709, loss_bbox: 0.1792, loss_mask: 0.1953, loss: 0.5491 2023-11-14 00:34:32,205 - mmdet - INFO - Epoch [9][5100/7330] lr: 1.000e-05, eta: 2:59:42, time: 0.453, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0331, loss_cls: 0.1279, acc: 95.0593, loss_bbox: 0.1810, loss_mask: 0.1938, loss: 0.5482 2023-11-14 00:34:54,656 - mmdet - INFO - Epoch [9][5150/7330] lr: 1.000e-05, eta: 2:59:19, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0313, loss_cls: 0.1309, acc: 94.9573, loss_bbox: 0.1831, loss_mask: 0.1963, loss: 0.5544 2023-11-14 00:35:16,792 - mmdet - INFO - Epoch [9][5200/7330] lr: 1.000e-05, eta: 2:58:57, time: 0.443, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0324, loss_cls: 0.1291, acc: 94.9370, loss_bbox: 0.1828, loss_mask: 0.2016, loss: 0.5585 2023-11-14 00:35:38,922 - mmdet - INFO - Epoch [9][5250/7330] lr: 1.000e-05, eta: 2:58:35, time: 0.443, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0340, loss_cls: 0.1309, acc: 94.9995, loss_bbox: 0.1855, loss_mask: 0.1989, loss: 0.5623 2023-11-14 00:36:00,903 - mmdet - INFO - Epoch [9][5300/7330] lr: 1.000e-05, eta: 2:58:12, time: 0.440, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0332, loss_cls: 0.1276, acc: 95.0613, loss_bbox: 0.1825, loss_mask: 0.1991, loss: 0.5548 2023-11-14 00:36:23,082 - mmdet - INFO - Epoch [9][5350/7330] lr: 1.000e-05, eta: 2:57:50, time: 0.444, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0329, loss_cls: 0.1293, acc: 94.9648, loss_bbox: 0.1875, loss_mask: 0.1986, loss: 0.5610 2023-11-14 00:36:44,938 - mmdet - INFO - Epoch [9][5400/7330] lr: 1.000e-05, eta: 2:57:28, time: 0.437, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0331, loss_cls: 0.1322, acc: 94.9241, loss_bbox: 0.1845, loss_mask: 0.2018, loss: 0.5651 2023-11-14 00:37:07,356 - mmdet - INFO - Epoch [9][5450/7330] lr: 1.000e-05, eta: 2:57:06, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0326, loss_cls: 0.1303, acc: 95.0442, loss_bbox: 0.1790, loss_mask: 0.1958, loss: 0.5509 2023-11-14 00:37:29,630 - mmdet - INFO - Epoch [9][5500/7330] lr: 1.000e-05, eta: 2:56:43, time: 0.445, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0329, loss_cls: 0.1299, acc: 95.0051, loss_bbox: 0.1815, loss_mask: 0.1989, loss: 0.5549 2023-11-14 00:37:51,853 - mmdet - INFO - Epoch [9][5550/7330] lr: 1.000e-05, eta: 2:56:21, time: 0.444, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0332, loss_cls: 0.1303, acc: 94.9951, loss_bbox: 0.1842, loss_mask: 0.2011, loss: 0.5617 2023-11-14 00:38:14,082 - mmdet - INFO - Epoch [9][5600/7330] lr: 1.000e-05, eta: 2:55:59, time: 0.445, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0322, loss_cls: 0.1312, acc: 94.9148, loss_bbox: 0.1785, loss_mask: 0.1937, loss: 0.5482 2023-11-14 00:38:36,180 - mmdet - INFO - Epoch [9][5650/7330] lr: 1.000e-05, eta: 2:55:36, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0325, loss_cls: 0.1335, acc: 94.8572, loss_bbox: 0.1856, loss_mask: 0.2008, loss: 0.5656 2023-11-14 00:38:58,343 - mmdet - INFO - Epoch [9][5700/7330] lr: 1.000e-05, eta: 2:55:14, time: 0.443, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0321, loss_cls: 0.1312, acc: 94.9619, loss_bbox: 0.1798, loss_mask: 0.1956, loss: 0.5500 2023-11-14 00:39:20,598 - mmdet - INFO - Epoch [9][5750/7330] lr: 1.000e-05, eta: 2:54:52, time: 0.445, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0330, loss_cls: 0.1283, acc: 94.9998, loss_bbox: 0.1787, loss_mask: 0.1918, loss: 0.5451 2023-11-14 00:39:42,890 - mmdet - INFO - Epoch [9][5800/7330] lr: 1.000e-05, eta: 2:54:30, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0333, loss_cls: 0.1346, acc: 94.8469, loss_bbox: 0.1832, loss_mask: 0.1978, loss: 0.5619 2023-11-14 00:40:04,863 - mmdet - INFO - Epoch [9][5850/7330] lr: 1.000e-05, eta: 2:54:07, time: 0.439, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0319, loss_cls: 0.1282, acc: 95.1167, loss_bbox: 0.1784, loss_mask: 0.1946, loss: 0.5448 2023-11-14 00:40:26,909 - mmdet - INFO - Epoch [9][5900/7330] lr: 1.000e-05, eta: 2:53:45, time: 0.441, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0322, loss_cls: 0.1293, acc: 95.0898, loss_bbox: 0.1795, loss_mask: 0.1998, loss: 0.5521 2023-11-14 00:40:49,113 - mmdet - INFO - Epoch [9][5950/7330] lr: 1.000e-05, eta: 2:53:23, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0336, loss_cls: 0.1360, acc: 94.6951, loss_bbox: 0.1927, loss_mask: 0.2030, loss: 0.5778 2023-11-14 00:41:11,416 - mmdet - INFO - Epoch [9][6000/7330] lr: 1.000e-05, eta: 2:53:00, time: 0.446, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0343, loss_cls: 0.1363, acc: 94.7178, loss_bbox: 0.1898, loss_mask: 0.2009, loss: 0.5745 2023-11-14 00:41:33,666 - mmdet - INFO - Epoch [9][6050/7330] lr: 1.000e-05, eta: 2:52:38, time: 0.445, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0323, loss_cls: 0.1267, acc: 95.1221, loss_bbox: 0.1798, loss_mask: 0.1973, loss: 0.5480 2023-11-14 00:41:55,935 - mmdet - INFO - Epoch [9][6100/7330] lr: 1.000e-05, eta: 2:52:16, time: 0.445, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0306, loss_cls: 0.1312, acc: 94.9976, loss_bbox: 0.1807, loss_mask: 0.1959, loss: 0.5498 2023-11-14 00:42:18,248 - mmdet - INFO - Epoch [9][6150/7330] lr: 1.000e-05, eta: 2:51:54, time: 0.446, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0348, loss_cls: 0.1367, acc: 94.7080, loss_bbox: 0.1875, loss_mask: 0.1999, loss: 0.5728 2023-11-14 00:42:40,656 - mmdet - INFO - Epoch [9][6200/7330] lr: 1.000e-05, eta: 2:51:31, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0326, loss_cls: 0.1334, acc: 94.8875, loss_bbox: 0.1857, loss_mask: 0.1970, loss: 0.5616 2023-11-14 00:43:02,863 - mmdet - INFO - Epoch [9][6250/7330] lr: 1.000e-05, eta: 2:51:09, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0326, loss_cls: 0.1325, acc: 94.8574, loss_bbox: 0.1859, loss_mask: 0.2027, loss: 0.5664 2023-11-14 00:43:25,210 - mmdet - INFO - Epoch [9][6300/7330] lr: 1.000e-05, eta: 2:50:47, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0343, loss_cls: 0.1308, acc: 94.9968, loss_bbox: 0.1833, loss_mask: 0.1983, loss: 0.5593 2023-11-14 00:43:47,413 - mmdet - INFO - Epoch [9][6350/7330] lr: 1.000e-05, eta: 2:50:25, time: 0.444, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0319, loss_cls: 0.1293, acc: 95.0264, loss_bbox: 0.1796, loss_mask: 0.1997, loss: 0.5522 2023-11-14 00:44:09,725 - mmdet - INFO - Epoch [9][6400/7330] lr: 1.000e-05, eta: 2:50:02, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0333, loss_cls: 0.1322, acc: 94.8501, loss_bbox: 0.1853, loss_mask: 0.1997, loss: 0.5632 2023-11-14 00:44:32,137 - mmdet - INFO - Epoch [9][6450/7330] lr: 1.000e-05, eta: 2:49:40, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0304, loss_cls: 0.1283, acc: 95.0776, loss_bbox: 0.1799, loss_mask: 0.1958, loss: 0.5460 2023-11-14 00:44:54,297 - mmdet - INFO - Epoch [9][6500/7330] lr: 1.000e-05, eta: 2:49:18, time: 0.443, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0335, loss_cls: 0.1352, acc: 94.8057, loss_bbox: 0.1879, loss_mask: 0.2007, loss: 0.5702 2023-11-14 00:45:16,463 - mmdet - INFO - Epoch [9][6550/7330] lr: 1.000e-05, eta: 2:48:56, time: 0.443, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0332, loss_cls: 0.1326, acc: 94.9941, loss_bbox: 0.1832, loss_mask: 0.2038, loss: 0.5654 2023-11-14 00:45:38,535 - mmdet - INFO - Epoch [9][6600/7330] lr: 1.000e-05, eta: 2:48:33, time: 0.441, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0326, loss_cls: 0.1325, acc: 94.8921, loss_bbox: 0.1845, loss_mask: 0.1992, loss: 0.5598 2023-11-14 00:46:00,958 - mmdet - INFO - Epoch [9][6650/7330] lr: 1.000e-05, eta: 2:48:11, time: 0.448, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0322, loss_cls: 0.1334, acc: 94.8621, loss_bbox: 0.1847, loss_mask: 0.1964, loss: 0.5600 2023-11-14 00:46:23,098 - mmdet - INFO - Epoch [9][6700/7330] lr: 1.000e-05, eta: 2:47:49, time: 0.443, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0323, loss_cls: 0.1250, acc: 95.1467, loss_bbox: 0.1769, loss_mask: 0.1953, loss: 0.5414 2023-11-14 00:46:45,628 - mmdet - INFO - Epoch [9][6750/7330] lr: 1.000e-05, eta: 2:47:27, time: 0.451, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0324, loss_cls: 0.1332, acc: 94.8044, loss_bbox: 0.1835, loss_mask: 0.2006, loss: 0.5621 2023-11-14 00:47:08,087 - mmdet - INFO - Epoch [9][6800/7330] lr: 1.000e-05, eta: 2:47:04, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0326, loss_cls: 0.1316, acc: 94.9128, loss_bbox: 0.1827, loss_mask: 0.1959, loss: 0.5550 2023-11-14 00:47:30,422 - mmdet - INFO - Epoch [9][6850/7330] lr: 1.000e-05, eta: 2:46:42, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0337, loss_cls: 0.1354, acc: 94.7888, loss_bbox: 0.1850, loss_mask: 0.2036, loss: 0.5708 2023-11-14 00:47:52,707 - mmdet - INFO - Epoch [9][6900/7330] lr: 1.000e-05, eta: 2:46:20, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0329, loss_cls: 0.1292, acc: 94.9734, loss_bbox: 0.1819, loss_mask: 0.1990, loss: 0.5545 2023-11-14 00:48:14,906 - mmdet - INFO - Epoch [9][6950/7330] lr: 1.000e-05, eta: 2:45:58, time: 0.444, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0333, loss_cls: 0.1310, acc: 94.9180, loss_bbox: 0.1851, loss_mask: 0.1965, loss: 0.5579 2023-11-14 00:48:37,195 - mmdet - INFO - Epoch [9][7000/7330] lr: 1.000e-05, eta: 2:45:35, time: 0.446, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0321, loss_cls: 0.1336, acc: 94.7817, loss_bbox: 0.1856, loss_mask: 0.1995, loss: 0.5632 2023-11-14 00:48:59,158 - mmdet - INFO - Epoch [9][7050/7330] lr: 1.000e-05, eta: 2:45:13, time: 0.439, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0303, loss_cls: 0.1278, acc: 95.1401, loss_bbox: 0.1781, loss_mask: 0.1944, loss: 0.5427 2023-11-14 00:49:21,514 - mmdet - INFO - Epoch [9][7100/7330] lr: 1.000e-05, eta: 2:44:51, time: 0.447, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0329, loss_cls: 0.1298, acc: 95.0762, loss_bbox: 0.1758, loss_mask: 0.1957, loss: 0.5466 2023-11-14 00:49:44,063 - mmdet - INFO - Epoch [9][7150/7330] lr: 1.000e-05, eta: 2:44:29, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0335, loss_cls: 0.1355, acc: 94.7446, loss_bbox: 0.1877, loss_mask: 0.2035, loss: 0.5737 2023-11-14 00:50:06,648 - mmdet - INFO - Epoch [9][7200/7330] lr: 1.000e-05, eta: 2:44:07, time: 0.452, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0347, loss_cls: 0.1358, acc: 94.7400, loss_bbox: 0.1882, loss_mask: 0.2011, loss: 0.5720 2023-11-14 00:50:29,104 - mmdet - INFO - Epoch [9][7250/7330] lr: 1.000e-05, eta: 2:43:44, time: 0.449, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0319, loss_cls: 0.1262, acc: 95.1243, loss_bbox: 0.1782, loss_mask: 0.1977, loss: 0.5465 2023-11-14 00:50:51,124 - mmdet - INFO - Epoch [9][7300/7330] lr: 1.000e-05, eta: 2:43:22, time: 0.440, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0314, loss_cls: 0.1285, acc: 95.1077, loss_bbox: 0.1729, loss_mask: 0.1963, loss: 0.5414 2023-11-14 00:51:05,093 - mmdet - INFO - Saving checkpoint at 9 epochs 2023-11-14 00:51:51,878 - mmdet - INFO - Evaluating bbox... 2023-11-14 00:52:22,562 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.498 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.714 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.546 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.320 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.540 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 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.421 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.657 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.768 2023-11-14 00:52:22,565 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.590 | bicycle | 0.391 | car | 0.499 | | motorcycle | 0.505 | airplane | 0.709 | bus | 0.708 | | train | 0.705 | truck | 0.470 | boat | 0.336 | | traffic light | 0.315 | fire hydrant | 0.754 | stop sign | 0.685 | | parking meter | 0.562 | bench | 0.321 | bird | 0.423 | | cat | 0.750 | dog | 0.693 | horse | 0.641 | | sheep | 0.605 | cow | 0.656 | elephant | 0.717 | | bear | 0.769 | zebra | 0.687 | giraffe | 0.717 | | backpack | 0.243 | umbrella | 0.475 | handbag | 0.261 | | tie | 0.416 | suitcase | 0.494 | frisbee | 0.705 | | skis | 0.311 | snowboard | 0.489 | sports ball | 0.491 | | kite | 0.470 | baseball bat | 0.454 | baseball glove | 0.458 | | skateboard | 0.610 | surfboard | 0.478 | tennis racket | 0.566 | | bottle | 0.474 | wine glass | 0.424 | cup | 0.517 | | fork | 0.483 | knife | 0.306 | spoon | 0.302 | | bowl | 0.473 | banana | 0.296 | apple | 0.273 | | sandwich | 0.482 | orange | 0.377 | broccoli | 0.261 | | carrot | 0.266 | hot dog | 0.455 | pizza | 0.574 | | donut | 0.578 | cake | 0.460 | chair | 0.376 | | couch | 0.490 | potted plant | 0.359 | bed | 0.485 | | dining table | 0.334 | toilet | 0.675 | tv | 0.647 | | laptop | 0.701 | mouse | 0.660 | remote | 0.434 | | keyboard | 0.572 | cell phone | 0.460 | microwave | 0.626 | | oven | 0.413 | toaster | 0.511 | sink | 0.461 | | refrigerator | 0.687 | book | 0.206 | clock | 0.528 | | vase | 0.426 | scissors | 0.417 | teddy bear | 0.563 | | hair drier | 0.272 | toothbrush | 0.383 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:52:22,565 - mmdet - INFO - Evaluating segm... 2023-11-14 00:52:52,382 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.444 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.685 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.477 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.242 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.479 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.635 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.363 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.718 2023-11-14 00:52:52,384 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.513 | bicycle | 0.231 | car | 0.459 | | motorcycle | 0.401 | airplane | 0.542 | bus | 0.685 | | train | 0.687 | truck | 0.447 | boat | 0.317 | | traffic light | 0.302 | fire hydrant | 0.712 | stop sign | 0.669 | | parking meter | 0.544 | bench | 0.245 | bird | 0.353 | | cat | 0.731 | dog | 0.646 | horse | 0.481 | | sheep | 0.540 | cow | 0.554 | elephant | 0.643 | | bear | 0.748 | zebra | 0.592 | giraffe | 0.547 | | backpack | 0.233 | umbrella | 0.521 | handbag | 0.240 | | tie | 0.381 | suitcase | 0.508 | frisbee | 0.668 | | skis | 0.060 | snowboard | 0.305 | sports ball | 0.493 | | kite | 0.344 | baseball bat | 0.328 | baseball glove | 0.467 | | skateboard | 0.386 | surfboard | 0.398 | tennis racket | 0.583 | | bottle | 0.455 | wine glass | 0.379 | cup | 0.513 | | fork | 0.252 | knife | 0.219 | spoon | 0.221 | | bowl | 0.438 | banana | 0.251 | apple | 0.272 | | sandwich | 0.499 | orange | 0.370 | broccoli | 0.238 | | carrot | 0.230 | hot dog | 0.353 | pizza | 0.552 | | donut | 0.569 | cake | 0.465 | chair | 0.268 | | couch | 0.413 | potted plant | 0.305 | bed | 0.388 | | dining table | 0.195 | toilet | 0.643 | tv | 0.665 | | laptop | 0.678 | mouse | 0.648 | remote | 0.385 | | keyboard | 0.551 | cell phone | 0.436 | microwave | 0.650 | | oven | 0.381 | toaster | 0.538 | sink | 0.422 | | refrigerator | 0.695 | book | 0.157 | clock | 0.530 | | vase | 0.415 | scissors | 0.325 | teddy bear | 0.530 | | hair drier | 0.238 | toothbrush | 0.246 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 00:52:52,795 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_7.pth was removed 2023-11-14 00:52:56,466 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_9.pth. 2023-11-14 00:52:56,467 - mmdet - INFO - Best bbox_mAP is 0.4977 at 9 epoch. 2023-11-14 00:52:56,467 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 00:52:56,467 - mmdet - INFO - Epoch(val) [9][625] bbox_mAP: 0.4977, bbox_mAP_50: 0.7143, bbox_mAP_75: 0.5457, bbox_mAP_s: 0.3195, bbox_mAP_m: 0.5397, bbox_mAP_l: 0.6460, bbox_mAP_copypaste: 0.4977 0.7143 0.5457 0.3195 0.5397 0.6460, segm_mAP: 0.4436, segm_mAP_50: 0.6845, segm_mAP_75: 0.4772, segm_mAP_s: 0.2419, segm_mAP_m: 0.4795, segm_mAP_l: 0.6346, segm_mAP_copypaste: 0.4436 0.6845 0.4772 0.2419 0.4795 0.6346 2023-11-14 00:53:23,235 - mmdet - INFO - Epoch [10][50/7330] lr: 1.000e-05, eta: 2:42:43, time: 0.535, data_time: 0.092, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0324, loss_cls: 0.1287, acc: 94.9792, loss_bbox: 0.1827, loss_mask: 0.1978, loss: 0.5536 2023-11-14 00:53:46,855 - mmdet - INFO - Epoch [10][100/7330] lr: 1.000e-05, eta: 2:42:22, time: 0.472, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0343, loss_cls: 0.1369, acc: 94.6838, loss_bbox: 0.1916, loss_mask: 0.2021, loss: 0.5788 2023-11-14 00:54:09,653 - mmdet - INFO - Epoch [10][150/7330] lr: 1.000e-05, eta: 2:42:00, time: 0.456, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0325, loss_cls: 0.1271, acc: 95.1030, loss_bbox: 0.1795, loss_mask: 0.1962, loss: 0.5467 2023-11-14 00:54:32,864 - mmdet - INFO - Epoch [10][200/7330] lr: 1.000e-05, eta: 2:41:38, time: 0.464, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0329, loss_cls: 0.1301, acc: 95.0210, loss_bbox: 0.1842, loss_mask: 0.1976, loss: 0.5571 2023-11-14 00:54:55,355 - mmdet - INFO - Epoch [10][250/7330] lr: 1.000e-05, eta: 2:41:15, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0308, loss_cls: 0.1242, acc: 95.1643, loss_bbox: 0.1766, loss_mask: 0.1927, loss: 0.5358 2023-11-14 00:55:17,752 - mmdet - INFO - Epoch [10][300/7330] lr: 1.000e-05, eta: 2:40:53, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0311, loss_cls: 0.1194, acc: 95.4065, loss_bbox: 0.1686, loss_mask: 0.1936, loss: 0.5249 2023-11-14 00:55:40,528 - mmdet - INFO - Epoch [10][350/7330] lr: 1.000e-05, eta: 2:40:31, time: 0.455, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0317, loss_cls: 0.1270, acc: 95.0049, loss_bbox: 0.1818, loss_mask: 0.1974, loss: 0.5494 2023-11-14 00:56:03,411 - mmdet - INFO - Epoch [10][400/7330] lr: 1.000e-05, eta: 2:40:09, time: 0.458, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0339, loss_cls: 0.1354, acc: 94.8113, loss_bbox: 0.1900, loss_mask: 0.2027, loss: 0.5753 2023-11-14 00:56:26,314 - mmdet - INFO - Epoch [10][450/7330] lr: 1.000e-05, eta: 2:39:47, time: 0.458, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0342, loss_cls: 0.1274, acc: 95.0730, loss_bbox: 0.1838, loss_mask: 0.2017, loss: 0.5590 2023-11-14 00:56:49,386 - mmdet - INFO - Epoch [10][500/7330] lr: 1.000e-05, eta: 2:39:25, time: 0.461, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0343, loss_cls: 0.1390, acc: 94.5056, loss_bbox: 0.1907, loss_mask: 0.1993, loss: 0.5775 2023-11-14 00:57:12,254 - mmdet - INFO - Epoch [10][550/7330] lr: 1.000e-05, eta: 2:39:03, time: 0.457, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0342, loss_cls: 0.1334, acc: 94.8738, loss_bbox: 0.1819, loss_mask: 0.1984, loss: 0.5618 2023-11-14 00:57:35,163 - mmdet - INFO - Epoch [10][600/7330] lr: 1.000e-05, eta: 2:38:41, time: 0.458, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0319, loss_cls: 0.1279, acc: 95.0703, loss_bbox: 0.1817, loss_mask: 0.1955, loss: 0.5497 2023-11-14 00:57:58,001 - mmdet - INFO - Epoch [10][650/7330] lr: 1.000e-05, eta: 2:38:19, time: 0.457, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0342, loss_cls: 0.1352, acc: 94.7729, loss_bbox: 0.1885, loss_mask: 0.1986, loss: 0.5692 2023-11-14 00:58:20,942 - mmdet - INFO - Epoch [10][700/7330] lr: 1.000e-05, eta: 2:37:57, time: 0.459, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0321, loss_cls: 0.1292, acc: 95.0530, loss_bbox: 0.1756, loss_mask: 0.1946, loss: 0.5433 2023-11-14 00:58:43,957 - mmdet - INFO - Epoch [10][750/7330] lr: 1.000e-05, eta: 2:37:35, time: 0.460, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0332, loss_cls: 0.1310, acc: 94.9426, loss_bbox: 0.1821, loss_mask: 0.1958, loss: 0.5545 2023-11-14 00:59:06,743 - mmdet - INFO - Epoch [10][800/7330] lr: 1.000e-05, eta: 2:37:13, time: 0.456, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0318, loss_cls: 0.1252, acc: 95.1731, loss_bbox: 0.1798, loss_mask: 0.1941, loss: 0.5419 2023-11-14 00:59:29,164 - mmdet - INFO - Epoch [10][850/7330] lr: 1.000e-05, eta: 2:36:51, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0321, loss_cls: 0.1295, acc: 94.9829, loss_bbox: 0.1780, loss_mask: 0.1970, loss: 0.5483 2023-11-14 00:59:51,862 - mmdet - INFO - Epoch [10][900/7330] lr: 1.000e-05, eta: 2:36:28, time: 0.454, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0325, loss_cls: 0.1254, acc: 95.1760, loss_bbox: 0.1789, loss_mask: 0.1929, loss: 0.5411 2023-11-14 01:00:14,167 - mmdet - INFO - Epoch [10][950/7330] lr: 1.000e-05, eta: 2:36:06, time: 0.446, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1311, acc: 94.9287, loss_bbox: 0.1866, loss_mask: 0.1986, loss: 0.5614 2023-11-14 01:00:37,359 - mmdet - INFO - Epoch [10][1000/7330] lr: 1.000e-05, eta: 2:35:44, time: 0.464, data_time: 0.031, memory: 5732, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0367, loss_cls: 0.1432, acc: 94.4546, loss_bbox: 0.1982, loss_mask: 0.2077, loss: 0.5999 2023-11-14 01:00:59,700 - mmdet - INFO - Epoch [10][1050/7330] lr: 1.000e-05, eta: 2:35:22, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0315, loss_cls: 0.1261, acc: 95.1304, loss_bbox: 0.1805, loss_mask: 0.1950, loss: 0.5452 2023-11-14 01:01:22,358 - mmdet - INFO - Epoch [10][1100/7330] lr: 1.000e-05, eta: 2:35:00, time: 0.453, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0333, loss_cls: 0.1283, acc: 95.0623, loss_bbox: 0.1795, loss_mask: 0.1958, loss: 0.5497 2023-11-14 01:01:45,118 - mmdet - INFO - Epoch [10][1150/7330] lr: 1.000e-05, eta: 2:34:38, time: 0.455, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0339, loss_cls: 0.1366, acc: 94.7036, loss_bbox: 0.1915, loss_mask: 0.1986, loss: 0.5734 2023-11-14 01:02:07,448 - mmdet - INFO - Epoch [10][1200/7330] lr: 1.000e-05, eta: 2:34:16, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0320, loss_cls: 0.1299, acc: 95.0281, loss_bbox: 0.1831, loss_mask: 0.1999, loss: 0.5574 2023-11-14 01:02:29,860 - mmdet - INFO - Epoch [10][1250/7330] lr: 1.000e-05, eta: 2:33:53, time: 0.448, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0324, loss_cls: 0.1342, acc: 94.7988, loss_bbox: 0.1871, loss_mask: 0.1995, loss: 0.5657 2023-11-14 01:02:52,065 - mmdet - INFO - Epoch [10][1300/7330] lr: 1.000e-05, eta: 2:33:31, time: 0.444, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0309, loss_cls: 0.1239, acc: 95.1997, loss_bbox: 0.1766, loss_mask: 0.1963, loss: 0.5392 2023-11-14 01:03:14,811 - mmdet - INFO - Epoch [10][1350/7330] lr: 1.000e-05, eta: 2:33:09, time: 0.455, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0318, loss_cls: 0.1286, acc: 95.0142, loss_bbox: 0.1806, loss_mask: 0.1972, loss: 0.5514 2023-11-14 01:03:37,484 - mmdet - INFO - Epoch [10][1400/7330] lr: 1.000e-05, eta: 2:32:47, time: 0.454, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0331, loss_cls: 0.1310, acc: 94.9746, loss_bbox: 0.1839, loss_mask: 0.1999, loss: 0.5616 2023-11-14 01:03:59,942 - mmdet - INFO - Epoch [10][1450/7330] lr: 1.000e-05, eta: 2:32:25, time: 0.449, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0325, loss_cls: 0.1319, acc: 94.9038, loss_bbox: 0.1848, loss_mask: 0.2037, loss: 0.5653 2023-11-14 01:04:22,262 - mmdet - INFO - Epoch [10][1500/7330] lr: 1.000e-05, eta: 2:32:02, time: 0.446, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0321, loss_cls: 0.1277, acc: 95.0923, loss_bbox: 0.1780, loss_mask: 0.1950, loss: 0.5449 2023-11-14 01:04:44,577 - mmdet - INFO - Epoch [10][1550/7330] lr: 1.000e-05, eta: 2:31:40, time: 0.446, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0333, loss_cls: 0.1301, acc: 94.9910, loss_bbox: 0.1806, loss_mask: 0.1950, loss: 0.5514 2023-11-14 01:05:07,231 - mmdet - INFO - Epoch [10][1600/7330] lr: 1.000e-05, eta: 2:31:18, time: 0.453, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0325, loss_cls: 0.1307, acc: 94.9800, loss_bbox: 0.1833, loss_mask: 0.1978, loss: 0.5556 2023-11-14 01:05:30,363 - mmdet - INFO - Epoch [10][1650/7330] lr: 1.000e-05, eta: 2:30:56, time: 0.463, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0313, loss_cls: 0.1320, acc: 94.8623, loss_bbox: 0.1822, loss_mask: 0.1944, loss: 0.5524 2023-11-14 01:05:52,733 - mmdet - INFO - Epoch [10][1700/7330] lr: 1.000e-05, eta: 2:30:34, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0309, loss_cls: 0.1258, acc: 95.1541, loss_bbox: 0.1777, loss_mask: 0.1991, loss: 0.5460 2023-11-14 01:06:14,998 - mmdet - INFO - Epoch [10][1750/7330] lr: 1.000e-05, eta: 2:30:11, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0343, loss_cls: 0.1327, acc: 94.8691, loss_bbox: 0.1855, loss_mask: 0.1983, loss: 0.5625 2023-11-14 01:06:37,787 - mmdet - INFO - Epoch [10][1800/7330] lr: 1.000e-05, eta: 2:29:49, time: 0.456, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0330, loss_cls: 0.1294, acc: 94.9788, loss_bbox: 0.1838, loss_mask: 0.2005, loss: 0.5592 2023-11-14 01:07:00,671 - mmdet - INFO - Epoch [10][1850/7330] lr: 1.000e-05, eta: 2:29:27, time: 0.458, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0320, loss_cls: 0.1243, acc: 95.1824, loss_bbox: 0.1770, loss_mask: 0.1982, loss: 0.5422 2023-11-14 01:07:23,302 - mmdet - INFO - Epoch [10][1900/7330] lr: 1.000e-05, eta: 2:29:05, time: 0.453, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0344, loss_cls: 0.1324, acc: 94.8784, loss_bbox: 0.1832, loss_mask: 0.1945, loss: 0.5567 2023-11-14 01:07:45,389 - mmdet - INFO - Epoch [10][1950/7330] lr: 1.000e-05, eta: 2:28:43, time: 0.442, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0321, loss_cls: 0.1230, acc: 95.2285, loss_bbox: 0.1725, loss_mask: 0.1962, loss: 0.5371 2023-11-14 01:08:07,948 - mmdet - INFO - Epoch [10][2000/7330] lr: 1.000e-05, eta: 2:28:21, time: 0.451, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0331, loss_cls: 0.1282, acc: 94.9839, loss_bbox: 0.1813, loss_mask: 0.2016, loss: 0.5567 2023-11-14 01:08:30,674 - mmdet - INFO - Epoch [10][2050/7330] lr: 1.000e-05, eta: 2:27:58, time: 0.454, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0327, loss_cls: 0.1261, acc: 95.1331, loss_bbox: 0.1801, loss_mask: 0.1956, loss: 0.5467 2023-11-14 01:08:53,307 - mmdet - INFO - Epoch [10][2100/7330] lr: 1.000e-05, eta: 2:27:36, time: 0.453, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0351, loss_cls: 0.1351, acc: 94.7153, loss_bbox: 0.1886, loss_mask: 0.2026, loss: 0.5748 2023-11-14 01:09:15,836 - mmdet - INFO - Epoch [10][2150/7330] lr: 1.000e-05, eta: 2:27:14, time: 0.451, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0316, loss_cls: 0.1266, acc: 95.0537, loss_bbox: 0.1781, loss_mask: 0.1927, loss: 0.5403 2023-11-14 01:09:38,313 - mmdet - INFO - Epoch [10][2200/7330] lr: 1.000e-05, eta: 2:26:52, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0318, loss_cls: 0.1249, acc: 95.1221, loss_bbox: 0.1776, loss_mask: 0.1993, loss: 0.5452 2023-11-14 01:10:00,911 - mmdet - INFO - Epoch [10][2250/7330] lr: 1.000e-05, eta: 2:26:30, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0329, loss_cls: 0.1325, acc: 94.9153, loss_bbox: 0.1867, loss_mask: 0.1993, loss: 0.5644 2023-11-14 01:10:23,534 - mmdet - INFO - Epoch [10][2300/7330] lr: 1.000e-05, eta: 2:26:08, time: 0.452, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0315, loss_cls: 0.1253, acc: 95.0586, loss_bbox: 0.1800, loss_mask: 0.1970, loss: 0.5462 2023-11-14 01:10:45,853 - mmdet - INFO - Epoch [10][2350/7330] lr: 1.000e-05, eta: 2:25:45, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0322, loss_cls: 0.1266, acc: 95.1562, loss_bbox: 0.1734, loss_mask: 0.1936, loss: 0.5376 2023-11-14 01:11:08,297 - mmdet - INFO - Epoch [10][2400/7330] lr: 1.000e-05, eta: 2:25:23, time: 0.449, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0321, loss_cls: 0.1243, acc: 95.1970, loss_bbox: 0.1736, loss_mask: 0.1927, loss: 0.5355 2023-11-14 01:11:31,236 - mmdet - INFO - Epoch [10][2450/7330] lr: 1.000e-05, eta: 2:25:01, time: 0.459, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0321, loss_cls: 0.1252, acc: 95.1653, loss_bbox: 0.1768, loss_mask: 0.1940, loss: 0.5406 2023-11-14 01:11:53,471 - mmdet - INFO - Epoch [10][2500/7330] lr: 1.000e-05, eta: 2:24:39, time: 0.445, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0334, loss_cls: 0.1266, acc: 95.1963, loss_bbox: 0.1808, loss_mask: 0.1948, loss: 0.5480 2023-11-14 01:12:16,076 - mmdet - INFO - Epoch [10][2550/7330] lr: 1.000e-05, eta: 2:24:17, time: 0.452, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0341, loss_cls: 0.1339, acc: 94.8396, loss_bbox: 0.1880, loss_mask: 0.2037, loss: 0.5727 2023-11-14 01:12:38,521 - mmdet - INFO - Epoch [10][2600/7330] lr: 1.000e-05, eta: 2:23:54, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0319, loss_cls: 0.1259, acc: 95.2195, loss_bbox: 0.1785, loss_mask: 0.1969, loss: 0.5460 2023-11-14 01:13:01,255 - mmdet - INFO - Epoch [10][2650/7330] lr: 1.000e-05, eta: 2:23:32, time: 0.455, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0314, loss_cls: 0.1252, acc: 95.2097, loss_bbox: 0.1758, loss_mask: 0.2004, loss: 0.5438 2023-11-14 01:13:23,553 - mmdet - INFO - Epoch [10][2700/7330] lr: 1.000e-05, eta: 2:23:10, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0323, loss_cls: 0.1230, acc: 95.2361, loss_bbox: 0.1753, loss_mask: 0.1914, loss: 0.5340 2023-11-14 01:13:46,255 - mmdet - INFO - Epoch [10][2750/7330] lr: 1.000e-05, eta: 2:22:48, time: 0.454, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0330, loss_cls: 0.1306, acc: 94.8730, loss_bbox: 0.1846, loss_mask: 0.2044, loss: 0.5644 2023-11-14 01:14:08,732 - mmdet - INFO - Epoch [10][2800/7330] lr: 1.000e-05, eta: 2:22:26, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0332, loss_cls: 0.1329, acc: 94.9678, loss_bbox: 0.1858, loss_mask: 0.1969, loss: 0.5610 2023-11-14 01:14:31,523 - mmdet - INFO - Epoch [10][2850/7330] lr: 1.000e-05, eta: 2:22:04, time: 0.456, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0360, loss_cls: 0.1340, acc: 94.8906, loss_bbox: 0.1837, loss_mask: 0.1970, loss: 0.5630 2023-11-14 01:14:54,216 - mmdet - INFO - Epoch [10][2900/7330] lr: 1.000e-05, eta: 2:21:41, time: 0.454, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0313, loss_cls: 0.1256, acc: 95.2375, loss_bbox: 0.1757, loss_mask: 0.1972, loss: 0.5423 2023-11-14 01:15:16,703 - mmdet - INFO - Epoch [10][2950/7330] lr: 1.000e-05, eta: 2:21:19, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0318, loss_cls: 0.1263, acc: 95.0820, loss_bbox: 0.1781, loss_mask: 0.1962, loss: 0.5436 2023-11-14 01:15:39,050 - mmdet - INFO - Epoch [10][3000/7330] lr: 1.000e-05, eta: 2:20:57, time: 0.447, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0307, loss_cls: 0.1264, acc: 95.1414, loss_bbox: 0.1750, loss_mask: 0.1916, loss: 0.5361 2023-11-14 01:16:01,601 - mmdet - INFO - Epoch [10][3050/7330] lr: 1.000e-05, eta: 2:20:35, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0325, loss_cls: 0.1338, acc: 94.8701, loss_bbox: 0.1869, loss_mask: 0.1942, loss: 0.5595 2023-11-14 01:16:24,405 - mmdet - INFO - Epoch [10][3100/7330] lr: 1.000e-05, eta: 2:20:13, time: 0.456, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0331, loss_cls: 0.1362, acc: 94.7363, loss_bbox: 0.1858, loss_mask: 0.1974, loss: 0.5649 2023-11-14 01:16:47,018 - mmdet - INFO - Epoch [10][3150/7330] lr: 1.000e-05, eta: 2:19:50, time: 0.452, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0334, loss_cls: 0.1288, acc: 94.9612, loss_bbox: 0.1816, loss_mask: 0.1961, loss: 0.5508 2023-11-14 01:17:09,671 - mmdet - INFO - Epoch [10][3200/7330] lr: 1.000e-05, eta: 2:19:28, time: 0.453, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1309, acc: 94.9573, loss_bbox: 0.1833, loss_mask: 0.1983, loss: 0.5575 2023-11-14 01:17:31,951 - mmdet - INFO - Epoch [10][3250/7330] lr: 1.000e-05, eta: 2:19:06, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0330, loss_cls: 0.1267, acc: 95.0947, loss_bbox: 0.1794, loss_mask: 0.1958, loss: 0.5470 2023-11-14 01:17:54,412 - mmdet - INFO - Epoch [10][3300/7330] lr: 1.000e-05, eta: 2:18:44, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1323, acc: 94.8525, loss_bbox: 0.1854, loss_mask: 0.1968, loss: 0.5594 2023-11-14 01:18:16,655 - mmdet - INFO - Epoch [10][3350/7330] lr: 1.000e-05, eta: 2:18:22, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0327, loss_cls: 0.1255, acc: 95.1345, loss_bbox: 0.1766, loss_mask: 0.1931, loss: 0.5397 2023-11-14 01:18:39,625 - mmdet - INFO - Epoch [10][3400/7330] lr: 1.000e-05, eta: 2:17:59, time: 0.459, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0319, loss_cls: 0.1251, acc: 95.1399, loss_bbox: 0.1756, loss_mask: 0.1922, loss: 0.5372 2023-11-14 01:19:01,805 - mmdet - INFO - Epoch [10][3450/7330] lr: 1.000e-05, eta: 2:17:37, time: 0.444, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0307, loss_cls: 0.1202, acc: 95.3508, loss_bbox: 0.1731, loss_mask: 0.1963, loss: 0.5311 2023-11-14 01:19:24,226 - mmdet - INFO - Epoch [10][3500/7330] lr: 1.000e-05, eta: 2:17:15, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0308, loss_cls: 0.1247, acc: 95.1943, loss_bbox: 0.1721, loss_mask: 0.1965, loss: 0.5363 2023-11-14 01:19:46,478 - mmdet - INFO - Epoch [10][3550/7330] lr: 1.000e-05, eta: 2:16:53, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0329, loss_cls: 0.1295, acc: 95.0654, loss_bbox: 0.1785, loss_mask: 0.1959, loss: 0.5499 2023-11-14 01:20:09,362 - mmdet - INFO - Epoch [10][3600/7330] lr: 1.000e-05, eta: 2:16:31, time: 0.458, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0318, loss_cls: 0.1244, acc: 95.1980, loss_bbox: 0.1700, loss_mask: 0.1888, loss: 0.5276 2023-11-14 01:20:31,669 - mmdet - INFO - Epoch [10][3650/7330] lr: 1.000e-05, eta: 2:16:08, time: 0.446, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0307, loss_cls: 0.1271, acc: 95.1646, loss_bbox: 0.1787, loss_mask: 0.1975, loss: 0.5446 2023-11-14 01:20:54,348 - mmdet - INFO - Epoch [10][3700/7330] lr: 1.000e-05, eta: 2:15:46, time: 0.454, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0326, loss_cls: 0.1354, acc: 94.7104, loss_bbox: 0.1883, loss_mask: 0.2019, loss: 0.5706 2023-11-14 01:21:17,255 - mmdet - INFO - Epoch [10][3750/7330] lr: 1.000e-05, eta: 2:15:24, time: 0.458, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0309, loss_cls: 0.1287, acc: 95.0454, loss_bbox: 0.1810, loss_mask: 0.1962, loss: 0.5494 2023-11-14 01:21:39,837 - mmdet - INFO - Epoch [10][3800/7330] lr: 1.000e-05, eta: 2:15:02, time: 0.452, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0327, loss_cls: 0.1343, acc: 94.8037, loss_bbox: 0.1877, loss_mask: 0.2045, loss: 0.5711 2023-11-14 01:22:02,435 - mmdet - INFO - Epoch [10][3850/7330] lr: 1.000e-05, eta: 2:14:40, time: 0.452, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0319, loss_cls: 0.1323, acc: 94.8806, loss_bbox: 0.1859, loss_mask: 0.2004, loss: 0.5632 2023-11-14 01:22:25,102 - mmdet - INFO - Epoch [10][3900/7330] lr: 1.000e-05, eta: 2:14:17, time: 0.453, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0323, loss_cls: 0.1243, acc: 95.1653, loss_bbox: 0.1734, loss_mask: 0.1927, loss: 0.5348 2023-11-14 01:22:48,006 - mmdet - INFO - Epoch [10][3950/7330] lr: 1.000e-05, eta: 2:13:55, time: 0.458, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0342, loss_cls: 0.1323, acc: 94.8621, loss_bbox: 0.1834, loss_mask: 0.1959, loss: 0.5591 2023-11-14 01:23:10,141 - mmdet - INFO - Epoch [10][4000/7330] lr: 1.000e-05, eta: 2:13:33, time: 0.443, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0312, loss_cls: 0.1245, acc: 95.1677, loss_bbox: 0.1773, loss_mask: 0.1919, loss: 0.5357 2023-11-14 01:23:32,480 - mmdet - INFO - Epoch [10][4050/7330] lr: 1.000e-05, eta: 2:13:11, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0331, loss_cls: 0.1287, acc: 95.0203, loss_bbox: 0.1791, loss_mask: 0.1973, loss: 0.5506 2023-11-14 01:23:55,060 - mmdet - INFO - Epoch [10][4100/7330] lr: 1.000e-05, eta: 2:12:49, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0140, loss_rpn_bbox: 0.0362, loss_cls: 0.1405, acc: 94.5244, loss_bbox: 0.1965, loss_mask: 0.2025, loss: 0.5897 2023-11-14 01:24:17,722 - mmdet - INFO - Epoch [10][4150/7330] lr: 1.000e-05, eta: 2:12:26, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0333, loss_cls: 0.1321, acc: 94.8743, loss_bbox: 0.1845, loss_mask: 0.2026, loss: 0.5652 2023-11-14 01:24:40,146 - mmdet - INFO - Epoch [10][4200/7330] lr: 1.000e-05, eta: 2:12:04, time: 0.448, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0331, loss_cls: 0.1306, acc: 94.9268, loss_bbox: 0.1848, loss_mask: 0.2023, loss: 0.5633 2023-11-14 01:25:02,465 - mmdet - INFO - Epoch [10][4250/7330] lr: 1.000e-05, eta: 2:11:42, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0312, loss_cls: 0.1269, acc: 95.0862, loss_bbox: 0.1756, loss_mask: 0.1993, loss: 0.5448 2023-11-14 01:25:25,143 - mmdet - INFO - Epoch [10][4300/7330] lr: 1.000e-05, eta: 2:11:20, time: 0.454, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0334, loss_cls: 0.1328, acc: 94.9614, loss_bbox: 0.1876, loss_mask: 0.2011, loss: 0.5686 2023-11-14 01:25:47,995 - mmdet - INFO - Epoch [10][4350/7330] lr: 1.000e-05, eta: 2:10:58, time: 0.457, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0346, loss_cls: 0.1331, acc: 94.8948, loss_bbox: 0.1867, loss_mask: 0.1982, loss: 0.5656 2023-11-14 01:26:10,639 - mmdet - INFO - Epoch [10][4400/7330] lr: 1.000e-05, eta: 2:10:35, time: 0.453, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0333, loss_cls: 0.1306, acc: 95.0090, loss_bbox: 0.1798, loss_mask: 0.1964, loss: 0.5524 2023-11-14 01:26:33,193 - mmdet - INFO - Epoch [10][4450/7330] lr: 1.000e-05, eta: 2:10:13, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0313, loss_cls: 0.1266, acc: 95.1392, loss_bbox: 0.1773, loss_mask: 0.1947, loss: 0.5417 2023-11-14 01:26:55,552 - mmdet - INFO - Epoch [10][4500/7330] lr: 1.000e-05, eta: 2:09:51, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0291, loss_cls: 0.1236, acc: 95.2446, loss_bbox: 0.1786, loss_mask: 0.1958, loss: 0.5380 2023-11-14 01:27:17,670 - mmdet - INFO - Epoch [10][4550/7330] lr: 1.000e-05, eta: 2:09:29, time: 0.442, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0299, loss_cls: 0.1212, acc: 95.3474, loss_bbox: 0.1705, loss_mask: 0.1931, loss: 0.5262 2023-11-14 01:27:39,689 - mmdet - INFO - Epoch [10][4600/7330] lr: 1.000e-05, eta: 2:09:06, time: 0.440, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0304, loss_cls: 0.1253, acc: 95.1946, loss_bbox: 0.1773, loss_mask: 0.1959, loss: 0.5406 2023-11-14 01:28:01,958 - mmdet - INFO - Epoch [10][4650/7330] lr: 1.000e-05, eta: 2:08:44, time: 0.445, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0314, loss_cls: 0.1231, acc: 95.3081, loss_bbox: 0.1764, loss_mask: 0.1966, loss: 0.5391 2023-11-14 01:28:24,579 - mmdet - INFO - Epoch [10][4700/7330] lr: 1.000e-05, eta: 2:08:22, time: 0.452, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0319, loss_cls: 0.1301, acc: 94.9658, loss_bbox: 0.1811, loss_mask: 0.1935, loss: 0.5485 2023-11-14 01:28:46,954 - mmdet - INFO - Epoch [10][4750/7330] lr: 1.000e-05, eta: 2:08:00, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0314, loss_cls: 0.1301, acc: 95.0405, loss_bbox: 0.1816, loss_mask: 0.1974, loss: 0.5532 2023-11-14 01:29:09,705 - mmdet - INFO - Epoch [10][4800/7330] lr: 1.000e-05, eta: 2:07:37, time: 0.455, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0133, loss_rpn_bbox: 0.0336, loss_cls: 0.1324, acc: 94.9749, loss_bbox: 0.1822, loss_mask: 0.1999, loss: 0.5613 2023-11-14 01:29:32,139 - mmdet - INFO - Epoch [10][4850/7330] lr: 1.000e-05, eta: 2:07:15, time: 0.449, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0332, loss_cls: 0.1293, acc: 95.0386, loss_bbox: 0.1838, loss_mask: 0.1974, loss: 0.5563 2023-11-14 01:29:54,458 - mmdet - INFO - Epoch [10][4900/7330] lr: 1.000e-05, eta: 2:06:53, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0305, loss_cls: 0.1237, acc: 95.2117, loss_bbox: 0.1761, loss_mask: 0.1955, loss: 0.5375 2023-11-14 01:30:16,899 - mmdet - INFO - Epoch [10][4950/7330] lr: 1.000e-05, eta: 2:06:31, time: 0.449, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0297, loss_cls: 0.1215, acc: 95.2937, loss_bbox: 0.1708, loss_mask: 0.1908, loss: 0.5234 2023-11-14 01:30:39,508 - mmdet - INFO - Epoch [10][5000/7330] lr: 1.000e-05, eta: 2:06:09, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0346, loss_cls: 0.1317, acc: 94.9294, loss_bbox: 0.1892, loss_mask: 0.2003, loss: 0.5678 2023-11-14 01:31:01,804 - mmdet - INFO - Epoch [10][5050/7330] lr: 1.000e-05, eta: 2:05:46, time: 0.446, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0301, loss_cls: 0.1231, acc: 95.2417, loss_bbox: 0.1735, loss_mask: 0.1981, loss: 0.5358 2023-11-14 01:31:24,100 - mmdet - INFO - Epoch [10][5100/7330] lr: 1.000e-05, eta: 2:05:24, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0332, loss_cls: 0.1308, acc: 94.8457, loss_bbox: 0.1802, loss_mask: 0.1944, loss: 0.5488 2023-11-14 01:31:46,215 - mmdet - INFO - Epoch [10][5150/7330] lr: 1.000e-05, eta: 2:05:02, time: 0.442, data_time: 0.019, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0308, loss_cls: 0.1228, acc: 95.2241, loss_bbox: 0.1748, loss_mask: 0.1914, loss: 0.5315 2023-11-14 01:32:08,638 - mmdet - INFO - Epoch [10][5200/7330] lr: 1.000e-05, eta: 2:04:39, time: 0.448, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0337, loss_cls: 0.1246, acc: 95.2029, loss_bbox: 0.1734, loss_mask: 0.1933, loss: 0.5368 2023-11-14 01:32:30,848 - mmdet - INFO - Epoch [10][5250/7330] lr: 1.000e-05, eta: 2:04:17, time: 0.444, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0321, loss_cls: 0.1314, acc: 94.9956, loss_bbox: 0.1783, loss_mask: 0.1950, loss: 0.5495 2023-11-14 01:32:53,329 - mmdet - INFO - Epoch [10][5300/7330] lr: 1.000e-05, eta: 2:03:55, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0330, loss_cls: 0.1300, acc: 94.9749, loss_bbox: 0.1836, loss_mask: 0.1956, loss: 0.5540 2023-11-14 01:33:15,676 - mmdet - INFO - Epoch [10][5350/7330] lr: 1.000e-05, eta: 2:03:33, time: 0.447, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0323, loss_cls: 0.1243, acc: 95.1785, loss_bbox: 0.1764, loss_mask: 0.1998, loss: 0.5449 2023-11-14 01:33:38,070 - mmdet - INFO - Epoch [10][5400/7330] lr: 1.000e-05, eta: 2:03:10, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0332, loss_cls: 0.1299, acc: 94.9656, loss_bbox: 0.1816, loss_mask: 0.1953, loss: 0.5518 2023-11-14 01:34:00,794 - mmdet - INFO - Epoch [10][5450/7330] lr: 1.000e-05, eta: 2:02:48, time: 0.455, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0316, loss_cls: 0.1300, acc: 94.9089, loss_bbox: 0.1834, loss_mask: 0.1960, loss: 0.5536 2023-11-14 01:34:23,310 - mmdet - INFO - Epoch [10][5500/7330] lr: 1.000e-05, eta: 2:02:26, time: 0.450, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0341, loss_cls: 0.1331, acc: 94.8804, loss_bbox: 0.1844, loss_mask: 0.2022, loss: 0.5671 2023-11-14 01:34:46,245 - mmdet - INFO - Epoch [10][5550/7330] lr: 1.000e-05, eta: 2:02:04, time: 0.459, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0349, loss_cls: 0.1357, acc: 94.7725, loss_bbox: 0.1876, loss_mask: 0.1981, loss: 0.5696 2023-11-14 01:35:08,639 - mmdet - INFO - Epoch [10][5600/7330] lr: 1.000e-05, eta: 2:01:42, time: 0.448, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0321, loss_cls: 0.1269, acc: 95.0676, loss_bbox: 0.1768, loss_mask: 0.1967, loss: 0.5441 2023-11-14 01:35:30,819 - mmdet - INFO - Epoch [10][5650/7330] lr: 1.000e-05, eta: 2:01:19, time: 0.444, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0304, loss_cls: 0.1260, acc: 95.1489, loss_bbox: 0.1784, loss_mask: 0.1946, loss: 0.5403 2023-11-14 01:35:53,619 - mmdet - INFO - Epoch [10][5700/7330] lr: 1.000e-05, eta: 2:00:57, time: 0.456, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0311, loss_cls: 0.1302, acc: 94.9585, loss_bbox: 0.1826, loss_mask: 0.1945, loss: 0.5503 2023-11-14 01:36:16,436 - mmdet - INFO - Epoch [10][5750/7330] lr: 1.000e-05, eta: 2:00:35, time: 0.456, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0135, loss_rpn_bbox: 0.0333, loss_cls: 0.1293, acc: 95.0359, loss_bbox: 0.1830, loss_mask: 0.2017, loss: 0.5608 2023-11-14 01:36:38,812 - mmdet - INFO - Epoch [10][5800/7330] lr: 1.000e-05, eta: 2:00:13, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0334, loss_cls: 0.1314, acc: 94.8765, loss_bbox: 0.1846, loss_mask: 0.1998, loss: 0.5605 2023-11-14 01:37:01,288 - mmdet - INFO - Epoch [10][5850/7330] lr: 1.000e-05, eta: 1:59:51, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0325, loss_cls: 0.1264, acc: 95.1125, loss_bbox: 0.1767, loss_mask: 0.1964, loss: 0.5438 2023-11-14 01:37:23,971 - mmdet - INFO - Epoch [10][5900/7330] lr: 1.000e-05, eta: 1:59:28, time: 0.454, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0142, loss_rpn_bbox: 0.0326, loss_cls: 0.1311, acc: 94.9211, loss_bbox: 0.1836, loss_mask: 0.1978, loss: 0.5593 2023-11-14 01:37:46,528 - mmdet - INFO - Epoch [10][5950/7330] lr: 1.000e-05, eta: 1:59:06, time: 0.451, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0321, loss_cls: 0.1313, acc: 94.9375, loss_bbox: 0.1824, loss_mask: 0.2001, loss: 0.5584 2023-11-14 01:38:08,865 - mmdet - INFO - Epoch [10][6000/7330] lr: 1.000e-05, eta: 1:58:44, time: 0.447, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0308, loss_cls: 0.1249, acc: 95.2161, loss_bbox: 0.1752, loss_mask: 0.1983, loss: 0.5400 2023-11-14 01:38:31,120 - mmdet - INFO - Epoch [10][6050/7330] lr: 1.000e-05, eta: 1:58:22, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0319, loss_cls: 0.1265, acc: 95.1001, loss_bbox: 0.1799, loss_mask: 0.1983, loss: 0.5477 2023-11-14 01:38:53,812 - mmdet - INFO - Epoch [10][6100/7330] lr: 1.000e-05, eta: 1:57:59, time: 0.454, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0301, loss_cls: 0.1222, acc: 95.2478, loss_bbox: 0.1698, loss_mask: 0.1900, loss: 0.5233 2023-11-14 01:39:15,791 - mmdet - INFO - Epoch [10][6150/7330] lr: 1.000e-05, eta: 1:57:37, time: 0.440, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0310, loss_cls: 0.1260, acc: 95.1770, loss_bbox: 0.1767, loss_mask: 0.1920, loss: 0.5364 2023-11-14 01:39:38,234 - mmdet - INFO - Epoch [10][6200/7330] lr: 1.000e-05, eta: 1:57:15, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0132, loss_rpn_bbox: 0.0344, loss_cls: 0.1349, acc: 94.8296, loss_bbox: 0.1913, loss_mask: 0.2010, loss: 0.5748 2023-11-14 01:40:00,320 - mmdet - INFO - Epoch [10][6250/7330] lr: 1.000e-05, eta: 1:56:53, time: 0.442, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0317, loss_cls: 0.1245, acc: 95.1924, loss_bbox: 0.1757, loss_mask: 0.1970, loss: 0.5409 2023-11-14 01:40:22,744 - mmdet - INFO - Epoch [10][6300/7330] lr: 1.000e-05, eta: 1:56:30, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0314, loss_cls: 0.1266, acc: 95.0889, loss_bbox: 0.1780, loss_mask: 0.1944, loss: 0.5426 2023-11-14 01:40:45,315 - mmdet - INFO - Epoch [10][6350/7330] lr: 1.000e-05, eta: 1:56:08, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0319, loss_cls: 0.1253, acc: 95.1946, loss_bbox: 0.1761, loss_mask: 0.1945, loss: 0.5391 2023-11-14 01:41:07,975 - mmdet - INFO - Epoch [10][6400/7330] lr: 1.000e-05, eta: 1:55:46, time: 0.453, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0340, loss_cls: 0.1350, acc: 94.7942, loss_bbox: 0.1885, loss_mask: 0.1995, loss: 0.5700 2023-11-14 01:41:30,819 - mmdet - INFO - Epoch [10][6450/7330] lr: 1.000e-05, eta: 1:55:24, time: 0.457, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0332, loss_cls: 0.1296, acc: 95.0381, loss_bbox: 0.1838, loss_mask: 0.1986, loss: 0.5576 2023-11-14 01:41:53,189 - mmdet - INFO - Epoch [10][6500/7330] lr: 1.000e-05, eta: 1:55:01, time: 0.447, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0338, loss_cls: 0.1253, acc: 95.1660, loss_bbox: 0.1776, loss_mask: 0.1988, loss: 0.5478 2023-11-14 01:42:15,965 - mmdet - INFO - Epoch [10][6550/7330] lr: 1.000e-05, eta: 1:54:39, time: 0.455, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0325, loss_cls: 0.1301, acc: 94.9868, loss_bbox: 0.1797, loss_mask: 0.1945, loss: 0.5487 2023-11-14 01:42:38,465 - mmdet - INFO - Epoch [10][6600/7330] lr: 1.000e-05, eta: 1:54:17, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0316, loss_cls: 0.1281, acc: 95.0217, loss_bbox: 0.1786, loss_mask: 0.1977, loss: 0.5482 2023-11-14 01:43:01,019 - mmdet - INFO - Epoch [10][6650/7330] lr: 1.000e-05, eta: 1:53:55, time: 0.451, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0342, loss_cls: 0.1306, acc: 94.9746, loss_bbox: 0.1826, loss_mask: 0.2006, loss: 0.5600 2023-11-14 01:43:23,381 - mmdet - INFO - Epoch [10][6700/7330] lr: 1.000e-05, eta: 1:53:33, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0315, loss_cls: 0.1287, acc: 95.0593, loss_bbox: 0.1776, loss_mask: 0.1938, loss: 0.5422 2023-11-14 01:43:45,919 - mmdet - INFO - Epoch [10][6750/7330] lr: 1.000e-05, eta: 1:53:10, time: 0.451, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0322, loss_cls: 0.1290, acc: 95.0439, loss_bbox: 0.1815, loss_mask: 0.1965, loss: 0.5510 2023-11-14 01:44:08,141 - mmdet - INFO - Epoch [10][6800/7330] lr: 1.000e-05, eta: 1:52:48, time: 0.444, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0306, loss_cls: 0.1236, acc: 95.2021, loss_bbox: 0.1792, loss_mask: 0.1953, loss: 0.5405 2023-11-14 01:44:30,658 - mmdet - INFO - Epoch [10][6850/7330] lr: 1.000e-05, eta: 1:52:26, time: 0.450, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0325, loss_cls: 0.1313, acc: 94.9148, loss_bbox: 0.1803, loss_mask: 0.1962, loss: 0.5524 2023-11-14 01:44:53,354 - mmdet - INFO - Epoch [10][6900/7330] lr: 1.000e-05, eta: 1:52:04, time: 0.454, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0335, loss_cls: 0.1338, acc: 94.8582, loss_bbox: 0.1873, loss_mask: 0.2006, loss: 0.5676 2023-11-14 01:45:15,941 - mmdet - INFO - Epoch [10][6950/7330] lr: 1.000e-05, eta: 1:51:41, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0295, loss_cls: 0.1263, acc: 95.1147, loss_bbox: 0.1769, loss_mask: 0.1955, loss: 0.5394 2023-11-14 01:45:38,452 - mmdet - INFO - Epoch [10][7000/7330] lr: 1.000e-05, eta: 1:51:19, time: 0.450, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0322, loss_cls: 0.1276, acc: 95.0886, loss_bbox: 0.1809, loss_mask: 0.1943, loss: 0.5477 2023-11-14 01:46:01,036 - mmdet - INFO - Epoch [10][7050/7330] lr: 1.000e-05, eta: 1:50:57, time: 0.452, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0338, loss_cls: 0.1301, acc: 94.9351, loss_bbox: 0.1815, loss_mask: 0.1997, loss: 0.5575 2023-11-14 01:46:23,504 - mmdet - INFO - Epoch [10][7100/7330] lr: 1.000e-05, eta: 1:50:35, time: 0.449, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0299, loss_cls: 0.1260, acc: 95.0659, loss_bbox: 0.1743, loss_mask: 0.1970, loss: 0.5388 2023-11-14 01:46:45,861 - mmdet - INFO - Epoch [10][7150/7330] lr: 1.000e-05, eta: 1:50:12, time: 0.447, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0320, loss_cls: 0.1249, acc: 95.1821, loss_bbox: 0.1767, loss_mask: 0.1968, loss: 0.5422 2023-11-14 01:47:08,966 - mmdet - INFO - Epoch [10][7200/7330] lr: 1.000e-05, eta: 1:49:50, time: 0.462, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0332, loss_cls: 0.1295, acc: 94.9836, loss_bbox: 0.1828, loss_mask: 0.1995, loss: 0.5569 2023-11-14 01:47:31,231 - mmdet - INFO - Epoch [10][7250/7330] lr: 1.000e-05, eta: 1:49:28, time: 0.445, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0316, loss_cls: 0.1327, acc: 94.9038, loss_bbox: 0.1854, loss_mask: 0.2019, loss: 0.5643 2023-11-14 01:47:53,718 - mmdet - INFO - Epoch [10][7300/7330] lr: 1.000e-05, eta: 1:49:06, time: 0.450, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0338, loss_cls: 0.1354, acc: 94.7288, loss_bbox: 0.1890, loss_mask: 0.2001, loss: 0.5705 2023-11-14 01:48:07,709 - mmdet - INFO - Saving checkpoint at 10 epochs 2023-11-14 01:48:57,775 - mmdet - INFO - Evaluating bbox... 2023-11-14 01:49:26,000 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.498 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.715 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.545 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.316 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.540 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.645 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.425 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.661 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.766 2023-11-14 01:49:26,003 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.591 | bicycle | 0.389 | car | 0.499 | | motorcycle | 0.504 | airplane | 0.697 | bus | 0.717 | | train | 0.712 | truck | 0.471 | boat | 0.331 | | traffic light | 0.319 | fire hydrant | 0.761 | stop sign | 0.682 | | parking meter | 0.560 | bench | 0.321 | bird | 0.424 | | cat | 0.768 | dog | 0.696 | horse | 0.640 | | sheep | 0.608 | cow | 0.645 | elephant | 0.721 | | bear | 0.773 | zebra | 0.702 | giraffe | 0.716 | | backpack | 0.238 | umbrella | 0.484 | handbag | 0.261 | | tie | 0.419 | suitcase | 0.499 | frisbee | 0.724 | | skis | 0.319 | snowboard | 0.474 | sports ball | 0.489 | | kite | 0.475 | baseball bat | 0.456 | baseball glove | 0.460 | | skateboard | 0.615 | surfboard | 0.483 | tennis racket | 0.569 | | bottle | 0.474 | wine glass | 0.422 | cup | 0.513 | | fork | 0.498 | knife | 0.318 | spoon | 0.306 | | bowl | 0.476 | banana | 0.297 | apple | 0.276 | | sandwich | 0.476 | orange | 0.368 | broccoli | 0.259 | | carrot | 0.255 | hot dog | 0.463 | pizza | 0.577 | | donut | 0.572 | cake | 0.459 | chair | 0.375 | | couch | 0.481 | potted plant | 0.355 | bed | 0.494 | | dining table | 0.337 | toilet | 0.679 | tv | 0.641 | | laptop | 0.706 | mouse | 0.636 | remote | 0.435 | | keyboard | 0.572 | cell phone | 0.452 | microwave | 0.637 | | oven | 0.417 | toaster | 0.447 | sink | 0.450 | | refrigerator | 0.688 | book | 0.204 | clock | 0.532 | | vase | 0.433 | scissors | 0.429 | teddy bear | 0.566 | | hair drier | 0.263 | toothbrush | 0.383 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 01:49:26,003 - mmdet - INFO - Evaluating segm... 2023-11-14 01:49:54,868 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.444 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.685 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.477 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.478 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.635 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.366 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.719 2023-11-14 01:49:54,870 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.514 | bicycle | 0.236 | car | 0.457 | | motorcycle | 0.401 | airplane | 0.539 | bus | 0.690 | | train | 0.685 | truck | 0.446 | boat | 0.309 | | traffic light | 0.297 | fire hydrant | 0.713 | stop sign | 0.673 | | parking meter | 0.550 | bench | 0.246 | bird | 0.357 | | cat | 0.741 | dog | 0.647 | horse | 0.481 | | sheep | 0.537 | cow | 0.552 | elephant | 0.649 | | bear | 0.752 | zebra | 0.610 | giraffe | 0.553 | | backpack | 0.228 | umbrella | 0.525 | handbag | 0.239 | | tie | 0.382 | suitcase | 0.507 | frisbee | 0.681 | | skis | 0.063 | snowboard | 0.293 | sports ball | 0.487 | | kite | 0.344 | baseball bat | 0.337 | baseball glove | 0.481 | | skateboard | 0.387 | surfboard | 0.399 | tennis racket | 0.588 | | bottle | 0.454 | wine glass | 0.387 | cup | 0.514 | | fork | 0.259 | knife | 0.227 | spoon | 0.220 | | bowl | 0.441 | banana | 0.250 | apple | 0.270 | | sandwich | 0.496 | orange | 0.362 | broccoli | 0.235 | | carrot | 0.223 | hot dog | 0.370 | pizza | 0.549 | | donut | 0.564 | cake | 0.466 | chair | 0.271 | | couch | 0.405 | potted plant | 0.303 | bed | 0.384 | | dining table | 0.200 | toilet | 0.640 | tv | 0.667 | | laptop | 0.679 | mouse | 0.642 | remote | 0.391 | | keyboard | 0.545 | cell phone | 0.434 | microwave | 0.652 | | oven | 0.379 | toaster | 0.482 | sink | 0.417 | | refrigerator | 0.696 | book | 0.154 | clock | 0.531 | | vase | 0.422 | scissors | 0.320 | teddy bear | 0.526 | | hair drier | 0.236 | toothbrush | 0.251 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 01:49:55,250 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_9.pth was removed 2023-11-14 01:49:58,607 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_10.pth. 2023-11-14 01:49:58,608 - mmdet - INFO - Best bbox_mAP is 0.4979 at 10 epoch. 2023-11-14 01:49:58,608 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 01:49:58,608 - mmdet - INFO - Epoch(val) [10][625] bbox_mAP: 0.4979, bbox_mAP_50: 0.7150, bbox_mAP_75: 0.5448, bbox_mAP_s: 0.3157, bbox_mAP_m: 0.5395, bbox_mAP_l: 0.6447, bbox_mAP_copypaste: 0.4979 0.7150 0.5448 0.3157 0.5395 0.6447, segm_mAP: 0.4437, segm_mAP_50: 0.6851, segm_mAP_75: 0.4774, segm_mAP_s: 0.2401, segm_mAP_m: 0.4781, segm_mAP_l: 0.6349, segm_mAP_copypaste: 0.4437 0.6851 0.4774 0.2401 0.4781 0.6349 2023-11-14 01:50:24,788 - mmdet - INFO - Epoch [11][50/7330] lr: 1.000e-05, eta: 1:48:28, time: 0.523, data_time: 0.089, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0316, loss_cls: 0.1268, acc: 95.1438, loss_bbox: 0.1789, loss_mask: 0.1944, loss: 0.5431 2023-11-14 01:50:47,715 - mmdet - INFO - Epoch [11][100/7330] lr: 1.000e-05, eta: 1:48:06, time: 0.459, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0316, loss_cls: 0.1228, acc: 95.2549, loss_bbox: 0.1738, loss_mask: 0.1954, loss: 0.5359 2023-11-14 01:51:10,357 - mmdet - INFO - Epoch [11][150/7330] lr: 1.000e-05, eta: 1:47:44, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0307, loss_cls: 0.1318, acc: 94.9099, loss_bbox: 0.1812, loss_mask: 0.1944, loss: 0.5496 2023-11-14 01:51:32,975 - mmdet - INFO - Epoch [11][200/7330] lr: 1.000e-05, eta: 1:47:22, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0320, loss_cls: 0.1266, acc: 95.0222, loss_bbox: 0.1765, loss_mask: 0.1928, loss: 0.5394 2023-11-14 01:51:55,373 - mmdet - INFO - Epoch [11][250/7330] lr: 1.000e-05, eta: 1:46:59, time: 0.448, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0307, loss_cls: 0.1199, acc: 95.3623, loss_bbox: 0.1708, loss_mask: 0.1941, loss: 0.5267 2023-11-14 01:52:17,981 - mmdet - INFO - Epoch [11][300/7330] lr: 1.000e-05, eta: 1:46:37, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0315, loss_cls: 0.1229, acc: 95.1924, loss_bbox: 0.1760, loss_mask: 0.1970, loss: 0.5391 2023-11-14 01:52:42,829 - mmdet - INFO - Epoch [11][350/7330] lr: 1.000e-05, eta: 1:46:15, time: 0.497, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0295, loss_cls: 0.1226, acc: 95.2878, loss_bbox: 0.1731, loss_mask: 0.1958, loss: 0.5329 2023-11-14 01:53:05,074 - mmdet - INFO - Epoch [11][400/7330] lr: 1.000e-05, eta: 1:45:53, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0320, loss_cls: 0.1254, acc: 95.1387, loss_bbox: 0.1772, loss_mask: 0.1966, loss: 0.5434 2023-11-14 01:53:27,702 - mmdet - INFO - Epoch [11][450/7330] lr: 1.000e-05, eta: 1:45:31, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0312, loss_cls: 0.1272, acc: 95.0818, loss_bbox: 0.1797, loss_mask: 0.1958, loss: 0.5463 2023-11-14 01:53:52,307 - mmdet - INFO - Epoch [11][500/7330] lr: 1.000e-05, eta: 1:45:09, time: 0.492, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0323, loss_cls: 0.1255, acc: 95.1331, loss_bbox: 0.1754, loss_mask: 0.1932, loss: 0.5379 2023-11-14 01:54:14,742 - mmdet - INFO - Epoch [11][550/7330] lr: 1.000e-05, eta: 1:44:47, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0306, loss_cls: 0.1216, acc: 95.3081, loss_bbox: 0.1746, loss_mask: 0.1946, loss: 0.5313 2023-11-14 01:54:37,805 - mmdet - INFO - Epoch [11][600/7330] lr: 1.000e-05, eta: 1:44:25, time: 0.461, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0322, loss_cls: 0.1266, acc: 95.0432, loss_bbox: 0.1812, loss_mask: 0.1979, loss: 0.5500 2023-11-14 01:55:00,424 - mmdet - INFO - Epoch [11][650/7330] lr: 1.000e-05, eta: 1:44:03, time: 0.452, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0315, loss_cls: 0.1232, acc: 95.2400, loss_bbox: 0.1743, loss_mask: 0.1958, loss: 0.5362 2023-11-14 01:55:22,946 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 01:55:22,946 - mmdet - INFO - Epoch [11][700/7330] lr: 1.000e-05, eta: 1:43:40, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0308, loss_cls: 0.1225, acc: 95.2131, loss_bbox: 0.1807, loss_mask: 0.1950, loss: 0.5405 2023-11-14 01:55:45,827 - mmdet - INFO - Epoch [11][750/7330] lr: 1.000e-05, eta: 1:43:18, time: 0.458, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0330, loss_cls: 0.1281, acc: 95.0146, loss_bbox: 0.1802, loss_mask: 0.1985, loss: 0.5523 2023-11-14 01:56:08,550 - mmdet - INFO - Epoch [11][800/7330] lr: 1.000e-05, eta: 1:42:56, time: 0.454, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0313, loss_cls: 0.1252, acc: 95.1345, loss_bbox: 0.1780, loss_mask: 0.1994, loss: 0.5453 2023-11-14 01:56:31,063 - mmdet - INFO - Epoch [11][850/7330] lr: 1.000e-05, eta: 1:42:34, time: 0.450, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0308, loss_cls: 0.1249, acc: 95.1531, loss_bbox: 0.1784, loss_mask: 0.1960, loss: 0.5406 2023-11-14 01:56:53,802 - mmdet - INFO - Epoch [11][900/7330] lr: 1.000e-05, eta: 1:42:12, time: 0.455, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0311, loss_cls: 0.1200, acc: 95.3069, loss_bbox: 0.1712, loss_mask: 0.1923, loss: 0.5260 2023-11-14 01:57:16,645 - mmdet - INFO - Epoch [11][950/7330] lr: 1.000e-05, eta: 1:41:49, time: 0.457, data_time: 0.032, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0335, loss_cls: 0.1287, acc: 95.0078, loss_bbox: 0.1828, loss_mask: 0.1986, loss: 0.5553 2023-11-14 01:57:39,680 - mmdet - INFO - Epoch [11][1000/7330] lr: 1.000e-05, eta: 1:41:27, time: 0.461, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0318, loss_cls: 0.1271, acc: 95.1350, loss_bbox: 0.1818, loss_mask: 0.1986, loss: 0.5510 2023-11-14 01:58:02,491 - mmdet - INFO - Epoch [11][1050/7330] lr: 1.000e-05, eta: 1:41:05, time: 0.456, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0305, loss_cls: 0.1249, acc: 95.1973, loss_bbox: 0.1782, loss_mask: 0.1944, loss: 0.5400 2023-11-14 01:58:24,988 - mmdet - INFO - Epoch [11][1100/7330] lr: 1.000e-05, eta: 1:40:43, time: 0.450, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0333, loss_cls: 0.1259, acc: 95.1033, loss_bbox: 0.1750, loss_mask: 0.1937, loss: 0.5409 2023-11-14 01:58:47,932 - mmdet - INFO - Epoch [11][1150/7330] lr: 1.000e-05, eta: 1:40:21, time: 0.459, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0324, loss_cls: 0.1265, acc: 95.1638, loss_bbox: 0.1769, loss_mask: 0.1926, loss: 0.5406 2023-11-14 01:59:10,253 - mmdet - INFO - Epoch [11][1200/7330] lr: 1.000e-05, eta: 1:39:58, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0308, loss_cls: 0.1244, acc: 95.2041, loss_bbox: 0.1768, loss_mask: 0.1947, loss: 0.5386 2023-11-14 01:59:32,749 - mmdet - INFO - Epoch [11][1250/7330] lr: 1.000e-05, eta: 1:39:36, time: 0.450, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0298, loss_cls: 0.1165, acc: 95.4961, loss_bbox: 0.1700, loss_mask: 0.1931, loss: 0.5207 2023-11-14 01:59:55,236 - mmdet - INFO - Epoch [11][1300/7330] lr: 1.000e-05, eta: 1:39:14, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0307, loss_cls: 0.1240, acc: 95.2515, loss_bbox: 0.1754, loss_mask: 0.1953, loss: 0.5359 2023-11-14 02:00:18,122 - mmdet - INFO - Epoch [11][1350/7330] lr: 1.000e-05, eta: 1:38:52, time: 0.458, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0321, loss_cls: 0.1280, acc: 95.0583, loss_bbox: 0.1863, loss_mask: 0.1996, loss: 0.5574 2023-11-14 02:00:40,755 - mmdet - INFO - Epoch [11][1400/7330] lr: 1.000e-05, eta: 1:38:29, time: 0.453, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0319, loss_cls: 0.1231, acc: 95.1838, loss_bbox: 0.1786, loss_mask: 0.1955, loss: 0.5399 2023-11-14 02:01:03,753 - mmdet - INFO - Epoch [11][1450/7330] lr: 1.000e-05, eta: 1:38:07, time: 0.460, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0338, loss_cls: 0.1308, acc: 94.8501, loss_bbox: 0.1862, loss_mask: 0.1967, loss: 0.5599 2023-11-14 02:01:26,673 - mmdet - INFO - Epoch [11][1500/7330] lr: 1.000e-05, eta: 1:37:45, time: 0.458, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0311, loss_cls: 0.1239, acc: 95.2744, loss_bbox: 0.1799, loss_mask: 0.1959, loss: 0.5417 2023-11-14 02:01:49,162 - mmdet - INFO - Epoch [11][1550/7330] lr: 1.000e-05, eta: 1:37:23, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0328, loss_cls: 0.1225, acc: 95.3123, loss_bbox: 0.1731, loss_mask: 0.1916, loss: 0.5326 2023-11-14 02:02:11,796 - mmdet - INFO - Epoch [11][1600/7330] lr: 1.000e-05, eta: 1:37:01, time: 0.453, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0318, loss_cls: 0.1240, acc: 95.1848, loss_bbox: 0.1776, loss_mask: 0.1959, loss: 0.5407 2023-11-14 02:02:34,789 - mmdet - INFO - Epoch [11][1650/7330] lr: 1.000e-05, eta: 1:36:38, time: 0.460, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0321, loss_cls: 0.1286, acc: 95.0134, loss_bbox: 0.1807, loss_mask: 0.1966, loss: 0.5505 2023-11-14 02:02:57,780 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:02:57,780 - mmdet - INFO - Epoch [11][1700/7330] lr: 1.000e-05, eta: 1:36:16, time: 0.460, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0338, loss_cls: 0.1325, acc: 94.8726, loss_bbox: 0.1829, loss_mask: 0.1981, loss: 0.5604 2023-11-14 02:03:20,266 - mmdet - INFO - Epoch [11][1750/7330] lr: 1.000e-05, eta: 1:35:54, time: 0.450, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0322, loss_cls: 0.1238, acc: 95.2590, loss_bbox: 0.1741, loss_mask: 0.1952, loss: 0.5366 2023-11-14 02:03:42,608 - mmdet - INFO - Epoch [11][1800/7330] lr: 1.000e-05, eta: 1:35:32, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0328, loss_cls: 0.1308, acc: 94.9878, loss_bbox: 0.1833, loss_mask: 0.2005, loss: 0.5599 2023-11-14 02:04:05,111 - mmdet - INFO - Epoch [11][1850/7330] lr: 1.000e-05, eta: 1:35:10, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0302, loss_cls: 0.1211, acc: 95.3093, loss_bbox: 0.1725, loss_mask: 0.1936, loss: 0.5279 2023-11-14 02:04:27,685 - mmdet - INFO - Epoch [11][1900/7330] lr: 1.000e-05, eta: 1:34:47, time: 0.452, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0334, loss_cls: 0.1268, acc: 95.1377, loss_bbox: 0.1815, loss_mask: 0.1969, loss: 0.5507 2023-11-14 02:04:50,514 - mmdet - INFO - Epoch [11][1950/7330] lr: 1.000e-05, eta: 1:34:25, time: 0.457, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0338, loss_cls: 0.1300, acc: 94.9824, loss_bbox: 0.1836, loss_mask: 0.2012, loss: 0.5622 2023-11-14 02:05:13,056 - mmdet - INFO - Epoch [11][2000/7330] lr: 1.000e-05, eta: 1:34:03, time: 0.451, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0311, loss_cls: 0.1204, acc: 95.3386, loss_bbox: 0.1757, loss_mask: 0.1934, loss: 0.5317 2023-11-14 02:05:36,067 - mmdet - INFO - Epoch [11][2050/7330] lr: 1.000e-05, eta: 1:33:41, time: 0.460, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0317, loss_cls: 0.1310, acc: 94.9492, loss_bbox: 0.1818, loss_mask: 0.1949, loss: 0.5518 2023-11-14 02:05:58,312 - mmdet - INFO - Epoch [11][2100/7330] lr: 1.000e-05, eta: 1:33:18, time: 0.445, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0309, loss_cls: 0.1217, acc: 95.2922, loss_bbox: 0.1711, loss_mask: 0.1952, loss: 0.5296 2023-11-14 02:06:21,031 - mmdet - INFO - Epoch [11][2150/7330] lr: 1.000e-05, eta: 1:32:56, time: 0.454, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0325, loss_cls: 0.1252, acc: 95.1619, loss_bbox: 0.1776, loss_mask: 0.1975, loss: 0.5443 2023-11-14 02:06:43,566 - mmdet - INFO - Epoch [11][2200/7330] lr: 1.000e-05, eta: 1:32:34, time: 0.451, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0325, loss_cls: 0.1263, acc: 95.1223, loss_bbox: 0.1794, loss_mask: 0.2004, loss: 0.5509 2023-11-14 02:07:05,938 - mmdet - INFO - Epoch [11][2250/7330] lr: 1.000e-05, eta: 1:32:12, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0322, loss_cls: 0.1302, acc: 94.9648, loss_bbox: 0.1815, loss_mask: 0.1999, loss: 0.5560 2023-11-14 02:07:28,496 - mmdet - INFO - Epoch [11][2300/7330] lr: 1.000e-05, eta: 1:31:49, time: 0.451, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0324, loss_cls: 0.1287, acc: 95.0049, loss_bbox: 0.1784, loss_mask: 0.1963, loss: 0.5466 2023-11-14 02:07:50,968 - mmdet - INFO - Epoch [11][2350/7330] lr: 1.000e-05, eta: 1:31:27, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0331, loss_cls: 0.1286, acc: 95.0579, loss_bbox: 0.1770, loss_mask: 0.1965, loss: 0.5475 2023-11-14 02:08:13,308 - mmdet - INFO - Epoch [11][2400/7330] lr: 1.000e-05, eta: 1:31:05, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1278, acc: 95.0940, loss_bbox: 0.1811, loss_mask: 0.1921, loss: 0.5460 2023-11-14 02:08:35,871 - mmdet - INFO - Epoch [11][2450/7330] lr: 1.000e-05, eta: 1:30:43, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0304, loss_cls: 0.1252, acc: 95.1218, loss_bbox: 0.1746, loss_mask: 0.1932, loss: 0.5335 2023-11-14 02:08:58,778 - mmdet - INFO - Epoch [11][2500/7330] lr: 1.000e-05, eta: 1:30:20, time: 0.458, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0320, loss_cls: 0.1261, acc: 95.1118, loss_bbox: 0.1791, loss_mask: 0.1983, loss: 0.5468 2023-11-14 02:09:21,474 - mmdet - INFO - Epoch [11][2550/7330] lr: 1.000e-05, eta: 1:29:58, time: 0.454, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0321, loss_cls: 0.1263, acc: 95.0808, loss_bbox: 0.1799, loss_mask: 0.1969, loss: 0.5467 2023-11-14 02:09:44,242 - mmdet - INFO - Epoch [11][2600/7330] lr: 1.000e-05, eta: 1:29:36, time: 0.455, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0139, loss_rpn_bbox: 0.0328, loss_cls: 0.1264, acc: 95.0847, loss_bbox: 0.1743, loss_mask: 0.1918, loss: 0.5392 2023-11-14 02:10:06,615 - mmdet - INFO - Epoch [11][2650/7330] lr: 1.000e-05, eta: 1:29:14, time: 0.447, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0311, loss_cls: 0.1262, acc: 95.0510, loss_bbox: 0.1789, loss_mask: 0.1929, loss: 0.5410 2023-11-14 02:10:29,520 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:10:29,520 - mmdet - INFO - Epoch [11][2700/7330] lr: 1.000e-05, eta: 1:28:51, time: 0.458, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0326, loss_cls: 0.1299, acc: 94.9153, loss_bbox: 0.1867, loss_mask: 0.1994, loss: 0.5611 2023-11-14 02:10:52,042 - mmdet - INFO - Epoch [11][2750/7330] lr: 1.000e-05, eta: 1:28:29, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0322, loss_cls: 0.1249, acc: 95.1780, loss_bbox: 0.1771, loss_mask: 0.1935, loss: 0.5391 2023-11-14 02:11:14,277 - mmdet - INFO - Epoch [11][2800/7330] lr: 1.000e-05, eta: 1:28:07, time: 0.445, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0335, loss_cls: 0.1284, acc: 95.0117, loss_bbox: 0.1820, loss_mask: 0.1982, loss: 0.5533 2023-11-14 02:11:37,754 - mmdet - INFO - Epoch [11][2850/7330] lr: 1.000e-05, eta: 1:27:45, time: 0.470, data_time: 0.032, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0340, loss_cls: 0.1312, acc: 94.9646, loss_bbox: 0.1854, loss_mask: 0.1946, loss: 0.5577 2023-11-14 02:12:00,414 - mmdet - INFO - Epoch [11][2900/7330] lr: 1.000e-05, eta: 1:27:23, time: 0.453, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0345, loss_cls: 0.1293, acc: 95.0022, loss_bbox: 0.1818, loss_mask: 0.1966, loss: 0.5542 2023-11-14 02:12:23,096 - mmdet - INFO - Epoch [11][2950/7330] lr: 1.000e-05, eta: 1:27:00, time: 0.454, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0314, loss_cls: 0.1218, acc: 95.3162, loss_bbox: 0.1754, loss_mask: 0.1940, loss: 0.5341 2023-11-14 02:12:46,115 - mmdet - INFO - Epoch [11][3000/7330] lr: 1.000e-05, eta: 1:26:38, time: 0.460, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0352, loss_cls: 0.1329, acc: 94.8679, loss_bbox: 0.1860, loss_mask: 0.1978, loss: 0.5656 2023-11-14 02:13:08,786 - mmdet - INFO - Epoch [11][3050/7330] lr: 1.000e-05, eta: 1:26:16, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0325, loss_cls: 0.1270, acc: 95.0269, loss_bbox: 0.1809, loss_mask: 0.1944, loss: 0.5464 2023-11-14 02:13:31,514 - mmdet - INFO - Epoch [11][3100/7330] lr: 1.000e-05, eta: 1:25:54, time: 0.455, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0337, loss_cls: 0.1237, acc: 95.1855, loss_bbox: 0.1778, loss_mask: 0.1942, loss: 0.5415 2023-11-14 02:13:53,992 - mmdet - INFO - Epoch [11][3150/7330] lr: 1.000e-05, eta: 1:25:31, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0327, loss_cls: 0.1283, acc: 95.0693, loss_bbox: 0.1851, loss_mask: 0.1973, loss: 0.5551 2023-11-14 02:14:16,183 - mmdet - INFO - Epoch [11][3200/7330] lr: 1.000e-05, eta: 1:25:09, time: 0.444, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0310, loss_cls: 0.1244, acc: 95.2793, loss_bbox: 0.1717, loss_mask: 0.1909, loss: 0.5297 2023-11-14 02:14:38,970 - mmdet - INFO - Epoch [11][3250/7330] lr: 1.000e-05, eta: 1:24:47, time: 0.456, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0320, loss_cls: 0.1229, acc: 95.2217, loss_bbox: 0.1751, loss_mask: 0.1941, loss: 0.5357 2023-11-14 02:15:01,382 - mmdet - INFO - Epoch [11][3300/7330] lr: 1.000e-05, eta: 1:24:25, time: 0.448, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0344, loss_cls: 0.1271, acc: 95.0686, loss_bbox: 0.1819, loss_mask: 0.1960, loss: 0.5518 2023-11-14 02:15:23,666 - mmdet - INFO - Epoch [11][3350/7330] lr: 1.000e-05, eta: 1:24:02, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0310, loss_cls: 0.1249, acc: 95.1497, loss_bbox: 0.1769, loss_mask: 0.1900, loss: 0.5339 2023-11-14 02:15:46,867 - mmdet - INFO - Epoch [11][3400/7330] lr: 1.000e-05, eta: 1:23:40, time: 0.464, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0336, loss_cls: 0.1324, acc: 94.8083, loss_bbox: 0.1879, loss_mask: 0.1974, loss: 0.5638 2023-11-14 02:16:09,293 - mmdet - INFO - Epoch [11][3450/7330] lr: 1.000e-05, eta: 1:23:18, time: 0.449, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0306, loss_cls: 0.1281, acc: 95.0120, loss_bbox: 0.1803, loss_mask: 0.1955, loss: 0.5456 2023-11-14 02:16:31,689 - mmdet - INFO - Epoch [11][3500/7330] lr: 1.000e-05, eta: 1:22:56, time: 0.448, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0316, loss_cls: 0.1250, acc: 95.1406, loss_bbox: 0.1781, loss_mask: 0.1947, loss: 0.5408 2023-11-14 02:16:54,067 - mmdet - INFO - Epoch [11][3550/7330] lr: 1.000e-05, eta: 1:22:33, time: 0.448, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0324, loss_cls: 0.1295, acc: 95.0476, loss_bbox: 0.1823, loss_mask: 0.1957, loss: 0.5519 2023-11-14 02:17:16,280 - mmdet - INFO - Epoch [11][3600/7330] lr: 1.000e-05, eta: 1:22:11, time: 0.444, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0329, loss_cls: 0.1240, acc: 95.2144, loss_bbox: 0.1739, loss_mask: 0.1966, loss: 0.5382 2023-11-14 02:17:38,502 - mmdet - INFO - Epoch [11][3650/7330] lr: 1.000e-05, eta: 1:21:49, time: 0.444, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0312, loss_cls: 0.1266, acc: 95.0344, loss_bbox: 0.1837, loss_mask: 0.1979, loss: 0.5508 2023-11-14 02:18:01,083 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:18:01,083 - mmdet - INFO - Epoch [11][3700/7330] lr: 1.000e-05, eta: 1:21:26, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0329, loss_cls: 0.1313, acc: 94.9478, loss_bbox: 0.1854, loss_mask: 0.1961, loss: 0.5575 2023-11-14 02:18:23,589 - mmdet - INFO - Epoch [11][3750/7330] lr: 1.000e-05, eta: 1:21:04, time: 0.450, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0308, loss_cls: 0.1257, acc: 95.1711, loss_bbox: 0.1757, loss_mask: 0.1937, loss: 0.5367 2023-11-14 02:18:46,280 - mmdet - INFO - Epoch [11][3800/7330] lr: 1.000e-05, eta: 1:20:42, time: 0.454, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0335, loss_cls: 0.1339, acc: 94.8394, loss_bbox: 0.1896, loss_mask: 0.2015, loss: 0.5718 2023-11-14 02:19:09,028 - mmdet - INFO - Epoch [11][3850/7330] lr: 1.000e-05, eta: 1:20:20, time: 0.455, data_time: 0.031, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0324, loss_cls: 0.1221, acc: 95.2988, loss_bbox: 0.1743, loss_mask: 0.1922, loss: 0.5323 2023-11-14 02:19:31,647 - mmdet - INFO - Epoch [11][3900/7330] lr: 1.000e-05, eta: 1:19:58, time: 0.452, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0306, loss_cls: 0.1274, acc: 95.0779, loss_bbox: 0.1773, loss_mask: 0.1958, loss: 0.5437 2023-11-14 02:19:54,303 - mmdet - INFO - Epoch [11][3950/7330] lr: 1.000e-05, eta: 1:19:35, time: 0.453, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0321, loss_cls: 0.1344, acc: 94.8093, loss_bbox: 0.1877, loss_mask: 0.1989, loss: 0.5649 2023-11-14 02:20:16,580 - mmdet - INFO - Epoch [11][4000/7330] lr: 1.000e-05, eta: 1:19:13, time: 0.445, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0329, loss_cls: 0.1290, acc: 94.9841, loss_bbox: 0.1806, loss_mask: 0.1939, loss: 0.5468 2023-11-14 02:20:39,006 - mmdet - INFO - Epoch [11][4050/7330] lr: 1.000e-05, eta: 1:18:51, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0303, loss_cls: 0.1227, acc: 95.3362, loss_bbox: 0.1697, loss_mask: 0.1896, loss: 0.5239 2023-11-14 02:21:01,418 - mmdet - INFO - Epoch [11][4100/7330] lr: 1.000e-05, eta: 1:18:28, time: 0.448, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0329, loss_cls: 0.1264, acc: 95.1833, loss_bbox: 0.1792, loss_mask: 0.1951, loss: 0.5450 2023-11-14 02:21:23,772 - mmdet - INFO - Epoch [11][4150/7330] lr: 1.000e-05, eta: 1:18:06, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0317, loss_cls: 0.1292, acc: 94.9805, loss_bbox: 0.1825, loss_mask: 0.1982, loss: 0.5531 2023-11-14 02:21:45,764 - mmdet - INFO - Epoch [11][4200/7330] lr: 1.000e-05, eta: 1:17:44, time: 0.440, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0322, loss_cls: 0.1264, acc: 95.1084, loss_bbox: 0.1808, loss_mask: 0.1971, loss: 0.5473 2023-11-14 02:22:08,177 - mmdet - INFO - Epoch [11][4250/7330] lr: 1.000e-05, eta: 1:17:21, time: 0.448, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0136, loss_rpn_bbox: 0.0329, loss_cls: 0.1298, acc: 94.9434, loss_bbox: 0.1792, loss_mask: 0.1945, loss: 0.5500 2023-11-14 02:22:30,707 - mmdet - INFO - Epoch [11][4300/7330] lr: 1.000e-05, eta: 1:16:59, time: 0.451, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0328, loss_cls: 0.1254, acc: 95.2041, loss_bbox: 0.1782, loss_mask: 0.1903, loss: 0.5390 2023-11-14 02:22:53,524 - mmdet - INFO - Epoch [11][4350/7330] lr: 1.000e-05, eta: 1:16:37, time: 0.456, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0309, loss_cls: 0.1206, acc: 95.3147, loss_bbox: 0.1729, loss_mask: 0.1920, loss: 0.5284 2023-11-14 02:23:15,624 - mmdet - INFO - Epoch [11][4400/7330] lr: 1.000e-05, eta: 1:16:15, time: 0.442, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0307, loss_cls: 0.1268, acc: 95.0642, loss_bbox: 0.1757, loss_mask: 0.1953, loss: 0.5396 2023-11-14 02:23:37,711 - mmdet - INFO - Epoch [11][4450/7330] lr: 1.000e-05, eta: 1:15:52, time: 0.442, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0315, loss_cls: 0.1241, acc: 95.1875, loss_bbox: 0.1757, loss_mask: 0.1933, loss: 0.5363 2023-11-14 02:24:02,609 - mmdet - INFO - Epoch [11][4500/7330] lr: 1.000e-05, eta: 1:15:30, time: 0.498, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0342, loss_cls: 0.1235, acc: 95.2063, loss_bbox: 0.1779, loss_mask: 0.1995, loss: 0.5471 2023-11-14 02:24:24,927 - mmdet - INFO - Epoch [11][4550/7330] lr: 1.000e-05, eta: 1:15:08, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0314, loss_cls: 0.1239, acc: 95.1934, loss_bbox: 0.1778, loss_mask: 0.1912, loss: 0.5356 2023-11-14 02:24:47,312 - mmdet - INFO - Epoch [11][4600/7330] lr: 1.000e-05, eta: 1:14:46, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0348, loss_cls: 0.1359, acc: 94.7344, loss_bbox: 0.1907, loss_mask: 0.2019, loss: 0.5761 2023-11-14 02:25:11,207 - mmdet - INFO - Epoch [11][4650/7330] lr: 1.000e-05, eta: 1:14:24, time: 0.478, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0313, loss_cls: 0.1247, acc: 95.1528, loss_bbox: 0.1813, loss_mask: 0.1985, loss: 0.5456 2023-11-14 02:25:33,881 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:25:33,881 - mmdet - INFO - Epoch [11][4700/7330] lr: 1.000e-05, eta: 1:14:01, time: 0.454, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0326, loss_cls: 0.1299, acc: 94.9495, loss_bbox: 0.1803, loss_mask: 0.1968, loss: 0.5519 2023-11-14 02:25:56,382 - mmdet - INFO - Epoch [11][4750/7330] lr: 1.000e-05, eta: 1:13:39, time: 0.450, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0337, loss_cls: 0.1305, acc: 94.9160, loss_bbox: 0.1870, loss_mask: 0.2029, loss: 0.5660 2023-11-14 02:26:18,810 - mmdet - INFO - Epoch [11][4800/7330] lr: 1.000e-05, eta: 1:13:17, time: 0.449, data_time: 0.018, memory: 5732, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0313, loss_cls: 0.1201, acc: 95.3291, loss_bbox: 0.1742, loss_mask: 0.1930, loss: 0.5285 2023-11-14 02:26:41,310 - mmdet - INFO - Epoch [11][4850/7330] lr: 1.000e-05, eta: 1:12:55, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0310, loss_cls: 0.1239, acc: 95.2336, loss_bbox: 0.1765, loss_mask: 0.1926, loss: 0.5367 2023-11-14 02:27:03,822 - mmdet - INFO - Epoch [11][4900/7330] lr: 1.000e-05, eta: 1:12:32, time: 0.450, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0321, loss_cls: 0.1228, acc: 95.2356, loss_bbox: 0.1781, loss_mask: 0.1971, loss: 0.5420 2023-11-14 02:27:26,520 - mmdet - INFO - Epoch [11][4950/7330] lr: 1.000e-05, eta: 1:12:10, time: 0.454, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0342, loss_cls: 0.1317, acc: 94.8972, loss_bbox: 0.1853, loss_mask: 0.1995, loss: 0.5629 2023-11-14 02:27:48,652 - mmdet - INFO - Epoch [11][5000/7330] lr: 1.000e-05, eta: 1:11:48, time: 0.443, data_time: 0.018, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0318, loss_cls: 0.1257, acc: 95.1497, loss_bbox: 0.1743, loss_mask: 0.1887, loss: 0.5316 2023-11-14 02:28:10,845 - mmdet - INFO - Epoch [11][5050/7330] lr: 1.000e-05, eta: 1:11:25, time: 0.444, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0297, loss_cls: 0.1272, acc: 95.1182, loss_bbox: 0.1791, loss_mask: 0.1966, loss: 0.5452 2023-11-14 02:28:33,229 - mmdet - INFO - Epoch [11][5100/7330] lr: 1.000e-05, eta: 1:11:03, time: 0.448, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0316, loss_cls: 0.1283, acc: 94.9678, loss_bbox: 0.1802, loss_mask: 0.1955, loss: 0.5465 2023-11-14 02:28:55,771 - mmdet - INFO - Epoch [11][5150/7330] lr: 1.000e-05, eta: 1:10:41, time: 0.451, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0329, loss_cls: 0.1281, acc: 95.0425, loss_bbox: 0.1824, loss_mask: 0.1956, loss: 0.5507 2023-11-14 02:29:18,330 - mmdet - INFO - Epoch [11][5200/7330] lr: 1.000e-05, eta: 1:10:19, time: 0.451, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0335, loss_cls: 0.1324, acc: 94.8884, loss_bbox: 0.1843, loss_mask: 0.1988, loss: 0.5604 2023-11-14 02:29:40,865 - mmdet - INFO - Epoch [11][5250/7330] lr: 1.000e-05, eta: 1:09:56, time: 0.451, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0313, loss_cls: 0.1227, acc: 95.2271, loss_bbox: 0.1696, loss_mask: 0.1916, loss: 0.5270 2023-11-14 02:30:03,437 - mmdet - INFO - Epoch [11][5300/7330] lr: 1.000e-05, eta: 1:09:34, time: 0.451, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0335, loss_cls: 0.1276, acc: 95.1069, loss_bbox: 0.1751, loss_mask: 0.1915, loss: 0.5388 2023-11-14 02:30:25,677 - mmdet - INFO - Epoch [11][5350/7330] lr: 1.000e-05, eta: 1:09:12, time: 0.445, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0301, loss_cls: 0.1260, acc: 95.1604, loss_bbox: 0.1730, loss_mask: 0.1929, loss: 0.5342 2023-11-14 02:30:50,610 - mmdet - INFO - Epoch [11][5400/7330] lr: 1.000e-05, eta: 1:08:50, time: 0.499, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0298, loss_cls: 0.1219, acc: 95.2471, loss_bbox: 0.1711, loss_mask: 0.1924, loss: 0.5257 2023-11-14 02:31:12,986 - mmdet - INFO - Epoch [11][5450/7330] lr: 1.000e-05, eta: 1:08:28, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0317, loss_cls: 0.1200, acc: 95.3918, loss_bbox: 0.1708, loss_mask: 0.1905, loss: 0.5246 2023-11-14 02:31:35,303 - mmdet - INFO - Epoch [11][5500/7330] lr: 1.000e-05, eta: 1:08:05, time: 0.446, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0323, loss_cls: 0.1230, acc: 95.3074, loss_bbox: 0.1711, loss_mask: 0.1934, loss: 0.5318 2023-11-14 02:31:57,927 - mmdet - INFO - Epoch [11][5550/7330] lr: 1.000e-05, eta: 1:07:43, time: 0.452, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0334, loss_cls: 0.1315, acc: 94.8977, loss_bbox: 0.1828, loss_mask: 0.1983, loss: 0.5581 2023-11-14 02:32:20,244 - mmdet - INFO - Epoch [11][5600/7330] lr: 1.000e-05, eta: 1:07:21, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0311, loss_cls: 0.1268, acc: 95.0273, loss_bbox: 0.1766, loss_mask: 0.1965, loss: 0.5423 2023-11-14 02:32:42,593 - mmdet - INFO - Epoch [11][5650/7330] lr: 1.000e-05, eta: 1:06:58, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0314, loss_cls: 0.1196, acc: 95.2854, loss_bbox: 0.1759, loss_mask: 0.1948, loss: 0.5328 2023-11-14 02:33:05,324 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:33:05,324 - mmdet - INFO - Epoch [11][5700/7330] lr: 1.000e-05, eta: 1:06:36, time: 0.455, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0339, loss_cls: 0.1313, acc: 94.9365, loss_bbox: 0.1816, loss_mask: 0.1993, loss: 0.5585 2023-11-14 02:33:27,581 - mmdet - INFO - Epoch [11][5750/7330] lr: 1.000e-05, eta: 1:06:14, time: 0.445, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0298, loss_cls: 0.1221, acc: 95.2510, loss_bbox: 0.1716, loss_mask: 0.1963, loss: 0.5310 2023-11-14 02:33:50,029 - mmdet - INFO - Epoch [11][5800/7330] lr: 1.000e-05, eta: 1:05:52, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0307, loss_cls: 0.1212, acc: 95.3079, loss_bbox: 0.1747, loss_mask: 0.1947, loss: 0.5322 2023-11-14 02:34:12,260 - mmdet - INFO - Epoch [11][5850/7330] lr: 1.000e-05, eta: 1:05:29, time: 0.445, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0318, loss_cls: 0.1259, acc: 95.1160, loss_bbox: 0.1803, loss_mask: 0.1954, loss: 0.5453 2023-11-14 02:34:34,815 - mmdet - INFO - Epoch [11][5900/7330] lr: 1.000e-05, eta: 1:05:07, time: 0.451, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0345, loss_cls: 0.1304, acc: 94.9619, loss_bbox: 0.1864, loss_mask: 0.1993, loss: 0.5632 2023-11-14 02:34:57,341 - mmdet - INFO - Epoch [11][5950/7330] lr: 1.000e-05, eta: 1:04:45, time: 0.450, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0325, loss_cls: 0.1281, acc: 95.0444, loss_bbox: 0.1814, loss_mask: 0.1973, loss: 0.5513 2023-11-14 02:35:19,966 - mmdet - INFO - Epoch [11][6000/7330] lr: 1.000e-05, eta: 1:04:22, time: 0.453, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0335, loss_cls: 0.1257, acc: 95.1191, loss_bbox: 0.1753, loss_mask: 0.1982, loss: 0.5446 2023-11-14 02:35:42,260 - mmdet - INFO - Epoch [11][6050/7330] lr: 1.000e-05, eta: 1:04:00, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0339, loss_cls: 0.1334, acc: 94.8860, loss_bbox: 0.1862, loss_mask: 0.2013, loss: 0.5672 2023-11-14 02:36:04,731 - mmdet - INFO - Epoch [11][6100/7330] lr: 1.000e-05, eta: 1:03:38, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0325, loss_cls: 0.1288, acc: 95.0547, loss_bbox: 0.1784, loss_mask: 0.1958, loss: 0.5470 2023-11-14 02:36:27,403 - mmdet - INFO - Epoch [11][6150/7330] lr: 1.000e-05, eta: 1:03:16, time: 0.453, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0318, loss_cls: 0.1233, acc: 95.2490, loss_bbox: 0.1772, loss_mask: 0.1964, loss: 0.5407 2023-11-14 02:36:50,011 - mmdet - INFO - Epoch [11][6200/7330] lr: 1.000e-05, eta: 1:02:53, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0298, loss_cls: 0.1245, acc: 95.1519, loss_bbox: 0.1735, loss_mask: 0.1896, loss: 0.5282 2023-11-14 02:37:12,939 - mmdet - INFO - Epoch [11][6250/7330] lr: 1.000e-05, eta: 1:02:31, time: 0.459, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0339, loss_cls: 0.1331, acc: 94.8738, loss_bbox: 0.1880, loss_mask: 0.2060, loss: 0.5732 2023-11-14 02:37:35,236 - mmdet - INFO - Epoch [11][6300/7330] lr: 1.000e-05, eta: 1:02:09, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0322, loss_cls: 0.1303, acc: 95.0017, loss_bbox: 0.1810, loss_mask: 0.1968, loss: 0.5519 2023-11-14 02:37:58,219 - mmdet - INFO - Epoch [11][6350/7330] lr: 1.000e-05, eta: 1:01:46, time: 0.460, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0327, loss_cls: 0.1317, acc: 94.9248, loss_bbox: 0.1884, loss_mask: 0.1961, loss: 0.5605 2023-11-14 02:38:20,857 - mmdet - INFO - Epoch [11][6400/7330] lr: 1.000e-05, eta: 1:01:24, time: 0.453, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0333, loss_cls: 0.1320, acc: 94.9844, loss_bbox: 0.1819, loss_mask: 0.1998, loss: 0.5591 2023-11-14 02:38:43,443 - mmdet - INFO - Epoch [11][6450/7330] lr: 1.000e-05, eta: 1:01:02, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0333, loss_cls: 0.1252, acc: 95.1746, loss_bbox: 0.1778, loss_mask: 0.1946, loss: 0.5432 2023-11-14 02:39:05,941 - mmdet - INFO - Epoch [11][6500/7330] lr: 1.000e-05, eta: 1:00:40, time: 0.450, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0303, loss_cls: 0.1253, acc: 95.1479, loss_bbox: 0.1786, loss_mask: 0.1911, loss: 0.5362 2023-11-14 02:39:28,043 - mmdet - INFO - Epoch [11][6550/7330] lr: 1.000e-05, eta: 1:00:17, time: 0.442, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0317, loss_cls: 0.1303, acc: 94.9021, loss_bbox: 0.1845, loss_mask: 0.2011, loss: 0.5590 2023-11-14 02:39:50,343 - mmdet - INFO - Epoch [11][6600/7330] lr: 1.000e-05, eta: 0:59:55, time: 0.446, data_time: 0.018, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0319, loss_cls: 0.1231, acc: 95.2268, loss_bbox: 0.1746, loss_mask: 0.1949, loss: 0.5361 2023-11-14 02:40:12,575 - mmdet - INFO - Epoch [11][6650/7330] lr: 1.000e-05, eta: 0:59:33, time: 0.445, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0325, loss_cls: 0.1275, acc: 95.0698, loss_bbox: 0.1803, loss_mask: 0.1974, loss: 0.5487 2023-11-14 02:40:35,214 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:40:35,214 - mmdet - INFO - Epoch [11][6700/7330] lr: 1.000e-05, eta: 0:59:10, time: 0.453, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0331, loss_cls: 0.1342, acc: 94.8171, loss_bbox: 0.1883, loss_mask: 0.1985, loss: 0.5660 2023-11-14 02:40:57,366 - mmdet - INFO - Epoch [11][6750/7330] lr: 1.000e-05, eta: 0:58:48, time: 0.443, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0316, loss_cls: 0.1227, acc: 95.3140, loss_bbox: 0.1717, loss_mask: 0.1925, loss: 0.5301 2023-11-14 02:41:19,505 - mmdet - INFO - Epoch [11][6800/7330] lr: 1.000e-05, eta: 0:58:26, time: 0.443, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0326, loss_cls: 0.1281, acc: 95.0398, loss_bbox: 0.1810, loss_mask: 0.1999, loss: 0.5527 2023-11-14 02:41:41,873 - mmdet - INFO - Epoch [11][6850/7330] lr: 1.000e-05, eta: 0:58:04, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0328, loss_cls: 0.1272, acc: 95.1006, loss_bbox: 0.1800, loss_mask: 0.1946, loss: 0.5460 2023-11-14 02:42:04,512 - mmdet - INFO - Epoch [11][6900/7330] lr: 1.000e-05, eta: 0:57:41, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0322, loss_cls: 0.1284, acc: 95.0273, loss_bbox: 0.1786, loss_mask: 0.1943, loss: 0.5458 2023-11-14 02:42:26,927 - mmdet - INFO - Epoch [11][6950/7330] lr: 1.000e-05, eta: 0:57:19, time: 0.448, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0321, loss_cls: 0.1235, acc: 95.1582, loss_bbox: 0.1788, loss_mask: 0.1959, loss: 0.5418 2023-11-14 02:42:49,275 - mmdet - INFO - Epoch [11][7000/7330] lr: 1.000e-05, eta: 0:56:57, time: 0.447, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0319, loss_cls: 0.1284, acc: 95.1023, loss_bbox: 0.1804, loss_mask: 0.1931, loss: 0.5457 2023-11-14 02:43:11,997 - mmdet - INFO - Epoch [11][7050/7330] lr: 1.000e-05, eta: 0:56:34, time: 0.454, data_time: 0.019, memory: 5732, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0337, loss_cls: 0.1316, acc: 94.9282, loss_bbox: 0.1818, loss_mask: 0.1955, loss: 0.5558 2023-11-14 02:43:34,290 - mmdet - INFO - Epoch [11][7100/7330] lr: 1.000e-05, eta: 0:56:12, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0324, loss_cls: 0.1283, acc: 95.0183, loss_bbox: 0.1784, loss_mask: 0.1940, loss: 0.5457 2023-11-14 02:43:56,667 - mmdet - INFO - Epoch [11][7150/7330] lr: 1.000e-05, eta: 0:55:50, time: 0.448, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0302, loss_cls: 0.1178, acc: 95.4551, loss_bbox: 0.1677, loss_mask: 0.1917, loss: 0.5175 2023-11-14 02:44:18,998 - mmdet - INFO - Epoch [11][7200/7330] lr: 1.000e-05, eta: 0:55:27, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0323, loss_cls: 0.1284, acc: 95.0947, loss_bbox: 0.1821, loss_mask: 0.1977, loss: 0.5524 2023-11-14 02:44:41,352 - mmdet - INFO - Epoch [11][7250/7330] lr: 1.000e-05, eta: 0:55:05, time: 0.447, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0318, loss_cls: 0.1279, acc: 95.0134, loss_bbox: 0.1798, loss_mask: 0.1941, loss: 0.5453 2023-11-14 02:45:03,829 - mmdet - INFO - Epoch [11][7300/7330] lr: 1.000e-05, eta: 0:54:43, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0340, loss_cls: 0.1343, acc: 94.8503, loss_bbox: 0.1911, loss_mask: 0.2011, loss: 0.5723 2023-11-14 02:45:17,753 - mmdet - INFO - Saving checkpoint at 11 epochs 2023-11-14 02:46:06,807 - mmdet - INFO - Evaluating bbox... 2023-11-14 02:46:34,687 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.499 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.715 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.544 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 ] = 0.539 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.650 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.615 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.615 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.615 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.656 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.770 2023-11-14 02:46:34,689 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.590 | bicycle | 0.385 | car | 0.504 | | motorcycle | 0.507 | airplane | 0.711 | bus | 0.718 | | train | 0.708 | truck | 0.471 | boat | 0.340 | | traffic light | 0.312 | fire hydrant | 0.758 | stop sign | 0.670 | | parking meter | 0.552 | bench | 0.322 | bird | 0.425 | | cat | 0.767 | dog | 0.701 | horse | 0.635 | | sheep | 0.604 | cow | 0.649 | elephant | 0.713 | | bear | 0.786 | zebra | 0.696 | giraffe | 0.710 | | backpack | 0.241 | umbrella | 0.480 | handbag | 0.265 | | tie | 0.419 | suitcase | 0.501 | frisbee | 0.707 | | skis | 0.315 | snowboard | 0.480 | sports ball | 0.491 | | kite | 0.475 | baseball bat | 0.451 | baseball glove | 0.459 | | skateboard | 0.613 | surfboard | 0.483 | tennis racket | 0.567 | | bottle | 0.475 | wine glass | 0.425 | cup | 0.513 | | fork | 0.500 | knife | 0.315 | spoon | 0.302 | | bowl | 0.471 | banana | 0.290 | apple | 0.279 | | sandwich | 0.488 | orange | 0.376 | broccoli | 0.255 | | carrot | 0.260 | hot dog | 0.453 | pizza | 0.578 | | donut | 0.569 | cake | 0.456 | chair | 0.376 | | couch | 0.490 | potted plant | 0.366 | bed | 0.510 | | dining table | 0.345 | toilet | 0.686 | tv | 0.649 | | laptop | 0.700 | mouse | 0.653 | remote | 0.438 | | keyboard | 0.574 | cell phone | 0.454 | microwave | 0.627 | | oven | 0.412 | toaster | 0.447 | sink | 0.451 | | refrigerator | 0.689 | book | 0.207 | clock | 0.529 | | vase | 0.437 | scissors | 0.439 | teddy bear | 0.573 | | hair drier | 0.270 | toothbrush | 0.386 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 02:46:34,689 - mmdet - INFO - Evaluating segm... 2023-11-14 02:47:02,995 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.444 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.684 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.477 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.245 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.475 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.637 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.378 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.594 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.719 2023-11-14 02:47:02,998 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.513 | bicycle | 0.239 | car | 0.458 | | motorcycle | 0.399 | airplane | 0.543 | bus | 0.689 | | train | 0.685 | truck | 0.446 | boat | 0.315 | | traffic light | 0.301 | fire hydrant | 0.708 | stop sign | 0.658 | | parking meter | 0.544 | bench | 0.245 | bird | 0.353 | | cat | 0.749 | dog | 0.649 | horse | 0.480 | | sheep | 0.536 | cow | 0.549 | elephant | 0.644 | | bear | 0.763 | zebra | 0.598 | giraffe | 0.559 | | backpack | 0.237 | umbrella | 0.520 | handbag | 0.241 | | tie | 0.382 | suitcase | 0.507 | frisbee | 0.677 | | skis | 0.063 | snowboard | 0.291 | sports ball | 0.490 | | kite | 0.342 | baseball bat | 0.336 | baseball glove | 0.481 | | skateboard | 0.382 | surfboard | 0.396 | tennis racket | 0.582 | | bottle | 0.455 | wine glass | 0.384 | cup | 0.514 | | fork | 0.261 | knife | 0.227 | spoon | 0.221 | | bowl | 0.435 | banana | 0.242 | apple | 0.274 | | sandwich | 0.504 | orange | 0.367 | broccoli | 0.233 | | carrot | 0.225 | hot dog | 0.355 | pizza | 0.554 | | donut | 0.566 | cake | 0.466 | chair | 0.269 | | couch | 0.409 | potted plant | 0.308 | bed | 0.391 | | dining table | 0.204 | toilet | 0.644 | tv | 0.672 | | laptop | 0.676 | mouse | 0.643 | remote | 0.387 | | keyboard | 0.553 | cell phone | 0.430 | microwave | 0.655 | | oven | 0.367 | toaster | 0.484 | sink | 0.417 | | refrigerator | 0.697 | book | 0.157 | clock | 0.529 | | vase | 0.425 | scissors | 0.319 | teddy bear | 0.544 | | hair drier | 0.236 | toothbrush | 0.250 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 02:47:03,403 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_10.pth was removed 2023-11-14 02:47:06,775 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_11.pth. 2023-11-14 02:47:06,775 - mmdet - INFO - Best bbox_mAP is 0.4987 at 11 epoch. 2023-11-14 02:47:06,776 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 02:47:06,776 - mmdet - INFO - Epoch(val) [11][625] bbox_mAP: 0.4987, bbox_mAP_50: 0.7149, bbox_mAP_75: 0.5444, bbox_mAP_s: 0.3231, bbox_mAP_m: 0.5388, bbox_mAP_l: 0.6499, bbox_mAP_copypaste: 0.4987 0.7149 0.5444 0.3231 0.5388 0.6499, segm_mAP: 0.4437, segm_mAP_50: 0.6844, segm_mAP_75: 0.4771, segm_mAP_s: 0.2454, segm_mAP_m: 0.4749, segm_mAP_l: 0.6369, segm_mAP_copypaste: 0.4437 0.6844 0.4771 0.2454 0.4749 0.6369 2023-11-14 02:47:32,596 - mmdet - INFO - Epoch [12][50/7330] lr: 1.000e-06, eta: 0:54:06, time: 0.516, data_time: 0.092, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0316, loss_cls: 0.1178, acc: 95.3950, loss_bbox: 0.1725, loss_mask: 0.1868, loss: 0.5196 2023-11-14 02:47:55,180 - mmdet - INFO - Epoch [12][100/7330] lr: 1.000e-06, eta: 0:53:44, time: 0.452, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0304, loss_cls: 0.1201, acc: 95.3457, loss_bbox: 0.1740, loss_mask: 0.1938, loss: 0.5287 2023-11-14 02:48:18,049 - mmdet - INFO - Epoch [12][150/7330] lr: 1.000e-06, eta: 0:53:22, time: 0.457, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0341, loss_cls: 0.1293, acc: 95.0352, loss_bbox: 0.1820, loss_mask: 0.1989, loss: 0.5573 2023-11-14 02:48:40,489 - mmdet - INFO - Epoch [12][200/7330] lr: 1.000e-06, eta: 0:52:59, time: 0.449, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0315, loss_cls: 0.1269, acc: 95.0791, loss_bbox: 0.1789, loss_mask: 0.1915, loss: 0.5397 2023-11-14 02:49:03,486 - mmdet - INFO - Epoch [12][250/7330] lr: 1.000e-06, eta: 0:52:37, time: 0.460, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0324, loss_cls: 0.1215, acc: 95.2837, loss_bbox: 0.1722, loss_mask: 0.1946, loss: 0.5322 2023-11-14 02:49:26,229 - mmdet - INFO - Epoch [12][300/7330] lr: 1.000e-06, eta: 0:52:15, time: 0.455, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0324, loss_cls: 0.1254, acc: 95.1331, loss_bbox: 0.1733, loss_mask: 0.1950, loss: 0.5380 2023-11-14 02:49:48,306 - mmdet - INFO - Epoch [12][350/7330] lr: 1.000e-06, eta: 0:51:53, time: 0.441, data_time: 0.018, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0309, loss_cls: 0.1214, acc: 95.2866, loss_bbox: 0.1743, loss_mask: 0.1952, loss: 0.5334 2023-11-14 02:50:10,625 - mmdet - INFO - Epoch [12][400/7330] lr: 1.000e-06, eta: 0:51:30, time: 0.446, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0323, loss_cls: 0.1243, acc: 95.1841, loss_bbox: 0.1733, loss_mask: 0.1932, loss: 0.5357 2023-11-14 02:50:33,764 - mmdet - INFO - Epoch [12][450/7330] lr: 1.000e-06, eta: 0:51:08, time: 0.463, data_time: 0.034, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0359, loss_cls: 0.1325, acc: 94.7759, loss_bbox: 0.1904, loss_mask: 0.2000, loss: 0.5710 2023-11-14 02:50:56,222 - mmdet - INFO - Epoch [12][500/7330] lr: 1.000e-06, eta: 0:50:46, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0324, loss_cls: 0.1252, acc: 95.1580, loss_bbox: 0.1772, loss_mask: 0.1919, loss: 0.5375 2023-11-14 02:51:19,010 - mmdet - INFO - Epoch [12][550/7330] lr: 1.000e-06, eta: 0:50:24, time: 0.456, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0325, loss_cls: 0.1265, acc: 95.0583, loss_bbox: 0.1773, loss_mask: 0.1873, loss: 0.5364 2023-11-14 02:51:41,965 - mmdet - INFO - Epoch [12][600/7330] lr: 1.000e-06, eta: 0:50:01, time: 0.459, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0325, loss_cls: 0.1273, acc: 95.0979, loss_bbox: 0.1770, loss_mask: 0.1949, loss: 0.5443 2023-11-14 02:52:04,579 - mmdet - INFO - Epoch [12][650/7330] lr: 1.000e-06, eta: 0:49:39, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0334, loss_cls: 0.1316, acc: 94.8767, loss_bbox: 0.1873, loss_mask: 0.2024, loss: 0.5666 2023-11-14 02:52:27,500 - mmdet - INFO - Epoch [12][700/7330] lr: 1.000e-06, eta: 0:49:17, time: 0.458, data_time: 0.032, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0324, loss_cls: 0.1248, acc: 95.1594, loss_bbox: 0.1783, loss_mask: 0.1965, loss: 0.5432 2023-11-14 02:52:49,749 - mmdet - INFO - Epoch [12][750/7330] lr: 1.000e-06, eta: 0:48:54, time: 0.445, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0304, loss_cls: 0.1214, acc: 95.3064, loss_bbox: 0.1715, loss_mask: 0.1906, loss: 0.5247 2023-11-14 02:53:11,950 - mmdet - INFO - Epoch [12][800/7330] lr: 1.000e-06, eta: 0:48:32, time: 0.444, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0280, loss_cls: 0.1140, acc: 95.6030, loss_bbox: 0.1681, loss_mask: 0.1865, loss: 0.5061 2023-11-14 02:53:34,288 - mmdet - INFO - Epoch [12][850/7330] lr: 1.000e-06, eta: 0:48:10, time: 0.447, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0307, loss_cls: 0.1219, acc: 95.3142, loss_bbox: 0.1765, loss_mask: 0.1934, loss: 0.5339 2023-11-14 02:53:56,685 - mmdet - INFO - Epoch [12][900/7330] lr: 1.000e-06, eta: 0:47:48, time: 0.448, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0302, loss_cls: 0.1213, acc: 95.3401, loss_bbox: 0.1706, loss_mask: 0.1895, loss: 0.5224 2023-11-14 02:54:19,294 - mmdet - INFO - Epoch [12][950/7330] lr: 1.000e-06, eta: 0:47:25, time: 0.452, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0329, loss_cls: 0.1272, acc: 95.0322, loss_bbox: 0.1818, loss_mask: 0.1940, loss: 0.5476 2023-11-14 02:54:41,389 - mmdet - INFO - Epoch [12][1000/7330] lr: 1.000e-06, eta: 0:47:03, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0301, loss_cls: 0.1224, acc: 95.2183, loss_bbox: 0.1747, loss_mask: 0.1938, loss: 0.5317 2023-11-14 02:55:03,698 - mmdet - INFO - Epoch [12][1050/7330] lr: 1.000e-06, eta: 0:46:41, time: 0.446, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0314, loss_cls: 0.1265, acc: 95.1125, loss_bbox: 0.1781, loss_mask: 0.1960, loss: 0.5437 2023-11-14 02:55:25,628 - mmdet - INFO - Epoch [12][1100/7330] lr: 1.000e-06, eta: 0:46:18, time: 0.439, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0308, loss_cls: 0.1183, acc: 95.4143, loss_bbox: 0.1695, loss_mask: 0.1921, loss: 0.5215 2023-11-14 02:55:47,951 - mmdet - INFO - Epoch [12][1150/7330] lr: 1.000e-06, eta: 0:45:56, time: 0.446, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0295, loss_cls: 0.1168, acc: 95.5105, loss_bbox: 0.1626, loss_mask: 0.1904, loss: 0.5104 2023-11-14 02:56:10,001 - mmdet - INFO - Epoch [12][1200/7330] lr: 1.000e-06, eta: 0:45:34, time: 0.441, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0293, loss_cls: 0.1183, acc: 95.4282, loss_bbox: 0.1706, loss_mask: 0.1910, loss: 0.5204 2023-11-14 02:56:32,454 - mmdet - INFO - Epoch [12][1250/7330] lr: 1.000e-06, eta: 0:45:11, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0330, loss_cls: 0.1299, acc: 94.9580, loss_bbox: 0.1858, loss_mask: 0.1967, loss: 0.5571 2023-11-14 02:56:55,554 - mmdet - INFO - Epoch [12][1300/7330] lr: 1.000e-06, eta: 0:44:49, time: 0.462, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0316, loss_cls: 0.1179, acc: 95.4321, loss_bbox: 0.1685, loss_mask: 0.1914, loss: 0.5204 2023-11-14 02:57:17,844 - mmdet - INFO - Epoch [12][1350/7330] lr: 1.000e-06, eta: 0:44:27, time: 0.446, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0317, loss_cls: 0.1236, acc: 95.2280, loss_bbox: 0.1769, loss_mask: 0.1919, loss: 0.5350 2023-11-14 02:57:40,090 - mmdet - INFO - Epoch [12][1400/7330] lr: 1.000e-06, eta: 0:44:05, time: 0.445, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0319, loss_cls: 0.1261, acc: 95.0923, loss_bbox: 0.1797, loss_mask: 0.1985, loss: 0.5474 2023-11-14 02:58:02,370 - mmdet - INFO - Epoch [12][1450/7330] lr: 1.000e-06, eta: 0:43:42, time: 0.446, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0329, loss_cls: 0.1226, acc: 95.2329, loss_bbox: 0.1744, loss_mask: 0.1961, loss: 0.5383 2023-11-14 02:58:24,862 - mmdet - INFO - Epoch [12][1500/7330] lr: 1.000e-06, eta: 0:43:20, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0332, loss_cls: 0.1314, acc: 94.9614, loss_bbox: 0.1866, loss_mask: 0.2009, loss: 0.5640 2023-11-14 02:58:47,564 - mmdet - INFO - Epoch [12][1550/7330] lr: 1.000e-06, eta: 0:42:58, time: 0.454, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0348, loss_cls: 0.1316, acc: 94.9492, loss_bbox: 0.1893, loss_mask: 0.2022, loss: 0.5693 2023-11-14 02:59:09,971 - mmdet - INFO - Epoch [12][1600/7330] lr: 1.000e-06, eta: 0:42:35, time: 0.448, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0313, loss_cls: 0.1213, acc: 95.2471, loss_bbox: 0.1719, loss_mask: 0.1942, loss: 0.5295 2023-11-14 02:59:31,998 - mmdet - INFO - Epoch [12][1650/7330] lr: 1.000e-06, eta: 0:42:13, time: 0.441, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0303, loss_cls: 0.1214, acc: 95.3137, loss_bbox: 0.1735, loss_mask: 0.1907, loss: 0.5265 2023-11-14 02:59:53,943 - mmdet - INFO - Epoch [12][1700/7330] lr: 1.000e-06, eta: 0:41:51, time: 0.439, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0301, loss_cls: 0.1205, acc: 95.3486, loss_bbox: 0.1727, loss_mask: 0.1923, loss: 0.5270 2023-11-14 03:00:16,448 - mmdet - INFO - Epoch [12][1750/7330] lr: 1.000e-06, eta: 0:41:28, time: 0.450, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0307, loss_cls: 0.1199, acc: 95.2998, loss_bbox: 0.1711, loss_mask: 0.1913, loss: 0.5235 2023-11-14 03:00:39,100 - mmdet - INFO - Epoch [12][1800/7330] lr: 1.000e-06, eta: 0:41:06, time: 0.453, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0329, loss_cls: 0.1286, acc: 95.0872, loss_bbox: 0.1779, loss_mask: 0.1950, loss: 0.5460 2023-11-14 03:01:01,561 - mmdet - INFO - Epoch [12][1850/7330] lr: 1.000e-06, eta: 0:40:44, time: 0.449, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0306, loss_cls: 0.1236, acc: 95.1829, loss_bbox: 0.1768, loss_mask: 0.1928, loss: 0.5344 2023-11-14 03:01:24,127 - mmdet - INFO - Epoch [12][1900/7330] lr: 1.000e-06, eta: 0:40:22, time: 0.451, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0318, loss_cls: 0.1275, acc: 94.9873, loss_bbox: 0.1850, loss_mask: 0.1993, loss: 0.5548 2023-11-14 03:01:46,294 - mmdet - INFO - Epoch [12][1950/7330] lr: 1.000e-06, eta: 0:39:59, time: 0.443, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0291, loss_cls: 0.1165, acc: 95.4900, loss_bbox: 0.1659, loss_mask: 0.1892, loss: 0.5112 2023-11-14 03:02:08,844 - mmdet - INFO - Epoch [12][2000/7330] lr: 1.000e-06, eta: 0:39:37, time: 0.451, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0301, loss_cls: 0.1217, acc: 95.2847, loss_bbox: 0.1722, loss_mask: 0.1912, loss: 0.5258 2023-11-14 03:02:31,668 - mmdet - INFO - Epoch [12][2050/7330] lr: 1.000e-06, eta: 0:39:15, time: 0.457, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0323, loss_cls: 0.1211, acc: 95.3176, loss_bbox: 0.1734, loss_mask: 0.1946, loss: 0.5330 2023-11-14 03:02:54,131 - mmdet - INFO - Epoch [12][2100/7330] lr: 1.000e-06, eta: 0:38:52, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0327, loss_cls: 0.1301, acc: 94.9807, loss_bbox: 0.1834, loss_mask: 0.1994, loss: 0.5583 2023-11-14 03:03:16,137 - mmdet - INFO - Epoch [12][2150/7330] lr: 1.000e-06, eta: 0:38:30, time: 0.440, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0299, loss_cls: 0.1237, acc: 95.1821, loss_bbox: 0.1719, loss_mask: 0.1957, loss: 0.5331 2023-11-14 03:03:38,208 - mmdet - INFO - Epoch [12][2200/7330] lr: 1.000e-06, eta: 0:38:08, time: 0.441, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0319, loss_cls: 0.1220, acc: 95.2473, loss_bbox: 0.1738, loss_mask: 0.1944, loss: 0.5335 2023-11-14 03:04:00,305 - mmdet - INFO - Epoch [12][2250/7330] lr: 1.000e-06, eta: 0:37:46, time: 0.442, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0322, loss_cls: 0.1241, acc: 95.1702, loss_bbox: 0.1790, loss_mask: 0.1942, loss: 0.5416 2023-11-14 03:04:22,151 - mmdet - INFO - Epoch [12][2300/7330] lr: 1.000e-06, eta: 0:37:23, time: 0.437, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0304, loss_cls: 0.1212, acc: 95.3301, loss_bbox: 0.1737, loss_mask: 0.1944, loss: 0.5301 2023-11-14 03:04:44,692 - mmdet - INFO - Epoch [12][2350/7330] lr: 1.000e-06, eta: 0:37:01, time: 0.451, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0323, loss_cls: 0.1288, acc: 95.0491, loss_bbox: 0.1849, loss_mask: 0.1953, loss: 0.5531 2023-11-14 03:05:07,092 - mmdet - INFO - Epoch [12][2400/7330] lr: 1.000e-06, eta: 0:36:39, time: 0.448, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0307, loss_cls: 0.1220, acc: 95.2207, loss_bbox: 0.1733, loss_mask: 0.1885, loss: 0.5256 2023-11-14 03:05:29,725 - mmdet - INFO - Epoch [12][2450/7330] lr: 1.000e-06, eta: 0:36:16, time: 0.453, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0326, loss_cls: 0.1276, acc: 95.0332, loss_bbox: 0.1814, loss_mask: 0.1972, loss: 0.5510 2023-11-14 03:05:52,233 - mmdet - INFO - Epoch [12][2500/7330] lr: 1.000e-06, eta: 0:35:54, time: 0.450, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0314, loss_cls: 0.1208, acc: 95.3240, loss_bbox: 0.1717, loss_mask: 0.1947, loss: 0.5292 2023-11-14 03:06:14,518 - mmdet - INFO - Epoch [12][2550/7330] lr: 1.000e-06, eta: 0:35:32, time: 0.446, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0316, loss_cls: 0.1189, acc: 95.3787, loss_bbox: 0.1727, loss_mask: 0.1883, loss: 0.5217 2023-11-14 03:06:36,762 - mmdet - INFO - Epoch [12][2600/7330] lr: 1.000e-06, eta: 0:35:09, time: 0.445, data_time: 0.020, memory: 5732, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0300, loss_cls: 0.1192, acc: 95.3877, loss_bbox: 0.1697, loss_mask: 0.1921, loss: 0.5212 2023-11-14 03:06:59,195 - mmdet - INFO - Epoch [12][2650/7330] lr: 1.000e-06, eta: 0:34:47, time: 0.449, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0310, loss_cls: 0.1180, acc: 95.4180, loss_bbox: 0.1695, loss_mask: 0.1930, loss: 0.5226 2023-11-14 03:07:21,663 - mmdet - INFO - Epoch [12][2700/7330] lr: 1.000e-06, eta: 0:34:25, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0332, loss_cls: 0.1270, acc: 95.0571, loss_bbox: 0.1775, loss_mask: 0.1966, loss: 0.5457 2023-11-14 03:07:43,606 - mmdet - INFO - Epoch [12][2750/7330] lr: 1.000e-06, eta: 0:34:02, time: 0.439, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0301, loss_cls: 0.1205, acc: 95.2883, loss_bbox: 0.1761, loss_mask: 0.1955, loss: 0.5320 2023-11-14 03:08:05,897 - mmdet - INFO - Epoch [12][2800/7330] lr: 1.000e-06, eta: 0:33:40, time: 0.446, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0314, loss_cls: 0.1199, acc: 95.3684, loss_bbox: 0.1726, loss_mask: 0.1944, loss: 0.5290 2023-11-14 03:08:28,516 - mmdet - INFO - Epoch [12][2850/7330] lr: 1.000e-06, eta: 0:33:18, time: 0.452, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0318, loss_cls: 0.1245, acc: 95.1738, loss_bbox: 0.1767, loss_mask: 0.1906, loss: 0.5353 2023-11-14 03:08:50,957 - mmdet - INFO - Epoch [12][2900/7330] lr: 1.000e-06, eta: 0:32:56, time: 0.449, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0323, loss_cls: 0.1220, acc: 95.2527, loss_bbox: 0.1776, loss_mask: 0.1948, loss: 0.5378 2023-11-14 03:09:13,234 - mmdet - INFO - Epoch [12][2950/7330] lr: 1.000e-06, eta: 0:32:33, time: 0.445, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0309, loss_cls: 0.1213, acc: 95.3660, loss_bbox: 0.1751, loss_mask: 0.1905, loss: 0.5293 2023-11-14 03:09:35,425 - mmdet - INFO - Epoch [12][3000/7330] lr: 1.000e-06, eta: 0:32:11, time: 0.444, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0092, loss_rpn_bbox: 0.0316, loss_cls: 0.1179, acc: 95.5083, loss_bbox: 0.1712, loss_mask: 0.1938, loss: 0.5236 2023-11-14 03:09:57,846 - mmdet - INFO - Epoch [12][3050/7330] lr: 1.000e-06, eta: 0:31:49, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0330, loss_cls: 0.1299, acc: 94.9937, loss_bbox: 0.1865, loss_mask: 0.2020, loss: 0.5639 2023-11-14 03:10:20,169 - mmdet - INFO - Epoch [12][3100/7330] lr: 1.000e-06, eta: 0:31:26, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0308, loss_cls: 0.1259, acc: 95.1658, loss_bbox: 0.1797, loss_mask: 0.1925, loss: 0.5407 2023-11-14 03:10:42,958 - mmdet - INFO - Epoch [12][3150/7330] lr: 1.000e-06, eta: 0:31:04, time: 0.456, data_time: 0.030, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0314, loss_cls: 0.1264, acc: 95.1140, loss_bbox: 0.1804, loss_mask: 0.1921, loss: 0.5424 2023-11-14 03:11:05,083 - mmdet - INFO - Epoch [12][3200/7330] lr: 1.000e-06, eta: 0:30:42, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0328, loss_cls: 0.1299, acc: 94.9490, loss_bbox: 0.1856, loss_mask: 0.1978, loss: 0.5585 2023-11-14 03:11:27,868 - mmdet - INFO - Epoch [12][3250/7330] lr: 1.000e-06, eta: 0:30:20, time: 0.456, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0340, loss_cls: 0.1311, acc: 94.9226, loss_bbox: 0.1819, loss_mask: 0.1988, loss: 0.5580 2023-11-14 03:11:49,861 - mmdet - INFO - Epoch [12][3300/7330] lr: 1.000e-06, eta: 0:29:57, time: 0.440, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0317, loss_cls: 0.1242, acc: 95.1790, loss_bbox: 0.1774, loss_mask: 0.1955, loss: 0.5412 2023-11-14 03:12:12,497 - mmdet - INFO - Epoch [12][3350/7330] lr: 1.000e-06, eta: 0:29:35, time: 0.453, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0335, loss_cls: 0.1293, acc: 94.9788, loss_bbox: 0.1824, loss_mask: 0.1980, loss: 0.5560 2023-11-14 03:12:35,103 - mmdet - INFO - Epoch [12][3400/7330] lr: 1.000e-06, eta: 0:29:13, time: 0.452, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0305, loss_cls: 0.1201, acc: 95.3418, loss_bbox: 0.1693, loss_mask: 0.1926, loss: 0.5235 2023-11-14 03:12:57,472 - mmdet - INFO - Epoch [12][3450/7330] lr: 1.000e-06, eta: 0:28:50, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0316, loss_cls: 0.1224, acc: 95.2083, loss_bbox: 0.1752, loss_mask: 0.1930, loss: 0.5337 2023-11-14 03:13:20,164 - mmdet - INFO - Epoch [12][3500/7330] lr: 1.000e-06, eta: 0:28:28, time: 0.454, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0335, loss_cls: 0.1269, acc: 95.1062, loss_bbox: 0.1806, loss_mask: 0.1972, loss: 0.5494 2023-11-14 03:13:42,508 - mmdet - INFO - Epoch [12][3550/7330] lr: 1.000e-06, eta: 0:28:06, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0325, loss_cls: 0.1259, acc: 95.0720, loss_bbox: 0.1813, loss_mask: 0.1964, loss: 0.5478 2023-11-14 03:14:04,925 - mmdet - INFO - Epoch [12][3600/7330] lr: 1.000e-06, eta: 0:27:43, time: 0.448, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0304, loss_cls: 0.1213, acc: 95.3037, loss_bbox: 0.1748, loss_mask: 0.1913, loss: 0.5288 2023-11-14 03:14:26,987 - mmdet - INFO - Epoch [12][3650/7330] lr: 1.000e-06, eta: 0:27:21, time: 0.441, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0300, loss_cls: 0.1226, acc: 95.2546, loss_bbox: 0.1766, loss_mask: 0.1943, loss: 0.5339 2023-11-14 03:14:49,707 - mmdet - INFO - Epoch [12][3700/7330] lr: 1.000e-06, eta: 0:26:59, time: 0.454, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0310, loss_cls: 0.1223, acc: 95.2590, loss_bbox: 0.1749, loss_mask: 0.1909, loss: 0.5307 2023-11-14 03:15:12,205 - mmdet - INFO - Epoch [12][3750/7330] lr: 1.000e-06, eta: 0:26:37, time: 0.450, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0313, loss_cls: 0.1255, acc: 95.1394, loss_bbox: 0.1801, loss_mask: 0.1960, loss: 0.5453 2023-11-14 03:15:34,506 - mmdet - INFO - Epoch [12][3800/7330] lr: 1.000e-06, eta: 0:26:14, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0145, loss_rpn_bbox: 0.0320, loss_cls: 0.1310, acc: 94.9385, loss_bbox: 0.1791, loss_mask: 0.1995, loss: 0.5562 2023-11-14 03:15:56,777 - mmdet - INFO - Epoch [12][3850/7330] lr: 1.000e-06, eta: 0:25:52, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0332, loss_cls: 0.1250, acc: 95.1055, loss_bbox: 0.1751, loss_mask: 0.1950, loss: 0.5394 2023-11-14 03:16:18,816 - mmdet - INFO - Epoch [12][3900/7330] lr: 1.000e-06, eta: 0:25:30, time: 0.441, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0297, loss_cls: 0.1161, acc: 95.5117, loss_bbox: 0.1641, loss_mask: 0.1901, loss: 0.5105 2023-11-14 03:16:41,313 - mmdet - INFO - Epoch [12][3950/7330] lr: 1.000e-06, eta: 0:25:07, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0310, loss_cls: 0.1243, acc: 95.1965, loss_bbox: 0.1761, loss_mask: 0.1951, loss: 0.5385 2023-11-14 03:17:04,058 - mmdet - INFO - Epoch [12][4000/7330] lr: 1.000e-06, eta: 0:24:45, time: 0.455, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0319, loss_cls: 0.1250, acc: 95.1284, loss_bbox: 0.1805, loss_mask: 0.1942, loss: 0.5431 2023-11-14 03:17:26,298 - mmdet - INFO - Epoch [12][4050/7330] lr: 1.000e-06, eta: 0:24:23, time: 0.445, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0323, loss_cls: 0.1255, acc: 95.0823, loss_bbox: 0.1794, loss_mask: 0.1986, loss: 0.5473 2023-11-14 03:17:48,955 - mmdet - INFO - Epoch [12][4100/7330] lr: 1.000e-06, eta: 0:24:00, time: 0.453, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0317, loss_cls: 0.1239, acc: 95.2136, loss_bbox: 0.1746, loss_mask: 0.1921, loss: 0.5347 2023-11-14 03:18:11,232 - mmdet - INFO - Epoch [12][4150/7330] lr: 1.000e-06, eta: 0:23:38, time: 0.445, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0301, loss_cls: 0.1211, acc: 95.3115, loss_bbox: 0.1761, loss_mask: 0.1952, loss: 0.5328 2023-11-14 03:18:33,464 - mmdet - INFO - Epoch [12][4200/7330] lr: 1.000e-06, eta: 0:23:16, time: 0.445, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0330, loss_cls: 0.1256, acc: 95.0996, loss_bbox: 0.1807, loss_mask: 0.1990, loss: 0.5504 2023-11-14 03:18:56,192 - mmdet - INFO - Epoch [12][4250/7330] lr: 1.000e-06, eta: 0:22:54, time: 0.454, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0332, loss_cls: 0.1262, acc: 95.0686, loss_bbox: 0.1790, loss_mask: 0.1957, loss: 0.5458 2023-11-14 03:19:18,406 - mmdet - INFO - Epoch [12][4300/7330] lr: 1.000e-06, eta: 0:22:31, time: 0.444, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0323, loss_cls: 0.1219, acc: 95.2463, loss_bbox: 0.1757, loss_mask: 0.1952, loss: 0.5358 2023-11-14 03:19:40,614 - mmdet - INFO - Epoch [12][4350/7330] lr: 1.000e-06, eta: 0:22:09, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0315, loss_cls: 0.1249, acc: 95.0527, loss_bbox: 0.1752, loss_mask: 0.1947, loss: 0.5374 2023-11-14 03:20:02,982 - mmdet - INFO - Epoch [12][4400/7330] lr: 1.000e-06, eta: 0:21:47, time: 0.447, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0294, loss_cls: 0.1237, acc: 95.2310, loss_bbox: 0.1746, loss_mask: 0.1920, loss: 0.5308 2023-11-14 03:20:25,386 - mmdet - INFO - Epoch [12][4450/7330] lr: 1.000e-06, eta: 0:21:24, time: 0.448, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0333, loss_cls: 0.1264, acc: 95.0415, loss_bbox: 0.1766, loss_mask: 0.1972, loss: 0.5451 2023-11-14 03:20:47,821 - mmdet - INFO - Epoch [12][4500/7330] lr: 1.000e-06, eta: 0:21:02, time: 0.449, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0319, loss_cls: 0.1223, acc: 95.3093, loss_bbox: 0.1741, loss_mask: 0.1949, loss: 0.5347 2023-11-14 03:21:10,089 - mmdet - INFO - Epoch [12][4550/7330] lr: 1.000e-06, eta: 0:20:40, time: 0.445, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0313, loss_cls: 0.1225, acc: 95.2610, loss_bbox: 0.1767, loss_mask: 0.1973, loss: 0.5391 2023-11-14 03:21:32,308 - mmdet - INFO - Epoch [12][4600/7330] lr: 1.000e-06, eta: 0:20:17, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0319, loss_cls: 0.1226, acc: 95.2549, loss_bbox: 0.1769, loss_mask: 0.1970, loss: 0.5405 2023-11-14 03:21:54,637 - mmdet - INFO - Epoch [12][4650/7330] lr: 1.000e-06, eta: 0:19:55, time: 0.447, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0305, loss_cls: 0.1235, acc: 95.1506, loss_bbox: 0.1743, loss_mask: 0.1927, loss: 0.5325 2023-11-14 03:22:17,090 - mmdet - INFO - Epoch [12][4700/7330] lr: 1.000e-06, eta: 0:19:33, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0318, loss_cls: 0.1234, acc: 95.2068, loss_bbox: 0.1749, loss_mask: 0.1935, loss: 0.5348 2023-11-14 03:22:39,508 - mmdet - INFO - Epoch [12][4750/7330] lr: 1.000e-06, eta: 0:19:10, time: 0.448, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0334, loss_cls: 0.1313, acc: 94.8464, loss_bbox: 0.1846, loss_mask: 0.1995, loss: 0.5610 2023-11-14 03:23:01,506 - mmdet - INFO - Epoch [12][4800/7330] lr: 1.000e-06, eta: 0:18:48, time: 0.440, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0289, loss_cls: 0.1170, acc: 95.4355, loss_bbox: 0.1712, loss_mask: 0.1916, loss: 0.5187 2023-11-14 03:23:23,813 - mmdet - INFO - Epoch [12][4850/7330] lr: 1.000e-06, eta: 0:18:26, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0323, loss_cls: 0.1237, acc: 95.2620, loss_bbox: 0.1772, loss_mask: 0.1962, loss: 0.5415 2023-11-14 03:23:46,283 - mmdet - INFO - Epoch [12][4900/7330] lr: 1.000e-06, eta: 0:18:04, time: 0.449, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0335, loss_cls: 0.1265, acc: 95.1328, loss_bbox: 0.1773, loss_mask: 0.1956, loss: 0.5454 2023-11-14 03:24:08,307 - mmdet - INFO - Epoch [12][4950/7330] lr: 1.000e-06, eta: 0:17:41, time: 0.440, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0309, loss_cls: 0.1245, acc: 95.1814, loss_bbox: 0.1745, loss_mask: 0.1961, loss: 0.5377 2023-11-14 03:24:30,427 - mmdet - INFO - Epoch [12][5000/7330] lr: 1.000e-06, eta: 0:17:19, time: 0.442, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0319, loss_cls: 0.1289, acc: 95.0266, loss_bbox: 0.1822, loss_mask: 0.2004, loss: 0.5554 2023-11-14 03:24:52,940 - mmdet - INFO - Epoch [12][5050/7330] lr: 1.000e-06, eta: 0:16:57, time: 0.450, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0330, loss_cls: 0.1227, acc: 95.2234, loss_bbox: 0.1781, loss_mask: 0.1963, loss: 0.5416 2023-11-14 03:25:14,826 - mmdet - INFO - Epoch [12][5100/7330] lr: 1.000e-06, eta: 0:16:34, time: 0.438, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0309, loss_cls: 0.1218, acc: 95.2798, loss_bbox: 0.1744, loss_mask: 0.1955, loss: 0.5337 2023-11-14 03:25:37,269 - mmdet - INFO - Epoch [12][5150/7330] lr: 1.000e-06, eta: 0:16:12, time: 0.449, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0333, loss_cls: 0.1293, acc: 94.9741, loss_bbox: 0.1846, loss_mask: 0.1973, loss: 0.5566 2023-11-14 03:25:59,675 - mmdet - INFO - Epoch [12][5200/7330] lr: 1.000e-06, eta: 0:15:50, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0324, loss_cls: 0.1247, acc: 95.2068, loss_bbox: 0.1791, loss_mask: 0.1960, loss: 0.5439 2023-11-14 03:26:22,092 - mmdet - INFO - Epoch [12][5250/7330] lr: 1.000e-06, eta: 0:15:27, time: 0.448, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0322, loss_cls: 0.1271, acc: 95.0513, loss_bbox: 0.1827, loss_mask: 0.1965, loss: 0.5494 2023-11-14 03:26:43,931 - mmdet - INFO - Epoch [12][5300/7330] lr: 1.000e-06, eta: 0:15:05, time: 0.437, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0307, loss_cls: 0.1252, acc: 95.1899, loss_bbox: 0.1781, loss_mask: 0.1929, loss: 0.5376 2023-11-14 03:27:06,098 - mmdet - INFO - Epoch [12][5350/7330] lr: 1.000e-06, eta: 0:14:43, time: 0.443, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0312, loss_cls: 0.1180, acc: 95.4187, loss_bbox: 0.1692, loss_mask: 0.1934, loss: 0.5229 2023-11-14 03:27:28,194 - mmdet - INFO - Epoch [12][5400/7330] lr: 1.000e-06, eta: 0:14:20, time: 0.442, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0310, loss_cls: 0.1222, acc: 95.2825, loss_bbox: 0.1731, loss_mask: 0.1900, loss: 0.5269 2023-11-14 03:27:50,503 - mmdet - INFO - Epoch [12][5450/7330] lr: 1.000e-06, eta: 0:13:58, time: 0.445, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0320, loss_cls: 0.1232, acc: 95.1787, loss_bbox: 0.1766, loss_mask: 0.1930, loss: 0.5362 2023-11-14 03:28:12,922 - mmdet - INFO - Epoch [12][5500/7330] lr: 1.000e-06, eta: 0:13:36, time: 0.449, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0338, loss_cls: 0.1284, acc: 95.0183, loss_bbox: 0.1881, loss_mask: 0.1986, loss: 0.5609 2023-11-14 03:28:35,015 - mmdet - INFO - Epoch [12][5550/7330] lr: 1.000e-06, eta: 0:13:14, time: 0.442, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0292, loss_cls: 0.1162, acc: 95.4993, loss_bbox: 0.1678, loss_mask: 0.1904, loss: 0.5139 2023-11-14 03:28:57,111 - mmdet - INFO - Epoch [12][5600/7330] lr: 1.000e-06, eta: 0:12:51, time: 0.442, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0300, loss_cls: 0.1220, acc: 95.2842, loss_bbox: 0.1758, loss_mask: 0.1966, loss: 0.5345 2023-11-14 03:29:19,319 - mmdet - INFO - Epoch [12][5650/7330] lr: 1.000e-06, eta: 0:12:29, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0120, loss_rpn_bbox: 0.0341, loss_cls: 0.1281, acc: 95.1287, loss_bbox: 0.1853, loss_mask: 0.1965, loss: 0.5560 2023-11-14 03:29:41,369 - mmdet - INFO - Epoch [12][5700/7330] lr: 1.000e-06, eta: 0:12:07, time: 0.441, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0306, loss_cls: 0.1261, acc: 95.1162, loss_bbox: 0.1801, loss_mask: 0.1952, loss: 0.5434 2023-11-14 03:30:03,659 - mmdet - INFO - Epoch [12][5750/7330] lr: 1.000e-06, eta: 0:11:44, time: 0.446, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0110, loss_rpn_bbox: 0.0301, loss_cls: 0.1216, acc: 95.2686, loss_bbox: 0.1784, loss_mask: 0.1977, loss: 0.5388 2023-11-14 03:30:25,433 - mmdet - INFO - Epoch [12][5800/7330] lr: 1.000e-06, eta: 0:11:22, time: 0.435, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0299, loss_cls: 0.1150, acc: 95.5332, loss_bbox: 0.1664, loss_mask: 0.1913, loss: 0.5124 2023-11-14 03:30:47,720 - mmdet - INFO - Epoch [12][5850/7330] lr: 1.000e-06, eta: 0:11:00, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0310, loss_cls: 0.1208, acc: 95.3403, loss_bbox: 0.1718, loss_mask: 0.1884, loss: 0.5229 2023-11-14 03:31:10,090 - mmdet - INFO - Epoch [12][5900/7330] lr: 1.000e-06, eta: 0:10:37, time: 0.447, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0320, loss_cls: 0.1236, acc: 95.2720, loss_bbox: 0.1777, loss_mask: 0.1966, loss: 0.5423 2023-11-14 03:31:32,729 - mmdet - INFO - Epoch [12][5950/7330] lr: 1.000e-06, eta: 0:10:15, time: 0.453, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0331, loss_cls: 0.1277, acc: 95.0364, loss_bbox: 0.1858, loss_mask: 0.2016, loss: 0.5608 2023-11-14 03:31:54,925 - mmdet - INFO - Epoch [12][6000/7330] lr: 1.000e-06, eta: 0:09:53, time: 0.444, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0318, loss_cls: 0.1252, acc: 95.1133, loss_bbox: 0.1767, loss_mask: 0.1942, loss: 0.5394 2023-11-14 03:32:16,646 - mmdet - INFO - Epoch [12][6050/7330] lr: 1.000e-06, eta: 0:09:30, time: 0.434, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0291, loss_cls: 0.1156, acc: 95.4636, loss_bbox: 0.1630, loss_mask: 0.1894, loss: 0.5077 2023-11-14 03:32:38,898 - mmdet - INFO - Epoch [12][6100/7330] lr: 1.000e-06, eta: 0:09:08, time: 0.445, data_time: 0.021, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0326, loss_cls: 0.1275, acc: 95.0662, loss_bbox: 0.1787, loss_mask: 0.1964, loss: 0.5471 2023-11-14 03:33:00,934 - mmdet - INFO - Epoch [12][6150/7330] lr: 1.000e-06, eta: 0:08:46, time: 0.441, data_time: 0.028, memory: 5732, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0330, loss_cls: 0.1317, acc: 94.9314, loss_bbox: 0.1868, loss_mask: 0.1983, loss: 0.5622 2023-11-14 03:33:23,126 - mmdet - INFO - Epoch [12][6200/7330] lr: 1.000e-06, eta: 0:08:24, time: 0.444, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0319, loss_cls: 0.1242, acc: 95.1931, loss_bbox: 0.1780, loss_mask: 0.1968, loss: 0.5423 2023-11-14 03:33:45,447 - mmdet - INFO - Epoch [12][6250/7330] lr: 1.000e-06, eta: 0:08:01, time: 0.446, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0307, loss_cls: 0.1227, acc: 95.3308, loss_bbox: 0.1738, loss_mask: 0.1947, loss: 0.5340 2023-11-14 03:34:07,522 - mmdet - INFO - Epoch [12][6300/7330] lr: 1.000e-06, eta: 0:07:39, time: 0.442, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0308, loss_cls: 0.1261, acc: 95.1431, loss_bbox: 0.1785, loss_mask: 0.1928, loss: 0.5395 2023-11-14 03:34:29,268 - mmdet - INFO - Epoch [12][6350/7330] lr: 1.000e-06, eta: 0:07:17, time: 0.435, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0297, loss_cls: 0.1236, acc: 95.2415, loss_bbox: 0.1725, loss_mask: 0.1929, loss: 0.5298 2023-11-14 03:34:51,586 - mmdet - INFO - Epoch [12][6400/7330] lr: 1.000e-06, eta: 0:06:54, time: 0.446, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0311, loss_cls: 0.1239, acc: 95.1443, loss_bbox: 0.1770, loss_mask: 0.1928, loss: 0.5361 2023-11-14 03:35:13,706 - mmdet - INFO - Epoch [12][6450/7330] lr: 1.000e-06, eta: 0:06:32, time: 0.442, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0113, loss_rpn_bbox: 0.0313, loss_cls: 0.1210, acc: 95.3149, loss_bbox: 0.1771, loss_mask: 0.1924, loss: 0.5331 2023-11-14 03:35:36,004 - mmdet - INFO - Epoch [12][6500/7330] lr: 1.000e-06, eta: 0:06:10, time: 0.446, data_time: 0.029, memory: 5732, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0314, loss_cls: 0.1255, acc: 95.1545, loss_bbox: 0.1754, loss_mask: 0.1933, loss: 0.5371 2023-11-14 03:35:58,356 - mmdet - INFO - Epoch [12][6550/7330] lr: 1.000e-06, eta: 0:05:47, time: 0.447, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0343, loss_cls: 0.1274, acc: 95.0430, loss_bbox: 0.1831, loss_mask: 0.1987, loss: 0.5551 2023-11-14 03:36:20,810 - mmdet - INFO - Epoch [12][6600/7330] lr: 1.000e-06, eta: 0:05:25, time: 0.449, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0311, loss_cls: 0.1226, acc: 95.2542, loss_bbox: 0.1728, loss_mask: 0.1945, loss: 0.5327 2023-11-14 03:36:43,421 - mmdet - INFO - Epoch [12][6650/7330] lr: 1.000e-06, eta: 0:05:03, time: 0.452, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0321, loss_cls: 0.1261, acc: 95.1165, loss_bbox: 0.1759, loss_mask: 0.1963, loss: 0.5428 2023-11-14 03:37:05,583 - mmdet - INFO - Epoch [12][6700/7330] lr: 1.000e-06, eta: 0:04:41, time: 0.443, data_time: 0.024, memory: 5732, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0321, loss_cls: 0.1271, acc: 95.0493, loss_bbox: 0.1796, loss_mask: 0.1942, loss: 0.5440 2023-11-14 03:37:27,411 - mmdet - INFO - Epoch [12][6750/7330] lr: 1.000e-06, eta: 0:04:18, time: 0.436, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0303, loss_cls: 0.1217, acc: 95.2253, loss_bbox: 0.1793, loss_mask: 0.1939, loss: 0.5355 2023-11-14 03:37:49,570 - mmdet - INFO - Epoch [12][6800/7330] lr: 1.000e-06, eta: 0:03:56, time: 0.443, data_time: 0.027, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0315, loss_cls: 0.1231, acc: 95.3149, loss_bbox: 0.1731, loss_mask: 0.1912, loss: 0.5300 2023-11-14 03:38:12,152 - mmdet - INFO - Epoch [12][6850/7330] lr: 1.000e-06, eta: 0:03:34, time: 0.452, data_time: 0.026, memory: 5732, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0346, loss_cls: 0.1298, acc: 94.9949, loss_bbox: 0.1852, loss_mask: 0.2019, loss: 0.5644 2023-11-14 03:38:34,588 - mmdet - INFO - Epoch [12][6900/7330] lr: 1.000e-06, eta: 0:03:11, time: 0.449, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0308, loss_cls: 0.1210, acc: 95.3125, loss_bbox: 0.1716, loss_mask: 0.1920, loss: 0.5265 2023-11-14 03:38:56,716 - mmdet - INFO - Epoch [12][6950/7330] lr: 1.000e-06, eta: 0:02:49, time: 0.443, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0320, loss_cls: 0.1231, acc: 95.2524, loss_bbox: 0.1774, loss_mask: 0.1947, loss: 0.5389 2023-11-14 03:39:18,644 - mmdet - INFO - Epoch [12][7000/7330] lr: 1.000e-06, eta: 0:02:27, time: 0.439, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0308, loss_cls: 0.1180, acc: 95.4553, loss_bbox: 0.1698, loss_mask: 0.1904, loss: 0.5194 2023-11-14 03:39:40,625 - mmdet - INFO - Epoch [12][7050/7330] lr: 1.000e-06, eta: 0:02:04, time: 0.440, data_time: 0.022, memory: 5732, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0325, loss_cls: 0.1245, acc: 95.2209, loss_bbox: 0.1791, loss_mask: 0.1972, loss: 0.5450 2023-11-14 03:40:03,041 - mmdet - INFO - Epoch [12][7100/7330] lr: 1.000e-06, eta: 0:01:42, time: 0.448, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0119, loss_rpn_bbox: 0.0318, loss_cls: 0.1248, acc: 95.1326, loss_bbox: 0.1775, loss_mask: 0.1946, loss: 0.5406 2023-11-14 03:40:24,986 - mmdet - INFO - Epoch [12][7150/7330] lr: 1.000e-06, eta: 0:01:20, time: 0.439, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0323, loss_cls: 0.1253, acc: 95.2012, loss_bbox: 0.1747, loss_mask: 0.1916, loss: 0.5357 2023-11-14 03:40:47,000 - mmdet - INFO - Epoch [12][7200/7330] lr: 1.000e-06, eta: 0:00:57, time: 0.440, data_time: 0.025, memory: 5732, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0326, loss_cls: 0.1286, acc: 95.0112, loss_bbox: 0.1810, loss_mask: 0.1939, loss: 0.5484 2023-11-14 03:41:09,537 - mmdet - INFO - Epoch [12][7250/7330] lr: 1.000e-06, eta: 0:00:35, time: 0.451, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0126, loss_rpn_bbox: 0.0339, loss_cls: 0.1346, acc: 94.8274, loss_bbox: 0.1839, loss_mask: 0.2001, loss: 0.5650 2023-11-14 03:41:31,641 - mmdet - INFO - Epoch [12][7300/7330] lr: 1.000e-06, eta: 0:00:13, time: 0.442, data_time: 0.023, memory: 5732, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0313, loss_cls: 0.1157, acc: 95.5383, loss_bbox: 0.1675, loss_mask: 0.1925, loss: 0.5174 2023-11-14 03:41:45,483 - mmdet - INFO - Saving checkpoint at 12 epochs 2023-11-14 03:42:35,865 - mmdet - INFO - Evaluating bbox... 2023-11-14 03:43:04,389 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.500 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.717 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.543 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.322 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.540 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.652 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.617 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 ] = 0.658 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.774 2023-11-14 03:43:04,391 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.590 | bicycle | 0.389 | car | 0.503 | | motorcycle | 0.508 | airplane | 0.710 | bus | 0.717 | | train | 0.711 | truck | 0.470 | boat | 0.338 | | traffic light | 0.315 | fire hydrant | 0.760 | stop sign | 0.688 | | parking meter | 0.553 | bench | 0.324 | bird | 0.426 | | cat | 0.760 | dog | 0.703 | horse | 0.643 | | sheep | 0.606 | cow | 0.651 | elephant | 0.716 | | bear | 0.779 | zebra | 0.698 | giraffe | 0.716 | | backpack | 0.244 | umbrella | 0.483 | handbag | 0.268 | | tie | 0.420 | suitcase | 0.503 | frisbee | 0.715 | | skis | 0.320 | snowboard | 0.489 | sports ball | 0.490 | | kite | 0.474 | baseball bat | 0.449 | baseball glove | 0.463 | | skateboard | 0.612 | surfboard | 0.486 | tennis racket | 0.567 | | bottle | 0.472 | wine glass | 0.427 | cup | 0.514 | | fork | 0.503 | knife | 0.317 | spoon | 0.309 | | bowl | 0.476 | banana | 0.292 | apple | 0.280 | | sandwich | 0.483 | orange | 0.376 | broccoli | 0.258 | | carrot | 0.259 | hot dog | 0.449 | pizza | 0.581 | | donut | 0.575 | cake | 0.454 | chair | 0.378 | | couch | 0.497 | potted plant | 0.365 | bed | 0.503 | | dining table | 0.338 | toilet | 0.686 | tv | 0.651 | | laptop | 0.707 | mouse | 0.650 | remote | 0.443 | | keyboard | 0.587 | cell phone | 0.459 | microwave | 0.627 | | oven | 0.409 | toaster | 0.496 | sink | 0.457 | | refrigerator | 0.682 | book | 0.202 | clock | 0.527 | | vase | 0.435 | scissors | 0.444 | teddy bear | 0.571 | | hair drier | 0.259 | toothbrush | 0.385 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 03:43:04,392 - mmdet - INFO - Evaluating segm... 2023-11-14 03:43:33,082 - mmdet - INFO - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.445 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=1000 ] = 0.687 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=1000 ] = 0.478 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=1000 ] = 0.244 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=1000 ] = 0.477 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.638 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=1000 ] = 0.556 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 ] = 0.595 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=1000 ] = 0.720 2023-11-14 03:43:33,084 - mmdet - INFO - +---------------+-------+--------------+-------+----------------+-------+ | category | AP | category | AP | category | AP | +---------------+-------+--------------+-------+----------------+-------+ | person | 0.514 | bicycle | 0.236 | car | 0.458 | | motorcycle | 0.401 | airplane | 0.543 | bus | 0.685 | | train | 0.689 | truck | 0.446 | boat | 0.318 | | traffic light | 0.302 | fire hydrant | 0.709 | stop sign | 0.675 | | parking meter | 0.549 | bench | 0.245 | bird | 0.355 | | cat | 0.738 | dog | 0.646 | horse | 0.484 | | sheep | 0.540 | cow | 0.556 | elephant | 0.648 | | bear | 0.757 | zebra | 0.597 | giraffe | 0.556 | | backpack | 0.232 | umbrella | 0.522 | handbag | 0.240 | | tie | 0.381 | suitcase | 0.513 | frisbee | 0.681 | | skis | 0.065 | snowboard | 0.300 | sports ball | 0.488 | | kite | 0.340 | baseball bat | 0.337 | baseball glove | 0.482 | | skateboard | 0.383 | surfboard | 0.396 | tennis racket | 0.583 | | bottle | 0.453 | wine glass | 0.388 | cup | 0.513 | | fork | 0.259 | knife | 0.225 | spoon | 0.228 | | bowl | 0.442 | banana | 0.243 | apple | 0.279 | | sandwich | 0.498 | orange | 0.369 | broccoli | 0.232 | | carrot | 0.226 | hot dog | 0.359 | pizza | 0.556 | | donut | 0.570 | cake | 0.466 | chair | 0.268 | | couch | 0.416 | potted plant | 0.307 | bed | 0.386 | | dining table | 0.199 | toilet | 0.647 | tv | 0.673 | | laptop | 0.680 | mouse | 0.644 | remote | 0.390 | | keyboard | 0.560 | cell phone | 0.429 | microwave | 0.656 | | oven | 0.369 | toaster | 0.495 | sink | 0.421 | | refrigerator | 0.691 | book | 0.155 | clock | 0.532 | | vase | 0.423 | scissors | 0.321 | teddy bear | 0.538 | | hair drier | 0.222 | toothbrush | 0.250 | None | None | +---------------+-------+--------------+-------+----------------+-------+ 2023-11-14 03:43:33,554 - mmdet - INFO - The previous best checkpoint /mnt/petrelfs/lizhiqi/DINO/detection/work_dirs/mask_rcnn_flash_internimage_b_fpn_1x_coco/best_bbox_mAP_epoch_11.pth was removed 2023-11-14 03:43:37,117 - mmdet - INFO - Now best checkpoint is saved as best_bbox_mAP_epoch_12.pth. 2023-11-14 03:43:37,117 - mmdet - INFO - Best bbox_mAP is 0.5005 at 12 epoch. 2023-11-14 03:43:37,117 - mmdet - INFO - Exp name: mask_rcnn_flash_internimage_b_fpn_1x_coco.py 2023-11-14 03:43:37,117 - mmdet - INFO - Epoch(val) [12][625] bbox_mAP: 0.5005, bbox_mAP_50: 0.7167, bbox_mAP_75: 0.5434, bbox_mAP_s: 0.3224, bbox_mAP_m: 0.5401, bbox_mAP_l: 0.6520, bbox_mAP_copypaste: 0.5005 0.7167 0.5434 0.3224 0.5401 0.6520, segm_mAP: 0.4446, segm_mAP_50: 0.6865, segm_mAP_75: 0.4778, segm_mAP_s: 0.2445, segm_mAP_m: 0.4768, segm_mAP_l: 0.6375, segm_mAP_copypaste: 0.4446 0.6865 0.4778 0.2445 0.4768 0.6375