| return { | |
| "meta": { | |
| "epoch": 20, | |
| "iter": 19141, | |
| "cfg": "default_scope = 'mmpose'\ndefault_hooks = dict(\n timer=dict(type='IterTimerHook'),\n logger=dict(type='LoggerHook', interval=50),\n param_scheduler=dict(type='ParamSchedulerHook'),\n checkpoint=dict(\n type='CheckpointHook',\n interval=10,\n save_best='coco-wholebody/AP',\n rule='greater',\n max_keep_ckpts=1),\n sampler_seed=dict(type='DistSamplerSeedHook'),\n visualization=dict(type='PoseVisualizationHook', enable=False))\ncustom_hooks = [\n dict(\n type='EMAHook',\n ema_type='ExpMomentumEMA',\n momentum=0.0002,\n update_buffers=True,\n priority=49),\n dict(\n type='mmdet.PipelineSwitchHook',\n switch_epoch=240,\n switch_pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n shift_factor=0.0,\n scale_factor=[0.75, 1.25],\n rotate_factor=60),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=0.5)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n ])\n]\nenv_cfg = dict(\n cudnn_benchmark=False,\n mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),\n dist_cfg=dict(backend='nccl'))\nvis_backends = [dict(type='LocalVisBackend')]\nvisualizer = dict(\n type='PoseLocalVisualizer',\n vis_backends=[dict(type='LocalVisBackend')],\n name='visualizer')\nlog_processor = dict(\n type='LogProcessor', window_size=50, by_epoch=True, num_digits=6)\nlog_level = 'INFO'\nload_from = None\nresume = False\nbackend_args = dict(backend='local')\ntrain_cfg = dict(by_epoch=True, max_epochs=60, val_interval=10)\nval_cfg = dict()\ntest_cfg = dict()\nmax_epochs = 270\nstage2_num_epochs = 30\nbase_lr = 0.004\nrandomness = dict(seed=21)\noptim_wrapper = dict(\n type='OptimWrapper',\n optimizer=dict(type='AdamW', lr=0.004, weight_decay=0.05),\n paramwise_cfg=dict(\n norm_decay_mult=0, bias_decay_mult=0, bypass_duplicate=True),\n clip_grad=dict(max_norm=1.0, norm_type=2))\nparam_scheduler = [\n dict(\n type='LinearLR', start_factor=1e-05, by_epoch=False, begin=0,\n end=1000),\n dict(\n type='CosineAnnealingLR',\n eta_min=0.0002,\n begin=135,\n end=270,\n T_max=135,\n by_epoch=True,\n convert_to_iter_based=True)\n]\nauto_scale_lr = dict(base_batch_size=512)\ncodec = dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)\nmodel = dict(\n type='PoseEstimatorDistiller',\n two_dis=True,\n teacher_pretrained=\n '/home/yangzhendong/Projects/mmpose/work_dirs/rtmpose_x_dis_l__coco-ubody-384x288/rtm-l_66.4.pth',\n teacher_cfg=\n 'configs/wholebody_2d_keypoint/rtmpose/ubody/rtmpose-l_8xb32-270e_coco-ubody-wholebody-384x288.py',\n student_cfg=\n 'configs/wholebody_2d_keypoint/rtmpose/ubody/rtmpose-l_8xb32-270e_coco-ubody-wholebody-384x288.py',\n distill_cfg=[\n dict(methods=[\n dict(\n type='MGD_2Loss',\n name='loss_mgd',\n use_this=True,\n student_channels=1024,\n teacher_channels=1024,\n alpha_mgd=7e-05,\n lambda_mgd=0.15)\n ]),\n dict(methods=[\n dict(type='NKDLoss', name='loss_nkd', use_this=True, weight=1)\n ])\n ],\n data_preprocessor=dict(\n type='PoseDataPreprocessor',\n mean=[123.675, 116.28, 103.53],\n std=[58.395, 57.12, 57.375],\n bgr_to_rgb=True),\n train_cfg=dict(max_epochs=60, val_interval=10))\ndataset_type = 'CocoWholeBodyDataset'\ndata_mode = 'topdown'\ndata_root = '/data/'\ntrain_pipeline = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform', scale_factor=[0.6, 1.4], rotate_factor=80),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=1.0)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n]\nval_pipeline = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n]\ntrain_pipeline_stage2 = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n shift_factor=0.0,\n scale_factor=[0.75, 1.25],\n rotate_factor=60),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=0.5)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n]\ndatasets = [\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Magic_show/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Magic_show/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Entertainment/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Entertainment/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/ConductMusic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/ConductMusic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Online_class/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Online_class/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TalkShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TalkShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Speech/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Speech/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Fitness/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Fitness/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Interview/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Interview/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Olympic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Olympic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TVShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TVShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Singing/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Singing/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/SignLanguage/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/SignLanguage/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Movie/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Movie/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/LiveVlog/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/LiveVlog/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/VideoConference/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/VideoConference/'),\n pipeline=[])\n]\ndataset_coco = dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[])\nscene = [\n 'Magic_show', 'Entertainment', 'ConductMusic', 'Online_class', 'TalkShow',\n 'Speech', 'Fitness', 'Interview', 'Olympic', 'TVShow', 'Singing',\n 'SignLanguage', 'Movie', 'LiveVlog', 'VideoConference'\n]\ni = 14\ntrain_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n sampler=dict(type='DefaultSampler', shuffle=True),\n dataset=dict(\n type='CombinedDataset',\n metainfo=dict(from_file='configs/_base_/datasets/coco_wholebody.py'),\n datasets=[\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Magic_show/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Magic_show/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Entertainment/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Entertainment/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/ConductMusic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/ConductMusic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Online_class/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Online_class/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TalkShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TalkShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Speech/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Speech/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Fitness/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Fitness/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Interview/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Interview/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Olympic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Olympic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TVShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TVShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Singing/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Singing/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/SignLanguage/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/SignLanguage/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Movie/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Movie/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/LiveVlog/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/LiveVlog/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/VideoConference/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/VideoConference/'),\n pipeline=[])\n ],\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n scale_factor=[0.6, 1.4],\n rotate_factor=80),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=1.0)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n ],\n test_mode=False))\nval_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n drop_last=False,\n sampler=dict(type='DefaultSampler', shuffle=False, round_up=False),\n dataset=dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_val_v1.0.json',\n bbox_file=\n '/data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json',\n data_prefix=dict(img='coco/val2017/'),\n test_mode=True,\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n ]))\ntest_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n drop_last=False,\n sampler=dict(type='DefaultSampler', shuffle=False, round_up=False),\n dataset=dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_val_v1.0.json',\n bbox_file=\n '/data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json',\n data_prefix=dict(img='coco/val2017/'),\n test_mode=True,\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n ]))\nval_evaluator = dict(\n type='CocoWholeBodyMetric',\n ann_file='/data/coco/annotations/coco_wholebody_val_v1.0.json')\ntest_evaluator = dict(\n type='CocoWholeBodyMetric',\n ann_file='/data/coco/annotations/coco_wholebody_val_v1.0.json')\nfind_unused_parameters = True\nmgd = True\nnkd = True\nlauncher = 'pytorch'\nwork_dir = './work_dirs/rtmpose_l-ll__coco-ubody-384x288'\n", | |
| "seed": 21, | |
| "experiment_name": "rtmpose_l-ll__coco-ubody-384x288_20230706_095637", | |
| "time": "20230706_131003", | |
| "mmengine_version": "0.7.2", | |
| "dataset_meta": { | |
| "dataset_name": "coco_wholebody", | |
| "num_keypoints": 133, | |
| "keypoint_colors": { | |
| "type": "ndarray", | |
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| "dict": {}, | |
| }, | |
| "num_skeleton_links": 65, | |
| "skeleton_link_colors": { | |
| "type": "ndarray", | |
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| "dict": {}, | |
| }, | |
| "dataset_keypoint_weights": { | |
| "type": "ndarray", | |
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| "dict": {}, | |
| }, | |
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| "cfg": "default_scope = 'mmpose'\ndefault_hooks = dict(\n timer=dict(type='IterTimerHook'),\n logger=dict(type='LoggerHook', interval=50),\n param_scheduler=dict(type='ParamSchedulerHook'),\n checkpoint=dict(\n type='CheckpointHook',\n interval=10,\n save_best='coco-wholebody/AP',\n rule='greater',\n max_keep_ckpts=1),\n sampler_seed=dict(type='DistSamplerSeedHook'),\n visualization=dict(type='PoseVisualizationHook', enable=False))\ncustom_hooks = [\n dict(\n type='EMAHook',\n ema_type='ExpMomentumEMA',\n momentum=0.0002,\n update_buffers=True,\n priority=49),\n dict(\n type='mmdet.PipelineSwitchHook',\n switch_epoch=240,\n switch_pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n shift_factor=0.0,\n scale_factor=[0.75, 1.25],\n rotate_factor=60),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=0.5)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n ])\n]\nenv_cfg = dict(\n cudnn_benchmark=False,\n mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),\n dist_cfg=dict(backend='nccl'))\nvis_backends = [dict(type='LocalVisBackend')]\nvisualizer = dict(\n type='PoseLocalVisualizer',\n vis_backends=[dict(type='LocalVisBackend')],\n name='visualizer')\nlog_processor = dict(\n type='LogProcessor', window_size=50, by_epoch=True, num_digits=6)\nlog_level = 'INFO'\nload_from = None\nresume = False\nbackend_args = dict(backend='local')\ntrain_cfg = dict(by_epoch=True, max_epochs=60, val_interval=10)\nval_cfg = dict()\ntest_cfg = dict()\nmax_epochs = 270\nstage2_num_epochs = 30\nbase_lr = 0.004\nrandomness = dict(seed=21)\noptim_wrapper = dict(\n type='OptimWrapper',\n optimizer=dict(type='AdamW', lr=0.004, weight_decay=0.05),\n paramwise_cfg=dict(\n norm_decay_mult=0, bias_decay_mult=0, bypass_duplicate=True),\n clip_grad=dict(max_norm=1.0, norm_type=2))\nparam_scheduler = [\n dict(\n type='LinearLR', start_factor=1e-05, by_epoch=False, begin=0,\n end=1000),\n dict(\n type='CosineAnnealingLR',\n eta_min=0.0002,\n begin=135,\n end=270,\n T_max=135,\n by_epoch=True,\n convert_to_iter_based=True)\n]\nauto_scale_lr = dict(base_batch_size=512)\ncodec = dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)\nmodel = dict(\n type='PoseEstimatorDistiller',\n two_dis=True,\n teacher_pretrained=\n '/home/yangzhendong/Projects/mmpose/work_dirs/rtmpose_x_dis_l__coco-ubody-384x288/rtm-l_66.4.pth',\n teacher_cfg=\n 'configs/wholebody_2d_keypoint/rtmpose/ubody/rtmpose-l_8xb32-270e_coco-ubody-wholebody-384x288.py',\n student_cfg=\n 'configs/wholebody_2d_keypoint/rtmpose/ubody/rtmpose-l_8xb32-270e_coco-ubody-wholebody-384x288.py',\n distill_cfg=[\n dict(methods=[\n dict(\n type='MGD_2Loss',\n name='loss_mgd',\n use_this=True,\n student_channels=1024,\n teacher_channels=1024,\n alpha_mgd=7e-05,\n lambda_mgd=0.15)\n ]),\n dict(methods=[\n dict(type='NKDLoss', name='loss_nkd', use_this=True, weight=1)\n ])\n ],\n data_preprocessor=dict(\n type='PoseDataPreprocessor',\n mean=[123.675, 116.28, 103.53],\n std=[58.395, 57.12, 57.375],\n bgr_to_rgb=True),\n train_cfg=dict(max_epochs=60, val_interval=10))\ndataset_type = 'CocoWholeBodyDataset'\ndata_mode = 'topdown'\ndata_root = '/data/'\ntrain_pipeline = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform', scale_factor=[0.6, 1.4], rotate_factor=80),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=1.0)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n]\nval_pipeline = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n]\ntrain_pipeline_stage2 = [\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n shift_factor=0.0,\n scale_factor=[0.75, 1.25],\n rotate_factor=60),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=0.5)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n]\ndatasets = [\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Magic_show/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Magic_show/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Entertainment/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Entertainment/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/ConductMusic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/ConductMusic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Online_class/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Online_class/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TalkShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TalkShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Speech/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Speech/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Fitness/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Fitness/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Interview/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Interview/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Olympic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Olympic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TVShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TVShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Singing/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Singing/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/SignLanguage/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/SignLanguage/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Movie/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Movie/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/LiveVlog/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/LiveVlog/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/VideoConference/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/VideoConference/'),\n pipeline=[])\n]\ndataset_coco = dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[])\nscene = [\n 'Magic_show', 'Entertainment', 'ConductMusic', 'Online_class', 'TalkShow',\n 'Speech', 'Fitness', 'Interview', 'Olympic', 'TVShow', 'Singing',\n 'SignLanguage', 'Movie', 'LiveVlog', 'VideoConference'\n]\ni = 14\ntrain_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n sampler=dict(type='DefaultSampler', shuffle=True),\n dataset=dict(\n type='CombinedDataset',\n metainfo=dict(from_file='configs/_base_/datasets/coco_wholebody.py'),\n datasets=[\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_train_v1.0.json',\n data_prefix=dict(img='coco/train2017/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Magic_show/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Magic_show/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Entertainment/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Entertainment/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/ConductMusic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/ConductMusic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/Online_class/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Online_class/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TalkShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TalkShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Speech/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Speech/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Fitness/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Fitness/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Interview/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Interview/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Olympic/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Olympic/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/TVShow/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/TVShow/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Singing/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Singing/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/SignLanguage/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/SignLanguage/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/Movie/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/Movie/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='UBody/annotations/LiveVlog/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/LiveVlog/'),\n pipeline=[]),\n dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file=\n 'UBody/annotations/VideoConference/keypoint_annotation.json',\n data_prefix=dict(img='UBody/images/VideoConference/'),\n pipeline=[])\n ],\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='RandomFlip', direction='horizontal'),\n dict(type='RandomHalfBody'),\n dict(\n type='RandomBBoxTransform',\n scale_factor=[0.6, 1.4],\n rotate_factor=80),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='mmdet.YOLOXHSVRandomAug'),\n dict(\n type='Albumentation',\n transforms=[\n dict(type='Blur', p=0.1),\n dict(type='MedianBlur', p=0.1),\n dict(\n type='CoarseDropout',\n max_holes=1,\n max_height=0.4,\n max_width=0.4,\n min_holes=1,\n min_height=0.2,\n min_width=0.2,\n p=1.0)\n ]),\n dict(\n type='GenerateTarget',\n encoder=dict(\n type='SimCCLabel',\n input_size=(288, 384),\n sigma=(6.0, 6.93),\n simcc_split_ratio=2.0,\n normalize=False,\n use_dark=False)),\n dict(type='PackPoseInputs')\n ],\n test_mode=False))\nval_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n drop_last=False,\n sampler=dict(type='DefaultSampler', shuffle=False, round_up=False),\n dataset=dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_val_v1.0.json',\n bbox_file=\n '/data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json',\n data_prefix=dict(img='coco/val2017/'),\n test_mode=True,\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n ]))\ntest_dataloader = dict(\n batch_size=32,\n num_workers=10,\n persistent_workers=True,\n drop_last=False,\n sampler=dict(type='DefaultSampler', shuffle=False, round_up=False),\n dataset=dict(\n type='CocoWholeBodyDataset',\n data_root='/data/',\n data_mode='topdown',\n ann_file='coco/annotations/coco_wholebody_val_v1.0.json',\n bbox_file=\n '/data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json',\n data_prefix=dict(img='coco/val2017/'),\n test_mode=True,\n pipeline=[\n dict(type='LoadImage', backend_args=dict(backend='local')),\n dict(type='GetBBoxCenterScale'),\n dict(type='TopdownAffine', input_size=(288, 384)),\n dict(type='PackPoseInputs')\n ]))\nval_evaluator = dict(\n type='CocoWholeBodyMetric',\n ann_file='/data/coco/annotations/coco_wholebody_val_v1.0.json')\ntest_evaluator = dict(\n type='CocoWholeBodyMetric',\n ann_file='/data/coco/annotations/coco_wholebody_val_v1.0.json')\nfind_unused_parameters = True\nmgd = True\nnkd = True\nlauncher = 'pytorch'\nwork_dir = './work_dirs/rtmpose_l-ll__coco-ubody-384x288'\n", | |
| "seed": 21, | |
| "experiment_name": "rtmpose_l-ll__coco-ubody-384x288_20230706_095637", | |
| "mmengine_version": "0.7.2", | |
| "epoch": 19, | |
| "iter": 19139, | |
| "max_epochs": 60, | |
| "max_iters": 57420, | |
| "eta": {"type": "float64", "repr": "0.0", "dict": {}}, | |
| "last_ckpt": "/home/yangzhendong/Projects/mmpose/work_dirs/rtmpose_l-ll__coco-ubody-384x288/epoch_20.pth", | |
| "best_score": {"type": "float64", "repr": "0.665450746403108", "dict": {}}, | |
| "best_ckpt": "/home/yangzhendong/Projects/mmpose/work_dirs/rtmpose_l-ll__coco-ubody-384x288/best_coco-wholebody_AP_epoch_20.pth", | |
| "dataset_meta": { | |
| "dataset_name": "coco_wholebody", | |
| "num_keypoints": 133, | |
| "keypoint_colors": { | |
| "type": "ndarray", | |
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| "dict": {}, | |
| }, | |
| "num_skeleton_links": 65, | |
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| "3": "left_ear", | |
| "4": "right_ear", | |
| "5": "left_shoulder", | |
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| "9": "left_wrist", | |
| "10": "right_wrist", | |
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| "12": "right_hip", | |
| "13": "left_knee", | |
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| "15": "left_ankle", | |
| "16": "right_ankle", | |
| "17": "left_big_toe", | |
| "18": "left_small_toe", | |
| "19": "left_heel", | |
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| "21": "right_small_toe", | |
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| "88": "face-65", | |
| "89": "face-66", | |
| "90": "face-67", | |
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| "92": "left_thumb1", | |
| "93": "left_thumb2", | |
| "94": "left_thumb3", | |
| "95": "left_thumb4", | |
| "96": "left_forefinger1", | |
| "97": "left_forefinger2", | |
| "98": "left_forefinger3", | |
| "99": "left_forefinger4", | |
| "100": "left_middle_finger1", | |
| "101": "left_middle_finger2", | |
| "102": "left_middle_finger3", | |
| "103": "left_middle_finger4", | |
| "104": "left_ring_finger1", | |
| "105": "left_ring_finger2", | |
| "106": "left_ring_finger3", | |
| "107": "left_ring_finger4", | |
| "108": "left_pinky_finger1", | |
| "109": "left_pinky_finger2", | |
| "110": "left_pinky_finger3", | |
| "111": "left_pinky_finger4", | |
| "112": "right_hand_root", | |
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| "116": "right_thumb4", | |
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| "121": "right_middle_finger1", | |
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| "129": "right_pinky_finger1", | |
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| "131": "right_pinky_finger3", | |
| "132": "right_pinky_finger4", | |
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| }, | |
| "resumed_keys": { | |
| "cfg": True, | |
| "seed": True, | |
| "experiment_name": True, | |
| "mmengine_version": True, | |
| "epoch": True, | |
| "iter": True, | |
| "max_epochs": True, | |
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| "train/data_time": True, | |
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| "train/loss_nkd": True, | |
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| "eta": True, | |
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| "val/time": True, | |
| "val/coco-wholebody/AP": True, | |
| "val/coco-wholebody/AP ": {"5": True, "75": True}, | |
| "val/coco-wholebody/AP (M)": True, | |
| "val/coco-wholebody/AP (L)": True, | |
| "val/coco-wholebody/AR": True, | |
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| "val/coco-wholebody/AR (L)": True, | |
| "best_score": True, | |
| "best_ckpt": True, | |
| }, | |
| }, | |
| } | |