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137 changes: 137 additions & 0 deletions
137
...s/body_3d_keypoint/pose_lift/h36m/pose-lift_motionbert-243frm_8xb32-120e_h36m-original.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,137 @@ | ||
| _base_ = ['../../../_base_/default_runtime.py'] | ||
|
|
||
| vis_backends = [ | ||
| dict(type='LocalVisBackend'), | ||
| ] | ||
| visualizer = dict( | ||
| type='Pose3dLocalVisualizer', vis_backends=vis_backends, name='visualizer') | ||
|
|
||
| # runtime | ||
| train_cfg = dict(max_epochs=120, val_interval=10) | ||
|
|
||
| # optimizer | ||
| optim_wrapper = dict( | ||
| optimizer=dict(type='AdamW', lr=0.0002, weight_decay=0.01)) | ||
|
|
||
| # learning policy | ||
| param_scheduler = [ | ||
| dict(type='ExponentialLR', gamma=0.99, end=120, by_epoch=True) | ||
| ] | ||
|
|
||
| auto_scale_lr = dict(base_batch_size=512) | ||
|
|
||
| # hooks | ||
| default_hooks = dict( | ||
| checkpoint=dict( | ||
| type='CheckpointHook', | ||
| save_best='MPJPE', | ||
| rule='less', | ||
| max_keep_ckpts=1), | ||
| logger=dict(type='LoggerHook', interval=20), | ||
| ) | ||
|
|
||
| # codec settings | ||
| train_codec = dict( | ||
| type='MotionBERTLabel', num_keypoints=17, concat_vis=True, mode='train') | ||
| val_codec = dict( | ||
| type='MotionBERTLabel', num_keypoints=17, concat_vis=True, rootrel=True) | ||
|
|
||
| # model settings | ||
| model = dict( | ||
| type='PoseLifter', | ||
| backbone=dict( | ||
| type='DSTFormer', | ||
| in_channels=3, | ||
| feat_size=512, | ||
| depth=5, | ||
| num_heads=8, | ||
| mlp_ratio=2, | ||
| seq_len=243, | ||
| att_fuse=True, | ||
| ), | ||
| head=dict( | ||
| type='MotionRegressionHead', | ||
| in_channels=512, | ||
| out_channels=3, | ||
| embedding_size=512, | ||
| loss=dict(type='MPJPEVelocityJointLoss'), | ||
| decoder=val_codec, | ||
| ), | ||
| test_cfg=dict(flip_test=True)) | ||
|
|
||
| # base dataset settings | ||
| dataset_type = 'Human36mDataset' | ||
| data_root = 'data/h36m/' | ||
|
|
||
| # pipelines | ||
| train_pipeline = [ | ||
| dict(type='GenerateTarget', encoder=train_codec), | ||
| dict( | ||
| type='RandomFlipAroundRoot', | ||
| keypoints_flip_cfg=dict(center_mode='static', center_x=0.), | ||
| target_flip_cfg=dict(center_mode='static', center_x=0.), | ||
| flip_label=True), | ||
| dict( | ||
| type='PackPoseInputs', | ||
| meta_keys=('id', 'category_id', 'target_img_path', 'flip_indices', | ||
| 'factor', 'camera_param')) | ||
| ] | ||
| val_pipeline = [ | ||
| dict(type='GenerateTarget', encoder=val_codec), | ||
| dict( | ||
| type='PackPoseInputs', | ||
| meta_keys=('id', 'category_id', 'target_img_path', 'flip_indices', | ||
| 'factor', 'camera_param')) | ||
| ] | ||
|
|
||
| # data loaders | ||
| train_dataloader = dict( | ||
| batch_size=32, | ||
| prefetch_factor=4, | ||
| pin_memory=True, | ||
| num_workers=2, | ||
| persistent_workers=True, | ||
| sampler=dict(type='DefaultSampler', shuffle=True), | ||
| dataset=dict( | ||
| type=dataset_type, | ||
| ann_file='annotation_body3d/fps50/h36m_train_original.npz', | ||
| seq_len=1, | ||
| multiple_target=243, | ||
| multiple_target_step=81, | ||
| camera_param_file='annotation_body3d/cameras.pkl', | ||
| data_root=data_root, | ||
| data_prefix=dict(img='images/'), | ||
| pipeline=train_pipeline, | ||
| )) | ||
|
|
||
| val_dataloader = dict( | ||
| batch_size=32, | ||
| prefetch_factor=4, | ||
| pin_memory=True, | ||
| num_workers=2, | ||
| persistent_workers=True, | ||
| sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), | ||
| dataset=dict( | ||
| type=dataset_type, | ||
| ann_file='annotation_body3d/fps50/h36m_test_original.npz', | ||
| factor_file='annotation_body3d/fps50/h36m_factors.npy', | ||
| seq_len=1, | ||
| seq_step=1, | ||
| multiple_target=243, | ||
| camera_param_file='annotation_body3d/cameras.pkl', | ||
| data_root=data_root, | ||
| data_prefix=dict(img='images/'), | ||
| pipeline=val_pipeline, | ||
| test_mode=True, | ||
| )) | ||
| test_dataloader = val_dataloader | ||
|
|
||
| # evaluators | ||
| skip_list = [ | ||
| 'S9_Greet', 'S9_SittingDown', 'S9_Wait_1', 'S9_Greeting', 'S9_Waiting_1' | ||
| ] | ||
| val_evaluator = [ | ||
| dict(type='MPJPE', mode='mpjpe', skip_list=skip_list), | ||
| dict(type='MPJPE', mode='p-mpjpe', skip_list=skip_list) | ||
| ] | ||
| test_evaluator = val_evaluator |
142 changes: 142 additions & 0 deletions
142
...body_3d_keypoint/pose_lift/h36m/pose-lift_motionbert-ft-243frm_8xb32-60e_h36m-original.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,142 @@ | ||
| _base_ = ['../../../_base_/default_runtime.py'] | ||
|
|
||
| vis_backends = [ | ||
| dict(type='LocalVisBackend'), | ||
| ] | ||
| visualizer = dict( | ||
| type='Pose3dLocalVisualizer', vis_backends=vis_backends, name='visualizer') | ||
|
|
||
| # runtime | ||
| train_cfg = dict(max_epochs=60, val_interval=10) | ||
|
|
||
| # optimizer | ||
| optim_wrapper = dict( | ||
| optimizer=dict(type='AdamW', lr=0.0002, weight_decay=0.01)) | ||
|
|
||
| # learning policy | ||
| param_scheduler = [ | ||
| dict(type='ExponentialLR', gamma=0.99, end=60, by_epoch=True) | ||
| ] | ||
|
|
||
| auto_scale_lr = dict(base_batch_size=512) | ||
|
|
||
| # hooks | ||
| default_hooks = dict( | ||
| checkpoint=dict( | ||
| type='CheckpointHook', | ||
| save_best='MPJPE', | ||
| rule='less', | ||
| max_keep_ckpts=1), | ||
| logger=dict(type='LoggerHook', interval=20), | ||
| ) | ||
|
|
||
| # codec settings | ||
| train_codec = dict( | ||
| type='MotionBERTLabel', num_keypoints=17, concat_vis=True, mode='train') | ||
| val_codec = dict( | ||
| type='MotionBERTLabel', num_keypoints=17, concat_vis=True, rootrel=True) | ||
|
|
||
| # model settings | ||
| model = dict( | ||
| type='PoseLifter', | ||
| backbone=dict( | ||
| type='DSTFormer', | ||
| in_channels=3, | ||
| feat_size=512, | ||
| depth=5, | ||
| num_heads=8, | ||
| mlp_ratio=2, | ||
| seq_len=243, | ||
| att_fuse=True, | ||
| ), | ||
| head=dict( | ||
| type='MotionRegressionHead', | ||
| in_channels=512, | ||
| out_channels=3, | ||
| embedding_size=512, | ||
| loss=dict(type='MPJPEVelocityJointLoss'), | ||
| decoder=val_codec, | ||
| ), | ||
| test_cfg=dict(flip_test=True), | ||
| init_cfg=dict( | ||
| type='Pretrained', | ||
| checkpoint='https://download.openmmlab.com/mmpose/v1/body_3d_keypoint/' | ||
| 'pose_lift/h36m/motionbert_pretrain_h36m-29ffebf5_20230719.pth'), | ||
| ) | ||
|
|
||
| # base dataset settings | ||
| dataset_type = 'Human36mDataset' | ||
| data_root = 'data/h36m/' | ||
|
|
||
| # pipelines | ||
| train_pipeline = [ | ||
| dict(type='GenerateTarget', encoder=train_codec), | ||
| dict( | ||
| type='RandomFlipAroundRoot', | ||
| keypoints_flip_cfg=dict(center_mode='static', center_x=0.), | ||
| target_flip_cfg=dict(center_mode='static', center_x=0.), | ||
| flip_label=True), | ||
| dict( | ||
| type='PackPoseInputs', | ||
| meta_keys=('id', 'category_id', 'target_img_path', 'flip_indices', | ||
| 'factor', 'camera_param')) | ||
| ] | ||
| val_pipeline = [ | ||
| dict(type='GenerateTarget', encoder=val_codec), | ||
| dict( | ||
| type='PackPoseInputs', | ||
| meta_keys=('id', 'category_id', 'target_img_path', 'flip_indices', | ||
| 'factor', 'camera_param')) | ||
| ] | ||
|
|
||
| # data loaders | ||
| train_dataloader = dict( | ||
| batch_size=32, | ||
| prefetch_factor=4, | ||
| pin_memory=True, | ||
| num_workers=2, | ||
| persistent_workers=True, | ||
| sampler=dict(type='DefaultSampler', shuffle=True), | ||
| dataset=dict( | ||
| type=dataset_type, | ||
| ann_file='annotation_body3d/fps50/h36m_train_original.npz', | ||
| seq_len=1, | ||
| multiple_target=243, | ||
| multiple_target_step=81, | ||
| camera_param_file='annotation_body3d/cameras.pkl', | ||
| data_root=data_root, | ||
| data_prefix=dict(img='images/'), | ||
| pipeline=train_pipeline, | ||
| )) | ||
|
|
||
| val_dataloader = dict( | ||
| batch_size=32, | ||
| prefetch_factor=4, | ||
| pin_memory=True, | ||
| num_workers=2, | ||
| persistent_workers=True, | ||
| sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), | ||
| dataset=dict( | ||
| type=dataset_type, | ||
| ann_file='annotation_body3d/fps50/h36m_test_original.npz', | ||
| factor_file='annotation_body3d/fps50/h36m_factors.npy', | ||
| seq_len=1, | ||
| seq_step=1, | ||
| multiple_target=243, | ||
| camera_param_file='annotation_body3d/cameras.pkl', | ||
| data_root=data_root, | ||
| data_prefix=dict(img='images/'), | ||
| pipeline=val_pipeline, | ||
| test_mode=True, | ||
| )) | ||
| test_dataloader = val_dataloader | ||
|
|
||
| # evaluators | ||
| skip_list = [ | ||
| 'S9_Greet', 'S9_SittingDown', 'S9_Wait_1', 'S9_Greeting', 'S9_Waiting_1' | ||
| ] | ||
| val_evaluator = [ | ||
| dict(type='MPJPE', mode='mpjpe', skip_list=skip_list), | ||
| dict(type='MPJPE', mode='p-mpjpe', skip_list=skip_list) | ||
| ] | ||
| test_evaluator = val_evaluator |
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