[Feature] C2F dataset part

configs/body/3d_kpt_sview_rgb_img/end2end/h36m/coarse2fine_h36m.py

@@ -0,0 +1,194 @@
+log_level = 'INFO'
+load_from = None
+resume_from = None
+dist_params = dict(backend='nccl')
+workflow = [('train', 1)]
+checkpoint_config = dict(interval=10)
+evaluation = dict(interval=10, metric=['mpjpe', 'p-mpjpe'], save_best='MPJPE')
+
+# optimizer settings
+optimizer = dict(
+    type='Adam',
+    lr=1e-3,
+)
+optimizer_config = dict(grad_clip=None)
+# learning policy
+lr_config = dict(
+    policy='step',
+    by_epoch=False,
+    step=100000,
+    gamma=0.96,
+)
+
+total_epochs = 200
+
+log_config = dict(
+    interval=50,
+    hooks=[
+        dict(type='TextLoggerHook'),
+        # dict(type='TensorboardLoggerHook')
+    ])
+
+channel_cfg = dict(
+    num_output_channels=17,
+    dataset_joints=17,
+    dataset_channel=[
+        [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16],
+    ],
+    inference_channel=[
+        0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
+    ])
+
+# model settings
+model = dict(
+    type='PoseLifter',
+    pretrained=None,
+    backbone=dict(
+        type='HourglassNet',
+        downsample_times=2,
+        num_stacks=5,
+        feat_channel=[1, 2, 4, 8, 64]),
+    keypoint_head=dict(
+        type='TemporalRegressionHead',
+        in_channels=1024,
+        num_joints=16,  # do not predict root joint
+        loss_keypoint=dict(type='MSELoss')),
+    train_cfg=dict(),
+    test_cfg=dict(restore_global_position=True))
+
+# data settings
+data_root = 'data/h36m'
+data_cfg = dict(
+    image_size=[256, 256],
+    heatmap_size=[64, 64, [1, 2, 4, 8, 64]],
+    heatmap3d_depth_bound=0.5,
+    num_joints=17,
+    seq_len=1,
+    seq_frame_interval=1,
+    causal=True,
+    joint_2d_src='gt',
+    need_camera_param=True,
+    camera_param_file=f'{data_root}/annotation_body3d/cameras.pkl',
+)
+
+# 3D joint normalization parameters
+# From file: '{data_root}/annotation_body3d/fps50/joint3d_rel_stats.pkl'
+joint_3d_normalize_param = dict(
+    mean=[[-2.55652589e-04, -7.11960570e-03, -9.81433052e-04],
+          [-5.65463051e-03, 3.19636009e-01, 7.19329269e-02],
+          [-1.01705840e-02, 6.91147892e-01, 1.55352986e-01],
+          [2.55651315e-04, 7.11954606e-03, 9.81423866e-04],
+          [-5.09729780e-03, 3.27040413e-01, 7.22258095e-02],
+          [-9.99656606e-03, 7.08277383e-01, 1.58016408e-01],
+          [2.90583676e-03, -2.11363307e-01, -4.74210915e-02],
+          [5.67537804e-03, -4.35088906e-01, -9.76974016e-02],
+          [5.93884964e-03, -4.91891970e-01, -1.10666618e-01],
+          [7.37352083e-03, -5.83948619e-01, -1.31171400e-01],
+          [5.41920653e-03, -3.83931702e-01, -8.68145417e-02],
+          [2.95964662e-03, -1.87567488e-01, -4.34536934e-02],
+          [1.26585822e-03, -1.20170579e-01, -2.82526049e-02],
+          [4.67186639e-03, -3.83644089e-01, -8.55125784e-02],
+          [1.67648571e-03, -1.97007177e-01, -4.31368364e-02],
+          [8.70569015e-04, -1.68664569e-01, -3.73902498e-02]],
+    std=[[0.11072244, 0.02238818, 0.07246294],
+         [0.15856311, 0.18933832, 0.20880479],
+         [0.19179935, 0.24320062, 0.24756193],
+         [0.11072181, 0.02238805, 0.07246253],
+         [0.15880454, 0.19977188, 0.2147063],
+         [0.18001944, 0.25052739, 0.24853247],
+         [0.05210694, 0.05211406, 0.06908241],
+         [0.09515367, 0.10133032, 0.12899733],
+         [0.11742458, 0.12648469, 0.16465091],
+         [0.12360297, 0.13085539, 0.16433336],
+         [0.14602232, 0.09707956, 0.13952731],
+         [0.24347532, 0.12982249, 0.20230181],
+         [0.2446877, 0.21501816, 0.23938235],
+         [0.13876084, 0.1008926, 0.1424411],
+         [0.23687529, 0.14491219, 0.20980829],
+         [0.24400695, 0.23975028, 0.25520584]])
+
+train_pipeline = [
+    # dict(
+    #     type='GetRootCenteredPose',
+    #     item='target',
+    #     visible_item='target_visible',
+    #     root_index=0,
+    #     root_name='root_position',
+    #     remove_root=True),
+    # dict(type='LoadImageFromFile'),
+    # dict(type='ToTensor'),
+    # dict(
+    #     type='NormalizeTensor',
+    #     mean=[0.485, 0.456, 0.406],
+    #     std=[0.229, 0.224, 0.225]),
+    dict(type='LoadImageFromFile'),
+    dict(type='TopDownRandomFlip', flip_prob=0.5),
+    dict(
+        type='TopDownHalfBodyTransform',
+        num_joints_half_body=8,
+        prob_half_body=0.3),
+    dict(
+        type='TopDownGetRandomScaleRotation', rot_factor=40, scale_factor=0.5),
+    dict(type='TopDownAffine'),
+    dict(type='ToTensor'),
+    dict(
+        type='NormalizeTensor',
+        mean=[0.485, 0.456, 0.406],
+        std=[0.229, 0.224, 0.225]),
+    dict(
+        type='GetRootCenteredPose',
+        item='target',
+        visible_item='target_visible',
+        root_index=0,
+        root_name='root_position',
+        remove_root=True),
+    # dict(
+    #     type='CameraProjection',
+    #     item='target',
+    #     mode='camera_to_pixel',
+    #     output_name='joint_2d_pixel',
+    # ),
+    dict(
+        type='Generate3DHeatmapTarget_h36m',
+        sigma=2.5,
+        max_bound=1,
+    ),
+    dict(
+        type='Collect',
+        keys=[('img', 'input'), 'target'],
+        meta_name='metas',
+        meta_keys=[
+            'target_image_path',
+            'flip_pairs',
+            'root_position',
+            'root_position_index',
+        ])
+]
+
+val_pipeline = train_pipeline
+test_pipeline = val_pipeline
+
+data = dict(
+    samples_per_gpu=3,
+    workers_per_gpu=0,
+    val_dataloader=dict(samples_per_gpu=64),
+    test_dataloader=dict(samples_per_gpu=64),
+    train=dict(
+        type='Body3DH36MDataset_E2E',
+        ann_file=f'{data_root}/annotation_body3d/fps50/h36m_train.npz',
+        img_prefix=f'{data_root}/images/',
+        data_cfg=data_cfg,
+        pipeline=train_pipeline),
+    val=dict(
+        type='Body3DH36MDataset',
+        ann_file=f'{data_root}/annotation_body3d/fps50/h36m_test.npz',
+        img_prefix=f'{data_root}/images/',
+        data_cfg=data_cfg,
+        pipeline=val_pipeline),
+    test=dict(
+        type='Body3DH36MDataset',
+        ann_file=f'{data_root}/annotation_body3d/fps50/h36m_test.npz',
+        img_prefix=f'{data_root}/images/',
+        data_cfg=data_cfg,
+        pipeline=test_pipeline),
+)

mmpose/datasets/datasets/body3d/__init__.py

@@ -1,8 +1,11 @@
 from .body3d_h36m_dataset import Body3DH36MDataset
+from .body3d_h36m_end2end_dataset import Body3DH36MDataset_E2E
 from .body3d_mpi_inf_3dhp_dataset import Body3DMpiInf3dhpDataset
 from .body3d_semi_supervision_dataset import Body3DSemiSupervisionDataset
 
 __all__ = [
-    'Body3DH36MDataset', 'Body3DSemiSupervisionDataset',
-    'Body3DMpiInf3dhpDataset'
+    'Body3DH36MDataset',
+    'Body3DSemiSupervisionDataset',
+    'Body3DMpiInf3dhpDataset',
+    'Body3DH36MDataset_E2E',
 ]