mirror of https://github.com/open-mmlab/mmpose
157 lines
4.6 KiB
Python
157 lines
4.6 KiB
Python
dataset_info = dict(
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dataset_name='mhp',
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paper_info=dict(
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author='Zhao, Jian and Li, Jianshu and Cheng, Yu and '
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'Sim, Terence and Yan, Shuicheng and Feng, Jiashi',
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title='Understanding humans in crowded scenes: '
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'Deep nested adversarial learning and a '
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'new benchmark for multi-human parsing',
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container='Proceedings of the 26th ACM '
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'international conference on Multimedia',
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year='2018',
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homepage='https://lv-mhp.github.io/dataset',
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),
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keypoint_info={
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0:
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dict(
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name='right_ankle',
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id=0,
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color=[255, 128, 0],
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type='lower',
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swap='left_ankle'),
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1:
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dict(
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name='right_knee',
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id=1,
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color=[255, 128, 0],
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type='lower',
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swap='left_knee'),
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2:
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dict(
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name='right_hip',
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id=2,
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color=[255, 128, 0],
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type='lower',
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swap='left_hip'),
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3:
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dict(
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name='left_hip',
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id=3,
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color=[0, 255, 0],
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type='lower',
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swap='right_hip'),
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4:
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dict(
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name='left_knee',
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id=4,
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color=[0, 255, 0],
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type='lower',
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swap='right_knee'),
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5:
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dict(
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name='left_ankle',
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id=5,
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color=[0, 255, 0],
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type='lower',
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swap='right_ankle'),
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6:
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dict(name='pelvis', id=6, color=[51, 153, 255], type='lower', swap=''),
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7:
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dict(name='thorax', id=7, color=[51, 153, 255], type='upper', swap=''),
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8:
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dict(
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name='upper_neck',
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id=8,
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color=[51, 153, 255],
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type='upper',
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swap=''),
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9:
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dict(
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name='head_top', id=9, color=[51, 153, 255], type='upper',
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swap=''),
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10:
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dict(
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name='right_wrist',
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id=10,
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color=[255, 128, 0],
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type='upper',
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swap='left_wrist'),
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11:
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dict(
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name='right_elbow',
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id=11,
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color=[255, 128, 0],
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type='upper',
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swap='left_elbow'),
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12:
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dict(
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name='right_shoulder',
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id=12,
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color=[255, 128, 0],
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type='upper',
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swap='left_shoulder'),
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13:
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dict(
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name='left_shoulder',
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id=13,
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color=[0, 255, 0],
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type='upper',
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swap='right_shoulder'),
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14:
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dict(
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name='left_elbow',
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id=14,
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color=[0, 255, 0],
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type='upper',
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swap='right_elbow'),
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15:
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dict(
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name='left_wrist',
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id=15,
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color=[0, 255, 0],
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type='upper',
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swap='right_wrist')
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},
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skeleton_info={
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0:
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dict(link=('right_ankle', 'right_knee'), id=0, color=[255, 128, 0]),
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1:
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dict(link=('right_knee', 'right_hip'), id=1, color=[255, 128, 0]),
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2:
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dict(link=('right_hip', 'pelvis'), id=2, color=[255, 128, 0]),
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3:
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dict(link=('pelvis', 'left_hip'), id=3, color=[0, 255, 0]),
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4:
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dict(link=('left_hip', 'left_knee'), id=4, color=[0, 255, 0]),
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5:
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dict(link=('left_knee', 'left_ankle'), id=5, color=[0, 255, 0]),
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6:
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dict(link=('pelvis', 'thorax'), id=6, color=[51, 153, 255]),
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7:
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dict(link=('thorax', 'upper_neck'), id=7, color=[51, 153, 255]),
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8:
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dict(link=('upper_neck', 'head_top'), id=8, color=[51, 153, 255]),
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9:
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dict(link=('upper_neck', 'right_shoulder'), id=9, color=[255, 128, 0]),
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10:
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dict(
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link=('right_shoulder', 'right_elbow'), id=10, color=[255, 128,
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0]),
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11:
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dict(link=('right_elbow', 'right_wrist'), id=11, color=[255, 128, 0]),
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12:
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dict(link=('upper_neck', 'left_shoulder'), id=12, color=[0, 255, 0]),
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13:
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dict(link=('left_shoulder', 'left_elbow'), id=13, color=[0, 255, 0]),
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14:
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dict(link=('left_elbow', 'left_wrist'), id=14, color=[0, 255, 0])
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},
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joint_weights=[
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1.5, 1.2, 1., 1., 1.2, 1.5, 1., 1., 1., 1., 1.5, 1.2, 1., 1., 1.2, 1.5
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],
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# Adapted from COCO dataset.
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sigmas=[
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0.089, 0.083, 0.107, 0.107, 0.083, 0.089, 0.026, 0.026, 0.026, 0.026,
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0.062, 0.072, 0.179, 0.179, 0.072, 0.062
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])
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