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dataset_info = dict(
dataset_name='mpi_inf_3dhp',
paper_info=dict(
author='ehta, Dushyant and Rhodin, Helge and Casas, Dan and '
'Fua, Pascal and Sotnychenko, Oleksandr and Xu, Weipeng and '
'Theobalt, Christian',
title='Monocular 3D Human Pose Estimation In The Wild Using Improved '
'CNN Supervision',
container='2017 international conference on 3D vision (3DV)',
year='2017',
homepage='http://gvv.mpi-inf.mpg.de/3dhp-dataset',
),
keypoint_info={
0:
dict(
name='head_top', id=0, color=[51, 153, 255], type='upper',
swap=''),
1:
dict(name='neck', id=1, color=[51, 153, 255], type='upper', swap=''),
2:
dict(
name='right_shoulder',
id=2,
color=[255, 128, 0],
type='upper',
swap='left_shoulder'),
3:
dict(
name='right_elbow',
id=3,
color=[255, 128, 0],
type='upper',
swap='left_elbow'),
4:
dict(
name='right_wrist',
id=4,
color=[255, 128, 0],
type='upper',
swap='left_wrist'),
5:
dict(
name='left_shoulder',
id=5,
color=[0, 255, 0],
type='upper',
swap='right_shoulder'),
6:
dict(
name='left_elbow',
id=6,
color=[0, 255, 0],
type='upper',
swap='right_elbow'),
7:
dict(
name='left_wrist',
id=7,
color=[0, 255, 0],
type='upper',
swap='right_wrist'),
8:
dict(
name='right_hip',
id=8,
color=[255, 128, 0],
type='lower',
swap='left_hip'),
9:
dict(
name='right_knee',
id=9,
color=[255, 128, 0],
type='lower',
swap='left_knee'),
10:
dict(
name='right_ankle',
id=10,
color=[255, 128, 0],
type='lower',
swap='left_ankle'),
11:
dict(
name='left_hip',
id=11,
color=[0, 255, 0],
type='lower',
swap='right_hip'),
12:
dict(
name='left_knee',
id=12,
color=[0, 255, 0],
type='lower',
swap='right_knee'),
13:
dict(
name='left_ankle',
id=13,
color=[0, 255, 0],
type='lower',
swap='right_ankle'),
14:
dict(name='root', id=14, color=[51, 153, 255], type='lower', swap=''),
15:
dict(name='spine', id=15, color=[51, 153, 255], type='upper', swap=''),
16:
dict(name='head', id=16, color=[51, 153, 255], type='upper', swap='')
},
skeleton_info={
0: dict(link=('neck', 'right_shoulder'), id=0, color=[255, 128, 0]),
1: dict(
link=('right_shoulder', 'right_elbow'), id=1, color=[255, 128, 0]),
2:
dict(link=('right_elbow', 'right_wrist'), id=2, color=[255, 128, 0]),
3: dict(link=('neck', 'left_shoulder'), id=3, color=[0, 255, 0]),
4: dict(link=('left_shoulder', 'left_elbow'), id=4, color=[0, 255, 0]),
5: dict(link=('left_elbow', 'left_wrist'), id=5, color=[0, 255, 0]),
6: dict(link=('root', 'right_hip'), id=6, color=[255, 128, 0]),
7: dict(link=('right_hip', 'right_knee'), id=7, color=[255, 128, 0]),
8: dict(link=('right_knee', 'right_ankle'), id=8, color=[255, 128, 0]),
9: dict(link=('root', 'left_hip'), id=9, color=[0, 255, 0]),
10: dict(link=('left_hip', 'left_knee'), id=10, color=[0, 255, 0]),
11: dict(link=('left_knee', 'left_ankle'), id=11, color=[0, 255, 0]),
12: dict(link=('head_top', 'head'), id=12, color=[51, 153, 255]),
13: dict(link=('head', 'neck'), id=13, color=[51, 153, 255]),
14: dict(link=('neck', 'spine'), id=14, color=[51, 153, 255]),
15: dict(link=('spine', 'root'), id=15, color=[51, 153, 255])
},
joint_weights=[1.] * 17,
sigmas=[])
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