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dataset_info = dict(
dataset_name='h36m',
paper_info=dict(
author='Ionescu, Catalin and Papava, Dragos and '
'Olaru, Vlad and Sminchisescu, Cristian',
title='Human3.6M: Large Scale Datasets and Predictive '
'Methods for 3D Human Sensing in Natural Environments',
container='IEEE Transactions on Pattern Analysis and '
'Machine Intelligence',
year='2014',
homepage='http://vision.imar.ro/human3.6m/description.php',
),
keypoint_info={
0:
dict(name='root', id=0, color=[51, 153, 255], type='lower', swap=''),
1:
dict(
name='right_hip',
id=1,
color=[255, 128, 0],
type='lower',
swap='left_hip'),
2:
dict(
name='right_knee',
id=2,
color=[255, 128, 0],
type='lower',
swap='left_knee'),
3:
dict(
name='right_foot',
id=3,
color=[255, 128, 0],
type='lower',
swap='left_foot'),
4:
dict(
name='left_hip',
id=4,
color=[0, 255, 0],
type='lower',
swap='right_hip'),
5:
dict(
name='left_knee',
id=5,
color=[0, 255, 0],
type='lower',
swap='right_knee'),
6:
dict(
name='left_foot',
id=6,
color=[0, 255, 0],
type='lower',
swap='right_foot'),
7:
dict(name='spine', id=7, color=[51, 153, 255], type='upper', swap=''),
8:
dict(name='thorax', id=8, color=[51, 153, 255], type='upper', swap=''),
9:
dict(
name='neck_base',
id=9,
color=[51, 153, 255],
type='upper',
swap=''),
10:
dict(name='head', id=10, color=[51, 153, 255], type='upper', swap=''),
11:
dict(
name='left_shoulder',
id=11,
color=[0, 255, 0],
type='upper',
swap='right_shoulder'),
12:
dict(
name='left_elbow',
id=12,
color=[0, 255, 0],
type='upper',
swap='right_elbow'),
13:
dict(
name='left_wrist',
id=13,
color=[0, 255, 0],
type='upper',
swap='right_wrist'),
14:
dict(
name='right_shoulder',
id=14,
color=[255, 128, 0],
type='upper',
swap='left_shoulder'),
15:
dict(
name='right_elbow',
id=15,
color=[255, 128, 0],
type='upper',
swap='left_elbow'),
16:
dict(
name='right_wrist',
id=16,
color=[255, 128, 0],
type='upper',
swap='left_wrist')
},
skeleton_info={
0:
dict(link=('root', 'left_hip'), id=0, color=[0, 255, 0]),
1:
dict(link=('left_hip', 'left_knee'), id=1, color=[0, 255, 0]),
2:
dict(link=('left_knee', 'left_foot'), id=2, color=[0, 255, 0]),
3:
dict(link=('root', 'right_hip'), id=3, color=[255, 128, 0]),
4:
dict(link=('right_hip', 'right_knee'), id=4, color=[255, 128, 0]),
5:
dict(link=('right_knee', 'right_foot'), id=5, color=[255, 128, 0]),
6:
dict(link=('root', 'spine'), id=6, color=[51, 153, 255]),
7:
dict(link=('spine', 'thorax'), id=7, color=[51, 153, 255]),
8:
dict(link=('thorax', 'neck_base'), id=8, color=[51, 153, 255]),
9:
dict(link=('neck_base', 'head'), id=9, color=[51, 153, 255]),
10:
dict(link=('thorax', 'left_shoulder'), id=10, color=[0, 255, 0]),
11:
dict(link=('left_shoulder', 'left_elbow'), id=11, color=[0, 255, 0]),
12:
dict(link=('left_elbow', 'left_wrist'), id=12, color=[0, 255, 0]),
13:
dict(link=('thorax', 'right_shoulder'), id=13, color=[255, 128, 0]),
14:
dict(
link=('right_shoulder', 'right_elbow'), id=14, color=[255, 128,
0]),
15:
dict(link=('right_elbow', 'right_wrist'), id=15, color=[255, 128, 0])
},
joint_weights=[1.] * 17,
sigmas=[],
stats_info=dict(bbox_center=(528., 427.), bbox_scale=400.))
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