[c1b1c5]: / ViTPose / configs / _base_ / datasets / jhmdb.py

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dataset_info = dict(
dataset_name='jhmdb',
paper_info=dict(
author='H. Jhuang and J. Gall and S. Zuffi and '
'C. Schmid and M. J. Black',
title='Towards understanding action recognition',
container='International Conf. on Computer Vision (ICCV)',
year='2013',
homepage='http://jhmdb.is.tue.mpg.de/dataset',
),
keypoint_info={
0:
dict(name='neck', id=0, color=[255, 128, 0], type='upper', swap=''),
1:
dict(name='belly', id=1, color=[255, 128, 0], type='upper', swap=''),
2:
dict(name='head', id=2, color=[255, 128, 0], type='upper', swap=''),
3:
dict(
name='right_shoulder',
id=3,
color=[0, 255, 0],
type='upper',
swap='left_shoulder'),
4:
dict(
name='left_shoulder',
id=4,
color=[0, 255, 0],
type='upper',
swap='right_shoulder'),
5:
dict(
name='right_hip',
id=5,
color=[0, 255, 0],
type='lower',
swap='left_hip'),
6:
dict(
name='left_hip',
id=6,
color=[51, 153, 255],
type='lower',
swap='right_hip'),
7:
dict(
name='right_elbow',
id=7,
color=[51, 153, 255],
type='upper',
swap='left_elbow'),
8:
dict(
name='left_elbow',
id=8,
color=[51, 153, 255],
type='upper',
swap='right_elbow'),
9:
dict(
name='right_knee',
id=9,
color=[51, 153, 255],
type='lower',
swap='left_knee'),
10:
dict(
name='left_knee',
id=10,
color=[255, 128, 0],
type='lower',
swap='right_knee'),
11:
dict(
name='right_wrist',
id=11,
color=[255, 128, 0],
type='upper',
swap='left_wrist'),
12:
dict(
name='left_wrist',
id=12,
color=[255, 128, 0],
type='upper',
swap='right_wrist'),
13:
dict(
name='right_ankle',
id=13,
color=[0, 255, 0],
type='lower',
swap='left_ankle'),
14:
dict(
name='left_ankle',
id=14,
color=[0, 255, 0],
type='lower',
swap='right_ankle')
},
skeleton_info={
0: dict(link=('right_ankle', 'right_knee'), id=0, color=[255, 128, 0]),
1: dict(link=('right_knee', 'right_hip'), id=1, color=[255, 128, 0]),
2: dict(link=('right_hip', 'belly'), id=2, color=[255, 128, 0]),
3: dict(link=('belly', 'left_hip'), id=3, color=[0, 255, 0]),
4: dict(link=('left_hip', 'left_knee'), id=4, color=[0, 255, 0]),
5: dict(link=('left_knee', 'left_ankle'), id=5, color=[0, 255, 0]),
6: dict(link=('belly', 'neck'), id=6, color=[51, 153, 255]),
7: dict(link=('neck', 'head'), id=7, color=[51, 153, 255]),
8: dict(link=('neck', 'right_shoulder'), id=8, color=[255, 128, 0]),
9: dict(
link=('right_shoulder', 'right_elbow'), id=9, color=[255, 128, 0]),
10:
dict(link=('right_elbow', 'right_wrist'), id=10, color=[255, 128, 0]),
11: dict(link=('neck', 'left_shoulder'), id=11, color=[0, 255, 0]),
12:
dict(link=('left_shoulder', 'left_elbow'), id=12, color=[0, 255, 0]),
13: dict(link=('left_elbow', 'left_wrist'), id=13, color=[0, 255, 0])
},
joint_weights=[
1., 1., 1., 1., 1., 1., 1., 1.2, 1.2, 1.2, 1.2, 1.5, 1.5, 1.5, 1.5
],
# Adapted from COCO dataset.
sigmas=[
0.025, 0.107, 0.025, 0.079, 0.079, 0.107, 0.107, 0.072, 0.072, 0.087,
0.087, 0.062, 0.062, 0.089, 0.089
])