# Copyright (c) OpenMMLab. All rights reserved.
# Adapt from https://github.com/open-mmlab/mmpose/blob/master/mmpose/datasets/datasets/base/kpt_2d_sview_rgb_img_top_down_dataset.py
import logging
from easycv.datasets.registry import DATASOURCES
from easycv.framework.errors import ValueError
from .top_down import PoseTopDownSource
CROWDPOSE_DATASET_INFO = dict(
dataset_name='Crowd Pose',
paper_info=dict(
author=
'Jiefeng Li, Can Wang, Hao Zhu, Yihuan Mao, Hao-Shu Fang, Cewu Lu',
title=
'CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark',
year='2018',
container='Computer Vision and Pattern Recognition',
homepage='https://arxiv.org/abs/1812.00324'),
keypoint_info={
0:
dict(
name='left_shoulder',
id=0,
color=[51, 153, 255],
type='upper',
swap='left_elbow'),
1:
dict(
name='right_shoulder',
id=1,
color=[51, 153, 255],
type='upper',
swap='right_elbow'),
2:
dict(
name='left_elbow',
id=2,
color=[51, 153, 255],
type='upper',
swap='left_wrist'),
3:
dict(
name='right_elbow',
id=3,
color=[51, 153, 255],
type='upper',
swap='right_wrist'),
4:
dict(
name='left_wrist',
id=4,
color=[51, 153, 255],
type='upper',
swap=''),
5:
dict(
name='right_wrist', id=5, color=[0, 255, 0], type='upper',
swap=''),
6:
dict(
name='left_hip',
id=6,
color=[255, 128, 0],
type='lower',
swap='left_knee'),
7:
dict(
name='right_hip',
id=7,
color=[0, 255, 0],
type='lower',
swap='right_knee'),
8:
dict(
name='left_knee',
id=8,
color=[255, 128, 0],
type='lower',
swap='left_ankle'),
9:
dict(
name='right_knee',
id=9,
color=[0, 255, 0],
type='lower',
swap='right_ankle'),
10:
dict(
name='left_ankle',
id=10,
color=[255, 128, 0],
type='lower',
swap=''),
11:
dict(
name='right_ankle',
id=11,
color=[0, 255, 0],
type='lower',
swap=''),
12:
dict(
name='head', id=12, color=[255, 128, 0], type='upper',
swap='neck'),
13:
dict(
name='neck',
id=13,
color=[0, 255, 0],
type='upper',
swap='left_shoulder'),
},
skeleton_info={
0: dict(link=('head', 'neck'), id=0, color=[0, 255, 0]),
1: dict(link=('neck', 'left_shoulder'), id=1, color=[0, 255, 0]),
2: dict(link=('neck', 'right_shoulder'), id=2, color=[255, 128, 0]),
3:
dict(link=('left_shoulder', 'left_elbow'), id=3, color=[255, 128, 0]),
4: dict(link=('left_elbow', 'left_wrist'), id=4, color=[51, 153, 255]),
5: dict(
link=('right_shoulder', 'right_elbow'), id=5, color=[51, 153,
255]),
6:
dict(link=('right_elbow', 'right_wrist'), id=6, color=[51, 153, 255]),
7: dict(link=('neck', 'right_hip'), id=7, color=[51, 153, 255]),
8: dict(link=('neck', 'left_hip'), id=8, color=[0, 255, 0]),
9: dict(link=('right_hip', 'right_knee'), id=9, color=[255, 128, 0]),
10: dict(link=('right_knee', 'right_ankle'), id=10, color=[0, 255, 0]),
11: dict(link=('left_hip', 'left_knee'), id=11, color=[255, 128, 0]),
12:
dict(link=('left_knee', 'left_ankle'), id=12, color=[51, 153, 255])
},
joint_weights=[
1., 1., 1., 1., 1., 1., 1., 1.2, 1.2, 1.5, 1.5, 1., 1., 1.2
],
sigmas=[
0.026, 0.025, 0.025, 0.035, 0.035, 0.079, 0.079, 0.072, 0.072, 0.062,
0.062, 0.107, 0.107, 0.087
])
[docs]@DATASOURCES.register_module
class PoseTopDownSourceCrowdPose(PoseTopDownSource):
"""
CrowdPose keypoint indexes::
0 'left_shoulder',
1 'right_shoulder',
2 'left_elbow',
3 'right_elbow',
4 'left_wrist',
5 'right_wrist',
6 'left_hip',
7 'right_hip',
8 'left_knee',
9 'right_knee',
10 'left_ankle',
11 'right_ankle',
12 'head',
13 'neck'
Args:
ann_file (str): Path to the annotation file.
img_prefix (str): Path to a directory where images are held.
Default: None.
data_cfg (dict): config
dataset_info (DatasetInfo): A class containing all dataset info.
test_mode (bool): Store True when building test or
validation dataset. Default: False.
"""
[docs] def __init__(self,
ann_file,
img_prefix,
data_cfg,
dataset_info=None,
test_mode=False,
**kwargs):
if dataset_info is None:
logging.info(
'dataset_info is missing, use default coco dataset info')
dataset_info = CROWDPOSE_DATASET_INFO
self.use_gt_bbox = data_cfg.get('use_gt_bbox', True)
self.bbox_file = data_cfg.get('bbox_file', None)
self.det_bbox_thr = data_cfg.get('det_bbox_thr', 0.0)
super().__init__(
ann_file,
img_prefix,
data_cfg,
dataset_info=dataset_info,
test_mode=test_mode)