dataset_info = dict( dataset_name='mpii', paper_info=dict( author='Mykhaylo Andriluka and Leonid Pishchulin and ' 'Peter Gehler and Schiele, Bernt', title='2D Human Pose Estimation: New Benchmark and ' 'State of the Art Analysis', container='IEEE Conference on Computer Vision and ' 'Pattern Recognition (CVPR)', year='2014', homepage='http://human-pose.mpi-inf.mpg.de/', ), keypoint_info={ 0: dict( name='right_ankle', id=0, color=[255, 128, 0], type='lower', swap='left_ankle'), 1: dict( name='right_knee', id=1, color=[255, 128, 0], type='lower', swap='left_knee'), 2: dict( name='right_hip', id=2, color=[255, 128, 0], type='lower', swap='left_hip'), 3: dict( name='left_hip', id=3, color=[0, 255, 0], type='lower', swap='right_hip'), 4: dict( name='left_knee', id=4, color=[0, 255, 0], type='lower', swap='right_knee'), 5: dict( name='left_ankle', id=5, color=[0, 255, 0], type='lower', swap='right_ankle'), 6: dict(name='pelvis', id=6, color=[51, 153, 255], type='lower', swap=''), 7: dict(name='thorax', id=7, color=[51, 153, 255], type='upper', swap=''), 8: dict( name='upper_neck', id=8, color=[51, 153, 255], type='upper', swap=''), 9: dict( name='head_top', id=9, color=[51, 153, 255], type='upper', swap=''), 10: dict( name='right_wrist', id=10, color=[255, 128, 0], type='upper', swap='left_wrist'), 11: dict( name='right_elbow', id=11, color=[255, 128, 0], type='upper', swap='left_elbow'), 12: dict( name='right_shoulder', id=12, color=[255, 128, 0], type='upper', swap='left_shoulder'), 13: dict( name='left_shoulder', id=13, color=[0, 255, 0], type='upper', swap='right_shoulder'), 14: dict( name='left_elbow', id=14, color=[0, 255, 0], type='upper', swap='right_elbow'), 15: dict( name='left_wrist', id=15, color=[0, 255, 0], type='upper', swap='right_wrist') }, 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', 'pelvis'), id=2, color=[255, 128, 0]), 3: dict(link=('pelvis', '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=('pelvis', 'thorax'), id=6, color=[51, 153, 255]), 7: dict(link=('thorax', 'upper_neck'), id=7, color=[51, 153, 255]), 8: dict(link=('upper_neck', 'head_top'), id=8, color=[51, 153, 255]), 9: dict(link=('upper_neck', 'right_shoulder'), id=9, color=[255, 128, 0]), 10: dict( link=('right_shoulder', 'right_elbow'), id=10, color=[255, 128, 0]), 11: dict(link=('right_elbow', 'right_wrist'), id=11, color=[255, 128, 0]), 12: dict(link=('upper_neck', 'left_shoulder'), id=12, color=[0, 255, 0]), 13: dict(link=('left_shoulder', 'left_elbow'), id=13, color=[0, 255, 0]), 14: dict(link=('left_elbow', 'left_wrist'), id=14, color=[0, 255, 0]) }, joint_weights=[ 1.5, 1.2, 1., 1., 1.2, 1.5, 1., 1., 1., 1., 1.5, 1.2, 1., 1., 1.2, 1.5 ], # Adapted from COCO dataset. sigmas=[ 0.089, 0.083, 0.107, 0.107, 0.083, 0.089, 0.026, 0.026, 0.026, 0.026, 0.062, 0.072, 0.179, 0.179, 0.072, 0.062 ])