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=[])