Implement a custom dataset for training and testing.
custom_camera_params = {
'id': None,
'res_w': None, # Pulled from metadata
'res_h': None, # Pulled from metadata
# Dummy camera parameters (taken from Human3.6M), only for visualization purposes
'azimuth': 70, # Only used for visualization
'orientation': [0.1407056450843811, -0.1500701755285263, -0.755240797996521, 0.6223280429840088],
'translation': [1841.1070556640625, 4955.28466796875, 1563.4454345703125],
}
class CustomDataset(MocapDataset):
"""Creates a custom dataset with the Human36m skeleton."""
def __init__(self, detections_path, remove_static_joints=True):
super().__init__(fps=None, skeleton=h36m_skeleton)
self._cameras = {}
self._data = {}
# Load serialized dataset
data = np.load(detections_path, allow_pickle=True)
resolutions = data['metadata'].item()['video_metadata']
for video_name, res in resolutions.items():
cam = {}
cam.update(custom_camera_params)
cam['orientation'] = np.array(cam['orientation'], dtype='float32')
cam['translation'] = np.array(cam['translation'], dtype='float32')
cam['translation'] = cam['translation']/1000 # mm to meters
cam['id'] = video_name
cam['res_w'] = res['w']
cam['res_h'] = res['h']
self._cameras[video_name] = [cam]
self._data[video_name] = {'custom': { 'cameras': cam } }
if remove_static_joints:
# Bring the skeleton to 17 joints instead of the original 32
self.remove_joints([
4, 5, 9, 10, 11, 16, 20, 21, 22, 23, 24, 28, 29, 30, 31
])
# Rewire shoulders to the correct parents
self._skeleton._parents[11] = 8
self._skeleton._parents[14] = 8
def supports_semi_supervised(self):
return False