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Proper initialization and registration of the Dataset. TODO: Implemen…
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…t __len__.
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@kaseris
kaseris committed Jan 29, 2024
1 parent 6d9d81a commit 2191184
Showing 1 changed file with 40 additions and 74 deletions.
114 changes: 40 additions & 74 deletions src/skelcast/data/human36m/human36m.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@

from skelcast.data import DATASETS
from skelcast.data.human36m.camera import normalize_screen_coordinates
from skelcast.data.human36m.human36mwbparams import h36m_cameras_intrinsic_params, h36m_cameras_extrinsic_params
from skelcast.data.human36m.skeleton import Skeleton

from skelcast.data.human36m.quaternion import qeuler_np, qfix
Expand Down Expand Up @@ -144,76 +143,43 @@ def skeleton(self):
@DATASETS.register_module()
class Human36MDataset(MocapDataset):
def __init__(self, path, seq_len=27):

self.seq_len = seq_len
# Load serialized dataset
check_data = np.load(path, allow_pickle=True)
self.metadata = check_data['metadata'].item()
train_data = check_data['train_data'].item()

# prepare skeleton
joints_left = self.metadata['left_side']
joints_right = self.metadata['right_side']

self.kps_order = ['body', 'left_foot', 'right_foot', 'face', 'left_hand', 'right_hand']
# below orj parents
body_parents = [-1, 0, 0, 0, 0, 0, 0, 5, 6, 7, 8, 5, 6, 11, 12, 13, 14]
left_foot_parents = [15, 15, 15]
right_foot_parents = [16, 16, 16]
face_parents = [0] * len(self.metadata["face"]) # for face, you can use nose as parents of all
left_hand_parents = [9, 91, 92, 93, 94, 91, 96, 97, 98, 91, 100, 101, 102, 91, 104, 105, 106, 91, 108, 109, 110]
right_hand_parents = [10, 112, 113, 114, 115, 112, 117, 118, 119, 112, 121, 122, 123, 112, 125, 126, 127, 112, 129, 130, 131]

self.parents = body_parents + left_foot_parents + right_foot_parents + face_parents + left_hand_parents + right_hand_parents

self.num_kps = len(self.parents)

self.keypoints_metadata = {'layout_name': 'h3wb',
'num_joints': self.num_kps,
'keypoints_symmetry': [joints_left, joints_right]
}

h3wb_skeleton = Skeleton(parents=self.parents,
joints_left=joints_left,
joints_right=joints_right)

super().__init__(fps=50, skeleton=h3wb_skeleton)

# we can use the same camera parameters since the intrinsics are the same!!
self._cameras = copy.deepcopy(h36m_cameras_extrinsic_params)
for cameras in self._cameras.values():
for i, cam in enumerate(cameras):
cam.update(h36m_cameras_intrinsic_params[i])
for k, v in cam.items():
if k not in ['id', 'res_w', 'res_h']:
cam[k] = np.array(v, dtype='float32')

# Normalize camera frame
cam['center'] = normalize_screen_coordinates(cam['center'], w=cam['res_w'], h=cam['res_h']).astype(
'float32')
cam['focal_length'] = cam['focal_length'] / cam['res_w'] * 2
if 'translation' in cam:
cam['translation'] = cam['translation'] / 1000 # mm to meters

# Add intrinsic parameters vector
cam['intrinsic'] = np.concatenate((cam['focal_length'],
cam['center'],
cam['radial_distortion'],
cam['tangential_distortion']))

self.camera_order_id = ['54138969', '55011271', '58860488', '60457274']
self._data = {}
self._cameras_full_data = {}
for subject, actions in train_data.items():
self._data[subject] = {}
self._cameras_full_data[subject] = [self.metadata[subject][cam] for cam in self.camera_order_id]
for action_name, act_data in actions.items():
if len(act_data['global_3d']) < self.seq_len:
# if the sequence length is too short lets skip it!
continue
self._data[subject][action_name] = {
'positions': act_data['global_3d'].squeeze(), # global coord
'cameras': [self.metadata[subject][cam] for cam in self.camera_order_id],
'positions_3d': [act_data[cam]['camera_3d'].squeeze() for cam in self.camera_order_id],
'pose_2d': [act_data[cam]['pose_2d'].squeeze() for cam in self.camera_order_id]
}
skeleton = Skeleton(offsets=[
[ 0. , 0. , 0. ],
[-132.948591, 0. , 0. ],
[ 0. , -442.894612, 0. ],
[ 0. , -454.206447, 0. ],
[ 0. , 0. , 162.767078],
[ 0. , 0. , 74.999437],
[ 132.948826, 0. , 0. ],
[ 0. , -442.894413, 0. ],
[ 0. , -454.20659 , 0. ],
[ 0. , 0. , 162.767426],
[ 0. , 0. , 74.999948],
[ 0. , 0.1 , 0. ],
[ 0. , 233.383263, 0. ],
[ 0. , 257.077681, 0. ],
[ 0. , 121.134938, 0. ],
[ 0. , 115.002227, 0. ],
[ 0. , 257.077681, 0. ],
[ 0. , 151.034226, 0. ],
[ 0. , 278.882773, 0. ],
[ 0. , 251.733451, 0. ],
[ 0. , 0. , 0. ],
[ 0. , 0. , 99.999627],
[ 0. , 100.000188, 0. ],
[ 0. , 0. , 0. ],
[ 0. , 257.077681, 0. ],
[ 0. , 151.031437, 0. ],
[ 0. , 278.892924, 0. ],
[ 0. , 251.72868 , 0. ],
[ 0. , 0. , 0. ],
[ 0. , 0. , 99.999888],
[ 0. , 137.499922, 0. ],
[ 0. , 0. , 0. ]
],
parents=[-1, 0, 1, 2, 3, 4, 0, 6, 7, 8, 9, 0, 11, 12, 13, 14, 12,
16, 17, 18, 19, 20, 19, 22, 12, 24, 25, 26, 27, 28, 27, 30],
joints_left=[1, 2, 3, 4, 5, 24, 25, 26, 27, 28, 29, 30, 31],
joints_right=[6, 7, 8, 9, 10, 16, 17, 18, 19, 20, 21, 22, 23])
super().__init__(path, skeleton, fps=50)
self.compute_positions()

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