def read_3d_data(dataset):
for subject in dataset.subjects():
for action in dataset[subject].keys():
anim = dataset[subject][action]
positions_3d = []
for cam in anim['cameras']:
pos_3d = world_to_camera(anim['positions'],
R=cam['orientation'],
t=cam['translation'])
# pos_3d[:, :] -= pos_3d[:, :1] # keep this, remove at model training.
positions_3d.append(pos_3d)
anim['positions_3d'] = positions_3d
return dataset
def prepare_data():
print('Preparing data...')
print(dataset.subjects())
for subject in dataset.subjects():
for action in dataset[subject].keys():
anim = dataset[subject][action]
if 'positions' in anim:
positions_3d = []
for cam in anim['cameras']:
pos_3d = world_to_camera(anim['positions'],
R=cam['orientation'],
t=cam['translation'])
pos_3d[:,
1:] -= pos_3d[:, :
1] # Remove global offset, but keep trajectory in first position
positions_3d.append(pos_3d)
anim['positions_3d'] = positions_3d
exit(0)
# Create 2D pose file
print('')
print('Computing ground-truth 2D poses...')
dataset = Human36mDataset(output_filename + '.npz')
output_2d_poses = {}
for subject in dataset.subjects():
output_2d_poses[subject] = {}
for action in dataset[subject].keys():
anim = dataset[subject][action]
positions_2d = []
for cam in anim['cameras']:
pos_3d = world_to_camera(anim['positions'],
R=cam['orientation'],
t=cam['translation'])
pos_2d = wrap(project_to_2d, True, pos_3d, cam['intrinsic'])
pos_2d_pixel_space = image_coordinates(pos_2d,
w=cam['res_w'],
h=cam['res_h'])
positions_2d.append(pos_2d_pixel_space.astype('float32'))
output_2d_poses[subject][action] = positions_2d
print('Saving...')
metadata = {
'num_joints':
dataset.skeleton().num_joints(),
'keypoints_symmetry':
[dataset.skeleton().joints_left(),
dataset.skeleton().joints_right()]
exit(0)
# Create 2D pose file
print("")
print("Computing ground-truth 2D poses...")
dataset = Human36mDataset(output_filename + ".npz")
output_2d_poses = {}
for subject in dataset.subjects():
output_2d_poses[subject] = {}
for action in dataset[subject].keys():
anim = dataset[subject][action]
positions_2d = []
for cam in anim["cameras"]:
pos_3d = world_to_camera(anim["positions"],
R=cam["orientation"],
t=cam["translation"])
pos_2d = wrap(project_to_2d,
pos_3d,
cam["intrinsic"],
unsqueeze=True)
pos_2d_pixel_space = image_coordinates(pos_2d,
w=cam['res_w'],
h=cam['res_h'])
positions_2d.append(pos_2d_pixel_space.astype("float32"))
output_2d_poses[subject][action] = positions_2d
print("Saving...")
metadata = {
"num_joints":
dataset.skeleton().num_joints(),