data_stats.py 文件源码

def compute_moments(pose_seq_input):
    labs, poses = pose_seq_input.load_to_ram(True)

    mask = np.zeros(np.shape(poses), dtype=np.bool)
    print('Computing Masks...')
    t = trange(len(pose_seq_input.train_keys), dynamic_ncols=True)
    for k in t:
        mask[k, :, :, :labs[k, 3]] = True

    poses = np.transpose(poses, [1, 2, 3, 0])
    mask = np.transpose(mask, [1, 2, 3, 0])

    masked_pose = np.reshape(poses[mask], [pose_seq_input.pshape[0], pose_seq_input.pshape[1], -1])

    del mask
    del labs
    del poses
    print('Computing Moments...')
    skel_mean = np.reshape(np.mean(masked_pose, axis=(0, 2)), [1, 1, 1, 3])
    skel_std = np.reshape(np.std(masked_pose, axis=(0, 2)), [1, 1, 1, 3])

    del masked_pose
    print(skel_mean, skel_std)
    save_arr(pose_seq_input, skel_mean, 'skel_mean')
    save_arr(pose_seq_input, skel_std, 'skel_std')