pose_transforms_mm.py

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import numpy as np
 
def make_np_keypoints(pose_list):
    num_frame = len(pose_list)
    num_person = max([len(x['keypoints']) for x in pose_list])
    num_keypoint = 17
    keypoint = np.zeros((num_frame, num_person, num_keypoint, 2), dtype=np.float16)
    keypoint_score = np.zeros((num_frame, num_person, num_keypoint), dtype=np.float16)
    
    for i, poses in enumerate(pose_list):
        keypoint[i] = poses['keypoints'][:, :, :2]
        keypoint_score[i] = poses['keypoints'][:, :, 2]
 
    keypoint = keypoint.transpose((1, 0, 2, 3))
    keypoint_score = keypoint_score.transpose((1, 0, 2))
 
    return {'keypoint' : keypoint, 'keypoint_score' : keypoint_score, 'clip_len' : num_frame}
 
 
def make_action_input_posec3d(pose_list, img_shape):
    num_frame = len(pose_list)
    fake_anno = dict(
        frame_dir='',
        label=-1,
        img_shape=img_shape,
        original_shape=img_shape,
        start_index=0,
        modality='Pose',
        total_frames=num_frame)
    
    fake_anno.update(make_np_keypoints(pose_list))
 
    return fake_anno
 
 
__make_data_func__ = {
    "PoseC3D" : make_action_input_posec3d,
}
 
def make_action_input(type, **args):
    return __make_data_func__[type](**args)
 
def get_action_input_func(type):
    return __make_data_func__[type]