def _load_frames( video_file: Path, frame_idx: Union[slice, List[slice], List[int]], ) -> Iterator[Image]: from torchvideo.internal.readers import default_loader return default_loader(video_file, frame_idx)
def _load_frames(self, frames_idx, video_file): from torchvideo.internal.readers import default_loader from torchvideo.samplers import frame_idx_to_list if os.path.splitext(video_file)[-1] in ['.NPY', '.npy']: vid = np.load(video_file) frames_idx = np.array(frame_idx_to_list(frames_idx)) vid = vid[frames_idx] return (Image.fromarray(frame) for frame in vid) else: return default_loader(video_file, frames_idx)