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2.41 kB
| from PIL import Image | |
| import math | |
| from decord import VideoReader, cpu | |
| import numpy as np | |
| import os | |
| import torch | |
| def _get_rawvideo_dec(video_path, image_processor, max_frames=64, image_resolution=224, video_framerate=1, s=None, e=None): | |
| # speed up video decode via decord. | |
| video_mask = np.zeros(max_frames, dtype=np.int64) | |
| max_video_length = 0 | |
| # T x 3 x H x W | |
| video = np.zeros((max_frames, 3, image_resolution, image_resolution), dtype=np.float64) | |
| if s is None: | |
| start_time, end_time = None, None | |
| else: | |
| start_time = int(s) | |
| end_time = int(e) | |
| start_time = start_time if start_time >= 0. else 0. | |
| end_time = end_time if end_time >= 0. else 0. | |
| if start_time > end_time: | |
| start_time, end_time = end_time, start_time | |
| elif start_time == end_time: | |
| end_time = start_time + 1 | |
| if os.path.exists(video_path): | |
| vreader = VideoReader(video_path, ctx=cpu(0)) | |
| else: | |
| print(video_path) | |
| raise FileNotFoundError | |
| fps = vreader.get_avg_fps() | |
| f_start = 0 if start_time is None else int(start_time * fps) | |
| f_end = int(min(1000000000 if end_time is None else end_time * fps, len(vreader) - 1)) | |
| num_frames = f_end - f_start + 1 | |
| if num_frames > 0: | |
| # T x 3 x H x W | |
| sample_fps = int(video_framerate) | |
| t_stride = int(round(float(fps) / sample_fps)) | |
| all_pos = list(range(f_start, f_end + 1, t_stride)) | |
| if len(all_pos) > max_frames: | |
| sample_pos = [all_pos[_] for _ in np.linspace(0, len(all_pos) - 1, num=max_frames, dtype=int)] | |
| else: | |
| sample_pos = all_pos | |
| patch_images = [Image.fromarray(f) for f in vreader.get_batch(sample_pos).asnumpy()] | |
| patch_images = [image_processor.preprocess(img, return_tensors='pt')['pixel_values'][0] for img in patch_images] | |
| slice_len = len(patch_images) | |
| max_video_length = max_video_length if max_video_length > slice_len else slice_len | |
| if slice_len < 1: | |
| pass | |
| else: | |
| while len(patch_images) < max_frames: | |
| patch_images.append(torch.zeros((3, image_resolution, image_resolution))) | |
| # video[:slice_len, ...] = patch_images | |
| else: | |
| print("video path: {} error.".format(video_path)) | |
| video_mask[:max_video_length] = [1] * max_video_length | |
| return patch_images, video_mask |