Vid_1158.mp4

# More complex visual feature extraction def extract_visual_features(frames): model = models.resnet50(pretrained=True) model.fc = torch.nn.Identity() # Remove the final classification layer device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') model.to(device) model.eval()

To prepare a feature for a video file named "vid_1158.mp4", we'll need to consider what kind of features are typically extracted or used in the context of video analysis or processing. Features in video analysis can range from simple metadata to complex descriptors of the video content. vid_1158.mp4

visual_features = [] for frame in frames: frame = transform(frame) frame = frame.unsqueeze(0).to(device) feature = model(frame) feature = feature.squeeze(0).detach().cpu().numpy() visual_features.append(feature) return visual_features vid_1158.mp4

video_path = "vid_1158.mp4" simple_features = extract_simple_features(video_path) frames = load_video(video_path) visual_features = extract_visual_features(frames) vid_1158.mp4