Anal Friend Request.mp4 ⚡

# Load video and extract frames def video_to_tensor(video_path): cap = cv2.VideoCapture(video_path) frames = [] while cap.isOpened(): ret, frame - cv2.read() if not ret: break frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) frame = transform(frame) frames.append(frame) cap.release() return torch.stack(frames)

print(features.shape) The extracted features can be used for various downstream tasks such as video clustering, similarity search, classification, etc. anal friend request.mp4

# Prepare a transform for preprocessing frames transform = transforms.Compose([ transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ]) anal friend request.mp4

# Modify the model to output features num_ftrs = model.fc.in_features model.fc = nn.Identity() # Replace the classification layer with an identity function anal friend request.mp4

# Extract features with torch.no_grad(): features = model(video_tensor)