Anal Friend Request.mp4 -

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

# Load a pre-trained model model = torchvision.models.video.i3d_resnet50(pretrained=True) anal friend request.mp4

# Reshape for model video_tensor = video_tensor.unsqueeze(0) # Add batch dimension print(features

# 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

# 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)