# Display or save frame if needed # ...

# Load a pre-trained model model = torchvision.models.resnet50(pretrained=True) model.eval() # Set to evaluation mode

# Get features with torch.no_grad(): features = model(tensor_frame)

while True: ret, frame = video_capture.read() if not ret: break # Convert to RGB and apply transform rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) tensor_frame = transform(rgb_frame)