Da (3).mp4 < ULTIMATE >

# Process features as needed print(features.shape)

# Read video video_capture = cv2.VideoCapture('da (3).mp4') da (3).mp4

# Transform to apply to frames transform = transforms.Compose([ transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ]) # Process features as needed print(features

video_capture.release() This example demonstrates a basic approach to extracting features from video frames using a pre-trained ResNet50 model. You can adapt it based on your specific requirements, such as changing the model, applying different transformations, or processing the features further. such as changing the model

# Add batch dimension tensor_frame = tensor_frame.unsqueeze(0)