pip install torch torchvision We'll use the SlowFast model pre-trained on Kinetics-400. This example assumes you're familiar with PyTorch basics.

video_path = '22241.mp4' frames_tensor = load_video(video_path) def extract_features(model, video_tensor): # This may need to be adjusted based on the model and the input requirements inputs = video_tensor.unsqueeze(0) # Add batch dimension with torch.no_grad(): features = model(inputs) return features.squeeze()

features = extract_features(model, frames_tensor) print(features.shape) You might want to save these features for later use:

For simplicity and effectiveness, let's outline a method using PyTorch and a pre-trained model. We'll use a model pre-trained on the Kinetics dataset, which is a common benchmark for video action recognition tasks. Specifically, we can leverage the SlowFast model, which has shown excellent performance on various video understanding tasks. Ensure you have PyTorch and torchvision installed. If not, you can install them via pip:

model = prepare_model() To extract features, we first need to preprocess the video. This involves loading the video, possibly resizing it, and converting it into a tensor that the model can process.