# Extract features with torch.no_grad(): outputs = model(inputs) return outputs.detach().cpu().numpy() # Extract features with torch
: Preprocess your video data. This can involve converting videos into frames, resizing them to a uniform size, and possibly applying data augmentation techniques. resizing them to a uniform size
: Once the model is fine-tuned, you can extract features from your videos. This typically involves taking the output of one of the layers (often a layer before the final classification layer) as the feature representation. improving its performance.
: Fine-tune your chosen model on your specific dataset. This step adapts the pre-trained model to your particular task, improving its performance.