Shkd257 Avi · Top & Premium

# Create a directory to store frames if it doesn't exist frame_dir = 'frames' if not os.path.exists(frame_dir): os.makedirs(frame_dir)

def extract_features(frame_path): img = image.load_img(frame_path, target_size=(224, 224)) img_data = image.img_to_array(img) img_data = np.expand_dims(img_data, axis=0) img_data = preprocess_input(img_data) features = model.predict(img_data) return features shkd257 avi

cap.release() print(f"Extracted {frame_count} frames.") Now, let's use a pre-trained VGG16 model to extract features from these frames. # Create a directory to store frames if

pip install tensorflow opencv-python numpy You'll need to extract frames from your video. Here's a simple way to do it: shkd257 avi