pip install opencv-python torch torchvision numpy You'll need to load the video, extract frames, and then feed these frames into a deep learning model to generate features.

# Example model: ResNet50 model = torchvision.models.resnet50(pretrained=True) model.fc = torch.nn.Identity() # Modify to output features before the final layer

import torch import torchvision import torchvision.transforms as transforms

def extract_frames(video_path): cap = cv2.VideoCapture(video_path) frames = [] while cap.isOpened(): ret, frame = cap.read() if not ret: break # Convert to RGB (OpenCV reads in BGR) frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) frames.append(frame) cap.release() return frames For generating deep features, you might want to use a pre-trained model. A common choice is a convolutional neural network (CNN) like VGG16 or ResNet50.