# Transform transform = transforms.Compose([ transforms.Resize((112, 112)), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ])
# Assuming you have a video file and want to extract a feature vector SSIS00338.mp4
def extract_basic_features(video_path): cap = cv2.VideoCapture(video_path) if not cap.isOpened(): print("Error opening video") return fps = cap.get(cv2.CAP_PROP_FPS) frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) duration = frame_count / fps print(f"Video Path: {video_path}") print(f"FPS: {fps}") print(f"Frame Count: {frame_count}") print(f"Duration (seconds): {duration}") # Transform transform = transforms
pip install opencv-python You can extract basic features such as video duration, frame rate, and frame count. SSIS00338.mp4
# Load model model = video.r3d_18(pretrained=True)
# Load and transform video... # This part is highly specific to your video loading and transformation needs