content_features = analyze_video_content("SNIS-896.mp4") print(content_features) You could combine these steps into a single function or script to generate a comprehensive set of features for your video.
metadata = extract_metadata("SNIS-896.mp4") print(metadata) For a basic content analysis, let's consider extracting a feature like the average color of the video: SNIS-896.mp4
features = generate_video_features("SNIS-896.mp4") print(features) This example provides a basic framework. The type of features you need to extract will depend on your specific use case. More complex analyses might involve machine learning models for object detection, facial recognition, or action classification. content_features = analyze_video_content("SNIS-896
import ffmpeg
def analyze_video_content(video_path): cap = cv2.VideoCapture(video_path) if not cap.isOpened(): return frame_count = 0 sum_b = 0 sum_g = 0 sum_r = 0 More complex analyses might involve machine learning models
pip install opencv-python ffmpeg-python moviepy Here's a basic example of how to extract some metadata:
while cap.isOpened(): ret, frame = cap.read() if not ret: break frame_count += 1 sum_b += np.mean(frame[:,:,0]) sum_g += np.mean(frame[:,:,1]) sum_r += np.mean(frame[:,:,2]) cap.release() avg_b = sum_b / frame_count avg_g = sum_g / frame_count avg_r = sum_r / frame_count