Snis-896.mp4 May 2026

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.

def extract_metadata(video_path): probe = ffmpeg.probe(video_path) video_stream = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None) width = int(video_stream['width']) height = int(video_stream['height']) duration = float(probe['format']['duration']) return { 'width': width, 'height': height, 'duration': duration, } SNIS-896.mp4

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: features = generate_video_features("SNIS-896

import cv2 import numpy as np

return { 'avg_color': (avg_r, avg_g, avg_b) } SNIS-896.mp4