How to Extract AI-Ready Prompts from Any Video Using Computer Vision

How to Extract AI-Ready Prompts from Any Video Using Computer Vision If you've ever tried to describe a video scene in words precise enough for Sora or Runway to reproduce, you know the frustration. Human descriptions tend to be vague — we say "moody" when the AI needs "low-key lighting, 5600K color temperature, desaturated teal shadows with lifted blacks." Computer vision can close that gap by systematically extracting visual attributes from video frames. In this article, I'll walk through the practical techniques for building a frame-level analysis system that turns any video into structured prompt data. Why Frame Analysis Matters for Prompt Quality Most people approach AI video generation by writing prompts from memory or imagination. The problem: we're remarkably bad at articulating visual details. Consider describing a 10-second clip from a cooking video. You might write: "A chef cooking in a kitchen" But the visual reality contains dozens of describable attributes: "Overhead shot