The Nex Video Frame Pipeline is a developer-centric utility that automates the complex process of turning a standard MP4 video into a high-performance, web-optimized frame sequence. It performs a multi-stage operation: analyzing video metadata via ffprobe, calculating an optimal frame-to-scroll-depth ratio, and extracting synchronized frames at dual resolutions (Desktop/Mobile). It uses an intelligent FFmpeg libwebp fast-path with a Pillow fallback to ensure it runs in any environment where Python and FFmpeg are available.

Manually extracting frames for “Apple-style” scroll animations is tedious and error-prone. This skill handles the heavy lifting by ensuring your frame naming is perfectly sequential, your payloads stay within web budgets (15MB Desktop / 5MB Mobile), and your aspect ratios remain consistent across devices. It eliminates the guesswork of “how many frames do I need for this duration?” by using a proven mathematical formula for smooth scrolling.

The pipeline generates organized directories of WebP images and a critical manifest.json. This manifest includes source metadata and a recommended scroll height, making it ready for immediate injection into scroll-driven animation engines like GSAP or NEX Scroll. It automatically warns you if your total file size is likely to cause performance issues on mobile devices.

Automated dual-resolution (Desktop/Mobile) extraction.
Smart frame-count calculation based on video duration.
Payload budget monitoring and optimization recommendations.
Robust FFmpeg/Pillow fallback architecture.
Standardized manifest generation for downstream JS engines.

Built by Nex AI. More skills and info at https://nex-ai.be and https://slopsome.com.