Video Frame Extractor — Hybrid Browser & Server (FastAPI + FFmpeg)

Video Frame Extractor is a complete, production-ready web application that extracts high-quality JPEG frames from any video file. What makes it unique is its HYBRID architecture: on capable desktop browsers, the entire extraction happens LOCALLY using WebAssembly (ffmpeg.wasm) — the video never leaves the user's device. On mobile or weaker devices, it automatically falls back to server-side processing using native FFmpeg. The user always gets a result.

Built with FastAPI (Python) and Docker, it deploys on any VPS in minutes. The interface ships in 6 languages (English, French, Arabic, Spanish, German, Chinese) with full right-to-left support, and includes a polished light/dark theme. No database required, no sign-up, no external dependencies to configure.

This is clean, well-documented, single-purpose code — easy to read, rebrand, and extend. Whether you want to launch your own frame-extraction service or integrate the engine into a larger product, everything you need is included: the hybrid client engine, the FastAPI backend, the Docker setup, and full documentation.

WHAT YOU GET

• Full source code (Python / FastAPI backend + vanilla JS frontend)
• Hybrid in-browser + server-side extraction engine
• Docker & docker-compose files for one-command deployment
• 6-language UI with RTL + light/dark theme
• Complete README with setup, configuration & customization guide
• No license keys, no obfuscation — 100% editable source

WHAT YOU GET

• Full source code (Python / FastAPI backend + vanilla JS frontend)
• Hybrid in-browser + server-side extraction engine
• Docker & docker-compose files for one-command deployment
• 6-language UI with RTL + light/dark theme
• Complete README with setup, configuration & customization guide
• No license keys, no obfuscation — 100% editable source

NOTE ON FILE SIZE: The download is intentionally lightweight (~52 KB) because it contains pure, clean source code — not bundled dependencies. All heavy libraries (FFmpeg, Python packages) are installed automatically at build time via Docker. This means you get readable, maintainable code and a reproducible one-command deployment — not a bloated archive.