screenshot-to-code turns static visuals into production-ready frontend code using AI vision models including GPT-4V, Claude Opus 4.5, and Gemini. Drop in a screenshot, a Figma export, or a URL, and the tool returns clean HTML with Tailwind CSS, React components, or plain Vue — no manual translation from design to markup. It also supports video recordings, letting developers iterate on UI animations frame-by-frame.
The project sits at over 71,000 GitHub stars and is one of the most-starred design-to-code repositories in existence. Unlike prompt-first builders like v0 or Bolt.new that start from a text description, screenshot-to-code is pixel-first: it reads the actual layout, color, and spacing of what you show it. This makes it especially useful when working from existing designs, Figma mockups, or cloning reference UIs where fidelity matters more than flexibility.
Self-hosting is straightforward via Docker, and a managed hosted version is available at screenshottocode.com for teams that prefer not to manage API keys directly. The tool is MIT-licensed, actively maintained, and serves as a benchmark reference implementation for the screenshot-to-code problem — making it an important anchor for comparison content covering tools like v0, Galileo AI, and Locofy.
