Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset

Hugo Laurençon, Leo Tronchon, Victor Sanh

Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset: 57 upvotes on Hugging Face Daily Papers, #3 of 14 papers on 2024-03-15. Day-by-day upvote history.

Using vision-language models (VLMs) in web development presents a promising strategy to increase efficiency and unblock no-code solutions: by providing a screenshot or a sketch of a UI, a VLM could generate the code to reproduce it, for instance in a language like HTML. Despite the advancements in VLMs for various tasks, the specific challenge of converting a screenshot into a corresponding HTML has been minimally explored. We posit that this is mainly due to the absence of a suitable, high-quality dataset. This work introduces WebSight, a synthetic dataset consisting of 2 million pairs of HTML codes and their corresponding screenshots. We fine-tune a foundational VLM on our dataset and show proficiency in converting webpage screenshots to functional HTML code. To accelerate the research in this area, we open-source WebSight.

Paper page on Hugging Face · arXiv

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