Ucas-HaoranWei/GOT-OCR2.0

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

8216 stars · 711 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official implementation of GOT-OCR2.0, a unified end-to-end vision-language model for general OCR that converts images of text, documents, formulas, and charts into structured text. It is a research codebase with a Hugging Face model, now also integrated into the transformers library.

Use cases

• extract text from images with ocr
• convert scanned pdf documents to markdown
• recognize math formulas from screenshots
• parse tables and charts into text
• run ocr with a vision language model
• fine-tune an ocr model on my own data

When to choose

• you need end-to-end OCR beyond plain text, including formulas, tables, and charts
• you want a Hugging Face transformers-compatible OCR model
• you are doing document-parsing research or building document ingestion pipelines

When to avoid

• you need a lightweight CPU-only OCR like Tesseract
• you require a permissive license - the repo has no license, limiting commercial use
• you need production support or a stable API rather than research code

Facets

library · maturity active

ocr machine-learning deep-learning llm-inference image-processing pdf computer-vision artificial-intelligence pdf deep-learning python cross-platform ocr-2-0 vision-language-model end-to-end-ocr document-parsing research-code no-license natural-language-processing gpu linux

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markdown · JSON · MCP: product_card(name="Ucas-HaoranWei/GOT-OCR2.0")