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How to read mixed-language and handwritten scans in one run with Indra

OCR scans in many scripts and handwriting, with a CJK-only or RTL-only fallback when needed.

  • Research
  • Advanced
  • 45 minutes
  • From the README
  • Any agent

Who it is forA team processing archival or community documents in Chinese, Arabic, Hindi, or handwritten Latin text who needs one tool for all of them.

The problemMost OCR tools need a separate setup per script, and handwriting is often skipped entirely.

The outcomeMarkdown or text output for pages in many scripts, with handwriting read where it appears in Latin script.

What you need first

  • Python 3.10 or newer (the README says it is tested on Linux and macOS)
  • pip to install the indra-ocr package
  • An internet connection for the first run, which downloads about 76 MB of models from Hugging Face
  • The PDFs or images to read

Steps

  1. Run pip install indra-ocr.
  2. Run indra-ocr <file>.pdf --mode ocr --timings to OCR every page and see the time per page on stderr. (inferred, check the README)
  3. Check the output for the scripts you care about, such as Chinese, Arabic, or Devanagari.
  4. Confirm the handwriting pages read as expected, keeping in mind the README gives a 25.2% handwriting score on its tests.
  5. Use indra-ocr <file>.pdf --format text if you only need plain lines. (inferred, check the README)

Prompt for your agent

Using the repo datalab-to/indra, install indra-ocr and run `indra-ocr <file>.pdf --mode ocr --timings` on <file>.pdf. Expected output: markdown with the text in each script and per-page timings on stderr. Verify the text for each script against the source page, since handwriting accuracy is limited.

Caveat. The README reports low handwriting accuracy on its own tests, so results on handwritten pages need a human check before use.

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