tesseract-ocr
@tesseract-ocr • Tesseract OCR. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
95%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
14 repos
Visible snapshot
3 repositories updated in the last 90 days.
Leading language
Unknown
Portfolio mix
Unknown (7), HTML (2), C++ (1)
Average size
6.5K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2026-07-25(31d ago)GitHub API fallback14 repositories
95%
of the visible star count comes from this organization's top three repositories.
6.5K
stars per repository in this same snapshot.
Unknown
is the most common language here, with 3 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 84% of its visible star count.
Flagship share 84%Breakout repo: tesseract
Organization pages work best when you separate portfolio breadth from flagship concentration. In tesseract-ocr's case, the visible top three repositories account for about 95% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Unknown (7), HTML (2), C++ (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | tesseract-ocr/tesseract Tesseract Open Source OCR Engine (main repository) | C++ | 76.2K |
| 2 | tesseract-ocr/tessdata Trained models with fast variant of the "best" LSTM models + legacy models | 7.6K | |
| 3 | tesseract-ocr/tessdoc Tesseract documentation | HTML | 2.4K |
| 4 | tesseract-ocr/tessdata_best Best (most accurate) trained LSTM models. | 1.6K | |
| 5 | tesseract-ocr/langdata Source training data for Tesseract for lots of languages | 872 | |
| 6 | tesseract-ocr/tesstrain Train Tesseract LSTM with make | Python | 723 |
| 7 | tesseract-ocr/tessdata_fast Fast integer versions of trained LSTM models | 610 | |
| 8 | tesseract-ocr/docs Various documents related to Tesseract OCR | 270 | |
| 9 | tesseract-ocr/langdata_lstm Data used for LSTM model training | 127 | |
| 10 | tesseract-ocr/tesseract-ocr.github.io Tesseract documentation | Ruby | 75 |
| 11 | tesseract-ocr/tessconfigs Tesseract Config files | Makefile | 36 |
| 12 | tesseract-ocr/test Repository for tesseract testing | Shell | 34 |
| 13 | tesseract-ocr/tessdata_contrib User contributed (non Google) OCR models for Tesseract | 33 | |
| 14 | tesseract-ocr/tessapi Tesseract source code and API documentation | HTML | 13 |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.