JinpengLI/deep_ocr
make a better chinese character recognition OCR than tesseract observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3629
- days_rel: n/a
- days_push: 3216
- n_releases_24m: 0
Adoption not part of the score
1511 stars · 481 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python-based deep learning OCR tool built on Caffe that recognizes Chinese characters, positioned as a better alternative to Tesseract for Chinese text. It also includes experimental Chinese ID card recognition and Docker images for CPU-based deployment.
Use cases
- recognize chinese text in images better than tesseract
- ocr chinese characters from screenshots
- extract text from chinese id card images
- train custom chinese character recognition models with caffe
- run chinese ocr in a docker container on cpu
When to avoid
- you need a maintained project with recent updates or a license
- you need OCR for non-Chinese languages
- you need production-grade ID card recognition, which the author notes is unstable
- you work outside Linux/Ubuntu
Facets
library · maturity abandoned
ocr image-processing machine-learning deep-learning computer-vision image-processing machine-learning python cli chinese-ocr caffe character-recognition id-card-recognition tesseract-alternative natural-language-processing linux docker
1 source
- readme: https://github.com/JinpengLI/deep_ocr · fetched 2026-08-28 · 8f9b581280c1
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| JinpengLI/deep_ocr | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="JinpengLI/deep_ocr")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem