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Sierkinhane/CRNN_Chinese_Characters_Rec

(CRNN) Chinese Characters Recognition. observed · 2026-08-28

github.com/Sierkinhane/CRNN_Chinese_Characters_Rec · Python 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: 2898
  • days_rel: n/a
  • days_push: 1389
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1875 stars · 533 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of a CRNN (convolutional recurrent neural network) model for recognizing Chinese characters in images. It includes training scripts, configuration files, and pretrained checkpoints for Chinese text recognition.

Use cases

  • recognize chinese text in images
  • train an ocr model for chinese characters
  • run crnn text recognition on a photo
  • fine-tune a chinese character recognition model on my own dataset
  • extract text from chinese screenshots

When to choose

  • you need to recognize Chinese characters specifically
  • you want a trainable PyTorch OCR model you can fine-tune on custom data
  • you want a simple, well-known CRNN baseline for scene text recognition

When to avoid

  • you need production-ready OCR with active maintenance and a license
  • you need multi-language or Latin-script OCR out of the box
  • you need a packaged CLI or API rather than research code

Facets

library · maturity maintenance

ocr deep-learning image-processing machine-learning computer-vision deep-learning image-processing python windows crnn chinese-characters pytorch text-recognition ctc-loss natural-language-processing linux gpu

1 source

Member repositories

RepositoryRoleHealth v2
Sierkinhane/CRNN_Chinese_Characters_Recmain32

For agents

markdown · JSON · MCP: product_card(name="Sierkinhane/CRNN_Chinese_Characters_Rec")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem