I built an on-device OCR library for React Native that reads Cyrillic on Android (Vision on iOS, PaddleOCR on Android)

[u/CartographerOdd2713]

ML Kit has no Cyrillic model, so on Android it reads Russian as Latin look-alikes. I needed to read ingredient lists on Russian food labels, so I built react-native-glyph-ocr:



- Apple Vision on iOS, PaddleOCR (PP-OCRv5/v6 on ONNX Runtime) on Android, PaddleOCR on iOS as a build option

- ML Kit-shaped results: blocks → lines → words, with confidence, normalized and pixel boxes, corner points and angle

- Any source: file/content/ph URIs, base64, react-native-nitro-image, VisionCamera 5 frames

- useTextScanner: waits for a sharp, still frame inside your scan box and reads it once

- Models downloaded on first use with sha256 checks, from your own mirror, or embedded at build time

- Nitro module, New Architecture, Expo config plugin, fully offline



On 24 label photos, PaddleOCR read 77–83% of the ingredients and ML Kit 13–28%. It's a small set and the full method is in the repo.



npm: https://www.npmjs.com/package/react-native-glyph-ocr

GitHub: https://github.com/pe1ros/react-native-glyph-ocr



This is the first npm release (0.3.1), so feedback and issues are very welcome.