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MonOCR

MonOCR Feature Graphic

English | မြန်မာဘာသာ | ဘာသာမန်


Mon is spoken by roughly one million people across Myanmar and Thailand. UNESCO classifies it as vulnerable — and no OCR toolchain existed for it before this project.

MonOCR takes an image of Mon script and returns text. It runs on Web, Android, and iOS — fully offline, no data leaves the device.

Built and maintained by the Mon developer community.


Live


Models

Two models are actively trained and maintained:

v3.5 — Mobile v4 — Server
Purpose On-device / edge Server-side / documents
Architecture MobileNetV3 + 2×BiLSTM(512) + CTC Swin-T Encoder + 6-layer Transformer Decoder
Parameters 11.4M ~54M
Input Grayscale, 160px height RGB, 224×1024px
Export ONNX FP32/FP16/INT8 · CoreML ONNX only
Inference (CPU) ~30ms/line ~180ms/line

The mobile model (v3.5) runs on-device across Web (WASM), Android (NNAPI), and iOS (Core ML). The server model (v4) handles complex document images with colour backgrounds and longer text sequences.

Because high-quality Mon datasets are scarce, validated samples from the app's feedback flow feed directly into future training rounds.


Platform

The mobile model (v3.5) deploys to Web, Android, and iOS — each using the format that enables hardware acceleration:

Platform Format Acceleration
Web ONNX WASM
Android ONNX NNAPI
iOS CoreML .mlpackage Apple Neural Engine

Resources


Contributing

Janakh Pon · Oung Seik Nyan · Rajel Da Key · MonDevHub

About

The MonOCR Platform: Academic-grade OCR for the Mon language. High-performance, privacy-first ecosystem across Web (SvelteKit), iOS (SwiftUI), and Android (Kotlin).

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