KhmerOCR

A high-performance Khmer Optical Character Recognition (OCR) engine tailored for documents. This model was trained on 3 million text lines using over 800+ Khmer fonts to ensure robust recognition across various styles and weights.

Important

Update: The library now supports full document processing, layout detection, and multi-format exports (PDF, DOCX, HTML, Markdown).

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Features

• Fast: Optimized for Khmer script using ONNX Runtime for fast inference
• Native C++ Engine: High-performance C/C++ implementation with C API for FFI bindings
• Font Detection: Automatically identifies and preserves Moul vs. Regular font styles
• Multi-format Export: Convert images or PDFs into editable .docx, .md, .html, or .txt files
• PDF Support: High-resolution PDF rendering and processing via PyMuPDF
• Cross-Platform: Supports macOS, Linux, Windows, iOS, and Android

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Installation

Python

pip install git+https://github.com/seanghay/KhmerOCR

C++ Library

See cpp/README.md for build instructions.

cd cpp
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)

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Usage

Python CLI

For single images or documents, run:

khmerocr document.jpg --format docx

Python CLI Options

Option	Shortcut	Description	Default
--output	-o	Custom output path	input_filename.{format}
--format	-f	Output format: txt, html, docx, md	txt

C++ CLI

The C++ CLI is a lightweight inference tool focused on text extraction. For document formatting (DOCX, HTML, etc.), use the Python CLI.

# Full OCR (detect + recognize)
./cpp/build/khmerocr image.png

# JSON output
./cpp/build/khmerocr -j image.png

# Detection only
./cpp/build/khmerocr -d image.png

# Recognition only (for pre-cropped text images)
./cpp/build/khmerocr -r cropped_text.png

# Verbose output with confidence scores
./cpp/build/khmerocr -v image.png

Option	Shortcut	Description
--json	-j	Output results in JSON format
--detect-only	-d	Only detect text regions, skip recognition
--recognize-only	-r	Only recognize (skip detection)
--verbose	-v	Show confidence scores
--model-dir	-m	Custom model directory path

Example Output

When processing a line, the engine provides rich metadata:

{
  "text": "លទ្ធផលនៃការធ្វើកំណែទប្រង់លើទូរគមនាគមន៍កម្ពុជា",
  "text_confidence": 0.9804,
  "font": "Moul",
  "font_confidence": 0.9999
}

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Examples

Input	Detected Text	Font Style
[Line 1]	យេម៉ែនលង់ក្នុងសង្គ្រាម...	Bold
[Line 2]	ក្រសួងមហាផ្ទៃឱ្យត្រៀម...	Bold
[Line 3]	លទ្ធផលនៃការធ្វើកំណែ...	Moul

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Milestones

• Basic Font Style Detection
• Multi-line Document Support
• Export to DOCX/HTML/Markdown
• Add English & Symbol support
• Add ONNXRuntime for faster inference
• Add C/C++ Inference Engine

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License

Distributed under the MIT License. See the LICENSE file for more information.

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Contact

Seanghay Yath

• Email: seanghay.dev@gmail.com
• Telegram: @seanghay_yath

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Sponsored by KhmerScan

(បម្លែងរូបភាពទៅជាអត្ថបទខ្មែរ)