pp_ocr 0.1.2

Flutter plugin for offline OCR using PP-OCRv6 (PaddleOCR) with ONNX Runtime C++ inference. Supports text detection and recognition on Windows.

pp_ocr

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A Flutter plugin for offline OCR (Optical Character Recognition) on Windows, powered by PaddleOCR's PP-OCRv6 models and ONNX Runtime.

Features

• Offline OCR — No internet connection required. All inference runs locally.
• Text Detection — DB (Differentiable Binarization) based text detection.
• Text Recognition — CRNN + CTC based text recognition with support for Chinese, English, and 18,000+ characters.
• Unicode Path Support — Correctly handles non-ASCII file paths (Chinese, Japanese, etc.) on Windows.
• Bounding Box Overlay — Returns detection boxes with recognized text and confidence scores.

Platform Support

Platform	Support
Windows	✅
Android	❌
iOS	❌
macOS	❌
Linux	❌

Requirements

• Flutter >= 3.0.0
• Windows 10 or later
• Visual Studio 2022 with CMake support
• ONNX Runtime 1.20.1 (auto-downloaded during build)
• OpenCV 4.9.0 (auto-downloaded or pre-built)

Installation

Add this to your pubspec.yaml:

dependencies:
  pp_ocr: ^0.1.2

Model Files

Download the PP-OCRv6 ONNX models and place them in a model/ directory:

model/
├── det.onnx            # Text detection model
├── inference.onnx       # Text recognition model
└── ppocr_v6_dict.txt    # Character dictionary (18,708 entries)

Models can be obtained from PaddleOCR and converted to ONNX format using Paddle2ONNX.

Usage

import 'package:paddle_ocr/paddle_ocr.dart';

final ocr = PaddleOcr();

// Initialize with model paths
await ocr.initialize(
  detModelPath: 'path/to/det.onnx',
  recModelPath: 'path/to/inference.onnx',
  dictPath: 'path/to/ppocr_v6_dict.txt',
);

// Recognize text from an image file
final results = await ocr.recognizeImage('path/to/image.png');

for (final result in results) {
  print('Text: ${result.text}');
  print('Confidence: ${result.confidence}');
  print('Box: ${result.box}');
}

See the example app for a complete demo with image picker and visual box overlay.

Architecture

The plugin consists of:

• Dart layer (lib/) — Platform interface and method channel implementation
• C++ layer (windows/) — Native OCR engine using ONNX Runtime and OpenCV
  • ocr_engine.cpp — Text detection (DB) and recognition (CRNN+CTC) pipeline
  • paddle_ocr_plugin.cpp — Flutter method channel handler
  • debug_utils.h — UTF-8 validation and debug logging utilities

License

This project is licensed under the MIT License.

This project uses the following third-party components:

• OpenCV (Apache License 2.0)
• PaddleOCR PP-OCRv6 models (Apache License 2.0)
• ONNX Runtime (MIT License)

See NOTICE for details.