id_ocr 0.1.0

A robust Flutter plugin for CNIC (Computerized National Identity Card) OCR with specialized support for Urdu and Sindhi scripts using Google ML Kit and Tesseract.

id_ocr

A robust and versatile Flutter plugin for CNIC (Computerized National Identity Card) detection and OCR, with specialized support for Urdu and Sindhi scripts.

This plugin combines the power of Google ML Kit for fast document detection and standard text recognition (English/Numeric) with Tesseract OCR as a fallback for complex Urdu and Sindhi scripts.

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✨ Features

• Guided Card Scanning: Automatic document cropping and perspective correction using google_mlkit_document_scanner.
• Hybrid OCR Engine:
  • Google ML Kit: High-speed extraction for English names, CNIC numbers, and dates.
  • Tesseract fallback: Specialized support for Urdu and Sindhi script extraction (names, addresses).
• Comprehensive Data Model: Extracts and maps data to a structured CnicModel (Name, Father's Name, CNIC Number, Date of Birth, Expiry Date, and Address).
• Customizable UI Flow: Easy-to-integrate services that can fit any design language.
• Micro-Animations: Built-in support for scanning animations and loaders.

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🚀 Getting Started

1. Add Dependency

Add this to your package's pubspec.yaml file:

dependencies:
  id_ocr: ^0.1.0

2. Platform Setup

Android

Update your android/app/build.gradle:

• minSdkVersion should be at least 21.

Add permissions to AndroidManifest.xml:

<uses-permission android:name="android.permission.CAMERA" />
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />

iOS

Add the following to your ios/Runner/Info.plist:

<key>NSCameraUsageDescription</key>
<string>We need access to your camera to scan the CNIC.</string>
<key>NSPhotoLibraryUsageDescription</key>
<string>We need access to your gallery to upload the CNIC image.</string>

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🛠 Usage

Integrating id_ocr is straightforward. You can use the ScannerService for capturing images and OcrService for processing them.

Simple Example

import 'package:id_ocr/id_ocr.dart';

// 1. Initialize services
final ScannerService _scannerService = ScannerService();
final OcrService _ocrService = OcrService();

// 2. Scan and Process
Future<void> scanAndExtract() async {
  // Capture image using document scanner
  final String? path = await _scannerService.scanDocument();
  
  if (path != null) {
    // Process the image for the front side
    CnicModel extractedData = await _ocrService.processImage(path, isFront: true);
    
    print('Name: ${extractedData.name}');
    print('CNIC: ${extractedData.cnicNumber}');
  }
}

Data Model

The CnicModel contains the following fields:

• name: Full name of the individual.
• fatherName: Father's or Husband's name.
• cnicNumber: 13-digit identity number.
• dob: Date of Birth.
• expiry: Card expiry date.
• address: Residential address (typically from the back side).

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🏗 Built-in UI (Example App)

The plugin comes with a complete implementation example using GetX that showcases a guided step-by-step scanning flow. Check the example folder for details.

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📜 License

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

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🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests to improve the OCR accuracy or add new features.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request