📱 DocScan - Flutter Document Scanner & Text Editor

DocScan is an open-source Flutter app that lets you scan documents, recognize text, and edit it instantly using Google ML Kit Text Recognition.
You can take a photo of any document, extract its text, and edit or copy it — all within one simple and modern UI.

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✨ Features

✅ Document Scanning – Capture clear document images using CameraX
✅ Text Recognition (OCR) – Extract text from scanned images with Google ML Kit
✅ Text Editing – Built-in editor to modify recognized text directly in the app
✅ Copy to Clipboard – Quickly copy recognized text for reuse anywhere
✅ Clean Material UI – Minimal, modern, and responsive Flutter design
✅ Offline Functionality – Works fully offline after installation

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🧠 Tech Stack

• Flutter (Dart)
• Google ML Kit (Text Recognition)
• CameraX
• Material Design Components
• Clipboard API for easy text copy

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📸 Screenshots

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🏗️ How It Works

1. Open the app and capture a document using your camera.
2. The app automatically detects and extracts text using ML Kit OCR.
3. View the recognized text on screen.
4. Edit or copy the text easily.

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🏗️ Folder Structure

lib/
│
├── main.dart
├── screens/
│   ├── onboarding_screen.dart
│   ├── text_recognizer_screen.dart
│   ├── editor_screen.dart
│
└── widgets/
    └── custom_button.dart

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🚀 Getting Started

1. Clone the repository

git clone https://github.com/aamirali65/docscanner
cd docscan_flutter

2. Install dependencies

flutter pub get

3. Run the app

flutter run

⚙️ Permissions Required

• Camera Permission – To scan and capture documents
• Storage Permission – To access images for text recognition

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🧩 How It Works

1. Launch the app and capture or pick a document image.
2. ML Kit automatically extracts all readable text from the image.
3. View and edit the recognized text inside the built-in editor.
4. Copy or save the text for later use.

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💡 Why I Built This

I built DocScan to explore how on-device machine learning can be integrated with Flutter.
It’s a simple but powerful example of combining OCR, document scanning, and text editing in one seamless experience.
The goal was to create a tool that feels lightweight, works offline, and performs fast even on low-end devices.

🪪 License

This project is licensed under the MIT License.
You’re free to use, modify, and share it with proper attribution.