TextLens: Image & PDF Text Extractor

A powerful, user-friendly desktop application for extracting text from images and PDF documents using Tesseract OCR.

✨ Features

• Multi-Format Support: Process PNG, JPG/JPEG, BMP, TIFF images and PDF documents
• PDF Navigation: Preview, navigate through pages, and selectively OCR pages
• Enhanced OCR: Advanced image preprocessing for improved text recognition accuracy
• Modern UI: Intuitive interface with multiple themes (light/dark) and customizable text display
• Workflow Tools: File history, drag & drop support, copy/save functions
• Responsive Design: Asynchronous processing with worker threads prevents UI freezing

🚀 Quick Start

Prerequisites

• Python 3.7+
• Tesseract OCR Engine (with appropriate language data files)

Installation

1. Clone the repository

   git clone https://github.com/Mxneeb/TextLens-IMG-PDF-Text-Extractor.git
   cd TextLens-IMG-PDF-Text-Extractor

2. Set up virtual environment (recommended)

   python -m venv venv
   
   # Windows
   venv\Scripts\activate
   
   # macOS/Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the application

   python gui.py

📦 Dependencies

• PyQt6: Modern GUI framework
• Pytesseract: Python wrapper for Tesseract OCR
• OpenCV-Python: Image processing library
• PyMuPDF: PDF handling
• NumPy: Numerical operations

🖼️ Screenshots

🔧 Advanced Configuration

Tesseract Installation

Windows

1. Download the installer from UB Mannheim
2. During installation, make sure to:
   • Add Tesseract to PATH
   • Install language data files (at minimum, English)

macOS

brew install tesseract
brew install tesseract-lang  # for additional language support

Linux

sudo apt install tesseract-ocr
sudo apt install tesseract-ocr-eng  # for English language data

📂 Project Structure

TextLens-IMG-PDF-Text-Extractor/
├── gui.py                 # Main application GUI
├── source/
│   └── source.py          # OCR and image processing logic
├── icons/                 # UI icons
├── history/               # Created at runtime (user settings & history)
├── README.md
└── requirements.txt

🔮 Future Enhancements

• Language selection in GUI
• Advanced image preprocessing options
• Export to searchable PDF
• Batch processing
• Cross-platform binary releases

📄 License

MIT License - see the LICENSE file for details.

👨‍💻 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request