CorpusAid-PDF

A robust and efficient application for extracting text from PDF files while preserving layout or intelligently handling multi-column documents. Supports various output formats including TXT, HTML, Markdown, and DOCX.

Features

• Column-aware Extraction: Intelligently detects and extracts text from multi-column layouts, maintaining the correct reading order. Ideal for academic papers, magazines, and newspapers.
• Layout-preserved Extraction: Preserves the original document formatting, including spacing, indentation, and special characters. Suitable for forms, technical documents, and code listings.
• Multiple Output Formats: Export extracted text as TXT, HTML, Markdown, or DOCX.
• User-Friendly GUI: Intuitive interface for easy file selection, option configuration, and extraction.
• Batch Processing: Process multiple PDF files simultaneously.
• Search Functionality: Search within the extracted text for specific keywords.
• PDF Preview: Preview PDF pages within the application.
• Zoom and Fit-to-Width: Adjust the PDF preview for optimal viewing.
• Dark/Light Themes: Choose your preferred theme for a comfortable user experience.
• Drag and Drop Support: Drag and drop PDF files directly into the application.
• Cross-Platform: Works on Windows, macOS, and Linux.

Installation

Requires Python 3.7+ and the following libraries:

• PyMuPDF (fitz)
• PySide6
• docx

You can install these dependencies using pip:

pip install pymupdf PySide6 python-docx

Usage

1. Open PDF(s): Use the "Open PDF(s)" button or drag and drop PDF files into the application window.
2. Select Output Folder: Choose the destination folder for the extracted text files using the "Save As" button.
3. Choose Extraction Mode: Select either "Column-aware" or "Layout-preserved" mode based on the document's structure.
4. Select Output Format: Choose the desired output format (TXT, HTML, Markdown, DOCX).
5. Process PDF(s): Click the "Process PDF(s)" button to start the extraction process. A progress bar will indicate the progress.
6. View Results: The extracted text will be displayed in the "Processed Text" tab. You can also preview the original PDF in the "Original PDF" tab.

Contributing

Contributions are welcome! Please feel free to submit bug reports, feature requests, or pull requests.

License

This project is licensed under the MIT License. (Create a LICENSE file with the MIT license text).

Screenshots (Optional)

Include screenshots of your application here.

Contact

For any questions or issues, please contact [[email protected]].