PDFXtract

::A cross-platform utility that converts PDF documents into Markdown-formatted text::

MacOS	Windows

Description

PDFXtract is a simple yet powerful utility for converting PDF files to plain text with Markdown formatting. Whether you are an academic researcher, a data analyst, or just someone who needs to extract text from a PDF document, PDFXtract has got you covered.

Features

• PDF to Markdown: Extracts text from a PDF and formats it in Markdown for easy reading and further editing.
• Multi-Page Support: Handles multi-page PDFs with ease.
• Clipboard Integration: Copy the entire text or a specific page directly to your clipboard.
• Markdown Preview: Preview how the Markdown-formatted text will look in a web browser.
• Cross-Platform: Available for both Windows and macOS.

Installation

For Windows Users

• Download the .exe file from the Releases page.
• Double-click the .exe file to install PDFXtract.
• Follow the on-screen instructions to complete the installation.
• You can press here, too.

For macOS Users

• Download the .dmg file from the Releases page.
• Double-click the .dmg file to mount it.
• Drag the PDFXtract.app into your Applications folder.
• You can press here, too.

Use src.py for your custom use

• Download the src.py and requirements.txt files.
• Install the required packages using pip install -r requirements.txt.
• Run the src.py file using python src.py or python3 src.py.

How to Use

1. Open PDF File: Click the "Open PDF File" button to load your PDF.
2. Convert: Click the "Convert" button to start the extraction process.
3. Copy to Clipboard: If you want to copy the text to your clipboard, click the "Copy to Clipboard" button.
4. Copy Specific Page: To copy a specific page, enter the page number and click the "Copy Specific Page" button.
5. Preview Markdown: Click the "Preview Markdown" button to see how the Markdown-formatted text will appear in a web browser.

Contributing

I welcome contributions from the community. Feel free to submit issues or create pull requests.

License

This project is licensed under the MIT License.

Author

• @wjgoarxiv