Paper Markdown Extractor

A small Qt desktop GUI for converting academic PDFs into clean Markdown. It extracts:

• Native PDF text with heading heuristics
• Tables, using PyMuPDF table detection
• Images into an adjacent images/ directory
• Display equations cropped as broad row images for higher visual fidelity, including right-edge equation numbers, with text math blocks available as a fallback
• Optional OCR fallback for scanned pages when Tesseract is installed
• Integrated Markdown preview with local images, equation crops, and tables rendered from the generated output

The fast path is built for digitally generated academic papers. A 10-page text PDF should usually finish well under one minute on a modern laptop. Scanned PDFs are slower because OCR requires page rendering.

Setup

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt

Optional OCR engine for scanned PDFs:

brew install tesseract

Run

python -m paper_md_extractor

Choose a PDF, choose an output folder, then click Convert. The app previews the generated Markdown and writes:

• <paper-name>.md
• images/ with extracted page images

Screenshots

Notes

PDFs do not reliably encode equations, reading order, or table structure semantically. This app favors a fast deterministic extraction pipeline and keeps the output editable. For image-only scanned papers, enable OCR and expect slower conversion.