Texify

Texify converts equations and surrounding text into markdown with embedded Latex blocks that can be parsed by MathJax. You can use a web app to select your equations from pdf files, or run it on a folder of images.

Community

Discord is where we discuss future development.

Limitations

OCR is complicated, and texify is not perfect. Here are some known limitations:

• It will OCR equations and surrounding text, but is not good for general purpose OCR. Think sections of a page instead of a whole page.
• It is English-only for now.
• The output format will be markdown with embedded mathjax for equations. It will not be pure latex.

Installation

This has been tested on Mac and Linux (Ubuntu and Debian). You'll need python 3.10+ and poetry.

• git clone https://github.com/VikParuchuri/texify.git
• cd texify
• poetry install

The first time you run it, model weights will be automatically downloaded.

Usage

First, some configuration:

• Set your torch device in the local.env file. For example, TORCH_DEVICE=cuda or TORCH_DEVICE=mps. cpu is the default.
• Inspect the other settings in texify/settings.py. You can override any settings in the local.env file, or by setting environment variables.

Convert an image or directory of images

Run ocr_image.py, like this:

python ocr_image.py /path/to/folder_or_file --max 8 --json_path results.json

• --max is how many images in the folder to convert at most. Omit this to convert all images in the folder.
• --json_path is an optional path to a json file where the results will be saved. If you omit this, the results will be saved to data/results.json.

App for converting PDF regions

I've included a streamlit app that can be used to select equations from PDF files. To run it, do this:

streamlit run ocr_app.py

This app will allow you to select the specific equations you want to convert to Latex on each page, and copy out the results.

Commercial usage

This model is trained on top of the openly licensed Donut model, and thus can be used for commercial purposes.

Thanks

This work would not have been possible without lots of amazing open source work. I particularly want to acknowledge Nougat and Latex-OCR by Lukas Blecher, which were the inspiration for this project.