Handwritten Text Recognition for Xournal++ Using Deep Learning

The Xournal++ HTR project aims to enhance the Xournal++ note-taking application by integrating handwritten text recognition (HTR) capabilities, allowing users to make their handwritten notes searchable. This open-source initiative emphasizes user privacy by processing data locally. The project employs a Lua plugin for Xournal++ alongside a Python backend for the recognition process.

To set up the project, users need to create a Conda environment and install necessary dependencies, following specific installation instructions. The design of the project supports both stable production features and experimentation with new algorithms, featuring a backend that can accommodate various recognition models. Future developments will focus on improving HTR performance through model retraining, data augmentation, and the incorporation of language models.

The repository encourages community contributions, utilizing a branching strategy to ensure stability in the master branch while allowing for ongoing development in feature branches. Acknowledgments are given to individuals and institutions that have contributed to the project's progress. For further information, the Xournal++ HTR GitHub repository is available for access.