oic-toolkit

A consolidated Python package for image informatics and bioimage analysis workflows, maintained by the VAI Optical Imaging Core.

Getting Started

Installation

You can install the library directly either from PyPi or from this repository.

pip install oic-toolkit
pip install "oic-toolkit @ git+https://github.com/vaioic/oic-toolkit.git@main"

If you need the latest bleeding-edge version (which likely contains bugs and other incomplete code)

pip install "oic-toolkit @ git+https://github.com/vaioic/oic-toolkit.git@dev"

Issues

If you encounter any issues with running the code or have any questions, please create an Issue or send an email to opticalimaging@vai.org. If you are reporting a bug, please include any error messages to aid with troubleshooting.

License

This project is licensed under the GPLv3 license. For more details, see LICENSE.

Citing & Acknowledgements

This repository is publicly available for open-source use, but it is developed and maintained by the Optical Imaging Core at the Van Andel Institute. If code from this repository contributed to data used in a publication, abstract, or presentation, please cite and acknowledge our work based on your affiliation:

For External Users

Please cite this repository and acknowledge the author(s) in your publication's materials, methods, or acknowledgements section:

"Image analysis pipelines were adapted from open-source tools developed by the Optical Imaging Core at the Van Andel Institute (GitHub:oic-toolkit)."

If you require custom adjustments or advanced analysis support, please contact us at opticalimaging@vai.org.

For Internal Users & Close Collaborators

If you are an internal researcher or an external collaborator working directly with our staff, please include our Research Resource Identifier (RRID) in your materials and methods section:

"Image analysis and data processing were performed in collaboration with the Optical Imaging Core at the Van Andel Institute (RRID:SCR_021968)."

Please review the Acknowledgement and Authorship Guidelines on VAI's Core Technology and Services website

Contributors

Development

Setup

This project uses uv to manage the development environment.

If you are modifying the toolkit while simultaneously running analysis scripts in another project, install it in editable mode.

1. Clone the repository

   git clone https://github.com/vaioic/oic-toolkit.git
   cd oic-toolkit
   

2. Sync the environment

   uv sync
   

3. Link this toolbox in your analysis project

   uv add --editable "path/to/oic-toolkit"
   

Note: You should change this to the published version when you are done.

Code style and testing

This project also uses ruff for ultra-fast linting and code formatting, and pytest for unit tests.

# Run linting checks
uv run ruff check

# Auto-format codebase
uv run ruff format

# Run test suite
uv run pytest

Changelog

v0.1.0 (2027-07-02)

• Initial release with common segmentation and registration functions.