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Action classification for TZYX/TYX shaped images, Static classification for TYX/YX shaped images

Project description

Oneat

Developed by KapoorLabs

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This product is a testament to our expertise at KapoorLabs, where we specialize in creating cutting-edge solutions. We offer bespoke pipeline development services, transforming your developmental biology questions into publishable figures with our advanced computer vision and AI tools. Leverage our expertise and resources to achieve end-to-end solutions that make your research stand out.

Note: The tools and pipelines showcased here represent only a fraction of what we can achieve. For tailored and comprehensive solutions beyond what was done in the referenced publication, engage with us directly. Our team is ready to provide the expertise and custom development you need to take your research to the next level. Visit us at KapoorLabs.

License BSD-3 PyPI Python Version codecov

Action classification for TZYX shaped images, Static classification for TYX shaped images


This caped package was generated with Cookiecutter using @caped's cookiecutter-template template.

Installation

You can install oneat via pip:

pip install oneat

To install latest development version :

pip install git+https://github.com/Kapoorlabs-CAPED/caped-ai-oneat.git

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

Computational Support

This work was granted access to the HPC resources of IDRIS under the allocation 2022 - [AD011013695], 2023 - [AD011013695R1], 2024 - [AD011013695R2] made by GENCI for training the models for action classification in 3D + time datasets.

License

Distributed under the terms of the BSD-3 license, "oneat" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.

Project details


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