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Metrics Library to Evaluate Machine Learning Algorithms in Python

Project description

PyPI version PyPI - Downloads PyPI - License codecov tests PyPI - Python Version

onemetric

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Installation

pip install onemetric

Documentation

The official documentation is hosted on Github Pages: https://skalskip.github.io/onemetric

Contribute

Feel free to file issues or pull requests. Let us know what metrics should be part of onemetric!

Citation

Please cite onemetric in your publications if this is useful for your research. Here is an example BibTeX entry:

@MISC{onemetric,
   author = {Piotr Skalski},
   title = {{onemetric}},
   howpublished = "\url{https://github.com/SkalskiP/onemetric/}",
   year = {2021},
}

License

This project is licensed under the BSD 3 - see the LICENSE file for details.

Acknowledgements

Building onemetric would have been much more difficult if not for the efforts and persistence of many open-source developers. Their ideas were the help and inspiration in creating this library. Thank you!

  1. Confusion Matrix for Object Detection link by kaanakan.
  2. Mean Average Precision for Object Detection link by bes-dev.
  3. YOLOv3 in PyTorch link by ultralytics.

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