Metadata-Version: 2.1
Name: evalutils
Version: 0.5.0
Summary: evalutils helps users create extensions for grand-challenge.org
Home-page: https://github.com/comic/evalutils
License: MIT
Author: James Meakin
Author-email: evalutils@jmsmkn.com
Requires-Python: >=3.9,<4.0
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Project-URL: Repository, https://github.com/comic/evalutils
Description-Content-Type: text/markdown

# evalutils

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[![PyPI version](https://badge.fury.io/py/evalutils.svg)](https://badge.fury.io/py/evalutils)
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evalutils contains useful functions for evaluating machine learning models in the context of medical imaging.

  - Free software: MIT license
  - Documentation: <https://comic.github.io/evalutils/>.

## Features

  - Bounding box annotations with Jaccard Index calculations
  - Calculations of bootstrapped ROC curves
  - Scoring for detection tasks
  - Efficient calculation of confusion matrices, jaccard scores, dice scores, hausdorff distances,
    absolute volume differences, and relative volume differences

## Getting Started

[evalutils](https://github.com/comic/evalutils) requires Python 3.9 or above, and can be installed from `pip`.
Please see the [Getting Started](https://comic.github.io/evalutils/usage.html) documentation for more details.

