https://github.com/comic/evalutils
evalutils helps users create extensions for grand-challenge.org
https://github.com/comic/evalutils
docker machine-learning pandas python36 scikit-learn simpleitk
Last synced: 9 days ago
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evalutils helps users create extensions for grand-challenge.org
- Host: GitHub
- URL: https://github.com/comic/evalutils
- Owner: comic
- License: mit
- Created: 2018-03-22T14:02:29.000Z (about 7 years ago)
- Default Branch: main
- Last Pushed: 2025-04-10T15:29:30.000Z (about 1 month ago)
- Last Synced: 2025-04-13T08:19:46.840Z (about 1 month ago)
- Topics: docker, machine-learning, pandas, python36, scikit-learn, simpleitk
- Language: Python
- Homepage: https://grand-challenge.org
- Size: 1.41 MB
- Stars: 23
- Watchers: 4
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: HISTORY.md
- Contributing: docs/contributing.rst
- License: LICENSE
Awesome Lists containing this project
README
# evalutils
[](https://github.com/comic/evalutils/actions?query=workflow%3ACI+branch%3Amain)
[](https://badge.fury.io/py/evalutils)
[](https://pypi.org/project/evalutils/)
[](https://comic.github.io/evalutils/)
[](https://github.com/ambv/black)evalutils contains useful functions for evaluating machine learning models in the context of medical imaging.
- Free software: MIT license
- Documentation: .## 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.