Metadata-Version: 2.1
Name: liver-ct-segmentation-package
Version: 1.6.0
Summary: Prediction package for U-Net models trained on the LiTS dataset.
Home-page: https://github.com/luiskuhn/liver-ct-segmentation-package
Author: Luis Kuhn Cuellar
Author-email: luis.kuhn@gmail.com
License: MIT
Keywords: liver-ct-segmentation-package
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Requires-Dist: rich (==9.10.0)
Requires-Dist: torch (==1.7.1)
Requires-Dist: pytorch-lightning (==1.1.8)
Requires-Dist: mlflow (==1.13.1)
Requires-Dist: mrcfile (==1.3.0)
Requires-Dist: captum (==0.4.0)

=============================
liver-ct-segmentation-package
=============================

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        :alt: Documentation Status

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Prediction package for reproducible U-Net models trained on the LiTS dataset. These models are trained using the mlf-core framework (https://github.com/mlf-core/liver-ct-segmentation/).

* Free software: MIT
* Documentation: https://liverctsegmentationpackage.readthedocs.io.


Features
--------

* Model download CLI: liver-ct-seg-model-dl
* Prediction CLI: liver-ct-seg-pred
* Uncertainty of prediction CLI: liver-ct-seg-uncert
* Input feature importance (Guided Grad-CAM) CLI: liver-ct-seg-feat-ggcam

Credits
-------

This package was created with mlf-core_ using cookiecutter_.

.. _mlf-core: https://mlf-core.com
.. _cookiecutter: https://github.com/audreyr/cookiecutter


==========
Changelog
==========

This project adheres to `Semantic Versioning <https://semver.org/>`_.

1.6.0 (2021-11-01)
---------------------------------------------

**Added**

* Introduced command to compute uncertainty of prediction, via the monte-carlo dropout procedure.

* Introduced command to compute input feature importance via the guided grad-cam algorithm, as implemented by the captum lib.

**Fixed**

**Dependencies**

**Deprecated**


1.5.0 (2021-09-01)
---------------------------------------------

**Added**

* First working prototype

**Fixed**

**Dependencies**

**Deprecated**


0.1.0-SNAPSHOT (2021-07-28)
---------------------------------------------

**Added**

* Created the project using mlf-core

**Fixed**

**Dependencies**

**Deprecated**


