Metadata-Version: 2.1
Name: root-tissue-seg-package
Version: 1.0.4
Summary: An mlf-core prediction package for root tissue segmentation.
Home-page: https://github.com/qbic-pipelines/rts-prediction-package/
Author: Julian Wanner
Author-email: jwgithub@mailbox.org
License: MIT
Keywords: root tissue segmentation
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 (~=10.11.0)
Requires-Dist: click (~=8.0.1)
Requires-Dist: setuptools (~=58.2.0)
Requires-Dist: numpy (~=1.21.2)
Requires-Dist: torch (~=1.9.1)
Requires-Dist: pytorch-lightning (~=1.4.9)
Requires-Dist: torch-optimizer (~=0.1.0)
Requires-Dist: tifffile (~=2021.8.30)
Requires-Dist: PyYAML (~=5.4.1)
Requires-Dist: torchvision (~=0.10.1)

================================
Root-Tissue-Segmentation Package
================================

.. image:: https://github.com/qbic-pipelines/rts-prediction-package/workflows/Build%20rts_package%20Package/badge.svg
        :target: https://github.com/qbic-pipelines/rts-prediction-package/workflows/Build%20rts_package%20Package/badge.svg
        :alt: Github Workflow Build rts_package Status

.. image:: https://github.com/qbic-pipelines/rts-prediction-package/workflows/Run%20rts_package%20Tox%20Test%20Suite/badge.svg
        :target: https://github.com/qbic-pipelines/rts-prediction-package/workflows/Run%20rts_package%20Tox%20Test%20Suite/badge.svg
        :alt: Github Workflow Tests Status

.. image:: https://img.shields.io/pypi/v/rts_package.svg
        :target: https://pypi.python.org/pypi/rts_package
        :alt: PyPI Status


.. image:: https://readthedocs.org/projects/rts_package/badge/?version=latest
        :target: https://rts_package.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status

.. image:: https://flat.badgen.net/dependabot/thepracticaldev/dev.to?icon=dependabot
        :target: https://flat.badgen.net/dependabot/thepracticaldev/dev.to?icon=dependabot
        :alt: Dependabot Enabled


Prediction package for reproducible U-Net models, trained for semantic segmentation of microscopy images of root tissue from *A. thaliana* (https://github.com/qbic-pipelines/root-tissue-segmentation-core/). These models are trained using the mlf-core framework and tested for reproducibility. This package can be deployed within an analysis pipeline as a module for root tissue segmentation (rts) of fluorescence microscopy images.

* Free software: MIT
* Documentation: https://rts-package.readthedocs.io.


Package Tools
-------------

* Prediction CLI: ``rts_package``


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/>`_.


1.0.0 (2021-08-10)
------------------

**Added**

**Fixed**

**Dependencies**

**Deprecated**


0.1.0 (2021-08-10)
------------------

**Added**

* Created the project using mlf-core

**Fixed**

**Dependencies**

**Deprecated**


