Release of version 1.0.0 (#163, Closes #152)

* Update documentation
* Update packages
* Removed unused imports
* Convert `sewar` to optional dependency
* Add logo
* Add warning this software is not meant for medical use.
* Bump version -> v1.0.0

.github/workflows/pylint.yml

@@ -14,7 +14,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install pylint
+        pip install pylint sewar
         pip install -e ".[dev]"
     - name: Analysing the code with pylint
       run: |

CODE_OF_CONDUCT.md → CODE_OF_CONDUCT.rst

@@ -1,6 +1,9 @@
-# Contributor Covenant Code of Conduct
 
-## Our Pledge
+Contributor Covenant Code of Conduct
+====================================
+
+Our Pledge
+----------
 
 In the interest of fostering an open and welcoming environment, we as
 contributors and maintainers pledge to making participation in our project and
@@ -9,11 +12,13 @@ size, disability, ethnicity, sex characteristics, gender identity and expression
 level of experience, education, socio-economic status, nationality, personal
 appearance, race, religion, or sexual identity and orientation.
 
-## Our Standards
+Our Standards
+-------------
 
 Examples of behavior that contributes to creating a positive environment
 include:
 
+
 * Using welcoming and inclusive language
 * Being respectful of differing viewpoints and experiences
 * Gracefully accepting constructive criticism
@@ -22,16 +27,18 @@ include:
 
 Examples of unacceptable behavior by participants include:
 
+
 * The use of sexualized language or imagery and unwelcome sexual attention or
- advances
+  advances
 * Trolling, insulting/derogatory comments, and personal or political attacks
 * Public or private harassment
 * Publishing others' private information, such as a physical or electronic
- address, without explicit permission
+  address, without explicit permission
 * Other conduct which could reasonably be considered inappropriate in a
- professional setting
+  professional setting
 
-## Our Responsibilities
+Our Responsibilities
+--------------------
 
 Project maintainers are responsible for clarifying the standards of acceptable
 behavior and are expected to take appropriate and fair corrective action in
@@ -43,7 +50,8 @@ that are not aligned to this Code of Conduct, or to ban temporarily or
 permanently any contributor for other behaviors that they deem inappropriate,
 threatening, offensive, or harmful.
 
-## Scope
+Scope
+-----
 
 This Code of Conduct applies both within project spaces and in public spaces
 when an individual is representing the project or its community. Examples of
@@ -52,7 +60,8 @@ address, posting via an official social media account, or acting as an appointed
 representative at an online or offline event. Representation of a project may be
 further defined and clarified by project maintainers.
 
-## Enforcement
+Enforcement
+-----------
 
 Instances of abusive, harassing, or otherwise unacceptable behavior may be
 reported by contacting the project team at [email protected]. All
@@ -65,12 +74,11 @@ Project maintainers who do not follow or enforce the Code of Conduct in good
 faith may face temporary or permanent repercussions as determined by other
 members of the project's leadership.
 
-## Attribution
+Attribution
+-----------
 
-This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+This Code of Conduct is adapted from the `Contributor Covenant <https://www.contributor-covenant.org>`_\ , version 1.4,
 available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
 
-[homepage]: https://www.contributor-covenant.org
-
 For answers to common questions about this code of conduct, see
 https://www.contributor-covenant.org/faq

README.rst

@@ -0,0 +1,63 @@
+.. image:: https://github.com/NKI-AI/direct/actions/workflows/tox.yml/badge.svg
+   :target: https://github.com/NKI-AI/direct/actions/workflows/tox.yml
+   :alt: tox
+
+.. image:: https://github.com/NKI-AI/direct/actions/workflows/pylint.yml/badge.svg
+   :target: https://github.com/NKI-AI/direct/actions/workflows/pylint.yml
+   :alt: pylint
+
+.. image:: https://github.com/NKI-AI/direct/actions/workflows/black.yml/badge.svg
+   :target: https://github.com/NKI-AI/direct/actions/workflows/black.yml
+   :alt: black
+
+.. image:: https://codecov.io/gh/NKI-AI/direct/branch/main/graph/badge.svg?token=STYAUFCKJY
+   :target: https://codecov.io/gh/NKI-AI/direct
+   :alt: codecov
+
+
+DIRECT: Deep Image REConstruction Toolkit
+=========================================
+
+``DIRECT`` is a Python, end-to-end pipeline for solving Inverse Problems emerging in Imaging Processing. It is built with PyTorch and stores state-of-the-art Deep Learning imaging inverse problem solvers such as denoising, dealiasing and reconstruction. By defining a base forward linear or non-linear operator, ``DIRECT`` can be used for training models for recovering images such as MRIs from partially observed or noisy input data.
+``DIRECT`` stores inverse problem solvers such as the Learned Primal Dual algorithm, Recurrent Inference Machine and Recurrent Variational Network, which were part of the winning solution in Facebook & NYUs FastMRI challenge in 2019 and the Calgary-Campinas MRI reconstruction challenge at MIDL 2020. For a full list of the baselines currently implemented in DIRECT see `here <#baselines-and-trained-models>`_.
+
+.. raw:: html
+
+   <div align="center">
+     <img src=".github/direct.png"/>
+   </div>
+
+
+
+Installation and Quick Start
+----------------------------
+
+Check out the `documentation <https://docs.aiforoncology.nl/direct>`_ for installation and a quick start.
+
+Projects
+--------
+In the `projects <https://github.com/NKI-AI/direct/tree/main/projects>`_ folder baseline model configurations are provided for each project.
+
+Baselines and trained models
+----------------------------
+
+We provide a set of baseline results and trained models in the `DIRECT Model Zoo <https://docs.aiforoncology.nl/direct/model_zoo.html>`_. Baselines and trained models include the `Recurrent Variational Network (RecurrentVarNet) <https://arxiv.org/abs/2111.09639>`_, the `Recurrent Inference Machine (RIM) <https://www.sciencedirect.com/science/article/abs/pii/S1361841518306078>`_, the `End-to-end Variational Network (VarNet) <https://arxiv.org/pdf/2004.06688.pdf>`_, the `Learned Primal Dual Network (LDPNet) <https://arxiv.org/abs/1707.06474>`_, the `X-Primal Dual Network (XPDNet) <https://arxiv.org/abs/2010.07290>`_, the `KIKI-Net <https://pubmed.ncbi.nlm.nih.gov/29624729/>`_, the `U-Net <https://arxiv.org/abs/1811.08839>`_, the `Joint-ICNet <https://openaccess.thecvf.com/content/CVPR2021/papers/Jun_Joint_Deep_Model-Based_MR_Image_and_Coil_Sensitivity_Reconstruction_Network_CVPR_2021_paper.pdf>`_, and the `AIRS Medical fastmri model (MultiDomainNet) <https://arxiv.org/pdf/2012.06318.pdf>`_.
+
+License and usage
+-----------------
+
+DIRECT is not intended for clinical use. DIRECT is released under the `Apache 2.0 License <LICENSE>`_.
+
+Citing DIRECT
+-------------
+
+If you use DIRECT in your own research, or want to refer to baseline results published in the `DIRECT Model Zoo <model_zoo.rst>`_\ , please use the following BiBTeX entry:
+
+.. code-block:: BibTeX
+
+   @misc{DIRECTTOOLKIT,
+     author =       {Yiasemis, George and Moriakov, Nikita and Karkalousos, Dimitrios and Caan, Matthan and Teuwen, Jonas},
+     title =        {DIRECT: Deep Image REConstruction Toolkit},
+     howpublished = {\url{https://github.com/NKI-AI/direct}},
+     year =         {2021}
+   }

authors.rst

@@ -0,0 +1,13 @@
+Credits
+=======
+
+Development Lead
+----------------
+* Jonas Teuwen [email protected]
+* George Yiasemis [email protected]
+
+Contributors
+------------
+* Nikita Moriakov [email protected]
+* Dimitrios Karkalousos [email protected]
+* Matthan W.A. Caan [email protected]

contributing.md → contributing.rst

@@ -1,106 +1,134 @@
-# Contributing
+
+Contributing
+============
+
 Contributions are welcome, and they are greatly appreciated! Every little bit
 helps, and credit will always be given.
 
 You can contribute in many ways:
 
-## Types of Contributions
-### Report Bugs
+Types of Contributions
+----------------------
+
+Report Bugs
+^^^^^^^^^^^
+
 Report bugs at https://github.com/NKI-AI/direct/issues.
 
 If you are reporting a bug, please include:
 
+
 * Your operating system name and version.
 * Any details about your local setup that might be helpful in troubleshooting.
 * Detailed steps to reproduce the bug.
 
+Fix Bugs
+^^^^^^^^
 
-### Fix Bugs
 Look through the GitHub issues for bugs. Anything tagged with "bug" and "help
 wanted" is open to whoever wants to implement it.
 
+Implement Features
+^^^^^^^^^^^^^^^^^^
 
-### Implement Features
 Look through the GitHub issues for features. Anything tagged with "enhancement"
 and "help wanted" is open to whoever wants to implement it.
 
+Write Documentation
+^^^^^^^^^^^^^^^^^^^
 
-### Write Documentation
 DIRECT could always use more documentation, whether as part of the
 official DIRECT docs, in docstrings, or even on the web in blog posts,
 articles, and such.
 
-### Submit Feedback
+Submit Feedback
+^^^^^^^^^^^^^^^
+
 The best way to send feedback is to file an issue at https://github.com/NKI-AI/direct/issues.
 
 If you are proposing a feature:
 
+
 * Explain in detail how it would work.
 * Keep the scope as narrow as possible, to make it easier to implement.
 * Remember that this is a volunteer-driven project, and that contributions
   are welcome :)
 
-### Get Started!
+Get Started!
+^^^^^^^^^^^^
+
+Ready to contribute? Here's how to set up ``direct`` for local development.
 
-Ready to contribute? Here's how to set up `direct` for local development.
 
-1. Fork the `direct` repo on GitHub.
-2. Clone your fork locally::
+#. Fork the ``direct`` repo on GitHub.
+#. 
+   Clone your fork locally:
 
     $ git clone [email protected]:your_name_here/direct.git
 
-3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development::
+#. 
+   Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
 
     $ mkvirtualenv direct
     $ cd direct/
     $ python setup.py develop
 
-4. Create a branch for local development::
+#. 
+   Create a branch for local development:
 
     $ git checkout -b name-of-your-bugfix-or-feature
 
    Now you can make your changes locally.
 
-5. When you're done making changes, check that your changes pass flake8 and the
-   tests, including testing other Python versions with tox::
+#. 
+   When you're done making changes, check that your changes pass flake8 and the
+   tests, including testing other Python versions with tox:
 
     $ flake8 direct tests
     $ python setup.py test or pytest
     $ tox
 
    To get flake8 and tox, just pip install them into your virtualenv.
 
-6. Commit your changes and push your branch to GitHub::
+#. 
+   Commit your changes and push your branch to GitHub:
 
     $ git add .
     $ git commit -m "Your detailed description of your changes."
     $ git push origin name-of-your-bugfix-or-feature
 
-7. Submit a pull request through the GitHub website.
+#. 
+   Submit a pull request through the GitHub website.
+
+Pull Request Guidelines
+^^^^^^^^^^^^^^^^^^^^^^^
 
-### Pull Request Guidelines
 Before you submit a pull request, check that it meets these guidelines:
 
-1. The pull request should include tests.
-2. If the pull request adds functionality, the docs should be updated. Put
+
+#. The pull request should include tests.
+#. If the pull request adds functionality, the docs should be updated. Put
    your new functionality into a function with a docstring, and add the
    feature to the list in README.rst.
-3. The pull request should work for Python 3.8 and 3.9 and for PyPy. Check Github actions and see that all tests pass.
+#. The pull request should work for Python 3.8 and 3.9 and for PyPy. Check Github actions and see that all tests pass.
+
+Tests
+^^^^^
 
-### Tests
 To run tests:
-`pytest`
+``pytest``
 
+Deploying
+^^^^^^^^^
 
-### Deploying
 A reminder for the maintainers on how to deploy.
 Make sure all your changes are committed (including an entry in HISTORY.md).
-Then run::
+Then run:
+
+.. code-block::
 
-```
-bump2version patch # possible: major / minor / patch
-git push
-git push --tags
-```
+   bump2version patch # possible: major / minor / patch
+   git push
+   git push --tags
 
 Travis will then deploy to PyPI if tests pass.