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Contributing to Anno-Mage

How to contribute

The preferred workflow for contributing to Anno-Mage is to fork the main repository on GitHub, clone, and develop on a branch. Steps:

  1. Fork the project repository by clicking on the 'Fork' button near the top right of the page. This creates a copy of the code under your GitHub user account. For more details on how to fork a repository see this guide.

  2. Clone your fork of the Anno-Mage repo from your GitHub account to your local disk:

    $ git clone git@github.com:YourLogin/semi-auto-image-annotation-tool.git
$ cd semi-auto-image-annotation-tool

  3. Create a feature branch to hold your development changes:

    $ git checkout -b my-feature

    Always use a feature branch. It's good practice to never work on the master branch!

  4. Develop the feature on your feature branch. Add changed files using git add and then git commit files:

    $ git add modified_files
$ git commit

    to record your changes in Git, then push the changes to your GitHub account with:

    $ git push -u origin my-feature

  5. Follow these instructions to create a pull request from your fork. This will send an email to the committers.

(If any of the above seems like magic to you, please look up the Git documentation on the web, or ask a friend or another contributor for help.)

Pull Request Checklist

We recommended that your contribution complies with the following rules before you submit a pull request:

  • Follow the PEP8 coding convention.

  • Give your pull request a helpful title that summarises what your contribution does. In some cases Fix <ISSUE TITLE> is enough. Fix #<ISSUE NUMBER> is not enough.

  • Often pull requests resolve one or more other issues (or pull requests). If merging your pull request means that some other issues/PRs should be closed, you should use keywords to create link to them (e.g., Fixes #1234; multiple issues/PRs are allowed as long as each one is preceded by a keyword). Upon merging, those issues/PRs will automatically be closed by GitHub. If your pull request is simply related to some other issues/PRs, create a link to them without using the keywords (e.g., See also #1234).

  • All public methods should have informative docstrings with sample usage presented as doctests when appropriate.

  • Please prefix the title of your pull request with [MRG] (Ready for Merge), if the contribution is complete and ready for a detailed review. Two core developers will review your code and change the prefix of the pull request to [MRG + 1] and [MRG + 2] on approval, making it eligible for merging. An incomplete contribution -- where you expect to do more work before receiving a full review -- should be prefixed [WIP] (to indicate a work in progress) and changed to [MRG] when it matures. WIPs may be useful to: indicate you are working on something to avoid duplicated work, request broad review of functionality or API, or seek collaborators. WIPs often benefit from the inclusion of a task list in the PR description.

  • At least one paragraph of narrative documentation with links to references in the literature (with PDF links when possible) and the example.

You can also check for common programming errors with the following tools:

  • No flake8 warnings, check with:
$ pip install flake8
$ flake8 path/to/repo

Documentation

We are glad to accept any sort of documentation: function docstrings, reStructuredText documents (like this one), tutorials, etc. reStructuredText documents live in the source code repository under the doc/ directory.

You can edit the documentation using any text editor and then generate the HTML output by typing make html from the doc/ directory. Alternatively, make can be used to quickly generate the documentation without the example gallery. The resulting HTML files will be placed in _build/html/stable and are viewable in a web browser. See the README file in the doc/ directory for more information.

For building the documentation, you will need sphinx, matplotlib, and pillow.

When you are writing documentation, it is important to keep a good compromise between mathematical and algorithmic details, and give intuition to the reader on what the algorithm does. It is best to always start with a small paragraph with a hand-waving explanation of what the method does to the data and a figure (coming from an example) illustrating it.

Further Information

Join the Anno-Mage Keras channel on Keras.io Slack.