MindCV Contributing Guidelines

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

Contributor License Agreement

It's required to sign CLA before your first code submission to MindCV community.

For individual contributor, please refer to ICLA online document for the detailed information.

Types of Contributions

Report Bugs

Report bugs at https://github.com/mindspore-lab/mindcv/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

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement it.

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

MindCV could always use more documentation, whether as part of the official MindCV docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/mindspore-lab/mindcv/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 :)

Getting Started

Ready to contribute? Here's how to set up mindcv for local development.

1. Fork the mindcv repo on GitHub.
2. Clone your fork locally:

git clone git@github.com:your_name_here/mindcv.git

After that, you should add official repository as the upstream repository:

git remote add upstream git@github.com:mindspore-lab/mindcv

3. Install your local copy into a conda environment. Assuming you have conda installed, this is how you set up your fork for local development:

conda create -n mindcv python=3.8
conda activate mindcv
cd mindcv
pip install -e .

4. 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 the linters and the tests:

pre-commit run --show-diff-on-failure --color=always --all-files
pytest

If all static linting are passed, you will get output like:

otherwise, you need to fix the warnings according to the output:

To get pre-commit and pytest, just pip install them into your conda environment.

6. 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.

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 your new functionality into a function with a docstring, and add the feature to the list in README.md.
3. The pull request should work for Python 3.7, 3.8 and 3.9, and for PyPy. Check https://github.com/mindspore-lab/mindcv/actions and make sure that the tests pass for all supported Python versions.

Tips

You can install the git hook scripts instead of linting with pre-commit run -a manually.

run flowing command to set up the git hook scripts

pre-commit install

now pre-commit will run automatically on git commit!

Releasing

A reminder for the maintainers on how to deploy. Make sure all your changes are committed (including an entry in HISTORY.md). Then run:

bump2version patch # possible: major / minor / patch
git push
git push --tags

GitHub Action will then deploy to PyPI if tests pass.