Contributing to the Roboflow Inference Server 🛠️¶
Thank you for your interest in contributing to Inference.
We welcome any contributions to help us improve the quality of Inference.
Interested in seeing a new model in Inference? File a Feature Request on GitHub.
We welcome contributions to:
- Add support for running inference on a new model.
- Report bugs and issues in the project.
- Submit a request for a new task or feature.
- Improve our test coverage.
The Inference Server provides a standard interface through which you can work with computer vision models. With Inference Server, you can use state-of-the-art models with your own weights without having to spend time installing dependencies, configuring environments, and writing inference code.
We welcome contributions that add support for new models to the project. Before you begin, please make sure that another contributor has not already begun work on the model you want to add. You can check the project README for our roadmap on adding more models.
You will need to add documentation for your model and link to it from the
inference-server README. You can add a new page to the
docs/models directory that describes your model and how to use it. You can use the existing model documentation as a guide for how to structure your documentation.
How to Contribute Changes¶
First, fork this repository to your own GitHub account. Create a new branch that describes your changes (i.e.
line-counter-docs). Push your changes to the branch on your fork and then submit a pull request to this repository.
When creating new functions, please ensure you have the following:
- Docstrings for the function and all parameters.
- Examples in the documentation for the function.
- Created an entry in our docs to autogenerate the documentation for the function.
All pull requests will be reviewed by the maintainers of the project. We will provide feedback and ask for changes if necessary.
PRs must pass all tests and linting requirements before they can be merged.
🧹 Code quality¶
We provide two handy commands inside the
make styleto format the code
make check_code_qualityto check code quality (PEP8 basically)
pytests is used to run our tests.