PytorchImagePipeline 0.0.2

This is a repository for creating and running Pytorch Image Pipelines.

PytorchPipeline

This is a repository for creating and running Pytorch Image Pipelines.

• Github repository: https://github.com/makanu/PytorchPipeline/
• Documentation https://makanu.github.io/PytorchPipeline/

Getting started with your project

1. Create a New Repository

First, create a repository on GitHub with the same name as this project, and then run the following commands:

git init -b main
git add .
git commit -m "init commit"
git remote add origin [e-mail]:makanu/PytorchPipeline.git
git push -u origin main

2. Set Up Your Development Environment

Then, install the environment and the pre-commit hooks with

make install

This will also generate your uv.lock file

3. Run the pre-commit hooks

Initially, the CI/CD pipeline might be failing due to formatting issues. To resolve those run:

uv run pre-commit run -a

4. Commit the changes

Lastly, commit the changes made by the two steps above to your repository.

git add .
git commit -m 'Fix formatting issues'
git push origin main

You are now ready to start development on your project! The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPI, see here. For activating the automatic documentation with MkDocs, see here. To enable the code coverage reports, see here.

Releasing a new version

• Create an API Token on PyPI.
• Add the API Token to your projects secrets with the name PYPI_TOKEN by visiting this page.
• Create a new release on Github.
• Create a new tag in the form *.*.*.

For more details, see here.

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Repository initiated with fpgmaas/cookiecutter-uv.