One of the biggest improvements I’ve made to Otary isn’t a new API—it’s a new way to learn it.
I’ve just released a brand-new Tutorials section for the library.
When discovering a new Python library, I rarely start with the API reference. I want practical examples that show how the library is intended to be used and how different components fit together.
That’s exactly what these tutorials aim to provide.
With step-by-step guides, you can progressively discover how to build image processing and computer vision workflows while learning the design philosophy behind Otary:
- One unified library for image processing and 2D geometry
- A clean, Pythonic API focused on readability
- Interactive workflows that are easy to explore in Jupyter notebooks
- Practical examples you can adapt to your own projects
I’ve just released a brand-new Tutorials section for the library.
When discovering a new Python library, I rarely start with the API reference. I want practical examples that show how the library is intended to be used and how different components fit together.
That’s exactly what these tutorials aim to provide.
With step-by-step guides, you can progressively discover how to build image processing and computer vision workflows while learning the design philosophy behind Otary:
- One unified library for image processing and 2D geometry - A clean, Pythonic API focused on readability - Interactive workflows that are easy to explore in Jupyter notebooks - Practical examples you can adapt to your own projects