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
Otary gets even smarter with the addition of 17 binarization methods now available!
I am thrilled to share a new update to Otary, my open-source Python library dedicated to image manipulation and 2D geometry processing.
Otary now includes 17 binarization methods, designed to make experimentation both simple for beginners and powerful for advanced users.
5 basic methods: easily accessible for quick and efficient use: simple, otsu, adaptive, bradley, and sauvola.
These methods are the most classic and effective, perfect for new users and for 90% of practical cases.
12 advanced methods: for users who want to explore, compare, and understand more sophisticated approaches.
They are intended for image processing specialists and researchers who want to experiment with new ideas.
The documentation presents a summary table of the 17 methods, classified by year of publication and accompanied by links to the original scientific articles.
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