Otary library, shape your images, image your shapes.
Otary — elegant, readable, and powerful image and 2D geometry Python library.
The main features of Otary are:
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Unification: Otary offers a cohesive solution for image and geometry manipulation, letting you work seamlessly without switching tools.
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Readability: Self-explanatory by design. Otary’s clean, readable code eliminates the need for comments, making it easy for beginners to learn and for experts to build efficiently.
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Performance: optimized for speed and efficiency, making it suitable for high-performance applications. It is built on top of NumPy and OpenCV, which are known for their speed and performance.
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Interactivity: designed to be Interactive and user-friendly, ideal for Jupyter notebooks and live exploration.
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Flexibility: provides a flexible and extensible architecture, allowing developers to customize and extend its functionality as needed.
Otary is available on PyPI. You can install it with:
pip install otaryLet me illustrate the usage of Otary with a simple example. Imagine you need to:
- read an image from a pdf file
- draw an rectangle on it, shift and rotate the rectangle
- crop a part of the image
- rotate the cropped image
- apply a threshold
- show the image
In order to compare the use of Otary versus other libraries, I will use the same example but with different libraries. Try it yourself on your favorite LLM (like ChatGPT) by copying the query:
Generate a python code to read an image from a pdf, draw a rectangle on it, shift and rotate the rectangle, crop a part of the image, rotate the cropped image, apply a threshold on the image.
Using Otary you can do it with few lines of code:
import otary as ot
im = ot.Image.from_pdf("path/to/you/file.pdf", page_nb=0)
rectangle = ot.Rectangle([[1, 1], [4, 1], [4, 4], [1, 4]]) * 100
rectangle.shift([50, 50]).rotate(angle=30, is_degree=True)
im = (
im.draw_polygons([rectangle])
.crop(x0=50, y0=50, x1=450, y1=450)
.rotate(angle=90, is_degree=True)
.threshold_simple(thresh=200)
)
im.show()Using Otary makes the code:
- Much more readable and hence maintainable
- Much more interactive
- Much simpler, simplifying libraries management by only using one library and not manipulating multiple libraries like Pillow, OpenCV, Scikit-Image, PyMuPDF etc.
In a Jupyter notebook, you can easily test and iterate on transformations by simply commenting part of the code as you need it.
im = (
im.draw_polygons([rectangle])
# .crop(x0=50, y0=50, x1=450, y1=450)
# .rotate(angle=90, is_degree=True)
.threshold_simple(thresh=200)
)