Kornia - A PyTorch Based Differentiable Computer Vision Library

 Kornia is amazing.  A computer vision and image processing library built as an extension of PyTorch. Where everything inside of it is differentiable.  So computer vision and image processing algorithms can be directly dropped in as additional layers in a deep learning neural net system (that was built based on PyTorch).  

Kornia is open source, and an official part of the pPyTorch eco-system.  It is based on OpenCV, so if you know how to work with OpenCV, it's very similarly structured.  The difference is that Kornia is implemented using PyTorch, and processes tensors rather than NumPy arrays when working with images.  And of course everything is differentiable, which is not true for OpenCV.

Here's a quick into video into on 'Kornia: Computer Vision Library for PyTorch'.

Here's a much longer deep dive video presentation into all that is the Kornia Library from 4 months ago.

Here's the Kornia main site.

Here's the Kornia documentation site.

Here's the official Kornia GitHub code site.

Here are some Kornia example Jupyter notebooks you can run on Colab.

There is a specific section in the PyTorch community forum on Kornia.

Here's the pip site for Kornia (you can use pip to install it).

Here's a blog post on Kornia on the opencv site.


Popular posts from this blog

Simulating the Universe with Machine Learning

CycleGAN: a GAN architecture for learning unpaired image to image transformations

Pix2Pix: a GAN architecture for image to image transformation