OpenCV-Inspired Kornia Is a Differentiable Computer Vision Library for PyTorch

OpenCV is today's most popular image processing library, covering everything from classic image processing algorithms to cutting-edge deep learning pretrained models. However because OpenCV is not differentiable it mainly focuses on pre-processing tasks and cannot be embedded in an entire training process. Inspired by OpenCV, Kornia is based on PyTorch and designed to solve generic computer vision problems. It contains a set of routines for performing color space conversions, and differentiable modules for performing tasks such as image filtering and edge detection. Kornia's core code can efficiently define and compute the gradient of complex functions with reverse-mode auto-differentiation. Kornia consists of subset packages containing operators which can be inserted into neural networks to enable models to perform tasks such as image transformations, epipolar geometry, and depth estimation.