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Kornia is a differentiable computer vision library for PyTorch.

It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.

Overview

Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors.

At a granular level, Kornia is a library that consists of the following components:

Installation

From pip:

pip install kornia
pip install kornia[x]  # to get the training API !

python setup.py install

pip install -e .

pip install git+https://github.com/kornia/kornia

Examples

Run our Jupyter notebooks tutorials to learn to use the library.