Differentiable Computer Vision Library
Kornia — http://www.kornia.org & https://github.com/kornia/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.
Inspired by OpenCV, 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.
The project is completely developed based on the community demand by an altruist and constantly growing developers team. In case you want to become a sponsor or a collaborator of the project, please feel to contact us. For sponsors, you can donate through a charitable tax-deductible stipend via the Open Source Vision Foundation (OSVF).
For further information, please contact us at [email protected]