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| Component | Description |
|---|---|
| kornia | a Differentiable Computer Vision library, with strong GPU support |
| kornia.augmentation | a module to perform data augmentation in the GPU |
| kornia.color | a set of routines to perform color space conversions |
| kornia.contrib | a compilation of user contrib and experimental operators |
| kornia.enhance | a module to perform normalization and intensity transformation |
| kornia.feature | a module to perform feature detection |
| kornia.filters | a module to perform image filtering and edge detection |
| kornia.geometry | a geometric computer vision library to perform image transformations, 3D linear algebra and conversions using different camera models |
| kornia.losses | a stack of loss functions to solve different vision tasks |
| kornia.morphology | a module to perform morphological operations |
| kornia.utils | image to tensor utilities and metrics for vision problems |
1pip install kornia
2pip install kornia[x] # to get the training API !python setup.py installpip install -e .pip install git+https://github.com/kornia/kornia
1@inproceedings{eriba2019kornia,
2 author = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
3 title = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
4 booktitle = {Winter Conference on Applications of Computer Vision},
5 year = {2020},
6 url = {https://arxiv.org/pdf/1910.02190.pdf}
7}