%global _empty_manifest_terminate_build 0
Name: python-kornia
Version: 0.6.11
Release: 1
Summary: Open Source Differentiable Computer Vision Library for PyTorch
License: Apache-2.0
URL: https://www.kornia.org
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c6/3d/5316e028cccd6838419ac4fc0ecefd132e4ea551b8b0058e62510d9ba661/kornia-0.6.11.tar.gz
BuildArch: noarch
Requires: python3-packaging
Requires: python3-torch
Requires: python3-isort
Requires: python3-kornia-rs
Requires: python3-mypy[reports]
Requires: python3-numpy
Requires: python3-opencv-python
Requires: python3-pre-commit
Requires: python3-pydocstyle
Requires: python3-pytest
Requires: python3-pytest-cov
Requires: python3-scipy
Requires: python3-furo
Requires: python3-kornia-moons
Requires: python3-matplotlib
Requires: python3-opencv-python
Requires: python3-PyYAML
Requires: python3-sphinx
Requires: python3-sphinx-autodoc-defaultargs
Requires: python3-sphinx-autodoc-typehints
Requires: python3-sphinx-copybutton
Requires: python3-sphinx-design
Requires: python3-sphinxcontrib-bibtex
Requires: python3-sphinxcontrib-gtagjs
Requires: python3-sphinxcontrib-youtube
Requires: python3-torchvision
Requires: python3-accelerate
%description
English | [简体中文](README_zh-CN.md)
Website •
Docs •
Try it Now •
Tutorials •
Examples •
Blog •
Community
[](https://pypi.org/project/kornia)
[](https://pypi.org/project/kornia)
[](https://pepy.tech/project/kornia)
[](LICENCE)
[](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
[](https://twitter.com/kornia_foss)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_nightly.yml)
[](https://github.com/kornia/kornia/actions/workflows/tests_cuda.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu_half.yml)
[](https://codecov.io/gh/kornia/kornia)
[](https://kornia.readthedocs.io/en/latest/?badge=latest)
[](https://results.pre-commit.ci/latest/github/kornia/kornia/master)
*Kornia* is a differentiable computer vision library for [PyTorch](https://pytorch.org).
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:
| **Component** | **Description** |
|----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|
| [kornia](https://kornia.readthedocs.io/en/latest/index.html) | a Differentiable Computer Vision library, with strong GPU support |
| [kornia.augmentation](https://kornia.readthedocs.io/en/latest/augmentation.html) | a module to perform data augmentation in the GPU |
| [kornia.color](https://kornia.readthedocs.io/en/latest/color.html) | a set of routines to perform color space conversions |
| [kornia.contrib](https://kornia.readthedocs.io/en/latest/contrib.html) | a compilation of user contrib and experimental operators |
| [kornia.enhance](https://kornia.readthedocs.io/en/latest/enhance.html) | a module to perform normalization and intensity transformation |
| [kornia.feature](https://kornia.readthedocs.io/en/latest/feature.html) | a module to perform feature detection |
| [kornia.filters](https://kornia.readthedocs.io/en/latest/filters.html) | a module to perform image filtering and edge detection |
| [kornia.geometry](https://kornia.readthedocs.io/en/latest/geometry.html) | a geometric computer vision library to perform image transformations, 3D linear algebra and conversions using different camera models |
| [kornia.losses](https://kornia.readthedocs.io/en/latest/losses.html) | a stack of loss functions to solve different vision tasks |
| [kornia.morphology](https://kornia.readthedocs.io/en/latest/morphology.html) | a module to perform morphological operations |
| [kornia.utils](https://kornia.readthedocs.io/en/latest/utils.html) | image to tensor utilities and metrics for vision problems |
## Installation
### From pip:
```bash
pip install kornia
pip install kornia[x] # to get the training API !
```
Other installation options
#### From source:
```bash
python setup.py install
```
#### From source with symbolic links:
```bash
pip install -e .
```
#### From source using pip:
```bash
pip install git+https://github.com/kornia/kornia
```
## Examples
Run our Jupyter notebooks [tutorials](https://kornia-tutorials.readthedocs.io/en/latest/) to learn to use the library.
- :white_check_mark: [Image Matching](https://kornia.readthedocs.io/en/latest/applications/image_matching.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/akhaliq/Kornia-LoFTR).
- :white_check_mark: [Face Detection](https://kornia.readthedocs.io/en/latest/applications/face_detection.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/frapochetti/blurry-faces).
## Cite
If you are using kornia in your research-related documents, it is recommended that you cite the paper. See more in [CITATION](https://github.com/kornia/kornia/blob/master/CITATION.md).
```bibtex
@inproceedings{eriba2019kornia,
author = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
title = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
booktitle = {Winter Conference on Applications of Computer Vision},
year = {2020},
url = {https://arxiv.org/pdf/1910.02190.pdf}
}
```
## Contributing
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. Please, consider reading the [CONTRIBUTING](https://github.com/kornia/kornia/blob/master/CONTRIBUTING.rst) notes. The participation in this open source project is subject to [Code of Conduct](https://github.com/kornia/kornia/blob/master/CODE_OF_CONDUCT.md).
## Community
- **Forums:** discuss implementations, research, etc. [GitHub Forums](https://github.com/kornia/kornia/discussions)
- **GitHub Issues:** bug reports, feature requests, install issues, RFCs, thoughts, etc. [OPEN](https://github.com/kornia/kornia/issues/new/choose)
- **Slack:** Join our workspace to keep in touch with our core contributors and be part of our community. [JOIN HERE](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
- For general information, please visit our website at www.kornia.org
Made with [contrib.rocks](https://contrib.rocks).
%package -n python3-kornia
Summary: Open Source Differentiable Computer Vision Library for PyTorch
Provides: python-kornia
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-kornia
English | [简体中文](README_zh-CN.md)
Website •
Docs •
Try it Now •
Tutorials •
Examples •
Blog •
Community
[](https://pypi.org/project/kornia)
[](https://pypi.org/project/kornia)
[](https://pepy.tech/project/kornia)
[](LICENCE)
[](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
[](https://twitter.com/kornia_foss)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_nightly.yml)
[](https://github.com/kornia/kornia/actions/workflows/tests_cuda.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu_half.yml)
[](https://codecov.io/gh/kornia/kornia)
[](https://kornia.readthedocs.io/en/latest/?badge=latest)
[](https://results.pre-commit.ci/latest/github/kornia/kornia/master)
*Kornia* is a differentiable computer vision library for [PyTorch](https://pytorch.org).
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:
| **Component** | **Description** |
|----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|
| [kornia](https://kornia.readthedocs.io/en/latest/index.html) | a Differentiable Computer Vision library, with strong GPU support |
| [kornia.augmentation](https://kornia.readthedocs.io/en/latest/augmentation.html) | a module to perform data augmentation in the GPU |
| [kornia.color](https://kornia.readthedocs.io/en/latest/color.html) | a set of routines to perform color space conversions |
| [kornia.contrib](https://kornia.readthedocs.io/en/latest/contrib.html) | a compilation of user contrib and experimental operators |
| [kornia.enhance](https://kornia.readthedocs.io/en/latest/enhance.html) | a module to perform normalization and intensity transformation |
| [kornia.feature](https://kornia.readthedocs.io/en/latest/feature.html) | a module to perform feature detection |
| [kornia.filters](https://kornia.readthedocs.io/en/latest/filters.html) | a module to perform image filtering and edge detection |
| [kornia.geometry](https://kornia.readthedocs.io/en/latest/geometry.html) | a geometric computer vision library to perform image transformations, 3D linear algebra and conversions using different camera models |
| [kornia.losses](https://kornia.readthedocs.io/en/latest/losses.html) | a stack of loss functions to solve different vision tasks |
| [kornia.morphology](https://kornia.readthedocs.io/en/latest/morphology.html) | a module to perform morphological operations |
| [kornia.utils](https://kornia.readthedocs.io/en/latest/utils.html) | image to tensor utilities and metrics for vision problems |
## Installation
### From pip:
```bash
pip install kornia
pip install kornia[x] # to get the training API !
```
Other installation options
#### From source:
```bash
python setup.py install
```
#### From source with symbolic links:
```bash
pip install -e .
```
#### From source using pip:
```bash
pip install git+https://github.com/kornia/kornia
```
## Examples
Run our Jupyter notebooks [tutorials](https://kornia-tutorials.readthedocs.io/en/latest/) to learn to use the library.
- :white_check_mark: [Image Matching](https://kornia.readthedocs.io/en/latest/applications/image_matching.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/akhaliq/Kornia-LoFTR).
- :white_check_mark: [Face Detection](https://kornia.readthedocs.io/en/latest/applications/face_detection.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/frapochetti/blurry-faces).
## Cite
If you are using kornia in your research-related documents, it is recommended that you cite the paper. See more in [CITATION](https://github.com/kornia/kornia/blob/master/CITATION.md).
```bibtex
@inproceedings{eriba2019kornia,
author = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
title = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
booktitle = {Winter Conference on Applications of Computer Vision},
year = {2020},
url = {https://arxiv.org/pdf/1910.02190.pdf}
}
```
## Contributing
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. Please, consider reading the [CONTRIBUTING](https://github.com/kornia/kornia/blob/master/CONTRIBUTING.rst) notes. The participation in this open source project is subject to [Code of Conduct](https://github.com/kornia/kornia/blob/master/CODE_OF_CONDUCT.md).
## Community
- **Forums:** discuss implementations, research, etc. [GitHub Forums](https://github.com/kornia/kornia/discussions)
- **GitHub Issues:** bug reports, feature requests, install issues, RFCs, thoughts, etc. [OPEN](https://github.com/kornia/kornia/issues/new/choose)
- **Slack:** Join our workspace to keep in touch with our core contributors and be part of our community. [JOIN HERE](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
- For general information, please visit our website at www.kornia.org
Made with [contrib.rocks](https://contrib.rocks).
%package help
Summary: Development documents and examples for kornia
Provides: python3-kornia-doc
%description help
English | [简体中文](README_zh-CN.md)
Website •
Docs •
Try it Now •
Tutorials •
Examples •
Blog •
Community
[](https://pypi.org/project/kornia)
[](https://pypi.org/project/kornia)
[](https://pepy.tech/project/kornia)
[](LICENCE)
[](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
[](https://twitter.com/kornia_foss)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_nightly.yml)
[](https://github.com/kornia/kornia/actions/workflows/tests_cuda.yml)
[](https://github.com/kornia/kornia/actions/workflows/scheduled_test_cpu_half.yml)
[](https://codecov.io/gh/kornia/kornia)
[](https://kornia.readthedocs.io/en/latest/?badge=latest)
[](https://results.pre-commit.ci/latest/github/kornia/kornia/master)
*Kornia* is a differentiable computer vision library for [PyTorch](https://pytorch.org).
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:
| **Component** | **Description** |
|----------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|
| [kornia](https://kornia.readthedocs.io/en/latest/index.html) | a Differentiable Computer Vision library, with strong GPU support |
| [kornia.augmentation](https://kornia.readthedocs.io/en/latest/augmentation.html) | a module to perform data augmentation in the GPU |
| [kornia.color](https://kornia.readthedocs.io/en/latest/color.html) | a set of routines to perform color space conversions |
| [kornia.contrib](https://kornia.readthedocs.io/en/latest/contrib.html) | a compilation of user contrib and experimental operators |
| [kornia.enhance](https://kornia.readthedocs.io/en/latest/enhance.html) | a module to perform normalization and intensity transformation |
| [kornia.feature](https://kornia.readthedocs.io/en/latest/feature.html) | a module to perform feature detection |
| [kornia.filters](https://kornia.readthedocs.io/en/latest/filters.html) | a module to perform image filtering and edge detection |
| [kornia.geometry](https://kornia.readthedocs.io/en/latest/geometry.html) | a geometric computer vision library to perform image transformations, 3D linear algebra and conversions using different camera models |
| [kornia.losses](https://kornia.readthedocs.io/en/latest/losses.html) | a stack of loss functions to solve different vision tasks |
| [kornia.morphology](https://kornia.readthedocs.io/en/latest/morphology.html) | a module to perform morphological operations |
| [kornia.utils](https://kornia.readthedocs.io/en/latest/utils.html) | image to tensor utilities and metrics for vision problems |
## Installation
### From pip:
```bash
pip install kornia
pip install kornia[x] # to get the training API !
```
Other installation options
#### From source:
```bash
python setup.py install
```
#### From source with symbolic links:
```bash
pip install -e .
```
#### From source using pip:
```bash
pip install git+https://github.com/kornia/kornia
```
## Examples
Run our Jupyter notebooks [tutorials](https://kornia-tutorials.readthedocs.io/en/latest/) to learn to use the library.
- :white_check_mark: [Image Matching](https://kornia.readthedocs.io/en/latest/applications/image_matching.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/akhaliq/Kornia-LoFTR).
- :white_check_mark: [Face Detection](https://kornia.readthedocs.io/en/latest/applications/face_detection.html) Integrated to [Huggingface Spaces](https://huggingface.co/spaces). See [Gradio Web Demo](https://huggingface.co/spaces/frapochetti/blurry-faces).
## Cite
If you are using kornia in your research-related documents, it is recommended that you cite the paper. See more in [CITATION](https://github.com/kornia/kornia/blob/master/CITATION.md).
```bibtex
@inproceedings{eriba2019kornia,
author = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
title = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
booktitle = {Winter Conference on Applications of Computer Vision},
year = {2020},
url = {https://arxiv.org/pdf/1910.02190.pdf}
}
```
## Contributing
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. Please, consider reading the [CONTRIBUTING](https://github.com/kornia/kornia/blob/master/CONTRIBUTING.rst) notes. The participation in this open source project is subject to [Code of Conduct](https://github.com/kornia/kornia/blob/master/CODE_OF_CONDUCT.md).
## Community
- **Forums:** discuss implementations, research, etc. [GitHub Forums](https://github.com/kornia/kornia/discussions)
- **GitHub Issues:** bug reports, feature requests, install issues, RFCs, thoughts, etc. [OPEN](https://github.com/kornia/kornia/issues/new/choose)
- **Slack:** Join our workspace to keep in touch with our core contributors and be part of our community. [JOIN HERE](https://join.slack.com/t/kornia/shared_invite/zt-csobk21g-2AQRi~X9Uu6PLMuUZdvfjA)
- For general information, please visit our website at www.kornia.org
Made with [contrib.rocks](https://contrib.rocks).
%prep
%autosetup -n kornia-0.6.11
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-kornia -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon Apr 10 2023 Python_Bot - 0.6.11-1
- Package Spec generated
