%global _empty_manifest_terminate_build 0 Name: python-caer Version: 2.0.8 Release: 1 Summary: A lightweight Computer Vision library for high-performance AI research - Modern Computer Vision on the Fly. License: MIT License URL: https://github.com/jasmcaus/caer Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d8/d2/22ebe136e0f62bb93753c9f979fd2c899de5a0d63ca8d3afd7d8fa47dce3/caer-2.0.8.tar.gz BuildArch: noarch Requires: python3-mypy Requires: python3-numpy Requires: python3-opencv-contrib-python Requires: python3-typing-extensions %description [![Python](https://img.shields.io/pypi/pyversions/caer.svg)][py-versions] [![PyPI](https://badge.fury.io/py/caer.svg)][pypi-latest-version] [![Twitter](https://img.shields.io/twitter/follow/jasmcaus.svg?style=flatl&label=Follow&logo=twitter&logoColor=white&color=1da1f2)][twitter-badge] [![Downloads](https://pepy.tech/badge/caer)][downloads] [![ReadTheDocs](https://readthedocs.org/projects/caer/badge/?version=latest)][docs] [![license](https://img.shields.io/github/license/jasmcaus/caer?label=license)][license] # Caer - Modern Computer Vision on the Fly Caer is a *lightweight, high-performance* Vision library for high-performance AI research. We wrote this framework to simplify your approach towards Computer Vision by abstracting away unnecessary boilerplate code giving you the **flexibility** to quickly prototype deep learning models and research ideas. The end result is a library quite different in its design, that’s easy to understand, plays well with others, and is a lot of fun to use. Our elegant, *type-checked* API and design philosophy makes Caer ideal for students, researchers, hobbyists and even experts in the fields of Deep Learning and Computer Vision. ## Overview Caer is a Python library that consists of the following components: | Component | Description | | ---- | --- | | [**caer**](https://github.com/jasmcaus/caer/) | A lightweight GPU-accelerated Computer Vision library for high-performance AI research | | [**caer.color**](https://github.com/jasmcaus/caer/tree/master/caer/color) | Colorspace operations | | [**caer.data**](https://github.com/jasmcaus/caer/tree/master/caer/data) | Standard high-quality test images and example data | | [**caer.path**](https://github.com/jasmcaus/caer/tree/master/caer/path) | OS-specific path manipulations | | [**caer.preprocessing**](https://github.com/jasmcaus/caer/tree/master/caer/preprocessing) | Image preprocessing utilities. | | [**caer.transforms**](https://github.com/jasmcaus/caer/tree/master/caer/transforms) | Powerful image transformations and augmentations | | [**caer.video**](https://github.com/jasmcaus/caer/tree/master/caer/video) | Video processing utilities | Usually, Caer is used either as: - a replacement for OpenCV to use the power of GPUs. - a Computer Vision research platform that provides maximum flexibility and speed. # Installation See the Caer **[Installation][install]** guide for detailed installation instructions (including building from source). Currently, `caer` supports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended). To install the current release: ```shell $ pip install --upgrade caer ``` # Getting Started ## Minimal Example ```python import caer # Load a standard 640x427 test image that ships out-of-the-box with caer sunrise = caer.data.sunrise(rgb=True) # Resize the image to 400x400 while MAINTAINING aspect ratio resized = caer.resize(sunrise, target_size=(400,400), preserve_aspect_ratio=True) ``` caer.resize() For more examples, see the [Caer demos](https://github.com/jasmcaus/caer/blob/master/examples/) or [Read the documentation](http://caer.rtfd.io) # Resources - [**PyPi**](https://pypi.org/project/caer) - [**Documentation**](https://github.com/jasmcaus/caer/blob/master/docs/README.md) - [**Issue tracking**](https://github.com/jasmcaus/caer/issues) # Contributing We appreciate all contributions, feedback and issues. If you plan to contribute new features, utility functions, or extensions to the core, please go through our [Contribution Guidelines][contributing]. To contribute, start working through the `caer` codebase, read the [Documentation][docs], navigate to the [Issues][issues] tab and start looking through interesting issues. Current contributors can be viewed either from the [Contributors][contributors] file or by using the `caer.__contributors__` command. # Asking for help If you have any questions, please: 1. [Read the docs](https://caer.rtfd.io/en/latest/). 2. [Look it up in our Github Discussions (or add a new question)](https://github.com/jasmcaus/caer/discussions). 2. [Search through the issues](https://github.com/jasmcaus/caer/issues). # License Caer is open-source and released under the [MIT License](LICENSE). # BibTeX If you want to cite the framework feel free to use this (but only if you loved it 😊): ```bibtex @article{jasmcaus, title={Caer}, author={Dsouza, Jason}, journal={GitHub. Note: https://github.com/jasmcaus/caer}, volume={2}, year={2020-2021} } ``` [contributing]: https://github.com/jasmcaus/caer/blob/master/.github/CONTRIBUTING.md [docs]: https://caer.rtfd.io [contributors]: https://github.com/jasmcaus/caer/blob/master/CONTRIBUTORS [coc]: https://github.com/jasmcaus/caer/blob/master/CODE_OF_CONDUCT.md [issues]: https://github.com/jasmcaus/caer/issues [install]: https://github.com/jasmcaus/caer/blob/master/INSTALL.md [demos]: https://github.com/jasmcaus/caer/blob/master/examples/ [twitter-badge]: https://twitter.com/jasmcaus [downloads]: https://pepy.tech/project/caer [py-versions]: https://pypi.org/project/caer/ [pypi-latest-version]: https://pypi.org/project/caer/ [license]: https://github.com/jasmcaus/caer/blob/master/LICENSE %package -n python3-caer Summary: A lightweight Computer Vision library for high-performance AI research - Modern Computer Vision on the Fly. Provides: python-caer BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-caer [![Python](https://img.shields.io/pypi/pyversions/caer.svg)][py-versions] [![PyPI](https://badge.fury.io/py/caer.svg)][pypi-latest-version] [![Twitter](https://img.shields.io/twitter/follow/jasmcaus.svg?style=flatl&label=Follow&logo=twitter&logoColor=white&color=1da1f2)][twitter-badge] [![Downloads](https://pepy.tech/badge/caer)][downloads] [![ReadTheDocs](https://readthedocs.org/projects/caer/badge/?version=latest)][docs] [![license](https://img.shields.io/github/license/jasmcaus/caer?label=license)][license] # Caer - Modern Computer Vision on the Fly Caer is a *lightweight, high-performance* Vision library for high-performance AI research. We wrote this framework to simplify your approach towards Computer Vision by abstracting away unnecessary boilerplate code giving you the **flexibility** to quickly prototype deep learning models and research ideas. The end result is a library quite different in its design, that’s easy to understand, plays well with others, and is a lot of fun to use. Our elegant, *type-checked* API and design philosophy makes Caer ideal for students, researchers, hobbyists and even experts in the fields of Deep Learning and Computer Vision. ## Overview Caer is a Python library that consists of the following components: | Component | Description | | ---- | --- | | [**caer**](https://github.com/jasmcaus/caer/) | A lightweight GPU-accelerated Computer Vision library for high-performance AI research | | [**caer.color**](https://github.com/jasmcaus/caer/tree/master/caer/color) | Colorspace operations | | [**caer.data**](https://github.com/jasmcaus/caer/tree/master/caer/data) | Standard high-quality test images and example data | | [**caer.path**](https://github.com/jasmcaus/caer/tree/master/caer/path) | OS-specific path manipulations | | [**caer.preprocessing**](https://github.com/jasmcaus/caer/tree/master/caer/preprocessing) | Image preprocessing utilities. | | [**caer.transforms**](https://github.com/jasmcaus/caer/tree/master/caer/transforms) | Powerful image transformations and augmentations | | [**caer.video**](https://github.com/jasmcaus/caer/tree/master/caer/video) | Video processing utilities | Usually, Caer is used either as: - a replacement for OpenCV to use the power of GPUs. - a Computer Vision research platform that provides maximum flexibility and speed. # Installation See the Caer **[Installation][install]** guide for detailed installation instructions (including building from source). Currently, `caer` supports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended). To install the current release: ```shell $ pip install --upgrade caer ``` # Getting Started ## Minimal Example ```python import caer # Load a standard 640x427 test image that ships out-of-the-box with caer sunrise = caer.data.sunrise(rgb=True) # Resize the image to 400x400 while MAINTAINING aspect ratio resized = caer.resize(sunrise, target_size=(400,400), preserve_aspect_ratio=True) ``` caer.resize() For more examples, see the [Caer demos](https://github.com/jasmcaus/caer/blob/master/examples/) or [Read the documentation](http://caer.rtfd.io) # Resources - [**PyPi**](https://pypi.org/project/caer) - [**Documentation**](https://github.com/jasmcaus/caer/blob/master/docs/README.md) - [**Issue tracking**](https://github.com/jasmcaus/caer/issues) # Contributing We appreciate all contributions, feedback and issues. If you plan to contribute new features, utility functions, or extensions to the core, please go through our [Contribution Guidelines][contributing]. To contribute, start working through the `caer` codebase, read the [Documentation][docs], navigate to the [Issues][issues] tab and start looking through interesting issues. Current contributors can be viewed either from the [Contributors][contributors] file or by using the `caer.__contributors__` command. # Asking for help If you have any questions, please: 1. [Read the docs](https://caer.rtfd.io/en/latest/). 2. [Look it up in our Github Discussions (or add a new question)](https://github.com/jasmcaus/caer/discussions). 2. [Search through the issues](https://github.com/jasmcaus/caer/issues). # License Caer is open-source and released under the [MIT License](LICENSE). # BibTeX If you want to cite the framework feel free to use this (but only if you loved it 😊): ```bibtex @article{jasmcaus, title={Caer}, author={Dsouza, Jason}, journal={GitHub. Note: https://github.com/jasmcaus/caer}, volume={2}, year={2020-2021} } ``` [contributing]: https://github.com/jasmcaus/caer/blob/master/.github/CONTRIBUTING.md [docs]: https://caer.rtfd.io [contributors]: https://github.com/jasmcaus/caer/blob/master/CONTRIBUTORS [coc]: https://github.com/jasmcaus/caer/blob/master/CODE_OF_CONDUCT.md [issues]: https://github.com/jasmcaus/caer/issues [install]: https://github.com/jasmcaus/caer/blob/master/INSTALL.md [demos]: https://github.com/jasmcaus/caer/blob/master/examples/ [twitter-badge]: https://twitter.com/jasmcaus [downloads]: https://pepy.tech/project/caer [py-versions]: https://pypi.org/project/caer/ [pypi-latest-version]: https://pypi.org/project/caer/ [license]: https://github.com/jasmcaus/caer/blob/master/LICENSE %package help Summary: Development documents and examples for caer Provides: python3-caer-doc %description help [![Python](https://img.shields.io/pypi/pyversions/caer.svg)][py-versions] [![PyPI](https://badge.fury.io/py/caer.svg)][pypi-latest-version] [![Twitter](https://img.shields.io/twitter/follow/jasmcaus.svg?style=flatl&label=Follow&logo=twitter&logoColor=white&color=1da1f2)][twitter-badge] [![Downloads](https://pepy.tech/badge/caer)][downloads] [![ReadTheDocs](https://readthedocs.org/projects/caer/badge/?version=latest)][docs] [![license](https://img.shields.io/github/license/jasmcaus/caer?label=license)][license] # Caer - Modern Computer Vision on the Fly Caer is a *lightweight, high-performance* Vision library for high-performance AI research. We wrote this framework to simplify your approach towards Computer Vision by abstracting away unnecessary boilerplate code giving you the **flexibility** to quickly prototype deep learning models and research ideas. The end result is a library quite different in its design, that’s easy to understand, plays well with others, and is a lot of fun to use. Our elegant, *type-checked* API and design philosophy makes Caer ideal for students, researchers, hobbyists and even experts in the fields of Deep Learning and Computer Vision. ## Overview Caer is a Python library that consists of the following components: | Component | Description | | ---- | --- | | [**caer**](https://github.com/jasmcaus/caer/) | A lightweight GPU-accelerated Computer Vision library for high-performance AI research | | [**caer.color**](https://github.com/jasmcaus/caer/tree/master/caer/color) | Colorspace operations | | [**caer.data**](https://github.com/jasmcaus/caer/tree/master/caer/data) | Standard high-quality test images and example data | | [**caer.path**](https://github.com/jasmcaus/caer/tree/master/caer/path) | OS-specific path manipulations | | [**caer.preprocessing**](https://github.com/jasmcaus/caer/tree/master/caer/preprocessing) | Image preprocessing utilities. | | [**caer.transforms**](https://github.com/jasmcaus/caer/tree/master/caer/transforms) | Powerful image transformations and augmentations | | [**caer.video**](https://github.com/jasmcaus/caer/tree/master/caer/video) | Video processing utilities | Usually, Caer is used either as: - a replacement for OpenCV to use the power of GPUs. - a Computer Vision research platform that provides maximum flexibility and speed. # Installation See the Caer **[Installation][install]** guide for detailed installation instructions (including building from source). Currently, `caer` supports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended). To install the current release: ```shell $ pip install --upgrade caer ``` # Getting Started ## Minimal Example ```python import caer # Load a standard 640x427 test image that ships out-of-the-box with caer sunrise = caer.data.sunrise(rgb=True) # Resize the image to 400x400 while MAINTAINING aspect ratio resized = caer.resize(sunrise, target_size=(400,400), preserve_aspect_ratio=True) ``` caer.resize() For more examples, see the [Caer demos](https://github.com/jasmcaus/caer/blob/master/examples/) or [Read the documentation](http://caer.rtfd.io) # Resources - [**PyPi**](https://pypi.org/project/caer) - [**Documentation**](https://github.com/jasmcaus/caer/blob/master/docs/README.md) - [**Issue tracking**](https://github.com/jasmcaus/caer/issues) # Contributing We appreciate all contributions, feedback and issues. If you plan to contribute new features, utility functions, or extensions to the core, please go through our [Contribution Guidelines][contributing]. To contribute, start working through the `caer` codebase, read the [Documentation][docs], navigate to the [Issues][issues] tab and start looking through interesting issues. Current contributors can be viewed either from the [Contributors][contributors] file or by using the `caer.__contributors__` command. # Asking for help If you have any questions, please: 1. [Read the docs](https://caer.rtfd.io/en/latest/). 2. [Look it up in our Github Discussions (or add a new question)](https://github.com/jasmcaus/caer/discussions). 2. [Search through the issues](https://github.com/jasmcaus/caer/issues). # License Caer is open-source and released under the [MIT License](LICENSE). # BibTeX If you want to cite the framework feel free to use this (but only if you loved it 😊): ```bibtex @article{jasmcaus, title={Caer}, author={Dsouza, Jason}, journal={GitHub. Note: https://github.com/jasmcaus/caer}, volume={2}, year={2020-2021} } ``` [contributing]: https://github.com/jasmcaus/caer/blob/master/.github/CONTRIBUTING.md [docs]: https://caer.rtfd.io [contributors]: https://github.com/jasmcaus/caer/blob/master/CONTRIBUTORS [coc]: https://github.com/jasmcaus/caer/blob/master/CODE_OF_CONDUCT.md [issues]: https://github.com/jasmcaus/caer/issues [install]: https://github.com/jasmcaus/caer/blob/master/INSTALL.md [demos]: https://github.com/jasmcaus/caer/blob/master/examples/ [twitter-badge]: https://twitter.com/jasmcaus [downloads]: https://pepy.tech/project/caer [py-versions]: https://pypi.org/project/caer/ [pypi-latest-version]: https://pypi.org/project/caer/ [license]: https://github.com/jasmcaus/caer/blob/master/LICENSE %prep %autosetup -n caer-2.0.8 %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-caer -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 25 2023 Python_Bot - 2.0.8-1 - Package Spec generated