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# 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 |
<!-- | [**caer.utils**](https://github.com/jasmcaus/caer/tree/master/caer/utils) | Generic utilities | -->
<!-- | [**caer.filters**](https://github.com/jasmcaus/caer/tree/master/caer/filters) | Sharpening, edge finding, rank filters, thresholding, etc | -->
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)
```
<img src="examples/thumbs/resize-with-ratio.png" alt="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).
3. [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={Jason},
journal={GitHub. Note: https://github.com/jasmcaus/caer},
volume={2},
year={2020-2025}
}
```
[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
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The end result is a library quite different in its design, that\u2019s easy to understand, plays well with others, and is a lot of fun to use.\n\nOur 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.\n\n## Overview\n\nCaer is a Python library that consists of the following components:\n\n| Component | Description |\n| ----------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- |\n| [**caer**](https://github.com/jasmcaus/caer/) | A lightweight GPU-accelerated Computer Vision library for high-performance AI research |\n| [**caer.color**](https://github.com/jasmcaus/caer/tree/master/caer/color) | Colorspace operations |\n| [**caer.data**](https://github.com/jasmcaus/caer/tree/master/caer/data) | Standard high-quality test images and example data |\n| [**caer.path**](https://github.com/jasmcaus/caer/tree/master/caer/path) | OS-specific path manipulations |\n| [**caer.preprocessing**](https://github.com/jasmcaus/caer/tree/master/caer/preprocessing) | Image preprocessing utilities. |\n| [**caer.transforms**](https://github.com/jasmcaus/caer/tree/master/caer/transforms) | Powerful image transformations and augmentations |\n| [**caer.video**](https://github.com/jasmcaus/caer/tree/master/caer/video) | Video processing utilities |\n\n<!-- | [**caer.utils**](https://github.com/jasmcaus/caer/tree/master/caer/utils) | Generic utilities | -->\n<!-- | [**caer.filters**](https://github.com/jasmcaus/caer/tree/master/caer/filters) | Sharpening, edge finding, rank filters, thresholding, etc | -->\n\nUsually, Caer is used either as:\n\n- a replacement for OpenCV to use the power of GPUs.\n- a Computer Vision research platform that provides maximum flexibility and speed.\n\n# Installation\n\nSee the Caer **[Installation][install]** guide for detailed installation instructions (including building from source).\n\nCurrently, `caer` supports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended).\nTo install the current release:\n\n```shell\n$ pip install --upgrade caer\n```\n\n# Getting Started\n\n## Minimal Example\n\n```python\nimport caer\n\n# Load a standard 640x427 test image that ships out-of-the-box with caer\nsunrise = caer.data.sunrise(rgb=True)\n\n# Resize the image to 400x400 while MAINTAINING aspect ratio\nresized = caer.resize(sunrise, target_size=(400,400), preserve_aspect_ratio=True)\n```\n\n<img src=\"examples/thumbs/resize-with-ratio.png\" alt=\"caer.resize()\" />\n\nFor more examples, see the [Caer demos](https://github.com/jasmcaus/caer/blob/master/examples/) or [Read the documentation](http://caer.rtfd.io)\n\n# Resources\n\n- [**PyPi**](https://pypi.org/project/caer)\n- [**Documentation**](https://github.com/jasmcaus/caer/blob/master/docs/README.md)\n- [**Issue tracking**](https://github.com/jasmcaus/caer/issues)\n\n# Contributing\n\nWe appreciate all contributions, feedback and issues. 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[Search through the issues](https://github.com/jasmcaus/caer/issues).\n\n# License\n\nCaer is open-source and released under the [MIT License](LICENSE).\n\n# BibTeX\n\nIf you want to cite the framework feel free to use this (but only if you loved it \ud83d\ude0a):\n\n```bibtex\n@article{jasmcaus,\n title={Caer},\n author={Jason},\n journal={GitHub. 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