Metadata-Version: 2.1
Name: caer
Version: 1.9.4
Summary: A lightweight Computer Vision library for high-performance AI research - Modern Computer Vision on the Fly.
Home-page: https://github.com/jasmcaus/caer
Author: Jason Dsouza
Author-email: jasmcaus@gmail.com
Maintainer: Jason Dsouza
License: MIT License
Download-URL: https://pypi.org/project/caer
Project-URL: Bug Tracker, https://github.com/jasmcaus/caer/issues
Project-URL: Documentation, https://caer.readthedocs.io/
Project-URL: Funding, https://www.paypal.me/jasmcaus
Project-URL: Source Code, https://github.com/jasmcaus/caer
Keywords: caer,computer vision,toolkit,deep learning,image processing,video processing,video stablization,video streaming,machine learning,gpu,artificial intelligence,data science,machine vision,opencv,multithreading,FFMpeg
Platform: Any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: opencv-contrib-python

<div align="center">
<!-- ![Caer Logo](https://github.com/jasmcaus/caer/blob/dev/docs/sphinx-theme/_static/thumbs/caer-logo-flat.png) -->
<img src="https://github.com/jasmcaus/caer/blob/dev/docs/sphinx-theme/_static/thumbs/caer-logo-flat.png" alt="Caer Logo" / >

---

[![Python](https://img.shields.io/pypi/pyversions/caer.svg)][py-versions]
[![PyPI](https://badge.fury.io/py/caer.svg)][pypi-latest-version]
[![Downloads](https://pepy.tech/badge/caer)][downloads]
[![Documentation Status](https://readthedocs.org/projects/caer/badge/?version=latest)](https://caer.readthedocs.io/en/latest/?badge=latest)
[![license](https://img.shields.io/github/license/jasmcaus/caer?label=license)][license]

</div>

# Caer - Modern Computer Vision on the Fly

Caer is a lightweight Computer Vision library for high-performance AI research. It simplifies your approach towards Computer Vision by abstracting away unnecessary boilerplate code enabling maximum flexibility. By offering powerful image and video processing algorithms, Caer provides both casual and advanced users with an elegant interface for Machine vision operations.

It leverages the power of libraries like OpenCV and Pillow to speed up your Computer Vision workflow — making it ideal if you want to quickly test out something.

This design philosophy makes Caer ideal for students, researchers, hobbyists and even experts in the fields of Deep Learning and Computer Vision to quickly prototype deep learning models or research ideas.


## 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.augment**](https://github.com/jasmcaus/caer/tree/master/caer/augment) | Powerful augmentation functions |
| [**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) | Image transformations |
| [**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

## Examples
```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), keep_aspect_ratio=True)
```

For more examples, see the [Caer demos](https://github.com/jasmcaus/caer/blob/master/examples/).

## 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. If you plan to contribute new features, utility functions, or extensions to the core, please go through our [Contribution Guidelines][contributing]. By participating, you are expected to uphold the [Code of Conduct][coc].

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.


# License

Caer is released under the [MIT License](https://github.com/jasmcaus/caer/blob/master/LICENSE).

[contributing]: https://github.com/jasmcaus/caer/blob/master/.github/CONTRIBUTING.md
[docs]: https://github.com/jasmcaus/caer/blob/master/docs/
[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/

[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

