<h2>Overview</h2>
<p>Caer is a lightweight, high-performance Vision library for high-performance AI research. It aims to simplify the approach towards Computer Vision by abstracting away unnecessary boilerplate code, allowing for quick prototyping of deep learning models and research ideas. Caer is designed to be easy to understand, integrate well with other libraries, and enjoyable to use. The library is ideal for students, researchers, hobbyists, and experts in the fields of Deep Learning and Computer Vision.</p>
<h2>Features</h2>
<ul>
<li><strong>caer</strong>: A lightweight GPU-accelerated Computer Vision library for high-performance AI research.</li>
<li><strong>caer.color</strong>: Colorspace operations.</li>
<li><strong>caer.data</strong>: Standard high-quality test images and example data.</li>
<li><strong>caer.path</strong>: OS-specific path manipulations.</li>
<li><strong>caer.preprocessing</strong>: Image preprocessing utilities.</li>
<li><strong>caer.transforms</strong>: Powerful image transformations and augmentations.</li>
<li><strong>caer.video</strong>: Video processing utilities.</li>
</ul>


Jasmcaus

Caer