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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 fully compatible with other frameworks such as PyTorch and Tensorflow.

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.

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