A library for deriving color data from image files

Detect a set of colors that capture the mood of the image in order to reduce the number of distinct colors used in the image such that the new image should be as visually similar as possible to the original image.

This repository implements K-Means clustering for color quantization in images, running on CPU. The program reduces the number of colors in an image while maintaining visual quality, making it useful for compression and artistic effects.

This is a GPU-accelerated version of K-Means color quantization using CUDA and PyTorch, significantly speeding up the clustering process compared to CPU execution.