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Image Compression using K-Means Clustering

Overview

This project implements image compression by reducing the number of colors in an image using K-Means clustering. The algorithm clusters similar pixel colors, replacing them with the cluster centroids to achieve compression while maintaining visual quality.

Features

  • Compresses images by reducing the number of unique colors.
  • Uses K-Means clustering to group similar colors.
  • Allows customization of the number of clusters (colors) for compression.
  • Visualizes the original and compressed images for comparison.

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