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An image compression web app that uses K-means clustering for optimized lossy compression. The program uses Streamlit to allow the user to upload their own photo and allow them to choose how lossy the compression should be.

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Kmeans Image Compression Web App

This is a web-app built with Streamlit and coded in Python that uses the machine learning algorithm, K-means clustering, in order to efficiently compress images.

The user can upload their own images and choose the colour space, and the algorithm will use machine learnining techniques in order to optimize the remaining colours, resulting in the most efficient lossy compression.

This project was done in conjunction to a Coursera Guided Project, but the implementation of a user-centered web app was of my own doing. This project is available under an MIT License.

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An image compression web app that uses K-means clustering for optimized lossy compression. The program uses Streamlit to allow the user to upload their own photo and allow them to choose how lossy the compression should be.

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