GitHub / areeba0 / Image-Segmentation-with-Lazy-Snapping-and-K-Means-Clustering

This Jupyter notebook demonstrates image segmentation using Lazy Snapping and K-Means Clustering. It showcases how these algorithms can partition an image into segments based on pixel intensity and user-defined masks.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/areeba0%2FImage-Segmentation-with-Lazy-Snapping-and-K-Means-Clustering
PURL: pkg:github/areeba0/Image-Segmentation-with-Lazy-Snapping-and-K-Means-Clustering

Topics: background-segmentation, cluster-centroids, euclidean-distance, foreground-extraction, image-segmentation, jupyter-notebook, k-means-clustering, lazy-snapping, likelihood-computation, matplotlib, numpy, pandas, python, seed-pixels

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• Readme
• Dependencies