This project focuses on implementing K-means and Gaussian Mixture Models (GMM) for image segmentation with a strong emphasis on performance optimization. Leveraging specific functions like einsum and libraries like numpy and scikit learn, the approach was designed to achieve rapid and parallelized segmentation. I managed to significantly enhance processing speed with minimal compromise on accuracy.