Q 1 - Clustering [ 20 points] KMeans has wide applications in different areas including image processing. In this question, you will use Kmeans to perform image segmentation which is a process of partitioning an image into multiple regions.Your KMeans implementation will take an image as input and number of clusters (K) and will segment the image into K number of clusters based on the similarity of pixels as shown below: Clustered image with K=5 The resultant image should ideally show each or similar objects in same cluster. Similarity, in the context of this assignment, is determined by RGB values. a) [14 Point] Implement K-means algorithm to cluster these points. K-means will take an image and number of clusters (K) to be formed and will partition the image into given number of clusters. The algorithm will stop if there is no significant change coming in these segments. b) [06 Points] Provide graphical visualization of the process of formation of clusters. The code will be written in the attached Q1_clustering.py file. Some sample images are attached with the assignment. In addition to submitting the code, you will also submit the result of clustering of these images in a pdf file. Q 1 - Clustering [ 20 points] KMeans has wide applications in different areas including image processing. In this question, you will use Kmeans to perform image segmentation which is a process of partitioning an image into multiple regions.Your KMeans implementation will take an image as input and number of clusters (K) and will segment the image into K number of clusters based on the similarity of pixels as shown below: Clustered image with K=5 The resultant image should ideally show each or similar objects in same cluster. Similarity, in the context of this assignment, is determined by RGB values. a) [14 Point] Implement K-means algorithm to cluster these points. K-means will take an image and number of clusters (K) to be formed and will partition the image into given number of clusters. The algorithm will stop if there is no significant change coming in these segments. b) [06 Points] Provide graphical visualization of the process of formation of clusters. The code will be written in the attached Q1_clustering.py file. Some sample images are attached with the assignment. In addition to submitting the code, you will also submit the result of clustering of these images in a pdf file