SampleApp.MainForm.runKMeans C# (CSharp) Method

        private void runKMeans()
        {
            // Retrieve the number of clusters
            int k = (int)numClusters.Value;

            // Load original image
            Bitmap image = Properties.Resources.leaf;

            // Create converters
            ImageToArray imageToArray = new ImageToArray(min: -1, max: +1);
            ArrayToImage arrayToImage = new ArrayToImage(image.Width, image.Height, min: -1, max: +1);

            // Transform the image into an array of pixel values
            double[][] pixels; imageToArray.Convert(image, out pixels);


            // Create a K-Means algorithm using given k and a
            //  square Euclidean distance as distance metric.
            KMeans kmeans = new KMeans(k, new SquareEuclidean())
            {
                Tolerance = 0.05
            };

            // Compute the K-Means algorithm until the difference in
            //  cluster centroids between two iterations is below 0.05
            int[] idx = kmeans.Learn(pixels).Decide(pixels);


            // Replace every pixel with its corresponding centroid
            pixels.Apply((x, i) => kmeans.Clusters.Centroids[idx[i]], result: pixels);

            // Show resulting image in the picture box
            Bitmap result; arrayToImage.Convert(pixels, out result);

            pictureBox.Image = result;
        }