private void btn_Start_Click(object sender, EventArgs e)
{
Color[] cluster = new Color[Colors.Count];
for (int i = 0; i < cluster.Length; i++)
{
cluster[i] = Colors[i].ToColor();
}
Algorithm.ML.KMeans.BitmapClustering means = new Algorithm.ML.KMeans.BitmapClustering(cluster);
Algorithm.ML.KMeans.ProgressState pr = new Algorithm.ML.KMeans.ProgressState();
Task t = Task.Run(() =>
{
means.Teach((Bitmap)pb_Source.Image, ref pr);
Bitmap image = means.Compute((Bitmap)pb_Source.Image);
this.Invoke((Action)(() =>
{
pb_Cluster.Image = image;
}));
}
);
while (t.IsCompleted == false)
{
if (ob_Progress.Value < ob_Progress.Maximum)
{
ob_Progress.Value++;
}
else
{
ob_Progress.Value = 0;
}
Application.DoEvents();
}
for (int i = 0; i < means.Clusters.Length; i++)
{
ColorBuffer buffer = new ColorBuffer();
buffer.FromColor(means.Clusters[i]);
Colors[i] = buffer;
lb_Color.Items[i] = buffer;
}
ob_Progress.Value = 0;
}
private void btn_FromImageColor_Click(object sender, EventArgs e)
{
Random rnd = new Random();
Bitmap source = (Bitmap)pb_Source.Image;
int x = rnd.Next(0, source.Width);
int y = rnd.Next(0, source.Height);
Color color = source.GetPixel(x, y);
ColorBuffer buffer = new ColorBuffer();
buffer.FromColor(color);
Colors.Add(buffer);
lb_Color.Items.Add(buffer);
if (lb_Color.Items.Count > 0 && pb_Source.Image != null)
{
btn_Start.Enabled = true;
}
else
{
btn_Start.Enabled = false;
}
}
