private bool initClustering()
{
if (!loaded)
{
return(false);
}
mClusters.Clear();
HashSet <ColorPoint> mSet = new HashSet <ColorPoint>();
Random rand = new Random();
int cluserCount;
if (!int.TryParse(txtClusterCount.Text, out cluserCount))
{
MessageBox.Show("Number of Clusters should be an integer!");
return(false);
}
for (int i = 0; i < cluserCount; i++)
{
ColorPoint p = mColorPoints[rand.Next(0, mColorPoints.Count)];
while (mSet.Contains(p))
{
p = mColorPoints[rand.Next(0, mColorPoints.Count)];
}
mClusters.Add(new Cluster(p.r, p.g, p.b));
}
updateClusteringWorkload();
keepClustering = true;
return(true);
}
private void loadImage(string filename)
{
if (loaded)
{
return;
}
Bitmap bmap = new Bitmap(ofd_image.FileName);
mColorPoints = null;
mClusters.Clear();
mColorPointDict.Clear();
mHeight = bmap.Height;
mWidth = bmap.Width;
pbProgress.Maximum = mWidth * mHeight;
pbProgress.Value = 0;
for (int i = 0; i < mHeight; i++)
{
for (int j = 0; j < mWidth; j++)
{
Color pixel = bmap.GetPixel(j, i);
ColorPoint cp = new ColorPoint(pixel.R, pixel.G, pixel.B);
List <PixelPoint> lpp;
if (mColorPointDict.ContainsKey(cp))
{
lpp = mColorPointDict[cp];
}
else
{
lpp = new List <PixelPoint>();
mColorPointDict[cp] = lpp;
}
PixelPoint pp = new PixelPoint(j, i);
lpp.Add(pp);
pbProgress.Value += 1;
}
}
mColorPoints = mColorPointDict.Keys.ToList();
btnLoadImage.Enabled = false;
btnClear.Enabled = true;
btnConvert.Enabled = true;
loaded = true;
keepClustering = true;
drawBitmap();
pbProgress.Value = 0;
}
private Cluster getClosestCluster(ColorPoint p)
{
Cluster closest = mClusters[0];
double d = p.distance(closest.getMean());
double t;
Cluster tc;
for (int i = 1; i < mClusters.Count; i++)
{
tc = mClusters[i];
t = p.distance(tc.getMean());
if (t < d)
{
d = t;
closest = tc;
}
}
return(closest);
}
public void addPoint(ColorPoint p)
{
mutexPoints.WaitOne();
points.Add(p);
mutexPoints.ReleaseMutex();
}
public Cluster(int r, int g, int b)
{
mean = new ColorPoint(r, g, b);
}
