public KMeans(Bitmap bmp, int numCluster, Colour.Types model)
{
_image = (Bitmap)bmp.Clone();
_processedImage = (Bitmap)bmp.Clone();
_model = model;
_previousCluster = new Dictionary<string, Cluster>();
_currentCluster = new Dictionary<string, Cluster>();
FindTopXColours(numCluster); //find top X colours in the image
//create clusters for top X colours
for (int i = 0; i < _topColours.Length; i++)
{
PixelData pd = Colour.GetPixelData(_topColours[i].R, _topColours[i].G, _topColours[i].B, model);
_previousCluster.Add(_topColours[i].Name, new Cluster(pd.Ch1, pd.Ch2, pd.Ch3));
_currentCluster.Add(_topColours[i].Name, new Cluster(pd.Ch1, pd.Ch2, pd.Ch3));
}
}
public KMeans(Bitmap bmp, int numCluster, Colour.Types model)
{
_image = (Bitmap)bmp.Clone();
_processedImage = (Bitmap)bmp.Clone();
_model = model;
_previousCluster = new Dictionary <string, Cluster>();
_currentCluster = new Dictionary <string, Cluster>();
FindTopXColours(numCluster); //find top X colours in the image
//create clusters for top X colours
for (int i = 0; i < _topColours.Length; i++)
{
PixelData pd = Colour.GetPixelData(_topColours[i].R, _topColours[i].G, _topColours[i].B, model);
_previousCluster.Add(_topColours[i].Name, new Cluster(pd.Ch1, pd.Ch2, pd.Ch3));
_currentCluster.Add(_topColours[i].Name, new Cluster(pd.Ch1, pd.Ch2, pd.Ch3));
}
}