/// <summary>
/// Does the internal processing to actually create the breaks.
/// </summary>
/// <param name="numBreaks">number of breaks</param>
/// <param name="tuples">asc ordered input of values and their occurence counts</param>
/// <returns>created breaks</returns>
private static List <double> ClassifyByJenksFisher(int numBreaks, List <ValueCountTuple> tuples)
{
var breaksArray = new List <double>(numBreaks);
if (numBreaks == 0)
{
return(breaksArray);
}
// avoid array <-> list conversations
breaksArray.AddRange(Enumerable.Repeat(0.0d, numBreaks));
var classificator = new JenksFisher(tuples, numBreaks);
if (numBreaks > 1)
{
// runs the actual calculation
classificator.CalculateAll();
int lastClassBreakIndex = classificator.FindMaxBreakIndex(classificator._bufferSize - 1, 0, classificator._bufferSize);
while (--numBreaks != 0)
{
// assign the break values to the result
breaksArray[numBreaks] = tuples[lastClassBreakIndex + numBreaks].Value;
if (numBreaks > 1)
{
classificator._classBreaksIndex -= classificator._bufferSize;
lastClassBreakIndex = classificator._classBreaks[classificator._classBreaksIndex + lastClassBreakIndex];
}
}
}
breaksArray[0] = tuples[0].Value; // break for the first class is the minimum of the dataset.
return(breaksArray);
}
public bool TestFl()
{
//get fl contours
var rootDir = @"P:\Projects\N3 Imaging\Images\09042018_jewerly\test";
var files = Directory.GetFiles(rootDir, "*.bmp", SearchOption.TopDirectoryOnly);
Mat combinedFlMask = null;
foreach (var file in files)
{
Mat fl = Cv2.ImRead(file);
Mat fl_hls = new Mat();
Cv2.CvtColor(fl, fl_hls, ColorConversionCodes.BGR2HLS);
var fl_hls_split = Cv2.Split(fl_hls);
Mat H = fl_hls_split[0].Clone(), L, S;
H.ConvertTo(H, MatType.CV_16UC1);
H = 2 * H; //opencv H is from 0 .. 180
L = (100 * fl_hls_split[1]) / 255; //L and S range is from 0..255
S = (100 * fl_hls_split[2]) / 255; //L and S range is from 0..255
var l = (uint)Cv2.Mean(L)[0];
var s = (uint)Cv2.Mean(S)[0];
var h = (uint)Cv2.Mean(H)[0];
Debug.WriteLine(H.Dump());
var L_vector_ptr = (L.Reshape(1, L.Rows * L.Cols)).Data;
var L_vector = new byte[L.Rows * L.Cols];
Marshal.Copy(L_vector_ptr, L_vector, 0, L.Rows * L.Cols);
//Debug.WriteLine(string.Join("\n", L_vector));
var jenksBreaks =
JenksFisher.CreateJenksFisherBreaksArray(L_vector.Select(p => (double)p).ToList(), 4);
var jenksBreaks1 = JenksFisher.getJenksBreaks(L_vector.Select(p => (double)p).ToList(), 4);
Mat threshold = new Mat();
Cv2.InRange(fl_hls, new Scalar(0, 0, 0), new Scalar(255, jenksBreaks[2], 255), threshold);
Cv2.ImShow("threshold", threshold);
Cv2.WaitKey();
Cv2.DestroyAllWindows();
//Debug.WriteLine(fl_hls_split[1].Dump());
}
Cv2.WaitKey();
Cv2.DestroyAllWindows();
return(true);
}