private static void ToHSV()
{
//int max = 0;
//int saturation = 0;
//var hsvImg = ImageBefor.Convert<Hsv, byte>();
// using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 180.0f)))
// {
// histogram.Calculate(new Image<Gray, byte>[] { hsvImg[0] }, false, null);
// List<float> hist = new List<float>(histogram.GetBinValues());
// max = hist.IndexOf((int)hist.Max());
// }
// var imgMax = ImageBefor.Convert<Hsv,byte>()[0].CopyBlank().Add(new Gray(max));
// hsvImg[0] = imgMax;
//using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 255.0f)))
//{
// histogram.Calculate(new Image<Gray, byte>[] { hsvImg[1] }, false, null);
// List<float> hist = new List<float>(histogram.GetBinValues());
// saturation = hist.IndexOf((int)hist.Max());
//}
//var satMask = ImageBefor.Convert<Hsv, byte>()[0].CopyBlank().Add(new Gray(saturation));
//hsvImg[1] = imgMax;
//using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 255.0f)))
//{
// histogram.Calculate(new Image<Gray, byte>[] { hsvImg[2] }, false, null);
// List<float> hist = new List<float>(histogram.GetBinValues());
//}
//ImageAfter = hsvImg[2].Convert<Bgr, byte>();
int max = 0;
int saturation = 0;
var hsvImg = ImageBefor.Convert <Hsv, byte>();
using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 180.0f)))
{
histogram.Calculate(new Image <Gray, byte>[] { hsvImg[0] }, false, null);
List <float> hist = new List <float>(histogram.GetBinValues());
max = hist.IndexOf((int)hist.Max());
}
var imgMax = ImageBefor.Convert <Hsv, byte>()[0].CopyBlank().Add(new Gray(max));
hsvImg[0] = imgMax;
using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 255.0f)))
{
histogram.Calculate(new Image <Gray, byte>[] { hsvImg[1] }, false, null);
List <float> hist = new List <float>(histogram.GetBinValues());
saturation = hist.IndexOf((int)hist.Max());
}
//var saturationMask =
//var satMask = ImageBefor.Convert<Hsv, byte>()[0].CopyBlank().Add(new Gray(saturation));
//hsvImg[1] = imgMax;
//using (DenseHistogram histogram = new DenseHistogram(256, new RangeF(0.0f, 255.0f)))
//{
// histogram.Calculate(new Image<Gray, byte>[] { hsvImg[2] }, false, null);
// List<float> hist = new List<float>(histogram.GetBinValues());
//}
ImageAfter = hsvImg[2].Convert <Bgr, byte>();
}
public static void Test()
{
if (ImageBefor != null)
{
//ToHSV();
Mat kernel = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Rectangle, new Size(9, 9), new Point(-1, -1));
ImageAfter = ImageBefor.MorphologyEx(Emgu.CV.CvEnum.MorphOp.Tophat, kernel, new Point(-1, -1), 1, BorderType.Default, new MCvScalar(1.0));
//Image<Hsv, byte> bgraImage = ImageBefor.Convert<Hsv, byte>();
////for (int i = 0; i < 2; i++)
////{
// ImageAfter = bgraImage[2].Convert<Bgr, byte>(); //Thread.Sleep(3000);
////}
//ImageAfter = ImageBefor.Convert<Gray, float>().Laplace(13).Convert<Bgr,byte>();
//Image<Hsv, byte> hsvImage = ImageBefor.Convert<Hsv, byte>();
//hsvImage[1] = hsvImage[1].Add(new Gray(255));
//hsvImage[2] = hsvImage[2].Add(new Gray(255));
//List<double> hue = new List<double>();
//for (int x = 0; x < hsvImage.Height; x++)
//{
// for (int y = 0; y < hsvImage.Width; y++)
// {
// hue.Add(hsvImage[x, y].Hue);
// }
//}
//var max = hue.GroupBy(x => x).OrderByDescending(x => x.Count()).First().Key;
//hue = hue.GroupBy(x => x).Select(x => x.Key).ToList();
//var median = hue[hue.Count / 2];
//for (int x = 0; x < hsvImage.Height; x++)
//{
// for (int y = 0; y < hsvImage.Width; y++)
// {
// var pix = hsvImage[x, y].Hue;
// if (pix > max + 10 || pix < max - 10)
// {
// hsvImage.Data[x, y, 0] = 90;
// }
// else
// {
// hsvImage.Data[x, y, 0] = 180;
// }
// }
//}
//ImageAfter = hsvImage.Convert<Bgr, byte>();
//Image<Bgra, byte> bgraImage = ImageBefor.Convert<Bgra, byte>();
//for (int i = 0; i < 4; i++)
//{
// ImageAfter = bgraImage[i].Convert<Bgr, byte>(); Thread.Sleep(3000);
//}
//Image<Hls, byte> hsvImage = ImageBefor.Convert<Hls, byte>();
//for (int i = 0; i < 3; i++)
//{
// ImageAfter = hsvImage[i].Convert<Bgr, byte>();Thread.Sleep(3000);
//}
//Image<Lab, byte> LabImage = ImageBefor.Convert<Lab, byte>();
//for (int i = 0; i < 3; i++)
//{
// ImageAfter = LabImage[i].Convert<Bgr, byte>(); Thread.Sleep(3000);
//}
//Image<Luv, byte> LuvImage = ImageBefor.Convert<Luv, byte>();
//for (int i = 0; i < 3; i++)
//{
// ImageAfter = LuvImage[i].Convert<Bgr, byte>(); Thread.Sleep(3000);
//}
//Image<Ycc, byte> YccImage = ImageBefor.Convert<Ycc, byte>();
//for (int i = 0; i < 3; i++)
//{
// ImageAfter = YccImage[i].Convert<Bgr, byte>(); Thread.Sleep(3000);
//}
//using (DefectsFinder df = new DefectsFinder(ImageBefor))
//{
// df.SearchDefects();
// //CvInvoke.FillPoly(ImageAfter, new VectorOfVectorOfPoint( df.LargeDefectsContoursMatrix[2]), new MCvScalar(255, 0, 255), LineType.FourConnected);
// using (ImageCleaner ci = new ImageCleaner(ImageBefor))
// {
// //ImageAfter = ci.ClearImageByDefects();
// ImageAfter = ci.SpiralCleanLargeDefects(df.LargeDefectsContoursMatrix);
// using (Dust dust = new Dust(ImageAfter, df.SmallDefectsContoursMatrix))
// {
// //CvInvoke.FillPoly(ImageAfter, defectsFinder.SmallDefectsContoursMatrix, new MCvScalar(255,0,255), LineType.FourConnected);
// ImageAfter = dust.RemoveDustDefects();
// }
// }
//}
//using (DefectsFinder df = new DefectsFinder(ImageBefor))
//{
// df.SearchDefects();
// //CvInvoke.FillPoly(ImageAfter, new VectorOfVectorOfPoint( df.LargeDefectsContoursMatrix[2]), new MCvScalar(255, 0, 255), LineType.FourConnected);
// using (ImageCleaner ci = new ImageCleaner(ImageBefor))
// {
// ImageAfter = ci.InPaintMethod(df.LargeDefectsContoursMatrix, InpaintType.NS);
// }
//}
}
else
{
throw new ArgumentNullException(nameof(ImageBefor));
}
}
