private void Test_Accuracy_Click(object sender, RoutedEventArgs e)
{
var Scanned_files = Directory.GetFiles("C:/Users/CPT Danko/Desktop/ObjectDScan");
foreach (var file in Scanned_files)
{
var image = new Image <Gray, byte>(file);
var name = Path.GetFileName(file);
int label = int.Parse(name.Substring(name.IndexOf("_") - 1, 1));
var index = TestD.FindIndex(x => x.Class == label);
System.Drawing.PointF[] centers;
byte[] NoZeroPxls;
List <Image <Gray, byte> > NewImage = new List <Image <Gray, byte> >();
System.Drawing.Point[] contour;
(NoZeroPxls, centers, contour) = ProceessImage(image);
var LabeledArray = FrameObj.Calculate_Kmeans(centers, NoZeroPxls, image.Size);
var Regions = FrameObj.CalculateRegions(LabeledArray);
Image <Bgr, byte> colored = new Image <Bgr, byte>(512, 424);
if (index > -1)
{
TestD[index].Images.Add(image);
TestD[index].RegionsValues.Add(Regions.ToArray());
TestD[index].ImageContours.Add(contour);
TestD[index].NonZeroPixels.Add(NoZeroPxls.Length);
}
else
{
ImageDataset img = new ImageDataset();
img.Images = new List <Image <Gray, byte> >();
img.RegionsValues = new List <float[]>();
img.ImageContours = new List <System.Drawing.Point[]>();
img.NonZeroPixels = new List <int>();
img.Images.Add(image);
img.Class = label;
img.RegionsValues.Add(Regions.ToArray());
img.ImageContours.Add(contour);
img.NonZeroPixels.Add(NoZeroPxls.Length);
TestD.Add(img);
}
}
;
Train_KNN_Full();
Test_KNN();
if (confMat.IsActive == false)
{
confMat.Show();
}
counter++;
DetectedClass.Content = counter;
}
private void Load_Data()
{
var images = Directory.GetFiles("C:/Users/CPT Danko/Desktop/images_1");
if (File.Exists("C:/Users/CPT Danko/Pictures/ObjectValues.txt"))
{
File.Delete("C:/Users/CPT Danko/Pictures/ObjectValues.txt");
}
for (var image = 0; image < images.Length; image++)
{
var SelectImg = new Image <Gray, byte>(images[image]);
var ImgName = Path.GetFileName(images[image]);
var label = int.Parse(ImgName.Substring(ImgName.IndexOf("_") - 2, 2));
var index = Datasets.FindIndex(x => x.Class == label);
System.Drawing.PointF[] centers;
byte[] NoZeroPxls;
List <Image <Gray, byte> > NewImage = new List <Image <Gray, byte> >();
System.Drawing.Point[] contour;
(NoZeroPxls, centers, contour) = ProceessImage(SelectImg);
var LabeledArray = FrameObj.Calculate_Kmeans(centers, NoZeroPxls, SelectImg.Size);
var Regions = FrameObj.CalculateRegions(LabeledArray);
Image <Bgr, byte> colored = new Image <Bgr, byte>(512, 424);
if (label == 6)
{
foreach (var pixel in LabeledArray)
{
switch (pixel.Z)
{
case 0:
colored[(int)(pixel.Y), (int)(pixel.X)] = new Bgr(0, 255, 0);
break;
case 1:
colored[(int)(pixel.Y), (int)(pixel.X)] = new Bgr(0, 0, 255);
break;
case 2:
colored[(int)(pixel.Y), (int)(pixel.X)] = new Bgr(255, 0, 0);
break;
case 3:
colored[(int)(pixel.Y), (int)(pixel.X)] = new Bgr(0, 247, 255);
break;
}
}
CvInvoke.Polylines(colored, Array.ConvertAll(centers, System.Drawing.Point.Round), true, new MCvScalar(255, 255, 255), 1);
//BitmapSource FrameBitmap = BitmapSourceConvert.ToBitmapSource(colored);
//LoadCapture.Source = FrameBitmap;
//colored.Save("C:/Users/CPT Danko/Desktop/Fotky_bakalárka/06.png");
}
if (index > -1)
{
Datasets[index].Images.Add(SelectImg);
Datasets[index].RegionsValues.Add(Regions.ToArray());
Datasets[index].ImageContours.Add(contour);
Datasets[index].NonZeroPixels.Add(NoZeroPxls.Length);
}
else
{
ImageDataset img = new ImageDataset();
img.Images = new List <Image <Gray, byte> >();
img.RegionsValues = new List <float[]>();
img.ImageContours = new List <System.Drawing.Point[]>();
img.NonZeroPixels = new List <int>();
img.Images.Add(SelectImg);
img.Class = label;
img.RegionsValues.Add(Regions.ToArray());
img.ImageContours.Add(contour);
img.NonZeroPixels.Add(NoZeroPxls.Length);
Datasets.Add(img);
}
string ImageTrainData = label + "*" + "*" + ImgName;
foreach (var region in Regions)
{
ImageTrainData += region.ToString() + "*";
}
File.AppendAllText("C:/Users/CPT Danko/Pictures/ObjectValues.txt", ImageTrainData + Environment.NewLine);
}
IsDataLoaded = true;
frameCount = 0;
}
private void DoWork(object sender, DoWorkEventArgs e)
{
for (var image = 0; image < images.Length; image++)
{
var SelectImg = new Image <Gray, byte>(images[image]);
var ImgName = Path.GetFileName(images[image]);
var label = int.Parse(ImgName.Substring(ImgName.IndexOf("_") - 2, 2));
var index = Datasets.FindIndex(x => x.Class == label);
System.Drawing.PointF[] centers;
byte[] NoZeroPxls;
List <Image <Gray, byte> > NewImage = new List <Image <Gray, byte> >();
System.Drawing.Point[] contour;
(NoZeroPxls, centers, contour) = ProceessImage(SelectImg);
var LabeledArray = FrameObj.Calculate_Kmeans(centers, NoZeroPxls, SelectImg.Size);
var Regions = FrameObj.CalculateRegions(LabeledArray);
Image <Bgr, byte> colored = new Image <Bgr, byte>(512, 424);
if (index > -1)
{
Datasets[index].Images.Add(SelectImg);
Datasets[index].RegionsValues.Add(Regions.ToArray());
Datasets[index].ImageContours.Add(contour);
Datasets[index].NonZeroPixels.Add(NoZeroPxls.Length);
}
else
{
ImageDataset img = new ImageDataset();
img.Images = new List <Image <Gray, byte> >();
img.RegionsValues = new List <float[]>();
img.ImageContours = new List <System.Drawing.Point[]>();
img.NonZeroPixels = new List <int>();
img.Images.Add(SelectImg);
img.Class = label;
img.RegionsValues.Add(Regions.ToArray());
img.ImageContours.Add(contour);
img.NonZeroPixels.Add(NoZeroPxls.Length);
Datasets.Add(img);
Class_Select.Dispatcher.Invoke(() =>
{
Class_Select.Items.Add(label);
}
);
IndexList.Dispatcher.Invoke(() =>
{
IndexList.Items.Add(label);
});
}
bckgroundworker1.ReportProgress(image);
}
IsDataLoaded = true;
frameCount = 0;
}
