//Elvégzi a karakterek keresését a bemeneti képen és a bemeneti listába visszaírja a megtalált karakterek adatait.
public Image <Bgr, Byte> ProcessImage(Image <Gray, byte> grayFrame, out List <int[]> foundXO)
{
Image <Bgr, Byte> rv = grayFrame.Copy().Convert <Bgr, Byte>();
//Kontraszt beállítás
if (equalizeHist)
{
grayFrame._EqualizeHist();
}
//Élsimítás
Image <Gray, byte> smoothedGrayFrame = grayFrame.PyrDown();
smoothedGrayFrame = smoothedGrayFrame.PyrUp();
//Éldetektálás
Image <Gray, byte> cannyFrame = null;
if (noiseFilter)
{
cannyFrame = smoothedGrayFrame.Canny(cannyThreshold, cannyThreshold);
}
//Élsimítás
if (blur)
{
grayFrame = smoothedGrayFrame;
}
//Bináris konvertálás
CvInvoke.cvAdaptiveThreshold(grayFrame, grayFrame, 255, Emgu.CV.CvEnum.ADAPTIVE_THRESHOLD_TYPE.CV_ADAPTIVE_THRESH_MEAN_C, Emgu.CV.CvEnum.THRESH.CV_THRESH_BINARY, adaptiveThresholdBlockSize + adaptiveThresholdBlockSize % 2 + 1, adaptiveThresholdParameter);
grayFrame._Not();
if (addCanny)
{
if (cannyFrame != null)
{
grayFrame._Or(cannyFrame);
}
}
this.binarizedFrame = grayFrame;
if (cannyFrame != null)
{
cannyFrame = cannyFrame.Dilate(3);
}
//Kontúrok kigyűjtése
var sourceContours = grayFrame.FindContours(Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_NONE, Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_LIST);
//Kontúrok szűrése
contours = FilterContours(sourceContours, cannyFrame, grayFrame.Width, grayFrame.Height);
//Minták rögzítése.
lock (foundTemplates)
foundTemplates.Clear();
samples.Clear();
lock (templates)
Parallel.ForEach <Contour <Point> >(contours, (contour) =>
{
var arr = contour.ToArray();
Template sample = new Template(arr, contour.Area, samples.templateSize);
lock (samples)
samples.Add(sample);
if (!onlyFindContours) //Ha a keresendő karakterek mintáit rögzítjük, akkor ne fusson le.
{
FoundTemplateDesc desc = finder.FindTemplate(templates, sample);
if (desc != null)
{
lock (foundTemplates)
foundTemplates.Add(desc);
}
}
}
);
FilterByIntersection(ref foundTemplates);
foundXO = new List <int[]>();
//A megtalált karaktereket rárajzolja a képre és összeállítja a kimeneti listát a karkaterek adatairól.
foreach (FoundTemplateDesc found in foundTemplates)
{
Rectangle foundRect = found.sample.contour.SourceBoundingRect;
Point p1 = new Point((foundRect.Left + foundRect.Right) / 2, foundRect.Top);
string text = found.template.name;
MCvFont f = new MCvFont(FONT.CV_FONT_HERSHEY_COMPLEX, 1.0, 1.0);
if (text == "X" && foundRect.Area() < 4000 && foundRect.Area() > 1000)
{
rv.Draw(foundRect, new Bgr(0, 255, 0), 4);
foundXO.Add(new int[5] {
foundRect.Center().X, foundRect.Center().Y, 1, foundRect.Width, foundRect.Height
});
}
else if (text == "O" && foundRect.Area() < 4000 && foundRect.Area() > 1000)
{
rv.Draw(foundRect, new Bgr(0, 0, 255), 4);
foundXO.Add(new int[5] {
foundRect.Center().X, foundRect.Center().Y, 0, foundRect.Width, foundRect.Height
});
}
}
return(rv);
}
public Image <Bgr, Byte> ProcessImage(Image <Gray, byte> grayFrame, out List <int[]> foundXO)
{
Image <Bgr, Byte> rv = grayFrame.Copy().Convert <Bgr, Byte>();
if (equalizeHist)
{
grayFrame._EqualizeHist();//autocontrast
}
//smoothed
Image <Gray, byte> smoothedGrayFrame = grayFrame.PyrDown();
smoothedGrayFrame = smoothedGrayFrame.PyrUp();
//canny
Image <Gray, byte> cannyFrame = null;
if (noiseFilter)
{
cannyFrame = smoothedGrayFrame.Canny(cannyThreshold, cannyThreshold);
}
//smoothing
if (blur)
{
grayFrame = smoothedGrayFrame;
}
//binarize
CvInvoke.cvAdaptiveThreshold(grayFrame, grayFrame, 255, Emgu.CV.CvEnum.ADAPTIVE_THRESHOLD_TYPE.CV_ADAPTIVE_THRESH_MEAN_C, Emgu.CV.CvEnum.THRESH.CV_THRESH_BINARY, adaptiveThresholdBlockSize + adaptiveThresholdBlockSize % 2 + 1, adaptiveThresholdParameter);
//
grayFrame._Not();
//
if (addCanny)
{
if (cannyFrame != null)
{
grayFrame._Or(cannyFrame);
}
}
//
this.binarizedFrame = grayFrame;
//dilate canny contours for filtering
if (cannyFrame != null)
{
cannyFrame = cannyFrame.Dilate(3);
}
//find contours
var sourceContours = grayFrame.FindContours(Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_NONE, Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_LIST);
//filter contours
contours = FilterContours(sourceContours, cannyFrame, grayFrame.Width, grayFrame.Height);
//find templates
lock (foundTemplates)
foundTemplates.Clear();
samples.Clear();
lock (templates)
Parallel.ForEach <Contour <Point> >(contours, (contour) =>
{
var arr = contour.ToArray();
Template sample = new Template(arr, contour.Area, samples.templateSize);
lock (samples)
samples.Add(sample);
if (!onlyFindContours)
{
FoundTemplateDesc desc = finder.FindTemplate(templates, sample);
if (desc != null)
{
lock (foundTemplates)
foundTemplates.Add(desc);
}
}
}
);
FilterByIntersection(ref foundTemplates);
foundXO = new List <int[]>();
foreach (FoundTemplateDesc found in foundTemplates)
{
if (found.template.name.EndsWith(".png") || found.template.name.EndsWith(".jpg"))
{
continue;
}
Rectangle foundRect = found.sample.contour.SourceBoundingRect;
Point p1 = new Point((foundRect.Left + foundRect.Right) / 2, foundRect.Top);
string text = found.template.name;
MCvFont f = new MCvFont(FONT.CV_FONT_HERSHEY_COMPLEX, 1.0, 1.0);
//rv.Draw((found.angle*180/Math.PI).ToString(), ref f, foundRect.Center(), new Bgr(0, 0, 0));
if (text == "X" && foundRect.Area() < 4000 && foundRect.Area() > 1000)
{
rv.Draw(foundRect, new Bgr(0, 255, 0), 4);
foundXO.Add(new int[5] {
foundRect.Center().X, foundRect.Center().Y, 1, foundRect.Width, foundRect.Height
});
}
else if (text == "O" && foundRect.Area() < 4000 && foundRect.Area() > 1000)
{
rv.Draw(foundRect, new Bgr(0, 0, 255), 4);
foundXO.Add(new int[5] {
foundRect.Center().X, foundRect.Center().Y, 0, foundRect.Width, foundRect.Height
});
}
//rv.Draw(new CircleF(new PointF(foundRect.Center().X, foundRect.Center().Y), 10), new Bgr(0, 255, 0), 3);
//e.Graphics.DrawRectangle(borderPen, foundRect);
//e.Graphics.DrawString(text, font, bgBrush, new PointF(p1.X + 1 - font.Height / 3, p1.Y + 1 - font.Height));
//e.Graphics.DrawString(text, font, foreBrush, new PointF(p1.X - font.Height / 3, p1.Y - font.Height));
}
return(rv);
}