public Rectangle camshift(Image <Bgr, byte> frame, Rectangle trackerbox, Mat HIST)
{
Mat HSV = new Mat();
CvInvoke.CvtColor(frame, HSV, ColorConversion.Bgr2Hsv);
float[] range = { 0, 180 };
int[] histsize = { 24 };
int[] channels = { 0, 0 };
int[] Chn = { 0 };
Mat dst = new Mat();
float[] Range = { 0, 180 };
var vhue = new VectorOfMat(HSV);
CvInvoke.CalcBackProject(vhue, Chn, HIST, dst, Range, 1);
Mat element = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(5, 5), new Point(1, 1));//
CvInvoke.Erode(dst, dst, element, new Point(1, 1), 1, BorderType.Default, new MCvScalar(0, 0, 0));
Mat DST = new Mat();
MCvTermCriteria termCrit = new MCvTermCriteria(10, 1);
try
{
RotatedRect result = CvInvoke.CamShift(dst, ref trackerbox, termCrit);
}
catch (Exception e) { MessageBox.Show(e.ToString()); }
tbox = trackerbox;
return(trackerbox);
}
protected override CamshiftOutput DoProcess(TrackingInput input)
{
var output = new CamshiftOutput();
Image <Gray, byte> grayscaleInput = input.Captured.ToImage <Gray, byte>();
if (input.Config.StartNewTrack)
{
_trackStarted = false;
_backProjection = grayscaleInput.Copy();
var trackingRegion = input.Config.ObjectOfInterest;
grayscaleInput.ROI = trackingRegion;
var inputRoiImage = grayscaleInput.Copy();
grayscaleInput.ROI = Rectangle.Empty; //clear the roi
StartNewTrack(input.Config.ObjectOfInterest, grayscaleInput, inputRoiImage, output);
}
if (_trackStarted)
{
using (VectorOfMat vectorMatGrayscaleInput = new VectorOfMat(grayscaleInput.Mat))
{
CvInvoke.CalcBackProject(vectorMatGrayscaleInput, _channels, _histogram, _backProjection, _ranges, 1);
}
output.ObjectOfInterest = CvInvoke.CamShift(_backProjection, ref _rectangleSearchWindow, TermCriteria);
}
output.BackProjection = _backProjection;
return(output);
}
private void button2_Click(object sender, EventArgs e)
{
int[] ch = { 0, 0 };
CvInvoke.MixChannels(hsvImage, hueImage, ch);
//【2】直方图计算，并归一化
float[] hue_range = new float[2] {
0.00f, 180.00f
};
Mat hist = new Mat(hueImage.Size, Emgu.CV.CvEnum.DepthType.Cv8U, 1);
int[] channels = new int[1] {
0
};
int[] histSize = new int[1] {
Math.Max(g_bins, 2)
};
float[] ranges = new float[2] {
0, 180
};
CvInvoke.CalcHist(hueImage, channels, null, hist, histSize, ranges, true);
CvInvoke.Normalize(hist, hist, 0, 255, NormType.MinMax, DepthType.Default, null);
//【3】计算反向投影
Mat backproj = new Mat();
CvInvoke.CalcBackProject(hueImage, channels, hist, backproj, ranges, 1);
//【4】显示反向投影
imageBox2.Image = backproj;
//【5】绘制直方图
Image <Gray, float> img = new Image <Gray, float>(hist.Bitmap);
float[] data = new float[img.Data.Length];
for (int i = 0; i < img.Data.Length; i++)
{
data[i] = img.Data[i, 0, 0];
}
float max = data[0];
//获取最大值
for (int i = 1; i < data.Length; i++)
{
if (data[i] > max)
{
max = data[i];
}
}
Image <Bgr, byte> image = new Image <Bgr, byte>(300, 300, new Bgr(0, 0, 0));
for (int i = 0; i < data.Length; i++)
{
data[i] = data[i] * 256 / max;
image.Draw(new LineSegment2DF(new PointF(i + 20, 255), new PointF(i + 21, 255 - data[i])), new Bgr(255, 255, 255), 2);
}
imageBox3.Image = image;
}
static void RunMeanshiftDemo()
{
VideoCapture video = new VideoCapture("mleko.mp4"); // mleko.mp4
//VideoCapture video = new VideoCapture("mouthwash.avi"); // mouthwash.avi
var firstFrame = new Mat();
video.Read(firstFrame);
int x = 290, y = 230, width = 100, height = 15; // mleko.mp4
//int x = 300, y = 305, width = 100, height = 115; // mouthwash.avi
var roi = new Mat(firstFrame, new Rectangle(x, y, width, height));
ShowHueEmphasizedImage(roi);
CvInvoke.Imshow("Roi", roi);
var roiHsv = new Mat();
CvInvoke.CvtColor(roi, roiHsv, ColorConversion.Bgr2Hsv);
var histogram = new Mat();
CvInvoke.CalcHist(new VectorOfMat(new Mat[] { roiHsv }), new int[] { 0 }, null, histogram, new int[] { 180 }, new float[] { 0, 180 }, false);
CvInvoke.Normalize(histogram, histogram, 0, 255, NormType.MinMax);
show2DHueHistogram(histogram);
var nextFrame = new Mat();
var nextFrameHsv = new Mat();
var mask = new Mat();
var trackingWindow = new Rectangle(x, y, width, height);
while (true)
{
video.Read(nextFrame);
if (nextFrame.IsEmpty)
{
break;
}
CvInvoke.CvtColor(nextFrame, nextFrameHsv, ColorConversion.Bgr2Hsv);
CvInvoke.CalcBackProject(new VectorOfMat(new Mat[] { nextFrameHsv }), new int[] { 0 }, histogram, mask, new float[] { 0, 180 }, 1);
CvInvoke.Imshow("mask", mask);
CvInvoke.MeanShift(mask, ref trackingWindow, new MCvTermCriteria(10, 1));
CvInvoke.Rectangle(nextFrame, trackingWindow, new MCvScalar(0, 255, 0), 2);
CvInvoke.Imshow("nextFrame", nextFrame);
CvInvoke.WaitKey(60);
}
Console.WriteLine("Koniec filmu.");
CvInvoke.WaitKey();
}
public void tracking(Mat hist_roi)
{
using (var nextframe = cap.QueryFrame().ToImage <Bgr, Byte>())
{
if (nextframe != null)
{
float[] range = { 0, 180 };
int[] histsize = { 180 };
int[] channels = { 0, 0 };
int[] Chn = { 0 };
//Rectangle ret = new Rectangle();
//ret = nextframe.Mat;
Rectangle trackwindow = new Rectangle(rectx, recty, rectw, recth);
Mat hsv = new Mat();
Mat hist = new DenseHistogram(16, new RangeF(0, 16));
CvInvoke.CvtColor(nextframe, hsv, ColorConversion.Bgr2Hsv);//hsv
Mat mask = new Mat();
CvInvoke.InRange(hsv, new ScalarArray(new MCvScalar(0, 60, 32)), new ScalarArray(new MCvScalar(180, 256, 255)), mask);
Mat hue = new Mat();
hue.Create(hsv.Rows, hsv.Cols, hsv.Depth, 0);
//CvInvoke.MixChannels()
int[] chn = { 0, 0 };
var vhue = new VectorOfMat(hue);
var vhsv = new VectorOfMat(hsv);
//var vhsv = new VectorOfMat(hsv);
CvInvoke.MixChannels(vhsv, vhue, chn);
Mat dst = new Mat();
float[] Range = { 0, 180, 0, 255 };
CvInvoke.CalcBackProject(vhue, Chn, hist_roi, dst, Range, 1);
Size s = new Size(5, 5);
// CvInvoke.GetStructuringElement(ElementShape.Ellipse,s);
CvInvoke.Threshold(dst, dst, 50, 255, 0);
imageBox1.Image = dst;
// MCvTermCriteria termcriteria = new MCvTermCriteria(TermCritType.Eps | TermCritType.Iter, 10, 1);
MCvTermCriteria termCrit = new MCvTermCriteria(10, 0.1);
RotatedRect result = CvInvoke.CamShift(dst, ref trackerbox, termCrit);
var grayframe = nextframe.Convert <Gray, byte>();
grayframe.ROI = trackerbox;
var grayface = grayframe.Copy().Mat;
var faces = haar.DetectMultiScale(grayface, 1.1, 10, Size.Empty);
int totalface = faces.Length;
RectangleF ret = trackerbox;
// PointF[] PTS = CvInvoke.BoxPoints(ret);
// Point[] pts = new Point[10];
//for (int x = 0; x < PTS.Length; x++)
// {
// pts[x] = Point.Round(PTS[x]);
CvInvoke.CvtColor(dst, nextframe, ColorConversion.Gray2Bgr);
//CvInvoke.Polylines(nextframe, pts, true, new MCvScalar(255, 0));
// if (totalface == 1)
// {
MCvScalar color = new MCvScalar(0, 0, 255);
CvInvoke.Ellipse(nextframe, ret, color, 3, LineType.AntiAlias);
// }
}
imageBox1.Image = nextframe;
} //while loop end*/
}
private void backProjectionToolStripMenuItem_Click(object sender, EventArgs e)
{
try
{
if (pictureBox1.Image == null)
{
return;
}
var img = new Bitmap(pictureBox1.Image)
.ToImage <Gray, byte>();
Image <Gray, byte> img1 = null;
OpenFileDialog dialog = new OpenFileDialog();
if (dialog.ShowDialog() == DialogResult.OK)
{
img1 = new Image <Gray, byte>(dialog.FileName);
}
Mat hist = new Mat();
Mat hist1 = new Mat();
float[] ranges = new float[] { 0, 256 };
int[] channel = { 0 };
int[] histSize = { 256 };
VectorOfMat ms = new VectorOfMat();
ms.Push(img);
VectorOfMat ms1 = new VectorOfMat();
ms1.Push(img1);
CvInvoke.CalcHist(ms, channel, null, hist, histSize, ranges, false);
CvInvoke.CalcHist(ms1, channel, null, hist1, histSize, ranges, false);
CvInvoke.Normalize(hist, hist);
CvInvoke.Normalize(hist1, hist1);
Mat proj = new Mat();
CvInvoke.CalcBackProject(ms, channel, hist, proj, ranges);
HistogramViewer viewer = new HistogramViewer();
viewer.Text = "Image Histogram";
viewer.ShowIcon = false;
viewer.HistogramCtrl.AddHistogram("Image1 Histogram", Color.Blue, hist, 256, ranges);
viewer.HistogramCtrl.Refresh();
viewer.Show();
HistogramViewer viewer1 = new HistogramViewer();
viewer1.Text = "Image Histogram";
viewer1.ShowIcon = false;
viewer1.HistogramCtrl.AddHistogram("Image2 Histogram", Color.Blue, hist1, 256, ranges);
viewer1.HistogramCtrl.Refresh();
viewer1.Show();
pictureBox1.Image = proj.ToBitmap();
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
