|
public Detect ( Byte>.Image |
||
| img | Byte>.Image | The input image |
| blobs | CvBlobs | The storage for the detected blobs |
| 리턴 | uint | |
/*
public void TestCodeBookBGModel()
{
using (Capture capture = new Capture())
using (BGCodeBookModel<Bgr> model = new BGCodeBookModel<Bgr>())
{
ImageViewer viewer = new ImageViewer();
Image<Gray, byte> fgMask = capture.QueryFrame().Convert<Gray, Byte>();
Application.Idle += delegate(Object sender, EventArgs args)
{
Mat frame = capture.QueryFrame();
model.Apply(frame);
viewer.Image = model.ForegroundMask;
};
viewer.ShowDialog();
}
}
public void TestBlobTracking()
{
MCvFGDStatModelParams fgparam = new MCvFGDStatModelParams();
fgparam.alpha1 = 0.1f;
fgparam.alpha2 = 0.005f;
fgparam.alpha3 = 0.1f;
fgparam.delta = 2;
fgparam.is_obj_without_holes = 1;
fgparam.Lc = 32;
fgparam.Lcc = 16;
fgparam.minArea = 15;
fgparam.N1c = 15;
fgparam.N1cc = 25;
fgparam.N2c = 25;
fgparam.N2cc = 35;
fgparam.perform_morphing = 0;
fgparam.T = 0.9f;
BlobTrackerAutoParam<Bgr> param = new BlobTrackerAutoParam<Bgr>();
param.BlobDetector = new BlobDetector(Emgu.CV.CvEnum.BlobDetectorType.CC);
param.FGDetector = new FGDetector<Bgr>(Emgu.CV.CvEnum.ForgroundDetectorType.Fgd, fgparam);
param.BlobTracker = new BlobTracker(Emgu.CV.CvEnum.BLOBTRACKER_TYPE.MSFG);
param.FGTrainFrames = 10;
BlobTrackerAuto<Bgr> tracker = new BlobTrackerAuto<Bgr>(param);
//MCvFont font = new MCvFont(Emgu.CV.CvEnum.FontFace.HersheySimplex, 1.0, 1.0);
using(ImageViewer viewer = new ImageViewer())
using (Capture capture = new Capture())
{
capture.ImageGrabbed += delegate(object sender, EventArgs e)
{
tracker.Process(capture.RetrieveBgrFrame());
//Image<Bgr, Byte> img = capture.RetrieveBgrFrame();
Image<Bgr, Byte> img = tracker.ForegroundMask.Convert<Bgr, Byte>();
foreach (MCvBlob blob in tracker)
{
img.Draw((Rectangle)blob, new Bgr(255.0, 255.0, 255.0), 2);
img.Draw(blob.ID.ToString(), Point.Round(blob.Center), CvEnum.FontFace.HersheySimplex, 1.0, new Bgr(255.0, 255.0, 255.0));
}
viewer.Image = img;
};
capture.Start();
viewer.ShowDialog();
}
}*/
public void TestCvBlob()
{
//MCvFont font = new MCvFont(Emgu.CV.CvEnum.FontFace.HersheySimplex, 0.5, 0.5);
using (CvTracks tracks = new CvTracks())
using (ImageViewer viewer = new ImageViewer())
using (Capture capture = new Capture())
using (Mat fgMask = new Mat())
{
//BGStatModel<Bgr> bgModel = new BGStatModel<Bgr>(capture.QueryFrame(), Emgu.CV.CvEnum.BG_STAT_TYPE.GAUSSIAN_BG_MODEL);
BackgroundSubtractorMOG2 bgModel = new BackgroundSubtractorMOG2(0, 0, true);
//BackgroundSubstractorMOG bgModel = new BackgroundSubstractorMOG(0, 0, 0, 0);
capture.ImageGrabbed += delegate(object sender, EventArgs e)
{
Mat frame = new Mat();
capture.Retrieve(frame);
bgModel.Apply(frame, fgMask);
using (CvBlobDetector detector = new CvBlobDetector())
using (CvBlobs blobs = new CvBlobs())
{
detector.Detect(fgMask.ToImage<Gray, Byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
tracks.Update(blobs, 20.0, 10, 0);
Image<Bgr, Byte> result = new Image<Bgr, byte>(frame.Size);
using (Image<Gray, Byte> blobMask = detector.DrawBlobsMask(blobs))
{
frame.CopyTo(result, blobMask);
}
//CvInvoke.cvCopy(frame, result, blobMask);
foreach (KeyValuePair<uint, CvTrack> pair in tracks)
{
if (pair.Value.Inactive == 0) //only draw the active tracks.
{
CvBlob b = blobs[pair.Value.BlobLabel];
Bgr color = detector.MeanColor(b, frame.ToImage<Bgr, Byte>());
result.Draw(pair.Key.ToString(), pair.Value.BoundingBox.Location, CvEnum.FontFace.HersheySimplex, 0.5, color);
result.Draw(pair.Value.BoundingBox, color, 2);
Point[] contour = b.GetContour();
result.Draw(contour, new Bgr(0, 0, 255), 1);
}
}
viewer.Image = frame.ToImage<Bgr, Byte>().ConcateVertical(fgMask.ToImage<Bgr, Byte>().ConcateHorizontal(result));
}
};
capture.Start();
viewer.ShowDialog();
}
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Image <Bgr, Byte> smoothedFrame = new Image <Bgr, byte>(frame.Size);
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//CvInvoke.PutText(frame, blob.ID.ToString(), Point.Round(blob.Center), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
private void Application_Idle(object sender, EventArgs e)
{
Mat a = cap.QueryFrame();
if (a != null)
{
System.Threading.Thread.Sleep((int)(1000.0 / fps - 5));
imageBox1.Image = a;
GC.Collect();
}
// 讀取彩色影像
Image <Bgr, byte> image01 = new Image <Bgr, byte>(imageBox1.Image.Bitmap);
imageBox1.Image = image01;
var image2 = image01.InRange(new Bgr(10, 1, 13), new Bgr(76, 144, 240));
var image2_not = image2.Not();
using (CvBlobs blobs = new CvBlobs())
{
blobDetector.Detect(image2, blobs);
var image3 = image01.Copy();
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(image3, b.BoundingBox, new MCvScalar(255.255, 255, 0), 5);
}
imageBox1.Image = image01;
imageBox2.Image = image2;
imageBox3.Image = image3;
imageBox4.Image = image2_not;
}
}
static Image <Bgr, Byte> _doDetect(string fileName)
{
Debug.WriteLine($"Processing: {fileName}");
var frameOrig = new Image <Bgr, Byte>(fileName);
var frame = frameOrig.Convert <Gray, Byte>();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(19, 19), 7); //filter out noises
var smoothedImage = smoothedFrame.ToImage <Gray, Byte>();
if (_original == null)
{
_original = smoothedImage;
return(null);
}
var frameDelta = smoothedImage.AbsDiff(_original);
var thresh = frameDelta.ThresholdBinary(new Gray(25), new Gray(255));
thresh = thresh.Dilate(2);
//File.WriteAllBytes(@"C:\Temp\imagery\aathreh.jpg", thresh.ToJpegData(95));
_original = smoothedImage;
//var cnts = new VectorOfVectorOfPoint();
//CvInvoke.FindContours(thresh.Copy(), cnts, null, RetrType.External,
// ChainApproxMethod.ChainApproxSimple);
//var goer = false;
//for (var i = 0; i < cnts.Size; i++)
//{
// var c = cnts[i];
// if (CvInvoke.ContourArea(c) < 500)
// {
// continue;
// }
// goer = true;
// //Debug.WriteLine(CvInvoke.ContourArea(c));
// //var rect = CvInvoke.BoundingRectangle(c);
// //CvInvoke.Rectangle(frame, rect, new MCvScalar(255.0, 255.0, 255.0), 2);
//}
////// File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
// return goer;
//Mat forgroundMask = new Mat();
//_fgDetector.Apply(smoothedFrame, forgroundMask);
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(thresh, blobs);
blobs.FilterByArea(1600, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
//File.WriteAllBytes(@"C:\Temp\imagery\aaout.jpg", smoothedImage.ToJpegData(95));
_tracker.Update(blobs, scale, 5, 5);
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
CvInvoke.Rectangle(frameOrig, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
CvInvoke.PutText(frameOrig, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
// File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
// File.WriteAllBytes(@"C:\Temp\imagery\aablur.jpg", smoothedFrame.ToImage<Gray, byte>().ToJpegData(95));
return(_tracker.Count > 0 ? frameOrig : null);
//var cnts = new VectorOfVectorOfPoint();
//CvInvoke.FindContours(thresh.Copy(), cnts, null, RetrType.External,
// ChainApproxMethod.ChainApproxSimple);
//for (var i = 0; i < cnts.Size; i++)
//{
// var c = cnts[i];
// Debug.WriteLine(CvInvoke.ContourArea(c));
// var rect = CvInvoke.BoundingRectangle(c);
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//}
//Mat smoothedFrame = new Mat();
//CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(23, 23), 5); //filter out noises
////frame._SmoothGaussian(3);
//Mat forgroundMask = new Mat();
//_fgDetector.Apply(smoothedFrame, forgroundMask);
//CvBlobs blobs = new CvBlobs();
//_blobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), blobs);
//blobs.FilterByArea(100, int.MaxValue);
//float scale = (frame.Width + frame.Width) / 2.0f;
//File.WriteAllBytes(@"C:\Temp\imagery\aaout.jpg", forgroundMask.ToImage<Gray, byte>().ToJpegData(95));
//_tracker.Update(blobs, scale, 5, 5);
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
//}
//File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
//File.WriteAllBytes(@"C:\Temp\imagery\aablur.jpg", smoothedFrame.ToImage<Gray, byte>().ToJpegData(95));
//Console.WriteLine($" >>>> Tracker: {_tracker.Count}, Blobs: {blobs.Count}");
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
//}
//imageBox1.Image = frame;
//imageBox2.Image = forgroundMask;
}
/// <summary>
/// 图漾粗略找合适的轮廓
/// </summary>
/// <param name="point_3d">三维点</param>
public static void getContours(float[] point_3d)
{
GLB.TitleStr = "";
int AREA = GLB.BUFW * GLB.BUFH; //总面积
var gray = GLB.MyFrame.Convert <Gray, Byte>(); //灰度化
Emgu.CV.Cvb.CvBlobs myBlobs = new Emgu.CV.Cvb.CvBlobs();
Emgu.CV.Cvb.CvBlobDetector bd = new Emgu.CV.Cvb.CvBlobDetector();
uint n = bd.Detect(gray, myBlobs);//发现区块
////遍历各区块:
for (uint i = 1; i <= myBlobs.Count; i++)
{
int area = myBlobs[i].Area; //获取面积
RotatedRect rect = CvInvoke.MinAreaRect(new VectorOfPoint(myBlobs[i].GetContour())); //最小矩形
float width = rect.Size.Width; //像素宽
float height = rect.Size.Height; //像素长
if (height < width)
{
float temp = height;
height = width;
width = temp;
}
float H2W = height / width;
if (area > 0.02 * AREA && area < 0.75 * AREA && H2W > 1 && H2W < 2)//通过面积 长宽比 初略筛选
{
if (getProduceInfo(myBlobs[i], point_3d) == true)
{
if (ProduceMacth() == true)//匹配成功
{
//////#########################################队列求均值--获取中心坐标#################################################
//GLB.avgCameraPoint3.Enqueue(new Point3(GLB.camera_device_point.X, GLB.camera_device_point.Y, GLB.camera_device_point.Z));
//if (GLB.avgCameraPoint3.Count > 5)
//{
// GLB.avgCameraPoint3.Dequeue();
//}
//else
//{
// return ;
//}
//GLB.camera_device_point.Z = (int)GLB.avgCameraPoint3.Average(o => o.Z);//中心点的深度//Z
//GLB.camera_device_point.Y = (int)GLB.avgCameraPoint3.Average(o => o.Y);//Y
//GLB.camera_device_point.X = (int)GLB.avgCameraPoint3.Average(o => o.X);//X
//RotatedRect boxCenter = new RotatedRect(new PointF((float )GLB.obj.jd.Average(o => o.X), (float)GLB.obj.jd.Average(o => o.Y)), new Size(8, 8), 0);
//CvInvoke.Ellipse(GLB.MyFrame, boxCenter, new MCvScalar(255, 0, 0), 4);//在中心画一个小圆
//CvInvoke.PutText(GLB.MyFrame, "x:" + (float)GLB.obj.jd.Average(o => o.X) + "y:" + (float)GLB.obj.jd.Average(o => o.Y) + "XC=" + GLB.obj.xCenter + "YC=" + GLB.obj.yCenter + "Depth=" + GLB.obj.Depth, new System.Drawing.Point((int)GLB.obj.jd.Average(o => o.X) - 176, (int)GLB.obj.jd.Average(o => o.Y) + 25), Emgu.CV.CvEnum.FontFace.HersheyDuplex, .75, new MCvScalar(255, 255, 255), 2);//深度显示
////////队列求均值
//GLB.avgAngle.Enqueue((float)GLB.obj.Angle);
//if (GLB.avgAngle.Count > 5)
//{
// GLB.avgAngle.Dequeue();
//}
//else
//{
// return ;
//}
//GLB.obj.Angle = GLB.avgAngle.Average();//旋转角
//CvInvoke.PutText(GLB.MyFrame, "Angl=" + GLB.obj.Angle, new System.Drawing.Point((int)GLB.obj.jd[3].X, (int)GLB.obj.jd[3].Y), Emgu.CV.CvEnum.FontFace.HersheyDuplex, .75, new MCvScalar(0, 0, 255), 2);
////#########################################坐标换算#################################################
GLB.robot_device_point.X = GLB.MatTuYangCam[0] * GLB.camera_device_point.X + GLB.MatTuYangCam[1] * GLB.camera_device_point.Y + GLB.MatTuYangCam[2];
GLB.robot_device_point.Y = GLB.MatTuYangCam[3] * GLB.camera_device_point.X + GLB.MatTuYangCam[4] * GLB.camera_device_point.Y + GLB.MatTuYangCam[5];
GLB.robot_device_point.Z = 2818 - GLB.camera_device_point.Z;
GLB.device_angl += -2.6f;//相机与机器人夹角2.6度
GLB.device_angl = (float)(GLB.device_angl * Math.PI / 180f);
//限定范围
if (GLB.robot_device_point.X < -600 || GLB.robot_device_point.X > 600 ||
GLB.robot_device_point.Y < -2200 || GLB.robot_device_point.Y > -800 ||
GLB.robot_device_point.Z < 280 || GLB.robot_device_point.Z > 1100)
{
GLB.Match_success = false;
GLB.TitleStr += "，但是超出范围";
}
else
{
GLB.Match_success = true;
}
}
else
{
GLB.Match_success = false;
}
}
}
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Mat frame_crop = frame;
Image <Hsv, Byte> currenthsvFrame = (frame.ToImage <Bgr, Byte>()).Convert <Hsv, Byte>();
Image <Gray, Byte> color_one = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_two = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_three = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_four = new Image <Gray, Byte>(frame.Width, frame.Height);
/*
* Color one is Red
* Color two is Blue
* Color three is Green
* Color Four is Yellow
* Green is in Right Index Finger
* Blue is in Left Index Finger
* Red in Right Thumb
* Yelloe in Left Thumb
*/
Hsv hsv_min_color_one = new Hsv(0, 135, 110);
//Hsv hsv_max_color_one = new Hsv(6, 255, 255);
Hsv hsv_max_color_one = new Hsv(8, 255, 255);
Hsv hsv_min_color_two = new Hsv(112, 53, 10);
Hsv hsv_max_color_two = new Hsv(119, 255, 255);
/*
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);
*/
Hsv hsv_min_color_three = new Hsv(83, 109, 105);
Hsv hsv_max_color_three = new Hsv(109, 255, 255);
Hsv hsv_min_color_four = new Hsv(18, 155, 155);
Hsv hsv_max_color_four = new Hsv(35, 255, 255);
color_one = currenthsvFrame.InRange(hsv_min_color_one, hsv_max_color_one);
color_two = currenthsvFrame.InRange(hsv_min_color_two, hsv_max_color_two);
color_three = currenthsvFrame.InRange(hsv_min_color_three, hsv_max_color_three);
color_four = currenthsvFrame.InRange(hsv_min_color_four, hsv_max_color_four);
//Blob detection
#region Blob Detection
//Color one detection
Image <Bgr, Byte> smoothedFrame_cone = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_one, smoothedFrame_cone, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cone = new Mat();
fgDetector.Apply(smoothedFrame_cone, forgroundMask_cone);
CvBlobs blobs_color_one = new CvBlobs();
blobDetector.Detect(forgroundMask_cone.ToImage <Gray, byte>(), blobs_color_one);
blobs_color_one.FilterByArea(minarea, maxarea);
//Color two Blob Detection
Image <Bgr, Byte> smoothedFrame_ctwo = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_two, smoothedFrame_ctwo, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_ctwo = new Mat();
fgDetector.Apply(smoothedFrame_ctwo, forgroundMask_ctwo);
CvBlobs blobs_color_two = new CvBlobs();
blobDetector.Detect(forgroundMask_ctwo.ToImage <Gray, byte>(), blobs_color_two);
blobs_color_two.FilterByArea(minarea, maxarea);
//Color three blob detection
Image <Bgr, Byte> smoothedFrame_cthree = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_three, smoothedFrame_cthree, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cthree = new Mat();
fgDetector.Apply(smoothedFrame_cthree, forgroundMask_cthree);
CvBlobs blobs_color_three = new CvBlobs();
blobDetector.Detect(forgroundMask_cthree.ToImage <Gray, byte>(), blobs_color_three);
blobs_color_three.FilterByArea(minarea, maxarea);
//Color four detection
Image <Bgr, Byte> smoothedFrame_cfour = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_four, smoothedFrame_cfour, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cfour = new Mat();
fgDetector.Apply(smoothedFrame_cfour, forgroundMask_cfour);
CvBlobs blobs_color_four = new CvBlobs();
blobDetector.Detect(forgroundMask_cfour.ToImage <Gray, byte>(), blobs_color_four);
blobs_color_four.FilterByArea(minarea, maxarea);
//Makers Interpretition
float[] cent_color_one = new float[2];
float[] cent_color_two = new float[2];
float[] cent_color_three = new float[2];
float[] cent_color_four = new float[2];
//Centroids of Markers
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_one[0] = b.Centroid.X;
cent_color_one[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_two)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_two[0] = b.Centroid.X;
cent_color_two[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_three[0] = b.Centroid.X;
cent_color_three[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_four)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_four[0] = b.Centroid.X;
cent_color_four[1] = b.Centroid.Y;
}
#endregion
#region Calculation
int click_flag = 0;
int[] x_cor = new int[4];
int[] y_cor = new int[4];
if (blobs_color_one.Count != 0 && blobs_color_two.Count != 0 && blobs_color_three.Count != 0 && blobs_color_four.Count != 0)
{
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
foreach (var pairr in blobs_color_two)
{
CvBlob c = pairr.Value;
if ((b.Centroid.X - c.Centroid.X) * (b.Centroid.X - c.Centroid.X) + (b.Centroid.Y - c.Centroid.Y) * (b.Centroid.Y - c.Centroid.Y) <= 5000)
{
click_flag = 1;
x_cor[0] = ((int)b.Centroid.X);
x_cor[1] = ((int)c.Centroid.X);
y_cor[0] = ((int)b.Centroid.Y);
y_cor[1] = ((int)c.Centroid.Y);
break;
}
}
if (click_flag == 1)
{
break;
}
}
if (click_flag == 1)
{
click_flag = 0;
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
foreach (var pairr in blobs_color_four)
{
CvBlob c = pairr.Value;
if ((b.Centroid.X - c.Centroid.X) * (b.Centroid.X - c.Centroid.X) + (b.Centroid.Y - c.Centroid.Y) * (b.Centroid.Y - c.Centroid.Y) <= 10000)
{
click_flag = 1;
x_cor[2] = ((int)b.Centroid.X);
x_cor[3] = ((int)c.Centroid.X);
y_cor[2] = ((int)b.Centroid.Y);
y_cor[3] = ((int)c.Centroid.Y);
break;
}
}
if (click_flag == 1)
{
break;
}
}
}
}
if (click_flag == 1)
{
//MessageBox.Show("clicked");
SoundPlayer simpleSound = new SoundPlayer(@"click_sound.wav");
simpleSound.Play();
Array.Sort(x_cor);
Array.Sort(y_cor);
Bitmap ori_image = frame_crop.ToImage <Bgr, Byte>().ToBitmap();
Bitmap crop_image = new Bitmap(x_cor[2] - x_cor[1], y_cor[2] - y_cor[1]);
Graphics g = Graphics.FromImage(crop_image);
g.DrawImage(ori_image, -x_cor[1], -y_cor[1]);
//string name = string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}.jpg",DateTime.Now);
frame.Save(@"C:\Users\Shubhankar\Pictures\Camera Roll\" + string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}_original.jpg", DateTime.Now));
crop_image.Save(@"C:\Users\Shubhankar\Pictures\Camera Roll\" + string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}.jpg", DateTime.Now));
Thread.Sleep(500);
}
#endregion
#region Click Gesture
#endregion
captureImageBox.Image = frame;
grayscaleImageBox.Image = color_one;
smoothedGrayscaleImageBox.Image = color_two;
cannyImageBox.Image = color_three;
Color4ImageBox.Image = color_four;
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
IImage image = (IImage)frame;//这一步是重点
faceImage = frame.Bitmap;
DetectFace.Detect(image
, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
#region 多人识别 多人识别存在较大误差率（图片库 如果高清，识别效果就是好）
//Graphics g1 = Graphics.FromImage(frame.Bitmap);
//List<FaceIdentifyModel> tempList = new List<FaceIdentifyModel>();
//foreach (Rectangle face in faces)
//{
// Image rectImage1 = ImageHelper.CaptureImage(frame.Bitmap, face);
// FaceIdentifyModel MoreIdentifyInfo = FaceAPI.FaceIdentify(rectImage1, tb_Group.Text.Trim(), 1, 1);//人脸识别 一个人的识别效果比较好
// MoreIdentifyInfo.rect = face;
// tempList.Add(MoreIdentifyInfo);
//}
//Color color_of_pen1 = Color.Gray;
//color_of_pen1 = Color.Yellow;
//Pen pen1 = new Pen(color_of_pen1, 2.0f);
//Font font1 = new Font("微软雅黑", 16, GraphicsUnit.Pixel);
//SolidBrush drawBrush1 = new SolidBrush(Color.Yellow);
//tb_Identify.Text = tempList.ToJson();
//foreach (var t in tempList)
//{
// g1.DrawRectangle(pen1, t.rect);
// if (t.result != null)
// {
// g1.DrawString(t.result[0].user_info.Replace("，", "\r\n"), font1, drawBrush1, new Point(t.rect.X + 20, t.rect.Y - 20));
// }
//}
#endregion
#region 单人识别
//单人 人脸识别 多人效果比较差
foreach (Rectangle face in faces)
{
#region 采用画图，显示自己的文本框
Graphics g = Graphics.FromImage(frame.Bitmap);
ImageModel tempImage = new ImageModel();
tempImage.Rect = face;
tempImage.Image = frame.Bitmap;
//接口查询速度差
//string faceInfo = FaceAPI.FaceDetect(ImageHelper.CaptureImage(frame.Bitmap, face));//人脸检测
Image rectImage = ImageHelper.CaptureImage(frame.Bitmap, face);
FaceIdentifyModel IdentifyInfo = FaceAPI.FaceIdentify(rectImage, tb_Group.Text.Trim(), 1, 1);//人脸识别 一个人的识别效果比较好 // tb_Result.Text = faceInfo;
tb_Identify.Text = IdentifyInfo.ToJson().ToString();
//采用画板
Color color_of_pen = Color.Gray;
color_of_pen = Color.Yellow;
Pen pen = new Pen(color_of_pen, 2.0f);
Rectangle rect = face;
g.DrawRectangle(pen, rect);
Font font = new Font("微软雅黑", 16, GraphicsUnit.Pixel);
SolidBrush drawBrush = new SolidBrush(Color.Yellow);
if (IdentifyInfo != null)
{
if (IdentifyInfo.result != null)
{
for (int i = 0; i < IdentifyInfo.result.Count; i++)
{
string faceInfo = "";
faceInfo = IdentifyInfo.result[i].user_info.Replace("，", "\r\n");
//显示用户信息
g.DrawString(faceInfo, font, drawBrush, new Point(face.X + 20, face.Y - 20));
}
}
}
//CvInvoke.Rectangle(frame, face, new MCvScalar(255.0, 255.0, 255.0), 2);
//CvInvoke.PutText(frame, faceInfo, new Point(face.X + 20, face.Y - 20), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
// 保存原始截图
//System.Drawing.Image ResourceImage = frame.Bitmap;
//ResourceImage.Save(saveDir + saveFileName);
//线程队列 保存人脸识别截图
QueueHelper.WriteImage(tempImage);
//t1 = new Thread(new ThreadStart(() =>
//{
// faceInfo = FaceAPI.FaceDetect(ImageHelper.CaptureImage(frame.Bitmap, face));
// this.Invoke(new Action(() =>
// {
// g.DrawString(faceInfo, font, drawBrush, new Point(face.X + 20, face.Y - 20));
// }));
//}));
//t1.IsBackground = true;
//t1.Start();
#endregion
}
#endregion
#region 视频调用原有的Open CV 不支持中文字
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// #region 视频中调用open CV 上直接画文本框
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, "man,show", new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
// if (b.BoundingBox.Width < 100 || b.BoundingBox.Height < 50)
// {
// continue;
// }
// #endregion
//}
#endregion
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Mat grayFrame = new Mat();
CvInvoke.CvtColor(frame, grayFrame, ColorConversion.Bgr2Gray);
//Mat smallGrayFrame = new Mat();
//CvInvoke.PyrDown(grayFrame, smallGrayFrame);
//Mat smoothedGrayFrame = new Mat();
//CvInvoke.PyrUp(smallGrayFrame, smoothedGrayFrame);
//Image<Gray, Byte> smallGrayFrame = grayFrame.PyrDown();
//Image<Gray, Byte> smoothedGrayFrame = smallGrayFrame.PyrUp();
//Mat cannyFrame = new Mat();
//CvInvoke.Canny(smoothedGrayFrame, cannyFrame, 100, 60);
//Image<Gray, Byte> cannyFrame = smoothedGrayFrame.Canny(100, 60);
Image <Bgra, Byte> _frame = frame.ToImage <Bgra, Byte>();
Image <Gray, Byte> _grayFrame = grayFrame.ToImage <Gray, Byte>();
Image <Gray, Byte>[] rgb_frame = _frame.Split(); //components of rgb image
Image <Gray, Byte> red_com = rgb_frame[2] - _grayFrame;
var red_bi = red_com.Convert <Gray, byte>().ThresholdBinary(new Gray(redThres), new Gray(255));
Image <Gray, Byte> blue_com = rgb_frame[0] - _grayFrame;
var blue_bi = blue_com.Convert <Gray, byte>().ThresholdBinary(new Gray(blueThres), new Gray(255));
Image <Gray, Byte> green_com = rgb_frame[1] - _grayFrame;
var green_bi = green_com.Convert <Gray, byte>().ThresholdBinary(new Gray(greenThres), new Gray(255));
//System.Windows.Forms.MessageBox.Show("");
///////////////////////////////////////////////////////////////////////////////////
//Blob detection
//Red Blob detection
Image <Bgr, Byte> smoothedFrame_r = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(red_bi, smoothedFrame_r, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_r = new Mat();
fgDetector.Apply(smoothedFrame_r, forgroundMask_r);
CvBlobs blobs_r = new CvBlobs();
blobDetector.Detect(forgroundMask_r.ToImage <Gray, byte>(), blobs_r);
blobs_r.FilterByArea(minarea, maxarea);
//blue Blob Detection
Image <Bgr, Byte> smoothedFrame_b = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(blue_bi, smoothedFrame_b, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_b = new Mat();
fgDetector.Apply(smoothedFrame_b, forgroundMask_b);
CvBlobs blobs_b = new CvBlobs();
blobDetector.Detect(forgroundMask_b.ToImage <Gray, byte>(), blobs_b);
blobs_b.FilterByArea(minarea, maxarea);
//Green blob detection
Image <Bgr, Byte> smoothedFrame_g = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(green_bi, smoothedFrame_g, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_g = new Mat();
fgDetector.Apply(smoothedFrame_g, forgroundMask_g);
CvBlobs blobs_g = new CvBlobs();
blobDetector.Detect(forgroundMask_g.ToImage <Gray, byte>(), blobs_g);
blobs_g.FilterByArea(minarea, maxarea);
//Mouse Interpretition
float[] cent_r = new float[2];
float[] cent_g = new float[2];
float[] cent_b = new float[2];
//Corsor control with Green Marker
foreach (var pair in blobs_g)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_g[0] = b.Centroid.X;
cent_g[1] = b.Centroid.Y;
}
if (blobs_g.Count == 1 || mouseflag != 0)
{
//Cursor Movement Controlled
//Primary Screem
//if (Screen.AllScreens.Length == 1)
{
Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * (int)cent_g[0] * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_g[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
}
//Secondary Screen
//Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * Screen.AllScreens[1].Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_g[1]) * Screen.AllScreens[1].Bounds.Height / capture.Height);
//Number of Screen = 2 and both a same time
/* if (Screen.AllScreens.Length == 2)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_g[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
* //Number of screen =3 and all at same time
* if (Screen.AllScreens.Length == 3)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width + Screen.AllScreens[2].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_g[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
*/
/*
* //Check for Clicks
* if (blobs_r.Count == 1)
* {
* if(blobs_g.Count == 0)
* {
* if(ccount == 1)
* {
* //double click
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* Thread.Sleep(150);
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
* else
* {
* ccount--;
* }
* }
*
* else if ((cent_g[0] - cent_r[0] >= 10 || cent_r[0] - cent_g[0] <= 10) && (cent_g[1] - cent_r[1] >= 10 || cent_r[1] - cent_g[1] <= 10))
* {
* ccount = safevalue;
* mouseflag = 1;
* //single click
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
* }
* else
* {
* ccount = 0;
*
* }
*
* }
*
* if (blobs_b.Count == 1)
* {
* foreach (var pair in blobs_b)
* {
* CvBlob b = pair.Value;
* CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
* cent_b[0] = b.Centroid.X;
* cent_b[1] = b.Centroid.Y;
* }
*
* if (blobs_g.Count == 1 && (cent_g[0] - cent_b[0] >= 10 || cent_b[0] - cent_g[0] <= 10) && (cent_g[1] - cent_b[1] >= 10 || cent_b[1] - cent_g[1] <= 10))
* {
* //right click
* mouse_event(MOUSEEVENTF_RIGHTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_RIGHTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
*
* else if(blobs_g.Count == 0)
* {
* mouse_event(MOUSEEVENTF_VWHEEL, 0, 0, (scroll_y - (int)cent_b[1]) * scroll_mul_v, 0);
* mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, (scroll_x - (int)cent_b[0]) * scroll_mul_h, 0);
* scroll_y = (int)cent_b[1];
* scroll_x = (int)cent_b[0];
*
* }
*/
}
captureImageBox.Image = frame;
grayscaleImageBox.Image = red_bi;
smoothedGrayscaleImageBox.Image = green_bi;
cannyImageBox.Image = blue_bi;
}
public CameraTrackingFindSubjectsReturnModel FindSubjects()
{
double largestW = 0;
double largestH = 0;
double centerX = 0;
double centerY = 0;
bool foundSubject = false;
Rectangle subject = new Rectangle();
// get detection 'blobs' or regions
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(this.lastMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (this.lastFrame.Width + this.lastFrame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
FrameWidth = this.lastFrame.Width;
FrameHeight = this.lastFrame.Height;
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
// limit the largest and smallest size boxes we care about.
if (b.BoundingBox.Width < (this.lastFrame.Width / this.smallestDetectionWidthSizeDivisor) ||
b.BoundingBox.Height < (this.lastFrame.Height / this.smallestDetectionHeightSizeDivisor) ||
(b.BoundingBox.Width > (this.lastFrame.Width / this.largestDetectionWidthSizeDivisor) &&
b.BoundingBox.Height > (this.lastFrame.Height / this.largestDetectionHeightSizeDivisor)))
{
continue;
}
// keep track of the largest regions as we only care to track the largest
if (b.BoundingBox.Width > largestW)
{
subject = b.BoundingBox;
largestW = b.BoundingBox.Width;
largestH = b.BoundingBox.Height;
centerX = b.Centroid.X;
centerY = b.Centroid.Y;
CvInvoke.Rectangle(
this.lastFrame,
b.BoundingBox,
new MCvScalar(
255.0,
255.0,
255.0),
20);
CvInvoke.PutText(
this.lastFrame,
b.Id.ToString(),
new Point(
(int)Math.Round(b.Centroid.X),
(int)Math.Round(b.Centroid.Y)),
FontFace.HersheyPlain,
1.0,
new MCvScalar(255.0, 255.0, 255.0));
foundSubject = true;
}
else
{
CvInvoke.Rectangle(
this.lastFrame,
b.BoundingBox,
new MCvScalar(
255.0,
255.0,
255.0),
1);
CvInvoke.PutText(
this.lastFrame,
b.Id.ToString(),
new Point(
(int)Math.Round(b.Centroid.X),
(int)Math.Round(b.Centroid.Y)),
FontFace.HersheyPlain,
1.0,
new MCvScalar(
255.0,
255.0,
255.0));
}
}
return(new CameraTrackingFindSubjectsReturnModel()
{
CenterX = centerX,
CenterY = centerY,
BoundingBox = subject,
FoundSubject = foundSubject
});
}
private void ExtractBlobAndCrop(Image <Gray, byte> skin)
{
using (MemStorage storage = new MemStorage())
{
Image <Gray, Byte> smoothedFrame = new Image <Gray, byte>(skin.Size);
CvInvoke.GaussianBlur(skin, smoothedFrame, new Size(3, 3), 1); //filter out noises
imageBoxFrameGrabber.Image = skin;
Mat forgroundMask = new Mat();
Mat ss = new Mat();
ss = skin.Mat;
//grabber.Retrieve(ss);
fgDetector.Apply(ss, forgroundMask);
//imageBox1.Image = forgroundMask;
CvBlobs blobs = new CvBlobs();
//blobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), blobs);
blobDetector.Detect(skin, blobs);
blobs.FilterByArea(30000, 150000);
CvBlob b = null;
CvBlob btemp;
int area = 0;
foreach (var pair in blobs)
{
btemp = pair.Value;
if (area < btemp.Area)
{
b = pair.Value;
area = btemp.Area;
}
}
//Crop LArgest Blob
Bitmap skin_bit = skin.ToBitmap();
//MessageBox.Show("" + area);
if (area != 0)
{
CvInvoke.Rectangle(currentFrame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//Rectangle rec = new Rectangle(b.BoundingBox.X, b.BoundingBox.Y, b.BoundingBox.Width, b.BoundingBox.Height);
Bitmap crop_image = new Bitmap((b.BoundingBox.Width > b.BoundingBox.Height ? b.BoundingBox.Width : b.BoundingBox.Height), (b.BoundingBox.Width > b.BoundingBox.Height ? b.BoundingBox.Width : b.BoundingBox.Height));
//Bitmap crop_image = skin_bit.Clone(rec, skin_bit.PixelFormat);
Graphics g = Graphics.FromImage(crop_image);
g.DrawImage(skin_bit, -b.BoundingBox.X, -b.BoundingBox.Y);
//g.DrawImage(skin_bit, -50, -50);
croped = new Image <Gray, Byte>(crop_image).Resize(350, 350, Inter.Cubic);
croped1 = new Image <Gray, Byte>(crop_image).Resize(100, 100, Inter.Cubic);
croped2 = new Image <Gray, Byte>(crop_image).Resize(50, 50, Inter.Cubic);
int gesture_number = fow_prop.image(croped2);
label1.Text = "" + gesture_number;
imageBoxSkin.Image = croped;
crop_image.Dispose();
skin_bit.Dispose();
}
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Image <Hsv, Byte> currenthsvFrame = (frame.ToImage <Bgr, Byte>()).Convert <Hsv, Byte>();
Image <Gray, Byte> color_one = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_two = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_three = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_four = new Image <Gray, Byte>(frame.Width, frame.Height);
/*
* Color one is Red
* Color two is Blue
* Color three is Green
* Color Four is Yellow
* Green is in Right Index Finger
* Blue is in Left Index Finger
* Red in Right Thumb
* Yelloe in Left Thumb
*/
/* Hsv hsv_min_color_one = new Hsv(0, 135, 110);
* Hsv hsv_max_color_one = new Hsv(6, 255, 255);
* Hsv hsv_min_color_two = new Hsv(112, 53, 10);
* Hsv hsv_max_color_two = new Hsv(119, 255, 255);
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);*/
Hsv hsv_min_color_one = new Hsv(0, 135, 50);
//Hsv hsv_max_color_one = new Hsv(6, 255, 255);
Hsv hsv_max_color_one = new Hsv(8, 255, 255);
Hsv hsv_min_color_two = new Hsv(112, 53, 10);
Hsv hsv_max_color_two = new Hsv(119, 255, 255);
/*
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);
*/
Hsv hsv_min_color_three = new Hsv(65, 70, 0);
Hsv hsv_max_color_three = new Hsv(109, 255, 255);
Hsv hsv_min_color_four = new Hsv(18, 155, 155);
Hsv hsv_max_color_four = new Hsv(35, 255, 255);
color_one = currenthsvFrame.InRange(hsv_min_color_one, hsv_max_color_one);
color_two = currenthsvFrame.InRange(hsv_min_color_two, hsv_max_color_two);
color_three = currenthsvFrame.InRange(hsv_min_color_three, hsv_max_color_three);
color_four = currenthsvFrame.InRange(hsv_min_color_four, hsv_max_color_four);
//Blob detection
#region Blob Detection
//Color one detection
Image <Bgr, Byte> smoothedFrame_cone = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_one, smoothedFrame_cone, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cone = new Mat();
fgDetector.Apply(smoothedFrame_cone, forgroundMask_cone);
CvBlobs blobs_color_one = new CvBlobs();
blobDetector.Detect(forgroundMask_cone.ToImage <Gray, byte>(), blobs_color_one);
blobs_color_one.FilterByArea(minarea, maxarea);
//Color two Blob Detection
Image <Bgr, Byte> smoothedFrame_ctwo = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_two, smoothedFrame_ctwo, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_ctwo = new Mat();
fgDetector.Apply(smoothedFrame_ctwo, forgroundMask_ctwo);
CvBlobs blobs_color_two = new CvBlobs();
blobDetector.Detect(forgroundMask_ctwo.ToImage <Gray, byte>(), blobs_color_two);
blobs_color_two.FilterByArea(minarea, maxarea);
//Color three blob detection
Image <Bgr, Byte> smoothedFrame_cthree = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_three, smoothedFrame_cthree, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cthree = new Mat();
fgDetector.Apply(smoothedFrame_cthree, forgroundMask_cthree);
CvBlobs blobs_color_three = new CvBlobs();
blobDetector.Detect(forgroundMask_cthree.ToImage <Gray, byte>(), blobs_color_three);
blobs_color_three.FilterByArea(minarea, maxarea);
//Color four detection
Image <Bgr, Byte> smoothedFrame_cfour = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_four, smoothedFrame_cfour, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cfour = new Mat();
fgDetector.Apply(smoothedFrame_cfour, forgroundMask_cfour);
CvBlobs blobs_color_four = new CvBlobs();
blobDetector.Detect(forgroundMask_cfour.ToImage <Gray, byte>(), blobs_color_four);
blobs_color_four.FilterByArea(minarea, maxarea);
#endregion
//Makers Interpretition
float[] cent_color_one = new float[2];
float[] cent_color_two = new float[2];
float[] cent_color_three = new float[2];
float[] cent_color_four = new float[2];
cent_color_one[0] = 0;
cent_color_one[1] = 0;
cent_color_two[0] = 0;
cent_color_two[1] = 0;
cent_color_three[0] = green_history_x;
cent_color_three[1] = green_history_y;
cent_color_four[0] = 0;
cent_color_four[1] = 0;
//Corsor control with Green Marker
if (blobs_color_three.Count == 1 || mouseflag != 0)
{
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cursor_history_x.Enqueue((int)b.Centroid.X);
cursor_history_y.Enqueue((int)b.Centroid.Y);
cursor_history_x.Dequeue();
cursor_history_y.Dequeue();
cent_color_three[0] = (int)b.Centroid.X;
cent_color_three[1] = (int)b.Centroid.Y;
/*int temp_sum = 0;
* int[] temp = cursor_history_x.ToArray();
* for (int i = 0; i < queue_cursor_length; i++)
* temp_sum += temp[i];
* cent_color_three[0] = temp_sum / queue_cursor_length;
*
* temp_sum = 0;
* temp = cursor_history_y.ToArray();
* for (int i = 0; i < queue_cursor_length; i++)
* temp_sum += temp[i];
* cent_color_three[1] = temp_sum / queue_cursor_length;
*
* green_history_x = (int)cent_color_three[0];
* green_history_y = (int)cent_color_three[1];*/
}
//Cursor Movement Controlled
//Primary Screem
// if (Screen.AllScreens.Length == 1)
{
//Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * (int)cent_color_three[0] * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_color_three[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
Cursor.Position = new Point((int)((cursor_mul_x * (int)cent_color_three[0]) * (Screen.PrimaryScreen.Bounds.Width) / capture.Width) + cursor_add_x, (((int)cursor_mul_y * (int)cent_color_three[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height) + cursor_add_y);
//mouse_event(MOUSEEVENTF_MOVE, ( (-(int)cent_color_three[0] + green_history_x)), ( (-(int)cent_color_three[1] + green_history_y)),0,0);
//mouse_event(MOUSEEVENTF_ABSOLUTE, 0, 0, 0, 0);
}
//Secondary Screen
//Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * Screen.AllScreens[1].Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_color_three[1]) * Screen.AllScreens[1].Bounds.Height / capture.Height);
//Number of Screen = 2 and both a same time
/* if (Screen.AllScreens.Length == 2)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_color_three[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
* //Number of screen =3 and all at same time
* if (Screen.AllScreens.Length == 3)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width + Screen.AllScreens[2].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_color_three[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
*/
//Check for Clicks
if (blobs_color_one.Count == 1)
{
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_one[0] = b.Centroid.X;
cent_color_one[1] = b.Centroid.Y;
}
if (blobs_color_three.Count == 0)
{
if (ccount == 1)
{
//double click
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
Thread.Sleep(150);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
}
else
{
ccount--;
}
}
else if ((cent_color_one[0] - cent_color_three[0]) * (cent_color_one[0] - cent_color_three[0]) + (cent_color_one[1] - cent_color_three[1]) * (cent_color_one[1] - cent_color_three[1]) <= 5000)
{
ccount = safevalue;
mouseflag = 1;
//single click
mouse_event(MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE, 0, 0, 0, 0);
}
}
else
{
ccount = 0;
}
}
if (blobs_color_two.Count == 1)
{
foreach (var pair in blobs_color_two)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_two[0] = b.Centroid.X;
cent_color_two[1] = b.Centroid.Y;
}
if (blobs_color_three.Count == 1 && ((cent_color_three[0] - cent_color_two[0]) * (cent_color_three[0] - cent_color_two[0]) + (cent_color_three[1] - cent_color_two[1]) * (cent_color_three[1] - cent_color_two[1]) <= 5000))
{
//right click
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_RIGHTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_RIGHTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
}
else //if(blobs_g.Count == 0)
{
//MessageBox.Show("d");
//Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * green_history_x * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * green_history_y) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
//mouse_event(MOUSEEVENTF_VWHEEL, 0, 0, (scroll_y - (int)cent_color_two[1]) * scroll_mul_v, 0);
mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, (uint)((scroll_x - (int)cent_color_two[0]) * scroll_mul_h), 0);
mouse_event(MOUSEEVENTF_VWHEEL, (uint)Cursor.Position.X, (uint)Cursor.Position.Y, 50, 0);
//mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, 50, 0);
scroll_y = (int)cent_color_two[1];
scroll_x = (int)cent_color_two[0];
}
}
captureImageBox.Image = frame;
grayscaleImageBox.Image = color_one;
smoothedGrayscaleImageBox.Image = color_two;
cannyImageBox.Image = color_three;
Color4ImageBox.Image = color_four;
}
public static WriteableBitmap DrawBlobBoundingBoxsCV(WriteableBitmap writeableBitmap, WriteableBitmap gradientBitmapRef, WriteableBitmap realBitmapRef)
{
Bitmap normalBitmap = BitmapFromWriteableBitmap(writeableBitmap);
var cvImage = new Image<Gray, byte>(new Bitmap(normalBitmap));
//var classifications = ClassifyBitmap( writeableBitmap, cvImage );
if (cvImage != null)
{
// This takes our nice looking color png and converts it to black and white
Image<Gray, byte> greyImg = cvImage.Convert<Gray, byte>();
// We again threshold it based on brightness...BUT WE INVERT THE PNG. BLOB DETECTOR DETECTS WHITE NOT BLACK
// this will esentially eliminate the color differences
// you could also do cool things like threshold only certain colors here for a color based blob detector
Image<Gray, Byte> greyThreshImg = greyImg.ThresholdBinaryInv(new Gray(150), new Gray(255));
Emgu.CV.Cvb.CvBlobs resultingImgBlobs = new Emgu.CV.Cvb.CvBlobs();
Emgu.CV.Cvb.CvBlobDetector bDetect = new Emgu.CV.Cvb.CvBlobDetector();
uint numWebcamBlobsFound = bDetect.Detect(greyThreshImg, resultingImgBlobs);
// This is a simple way of just drawing all blobs reguardless of their size and not iterating through them
// It draws on top of whatever you input. I am inputting the threshold image. Specifying an alpha to draw with of 0.5 so its half transparent.
//Emgu.CV.Image<Bgr, byte> blobImg = bDetect.DrawBlobs(webcamThreshImg, resultingWebcamBlobs, Emgu.CV.Cvb.CvBlobDetector.BlobRenderType.Default, 0.5);
// Here we can iterate through each blob and use the slider to set a threshold then draw a red box around it
Image<Rgb, byte> blobImg = greyThreshImg.Convert<Rgb, byte>();
Rgb red = new Rgb(255, 0, 0);
int blobNumber = 0;
// Lets try and iterate the blobs?
foreach (Emgu.CV.Cvb.CvBlob targetBlob in resultingImgBlobs.Values)
{
int imageArea = blobImg.Width*blobImg.Height;
int blobArea = targetBlob.Area;
int blobBoundingBoxArea = targetBlob.BoundingBox.Width*targetBlob.BoundingBox.Height;
// Only use blobs with area greater than some threshold
// If the blob bounding rect is basically size of the whole image ignore it for now
if (blobArea > 200.0 && blobBoundingBoxArea < (imageArea*0.99))
{
Rectangle rectangle = targetBlob.BoundingBox;
int CentroidX = (int)targetBlob.Centroid.X;
int CentroidY = (int)targetBlob.Centroid.Y;
int croppedWidth = rectangle.Width + 50;
int croppedHeight = rectangle.Height + 50;
int CroppedX = CentroidX - (int)(croppedWidth / 2.0);
int CroppedY = CentroidY - (int)(croppedHeight / 2.0);
var croppedBlobBitmap = writeableBitmap.Crop(CroppedX, CroppedY, croppedWidth, croppedHeight);
var croppedGradientBlobBitmap = gradientBitmapRef.Crop(CroppedX, CroppedY, croppedWidth, croppedHeight);
var croppedRealBitmapRef = realBitmapRef.Crop(CroppedX, CroppedY, croppedWidth, croppedHeight);
double blobAngle = -RadianToDegree(CalculateBlobAngle(targetBlob));
CroppedX = (int) (croppedWidth/2.0);
CroppedY = (int) (croppedHeight/2.0);
var rotatedandCroppedBlobBitmap = RotateWriteableBitmap(croppedBlobBitmap, blobAngle);
var rotatedGradientBlobBitmap = RotateColorWriteableBitmap(croppedGradientBlobBitmap, blobAngle);
var rotatedRealBitmapRef = RotateColorWriteableBitmap(croppedRealBitmapRef, blobAngle);
var refinedBitmap = DrawBlobBoundingBoxsAroundCroppedBitmap(rotatedandCroppedBlobBitmap, rotatedGradientBlobBitmap, rotatedRealBitmapRef, 1);
rotatedGradientBlobBitmap = DrawBlobBoundingBoxsAroundCroppedBitmap(rotatedandCroppedBlobBitmap, rotatedGradientBlobBitmap, rotatedRealBitmapRef, 2);
rotatedRealBitmapRef = DrawBlobBoundingBoxsAroundCroppedBitmap(rotatedandCroppedBlobBitmap, rotatedGradientBlobBitmap, rotatedRealBitmapRef, 3);
var areaCheck = refinedBitmap.PixelHeight*refinedBitmap.PixelWidth;
if (areaCheck >= 200)
{
blobNumber++;
var thresholded = refinedBitmap.Clone();
ThresholdBitmap(thresholded, 10, false);
BitmapColorer.ColorBitmap(thresholded);
System.Windows.Media.Color blobColor = PixelColorOfCentralBlob(thresholded);
BitmapColorer.EraseAllButCertainColorandWhite(thresholded, blobColor);
var shouldFlip = shouldFlipThresholdedBitmap(thresholded, blobColor);
if (shouldFlip)
{
thresholded = thresholded.Rotate(180);
rotatedGradientBlobBitmap = rotatedGradientBlobBitmap.Rotate(180);
rotatedRealBitmapRef = rotatedRealBitmapRef.Rotate(180);
}
var orientedBitmap = NormalizeBitmapSize(thresholded);
var orientedGradientBitmap = NormalizeBitmapSize(rotatedGradientBlobBitmap);
var orientedRealBitmap = NormalizeBitmapSize(rotatedRealBitmapRef);
ApplyBlobMaskToOtherBitmaps(orientedBitmap, orientedGradientBitmap, orientedRealBitmap, blobColor);
string fileName1 = saveDirectory + "\\croppedBlob" + blobNumber + ".png";
ExtensionMethods.Save(orientedRealBitmap, fileName1);
}
}
}
}
return writeableBitmap;
}
public static WriteableBitmap DrawBlobBoundingBoxsAroundCroppedBitmap(WriteableBitmap writeableBitmap,
WriteableBitmap gradientBitmapRef, WriteableBitmap realBitmapRef, int returnBitmapIndex)
{
Bitmap normalBitmap = BitmapFromWriteableBitmap(writeableBitmap);
var cvImage = new Image<Gray, byte>(new Bitmap(normalBitmap));
if (cvImage != null)
{
Image<Gray, byte> greyImg = cvImage.Convert<Gray, byte>();
Image<Gray, Byte> greyThreshImg = greyImg.ThresholdBinaryInv(new Gray(150), new Gray(255));
Emgu.CV.Cvb.CvBlobs resultingImgBlobs = new Emgu.CV.Cvb.CvBlobs();
Emgu.CV.Cvb.CvBlobDetector bDetect = new Emgu.CV.Cvb.CvBlobDetector();
uint numWebcamBlobsFound = bDetect.Detect(greyThreshImg, resultingImgBlobs);
Image<Rgb, byte> blobImg = greyThreshImg.Convert<Rgb, byte>();
Rgb red = new Rgb(255, 0, 0);
int blobNumber = 0;
foreach (Emgu.CV.Cvb.CvBlob targetBlob in resultingImgBlobs.Values)
{
int imageArea = blobImg.Width*blobImg.Height;
int blobArea = targetBlob.Area;
int blobBoundingBoxArea = targetBlob.BoundingBox.Width*targetBlob.BoundingBox.Height;
if (blobArea > 200.0 && blobBoundingBoxArea < (imageArea*0.99))
{
blobNumber++;
Rectangle rectangle = targetBlob.BoundingBox;
Rect convertedRect = new Rect(rectangle.X - 10, rectangle.Y - 10, rectangle.Width + 20,
rectangle.Height + 20);
//BitmapColorer.DrawRectangle(writeableBitmap, convertedRect);
writeableBitmap = writeableBitmap.Crop(rectangle.X - 10, rectangle.Y - 10, rectangle.Width + 20,
rectangle.Height + 20);
gradientBitmapRef = gradientBitmapRef.Crop(rectangle.X - 10, rectangle.Y - 10,
rectangle.Width + 20, rectangle.Height + 20);
realBitmapRef = realBitmapRef.Crop(rectangle.X - 10, rectangle.Y - 10, rectangle.Width + 20,
rectangle.Height + 20);
}
}
}
if (returnBitmapIndex == 1)
{
return writeableBitmap;
}
else if (returnBitmapIndex == 2)
{
return gradientBitmapRef;
}
else
{
return realBitmapRef;
}
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Image <Bgr, Byte> ImageFrame = frame.ToImage <Bgr, Byte>();
long matchTime;
Mat result = new Mat();
Mat mask = new Mat();
Mat homography = new Mat();
Rectangle personROI = new Rectangle();
Mat modelImage = new Mat();
Mat observedImage = new Mat();
Rectangle roi = new Rectangle(213, 0, 213, 480); // set the roi image.ROI = new Rectangle(x, Y, Width, Height);
//ImageFrame.ROI = roi;
ImageFrame.Draw(roi, new Bgr(Color.Green), 5);
if (ImageFrame != null) // confirm that image is valid
{
Rectangle[] results = FindPedestrian.Find(frame, true, out processingTime);
if (people.Count == 0)
{
foreach (Rectangle rect in results)
{
if (rect.Width >= 150)
{
personROI.X = rect.X;
personROI.Y = rect.Y;
personROI.Width = rect.Width;
personROI.Height = rect.Height;
Mat person = new Mat(frame, personROI);
people.Add(person);
ImageFrame.Draw(rect, new Bgr(Color.Red), 5);
//Console.WriteLine(index);
}
}
}
else
{
foreach (Rectangle rect in results)
{
ImageFrame.Draw(rect, new Bgr(Color.Red), 5);
var check = false;
var temp = new List <Mat>(people);
foreach (Mat aperson in people)
{
Mat img = new Mat(frame, rect);
observedImage = aperson;
modelImage = img;
result = Draw(modelImage, observedImage, out matchTime, out check);
if (!check)
{
temp.Add(img);
++counter;
Console.WriteLine("Counter: " + counter);
break;
}
}
people = new List <Mat>(temp);
Console.WriteLine("End for frame processing");
}
}
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
//_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(1000, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//CvInvoke.PutText(frame, blob.ID.ToString(), Point.Round(blob.Center), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = ImageFrame;
//Console.WriteLine(ImageFrame.Size);
imageBox2.Image = result;
//imageBox2.Image = forgroundMask;
}
//people.Clear();
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
IImage image = (IImage)frame;//这一步是重点
faceImage = frame.Bitmap;
DetectFace.Detect(image
, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
#region 多人识别
Graphics g1 = Graphics.FromImage(frame.Bitmap);
List <FaceIdentifyModel> tempList = new List <FaceIdentifyModel>();
foreach (Rectangle face in faces)
{
Image rectImage1 = ImageHelper.CaptureImage(frame.Bitmap, face);// 自己封装的方法，通过大图截取矩形框的人脸图片，返回Image 对象
FaceIdentifyModel MoreIdentifyInfo = FaceAPI.FaceIdentify(rectImage1, tb_Group.Text.Trim(), 1, 1);
MoreIdentifyInfo.rect = face;
tempList.Add(MoreIdentifyInfo);
}
Color color_of_pen1 = Color.Gray;
color_of_pen1 = Color.Yellow;
Pen pen1 = new Pen(color_of_pen1, 2.0f);
Font font1 = new Font("微软雅黑", 16, GraphicsUnit.Pixel);
SolidBrush drawBrush1 = new SolidBrush(Color.Yellow);
tb_Identify.Text = tempList.ToJson();
foreach (var t in tempList)
{
g1.DrawRectangle(pen1, t.rect);
if (t.result != null)
{
g1.DrawString(t.result[0].user_info.Replace("，", "\r\n"), font1, drawBrush1, new Point(t.rect.X + 20, t.rect.Y - 20));
}
125
}
#endregion
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}