public override void Process(Image <Bgr, byte> image, out Image <Bgr, byte> annotatedImage, out List <object> data)
{
base.Process(image, out annotatedImage, out data);
// apply the current image to the foreground mask
_subtractor.Apply(image, _foregroundMask);
// add the mask to the motion history
_motionHistory.Update(_foregroundMask);
// selector for desired image to be viewed
switch (_bgSubImageType)
{
case BgSubImageType.FgMask:
annotatedImage = _foregroundMask.ToImage <Bgr, byte>();
break;
case BgSubImageType.Background:
_subtractor.GetBackgroundImage(annotatedImage);
break;
default:
data = new List <object>();
DrawMotion(ref annotatedImage, ref data);
break;
}
}
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;
}
void frame(object sender, EventArgs e)//捕捉帧进行线程函数
{
double sum_pix = 0;
double angle = 0;
VectorOfRect rects = new VectorOfRect(); //创建VectorOfRect存储运动矩形。
Mat _segMask = new Mat(); //创建背景蒙版图片。
_capture.Retrieve(scr); //获取帧数据。
// CvInvoke.Resize(scr, scr, new Size(320, 480));
_motionDetect.Apply(scr, mask); //进行运动检测。
CvInvoke.MedianBlur(mask, mask, 5); //中值滤波。
_motionhistory.Update(mask); //更新背景图片。
_motionhistory.GetMotionComponents(_segMask, rects); //获取背景蒙版及运动矩形。
for (int j = 0; j < rects.ToArray().Length; j++) //遍历所有运动矩形。
{
if (rects[j].Width * rects[j].Height > 1000) //删除一些较小的矩形采用面积的方式。
{
CvInvoke.Rectangle(scr, rects[j], new MCvScalar(0, 0, 255)); //在scr图像总绘制运动矩形。
_motionhistory.MotionInfo(_segMask, rects[j], out angle, out sum_pix); //指定矩阵获取运动的角度和像素值。
CvInvoke.PutText(scr, "angle : " + (int)angle, rects[j].Location, Emgu.CV.CvEnum.FontFace.HersheyComplex, 0.5, new MCvScalar(0, 255, 0)); //绘制运动的角度。
}
}
imageBox1.Image = drar_rect(scr);
// imageBox1.Image = scr;//显示图像。
imageBox2.Image = mask;//显示运动检测输出图像。
}
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));
}
//imageBox11.Image = null;
//imageBox12.Image = null;
imageBox11.Image = frame;
imageBox12.Image = forgroundMask;
}
private void ProcImage3(ref System.Drawing.Bitmap src, ref System.Drawing.Bitmap srcB, out System.Drawing.Bitmap dst)
{
dst = null;
Mat srcImg = BitmapConverter.ToMat(src);
Cv2.CvtColor(srcImg, srcImg, ColorConversionCodes.BGRA2BGR);
Mat srcImgB = BitmapConverter.ToMat(srcB);
Cv2.CvtColor(srcImgB, srcImgB, ColorConversionCodes.BGRA2BGR);
Mat mask = new Mat();
double threshold = App.appSettings.DarkAreaThreshold;
BackgroundSubtractor backSub = BackgroundSubtractorMOG2.Create(1, threshold, true);
//BackgroundSubtractor backSub = BackgroundSubtractorMOG.Create(1, 5, 0.7, 0);
//BackgroundSubtractor backSub = BackgroundSubtractorGMG.Create(1, 0.5);
backSub.Apply(srcImgB, mask, 1);
backSub.Apply(srcImg, mask, 0);
Cv2.Threshold(mask, mask, 180, 255, ThresholdTypes.Binary);
var element = Cv2.GetStructuringElement(
MorphShapes.Rect,
new OpenCvSharp.Size(2 * 2 + 1, 2 * 2 + 1),
new OpenCvSharp.Point(2, 2));
Mat tmp = new Mat();
Cv2.MorphologyEx(mask, tmp, MorphTypes.Close, element, null, App.appSettings.Iterations);
Cv2.MorphologyEx(tmp, mask, MorphTypes.Open, element, null, App.appSettings.Iterations2);
Cv2.Erode(mask, tmp, element);
dst = BitmapConverter.ToBitmap(tmp);
}
/// <summary>
/// Updates motion history with current image
/// </summary>
private void UpdateMotionHistory()
{
if (_currentImage != null)
{
Image <Gray, byte> image;
using (image = _currentImage.Clone())
{
image = Prepare(image);
ComputerVisionMonitors[eComputerVisionMonitor.MonitorC].ShowFrame(image);
Mat motion = new Mat();
motion = image.Mat;
_forgroundDetector.Apply(motion, _foreground);
_motionHistory.Update(_foreground);
}
}
}
public CameraTrackingUpdateReturnModel Update()
{
// capture frame
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(FrameBlurStrength, FrameBlurStrength), 1); //filter out noises
// get mask for preview
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
LastFrame = frame;
LastMask = forgroundMask;
return(new CameraTrackingUpdateReturnModel()
{
Frame = frame,
Mask = forgroundMask
});
}
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;
}
private bool testDiff()
{
if (_forgroundDetector == null)
{
//Emgu.CV.O
_forgroundDetector = new BackgroundSubtractorMOG2(20, 16f, true);
}
bool result = false;
using (Mat _forgroundMask = new Mat())
{
if (nextFrame != null)
{
_forgroundDetector.Apply(nextFrame, _forgroundMask);
}
else
{
return
(false);
}
decimal backGroundCounter = 0;
decimal whiteColorCounter = 0;
//double delta = 0.01;
decimal deltaCounter = this.numUpDown_Sens.Value;
decimal whitePixelsSettings = this.numUpDown_WhitePixels.Value;
int colorLimit = 200;
using (Bitmap img = _forgroundMask.Bitmap)
{
using (Bitmap origImg = nextFrame.Bitmap)
{
curSearchResult.RGBprofile = "";
curSearchResult.RGBprofileXY = "";
foreach (Rectangle Rect in ListRect)
{
for (int i = 0; i < Rect.Height; ++i)
{
for (int j = 0; j < Rect.Width; ++j)
{
//if (_forgroundMask.Bitmap.GetPixel(Rect.X + j, Rect.Y + i).GetBrightness() > delta)
if (img.GetPixel(Rect.X + j, Rect.Y + i).ToArgb() != -16777216)
{
backGroundCounter++;
if (origImg.GetPixel(Rect.X + j, Rect.Y + i).R > colorLimit &&
origImg.GetPixel(Rect.X + j, Rect.Y + i).G > colorLimit &&
origImg.GetPixel(Rect.X + j, Rect.Y + i).B > colorLimit
)
{
whiteColorCounter++;
curSearchResult.RGBprofile += string.Format("(R={0},G={1},B={2})|",
origImg.GetPixel(Rect.X + j, Rect.Y + i).R,
origImg.GetPixel(Rect.X + j, Rect.Y + i).G,
origImg.GetPixel(Rect.X + j, Rect.Y + i).B);
curSearchResult.RGBprofileXY += string.Format("(X={0},Y={1})|", Rect.X + j, Rect.Y + i);
}
}
}
}
}
}
}
if (backGroundCounter > deltaCounter && whiteColorCounter > whitePixelsSettings)
{
result = true;
if (!b_AutoRun)
{
pictureBox2.Image = _forgroundMask.Bitmap.Clone() as Bitmap;
pictureBox2.Refresh();
}
curSearchResult.backGroundCounter = backGroundCounter;
curSearchResult.frameNumber = this.frameNum;
curSearchResult.whiteColorCounter = whiteColorCounter;
}
_forgroundMask.Dispose();
}
return(result);
}
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;
}
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;
}
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;
}
private void ProcessFrame(object sender, EventArgs e)
{
Mat image = new Mat();
_capture.Retrieve(image);
if (_forgroundDetector == null)
{
_forgroundDetector = new BackgroundSubtractorMOG2();
}
_forgroundDetector.Apply(image, _forgroundMask);
capturedImageBox.Image = image;
//update the motion history
_motionHistory.Update(_forgroundMask);
foreground.Image = _forgroundMask;
#region get a copy of the motion mask and enhance its color
double[] minValues, maxValues;
Point[] minLoc, maxLoc;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
Mat motionMask = new Mat();
using (ScalarArray sa = new ScalarArray(255.0 / maxValues[0]))
CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
//Image<Gray, Byte> motionMask = _motionHistory.Mask.Mul(255.0 / maxValues[0]);
#endregion
//create the motion image
// Image<Bgr, Byte> motionImage = new Image<Bgr, byte>(motionMask.Size);
//display the motion pixels in blue (first channel)
//motionImage[0] = motionMask;
// CvInvoke.InsertChannel(motionMask, motionImage, 0);
//Threshold to define a motion area, reduce the value to detect smaller motion
// double minArea = 100;
//storage.Clear(); //clear the storage
Rectangle[] rects;
using (VectorOfRect boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(_segMask, boundingRect);
rects = boundingRect.ToArray();
}
//iterate through each of the motion component
foreach (Rectangle comp in rects)
{
time.Start();
// find the angle and motion pixel count of the specific area
double angle, motionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
if (Main.security.Text == "SECURITY MODE ON")
{
long x = time.ElapsedMilliseconds;
if (x > ellapsed_time)
{
if (motionPixelCount > pixel_count)
{
//MessageBox.Show("My message here");
Console.Beep(5000, 1000);
if (Main.connected == true)
{
chat.send(Encoding.ASCII.GetBytes("Someone is in the room"));
}
break;
time.Stop();
}
}
}
}
}
private void ProcessFrame(object sender, EventArgs e)
{
Mat image = new Mat();
_capture.Retrieve(image);
if (_forgroundDetector == null)
{
_forgroundDetector = new BackgroundSubtractorMOG2();
}
_forgroundDetector.Apply(image, _forgroundMask);
//update the motion history
_motionHistory.Update(_forgroundMask);
#region get a copy of the motion mask and enhance its color
double[] minValues, maxValues;
Point[] minLoc, maxLoc;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
Mat motionMask = new Mat();
using (ScalarArray sa = new ScalarArray(255.0 / maxValues[0]))
CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
//Image<Gray, Byte> motionMask = _motionHistory.Mask.Mul(255.0 / maxValues[0]);
#endregion
//DetectFace.Detect(image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml", faces, eyes, tryUseCuda, out detectionTime);
//create the motion image
Mat motionImage = new Mat(motionMask.Size.Height, motionMask.Size.Width, DepthType.Cv8U, 3);
//display the motion pixels in blue (first channel)
//motionImage[0] = motionMask;
CvInvoke.InsertChannel(motionMask, motionImage, 0);
//Threshold to define a motion area, reduce the value to detect smaller motion
double minArea = 100;
//storage.Clear(); //clear the storage
Rectangle[] rects;
using (VectorOfRect boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(_segMask, boundingRect);
rects = boundingRect.ToArray();
}
List <Rectangle> Availablerects = new List <Rectangle>();
foreach (Rectangle comp in rects)
{
int area = comp.Width * comp.Height;
//reject the components that have small area;
if (area < minArea)
{
continue;
}
double angle, motionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
//reject the area that contains too few motion
if (motionPixelCount < area * size)
{
continue;
}
else
{
Availablerects.Add(comp);
}
}
//iterate through each of the motion component
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
Task task2 = new Task(() =>
{
Mat Detectmat = new Mat();
Detectmat = image;
DetectFace.Detect(Detectmat, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml", faces, eyes, tryUseCuda, out detectionTime);
if (faces.Count > 0)
{
label1.Text = "detectionTime:" + detectionTime.ToString();
for (int i = 0; i < faces.Count; i++)
{
Bitmap bt2 = DetectFace.Cutbitmap(Detectmat.Bitmap, faces[i].X, faces[i].Y, faces[i].Width, faces[i].Height);
Emgu.CV.Image <Bgr, Byte> currentFrame1 = new Emgu.CV.Image <Bgr, Byte>(bt2); //只能这么转
Mat invert1 = new Mat();
CvInvoke.BitwiseAnd(currentFrame1, currentFrame1, invert1); //这是官网上的方法，变通用。没看到提供其它方法直接转换的。
faceimage.Image = invert1;
string filePath = "G:\\motion1\\" + DateTime.Now.ToString("人脸-yyyy年MM月dd日HH点mm分ss秒") + i.ToString() + "-" + faces.Count.ToString() + ".jpg";
bt2.Save(filePath);
System.Media.SystemSounds.Beep.Play();
}
Bitmap bt1 = Detectmat.Bitmap;
string filePath2 = "G:\\motion1\\" + DateTime.Now.ToString("原图-yyyy年MM月dd日HH点mm分ss秒") + ".jpg";
//System.Diagnostics.Debug.WriteLine("准备保存原图" + detectionTime.ToString());
bt1.Save(filePath2);
}
});
task2.Start();
foreach (Rectangle comp in Availablerects)
{
int area = comp.Width * comp.Height;
//reject the components that have small area;
if (area < minArea)
{
continue;
}
// find the angle and motion pixel count of the specific area
double angle, motionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
//reject the area that contains too few motion
if (motionPixelCount < area * size)
{
continue;
}
//Draw each individual motion in red
//=================转换mat格式为bitmap并裁切===========================
Task task = new Task(() =>
{
Bitmap bt = DetectFace.Cutbitmap(image.Bitmap, comp.X, comp.Y, comp.Width, comp.Height);
Emgu.CV.Image <Bgr, Byte> currentFrame = new Emgu.CV.Image <Bgr, Byte>(bt); //只能这么转
Mat invert = new Mat();
CvInvoke.BitwiseAnd(currentFrame, currentFrame, invert); //这是官网上的方法，变通用。没看到提供其它方法直接转换的。
moveimage.Image = invert;
});
task.Start();
try
{
DrawMotion(motionImage, comp, angle, new Bgr(Color.Red));
DrawMotion(capturedImageBox.Image, comp, angle, new Bgr(Color.Red));
}
catch (Exception a)
{
}
#region//area
/*
* bool time = false;
* if ((comp.X > 1770 && comp.X < 1830) && (comp.Y > 2 && comp.Y < 40))
* {
* time = true;
* }
* if (youxiaorects.Count < 50&&!time)
* {
* if (capturedImageBox.Image != null)
* {
* Random rd = new Random();
* Bitmap bt = new Bitmap(capturedImageBox.Image.Bitmap);
* // string filePath = "G:\\motion\\" + DateTime.Now.ToString("yyyy年MM月dd日HH点mm分ss秒") + ".jpg";
* // image.Save(filePath);
*
* }
* }
*/
#endregion
}
#region//垃圾堆
//=================当检测到图像更变，获取更变区域坐标与大小时，尝试将更变区域保存 传入人脸识别函数分析=====================
//===============根据更变区域个数来动态创建线程，增加效率======================
/* Thread[] downloadThread;
* Thread face=new Thread(confirmface);
* face.Start();*/
/* int areacount = Availablerects.Count;
* //声名下载线程，这是C#的优势，即数组初始化时，不需要指定其长度，可以在使用时才指定。
*
* //这个声名应为类级，这样也就为其它方法控件它们提供了可能
*
* ThreadStart startDownload = new ThreadStart(confirmface);
* //线程起始设置：即每个线程都执行DownLoad()
* downloadThread = new Thread[areacount];//为线程申请资源，确定线程总数
* for (int k = 0; k < areacount; k++)//开启指定数量的线程数
* {
* downloadThread[k] = new Thread(startDownload);//指定线程起始设置
* downloadThread[k].Start();//逐个开启线程
* }*/
#endregion
#region//_forgroundMask
/*
* // find and draw the overall motion angle
* double overallAngle, overallMotionPixelCount;
*
* _motionHistory.MotionInfo(_forgroundMask, new Rectangle(Point.Empty, motionMask.Size), out overallAngle, out overallMotionPixelCount);
* // DrawMotion(motionImage, new Rectangle(Point.Empty, motionMask.Size), overallAngle, new Bgr(Color.Green));
* // DrawMotion(image, new Rectangle(Point.Empty, image.Size), overallAngle, new Bgr(Color.Green));
* if (this.Disposing || this.IsDisposed)
* return;
*/
/* foreach (Rectangle face in faces)
* CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
* foreach (Rectangle eye in eyes)
* CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);*/
capturedImageBox.Image = image;
// forgroundImageBox.Image = _forgroundMask;
//Display the amount of motions found on the current image
//UpdateText(String.Format("Total Motions found: {0}; Motion Pixel count: {1} detectionTime:{2} ", rects.Length, overallMotionPixelCount, detectionTime));
//Display the image of the motion
// motionImageBox.Image = motionImage;
#endregion
}
private void ProcessFrame(object sender, EventArgs e)
{
Mat image = new Mat();
_capture.Retrieve(image);
if (_forgroundDetector == null)
{
_forgroundDetector = new BackgroundSubtractorMOG2();
}
_forgroundDetector.Apply(image, _forgroundMask);
//update the motion history
_motionHistory.Update(_forgroundMask);
#region get a copy of the motion mask and enhance its color
double[] minValues, maxValues;
Point[] minLoc, maxLoc;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
Mat motionMask = new Mat();
using (ScalarArray sa = new ScalarArray(255.0 / maxValues[0]))
CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
//Image<Gray, Byte> motionMask = _motionHistory.Mask.Mul(255.0 / maxValues[0]);
#endregion
//create the motion image
Mat motionImage = new Mat(motionMask.Size.Height, motionMask.Size.Width, DepthType.Cv8U, 3);
//display the motion pixels in blue (first channel)
//motionImage[0] = motionMask;
CvInvoke.InsertChannel(motionMask, motionImage, 0);
//Threshold to define a motion area, reduce the value to detect smaller motion
double minArea = 100;
//storage.Clear(); //clear the storage
Rectangle[] rects;
using (VectorOfRect boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(_segMask, boundingRect);
rects = boundingRect.ToArray();
}
//iterate through each of the motion component
foreach (Rectangle comp in rects)
{
int area = comp.Width * comp.Height;
//reject the components that have small area;
if (area < minArea)
{
continue;
}
// find the angle and motion pixel count of the specific area
double angle, motionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
//reject the area that contains too few motion
if (motionPixelCount < area * 0.05)
{
continue;
}
//Draw each individual motion in red
DrawMotion(motionImage, comp, angle, new Bgr(Color.Red));
}
// find and draw the overall motion angle
double overallAngle, overallMotionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, new Rectangle(Point.Empty, motionMask.Size), out overallAngle, out overallMotionPixelCount);
DrawMotion(motionImage, new Rectangle(Point.Empty, motionMask.Size), overallAngle, new Bgr(Color.Green));
if (this.Disposing || this.IsDisposed)
{
return;
}
capturedImageBox.Image = image;
forgroundImageBox.Image = _forgroundMask;
//Display the amount of motions found on the current image
UpdateText(String.Format("Total Motions found: {0}; Motion Pixel count: {1}", rects.Length, overallMotionPixelCount));
//Display the image of the motion
motionImageBox.Image = motionImage;
}
public List <IImage> ProcessFrame(IImage original)
{
List <IImage> processedImages = new List <IImage>();
Mat foregroundBlobs = new Mat();
Mat motionMask = new Mat();
Mat segmentMask = new Mat();
//threshold to define the minimum motion area
double minArea = AdjustableParameters["MinMotionArea"].CurrentValue;
//threshold to define the minimun motion 1/20th of the size of the bounding blob
double minMotion = AdjustableParameters["MinMotionDistance"].CurrentValue;
Rectangle[] motionComponents;
_backgroundSubtractor.Apply(original, foregroundBlobs);
//update the motion-history
_motionHistory.Update(foregroundBlobs);
//Get a copy of the mask and enhance its color
double[] minValues, maxValues;
Point[] minLocation, maxLocation;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLocation, out maxLocation);
//Mutiply the copy by a scalar array outputs motionMask
using (ScalarArray myScalar = new ScalarArray(255.0 / maxValues[0]))
CvInvoke.Multiply(_motionHistory.Mask, myScalar, motionMask, 1, Emgu.CV.CvEnum.DepthType.Cv8U);
//Create the motion image
Mat motionImage = new Mat(motionMask.Size.Height, motionMask.Size.Width, Emgu.CV.CvEnum.DepthType.Cv8U, 3);
motionImage.SetTo(new MCvScalar(0));
//Insert the motion mask into the blue channel of the motionImage
CvInvoke.InsertChannel(motionMask, motionImage, 0);
//Get the motion components
using (VectorOfRect boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(segmentMask, boundingRect);
motionComponents = boundingRect.ToArray();
}
//Loop through the motion components
foreach (Rectangle component in motionComponents)
{
int area = component.Width * component.Height;
//reject components that are smaller that the threshold
if (area < minArea)
{
continue;
}
//find angle and pixel count for the motionComponent
double angle, pixelCount;
_motionHistory.MotionInfo(foregroundBlobs, component, out angle, out pixelCount);
//reject component of motion pixel count is less than the min threshold
if (pixelCount < area * minMotion)
{
continue;
}
//draw motions in red
DrawMotion(motionImage, component, angle, new Bgr(Color.Red));
}
// find and draw the overall motion angle
double overallAngle, overallMotionPixelCount;
_motionHistory.MotionInfo(foregroundBlobs, new Rectangle(Point.Empty, motionMask.Size), out overallAngle, out overallMotionPixelCount);
DrawMotion(motionImage, new Rectangle(Point.Empty, motionMask.Size), overallAngle, new Bgr(Color.Green));
processedImages.Add(foregroundBlobs);
processedImages.Add(motionImage);
processedImages.Add(segmentMask);
return(processedImages);
}
protected override MotionDetectorOutput DoProcess(MotionDetectorInput input)
{
var output = new MotionDetectorOutput();
var subtractorConfig = input.Settings.SubtractorConfig;
if (_foregroundDetector == null || !_currentSubtractorConfig.Equals(subtractorConfig))
{
if (_foregroundDetector != null)
{
_foregroundDetector.Dispose();
}
_foregroundDetector = new BackgroundSubtractorMOG2(
subtractorConfig.History
, subtractorConfig.Threshold
, subtractorConfig.ShadowDetection);
_currentSubtractorConfig = subtractorConfig;
}
_foregroundDetector.Apply(input.Captured, _forgroundMask);
_motionHistory.Update(_forgroundMask);
#region get a copy of the motion mask and enhance its color
double[] minValues, maxValues;
Point[] minLoc, maxLoc;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
var motionMask = new Mat();
using (var sa = new ScalarArray(255.0 / maxValues[0]))
{
CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
}
#endregion
if (input.SetCapturedImage)
{
output.ForegroundImage = _forgroundMask.ToImage <Bgr, byte>();
output.MotionImage = new Image <Bgr, byte>(motionMask.Size);
CvInvoke.InsertChannel(motionMask, output.MotionImage, 0);
}
Rectangle[] motionComponents;
using (var boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(_segMask, boundingRect);
motionComponents = boundingRect.ToArray();
}
foreach (Rectangle motionComponent in motionComponents)
{
int area = motionComponent.Area();
//reject the components that have small area;
if (area < input.Settings.MinimumArea || area > input.Settings.MaximumArea)
{
continue;
}
// find the angle and motion pixel count of the specific area
double angle, motionPixelCountDouble;
_motionHistory.MotionInfo(_forgroundMask, motionComponent, out angle, out motionPixelCountDouble);
int motionPixelCount = (int)motionPixelCountDouble;
//reject the area that contains too few motion
if (motionPixelCount < area * input.Settings.MinimumPercentMotionInArea)
{
continue;
}
var motionSection = new MotionSection();
motionSection.Area = area;
motionSection.Region = motionComponent;
motionSection.Angle = angle;
motionSection.PixelsInMotionCount = motionPixelCount;
output.MotionSections.Add(motionSection);
}
if (output.IsDetected)
{
switch (input.Settings.BiggestMotionType)
{
case BiggestMotionType.Unspecified:
break;
case BiggestMotionType.Area:
output.MotionSections.Sort((x, y) => y.Area.CompareTo(x.Area));
break;
case BiggestMotionType.Pixels:
output.MotionSections.Sort((x, y) => y.PixelsInMotionCount.CompareTo(x.PixelsInMotionCount));
break;
}
output.BiggestMotion = output.MotionSections.FirstOrDefault();
}
double overallAngle, overallMotionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, new Rectangle(Point.Empty, motionMask.Size), out overallAngle, out overallMotionPixelCount);
output.OverallAngle = overallAngle;
output.OverallMotionPixelCount = Convert.ToInt32(overallMotionPixelCount);
return(output);
}
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();
}
}
}
