private Mat detectFace(Mat image)
{
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
bool tryUseCuda = true;
DetectFace.Detect(image, "haarcascade_frontalface_default.xml", faces, tryUseCuda, out detectionTime);
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
return(image);
}
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
}
