public mouse()
{
InitializeComponent();
//CvInvoke.UseOpenCL = false;
while (global.capture == null)
{
}
try
{
capture = global.capture; //new Capture();
// capture = new Capture();
//if (capture != null) capture.FlipHorizontal = !capture.FlipHorizontal;
capture.ImageGrabbed += ProcessFrame;
}
catch (NullReferenceException excpt)
{
MessageBox.Show(excpt.Message);
}
// MessageBox.Show("" + Screen.PrimaryScreen.Bounds + " __ " + capture.Width + " " + capture.Height);
fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2();
blobDetector = new Emgu.CV.Cvb.CvBlobDetector();
cursor_history_x = new Queue <int>();
cursor_history_y = new Queue <int>();
//initilize queue with initial
for (int i = 0; i < queue_cursor_length; i++)
{
cursor_history_x.Enqueue(Screen.PrimaryScreen.Bounds.Width / 2);
cursor_history_y.Enqueue(Screen.PrimaryScreen.Bounds.Height / 2);
}
}
public gesture()
{
InitializeComponent();
fow_prop = new gesture_recog();
fow_prop.Show();
//CvInvoke.UseOpenCL = false;
try
{
grabber = global.capture;
}
catch (NullReferenceException excpt)
{
MessageBox.Show(excpt.Message);
}
grabber.QueryFrame();
frameWidth = grabber.Width;
frameHeight = grabber.Height;
// detector = new AdaptiveSkinDetector(1, AdaptiveSkinDetector.MorphingMethod.NONE);
hsv_min = new Hsv(0, 45, 0);
hsv_max = new Hsv(20, 254, 254);
// YCrCb_min = new Ycc(0, 131, 80);
//YCrCb_max = new Ycc(255, 185, 135);
YCrCb_min = new Ycc(0, 130, 80);
YCrCb_max = new Ycc(255, 185, 135);
index = 0;
for (int i = 0; i < 10; i++)
{
na[i] = 1;
}
fgDetector = new BackgroundSubtractorMOG2();
blobDetector = new Emgu.CV.Cvb.CvBlobDetector();
Application.Idle += new EventHandler(FrameGrabber);
}
public JavsMotion()
{
AdjustableParameters = new Dictionary <string, ParameterProfile>();
AdjustableParameters["MinMotionArea"] = new ParameterProfile
{
Description = "Minimum Motion Size Threshold",
MaxValue = 1000,
MinValue = 5,
CurrentValue = 100,
Interval = 1
};
AdjustableParameters["MinMotionDistance"] = new ParameterProfile
{
Description = "Minimum Motion Distance Threshold",
MaxValue = 1,
MinValue = 0.005,
CurrentValue = 0.05,
Interval = 0.005
};
//Try out various background subtractors
_backgroundSubtractor = new BackgroundSubtractorMOG2();
//Can the parameters taken by this constructor be adjusted during capture?
_motionHistory = new MotionHistory(
1.0, //in second, the duration of motion history you wants to keep
0.05, //in second, maxDelta for cvCalcMotionGradient
0.5); //in second, minDelta for cvCalcMotionGradient
}
public CameraTracking(int subtractionHistory, int subtractionThreshold, int frameBlurStrength, int largestDetectionHeightSizeDivisor, int largestDetectionWidthSizeDivisor, int smallestDetectionHeightSizeDivisor, int smallestDetectionWidthSizeDivisor)
{
FrameBlurStrength = frameBlurStrength;
LargestDetectionHeightSizeDivisor = largestDetectionHeightSizeDivisor;
LargestDetectionWidthSizeDivisor = largestDetectionWidthSizeDivisor;
SmallestDetectionHeightSizeDivisor = smallestDetectionHeightSizeDivisor;
SmallestDetectionWidthSizeDivisor = smallestDetectionWidthSizeDivisor;
try
{
_cameraCapture = new VideoCapture();
// I had to set this by hand to match our camera as opencv doesn't always pull these properties correctly and sometimes shows funky frames or nothing at all
// _cameraCapture.SetCaptureProperty(CapProp.FrameWidth, 1600);
// _cameraCapture.SetCaptureProperty(CapProp.FrameHeight, 1200);
// _cameraCapture.SetCaptureProperty(CapProp.FourCC, Emgu.CV.VideoWriter.Fourcc('Y', 'U', 'Y', '2'));
_fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2(subtractionHistory, subtractionThreshold);
_blobDetector = new CvBlobDetector();
_tracker = new CvTracks();
Ready = true;
}
catch (Exception e)
{
Ready = false;
}
}
public Detector()
{
cascade = new CascadeClassifier(@"../cascade/cars.xml");
dScaleFactor = 1.1;
uMinNeighbors = 2;
minSize = new Size(100, 100);
this.bckSub = BackgroundSubtractorKNN.Create();
this.fgMask = new Mat();
this.kernel1 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
this.kernel2 = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
}
/// <summary>
/// Motion Detector Constructor
/// </summary>
/// <param name="imagingData">Common Image Processing Imaging Data</param>
public MotionDetector(IImageData imagingData)
{
ImagingData = imagingData;
//Set values for properties
MinMotionAreaThreshold = DEFAULT_MIN_MOTION_AREA_THRESHOLD;
MinMotionPixelFactor = DEFAULT_MIN_MOTION_PIXEL_FACTOR;
GrayThreshold = DEFAULT_GRAY_THRESHOLD;
//Instantiate private members
_motionHistory = new MotionHistory(MOTION_HISTORY_DURATION, MOTION_HISTORY_MAX_DELTA, MOTION_HISTORY_MIN_DELTA);
_forgroundDetector = new BackgroundSubtractorMOG2();
_segMask = new Mat();
_foreground = new Mat();
ComputerVisionMonitors = new Dictionary <eComputerVisionMonitor, IComputerVisionMonitor>();
}
void Run()
{
try
{
_cameraCapture = new VideoCapture(1);
_fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2();
_blobDetector = new CvBlobDetector();
_tracker = new CvTracks();
Application.Idle += ProcessFrame;
}
catch (Exception e)
{
}
}
public camera()
{
InitializeComponent();
CvInvoke.UseOpenCL = false;
try
{
capture = global.capture;
capture.ImageGrabbed += ProcessFrame;
}
catch (NullReferenceException excpt)
{
MessageBox.Show(excpt.Message);
}
fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2();
blobDetector = new Emgu.CV.Cvb.CvBlobDetector();
}
void Run()
{
try
{
_cameraCapture = new Capture();
}
catch (Exception e)
{
MessageBox.Show(e.Message);
return;
}
_fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2();
_blobDetector = new CvBlobDetector();
//_tracker = new BlobTrackerAuto<Bgr>();
Application.Idle += ProcessFrame;
}
void Run()
{
try
{
_cameraCapture = new VideoCapture();
}
catch (Exception e)
{
MessageBox.Show(e.Message);
return;
}
_fgDetector = new BackgroundSubtractorMOG2();
_blobDetector = new CvBlobDetector();
_tracker = new CvTracks();
Application.Idle += ProcessFrame;
}
static void Main(string[] args)
{
if (args.Length == 0)
{
Console.WriteLine("Please pass in camera name and address");
return;
}
var codeFiles = @"C:\Users\jakka\Documents\code.txt";
_code = File.ReadAllText(codeFiles);
AppDomain.CurrentDomain.ProcessExit += CurrentDomain_ProcessExit;
_fgDetector = new BackgroundSubtractorMOG2();
_blobDetector = new CvBlobDetector();
_tracker = new CvTracks();
_name = args[0];
var address = args[1];
var fn = Path.Combine(Path.GetTempPath(), "survel");
if (!Directory.Exists(fn))
{
Directory.CreateDirectory(fn);
}
else
{
//foreach (var f in Directory.GetFiles(fn))
//{
// File.Delete(f);
//}
}
Task.Run(async() =>
{
await _processor(address, fn);
});
_watcher(_name, fn).GetAwaiter().GetResult();
}
LineSegment2DF Line2 = new LineSegment2DF(); //十字光标
public Form1()
{
InitializeComponent();
_motionDetect = new BackgroundSubtractorMOG2();//默认参数实例化类。
//_motionhistory = new MotionHistory(0.01, 0.05, 0.5);
OpenFileDialog op = new OpenFileDialog();
string path = "";
_capture = new Capture("1.avi"); //打开运行目录下的1.avi视频。
if (_capture != null) //if camera capture has been successfully created
{
_motionhistory = new MotionHistory(
0.1, //运动持续时间。
0.5, //运动最长时间。
0.05); //运动最短时间。
_capture.ImageGrabbed += frame; //捕捉帧触发事件
_capture.Start(); //开启捕捉真事件。
}
}
static void Main(string[] args)
{
_cameraCapture = new VideoCapture(1);
_fgDetector = new Emgu.CV.VideoSurveillance.BackgroundSubtractorMOG2();
_blobDetector = new CvBlobDetector();
_tracker = new CvTracks();
Task.Run(() =>
{
DetectFaces();
})
.ContinueWith((p) =>
{
if (p != null && p.IsFaulted)
{
Console.WriteLine(p.Exception.InnerException.Message);
}
});
Task.Run(() =>
{
IdentifyFaces();
})
.ContinueWith((p) =>
{
if (p != null && p.IsFaulted)
{
Console.WriteLine(p.Exception.InnerException.Message);
}
});
Console.ReadKey();
}
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);
}
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 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;
}
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 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);
}
internal BackgroundSubtractorShould(BackgroundSubtractor subtractor) : base(subtractor)
{
this.subtractor = subtractor;
}
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();
}
}
}
}
}
