public static void DrawRect(this IplImage ipl, CvRect rect, CvColor color, int thickNess)
{
var roi = ipl.ROI;
ipl.ResetROI();
ipl.DrawRect(rect.X, rect.Y, rect.X + rect.Width, rect.Y + rect.Height, color, thickNess);
ipl.SetROI(roi);
}
public MainWindow()
{
InitializeComponent();
//ViewModel からのｽｸﾘﾌﾟﾄ実行用のdelegate
DataContextChanged += (o, e) =>
{
ViewModel vm = DataContext as ViewModel;
if (vm != null)
{
vm._ExecuteScript += (sender, arg) =>
{
Dispatcher.Invoke(new Action(() => { pythonConsole.Pad.Console.RunStatements(arg.cmd); }));
};
vm._DrawCameraBitmap += (sender, arg) =>
{
Dispatcher.BeginInvoke(new Action(() =>
{
IplImage img = vm.VisionControl.GetCameraImage();
DrawCameraViewEventArgs a = arg as DrawCameraViewEventArgs;
if (a._draw == 1)
{
CvRect rect = new CvRect(a._x1, a._y1, a._x2, a._y2);
img.DrawRect(rect, new CvScalar(255, 0, 0), 2);
}
else if (a._draw == 2)
{
int x1 = a._x1 - a._x2 / 2;
int x2 = a._x1 + a._x2 / 2;
int y1 = a._y1 - a._y2 / 2;
int y2 = a._y1 + a._y2 / 2;
img.DrawLine(x1, a._y1, x2, a._y1, new CvScalar(255, 0, 0), 2);
img.DrawLine(a._x1, y1, a._x1, y2, new CvScalar(255, 0, 0), 2);
}
if (VM.CenterLine == true)
{
img.DrawLine(0, 320, 640, 320, new CvScalar(255, 0, 0, 0), 2);
img.DrawLine(320, 0, 320, 640, new CvScalar(255, 0, 0, 0), 2);
}
WriteableBitmapConverter.ToWriteableBitmap(img, _col_wb);
cameraImage.Source = _col_wb;
img.Dispose();
//cameraImage.Source = vm.VisionControl.GetCameraBitmap();
}));
};
}
};
pythonConsole.Pad.Host.ConsoleCreated += new PythonConsoleControl.ConsoleCreatedEventHandler(Host_ConsoleCreated);
}
private void CaptureCameraCallback()
{
const double ScaleFactor = 2.5;
const int MinNeighbors = 1;
CvSize MinSize = new CvSize(30, 30);
//mengambil data dari kamera langsung
CvCapture cap = CvCapture.FromCamera(2);
//menggunakan cascade classifier
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile("haarcascade_eye.xml");
//deteksi mata
while (true)
{
IplImage img = cap.QueryFrame();
CvSeq <CvAvgComp> eyes = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), ScaleFactor, MinNeighbors, HaarDetectionType.DoCannyPruning, MinSize);
foreach (CvAvgComp mata in eyes.AsParallel())
{
img.DrawRect(mata.Rect, CvColor.Red);
if (mata.Rect.Left > pctCvWindow.Width / 2)
{
try
{
IplImage MataImg1 = img.Clone();
Cv.SetImageROI(MataImg1, mata.Rect);
IplImage MataImg2 = Cv.CreateImage(mata.Rect.Size, MataImg1.Depth, MataImg1.NChannels);
Cv.Copy(MataImg1, MataImg2, null);
Cv.ResetImageROI(MataImg1);
Bitmap MataBitmap = BitmapConverter.ToBitmap(MataImg2);
Console.WriteLine("Mata terdeteksi, HIDUPKAN vibrator!!!");
}
catch { }
}
}
//keluar (while) , mata tidak terdeteksi.
Bitmap bm = BitmapConverter.ToBitmap(img);
bm.SetResolution(pctCvWindow.Width, pctCvWindow.Height);
pctCvWindow.Image = bm;
img = null;
bm = null;
Console.WriteLine("Mata TIDAK terdeteksi, MATIKAN vibrator!!!");
}
}
private void CaptureMotion()
{
try
{
float wFactor = (float)this.Width / (float)CaptureBox.Width;
float hFactor = (float)this.Height / (float)CaptureBox.Height;
CvArr array = null;
CvCapture cap = CvCapture.FromCamera(CaptureDevice.Any);
this.Invoke(new Action(() =>
{
lblLoading.Visible = false;
GBBox.Visible = true;
CamBox.Visible = true;
RadarBox.Visible = true;
lblGhost.Visible = true;
GhostBox.Visible = true;
lblDescription.Visible = true;
CaptureBox.Visible = true;
}));
SoundTrack.Play();
SoundTrack = new SoundPlayer("Alarm.wav");
Thread.Sleep(3600);
while (true)
{
IplImage img = cap.QueryFrame();
if (img == null)
{
continue;
}
//int black = img
//if (black < 10)
//{
// MessageBox.Show("Please get off cameras' field of view and switch off the lights!", "Ghost Busters Cam");
// continue;
//}
img.Flip(array, FlipMode.Y);
string filepath = "haarcascade_frontalface_alt2.xml";
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile(filepath);
CvSeq <CvAvgComp> faces = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), 3.0, 1,
HaarDetectionType.Zero, new CvSize(70, 70),
new CvSize(500, 500));
Bitmap Image = BitmapConverter.ToBitmap(img);
Image.SetResolution(240, 180);
this.Invoke(new Action(() =>
{
CaptureBox.Image = Image;
}));
foreach (CvAvgComp face in faces)
{
IplImage ClonedImage = img.Clone();
Cv.SetImageROI(ClonedImage, face.Rect);
IplImage ThisFace = Cv.CreateImage(face.Rect.Size, ClonedImage.Depth, ClonedImage.NChannels);
Cv.Copy(ClonedImage, ThisFace, null);
Cv.ResetImageROI(ClonedImage);
Bitmap GhostImage = BitmapConverter.ToBitmap(ThisFace);
GhostImage.SetResolution(114, 103);
img.DrawRect(face.Rect, CvColor.Red, 3);
Bitmap FaceImage = BitmapConverter.ToBitmap(img);
FaceImage.SetResolution(240, 180);
this.Invoke(new Action(() =>
{
AlertTimer.Enabled = true;
CaptureBox.Image = FaceImage;
GhostBox.Image = GhostImage;
}));
SoundTrack.Play();
Thread.Sleep(2500);
this.Invoke(new Action(() =>
{
AlertTimer.Enabled = false;
lblGhostAlert.Visible = false;
}));
SoundTrack.Stop();
break;
}
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
EyeRects Recognize(PictureBox bb, Panel container)
{
const double ScaleFactor = 2.5;
const int MinNeighbors = 1;
CvSize MinSize = new CvSize(30, 30);
//CvCapture cap = CvCapture.FromCamera(1);
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile("haarcascade_eye.xml");
//IplImage img = cap.QueryFrame();
IplImage img = IplImage.FromBitmap(new Bitmap(bb.Image));
CvSeq <CvAvgComp> eyes = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), ScaleFactor, MinNeighbors, HaarDetectionType.DoCannyPruning, MinSize);
img.DrawRect(new CvRect(30, 30, bb.Image.Width - 30, bb.Image.Height - 60), CvColor.Yellow);
var rcs = new EyeRects();
foreach (CvAvgComp eye in eyes.AsParallel())
{
rcs.AddRect(eye.Rect);
img.DrawRect(eye.Rect, CvColor.Yellow);
if (eye.Rect.Left > pn.Width / 2)
{
try
{
IplImage rightEyeImg1 = img.Clone();
Cv.SetImageROI(rightEyeImg1, eye.Rect);
IplImage rightEyeImg2 = Cv.CreateImage(eye.Rect.Size, rightEyeImg1.Depth, rightEyeImg1.NChannels);
Cv.Copy(rightEyeImg1, rightEyeImg2, null);
Cv.ResetImageROI(rightEyeImg1);
//Bitmap rightEyeBm = BitmapConverter.ToBitmap(rightEyeImg2);
//spMain.Panel2.Image = rightEyeBm;
}
catch { }
}
else
{
try
{
IplImage leftEyeImg1 = img.Clone();
Cv.SetImageROI(leftEyeImg1, eye.Rect);
IplImage leftEyeImg2 = Cv.CreateImage(eye.Rect.Size, leftEyeImg1.Depth, leftEyeImg1.NChannels);
Cv.Copy(leftEyeImg1, leftEyeImg2, null);
Cv.ResetImageROI(leftEyeImg1);
//Bitmap leftEyeBm = BitmapConverter.ToBitmap(leftEyeImg2);
//pctLeftEye.Image = leftEyeBm;
}
catch { }
}
}
Bitmap bm = BitmapConverter.ToBitmap(img);
//bm.SetResolution(1500, 1500);
//pctCvWindow.Image = bm;
//PictureBox pb = new PictureBox();
//pb.Image = bm;
//pb.Image = bm;
bb.Image = bm;
//spMain.Panel2.Controls.Clear();
if (pn.Controls.Count < 1)
{
pn.Controls.Add(bb);
//bb.Click += bb_Click;
}
bb.Dock = DockStyle.Fill;
//pb.Image = bm;
img = null;
bm = null;
return(rcs);
}
private void CaptureMotion()
{
try
{
float wFactor = (float)this.Width / (float)CaptureBox.Width;
float hFactor = (float)this.Height / (float)CaptureBox.Height;
CvArr array = null;
CvCapture cap = CvCapture.FromCamera(CaptureDevice.Any);
this.Invoke(new Action(() =>
{
lblLoading.Visible = false;
radioButton1.Visible = true;
radioButton2.Visible = true;
}));
while (true)
{
IplImage img = cap.QueryFrame();
if (img == null)
{
continue;
}
img.Flip(array, FlipMode.Y);
if (mode == 1)
{
string filepath = "haarcascade_frontalface_alt2.xml";
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile(filepath);
CvSeq <CvAvgComp> faces = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), 3.0, 1,
HaarDetectionType.Zero, new CvSize(70, 70),
new CvSize(500, 500));
foreach (CvAvgComp face in faces)
{
//IplImage ClonedImage = img.Clone();
//Cv.SetImageROI(ClonedImage, face.Rect);
//IplImage ThisFace = Cv.CreateImage(face.Rect.Size, ClonedImage.Depth, ClonedImage.NChannels);
//Cv.Copy(ClonedImage, ThisFace, null);
//Cv.ResetImageROI(ClonedImage);
//Bitmap FaceImage = BitmapConverter.ToBitmap(ThisFace);
//FaceImage.SetResolution(240, 180);
//CaptureBox.Image = FaceImage;
img.DrawRect(face.Rect, CvColor.Red, 3);
Bitmap FaceImage = BitmapConverter.ToBitmap(img);
FaceImage.SetResolution(240, 180);
CaptureBox.Image = FaceImage;
this.Invoke(new Action(() =>
{
LifeBox.Left = (int)(face.Rect.Left * wFactor - (float)(LifeBox.Width / 2.0) - (float)(this.Width / 2.0));
LifeBox.Top = (int)(face.Rect.Top * hFactor - (float)(LifeBox.Height / 2.0) - (float)(this.Height / 2.0));
if (LifeBox.Left > (this.Width - LifeBox.Width - 12))
{
LifeBox.Left = (this.Width - LifeBox.Width - 24);
}
if (LifeBox.Top > (this.Height - LifeBox.Height - 48))
{
LifeBox.Top = (this.Height - LifeBox.Height - 48);
}
if (LifeBox.Left < 12)
{
LifeBox.Left = 12;
}
if (LifeBox.Top < 12)
{
LifeBox.Top = 12;
}
Thread.Sleep(30);
}));
break;
}
}
else
{
int AllBlobs = 0;
CvBlobs blobs = null;
IplImage imgHSVsrc = Cv.CreateImage(Cv.GetSize(img), BitDepth.U8, 3);
IplImage imgHSVdst = Cv.CreateImage(Cv.GetSize(img), BitDepth.U8, 1);
Cv.CvtColor(img, imgHSVsrc, ColorConversion.BgrToHsv);
Cv.InRangeS(imgHSVsrc, new CvScalar(86, 80, 30), new CvScalar(115, 250, 250), imgHSVdst);
Cv.ReleaseImage(imgHSVsrc);
blobs = new CvBlobs(imgHSVdst);
blobs.FilterByArea(7000, 40000);
AllBlobs = blobs.Count;
foreach (KeyValuePair <int, CvBlob> blob in blobs)
{
CvBlob CurrentBlob = blob.Value;
CvRect BlobRect = CurrentBlob.Rect;
CvPoint Point1, Point2;
Point1.X = BlobRect.X;
Point1.Y = BlobRect.Y;
Point2.X = BlobRect.X + BlobRect.Width;
Point2.Y = BlobRect.Y + BlobRect.Height;
img.DrawRect(Point1, Point2, CvColor.LightGreen, 3, LineType.AntiAlias);
this.Invoke(new Action(() =>
{
LifeBox.Left = (int)(BlobRect.Left * wFactor - (float)(LifeBox.Width / 2.0) - (float)(this.Width / 2.0));
LifeBox.Top = (int)(BlobRect.Top * hFactor - (float)(LifeBox.Height / 2.0) - (float)(this.Height / 2.0));
if (LifeBox.Left > (this.Width - LifeBox.Width - 12))
{
LifeBox.Left = (this.Width - LifeBox.Width - 24);
}
if (LifeBox.Top > (this.Height - LifeBox.Height - 48))
{
LifeBox.Top = (this.Height - LifeBox.Height - 48);
}
if (LifeBox.Left < 12)
{
LifeBox.Left = 12;
}
if (LifeBox.Top < 12)
{
LifeBox.Top = 12;
}
Thread.Sleep(30);
}));
break;
}
Bitmap Item = BitmapConverter.ToBitmap(img);
Item.SetResolution(240, 180);
CaptureBox.Image = Item;
Bitmap HSVItem = BitmapConverter.ToBitmap(imgHSVdst);
HSVItem.SetResolution(240, 180);
HSVCaptureBox.Image = HSVItem;
Cv.ReleaseImage(imgHSVdst);
}
}
}
catch (Exception e)
{
Console.WriteLine("ERROR: " + e.Message + "DETAILS: " + e.StackTrace);
}
}
private void CaptureCameraCallback()
{
const double ScaleFactor = 2.5;
const int MinNeighbors = 1;
CvSize MinSize = new CvSize(30, 30);
CvCapture cap = CvCapture.FromCamera(1);
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile("haarcascade_eye.xml");
while (true)
{
IplImage img = cap.QueryFrame();
//IplImage src = new IplImage(new CvSize(600, 400),BitDepth.U8,1);
//Cv.Resize(img, src, Interpolation.Linear);
CvSeq <CvAvgComp> eyes = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), ScaleFactor, MinNeighbors, HaarDetectionType.DoCannyPruning, MinSize);
foreach (CvAvgComp eye in eyes.AsParallel())
{
img.DrawRect(eye.Rect, CvColor.Red);
if (eye.Rect.Left > pctCvWindow.Width / 2)
{
try
{
IplImage rightEyeImg1 = img.Clone();
Cv.SetImageROI(rightEyeImg1, eye.Rect);
IplImage rightEyeImg2 = Cv.CreateImage(eye.Rect.Size, rightEyeImg1.Depth, rightEyeImg1.NChannels);
Cv.Copy(rightEyeImg1, rightEyeImg2, null);
Cv.ResetImageROI(rightEyeImg1);
Bitmap rightEyeBm = BitmapConverter.ToBitmap(rightEyeImg2);
pctRightEye.Image = rightEyeBm;
}
catch { }
}
else
{
try
{
IplImage leftEyeImg1 = img.Clone();
Cv.SetImageROI(leftEyeImg1, eye.Rect);
IplImage leftEyeImg2 = Cv.CreateImage(eye.Rect.Size, leftEyeImg1.Depth, leftEyeImg1.NChannels);
Cv.Copy(leftEyeImg1, leftEyeImg2, null);
Cv.ResetImageROI(leftEyeImg1);
Bitmap leftEyeBm = BitmapConverter.ToBitmap(leftEyeImg2);
//pctLeftEye.Image = leftEyeBm;
//pctLeftEye.Visible = false;
}catch {}
}
}
Bitmap bm = BitmapConverter.ToBitmap(img);
bm.SetResolution(pctCvWindow.Width, pctCvWindow.Height);
pctCvWindow.Image = bm;
img = null;
bm = null;
}
}
