public void FaceppThread( )
{
facesDetected = smallGrayFrame.DetectHaarCascade(
haar,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20))[0];
int NUM = 0;
for (int i = 0; i < facesDetected.Length; i++)
{
MCvAvgComp f = facesDetected[i];
DETECTED = true;
this.smallGrayFrame.ROI = f.rect;
Image <Gray, Byte> roiImage = new Image <Gray, Byte> (f.rect.Size);
this.smallGrayFrame.Copy(roiImage, smallGrayFrame);
fsFileName = "DECT.jpg";
roiImage.Save(fsFileName);
DetectResult res_ = fs.Detection_DetectImg(this.smallGrayFrame);
DetectResult res = fs.Detection_DetectImg(System.Environment.CurrentDirectory + "\\" + fsFileName);
if (res.face.Count > 0)
{
age[NUM] = res.face[0].attribute.age;
gender[NUM] = res.face[0].attribute.gender;
NUM++;
}
}
if (DETECTED == true)
{
processingData( );
}
}
private void DrawFaces(Image <Bgr, Byte> image)
{
MCvAvgComp[] Faces = Sensor.FaceManager.Faces;
String[] Names = Sensor.FaceManager.Names;
Image <Gray, byte>[] Thumbs = Sensor.FaceManager.Thumbs;
for (int i = 0; i < Faces.Length; i++)
{
// Draw Rect
MCvAvgComp f = Faces[i];
if (f.rect == null)
{
continue;
}
image.Draw(f.rect, border, 2);
// Draw text
var rect = new Rectangle(f.rect.X, f.rect.Y + f.rect.Height + 20, f.rect.Width, f.rect.Height);
DrawText(image, rect, Names[i] != null ? Names[i] : "");
// Draw thumb
if (Thumbs[i] != null)
{
this.imageTrainedFace.Source = ToBitmapSource(Thumbs[i]);
}
}
}
public MCvAvgComp[] DetectEyes(FrameData data)
{
MCvAvgComp face = data.Face;
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
Point startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 3 / 11));
Rectangle possibleROI_eyes = new Rectangle(startingPointSearchEyes, searchEyesAreaSize);
data.GrayFrame.ROI = possibleROI_eyes;
MCvAvgComp[] eyesDetected = _eyes.Detect(data.GrayFrame, 1.15, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_ROUGH_SEARCH, new Size(20, 20));
data.GrayFrame.ROI = Rectangle.Empty;
if (eyesDetected.Length != 0)
{
Rectangle eyeRect = eyesDetected[0].rect;
eyeRect.Offset(possibleROI_eyes.X, possibleROI_eyes.Y);
data.GrayFrame.ROI = eyeRect;
data.GrayFrame.ROI = possibleROI_eyes;
data.EyesROI = possibleROI_eyes;
MCvAvgComp[] singleEyesDetected = _singleEyes.Detect(data.GrayFrame, 1.5, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_ROUGH_SEARCH, new Size(20, 20));
data.GrayFrame.ROI = Rectangle.Empty;
return(singleEyesDetected);
}
throw new NoEyesDetectedException();
}
public MCvAvgComp DetectMouth(FrameData data)
{
MCvAvgComp face = data.Face;
Int32 yCoordStartSearchMouth = face.rect.Top + (face.rect.Height * 7 / 11);
Point startingPointSearchMouth = new Point(face.rect.X, yCoordStartSearchMouth);
Size searchMouthAreaSize = new Size(face.rect.Width, (face.rect.Height * 4 / 11));
Rectangle possibleROI_mouth = new Rectangle(startingPointSearchMouth, searchMouthAreaSize);
data.GrayFrame.ROI = possibleROI_mouth;
data.MouthROI = possibleROI_mouth;
MCvAvgComp[] mouthDetected = _mouth.Detect(data.GrayFrame, 1.15, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_ROUGH_SEARCH, new Size(30, 20));
data.GrayFrame.ROI = Rectangle.Empty;
if (mouthDetected.Length > 0)
{
if (mouthDetected[0].rect.Height != 0 && mouthDetected[0].rect.Width != 0)
{
var mouthRect = mouthDetected[0].rect;
mouthRect.Offset(possibleROI_mouth.X, possibleROI_mouth.Y);
data.GrayFrame.ROI = mouthRect;
return(mouthDetected[0]);
}
}
throw new NoMouthDetectedException();
}
public Image <Bgr, Byte> FaceDetection(Image Image)
{
face = new HaarCascade("haarcascade_frontalface_default.xml");
Utility UTl = new Utility();
//Get the current frame form capture device
Image <Bgr, Byte> currentFrame = UTl.ImageToBgrByte(Image);
//Convert it to Grayscale
gray = currentFrame.Convert <Gray, Byte>();
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(face, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
//Action for element detected
try
{
MCvAvgComp f = facesDetected[0][0];
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//draw the face detected in the 0th (gray) channel with blue color
currentFrame.Draw(f.rect, new Bgr(Color.White), 2);
}
catch (Exception ex)
{
MessageBox.Show("Camera Error: Empty frames arrived" + ex.Message.ToString(), "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
return(currentFrame);
}
/// <summary>
/// This method returns the 2 ROIs that are more "aligned", i.e. with the
/// lowest difference in the Y coordinate
/// It calculates the distances between all the ROIs and selects the appropriate pair
/// </summary>
/// <param name="ROIs"></param>
/// <returns></returns>
private MCvAvgComp[] AlignedROIs(MCvAvgComp[] ROIs)
{
MCvAvgComp[] alignedROIs = new MCvAvgComp[2];
int N = ROIs.Length;
Matrix <int> distancesY = new Matrix <int>(N, N);
distancesY = distancesY.Add(100000);
double minimum;
double maximum;
Point minimumLocation;
Point maximumLocation;
for (int i = 0; i < N; i++)
{
for (int j = i + 1; j < N; j++)
{
// If both rectangles do not intersect, we add their distance to the matrix
// MT: Min distance of 2 x roi.width
if (ROIs[j].rect.IntersectsWith(ROIs[i].rect) == false && Math.Abs(ROIs[j].rect.X - ROIs[i].rect.X) > ROIs[j].rect.Width * 2.5)
{
distancesY[i, j] = Math.Abs(ROIs[j].rect.Y - ROIs[i].rect.Y);
}
}
}
distancesY.MinMax(out minimum, out maximum, out minimumLocation, out maximumLocation);
alignedROIs[0] = ROIs[minimumLocation.X];
alignedROIs[1] = ROIs[minimumLocation.Y];
return(alignedROIs);
}
public void ProcessImage(object sender, EventArgs e)
{
Image <Bgr, Byte> frame = _capture.QueryFrame();
Image <Gray, Byte> grayImage = frame.Convert <Gray, Byte>();
grayImage._EqualizeHist();
System.Drawing.Rectangle imageArea = grayImage.ROI;
System.Drawing.Rectangle mouseStableArea =
new System.Drawing.Rectangle((int)(imageArea.Width * 0.4), (int)(imageArea.Height * 0.4), (int)(imageArea.Width * 0.2), (int)(imageArea.Height * 0.2));
//draw the stable area where the face will not trigger a movement;
frame.Draw(mouseStableArea, new Bgr(255, 0, 0), 1);
MCvAvgComp[] faces = grayImage.DetectHaarCascade(_face)[0];
if (faces.Length > 0)
{ //if there is at least one face
#region find the biggest face
MCvAvgComp biggestFace = faces[0];
for (int i = 1; i < faces.Length; i++)
{
if (faces[i].rect.Width * faces[i].rect.Height > biggestFace.rect.Width * biggestFace.rect.Height)
{
biggestFace = faces[i];
}
}
#endregion
//draw a yellow rectangle around the face
frame.Draw(biggestFace.rect, new Bgr(255, 255, 0.0), 1);
Point biggestFaceCenter = new Point(biggestFace.rect.X + biggestFace.rect.Width / 2, biggestFace.rect.Y + biggestFace.rect.Height / 2);
Point imageAreaCenter = new Point(imageArea.X + imageArea.Width / 2, imageArea.Y + imageArea.Height / 2);
//draw a green cross at the center of the biggest face
frame.Draw(
new Cross2DF(biggestFaceCenter, biggestFace.rect.Width * 0.1f, biggestFace.rect.Height * 0.1f),
new Bgr(0, 255, 0), 1);
if (!mouseStableArea.Contains(biggestFaceCenter))
{ //the point is far enough from the center to triger a movement
//horizontal fraction is a value in [-0.5, 0.5] where
//-0.5 refer to the far left and
//0.5 refer to the far right
double horizontalFraction = (double)(biggestFaceCenter.X - imageAreaCenter.X) / imageArea.Width;
//do the same for vertical fraction
double verticalFraction = (double)(biggestFaceCenter.Y - imageAreaCenter.Y) / imageArea.Height;
Rectangle rect = System.Windows.Forms.Screen.PrimaryScreen.Bounds;
int maxMouseSpeed = rect.Width / 20;
System.Drawing.Point p;
GetCursorPos(out p);
p.X = Math.Min(Math.Max(0, p.X + (int)((maxMouseSpeed / 2) * horizontalFraction)), rect.Width);
p.Y = Math.Min(Math.Max(0, p.Y + (int)((maxMouseSpeed / 2) * verticalFraction)), rect.Height);
SetCursorPos(p.X, p.Y);
}
}
imageBox1.Image = frame;
}
void Process(object sender, EventArgs e)
{
FrameData data = CaptureFrame();
Boolean processed = false;
if (data != null)
{
data.Epoch = currentEpoch++;
try
{
MCvAvgComp face = detectors.DetectFace(data);
data.Face = face;
MCvAvgComp mouth = detectors.DetectMouth(data);
data.Mouth = mouth;
MCvAvgComp[] eyes = detectors.DetectEyes(data);
data.Eyes = eyes;
data.EyesCount = eyes.Length;
if (data.EyesCount == 2)
{
framesWithoutEyes = 0;
bool rotated = UpdateRotation(data.Eyes);
data.Rotated = rotated;
data.Rotation = rotateAngle;
EventListeners(data);
processed = true;
}
else if (data.EyesCount > 2)
{
Console.WriteLine("More than three eyes detected. Possible errors");
}
else
{
framesWithoutEyes++;
if (framesWithoutEyes > FRAMES_TO_RESET_ROTATION)
{
framesWithoutEyes = 0;
this.rotateAngle = 0.0;
}
}
}
catch (NoFaceDetectedException)
{
}
catch (NoEyesDetectedException)
{
}
catch (NoMouthDetectedException)
{
}
}
if (!processed)
{
data.Empty = true;
//EventListeners(EMPTY);
EventListeners(data);
}
}
private void addToFlow(Image <Bgr, byte> result, MCvAvgComp f, string name)
{
PictureBox pbox = new PictureBox();
pbox.Tag = new object[] { new int[] { f.rect.X, f.rect.Y, f.rect.Width, f.rect.Height }, name };
pbox.Click += new EventHandler(pbox_Click);
pbox.ContextMenuStrip = contextMenuStrip1;
pbox.SizeMode = PictureBoxSizeMode.StretchImage;
pbox.Height = 50;
pbox.Width = 50;
pbox.Cursor = Cursors.Hand;
pbox.Image = result.Copy(f.rect).Bitmap;
flowLayoutPanel1.Controls.Add(pbox);
}
public FaceController(MCvAvgComp f, int confidence)
{
//Center
//this.location.X = f.rect.Location.X + (f.rect.Width / 2);
//this.location.Y = f.rect.Location.Y + (f.rect.Height / 2);
this.location.X = f.rect.Location.X;
this.location.Y = f.rect.Location.Y;
this.Rect = new Microsoft.Xna.Framework.Rectangle(
(int)this.Location.X,
(int)this.Location.Y, f.rect.Width, f.rect.Height);
this.Confidence = (ConfidenceAmount)confidence;
this.Scale = f.rect.Right - f.rect.Left;
}
public MCvAvgComp DetectFace(FrameData data)
{
MCvAvgComp[] facesDetected = _faces.Detect(data.GrayFrame, 1.05, 1, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(20, 20));
if (facesDetected.Length == 1)
{
MCvAvgComp face = facesDetected[0];
return(face);
}
else if (facesDetected.Length > 1)
{
Console.WriteLine("HaarDetectors.DetectFace: more than two faces detected. Possible errors");
MCvAvgComp face = facesDetected[0];
return(face);
}
throw new NoFaceDetectedException();
}
public DetectedFace DetectFirstFace(Image <Bgr, Byte> frame, string newLabel = null)
{
var result = new DetectedFace();
var gray = frame.Convert <Gray, Byte>();
var facesDetected = gray.DetectHaarCascade(
_face,
1.2,
10,
HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
gray.Dispose();
if (!facesDetected[0].Any())
{
return(null);
}
MCvAvgComp faceInfo = facesDetected[0].First();
result.FaceInfo = faceInfo;
var faceImage = frame.Copy(faceInfo.rect)
.Convert <Gray, byte>()
.Resize(100, 100,
INTER.CV_INTER_CUBIC);
if (!String.IsNullOrEmpty(newLabel))
{
_recognizerProvider.AddNewLabel(newLabel, faceImage);
_rep.Save(newLabel, faceImage);
result.Label = newLabel;
return(result);
}
if (_recognizerProvider.HasConfiguredFaces())
{
result.Label = _recognizerProvider.GetRecognizer()
.Recognize(faceImage);
}
else
{
result.Label = UnknownLabel;
}
faceImage.Dispose();
return(result);
}
// Worker Thread가 실제 하는 일
void worker_DoWork(object sender, DoWorkEventArgs e)
{
Image <Gray, Byte> grayFrame = (Image <Gray, Byte>)e.Argument;
// 머신러닝을 이용한 얼굴 인식 Haaracascade 돌리기
MCvAvgComp[][] facesDetected = grayFrame.DetectHaarCascade(_faces, 1.1, 0, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(20, 20));
if (facesDetected[0].Length != 0)
{
face = facesDetected[0][0];
#region 얼굴 인식한것을 토대로 눈 찾기
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
System.Drawing.Point startingPointSearchEyes = new System.Drawing.Point(face.rect.X, yCoordStartSearchEyes);
System.Drawing.Point endingPointSearchEyes = new System.Drawing.Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 2 / 9));
Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 2 / 9));
System.Drawing.Point lowerEyesPointOptimized = new System.Drawing.Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
System.Drawing.Point startingLeftEyePointOptimized = new System.Drawing.Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Rectangle leftEyeArea = new Rectangle(new System.Drawing.Point(startingPointSearchEyes.X + 25, startingPointSearchEyes.Y + 10),
new Size(eyeAreaSize.Width - 25, eyeAreaSize.Height - 20));
Rectangle rightEyeArea = new Rectangle(new System.Drawing.Point(startingLeftEyePointOptimized.X + 5, startingLeftEyePointOptimized.Y + 10),
new Size(eyeAreaSize.Width - 33, eyeAreaSize.Height - 20));
#endregion
//#region 눈 영역 그리기
//a = new LineSegment2D(startingPointSearchEyes, endingPointSearchEyes);
//b = new LineSegment2D(new System.Drawing.Point(lowerEyesPointOptimized.X, lowerEyesPointOptimized.Y),
// new System.Drawing.Point((lowerEyesPointOptimized.X + face.rect.Width), (yCoordStartSearchEyes + searchEyesAreaSize.Height)));
//d = new Bgr(Color.Chocolate);
////그리기
//frame.Draw(a, d, 3);
//frame.Draw(b, d, 3);
//#endregion
#region 눈 영역 검출한 Rectangle의 크기가 양수일 경우에만 눈 영역 적출하기
if (leftEyeArea.Width > 0 && leftEyeArea.Height > 0 && rightEyeArea.Width > 0 && rightEyeArea.Height > 0)
{
possibleROI_leftEye = leftEyeArea;
possibleROI_rightEye = rightEyeArea;
}
#endregion
}// if(faceDetect[0])
}
private bool DoEyesRegionExtraction(Image <Gray, Byte> input, TrackData trackData)
{
// We assume there's only one face in the video
MCvAvgComp[][] facesDetected = input.DetectHaarCascade(
haarCascade,
Settings.Instance.Eyestracker.ScaleFactor,
2, //Min. neighbours, higher value reduces false detection
HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT,
Settings.Instance.Eyestracker.SizeMin);
if (facesDetected[0].Length == 1)
{
MCvAvgComp face = facesDetected[0][0];
if (face.rect.X != 0 && face.rect.Width != 0)
{
if (face.rect.Height < 100)
{
return(false);
}
roiEyes = face.rect;
// Add some margin
//roiEyes.Y = Convert.ToInt32(roiEyes.Y * 0.90);
roiEyes.X = Convert.ToInt32(roiEyes.X * 0.85);
roiEyes.Height = Convert.ToInt32(roiEyes.Height * 1.2);
roiEyes.Width = Convert.ToInt32(roiEyes.Width * 1.4);
foundEyes = true;
trackData.EyesROI = roiEyes;
}
}
else
{
foundEyes = false;
roiEyes = new Rectangle(new Point(0, 0), new Size(0, 0));
}
Performance.Now.Stamp("Eyes X:" + roiEyes.X + " Y:" + roiEyes.Y + " W:" + roiEyes.Width + " H:" +
roiEyes.Height);
return(foundEyes);
}
private void detectFacesInFrame(Image <Bgr, byte> currentFrame)
{
currentDetectedFace = null;
Image <Gray, byte> grayFrame = currentFrame.Convert <Gray, Byte>();
MCvAvgComp[][] facesDetected = grayFrame.DetectHaarCascade(
FaceCascade, 1.2, 10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new System.Drawing.Size(20, 20));
nCurrentlyDetectedFaces = facesDetected[0].Length;
//apenas processamos quando ha exactamente 1 face
if (nCurrentlyDetectedFaces == 1)
{
MCvAvgComp faceFound = facesDetected[0][0];
currentDetectedFace = currentFrame.Copy(faceFound.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
currentDetectedFace._EqualizeHist();
}
}
// hàm chụp khuôn mặt đc phát hiện và lưu vào database
private void capture(string name, string phone, string email, DateTime dob)
{
//lấy frame hiện tại của camera
gray = grabber.QueryGrayFrame().Resize(imageBoxFrameGrabber.Width, imageBoxFrameGrabber.Height, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//phát hiện khuôn mặt
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
// nếu phát hiện được khuôn mặt nào
if (facesDetected[0].Length > 0)
{
// lấy khuôn mặt đc phát hiện
MCvAvgComp f = facesDetected[0][0];
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();//Convert<gray,>();
// chỉnh lại kích thước khuôn mặt để so sánh với dữ liệu
TrainedFace = result.Resize(Constants.DETECTED_FRAME_WIDTH, Constants.DETECTED_FRAME_HEIGHT, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
// tạo đối tượng Face
Face newFace = new Face(name, phone, email, dob, TrainedFace);
try
{
// lưu vào cơ sở dữ liệu
SQLServerHelper.getInstance().insertFace(newFace);
// thêm khuôn mặt vào khung Training
lstFaces.Controls.Add(CreatePanel(TrainedFace));
}
catch (Exception ex)
{
MessageBox.Show("Error:" + ex.Message, "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
}
public String[] Recognize()
{
if (null == Faces || null == Gray || null == recognizer || initEigen)
{
return(null);
}
Array.Clear(Names, 0, Names.Length);
for (int i = 0; i < Faces.Length; i++)
{
MCvAvgComp f = Faces[i];
if (null == f.rect)
{
continue;
}
// Build a thumbnail
Thumbs[i] = Gray.Copy(f.rect).Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
// Recognize
Names[i] = recognizer.Recognize(Thumbs[i]);
}
return(Names);
}
public void DetectObj(Emgu.CV.Image <Emgu.CV.Structure.Bgr, byte> image)
{
if (m_harrDetector == null)
{
throw new ArgumentNullException("HaarCascade", "haarCascade not initilized.");
}
MCvAvgComp[][] EyeDetected = null;
MCvAvgComp[][] LeftEyeDetected = null;
MCvAvgComp[][] RightEyeDetected = null;
EyeDetected = image.DetectHaarCascade(
m_harrDetector,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
m_MinEyeSize);
if (EyeDetected.Length > 1)
{
Rectangle rcROI = image.ROI;
MCvAvgComp eyepair = EyeDetected[0][0];
int width = Convert.ToInt32(eyepair.rect.Width * 1.5);
int height = Convert.ToInt32(eyepair.rect.Height * 1.5);
Rectangle rectEye = new Rectangle(eyepair.rect.X - 10,
eyepair.rect.Y - 10, width, height);
Rectangle rectLeftEye = new Rectangle(eyepair.rect.X - 10,
eyepair.rect.Y - 10, width, height);
Rectangle rectRightEye = new Rectangle(eyepair.rect.X - 10 + width / 2,
eyepair.rect.Y - 10, width, height);
Rectangle rcLeft = Rectangle.Empty;
Rectangle rcRight = Rectangle.Empty;
if (rcROI != Rectangle.Empty)
{
rectEye.X += rcROI.X;
rectEye.Y += rcROI.Y;
rectLeftEye.X += rcROI.X;
rectLeftEye.Y += rcROI.Y;
rectRightEye.X += rcROI.X;
rectRightEye.Y += rcROI.Y;
}
image.ROI = rectLeftEye;
if (m_LeftEyeDetector != null)
{
LeftEyeDetected = image.DetectHaarCascade(
m_LeftEyeDetector,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
m_MinEyeSize);
//Project into no ROI space
for (int i = 0; i < LeftEyeDetected[0].Length; i++)
{
LeftEyeDetected[0][i].rect.X += (rectLeftEye.X);
LeftEyeDetected[0][i].rect.Y += (rectLeftEye.Y);
}
}
image.ROI = rectEye;
if (LeftEyeDetected[0].Length > 1)
{// if already detected more than one eyes, then both eye should already be detected
foreach (MCvAvgComp eye in LeftEyeDetected[0])
{
if (rcLeft == Rectangle.Empty || rcLeft.X > eye.rect.X)
{
rcLeft = eye.rect;
}
if (rcRight == Rectangle.Empty || rcRight.X < eye.rect.X)
{
rcRight = eye.rect;
}
}
}
else if (m_RightEyeDetector != null)
{
RightEyeDetected = image.DetectHaarCascade(
m_RightEyeDetector,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
m_MinEyeSize);
//Project into no ROI space
for (int i = 0; i < RightEyeDetected[0].Length; i++)
{
RightEyeDetected[0][i].rect.X += rectEye.X;
RightEyeDetected[0][i].rect.Y += rectEye.Y;
}
// we only need the right eye
rcRight = Rectangle.Empty;
foreach (MCvAvgComp eye in RightEyeDetected[0])
{
if (rcRight == Rectangle.Empty || rcRight.X < eye.rect.X)
{
rcRight = eye.rect;
}
}
}
m_rcBestLeftEye = rcLeft;
m_rcBestRightEye = rcRight;
m_rcBestEyeDetected = EyeDetected[0][0].rect;
//Project into the original ROI
if (rcROI != Rectangle.Empty)
{
m_rcBestLeftEye.X -= rcROI.X;
m_rcBestLeftEye.Y -= rcROI.Y;
m_rcBestRightEye.X -= rcROI.X;
m_rcBestRightEye.Y -= rcROI.Y;
}
image.ROI = rcROI;
}
}
public void DibujarRecognitionRectangle(MCvAvgComp face)
{
//Dibuja un rectangulo de color verde delimitando el o los rostros detectados
_ActualFrame.Draw(face.rect, new Bgr(Color.Green), 2);
}
private static void DetectAndDrawEyes(Image <Bgr, byte> image, Image <Gray, byte> gray, MCvAvgComp f, HaarCascade eye)
{
gray.ROI = f.rect;
MCvAvgComp[][] eyesDetected = gray.DetectHaarCascade(
eye,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
gray.ROI = Rectangle.Empty;
foreach (MCvAvgComp e in eyesDetected[0])
{
Rectangle eyeRect = e.rect;
eyeRect.Offset(f.rect.X, f.rect.Y);
image.Draw(eyeRect, new Bgr(Color.Red), 2);
}
}
void FrameGrabber(object sender, EventArgs e)
{
//We are acquiring a new frame
Image <Bgr, Byte> frame = _capture.QueryFrame();
//We convert it to grayscale
Image <Gray, Byte> grayFrame = frame.Convert <Gray, Byte>();
//Equalization step
grayFrame._EqualizeHist();
// We assume there's only one face in the video
MCvAvgComp[][] facesDetected = grayFrame.DetectHaarCascade(_faces, 1.1, 1, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(20, 20));
if (facesDetected[0].Length == 1)
{
MCvAvgComp face = facesDetected[0][0];
//Set the region of interest on the faces
#region Luca Del Tongo Search Roi based on Face Metric Estimation --- based on empirical measuraments on a couple of photos --- a really trivial heuristic
// Our Region of interest where find eyes will start with a sample estimation using face metric
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
Point startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
Point endingPointSearchEyes = new Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 2 / 9));
Point lowerEyesPointOptimized = new Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 2 / 9));
Point startingLeftEyePointOptimized = new Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Rectangle possibleROI_eyes = new Rectangle(startingPointSearchEyes, searchEyesAreaSize);
Rectangle possibleROI_rightEye = new Rectangle(startingPointSearchEyes, eyeAreaSize);
Rectangle possibleROI_leftEye = new Rectangle(startingLeftEyePointOptimized, eyeAreaSize);
#endregion
#region Drawing Utilities
// Let's draw our search area, first the upper line
frame.Draw(new LineSegment2D(startingPointSearchEyes, endingPointSearchEyes), new Bgr(Color.White), 3);
// draw the bottom line
frame.Draw(new LineSegment2D(lowerEyesPointOptimized, new Point((lowerEyesPointOptimized.X + face.rect.Width), (yCoordStartSearchEyes + searchEyesAreaSize.Height))), new Bgr(Color.White), 3);
// draw the eyes search vertical line
frame.Draw(new LineSegment2D(startingLeftEyePointOptimized, new Point(startingLeftEyePointOptimized.X, (yCoordStartSearchEyes + searchEyesAreaSize.Height))), new Bgr(Color.White), 3);
MCvFont font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.6d, 0.6d);
frame.Draw("Search Eyes Area", ref font, new Point((startingLeftEyePointOptimized.X - 80), (yCoordStartSearchEyes + searchEyesAreaSize.Height + 15)), new Bgr(Color.Yellow));
frame.Draw("Right Eye Area", ref font, new Point(startingPointSearchEyes.X, startingPointSearchEyes.Y - 10), new Bgr(Color.Yellow));
frame.Draw("Left Eye Area", ref font, new Point(startingLeftEyePointOptimized.X + searchEyesAreaSize.Height / 2, startingPointSearchEyes.Y - 10), new Bgr(Color.Yellow));
#endregion
grayFrame.ROI = possibleROI_leftEye;
MCvAvgComp[][] leftEyesDetected = grayFrame.DetectHaarCascade(_eyes, 1.15, 0, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
grayFrame.ROI = Rectangle.Empty;
grayFrame.ROI = possibleROI_rightEye;
MCvAvgComp[][] rightEyesDetected = grayFrame.DetectHaarCascade(_eyes, 1.15, 0, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
grayFrame.ROI = Rectangle.Empty;
//If we are able to find eyes inside the possible face, it should be a face, maybe we find also a couple of eyes
if (leftEyesDetected[0].Length != 0 && rightEyesDetected[0].Length != 0)
{
//draw the face
frame.Draw(face.rect, new Bgr(Color.Violet), 2);
#region Hough Circles Eye Detection
grayFrame.ROI = possibleROI_leftEye;
CircleF[] leftEyecircles = grayFrame.HoughCircles(new Gray(180), new Gray(70), 5.0, 10.0, 1, 200)[0];
grayFrame.ROI = Rectangle.Empty;
foreach (CircleF circle in leftEyecircles)
{
float x = circle.Center.X + startingLeftEyePointOptimized.X;
float y = circle.Center.Y + startingLeftEyePointOptimized.Y;
frame.Draw(new CircleF(new PointF(x, y), circle.Radius), new Bgr(Color.RoyalBlue), 4);
}
grayFrame.ROI = possibleROI_rightEye;
CircleF[] rightEyecircles = grayFrame.HoughCircles(new Gray(180), new Gray(70), 5.0, 10.0, 1, 200)[0];
grayFrame.ROI = Rectangle.Empty;
foreach (CircleF circle in rightEyecircles)
{
float x = circle.Center.X + startingPointSearchEyes.X;
float y = circle.Center.Y + startingPointSearchEyes.Y;
frame.Draw(new CircleF(new PointF(x, y), circle.Radius), new Bgr(Color.RoyalBlue), 4);
}
#endregion
//Uncomment this to draw all rectangle eyes
//foreach (MCvAvgComp eyeLeft in leftEyesDetected[0])
//{
// Rectangle eyeRect = eyeLeft.rect;
// eyeRect.Offset(startingLeftEyePointOptimized.X, startingLeftEyePointOptimized.Y);
// frame.Draw(eyeRect, new Bgr(Color.Red), 2);
//}
//foreach (MCvAvgComp eyeRight in rightEyesDetected[0])
//{
// Rectangle eyeRect = eyeRight.rect;
// eyeRect.Offset(startingPointSearchEyes.X, startingPointSearchEyes.Y);
// frame.Draw(eyeRect, new Bgr(Color.Red), 2);
//}
}
imageBoxCapturedFrame.Image = frame;
}
}
private void face_detect()
{
gray = face_image.Convert <Gray, byte>();//將camera輸出影像轉為灰階(EmguCV 語法)
//人臉抓取語法
faces =
gray.DetectHaarCascade(haar, 1.2, 10,
HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(25, 25))[0];
Image Input = face_image.ToBitmap();//轉檔camera輸出影像為Bitmap
//判斷人臉抓取是否為空
if (faces.Length > 0)
{
if (c_flag == 0)
{
Camera_timer.Stop(); //抓取到人臉後camera_timer停止
Count_timer.Start(); //計數圖片顯示
}
else
{
//Array.Clear(pic, 0, pic.Length);
Countbox.Image = timePhotos[c_flag];
c_flag = 0;
//Array.Clear(pic, 0, pic.Length);
Camera_timer.Stop(); //抓取到人臉後camera_timer停止
MCvAvgComp face = faces[0]; //宣告取得的人臉為face
//face_image.Draw(face.rect, new Bgr(Color.Red), 3);//將camera輸出影像對應抓取到的人臉，標記紅框
//將取得的人臉分割出來並另存為Bitmap
ExtractedFace = new Bitmap(face.rect.Width, face.rect.Height);
FaceCanvas = Graphics.FromImage(ExtractedFace);
FaceCanvas.DrawImage(Input, 0, 0, face.rect, GraphicsUnit.Pixel);
ExtractedFace.RotateFlip(RotateFlipType.Rotate270FlipNone); //旋轉影像
pictureBoxCenter.Visible = true; //顯示大圖影像
pictureBoxCenter.Image = ExtractedFace; //將分割的人臉載入當前的picturebox中
pictureBoxCenter.SizeMode = PictureBoxSizeMode.Zoom;
Invalidate();//清空box，重新繪製圖片
//半透明處理
matrix = new ColorMatrix(nArray);
attributes.SetColorMatrix(matrix, ColorMatrixFlag.Default, ColorAdjustType.Bitmap);
Image srcImage = (Image)ExtractedFace;
Bitmap resultImage = new Bitmap(srcImage.Width, srcImage.Height);
Graphics g = Graphics.FromImage(resultImage);
g.DrawImage(srcImage, new Rectangle(0, 0, srcImage.Width, srcImage.Height), 0, 0, srcImage.Width, srcImage.Height, GraphicsUnit.Pixel, attributes);
ExtFaces = resultImage;
in_taiwan();
//分割動畫距離格數
vx = (pictureBoxCenter.Location.X - pic[faceNo].Location.X) / fps;
vy = (pictureBoxCenter.Location.Y - pic[faceNo].Location.Y) / fps;
picout();
faceNo = (faceNo + 1) % (cnt_x * cnt_y); //faceNO++，限制圖片載量(台灣外部)
faces = null; //抓取一次人臉，清空一次，釋放記憶體
Countbox.Visible = false;
}
}
//攝影機影像顯示
pictureBoxCamera.Image = face_image.ToBitmap();
pictureBoxCamera.SizeMode = PictureBoxSizeMode.Zoom;
}
public FaceController(MCvAvgComp f) : this(f, 0)
{
}
private void ProcessFrame(object sender, EventArgs arg)
{
Image<Bgr, Byte> ImageFrame = this.cameracapture.getFrame();
if (ImageFrame != null)
{
countframes += 1;
Image<Gray, byte> grayframe = cameracapture.getGrayFrame(ImageFrame);
grayframe._EqualizeHist();
MCvAvgComp[][] facesDetected = this.face.detectFace(grayframe, haarface);
if (facesDetected[0].Length == 1)
{
MCvAvgComp face = facesDetected[0][0];
//Set the region of interest on the faces
// Our Region of interest where find eyes will start with a sample estimation using face metric
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
Point startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
Point endingPointSearchEyes = new Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 2 / 9));
Point lowerEyesPointOptimized = new Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 2 / 9));
Point startingLeftEyePointOptimized = new Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Rectangle possibleROI_eyes = new Rectangle(startingPointSearchEyes, searchEyesAreaSize);
Rectangle possibleROI_rightEye = new Rectangle(startingPointSearchEyes, eyeAreaSize);
Rectangle possibleROI_leftEye = new Rectangle(startingLeftEyePointOptimized, eyeAreaSize);
grayframe.ROI = possibleROI_leftEye;
MCvAvgComp[][] leftEyesDetected = this.eye.detectEyes(grayframe, haareyes);
grayframe.ROI = Rectangle.Empty;
grayframe.ROI = possibleROI_rightEye;
MCvAvgComp[][] rightEyesDetected = this.eye.detectEyes(grayframe, haareyes);
grayframe.ROI = Rectangle.Empty;
//If we are able to find eyes inside the possible face, it should be a face, maybe we find also a couple of eyes
if (leftEyesDetected[0].Length != 0 && rightEyesDetected[0].Length != 0)
{
eyes_count += 1;
//draw the face
ImageFrame.Draw(face.rect, new Bgr(Color.Red), 2);
MCvAvgComp eyeLeft = leftEyesDetected[0][0];
MCvAvgComp eyeRight = leftEyesDetected[0][0];
// Draw the Left Eye
Rectangle eyeRectL = eyeLeft.rect;
eyeRectL.Offset(startingLeftEyePointOptimized.X, startingLeftEyePointOptimized.Y);
ImageFrame.Draw(eyeRectL, new Bgr(Color.Red), 2);
//Draw the Right Eye
Rectangle eyeRectR = eyeRight.rect;
eyeRectR.Offset(startingPointSearchEyes.X, startingPointSearchEyes.Y);
ImageFrame.Draw(eyeRectR, new Bgr(Color.Red), 2);
}
imageBox1.Image = ImageFrame;
}
}
}
void FaceGrabber(object sender, EventArgs e)
{
currentFrame = grabber.QueryFrame();
if (currentFrame != null)
{
label1.Show();
currentFrameCopy = currentFrame.Copy();
Image <Bgr, Byte> frame = grabber.QueryFrame();
Image <Gray, Byte> grayFrame = frame.Convert <Gray, Byte>();
grayFrame._EqualizeHist();
MCvAvgComp[][] facesDetected = grayFrame.DetectHaarCascade(_face, 1.1, 1, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(20, 20));
// MCvAvgComp[][] lefteyeDeteced = grayFrame.DetectHaarCascade(leye, 1.1, 1, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(20, 20));
if (facesDetected[0].Length == 1)
{
MCvAvgComp face = facesDetected[0][0];
#region on Face Metric Estimation --- based on empirical measuraments on a couple of photos --- a really trivial heuristic
//// Our Region of interest where find eyes will start with a sample estimation using face metric
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
Point startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
//Point endingPointSearchEyes = new Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
//richTextBox1.Text = face.rect.Top.ToString();
Size searchEyesAreaSize = new Size(face.rect.Width * 5 / 2, (face.rect.Height * 2 / 5));
//Point lowerEyesPointOptimized = new Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 2 / 9));
Point startingLeftEyePointOptimized = new Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Rectangle possibleROI_eyes = new Rectangle(startingPointSearchEyes, searchEyesAreaSize);
Rectangle possibleROI_rightEye = new Rectangle(startingPointSearchEyes, eyeAreaSize);
Rectangle possibleROI_leftEye = new Rectangle(startingLeftEyePointOptimized, eyeAreaSize);
#endregion
int widthNav = (frame.Width / 10 * 2);
int heightNav = (frame.Height / 10 * 2);
Rectangle nav = new Rectangle(new Point(frame.Width / 25 - widthNav / 2, frame.Height / 2 - heightNav / 2), searchEyesAreaSize);
frame.Draw(nav, new Bgr(Color.Lavender), 3);
Point cursor = new Point(face.rect.X + searchEyesAreaSize.Width / 2, yCoordStartSearchEyes);
grayFrame.ROI = possibleROI_eyes;
MCvAvgComp[][] EyesDetected = grayFrame.DetectHaarCascade(eyes, 1.15, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
grayFrame.ROI = Rectangle.Empty;
if (EyesDetected[0].Length != 0)
{
sw.Reset();
frame.Draw(face.rect, new Bgr(Color.Yellow), 1);
foreach (MCvAvgComp eye in EyesDetected[0])
{
Rectangle eyeRect = eye.rect;
eyeRect.Offset(possibleROI_eyes.X, possibleROI_eyes.Y);
grayFrame.ROI = eyeRect;
frame.Draw(eyeRect, new Bgr(Color.DarkSeaGreen), 2);
frame.Draw(possibleROI_eyes, new Bgr(Color.DeepPink), 2);
if (nav.Left < cursor.X && cursor.X < (nav.Left + 20 * nav.Width) && nav.Top < cursor.Y && cursor.Y < nav.Top + 3 * nav.Height)
{
LineSegment2D CursorDraw = new LineSegment2D(cursor, new Point(cursor.X, cursor.Y + 1));
frame.Draw(CursorDraw, new Bgr(Color.White), 3);
int right = (frame.Width * (cursor.X - nav.Right)) / nav.Width;
int xCoord = (frame.Width * (cursor.X - nav.Left)) / nav.Width + 2 * right;
int yCoord = (frame.Width * (cursor.Y - nav.Top)) / nav.Height;
Cursor.Position = new Point(xCoord, yCoord);
}
}
}
grayFrame.ROI = possibleROI_leftEye;
MCvAvgComp[][] leftEyesDetected = grayFrame.DetectHaarCascade(leye, 1.15, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
grayFrame.ROI = Rectangle.Empty;
grayFrame.ROI = possibleROI_rightEye;
MCvAvgComp[][] rightEyesDetected = grayFrame.DetectHaarCascade(reye, 1.15, 3, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
grayFrame.ROI = Rectangle.Empty;
//If we are able to find eyes inside the possible face, it should be a face, maybe we find also a couple of eyes
if (leftEyesDetected[0].Length != 0 && rightEyesDetected[0].Length != 0)
{
sw.Stop();
//draw the face
frame.Draw(face.rect, new Bgr(Color.Violet), 2);
grayFrame.ROI = possibleROI_leftEye;
grayFrame.ROI = Rectangle.Empty;
grayFrame.ROI = possibleROI_rightEye;
grayFrame.ROI = Rectangle.Empty;
}
else
if (leftEyesDetected[0].Length == 0)
{
timer1.Enabled = true;
sw.Start();
//timer1_Tick();
if (label1.Text == "0:00:03")
{
DoMouseClick();
sw.Reset();
}
}
imageBoxSkin.Image = frame;
}
}
}
void FrameGrabber(object sender, EventArgs e)
{
//We are acquiring a new frame
//_capture.SetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_FRAME_WIDTH, 1280);
//_capture.SetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_FRAME_HEIGHT, 720);
frame = _capture.QueryFrame().Resize(800, 800, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//We convert it to grayscale
grayFrame = frame.Convert <Gray, Byte>();
//Equalization step
grayFrame._EqualizeHist();
// We assume there's only one face in the video
//MCvAvgComp[][] facesDetected = grayFrame.DetectHaarCascade(_faces, faceScaleRate, faceMinNeighbourTheshold, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(frame.Height / 4, frame.Width / 4));
if (StopFace == false)
{
facesDetected = grayFrame.DetectHaarCascade(_faces, faceScaleRate, faceMinNeighbourTheshold, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(25, 25));
}
if (facesDetected[0].Length == 1)
{
MCvAvgComp face = facesDetected[0][0];
//Set the region of interest on the faces
#region Search Roi based on Face Metric Estimation --- based on empirical measuraments on a couple of photos --- a really trivial heuristic
// Our Region of interest where find eyes will start with a sample estimation using face metric
//Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 12);
//startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
//Point endingPointSearchEyes = new Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
//Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 2 / 10));
//Point lowerEyesPointOptimized = new Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
//Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 3 / 10));
//startingLeftEyePointOptimized = new Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Int32 yCoordStartSearchEyes = face.rect.Top + (face.rect.Height * 3 / 11);
startingPointSearchEyes = new Point(face.rect.X, yCoordStartSearchEyes);
Point endingPointSearchEyes = new Point((face.rect.X + face.rect.Width), yCoordStartSearchEyes);
Size searchEyesAreaSize = new Size(face.rect.Width, (face.rect.Height * 2 / 9));
Point lowerEyesPointOptimized = new Point(face.rect.X, yCoordStartSearchEyes + searchEyesAreaSize.Height);
Size eyeAreaSize = new Size(face.rect.Width / 2, (face.rect.Height * 2 / 9));
startingLeftEyePointOptimized = new Point(face.rect.X + face.rect.Width / 2, yCoordStartSearchEyes);
Rectangle possibleROI_eyes = new Rectangle(startingPointSearchEyes, searchEyesAreaSize);
possibleROI_rightEye = new Rectangle(startingPointSearchEyes, eyeAreaSize);
possibleROI_leftEye = new Rectangle(startingLeftEyePointOptimized, eyeAreaSize);
#endregion
#region Drawing Utilities
// Let's draw our search area, first the upper line
frame.Draw(new LineSegment2D(startingPointSearchEyes, endingPointSearchEyes), new Bgr(Color.White), 3);
// draw the bottom line
frame.Draw(new LineSegment2D(lowerEyesPointOptimized, new Point((lowerEyesPointOptimized.X + face.rect.Width), (yCoordStartSearchEyes + searchEyesAreaSize.Height))), new Bgr(Color.White), 3);
// draw the eyes search vertical line
frame.Draw(new LineSegment2D(startingLeftEyePointOptimized, new Point(startingLeftEyePointOptimized.X, (yCoordStartSearchEyes + searchEyesAreaSize.Height))), new Bgr(Color.White), 3);
MCvFont font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.6d, 0.6d);
frame.Draw("", ref font, new Point((startingLeftEyePointOptimized.X - 80), (yCoordStartSearchEyes + searchEyesAreaSize.Height + 15)), new Bgr(Color.Yellow));
frame.Draw("Right Eye", ref font, new Point(startingPointSearchEyes.X, startingPointSearchEyes.Y - 10), new Bgr(Color.Yellow));
frame.Draw("Left Eye", ref font, new Point(startingLeftEyePointOptimized.X + searchEyesAreaSize.Height / 2, startingPointSearchEyes.Y - 10), new Bgr(Color.Yellow));
#endregion
if (STopROI == false)
{
grayFrame.ROI = possibleROI_rightEye;
rightEyesDetected = grayFrame.DetectHaarCascade(_eyes, rightScaleRate, rightMinimumNeighbourThreshold, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(60, 60));
grayFrame.ROI = Rectangle.Empty;
grayFrame.ROI = possibleROI_leftEye;
leftEyesDetected = grayFrame.DetectHaarCascade(_eyes, leftScaleRate, leftMinimumNeighbourThreshold, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(60, 60));
grayFrame.ROI = Rectangle.Empty;
}
//If we are able to find eyes inside the possible face, it should be a face, maybe we find also a couple of eyes
//if (leftEyesDetected[0].Length != 0 && rightEyesDetected[0].Length != 0)
//{
//draw the face
frame.Draw(face.rect, new Bgr(Color.Violet), 2);
#region Hough Circles Eye Detection
Application.Idle += calcRightEye;
Application.Idle += calcLeftEye;
#endregion
imageBox1.Image = frame;
}
}
public void CrearTrainedFace(MCvAvgComp face)
{
//_TrainedFace se utiliza para enviar al proceso de reconocimiento recognizer.Recognize(_TrainedFace);
_TrainedFace = _ActualFrame.Copy(face.rect).Convert <Gray, byte>().Resize(100, 100, INTER.CV_INTER_CUBIC);
}
void Recognize(MCvAvgComp f)
{
result = current_frame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//draw the face detected in the 0th (gray) channel with blue color
current_frame.Draw(f.rect, new Bgr(Color.Red), 2);
if (training_images.ToArray().Length != 0)
{
float[] distances = recognizer.GetEigenDistances(result);
name = recognizer.Recognize(result);
if (name == null || name == "")
{
name = "someone_" + unknown_people;
unknown_people++;
MessageBox.Show("Unknown person detected.");
}
if (!recognized_people.Exists(n => n == name))
{
recognized_people.Add(name);
recognized_faces.Add(result);
last_positions.Add(f.rect);
recognized_flags.Add(true);
m_Terminal.Express("Person recognized: " + name, Expression_Types.Information);
}
else
{
int index = recognized_people.IndexOf(name);
recognized_faces[index] = result;
// Vision.voice.Speak("Hi " + name + "!, good to see you again.");
recognized_flags[index] = true;
}
detected_faces.Add(result);
//Draw the label for each face detected and recognized
current_frame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));
if (distances.Length > 0)
{
//Cerebro.consola.println(distances[0].ToString());
float min_distance = 9999999.0f;
foreach (float distance in distances)
{
if (distance < min_distance)
{
min_distance = distance;
}
}
if (min_distance > 1600)
{
training_images.Add(result);
face_labels.Add(name);
recognized_people.Add(name);
Save_Data();
}
}
}
else
{
training_images.Add(result);
face_labels.Add("Unknown");
recognized_people.Add("Unknown");
Save_Data();
}
if (unknown_people > 0)
{
m_Terminal.Express(unknown_people + " unknown people detected.", Expression_Types.Information);
}
}
public void FrameGrabber2(object sender, EventArgs e)
{
NamePersons.Add("");
face = new HaarCascade("haarcascade_frontalface_default.xml");
//Utility UTl = new Utility();
//Get the current frame form capture device
//Image<Bgr, Byte> currentFrame = UTl.ImageToBgrByte(Image);
try
{
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
}
catch (Exception exp)
{
grabber = new Capture("video002.mp4");
}
//Convert it to Grayscale
gray = currentFrame.Convert <Gray, Byte>();
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(face, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
//Action for element detected
try
{
MCvAvgComp f = facesDetected[0][0];
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//draw the face detected in the 0th (gray) channel with blue color
currentFrame.Draw(f.rect, new Bgr(Color.White), 2);
}
catch (Exception ex)
{
//MessageBox.Show("Camera Error: Empty frames arrived" + ex.Message.ToString(), "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
if (trainingImages.ToArray().Length != 0)
{
//TermCriteria for face recognition with numbers of trained images like maxIteration
MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);
//Eigen face recognizer
EigenObjectRecognizer recognizer = new EigenObjectRecognizer(
trainingImages.ToArray(),
labels.ToArray(),
3000,
ref termCrit);
name = recognizer.Recognize(result);
//Draw the label for each face detected and recognized
//currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));
}
//NamePersons[t - 1] = name;
NamePersons.Add("");
t = 0;
//Names concatenation of persons recognized
//for (int nnn = 0; nnn < facesDetected[0].Length; nnn++)
//{
// names = names + NamePersons[nnn] + ", ";
//}
//Show the faces procesed and recognized
emguImgFace.Image = currentFrame;
lblCandidateID.Text = name;
name = "";
//Clear the list(vector) of names
NamePersons.Clear();
}
