private string[] imageCheckRecognize(Image <Gray, byte> image)
{
string matchedResult = eigenRecog.Recognise(image);
string[] matchedData = matchedResult.Split(' ');
return(matchedData);
}
private void test()
{
Image <Gray, byte> testImage = new Image <Gray, byte>("E:/Images/tmp.jpg");
result = Eigen_Recog.Recognise(testImage);
distance = Eigen_Recog.Get_Eigen_Distance;
textBox1.Text = result;
textBox2.Text = distance.ToString();
imageBox7.Image = testImage;
imageBox1.Image = db.getResultImage(result);
}
private void ProcessFrame(object sender, EventArgs arg)
{
if (imageFrame != null)
{
Image <Gray, byte> greyImage = imageFrame.Copy().Convert <Gray, byte>();
greyImage = greyImage.SmoothMedian(3);
//stopWatch.Start();
var faces = face.Detect(greyImage, 1.3, 6, HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(120, 120), new Size(300, 300));
if (faces.Length == 0)
{
var eyeObjects = eyeWithGlass.DetectMultiScale(greyImage, 1.3, 6, minEye, maxEye);
if (eyeObjects.Length == 2)
{
#region comment
/*Console.WriteLine("helper");
* if(eyeObjects[0].X > eyeObjects[1].X)
* {
* var temp = eyeObjects[0];
* eyeObjects[0] = eyeObjects[1];
* eyeObjects[1] = temp;
* }
* int betweeneLength = eyeObjects[1].X - eyeObjects[0].X;
* int middleposition = eyeObjects[0].X + ((betweeneLength + eyeObjects[1].Width )/ 2);
* int forheadpeak = (int)(0.8 * betweeneLength);//
* int forheadpeakpeak = (int)(0.7 * betweeneLength);//
* int forheadbelowpeak = (int)(0.4 * betweeneLength);
* int foreheadpoint = (int)(0.6 * betweeneLength);
* int neareyebrowpoint = (int)(0.2 * betweeneLength);
* int lefteyebrowpoint = eyeObjects[0].X;//
* int righteyebrowpoint = eyeObjects[0].X + betweeneLength + eyeObjects[1].Width;//
* //int nosepoint =
* int xx = (int)((5.0 / 12.0) * betweeneLength);
* int margin = (int)((1.5 / 8.0) * betweeneLength);
*
* int x1 = (int)((1.0 / 16.0) * betweeneLength);
*
*
* int round = 3;
* int around = round-2;
* double tempcolor = 0;
* for (int i = 0; i<round; i++)
* {
* for (int j = 0; j < round; j++)
* {
* tempcolor += greyImage[middleposition - around + i, eyeObjects[0].Y + forheadpeak - around + j].Intensity;
* }
* }
* Gray skincolor = new Gray(tempcolor/(round*round));
* Point[] p = new Point[7];
* p[0] = new Point(middleposition, eyeObjects[0].Y - forheadpeak);
*
* p[1] = new Point(eyeObjects[0].X + (eyeObjects[0].Width / 2), eyeObjects[0].Y - forheadpeakpeak);
* p[2] = new Point(eyeObjects[0].X - x1, eyeObjects[0].Y - forheadbelowpeak);
* p[3] = new Point(lefteyebrowpoint - margin, eyeObjects[0].Y + (eyeObjects[0].Height/6));
*
* p[4] = new Point(righteyebrowpoint + margin, eyeObjects[0].Y + (eyeObjects[0].Height /6));
* p[5] = new Point(righteyebrowpoint + x1, eyeObjects[0].Y - forheadbelowpeak);
* p[6] = new Point(eyeObjects[1].X + (eyeObjects[1].Width / 2), eyeObjects[0].Y - forheadpeakpeak);
*
* //imageFrame.Draw(new Rectangle(new Point(eyeObjects[0].X, eyeObjects[0].Y), new Size(betweeneLength + eyeObjects[1].Width, eyeObjects[0].Height)), new Bgr(Color.Aqua), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition,eyeObjects[0].Y+ foreheadpoint), 1), new Bgr(Color.Yellow), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition,eyeObjects[0].Y - forheadpeak), 1), new Bgr(Color.Yellow), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.Gold), 2);
* //imageFrame.Draw(new CircleF(new PointF(lefteyebrowpoint - margin, eyeObjects[0].Y), 1), new Bgr(Color.AliceBlue), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint + margin, eyeObjects[0].Y), 1), new Bgr(Color.AliceBlue), 2);
* //imageFrame.Draw(new CircleF(new PointF(lefteyebrowpoint, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.DrawPolyline(p,true, new Bgr(Color.Azure), 2);
* greyImage.FillConvexPoly(p, skincolor);
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[0].X - x1, eyeObjects[0].Y - forheadbelowpeak), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint + x1, eyeObjects[0].Y - forheadbelowpeak), 1), new Bgr(Color.LimeGreen), 2);
*
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[0].X + (eyeObjects[0].Width / 2), eyeObjects[0].Y - forheadpeakpeak), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[1].X + (eyeObjects[1].Width / 2), eyeObjects[0].Y - forheadpeakpeak), 1), new Bgr(Color.LimeGreen), 2);
*/
#endregion
}
else //not see eye in frame
{
learningTag = true;
name = "Processing...";
userid = "Processing...";
timestampFlag = true;
faceRectangle = Rectangle.Empty;
realfaceRectangle = Rectangle.Empty;
label2.ForeColor = Color.DeepSkyBlue;
label2.Text = "Idle";
progressBar1.Value = 0;
recogNameResult.Clear();
recogDistanceResult.Clear();
Console.WriteLine("Clear");
}
ARDisplayFlag = false;
}
else
{
Parallel.ForEach(faces, facecount =>
{
try {
facePosition = new Point(facecount.rect.X, facecount.rect.Y);
faceRectangleSize = new Size(facecount.rect.Width, facecount.rect.Height);
faceRectangle = new Rectangle(facePosition, faceRectangleSize);
greyImage.ROI = faceRectangle;
var eyeObjects = eyeWithGlass.DetectMultiScale(greyImage, 1.3, 6, minEye, maxEye);
greyImage.ROI = Rectangle.Empty;
if (eyeObjects.Length == 2)
{
Console.WriteLine("eye detected...");
if (eyeObjects[0].X > eyeObjects[1].X)
{
var temp = eyeObjects[0];
eyeObjects[0] = eyeObjects[1];
eyeObjects[1] = temp;
}
int betweeneLength = eyeObjects[1].X - eyeObjects[0].X;
int lefteyebrowpoint = eyeObjects[0].X; //
int righteyebrowpoint = eyeObjects[1].X + eyeObjects[1].Width; //
int margin = (int)((1.5 / 8.0) * betweeneLength);
int neareyebrowpoint = (int)(0.2 * betweeneLength);
int faceheight = (int)(2.3 * betweeneLength);
realFacePosition = new Point(facePosition.X + lefteyebrowpoint - margin, facePosition.Y + eyeObjects[0].Y - neareyebrowpoint);
realfaceRectangleSize = new Size((righteyebrowpoint + margin) - (lefteyebrowpoint - margin), faceheight);
realfaceRectangle = new Rectangle(realFacePosition, realfaceRectangleSize);
greyImage.ROI = realfaceRectangle;
imageroi = greyImage.Copy();
greyImage.ROI = Rectangle.Empty;
if (eigenRecog.IsTrained)
{
imageroi._EqualizeHist();
imageroi = imageroi.Resize(ROIwidth, ROIheight, INTER.CV_INTER_LINEAR);
Image <Gray, byte> plainImage = imageroi.Copy();
imageroi.FillConvexPoly(pL, new Gray(128));
imageroi.FillConvexPoly(pR, new Gray(128));
//find the most relative face
progressBar1.Value = recogNameResult.Count;
if (recogNameResult.Count == maxImageCount && !ARDisplayFlag)
{
Console.WriteLine("Processing...");
int max = 0;
string mostFace = "";
double euclidVal = 0;
foreach (string value in recogNameResult.Distinct())
{
Console.WriteLine("\"{0}\" occurs {1} time(s).\n", value, recogNameResult.Count(v => v == value));
if (recogNameResult.Count(v => v == value) > max)
{
max = recogNameResult.Count(v => v == value);
mostFace = value;
}
}
name = mostFace;
userid = mydb.getUserIdFromSerrogate(name);
if (learningTag && !(name.Equals("UnknownNull") || name.Equals("UnknownFace")))
{
learnImage = imageroi;
matchedResult = eigenRecog.Recognise(learnImage);
//matchedResult = fishRecog.Recognise(learnImage);
string[] matchedData = matchedResult.Split(' ');
if ((Double.Parse(matchedData[1]) <= eigenRecog.getRecognizeTreshold) && (Double.Parse(matchedData[1]) != 0))
//if ((Double.Parse(matchedData[1]) <= fishRecog.getRecognizeTreshold) && (Double.Parse(matchedData[1]) != 0))
{
int ItemIndex = 0;
List <double> recogResultSum = new List <double>();
foreach (var item in recogNameResult)
{
if (mydb.getUserIdFromSerrogate(item).Equals(userid) && !item.Equals("UnknownNull"))
{
recogResultSum.Add(recogDistanceResult[ItemIndex]);
}
ItemIndex++;
}
meanDistance = recogResultSum.Sum() / recogResultSum.Count;
euclidVal = falsePositiveCheck(mydb.getComputeResultImage(name), imageroi.Copy());
if (euclidVal < 9000)
{
confident = (((double)recogResultSum.Count / (double)maxImageCount) * 100) * (1.00 - (euclidVal - (meanDistance * 130 / 100)) / 4500.00);
if (confident > 100)
{
confident = 100;
}
if (confident >= 80)
//if (meanDistance <= fishRecog.getRecognizeTreshold)
{
learnImage.Save(folderPath + tempPath);
plainImage.Save(folderPath + tempPath2);
Console.WriteLine(folderPath + tempPath);
string dbPath = (folderPath + tempPath).Replace("\\", "/");
string dbPathPlain = (folderPath + tempPath2).Replace("\\", "/");
mydb.InsertImageTraining(int.Parse(userid), dbPathPlain, dbPath, false);
//
//auto train
//
if (mydb.getSpecifyImageCount(userid) > 5)
{
mydb.DeleteOldestImage(userid);
}
//eigenRecog.reloadData();
//fishRecog.reloadData();
learningTag = false;
Console.WriteLine("Learning:" + userid + " Distance:" + meanDistance);
}
else
{
Console.WriteLine("Distance:" + meanDistance + "\n");
}
}
}
if (timestampFlag)
{
Image <Gray, byte> resultImage = imageroi;
resultImage.Save(folderPath + tempPath);
Console.WriteLine(folderPath + tempPath);
string dbPath = (folderPath + tempPath).Replace("\\", "/");
mydb.InsertTimestamp(userid, Environment.MachineName, confident.ToString(), dbPath, meanDistance.ToString(), euclidVal.ToString());
timestampFlag = false;
}
}
}
else
{
Console.WriteLine("recognizing...");
matchedResult = eigenRecog.Recognise(imageroi); //get serro+distance
Console.WriteLine("Result:" + matchedResult + "\n");
string[] matchedData = matchedResult.Split(' ');
if (!matchedResult[0].Equals("UnknownNull") && !matchedResult[0].Equals("UnknownFace"))
{
//Console.WriteLine(matchedData[0] +" "+ matchedData[1]);
recogNameResult.Add(matchedData[0]);
recogDistanceResult.Add(Double.Parse(matchedData[1]));
//File.AppendAllText(@"C:\Users\Xypher\Desktop\test2.csv", matchedData[1]+"\r\n");
}
}
}
}
}
catch
{
}
});
}
/*stopWatch.Stop();
* TimeSpan ts = stopWatch.Elapsed;
*
* string elapsedTime = String.Format("{0}",ts.TotalMilliseconds * 10000);
* stopWatch.Reset();*/
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
if (imageFrame != null)
{
Image <Gray, byte> greyImage = imageFrame.Copy().Convert <Gray, byte>();
//greyImage._SmoothGaussian(3);
//greyImage._EqualizeHist();
stopWatch.Start();
var faces = face.Detect(greyImage, 1.2, 6, HAAR_DETECTION_TYPE.FIND_BIGGEST_OBJECT, new Size(120, 120), new Size(200, 200));
if (faces.Length == 0)
{
var eyeObjects = eyeWithGlass.DetectMultiScale(greyImage, 1.2, 6, minEye, maxEye);
if (eyeObjects.Length == 2)
{
#region comment
/*Console.WriteLine("helper");
* if(eyeObjects[0].X > eyeObjects[1].X)
* {
* var temp = eyeObjects[0];
* eyeObjects[0] = eyeObjects[1];
* eyeObjects[1] = temp;
* }
* int betweeneLength = eyeObjects[1].X - eyeObjects[0].X;
* int middleposition = eyeObjects[0].X + ((betweeneLength + eyeObjects[1].Width )/ 2);
* int forheadpeak = (int)(0.8 * betweeneLength);//
* int forheadpeakpeak = (int)(0.7 * betweeneLength);//
* int forheadbelowpeak = (int)(0.4 * betweeneLength);
* int foreheadpoint = (int)(0.6 * betweeneLength);
* int neareyebrowpoint = (int)(0.2 * betweeneLength);
* int lefteyebrowpoint = eyeObjects[0].X;//
* int righteyebrowpoint = eyeObjects[0].X + betweeneLength + eyeObjects[1].Width;//
* //int nosepoint =
* int xx = (int)((5.0 / 12.0) * betweeneLength);
* int xxx = (int)((1.5 / 8.0) * betweeneLength);
*
* int x1 = (int)((1.0 / 16.0) * betweeneLength);
*
*
* int round = 3;
* int around = round-2;
* double tempcolor = 0;
* for (int i = 0; i<round; i++)
* {
* for (int j = 0; j < round; j++)
* {
* tempcolor += greyImage[middleposition - around + i, eyeObjects[0].Y + forheadpeak - around + j].Intensity;
* }
* }
* Gray skincolor = new Gray(tempcolor/(round*round));
* Point[] p = new Point[7];
* p[0] = new Point(middleposition, eyeObjects[0].Y - forheadpeak);
*
* p[1] = new Point(eyeObjects[0].X + (eyeObjects[0].Width / 2), eyeObjects[0].Y - forheadpeakpeak);
* p[2] = new Point(eyeObjects[0].X - x1, eyeObjects[0].Y - forheadbelowpeak);
* p[3] = new Point(lefteyebrowpoint - xxx, eyeObjects[0].Y + (eyeObjects[0].Height/6));
*
* p[4] = new Point(righteyebrowpoint + xxx, eyeObjects[0].Y + (eyeObjects[0].Height /6));
* p[5] = new Point(righteyebrowpoint + x1, eyeObjects[0].Y - forheadbelowpeak);
* p[6] = new Point(eyeObjects[1].X + (eyeObjects[1].Width / 2), eyeObjects[0].Y - forheadpeakpeak);
*
* //imageFrame.Draw(new Rectangle(new Point(eyeObjects[0].X, eyeObjects[0].Y), new Size(betweeneLength + eyeObjects[1].Width, eyeObjects[0].Height)), new Bgr(Color.Aqua), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition,eyeObjects[0].Y+ foreheadpoint), 1), new Bgr(Color.Yellow), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition,eyeObjects[0].Y - forheadpeak), 1), new Bgr(Color.Yellow), 2);
* //imageFrame.Draw(new CircleF(new PointF(middleposition, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.Gold), 2);
* //imageFrame.Draw(new CircleF(new PointF(lefteyebrowpoint - xxx, eyeObjects[0].Y), 1), new Bgr(Color.AliceBlue), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint + xxx, eyeObjects[0].Y), 1), new Bgr(Color.AliceBlue), 2);
* //imageFrame.Draw(new CircleF(new PointF(lefteyebrowpoint, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint, eyeObjects[0].Y - neareyebrowpoint), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.DrawPolyline(p,true, new Bgr(Color.Azure), 2);
* greyImage.FillConvexPoly(p, skincolor);
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[0].X - x1, eyeObjects[0].Y - forheadbelowpeak), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(righteyebrowpoint + x1, eyeObjects[0].Y - forheadbelowpeak), 1), new Bgr(Color.LimeGreen), 2);
*
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[0].X + (eyeObjects[0].Width / 2), eyeObjects[0].Y - forheadpeakpeak), 1), new Bgr(Color.LimeGreen), 2);
* //imageFrame.Draw(new CircleF(new PointF(eyeObjects[1].X + (eyeObjects[1].Width / 2), eyeObjects[0].Y - forheadpeakpeak), 1), new Bgr(Color.LimeGreen), 2);
*/
#endregion
}
else //not see eye in frame
{
name = "Processing...";
learningTag = true;
faceRectangle = Rectangle.Empty;
realfaceRectangle = Rectangle.Empty;
recogNameResult.Clear();
recogDistanceResult.Clear();
Console.WriteLine("Clear");
}
}
else
{
Parallel.ForEach(faces, facecount =>
{
try
{
facePosition = new Point(facecount.rect.X, facecount.rect.Y);
faceRectangleSize = new Size(facecount.rect.Width, facecount.rect.Height);
faceRectangle = new Rectangle(facePosition, faceRectangleSize);
greyImage.ROI = faceRectangle;
var eyeObjects = eyeWithGlass.DetectMultiScale(greyImage, 1.2, 6, minEye, maxEye);
greyImage.ROI = System.Drawing.Rectangle.Empty;
if (eyeObjects.Length == 2)
{
Console.WriteLine("eye detected...");
if (eyeObjects[0].X > eyeObjects[1].X)
{
var temp = eyeObjects[0];
eyeObjects[0] = eyeObjects[1];
eyeObjects[1] = temp;
}
int betweeneLength = eyeObjects[1].X - eyeObjects[0].X;
int lefteyebrowpoint = eyeObjects[0].X; //
int righteyebrowpoint = eyeObjects[0].X + betweeneLength + eyeObjects[1].Width; //
int xxx = (int)((1.5 / 8.0) * betweeneLength);
int neareyebrowpoint = (int)(0.2 * betweeneLength);
int faceheight = (int)(2.3 * betweeneLength);
realFacePosition = new Point(facePosition.X + lefteyebrowpoint - xxx, facePosition.Y + eyeObjects[0].Y - neareyebrowpoint);
realfaceRectangleSize = new Size((righteyebrowpoint + xxx) - (lefteyebrowpoint - xxx), faceheight);
realfaceRectangle = new Rectangle(realFacePosition, realfaceRectangleSize);
greyImage.ROI = realfaceRectangle;
imageroi = greyImage.Copy();
greyImage.ROI = new Rectangle();
if (eigenRecog.IsTrained)
{
imageroi._EqualizeHist();
imageroi = imageroi.Resize(ROIwidth, ROIheight, INTER.CV_INTER_LINEAR);
//find the most relative face
if (recogNameResult.Count == maxImageCount)
{
Console.WriteLine("Processing...");
int max = 0;
string mostFace = "";
foreach (string value in recogNameResult.Distinct())
{
Console.WriteLine("\"{0}\" occurs {1} time(s).\n", value, recogNameResult.Count(v => v == value));
if (recogNameResult.Count(v => v == value) > max)
{
max = recogNameResult.Count(v => v == value);
mostFace = value;
}
}
name = mostFace;
if (learningTag && !(name.Equals("UnknownNull") || name.Equals("UnknownFace")))
{
learnImage = imageroi;
matchedResult = eigenRecog.Recognise(learnImage);
string[] matchedData = matchedResult.Split(' ');
if ((Double.Parse(matchedData[1]) <= eigenRecog.getRecognizeTreshold) && (Double.Parse(matchedData[1]) != 0))
{
meanDistance = recogDistanceResult.Sum() / maxImageCount;
if (meanDistance <= eigenRecog.getRecognizeTreshold)
{
learnImage.Save(tempPath);
mydb.InsertImageTraining(name, tempPath, false);
if (mydb.getSpecifyImageCount(name) > 3)
{
mydb.DeleteOldestImage(name);
}
eigenRecog.reloadData();
learningTag = false;
Console.WriteLine("Learning:" + name + " Distance:" + meanDistance);
}
else
{
Console.WriteLine("Distance:" + meanDistance + "\n");
}
}
}
}
else
{
Console.WriteLine("recognizing...");
matchedResult = eigenRecog.Recognise(imageroi);
Console.WriteLine("Result:" + matchedResult + "\n");
File.AppendAllText(@logFolder + logName + "_ver1.0.txt", "Result:" + matchedResult + "\r\n");
string[] matchedData = matchedResult.Split(' ');
if (!matchedResult[0].Equals("UnknownNull") && !matchedResult[0].Equals("UnknownFace"))
{
//Console.WriteLine(matchedData[0] +" "+ matchedData[1]);
recogNameResult.Add(matchedData[0]);
recogDistanceResult.Add(Double.Parse(matchedData[1]));
}
}
}
}
}
catch (Exception e)
{
Console.Write(e);
}
});
}
stopWatch.Stop();
TimeSpan ts = stopWatch.Elapsed;
// Format and display the TimeSpan value.
string elapsedTime = String.Format("{0}",
ts.TotalMilliseconds * 10000);
textBox2.Text = elapsedTime;
//listView1.Items.Add(elapsedTime);
//File.AppendAllText(@logFolder + logName + "_ver1.0.txt", "Frametime: "+elapsedTime+"\r\n");
stopWatch.Reset();
}
}