face recognition [closed]
this is the part of code that we should use here the extracted faces are stocked in a folder
private void button2_Click(object sender, System.EventArgs e)
{
try
{
//Trained face counter
ContTrain = ContTrain + 1;
//Get a gray frame from capture device
gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//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 each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert<Gray, byte>();
break;
}
//resize face detected image for force to compare the same size with the
//test image with cubic interpolation type method
TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
trainingImages.Add(TrainedFace);
labels.Add(textBox1.Text);
//Show face added in gray scale
imageBox1.Image = TrainedFace;
//Write the number of triained faces in a file text for further load
File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");
//Write the labels of triained faces in a file text for further load
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");
File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
}
MessageBox.Show(textBox1.Text + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
catch
{
MessageBox.Show("Enable the face detection first", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
void FrameGrabber(object sender, EventArgs e)
{
label3.Text = "0";
//label4.Text = "";
NamePersons.Add("");
//Get the current frame form capture device
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//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 each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
t = t + 1;
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.Red), 2);
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("");
//Set the number of faces detected on the scene
label3.Text = facesDetected[0].Length.ToString();
/*
//Set the region of interest on the faces
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 ey in eyesDetected[0])
{
Rectangle eyeRect = ey.rect;
eyeRect.Offset(f.rect.X, f.rect.Y);
currentFrame.Draw(eyeRect, new Bgr(Color.Blue), 2);
}
*/
}
t = 0;
//Names concatenation of persons recognized ...
now, where is your question ?
can't help you with anything related to emgu, or c# (that's all pretty off-topic here), but 2 things:
re-training the facereco for each detected face is a total unnessecary waste. you want to do that only once, or when you data changed. also serializing the trained model, and re-loading that, will be much faster, than re-training.
if your dataset is changing continuously, consider using the lbp face reco instead. it has an update method, where you can just add new items, without uploading the complete imageset.
I make a search about lbp face reco, but i didnt find any thing like that in c# I found it in c++ i found someone who is using files instead of database, my problem for now is: who to use the code above which detect and make recognition, with my code which can only detect? i want to make a button called recognize so that when i click it the research for the matching start, comparing the input image with the images in Access database?
some emgu version should have lbp and fisher reco , too. (but no idea about the db, sorry.)