public string SaveString(string inputpath, string label, ref int index)
{
try
{
ContTrain = ContTrain + 1;
bool detected = false;
gray = new Image <Gray, byte>(inputpath);
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = gray.Copy(f.rect).Convert <Gray, byte>();
detected = true;
break;
}
if (!detected)
{
return(string.Empty);
}
TrainedFace = TrainedFace.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
TrainedFace = new Image <Gray, byte>(ImageProcessing.ImagePreProcessing(TrainedFace.ToBitmap()));
trainingImages.Add(TrainedFace);
labels.Add(label);
UpdateRecognizer();
return(BasicOperations.SaveImage(TrainedFace.ToBitmap(), ref index));;
}
catch
{
return(string.Empty);
}
}
private void btnBroweImg_Click(object sender, EventArgs e)
{
if (frmLogin.admin == false)
{
frmLogin loginForm = new frmLogin();
loginForm.Show();
return;
}
if (txtName.Text == "")
{
MessageBox.Show("Please enter name first.");
return;
}
openFileDialog1.FileName = String.Empty;
openFileDialog1.Filter = "JPEG Files (*.jpeg)|*.jpeg|PNG Files (*.png)|*.png|JPG Files (*.jpg)|*.jpg|GIF Files (*.gif)|*.gif";
openFileDialog1.Title = "Please select an image file to training.";
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
grabber = new Capture(openFileDialog1.FileName);
currentFrame = grabber.QueryFrame().Resize(473, 355, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Trained face counter
ContTrain = ContTrain + 1;
//Get a gray frame from capture device
gray = currentFrame.Convert <Gray, Byte>();
//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 = TrainedFace.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
trainingImages.Add(TrainedFace);
labels.Add(txtName.Text + "|" + (ContTrain).ToString());
//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(txtName.Text + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
txtName.Text = "";
}
}