private void LoadTrainnedFace()
{
try
{
LabelList.Clear();
TrainingImages.Clear();
// Load haarcascades for face detection
Face = new HaarCascade("haarcascade_frontalface_default.xml");
// Load the number of trained faces
var files = GetAllFiles(Application.StartupPath + "/TrainedFaces");
TrainedFacesCounter = files.Count;
foreach (var file in files)
{
TrainingImages.Add(new Image <Gray, byte>(file.FullName));
LabelList.Add(file.Name.Split('@')[0]);
}
}
catch
{
// By pass
}
}
public bool AddTrainingImage(string filename)
{
if (File.Exists(filename))
{
if (!TrainingImages.Contains(filename))
{
var fn = Path.GetFileNameWithoutExtension(filename);
var extension = Path.GetExtension(filename);
var fn_mark = Path.Combine(Path.GetDirectoryName(filename), fn + "_train" + extension);
if (File.Exists(fn_mark))
{
MarkedTrainingImages.Add(fn_mark);
TrainingImages.Add(filename);
return(true);
}
else
{
return(false);
}
}
else
{
return(false);
}
}
else
{
return(false);
}
}
private void FaceMonitoring(object sender, EventArgs e)
{
try
{
// Get the current frame form capture device
CurrentFrame = Grabber.QueryFrame().Resize(320, 240, INTER.CV_INTER_CUBIC);
//Video.Serve(CurrentFrame.Bytes);
//System.Diagnostics.Debug.Print(Convert.ToBase64String(CurrentFrame.Bytes));
// Convert it to Grayscale
Gray = CurrentFrame.Convert <Gray, byte>();
// Face Detector
MCvAvgComp[][] facesDetected = Gray.DetectHaarCascade(Face, 1.2, 10, HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
if (facesDetected == null)
{
return;
}
// Action for each element detected
foreach (MCvAvgComp face in facesDetected[0])
{
Result = CurrentFrame.Copy(face.rect).Convert <Gray, byte>().Resize(100, 100, INTER.CV_INTER_CUBIC);
// Draw the face detected in the 0th (gray) channel with blue color
CurrentFrame.Draw(face.rect, new Bgr(Color.Red), 2);
// Check if there is trained images to find a match
if (TrainingImages.ToArray().Length != 0)
{
var eigenDistanceThreshold = 3000;
var eps = 0.001;
// TermCriteria for face recognition with numbers of trained images like maxIteration
MCvTermCriteria termCrit = new MCvTermCriteria(TrainedFacesCounter, eps);
// Eigen face recognizer
FaceRecognitionEngine recognizer = new FaceRecognitionEngine(TrainingImages.ToArray(), LabelList.ToArray(), eigenDistanceThreshold, ref termCrit);
var imgLabel = recognizer.Recognize(Result);
LogStats($"{imgLabel} - Recognized");
// Draw the label for each face detected and recognized
// CurrentFrame.Draw(imgLabel, ref Font, new Point(face.rect.X - 2, face.rect.Y - 2), new Bgr(Color.White));
MethodInvoker inv = delegate { lblLabelName.Text = imgLabel.Replace("_", " ").ToUpper(); };
Invoke(inv);
}
}
// Show the face procesed and recognized
imageBoxFrameGrabber.Image = CurrentFrame;
}
catch
{
}
}
void button2Click(object sender, EventArgs e)
{
if (textBox1.Text.Equals(""))
{
MessageBox.Show("vui long nhap ten truoc khi luu....");
return;
}
else
{
try
{
ContTrain = ContTrain + 1;
grey = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
MCvAvgComp[][] facesDetected = gray.DetectHaarCasscade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUMING,
new Size(20, 20));
foreach (MCvAvgComp f in faceDetected[0])
{
TraniedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
TrainingImages.Add(TrainedFace);
labels.Add(textBox1.Text);
imageBox1.Image = TrainedFace;
File.writeAllText(Application.StartupPath + "/TrainedFaces/Trainedlabels.txt", trainingImages.ToArray().Length.ToString() + "%");
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
rainingImages.ToArray()[i - 1].Save(Application.StartupPath + "TrainedFaces/face" + i + ".bmp");
File.AppendAllText(Application.StartupPath + "/TrainedFaces/Trainedlabels.txt", labels.ToArray()[i - 1] + "%");
}
MessageBox.Show("khuon mat duoc phat hien va them vao", "Training ok", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
catch
{
MessageBox.Show("vui long chon chuc nang phat hien khuon mat truoc", "Training fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
}
public void Clear()
{
TrainingImages.Clear();
MarkedTrainingImages.Clear();
RecoginzingImages.Clear();
}
