private void btnRecognize_Click(object sender, EventArgs e)
{
if (string.IsNullOrWhiteSpace(PathPhoto) || string.IsNullOrWhiteSpace(
PathModel))
{
MessageBox.Show("need to select photo and model");
}
else
{
try
{
var userBmp = new Bitmap(PathPhoto);
var userImage = new Image <Gray, byte>(userBmp);
_faceRecognizer.Load(PathModel);
var result = _faceRecognizer.Predict(userImage.Resize(100, 100, Inter.Cubic));
var userId = result.Label;
var userRecord = new FRService().GetById(userId);
if (userRecord != null)
{
lblResult.Text = userRecord.UserName;
}
else
{
MessageBox.Show("User not enrolled in db");
}
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
}
public string RecognizeUser(Image <Gray, byte> userImage)
{
_faceRecognizer.Load(@"C:\Users\Dom\Documents\Visual Studio 2015\Projects\Emgu\Emgu\Faces\recognizerFilePath\file.yaml");
var result = _faceRecognizer.Predict(userImage.Resize(100, 100, Inter.Cubic));
return(result.Label.ToString());
}
static OpenCvTrainer()
{
Subjects = new Dictionary <int, string>();
SubjectSamples = new List <Tuple <int, Image <Gray, byte> > >();
var haarPath = @"haarcascade_frontalface_default.xml";
DetectionClassifier = new CascadeClassifier(haarPath);
FaceRecognizerData = new EigenFaceRecognizer();
if (File.Exists(Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "trainingFile.ocv")))
{
FaceRecognizerData.Load(Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "trainingFile.ocv"));
}
if (File.Exists(Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "trainingSubjects.txt")))
{
var lines = File.ReadAllLines((Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "trainingSubjects.txt")));
foreach (var line in lines)
{
if (!(string.IsNullOrEmpty(line)) && line.Contains(":"))
{
var items = line.Split(':');
Subjects.Add(int.Parse(items[0]), items[1]);
}
}
}
}
public JAVSFacialRecognizer()
{
_faceRecognizer = new EigenFaceRecognizer();
try
{
_faceRecognizer.Load(Environment.GetFolderPath(Environment.SpecialFolder.UserProfile) + "\\Documents\\test-recognizer.yaml");
}
catch
{
var fail = "fail";
}
}
private void button2_Click(object sender, EventArgs e)
{
if (comboBoxAlgorithm.Text == "EigenFaces")
{
try
{
string dataDirectory = Directory.GetCurrentDirectory() + "\\TrainedFaces\\trainedDataEigen.dat";
eigenFaceRecognizer = new EigenFaceRecognizer(eigenTrainedImageCounter, 3000);
eigenFaceRecognizer.Load(dataDirectory);
richTextBox1.Text += "Trained Database Loaded.";
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
MessageBox.Show("Nothing in binary database, please add at least a face(Simply train the prototype with the Add Face Button).", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
else if (comboBoxAlgorithm.Text == "FisherFaces")
{
try
{
string dataDirectory = Directory.GetCurrentDirectory() + "\\TrainedFaces\\trainedDataFisher.dat";
fisherFaceRecognizer = new FisherFaceRecognizer(fisherTrainedImageCounter, 3000);
fisherFaceRecognizer.Load(dataDirectory);
richTextBox1.Text += "Trained Database Loaded.";
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
MessageBox.Show("Nothing in binary database, please add at least a face(Simply train the prototype with the Add Face Button).", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
else if (comboBoxAlgorithm.Text == "LBPHFaces")
{
try
{
string dataDirectory = Directory.GetCurrentDirectory() + "\\TrainedFaces\\trainedDataLBPH.dat";
lbphFaceRecognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 400);
lbphFaceRecognizer.Load(dataDirectory);
richTextBox1.Text += "Trained Database Loaded.";
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
MessageBox.Show("Nothing in binary database, please add at least a face(Simply train the prototype with the Add Face Button).", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
}
public int RecognizeUser(Image <Gray, byte> userImage)
{
//creating new instatnce of facerecognizer
FaceRecognizer _faceRecognizer = new EigenFaceRecognizer(80, 1000);
// EigenObjectRecognizer recognizer = new EigenObjectRecognizer(trainingImages.ToArray(), ref termCrit);
// LBPHFaceRecognizer _faceRecognizer = new LBPHFaceRecognizer(1,8,8,8, double.PositiveInfinity);
string _recognizerFilePath = Application.StartupPath + "/traineddata";
_faceRecognizer.Load(_recognizerFilePath);
var result = _faceRecognizer.Predict(userImage.Resize(100, 100, Inter.Cubic));
return(result.Label);
}
public TrainingWindow()
{
InitializeComponent();
BDelete.IsEnabled = false;
BUpdate.IsEnabled = false;
isEditingXML = false;
listdata = TrainingData.Deserialize(IMAGES_PATH);
CBInterpolation.ItemsSource = Enum.GetValues(typeof(Emgu.CV.CvEnum.Inter));
CBInterpolation.SelectedIndex = 0;
CBGender.ItemsSource = Enum.GetValues(typeof(GenderEnum));
CBGender.SelectedIndex = 0;
foreach (TrainingData data in listdata)
{
switch (data.label)
{
case GenderEnum.MALE:
male++;
break;
case GenderEnum.FEMALE:
female++;
break;
default:
break;
}
}
TBGenderCount.Text = string.Format("Male: {0} Female: {1}", male, female);
currentData = new TrainingData();
Photo.Stretch = Stretch.Fill;
pathIndex = 0;
FaceRecognizer fr = new EigenFaceRecognizer(16, 123);
if (File.Exists(TRAINING_PATH))
{
fr.Load(TRAINING_PATH);
}
GenderClassifier.threshold = 100;
_genderClassifier = new GenderClassifier {
classifier = new CascadeClassifier("Classifiers\\haarcascade_frontalface_alt2.xml"),
faceRecognizer = fr,
recognizerHeight = MainWindow.recognitionHeight,
recognizerWidth = MainWindow.recognitionWidth
};
}
public void LoadRecognizerData()
{
_faceRecognizer.Load(_recognizerFilePath);
}
public MainWindow()
{
InitializeComponent();
Loaded += MainWindowLoaded;
Closing += MainWindowClosing;
ExcelManager.CreateSingleton(ConfigurationManager.AppSettings["DemographicsLocation"]);
Configuration confg = ConfigurationManager.OpenExeConfiguration(ConfigurationUserLevel.None);
if (confg.AppSettings.Settings["Width"] == null || !int.TryParse(confg.AppSettings.Settings["Width"].Value, out recognitionWidth))
{
recognitionWidth = 120;
confg.AppSettings.Settings.Add(new KeyValueConfigurationElement("Width", recognitionWidth.ToString()));
confg.Save(ConfigurationSaveMode.Modified);
ConfigurationManager.RefreshSection("appSettings");
}
if (confg.AppSettings.Settings["Height"] == null || !int.TryParse(confg.AppSettings.Settings["Height"].Value, out recognitionHeight))
{
recognitionHeight = 120;
confg.AppSettings.Settings.Add(new KeyValueConfigurationElement("Height", recognitionHeight.ToString()));
confg.Save(ConfigurationSaveMode.Modified);
ConfigurationManager.RefreshSection("appSettings");
}
if (confg.AppSettings.Settings["DemographicsLocation"] == null)
{
string path = @"..\demo.xlsx";
ExcelManager.CreateSingleton(path);
confg.AppSettings.Settings.Add(new KeyValueConfigurationElement("DemographicsLocation", path.ToString()));
confg.Save(ConfigurationSaveMode.Modified);
ConfigurationManager.RefreshSection("appSettings");
}
else
{
ExcelManager.CreateSingleton(ConfigurationManager.AppSettings["DemographicsLocation"]);
}
#if ON_TOP
StatusValue.Text = "Debugging!";
Activated += MainWindowActive;
Deactivated += MainWindowHidden;
#else
StatusValue.Text = "Release";
#endif
mouseController = new KinectMouseController();
FaceRecognizer fr = new EigenFaceRecognizer(14, 123);
fr.Load(TrainingWindow.TRAINING_PATH);
#if SHOW_CAMERA
imgViewer = new ImageViewer();
imgViewer.Show();
#endif
GenderClassifier.threshold = 50D;
_genderClassifier = new GenderClassifier {
classifier = new CascadeClassifier(CLASSIFIER_PATH),
faceRecognizer = fr,
recognizerWidth = recognitionWidth,
recognizerHeight = recognitionHeight
};
areaOfInterest = new Rectangle(CROPPED_X, CROPPED_Y, CROPPED_WIDTH, CROPPED_HEIGHT);
}
