public FaceRecognitionDB()
{
try
{
faceRecognizer.Read(Application.StartupPath + @"/../../Images/eigenRecognizer.yml");
fisherRecognizer.Read(Application.StartupPath + @"/../../Images/fisherRecognizer.yml");
LBPHFaceRecognizer.Read(Application.StartupPath + @"/../../Images/lpbhRecognizer.yml");
}
catch (Exception)
{
}
}
//Predikcijaš+v xyttrrtr
private void btnPredict_Click(object sender, EventArgs e)
{
try
{
Mat imageMat = null;
while (true)
{
imageMat = videoCapture.QueryFrame().Clone();
Image <Gray, byte> image = imageMat.ToImage <Gray, byte>().Resize(180, 200, Emgu.CV.CvEnum.Inter.Cubic);
Rectangle[] rectangles = classifier.DetectMultiScale(image, 1.1, 4);
if (rectangles.Count() > 0)
{
break;
}
}
if (imageMat != null)
{
imageMat = imageMat.ToImage <Gray, byte>().Resize(180, 200, Emgu.CV.CvEnum.Inter.Cubic).Mat;
faceRecognizer.Read(Application.StartupPath + @"/../../Images/Newfacerecognizer.yml");
var res = faceRecognizer.Predict(imageMat);
if (res.Distance > threshold)
{
txtBox_Label.Text = res.Label.ToString();
txtBox_distance.Text = res.Distance.ToString();
string foundImage = Application.StartupPath + @"/../../Images/face" + res.Label.ToString() + ".bmp";
imgBox1.Image = imageMat.ToImage <Gray, byte>();
picBox.Image = Image.FromFile(foundImage);
MessageBox.Show("Successufully found label", "Success", MessageBoxButtons.OK);
}
else
{
MessageBox.Show("Not Found", "INFO", MessageBoxButtons.OK);
}
}
videoCapture.Stop();
}
catch (Exception err)
{
MessageBox.Show(err.Message, "INFO", MessageBoxButtons.OK);
}
}
private void Recognize()
{
_faceRecognizer.Read(_faceRecognizerPath);
var result = _faceRecognizer.Predict(detectedFaceForRecognizer);
if (result.Label != 0)
{
RecognizedFace = _dataStoreAccess.GetUserName(result.Label);
}
}
/// <summary>
/// Reconnaît les visages dans une image
/// </summary>
/// <param name="fileName"></param>
/// <param name="labelsFileName"></param>
/// <param name="recognizerFileName"></param>
private void RecognizeFaces(string fileName, string labelsFileName, string recognizerFileName)
{
_faceLabels = GetLabels(labelsFileName);
using (EigenFaceRecognizer faceRecognizer = new EigenFaceRecognizer())
{
_currentFaceRecognizer = faceRecognizer;
faceRecognizer.Read(recognizerFileName);
RecognizeFaces(fileName);
}
}
/// <summary>
/// Reconnaît les visages dans toutes les images d'un répertoire
/// </summary>
/// <param name="directoryName"></param>
/// <param name="searchPattern"></param>
/// <param name="recursive"></param>
public void RecognizeFacesInDirectory(string directoryName, string labelsFileName, string recognizerFileName, string searchPattern = "*.jpg", bool recursive = false)
{
_faceLabels = GetLabels(labelsFileName);
using (EigenFaceRecognizer faceRecognizer = new EigenFaceRecognizer())
{
_currentFaceRecognizer = faceRecognizer;
faceRecognizer.Read(recognizerFileName);
foreach (var item in Directory.GetFiles(directoryName, searchPattern, recursive ? SearchOption.AllDirectories : SearchOption.TopDirectoryOnly))
{
RecognizeFaces(item);
}
}
}
public MainWindowViewModel()
{
_dataStoreAccess = new DataStoreAccess(_databasePath);
if (File.Exists(_faceRecognizerPath))
{
_faceRecognizer = new EigenFaceRecognizer();
_faceRecognizer.Read(_faceRecognizerPath);
}
else
{
_faceRecognizer = new EigenFaceRecognizer();
}
InitializeFaceDetection();
}
public FaceRecognitionService(DatabaseContext context)
{
try
{
_eigen = new EigenFaceRecognizer();
_FacesNamesArray = File.ReadAllLines(_recognizerFacesFileName);
_eigen.Read(_recognizerFileName);
_faceDetectionService = new FaceDetectionService();
_context = context;
}
catch (Exception ex)
{
throw ex;
}
}
private void BtnSnapshot_Click(object sender, EventArgs e)
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
using (Image <Bgr, byte> imageFrame = capture.QueryFrame().ToImage <Bgr, byte>()) {
if (imageFrame == null)
{
return;
}
using (Image <Gray, byte> grayImage = imageFrame.Convert <Gray, byte>()) {
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
using (var classifier = new CascadeClassifier(PluginOptions.CascadesPath + "haarcascade_frontalface_default.xml")) {
Rectangle[] part1 = classifier.DetectMultiScale(grayImage, 1.1, 10);
if (part1.Length == 0)
{
return;
}
LabelFacesList.Text = "";
foreach (Rectangle face in part1)
{
using (Image <Gray, byte> resultingImage = imageFrame.Copy(face).Convert <Gray, byte>().Resize(100, 100, Inter.Cubic)) {
if (PluginOptions.UseImageCorrection)
{
resultingImage._EqualizeHist();
}
imageFrame.Draw(face, new Bgr(Color.Blue), 2);
TestImage.Image = imageFrame;
if (TrainedImages.Count == 0)
{
continue;
}
using (FaceRecognizer recognizer = new EigenFaceRecognizer()) {
recognizer.Read(PluginOptions.PluginPath + "SavedCascade.xml");
LabelFacesList.Text +=
$"{PluginOptions.PeopleFaces.ElementAt(recognizer.Predict(resultingImage).Label).Value}\r\n";
}
}
}
}
}
}
}
}
public FaceRecognition()
{
_faceRecognizer = new EigenFaceRecognizer(0, double.PositiveInfinity);
if (File.Exists("face_recognizer"))
{
_faceRecognizer.Read("face_recognizer");
}
_knownFaces = new List <FaceData>();
_emptyFaceImage = CreateEmptyFaceImage();
InitializeComponent();
_captureTimer = new Timer()
{
Interval = Config.TimerResponseValue
};
_captureTimer.Elapsed += CaptureTimer_Elapsed;
}
public static EigenFaceRecognizer OldEigen()
{
EigenFaceRecognizer eigenRec = new EigenFaceRecognizer(80, 4000);
if (File.Exists(Application.StartupPath + "/data/recognizer.yaml"))
{
try
{
eigenRec.Read(Application.StartupPath + "/data/recognizer.yaml");
}
catch
{
}
}
else
{
eigenRec = NewEigen();
}
return(eigenRec);
}
public static EigenFaceRecognizer OldEigen()
{
/* Console.WriteLine("Bsd" + int.Parse(ConfigurationManager.AppSettings["RecognizerComponentsNum"])+
* int.Parse(ConfigurationManager.AppSettings["RecognizerThreshold"]));
* EigenFaceRecognizer eigenRec = new EigenFaceRecognizer(
* int.Parse(ConfigurationManager.AppSettings["RecognizerComponentsNum"]),
* int.Parse(ConfigurationManager.AppSettings["RecognizerThreshold"]));*/
EigenFaceRecognizer eigenRec = new EigenFaceRecognizer(7, tre);
try
{
eigenRec.Read(RecognizerDataPath);
}
catch
{
eigenRec = NewEigen();
}
return(eigenRec);
}
public Form1()
{
InitializeComponent();
EigenFaceRecognizer = new EigenFaceRecognizer(4, 800);
DataStoreAccess = new DataStoreAccess(ConnectionString);
FaceDetection = new CascadeClassifier(Path.GetFullPath($"{AppDomain.CurrentDomain.BaseDirectory}haarcascade_frontalface_default.xml"));
Frame = new Mat();
Faces = new List <Image <Gray, byte> >();
Labels = new List <int>();
if (File.Exists(YMLPath))
{
EigenFaceRecognizer.Read(YMLPath);
}
var allFaces = DataStoreAccess.CallFaces("ALL_USERS");
if (allFaces != null)
{
for (int i = 0; i < allFaces.Count; i++)
{
Stream stream = new MemoryStream();
stream.Write(allFaces[i].Image, 0, allFaces[i].Image.Length);
var faceImage = new Image <Gray, byte>(new Bitmap(stream));
Faces.Add(faceImage);
Labels.Add(allFaces[i].UserId);
}
EigenFaceRecognizer.Train(ConvertImageToMat(Faces).ToArray(), Labels.ToArray());
btnPredict.Enabled = true;
MessageBox.Show("Training Completed!");
}
else
{
MessageBox.Show("Nothing to traing!");
}
BeginCapture();
}
public string Predict(Image <Gray, byte> image)
{
faceRecognizer.Read(Application.StartupPath + @"/../../Images/faceRecognizer.yml");
var res = faceRecognizer.Predict(image);
DAL.Models.Label label = null;
//if(res.Distance > threshold)
if (res.Distance < 3500)
{
label = _context.Labels.FirstOrDefault(_ => _.LabelNumber == res.Label);
var user = _context.Users.FirstOrDefault(_ => _.Id == label.UserId);
Log.Logger.Information("{@VisitDate} User{@username} with UserId {@UserId} {@VisitType} home and has access to House", DateTime.Now, user.FirstName + " " + user.LastName, user.Id);
Log.CloseAndFlush();
return(user.FirstName + " " + user.LastName);
}
else
{
Log.Logger.Information("{@VisitDate} User{@username} with UserId {@UserId} {@VisitType} home and has access to House", DateTime.Now);
}
return(string.Empty);
}
public void LoadRecognizerData()
{
_faceRecognizer.Read(_recognizerFilePath);
}
private actionResult RecognizeFace(string[] parameters)
{
var ar = new actionResult();
if (MainCtl.TrainedImages.Count == 0)
{
ar.setError("Database contains no trained faces.");
return(ar);
}
#region Parameters parsing
switch (parameters.Length)
{
case 0: {
ar.setError("Path to image not specified.");
return(ar);
}
case 1: {
ar.setError("Face name not specified.");
return(ar);
}
}
Image <Gray, byte> grayImage;
if (string.IsNullOrEmpty(parameters[0]))
{
using (var capture = new VideoCapture()) {
Thread.Sleep(PluginOptions.CameraDelayMs);
grayImage = capture.QueryFrame().ToImage <Gray, byte>();
}
}
else
{
try {
grayImage = new Image <Gray, byte>(parameters[0]);
}
catch {
ar.setError("Invalid path to image.");
return(ar);
}
}
if (PluginOptions.UseImageCorrection)
{
grayImage._EqualizeHist();
}
#endregion
Rectangle[] faces;
using (var classifier = new CascadeClassifier(PluginOptions.CascadesPath + "haarcascade_frontalface_default.xml")) {
faces = classifier.DetectMultiScale(grayImage, 1.1, 10);
}
if (faces.Length == 0)
{
ar.setError("No trained faces found.");
return(ar);
}
var resultString = "";
foreach (Rectangle face in faces)
{
using (FaceRecognizer recognizer = new EigenFaceRecognizer()) {
recognizer.Read(PluginOptions.PluginPath + "SavedCascade.xml");
FaceRecognizer.PredictionResult recoResult = recognizer.Predict(grayImage.Copy(face).Resize(100, 100, Inter.Cubic));
resultString += $"<{PluginOptions.PeopleFaces.ElementAt(recoResult.Label)}:{recoResult.Distance}>";
}
}
grayImage.Dispose();
ar.setSuccess(resultString);
return(ar);
}
private void GetFacesList()
{
if (isTrained == true)
{
recognizer.Read(Config.TrainingFile);
return;
}
if (!File.Exists(Config.HaarCascadePath))
{
string message = "Can't find Harr Cascade file! \n";
message += Config.HaarCascadePath;
DialogResult results = MessageBox.Show(message, "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
cascadeClassifier = new CascadeClassifier(Config.HaarCascadePath);
faceList.Clear();
string line;
// create file to store face data if neccessary
if (!Directory.Exists(Config.FacePhotosPath))
{
Directory.CreateDirectory(Config.FacePhotosPath);
}
if (!File.Exists(Config.FaceListTextFile))
{
string message = "Can't find face data file!";
message += Config.FaceListTextFile;
message += "An empty file will be create if this is your first time running the application!";
DialogResult results = MessageBox.Show(message, "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
if (results == DialogResult.OK)
{
String dirName = Path.GetDirectoryName(Config.FaceListTextFile);
Directory.CreateDirectory(dirName);
File.Create(Config.FaceListTextFile).Close();
}
}
FaceData faceDataInstance = null;
StreamReader reader = new StreamReader(Config.FaceListTextFile);
int i = 0;
while ((line = reader.ReadLine()) != null)
{
string[] lineParts = line.Split(':');
faceDataInstance = new FaceData();
faceDataInstance.FaceImage = new Image <Gray, byte>(Config.FacePhotosPath + lineParts[0] + Config.ImageFileExtension);
faceDataInstance.PersonName = lineParts[1];
faceList.Add(faceDataInstance);
}
foreach (FaceData face in faceList)
{
imageList.Push(face.FaceImage.Mat);
nameList.Add(face.PersonName);
labelList.Push(new[] { i++ });
}
reader.Close();
//Train recognizer
if (imageList.Size > 0 && isTrained == false)
{
recognizer = new EigenFaceRecognizer(imageList.Size, double.PositiveInfinity);
recognizer.Train(imageList, labelList);
recognizer.Write(Config.TrainingFile);
isTrained = true;
}
}
