static string saveAFace(Bitmap ImageFrame, string name)
{
var faceToSave = new Image <Gray, byte>(ImageFrame);
Byte[] file;
IDataStoreAccess dataStore = new DataStoreAccess(_databasePath);
var username = string.IsNullOrEmpty(name) ? Guid.NewGuid().ToString() : name;
var filePath = Application.StartupPath + String.Format("/{0}.bmp", username);
faceToSave.ToBitmap().Save(filePath);
using (var stream = new FileStream(filePath, FileMode.Open, FileAccess.Read))
{
using (var reader = new BinaryReader(stream))
{
file = reader.ReadBytes((int)stream.Length);
}
}
return(dataStore.SaveFace(username, file));
}
void saveAFace(Rectangle face, Bitmap ImageFrame)
{
var faceToSave = new Image <Gray, byte>(ImageFrame);
Byte[] file;
IDataStoreAccess dataStore = new DataStoreAccess(_databasePath);
var username = Guid.NewGuid().ToString();
var filePath = Application.StartupPath + String.Format("/{0}.bmp", username);
faceToSave.ToBitmap().Save(filePath);
using (var stream = new FileStream(filePath, FileMode.Open, FileAccess.Read))
{
using (var reader = new BinaryReader(stream))
{
file = reader.ReadBytes((int)stream.Length);
}
}
var result = dataStore.SaveFace(username, file);
bckGroundTrainer.RunWorkerAsync();
MessageBox.Show(result, "Salvar resultado", MessageBoxButtons.OK);
}
void ProcessFrame(object sender, EventArgs arg)
{
//_cascadeClassifier = new CascadeClassifier(Application.StartupPath + "/haarcascade_frontalface_default.xml");
using (ImageFrame = _capture.QueryFrame().ToImage <Bgr, byte>())
{
if (ImageFrame != null)
{
var grayframe = ImageFrame.Convert <Gray, byte>();
var faces = _cascadeClassifier.DetectMultiScale(grayframe, 1.1, 10, Size.Empty); //the actual face detection happens here
int faceIndex = 1;
foreach (var face in faces)
{
ImageFrame.Draw(face, new Bgr(Color.BurlyWood), 3); //the detected face(s) is highlighted here using a box that is drawn around it/them
int predictedUserId;
Bitmap map = ImageFrame.Copy(face).Bitmap;
if (faceIndex == 1)
{
imageBox1.Image = new Image <Rgb, byte>(map);
}
else if (faceIndex == 2)
{
imageBox2.Image = new Image <Rgb, byte>(map);
}
else if (faceIndex == 3)
{
imageBox3.Image = new Image <Rgb, byte>(map);
}
faceIndex++;
try
{
predictedUserId = _recognizerEngine.RecognizeUser(new Image <Gray, byte>(map));
//Debug.WriteLine(predictedUserId);
}
catch { predictedUserId = -1; }
if (predictedUserId == -1)
{
saveAFace(face, map);
}
else
{
//proceed to documents library
IDataStoreAccess dataStore = new DataStoreAccess(_databasePath);
var username = dataStore.GetUsername(predictedUserId);
if (username != String.Empty)
{
lblUsername.Text =
String.Format("{1} Face Recognized as {0}", username, faces.Length);
}
else
{
saveAFace(face, map);
//MessageBox.Show("No Username for this face, Kindly register this face", "Authentication Result",
//MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
}
}
imgCamUser.Image = ImageFrame; //line 2
} //line 1
}
public RecognizerEngine(String databasePath, String recognizerFilePath)
{
_recognizerFilePath = recognizerFilePath;
_dataStoreAccess = new DataStoreAccess(databasePath);
_faceRecognizer = new LBPHFaceRecognizer(threshold: 53); //currently put 53 with 200x200,last test 55 with 200x200 work ok with some bad rec, 78 with 100x100 work ok//should play little more with this number. >100 -> almost recognize all time //new EigenFaceRecognizer(80, double.PositiveInfinity);
}
public static Image <Bgr, Byte> RecognizeImage(Image img, Label msgout = null)
{
if (img == null)
{
return(null);
}
using (var ImageFrame = new Image <Bgr, Byte>(new Bitmap(img)))
{
var _recognizerEngine = new RecognizerEngine(_databasePath, _trainerDataPath);
_recognizerEngine.TrainRecognizer();
if (ImageFrame == null)
{
System.Windows.Forms.MessageBox.Show("Nenhuma imagem fornecida.");
}
var grayframe = ImageFrame.Convert <Gray, byte>();
var faces = _cascadeClassifier.DetectMultiScale(grayframe, 1.1, 10, Size.Empty); //the actual face detection happens here
if (faces.Length == 0)
{
System.Windows.Forms.MessageBox.Show("Ops! Nenhum rosto foi identifcado.\n\nCarrege uma imagem com boa definição, tirada de ângulo frontal.");
}
//int faceIndex = 1;
var face = faces[0];
ImageFrame.Draw(face, new Bgr(Color.BurlyWood), 3); //the detected face(s) is highlighted here using a box that is drawn around it/them
int predictedUserId;
Bitmap map = ImageFrame.Copy(face).Bitmap;
try
{
predictedUserId = _recognizerEngine.RecognizeUser(new Image <Gray, byte>(map));
//Debug.WriteLine(predictedUserId);
}
catch { predictedUserId = -1; }
var username = "";
if (predictedUserId != -1)
{
//proceed to documents library
IDataStoreAccess dataStore = new DataStoreAccess(_databasePath);
username = dataStore.GetUsername(predictedUserId);
}
if (predictedUserId == -1 || username.Length == 0)
{
msgout.Text = "Atenção: usuário não identificado.";
msgout.ForeColor = System.Drawing.Color.Red;
}
else
{
msgout.Text = "Olá, " + username + "! Seu acesso está autorizado. :)";
msgout.ForeColor = System.Drawing.Color.Blue;
ImageFrame.Draw(username, new Point(face.X, face.Y), Emgu.CV.CvEnum.FontFace.HersheyPlain, 2, new Bgr(Color.Red), 2);
}
return(ImageFrame.Copy());
}
}
public static string TrainImage(Image img, string preName = "")
{
if (img == null)
{
return("");
}
using (var ImageFrame = new Image <Bgr, Byte>(new Bitmap(img)))
{
var _recognizerEngine = new RecognizerEngine(_databasePath, _trainerDataPath);
if (ImageFrame == null)
{
return(null);
}
var grayframe = ImageFrame.Convert <Gray, byte>();
var faces = _cascadeClassifier.DetectMultiScale(grayframe, 1.1, 10, Size.Empty); //the actual face detection happens here
//int faceIndex = 1;
if (faces.Length == 0)
{
throw new Exception("no_faces");
}
else if (faces.Length > 1)
{
throw new Exception("multiple_faces");
}
List <string> names = new List <string>();
foreach (var face in faces)
{
ImageFrame.Draw(face, new Bgr(Color.BurlyWood), 3); //the detected face(s) is highlighted here using a box that is drawn around it/them
int predictedUserId;
Bitmap map = ImageFrame.Copy(face).Bitmap;
try
{
predictedUserId = _recognizerEngine.RecognizeUser(new Image <Gray, byte>(map));
//Debug.WriteLine(predictedUserId);
}
catch { predictedUserId = -1; }
if (predictedUserId == -1)
{
string name = string.IsNullOrEmpty(preName) ? PromptForName("Identificação", "Identifique a pessoa", map) : preName;
saveAFace(map, name);
names.Add(name);
}
else
{
//proceed to documents library
IDataStoreAccess dataStore = new DataStoreAccess(_databasePath);
var username = dataStore.GetUsername(predictedUserId);
if (username != String.Empty)
{
if (preName != username)
{
string name = PromptForName("Identificação", "Identifique a pessoa", map, username);
if (name != username && name != preName)
{
saveAFace(map, name);
}
names.Add(name);
}
}
else
{
string name = string.IsNullOrEmpty(preName) ? PromptForName("Identificação", "Insira o nome da pessoa", map) : preName;
saveAFace(map, name);
names.Add(name);
}
}
}
return(string.Join(",", names.ToArray().Where(v => v.Length > 0)));
}
}
