public JsonResult RecognizeConcatPhoto(HttpPostedFileBase photo)
{
DataPath = Server.MapPath("~/App_Data/Faces");
//var uploadedFile = new byte[photo.InputStream.Length];
//photo.InputStream.Read(uploadedFile, 0, uploadedFile.Length);
FaceRecognizer.Load(DataPath);
Bitmap b = new Bitmap(Image.FromStream(photo.InputStream));
List <int> facesList = new List <int>();
List <FaceRecognizer.PredictionResult> PredictionResult = new List <FaceRecognizer.PredictionResult>();
FaceClassifier = new CascadeClassifier(Server.MapPath("~/App_Data/") + "haarcascade_frontalface_default.xml");
var persons = Enumerable.Empty <object>()
.Select(r => new { Id = 0, ShortName = "", FirstName = "", LastName = "" }) // prototype of anonymous type
.ToList();
persons.Remove(new { Id = 0, ShortName = "", FirstName = "", LastName = "" });
for (int j = 0; j < b.Width / 100; j++)
{
var b1 = b.Clone(new Rectangle(j * 100, 0, 100, 100), PixelFormat.Format32bppArgb);
var gray = new Image <Gray, byte>(b1);
gray._EqualizeHist();
Rectangle[] faces;
try
{
faces = FaceClassifier.DetectMultiScale(gray, 1.1, 1, new Size(50, 50), new Size(gray.Width, gray.Height));
}
catch (Exception e)
{
return(Json("There is no Faces: " + e));
}
var predict = FaceRecognizer.Predict(gray);
if (predict.Distance < 110)
{
var s = PhotoContext.People.Where(x => x.Id == predict.Label).Select(x => new { x.Id, x.ShortName, x.FirstName, x.LastName }).ToList();
persons.AddRange(s);
PredictionResult.Add(predict);
facesList.Add(predict.Label);
}
else
{
persons.Add(new { Id = 0, ShortName = "Unknown", FirstName = "", LastName = "" });
}
}
FaceRecognizer.Dispose();
return(Json(persons, JsonRequestBehavior.AllowGet));
}
public void Dispose()
{
recognizer.Dispose();
faces = null;
names = null;
GC.Collect();
}
public bool Train()
{
lock (_sync) {
if (_images.Count <= 1)
{
return(false);
}
if (_faceRecognizer != null)
{
_faceRecognizer.Dispose();
}
_faceRecognizer = new LBPHFaceRecognizer(1, 8, 8, 8, 100);
_faceRecognizer.Train(_images.ToArray(), _images.Select((c, i) => i).ToArray());
_shouldTrain = false;
return(true);
}
}