private bool IsEqualFaceDescriptros(FaceEncoding uploadedImageEncoding, PhotoFaceDescriptor databasePhoto)
{
bool result = false;
// определяем порог допустимой точности
const double precision = 0.6d;
if (databasePhoto != null)
{
FaceEncoding imageEncodingToCompare =
JsonConvert.DeserializeObject <FaceEncoding>(databasePhoto.Descriptor);
result = FaceRecognition.CompareFace(
uploadedImageEncoding, imageEncodingToCompare, precision);
}
return(result);
}
public async Task PopulateDescriptors()
{
var wantedPhotosFolderPath = String.Concat(
_appEnvironment.WebRootPath, "\\WantedFacePhotos\\", "photoCollection");
if (!Directory.Exists(wantedPhotosFolderPath))
{
Directory.CreateDirectory(wantedPhotosFolderPath);
}
var wantedFacePhotos = _context.LoadPhotoFilesTest();
string filePath = "";
foreach (var photo in wantedFacePhotos)
{
string photoName = string.Concat("\\photo.", photo.Mime);
filePath = string.Concat(wantedPhotosFolderPath, photoName);
await System.IO.File.WriteAllBytesAsync(filePath, photo.Photo);
Image photoImage = FaceRecognition.LoadImageFile(filePath);
IEnumerable <Location> faceLocations = _fr.FaceLocations(photoImage);
FaceEncoding faceEncoding = CreateImageDescriptor(filePath);
string encodingSerialized = faceEncoding != null
? JsonConvert.SerializeObject(faceEncoding)
: "";
PhotoFaceDescriptor desc;
if (!string.IsNullOrEmpty(encodingSerialized))
{
desc = new PhotoFaceDescriptor()
{
Id = Guid.NewGuid(),
PhotoFaceId = photo.PhotoId,
Descriptor = encodingSerialized
};
_context.PhotoFaceDescriptors.Add(desc);
_context.SaveChanges();
}
System.IO.File.Delete(filePath);
}
}
