private void Findface(Bitmap bitmap)
{
var img = 0;
var image = bitmap;
image.Save("test.png");
FSDK.LoadImageFromFile(ref img, "test.png");
Face.Source = new BitmapImage(new Uri("test.png", UriKind.Relative));
FSDK.TPoint[] array;
FSDK.DetectFacialFeatures(img, out array);
if (array != null)
{
Face.Source = DrawPoints(image, array);
}
FSDK.TFacePosition[] faces;
int faceCount = 0;
FSDK.DetectMultipleFaces(img, ref faceCount, out faces, 10000);
if (faces != null)
{
foreach (var f in faces)
{
Face.Source = DrawCircle(image, f.xc, f.yc, f.w);
}
}
}
public void DetectFeatures()
{
if (FacePosition == null)
{
FSDK.DetectFacialFeatures(ImageHandle, out Features);
}
else
{
FSDK.DetectFacialFeaturesInRegion(ImageHandle, ref FacePosition, out Features);
}
}
public static Face FacePreparation(String picDir, String _name, String _folderName, int _index, Face twarz, int _folderIndex)
{
int Image = 0;
if (FSDK.LoadImageFromFile(ref Image, picDir) != FSDK.FSDKE_OK)
{
Console.WriteLine("addSingleFace error ! ###############################################");
}
FSDK.TFacePosition FacePosition = new FSDK.TFacePosition();
if (FSDK.DetectFace(Image, ref FacePosition) != FSDK.FSDKE_OK)
{
Console.WriteLine("addSingleFace error ! ###############################################");
}
FSDK.TPoint[] FacialFeatures;
if (FSDK.DetectFacialFeatures(Image, out FacialFeatures) == FSDK.FSDKE_OK)
{
twarz.name = _name;
twarz.folderName = _folderName;
Console.WriteLine(twarz.name);
twarz.index = _index;
twarz.networkIndex = _folderIndex;
List <float> faceFeatures = FeatureConverter.GetFeatures(FacialFeatures);
twarz.features = faceFeatures;
if (twarz.ValidateFace() == 1)
{
Console.WriteLine("Wygenerowano dane twarzy");
}
else
{
Console.WriteLine("Blad twarzy " + twarz.name + " ###############################################");
}
}
else
{
Console.WriteLine("addSingleFace error ! ###############################################");
}
return(twarz);
}
private void matchesFace()
{
if (dataGridView1.Rows.Count > 0)
{
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Rows.Clear()));
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Refresh()));
}
for (int i = 0; i < SubjectList.Count; i++)
{
if (SubjectList.Count >= 1)
{
FSDK.GetMatchingThresholdAtFAR(FARValue / 100, ref FaceDetectionThreshold);
TFaceRecord DbSubject = SubjectList[i];
int MatchedCount = 0;
int FaceCount = FaceSearchList.Count;
float[] Similarities = new float[FaceCount];
float[] Smile = new float[FaceCount];
float[] EyesOpen = new float[FaceCount];
float[] Male = new float[FaceCount];
float[] Female = new float[FaceCount];
int[] Numbers = new int[FaceCount];
for (int k = 0; k < FaceSearchList.Count; k++)
{
float Similarity = 0.0f;
float ConfidenceSmile = 0.0f;
float ConfidenceEyesOpen = 0.0f;
float ConfidenceMale = 0.0f;
float ConfidenceFemale = 0.0f;
TFaceRecord SearchFace = FaceSearchList[k];
FSDK.MatchFaces(ref DbSubject.Template, ref SearchFace.Template, ref Similarity);
long MaxSizeInBytes = 100000;
string ExpressionValues = "";
string GenderValues = "";
FSDK.CImage CurrentImage = SearchFace.image;
FSDK.TPoint[] Facefeatures = null;
FSDK.DetectFacialFeatures(SearchFace.faceImage.ImageHandle, out Facefeatures);
if (Facefeatures != null)
{
FSDK.DetectFacialAttributeUsingFeatures(SearchFace.faceImage.ImageHandle, ref Facefeatures, "Expression", out ExpressionValues, MaxSizeInBytes);
FSDK.GetValueConfidence(ExpressionValues, "Smile", ref ConfidenceSmile);
FSDK.GetValueConfidence(ExpressionValues, "EyesOpen", ref ConfidenceEyesOpen);
FSDK.DetectFacialAttributeUsingFeatures(SearchFace.faceImage.ImageHandle, ref Facefeatures, "Gender", out GenderValues, MaxSizeInBytes);
FSDK.GetValueConfidence(GenderValues, "Male", ref ConfidenceMale);
FSDK.GetValueConfidence(GenderValues, "Female", ref ConfidenceFemale);
if (Similarity >= FaceDetectionThreshold)
{
Similarities[MatchedCount] = Similarity;
Smile[MatchedCount] = ConfidenceSmile;
EyesOpen[MatchedCount] = ConfidenceEyesOpen;
Male[MatchedCount] = ConfidenceMale;
Female[MatchedCount] = ConfidenceFemale;
Numbers[MatchedCount] = k;
++MatchedCount;
}
}
else
{
if (Similarity >= FaceDetectionThreshold)
{
Similarities[MatchedCount] = Similarity;
Smile[MatchedCount] = 0;
EyesOpen[MatchedCount] = 0;
Male[MatchedCount] = 0;
Female[MatchedCount] = 0;
Numbers[MatchedCount] = k;
++MatchedCount;
}
}
}
if (MatchedCount == 0)
{
MessageBox.Show("No matches found. You can try to increase the FAR parameter in the Options dialog box.", "No matches");
}
else
{
for (int j = 0; j < MatchedCount; j++)
{
if ((Similarities[j] * 100.0f) >= 30.0f)
{
resultImagelist.Images.Add(FaceSearchList[j].faceImage.ToCLRImage());
Image img1 = FaceSearchList[Numbers[j]].faceImage.ToCLRImage();
img1 = (Image)(new Bitmap(img1, new Size(100, 100)));
Image img2 = Image.FromFile(SubjectList[i].ImageFileName);
img2 = (Image)(new Bitmap(img2, new Size(100, 100)));
string feature = DbSubject.suspectName + " \r\n\nSimilarity = " + (Similarities[j] * 100).ToString() + " Smile:" + Smile[j] * 100 + " Eyes Open: " + EyesOpen[j] * 100
+ " Male:" + Male[j] * 100 + " Female: " + Female[j] * 100;
Object[] row = new Object[] { img1, img2, feature };
this.dataGridView1.Invoke(new MethodInvoker(() =>
this.dataGridView1.Rows.Add(row)));
}
}
}
}
}
}
