/// <summary>
/// Get how much the eyes are open, and how the much the person is smiling
/// </summary>
/// <returns>A number between 0 and 1 for each of the tuple</returns>
/// <remarks>The face's features need to be already detected using DetectFeatures, otherwise (null, null) will be returned</remarks>
public (float?eyesOpen, float?smile) GetExpression()
{
if (Features == null)
{
return(null, null);
}
if (FSDK.FSDKE_OK !=
FSDK.DetectFacialAttributeUsingFeatures(ImageHandle, ref Features, "Expression", out string response, 128))
{
return(null, null);
}
var splitResponse = response.Split('=', ';');
float?eyes = null;
float?smile = null;
string eyesString = splitResponse[3];
if (float.TryParse(eyesString, NumberStyles.AllowDecimalPoint, CultureInfo.InvariantCulture, out float eyesTemp))
{
eyes = eyesTemp;
}
string smileString = splitResponse[1];
if (float.TryParse(smileString, NumberStyles.AllowDecimalPoint, CultureInfo.InvariantCulture, out float smileTemp))
{
smile = smileTemp;
}
return(eyes, smile);
}
/// <summary>
/// Get how much the face's eyes are open
/// </summary>
/// <returns>A number between 0 and 1 indicating how much the face's eyes are open, null if failed</returns>
/// <remarks>
/// The face's Features need to have been detected beforehand using DetectFeatures(), otherwise null will be returned
/// Use <see cref="GetExpression"/> if detecting multiple attrbibutes
/// </remarks>
public float?GetEyesOpen()
{
if (Features == null)
{
return(null);
}
if (FSDK.FSDKE_OK !=
FSDK.DetectFacialAttributeUsingFeatures(ImageHandle, ref Features, "Expression", out string response, 128))
{
return(null);
}
string eyesOpen = response.Split('=', ';')[3];
if (float.TryParse(eyesOpen, NumberStyles.AllowDecimalPoint, CultureInfo.InvariantCulture, out float ret))
{
return(ret);
}
return(null);
}
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)));
}
}
}
}
}
}
public bool Recognize(ref string path, bool needCrop, bool needRotation = true)
{
FaceRectRelative = RectangleF.Empty;
LeftEyeCenter = RightEyeCenter = LeftMouth = LeftNose = RightNose = RightMouth = Vector2.Zero;
var executablePath = Path.GetDirectoryName(Application.ExecutablePath);
FSDK.TPoint[] pointFeature;
var image = new FSDK.CImage(path);
var faceRectangle = Rectangle.Empty;
var mouthRectangle = Rectangle.Empty;
FSDK.SetFaceDetectionThreshold(5);
FSDK.SetFaceDetectionParameters(true, true, 512);
var facePosition = image.DetectFace();
if (0 == facePosition.w)
{
MessageBox.Show("No faces detected", "Face Detection");
return(false);
}
if (needCrop)
{
RotatedAngle = facePosition.angle; // угол, на который повернута голова.
}
pointFeature = image.DetectFacialFeaturesInRegion(ref facePosition);
String AttributeValues; // определение пола
FSDK.DetectFacialAttributeUsingFeatures(image.ImageHandle, ref pointFeature, "Gender", out AttributeValues, 1024);
var ConfidenceMale = 0.0f;
var ConfidenceFemale = 0.0f;
var Age = 0.0f; // в этой версии распознавалки не работает.
FSDK.GetValueConfidence(AttributeValues, "Male", ref ConfidenceMale);
FSDK.GetValueConfidence(AttributeValues, "Female", ref ConfidenceFemale);
IsMale = ConfidenceMale > ConfidenceFemale;
FSDK.DetectFacialAttributeUsingFeatures(image.ImageHandle, ref pointFeature, "Age", out AttributeValues, 1024);
var left = facePosition.xc - (int)(facePosition.w * 0.6f);
left = left < 0 ? 0 : left;
// int top = facePosition.yc - (int)(facePosition.w * 0.5f); // верхушку определяет неправильлно. поэтому просто не будем обрезать :)
BottomFace = new Vector2(pointFeature[11].x, pointFeature[11].y);
var distance = pointFeature[2].y - pointFeature[11].y;
var top = pointFeature[16].y + distance - 15; // определение высоты по алгоритму старикана
top = top < 0 ? 0 : top;
var newWidth = (int)(facePosition.w * 1.2);
newWidth = newWidth > image.Width || newWidth == 0 ? image.Width : newWidth;
faceRectangle = new Rectangle(left, top, newWidth, BottomFace.Y + 15 < image.Height ? (int)(BottomFace.Y + 15) - top : image.Height - top - 1);
if (needCrop) // если это создание проекта - то нужно обрезать фотку и оставить только голову
{
var bmpImage = new Bitmap(path);
FaceColor = GetFaceColor(bmpImage, pointFeature);
var croppedImage = ImageEx.Crop(bmpImage, faceRectangle);
path = UserConfig.AppDataDir;
FolderEx.CreateDirectory(path);
path = Path.Combine(path, "tempHaarImage.jpg");
croppedImage.Save(path, ImageFormat.Jpeg);
croppedImage.Dispose();
return(Recognize(ref path, false));
}
LeftEyeCenter = new Vector2(pointFeature[0].x, pointFeature[0].y);
RightEyeCenter = new Vector2(pointFeature[1].x, pointFeature[1].y);
LeftMouth = new Vector2(pointFeature[3].x, pointFeature[3].y);
RightMouth = new Vector2(pointFeature[4].x, pointFeature[4].y);
LeftNose = new Vector2(pointFeature[45].x, pointFeature[45].y);
RightNose = new Vector2(pointFeature[46].x, pointFeature[46].y);
TopFace = new Vector2(pointFeature[66].x, pointFeature[66].y);
MiddleFace1 = new Vector2(pointFeature[66].x, pointFeature[66].y);
MiddleFace2 = new Vector2(pointFeature[5].x, pointFeature[5].y);
RightMiddleFace1 = new Vector2(pointFeature[67].x, pointFeature[67].y);
RightMiddleFace2 = new Vector2(pointFeature[6].x, pointFeature[6].y);
#region Поворот фотки по глазам!
if (needRotation)
{
var v = new Vector2(LeftEyeCenter.X - RightEyeCenter.X, LeftEyeCenter.Y - RightEyeCenter.Y);
v.Normalize(); // ПД !
var xVector = new Vector2(1, 0);
var xDiff = xVector.X - v.X;
var yDiff = xVector.Y - v.Y;
var angle = Math.Atan2(yDiff, xDiff) * 180.0 / Math.PI;
if (Math.Abs(angle) > 1 && angleCount <= 5) // поворачиваем наклоненные головы
{
++angleCount;
using (var ms = new MemoryStream(File.ReadAllBytes(path))) // Don't use using!!
{
var originalImg = (Bitmap)Image.FromStream(ms);
path = UserConfig.AppDataDir;
FolderEx.CreateDirectory(path);
path = Path.Combine(path, "tempHaarImage.jpg");
using (var ii = ImageEx.RotateImage(new Bitmap(originalImg), (float)-angle))
ii.Save(path, ImageFormat.Jpeg);
}
return(Recognize(ref path, false));
}
}
#endregion
var upperUpperLip = pointFeature[54]; // вехняя точка верхней губы
var lowerUpperLip = pointFeature[61]; // нижняя точка верхней губы
var lowerLip = pointFeature[64]; // верхняя точка нижней губы
var diff2 = Math.Abs(lowerUpperLip.y - upperUpperLip.y);
var diffX = Math.Abs(lowerLip.y - lowerUpperLip.y);
IsOpenSmile = diffX > diff2;
#region Переводим в относительные координаты
LeftMouth = new Vector2(LeftMouth.X / (image.Width * 1f), LeftMouth.Y / (image.Height * 1f));
RightMouth = new Vector2(RightMouth.X / (image.Width * 1f), RightMouth.Y / (image.Height * 1f));
LeftEyeCenter = new Vector2(LeftEyeCenter.X / (image.Width * 1f), LeftEyeCenter.Y / (image.Height * 1f));
RightEyeCenter = new Vector2(RightEyeCenter.X / (image.Width * 1f), RightEyeCenter.Y / (image.Height * 1f));
LeftNose = new Vector2(LeftNose.X / (image.Width * 1f), LeftNose.Y / (image.Height * 1f));
RightNose = new Vector2(RightNose.X / (image.Width * 1f), RightNose.Y / (image.Height * 1f));
TopFace = new Vector2(TopFace.X / (image.Width * 1f), TopFace.Y / (image.Height * 1f));
MiddleFace1 = new Vector2(MiddleFace1.X / (image.Width * 1f), MiddleFace1.Y / (image.Height * 1f));
MiddleFace2 = new Vector2(MiddleFace2.X / (image.Width * 1f), MiddleFace2.Y / (image.Height * 1f));
BottomFace = new Vector2(BottomFace.X / (image.Width * 1f), BottomFace.Y / (image.Height * 1f));
RightMiddleFace1 = new Vector2(RightMiddleFace1.X / (image.Width * 1f), RightMiddleFace1.Y / (image.Height * 1f));
RightMiddleFace2 = new Vector2(RightMiddleFace2.X / (image.Width * 1f), RightMiddleFace2.Y / (image.Height * 1f));
FacialFeatures = new List <Vector3>();
RealPoints = new List <Vector2>();
int index = 0;
var pointDepths = GetPointDepths();
foreach (var point in pointFeature)
{
FacialFeatures.Add(new Vector3(point.x / (image.Width * 1f), point.y / (image.Height * 1f), pointDepths[index++]));
RealPoints.Add(new Vector2(point.x, point.y));
}
#endregion
return(true);
}
