private static FaceDetails MapToDomain(this Microsoft.ProjectOxford.Face.Contract.Face face)
{
var emotion = GetEmotionValueFromScores(face.FaceAttributes.Emotion);
var domainEntity = new FaceDetails()
{
FaceId = face.FaceId.ToString(),
Age = face.FaceAttributes.Age,
Emotion = emotion.emotionValue,
EmotionScore = emotion.emotionScore,
HasBeard = face.FaceAttributes.FacialHair.Beard > FacialHairThreshold,
BeardScore = face.FaceAttributes.FacialHair.Beard,
HasMoustache = face.FaceAttributes.FacialHair.Moustache > FacialHairThreshold,
MoustacheScore = face.FaceAttributes.FacialHair.Moustache,
HasSideburns = face.FaceAttributes.FacialHair.Sideburns > FacialHairThreshold,
SideburnsScore = face.FaceAttributes.FacialHair.Sideburns,
Gender = face.FaceAttributes.Gender == "male" ? Gender.Male : Gender.Female,
HasGlasses = face.FaceAttributes.Glasses != Microsoft.ProjectOxford.Face.Contract.Glasses.NoGlasses,
GlassesType = (GlassesType)face.FaceAttributes.Glasses,
HeadPose = new HeadPose()
{
Pitch = face.FaceAttributes.HeadPose.Pitch, Roll = face.FaceAttributes.HeadPose.Roll, Yaw = face.FaceAttributes.HeadPose.Yaw
},
SmileScore = face.FaceAttributes.Smile,
BoundingBox = new Rectangle {
X = face.FaceRectangle.Left, Y = face.FaceRectangle.Top, Width = face.FaceRectangle.Width, Height = face.FaceRectangle.Height
},
};
return(domainEntity);
}
public CognitiveImageAnalysis()
{
VisionAnalysis = new AnalysisResult();
TextAnalysis = new OcrResults();
EmotionAnalysis = new Emotion[0];
FacialAnalysis = new Microsoft.ProjectOxford.Face.Contract.Face[0];
}
/// <summary> Function which submits a frame to the Emotion API. </summary>
/// <param name="frame"> The video frame to submit. </param>
/// <returns> A <see cref="Task{LiveCameraResult}"/> representing the asynchronous API call,
/// and containing the emotions returned by the API. </returns>
private async Task<LiveCameraResult> EmotionAnalysisFunction(VideoFrame frame)
{
// Encode image.
var jpg = frame.Image.ToMemoryStream(".jpg", s_jpegParams);
// Submit image to API.
FaceAPI.Contract.Face[] faces = null;
// See if we have local face detections for this image.
var localFaces = (OpenCvSharp.Rect[])frame.UserData;
if (localFaces == null || localFaces.Count() > 0)
{
// If localFaces is null, we're not performing local face detection.
// Use Cognigitve Services to do the face detection.
Properties.Settings.Default.FaceAPICallCount++;
faces = await _faceClient.DetectAsync(
jpg,
/* returnFaceId= */ false,
/* returnFaceLandmarks= */ false,
new FaceAPI.FaceAttributeType[1] { FaceAPI.FaceAttributeType.Emotion });
}
else
{
// Local face detection found no faces; don't call Cognitive Services.
faces = new FaceAPI.Contract.Face[0];
}
// Output.
return new LiveCameraResult
{
Faces = faces.Select(e => CreateFace(e.FaceRectangle)).ToArray(),
// Extract emotion scores from results.
EmotionScores = faces.Select(e => e.FaceAttributes.Emotion).ToArray()
};
}
private void ProcessMouth(Microsoft.ProjectOxford.Face.Contract.Face f)
{
double mouthWidth = Java.Lang.Math.Abs(f.FaceLandmarks.MouthRight.X - f.FaceLandmarks.MouthLeft.X);
double mouthHeight = Java.Lang.Math.Abs(f.FaceLandmarks.UpperLipBottom.Y - f.FaceLandmarks.UnderLipTop.Y);
mouthAperture = mouthHeight / mouthWidth;
}
private void ProcessEyes(Microsoft.ProjectOxford.Face.Contract.Face f)
{
double leftEyeWidth = Java.Lang.Math.Abs(f.FaceLandmarks.EyeLeftInner.X - f.FaceLandmarks.EyeLeftOuter.X);
double leftEyeHeight = Java.Lang.Math.Abs(f.FaceLandmarks.EyeLeftBottom.Y - f.FaceLandmarks.EyeLeftTop.Y);
double rightEyeWidth = Java.Lang.Math.Abs(f.FaceLandmarks.EyeRightInner.X - f.FaceLandmarks.EyeRightOuter.X);
double rightEyeHeight = Java.Lang.Math.Abs(f.FaceLandmarks.EyeRightBottom.Y - f.FaceLandmarks.EyeRightTop.Y);
eyeAperture = Java.Lang.Math.Max(leftEyeHeight / leftEyeWidth, rightEyeHeight / rightEyeWidth);
}
public MSFace(Microsoft.ProjectOxford.Face.Contract.Face f, Emotion e)
{
face = f;
emotion = e;
marks = new float[] {
e.Scores.Anger * 100,
e.Scores.Contempt * 100,
e.Scores.Disgust * 100,
e.Scores.Fear * 100,
e.Scores.Happiness * 100,
e.Scores.Sadness * 100,
e.Scores.Surprise * 100,
};
}
public static async Task <StorageFile> SaveFaceImageFile(StorageFile file, Microsoft.ProjectOxford.Face.Contract.Face face)
{
// get face file
var faceStartPoint = new Point(face.FaceRectangle.Left, face.FaceRectangle.Top);
var faceSize = new Size(face.FaceRectangle.Width, face.FaceRectangle.Height);
// save face file
var fileName = string.Format(@"{0}.jpg", face.FaceId);
var fileFaceImage =
await ApplicationData.Current.TemporaryFolder.CreateFileAsync(fileName, CreationCollisionOption.ReplaceExisting);
await CropBitmap.SaveCroppedBitmapAsync(file, fileFaceImage, faceStartPoint, faceSize);
return(fileFaceImage);
}
/// <summary> Function which submits a frame to the Face API. </summary>
/// <param name="frame"> The video frame to submit. </param>
/// <returns> A <see cref="Task{LiveCameraResult}"/> representing the asynchronous API call,
/// and containing the faces returned by the API. </returns>
private async Task <LiveCameraResult> FacesAnalysisFunction(VideoFrame frame)
{
// Encode image.
var jpg = frame.Image.ToMemoryStream(".jpg", s_jpegParams);
// Submit image to API.
var attrs = new List <FaceAPI.FaceAttributeType> {
FaceAPI.FaceAttributeType.Age,
FaceAPI.FaceAttributeType.Gender,
FaceAPI.FaceAttributeType.HeadPose,
FaceAPI.FaceAttributeType.Glasses,
FaceAPI.FaceAttributeType.FacialHair,
};
var faces = await _faceClient.DetectAsync(jpg, returnFaceAttributes : attrs);
// Count the API call.
Properties.Settings.Default.FaceAPICallCount++;
//IRUEL GET
LiveCameraResult result = new LiveCameraResult {
Faces = faces
};
Microsoft.ProjectOxford.Face.Contract.Face xx = new Microsoft.ProjectOxford.Face.Contract.Face();
xx = result.Faces[0];
Microsoft.ProjectOxford.Face.Contract.FaceAttributes dd = new Microsoft.ProjectOxford.Face.Contract.FaceAttributes();
dd = xx.FaceAttributes;
Trace.WriteLine(dd.Age.ToString() + ' ' + dd.Gender.ToString() + ' ' + dd.Glasses.ToString());
//return new LiveCameraResult
//{
// // Extract face rectangles from results.
// Faces = celebs.Select(c => CreateFace(c.FaceRectangle)).ToArray(),
// // Extract celebrity names from results.
// CelebrityNames = celebs.Select(c => c.Name).ToArray()
//};
// Output.
return(new LiveCameraResult {
Faces = faces
});
}
private static string GetFaceText(Face face)
{
string gender;
switch (face.FaceAttributes.Gender)
{
case "male":
gender = "man";
break;
case "female":
gender = "woman";
break;
default:
gender = "person";
break;
}
return($"`A {face.FaceAttributes.Age} years old {gender}`");
}
public void SetTransDriverlog(Tb_Trans_Driver_Logs t, Microsoft.ProjectOxford.Face.Contract.Face f)
{
t.EyeAperture = eyeAperture;
t.EyeLeftBottom_X = f.FaceLandmarks.EyeLeftBottom.X;
t.EyeLeftBottom_Y = f.FaceLandmarks.EyeLeftBottom.Y;
t.EyeLeftInner_X = f.FaceLandmarks.EyeLeftInner.X;
t.EyeLeftInner_Y = f.FaceLandmarks.EyeLeftInner.Y;
t.EyeLeftOuter_X = f.FaceLandmarks.EyeLeftOuter.X;
t.EyeLeftOuter_Y = f.FaceLandmarks.EyeLeftOuter.Y;
t.EyeLeftTop_X = f.FaceLandmarks.EyeLeftTop.X;
t.EyeLeftTop_Y = f.FaceLandmarks.EyeLeftTop.Y;
t.EyeRightBottom_X = f.FaceLandmarks.EyeRightBottom.X;
t.EyeRightBottom_Y = f.FaceLandmarks.EyeRightBottom.Y;
t.EyeRightInner_X = f.FaceLandmarks.EyeRightInner.X;
t.EyeRightInner_Y = f.FaceLandmarks.EyeRightInner.Y;
t.EyeRightOuter_X = f.FaceLandmarks.EyeRightOuter.X;
t.EyeRightOuter_Y = f.FaceLandmarks.EyeRightOuter.Y;
t.EyeRightTop_X = f.FaceLandmarks.EyeRightTop.X;
t.EyeRightTop_Y = f.FaceLandmarks.EyeRightTop.Y;
t.HeadPost_Pitch = f.FaceAttributes.HeadPose.Pitch;
t.HeadPost_PoseDeviation = headPoseDeviation;
t.HeadPost_Roll = f.FaceAttributes.HeadPose.Roll;
t.HeadPost_Yaw = f.FaceAttributes.HeadPose.Yaw;
t.MouthAperture = mouthAperture;
t.MouthLeft_X = f.FaceLandmarks.MouthLeft.X;
t.MouthLeft_Y = f.FaceLandmarks.MouthLeft.Y;
t.MouthRight_X = f.FaceLandmarks.MouthRight.X;
t.MouthRight_Y = f.FaceLandmarks.MouthRight.Y;
t.RefRegisterID = 1;
t.TransID = 1;
t.TimeStamp = DateTime.Now;
t.UnderLipBottom_X = f.FaceLandmarks.UnderLipBottom.X;
t.UnderLipBottom_Y = f.FaceLandmarks.UnderLipBottom.Y;
t.UnderLipTop_X = f.FaceLandmarks.UnderLipTop.X;
t.UnderLipTop_Y = f.FaceLandmarks.UnderLipTop.Y;
t.UpperLipBottom_X = f.FaceLandmarks.UpperLipBottom.X;
t.UpperLipBottom_Y = f.FaceLandmarks.UpperLipBottom.Y;
t.UpperLipTop_X = f.FaceLandmarks.UpperLipTop.X;
t.UpperLipTop_Y = f.FaceLandmarks.UpperLipTop.Y;
}
private void Logging(Face face)
{
InvokeGuiThread(() =>
{
recognizedLog.AppendText(string.Format("\n Average age: {0}", face.FaceAttributes.Age));
recognizedLog.AppendText(string.Format("\n Gender: {0}", face.FaceAttributes.Gender));
recognizedLog.AppendText(string.Format("\n Glasses: {0}", face.FaceAttributes.Glasses));
recognizedLog.AppendText(string.Format("\n Blur: {0}", face.FaceAttributes.Blur.Value));
recognizedLog.AppendText(string.Format("\n Noise: {0}", face.FaceAttributes.Noise.Value));
recognizedLog.AppendText(string.Format("\n Smile: {0}", face.FaceAttributes.Smile));
recognizedLog.AppendText(string.Format("\n Happiness: {0}", face.FaceAttributes.Emotion.Happiness));
recognizedLog.AppendText(string.Format("\n Anger: {0}", face.FaceAttributes.Emotion.Anger));
recognizedLog.AppendText(string.Format("\n Contempt: {0}", face.FaceAttributes.Emotion.Contempt));
recognizedLog.AppendText(string.Format("\n Disgust: {0}", face.FaceAttributes.Emotion.Disgust));
recognizedLog.AppendText(string.Format("\n Fear: {0}", face.FaceAttributes.Emotion.Fear));
recognizedLog.AppendText(string.Format("\n Neutral: {0}", face.FaceAttributes.Emotion.Neutral));
recognizedLog.AppendText(string.Format("\n Sadness: {0}", face.FaceAttributes.Emotion.Sadness));
recognizedLog.AppendText(string.Format("\n Surprise: {0}", face.FaceAttributes.Emotion.Surprise));
});
}
private async Task <LiveAnalyzeResult> EmotionAnalysisFunction(VideoFrame frame)
{
var jpg = frame.Image.ToMemoryStream(".jpg", s_jpegParams);
FaceAPI.Contract.Face[] faces = null;
var localFaces = (OpenCvSharp.Rect[])frame.UserData;
if (localFaces == null || localFaces.Count() > 0)
{
// If localFaces is null, we're not performing local face detection.
// Use Cognigitve Services to do the face detection.
//Properties.Settings.Default.FaceAPICallCount++;
faces = await _faceClient.DetectAsync(
jpg,
/* returnFaceId= */ false,
/* returnFaceLandmarks= */ false,
new FaceAPI.FaceAttributeType[1] {
FaceAPI.FaceAttributeType.Emotion
});
}
else
{
faces = new FaceAPI.Contract.Face[0];
}
if (faces.Any())
{
return(new LiveAnalyzeResult()
{
EmotionFaces = faces.ToArray()
});
}
return(default(LiveAnalyzeResult));
}
/// <summary>
/// Append detected face to UI binding collection
/// </summary>
/// <param name="collections">UI binding collection</param>
/// <param name="imagePath">Original image path, used for rendering face region</param>
/// <param name="face">Face structure returned from service</param>
public static void UpdateFace(ObservableCollection <FaceViewModel> collections, string imagePath, Microsoft.ProjectOxford.Face.Contract.Face face)
{
var renderingImage = LoadImageAppliedOrientation(imagePath);
collections.Add(new FaceViewModel()
{
ImageFile = renderingImage,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId.ToString(),
});
}
/// <summary>
/// Append detected face to UI binding collection
/// </summary>
/// <param name="collections">UI binding collection</param>
/// <param name="path">Original image path, used for rendering face region</param>
/// <param name="face">Face structure returned from service</param>
public static void UpdateFace(ObservableCollection <Face> collections, string path, Microsoft.ProjectOxford.Face.Contract.Face face)
{
collections.Add(new Face()
{
ImagePath = path,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId.ToString(),
});
}
private void ProcessHeadPose(Microsoft.ProjectOxford.Face.Contract.Face f)
{
headPoseDeviation = Java.Lang.Math.Abs(f.FaceAttributes.HeadPose.Yaw);
// this.headPoseIndicator.Margin = new Thickness((-f.FaceAttributes.HeadPose.Yaw / 90) * headPoseIndicatorHost.ActualWidth / 2, 0, 0, 0);
}