public static async Task <(Face[] faces, Person person, Emotion[] emotions)> DetectAndIdentifyFace(Bitmap image)
{
FaceServiceClient fsc = new FaceServiceClient(Settings.Instance.FaceApiKey, FaceApiEndpoint);
EmotionServiceClient esc = new EmotionServiceClient(Settings.Instance.EmotionApiKey);
//FACE Detection
//TODO add detection interval as param
Emotion[] emotions = null;
Person person = null;
Face[] faces = null;
//Detect and identify only once per 10 seconds
if (lastFaceDetectTime.AddSeconds(10) < DateTime.Now)
{
lastFaceDetectTime = DateTime.Now;
MemoryStream memoryStream = new MemoryStream();
image.Save(memoryStream, System.Drawing.Imaging.ImageFormat.Jpeg);
//We need to seek to begin
memoryStream.Seek(0, SeekOrigin.Begin);
faces = await fsc.DetectAsync(memoryStream, true, true, new List <FaceAttributeType>() { FaceAttributeType.Age, FaceAttributeType.Gender });
if (faces.Any())
{
var rec = new Microsoft.ProjectOxford.Common.Rectangle[] { faces.First().FaceRectangle.ToRectangle() };
//Emotions
//We need to seek to begin, due to problems with parallel access we needed to create new memory stream
memoryStream = new MemoryStream();
image.Save(memoryStream, System.Drawing.Imaging.ImageFormat.Jpeg);
memoryStream.Seek(0, SeekOrigin.Begin);
//We call Emotion API and we include face rectangle information,
//as this way the call is cheaper, as emotion api does not have to run face detection
emotions = await esc.RecognizeAsync(memoryStream, rec);
//Person Identification
var groups = await fsc.ListPersonGroupsAsync();
var groupId = groups.First().PersonGroupId;
//We are interested only in first candidate
var identifyResult = await fsc.IdentifyAsync(groupId, new Guid[] { faces.First().FaceId }, 1);
var candidate = identifyResult?.FirstOrDefault()?.Candidates?.FirstOrDefault();
if (candidate != null)
{
person = await fsc.GetPersonAsync(groupId, candidate.PersonId);
}
}
}
return(faces, person, emotions);
}
private async Task DetectAndShowEmotion()
{
this.progressIndicator.IsActive = true;
this.DetectFaceAttributes = true;
foreach (var child in this.hostGrid.Children.Where(c => !(c is Image)).ToArray())
{
this.hostGrid.Children.Remove(child);
}
ImageAnalyzer imageWithFace = this.DataContext as ImageAnalyzer;
if (imageWithFace != null)
{
double renderedImageXTransform = this.imageControl.RenderSize.Width / this.bitmapImage.PixelWidth;
double renderedImageYTransform = this.imageControl.RenderSize.Height / this.bitmapImage.PixelHeight;
if (imageWithFace.DetectedFaces == null)
{
await imageWithFace.DetectFacesAsync(detectFaceAttributes : this.DetectFaceAttributes, detectFaceLandmarks : this.DetectFaceLandmarks);
}
foreach (Face face in imageWithFace.DetectedFaces)
{
FaceIdentificationBorder faceUI = new FaceIdentificationBorder();
faceUI.Margin = new Thickness((face.FaceRectangle.Left * renderedImageXTransform) + ((this.ActualWidth - this.imageControl.RenderSize.Width) / 2),
(face.FaceRectangle.Top * renderedImageYTransform) + ((this.ActualHeight - this.imageControl.RenderSize.Height) / 2), 0, 0);
faceUI.BalloonBackground = this.BalloonBackground;
faceUI.BalloonForeground = this.BalloonForeground;
faceUI.ShowFaceRectangle(face.FaceRectangle.Width * renderedImageXTransform, face.FaceRectangle.Height * renderedImageYTransform);
Microsoft.ProjectOxford.Common.Rectangle rectangle = new Microsoft.ProjectOxford.Common.Rectangle();
rectangle.Height = face.FaceRectangle.Height;
rectangle.Left = face.FaceRectangle.Left;
rectangle.Top = face.FaceRectangle.Top;
rectangle.Width = face.FaceRectangle.Width;
Emotion emotion = new Emotion();
emotion.FaceRectangle = rectangle;
emotion.Scores = face.FaceAttributes.Emotion;
faceUI.ShowEmotionData(emotion);
this.hostGrid.Children.Add(faceUI);
if (!this.ShowMultipleFaces)
{
break;
}
}
}
this.progressIndicator.IsActive = false;
}
public async void DrawFaceRectangle(Emotion[] emotionResult, BitmapImage bitMapImage, String urlString)
{
if (emotionResult != null && emotionResult.Length > 0)
{
Windows.Storage.Streams.IRandomAccessStream stream = await Windows.Storage.Streams.RandomAccessStreamReference.CreateFromUri(new Uri(urlString)).OpenReadAsync();
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
double resizeFactorH = ImageCanvas.Height / decoder.PixelHeight;
double resizeFactorW = ImageCanvas.Width / decoder.PixelWidth;
foreach (var emotion in emotionResult)
{
Microsoft.ProjectOxford.Common.Rectangle faceRect = emotion.FaceRectangle;
Image Img = new Image();
BitmapImage BitImg = new BitmapImage();
// open the rectangle image, this will be our face box
Windows.Storage.Streams.IRandomAccessStream box = await Windows.Storage.Streams.RandomAccessStreamReference.CreateFromUri(new Uri("ms-appx:///Assets/rectangle.png", UriKind.Absolute)).OpenReadAsync();
BitImg.SetSource(box);
//rescale each facebox based on the API's face rectangle
var maxWidth = faceRect.Width * resizeFactorW;
var maxHeight = faceRect.Height * resizeFactorH;
var origHeight = BitImg.PixelHeight;
var origWidth = BitImg.PixelWidth;
var ratioX = maxWidth / (float)origWidth;
var ratioY = maxHeight / (float)origHeight;
var ratio = Math.Min(ratioX, ratioY);
var newHeight = (int)(origHeight * ratio);
var newWidth = (int)(origWidth * ratio);
BitImg.DecodePixelWidth = newWidth;
BitImg.DecodePixelHeight = newHeight;
// set the starting x and y coordiantes for each face box
Thickness margin = Img.Margin;
margin.Left = faceRect.Left * resizeFactorW;
margin.Top = faceRect.Top * resizeFactorH;
Img.Margin = margin;
Img.Source = BitImg;
ImageCanvas.Children.Add(Img);
}
}
}
private Face CreateFace(Microsoft.ProjectOxford.Common.Rectangle rect)
{
return(new Face
{
FaceRectangle = new FaceRectangle
{
Left = rect.Left,
Top = rect.Top,
Width = rect.Width,
Height = rect.Height
}
});
}
private Face CreateFace(Microsoft.ProjectOxford.Common.Rectangle faceRectangle)
{
return(new Face
{
FaceRectangle = new FaceRectangle
{
Left = faceRectangle.Left,
Top = faceRectangle.Top,
Width = faceRectangle.Width,
Height = faceRectangle.Height
}
});
}
private int RectDist(FaceRectangle rectID, Microsoft.ProjectOxford.Common.Rectangle rectE)
{
int xcID = Convert.ToInt32(Math.Round(Convert.ToDecimal(rectID.Left + rectID.Width / 2)));
int ycID = Convert.ToInt32(Math.Round(Convert.ToDecimal(rectID.Top + rectID.Height / 2)));
int xcE = Convert.ToInt32(Math.Round(Convert.ToDecimal(rectE.Left + rectE.Width / 2)));
int ycE = Convert.ToInt32(Math.Round(Convert.ToDecimal(rectE.Top + rectE.Height / 2)));
int dx = xcID - xcE;
int dy = ycID - ycE;
int dist = dx ^ 2 + dy ^ 2;
return(dist);
}
public void DrawFaceRectangle(Image image, BitmapImage bitmapSource, Emotion[] emotionResult)
{
if (emotionResult != null && emotionResult.Length > 0)
{
DrawingVisual visual = new DrawingVisual();
DrawingContext drawingContext = visual.RenderOpen();
drawingContext.DrawImage(bitmapSource,
new Rect(0, 0, bitmapSource.Width, bitmapSource.Height));
double dpi = bitmapSource.DpiX;
double resizeFactor = 96 / dpi;
foreach (var emotion in emotionResult)
{
Microsoft.ProjectOxford.Common.Rectangle faceRect = emotion.FaceRectangle;
drawingContext.DrawRectangle(
Brushes.Transparent,
new Pen(Brushes.Cyan, 4),
new Rect(
faceRect.Left * resizeFactor,
faceRect.Top * resizeFactor,
faceRect.Width * resizeFactor,
faceRect.Height * resizeFactor)
);
}
drawingContext.Close();
RenderTargetBitmap faceWithRectBitmap = new RenderTargetBitmap(
(int)(bitmapSource.PixelWidth * resizeFactor),
(int)(bitmapSource.PixelHeight * resizeFactor),
96,
96,
PixelFormats.Pbgra32);
faceWithRectBitmap.Render(visual);
image.Source = faceWithRectBitmap;
}
}
public async Task FaceDetection(string pathToFile)
{
string subscriptionKeyFace = "insert Face API Key here";
string subscriptionKeyEmo = "insert Emotions API Key here";
FaceServiceClient fSC = new FaceServiceClient(subscriptionKeyFace);
EmotionServiceClient eSC = new EmotionServiceClient(subscriptionKeyEmo);
using (Stream s = File.OpenRead(pathToFile))
{
var requiredFaceAttributes = new FaceAttributeType[] {
FaceAttributeType.Age,
FaceAttributeType.Gender,
FaceAttributeType.Smile,
FaceAttributeType.FacialHair,
FaceAttributeType.HeadPose,
FaceAttributeType.Glasses
};
var faces = await fSC.DetectAsync(s,
returnFaceLandmarks : true,
returnFaceAttributes : requiredFaceAttributes);
numOfFacesLabel.Text = "Number of Faces:" + faces.Length;
var faceRectangles = new List <Microsoft.ProjectOxford.Common.Rectangle>();
foreach (var face in faces)
{
var rect = face.FaceRectangle;
var landmarks = face.FaceLandmarks;
var age = face.FaceAttributes.Age;
var gender = face.FaceAttributes.Gender;
var glasses = face.FaceAttributes.Glasses;
var rectangle = new Microsoft.ProjectOxford.Common.Rectangle
{
Height = face.FaceRectangle.Height,
Width = face.FaceRectangle.Width,
Top = face.FaceRectangle.Top,
Left = face.FaceRectangle.Left,
};
faceRectangles.Add(rectangle);
try
{
ageLabel.Text = "Age: " + age;
Console.Write("Age: " + age);
genderLabel.Text = "Gender: " + gender;
glassesLabel.Text = "Does the person wear glasses? " + glasses;
}
catch (Exception e)
{
Console.Write("Error: " + e);
}
if (faces.Length > 0)
{
using (Stream str = File.OpenRead(pathToFile))
{
var emotions = await eSC.RecognizeAsync(str, faceRectangles.ToArray());
string emotionsList = "";
foreach (var emotion in emotions)
{
emotionsList += $@"Anger: {emotion.Scores.Anger}
Contempt: {emotion.Scores.Contempt}
Disgust: {emotion.Scores.Disgust}
Fear: {emotion.Scores.Fear}
Happiness: {emotion.Scores.Happiness}
Neutral: {emotion.Scores.Neutral}
Sadness: {emotion.Scores.Sadness}
Surprise: {emotion.Scores.Surprise}";
}
emotionsLabel.Text = emotionsList;
}
}
}
}
}
