public static async Task <ImageInsights> ProcessImageAsync(Func <Task <Stream> > imageStream, string imageId)
{
ImageAnalyzer analyzer = new ImageAnalyzer(imageStream);
analyzer.ShowDialogOnFaceApiErrors = true;
// trigger vision, face and emotion requests
await Task.WhenAll(analyzer.AnalyzeImageAsync(detectCelebrities: false, visualFeatures: DefaultVisualFeatureTypes), analyzer.DetectFacesAsync(detectFaceAttributes: true));
// trigger face match against previously seen faces
await analyzer.FindSimilarPersistedFacesAsync();
ImageInsights result = new ImageInsights {
ImageId = imageId
};
// assign computer vision results
result.VisionInsights = new VisionInsights
{
Caption = analyzer.AnalysisResult.Description?.Captions[0].Text,
Tags = analyzer.AnalysisResult.Tags != null?analyzer.AnalysisResult.Tags.Select(t => t.Name).ToArray() : new string[0]
};
// assign face api and emotion api results
List <FaceInsights> faceInsightsList = new List <FaceInsights>();
foreach (var face in analyzer.DetectedFaces)
{
FaceInsights faceInsights = new FaceInsights
{
FaceRectangle = face.FaceRectangle,
Age = face.FaceAttributes.Age,
Gender = face.FaceAttributes.Gender
};
SimilarFaceMatch similarFaceMatch = analyzer.SimilarFaceMatches.FirstOrDefault(s => s.Face.FaceId == face.FaceId);
if (similarFaceMatch != null)
{
faceInsights.UniqueFaceId = similarFaceMatch.SimilarPersistedFace.PersistedFaceId;
}
Emotion faceEmotion = CoreUtil.FindFaceClosestToRegion(analyzer.DetectedEmotion, face.FaceRectangle);
if (faceEmotion != null)
{
faceInsights.TopEmotion = faceEmotion.Scores.ToRankedList().First().Key;
}
faceInsightsList.Add(faceInsights);
}
result.FaceInsights = faceInsightsList.ToArray();
return(result);
}
public SimilarFace GetLastSimilarPersistedFaceForFace(BitmapBounds faceBox)
{
if (this.lastSimilarPersistedFaceSample == null || !this.lastSimilarPersistedFaceSample.Any())
{
return(null);
}
SimilarFaceMatch match =
this.lastSimilarPersistedFaceSample.Where(f => Util.AreFacesPotentiallyTheSame(faceBox, f.Face.FaceRectangle))
.OrderBy(f => Math.Abs(faceBox.X - f.Face.FaceRectangle.Left) + Math.Abs(faceBox.Y - f.Face.FaceRectangle.Top)).FirstOrDefault();
return(match?.SimilarPersistedFace);
}
public void UpdateVisitorDemographics(SimilarFaceMatch item)
{
AgeDistribution genderBasedAgeDistribution = null;
if (item.Face.FaceAttributes.Gender == Gender.Male)
{
Demographics.TotalMales++;
genderBasedAgeDistribution = Demographics.AgeGenderDistribution.MaleDistribution;
}
else
{
Demographics.TotalFemales++;
genderBasedAgeDistribution = Demographics.AgeGenderDistribution.FemaleDistribution;
}
if (item.Face.FaceAttributes.Age < 16)
{
genderBasedAgeDistribution.Age0To15++;
}
else if (item.Face.FaceAttributes.Age < 20)
{
genderBasedAgeDistribution.Age16To19++;
}
else if (item.Face.FaceAttributes.Age < 30)
{
genderBasedAgeDistribution.Age20s++;
}
else if (item.Face.FaceAttributes.Age < 40)
{
genderBasedAgeDistribution.Age30s++;
}
else if (item.Face.FaceAttributes.Age < 50)
{
genderBasedAgeDistribution.Age40s++;
}
else if (item.Face.FaceAttributes.Age < 60)
{
genderBasedAgeDistribution.Age50s++;
}
else
{
genderBasedAgeDistribution.Age60sAndOlder++;
}
//updating emotions as well:
UpdateVisitorEmotions(item);
}
private async void StartDriverIdAsync(ImageAnalyzer e)
{
if (this.isProcessingDriverId)
{
return;
}
if (!e.DetectedFaces.Any())
{
this.UpdateUIForNoDriverDetected();
return;
}
await Task.WhenAll(e.IdentifyFacesAsync(), e.FindSimilarPersistedFacesAsync());
SimilarFaceMatch faceMatch = e.SimilarFaceMatches.FirstOrDefault();
if (faceMatch != null)
{
string name = "Unknown";
IdentifiedPerson p = e.IdentifiedPersons.FirstOrDefault(f => f.FaceId == faceMatch.Face.FaceId);
if (p != null)
{
name = p.Person.Name;
}
else if (SettingsHelper.Instance.ShowAgeAndGender)
{
switch (faceMatch.Face.FaceAttributes.Gender)
{
case Gender.Male:
name = "Unknown male";
break;
case Gender.Female:
name = "Unknown female";
break;
}
}
this.driverId.Text = string.Format("{0}", name, faceMatch.SimilarPersistedFace.PersistedFaceId.GetValueOrDefault().ToString("N").Substring(0, 4));
}
this.isProcessingDriverId = false;
}
private async void StartDriverIdAsync(ImageAnalyzer e)
{
if (this.isProcessingDriverId)
{
return;
}
if (!e.DetectedFaces.Any())
{
this.UpdateUIForNoDriverDetected();
return;
}
await Task.WhenAll(e.IdentifyFacesAsync(), e.FindSimilarPersistedFacesAsync());
SimilarFaceMatch faceMatch = e.SimilarFaceMatches.FirstOrDefault();
if (faceMatch != null)
{
string name = "Unknown";
IdentifiedPerson p = e.IdentifiedPersons.FirstOrDefault(f => f.FaceId == faceMatch.Face.FaceId);
if (p != null)
{
name = p.Person.Name;
}
else
{
if (faceMatch.Face.FaceAttributes.Gender == "male")
{
name = "Unknown male";
}
else if (faceMatch.Face.FaceAttributes.Gender == "female")
{
name = "Unknown female";
}
}
this.driverId.Text = string.Format("{0}\nFace Id: {1}", name, faceMatch.SimilarPersistedFace.PersistedFaceId.ToString("N").Substring(0, 4));
}
this.isProcessingDriverId = false;
}
private void UpdateDemographics(SimilarFaceMatch item)
{
AgeDistribution genderBasedAgeDistribution = null;
switch (item.Face.FaceAttributes.Gender)
{
case Microsoft.Azure.CognitiveServices.Vision.Face.Models.Gender.Male:
this.demographics.OverallMaleCount++;
genderBasedAgeDistribution = this.demographics.AgeGenderDistribution.MaleDistribution;
break;
case Microsoft.Azure.CognitiveServices.Vision.Face.Models.Gender.Female:
this.demographics.OverallFemaleCount++;
genderBasedAgeDistribution = this.demographics.AgeGenderDistribution.FemaleDistribution;
break;
}
if (item.Face.FaceAttributes.Age < 16)
{
genderBasedAgeDistribution.Age0To15++;
}
else if (item.Face.FaceAttributes.Age < 20)
{
genderBasedAgeDistribution.Age16To19++;
}
else if (item.Face.FaceAttributes.Age < 30)
{
genderBasedAgeDistribution.Age20s++;
}
else if (item.Face.FaceAttributes.Age < 40)
{
genderBasedAgeDistribution.Age30s++;
}
else if (item.Face.FaceAttributes.Age < 50)
{
genderBasedAgeDistribution.Age40s++;
}
else
{
genderBasedAgeDistribution.Age50sAndOlder++;
}
}
private static string GetDisplayTextForPersonAsync(ImageAnalyzer analyzer, SimilarFaceMatch item)
{
// See if we identified this person against a trained model
IdentifiedPerson identifiedPerson = analyzer.IdentifiedPersons.FirstOrDefault(p => p.FaceId == item.Face.FaceId);
if (identifiedPerson != null)
{
return(identifiedPerson.Person.Name);
}
if (identifiedPerson == null)
{
// Let's see if this is a celebrity
if (analyzer.AnalysisResult?.Categories != null)
{
foreach (var category in analyzer.AnalysisResult.Categories.Where(c => c.Detail != null))
{
dynamic detail = JObject.Parse(category.Detail.ToString());
if (detail.celebrities != null)
{
foreach (var celebrity in detail.celebrities)
{
uint left = UInt32.Parse(celebrity.faceRectangle.left.ToString());
uint top = UInt32.Parse(celebrity.faceRectangle.top.ToString());
uint height = UInt32.Parse(celebrity.faceRectangle.height.ToString());
uint width = UInt32.Parse(celebrity.faceRectangle.width.ToString());
if (Util.AreFacesPotentiallyTheSame(new BitmapBounds {
Height = height, Width = width, X = left, Y = top
}, item.Face.FaceRectangle))
{
return(celebrity.name.ToString());
}
}
}
}
}
}
return(string.Empty);
}
private void UpdateDemographics(SimilarFaceMatch item)
{
AgeDistribution genderBasedAgeDistribution = null;
if (string.Compare(item.Face.FaceAttributes.Gender, "male", StringComparison.OrdinalIgnoreCase) == 0)
{
this.demographics.OverallMaleCount++;
genderBasedAgeDistribution = this.demographics.AgeGenderDistribution.MaleDistribution;
}
else
{
this.demographics.OverallFemaleCount++;
genderBasedAgeDistribution = this.demographics.AgeGenderDistribution.FemaleDistribution;
}
if (item.Face.FaceAttributes.Age < 16)
{
genderBasedAgeDistribution.Age0To15++;
}
else if (item.Face.FaceAttributes.Age < 20)
{
genderBasedAgeDistribution.Age16To19++;
}
else if (item.Face.FaceAttributes.Age < 30)
{
genderBasedAgeDistribution.Age20s++;
}
else if (item.Face.FaceAttributes.Age < 40)
{
genderBasedAgeDistribution.Age30s++;
}
else if (item.Face.FaceAttributes.Age < 50)
{
genderBasedAgeDistribution.Age40s++;
}
else
{
genderBasedAgeDistribution.Age50sAndOlder++;
}
}
private static string GetDisplayTextForPersonAsync(ImageAnalyzer analyzer, SimilarFaceMatch item)
{
// See if we identified this person against a trained model
IdentifiedPerson identifiedPerson = analyzer.IdentifiedPersons.FirstOrDefault(p => p.FaceId == item.Face.FaceId);
if (identifiedPerson != null)
{
return(identifiedPerson.Person.Name);
}
if (identifiedPerson == null)
{
// Let's see if this is a celebrity
if (analyzer.AnalysisResult?.Categories != null)
{
foreach (var category in analyzer.AnalysisResult.Categories.Where(c => c.Detail != null))
{
foreach (var celebrity in category.Detail.Celebrities)
{
var celebrityFaceRectangle = new Microsoft.Azure.CognitiveServices.Vision.Face.Models.FaceRectangle(
celebrity.FaceRectangle.Width,
celebrity.FaceRectangle.Height,
celebrity.FaceRectangle.Left,
celebrity.FaceRectangle.Top);
if (CoreUtil.AreFacesPotentiallyTheSame(celebrityFaceRectangle, item.Face.FaceRectangle))
{
return(celebrity.Name.ToString());
}
}
}
}
}
return(string.Empty);
}
public void UpdateVisitorEmotions(SimilarFaceMatch item)
{
EmotionDistribution genderBasedEmotionDistribution = null;
if (item.Face.FaceAttributes.Gender == Gender.Male)
{
genderBasedEmotionDistribution = Demographics.EmotionGenderDistribution.MaleDistribution;
}
else
{
genderBasedEmotionDistribution = Demographics.EmotionGenderDistribution.FemaleDistribution;
}
var emotions = new Dictionary <string, double>
{
{ "Anger", item.Face.FaceAttributes.Emotion.Anger },
{ "Contempt", item.Face.FaceAttributes.Emotion.Contempt },
{ "Disgust", item.Face.FaceAttributes.Emotion.Disgust },
{ "Fear", item.Face.FaceAttributes.Emotion.Fear },
{ "Happiness", item.Face.FaceAttributes.Emotion.Happiness },
{ "Neutral", item.Face.FaceAttributes.Emotion.Neutral },
{ "Sadness", item.Face.FaceAttributes.Emotion.Sadness },
{ "Surprise", item.Face.FaceAttributes.Emotion.Surprise }
};
var topEmotion = emotions.OrderByDescending(e => e.Value).FirstOrDefault();
switch (topEmotion.Key)
{
case "Anger":
genderBasedEmotionDistribution.Anger++;
break;
case "Contempt":
genderBasedEmotionDistribution.Contempt++;
break;
case "Disgust":
genderBasedEmotionDistribution.Disgust++;
break;
case "Fear":
genderBasedEmotionDistribution.Fear++;
break;
case "Happiness":
genderBasedEmotionDistribution.Happiness++;
break;
case "Neutral":
genderBasedEmotionDistribution.Neutral++;
break;
case "Sadness":
genderBasedEmotionDistribution.Sadness++;
break;
case "Surprise":
genderBasedEmotionDistribution.Surprise++;
break;
default:
break;
}
}
