public async void SaveCurrentEmotionsToFolder(EmotionScores emotions, Geoposition currentPosition, string photoFileName, string folderName = "EmotionDataFolder")
{
var currentEmotionData = new EmotionsData()
{
Anger = emotions.Anger,
Sadness = emotions.Sadness,
Neutral = emotions.Neutral,
Fear = emotions.Fear,
Disgust = emotions.Disgust,
Contempt = emotions.Contempt,
Hapiness = emotions.Happiness,
Suprise = emotions.Surprise,
};
var bestEmotionKey = emotions.ToRankedList().FirstOrDefault().Key;
var bestEmotionValue = emotions.ToRankedList().FirstOrDefault().Value;
currentEmotionData.BestEmotionName = bestEmotionKey;
currentEmotionData.BestEmotionScore = bestEmotionValue;
//currentEmotionData.position = currentPosition;
currentEmotionData.Longitude = currentPosition.Coordinate.Longitude;
currentEmotionData.Latitude = currentPosition.Coordinate.Latitude;
currentEmotionData.PhotoFileName = photoFileName;
currentEmotionData.DateTaken = DateTime.Now;
string fileName = DateTime.Now.ToString("yyyy-MM-dd--HH-mm-ss") + ".xml";
await SerializationController.SaveObjectToXml <EmotionsData>(currentEmotionData, fileName, folderName);
}
public async Task <string> Face_Analyse(Stream imageFileStream)
{
//Count Faces
Face[] faces = await faceServiceClient.DetectAsync(imageFileStream, returnFaceId : true, returnFaceLandmarks : false, returnFaceAttributes : faceAttributes);
if (faces.Count() > 1)
{
throw new Exception("Zu viele Gesichter erkannt...");
}
if (faces.Count() < 1)
{
throw new Exception("Kein Gesicht erkannt...");
}
//Emotion für Gesicht auslesen
EmotionScores emotionScores = faces[0].FaceAttributes.Emotion;
Dictionary <string, float> emotionList = new Dictionary <string, float>(emotionScores.ToRankedList());
//Zusammensetzen der Rückgabe
StringBuilder sb = new StringBuilder();
sb.Append("<div><table>");
foreach (KeyValuePair <string, float> element in emotionList)
{
sb.Append(String.Format("<tr><td>{0}: " + "</td><td>" + " {1}%" + "</td></tr>", Translate(element.Key), (element.Value * 100).ToString()));
}
sb.Append("</table></div>");
//Rückgabe
return(Newtonsoft.Json.JsonConvert.SerializeObject(sb.ToString()));
}
public void UpdateEmotion(EmotionScores scores)
{
var topEmotion = scores.ToRankedList().First();
this.filledBar.Background = this.emotionToColorMapping[topEmotion.Key];
this.emptySpaceRowDefinition.Height = new GridLength(1 - topEmotion.Value, Windows.UI.Xaml.GridUnitType.Star);
this.filledSpaceRowDefinition.Height = new GridLength(topEmotion.Value, Windows.UI.Xaml.GridUnitType.Star);
}
public string ParseEmotions(EmotionScores scores)
{
if (scores == null)
{
return(null);
}
return(scores.ToRankedList().FirstOrDefault().Key);
}
public void UpdateEmotion(EmotionScores scores)
{
var topEmotion = scores.ToRankedList().First();
string label = "", emoji = "";
switch (topEmotion.Key)
{
case "Anger":
label = "Angry";
emoji = "\U0001f620";
break;
case "Contempt":
label = "Contemptuous";
emoji = "\U0001f612";
break;
case "Disgust":
label = "Disgusted";
emoji = "\U0001f627";
break;
case "Fear":
label = "Afraid";
emoji = "\U0001f628";
break;
case "Happiness":
label = "Happy";
emoji = "\U0001f60a";
break;
case "Neutral":
label = "Neutral";
emoji = "\U0001f614";
break;
case "Sadness":
label = "Sad";
emoji = "\U0001f622";
break;
case "Surprise":
label = "Surprised";
emoji = "\U0001f632";
break;
default:
label = "";
emoji = "\U0001f60a";
break;
}
this.emotionEmoji.Text = emoji;
this.emotionText.Text = label;
}
public void ShowEmotionData(EmotionScores emotion)
{
this.EmotionData = emotion.ToRankedList().ToArray();
this.DataContext = this;
this.genderAgeGrid.Visibility = Visibility.Collapsed;
this.emotionGrid.Visibility = Visibility.Visible;
this.captionCanvas.Visibility = Visibility.Visible;
}
private System.Windows.Shapes.Rectangle ComposeRectangleBarFromEmotions(EmotionScores emotionScores)
{
var result = new System.Windows.Shapes.Rectangle();
var emotionRankedList = emotionScores.ToRankedList();
var gradientStopsCollection = new GradientStopCollection();
var occuringEmotions = new List <KeyValuePair <string, float> >();
foreach (var emotion in emotionRankedList.Reverse())
{
if (emotion.Value > 0.0)
{
occuringEmotions.Add(emotion);
}
}
var occuringEmotionsCount = occuringEmotions.Count;
var previousValue = 0.0f;
for (int i = 0; i < occuringEmotionsCount; i++)
{
var emotion = occuringEmotions[i];
var emotionColor = GetEmotionColor(emotion.Key);
var emotionValue = emotion.Value;
if (i == 0 || i == occuringEmotionsCount - 1)
{
if (i == 0)
{
previousValue = emotionValue;
}
var gradientStop = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStop);
}
else
{
var gradientStopStartPoint = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStopStartPoint);
previousValue += emotionValue;
var gradientStopEndPoint = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStopEndPoint);
}
}
var linearGradientBrush = new LinearGradientBrush(gradientStopsCollection, new System.Windows.Point(0.0, 0.0), new System.Windows.Point(0.0, 1.0));
var composedBar = new System.Windows.Shapes.Rectangle();
composedBar.Fill = linearGradientBrush;
composedBar.Width = 5.0;
composedBar.Margin = new Thickness(1.0, 0, 1.0, 0);
result = composedBar;
return(result);
}
public static Result ToMostProbable(this EmotionScores scores)
{
Contract.Assert(scores != null);
var first = scores.ToRankedList().FirstOrDefault();
if (first.Equals(default(KeyValuePair <string, float>)))
{
return(Result.Empty);
}
return(Result.FromScore(first.Key, first.Value));
}
private string getEmotion(EmotionScores emotion)
{
KeyValuePair <string, float> bestMatch = new KeyValuePair <string, float>("", 0);
foreach (KeyValuePair <string, float> item in emotion.ToRankedList())
{
if (item.Value > bestMatch.Value)
{
bestMatch = item;
}
}
return(bestMatch.Key + " (" + NumberHelpers.ToPercent(bestMatch.Value) + ")");
}
public static KeyValuePair <string, float> getDominantEmotion(EmotionScores scores)
{
var scoreList = scores.ToRankedList();
KeyValuePair <string, float> maxPair = scoreList.First();
foreach (var score in scoreList)
{
if (score.Value > maxPair.Value)
{
maxPair = score;
}
}
return(maxPair);
}
private void DrawEmotionText(Face face)
{
EmotionScores emotionScores = face.FaceAttributes.Emotion;
KeyValuePair <string, float> highestScoreEmotion = emotionScores.ToRankedList().FirstOrDefault();
TextBlock emotionText = new TextBlock
{
FontSize = 30,
Foreground = new SolidColorBrush(Colors.Yellow),
Text = $"{highestScoreEmotion.Key} ({highestScoreEmotion.Value * 100:0.##)}%"
};
Canvas.SetLeft(emotionText, face.FaceRectangle.Left);
Canvas.SetTop(emotionText, face.FaceRectangle.Top + face.FaceRectangle.Height + 2);
EmotionsCanvas.Children.Add(emotionText);
/// <summary>
/// Function to analyze face emotions, based on a given result score
/// </summary>
/// <param name="analysisResult"><see cref="Scores"/> result object</param>
/// <returns>A string with the current emotion</returns>
private string AnalyseEmotions(EmotionScores analysisResult)
{
string emotion = string.Empty;
var sortedEmotions = analysisResult.ToRankedList();
string currentEmotion = sortedEmotions.First().Key;
switch (currentEmotion)
{
case "Anger":
emotion = "angry";
break;
case "Contempt":
emotion = "contempt";
break;
case "Disgust":
emotion = "disgusted";
break;
case "Fear":
emotion = "scared";
break;
case "Happiness":
emotion = "happy";
break;
case "Neutral":
default:
emotion = "neutral";
break;
case "Sadness":
emotion = "sad";
break;
case "Suprise":
emotion = "suprised";
break;
}
return(emotion);
}
private Rectangle ComposeRectangleBarFromEmotions(EmotionScores emotionScores)
{
var emotionRankedList = emotionScores.ToRankedList();
var gradientStopsCollection = new GradientStopCollection();
var occuringEmotions = emotionRankedList.Reverse().Where(emotion => emotion.Value > 0.0).ToList();
var occuringEmotionsCount = occuringEmotions.Count;
var previousValue = 0.0f;
for (var i = 0; i < occuringEmotionsCount; i++)
{
var emotion = occuringEmotions[i];
var emotionColor = GetEmotionColor(emotion.Key);
var emotionValue = emotion.Value;
if (i == 0 || i == occuringEmotionsCount - 1)
{
if (i == 0)
{
previousValue = emotionValue;
}
var gradientStop = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStop);
}
else
{
var gradientStopStartPoint = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStopStartPoint);
previousValue += emotionValue;
var gradientStopEndPoint = new GradientStop(emotionColor, previousValue);
gradientStopsCollection.Add(gradientStopEndPoint);
}
}
var linearGradientBrush =
new LinearGradientBrush(gradientStopsCollection, new Point(0.0, 0.0), new Point(0.0, 1.0));
var composedBar = new Rectangle
{
Fill = linearGradientBrush,
Width = 5.0,
Margin = new Thickness(1.0, 0, 1.0, 0)
};
var result = composedBar;
return(result);
}
private string GetStrongestEmotion(EmotionScores emotionScores)
{
var rankedList = emotionScores.ToRankedList().Take(2).ToList();
if (rankedList[0].Key != "Neutral" && rankedList[0].Value > 0.7)
{
return(rankedList[0].Key);
}
if (rankedList[0].Key == "Neutral" && rankedList[1].Value > 0.2)
{
return(rankedList[1].Key);
}
if (rankedList[0].Value > 0.7)
{
return(rankedList[0].Key);
}
return(null);
}
private async void Button_ClickAsync(object sender, RoutedEventArgs e)
{
using (var captureStream = new InMemoryRandomAccessStream())
{
await _mediaCapture.CapturePhotoToStreamAsync(ImageEncodingProperties.CreateJpeg(), captureStream);
captureStream.Seek(0);
try
{
var faces = await fClient.DetectAsync(captureStream.AsStream(), true, false, faceAttributes);
//get photo attributes
var id = faces[0].FaceId;
var attributes = faces[0].FaceAttributes;
var age = attributes.Age;
var gender = attributes.Gender;
EmotionScores emotionScores = faces[0].FaceAttributes.Emotion;
var emotion = emotionScores.ToRankedList().First();
var facialHair = attributes.FacialHair;
var headPose = attributes.HeadPose;
var glasses = attributes.Glasses;
txtid.Text = "Id:- " + id.ToString();
txtage.Text = "Age:- " + age.ToString() + " Years";
txtgender.Text = "Gender:- " + gender.ToUpper();
txtemotion.Text = "Emotion:- " + emotion.Key.ToString();
txtglass.Text = "Glasses:- " + glasses.ToString();
Addtodb(txtid.Text, txtage.Text, txtgender.Text, txtemotion.Text, txtglass.Text);
}
catch (FaceAPIException ex)
{
var dialog = new MessageDialog(ex.ErrorMessage);
dialog.Title = ex.ErrorCode;
await dialog.ShowAsync();
}
catch (Exception exp)
{
var dialog = new MessageDialog(exp.Message);
dialog.Title = exp.Source;
await dialog.ShowAsync();
}
}
}
public static Emotion GetBestEmotion(this EmotionScores emotions)
{
var bestEmotion = emotions?.ToRankedList().FirstOrDefault().Key ?? nameof(EmotionScores.Neutral);
return((Emotion)Enum.Parse(typeof(Emotion), bestEmotion, true));
}
/// <summary> /// Get the dominant emotion as string /// </summary> /// <param name="scores"></param> /// <returns>The dominant emotion as a string</returns> public static string GetDominantEmotionAsString(EmotionScores scores) => scores.ToRankedList().First().Key;
private async Task ProcessCameraCapture(ImageAnalyzer e)
{
if (e == null)
{
this.lastDetectedFaceSample = null;
this.lastIdentifiedPersonSample = null;
this.lastSimilarPersistedFaceSample = null;
this.lastEmotionSample = null;
this.debugText.Text = "";
this.isProcessingPhoto = false;
return;
}
DateTime start = DateTime.Now;
// Compute Emotion, Age and Gender
await Task.WhenAll(e.DetectEmotionAsync(), e.DetectFacesAsync(detectFaceAttributes: true));
if (!e.DetectedEmotion.Any())
{
this.lastEmotionSample = null;
this.ShowTimelineFeedbackForNoFaces();
}
else
{
this.lastEmotionSample = e.DetectedEmotion;
averageScores = new EmotionScores
{
Happiness = e.DetectedEmotion.Average(em => em.Scores.Happiness),
Anger = e.DetectedEmotion.Average(em => em.Scores.Anger),
Sadness = e.DetectedEmotion.Average(em => em.Scores.Sadness),
Contempt = e.DetectedEmotion.Average(em => em.Scores.Contempt),
Disgust = e.DetectedEmotion.Average(em => em.Scores.Disgust),
Neutral = e.DetectedEmotion.Average(em => em.Scores.Neutral),
Fear = e.DetectedEmotion.Average(em => em.Scores.Fear),
Surprise = e.DetectedEmotion.Average(em => em.Scores.Surprise)
};
this.emotionDataTimelineControl.DrawEmotionData(averageScores);
}
if (e.DetectedFaces == null || !e.DetectedFaces.Any())
{
this.lastDetectedFaceSample = null;
}
else
{
this.lastDetectedFaceSample = e.DetectedFaces;
}
// Compute Face Identification and Unique Face Ids
await Task.WhenAll(e.IdentifyFacesAsync(), e.FindSimilarPersistedFacesAsync());
if (!e.IdentifiedPersons.Any())
{
this.lastIdentifiedPersonSample = null;
}
else
{
this.lastIdentifiedPersonSample = e.DetectedFaces.Select(f => new Tuple <Face, IdentifiedPerson>(f, e.IdentifiedPersons.FirstOrDefault(p => p.FaceId == f.FaceId)));
}
if (!e.SimilarFaceMatches.Any())
{
this.lastSimilarPersistedFaceSample = null;
}
else
{
this.lastSimilarPersistedFaceSample = e.SimilarFaceMatches;
if (ApplicationData.Current.RoamingSettings.Values.ContainsKey("DeviceName"))
{
deviceName = ApplicationData.Current.RoamingSettings.Values["DeviceName"].ToString();
deviceKey = ApplicationData.Current.RoamingSettings.Values["DeviceKey"].ToString();
foreach (var item in e.SimilarFaceMatches)
{
if (string.Compare(item.Face.FaceAttributes.Gender, "male", StringComparison.OrdinalIgnoreCase) == 0)
{
dataToHub.SendEmotions(averageScores.ToRankedList(), "Male", item.Face.FaceAttributes.Age.ToString("0"), deviceName, deviceKey);
}
else
{
dataToHub.SendEmotions(averageScores.ToRankedList(), "Female", item.Face.FaceAttributes.Age.ToString("0"), deviceName, deviceKey);
}
}
}
else
{
MessageDialog dialog = new MessageDialog("Make sure your device name and key are correct", "IoT Hub Parameters missing..");
await dialog.ShowAsync();
}
}
this.UpdateDemographics(e);
// this.debugText.Text = string.Format("Latency: {0}ms", (int)(DateTime.Now - start).TotalMilliseconds);
this.isProcessingPhoto = false;
}
private async Task ProcessCameraCapture(ImageAnalyzer e)
{
if (e == null)
{
this.lastDetectedFaceSample = null;
this.lastIdentifiedPersonSample = null;
this.lastSimilarPersistedFaceSample = null;
this.lastEmotionSample = null;
this.debugText.Text = "";
this.isProcessingPhoto = false;
return;
}
DateTime start = DateTime.Now;
// Compute Emotion, Age and Gender
await Task.WhenAll(e.DetectEmotionAsync(), e.DetectFacesAsync(detectFaceAttributes: true));
if (!e.DetectedEmotion.Any())
{
this.lastEmotionSample = null;
this.ShowTimelineFeedbackForNoFaces();
}
else
{
this.lastEmotionSample = e.DetectedEmotion;
EmotionScores averageScores = new EmotionScores
{
Happiness = e.DetectedEmotion.Average(em => em.Scores.Happiness),
Anger = e.DetectedEmotion.Average(em => em.Scores.Anger),
Sadness = e.DetectedEmotion.Average(em => em.Scores.Sadness),
Contempt = e.DetectedEmotion.Average(em => em.Scores.Contempt),
Disgust = e.DetectedEmotion.Average(em => em.Scores.Disgust),
Neutral = e.DetectedEmotion.Average(em => em.Scores.Neutral),
Fear = e.DetectedEmotion.Average(em => em.Scores.Fear),
Surprise = e.DetectedEmotion.Average(em => em.Scores.Surprise)
};
this.emotionDataTimelineControl.DrawEmotionData(averageScores);
CommunicateWithIoTHub emotions = new CommunicateWithIoTHub();
emotions.SendEmotions(averageScores.ToRankedList());
}
if (e.DetectedFaces == null || !e.DetectedFaces.Any())
{
this.lastDetectedFaceSample = null;
}
else
{
this.lastDetectedFaceSample = e.DetectedFaces;
}
// Compute Face Identification and Unique Face Ids
await Task.WhenAll(e.IdentifyFacesAsync(), e.FindSimilarPersistedFacesAsync());
if (!e.IdentifiedPersons.Any())
{
this.lastIdentifiedPersonSample = null;
}
else
{
this.lastIdentifiedPersonSample = e.DetectedFaces.Select(f => new Tuple <Face, IdentifiedPerson>(f, e.IdentifiedPersons.FirstOrDefault(p => p.FaceId == f.FaceId)));
}
if (!e.SimilarFaceMatches.Any())
{
this.lastSimilarPersistedFaceSample = null;
}
else
{
this.lastSimilarPersistedFaceSample = e.SimilarFaceMatches;
}
this.UpdateDemographics(e);
this.debugText.Text = string.Format("Latency: {0}ms", (int)(DateTime.Now - start).TotalMilliseconds);
this.isProcessingPhoto = false;
}
public static Tuple <string, float> GetDominantEmotion(EmotionScores scores)
{
return(scores.ToRankedList().Select(kv => new Tuple <string, float>(kv.Key, kv.Value)).First());
}
private Tuple <string, float> GetDominantEmotion(EmotionScores emotionScores)
{
return(emotionScores.ToRankedList().Select(kv => new Tuple <string, float>(kv.Key, kv.Value)).First());
}