|
public RecognizeAsync ( Stream imageStream ) : Task |
||
| imageStream | Stream | Stream of the image |
| return | Task |
|
public async Task<Emotion[]> GetEmotion()
{
try {
var emotionServiceClient = new EmotionServiceClient("keyemotio");
var emotion = await emotionServiceClient.RecognizeAsync(this.ImageResult.Url);
this.EmotionCollection = emotion;
var image = new EmotionView
{
Anger = emotion[0].Scores.Anger * 100,
Nombre = ImageResult.Nombre,
Url = ImageResult.Url,
Disgust = emotion[0].Scores.Disgust * 100,
Contempt = emotion[0].Scores.Contempt * 100,
Fear = emotion[0].Scores.Fear * 100,
Happiness = emotion[0].Scores.Happiness * 100,
Neutral = emotion[0].Scores.Neutral * 100,
Sadness = emotion[0].Scores.Sadness * 100,
Surprise = emotion[0].Scores.Surprise * 100
};
ImageCollection.Add(image);
return emotion;
}
catch(Exception)
{
return null;
}
}
private static async void DetecFacesAndDisplayResult(string fileLocation, string subscriptionKeyFace, string subscriptionKeyEmotion)
{
using (var fileStreamFace = File.OpenRead(fileLocation))
{
using (var fileStreamEmotions = File.OpenRead(fileLocation))
{
try
{
var faceServiceClient = new FaceServiceClient(subscriptionKeyFace);
var emotionServiceClient = new EmotionServiceClient(subscriptionKeyEmotion);
var faces = await faceServiceClient.DetectAsync(fileStreamFace, false, true, true);
Console.WriteLine(" > " + faces.Length + " detected.");
if (faces.Length > 0)
{
var faceRectangles = new List<Rectangle>();
foreach (var face in faces)
{
Console.WriteLine(" >> age: " + face.Attributes.Age + " gender:" + face.Attributes.Gender);
var rectangle = new Rectangle
{
Height = face.FaceRectangle.Height,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width
};
faceRectangles.Add(rectangle);
}
// on face detected we start emotion analysis
var emotions = await emotionServiceClient.RecognizeAsync(fileStreamEmotions, faceRectangles.ToArray());
var emotionsDetails = "";
foreach (var emotion in emotions)
{
emotionsDetails += $@" 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}
";
}
Console.WriteLine(" >> emotions: " + emotionsDetails);
}
}
catch (Exception exception)
{
Console.WriteLine(exception.ToString());
}
}
}
}
static async Task<Emotion[]> RecognizeEmotionsAsync(string imageUrl)
{
var client = new EmotionServiceClient(SubscriptionKey);
try
{
return await client.RecognizeAsync(imageUrl);
}
catch (Exception)
{
return null;
}
}
public async Task<IDictionary<Emotions, float>> ReadEmotionsFromImageStreamAndGetRankedEmotions(Stream imageStream)
{
EmotionServiceClient emotionServiceClient = new EmotionServiceClient(this.subscriptionKey);
Emotion[] emotions = await emotionServiceClient.RecognizeAsync(imageStream).ConfigureAwait(false);
Emotion emotion = emotions.FirstOrDefault();
if (emotion == null)
return null;
return this.CalculateAndRankScoreToDictionary(emotion.Scores);
}
private static async Task<Emotion[]> GetHappiness(Stream stream)
{
string emotionKey = "88f748eefd944a5d8d337a1765414bba";
EmotionServiceClient emotionClient = new EmotionServiceClient(emotionKey);
var emotionResults = await emotionClient.RecognizeAsync(stream);
if (emotionResults == null || emotionResults.Count() == 0)
{
throw new Exception("Can't detect face");
}
return emotionResults;
}
/// <summary>
/// Uploads the image to Project Oxford and detect emotions.
/// </summary>
/// <param name="imageFilePath">The image file path.</param>
/// <returns></returns>
private async Task<Emotion[]> UploadAndDetectEmotions(string url)
{
MainWindow window = (MainWindow)Application.Current.MainWindow;
string subscriptionKey = window.ScenarioControl.SubscriptionKey;
// -----------------------------------------------------------------------
// KEY SAMPLE CODE STARTS HERE
// -----------------------------------------------------------------------
window.Log("EmotionServiceClient is created");
//
// Create Project Oxford Emotion API Service client
//
EmotionServiceClient emotionServiceClient = new EmotionServiceClient(subscriptionKey);
window.Log("Calling EmotionServiceClient.RecognizeAsync()...");
try
{
//
// Detect the emotions in the URL
//
Emotion[] emotionResult = await emotionServiceClient.RecognizeAsync(url);
return emotionResult;
}
catch (Exception exception)
{
window.Log("Dection failed. Please make sure that you have the right subscription key and proper URL to detect.");
window.Log(exception.ToString());
return null;
}
// -----------------------------------------------------------------------
// KEY SAMPLE CODE ENDS HERE
// -----------------------------------------------------------------------
}
private async void btnTakePhoto_Click(object sender, RoutedEventArgs e)
{
btnTakePhoto.IsEnabled = false;
btnStartPreview.IsEnabled = false;
InMemoryRandomAccessStream stream = new InMemoryRandomAccessStream();
await mediaCapture.CapturePhotoToStreamAsync(ImageEncodingProperties.CreateJpeg(), stream);
stream.Seek(0);
BitmapImage bitmap = new BitmapImage();
bitmap.SetSource(stream);
captureImage.Source = bitmap;
stream.Seek(0);
Stream st = stream.AsStream();
if (isPreviewing == true) await mediaCapture.StopPreviewAsync();
isPreviewing = false;
previewElement.Visibility = Visibility.Collapsed;
progring.IsActive = true;
try
{
EmotionServiceClient emotionServiceClient =
new EmotionServiceClient("12345678901234567890123456789012");
// replace 12345678901234567890123456789012 with your key taken from https://www.projectoxford.ai/Subscription/
emotionResult = await emotionServiceClient.RecognizeAsync(st);
}
catch { }
progring.IsActive = false;
if ((emotionResult != null) && (emotionResult.Length > 0))
{
emo.Clear();
emo.Add(emotionResult[0]);
this.DataContext = emo.ElementAt(0);
}
btnStartPreview.IsEnabled = true;
btnTakePhoto.IsEnabled = true;
}
/// <summary>
/// Uploads the image to Project Oxford and detect emotions.
/// </summary>
/// <param name="imageFilePath">The image file path.</param>
/// <returns></returns>
private async Task<Emotion[]> UploadAndDetectEmotions(string imageFilePath)
{
MainWindow window = (MainWindow)Application.Current.MainWindow;
string subscriptionKey = window.ScenarioControl.SubscriptionKey;
window.Log("EmotionServiceClient is created");
// -----------------------------------------------------------------------
// KEY SAMPLE CODE STARTS HERE
// -----------------------------------------------------------------------
//
// Create Project Oxford Emotion API Service client
//
EmotionServiceClient emotionServiceClient = new EmotionServiceClient(subscriptionKey);
window.Log("Calling EmotionServiceClient.RecognizeAsync()...");
try
{
Emotion[] emotionResult;
using (Stream imageFileStream = File.OpenRead(imageFilePath))
{
//
// Detect the emotions in the URL
//
emotionResult = await emotionServiceClient.RecognizeAsync(imageFileStream);
return emotionResult;
}
}
catch (Exception exception)
{
window.Log(exception.ToString());
return null;
}
// -----------------------------------------------------------------------
// KEY SAMPLE CODE ENDS HERE
// -----------------------------------------------------------------------
}
async Task AddEmotionBasedTagsToPhotoAsync(PhotoResult photoResult)
{
// See comment at bottom of file
if (!string.IsNullOrEmpty(cognitiveServiceEmotionServiceKey))
{
EmotionServiceClient client = new EmotionServiceClient(
cognitiveServiceEmotionServiceKey);
// Open the photo file we just captured.
using (var stream = await photoResult.PhotoFile.OpenStreamForReadAsync())
{
// Call the cloud looking for emotions.
var results = await client.RecognizeAsync(stream);
// We're only taking the first result here.
var scores = results?.FirstOrDefault()?.Scores;
if (scores != null)
{
// This object has properties called Sadness, Happiness,
// Fear, etc. all with floating point values 0..1
var publicProperties = scores.GetType().GetRuntimeProperties();
// We'll have any property with a score > 0.5f.
var automaticTags =
publicProperties
.Where(
property => (float)property.GetValue(scores) > 0.5)
.Select(
property => property.Name)
.ToList();
if (automaticTags.Count > 0)
{
// Add them to our photo!
await this.photoControl.AddTagsToPhotoAsync(
photoResult.PhotoId,
automaticTags);
}
}
}
}
}
private async Task<Emotion[]> UploadAndDetectEmotion(Stream imageStream)
{
EmotionServiceClient = new EmotionServiceClient(Constants.EmotionApiKey);
try
{
Emotion[] emotionResult;
using (Stream imageFileStream = imageStream)
{
emotionResult = await EmotionServiceClient.RecognizeAsync(imageFileStream);
return emotionResult;
}
}
catch (Exception ex)
{
return new Emotion[0];
}
}
public async Task<ObservableCollection<Face>> UpdateEmotions(string selectedFile, ObservableCollection<Face> faces,
string subscriptionKeyEmotions)
{
using (var fileStreamEmotions = File.OpenRead(selectedFile))
{
var emotionServiceClient = new EmotionServiceClient(subscriptionKeyEmotions);
var emotions = await emotionServiceClient.RecognizeAsync(fileStreamEmotions, faces.Select(
face => new Rectangle
{
Height = face.Height,
Left = face.Left,
Top = face.Top,
Width = face.Width
}).ToArray());
foreach (var emotion in emotions)
{
foreach (var face in faces.Where(face => face.Height == emotion.FaceRectangle.Height &&
face.Left == emotion.FaceRectangle.Left &&
face.Top == emotion.FaceRectangle.Top &&
face.Width == emotion.FaceRectangle.Width))
{
face.Scores = emotion.Scores;
face.CalculateEmotion();
}
}
return faces;
}
}
// method to take a still image, send to APIs, and display result
public async void takePhoto_Click(object sender, RoutedEventArgs e)
{
try
{
takePhoto.IsEnabled = false;
photoFile = await KnownFolders.PicturesLibrary.CreateFileAsync(
PHOTO_FILE_NAME, CreationCollisionOption.GenerateUniqueName);
ImageEncodingProperties imageProperties = ImageEncodingProperties.CreateJpeg();
await mediaCapture.CapturePhotoToStorageFileAsync(imageProperties, photoFile);
takePhoto.IsEnabled = true;
statusBox.Text = "Take Photo succeeded: " + photoFile.Path;
IRandomAccessStream photoStream = await photoFile.OpenReadAsync();
IRandomAccessStream photoStream2 = await photoFile.OpenReadAsync();
BitmapImage bitmap = new BitmapImage();
bitmap.SetSource(photoStream);
await writeableBitmap.SetSourceAsync(photoStream2);
// and now for the face API call
statusBox.Text = "Uploading image for Face API";
Stream fs1 = await photoFile.OpenStreamForReadAsync();
Stream fs2 = await photoFile.OpenStreamForReadAsync();
var faceClient = new FaceServiceClient("9725d03742394560be3ff295e1e435a2");
var emotionClient = new EmotionServiceClient("c9306a1f134749759f1f4f9ae8838e1a");
faceResult = await faceClient.DetectAsync(fs1);
emotionResult = await emotionClient.RecognizeAsync(fs2);
numFaces = faceResult.Length;
statusBox.Text = "Number of faces detected: " + numFaces.ToString();
currentFace = 0;
if (numFaces > 0) // if faces were returned in the result, display the first one
{
displayFaceInfo();
displayImage();
}
}
catch (Exception ex)
{
statusBox.Text = ex.Message;
Cleanup();
}
finally
{
takePhoto.IsEnabled = true;
}
}
private async void DetectAsync()
{
Shell.SetBusyVisibility( Visibility.Visible, "Taking photo.." );
this.operationMode = OperationMode.Detect;
this.viewModel.PhotoFile = await this.camera.CapturePhotoToFileAsync();
await this.camera.CaptureManager.StopPreviewAsync();
if( this.led != null )
{
this.led.TurnOff();
}
Shell.SetBusyVisibility( Visibility.Visible, "Detecting your face.." );
Face.FaceServiceClient faceClient = new Face.FaceServiceClient( FACE_API_KEY );
Stream stream = await this.viewModel.PhotoFile.OpenStreamForReadAsync();
Face.Contract.Face[] faces = await faceClient.DetectAsync( stream, analyzesAge: true, analyzesGender: true );
VoiceGender voiceGender = VoiceGender.Male;
if( faces.Length == 1 )
{
Face.Contract.FaceAttribute face = faces[ 0 ].Attributes;
string greet;
if( face.Gender == "male" )
{
greet = "Hello Handsome!";
voiceGender = VoiceGender.Female;
}
else
{
greet = "Hey, Sexy!";
voiceGender = VoiceGender.Male;
}
this.viewModel.Greet = $"{greet} You look {face.Age} today.";
await this.SpeakAsync( this.viewModel.Greet, voiceGender, true );
}
else
{
this.viewModel.Greet = "I cannot see your face :(";
}
Shell.SetBusyVisibility( Visibility.Visible, "Detecting your emotions.." );
Emotion.EmotionServiceClient emotionClient = new Emotion.EmotionServiceClient( EMOTION_API_KEY );
stream = await this.viewModel.PhotoFile.OpenStreamForReadAsync();
Emotion.Contract.Emotion[] emotions = await emotionClient.RecognizeAsync( stream );
if( emotions.Length == 1 )
{
Emotion.Contract.Scores scores = emotions[ 0 ].Scores;
this.viewModel.Scores = scores;
bool like = scores.Happiness > scores.Anger + scores.Sadness + scores.Disgust;
this.viewModel.EvaluationResult = like
? "So you liked it! I'm so happy to hear that! :)"
: "Oh, really? I'm terribly sorry! :(";
await this.SpeakAsync( this.viewModel.EvaluationResult, voiceGender, false );
}
else
{
this.viewModel.EvaluationResult = "I cannot see your emotions :(";
}
this.operationMode = OperationMode.Done;
Shell.SetBusyVisibility( Visibility.Collapsed );
}
private async Task<Emotion[]> UploadAndDetectEmotion(string subscriptionKey, Stream imageStream)
{
try
{
var emotionServiceClient = new EmotionServiceClient(subscriptionKey);
var emotionResult = await emotionServiceClient.RecognizeAsync(imageStream);
return emotionResult;
}
catch (Exception ex)
{
Debug.WriteLine($"Error {ex}");
return null;
}
}