private async Task DetectarRostro(BitmapImage bitmapSource, Image img, string path)
{
try
{
faceList = await UploadAndDetectFaces(path);
if (faceList.Count > 0)
{
// Prepare to draw rectangles around the faces.
DrawingVisual visual = new DrawingVisual();
DrawingContext drawingContext = visual.RenderOpen();
drawingContext.DrawImage(bitmapSource,
new Rect(0, 0, bitmapSource.Width, bitmapSource.Height));
double dpi = bitmapSource.DpiX;
// Some images don't contain dpi info.
resizeFactor = (dpi == 0) ? 1 : 96 / dpi;
faceDescriptions = new String[faceList.Count];
for (int i = 0; i < faceList.Count; ++i)
{
DetectedFace face = faceList[i];
// Draw a rectangle on the face.
drawingContext.DrawRectangle(
System.Windows.Media.Brushes.Transparent,
new System.Windows.Media.Pen(System.Windows.Media.Brushes.Red, 2),
new Rect(
face.FaceRectangle.Left * resizeFactor,
face.FaceRectangle.Top * resizeFactor,
face.FaceRectangle.Width * resizeFactor,
face.FaceRectangle.Height * resizeFactor
)
);
// Store the face description.
faceDescriptions[i] = FaceDescription(face);
defaultStatusBarText = FaceDescription(face);
}
drawingContext.Close();
// Display the image with the rectangle around the face.
RenderTargetBitmap faceWithRectBitmap = new RenderTargetBitmap(
(int)(bitmapSource.PixelWidth * resizeFactor),
(int)(bitmapSource.PixelHeight * resizeFactor),
96,
96,
PixelFormats.Pbgra32);
faceWithRectBitmap.Render(visual);
// img = faceWithRectBitmap;
// Set the status bar text.
MessageBox.Show(defaultStatusBarText);
}
}
catch (Exception)
{
}
}
private List <Guid?> AddLargeFaceListFace(IFaceClient client, string largeFaceListId, string fileName)
{
var persistedFaceIds = new List <Guid?>();
for (int i = 1; i < 4; i++)
{
DetectedFace face = null;
using (FileStream stream = new FileStream(Path.Combine("TestImages", fileName + i + ".jpg"), FileMode.Open))
{
face = client.Face.DetectWithStreamAsync(stream, true, recognitionModel: recognitionModel).Result[0];
}
using (FileStream stream = new FileStream(Path.Combine("TestImages", fileName + i + ".jpg"), FileMode.Open))
{
var persistedFace = client.LargeFaceList.AddFaceFromStreamAsync(largeFaceListId, stream, null, new List <int> {
face.FaceRectangle.Left,
face.FaceRectangle.Top,
face.FaceRectangle.Width,
face.FaceRectangle.Height
}).Result;
persistedFaceIds.Add(persistedFace.PersistedFaceId);
}
}
return(persistedFaceIds);
}
public async Task <Person> CreatePersonWithFace(DetectedFace detectedFace, OrganizationUser organizationUser, Stream imageStream)
{
if (detectedFace?.FaceId == null)
{
return(null);
}
// Create person
var userPerson = await _faceClient.PersonGroupPerson.CreateAsync(
ConfigurationSettings.PersonGroupId,
organizationUser.Name,
JsonConvert.SerializeObject(organizationUser));
imageStream.Seek(0L, SeekOrigin.Begin);
await _faceClient.PersonGroupPerson.AddFaceFromStreamAsync(
ConfigurationSettings.PersonGroupId,
userPerson.PersonId,
imageStream);
var person = await _faceClient.PersonGroupPerson.GetAsync(ConfigurationSettings.PersonGroupId, userPerson.PersonId);
var blobName = $"{organizationUser.Email}.json";
await CreateBlobContent(blobName, ContainerSettings.PersonsContainer, person);
return(person);
}
/// <summary>
/// Get the cell for a face
/// </summary>
/// <param name="previewFrameSize">Webcam resolution</param>
/// <param name="face">Detected face</param>
/// <returns>Cell</returns>
private Cell CreateFaceCell(Size previewFrameSize, DetectedFace face)
{
var cellX = (face.FaceBox.X + face.FaceBox.Width / 2) / (uint)(previewFrameSize.Width / _columnsCount);
var cellY = (face.FaceBox.Y + face.FaceBox.Height / 2) / (uint)(previewFrameSize.Height / _rowsCount);
return(new Cell((int)cellX, (int)cellY));
}
internal FaceImageDimensions(DetectedFace faceToInclude, double facePercentage, int imageHeight, int imageWidth)
{
FaceRectangle faceRectangle = faceToInclude.FaceRectangle;
int imageSize = Calculate100Size(faceRectangle.Height > faceRectangle.Width ? faceRectangle.Height : faceRectangle.Width, facePercentage);
Calculate(faceRectangle, imageSize, imageHeight, imageWidth);
}
public static Member ToMember(this DetectedFace value)
{
var attribs = value.FaceAttributes;
var member = new Member
{
FaceId = value.FaceId.ToString(),
Gender = attribs.Gender.ToGenderType(),
Age = (double)attribs.Age,
Smile = (double)attribs.Smile,
FacialHair = attribs.FacialHair.Average(),
Glasses = attribs.Glasses.Average(),
Makeup = attribs.Makeup.Average(),
Emotion = new EmotionValues
(
attribs.Emotion.Anger,
attribs.Emotion.Contempt,
attribs.Emotion.Disgust,
attribs.Emotion.Fear,
attribs.Emotion.Happiness,
attribs.Emotion.Neutral,
attribs.Emotion.Sadness,
attribs.Emotion.Surprise
)
};
return(member);
}
public async Task <WriteableBitmap> MarkFaces(StorageFile file, DetectedFace[] faces)
{
if (faces.Length == 0)
{
return(null);
}
using (var stream = await file.OpenStreamForReadAsync())
{
WriteableBitmap wb = await BitmapFactory.FromStream(stream);
using (wb.GetBitmapContext())
{
for (int i = 0; i < faces.Length; ++i)
{
DetectedFace face = faces[i];
wb.DrawRectangle(
face.FaceRectangle.Left,
face.FaceRectangle.Top,
face.FaceRectangle.Left + face.FaceRectangle.Width,
face.FaceRectangle.Top + face.FaceRectangle.Height,
Colors.Red
);
}
}
return(wb);
}
}
private async void OnAnalyzeFaces(object sender, EventArgs e)
{
if (_photo == null)
{
return;
}
EnableAllButtons(false);
try
{
IList <DetectedFace> faces = await FaceDetection.MakeAnalysisRequest(_photo);
DetectedFace face = faces.FirstOrDefault();
ActivityIndicator.IsRunning = false;
if (face == null)
{
await DisplayAlert("Face Analysis", "No Faces Found", "OK");
return;
}
string smiling = face.FaceAttributes.Smile >= 0.75 ? "smiling" : "not smiling";
var analysis = $"{face.FaceAttributes.Age} year old {face.FaceAttributes.Gender} who is {smiling}.";
await DisplayAlert("Face Analysis", analysis, "OK");
}
catch (Exception ex)
{
await DisplayAlert("Analysis Error", ex.Message, "OK");
}
finally
{
EnableAllButtons(true);
}
}
public Identification(Person person, double confidence, IdentifyResult identifyResult, DetectedFace face)
{
Person = person;
IdentifyResult = identifyResult;
Face = face;
Confidence = confidence;
}
public async Task DetectSingleFaceAsync_Success()
{
// Arrange
var unitUnderTest = this.CreateFaceMatcher();
Stream photo = new MemoryStream();
DetectedFace expected = new DetectedFace
{
FaceId = Guid.NewGuid(),
FaceAttributes = new FaceAttributes(gender: Gender.Female)
};
var response = new Microsoft.Rest.HttpOperationResponse <IList <DetectedFace> >
{
Body = new[] { expected }
};
this.mockFaceOperations
.Setup(mock => mock.DetectWithStreamWithHttpMessagesAsync(
photo,
true, // returnFaceId
false, // returnFaceLandmarks
It.Is <IList <FaceAttributeType> >(list => list.Count == 1 && list.Contains(FaceAttributeType.Gender)),
null, // customeHeaders
It.IsAny <System.Threading.CancellationToken>()))
.Returns(Task.FromResult(response));
// Act
DetectedFace result = await unitUnderTest.DetectSingleFaceAsync(photo);
// Assert
result.ShouldNotBeNull();
result.FaceId.ShouldBe(expected.FaceId);
result.FaceAttributes.Gender.ShouldBe(expected.FaceAttributes.Gender);
}
private async Task HighlightDetectedFace(DetectedFace face)
{
var cx = ViewFinder.ActualWidth / VideoProps.Width;
var cy = ViewFinder.ActualHeight / VideoProps.Height;
DFace = face;
if (face == null)
{
FaceRect.Visibility = Visibility.Collapsed;
Counter.Visibility = Visibility.Collapsed;
dt.Stop();
IsFacePresent = false;
}
else
{
// Canvas.SetLeft(FaceRect, face.FaceBox.X);
// Canvas.SetTop(FaceRect, face.FaceBox.Y);
FaceRect.Margin = new Thickness(cx * face.FaceBox.X, cy * face.FaceBox.Y, 0, 0);
FaceRect.Width = cx * face.FaceBox.Width;
FaceRect.Height = cy * face.FaceBox.Height;
FaceRect.Visibility = Visibility.Visible;
Counter.Margin = new Thickness(cx * face.FaceBox.X, cy * face.FaceBox.Y, 0, 0);
Counter.Width = face.FaceBox.Width;
if (!IsFacePresent)
{
Counter.Visibility = Visibility.Visible;
IsFacePresent = true;
counter = 3; Counter.Text = counter.ToString();
dt.Start();
}
}
}
private async Task HighlightDetectedFace(DetectedFace face)
{
var cx = ViewFinder.ActualWidth / VideoProps.Width;
var cy = ViewFinder.ActualHeight / VideoProps.Height;
if (face == null)
{
FaceRect.Visibility = Visibility.Collapsed;
IsFacePresent = false;
last_emo = "";
EmoDesc.Visibility = EmoControl.Visibility = Visibility.Collapsed;
Desc.Visibility = Visibility.Visible;
}
else
{
// Canvas.SetLeft(FaceRect, face.FaceBox.X);
// Canvas.SetTop(FaceRect, face.FaceBox.Y);
FaceRect.Margin = new Thickness(cx * face.FaceBox.X, cy * face.FaceBox.Y, 0, 0);
FaceRect.Width = cx * face.FaceBox.Width;
FaceRect.Height = cy * face.FaceBox.Height;
FaceRect.Visibility = Visibility.Visible;
IsFacePresent = true;
EmoDesc.Visibility = EmoControl.Visibility = Visibility.Visible;
Desc.Visibility = Visibility.Collapsed;
}
}
public JsonResult FaceRecognitionResult(string xcoordinate, string ycoordinate)
{
IList <DetectedFace> faceList = JsonConvert.DeserializeObject <IList <DetectedFace> >(TempData.Peek("FaceList").ToString());
String[] faceDescriptions;
double xcoordinate_val = Convert.ToDouble(xcoordinate);
double ycoordinate_val = Convert.ToDouble(ycoordinate);
string face_desc = "";
if (faceList.Count > 0)
{
faceDescriptions = new String[faceList.Count];
for (int i = 0; i < faceList.Count; ++i)
{
DetectedFace face = faceList[i];
FaceRecognitionProcess oProcess = new FaceRecognitionProcess();
faceDescriptions[i] = oProcess.FaceDescription(face);
// Display the face description if the mouse is over this face rectangle.
if (xcoordinate_val >= face.FaceRectangle.Left && xcoordinate_val <= face.FaceRectangle.Left + face.FaceRectangle.Width &&
ycoordinate_val >= face.FaceRectangle.Top && ycoordinate_val <= face.FaceRectangle.Top + face.FaceRectangle.Height)
{
face_desc = faceDescriptions[i];
break;
}
}
}
return(Json(face_desc));
}
private void SaveFaceData(DetectedFace face)
{
var faceData = new
{
Source = cameraRadioButton.Checked ? "Câmera" : openFileDialog.FileName.Split('\\').LastOrDefault(),
FaceID = face.FaceId.ToString(),
Gender = face.FaceAttributes.Gender.ToString(),
Age = (int)face.FaceAttributes.Age,
Emotion = face.FaceAttributes.Emotion.ToRankedList().FirstOrDefault().Key,
Glasses = face.FaceAttributes.Glasses.ToString(),
EyeMakeup = face.FaceAttributes.Makeup.EyeMakeup,
LipMakeup = face.FaceAttributes.Makeup.LipMakeup,
Beard = face.FaceAttributes.FacialHair.Beard,
Bald = face.FaceAttributes.Hair.Bald,
HairColor = face.FaceAttributes.Hair.HairColor.GetTopHairColor()
};
var functionUrl = "http://localhost:7071/api/FaceReactionFunction";
var client = new RestClient(functionUrl);
var request = new RestRequest(Method.POST);
request.AddHeader("Content-Type", "application/json");
request.AddParameter("undefined", Newtonsoft.Json.JsonConvert.SerializeObject(faceData), ParameterType.RequestBody);
client.ExecuteAsync(request, null);
}
/// <summary>
/// FaceAPI実行
/// </summary>
public static async Task <DetectedFace> ExecuteFaceAPIAsync(string apiKey, string faceUriEndPoint, FaceAttributeType[] faceAttributes, ImageSource faceImageSource)
{
var ret = new DetectedFace();
try
{
// クライアント作成
var faceClient = new FaceClient(new ApiKeyServiceClientCredentials(apiKey), new System.Net.Http.DelegatingHandler[] { })
{
Endpoint = faceUriEndPoint,
};
// ストリーム(タップした画像)から検出処理
System.Diagnostics.Debug.WriteLine("FaceAPI実行");
var faceList = await faceClient.Face.DetectWithStreamAsync(Common.GetStreamFromImageSource(faceImageSource), true, false, faceAttributes);
if (faceList.Count == 0 || faceList == null)
{
await UserDialogs.Instance.AlertAsync($"顔検出できませんでした。", "ExecuteFaceAPIAsync", "OK");
return(null);
}
ret = faceList[0];
}
catch (APIErrorException ex)
{
await UserDialogs.Instance.AlertAsync($"APIErrorExceptionです。\n{ex}", "ExecuteFaceAPIAsync", "OK");
}
catch (Exception ex)
{
await UserDialogs.Instance.AlertAsync($"例外が発生しました。\n{ex}", "ExecuteFaceAPIAsync", "OK");
}
return(ret);
}
private EmotionType GetEmotion(DetectedFace detected)
{
if (detected.FaceAttributes.Emotion.Anger > 70)
{
return(EmotionType.Anger);
}
else if (detected.FaceAttributes.Emotion.Sadness > 70)
{
return(EmotionType.Sad);
}
else if (detected.FaceAttributes.Emotion.Happiness > 70)
{
return(EmotionType.Happy);
}
else if (detected.FaceAttributes.Emotion.Fear > 70)
{
return(EmotionType.Fear);
}
else if (detected.FaceAttributes.Emotion.Disgust > 70)
{
return(EmotionType.Disgust);
}
else if (detected.FaceAttributes.Emotion.Contempt > 70)
{
return(EmotionType.Contempt);
}
else if (detected.FaceAttributes.Emotion.Neutral > 70)
{
return(EmotionType.Neutral);
}
else
{
return(EmotionType.Unknown);
}
}
public FaceDetails(DetectedFace face, System.Windows.Size imageSize, int imgPixelWidth, int imgPixelHeight)
{
this.face = face;
InitializeComponent();
if (face.FaceOwner != null)
{
PersonNames.Text = $"{face.FaceOwner.Name} {face.FaceOwner.LastName}";
if (face.FaceOwner.DateOfBirth.HasValue)
{
PersonAge.Text = $"{(int)((DateTime.Now - face.FaceOwner.DateOfBirth.Value).TotalDays) / 365} lat";
}
}
sta.MouseEnter += FaceRectangle_MouseEnter;
sta.MouseLeave += FaceRectangle_MouseLeave;
var width = imageSize.Width;
var height = imageSize.Height;
var xRatio = width / imgPixelWidth;
var yRatio = height / imgPixelHeight;
var posX = face.FaceRectangle.Left;
var posY = face.FaceRectangle.Top;
var renderXpos = xRatio * posX;
var renderYpos = yRatio * posY;
Margin = new Thickness(renderXpos, renderYpos, 0, 0);
FaceRectangle.Width = face.FaceRectangle.Width * xRatio;
FaceRectangle.Height = face.FaceRectangle.Height * yRatio;
}
public void SetImageInfo(DetectedFace face)
{
id = face.FaceId.ToString();
age = face.FaceAttributes.Age;
gender = face.FaceAttributes.Gender;
imageDate = DateTime.Now;
AddEmotions(face.FaceAttributes.Emotion);
}
public void SetImageInfo(DetectedFace face)
{
UserId = SignInViewModel.currentUser.Id;
Age = face.FaceAttributes.Age;
Gender = face.FaceAttributes.Gender;
ImageDate = DateTime.Now;
AddEmotions(face.FaceAttributes.Emotion);
}
private static FaceCategory GetFaceCategory(DetectedFace face, string countryCode)
{
Debug.Assert(face.FaceAttributes.Gender.HasValue, "Face detection did not return a Gender");
FaceCategory searchCategory
= new FaceCategory(countryCode, face.FaceAttributes.Gender.Value.Convert());
return(searchCategory);
}
public FaceIcon(DetectedFace face)
{
Face = face;
InitializeComponent();
Loaded += FaceIcon_Loaded;
}
public Identification(string name, double confidence, IdentifyResult identifyResult, DetectedFace face)
{
Person = new Person();
Person.Name = name;
IdentifyResult = identifyResult;
Face = face;
Confidence = confidence;
}
// TODO: 7. 얼굴의 대표 감정을 얻어와 얼굴 사각형 표시하는 메서드 DisplayEmotion()
private void DisplayEmotion(BitmapImage softwareBitmap, DetectedFace emotion)
{
if (emotion != null)
{
var emotionName = EmotionHelper.GetTopEmotionName(emotion);
DrawFaceBox(softwareBitmap, emotion.FaceRectangle, emotionName);
}
}
private static void DrawRectangle(WriteableBitmap bitmap, DetectedFace face, Color color, int thinkness)
{
var left = face.FaceRectangle.Left;
var top = face.FaceRectangle.Top;
var width = face.FaceRectangle.Width;
var height = face.FaceRectangle.Height;
DrawRectangle(bitmap, left, top, width, height, color, thinkness);
}
public async void BtnTake_Clicked(object sender, EventArgs e)
{
await CrossMedia.Current.Initialize();
try
{
if (!CrossMedia.Current.IsCameraAvailable || !CrossMedia.Current.IsTakePhotoSupported)
{
await DisplayAlert("No Camera", ":( No camera available.", "OK");
return;
}
var file = await CrossMedia.Current.TakePhotoAsync(new Plugin.Media.Abstractions.StoreCameraMediaOptions
{
Directory = "Sample",
Name = "xamarin.jpg"
});
if (file == null)
{
return;
}
imgChoosed.Source = ImageSource.FromStream(() =>
{
var stream = file.GetStream();
return(stream);
});
Esperar.IsVisible = true;
Esperar.IsRunning = true;
lblResult.Text = null;
var faceList = await Task.Run(async() => await GetImageDescription(file.GetStream()));
Esperar.IsVisible = false;
Esperar.IsRunning = false;
file.Dispose();
Title = "Detecting...";
Title = String.Format(
"Detection Finished. {0} face(s) detected", faceList.Count);
faceDescriptions = new String[faceList.Count];
for (int i = 0; i < faceList.Count; ++i)
{
DetectedFace face = faceList[i];
faceDescriptions[i] = FaceDescription(face);
lblResult.Text = faceDescriptions[i] + "\r\n";
}
}
catch (Exception ex)
{
string test = ex.Message;
}
}
private static void Translate(Rectangle rectangle, DetectedFace detectedFace)
{
var translateTransform = new TranslateTransform()
{
X = detectedFace.FaceBox.X,
Y = detectedFace.FaceBox.Y
};
rectangle.RenderTransform = translateTransform;
}
private void AddFacialLandmark(DetectedFace face, Coordinate coordinate, double renderedImageXTransform, double renderedImageYTransform, Color color)
{
double dotSize = 3;
Rectangle b = new Rectangle {
Fill = new SolidColorBrush(color), Width = dotSize, Height = dotSize, HorizontalAlignment = HorizontalAlignment.Left, VerticalAlignment = VerticalAlignment.Top
};
b.Margin = new Thickness(((coordinate.X - face.FaceRectangle.Left) * renderedImageXTransform) - dotSize / 2, ((coordinate.Y - face.FaceRectangle.Top) * renderedImageYTransform) - dotSize / 2, 0, 0);
this.hostGrid.Children.Add(b);
}
// </snippet_uploaddetect>
// <snippet_facedesc>
// Creates a string out of the attributes describing the face.
private static string FaceDescription(DetectedFace face)
{
StringBuilder sb = new StringBuilder();
sb.Append("Face: ");
sb.Append("Pitch:" + face.FaceAttributes.HeadPose.Pitch + "Yaw:" + face.FaceAttributes.HeadPose.Yaw + "Roll:" + face.FaceAttributes.HeadPose.Roll);
// Return the built string.
return(sb.ToString());
}
/// <summary>
/// Get the cell for a face
/// </summary>
/// <param name="previewFrameSize">Webcam resolution</param>
/// <param name="face">Detected face</param>
/// <returns>Cell</returns>
private Cell CreateFaceCell(Size previewFrameSize, DetectedFace face)
{
var cellX = (face.FaceBox.X + face.FaceBox.Width / 2) / (uint)(previewFrameSize.Width / _columnsCount);
var cellY = (face.FaceBox.Y + face.FaceBox.Height / 2) / (uint)(previewFrameSize.Height / _rowsCount);
return new Cell((int)cellX, (int)cellY);
}