/// <summary>
/// Pick image for detection, and using the detected face as the face to person verify.
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private async void FaceImagePicker_Click(object sender, RoutedEventArgs e)
{
// Show image picker, show jpg type files only
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files(*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
PersonVerifyResult = string.Empty;
// User already picked one image
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
RightImageDisplay2.Source = renderingImage;
// Clear last time detection results
RightFaceResultCollection.Clear();
PersonVerifyButton.IsEnabled = (FacesCollection.Count != 0 && RightFaceResultCollection.Count != 0);
MainWindow.Log("Request: Detecting in {0}", pickedImagePath);
var sw = Stopwatch.StartNew();
// Call detection REST API, detect faces inside the image
using (var fileStream = File.OpenRead(pickedImagePath))
{
try
{
var faceServiceClient = FaceServiceClientHelper.GetInstance(this);
var faces = await faceServiceClient.Face.DetectWithStreamAsync(fileStream, recognitionModel : recognitionModel);
// Handle REST API calling error
if (faces == null)
{
return;
}
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Count, pickedImagePath);
// Convert detection results into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
// Detected faces are hosted in result container, will be used in the verification later
RightFaceResultCollection.Add(face);
}
PersonVerifyButton.IsEnabled = (FacesCollection.Count != 0 && RightFaceResultCollection.Count != 0);
}
catch (APIErrorException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.Body.Error.Code, ex.Body.Error.Message);
return;
}
}
}
GC.Collect();
}
private async void LoadImage_Click(object sender, RoutedEventArgs e)
{
// Show file picker dialog
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files (*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
// Clear last detection result
ResultCollection.Clear();
DetectedFaces.Clear();
ImageGlassesDisplay.Source = null;
DetectedResultsInText = string.Format("Detecting...");
// show Main Windows
MainWindow.Log("Request: Detecting {0}", pickedImagePath);
var sw = Stopwatch.StartNew();
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
faces = await faceServiceClient.DetectAsync(fStream, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Length, pickedImagePath);
DetectedResultsInText = string.Format("{0} face(s) has been detected. You can see the result", faces.Length);
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSizes, imageInfo))
{
ResultCollection.Add(face);
}
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
GC.Collect();
return;
}
GC.Collect();
}
}
}
public BitmapSource getMergedPicture(string userPicturePath, string hisPicturePath)
{
var hismanImage = UIHelper.LoadImageAppliedOrientation(hisPicturePath);
WriteableBitmap target = new WriteableBitmap(
hismanImage.PixelWidth,
hismanImage.PixelHeight,
hismanImage.DpiX, hismanImage.DpiY,
hismanImage.Format, null);
WriteableBitmap[] targets = { target };
getMergedPictureCore(userPicturePath, hisPicturePath, targets, hismanImage);
return(targets[0]);
}
/// <summary>
/// Pick image for face detection and set detection result to result container
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event argument</param>
private async void ImagePicker_Click(object sender, RoutedEventArgs e)
{
// Show file picker dialog
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files (*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
// Clear last detection result
ResultCollection.Clear();
DetectedFaces.Clear();
DetectedResultsInText = string.Format("Detecting...");
MainWindow.Log("Request: Detecting {0}", pickedImagePath);
var sw = Stopwatch.StartNew();
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
ProjectOxford.Face.Contract.Face[] faces = await faceServiceClient.DetectAsync(fStream, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Length, pickedImagePath);
DetectedResultsInText = string.Format("{0} face(s) has been detected", faces.Length);
foreach (var face in faces)
{
DetectedFaces.Add(new Face()
{
ImageFile = renderingImage,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId.ToString(),
Age = string.Format("{0:#} years old", face.FaceAttributes.Age),
Gender = face.FaceAttributes.Gender,
HeadPose = string.Format("Pitch: {0}, Roll: {1}, Yaw: {2}", Math.Round(face.FaceAttributes.HeadPose.Pitch, 2), Math.Round(face.FaceAttributes.HeadPose.Roll, 2), Math.Round(face.FaceAttributes.HeadPose.Yaw, 2)),
FacialHair = string.Format("FacialHair: {0}", face.FaceAttributes.FacialHair.Moustache + face.FaceAttributes.FacialHair.Beard + face.FaceAttributes.FacialHair.Sideburns > 0 ? "Yes" : "No"),
Glasses = string.Format("GlassesType: {0}", face.FaceAttributes.Glasses.ToString()),
Emotion = $"{GetEmotion(face.FaceAttributes.Emotion)}",
Hair = string.Format("Hair: {0}", GetHair(face.FaceAttributes.Hair)),
Makeup = string.Format("Makeup: {0}", ((face.FaceAttributes.Makeup.EyeMakeup || face.FaceAttributes.Makeup.LipMakeup) ? "Yes" : "No")),
EyeOcclusion = string.Format("EyeOccluded: {0}", ((face.FaceAttributes.Occlusion.EyeOccluded) ? "Yes" : "No")),
ForeheadOcclusion = string.Format("ForeheadOccluded: {0}", (face.FaceAttributes.Occlusion.ForeheadOccluded ? "Yes" : "No")),
MouthOcclusion = string.Format("MouthOccluded: {0}", (face.FaceAttributes.Occlusion.MouthOccluded ? "Yes" : "No")),
Accessories = $"{GetAccessories(face.FaceAttributes.Accessories)}",
Blur = string.Format("Blur: {0}", face.FaceAttributes.Blur.BlurLevel.ToString()),
Exposure = string.Format("{0}", face.FaceAttributes.Exposure.ExposureLevel.ToString()),
Noise = string.Format("Noise: {0}", face.FaceAttributes.Noise.NoiseLevel.ToString()),
});
}
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
ResultCollection.Add(face);
}
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
GC.Collect();
return;
}
GC.Collect();
}
}
}
/// <summary>
/// Pick image, detect and identify all faces detected
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void Identify_Click(object sender, RoutedEventArgs e)
{
// Show file picker
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files(*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
// Clear previous detection and identification results
TargetFaces.Clear();
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
var sw = Stopwatch.StartNew();
var faceServiceClient = FaceServiceClientHelper.GetInstance(this);
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
var faces = await faceServiceClient.Face.DetectWithStreamAsync(fStream, recognitionModel : recognitionModel, detectionModel : detectionModel);
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
TargetFaces.Add(face);
}
MainWindow.Log("Request: Identifying {0} face(s) in group \"{1}\"", faces.Count, GroupName);
// Identify each face
// Call identify REST API, the result contains identified person information
var identifyResult = await faceServiceClient.Face.IdentifyAsync((from face in faces where face.FaceId != null select face.FaceId.Value).ToList(), null, GroupName);
for (int idx = 0; idx < faces.Count; idx++)
{
// Update identification result for rendering
var face = TargetFaces[idx];
var res = identifyResult[idx];
if (res.Candidates.Count > 0 && Persons.Any(p => p.PersonId == res.Candidates[0].PersonId.ToString()))
{
face.PersonName = Persons.Where(p => p.PersonId == res.Candidates[0].PersonId.ToString()).First().PersonName;
}
else
{
face.PersonName = "Unknown";
}
}
var outString = new StringBuilder();
foreach (var face in TargetFaces)
{
outString.AppendFormat("Face {0} is identified as {1}. ", face.FaceId, face.PersonName);
}
MainWindow.Log("Response: Success. {0}", outString);
}
catch (APIErrorException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.Body.Error.Code, ex.Body.Error.Message);
}
}
}
GC.Collect();
}
/// <summary>
/// Pick image and call find similar with both two modes for each faces detected
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void FindSimilar_Click(object sender, RoutedEventArgs e)
{
// Show file picker
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files (*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var filePicker = dlg.ShowDialog();
if (filePicker.HasValue && filePicker.Value)
{
// User picked image
// Clear previous detection and find similar results
TargetFaces.Clear();
FindSimilarMatchPersonCollection.Clear();
FindSimilarMatchFaceCollection.Clear();
var sw = Stopwatch.StartNew();
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
// Detect all faces in the picked image
using (var fStream = File.OpenRead(pickedImagePath))
{
MainWindow.Log("Request: Detecting faces in {0}", SelectedFile);
var faceServiceClient = FaceServiceClientHelper.GetInstance(this);
IList <DetectedFace> faces = await faceServiceClient.Face.DetectWithStreamAsync(fStream);
// Update detected faces on UI
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
TargetFaces.Add(face);
}
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Count, SelectedFile);
// Find two modes similar faces for each face
foreach (var f in faces)
{
if (f.FaceId == null)
{
continue;
}
var faceId = f.FaceId.Value;
MainWindow.Log("Request: Finding similar faces in Personal Match Mode for face {0}", faceId);
try
{
// Default mode, call find matchPerson similar REST API, the result contains all the face ids which is personal similar to the query face
const int requestCandidatesCount = 4;
IList <SimilarFace> result = await faceServiceClient.Face.FindSimilarAsync(
faceId,
null,
_largeFaceListName,
maxNumOfCandidatesReturned : requestCandidatesCount);
// Update find matchPerson similar results collection for rendering
var personSimilarResult = new FindSimilarResult();
personSimilarResult.Faces = new ObservableCollection <Face>();
personSimilarResult.QueryFace = new Face()
{
ImageFile = SelectedFile,
Top = f.FaceRectangle.Top,
Left = f.FaceRectangle.Left,
Width = f.FaceRectangle.Width,
Height = f.FaceRectangle.Height,
FaceId = faceId.ToString(),
};
foreach (var fr in result)
{
var candidateFace = FacesCollection.First(ff => ff.FaceId == fr.PersistedFaceId.ToString());
Face newFace = new Face();
newFace.ImageFile = candidateFace.ImageFile;
newFace.Confidence = fr.Confidence;
newFace.FaceId = candidateFace.FaceId;
personSimilarResult.Faces.Add(newFace);
}
MainWindow.Log("Response: Found {0} similar faces for face {1}", personSimilarResult.Faces.Count, faceId);
FindSimilarMatchPersonCollection.Add(personSimilarResult);
}
catch (APIErrorException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.Body.Error.Code, ex.Body.Error.Message);
}
try
{
// Call find facial match similar REST API, the result faces the top N with the highest similar confidence
const int requestCandidatesCount = 4;
var result = await faceServiceClient.Face.FindSimilarAsync(
faceId,
null,
_largeFaceListName,
maxNumOfCandidatesReturned : requestCandidatesCount,
mode : FindSimilarMatchMode.MatchFace);
// Update "matchFace" similar results collection for rendering
var faceSimilarResults = new FindSimilarResult();
faceSimilarResults.Faces = new ObservableCollection <Face>();
faceSimilarResults.QueryFace = new Face()
{
ImageFile = SelectedFile,
Top = f.FaceRectangle.Top,
Left = f.FaceRectangle.Left,
Width = f.FaceRectangle.Width,
Height = f.FaceRectangle.Height,
FaceId = faceId.ToString(),
};
foreach (var fr in result)
{
var candidateFace = FacesCollection.First(ff => ff.FaceId == fr.PersistedFaceId.ToString());
Face newFace = new Face();
newFace.ImageFile = candidateFace.ImageFile;
newFace.Confidence = fr.Confidence;
newFace.FaceId = candidateFace.FaceId;
faceSimilarResults.Faces.Add(newFace);
}
MainWindow.Log("Response: Found {0} similar faces for face {1}", faceSimilarResults.Faces.Count, faceId);
FindSimilarMatchFaceCollection.Add(faceSimilarResults);
}
catch (APIErrorException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.Body.Error.Code, ex.Body.Error.Message);
}
}
}
}
GC.Collect();
}
/// <summary>
/// Pick image, detect and identify all faces detected
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void Identify_Click(object sender, RoutedEventArgs e)
{
// Show file picker
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files(*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
// Clear previous detection and identification results
TargetFaces.Clear();
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
var sw = Stopwatch.StartNew();
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = "7f9f9eb9d73e4606bbfca54abcf93996";
string subscriptionEndpoint = "https://westcentralus.api.cognitive.microsoft.com/face/v1.0";
var faceServiceClient = new FaceServiceClient(subscriptionKey, subscriptionEndpoint);
var requiredFaceAttributes = new FaceAttributeType[] {
FaceAttributeType.Age,
FaceAttributeType.Gender,
FaceAttributeType.Smile,
FaceAttributeType.Hair,
FaceAttributeType.HeadPose,
FaceAttributeType.Glasses,
FaceAttributeType.Emotion
};
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
var faces = await faceServiceClient.DetectAsync(fStream, true, true, requiredFaceAttributes);
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
TargetFaces.Add(face);
}
MainWindow.Log("Request: Identifying {0} face(s) in group \"{1}\"", faces.Length, this.GroupId);
// Identify each face
// Call identify REST API, the result contains identified person information
var identifyResult = await faceServiceClient.IdentifyAsync(faces.Select(ff => ff.FaceId).ToArray(), largePersonGroupId : this.GroupId);
for (int idx = 0; idx < faces.Length; idx++)
{
// Update identification result for rendering
var face = TargetFaces[idx];
var res = identifyResult[idx];
if (res.Candidates.Length > 0 && Persons.Any(p => p.PersonId == res.Candidates[0].PersonId.ToString()))
{
face.PersonName = Persons.Where(p => p.PersonId == res.Candidates[0].PersonId.ToString()).First().PersonName;
}
else
{
face.PersonName = "Unknown";
}
}
var outString = new StringBuilder();
foreach (var face in faces)
{
MainWindow.Log("\nFace ID : {0}", face.FaceId.ToString());
StringBuilder sb = new StringBuilder();
// Add the gender, age, and smile.
sb.Append("Gender: ");
sb.Append(face.FaceAttributes.Gender);
sb.Append("\n ");
sb.Append("Age: ");
sb.Append(face.FaceAttributes.Age);
sb.Append("\n ");
sb.Append(String.Format("smile {0:F1}%\n ", face.FaceAttributes.Smile * 100));
// Add the emotions. Display all emotions over 10%.
sb.Append("Emotion: ");
Microsoft.ProjectOxford.Common.Contract.EmotionScores emotionScores = face.FaceAttributes.Emotion;
if (emotionScores.Anger >= 0.1f)
{
sb.Append(
String.Format("anger {0:F1}%, ", emotionScores.Anger * 100));
}
if (emotionScores.Contempt >= 0.1f)
{
sb.Append(
String.Format("contempt {0:F1}%, ", emotionScores.Contempt * 100));
}
if (emotionScores.Disgust >= 0.1f)
{
sb.Append(
String.Format("disgust {0:F1}%, ", emotionScores.Disgust * 100));
}
if (emotionScores.Fear >= 0.1f)
{
sb.Append(
String.Format("fear {0:F1}%, ", emotionScores.Fear * 100));
}
if (emotionScores.Happiness >= 0.1f)
{
sb.Append(
String.Format("happiness {0:F1}%, ", emotionScores.Happiness * 100));
}
if (emotionScores.Neutral >= 0.1f)
{
sb.Append(
String.Format("neutral {0:F1}%, ", emotionScores.Neutral * 100));
}
if (emotionScores.Sadness >= 0.1f)
{
sb.Append(
String.Format("sadness {0:F1}%, ", emotionScores.Sadness * 100));
}
if (emotionScores.Surprise >= 0.1f)
{
sb.Append(
String.Format("surprise {0:F1}%, ", emotionScores.Surprise * 100));
}
sb.Append("\n ");
// Add glasses.
sb.Append(face.FaceAttributes.Glasses);
sb.Append("\n ");
// Add hair.
sb.Append("Hair: ");
var hair = face.FaceAttributes.Hair;
if (hair.Bald >= 0.01f)
{
sb.Append(String.Format("bald {0:F1}% ", hair.Bald * 100));
}
// Display all hair color attributes over 10%.
var hairColors = hair.HairColor;
foreach (var hairColor in hairColors)
{
if (hairColor.Confidence >= 0.1)
{
sb.Append(hairColor.Color.ToString());
sb.Append(String.Format(" {0:F1}% ", hairColor.Confidence * 100));
}
}
/*if (hair.HairColor.Length == 0)
* {
* if (hair.Invisible)
* sb.Append("Invisible");
* else
* sb.Append("Bald");
* }
* else
* {
* Contract.HairColorType returnColor = Contract.HairColorType.Unknown;
* double maxConfidence = 0.0f;
*
* for (int i = 0; i < hair.HairColor.Length; ++i)
* {
* if (hair.HairColor[i].Confidence > maxConfidence)
* {
* maxConfidence = hair.HairColor[i].Confidence;
* returnColor = hair.HairColor[i].Color;
* }
* }
*
* sb.Append(returnColor.ToString());
* }*/
sb.Append("\n");
MainWindow.Log("Face Attributes : {0}", sb);
MainWindow.Log("Face MouthLeft(X) : {0}", face.FaceLandmarks.MouthLeft.X);
}
foreach (var face in TargetFaces)
{
outString.AppendFormat("Face {0} is identified as {1}. ", face.FaceId, face.PersonName);
}
MainWindow.Log("Response: Success. {0}", outString);
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
}
}
}
GC.Collect();
}
/// <summary>
/// Pick image for face detection and set detection result to result container
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event argument</param>
private async void icon_Click(object sender, RoutedEventArgs e)
{
// Show file picker dialog
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files (*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
// Clear last detection result
ResultCollection.Clear();
DetectedFaces.Clear();
DetectedResultsInText = string.Format("Detecting...");
MainWindow.Log("Request: Detecting {0}", pickedImagePath);
var sw = Stopwatch.StartNew();
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
ProjectOxford.Face.Contract.Face[] faces = await faceServiceClient.DetectAsync(fStream, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Length, pickedImagePath);
DetectedResultsInText = string.Format("{0} face(s) has been detected", faces.Length);
//Create Image type
Image renderingImage_img = Image.FromFile(dlg.FileName);
foreach (var face in faces)
{
// add Glasses to face
// Gan kinh len
renderingImage_img = Add_icon(renderingImage_img, face);
//ImageGlassesDisplay.Source = (BitmapImage)renderingImage_bit;
}
renderingImage_img.Save("F:\\study\\Project\\New pj\\Cognitive-Face-Windows\\Images\\icon\\" + saveImage_Count.ToString() + ".jpg");
BitmapImage DisplayImage = new BitmapImage(new Uri("F:\\study\\Project\\New pj\\Cognitive-Face-Windows\\Images\\icon\\" + saveImage_Count.ToString() + ".jpg"));
ImageiconDisplay.Source = DisplayImage;
saveImage_Count++;
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSizes, imageInfo))
{
ResultCollection.Add(face);
}
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
GC.Collect();
return;
}
GC.Collect();
}
}
}
/// <summary>
/// open camera dialog
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void OpenCamera_Click(object sender, RoutedEventArgs e)
{
//OpenFaceButton.IsEnabled = false;
CameraOpen camera = new CameraOpen();
camera.ShowDialog();
//Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
//dlg.DefaultExt = ".jpg";
//dlg.Filter = "Image files (*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
//var filePicker = dlg.ShowDialog();
//if (filePicker.HasValue && filePicker.Value)
//{
// User picked image
// Clear previous detection and find similar results
TargetFaces.Clear();
FindSimilarMatchPersonCollection.Clear();
FindSimilarMatchFaceCollection.Clear();
var sw = Stopwatch.StartNew();
var pickedImagePath = @"D:\3.jpg"; //dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
// Detect all faces in the picked image
using (var fStream = File.OpenRead(pickedImagePath))
{
MainWindow.Log("Request: Detecting faces in {0}", SelectedFile);
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
var faces = await faceServiceClient.DetectAsync(fStream);
// Update detected faces on UI
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
TargetFaces.Add(face);
}
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Length, SelectedFile);
// Find two modes similar faces for each face
foreach (var f in faces)
{
var faceId = f.FaceId;
MainWindow.Log("Request: Finding similar faces in Personal Match Mode for face {0}", faceId);
try
{
// Default mode, call find matchPerson similar REST API, the result contains all the face ids which is personal similar to the query face
const int requestCandidatesCount = 4;
var result = await faceServiceClient.FindSimilarAsync(faceId, faceid_list, requestCandidatesCount);
//faceServiceClient.F
// Update find matchPerson similar results collection for rendering
var personSimilarResult = new FindSimilarResult();
personSimilarResult.Faces = new ObservableCollection <Face>();
personSimilarResult.QueryFace = new Face()
{
ImageFile = SelectedFile,
Top = f.FaceRectangle.Top,
Left = f.FaceRectangle.Left,
Width = f.FaceRectangle.Width,
Height = f.FaceRectangle.Height,
FaceId = faceId.ToString(),
};
foreach (var fr in result)
{
var candidateFace = FacesCollection.First(ff => ff.FaceId == fr.FaceId.ToString());
Face newFace = new Face();
newFace.ImageFile = candidateFace.ImageFile;
newFace.Confidence = fr.Confidence;
newFace.FaceId = candidateFace.FaceId;
personSimilarResult.Faces.Add(newFace);
}
MainWindow.Log("Response: Found {0} similar faces for face {1}", personSimilarResult.Faces.Count, faceId);
FindSimilarMatchPersonCollection.Add(personSimilarResult);
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
}
try
{
// Call find facial match similar REST API, the result faces the top N with the highest similar confidence
const int requestCandidatesCount = 4;
var result = await faceServiceClient.FindSimilarAsync(faceId, faceid_list, FindSimilarMatchMode.matchFace, requestCandidatesCount);
// Update "matchFace" similar results collection for rendering
var faceSimilarResults = new FindSimilarResult();
faceSimilarResults.Faces = new ObservableCollection <Face>();
faceSimilarResults.QueryFace = new Face()
{
ImageFile = SelectedFile,
Top = f.FaceRectangle.Top,
Left = f.FaceRectangle.Left,
Width = f.FaceRectangle.Width,
Height = f.FaceRectangle.Height,
FaceId = faceId.ToString(),
};
foreach (var fr in result)
{
var candidateFace = FacesCollection.First(ff => ff.FaceId == fr.FaceId.ToString());
Face newFace = new Face();
newFace.ImageFile = candidateFace.ImageFile;
//Bitmap imag = new Bitmap();
//(candidateFace.ImageFile);
//g2.
// MainWindow.Log("Response: Found {0} similar faces for face {1}", , faceId);
newFace.Confidence = fr.Confidence;
newFace.Top = candidateFace.Top;
newFace.Left = candidateFace.Left;
newFace.Width = candidateFace.Width;
newFace.Height = candidateFace.Height;
newFace.FaceId = fr.FaceId.ToString();//candidateFace.FaceId;
faceSimilarResults.Faces.Add(newFace);
}
var candidate1 = FacesCollection.First(ff => ff.FaceId == result[0].FaceId.ToString());
Bitmap graph = new Bitmap(UIHelper.ImageSourceToBitmap(candidate1.ImageFile).Width, UIHelper.ImageSourceToBitmap(candidate1.ImageFile).Height);
Graphics g2 = Graphics.FromImage(graph);
g2.DrawImage(UIHelper.ImageSourceToBitmap(candidate1.ImageFile), 0, 0);
// Rectangle zuibiao = new Rectangle(f.FaceRectangle.Left, f.FaceRectangle.Top, f.FaceRectangle.Width, f.FaceRectangle.Height);
Rectangle zuibiao = new Rectangle(candidate1.Left, candidate1.Top, candidate1.Width, candidate1.Height);
//g2.DrawImageUnscaled(UIHelper.ImageSourceToBitmap(candidateFace.ImageFile),0,0);
g2.DrawImage(UIHelper.ImageSourceToBitmap(SelectedFile), zuibiao, f.FaceRectangle.Left, f.FaceRectangle.Top, f.FaceRectangle.Width, f.FaceRectangle.Height, GraphicsUnit.Pixel);
System.Drawing.Image saveImage = System.Drawing.Image.FromHbitmap(graph.GetHbitmap());
saveImage.Save(@"E:\hackathon\ls\cognitive-Face-Windows\data1\image1.jpg", ImageFormat.Jpeg);
Bitmap graph1 = new Bitmap(UIHelper.ImageSourceToBitmap(candidate1.ImageFile).Width, UIHelper.ImageSourceToBitmap(candidate1.ImageFile).Height);
Graphics g3 = Graphics.FromImage(graph1);
g3.DrawImage(UIHelper.ImageSourceToBitmap(candidate1.ImageFile), 0, 0);
System.Drawing.Image saveImage1 = System.Drawing.Image.FromHbitmap(graph1.GetHbitmap());
saveImage1.Save(@"E:\hackathon\ls\cognitive-Face-Windows\image1.jpg", ImageFormat.Jpeg);
MainWindow.Log("Response: Found {0} similar faces for face {1}", faceSimilarResults.Faces.Count, faceId);
MergeImage1 = getMergedPicture(@"D:\3.jpg", @"E:\hackathon\ls\cognitive-Face-Windows\image1.jpg");
//MergeImage1 = getMergedPicture("D:\\3.jpg", "D:\\1.jpg");
FindSimilarMatchFaceCollection.Add(faceSimilarResults);
/* MediaPlayer player = new MediaPlayer();
* player.Open(new Uri(media_name[candidate1.FaceId].Substring(0, media_name[candidate1.FaceId].Length - 4) + ".WAV", UriKind.Relative));
* player.Play();*/
Thread.Sleep(4000);
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
}
}
}
//}
//GC.Collect();
// OpenFaceButton.IsEnabled = false;
GC.Collect();
}
/// <summary>
/// Pick image folder and detect all faces in these images
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void FolderPicker_Click(object sender, RoutedEventArgs e)
{
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
/*try
* {
* MainWindow.Log("Request: Face List {0} will be used to build a person database. Checking whether the face list exists.", _faceListName);
*
* await faceServiceClient.GetFaceListAsync(_faceListName);
* groupExists = true;
* MainWindow.Log("Response: Face List {0} exists.", _faceListName);
* }
* catch (FaceAPIException ex)
* {
* if (ex.ErrorCode != "FaceListNotFound")
* {
* MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
* return;
* }
* else
* {
* MainWindow.Log("Response: Face List {0} did not exist previously.", _faceListName);
* }
* }
*
* if (groupExists)
* {
* var cleanFaceList = System.Windows.MessageBox.Show(string.Format("Requires a clean up for face list \"{0}\" before setting up a new face list. Click OK to proceed, face list \"{0}\" will be cleared.", _faceListName), "Warning", MessageBoxButton.OKCancel);
* if (cleanFaceList == MessageBoxResult.OK)
* {
* await faceServiceClient.DeleteFaceListAsync(_faceListName);
* }
* else
* {
* return;
* }
* }*/
OpenCameraButton.IsEnabled = false;
OpenFaceButton.IsEnabled = false;
// Show folder picker
//System.Windows.Forms.FolderBrowserDialog dlg = new System.Windows.Forms.FolderBrowserDialog();
//var result = dlg.ShowDialog();
//string file_path = @"D:\microsoftAPI\cognitive-Face-Windows\Data\PersonGroup\Family1-Mom";
string file_path = @"E:\hackathon\ls\cognitive-Face-Windows\data1";
bool forceContinue = false;
// if (result == System.Windows.Forms.DialogResult.OK)
if (System.IO.Directory.Exists(file_path))
{
// Enumerate all ".jpg" files in the folder, call detect
List <Task> tasks = new List <Task>();
FacesCollection.Clear();
//DetectionFacesCollection.Clear();
TargetFaces.Clear();
FindSimilarMatchPersonCollection.Clear();
FindSimilarMatchFaceCollection.Clear();
SelectedFile = null;
// Set the suggestion count is intent to minimum the data preparation step only,
// it's not corresponding to service side constraint
const int SuggestionCount = 10;
int processCount = 0;
MainWindow.Log("Request: Preparing, detecting faces in chosen folder.");
//await faceServiceClient.CreateFaceListAsync(_faceListName, _faceListName, "face list for sample");
var imageList =
new ConcurrentBag <string>(
Directory.EnumerateFiles(file_path /*dlg.SelectedPath*/, "*.*", SearchOption.AllDirectories)
.Where(s => s.ToLower().EndsWith(".jpg") || s.ToLower().EndsWith(".png") || s.ToLower().EndsWith(".bmp") || s.ToLower().EndsWith(".gif")));
string img;
int invalidImageCount = 0;
int i = 0;
while (imageList.TryTake(out img))
{
tasks.Add(Task.Factory.StartNew(
async(obj) =>
{
var imgPath = obj as string;
// Call detection
using (var fStream = File.OpenRead(imgPath))
{
try
{
/*var faces =
* await faceServiceClient.AddFaceToFaceListAsync(_faceListName, fStream);*/
// ProjectOxford.Face.Contract.Face[] faces = await faceServiceClient.DetectAsync(fStream, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
var renderingImage = UIHelper.LoadImageAppliedOrientation(imgPath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
var faces1 = await faceServiceClient.DetectAsync(fStream);
// ObservableCollection<Face> detection_tmp = new ObservableCollection<Face>();
//faceServiceClient.
// Update detected faces on UI
//faces[0].FaceRectangle
foreach (var face in faces1)
{
// detection_tmp.Add(face);
//DetectionFacesCollection.
//_faceListName = _faceListName + "-" + face.FaceId;
faceid_list[i] = face.FaceId;
media_name.Add(face.FaceId.ToString(), imgPath);
i++;
//MainWindow.Log(" faceId", _faceListName);
// _faceListName.
//faceServiceClient.a
//var face_list = await faceServiceClient.AddFaceToFaceListAsync(_faceListName, File.OpenRead(face.ImageFile));
}
return(new Tuple <string, ClientContract.Face[]>(imgPath, faces1));
/*foreach (var face in faces)
* {
*
*
* }*/
}
catch (FaceAPIException ex)
{
// if operation conflict, retry.
if (ex.ErrorCode.Equals("ConcurrentOperationConflict"))
{
imageList.Add(imgPath);
return(null);
}
// if operation cause rate limit exceed, retry.
else if (ex.ErrorCode.Equals("RateLimitExceeded"))
{
imageList.Add(imgPath);
return(null);
}
/*else if (ex.ErrorMessage.Contains("more than 1 face in the image."))
* {
* Interlocked.Increment(ref invalidImageCount);
* }*/
// Here we simply ignore all detection failure in this sample
// You may handle these exceptions by check the Error.Error.Code and Error.Message property for ClientException object
return(new Tuple <string, ClientContract.Face[]>(imgPath, null));
}
}
},
img).Unwrap().ContinueWith((detectTask) =>
{
var res = detectTask?.Result;
if (res?.Item2 == null)
{
return;
}
// Update detected faces on UI
this.Dispatcher.Invoke(
new Action
<ObservableCollection <Face>, string, ClientContract.Face[]>(
UIHelper.UpdateFace),
FacesCollection,
res.Item1,
res.Item2);
}));
processCount++;
if (processCount >= SuggestionCount && !forceContinue)
{
var continueProcess =
System.Windows.Forms.MessageBox.Show(
"The images loaded have reached the recommended count, may take long time if proceed. Would you like to continue to load images?",
"Warning", System.Windows.Forms.MessageBoxButtons.YesNo);
if (continueProcess == System.Windows.Forms.DialogResult.Yes)
{
forceContinue = true;
}
else
{
break;
}
}
if (tasks.Count >= _maxConcurrentProcesses || imageList.IsEmpty)
{
await Task.WhenAll(tasks);
tasks.Clear();
}
}
if (invalidImageCount > 0)
{
MainWindow.Log("Warning: more or less than one face is detected in {0} images, can not add to face list.", invalidImageCount);
}
MainWindow.Log("Response: Success. Total {0} faces are detected.", FacesCollection.Count);
}
else
{
MainWindow.Log("cannot open file");
}
GC.Collect();
//OpenFaceButton.IsEnabled = true;
OpenFaceButton.IsEnabled = true;
OpenCameraButton.IsEnabled = true;
}
public async void getMergedPictureCore(string userPicturePath, string hisPicturePath, WriteableBitmap[] targets, BitmapImage hismanImage)
{
///renderingImag 是一个bitmap类型
var renderingImage = UIHelper.LoadImageAppliedOrientation(userPicturePath);
// Call detection REST API
using (var fStream = File.OpenRead(userPicturePath))
{
var fStream2 = File.OpenRead(hisPicturePath);
string subscriptionKey = "3f7c942ba5344a61b0645fc7f92377db";
string endpoint = "https://westcentralus.api.cognitive.microsoft.com/face/v1.0";
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
ProjectOxford.Face.Contract.Face[] faces = await faceServiceClient.DetectAsync(fStream, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
ProjectOxford.Face.Contract.Face[] faces2 = await faceServiceClient.DetectAsync(fStream2, false, true, new FaceAttributeType[] { FaceAttributeType.Gender, FaceAttributeType.Age, FaceAttributeType.Smile, FaceAttributeType.Glasses, FaceAttributeType.HeadPose, FaceAttributeType.FacialHair, FaceAttributeType.Emotion, FaceAttributeType.Hair, FaceAttributeType.Makeup, FaceAttributeType.Occlusion, FaceAttributeType.Accessories, FaceAttributeType.Noise, FaceAttributeType.Exposure, FaceAttributeType.Blur });
//DetectedResultsInText = string.Format("{0} face(s) has been detected", faces.Length);
if (faces.Length <= 0 || faces.Length <= 0)
{
//return SelectedFile;
return;
}
var face = faces[0];
var face2 = faces2[0];
///face0
int upLeftX = (int)face.FaceLandmarks.EyebrowLeftOuter.X;
int upLeftY = (int)face.FaceLandmarks.EyebrowLeftOuter.Y;
int upLeft2Y = (int)face.FaceLandmarks.EyebrowLeftInner.Y;
int upRight2Y = (int)face.FaceLandmarks.EyebrowRightInner.Y;
int upRightX = (int)face.FaceLandmarks.EyebrowRightOuter.X;
int upRightY = (int)face.FaceLandmarks.EyebrowRightOuter.Y;
int downLeftX = (int)face.FaceLandmarks.MouthLeft.X;
int downLeftY = (int)face.FaceLandmarks.MouthLeft.Y;
int downRightX = (int)face.FaceLandmarks.MouthRight.X;
int downRightY = (int)face.FaceLandmarks.MouthRight.Y;
int downMiddle = (int)face.FaceLandmarks.UnderLipBottom.Y;
///get offset
int faceNoseX = (int)(face.FaceLandmarks.NoseRootLeft.X + face.FaceLandmarks.NoseRootRight.X +
face.FaceLandmarks.NoseLeftAlarOutTip.X + face.FaceLandmarks.NoseRightAlarOutTip.X +
face.FaceLandmarks.NoseTip.X) / 5;
int faceNoseY = (int)(face.FaceLandmarks.NoseRootLeft.Y + face.FaceLandmarks.NoseRootRight.Y +
face.FaceLandmarks.NoseLeftAlarOutTip.Y + face.FaceLandmarks.NoseRightAlarOutTip.Y +
face.FaceLandmarks.NoseTip.Y) / 5;
int face2NoseX = (int)(face2.FaceLandmarks.NoseRootLeft.X + face2.FaceLandmarks.NoseRootRight.X +
face2.FaceLandmarks.NoseLeftAlarOutTip.X + face2.FaceLandmarks.NoseRightAlarOutTip.X +
face2.FaceLandmarks.NoseTip.X) / 5;
int face2NoseY = (int)(face2.FaceLandmarks.NoseRootLeft.Y + face2.FaceLandmarks.NoseRootRight.Y +
face2.FaceLandmarks.NoseLeftAlarOutTip.Y + face2.FaceLandmarks.NoseRightAlarOutTip.Y +
face2.FaceLandmarks.NoseTip.Y) / 5;
int offsetX = face2NoseX - faceNoseX;
int offsetY = face2NoseY - faceNoseY;
int pixelHeight = renderingImage.PixelHeight;
int bitsPerPixel = renderingImage.Format.BitsPerPixel;
int pixelWidth = renderingImage.PixelWidth;
int stride = pixelWidth * bitsPerPixel / 8;
int hismanStride = hismanImage.PixelWidth * hismanImage.Format.BitsPerPixel / 8;
int[] allPixels = new int[hismanStride * hismanImage.PixelHeight];
hismanImage.CopyPixels(allPixels, hismanStride, 0);
targets[0].WritePixels(
new Int32Rect(0, 0, hismanImage.PixelWidth, hismanImage.PixelHeight),
allPixels, hismanStride, 0);
////高度宽度矫正 TODO:
int up = upRightY < upLeftY ? upRightY : upLeftY;
up = up < upRight2Y ? up : upRight2Y;
up = up < upLeft2Y ? up : upLeft2Y;
int down = downRightY > downLeftY ? downRightY + 1 : downLeftY + 1;
down = down > downMiddle ? down : downMiddle;
int height = down - up;
int maxWidth = upRightX - upLeftX;
int minWidth = downRightX - downLeftX;
int halfWidthDiff = (maxWidth - minWidth) / 2;
down += height * 15 / 100;;
up -= height * 10 / 100;
height = down - up;
int[] leftEdge = new int[down - up];
int[] rightEdge = new int[down - up];
for (int i = 0; i < down - up - height / 10; i++)
{
leftEdge[i] = upLeftX + halfWidthDiff * i / height - (int)System.Math.Sqrt(maxWidth - System.Math.Abs((down - up) / 2 - i));
rightEdge[i] = upRightX - halfWidthDiff * i / height + (int)System.Math.Sqrt(maxWidth - System.Math.Abs((down - up) / 2 - i));
}
for (int i = down - up - height / 10; i < down - up; i++)
{
leftEdge[i] = upLeftX + halfWidthDiff * i / height;
rightEdge[i] = upRightX - halfWidthDiff * i / height;
}
List <byte[]> list = new List <byte[]>();
for (int i = up; i < down; i += 1)
{
int choosedWidth = rightEdge[i - up] - leftEdge[i - up];
int lineStride = choosedWidth * bitsPerPixel / 8;
byte[] pixels = new byte[lineStride];
var temp = new Int32Rect(leftEdge[i - up], i, choosedWidth, 1);
renderingImage.CopyPixels(temp, pixels, lineStride, 0);
list.Add(pixels);
}
for (int i = up; i < down; i += 1)
{
int choosedWidth = rightEdge[i - up] - leftEdge[i - up];
int lineStride = choosedWidth * bitsPerPixel / 8;
targets[0].WritePixels(new Int32Rect(leftEdge[i - up] + offsetX, i + offsetY, choosedWidth, 1), list[i - up], lineStride, 0);
}
}
}
/// <summary>
/// Pick image, detect and identify all faces detected
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event arguments</param>
private async void Identify_Click(object sender, RoutedEventArgs e)
{
// Show file picker
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files(*.jpg, *.png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
// User picked one image
// Clear previous detection and identification results
TargetFaces.Clear();
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
SelectedFile = renderingImage;
var sw = Stopwatch.StartNew();
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string subscriptionEndpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, subscriptionEndpoint);
// Call detection REST API
using (var fStream = File.OpenRead(pickedImagePath))
{
try
{
var faces = await faceServiceClient.DetectAsync(fStream);
// Convert detection result into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
TargetFaces.Add(face);
}
MainWindow.Log("Request: Identifying {0} face(s) in group \"{1}\"", faces.Length, GroupName);
// Identify each face
// Call identify REST API, the result contains identified person information
var identifyResult = await faceServiceClient.IdentifyAsync(GroupName, faces.Select(ff => ff.FaceId).ToArray());
for (int idx = 0; idx < faces.Length; idx++)
{
// Update identification result for rendering
var face = TargetFaces[idx];
var res = identifyResult[idx];
if (res.Candidates.Length > 0 && Persons.Any(p => p.PersonId == res.Candidates[0].PersonId.ToString()))
{
face.PersonName = Persons.Where(p => p.PersonId == res.Candidates[0].PersonId.ToString()).First().PersonName;
}
else
{
face.PersonName = "Unknown";
}
}
var outString = new StringBuilder();
foreach (var face in TargetFaces)
{
outString.AppendFormat("Face {0} is identified as {1}. ", face.FaceId, face.PersonName);
}
MainWindow.Log("Response: Success. {0}", outString);
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
}
}
}
GC.Collect();
}
/// <summary>
/// Pick image for detection, get detection result and put detection results into LeftResultCollection
/// </summary>
/// <param name="sender">Event sender</param>
/// <param name="e">Event argument</param>
private async void LeftImagePicker_Click(object sender, RoutedEventArgs e)
{
// Show image picker, show jpg type files only
Microsoft.Win32.OpenFileDialog dlg = new Microsoft.Win32.OpenFileDialog();
dlg.DefaultExt = ".jpg";
dlg.Filter = "Image files(*.jpg, *png, *.bmp, *.gif) | *.jpg; *.png; *.bmp; *.gif";
var result = dlg.ShowDialog();
if (result.HasValue && result.Value)
{
FaceVerifyResult = string.Empty;
// User already picked one image
var pickedImagePath = dlg.FileName;
var renderingImage = UIHelper.LoadImageAppliedOrientation(pickedImagePath);
var imageInfo = UIHelper.GetImageInfoForRendering(renderingImage);
LeftImageDisplay.Source = renderingImage;
// Clear last time detection results
LeftResultCollection.Clear();
FaceVerifyButton.IsEnabled = (LeftResultCollection.Count != 0 && RightResultCollection.Count != 0);
MainWindow.Log("Request: Detecting in {0}", pickedImagePath);
var sw = Stopwatch.StartNew();
// Call detection REST API, detect faces inside the image
using (var fileStream = File.OpenRead(pickedImagePath))
{
try
{
MainWindow mainWindow = Window.GetWindow(this) as MainWindow;
string subscriptionKey = mainWindow._scenariosControl.SubscriptionKey;
string endpoint = mainWindow._scenariosControl.SubscriptionEndpoint;
var faceServiceClient = new FaceServiceClient(subscriptionKey, endpoint);
var faces = await faceServiceClient.DetectAsync(fileStream);
// Handle REST API calling error
if (faces == null)
{
return;
}
MainWindow.Log("Response: Success. Detected {0} face(s) in {1}", faces.Length, pickedImagePath);
// Convert detection results into UI binding object for rendering
foreach (var face in UIHelper.CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
// Detected faces are hosted in result container, will be used in the verification later
LeftResultCollection.Add(face);
}
FaceVerifyButton.IsEnabled = (LeftResultCollection.Count != 0 && RightResultCollection.Count != 0);
}
catch (FaceAPIException ex)
{
MainWindow.Log("Response: {0}. {1}", ex.ErrorCode, ex.ErrorMessage);
return;
}
}
}
GC.Collect();
}
