private Face CalculateTextRectangleForRendering(Face face, int maxSize, Tuple <int, int> imageInfo, int left, int top, int height, int width)
{
var imageWidth = imageInfo.Item1;
var imageHeight = imageInfo.Item2;
float ratio = (float)imageWidth / imageHeight;
int uiWidth;
int uiHeight;
if (ratio > 1.0)
{
uiWidth = maxSize;
uiHeight = (int)(maxSize / ratio);
}
else
{
uiHeight = maxSize;
uiWidth = (int)(ratio * uiHeight);
}
int uiXOffset = (maxSize - uiWidth) / 2;
int uiYOffset = (maxSize - uiHeight) / 2;
float scale = (float)uiWidth / imageWidth;
face.Left = (int)((left * scale) + uiXOffset);
face.Top = (int)((top * scale) + uiYOffset);
face.Height = (int)(height * scale);
face.Width = (int)(width * scale);
return(face);
}
public ObservableCollection <Face> OcrGetFramesRectanglesForRecognizedText(OcrResults ocrResults, string selectedFile)
{
var frames = new ObservableCollection <Face>();
var imageInfo = GetImageInfoForRendering(selectedFile);
foreach (var region in ocrResults.Regions)
{
var face = new Face();
face = CalculateTextRectangleForRendering(face, MaxImageSize, imageInfo, region.Rectangle.Left,
region.Rectangle.Top, region.Rectangle.Height, region.Rectangle.Width);
face.ScoredEmotion = $"lines {region.Lines.Length}";
frames.Add(face);
}
return(frames);
}
public async Task <Tuple <ObservableCollection <Face>, ObservableCollection <Face> > > StartFaceDetection(string selectedFile, bool analyzeEmotion)
{
var detectedFaces = new ObservableCollection <Face>();
var facesRect = new ObservableCollection <Face>();
Debug.WriteLine("Request: Detecting {0}", selectedFile);
using (var fileStreamImage = File.OpenRead(selectedFile))
{
try
{
var client = new FaceServiceClient(_subscriptionKeyFace);
var faces = await client.DetectAsync(fileStreamImage, false, true, true);
Debug.WriteLine("Response: Success. Detected {0} face(s) in {1}", faces.Length, selectedFile);
var imageInfo = GetImageInfoForRendering(selectedFile);
Debug.WriteLine("{0} face(s) has been detected", faces.Length);
foreach (var face in faces)
{
var detectedFace = new Face()
{
ImagePath = selectedFile,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId,
Gender = face.Attributes.Gender,
Age = $"{face.Attributes.Age:#} years old",
};
detectedFaces.Add(detectedFace);
}
// Convert detection result into UI binding object for rendering
foreach (var face in CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
facesRect.Add(face);
}
// update emotions
if (analyzeEmotion)
{
detectedFaces = await UpdateEmotions(selectedFile, detectedFaces);
foreach (var faceRect in facesRect)
{
foreach (var detectedFace in detectedFaces.Where(detectedFace => faceRect.FaceId == detectedFace.FaceId))
{
faceRect.Scores = detectedFace.Scores;
}
}
}
}
catch (Exception ex)
{
Debug.WriteLine(ex.ToString());
}
var returnData = new Tuple <ObservableCollection <Face>, ObservableCollection <Face> >(detectedFaces, facesRect);
return(returnData);
}
}
public ObservableCollection<Face> OcrGetFramesRectanglesForRecognizedText(OcrResults ocrResults, string selectedFile)
{
var frames = new ObservableCollection<Face>();
var imageInfo = GetImageInfoForRendering(selectedFile);
foreach (var region in ocrResults.Regions)
{
var face = new Face();
face = CalculateTextRectangleForRendering(face, MaxImageSize, imageInfo, region.Rectangle.Left,
region.Rectangle.Top, region.Rectangle.Height, region.Rectangle.Width);
face.ScoredEmotion = $"lines {region.Lines.Length}";
frames.Add(face);
}
return frames;
}
public async Task<Tuple<ObservableCollection<Face>, ObservableCollection<Face>>> StartFaceDetection(string selectedFile, bool analyzeEmotion)
{
var detectedFaces = new ObservableCollection<Face>();
var facesRect = new ObservableCollection<Face>();
Debug.WriteLine("Request: Detecting {0}", selectedFile);
using (var fileStreamImage = File.OpenRead(selectedFile))
{
try
{
var client = new FaceServiceClient(_subscriptionKeyFace);
var faces = await client.DetectAsync(fileStreamImage, false, true, true);
Debug.WriteLine("Response: Success. Detected {0} face(s) in {1}", faces.Length, selectedFile);
var imageInfo = GetImageInfoForRendering(selectedFile);
Debug.WriteLine("{0} face(s) has been detected", faces.Length);
foreach (var face in faces)
{
var detectedFace = new Face()
{
ImagePath = selectedFile,
Left = face.FaceRectangle.Left,
Top = face.FaceRectangle.Top,
Width = face.FaceRectangle.Width,
Height = face.FaceRectangle.Height,
FaceId = face.FaceId,
Gender = face.Attributes.Gender,
Age = $"{face.Attributes.Age:#} years old",
};
detectedFaces.Add(detectedFace);
}
// Convert detection result into UI binding object for rendering
foreach (var face in CalculateFaceRectangleForRendering(faces, MaxImageSize, imageInfo))
{
facesRect.Add(face);
}
// update emotions
if (analyzeEmotion)
{
detectedFaces = await UpdateEmotions(selectedFile, detectedFaces);
foreach (var faceRect in facesRect)
{
foreach (var detectedFace in detectedFaces.Where(detectedFace => faceRect.FaceId == detectedFace.FaceId))
{
faceRect.Scores = detectedFace.Scores;
}
}
}
}
catch (Exception ex)
{
Debug.WriteLine(ex.ToString());
}
var returnData = new Tuple<ObservableCollection<Face>, ObservableCollection<Face>>(detectedFaces, facesRect);
return returnData;
}
}
private Face CalculateTextRectangleForRendering(Face face, int maxSize, Tuple<int, int> imageInfo, int left, int top, int height, int width)
{
var imageWidth = imageInfo.Item1;
var imageHeight = imageInfo.Item2;
float ratio = (float)imageWidth / imageHeight;
int uiWidth;
int uiHeight;
if (ratio > 1.0)
{
uiWidth = maxSize;
uiHeight = (int)(maxSize / ratio);
}
else
{
uiHeight = maxSize;
uiWidth = (int)(ratio * uiHeight);
}
int uiXOffset = (maxSize - uiWidth) / 2;
int uiYOffset = (maxSize - uiHeight) / 2;
float scale = (float)uiWidth / imageWidth;
face.Left = (int) ((left*scale) + uiXOffset);
face.Top = (int) ((top*scale) + uiYOffset);
face.Height = (int) (height*scale);
face.Width = (int) (width*scale);
return face;
}
