static float[] GetEmbedding(Bitmap image)
{
var faces = _faceDetectorLight.Forward(image);
using var cropped = Imaging.Crop(image, faces.First());
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
return(_faceEmbedder.Forward(aligned));
}
static string[] GetEmotionAndBeauty(Bitmap image, Rectangle face)
{
using var cropped = Imaging.Crop(image, face);
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
var emotion = _faceEmotionClassifier.Forward(aligned);
var emotionLabel = FaceEmotionClassifier.Labels[emotion.Argmax()];
var beauty = _faceBautyClassifier.Forward(aligned);
var beautyLabel = $"{Math.Round(2 * beauty.Max(), 1)}/10.0";
Console.WriteLine($"--> classified as [{emotionLabel}] emotion and [{beautyLabel}] beauty");
return(new string[] { emotionLabel, beautyLabel });
}
static string[] GetRaceAndAge(Bitmap image, Rectangle face)
{
using var cropped = Imaging.Crop(image, face);
var points = _faceLandmarksExtractor.Forward(cropped);
using var aligned = FaceLandmarksExtractor.Align(cropped, points);
var race = _faceRaceClassifier.Forward(aligned);
var raceLabel = FaceRaceClassifier.Labels[race.Argmax()];
var age = _faceAgeClassifier.Forward(aligned);
var ageLabel = FaceAgeClassifier.Labels[age.Argmax()];
Console.WriteLine($"--> classified as [{raceLabel}] race and [{ageLabel}] age");
return(new string[] { raceLabel, ageLabel });
}