static void FaceDetectorLightFPSTest(SessionOptions options, Bitmap bitmap)
{
int tic, toc, time;
float average;
var faceDetectorLight = new FaceDetectorLight(options);
Console.WriteLine($"FPS test for [{faceDetectorLight}]");
Console.WriteLine($"Initializing GPU device [{gpuId}]");
tic = Environment.TickCount;
_ = faceDetectorLight.Forward(bitmap);
toc = Environment.TickCount - tic;
Console.WriteLine($"Finished in [{toc}] mls.");
time = 0;
Console.WriteLine($"Running FPS test for [{iterations}] iterations");
for (int i = 0; i < iterations; i++)
{
tic = Environment.TickCount;
_ = faceDetectorLight.Forward(bitmap);
toc = Environment.TickCount - tic;
time += toc;
}
average = time / (float)iterations;
Console.WriteLine($"FPS --> [{oneSecond / average}]\n");
Console.WriteLine("Done.");
Console.ReadKey();
}
static void Main()
{
Console.WriteLine("FaceONNX: Race and age classification");
var files = Directory.GetFiles(@"..\..\..\images");
var path = @"..\..\..\results";
Directory.CreateDirectory(path);
_faceDetectorLight = new FaceDetectorLight();
_faceLandmarksExtractor = new FaceLandmarksExtractor();
_faceRaceClassifier = new FaceRaceClassifier();
_faceAgeClassifier = new FaceAgeClassifier();
var painter = new Painter()
{
PointPen = new Pen(Color.Yellow, 4),
Transparency = 0,
TextFont = new Font("Arial", 24)
};
Console.WriteLine($"Processing {files.Length} images");
foreach (var file in files)
{
using var bitmap = new Bitmap(file);
var filename = Path.GetFileName(file);
var faces = _faceDetectorLight.Forward(bitmap);
int i = 1;
Console.WriteLine($"Image: [{filename}] --> detected [{faces.Length}] faces");
foreach (var face in faces)
{
Console.Write($"\t[Face #{i++}]: ");
var labels = GetRaceAndAge(bitmap, face);
var paintData = new PaintData()
{
Rectangle = face,
Labels = labels
};
painter.Draw(bitmap, paintData);
}
bitmap.Save(Path.Combine(path, filename));
}
_faceDetectorLight.Dispose();
_faceLandmarksExtractor.Dispose();
_faceRaceClassifier.Dispose();
_faceAgeClassifier.Dispose();
Console.WriteLine("Done.");
Console.ReadKey();
}
static void Main()
{
Console.WriteLine("FaceONNX: Face embeddings classification");
var fits = Directory.GetFiles(@"..\..\..\images\fit");
_faceDetectorLight = new FaceDetectorLight();
_faceLandmarksExtractor = new FaceLandmarksExtractor();
_faceEmbedder = new FaceEmbedder();
var embeddings = new Embeddings();
foreach (var fit in fits)
{
using var bitmap = new Bitmap(fit);
var embedding = GetEmbedding(bitmap);
var name = Path.GetFileNameWithoutExtension(fit);
embeddings.Add(embedding, name);
}
Console.WriteLine($"Embeddings count: {embeddings.Count}");
var scores = Directory.GetFiles(@"..\..\..\images\score");
Console.WriteLine($"Processing {scores.Length} images");
foreach (var score in scores)
{
using var bitmap = new Bitmap(score);
var embedding = GetEmbedding(bitmap);
var proto = embeddings.FromSimilarity(embedding);
var label = proto.Item1;
var similarity = proto.Item2;
var filename = Path.GetFileName(score);
Console.WriteLine($"Image: [{filename}] --> classified as [{label}] with similarity [{similarity}]");
}
_faceDetectorLight.Dispose();
_faceLandmarksExtractor.Dispose();
_faceEmbedder.Dispose();
Console.WriteLine("Done.");
Console.ReadKey();
}
static void Main()
{
Console.WriteLine("FaceONNX: Emotion and beauty estimation");
var files = Directory.GetFiles(@"..\..\..\images");
var path = @"..\..\..\results";
Directory.CreateDirectory(path);
_faceDetectorLight = new FaceDetectorLight();
_faceLandmarksExtractor = new FaceLandmarksExtractor();
_faceEmotionClassifier = new FaceEmotionClassifier();
_faceBautyClassifier = new FaceBautyClassifier();
Console.WriteLine($"Processing {files.Length} images");
foreach (var file in files)
{
using var bitmap = new Bitmap(file);
var filename = Path.GetFileName(file);
var faces = _faceDetectorLight.Forward(bitmap);
int i = 1;
Console.WriteLine($"Image: [{filename}] --> detected [{faces.Length}] faces");
foreach (var face in faces)
{
Console.Write($"\t[Face #{i++}]: ");
var labels = GetEmotionAndBeauty(bitmap, face);
}
}
_faceDetectorLight.Dispose();
_faceLandmarksExtractor.Dispose();
_faceEmotionClassifier.Dispose();
_faceBautyClassifier.Dispose();
Console.WriteLine("Done.");
Console.ReadKey();
}
static void Main()
{
Console.WriteLine("FaceONNX: Gender classification");
var files = Directory.GetFiles(@"..\..\..\images");
using var faceDetectorLight = new FaceDetectorLight();
using var faceGenderClassifier = new FaceGenderClassifier();
var labels = FaceGenderClassifier.Labels;
foreach (var label in labels)
{
Directory.CreateDirectory(label);
}
Console.WriteLine($"Processing {files.Length} images");
foreach (var file in files)
{
using var bitmap = new Bitmap(file);
var filename = Path.GetFileName(file);
var faces = faceDetectorLight.Forward(bitmap);
int i = 1;
Console.WriteLine($"Image: [{filename}] --> detected [{faces.Length}] faces");
foreach (var face in faces)
{
Console.Write($"\t[Face #{i++}]: ");
var output = faceGenderClassifier.Forward(bitmap);
var gender = Vector.Argmax(output);
var label = labels[gender];
Console.WriteLine($"--> classified as [{label}] gender with probability [{output.Max()}]");
}
}
Console.WriteLine("Done.");
Console.ReadKey();
}
static void Main()
{
Console.WriteLine("FaceONNX: Face detection");
var files = Directory.GetFiles(@"..\..\..\images");
var path = @"..\..\..\results";
Directory.CreateDirectory(path);
using var faceDetectorLight = new FaceDetectorLight(0.95f, 0.25f);
var painter = new Painter()
{
BoxPen = new Pen(Color.Yellow, 4),
Transparency = 0,
};
Console.WriteLine($"Processing {files.Length} images");
foreach (var file in files)
{
using var bitmap = new Bitmap(file);
var output = faceDetectorLight.Forward(bitmap);
foreach (var rectangle in output)
{
var paintData = new PaintData()
{
Rectangle = rectangle,
Title = string.Empty
};
painter.Draw(bitmap, paintData);
}
var filename = Path.GetFileName(file);
bitmap.Save(Path.Combine(path, filename));
Console.WriteLine($"Image: [{filename}] --> detected [{output.Length}] faces");
}
Console.WriteLine("Done.");
Console.ReadKey();
}
