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();
}
private (Image, double) FindMostSimilarImage(IList <double> embedding)
{
if (!this.db.Images.Any())
{
return(null, double.MaxValue);
}
var mostSimilar = this.db
.Images
.Include(i => i.Embeddings)
.ThenInclude(e => e.Values)
.Include(i => i.Persons)
.ThenInclude(pi => pi.Person)
.ToList()
.OrderBy(i =>
i.Embeddings.Max(e => this.EucledianDistance(embedding, e)))
.First();
return(mostSimilar, mostSimilar.Embeddings.Max(e => this.EucledianDistance(embedding, e)));
}