public void FacialRecognitionProcessorStillReturnsInfoIfNoTrainingImages()
{
var processor = new FacialRecognitionProcessor();
var recoResult = RunFacialRecognitionProcessor(processor);
Assert.AreEqual(1, recoResult.Faces.Count());
var face = recoResult.Faces.First();
Assert.AreEqual(-1, face.EigenDistance);
Assert.IsNull(face.Key);
Assert.IsNotNull(face.GrayFace);
}
public void FacialRecognitionProcessorThrowsExceptionIfOnlyOneTrainingImage()
{
var faces = new List<TargetFace>();
var trainingImage = Directory.GetFiles(".", "train*.*").First();
faces.Add(new TargetFace
{
Key = trainingImage,
Image = new Bitmap(trainingImage)
});
var processor = new FacialRecognitionProcessor(faces);
RunFacialRecognitionProcessor(processor);
}
private RecognitionResult RunFacialRecognitionProcessor(FacialRecognitionProcessor processor)
{
var testFrame = new Bitmap("testframe.png");
var recoResult = new RecognitionResult
{
OriginalBitmap = testFrame,
ProcessedBitmap = (Bitmap)testFrame.Clone()
};
var trackingResults = Newtonsoft.Json.JsonConvert.DeserializeObject<TrackingResults>(File.ReadAllText("testframe.json"));
var sw = new Stopwatch();
sw.Start();
processor.Process(recoResult, trackingResults);
sw.Stop();
return recoResult;
}
public void FacialRecognitionProcessorSucessfullyRecognizesMe()
{
var faces = new List<TargetFace>();
foreach (var trainingImage in Directory.GetFiles(".", "train*.*"))
{
faces.Add(new TargetFace
{
Key = trainingImage,
Image = new Bitmap(trainingImage)
});
}
var processor = new FacialRecognitionProcessor(faces);
var recoResult = RunFacialRecognitionProcessor(processor);
Assert.AreEqual(1, recoResult.Faces.Count());
var face = recoResult.Faces.First();
Assert.AreEqual(789.8254, Math.Round(face.EigenDistance, 4));
Assert.AreEqual(@".\train_mike_2.png", face.Key);
Assert.IsNotNull(face.GrayFace);
}