private async void Analyzer()
{
// Use default parameter settings.
this.analyzer = MLAnalyzerFactory.Instance.FaceAnalyzer;
// Create an MLFrame by using the bitmap. Recommended image size: large than 320*320, less than 1920*1920.
MLFrame frame = MLFrame.FromBitmap(this.mBitmap);
// Call the AnalyseFrameAsync method to perform face detection
System.Threading.Tasks.Task <IList <MLFace> > faceAnalyseTask = this.analyzer.AnalyseFrameAsync(frame);
try
{
await faceAnalyseTask;
if (faceAnalyseTask.IsCompleted && faceAnalyseTask.Result != null)
{
IList <MLFace> faces = faceAnalyseTask.Result;
if (faces.Count > 0)
{
DisplaySuccess(faces.ElementAt(0));
}
}
else
{
DisplayFailure();
}
}
catch (Exception e)
{
//Operation failed.
DisplayFailure();
}
}
/// <summary>
/// Create Face Analyzer
/// </summary>
private void CreateFaceAnalyzer()
{
// Create a face analyzer. You can create an analyzer using the provided customized face detection parameter
// MLFaceAnalyzerSetting
MLFaceAnalyzerSetting setting =
new MLFaceAnalyzerSetting.Factory()
.SetFeatureType(MLFaceAnalyzerSetting.TypeFeatures)
.SetKeyPointType(MLFaceAnalyzerSetting.TypeKeypoints)
.SetMinFaceProportion(0.2f)
.AllowTracing()
.Create();
this.analyzer = MLAnalyzerFactory.Instance.GetFaceAnalyzer(setting);
this.analyzer.SetTransactor(new FaceAnalyzerTransactor(this.mOverlay));
}
