Ejemplo n.º 1
0
        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));
        }