using System; namespace ConsoleApp17 { class Program { static void PerformInference(Windows.Media.VideoFrame frame) { Console.WriteLine("Load squeezenet.onnx."); using (var model = Microsoft.AI.MachineLearning.LearningModel.LoadFromFilePath("squeezenet.onnx")) { Console.WriteLine("Create LearningModelSession."); using (var session = new Microsoft.AI.MachineLearning.LearningModelSession(model)) { Console.WriteLine("Create LearningModelBinding."); var binding = new Microsoft.AI.MachineLearning.LearningModelBinding(session); Console.WriteLine("Bind data_0."); binding.Bind("data_0", frame); Console.WriteLine("Evaluate."); var results = session.Evaluate(binding, ""); } Console.WriteLine("Success!\n"); } } static void Main(string[] args) { Console.WriteLine("Load kitten_224.png as StorageFile."); var name = AppDomain.CurrentDomain.BaseDirectory + "kitten_224.png"; var getFileFromPathTask = Windows.Storage.StorageFile.GetFileFromPathAsync(name); getFileFromPathTask.AsTask() .ContinueWith( (task) => { var image = task.Result; Console.WriteLine("Load StorageFile into Stream."); var stream_task = image.OpenReadAsync(); return stream_task.AsTask().Result; }) .ContinueWith( (task) => { using (var stream = task.Result) { Console.WriteLine("Create SoftwareBitmap from decoded Stream."); var decoder_task = Windows.Graphics.Imaging.BitmapDecoder.CreateAsync(stream); return decoder_task.AsTask().Result; } }) .ContinueWith( (task) => { var decoder = task.Result; var software_bitmap_task = decoder.GetSoftwareBitmapAsync(); return software_bitmap_task.AsTask().Result; }) .ContinueWith( (task) => { using (var software_bitmap = task.Result) { Console.WriteLine("Create VideoFrame."); var frame = Windows.Media.VideoFrame.CreateWithSoftwareBitmap(software_bitmap); PerformInference(frame); } }) .Wait(); } } }