private async Task StartPreviewAsync()
{
// Prevent the device from sleeping while the preview is running
_displayRequest.RequestActive();
// Setup preview source in UI and mirror if required
VideoCapture.Source = _mediaCapture;
VideoCapture.FlowDirection = _mirroringPreview ? FlowDirection.RightToLeft : FlowDirection.LeftToRight;
this.VideoProperties = this._mediaCapture.VideoDeviceController.GetMediaStreamProperties(MediaStreamType.VideoPreview) as VideoEncodingProperties;
// Start preview
await _mediaCapture.StartPreviewAsync();
_isPreviewing = true;
if (_isPreviewing)
{
await SetPreviewRotationAsync();
}
_timer = new DispatcherTimer
{
Interval = TimeSpan.FromSeconds(0.5)
};
_timer.Tick += async(sender, o) =>
{
if (_mediaCapture == null)
{
return;
}
const BitmapPixelFormat inputPixelFormat = BitmapPixelFormat.Bgra8;
var previewFrame = new Windows.Media.VideoFrame(inputPixelFormat, CameraResolutionWidth, CameraResolutionHeight);
await _mediaCapture.GetPreviewFrameAsync(previewFrame);
var imageBytes = await GetPixelBytesFromSoftwareBitmapAsync(previewFrame.SoftwareBitmap);
NewFrameCaptured?.Invoke(this, new NewFrameEventArgs(new Models.VideoFrame()
{
ImageBytes = imageBytes,
Timestamp = DateTime.Now
}));
previewFrame.Dispose();
};
_timer.Start();
}
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");
}
}
