public async Task <BearModelOutput> EvaluateAsync(BearModelInput input)
{
binding.Bind("data", input.data);
var result = await session.EvaluateAsync(binding, "0");
var output = new BearModelOutput();
output.classLabel = result.Outputs["classLabel"] as TensorString;
output.loss = result.Outputs["loss"] as IList <Dictionary <string, float> >;
return(output);
}
private async void RecognizeBear()
{
// 加载模型
StorageFile modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Assets/BearModel.onnx"));
BearModelModel model = await BearModelModel.CreateFromStreamAsync(modelFile);
// 构建输入数据
BearModelInput bearModelInput = await GetInputData();
// 推理
BearModelOutput output = await model.EvaluateAsync(bearModelInput);
tbBearType.Text = output.classLabel.GetAsVectorView().ToList().FirstOrDefault();
}
private async Task <BearModelInput> GetInputData()
{
// 将图片控件重绘到图片上
RenderTargetBitmap rtb = new RenderTargetBitmap();
await rtb.RenderAsync(imgBear);
// 取得所有像素值
var pixelBuffer = await rtb.GetPixelsAsync();
// 构造模型需要的输入格式
SoftwareBitmap softwareBitmap = SoftwareBitmap.CreateCopyFromBuffer(pixelBuffer, BitmapPixelFormat.Bgra8, rtb.PixelWidth, rtb.PixelHeight);
VideoFrame videoFrame = VideoFrame.CreateWithSoftwareBitmap(softwareBitmap);
ImageFeatureValue imageFeatureValue = ImageFeatureValue.CreateFromVideoFrame(videoFrame);
BearModelInput bearModelInput = new BearModelInput();
bearModelInput.data = imageFeatureValue;
return(bearModelInput);
}