private async void RecogNumberFromInk()
{
// 从文件加载模型
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Assets/mnist.onnx"));
var model = await mnistModel.CreateFromStreamAsync(modelFile);
// 组织输入
var inputArray = await GetInputDataFromInk();
var inputTensor = TensorFloat.CreateFromArray(new List <long> {
784
}, inputArray);
var modelInput = new mnistInput {
port = inputTensor
};
// 推理
var result = await model.EvaluateAsync(modelInput);
// 得到每个数字的得分
var scoreList = result.dense3port.GetAsVectorView().ToList();
// 从输出中取出得分最高的
var max = scoreList.IndexOf(scoreList.Max());
// 显示在控件中
lbResult.Text = max.ToString();
}
public async Task <mnistOutput> EvaluateAsync(mnistInput input)
{
binding.Bind("fc1x", input.fc1x);
var result = await session.EvaluateAsync(binding, "0");
var output = new mnistOutput();
output.activation3y = result.Outputs["activation3y"] as TensorFloat;
return(output);
}
public async Task <mnistOutput> EvaluateAsync(mnistInput input)
{
binding.Bind("port", input.port);
var result = await session.EvaluateAsync(binding, "0");
var output = new mnistOutput();
output.dense3port = result.Outputs["dense3port"] as TensorFloat;
return(output);
}