public async Task <sthv2_tpnOutput> EvaluateAsync(sthv2_tpnInput input)
{
binding.Bind("input", input.input);
var result = await session.EvaluateAsync(binding, "0");
var output = new sthv2_tpnOutput();
output.output = result.Outputs["output"] as TensorFloat;
return(output);
}
private async void CurrentVideoFrame(ThreadPoolTimer timer)
{
//複数スレッドでの同時実行を抑制
if (!semaphore.Wait(0))
{
return;
}
try
{
// カメラから256x256の画像を取得
VideoFrame previewFrame = new VideoFrame(BitmapPixelFormat.Bgra8, 256, 256);
await this.mediaCapture.GetPreviewFrameAsync(previewFrame);
if (frameBuffer.Count >= target_length)
{
frameBuffer.RemoveAt(0); // 先頭をpop
}
frameBuffer.Add(previewFrame); // 末尾に追加
frame_refresh_count += 1;
if (ModelGen != null && previewFrame != null && frame_refresh_count == target_length)
{
frame_refresh_count = 0;
ModelInput.input = CustomTensorize(frameBuffer, mean, std, true);
// Evaluate the model
ModelOutput = await ModelGen.EvaluateAsync(ModelInput);
// Convert output to datatype
var outtensor = ModelOutput.output;
IReadOnlyList <float> logits = outtensor.GetAsVectorView();
var exp_logits = logits.Select(l => Math.Exp(l));
var exp_logits_sum = exp_logits.Sum();
var probs = exp_logits.Select(el => el / exp_logits_sum);
////IReadOnlyList<float> vectorImage = ModelOutput.Plus214_Output_0.GetAsVectorView();
var prob_list = probs.ToList();
// Query to check for highest probability digit
var sorted_logt = prob_list.OrderBy(elm => - 1 * elm).ToList();
// Display the results on UI Thread.
var ignored = this.Dispatcher.RunAsync(Windows.UI.Core.CoreDispatcherPriority.Normal, () =>
{
int topk = 5;
string result = "";
for (int k = 0; k < topk; k++)
{
var prob = sorted_logt[k];
string label = labelList[prob_list.IndexOf(prob)];
result = result + "\n" + "Prob: " + prob.ToString("0.00") + ", Label: " + label;
}
//予測結果を表示
this.msgTbk.Text = result;
});
}
}
catch (Exception ex)
{
Debug.WriteLine(ex.Message);
}
finally
{
semaphore.Release();
}
}
