public static async Task <ResNet50Model> CreateResNet50Model(StorageFile file)
{
LearningModelPreview learningModel = await LearningModelPreview.LoadModelFromStorageFileAsync(file);
ResNet50Model model = new ResNet50Model();
model.learningModel = learningModel;
return(model);
}
private async Task EvaluteImageAsync(VideoFrame videoFrame)
{
try
{
var startTime = DateTime.Now;
if (model == null)
{
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri("ms-appx:///Model/Resnet50.onnx"));
if (modelFile != null)
{
model = new ResNet50Model();
await MLHelper.CreateModelAsync(modelFile, model);
}
}
var input = new ResNet50ModelInput()
{
image = videoFrame
};
var res = await model.EvaluateAsync(input) as ResNet50ModelOutput;
if (res != null)
{
var results = new List <LabelResult>();
foreach (var kv in res.classLabelProbs)
{
results.Add(new LabelResult
{
Label = kv.Key,
Result = (float)Math.Round(kv.Value * 100, 2)
});
}
results.Sort((p1, p2) =>
{
return(p2.Result.CompareTo(p1.Result));
});
await Dispatcher.RunAsync(Windows.UI.Core.CoreDispatcherPriority.High, () =>
{
previewControl.EvalutionTime = (DateTime.Now - startTime).TotalSeconds.ToString();
outputText.Text = res.classLabel.FirstOrDefault();
resultList.ItemsSource = results;
});
}
}
catch (Exception ex)
{
await AlertHelper.ShowMessageAsync(ex.ToString());
}
}