void HandleClassifications(VNRequest request, NSError error)
{
DispatchQueue.MainQueue.DispatchAsync(() =>
{
var observations = request.GetResults <VNClassificationObservation>();
if (observations == null)
{
Debug.WriteLine("Error: no results");
_machineLearningTask.TrySetResult(null);
return;
}
var best = observations[0];
if (best == null)
{
Debug.WriteLine("Error: no observations");
_machineLearningTask.TrySetResult(null);
return;
}
var result = new MachineLearningResult();
foreach (var observation in observations)
{
result.Observations.Add(new Observation {
Confidence = observation.Confidence, Identifier = observation.Identifier
});
}
_machineLearningTask.TrySetResult(result);
});
}
public Task <MachineLearningResult> AnalizeImageAsync(string mlModel, Stream imageStream)
{
if (_machineLearningTask != null)
{
_machineLearningTask.TrySetCanceled();
}
_machineLearningTask = new TaskCompletionSource <MachineLearningResult>();
Task.Run(() =>
{
try
{
mlModel = mlModel.Replace(".pb", "");
var imageClassifier = new ImageClassifier(mlModel);
BitmapFactory.Options options = new BitmapFactory.Options();
options.InMutable = true;
var mlResult = new MachineLearningResult();
using (var bitmap = BitmapFactory.DecodeStream(imageStream, null, options))
{
var result = imageClassifier.RecognizeImage(bitmap);
if (result != null)
{
foreach (var item in result)
{
mlResult.Observations.Add(new Observation {
Confidence = item.Item1, Identifier = item.Item2
});
}
}
bitmap.Recycle();
}
_machineLearningTask.TrySetResult(mlResult);
}
catch (Exception error)
{
Debug.WriteLine(error);
_machineLearningTask.TrySetResult(null);
}
});
return(_machineLearningTask.Task);
}
