public async Task <IEnumerable <ImageClassification> > Evalute(CoreMlInput source)
{
var tcs = new TaskCompletionSource <IEnumerable <ImageClassification> >();
var request = new VNCoreMLRequest(_model, (response, e) =>
{
if (e != null)
{
tcs.SetException(new NSErrorException(e));
}
else
{
var results = response.GetResults <VNClassificationObservation>();
tcs.SetResult(results.Select(r => new ImageClassification(r.Identifier, r.Confidence)).ToList());
}
});
// Pre-process image (scale down)
var buffer = source.Image.ToCVPixelBuffer(_targetImageSize);
var requestHandler = new VNImageRequestHandler(buffer, new NSDictionary());
requestHandler.Perform(new[] { request }, out NSError error);
var classifications = await tcs.Task;
if (error != null)
{
throw new NSErrorException(error);
}
return(classifications);
}
public async Task <IReadOnlyList <ImageClassification> > ClassifyImage(byte[] image)
{
if (!IsInitialized)
{
await Init();
}
try
{
var input = CoreMlInput.CreateFrom(image);
var results = await coreMlModel.Evalute(input);
return(results
.Where(p => p.Probability > 0.85)
.ToList());
}
catch (Exception ex)
{
throw new ImageClassifierException("Failed to classify image - check the inner exception for more details", ex);
}
}
