void MakePrediction(UIImage image)
{
//
// Get an input from the image
//
IMLFeatureProvider input = CreateInput(image);
//
// Predict what's in the image
//
var output = model.GetPrediction(input, out var error);
if (error != null)
{
Console.WriteLine($"Error predicting: {error}");
return;
}
var classLabel = output.GetFeatureValue("classLabel").StringValue;
//
// Display everything
//
Console.WriteLine($"Recognized:");
foreach (NSString n in output.FeatureNames)
{
var value = output.GetFeatureValue(n);
Console.WriteLine($" {n} == {value}");
}
var message = $"{classLabel.ToUpperInvariant ()} with probability {output.GetFeatureValue ("classLabelProbs").DictionaryValue[classLabel]}";
Console.WriteLine(message);
BeginInvokeOnMainThread(() => {
var alert = UIAlertController.Create(message, "I hope it's right!", UIAlertControllerStyle.Alert);
alert.AddAction(UIAlertAction.Create("OK", UIAlertActionStyle.Default, (obj) => {
DismissViewController(true, null);
}));
PresentViewController(alert, true, null);
});
}
public double UpdateEngagement(FaceAnchorReading f)
{
blink.Push((f.FacialExpressions["EyeBlinkLeft"].Value + f.FacialExpressions["EyeBlinkRight"].Value) / 2);
smile.Push((f.FacialExpressions["MouthSmileLeft"].Value + f.FacialExpressions["MouthSmileRight"].Value) / 2);
frown.Push((f.FacialExpressions["MouthFrownLeft"].Value + f.FacialExpressions["MouthFrownRight"].Value) / 2);
squint.Push((f.FacialExpressions["EyeSquintLeft"].Value + f.FacialExpressions["EyeSquintRight"].Value) / 2);
gazeIn.Push((f.FacialExpressions["EyeLookInLeft"].Value + f.FacialExpressions["EyeLookInRight"].Value) / 2);
gazeOut.Push((f.FacialExpressions["EyeLookOutLeft"].Value + f.FacialExpressions["EyeLookOutRight"].Value) / 2);
if (previousReading == null)
{
headSpeed.Push(0);
eyeDwell.Push(0);
headTilt.Push(0);
}
else
{
var deltaTime = f.ReadingTimestamp.Subtract(previousReading.ReadingTimestamp);
var deltaHead = VectorMagnitude(VectorDifference(previousReading.LookAtPointTransform, f.LookAtPointTransform));
headSpeed.Push((float)(deltaHead / deltaTime.TotalMilliseconds));
var leftEyeDisplacement = CoordinateDisplacement(f.LeftEyeTransform);
var rightEyeDisplacement = CoordinateDisplacement(f.RightEyeTransform);
var eyeDisplacement = Math.Abs(leftEyeDisplacement[0] + rightEyeDisplacement[0]) / 2;
eyeDwell.Push((float)(eyeDisplacement > 0 ? 1 / eyeDisplacement : 0));
headTilt.Push((float)(Math.Abs(leftEyeDisplacement[1] + rightEyeDisplacement[1]) / 2));
}
previousReading = f;
var modelInput = new CoreMLPathwayInput
{
PPI = PPI,
Blink = blink.Mean,
Smile = smile.Mean,
Frown = frown.Mean,
Squint = squint.Mean,
GazeIn = gazeIn.Mean,
GazeOut = gazeOut.Mean,
HeadSpeed = headSpeed.Mean,
EyeDwell = eyeDwell.Mean,
HeadTilt = headTilt.Mean
};
IMLFeatureProvider predictionOut = model.GetPrediction(modelInput, out _);
var targetFeatureValue = predictionOut.GetFeatureValue("target");
var prediction = targetFeatureValue.Int64Value;
var classProbabilityFeatureValue = predictionOut.GetFeatureValue("classProbability");
var probabilityx = classProbabilityFeatureValue.DictionaryValue.Values[0];
var probabilityy = classProbabilityFeatureValue.DictionaryValue.Values[1];
//// this is a bit hacky, but it's all relative
//value = (probabilityy.FloatValue - probabilityx.FloatValue - 0.5f) * 2f;
//value = (value < 0f) ? 0f : value;
value = probabilityy.FloatValue - probabilityx.FloatValue;
if (value < 0f)
{
Console.WriteLine(value + " negative !");
value = 0f;
}
else
{
Console.WriteLine(value);
}
return(value);
//return probabilityy.FloatValue;
//return prediction;
}
