/// <summary>
/// Make a prediction using the standard interface
/// </summary>
/// <param name="input">an instance of ObjectDetectorInput to predict from</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public ObjectDetectorOutput GetPrediction(ObjectDetectorInput input, out NSError error)
{
var prediction = model.GetPrediction(input, out error);
if (prediction == null)
{
return(null);
}
var confidenceValue = prediction.GetFeatureValue("confidence").MultiArrayValue;
var coordinatesValue = prediction.GetFeatureValue("coordinates").MultiArrayValue;
return(new ObjectDetectorOutput(confidenceValue, coordinatesValue));
}
/// <summary>
/// Make a prediction using the convenience interface
/// </summary>
/// <param name="image">Input image as color (kCVPixelFormatType_32RGBA) image buffer, 416 pizels wide by 416 pixels high</param>
/// <param name="iouThreshold">(optional) IOU Threshold override (default: 0.45) as double</param>
/// <param name="confidenceThreshold">(optional) Confidence Threshold override (default: 0.25) as double</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public ObjectDetectorOutput GetPrediction(CVPixelBuffer image, double iouThreshold, double confidenceThreshold, out NSError error)
{
var input = new ObjectDetectorInput(image, iouThreshold, confidenceThreshold);
return(GetPrediction(input, out error));
}
