/// <summary>
/// Construct the training data for the combo recognizer.
/// </summary>
/// <param name="testData">the data to test on</param>
/// <param name="rubine">the rubine recognizer</param>
/// <param name="dollar">the dollar recognizer</param>
/// <param name="zernike">the zernike recognizer</param>
/// <param name="image">the image recognizer</param>
/// <returns>a list of tuples (s,f) where s is a shape type and f is a set of features</returns>
private static List <KeyValuePair <ShapeType, Dictionary <string, object> > > TrainingDataCombo(
List <Shape> testData,
RubineRecognizerUpdateable rubine,
DollarRecognizer dollar,
ZernikeMomentRecognizerUpdateable zernike,
ImageRecognizer image)
{
List <KeyValuePair <ShapeType, Dictionary <string, object> > > data = new List <KeyValuePair <ShapeType, Dictionary <string, object> > >();
foreach (Shape shape in testData)
{
string z = zernike.Recognize(shape.SubstrokesL);
List <ShapeType> img = image.Recognize(shape.SubstrokesL);
List <string> r = new List <string>();
List <string> dAvg = new List <string>();
List <string> d = new List <string>();
foreach (Substroke s in shape.SubstrokesL)
{
r.Add(rubine.Recognize(s));
dAvg.Add(dollar.RecognizeAverage(s));
d.Add(dollar.Recognize(s));
}
Dictionary <string, object> features = ComboRecognizer.GetFeatures(shape.SubstrokesL.Count, z, img, r, dAvg, d);
data.Add(new KeyValuePair <ShapeType, Dictionary <string, object> >(shape.Type, features));
}
return(data);
}
public async override void TouchesEnded(Foundation.NSSet touches, UIEvent evt)
{
base.TouchesEnded(touches, evt);
AddPoint(touches);
// Start the recognition
var item = recognizer.Recognize(allPoints);
string display = string.Format("{0} - {1}, {2}", item.Name, item.Score, item.IndicativeAngleInDegrees);
NavigationItem.Prompt = display;
UILabel lbl = new UILabel();
lbl.Frame = new CGRect(item.BoundingRectangle.X, item.BoundingRectangle.Y, item.BoundingRectangle.Width, item.BoundingRectangle.Height);
lbl.BackgroundColor = UIColor.FromRGBA(0, 0, 255, 100);
lbl.Lines = 0;
lbl.LineBreakMode = UILineBreakMode.CharacterWrap;
lbl.Text = display;
Add(lbl);
await Task.Delay(4000);
await UIView.AnimateAsync(0.4, () =>
{
lbl.Alpha = 0;
});
lbl.RemoveFromSuperview();
}
/// <summary>
/// Checks this the vectors, and will fail the cast if the vector count is too small.
/// </summary>
void Check()
{
SaveList();
print(rawVectors.Count);
if (rawVectors.Count >= 40)
{
player.CastSpell(dollarR.Recognize(rawVectors.ToArray()));
}
else
{
player.CastSpell();
}
rawVectors = new HashSet <Vector2>();
}
public Dictionary <string, object> GetIndRecognitionResults(Shape shape, out double believedOrientation)
{
List <Substroke> strokes = shape.SubstrokesL;
int shapeHash = shape.GetHashCode();
int numStrokes = strokes.Count;
List <string> DollarAvgResults = new List <string>(numStrokes);
List <string> DollarResults = new List <string>(numStrokes);
List <string> RubineResults = new List <string>(numStrokes);
List <ShapeType> ImageResults;
string ZernikeResult;
ZernikeResult = _zernike.Recognize(strokes);
ImageResults = _image.Recognize(strokes);
foreach (Substroke s in strokes)
{
int hash = s.Id.GetHashCode();
string res;
res = _dollar.RecognizeAverage(s);
DollarAvgResults.Add(res);
res = _dollar.Recognize(s);
DollarResults.Add(res);
res = _rubine.Recognize(s);
RubineResults.Add(res);
}
Dictionary <string, object> features = GetFeatures(numStrokes, ZernikeResult, ImageResults, RubineResults, DollarAvgResults, DollarResults);
believedOrientation = 0.0;
return(features);
}
