/// <summary>
/// Construct the training data set that this recognizer will use to train the neural network.
/// </summary>
/// <param name="recognizer"></param>
/// <param name="goodGates"></param>
/// <param name="badGates"></param>
/// <returns></returns>
public static List <FeatureSet> ConstructTrainingSet(ImageRecognizer recognizer, IEnumerable <Shape> goodGates, IEnumerable <Shape> badGates)
{
List <FeatureSet> trainingData = new List <FeatureSet>();
foreach (Shape goodGate in goodGates)
{
ImageRecognitionResult result = (ImageRecognitionResult)recognizer.recognize(goodGate, null);
trainingData.Add(new FeatureSet(inputVectorForResult(result), new double[] { 1 }));
}
foreach (Shape badGate in badGates)
{
ImageRecognitionResult result = (ImageRecognitionResult)recognizer.recognize(badGate, null);
trainingData.Add(new FeatureSet(inputVectorForResult(result), new double[] { 0 }));
}
return(trainingData);
}
/// <summary>
/// Write a WEKA ARFF file to the given text writer for the given data.
/// Neither the ARFF file nor Weka is used by this class, but the format
/// is useful since Weka provides a very nice data exploration tool
/// (see http://www.cs.waikato.ac.nz/ml/weka/).
/// NOTE: This function does not close the given writer.
/// </summary>
/// <param name="writer"></param>
/// <param name="recognizer"></param>
/// <param name="goodGates"></param>
/// <param name="badGates"></param>
public static void WriteARFF(System.IO.TextWriter writer, ImageRecognizer recognizer, IEnumerable <Shape> goodGates, IEnumerable <Shape> badGates)
{
writer.WriteLine("@RELATION neuralImageRecognizerConfidence");
writer.WriteLine("@ATTRIBUTE partialHausdorff NUMERIC");
writer.WriteLine("@ATTRIBUTE modifiedHausdorff NUMERIC");
writer.WriteLine("@ATTRIBUTE yule NUMERIC");
writer.WriteLine("@ATTRIBUTE tanimoto NUMERIC");
writer.WriteLine("@ATTRIBUTE imageConfidence NUMERIC");
writer.WriteLine("@ATTRIBUTE imageType {AND,OR,XOR,XNOR,NOR,NOT,NAND,NotBubble}");
writer.WriteLine("@ATTRIBUTE idealConfidence NUMERIC");
writer.WriteLine("@DATA");
foreach (Shape gate in goodGates)
{
ImageRecognitionResult result = (ImageRecognitionResult)recognizer.recognize(gate, null);
writer.WriteLine(
result.PartialHausdorff + "," +
result.ModifiedHausdorff + "," +
result.Yule + "," +
result.Tanimoto + "," +
result.Confidence + "," +
result.Type.Name + ",1");
}
foreach (Shape gate in badGates)
{
ImageRecognitionResult result = (ImageRecognitionResult)recognizer.recognize(gate, null);
writer.WriteLine(
result.PartialHausdorff + "," +
result.ModifiedHausdorff + "," +
result.Yule + "," +
result.Tanimoto + "," +
result.Confidence + "," +
result.Type.Name + ",0");
}
}
public override RecognitionResult recognize(Shape shape, FeatureSketch featureSketch)
{
ImageRecognitionResult result = (ImageRecognitionResult)_imageRecognizer.recognize(shape, featureSketch);
return(filterResult(result));
}
