public static Dictionary <TessellatedSolid, double> PotentialFastener = new Dictionary <TessellatedSolid, double>(); // value is its certainty
internal static HashSet <TessellatedSolid> Run(
Dictionary <TessellatedSolid, List <PrimitiveSurface> > solidPrimitive,
Dictionary <TessellatedSolid, List <TessellatedSolid> > multipleRefs,
int threaded,
bool regenerateTrainingData = false)
{
var s = Stopwatch.StartNew();
s.Start();
Console.WriteLine();
Console.WriteLine("\nDetecting Fasteners ....\n");
Fasteners.Clear();
Nuts.Clear();
Washers.Clear();
PotentialFastener.Clear();
if (threaded != 0) // either all of them or some of them are threaded
{
FastenerPerceptronLearner.RunPerecptronLearner(regenerateTrainingData);
FastenerGaussianNaiveBayes.RunGaussianNaiveBayes();
// after training data is generated (or exists), now I should check and see
// if the csv containing weights and votes exists or not.
// Even if the trainingData csv doesnt exist but the csv of w and votes exist,
// we can run the classifier.
// In TrainingDataGenerator, if user says dont regenerate the training data,
// now check and see if the WeightsAndVotes.csv exists or not.
}
var fastener = new HashSet <TessellatedSolid>();
if (multipleRefs.Count == 1)
{
return(fastener);
}
if (threaded == 0) // non of them are threaded
{
AutoNonthreadedFastenerDetection.Run(solidPrimitive, multipleRefs);
}
else
{
if (threaded == 1) // all of them are threaded
{
AutoThreadedFastenerDetection.Run(solidPrimitive, multipleRefs);
}
else // some are threaded, some not
{
AutoSemiThreadedFastenerDetection.Run(solidPrimitive, multipleRefs);
}
}
RemoveDetectedFastenersFromPotentialFasteners();
return(fastener);
}
