public static string Classify(bool useRubine, float duration, bool righthandedness, List<float> SpeakerAngles, PointCollection pointHist, StylusPointCollection S, List<List<int>> hist, List<List<int>> ihist)
{
// Convert all parameters to format used in GestureTests
List<Vector2> InterpretedPoints = new List<Vector2>();
List<Vector2> StylusPoints = new List<Vector2>();
List<Vector2> VelocityHistory = new List<Vector2>();
List<Vector2> InverseVelocityHistory = new List<Vector2>();
foreach(Point P in pointHist)
InterpretedPoints.Add(new Vector2((float)P.X,(float)P.Y));
foreach(StylusPoint P in S)
StylusPoints.Add(new Vector2((float)P.X,(float)P.Y));
for (int i = 0; i < hist[0].Count; i++)
{
VelocityHistory.Add(new Vector2(hist[0][i], hist[1][i]));
InverseVelocityHistory.Add(new Vector2(ihist[0][i], ihist[1][i]));
}
// Create a new Sample, compute the features, and classify
GS = new GestureSample(GestureTests.Types.GestureType.unknown, righthandedness,duration,SpeakerAngles,InterpretedPoints,StylusPoints,VelocityHistory,InverseVelocityHistory);
GS.ComputeFeatures(GestureFeatures.PointsStroke);
if (useRubine)
return EC.Recognizer.Classify(GS).ToString();
WriteARFF();
Instances test = new Instances(new java.io.FileReader("outfile.arff"));
test.setClassIndex(0);
double clsLabel = cls.classifyInstance(test.instance(0));
test.instance(0).setClassValue(clsLabel);
// Return the appropriate label
return ((GestureType2D)((int)clsLabel+1)).ToString();
}
/// <summary>
/// Attempts to classify an unknown gesture sample.
/// </summary>
/// <param name="sample">the gesture sample to be classified</param>
/// <returns>the best guess for the given sample</returns>
public GestureType Classify(GestureSample sample)
{
float classificationScore = float.NegativeInfinity;
GestureType classification = GestureType.unknown;
//Compute the linear weighted function for each gesture class with the feature vector as input
//the class whose function yields the maximum value is the classification
foreach (GestureType gestureClass in Weights.Keys)
{
float classScore = ComputeScoreFor(gestureClass, sample.Features);
//Console.WriteLine(gestureClass.ToString() + " " + classScore);
if (classScore > classificationScore)
{
classificationScore = classScore;
classification = gestureClass;
}
}
return classification;
}
/// <summary>
/// Parses a given file and loads the gesture data from it.
/// </summary>
/// <param name="filename">path of file containing an instance of a gesture</param>
/// <returns>gesture sample loaded from the file. Returns null if an I/O error occurs.</returns>
private GestureSample LoadSample(string filename)
{
if (Config.Use3DMode == true)
return Load3DSample(filename);
GestureSample sample = null;
GestureType gesture = GestureType.unknown;
float duration = float.NaN;
bool rightHanded = false;
List<Vector2> interpretedPoints = new List<Vector2>();
List<Vector2> velocities = new List<Vector2>();
List<Vector2> inverseVelocities = new List<Vector2>();
List<Vector2> strokePoints = new List<Vector2>();
List<float> angles = new List<float>();
try
{
StreamReader reader = File.OpenText(filename);
while (!reader.EndOfStream)
{
string line = reader.ReadLine();
//end of file
if (line == null) continue;
//skip lines starting with '#' are comments
if (line.StartsWith("#")) continue;
//ignore empty lines
if (line == "") continue;
//split the line by the 'space' character
string[] tokens = line.Split(" ".ToCharArray());
//the first token provides information about the type of data to follow
switch (tokens[0])
{
case "GestureName:":
gesture = ReadGestureType(tokens[1]);
break;
case "Duration(ms):":
duration = float.Parse(tokens[1]);
break;
case "Handedness:":
rightHanded = (tokens[1] == "right");
break;
case "SpeakerAngles:":
int numAngles = int.Parse(tokens[1]);
for (int i = 0; i < numAngles; ++i)
{
string angle = reader.ReadLine();
string[] theta = angle.Split(" ,".ToCharArray());
angles.Add(float.Parse(theta[0]));
}
break;
case "InterpretedPoints:":
int numPoints = int.Parse(tokens[1]);
//read the points from succeeding lines.
for (int i = 0; i < numPoints; ++i)
{
string point = reader.ReadLine();
string[] xy = point.Split(" ,".ToCharArray());
interpretedPoints.Add(new Vector2(float.Parse(xy[0]), float.Parse(xy[1])));
}
break;
case "StrokePoints:":
int numStrokePoints = int.Parse(tokens[1]);
//read datapoints from succeeding lines.
for (int i = 0; i < numStrokePoints; ++i)
{
string point = reader.ReadLine();
string[] xy = point.Split(" ,".ToCharArray());
//180f, 134.34f
strokePoints.Add(new Vector2(float.Parse(xy[0]), float.Parse(xy[1])));
}
break;
case "Velocities:":
int numVelocities = int.Parse(tokens[1]);
//read datapoints from succeeding lines.
for (int i = 0; i < numVelocities; ++i)
{
string point = reader.ReadLine();
string[] xy = point.Split(" ,".ToCharArray());
velocities.Add(new Vector2(float.Parse(xy[0]), float.Parse(xy[1])));
}
break;
case "InverseVelocities:":
int numInverseVelocities = int.Parse(tokens[1]);
//read datapoints from succeeding lines.
for (int i = 0; i < numInverseVelocities; ++i)
{
string point = reader.ReadLine();
string[] xy = point.Split(" ,".ToCharArray());
inverseVelocities.Add(new Vector2(float.Parse(xy[0]), float.Parse(xy[1])));
}
break;
}
}
if (strokePoints.Count == 0)
strokePoints = GenerateStroke(interpretedPoints);
reader.Close();
sample = new GestureSample(gesture, rightHanded, duration, angles, interpretedPoints, strokePoints, velocities, inverseVelocities);
sample.ComputeFeatures(Config.FeaturesToUse);
}
catch (Exception e)
{
Console.WriteLine(e.Message);
Console.WriteLine(e.StackTrace);
}
return sample;
}
