public override void Train()
{
CheckError();
var dataset = new List <(Point3D label, CalibratingPushData data)>();
var errors = new List <double>();
foreach (var item in RawData)
{
var key = EyeGazeInfo.ToGazeVector(item.Key);
var data = EyeGazeInfo.ToGazeVector(item.Value.Face.GazeInfo.Vector);
var e = Math.Pow(key.X - data.X, 2) + Math.Pow(key.Y - data.Y, 2);
errors.Add(e);
dataset.Add((item.Key, item.Value));
}
errors.Sort();
var trainX = new Point[dataset.Count];
var trainY = new Point[dataset.Count];
int i = 0;
foreach (var item in dataset)
{
var label = EyeGazeInfo.ToGazeVector(item.label);
var train = EyeGazeInfo.ToGazeVector(item.data.Face.GazeInfo.Vector);
trainX[i] = new Point(train.X, label.X);
trainY[i] = new Point(train.Y, label.Y);
i++;
}
X.Train(trainX);
Y.Train(trainY);
CheckError();
}
public Point3D Apply(Point3D vec)
{
var ret = EyeGazeInfo.ToGazeVector(vec);
ret.X = X.Predict(ret.X);
ret.Y = Y.Predict(ret.Y);
return(ret);
}
private double CheckError()
{
var errors = new List <double>();
foreach (var item in TestData)
{
var input = EyeGazeInfo.ToGazeVector(item.Value.Face.GazeInfo.Vector);
var x = X.Predict(input.X);
var y = Y.Predict(input.Y);
var key = EyeGazeInfo.ToGazeVector(item.Key);
var error = Math.Sqrt(Math.Pow(x - key.X, 2) + Math.Pow(y - key.Y, 2));
errors.Add(error);
}
var errAvg = errors.Average();
var errMax = errors.Max();
Logger.Log(this, $"Error avg: {errAvg}");
Logger.Log(this, $"Error max: {errMax}");
return(errAvg);
}
public override void Train()
{
CheckError();
var trainX = new Point[RawData.Count];
var trainY = new Point[RawData.Count];
int i = 0;
foreach (var item in RawData)
{
var label = EyeGazeInfo.ToGazeVector(item.Key);
var train = EyeGazeInfo.ToGazeVector(item.Value.Face.GazeInfo.Vector);
trainX[i] = new Point(train.X, label.X);
trainY[i] = new Point(train.Y, label.Y);
i++;
}
X.Train(trainX);
Y.Train(trainY);
CheckError();
}
