public static Perseptron FromFile(String filename)
{
IFormatter formatter = new BinaryFormatter();
Stream stream = new FileStream(filename,
FileMode.Open,
FileAccess.Read,
FileShare.Read);
TrainedPerceptron ts = (TrainedPerceptron)formatter.Deserialize(stream);
stream.Close();
var p = new Perseptron(ts.sLayerSize, ts.aLayerSize, ts.rLayerSize);
p.vesaStoA = ts.v;
p.aLayerThreshold = ts.v0;
p.vesaAtoR = ts.w;
p.rLayerThresold = ts.w0;
return p;
}
private void TrainPerseptron()
{
var folderName = AppDomain.CurrentDomain.BaseDirectory;
var perFile = folderName + "\\per.data";
var imgsFolder = folderName + "\\Lightshot";
var imgsNames = Directory.GetFiles(imgsFolder);
var imgToVes = new Dictionary<int[], double[]>();
for (int i = 0; i < Letters.Length; i++)
{
var fn = String.Format("{0}\\Screenshot_{1}.png", imgsFolder, i + 1);
var img = new Bitmap(System.Drawing.Image.FromFile(fn));
var ves = new double[imgsNames.Length];
ves[i] = 1;
imgToVes.Add(BitmapEditor.ImgToInts(img), ves);
}
System.Diagnostics.Debug.WriteLine("Training start");
Perseptron p = new Perseptron(30 * 40, 30 * 40, Letters.Length);
p.Train(imgToVes);
p.Save(perFile);
}
