public NetNeural(int xPixelWidth, int xPixelHeight, int xHiddenNodes, int xOutputNodes, double xLearningRate, MODE xMode)
{
//SWITCH MODE
int netWidth = xPixelWidth, netHeight = xPixelHeight;
switch (xMode)
{
case MODE.HSENSOR:
netWidth = 1; //ONE LINE OF SENSORS
break;
}
//TRANSFER VARIABLES
PixelWidth = xPixelWidth;
PixelHeight = xPixelHeight;
NodesInput = netWidth * netHeight;
NodesHidden = xHiddenNodes;
NodesOutput = xOutputNodes;
LearningRate = xLearningRate;
Mode = xMode;
//SET MAIN SIZE
SizeNet = new Size(PixelWidth, PixelHeight);
SizeScale = Mod_PNG.getScale(SizeNet, new Size(140, 140), true); //KEEP RELATIONS
//INITIALIZE WEIGHTS
initWeights();
}
public static void drawCheck(Image xDraw, params UniPanel[] xPanel)
{
//CHECK DRAWN BITMAP
double[] dblArray = NetMain.Cam.getDoubleArray();
//GET ANSWER
int answer = NetMain.neuralNetworkQuery(dblArray, 0.0, true);
//ABBRUCH
if (xPanel.Length == 0 || answer == int.MinValue)
{
return;
}
//TRANSFER IMAGE AND TOOLTIP TO NEXT PANEL
for (int i = xPanel.Length - 2; i >= 0; i--)
{
if (xPanel[i].BackgroundImage != null)
{
xPanel[i + 1].BackgroundImage = xPanel[i].BackgroundImage;
}
;
xPanel[i + 1].setToolTip(xPanel[i].getToolTip());
}
//SET FIRST PANEL
Size size = xPanel[0].Size;
xDraw = (Bitmap)Mod_PNG.getScaleImage(xDraw, size, false);
Graphics g = Graphics.FromImage(xDraw);
g.DrawString(Mod_Convert.IntegerToString(answer), Fonts.getFontCooper(9), new SolidBrush(Color.Red), new Point(size.Width - 14, size.Height - 18));
xPanel[0].BackgroundImage = xDraw;
xPanel[0].setToolTip(NetMain.ConsoleBox.Tag.ToString());
}
public static Image ScaleDown(Image xImage)
{
//SCALE IMAGE DOWN
return(Mod_PNG.getScaleImage(xImage, NetMain.Net.SizeNet, false));
}
public static Image ScaleUp(Image xImage)
{
//SCALE IMAGE UP
return(Mod_PNG.getScaleImage(xImage, NetMain.Net.SizeScale, false));
}
