public DigitImage NextDigit()
{
/*byte[][] pixels = new byte[28][];
* for (int i = 0; i < pixels.Length; ++i)
* pixels[i] = new byte[28];*/
double[][] pixels = new double[28][];
for (int i = 0; i < 28; ++i)
{
pixels[i] = new double[28];
for (int j = 0; j < 28; ++j)
{
byte t = brImages.ReadByte();
double tt = t / 255f;
pixels[i][j] = tt;
}
}
int lbl = brLabels.ReadByte();
DigitImage dImage = new DigitImage(pixels, lbl);
return(dImage);
}
private void DibujarNumero(PictureBox box, Label lab, DigitImage numero)
{
int tam = 10;
int pixels = numero.pixels.Length;
Bitmap bmp = new Bitmap(box.Width, box.Height);
Graphics g = Graphics.FromImage(bmp);
Pen p = new Pen(Color.Black);
int x = 0, y = 0;
for (int i = 0; i < pixels; i++)
{
for (int j = 0; j < pixels; j++)
{
int v = 255 - (int)Math.Round(numero.pixels[i][j] * 255);
Color customColor = Color.FromArgb(v, v, v);
if (v == 255)
{
customColor = Color.FromArgb(102, 255, 51);
}
SolidBrush customBrush = new SolidBrush(customColor);
g.FillRectangle(customBrush, x, y, tam, tam);
g.DrawRectangle(p, x, y, tam, tam);
x += tam;
}
x = 0;
y += tam;
}
lab.Text = numero.label.ToString();
pictureBox1.Image = bmp;
pictureBox1.Update();
}
private void train_Click(object sender, EventArgs eargs)
{
MinistReader trainFileReader;
//DigitImage di;
double[] inputs = new double[784];
double[] outputs = new double[10];
int epocas = int.Parse(textBox1.Text);
for (int e = 1; e <= epocas; e++)
{
trainFileReader = new MinistReader(MinistReader.Modo.Train);
for (int c = 1; c < trainFileReader.numImages; c++) //trainFileReader.numImages
{
DigitImage di = trainFileReader.NextDigit();
for (int i = 0; i < di.pixels.Length; i++)
{
for (int j = 0; j < di.pixels[i].Length; j++)
{
inputs[di.pixels.Length * i + j] = di.pixels[i][j];
}
}
for (int i = 0; i < outputs.Length; i++)
{
outputs[i] = 0.01f;
}
outputs[di.LabelInt()] = 0.99f;
net.Train(new NeuralNetwork.DataSet(inputs, outputs), c, e);
}
trainFileReader.Close();
}
}
