/// <summary>
/// Determine the drawn image and determine the output
/// </summary>
/// <param name="sender">sender object</param>
/// <param name="e">event</param>
private void aiDetermineButton_Click(object sender, EventArgs e)
{
if (digitNN != null)
{
double[] input = DigitNN.transformBitmapdata(B);
byte result = digitNN.determine(input);
if (aiTextBox.Lines.Length == 6)
{
NeuralNetwork.CustomTextBox temp = new NeuralNetwork.CustomTextBox();
for (int i = 1; i < aiTextBox.Lines.Length; i++)
{
temp.Text += aiTextBox.Lines[i] + "\n";
}
temp.Text += "I think it is a " + result + " :)";
aiTextBox.Text = temp.Text;
}
else
{
aiTextBox.Text += "\nI think it is a " + result + " :)";
}
}
if (letterNN != null)
{
double[] input = LetterNN.transformBitmapdata(B);
char result = letterNN.determine(input);
if (aiTextBox.Lines.Length == 6)
{
NeuralNetwork.CustomTextBox temp = new NeuralNetwork.CustomTextBox();
for (int i = 1; i < aiTextBox.Lines.Length; i++)
{
temp.Text += aiTextBox.Lines[i] + "\n";
}
if (result != 0)
{
temp.Text += "I think it is a " + result + " :)";
}
else
{
temp.Text += "I'm not sure :(";
}
aiTextBox.Text = temp.Text;
}
else
{
if (result != 0)
{
aiTextBox.Text += "\nI think it is a " + result + " :)";
}
else
{
aiTextBox.Text += "\nI'm not sure :(";
}
}
}
}
/// <summary>
/// Thread for digit training
/// </summary>
private void trainDigitThread()
{
double[][] transformedData = DigitNN.transformBitmapdata(data);
int epochs = 30;
int batchSize = 10;
double[][] trainData = null;
double[][] validset = null;
byte[] trainLabels = null;
byte[] validsetLabels = null;
if (labelsDigit.Length == 10000)
{
DigitNN.splitIntoTrainAndValidset(transformedData, out trainData, out validset, labelsDigit.Length - labelsDigit.Length / 10);
DigitNN.splitIntoTrainAndValidsetLabels(labelsDigit, out trainLabels, out validsetLabels, labelsDigit.Length - labelsDigit.Length / 10);
}
if (labelsDigit.Length == 60000)
{
DigitNN.splitIntoTrainAndValidset(transformedData, out trainData, out validset, labelsDigit.Length - labelsDigit.Length / 6);
DigitNN.splitIntoTrainAndValidsetLabels(labelsDigit, out trainLabels, out validsetLabels, labelsDigit.Length - labelsDigit.Length / 6);
}
Train <byte> .trainNetwork(digitNN, trainData, validset, labelsDigit, validsetLabels, epochs, batchSize, aiTextBox);
pictureBoxAI.Image = Properties.Resources.ai;
}
