public void Recognize(double[] Input, RecognizeModel recognizeModel)
{
int i, j;
double total = 0.0;
double max = -1;
//Apply input to the network
for (i = 0; i < _preInputNum; i++)
{
_preInputLayer[i].Value = Input[i];
}
//Calculate Input Layer's Inputs and Outputs
for (i = 0; i < _inputNum; i++)
{
total = 0.0;
for (j = 0; j < _preInputNum; j++)
{
total += _preInputLayer[j].Value * _preInputLayer[j].Weights[i];
}
_inputLayer[i].InputSum = total;
_inputLayer[i].Output = F(total);
}
//Find the [Two] Highest Outputs
List <string> tempCharName = new List <string>(); //temp
List <double> tempError = new List <double>(); //temp
for (i = 0; i < _outputNum; i++)
{
total = 0.0;
for (j = 0; j < _inputNum; j++)
{
total += _inputLayer[j].Output * _inputLayer[j].Weights[i];
}
_outputLayer[i].InputSum = total;
_outputLayer[i].output = F(total);
tempCharName.Add(_outputLayer[i].Value); //temp
tempError.Add(1 - _outputLayer[i].output); //temp
if (_outputLayer[i].output > max)
{
recognizeModel.MatchedLow = recognizeModel.MatchedHigh;
recognizeModel.OutputLowValue = max;
max = _outputLayer[i].output;
recognizeModel.MatchedHigh = _outputLayer[i].Value;
recognizeModel.OutputHightValue = max;
}
}
//temp
foreach (var name in tempCharName)
{
Console.WriteLine(name);
}
foreach (var error in tempError)
{
Console.WriteLine(error);
}
//temp
}
private void StartRecognize(Bitmap character)
{
_recognizeModel = new RecognizeModel {
MatchedHigh = "?", MatchedLow = "?"
};
double[] input = ImageProcessing.ToMatrix(character,
_settings.SettingsModel.AverageImageHeight, _settings.SettingsModel.AverageImageWidth);
_initializeNetwork.NeuralNetwork.Recognize(input, _recognizeModel);
if (_recognizeModel.OutputHightValue > 0.1)
{
_viewModel.MatchedHightValue = _recognizeModel.MatchedHigh;
_viewModel.MatchedLowValue = _recognizeModel.MatchedLow;
_viewModel.MatchedHightPercent = Convert.ToInt32((100 * _recognizeModel.OutputHightValue)).ToString() + " %";
_viewModel.MatchedLowPercent = Convert.ToInt32((100 * _recognizeModel.OutputLowValue)).ToString() + " %";
_viewModel.LogTextBox += String.Format("Rozpoznano literę {0} - {1}, Drugie miejsce litera {2} - {3}\n",
_viewModel.MatchedHightValue, _viewModel.MatchedHightPercent, _viewModel.MatchedLowValue, _viewModel.MatchedLowPercent);
_licencePlate += _viewModel.MatchedHightValue;
_loosedLicencePlate += _viewModel.MatchedLowValue;
}
}
public void Recognize(double[] Input, RecognizeModel recognizeModel)
{
_neuralNet.Recognize(Input, recognizeModel);
}
