public void CheckOne()
{
ANeuralNetwork network = new ANeuralNetwork();
network.Load("..\\..\\..\\..\\savedData.txt");
var sampleDirs = Directory.GetDirectories("..\\..\\..\\..\\Data\\TestData\\").ToList();
int fCount = Directory.GetFiles("..\\..\\..\\..\\Data\\GroundData\\", "*.png", SearchOption.AllDirectories).Length;
var poliManager = new PolynomialManager();
poliManager.InitBasis(15, 100);
double count = 0;
foreach (var dir in sampleDirs)
{
var files = Directory.GetFiles(dir, "*.png", SearchOption.TopDirectoryOnly).ToList();
var index = new Random().Next(files.Count);
var file = files[index];
var value = Convert.ToInt32(new StreamReader(dir + "\\" + "value.txt").ReadToEnd());
++count;
ComplexMoments tmpMoments;
ProcessOneImage(file, poliManager, 100, out tmpMoments);
CvInvoke.Imshow(dir, tmpMoments.Real);
var tmpInput = tmpMoments.ToListOfDouble();
var output = network.Predict(tmpInput);
var predictedValue = Convert.ToInt32(output.IndexOf(output.Max()));
Console.WriteLine(predictedValue);
CvInvoke.WaitKey();
}
}
static void Main(string[] args)
{
ANeuralNetwork tmp = new ANeuralNetwork();
tmp.Load("..\\..\\..\\..\\PerceptronSavedData.txt");
var line = Console.ReadLine();
while (line!="q")
{
var tmpInput = line.Split().Select(double.Parse).ToList();
var tmpOutput = tmp.Predict(tmpInput);
foreach (var element in tmpOutput)
{
Console.WriteLine(element);
}
line = Console.ReadLine();
}
}
public void Check()
{
ANeuralNetwork network = new ANeuralNetwork();
network.Load("..\\..\\..\\..\\savedData.txt");
var sampleDirs = Directory.GetDirectories("..\\..\\..\\..\\Data\\TestData\\").ToList();
int fCount = Directory.GetFiles("..\\..\\..\\..\\Data\\GroundData\\", "*.png", SearchOption.AllDirectories).Length;
double precision = 0;
var poliManager = new PolynomialManager();
poliManager.InitBasis(15, 100);
double count = 0;
double trueCount = 0;
foreach (var dir in sampleDirs)
{
var files = Directory.GetFiles(dir, "*.png", SearchOption.TopDirectoryOnly).ToList();
var value = Convert.ToInt32(new StreamReader(dir + "\\" + "value.txt").ReadToEnd());
foreach (var file in files)
{
++count;
ComplexMoments tmpMoments;
ProcessOneImage(file, poliManager, 100, out tmpMoments);
var tmpInput = tmpMoments.ToListOfDouble();
var output = network.Predict(tmpInput);
var predictedValue = Convert.ToInt32(output.IndexOf(output.Max()));
if (predictedValue == value)
{
//++trueCount;
precision += Convert.ToDouble(100 / (double)fCount);
}
}
Console.WriteLine("Точность " + precision + "%");
//Console.WriteLine("Точность " + trueCount/count + "%");
}
}
