private void teachButton_Click(object sender, EventArgs e)
{
_terminate = false;
_error = 1.0;
_progress = 0;
_terminated = false;
_controlError = -1;
_updateProgress();
new Thread(() =>
{
var samples = CaptchasLibrary.GetRecognizedCaptchas();
var digitImages = new List <Image>();
var digitResults = new List <int>();
int controlStart = (int)(samples.Count * 0.8);
for (var i = 0; i < controlStart; i++)
{
var recognizer = new CaptchaRecognizer(samples[i].Image);
var rectangles = recognizer.SplitDigits();
for (var j = 0; j < rectangles.Length; j++)
{
digitImages.Add(ImageHelper.Crop(recognizer.Target, rectangles[j]));
digitResults.Add(int.Parse(samples[i].Answer.Substring(j, 1)));
}
}
var teacher = new NeuralNetworkTrainer(digitImages.ToArray(), digitResults.ToArray());
teacher.Run((net, data, epochs, reports, er, u, userData) =>
{
_error = net.MSE;
_progress = 1.0 * u / epochs;
if (_terminate)
{
return(-1);
}
return(0);
});
teacher.Network.Save(CaptchaRecognizer.NetworkPath);
var controlTotal = 0;
var controlPasses = 0;
for (var i = controlStart; i < samples.Count; i++)
{
var rec = new CaptchaRecognizer(samples[i].Image);
var res = rec.Recognize();
controlTotal++;
if (res.Result == samples[i].Answer)
{
controlPasses++;
}
}
_controlError = 1.0 * controlPasses / controlTotal;
_error = teacher.Network.MSE;
_terminate = true;
_terminated = true;
_progress = 1;
}).Start();
}
private string _process(HttpListenerContext context)
{
var rand = context.Request.QueryString["rand"];
var url = context.Request.QueryString["url"];
var errorStr = "{\"status\": \"error\"}";
if (url == null)
{
return(errorStr);
}
var captcha = new Captcha
{
Name = rand,
Source = url,
};
try
{
captcha.Download();
}
catch (Exception)
{
return(errorStr);
}
var tries = 5;
var results = new List <CaptchaRecognizer.RecognizeResult>();
for (var tryNo = 0; tryNo < tries; tryNo++)
{
var rec = new CaptchaRecognizer(captcha.Image);
try
{
var res = rec.Recognize();
results.Add(res);
if (res.Probability > 0.9)
{
break;
}
}
catch (CaptchaRecognizer.CantSplitDigitsException)
{
results.Add(new CaptchaRecognizer.RecognizeResult
{
Probabilities = new double[] { 0, 0, 0, 0 },
Result = "1111"// just random string
});
}
}
var result = results.OrderByDescending(x => x.Probability).First();
return("{\"status\": \"OK\", \"result\": \"" + result.Result + "\", \"probability\": \"" + result.Probability + "\"}");
}
public GeneticIndividual(CaptchaRecognizer recognizer, bool init = false)
{
_recognizer = recognizer;
if (init)
{
Items = Enumerable.Range(0, _recognizer.DigitsCount)
.Select(GenerateRandomItem)
.ToArray();
}
else
{
Items = new GeneticIndividualItem[_recognizer.DigitsCount];
}
}
private void _next()
{
try
{
_currentCaptcha = GKRegistration.GetNextCaptcha();
}
catch (Exception e)
{
Thread.Sleep(100);
MessageBox.Show(e.Message, "Error");
_next();
return;
}
imagePanel.BackgroundImage = _currentCaptcha.Image;
imagePanel.BackgroundImageLayout = ImageLayout.Stretch;
answerTextBox.Text = "";
randLabel.Text = _currentCaptcha.Name;
var img = _currentCaptcha.Image;
img = ImageHelper.Crop(img, new Rectangle(1, 1, img.Width - 2, img.Height - 2));
img = ImageHelper.Binarize(img);
img = ImageHelper.RemoveLines(img);
var recognizer = new CaptchaRecognizer(_currentCaptcha.Image);
var rects = recognizer.SplitDigits();
var drawArea = new Bitmap(img);
hintImagePanel.BackgroundImage = drawArea;
hintImagePanel.BackgroundImageLayout = ImageLayout.Stretch;
Graphics g = Graphics.FromImage(drawArea);
var pen = new Pen(Brushes.Blue);
foreach (var rect in rects)
{
g.DrawRectangle(pen, rect);
}
}
public GeneticPopolation(CaptchaRecognizer recognizer, int maxSize)
{
_recognizer = recognizer;
MaxSize = maxSize;
var consecutiveInvalidCount = 0;
while (Individuals.Count < MaxSize)
{
var nxt = GeneticIndividual.Mutation(new GeneticIndividual(_recognizer, true));
if (!nxt.IsInvalid())
{
consecutiveInvalidCount = 0;
Individuals.Add(nxt);
}
else
{
consecutiveInvalidCount++;
if (consecutiveInvalidCount > MaxConsecutiveFailures)
{
throw new CantSplitDigitsException();
}
}
}
}
public GeneticIndividualItem(CaptchaRecognizer recognizer, int x, int y)
{
_recognizer = recognizer;
X = x;
Y = y;
}
public Form1()
{
InitializeComponent();
timer1.Start();
var samples = CaptchasLibrary.GetRecognizedCaptchas();
for (var i = 0; i < Math.Min(20, samples.Count); i++)
{
Controls.Add(new Panel
{
Location = new Point(0, (CaptchaHeight + 3) * i),
Name = "imagePanel",
Size = new Size(CaptchaWidth, CaptchaHeight),
TabIndex = 0,
BackgroundImage = samples[i].Image,
BackgroundImageLayout = ImageLayout.Stretch
});
var img = samples[i].Image;
img = ImageHelper.Crop(img, new Rectangle(1, 1, img.Width - 2, img.Height - 2));
//img = ImageHelper.Binarize(img);
//img = ImageHelper.Blur(img);
img = ImageHelper.EdgeDetector(img);
Controls.Add(new Panel
{
Location = new Point(CaptchaWidth + 3, (CaptchaHeight + 3) * i),
Name = "imagePanel",
Size = new Size(CaptchaWidth, CaptchaHeight),
TabIndex = 0,
BackgroundImage = img,
BackgroundImageLayout = ImageLayout.Stretch
});
img = ImageHelper.RemoveLines2(img);
Controls.Add(new Panel
{
Location = new Point((CaptchaWidth + 3) * 2, (CaptchaHeight + 3) * i),
Name = "imagePanel",
Size = new Size(CaptchaWidth, CaptchaHeight),
TabIndex = 0,
BackgroundImage = img,
BackgroundImageLayout = ImageLayout.Stretch
});
var recognizer = new CaptchaRecognizer(samples[i].Image);
var rects = recognizer.SplitDigits();
var dividedPanel = new Panel
{
Location = new Point((CaptchaWidth + 3) * 3, (CaptchaHeight + 3) * i),
Name = "imagePanel",
Size = new Size(recognizer.Target.Width, recognizer.Target.Height),
TabIndex = 0,
BackgroundImageLayout = ImageLayout.Stretch
};
var drawArea = new Bitmap(recognizer.Target);
dividedPanel.BackgroundImage = drawArea;
Graphics g = Graphics.FromImage(drawArea);
var pen = new Pen(Brushes.Blue);
foreach (var rect in rects)
{
g.DrawRectangle(pen, rect);
}
Controls.Add(dividedPanel);
}
}
