public string GetTypeString()
{
string result = "";
switch (type)
{
case "object":
result = @ref;
break;
case "array":
return(items.GetTypeString() + "[]");
case "string":
if (@enum != null && @enum.Count > 0)
{
return($"({string.Join(" | ", @enum.Select(x => x is string ? "'" + Regex.Escape(x.ToString()) + "'" : x))})");
}
return("string");
default:
result = type ?? @ref;
break;
}
if (result?.StartsWith("#") ?? false)
{
return(PreProcessing.FixTypeName(result.Split('/').Last()));
}
return(result != null?PreProcessing.FixTypeName(result) : null);
}
public object Convert(object[] values, Type targetType, object parameter, CultureInfo culture)
{
for (int i = 0; i < values.Length; i++)
{
values[i] = PreProcessing.Convert(values[i], null, null, culture);
}
var value = MultiValueConverter.Convert(values, null, parameter, culture);
return(PostProcessing.Convert(value, null, null, culture));
}
/// <summary>
/// Resolves the input reference against the specified parent template. E.g. resolves the internally referenced input, and preprocesses this value as appropriate.
/// </summary>
/// <param name = "template"></param>
/// <returns></returns>
public object Resolve(FluTeCoreInstance template)
{
if (template.Inputs.ContainsKey(Key))
{
var input = (IBoundInput)template.Inputs[Key];
return(PreProcessing.Invoke(input.Value));
}
else
{
throw new KeyNotFoundException("An input reference tried to resolve an input that doesn't exist in the template.");
}
}
public static void prepareDocuments(List <Document> documents, HashSet <string> classifierGrams)
{
var filenames = from fullFilename
in Directory.EnumerateFiles("raw_texts/", "*.txt", SearchOption.AllDirectories)
select Path.GetFullPath(fullFilename);
List <string> list = filenames.ToList();
StreamReader sr2 = new StreamReader("stop_words.txt", Encoding.GetEncoding("ISO-8859-9"));
Language tr = LanguageFactory.Create(LanguageType.Turkish);
char[] seperators = { ' ', '\n', '\t', '\r', '\0' };
string[] stopWords = sr2.ReadToEnd().Split('\n');
Dictionary <string, int> allGrams = new Dictionary <string, int>();
List <Dictionary <string, int> > grams = new List <Dictionary <string, int> >();
Parallel.ForEach(list, i =>
{
StreamReader sr = new StreamReader(i, Encoding.GetEncoding("ISO-8859-9"));
string cleanData = PreProcessing.editFile(i, sr, sr2, tr, seperators, stopWords);
var gram = CreateGramsFrequencies.make2Gram(cleanData).Concat(CreateGramsFrequencies.make3gram(cleanData)).ToDictionary(e => e.Key, e => e.Value);//2gram ile 3 grami birlestir
grams.Add(gram);
documents.Add(new Document(Path.GetFileNameWithoutExtension(i), Directory.GetParent(i).Name, gram));
sr.Close();
});
foreach (var i in grams)
{
foreach (KeyValuePair <string, int> ix in i)
{
if (!allGrams.ContainsKey(ix.Key))
{
allGrams.Add(ix.Key, ix.Value);
}
else
{
allGrams[ix.Key] += ix.Value;
}
}
}
foreach (KeyValuePair <string, int> gram in allGrams)
{
if (gram.Value >= 50)
{
if (!classifierGrams.Contains(gram.Key))
{
classifierGrams.Add(gram.Key);
}
}
}
}
public object[] ConvertBack(object value, Type[] targetTypes, object parameter, CultureInfo culture)
{
value = PostProcessing.ConvertBack(value, null, null, culture);
var values = MultiValueConverter.ConvertBack(value, null, parameter, culture);
for (int i = 0; i < values.Length; i++)
{
values[i] = PreProcessing.ConvertBack(values[i], null, null, culture);
}
return(values);
}
private void btnReSampling_Click(object sender, EventArgs e)
{
var preProc = new PreProcessing();
var traceGroup = _drawingInk.Ink.ToTraceGroup();
var resamplingTraceGroup = preProc.ResampleTraceGroup(traceGroup);
_resultInk.Enabled = false;
_resultInk.Ink = resamplingTraceGroup.ToInk();
_resultInk.Enabled = true;
txtDrawingResult.Text = ReadTraceGroupInUnipenFormat(resamplingTraceGroup);
}
private void Predict()
{
string filePath = @"..\..\CNN\Configs\95,11__9__AFDAB.json";
Bitmap resized = new Bitmap(bmp, new Size(28, 28));
Bitmap preProcessing = null;
if (processingActive)
{
preProcessing = PreProcessing.MedianSmoothing(resized, 3);
}
else
{
preProcessing = resized;
}
Bitmap preproccessedImage = new Bitmap(preProcessing, new Size(bmp.Width, bmp.Height));
pbProccessedImage.Image = preproccessedImage;
resized = preProcessing;
input[0] = new Matrix(resized.Width, resized.Height);
bytes = new byte[28][];
for (int i = 0; i < input[0].rows; i++)
{
bytes[i] = new byte[28];
for (int j = 0; j < input[0].cols; j++)
{
Color c = resized.GetPixel(j, i);
input[0][i, j] = 255f - c.R;
bytes[i][j] = (byte)(255 - c.R);
}
}
input[0].Normalize(0f, 255f, 0f, 1f);
CnnNetwork cnn = new CnnNetwork(filePath);
Matrix output = cnn.Predict(input);
maxIndex = output.GetMaxRowIndex();
string guessText;
guessText = string.Format("This is %{0:f2} a {1}", output[maxIndex, 0] * 100, maxIndex);
lblGuess.Text = guessText;
lstOutput.Items.Clear();
for (int i = 0; i < output.rows; i++)
{
lstOutput.Items.Add(output[i, 0].ToString("F3"));
}
}
private void btnSmooth_Click(object sender, EventArgs e)
{
var traceGroup = _drawingInk.Ink.ToTraceGroup();
//txtUnipen.Text = ReadTraceGroupInUnipenFormat(traceGroup);
var preProc = new PreProcessing();
var newTraceGroup = preProc.SmoothenTraceGroup(traceGroup);
_resultInk.Enabled = false;
_resultInk.Ink = newTraceGroup.ToInk();
_resultInk.Enabled = true;
txtDrawingResult.Text = ReadTraceGroupInUnipenFormat(newTraceGroup);
}
private void LoadImage()
{
var openFileDialog = new OpenFileDialog
{
Filter = "images(*.png;*.jpg;*.bmp)|*.png;*.bmp;*jpg",
Title = "打开图片"
};
if (openFileDialog.ShowDialog() == true)
{
ImagePath = openFileDialog.FileName;
currentPreProcessing = new PreProcessing(ImagePath);
InputSource = currentPreProcessing.originalBitmap.ToBitmapSource();
}
}
private void btnEuclidean_Click(object sender, EventArgs e)
{
var featureExtractor = new PointFloatShapeFeatureExtractor();
var preProc = new PreProcessing();
var traceGroup = _drawingInk.Ink.ToTraceGroup();
var sampledTraceGroup = preProc.ResampleTraceGroup(chkIsNormalized.Checked?preProc.NormalizeSize(traceGroup): traceGroup);
var features = featureExtractor.ExtractFeature(sampledTraceGroup);
var testTraceGroup = _resultInk.Ink.ToTraceGroup();
var sampledTestTraceGroup = preProc.ResampleTraceGroup(chkIsNormalized.Checked?preProc.NormalizeSize(testTraceGroup): testTraceGroup);
var testFeatures = featureExtractor.ExtractFeature(sampledTestTraceGroup);
var eucDistance = featureExtractor.ComputeEuclideanDistance(features, testFeatures);
MessageBox.Show(@"Euclidean Distance = " + eucDistance);
}
public string GetTypeString()
{
string result = "";
switch (type)
{
case "object":
result = this is Parameter param ? param.@ref : "object";
break;
case "array":
return(items.GetTypeString() + "[]");
case "string":
if (@enum != null && @enum.Count > 0)
{
return($"({string.Join(" | ", @enum.Select(x => x is string ? "'" + Regex.Escape(x.ToString()) + "'" : x))})");
}
return("string");
default:
if (type != null)
{
result = type;
break;
}
if (this is Parameter param_)
{
result = param_.@ref;
result = result ?? ((param_.@in == "path") ? "string" : param_.schema.GetTypeString());
result = result ?? "object";
}
break;
}
if (result?.StartsWith("#") ?? false)
{
return(PreProcessing.FixTypeName(result.Split('/').Last()));
}
return(result != null?PreProcessing.FixTypeName(result) : null);
}
public void Run()
{
//Contour<Point> contours = grayImage.FindContours();
//List<Point> listPoints = contours.ToList();
List <Point> listPoints = PreProcessing.FindContours(grayImage);
//foreach (Point i in listPoints)
//{
// grayImage.Draw(new Rectangle(i, new Size(0, 0)), new Gray(0), 1);
// pictureBoxContour.Image = grayImage.ToBitmap();
// Thread.Sleep(10);
//}
//MessageBox.Show(listPoints.Count.ToString());
Image <Bgr, Byte> contoursGraph = PreProcessing.DrawContoursGraph(PreProcessing.BuildContoursGraph(listPoints));
//contoursGraph = contoursGraph.Resize(0.45, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
pictureBoxBinary.Image = contoursGraph.ToBitmap();
}
public void PreProcess()
{
Image <Bgr, Byte> originalImage = new Image <Bgr, Byte>(@"D:\Master\hand.jpg");
originalImage = PreProcessing.Cropping(originalImage, new Rectangle(0 + 10, 0 + 10, originalImage.Width - 30, originalImage.Height - 30));
originalImage = originalImage.Resize(0.45, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//originalImage = originalImage.Rotate(90.0, new Bgr(255, 255, 255));
pictureBoxOriginal.Image = originalImage.ToBitmap();
grayImage = PreProcessing.Convert2Grayscale(originalImage);
grayImage = PreProcessing.NoiseFilter(grayImage, 9);
pictureBoxGray.Image = grayImage.ToBitmap();
grayImage = PreProcessing.Binarization(grayImage, new Gray(255.0));
pictureBoxBinary.Image = grayImage.ToBitmap();
grayImage = PreProcessing.EdgeDetection(grayImage);
pictureBoxContour.Image = grayImage.ToBitmap();
int count = 0;
for (int i = 0; i < grayImage.Height; i++)
{
for (int j = 0; j < grayImage.Width; j++)
{
if (grayImage[i, j].Equals(new Gray(255)))
{
count++;
}
}
}
MessageBox.Show(count.ToString());
Thread t = new Thread(new ThreadStart(Run));
t.Start();
}
public TrainRecognizer()
{
_featureExtractor = new PointFloatShapeFeatureExtractor();
_inkFile = new InkFile();
_preProc = new PreProcessing();
}
private int _numOfChoice = 5; // K value in k-NN
public NNRecognizer()
{
_featureExtractor = new PointFloatShapeFeatureExtractor();
_preProc = new PreProcessing();
}
public void PreProcessTweets()
{
PreProcessing.WritePreProcessedTweets();
}
/*
* This method responsible for calling detectWords method
*/
/// <summary>
/// This method running 6 ocr process in pararell to detect ids in the receipt.
/// </summary>
/// <param name="imgName"></param>
/// <param name="img"></param>
private void InitReceiptsList(string imgName, Image img)
{
_logger.Debug($"Initializing Receipt list imgName: {imgName}");
PreProcessing preProccessing = new PreProcessing(img);
OcrResult ocrResults = null;
try
{
_logger.Debug("Ocr Processing started");
_logger.Debug($"OcrRead imgName: {imgName} - Mode1");
try
{
ocrResults = ocr.Read(preProccessing.GetMode1());
}
catch (Exception e)
{
_logger.Error($"Read", e);
}
if (ocrResults.Pages.Count > 0)
{
Receipt receipt = new Receipt(ocrResults.Pages[0].Width, ocrResults.Pages[0].Height, imgName, preProccessing.GetImageInNewResolution(), ConvertTo24bpp(img));//create receipt object with sizes and name
DetectWords(ocrResults, receipt);
var mode2 = new Task(() =>
{
try
{
_logger.Debug($"OcrRead imgName: {imgName} - New Resolution");
DetectWords(ocr.Read(preProccessing.GetMode2()), receipt);
}
catch (Exception e)
{
_logger.Error($"Error - OcrRead imgName: {imgName} - New Resolution", e);
}
});
var mode3 = new Task(() =>
{
try
{
_logger.Debug($"OcrRead imgName: {imgName} - Mode3");
DetectWords(ocr.Read(preProccessing.GetMode3()), receipt);
}
catch (Exception e)
{
_logger.Error($"Error - OcrRead imgName: {imgName} - Mode3", e);
}
});
var mode4 = new Task(() =>
{
try
{
_logger.Debug($"OcrRead imgName: {imgName} - Mode4");
var image = preProccessing.GetMode4();
DetectWords(ocr.Read(new Bitmap(image)), receipt);
}
catch (Exception e)
{
_logger.Error($"Error - OcrRead imgName: {imgName} - Mode4", e);
}
});
var mode5 = new Task(() =>
{
try
{
_logger.Debug($"OcrRead imgName: {imgName} - Mode5");
var image = preProccessing.GetMode5();
DetectWords(ocr.Read(new Bitmap(image)), receipt);
}
catch (Exception e)
{
_logger.Error($"Error - OcrRead imgName: {imgName} - Mode5", e);
}
});
var mode6 = new Task(() =>
{
try
{
_logger.Debug($"OcrRead imgName: {imgName} - Mode6");
var image = preProccessing.GetMode6();
DetectWords(ocr.Read(new Bitmap(image)), receipt);
}
catch (Exception e)
{
_logger.Error($"Error - OcrRead imgName: {imgName} - Mode6", e);
}
});
mode2.Start();
mode3.Start();
mode4.Start();
mode2.Wait();
mode3.Wait();
mode4.Wait();
mode5.Start();
mode6.Start();
mode5.Wait();
mode6.Wait();
//add receipt after trying all modes
_logger.Debug($"Adding receipt {receipt.GetName()} to list of ready receits");
this.receipts.Add(receipt);
}
}
catch (Exception e)
{
_logger.Error($"Error OcrRead imgName: {imgName} - Mode1", e);
}
}
