private void RunTesseract(string tag, Mat image)
{
using (var tesseract = OCRTesseract.Create(@"./tessdata", charWhitelist: @"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ.,:/-\*"))
{
tesseract.Run(image,
out var outputText, out var componentRects, out var componentTexts, out var componentConfidences, ComponentLevels.TextLine);
switch (tag)
{
case "0":
Results0.Text = outputText;
break;
case "1":
Results1.Text = outputText;
break;
case "2":
Results2.Text = outputText;
break;
default:
break;
}
}
}
private void DoOcr()
{
if (canvas.Children.Count >= 2 && (canvas.Children[1] as Rectangle) != null)
{
Rectangle rect = canvas.Children[1] as Rectangle;
GetRoi(rect, out int left, out int top, out int right, out int bottom);
OpenCvSharp.Mat m = new OpenCvSharp.Mat();
if (top < bottom && left < right && left >= 0 && right < viewModel.SourceMat.Cols && top >= 0 && bottom < viewModel.SourceMat.Rows)
{
viewModel.SourceMat.SubMat(top, bottom, left, right).CopyTo(m);
OpenCvSharp.Cv2.HConcat(new OpenCvSharp.Mat[] { m, m, m, m }, m);
viewModel.BitmapRoi = BitmapSourceConverter.ToBitmapSource(m);
using (var tesseract = OCRTesseract.Create(MainViewModel.TessData, "eng", "0123456789-", 3, 7)) // 7: Page Segmentation Mode 7:single text line
{
OpenCvSharp.Cv2.GaussianBlur(m, m, new OpenCvSharp.Size(5, 5), 0);
tesseract.Run(m,
out var outputText, out var componentRects, out var componentTexts, out var componentConfidences, ComponentLevels.TextLine);
string data = "(";
data += outputText + ")\n";
for (int i = 0; i < componentRects.Length; i++)
{
data += $"({componentTexts[i]}) apperred at {componentRects[i]} with confidence {componentConfidences[i]}\n";
}
tbxData.Text = outputText;
}
}
}
}
public void Create()
{
using (var tesseract = OCRTesseract.Create(TessData))
{
GC.KeepAlive(tesseract);
}
}
static void Main(string[] args)
{
var img = new Mat(@"image.png");
var gray = new Mat();
Cv2.CvtColor(img, gray, ColorConversionCodes.BGR2GRAY);
var ocr = OCRTesseract.Create("./tessdata", "eng");
string text;
Rect[] boxes;
string[] words;
float[] confidences;
ocr.Run(gray, out text, out boxes, out words, out confidences);
Console.WriteLine("text: " + text);
for (int i = 0; i < boxes.Count(); i++)
{
Console.WriteLine("boxes: " + boxes[i]);
Console.WriteLine("words: " + words[i]);
Console.WriteLine("confidences: " + confidences[i]);
}
Cv2.ImShow("test", gray);
Cv2.WaitKey();
}
public void Run()
{
using (var image = Image("alphabet.png"))
using (var tesseract = OCRTesseract.Create(TessData))
{
tesseract.Run(image,
out var outputText, out var componentRects, out var componentTexts, out var componentConfidences);
testOutputHelper.WriteLine(outputText);
Assert.NotEmpty(outputText);
}
}
internal static void Init()
{
Logger.LogInfo("Loading OCR data...");
var traineddataDir = RatConfig.Paths.Data + "\\";
var traineddataPath = traineddataDir + "bender.traineddata";
if (!System.IO.File.Exists(traineddataPath))
{
Logger.LogError("Could not find traineddata at: " + traineddataPath);
return;
}
ocrTesseractInstance = OCRTesseract.Create(traineddataDir, "bender", null, 3, 7);
}
public void Run()
{
Console.WriteLine(Directory.GetCurrentDirectory());
using (var image = Image("alphabet.png"))
using (var tesseract = OCRTesseract.Create(TessData))
{
tesseract.Run(image,
out var outputText, out var componentRects, out var componentTexts, out var componentConfidences);
Console.WriteLine(outputText);
Assert.NotEmpty(outputText);
}
}
////public override void Cleanup()
////{
//// // Clean up if needed
//// base.Cleanup();
////}
///
private void Run()
{
OpenFileDialog dialog = new OpenFileDialog();
dialog.Filter = "*.png|*.png|*.jpg|*.jpg";
if (dialog.ShowDialog() == true)
{
using (var fs = new FileStream(dialog.FileName, FileMode.Open))
using (var tesseract = OCRTesseract.Create(TessData, "eng", "0123456789-"))
{
Mat mat = Mat.FromStream(fs, ImreadModes.Grayscale);
Cv2.GaussianBlur(mat, mat, new Size(5, 5), 0);
tesseract.Run(mat,
out var outputText, out var componentRects, out var componentTexts, out var componentConfidences, ComponentLevels.TextLine);
string data = "(";
data += outputText + ")\n";
for (int i = 0; i < componentRects.Length; i++)
{
data += $"({componentTexts[i]}) apperred at {componentRects[i]} with confidence {componentConfidences[i]}\n";
}
Content = data;
}
}
}
static void Main(string[] args)
{
var imagePath = @"image.jpg";
var tessDataPath = @"";
var engine = OCRTesseract.Create(tessDataPath, null, null, 3, 3);
var mat = new Mat(imagePath);
var gray = mat.CvtColor(ColorConversionCodes.BGR2GRAY);
var canny = gray.Canny(10, 200);
canny.SaveImage("canny.png");
var weighted = new Mat(gray.Size(), MatType.CV_8UC1);
Cv2.AddWeighted(canny, 0.1, gray, 0.9, 0, weighted);
weighted.SaveImage("weighted.png");
engine.Run(weighted, out string text, out Rect[] rects, out string[] cText, out float[] conf,
ComponentLevels.TextLine);
var mask1 = new Mat(mat.Size(), MatType.CV_8UC1);
mask1.SetTo(0);
var mask2 = new Mat(mat.Size(), MatType.CV_8UC1);
mask2.SetTo(0);
for (int i = 0; i < conf.Length; i++)
{
if (conf[i] == 95)
{
continue;
}
var temp1 = new Mat(mask1, rects[i]);
var temp2 = new Mat(mask2, rects[i]);
var roi = new Mat(weighted, rects[i]);
var binary = new Mat(roi.Size(), MatType.CV_8UC1);
Cv2.Threshold(roi, binary, 0, 255, ThresholdTypes.Otsu);
var blured = binary.GaussianBlur(new Size(5, 5), 5);
blured.CopyTo(temp1);
temp2.SetTo(255);
}
mask1.SaveImage("mask1.png");
mask2.SaveImage("mask2.png");
var res1 = new Mat(mat.Size(), MatType.CV_8UC3);
var res2 = new Mat(mat.Size(), MatType.CV_8UC3);
Cv2.Inpaint(mat, mask1, res1, 10, InpaintMethod.NS);
Cv2.Inpaint(mat, mask2, res2, 10, InpaintMethod.NS);
Console.WriteLine(text);
res1.SaveImage("res1.png");
res2.SaveImage("res2.png");
Console.ReadLine();
}
