static void Main(string[] args)
{
Console.WriteLine("Loading image....");
var image = new Image <Bgr, byte>("data.png");
var tesOCRprovider = new Tesseract("./tessdata", "eng", OcrEngineMode.TesseractCubeCombined);
Console.WriteLine("Analysing data....");
tesOCRprovider.Recognize(image);
Tesseract.Character[] characters = tesOCRprovider.GetCharacters();
var text = tesOCRprovider.GetText();
Console.WriteLine("\n\n");
Console.WriteLine(text);
Console.WriteLine("\n\nDone");
Console.ReadLine();
}
public void TestOCRBgrText()
{
using (Tesseract ocr = GetTesseract())
using (Image <Bgr, Byte> img = new Image <Bgr, byte>(480, 200))
{
ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz,");
String message = "Hello, World";
CvInvoke.PutText(img, message, new Point(50, 100), CvEnum.FontFace.HersheySimplex, 1.0, new MCvScalar(0, 0, 255));
//ImageViewer.Show(img);
ocr.Recognize(img);
String messageOcr = ocr.GetText().TrimEnd('\n', '\r'); // remove end of line from ocr-ed text
EmguAssert.AreEqual(message, messageOcr, String.Format("'{0}' is not equal to '{1}'", message, messageOcr));
Tesseract.Character[] results = ocr.GetCharacters();
}
}
public MainWindow()
{
InitializeComponent();
for (var i = 1; i < 15; i++)
{
ListView1.Items.Add(new ParkingEntry {
Name = $"Person #{i}", PlateNumber = $"Plate #{i}", DateEntry = DateTime.Now, DateExit = DateTime.Now.AddHours(i)
});
}
var path = System.IO.Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location);
var folder = System.IO.Path.Combine(path, "tessdata");
_licensePlateDetector = new LicensePlateDetector(folder);
Mat m = new Mat(@"C:\Users\cayent\Desktop\ImageTest\222.jpg");
UMat um = m.GetUMat(AccessType.ReadWrite);
this.ImagePlate.Image = um;
//ProcessImage(m);
_ocr = new Tesseract(folder, "eng", OcrEngineMode.TesseractLstmCombined, "ABCDEFGHIJKLMNOPQRSTUVWXYZ 1234567890");
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
//create OCR engine
//_ocr = new Tesseract(System.AppDomain.CurrentDomain.BaseDirectory + @"\Data\\", "eng", OcrEngineMode.TesseractLstmCombined);
//_ocr.Init("", "eng", OcrEngineMode.TesseractLstmCombined);
//_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
_ocr.SetImage(m);
_ocr.Recognize();
var text1 = _ocr.GetBoxText();
var text2 = _ocr.GetCharacters();
var text3 = _ocr.GetHOCRText();
//var text4 = _ocr.GetOsdText(1);
var text5 = _ocr.GetTSVText();
var text6 = _ocr.GetUNLVText();
var text7 = _ocr.GetUTF8Text();
Plate.Text = text7;
}
private void button1_Click(object sender, EventArgs e)
{
OpenFileDialog op = new OpenFileDialog();
DialogResult res = op.ShowDialog();
if (res == DialogResult.OK)
{
filename = op.FileName;
Image img = Image.FromFile(filename);
Bitmap bimg = (Bitmap)img;
Image <Gray, byte> grayimg;
Bgr color = new Bgr(Color.Red);
gimg = new Image <Bgr, byte>(bimg);
try
{
grayimg = gimg.Convert <Gray, Byte>();
Image <Gray, byte> bimimg = grayimg.ThresholdBinary(new Gray(126), new Gray(255));
Tocr.Recognize(bimimg);
Tesseract.Character[] chararcters = Tocr.GetCharacters();
foreach (Tesseract.Character c in chararcters)
{
gimg.Draw(c.Region, color, 1);
}
pictureBox1.Image = gimg.Resize(pictureBox1.Width, pictureBox1.Height, Emgu.CV.CvEnum.Inter.Linear).Bitmap;
string txt = Tocr.GetText();
textBox1.Text = txt;
}
catch (Exception ex)
{
}
}
}
private void btnDetectPlate_Click(object sender, EventArgs e)
{
Image <Bgr, byte> image = (Image <Bgr, byte>)imgPlate.Image;
Mat thresh = new Mat();
Mat gray = new Mat();
CvInvoke.CvtColor(image, gray, ColorConversion.Bgr2Gray);
CvInvoke.Threshold(gray, thresh, 120, 255, ThresholdType.Otsu);
imgCannyPlate.Image = thresh;
_ocr.SetImage(thresh);
_ocr.Recognize();
var words = _ocr.GetCharacters();
string text = "";
foreach (var ass in words)
{
text += ass.Text;
}
richTextBox1.Text = text;
}
static void Main()
{
//using (Mat image = CvInvoke.Imread("../../characters/higher-res.jpg"))
//{
// var scaledImage = new Mat();
// CvInvoke.Resize(image, scaledImage, Size.Empty, 1.5, 1.5);
// DetectLinesInImage(scaledImage);
//}
//using (Mat toolbarObject = CvInvoke.Imread("../../../SURF_Resources/SURF_Toolbar_Mask.png", ImreadModes.Grayscale))
//using (Mat wordbrainObject = CvInvoke.Imread("../../../SURF_Resources/SURF_Wordbrain_Mask.png", ImreadModes.Grayscale))
//using (Mat scene = CvInvoke.Imread("../../../characters/Screenshot_20180530-100638_WordBrain.jpg", ImreadModes.Grayscale))
//{
// CompareImages(scene, toolbarObject, wordbrainObject);
// //DetectKeyPoints(scene);
//}
Console.WriteLine("Starting image recognition");
Task.Factory.StartNew(() =>
{
using (Image <Gray, byte> image =
new Image <Gray, byte>(Path.GetFullPath("../../../characters/result.png")))
{
using (Tesseract tesseractOcrProvider =
new Tesseract("C:\\Program Files\\Tesseract-OCR\\tessdata", "eng", OcrEngineMode.TesseractLstmCombined))
{
tesseractOcrProvider.SetVariable("segment_reward_chartype", "0.9");
tesseractOcrProvider.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ");
tesseractOcrProvider.SetImage(image);
tesseractOcrProvider.Recognize();
Tesseract.Character[] characters = tesseractOcrProvider.GetCharacters();
string text = tesseractOcrProvider.GetBoxText();
Console.WriteLine(text);
}
}
}).Wait();
Console.WriteLine("Called async image recognition");
}
private void loadImageButton_Click(object sender, EventArgs e)
{
if (openImageFileDialog.ShowDialog() == System.Windows.Forms.DialogResult.OK)
{
//Bgr drawColor = new Bgr(Color.Blue);
Gray drawColor = new Gray();
try
{
Image <Bgr, Byte> image = new Image <Bgr, byte>(openImageFileDialog.FileName);
using (Image <Gray, byte> gray = image.Convert <Gray, Byte>())
{
//image.ga
//CvInvoke.GaussianBlur(gray, gray, new Size(5, 5), 1.5);
CvInvoke.GaussianBlur(gray, gray, new Size(3, 3), 1.5);
gray.ROI = new Rectangle(gray.Width / 3, 0, gray.Width - (gray.Width / 3), gray.Height / 3);
_ocr.Recognize(gray);
Tesseract.Character[] characters = _ocr.GetCharacters();
foreach (Tesseract.Character c in characters)
{
Tesseract.Character c2 = c;
c2.Region.X = c.Region.X + (gray.Width / 3);
gray.Draw(c.Region, drawColor, 1);
}
imageBox1.Image = gray;
String text = _ocr.GetText();
ocrTextBox.Text = text;
}
}
catch (Exception exception)
{
MessageBox.Show(exception.Message);
}
}
}
public void DetectCharacters(Bitmap imageBitmap)
{
characterRecognizer = new Tesseract();
characterRecognizer.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
characterRecognizer.Init(@"./tessdata", "rus", OcrEngineMode.TesseractLstmCombined);
Image <Bgr, Byte> imageConverted = new Image <Bgr, Byte>(imageBitmap).Copy();
Mat mat = imageConverted.Mat;
Pix image = new Pix(mat);
characterRecognizer.SetImage(image);
var rec = characterRecognizer.Recognize();
var characters = characterRecognizer.GetCharacters();
for (int i = 0; i < characters.Length; i++)
{
var region = characters[i].Region;
if (region.Height == 0 || region.Width == 0)
{
Bitmap space = new Bitmap(32, 32);
for (int x = 0; x < space.Width; x++)
{
for (int y = 0; y < space.Height; y++)
{
space.SetPixel(x, y, Color.White);
}
}
space.Save("images\\" + i.ToString());
continue;
}
Bitmap letterBitmap = new Bitmap(region.Width, region.Height);
using (Graphics g = Graphics.FromImage(letterBitmap))
{
g.DrawImage(imageBitmap, new Rectangle(0, 0, letterBitmap.Width, letterBitmap.Height),
region,
GraphicsUnit.Pixel);
}
letterBitmap.Save("images\\" + i.ToString());
}
}
/// <summary>
/// Recognize the license plate number from a given image
/// </summary>
/// <remarks>
/// Uses a Tesseract OCR library to recognize the set of characters.
/// When you would like to distinguish single character PageSegMode.SingleChar should be used,
/// otherwise PageSegMode.SingleBlock will be applied.
/// Tesseract uses already prepared training data which consists of built-in data set and
/// special training set for polish license plates.
/// </remarks>
/// <param name="imgWithNumber">Mat containing the image of possible license plate area</param>
/// <param name="pageMode">PageSegMode which should be used when recognizing the character </param>
/// <returns>Recognized plate number</returns>
private string RecognizeNumber(Mat imgWithNumber, PageSegMode pageMode = PageSegMode.SingleChar)
{
Tesseract.Character[] characters;
StringBuilder licensePlateNumber = new StringBuilder();
using (var ocr = new Tesseract())
{
ocr.Init(
_ocrParams["TEST_DATA_PATH"],
_ocrParams["TEST_DATA_LANG"],
OcrEngineMode.LstmOnly);
ocr.SetVariable(
"tessedit_char_whitelist",
_ocrParams["WHITE_LIST"]);
ocr.SetVariable
("user_defined_dpi", "70");
ocr.PageSegMode = pageMode;
using (Mat tmp = imgWithNumber.Clone())
{
ocr.SetImage(tmp);
ocr.Recognize();
characters = ocr.GetCharacters();
for (int i = 0; i < characters.Length; i++)
{
licensePlateNumber.Append(characters[i].Text);
}
}
return(licensePlateNumber.ToString());
}
}
private void getOcr()
{
_ocr = new Tesseract("", "eng", OcrEngineMode.TesseractCubeCombined);
_ocr.SetVariable("tessedit_char_blacklist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ - 1234567890");
Bgr drawColor = new Bgr(Color.Blue);
Image <Gray, byte> gray = SoureceImage.Convert <Gray, byte>();
_ocr.Recognize(gray);
Tesseract.Character[] characters = _ocr.GetCharacters();
foreach (Tesseract.Character c in characters)
{
gray.Draw(c.Region, new Gray(0), 1);
}
DataSource = new DataTable();
DataSource.Columns.Add("字符串", typeof(System.String));
DataRow newLine = DataSource.NewRow();
newLine["字符串"] = _ocr.GetText();
DataSource.Rows.Add(newLine);
SoureceImage.Bitmap = gray.Bitmap;
ShowFormImage();
}
/// <summary> 识别MAT对象文本
/// 识别MAT对象文本
/// </summary>
/// <param name="ocr"></param>
/// <param name="image"></param>
/// <param name="imageColor"></param>
/// <returns></returns>
static string OcrImage(Tesseract ocr, Mat image, Mat imageColor)
{
try
{
Bgr drawCharColor = new Bgr(Color.Red);
if (image.NumberOfChannels == 1)
{
CvInvoke.CvtColor(image, imageColor, ColorConversion.Gray2Bgr);
}
else
{
image.CopyTo(imageColor);
}
#region Perform a full page OCR
ocr.SetImage(imageColor);
if (ocr.Recognize() != 0)
{
throw new Exception("Failed to recognizer image");
}
Tesseract.Character[] characters = ocr.GetCharacters();
//if (characters.Length == 0)
//{
// Mat imgGrey = new Mat();
// CvInvoke.CvtColor(image, imgGrey, ColorConversion.Bgr2Gray);
// Mat imgThresholded = new Mat();
// CvInvoke.Threshold(imgGrey, imgThresholded, 65, 255, ThresholdType.Binary);
// ocr.SetImage(imgThresholded);
// // 这里一直有异常
// characters = ocr.GetCharacters();
// imageColor = imgThresholded;
// if (characters.Length == 0)
// {
// CvInvoke.Threshold(image, imgThresholded, 190, 255, ThresholdType.Binary);
// ocr.SetImage(imgThresholded);
// characters = ocr.GetCharacters();
// imageColor = imgThresholded;
// }
//}
foreach (Tesseract.Character c in characters)
{
CvInvoke.Rectangle(imageColor, c.Region, drawCharColor.MCvScalar);
}
return(ocr.GetUTF8Text());
#endregion
#region Detect the text region before applying OCR.
//bool checkInvert = true;
//Rectangle[] regions;
//using (
// ERFilterNM1 er1 = new ERFilterNM1("trained_classifierNM1.xml", 8, 0.00025f, 0.13f, 0.4f, true, 0.1f))
//using (ERFilterNM2 er2 = new ERFilterNM2("trained_classifierNM2.xml", 0.3f))
//{
// int channelCount = image.NumberOfChannels;
// UMat[] channels = new UMat[checkInvert ? channelCount * 2 : channelCount];
// for (int i = 0; i < channelCount; i++)
// {
// UMat c = new UMat();
// CvInvoke.ExtractChannel(image, c, i);
// channels[i] = c;
// }
// if (checkInvert)
// {
// for (int i = 0; i < channelCount; i++)
// {
// UMat c = new UMat();
// CvInvoke.BitwiseNot(channels[i], c);
// channels[i + channelCount] = c;
// }
// }
// VectorOfERStat[] regionVecs = new VectorOfERStat[channels.Length];
// for (int i = 0; i < regionVecs.Length; i++)
// regionVecs[i] = new VectorOfERStat();
// try
// {
// for (int i = 0; i < channels.Length; i++)
// {
// er1.Run(channels[i], regionVecs[i]);
// er2.Run(channels[i], regionVecs[i]);
// }
// using (VectorOfUMat vm = new VectorOfUMat(channels))
// {
// regions = ERFilter.ERGrouping(image, vm, regionVecs, ERFilter.GroupingMethod.OrientationHoriz,
// "trained_classifier_erGrouping.xml", 0.5f);
// }
// }
// finally
// {
// foreach (UMat tmp in channels)
// if (tmp != null)
// tmp.Dispose();
// foreach (VectorOfERStat tmp in regionVecs)
// if (tmp != null)
// tmp.Dispose();
// }
// Rectangle imageRegion = new Rectangle(Point.Empty, imageColor.Size);
// for (int i = 0; i < regions.Length; i++)
// {
// Rectangle r = ScaleRectangle(regions[i], 1.1);
// r.Intersect(imageRegion);
// regions[i] = r;
// }
//}
//List<Tesseract.Character> allChars = new List<Tesseract.Character>();
//String allText = String.Empty;
//foreach (Rectangle rect in regions)
//{
// using (Mat region = new Mat(image, rect))
// {
// ocr.SetImage(region);
// if (ocr.Recognize() != 0)
// throw new Exception("Failed to recognize image");
// Tesseract.Character[] characters = ocr.GetCharacters();
// //convert the coordinates from the local region to global
// for (int i = 0; i < characters.Length; i++)
// {
// Rectangle charRegion = characters[i].Region;
// charRegion.Offset(rect.Location);
// characters[i].Region = charRegion;
// }
// allChars.AddRange(characters);
// allText += ocr.GetUTF8Text() + Environment.NewLine;
// }
//}
//Bgr drawRegionColor = new Bgr(Color.Red);
//foreach (Rectangle rect in regions)
//{
// CvInvoke.Rectangle(imageColor, rect, drawRegionColor.MCvScalar);
//}
//foreach (Tesseract.Character c in allChars)
//{
// CvInvoke.Rectangle(imageColor, c.Region, drawCharColor.MCvScalar);
//}
//return allText;
#endregion
}
catch (Exception ex)
{
return(string.Empty);
}
}
static void Main(string[] args)
{
string winName = "test-win";
string imagePath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "..", "..", "assets", "1234R.jpg");
Bitmap image = new Bitmap(imagePath);
Util.Gray(image);
byte threshold = Util.Otsu(image);
//Console.WriteLine("threshold is: " + threshold);
Util.Thresholding(image, threshold);
// 这一步调用 ToImage 之后 图片会自动逆时针转90度
Image <Bgr, byte> image1 = image.ToImage <Bgr, byte>();
//image1 = image1.Rotate(90, new Bgr(0, 0, 0));
Util.displayImg(winName + "1", image1);
//使用高斯滤波去除噪声
// 这里new Size(3, 3) 的3 很关键，好像太大 太小 都找不对顶点
CvInvoke.GaussianBlur(image1, image1, new Size(7, 7), 3);
Util.displayImg(winName + "2", image1);
Point left = new Point();
Point right = new Point();
image1 = Util.FindVertices(image1, ref left, ref right);
Util.displayImg(winName + "3", image1);
// 画线 看找到的顶点对不对
//Point[] points = new Point[2];
//points[0] = left;
//points[1] = right;
//image1.DrawPolyline(points, true, new Bgr(Color.Red), 10);
//image1.Save(Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "new.png"));
Console.WriteLine("1 left: " + left.X + " " + left.Y);
Console.WriteLine("1 right: " + right.X + " " + right.Y);
double angle = Util.getAngleTray(left, right, left, new Point(right.X, left.Y));
Console.WriteLine("angle is: " + angle);
// 旋转
image1 = image1.Rotate(90 + angle, new Bgr(0, 0, 0));
Util.displayImg(winName + "4", image1);
// 旋转后的顶点
image1 = Util.FindVertices(image1, ref left, ref right);
Util.displayImg(winName + "5", image1);
int cutWidth = 700;
int cutHeight = 800;
Bitmap MasterMap = new Bitmap(cutWidth, cutHeight, PixelFormat.Format32bppRgb);
Graphics g = Graphics.FromImage(MasterMap);
Rectangle dest = new Rectangle(0, 0, cutWidth, cutHeight);
Rectangle source = new Rectangle(left.X + 300, left.Y + 200, cutWidth, cutHeight);
g.DrawImage(image1.AsBitmap(), dest, source, GraphicsUnit.Pixel);
// 这里调用后 图片没有旋转 不知道为什么
image1 = MasterMap.ToImage <Bgr, byte>();
Util.displayImg(winName + "6", image1);
#region 开操作 没什么效果 https://www.cnblogs.com/ssyfj/p/9277688.html
//var image1 = image.ToImage<Bgr, byte>();
//Mat kernel1 = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Rectangle, new Size(10, 10), new Point(0, 0));
//image1.MorphologyEx(Emgu.CV.CvEnum.MorphOp.Gradient, kernel1, new Point(0, 0), 1, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar());
//image1.Save(Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "new.png"));
#endregion
string ocrPath = "./Properties/tessdata";
//string language = "chi_sim";
string language = "eng";
Tesseract ocr = new Tesseract(ocrPath, language, OcrEngineMode.Default);
ocr.SetImage(image1);
ocr.Recognize();
Tesseract.Character[] characters = ocr.GetCharacters();
string strRsult = string.Empty;
try
{
strRsult = ocr.GetUTF8Text();
Console.WriteLine(strRsult);
}
catch (Exception)
{
Console.WriteLine("Error");
return;
}
}
public IEnumerable <string> GetCharactersFromImage(byte[] imageData)
{
List <string> recognizedCharacters = new List <string>();
using (MemoryStream memoryStream = new MemoryStream(imageData))
{
Bitmap bitmapImage = (Bitmap)Image.FromStream(memoryStream);
Image <Gray, byte> image = new Image <Gray, byte>(bitmapImage);
using (Tesseract tesseract = new Tesseract(_tesseractPath, _language, OcrEngineMode.TesseractOnly))
{
tesseract.SetVariable("tessedit_char_whitelist", "QWERTYUIOPASDFGHJKLZXCVBNM");
tesseract.SetImage(image);
tesseract.Recognize();
IEnumerable <Tesseract.Character> characters = DiscardUncenteredCharacters(tesseract.GetCharacters());
foreach (Tesseract.Character character in characters)
{
if (!string.IsNullOrWhiteSpace(character.Text))
{
recognizedCharacters.Add(character.Text);
}
}
}
}
return(recognizedCharacters);
}
private void FindLicensePlate(
VectorOfVectorOfPoint contours, int[,] hierachy, int idx, IInputArray gray, IInputArray canny,
List <IInputOutputArray> licensePlateImagesList, List <IInputOutputArray> filteredLicensePlateImagesList,
List <RotatedRect> detectedLicensePlateRegionList,
List <string> licenses
)
{
for (; idx >= 0; idx = hierachy[idx, 0])
{
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
if (numberOfChildren == 0)
{
continue;
}
using (VectorOfPoint contour = contours[idx])
{
if (CvInvoke.ContourArea(contour) > 400)
{
if (numberOfChildren < 3)
{
//Если нашли менее 3-х символов, то не считаем это номером
//При этом надо проверить содержимое каждого элемента внутри может содержаться номер.
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
continue;
}
RotatedRect box = CvInvoke.MinAreaRect(contour);
if (box.Angle < -45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle += 90.0f;
}
else if (box.Angle > 45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle -= 90.0f;
}
double whRatio = (double)box.Size.Width / box.Size.Height;
if (!(3.0 < whRatio && whRatio < 10.0))
//if (!(1.0 < whRatio && whRatio < 2.0))
{
//если соотношение сторон не соответствует, то это не номер авто.
//Однако мы должны проверить вложения, номер может находиться внутри контура
//Contour<Point> child = contours.VNext;
if (hierachy[idx, 2] > 0)
{
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
}
continue;
}
using (UMat tmp1 = new UMat())
using (UMat tmp2 = new UMat())
{
PointF[] srcCorners = box.GetVertices();
PointF[] destCorners = new PointF[] {
new PointF(0, box.Size.Height - 1),
new PointF(0, 0),
new PointF(box.Size.Width - 1, 0),
new PointF(box.Size.Width - 1, box.Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(srcCorners, destCorners))
{
CvInvoke.WarpAffine(gray, tmp1, rot, Size.Round(box.Size));
}
//изменяем размер номера таким образом чтобы размер шрифта был примерно 10-12. Это даст большую точность
Size approxSize = new Size(240, 180);
double scale = Math.Min(approxSize.Width / box.Size.Width, approxSize.Height / box.Size.Height);
Size newSize = new Size((int)Math.Round(box.Size.Width * scale), (int)Math.Round(box.Size.Height * scale));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
//делаем отступы от краев
int edgePixelSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
UMat plate = new UMat(tmp2, newRoi);
UMat filteredPlate = FilterPlate(plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (UMat tmp = filteredPlate.Clone())
{
_ocr.Recognize();
//_ocr.Recognize(tmp);
words = _ocr.GetCharacters();
if (words.Length == 0)
{
continue;
}
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
licenses.Add(strBuilder.ToString());
licensePlateImagesList.Add(plate);
filteredLicensePlateImagesList.Add(filteredPlate);
detectedLicensePlateRegionList.Add(box);
}
}
}
}
}
private void button2_Click(object sender, EventArgs e) //procesiranje slike
{
c = 0; fields = new List <Image <Gray, byte> >(); grid = new int[9, 9];
OpenFileDialog opf = new OpenFileDialog();
if (opf.ShowDialog() != DialogResult.OK)
{
return;
}
Image <Gray, Byte> gray = new Image <Gray, byte>(opf.FileName);
imageBox1.Image = gray.Clone();
Image <Gray, Byte> izhod = new Image <Gray, byte>(gray.Width, gray.Height);
// binariziranje(adaptivna pragovna segmentacija)
izhod = gray.ThresholdAdaptive(new Gray(255), Emgu.CV.CvEnum.AdaptiveThresholdType.MeanC, Emgu.CV.CvEnum.ThresholdType.BinaryInv, 11, new Gray(11));
izhod._SmoothGaussian(1); //glajenje, (ni obvezno potrebno)
// imageBox2.Image = izhod.Clone();
var nova = izhod.Clone();
//posopek za iskanje najvecjega povezanega objekta
VectorOfVectorOfPoint vvp = new VectorOfVectorOfPoint();
Mat hierarchy = new Mat();
CvInvoke.FindContours(izhod, vvp, hierarchy, Emgu.CV.CvEnum.RetrType.Tree, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxNone);
int largest_contour_index = 0;
double largest_area = 0;
VectorOfPoint largestContour;
for (int i = 0; i < vvp.Size; i++)
{
double a = CvInvoke.ContourArea(vvp[i], false);
if (a > largest_area)
{
largest_area = a;
largest_contour_index = i;
}
}
largestContour = vvp[largest_contour_index];
Point[] lc = largestContour.ToArray();
//iskanje kote za perspektivna transformacija
Point topleft = new Point(gray.Width, gray.Height);
Point topright = new Point(0, gray.Height);
Point botright = new Point(0, 0);
Point botleft = new Point(gray.Width, 0);
foreach (Point p in lc)
{
if ((p.X + p.Y) < (topleft.X + topleft.Y))
{
topleft = p;
}
else if ((p.X - p.Y) > (topright.X - topright.Y))
{
topright = p;
}
else if ((p.X + p.Y) > (botright.X + botright.Y))
{
botright = p;
}
else if ((p.Y - p.X) > (botleft.Y - botleft.X))
{
botleft = p;
}
}
//prerisemo gridlines, da se znebimo linije, potem ostanejo le stevilke(lazja razpoznava)
CvInvoke.DrawContours(nova, vvp, largest_contour_index, new MCvScalar(0, 0, 0), 6, Emgu.CV.CvEnum.LineType.EightConnected, hierarchy, 1);
Image <Gray, Byte> warp = new Image <Gray, byte>(450, 450);
PointF[] src = new PointF[] { topleft, topright, botright, botleft };
PointF[] dst = new PointF[] { new Point(0, 0), new Point(450, 0), new Point(450, 450), new Point(0, 450) };
Mat warpmat = CvInvoke.GetPerspectiveTransform(src, dst); //racunamo matrika za transformacija
CvInvoke.WarpPerspective(nova, warp, warpmat, new Size(450, 450)); //izvedemo transformacija
//imageBox1.Image = nova;
imageBox2.Image = warp;
//warp._Erode(1); //krcenje ali sirjenje, ni potrebno
//warp._Dilate(1);
//razpoznava stevilk, 2 moznosti (izbira so radiogumbov)
if (radioButton1.Checked)
{
tess = new Tesseract(@"C:/Emgu/emgucv-windows-universal 3.0.0.2157/bin/", null, OcrEngineMode.Default, "123456789 ");
}
fields = new List <Image <Gray, byte> >(); //hranim polja za lazjo debagiranje
for (int i = 0; i < 9; i++)
{
for (int j = 0; j < 9; j++)
{
Image <Gray, Byte> temp = (warp.GetSubRect(new Rectangle(j * 50 + 3, i * 50 + 3, 44, 44))).Clone(); //malo izpustimo po robu polja
temp._SmoothGaussian(1);
Gray sum = temp.GetSum(); //ce ni dovolj beli pikslov(dele objektov), ni stevilka.
if (sum.Intensity < 30000)
{
continue;
}
//spet iscemo najvecji element v polju, predvidevam da je stevilo
VectorOfVectorOfPoint vvptemp = new VectorOfVectorOfPoint();
Mat hierarchytemp = new Mat();
CvInvoke.FindContours(temp, vvptemp, hierarchytemp, Emgu.CV.CvEnum.RetrType.Tree, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxNone);
int ind = 0;
double area = 100;
VectorOfPoint contour;
for (int k = 0; k < vvptemp.Size; k++)
{
double ar = CvInvoke.ContourArea(vvptemp[k], false);
if (ar > area)
{
area = ar;
ind = k;
}
}
if (area == 100)
{
continue; //ce je najvecjega kontura area manj kot 100 (polje je 44x44), povzamemem da ni stevilo
}
contour = vvptemp[ind]; //kontura stevlike
var tempimg = new Image <Gray, Byte>(44, 44, new Gray(0));
CvInvoke.DrawContours(tempimg, vvptemp, ind, new MCvScalar(255, 0, 0), -1, Emgu.CV.CvEnum.LineType.EightConnected, hierarchytemp);
//narisemo notranjosti najvecjega kontura v novi sliki z belo barvo
fields.Add(tempimg); //dodamo za pogled
if (radioButton2.Checked)
{
Rectangle br = CvInvoke.BoundingRectangle(contour);
int indeks = 0;
double vrednost = double.MaxValue;
for (int q = 0; q < 9; q++)
{ //racunamo podobnost s vsakem vzorcu
var kraj = tempimg.GetSubRect(new Rectangle(br.X, br.Y, vzorci[q].Width, vzorci[q].Height));
var pod = vzorci[q].AbsDiff(kraj);
var podobnost = pod.GetSum();
if (podobnost.Intensity < vrednost)
{
indeks = q + 1; //ker je zero based
vrednost = podobnost.Intensity;
}
}
grid[i, j] = indeks;//najbolj podobni je zaznana stevilka
}
else
{
tess.Recognize(tempimg); //raspoznava slike s pomocjo tesseract OCR vgrajen v openCV
var x = tess.GetCharacters();
if (x.Length == 1)
{
grid[i, j] = Convert.ToInt32(x[0].Text);
}
}
}
}
NarisiStevilke(); //izpisemo stevilki v polje
}
private void FindPlate(
VectorOfVectorOfPoint contours, int[,] hierachy, int idx, IInputArray gray, IInputArray canny,
List <IInputOutputArray> PlateImageList, List <IInputOutputArray> filteredPlateImageList, List <RotatedRect> detectedPlateRegionList,
List <String> word)
{
for (; idx >= 0; idx = hierachy[idx, 0])
{
// 寻找有多少个子轮廓
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
if (numberOfChildren == 0)
{
continue;
}
using (VectorOfPoint contour = contours[idx])
{
// 轮廓内的面积
if (CvInvoke.ContourArea(contour) > 400)
{
if (numberOfChildren < 3)
{
// 子轮廓小于3 认定不是字符串区域
// 再次去搜索这个子轮廓 子项索引
FindPlate(contours, hierachy, hierachy[idx, 2], gray, canny, PlateImageList,
filteredPlateImageList, detectedPlateRegionList, word);
continue;
}
// 旋转矩形 最小面积矩形
RotatedRect box = CvInvoke.MinAreaRect(contour);
if (box.Angle < -45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle += 90.0f;
}
else if (box.Angle > 45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle -= 90.0f;
}
double whRatio = (double)box.Size.Width / box.Size.Height;
// 字符串长度和宽度
if (!(3.0 < whRatio && whRatio < 10.0))
{
// 认定不是个字符串 但是继续搜索子区域
if (hierachy[idx, 2] > 0)
{
FindPlate(contours, hierachy, hierachy[idx, 2], gray, canny, PlateImageList,
filteredPlateImageList, detectedPlateRegionList, word);
continue;
}
}
using (Mat tmp1 = new Mat())
using (Mat tmp2 = new Mat())
{
PointF[] srcCorners = box.GetVertices();
PointF[] destConers = new PointF[]
{
new PointF(0, box.Size.Height - 1),
new PointF(0, 0),
new PointF(box.Size.Width - 1, 0),
new PointF(box.Size.Width - 1, box.Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(srcCorners, destConers))
{
CvInvoke.WarpAffine(gray, tmp1, rot, Size.Round(box.Size));
}
// 调整字符串大小
Size approxSize = new Size(240, 180);
double scale = Math.Min(approxSize.Width / box.Size.Width, approxSize.Height / box.Size.Height);
Size newSize = new Size((int)Math.Round(box.Size.Width * scale), (int)Math.Round(box.Size.Height * scale));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
// 移除边缘像素
int edgePixlSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixlSize, edgePixlSize),
tmp2.Size - new Size(2 * edgePixlSize, 2 * edgePixlSize));
Mat plate = new Mat(tmp2, newRoi);
Mat filteredPlate = FilterPlate(plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (Mat tmp = filteredPlate.Clone())
{
// 检测图片
_ocr.Recognize(tmp);
words = _ocr.GetCharacters();
if (words.Length == 0)
{
continue;
}
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
word.Add(strBuilder.ToString());
PlateImageList.Add(plate);
filteredPlateImageList.Add(filteredPlate);
detectedPlateRegionList.Add(box);
}
}
}
}
}
private void FindPlate(
VectorOfVectorOfPoint cevreler, int[,] hiyerarsi, int idx, IInputArray gri, IInputArray cannykenar,
List <IInputOutputArray> PlateGoruntuLisesi, List <IInputOutputArray> filtrelenmisPlateGoruntuListesi, List <RotatedRect> tespitEdilenPlateBolgesiListesi,
List <String> licenses)
{
for (; idx >= 0; idx = hiyerarsi[idx, 0])
{
int karaktersayisi = CharacterCount(hiyerarsi, idx);
if (karaktersayisi == 0)
{
continue;
}
using (VectorOfPoint cevre = cevreler[idx])
{
if (CvInvoke.ContourArea(cevre) > 400)
{
if (karaktersayisi < 3)
{
FindPlate(cevreler, hiyerarsi, hiyerarsi[idx, 2], gri, cannykenar, PlateGoruntuLisesi,
filtrelenmisPlateGoruntuListesi, tespitEdilenPlateBolgesiListesi, licenses);
continue;
}
RotatedRect kutu = CvInvoke.MinAreaRect(cevre);
if (kutu.Angle < -45.0)
{
float tmp = kutu.Size.Width;
kutu.Size.Width = kutu.Size.Height;
kutu.Size.Height = tmp;
kutu.Angle += 90.0f;
}
else if (kutu.Angle > 45.0)
{
float tmp = kutu.Size.Width;
kutu.Size.Width = kutu.Size.Height;
kutu.Size.Height = tmp;
kutu.Angle -= 90.0f;
}
double enboyoran = (double)kutu.Size.Width / kutu.Size.Height;
if (!(3.0 < enboyoran && enboyoran < 10.0))
{
if (hiyerarsi[idx, 2] > 0)
{
FindPlate(cevreler, hiyerarsi, hiyerarsi[idx, 2], gri, cannykenar, PlateGoruntuLisesi,
filtrelenmisPlateGoruntuListesi, tespitEdilenPlateBolgesiListesi, licenses);
}
continue;
}
using (UMat tmp1 = new UMat())
using (UMat tmp2 = new UMat())
{
PointF[] kutuKoseNokta = kutu.GetVertices(); // kutunun köşe noktalarını alır
PointF[] destCorners = new PointF[] {
new PointF(0, kutu.Size.Height - 1),
new PointF(0, 0),
new PointF(kutu.Size.Width - 1, 0),
new PointF(kutu.Size.Width - 1, kutu.Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(kutuKoseNokta, destCorners))
{
CvInvoke.WarpAffine(gri, tmp1, rot, Size.Round(kutu.Size));
}
Size yaklasikBoyut = new Size(240, 180); // yaklaşık boyut
double olcek = Math.Min(yaklasikBoyut.Width / kutu.Size.Width, yaklasikBoyut.Height / kutu.Size.Height);
Size newSize = new Size((int)Math.Round(kutu.Size.Width * olcek), (int)Math.Round(kutu.Size.Height * olcek));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
int edgePixelSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
UMat Plate = new UMat(tmp2, newRoi);
UMat filtrelenmisPlate = FilterPlate(Plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (UMat tmp = filtrelenmisPlate.Clone())
{
OCR.Recognize(tmp);
words = OCR.GetCharacters();
if (words.Length == 0)
{
continue;
}
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
int sayac = 0;
int bosluk = 0;
for (int i = 0; i < strBuilder.Length; i++)
{
if (strBuilder[i].ToString() == "." || strBuilder[i].ToString() == "?" || strBuilder[i].ToString() == "*" || strBuilder[i].ToString() == "-")
{
sayac++;
}
if (strBuilder[i].ToString() == " ")
{
bosluk++;
}
}
if (strBuilder[0].ToString() == "E" || strBuilder[0].ToString() == "F" || strBuilder[0].ToString() == "I" || strBuilder[0].ToString() == "T")
{
strBuilder.Remove(0, 1);
}
if (sayac == 0 && strBuilder.Length >= 9 && bosluk <= 2)
{
string[] parcalar;
String asd = strBuilder.ToString();
parcalar = asd.Split(' ');
if (parcalar.Length == 3)
{
CityCode = parcalar[0];
LetterGruop = parcalar[1];
NumberGroup = parcalar[2];
if (CityCode.Length == 3)
{
CityCode = CityCode.Remove(0, 1);
}
CityCode = CityCode.Replace('B', '8');
CityCode = CityCode.Replace('D', '0');
CityCode = CityCode.Replace('G', '6');
CityCode = CityCode.Replace('I', '1');
CityCode = CityCode.Replace('O', '0');
CityCode = CityCode.Replace('S', '5');
CityCode = CityCode.Replace('Z', '2');
CityCode = CityCode.Replace('L', '4');
LetterGruop = LetterGruop.Replace('2', 'Z');
LetterGruop = LetterGruop.Replace('0', 'D');
LetterGruop = LetterGruop.Replace('5', 'S');
LetterGruop = LetterGruop.Replace('6', 'G');
LetterGruop = LetterGruop.Replace('8', 'B');
LetterGruop = LetterGruop.Replace('1', 'I');
NumberGroup = NumberGroup.Replace('B', '8');
NumberGroup = NumberGroup.Replace('D', '0');
NumberGroup = NumberGroup.Replace('G', '6');
NumberGroup = NumberGroup.Replace('I', '1');
NumberGroup = NumberGroup.Replace('O', '0');
NumberGroup = NumberGroup.Replace('S', '5');
NumberGroup = NumberGroup.Replace('Z', '2');
NumberGroup = NumberGroup.Replace('A', '4');
if (NumberGroup.Length == 5)
{
NumberGroup = NumberGroup.Remove(4, 1);
}
strBuilder.Remove(0, strBuilder.Length);
strBuilder.Append(CityCode);
strBuilder.Append(" ");
strBuilder.Append(LetterGruop);
strBuilder.Append(" ");
strBuilder.Append(NumberGroup);
}
if (strBuilder.Length >= 7 && strBuilder.Length <= 10)
{
licenses.Add(strBuilder.ToString());
PlateGoruntuLisesi.Add(Plate);
filtrelenmisPlateGoruntuListesi.Add(filtrelenmisPlate);
tespitEdilenPlateBolgesiListesi.Add(kutu);
}
}
}
}
}
}
}
public IActionResult Steps(StepData uploadFile)
{
StepData stepData = new StepData();
ProcessCaptured processCaptured = new ProcessCaptured();
Image <Bgra, Byte> imgg = null;
Mat finalImg = new Mat();
using (MemoryStream ms = new MemoryStream())
{
if (ms != null)
{
CvInvoke.UseOpenCL = true;
uploadFile.FormFile.CopyTo(ms);
byte[] fileBytes = ms.ToArray();
imgg = processCaptured.GetImageFromStream(ms);
finalImg = imgg.Mat.Clone();
stepData = AddData(stepData, finalImg, "Orginal");
using (Mat im = imgg.Mat)
{
using (Mat threshold = new Mat())
{
using (Mat gray = new Mat())
{
using (Mat canny = new Mat())
{
using (Mat rectImg = new Mat())
{
CvInvoke.Threshold(im, threshold, 100, 255, ThresholdType.BinaryInv);
stepData = AddData(stepData, threshold, "Threshold");
CvInvoke.CvtColor(threshold, gray, ColorConversion.Bgr2Gray);
stepData = AddGrayData(stepData, gray, "Gray");
CvInvoke.Canny(gray, canny, 100, 50, 7);
stepData = AddData(stepData, canny, "Canny");
List <RotatedRect> rect = new List <RotatedRect>();
rect = Contours(canny);
if (rect != null && rect.Count > 0)
{
foreach (RotatedRect boxr in rect)
{
CvInvoke.Polylines(finalImg, Array.ConvertAll(boxr.GetVertices(), Point.Round), true,
new Bgr(Color.DarkOrange).MCvScalar, 2);
}
}
stepData = AddData(stepData, finalImg, "With Rectangle");
List <Mat> mat = RoI(rect, gray);
int i = 0;
//OCR
string path = AppContext.BaseDirectory;
Tesseract _ocr = new Tesseract(path, "eng", OcrEngineMode.TesseractLstmCombined);
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
foreach (Mat m in mat)
{
i += 1;
_ocr.SetImage(m);
_ocr.Recognize();
Tesseract.Character[] words = _ocr.GetCharacters();
//string wor=words.
StringBuilder sb = new StringBuilder();
foreach (var c in words)
{
sb.Append(c.Text);
}
stepData = AddData(stepData, m, i.ToString(), sb.ToString());
}
}
}
}
}
}
//Mat blur = new Mat();
//blur = Blur(im);
//stepData = AddData(stepData, blur, "Blur");
//Mat gray = new Mat();
//gray = Gray(blur);
//stepData = AddData(stepData, gray, "Gray");
//Mat threshold = new Mat();
//threshold = Threshold(im);
//stepData = AddData(stepData, threshold, "Threshold");
//Mat gray = new Mat();
//gray = Gray(threshold);
//stepData = AddGrayData(stepData, gray, "Gray");
//Mat canny = new Mat();
//canny = Canny(gray);
//stepData = AddData(stepData, canny, "Canny");
//List<RotatedRect> rect = new List<RotatedRect>();
//rect = Contours(canny);
//Mat rectImg = new Mat();
//rectImg = DrawRect(imgg.Mat, rect);
//stepData = AddData(stepData, rectImg, "With Rectangle");
//List<Mat> mat = RoI(rect, threshold.Clone());
//int i = 0;
//foreach (Mat m in mat)
//{
// i += 1;
// stepData = AddData(stepData, m, i.ToString());
//}
}
}
#region Old
//Image<Bgr, Byte> imgg = null;
//Image<Bgr, byte> tempImg = null;
//Image<Gray, Byte> GrayImg = null;
//Image<Gray, Byte> CannyImgTemp = null;
//Image<Bgr, Byte> CannyImg = null;
//Image<Bgr, byte> temp = null;
//int[,] hierachy = null;
//List<VectorOfPoint> box = new List<VectorOfPoint>();
//List<RotatedRect> boxList = new List<RotatedRect>();
//CvInvoke.UseOpenCL = true;
//using (MemoryStream ms = new MemoryStream())
//{
// if (ms != null)
// {
// uploadFile.FormFile.CopyTo(ms);
// byte[] fileBytes = ms.ToArray();
// imgg = processCaptured.GetImageFromStream(ms);
// Mat im = imgg.Mat;
// stepData = AddData(stepData, im, "Orginal");
// tempImg = imgg.Copy();
// }
//}
//using (Mat blur = new Mat())
//{
// using (Mat gray = new Mat())
// {
// using (Mat canny = new Mat())
// {
// Size kSize = new Size(3, 3);
// // CvInvoke.GaussianBlur(imgg, blur, kSize, 0);
// CvInvoke.Threshold(imgg, blur, 50, 255, ThresholdType.Binary);
// //CvInvoke.BilateralFilter(imgg, blur, -1, -1, 100);
// stepData = AddData(stepData, blur, "Gray");
// CvInvoke.Threshold(imgg, gray,50, 255, ThresholdType.Binary);
// //CvInvoke.CvtColor(blur, gray, ColorConversion.Bgr2Gray);
// stepData = AddData(stepData, gray, "Threshold");
// CvInvoke.Canny(imgg, canny, 100, 50, 3, false);
// CannyImgTemp = canny.ToImage<Gray, byte>();
// stepData = AddData(stepData, gray, "canny");
// //Find the Rectangle
// using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
// {
// using (VectorOfPoint approxContour = new VectorOfPoint())
// {
// //hierachy = CvInvoke.FindContourTree(canny, contours, ChainApproxMethod.ChainApproxSimple);
// CvInvoke.FindContours(canny, contours, null, RetrType.List, ChainApproxMethod.ChainApproxSimple);
// //for (int i = 0; i < hierachy.GetLength(0); i++)
// int count = contours.Size;
// for (int i = 0; i < count; i++)
// {
// CvInvoke.ApproxPolyDP(contours[i], approxContour, CvInvoke.ArcLength(contours[i], true) * 0.05, true);
// if (CvInvoke.ContourArea(approxContour, false) > 250)
// {
// // if (approxContour.Size <=6) //The contour has 4 vertices.
// // {
// //#region determine if all the angles in the contour are within [80, 100] degree
// //bool isRectangle = true;
// //Point[] pts = approxContour.ToArray();
// //LineSegment2D[] edges = PointCollection.PolyLine(pts, true);
// //for (int j = 0; j < edges.Length; j++)
// //{
// // double angle = Math.Abs(
// // edges[(j + 1) % edges.Length].GetExteriorAngleDegree(edges[j]));
// // if (angle < 80 || angle > 100)
// // {
// // isRectangle = false;
// // break;
// // }
// //}
// //#endregion
// //if (isRectangle)
// boxList.Add(CvInvoke.MinAreaRect(approxContour));
// // }
// }
// }
// }
// }
// }
// }
//}
//foreach (RotatedRect boxr in boxList)
//{
// CvInvoke.Polylines(tempImg, Array.ConvertAll(boxr.GetVertices(), Point.Round), true,
// new Bgr(Color.DarkOrange).MCvScalar, 2);
//}
//Mat pI = tempImg.Mat;
//stepData = AddData(stepData, pI, "Poly");
#endregion
return(View("Index", stepData));
}
public IActionResult Steps(StepData uploadFile)
{
StepData stepData = new StepData();
ProcessCaptured processCaptured = new ProcessCaptured();
Image <Bgra, Byte> imgg = null;
Mat finalImg = new Mat();
using (MemoryStream ms = new MemoryStream())
{
if (ms != null)
{
CvInvoke.UseOpenCL = true;
uploadFile.FormFile.CopyTo(ms);
byte[] fileBytes = ms.ToArray();
imgg = processCaptured.GetImageFromStream(ms);
finalImg = imgg.Mat.Clone();
stepData = AddData(stepData, finalImg, "Orginal");
using (Mat im = imgg.Mat)
{
using (Mat threshold = new Mat())
{
using (Mat gray = new Mat())
{
using (Mat canny = new Mat())
{
using (Mat rectImg = new Mat())
{
CvInvoke.Threshold(im, threshold, 100, 255, ThresholdType.BinaryInv);
stepData = AddData(stepData, threshold, "Threshold");
CvInvoke.CvtColor(threshold, gray, ColorConversion.Bgr2Gray);
stepData = AddGrayData(stepData, gray, "Gray");
CvInvoke.Canny(gray, canny, 100, 50, 7);
stepData = AddData(stepData, canny, "Canny");
List <RotatedRect> rect = new List <RotatedRect>();
rect = Contours(canny);
if (rect != null && rect.Count > 0)
{
foreach (RotatedRect boxr in rect)
{
CvInvoke.Polylines(finalImg, Array.ConvertAll(boxr.GetVertices(), Point.Round), true,
new Bgr(Color.DarkOrange).MCvScalar, 2);
}
}
stepData = AddData(stepData, finalImg, "With Rectangle");
List <Mat> mat = RoI(rect, gray);
int i = 0;
//OCR
string path = AppContext.BaseDirectory;
Tesseract _ocr = new Tesseract(path, "eng", OcrEngineMode.TesseractLstmCombined);
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
foreach (Mat m in mat)
{
i += 1;
_ocr.SetImage(m);
_ocr.Recognize();
Tesseract.Character[] words = _ocr.GetCharacters();
//string wor=words.
StringBuilder sb = new StringBuilder();
foreach (var c in words)
{
sb.Append(c.Text);
}
stepData = AddData(stepData, m, i.ToString(), sb.ToString());
}
}
}
}
}
}
//Mat blur = new Mat();
//blur = Blur(im);
//stepData = AddData(stepData, blur, "Blur");
//Mat gray = new Mat();
//gray = Gray(blur);
//stepData = AddData(stepData, gray, "Gray");
//Mat threshold = new Mat();
//threshold = Threshold(im);
//stepData = AddData(stepData, threshold, "Threshold");
//Mat gray = new Mat();
//gray = Gray(threshold);
//stepData = AddGrayData(stepData, gray, "Gray");
//Mat canny = new Mat();
//canny = Canny(gray);
//stepData = AddData(stepData, canny, "Canny");
//List<RotatedRect> rect = new List<RotatedRect>();
//rect = Contours(canny);
//Mat rectImg = new Mat();
//rectImg = DrawRect(imgg.Mat, rect);
//stepData = AddData(stepData, rectImg, "With Rectangle");
//List<Mat> mat = RoI(rect, threshold.Clone());
//int i = 0;
//foreach (Mat m in mat)
//{
// i += 1;
// stepData = AddData(stepData, m, i.ToString());
//}
}
}
return(View("Index", stepData));
}
private static string GetTextFromRect(List <RotatedRect> rectangles, UMat grayRectImg)
{
//CvInvoke.Erode(grayRectImg, grayRectImg, null, new Point(-1, -1), 1, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
//CvInvoke.Dilate(grayRectImg, grayRectImg, null, new Point(-1, -1), 2, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
UMat pyr = new UMat();
CvInvoke.PyrDown(grayRectImg, pyr);
CvInvoke.PyrUp(pyr, grayRectImg);
string tag = String.Empty;
for (int i = 0; i < rectangles.Count; i++)
{
using (UMat tmp1 = new UMat())
using (UMat tmp2 = new UMat())
{
PointF[] srcCorners = rectangles[i].GetVertices();
PointF[] destCorners = new PointF[] {
new PointF(0, rectangles[i].Size.Height - 1),
new PointF(0, 0),
new PointF(rectangles[i].Size.Width - 1, 0),
new PointF(rectangles[i].Size.Width - 1, rectangles[i].Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(srcCorners, destCorners))
{
//Applies (применяет) an affine transformation to an image.
CvInvoke.WarpAffine(grayRectImg, tmp1, rot, Size.Round(rectangles[i].Size));
}
//ResizeAndShow("contourAfterAffine", tmp1);
Size approxSize = new Size(240, 180);
//resize the license plate such that the front is ~ 10-12.
//This size of front results in better accuracy (четко,правильно) from tesseract
double scale = Math.Min((double)approxSize.Width / tmp1.Size.Width, (double)approxSize.Height / tmp1.Size.Height);
Size newSize = new Size((int)Math.Round(tmp1.Size.Width * scale), (int)Math.Round(tmp1.Size.Height * scale));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
//CvInvoke.Imshow("3. Resize", tmp2);
//removes some pixels from the edge
int edgePixelSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
UMat tagRegion = new UMat(tmp2, newRoi);
tagRegion = FilterRegion(tmp2);
ResizeAndShow("TagRegion", tagRegion);
//Get the region of interest on the texts
InitOcr("", "eng", OcrEngineMode.TesseractOnly);
using (UMat textRegion = tagRegion.Clone())
{
_ocr.Recognize(textRegion);
Tesseract.Character[] ch = _ocr.GetCharacters();
//int maxHeight = -1;
//for (int j = 0; j < ch.Length; j++)
//{
// if (ch[j].Region.Height > maxHeight)
// maxHeight = ch[j].Region.Height;
//}
//tag += "GetCharacters: ";
for (int j = 0; j < ch.Length; j++)
{
//if (0.75 * maxHeight <= ch[j].Region.Height && ch[j].Region.Height <= 1.25 * maxHeight)
//{
tag += ch[j].Text;
//}
}
tag += "\n";
}
}
}
return(tag);
}
private string OcrImage(Tesseract ocr, Mat image, OCRMode mode, Mat imageColor)
{
Bgr drawCharColor = new Bgr(Color.Red);
if (image.NumberOfChannels == 1)
{
CvInvoke.CvtColor(image, imageColor, ColorConversion.Gray2Bgr);
}
else
{
image.CopyTo(imageColor);
}
if (mode == OCRMode.FullPage)
{
ocr.SetImage(imageColor);
if (ocr.Recognize() != 0)
{
throw new Exception("Failed to recognizer image");
}
Tesseract.Character[] characters = ocr.GetCharacters();
if (characters.Length == 0)
{
Mat imgGrey = new Mat();
CvInvoke.CvtColor(image, imgGrey, ColorConversion.Bgr2Gray);
Mat imgThresholded = new Mat();
CvInvoke.Threshold(imgGrey, imgThresholded, 65, 255, ThresholdType.Binary);
ocr.SetImage(imgThresholded);
characters = ocr.GetCharacters();
imageColor = imgThresholded;
if (characters.Length == 0)
{
CvInvoke.Threshold(image, imgThresholded, 190, 255, ThresholdType.Binary);
ocr.SetImage(imgThresholded);
characters = ocr.GetCharacters();
imageColor = imgThresholded;
}
}
foreach (Tesseract.Character c in characters)
{
CvInvoke.Rectangle(imageColor, c.Region, drawCharColor.MCvScalar);
}
return(ocr.GetUTF8Text());
}
else
{
bool checkInvert = true;
Rectangle[] regions;
using (ERFilterNM1 er1 = new ERFilterNM1("trained_classifierNM1.xml", 8, 0.00025f, 0.13f, 0.4f, true, 0.1f))
using (ERFilterNM2 er2 = new ERFilterNM2("trained_classifierNM2.xml", 0.3f))
{
int channelCount = image.NumberOfChannels;
UMat[] channels = new UMat[checkInvert ? channelCount * 2 : channelCount];
for (int i = 0; i < channelCount; i++)
{
UMat c = new UMat();
CvInvoke.ExtractChannel(image, c, i);
channels[i] = c;
}
if (checkInvert)
{
for (int i = 0; i < channelCount; i++)
{
UMat c = new UMat();
CvInvoke.BitwiseNot(channels[i], c);
channels[i + channelCount] = c;
}
}
VectorOfERStat[] regionVecs = new VectorOfERStat[channels.Length];
for (int i = 0; i < regionVecs.Length; i++)
{
regionVecs[i] = new VectorOfERStat();
}
try
{
for (int i = 0; i < channels.Length; i++)
{
er1.Run(channels[i], regionVecs[i]);
er2.Run(channels[i], regionVecs[i]);
}
using (VectorOfUMat vm = new VectorOfUMat(channels))
{
regions = ERFilter.ERGrouping(image, vm, regionVecs, ERFilter.GroupingMethod.OrientationHoriz,
"trained_classifier_erGrouping.xml", 0.5f);
}
}
finally
{
foreach (UMat tmp in channels)
{
if (tmp != null)
{
tmp.Dispose();
}
}
foreach (VectorOfERStat tmp in regionVecs)
{
if (tmp != null)
{
tmp.Dispose();
}
}
}
Rectangle imageRegion = new Rectangle(Point.Empty, imageColor.Size);
for (int i = 0; i < regions.Length; i++)
{
Rectangle r = ScaleRectangle(regions[i], 1.1);
r.Intersect(imageRegion);
regions[i] = r;
}
}
List <Tesseract.Character> allChars = new List <Tesseract.Character>();
String allText = String.Empty;
foreach (Rectangle rect in regions)
{
using (Mat region = new Mat(image, rect))
{
ocr.SetImage(region);
if (ocr.Recognize() != 0)
{
throw new Exception("Failed to recognize image");
}
Tesseract.Character[] characters = ocr.GetCharacters();
//convert the coordinates from the local region to global
for (int i = 0; i < characters.Length; i++)
{
Rectangle charRegion = characters[i].Region;
charRegion.Offset(rect.Location);
characters[i].Region = charRegion;
}
allChars.AddRange(characters);
allText += ocr.GetUTF8Text() + Environment.NewLine;
}
}
Bgr drawRegionColor = new Bgr(Color.Red);
foreach (Rectangle rect in regions)
{
CvInvoke.Rectangle(imageColor, rect, drawRegionColor.MCvScalar);
}
foreach (Tesseract.Character c in allChars)
{
CvInvoke.Rectangle(imageColor, c.Region, drawCharColor.MCvScalar);
}
return(allText);
}
}
public StepData StepsVideo(string uploadFile)
{
StepData stepData = new StepData();
ProcessCaptured processCaptured = new ProcessCaptured();
Image <Bgra, Byte> imgg = null;
Mat finalImg = new Mat();
if (!string.IsNullOrWhiteSpace(uploadFile))
{
byte[] fileBytes = Convert.FromBase64String(uploadFile);
using (MemoryStream ms = new MemoryStream(fileBytes))
{
imgg = processCaptured.GetImageFromStream(ms);
finalImg = imgg.Mat.Clone();
//stepData = AddData(stepData, finalImg.Clone(), "Orginal");
using (Mat im = imgg.Mat.Clone())
{
using (Mat threshold = new Mat())
{
using (Mat gray = new Mat())
{
using (Mat canny = new Mat())
{
using (Mat rectImg = new Mat())
{
CvInvoke.Threshold(im, threshold, 100, 255, ThresholdType.BinaryInv);
//stepData = AddData(stepData, threshold, "Threshold");
CvInvoke.CvtColor(threshold, gray, ColorConversion.Bgr2Gray);
//stepData = AddGrayData(stepData, gray, "Gray");
CvInvoke.Canny(gray, canny, 100, 50, 7);
//stepData = AddData(stepData, canny, "Canny");
List <RotatedRect> rect = new List <RotatedRect>();
rect = Contours(canny);
if (rect != null && rect.Count > 0)
{
foreach (RotatedRect boxr in rect)
{
CvInvoke.Polylines(finalImg, Array.ConvertAll(boxr.GetVertices(), Point.Round), true,
new Bgr(Color.DarkOrange).MCvScalar, 2);
}
}
//stepData = AddData(stepData, finalImg, "With Rectangle");
List <Mat> mat = RoI(rect, gray);
int i = 0;
//OCR
string path = AppContext.BaseDirectory;
Tesseract _ocr = new Tesseract(path, "eng", OcrEngineMode.TesseractLstmCombined);
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890");
foreach (Mat m in mat)
{
i += 1;
_ocr.SetImage(m);
_ocr.Recognize();
Tesseract.Character[] words = _ocr.GetCharacters();
//string wor=words.
StringBuilder sb = new StringBuilder();
foreach (var c in words)
{
sb.Append(c.Text);
}
if (sb.Length > 3 && sb.Length <= 10)
{
stepData = AddData(stepData, m, i.ToString(), sb.ToString());
}
}
}
}
}
}
}
}
}
//return View("Index", stepData);
finalImg = null;
return(stepData);
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat src = capture.QueryFrame();
imageBox1.Image = src;
if (isOstu == true)
{
Size sz = src.Size;
Mat[] mat = src.Split();
Mat dst = new Mat(sz, DepthType.Cv8U, 1);
CvInvoke.CvtColor(src, dst, ColorConversion.Bgr2Gray);
CvInvoke.Threshold(dst, dst, 0, 255, ThresholdType.Binary | ThresholdType.Otsu);
imageBox2.Image = dst;
}
else if (isGray == true)
{
Size sz = src.Size;
Mat[] mat = src.Split();
Mat dst = new Mat(sz, DepthType.Cv8U, 1);
CvInvoke.CvtColor(src, dst, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
//CvInvoke.Threshold(dst, dst, 0, 255, ThresholdType.Binary | ThresholdType.Otsu);
imageBox2.Image = dst;
}
else if (isSobel == true)
{
int scale = 1;
int delta = 0;
Size sz = src.Size;
Mat[] mat = src.Split();
Mat gray = new Mat(sz, DepthType.Cv8U, 1);
Mat grad = new Mat(sz, DepthType.Cv8U, 1);
Mat grad_x = new Mat(sz, DepthType.Cv8U, 1), grad_y = new Mat(sz, DepthType.Cv8U, 1);
Mat abs_grad_x = new Mat(sz, DepthType.Cv8U, 1), abs_grad_y = new Mat(sz, DepthType.Cv8U, 1);
CvInvoke.CvtColor(src, gray, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
CvInvoke.Sobel(gray, grad_x, Emgu.CV.CvEnum.DepthType.Cv16S, 1, 0, 3, scale, delta, Emgu.CV.CvEnum.BorderType.Default);
CvInvoke.ConvertScaleAbs(grad_x, abs_grad_x, 1.0, 0.0);
CvInvoke.Sobel(gray, grad_y, Emgu.CV.CvEnum.DepthType.Cv16S, 0, 1, 3, scale, delta, Emgu.CV.CvEnum.BorderType.Default);
CvInvoke.ConvertScaleAbs(grad_y, abs_grad_y, 1.0, 0.0);
CvInvoke.AddWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
imageBox2.Image = grad;
}
else if (isCanny == true)
{
Size sz = src.Size;
Mat[] mat = src.Split();
Mat dst = new Mat(sz, DepthType.Cv8U, 1);
CvInvoke.CvtColor(src, dst, ColorConversion.Bgr2Gray);
CvInvoke.Canny(dst, dst, 50, 150, 3);
//CvInvoke.Threshold(dst, dst, 0, 255, ThresholdType.Binary | ThresholdType.Otsu);
imageBox2.Image = dst;
}
else if (isMedianBlur == true)
{
Size sz = src.Size;
Mat[] mat = src.Split();
Mat dst = new Mat(sz, DepthType.Cv8U, 3);
CvInvoke.MedianBlur(src, dst, 5);
imageBox2.Image = dst;
}
else if (isOcr == true)
{
Image <Bgr, byte> img;
img = new Image <Bgr, byte>(imageBox1.Image.Bitmap);
//imgEntrada.Draw(Rect, new Bgr(Color.Red), 3);
img.ROI = Rect;
Tesseract tess;
//tess = new Tesseract("tessdata", "eng", Tesseract.OcrEngineMode.OEM_TESSERACT_CUBE_COMBINED);
tess = new Tesseract(@"tessdata\", "eng", OcrEngineMode.TesseractLstmCombined);
tess.SetVariable("tessedit_char_whitelist", "1234567890");
Tesseract.Character[] words;
Mat dst = new Mat(img.Size, DepthType.Cv8U, 1);
CvInvoke.CvtColor(img.Mat, dst, ColorConversion.Bgr2Gray);
//CvInvoke.Threshold(dst, dst, 0, 255, ThresholdType.Binary | ThresholdType.Otsu);
CvInvoke.Canny(dst, dst, 50, 150, 3);
//threshold(dst1, dst2, 128, 255, THRESH_BINARY_INV);
CvInvoke.Threshold(dst, dst, 128, 255, ThresholdType.BinaryInv);
tess.SetImage(dst);
tess.Recognize();
words = tess.GetCharacters();
imageBox2.Image = dst;
txtOcr.Text = tess.GetUTF8Text();
}
else
{
imageBox2.Image = src;
}
}
private void FindLicensePlate(
VectorOfVectorOfPoint contours, int[,] hierachy, int idx, IInputArray gray, IInputArray canny,
List <IInputOutputArray> licensePlateImagesList, List <IInputOutputArray> filteredLicensePlateImagesList, List <RotatedRect> detectedLicensePlateRegionList,
List <String> licenses)
{
for (; idx >= 0; idx = hierachy[idx, 0])
{
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
//if it does not contains any children (charactor), it is not a license plate region
if (numberOfChildren == 0)
{
continue;
}
using (VectorOfPoint contour = contours[idx])
{
if (CvInvoke.ContourArea(contour) > 400)
{
if (numberOfChildren < 3)
{
//If the contour has less than 3 children, it is not a license plate (assuming license plate has at least 3 charactor)
//However we should search the children of this contour to see if any of them is a license plate
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
continue;
}
RotatedRect box = CvInvoke.MinAreaRect(contour);
if (box.Angle < -45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle += 90.0f;
}
else if (box.Angle > 45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle -= 90.0f;
}
double whRatio = (double)box.Size.Width / box.Size.Height;
if (!(3.0 < whRatio && whRatio < 10.0))
//if (!(1.0 < whRatio && whRatio < 2.0))
{
//if the width height ratio is not in the specific range,it is not a license plate
//However we should search the children of this contour to see if any of them is a license plate
//Contour<Point> child = contours.VNext;
if (hierachy[idx, 2] > 0)
{
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
}
continue;
}
using (UMat tmp1 = new UMat())
using (UMat tmp2 = new UMat())
{
PointF[] srcCorners = box.GetVertices();
PointF[] destCorners = new PointF[] {
new PointF(0, box.Size.Height - 1),
new PointF(0, 0),
new PointF(box.Size.Width - 1, 0),
new PointF(box.Size.Width - 1, box.Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(srcCorners, destCorners))
{
CvInvoke.WarpAffine(gray, tmp1, rot, Size.Round(box.Size));
}
//resize the license plate such that the front is ~ 10-12. This size of front results in better accuracy from tesseract
Size approxSize = new Size(240, 180);
double scale = Math.Min(approxSize.Width / box.Size.Width, approxSize.Height / box.Size.Height);
Size newSize = new Size((int)Math.Round(box.Size.Width * scale), (int)Math.Round(box.Size.Height * scale));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
//removes some pixels from the edge
int edgePixelSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
UMat plate = new UMat(tmp2, newRoi);
UMat filteredPlate = FilterPlate(plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (UMat tmp = filteredPlate.Clone())
{
_ocr.Recognize(tmp);
words = _ocr.GetCharacters();
if (words.Length == 0)
{
continue;
}
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
licenses.Add(strBuilder.ToString());
licensePlateImagesList.Add(plate);
filteredLicensePlateImagesList.Add(filteredPlate);
detectedLicensePlateRegionList.Add(box);
}
}
}
}
}
private void FindLicensePlate(
VectorOfVectorOfPoint contours, int[,] hierachy, int idx, Image <Gray, Byte> gray, Mat canny,
List <Image <Gray, Byte> > licensePlateImagesList, List <Image <Gray, Byte> > filteredLicensePlateImagesList, List <RotatedRect> detectedLicensePlateRegionList,
List <String> licenses)
{
for (; idx >= 0; idx = hierachy[idx, 0])
{
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
//if it does not contains any children (charactor), it is not a license plate region
if (numberOfChildren == 0)
{
continue;
}
using (VectorOfPoint contour = contours[idx])
{
if (CvInvoke.ContourArea(contour) > 400)
{
if (numberOfChildren < 3)
{
//If the contour has less than 3 children, it is not a license plate (assuming license plate has at least 3 charactor)
//However we should search the children of this contour to see if any of them is a license plate
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
continue;
}
RotatedRect box = CvInvoke.MinAreaRect(contour);
if (box.Angle < -45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle += 90.0f;
}
else if (box.Angle > 45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle -= 90.0f;
}
double whRatio = (double)box.Size.Width / box.Size.Height;
if (!(3.0 < whRatio && whRatio < 10.0))
//if (!(1.0 < whRatio && whRatio < 2.0))
{
//if the width height ratio is not in the specific range,it is not a license plate
//However we should search the children of this contour to see if any of them is a license plate
//Contour<Point> child = contours.VNext;
if (hierachy[idx, 2] > 0)
{
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
}
continue;
}
using (Image <Gray, Byte> tmp1 = gray.Copy(box))
//resize the license plate such that the front is ~ 10-12. This size of front results in better accuracy from tesseract
using (Image <Gray, Byte> tmp2 = tmp1.Resize(240, 180, Emgu.CV.CvEnum.Inter.Cubic, true))
{
//removes some pixels from the edge
int edgePixelSize = 2;
tmp2.ROI = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
Image <Gray, Byte> plate = tmp2.Copy();
Image <Gray, Byte> filteredPlate = FilterPlate(plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (Image <Gray, Byte> tmp = filteredPlate.Clone())
{
_ocr.Recognize(tmp);
words = _ocr.GetCharacters();
if (words.Length == 0)
{
continue;
}
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
licenses.Add(strBuilder.ToString());
licensePlateImagesList.Add(plate);
filteredLicensePlateImagesList.Add(filteredPlate);
detectedLicensePlateRegionList.Add(box);
}
}
}
}
}
public Tesseract.Character[] recognize(IInputArray image)
{
ocr.SetImage(image);
ocr.Recognize();
return(ocr.GetCharacters());
}
public StepData StepsVideo(string uploadFile)
{
StepData stepData = new StepData();
ProcessCaptured processCaptured = new ProcessCaptured();
Image <Bgra, Byte> imgg = null;
if (!string.IsNullOrWhiteSpace(uploadFile))
{
var element = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(22, 3), new Point(1, 1));
byte[] fileBytes = Convert.FromBase64String(uploadFile);
using (MemoryStream ms = new MemoryStream(fileBytes))
{
imgg = processCaptured.GetImageFromStream(ms);
Mat finalImg = new Mat();
using (Mat im = imgg.Mat.Clone())
{
using (Mat blur = new Mat())
{
using (Mat gray = new Mat())
{
using (Mat sobal = new Mat())
{
using (Mat threshold = new Mat())
{
using (Mat morpology = new Mat())
{
using (Mat canny = new Mat())
{
Size size = new Size(7, 7);
CvInvoke.Threshold(im, threshold, 100, 255, ThresholdType.Binary);
//CvInvoke.GaussianBlur(im, blur, size, 0);
CvInvoke.CvtColor(im, gray, ColorConversion.Bgr2Gray);
//CvInvoke.Sobel(gray, sobal, DepthType.Cv8U, 1, 0, 3);
//CvInvoke.Threshold(sobal, threshold, 0, 255, ThresholdType.Otsu);
//CvInvoke.MorphologyEx(gray, morpology, MorphOp.Close, element, new Point(0, 0), 1, BorderType.Default, new MCvScalar());
CvInvoke.Canny(gray, canny, 100, 50, 7);
finalImg = im.Clone();
var box = Contours(canny);
//Mat mat=DrawRect(finalImg, box);
List <Mat> roi = RoI(box, finalImg);
string path = AppContext.BaseDirectory;
using (Tesseract _ocr = new Tesseract(path, "eng", OcrEngineMode.TesseractLstmCombined))
{
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890");
foreach (Mat m in roi)
{
_ocr.SetImage(m);
_ocr.Recognize();
Tesseract.Character[] words = _ocr.GetCharacters();
//string wor=words.
StringBuilder sb = new StringBuilder();
foreach (var c in words)
{
sb.Append(c.Text);
}
string strTemp = sb.ToString().Replace(" ", "");
if (strTemp.ToString().Length > 3 && strTemp.Length <= 10)
{
stepData = AddData(stepData, m, "", strTemp);
}
}
}
}
}
}
}
}
}
}
}
}
imgg = null;
return(stepData);
}