Распознавание автомобильных номеров

#include "opencv2/opencv.hpp"
#include <vector>
#include <string>
#include <tesseract/baseapi.h>
using namespace std;
using namespace cv;
using namespace tesseract;
 
int main()
{
    // Указываем путь к данным для Tesseract
    string tessdataPath = "D://cv//car//packages//Tesseract-OCR.1.0.4//content//Tesseract-OCR//tessdata";
    CascadeClassifier cascade;
    cascade.load("D://cv//opencv//sources//data//haarcascades//haarcascade_russian_plate_number.xml");
    string car_image = "C://Users//HP//Desktop//курсач цои//image2.jpg";
    Mat image = imread(car_image, IMREAD_COLOR);
    Mat gray;
    cvtColor(image, gray, COLOR_BGR2GRAY);
    Mat blurredImage;
    GaussianBlur(gray, blurredImage, Size(5, 5), 0);
    Mat Imagebest;
    equalizeHist(blurredImage, Imagebest);
    Mat img_thresh;
    adaptiveThreshold(Imagebest, img_thresh, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 11, 2);
    vector<Rect> licence_plates;
    cascade.detectMultiScale(img_thresh, licence_plates, 1.2, 3, 0, Size(150, 30));
    TessBaseAPI tess;
    tess.Init(tessdataPath.c_str(), "eng+rus", OEM_DEFAULT);
    tess.SetPageSegMode(PSM_SINGLE_LINE);
    for (int i = 0; i < licence_plates.size(); i++)
    {
        rectangle(image, licence_plates[i], Scalar(255, 0, 0), 3, 8, 0);
        Mat plateROI = gray(licence_plates[i]);
        Mat tempImage;
        threshold(plateROI, tempImage, 0, 255, THRESH_BINARY | THRESH_OTSU);
        tess.SetImage(tempImage.data, tempImage.cols, tempImage.rows, 1, tempImage.cols);
        tess.Recognize(0);
        const char* licensePlateText = tess.GetUTF8Text();
        Point textLocation(licence_plates[i].x, licence_plates[i].y - 5);
        putText(image, licensePlateText, textLocation, FONT_HERSHEY_SIMPLEX, 0.8, Scalar(0, 255, 0), 2);
    }
    imshow("licence plate", image);
    imwrite("result.tif", image);
 
    waitKey(0);
    return 0;
}