OpenCV license plate recognition

Reference: A video tutorial at station b.
Tesseract needs to be installed to recognize text.
Python implementation:

import cv2
import numpy as np
import pytesseract

plate = cv2.CascadeClassifier("haarcascade_russian_plate_number.xml")
img = cv2.imread("car.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

plates = plate.detectMultiScale(gray, 1.1, 3)
for (x,y,w,h) in plates:
    cv2.rectangle(img, (x,y), (x+w,y+h), (0,0,255), 2)

roi = gray[y:y+h, x:x+w]
thres, roi = cv2.threshold(roi, 0, 255, cv2.THRESH_OTSU)

res = pytesseract.image_to_string(roi, lang="chi_sim+eng",config="--psm 8 --oem 3")
print(res)

cv2.imshow("img",roi)
cv2.waitKey()

C++ implementation:

#include <iostream>
#include <opencv2/opencv.hpp>


int main(int argc, char** argv)
{
    
    
	cv::CascadeClassifier plate;
	plate.load("haarcascade_russian_plate_number.xml");

	cv::Mat img = cv::imread("car.png"), gray;
	cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);

	std::vector<cv::Rect> plates;
	plate.detectMultiScale(gray, plates, 1.1, 3);

	for (size_t i = 0; i < plates.size(); i++)
	{
    
    
		cv::rectangle(img, plates[i], cv::Scalar(0, 0, 255), 2);
		cv::Mat roi = gray(cv::Rect(plates[i]));
		cv::threshold(roi, roi, 0, 255, cv::THRESH_OTSU);
	}

	system("tesseract roi.png result");
	cv::imwrite("result.png", img);
	return 0;
}