参考:b站某视频教程。
需要安装tesseract来识别文字。
python实现:
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++实现:
#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;
}