通过OpenCV中的矩形检测查找坐标

Question

我使用了互联网上某人的密码。我正在尝试从图像中找到矩形坐标。我成功地在图像中找到矩形并在其上绘制线条。经过这些过程后，我尝试从图像中的每个矩形中找到坐标 例如[x1：1，y1：1]，[x2：1，y2：2] .... [x4：4，y4：6]

这是我的项目工作方式的图片 https://i.imgur.com/oB5tYac.jpg

这是我想要我的项目工作的图像： https://i.imgur.com/QkFbCgN.jpg

我认为如果可以使用数组“ approx”，那就有解决方案。 也许没有..请帮助我。

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

using namespace cv;
using namespace std;

void CallBackFunc(int event, int x, int y, int flags, void* userdata) {

    if (event == EVENT_LBUTTONDOWN)
        printf("LBUTTON_DOWN down %d %d \n", x, y);
    else if (event == EVENT_RBUTTONDOWN)
        printf("RBUTTON_DOWN down %d %d \n", x, y);
    else if (event == EVENT_MBUTTONDOWN)
        printf("MBUTTON_DOWN down %d %d \n", x, y);


}

//Contour 영역 내에 텍스트 쓰기 

void setLabel(Mat& image, string str, vector<Point> contour)
{
    int fontface = FONT_HERSHEY_SIMPLEX;
    double scale = 0.5;
    int thickness = 1;
    int baseline = 0;

    Size text = getTextSize(str, fontface, scale, thickness, &baseline);
    Rect r = boundingRect(contour);

    Point pt(r.x + ((r.width - text.width) / 2), r.y + ((r.height + text.height) / 2));
    rectangle(image, pt + Point(0, baseline), pt + Point(text.width, -text.height), CV_RGB(200, 200, 200), FILLED);
    putText(image, str, pt, fontface, scale, CV_RGB(0, 0, 0), thickness, 8);

    printf("x값 : %d\n",r.x);
    printf("y값 : %d\n", r.y);
}



int main(int, char**)
{
    Mat img_input, img_result, img_gray;

    //이미지파일을 로드하여 image에 저장  
    img_input = imread("pipe.jpg", IMREAD_COLOR);
    if (img_input.empty())
    {
        cout << "Could not open or find the image" << std::endl;
        return -1;
    }
    resize(img_input, img_input, Size(0, 0), 0.25, 0.25, INTER_LINEAR);


    //그레이스케일 이미지로 변환  
    cvtColor(img_input, img_gray, COLOR_BGR2GRAY);

    //이진화 이미지로 변환
    Mat binary_image;
    threshold(img_gray, img_gray, 128, 255, THRESH_BINARY_INV | THRESH_OTSU);

    //contour를 찾는다.
    vector<vector<Point> > contours;
    findContours(img_gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

    //contour를 근사화한다.
    vector<Point2f> approx;
    img_result = img_input.clone();

    for (size_t i = 0; i < contours.size(); i++)
    {
        approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true) * 0.02, true);

        if (fabs(contourArea(Mat(approx))) > 400)  {

            int size = approx.size();

            //Contour를 근사화한 직선을 그린다.
            if (size % 2 == 0) {
                line(img_result, approx[0], approx[approx.size() - 1], Scalar(0, 255, 0), 1);

                for (int k = 0; k < size - 1; k++)
                    line(img_result, approx[k], approx[k + 1], Scalar(0, 255, 0), 1);

                for (int k = 0; k < size; k++){
                    circle(img_result, approx[k], 3, Scalar(0, 0, 255));

                }
            }
            else {
                line(img_result, approx[0], approx[approx.size() - 1], Scalar(0, 255, 0), 1);

                for (int k = 0; k < size - 1; k++)
                    line(img_result, approx[k], approx[k + 1], Scalar(0, 255, 0), 1);

                for (int k = 0; k < size; k++){
                    circle(img_result, approx[k], 3, Scalar(0, 0, 255)); 

                }

            }



            //도형을 판정한다.
            if (size == 3)
                setLabel(img_result, "triangle", contours[i]); //삼각형

            //이하는 해당 꼭지점을 가진 convex라면 찾는 도형
            else if (size == 4 && isContourConvex(Mat(approx)))
                setLabel(img_result, "rectangle", contours[i]); //사각형

            else if (size == 5 && isContourConvex(Mat(approx)))
                setLabel(img_result, "pentagon", contours[i]); //오각형

            else if (size == 6 && isContourConvex(Mat(approx)))
                setLabel(img_result, "hexagon", contours[i]);  //육각형

            else if (size == 10 && isContourConvex(Mat(approx)))
                setLabel(img_result, "decagon", contours[i]);    //십각형

        }

    }
    namedWindow("img", 0);
    setMouseCallback("img", CallBackFunc, NULL);







    imshow("input", img_input);
    imshow("img", img_result);


    waitKey(0);
    destroyAllWindows();


    return 0;
}