Question

所以我将同一个文件夹复制到两台不同的机器上，一台在Python上运行OpenCV，另一台机器在C ++上运行OpenCV。我实际上是将Python代码转换为C ++，我遇到了这个奇异的问题，其中Hough Circle探测器的输出不一样。

C ++的输出：

Radius min = 752
Radius max = 846
Total number of circles detected = 3
Circle - x: 1325.5  y: 1094.5 Radius: 759.537
Circle - x: 877.5  y: 1077.5 Radius: 790.734
Circle - x: 896.5  y: 512.5 Radius: 806.832

Python的输出：

Rmin = 752
Rmax = 846
[[[1326.5        1075.5           752.5333...]
  [896.5          512.5           806.8323...]
  [877.5         1077.5           790.7341...]]]

C ++来源：

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <string>
#include <iostream>
#include <math.h>
#include <vector>
#include <algorithm>

#define IMAGE_ROW 1882
struct O_HC{
    //return types known
    int circle[3];
    int circlesExist;
}outHC;
int main(string FILENAME)
{

    //something 
    Mat RGBimg = imread(FILENAME, CV_LOAD_IMAGE_COLOR);
    //something something
    if(! RGBimg.data)
    {
        std::cout << "Could not load image" << std::endl; 
    }
    else
    {
        /*
        //THIS PIECE OF CODE SHOWS THE IMAGE IN A WINDOW
        namedWindow("DisplayWindow", WINDOW_AUTOSIZE);
        imshow("DisplayWindow", RGBimg);
        waitKey(0);
        */

        //Code not involving RGBimg 
        outHC = houghcircles(RGBimg); 

    }
    return 0;

}

O_HC houghcircles(Mat RGBimg)
{
    vector<Vec3f> circles;

    cvtColor(RGBimg, GrayImg, CV_BGR2GRAY);
    Size size(t_cols * IMAGE_ROW / t_rows, IMAGE_ROW);
    resize(GrayImg, ResizedImg, size);

    std::cout << "t_cols : " << ResizedImg.cols << std::endl;
    std::cout << "t_rows : " << ResizedImg.rows << std::endl;
    t_rows = ResizedImg.rows;
    t_cols = ResizedImg.cols;

    medianBlur(ResizedImg, BlurredImg, 5);
    black_circle_radius_low = (int) (0.4 * std::min(t_rows,t_cols));
    black_circle_radius_upper = (int) (0.45 * std::min(t_rows,t_cols));

    std::cout << "Radius min = " << black_circle_radius_low << '\n';
    std::cout << "Radius max = " << black_circle_radius_upper << '\n';

    HoughCircles(BlurredImg, circles, CV_HOUGH_GRADIENT, 1, 300, 30, 30, black_circle_radius_low, black_circle_radius_upper);

    std::cout << "Total number of circles detected = " << circles.size() << std::endl;

    if(circles.size() == 0)
    {
         outHC.circlesExist = 0;
         outHC.circle[0] = 0;
         outHC.circle[1] = 0;
         outHC.circle[2] = 0;
    }
    else
    {
         outHC.circlesExist = 1;
         for( size_t i = 0; i < circles.size(); i++ )
         {
            std::cout << "Circle - x: " << circles[i][0] << "  y: " << circles[i][1] << " Radius: " << circles[i][2] << '\n';
              //Something else
         }
         outHC.circle[0] = (int)circles[0][0];
         outHC.circle[1] = (int)circles[0][1];
         outHC.circle[2] = (int)circles[0][2];
   }
   return outHC; 
}

Python代码：

    import cv2
    import cv2.cv as cv
    IMAGE_ROW = 1882
    img = cv2.imread(filename, 0)    
    [t_rows,t_cols]= img.shape
    img = cv2.resize(img, (t_cols*IMAGE_ROW/t_rows,IMAGE_ROW))
    img = cv2.medianBlur(img, 5)

    [t_rows,t_cols]=img.shape        
    limit=min(t_rows,t_cols)
    black_circle_radius_low=int(0.4*limit)
    black_circle_radius_upper=int(0.45*limit)
    circles = cv2.HoughCircles(img,cv.CV_HOUGH_GRADIENT,1,300,param1=30,param2=30,minRadius=black_circle_radius_low,maxRadius=black_circle_radius_upper)
    print circles

正如我们所看到的，第一个圆圈对于不同的语言是不同的。有没有人知道为什么会这样？

干杯。

PS： OpenCV 2.4.11 随Python一起安装， OpenCV 2.4.13 随C ++一起安装。如果重要，Python版本在Win7机器上运行，C ++版本在OS X Yosemite上运行。我不是那么精通Python，所以在这里和那里可能会出现一些语法错误。

编辑：

添加了一些代码以显示图像读取。

我的C ++ OpenCV Hough Circle Detection和我的Python OpenCV Hough Circle Detection的输出是不同的

0 个答案: