Question

我有两个代码用OpenCV执行Hough变换。一位我的同事写道：

#include <cv.h>
#include <highgui.h>
#include <math.h>
#include <iostream>
using namespace std;

int main(int argc, char** argv)
{


int p[3]; 

    IplImage* src;
    if( argc == 2 && (src=cvLoadImage(argv[1], 0))!= 0)
    {
        IplImage* dst = cvCreateImage( cvGetSize(src), 8, 1 );
        IplImage* color_dst = cvCreateImage( cvGetSize(src), 8, 3 );
        CvMemStorage* storage = cvCreateMemStorage(0);
        CvSeq* lines = 0;
        int i;
        cvCanny( src, dst, 50, 200, 3 );
        cvCvtColor( dst, color_dst, CV_GRAY2BGR );
#if 1
        lines = cvHoughLines2( dst,
                               storage,
                               CV_HOUGH_STANDARD,
                               1,
                               CV_PI/180,
                               100,
                               0,
                               0 );
        cout << lines->total << "\n";
        for( i = 0; i < MIN(lines->total,100); i++ )
        {
            float* line = (float*)cvGetSeqElem(lines,i);
            float rho = line[0];
            float theta = line[1];
            CvPoint pt1, pt2;
            double a = cos(theta), b = sin(theta);
            double x0 = a*rho, y0 = b*rho;
            pt1.x = cvRound(x0 + 1000*(-b));
            pt1.y = cvRound(y0 + 1000*(a));
            pt2.x = cvRound(x0 - 1000*(-b));
            pt2.y = cvRound(y0 - 1000*(a));
            cvLine( color_dst, pt1, pt2, CV_RGB(255,0,0), 3, 8, 0);
        }
#else
        lines = cvHoughLines2( dst,
                               storage,
                               CV_HOUGH_PROBABILISTIC,
                               1,
                               CV_PI/180,
                               80,
                               30,
                               10 );
        cout << lines->total << "\n";
        for( i = 0; i < lines->total; i++ )
        {
            CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
            cvLine( color_dst, line[0], line[1], CV_RGB(255,0,0), 3, 8 );
        }
#endif
        cvNamedWindow( "Source", 1 );
        cvShowImage( "Source", src );

        cvNamedWindow( "Hough", 1 );
        cvShowImage( "Hough", color_dst );

    p[0] = 1;
        p[1] = 100;
        p[2] = 0;
        cvSaveImage("/tmp/hough.jpg", color_dst, 0);


        cvWaitKey(0);
    }
}

和python中的wiki OpenCv Python Wiki中的一个

import cv2
import numpy as np

img = cv2.imread('dave.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)

lines = cv2.HoughLines(edges,1,np.pi/180,100)
for rho,theta in lines[0]:
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a*rho
    y0 = b*rho
    x1 = int(x0 + 1000*(-b))
    y1 = int(y0 + 1000*(a))
    x2 = int(x0 - 1000*(-b))
    y2 = int(y0 - 1000*(a))

    cv2.line(img,(x1,y1),(x2,y2),(0,0,255),2)

cv2.imwrite('houghlines3.jpg',img)

用于标准方法和

import cv2
import numpy as np

img = cv2.imread('dave.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
minLineLength = 30
maxLineGap = 10
lines = cv2.HoughLinesP(edges,1,np.pi/180,80,minLineLength,maxLineGap)
for x1,y1,x2,y2 in lines[0]:
    cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)

cv2.imwrite('houghlines5.jpg',img)

用于概率方法（将#IF 1更改为c ++中的#IF 0以使用概率方法）。

问题是这两个代码有完全不同的行为，我无法弄清楚原因。 c ++中的那个给出了很好的结果，特别是对于概率方法，而不是python中的那个。有人知道为什么吗？

谢谢：）

OpenCV HoughLines不同的行为python c ++

0 个答案: