如何解决OpenCV中的分段错误
我最近开始使用C ++做一些图像处理工作,并且遇到了分割错误的问题。希望有人可以帮助我弄清楚发生了什么事?谢谢!!问题是,下面附加的代码可以正常工作,但是如果声明了“ vector roi_corners(4);”,更改为“向量roi_corners;”然后使用“ push_back()”和“ clear()”来更新向量,将会得到分割错误。有人可以帮我弄清楚这个问题的原因吗?谢谢!!
OpenCV版本:4.4.0
MacOS版本:10.14.5
可行代码
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
#include <vector>
#define PI 3.14159265
#define WINDOW "Image Correction"
using namespace std;
using namespace cv;
vector< Point2f> roi_corners(4);
vector< Point2f> dst_corners(4);
Mat img1;
Mat cache;
int roi_id;
void On_mouse(int event,int x,int y,int flags,void*);
int main(int argc,char const *argv[])
{
//import image
roi_id = 0;
img1 = imread("Board.jpg");
if ( img1.empty() )
{
cerr << "Please Import an Image!!" << endl;
}
int factor = 60;//for pixel adjustment
cache = img1.clone();//copy for retake points
imshow(WINDOW,img1);
/*Run the point taking procedure*/
while(true){
setMouseCallback(WINDOW,On_mouse,0);
char c = (char)waitKey( 10 );
if(c=='n') break;//press 'n' when determine the four point you want
if(c=='e') {roi_id=0; img1 = cache.clone();} //press 'e' to retake the foru point
}
/*For adjustment point estimation*/
dst_corners[0].x = roi_corners[0].x;
dst_corners[0].y = roi_corners[0].y;
dst_corners[1].x = roi_corners[0].x+factor*1;
dst_corners[1].y = roi_corners[0].y;
dst_corners[2].x = roi_corners[0].x+factor*1;
dst_corners[2].y = roi_corners[0].y+factor*1;
dst_corners[3].x = roi_corners[0].x;
dst_corners[3].y = roi_corners[0].y+factor*1;
Mat M = getPerspectiveTransform(roi_corners,dst_corners);
Mat warped_image;
/*Print the corrected picture*/
Size sz = cache.size();
warpPerspective(cache,warped_image,M,Size(sz.width,sz.height)); // do perspective transformation
imshow("Corrected Image",warped_image);
waitKey(0);
cout<<"complete"<<endl;
return 0;
}
void On_mouse(int event,void*)
{ imshow(WINDOW,img1);
if(roi_id<4){
if (event == EVENT_LBUTTONDOWN){
roi_corners[roi_id].x=x;
roi_corners[roi_id].y=y;
cout<<"The Point You Take is: "<<x<<' '<<y<<endl;
roi_id++;
circle(img1,Point(x,y),2,Scalar(0,255),LINE_8,0);
imshow(WINDOW,img1);
}
}
}
如果我这样修改代码,它将显示段错误
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
#include <vector>
#define PI 3.14159265
#define WINDOW "Image Correction"
using namespace std;
using namespace cv;
vector< Point2f> roi_corners;
vector< Point2f> dst_corners;
Mat img1;
Mat cache;
void On_mouse(int event,0);
char c = (char)waitKey( 10 );
if(c=='n') break;//press 'n' when determine the four point you want
if(c=='e') {roi_corner.clear(); img1 = cache.clone();} //press 'e' to retake the foru point
}
/*For adjustment point estimation*/
dst_corners[0].x = roi_corners[0].x;
dst_corners[0].y = roi_corners[0].y;
dst_corners[1].x = roi_corners[0].x+factor*1;
dst_corners[1].y = roi_corners[0].y;
dst_corners[2].x = roi_corners[0].x+factor*1;
dst_corners[2].y = roi_corners[0].y+factor*1;
dst_corners[3].x = roi_corners[0].x;
dst_corners[3].y = roi_corners[0].y+factor*1;
Mat M = getPerspectiveTransform(roi_corners,img1);
if(roi_corners.size()<4){
if (event == EVENT_LBUTTONDOWN){
roi_corners.push_back(Point2f(x,y));
cout<<"The Point You Take is: "<<x<<' '<<y<<endl;
circle(img1,img1);
}
}
}
解决方法
您的代码有两件事。您声明一个包含4个元素的向量,但不对其进行初始化。根据您的平台和数据类型,您可能会看到不希望的行为。尝试在同一行上声明和初始化向量:
std::vector<cv::Point2f> roi_corners( 4,cv::Point2f(0.0,0.0) );
当然,如果用初始容量(size
)和初始值声明向量,则可以使用std::vector<>::operator[]
索引每个元素:
roi_corners[0] = cv::Point2f( 1.0,2.0 );
roi_corners[1] = cv::Point2f( 3.0,4.0 );
roi_corners[2] = cv::Point2f( 5.0,6.0 );
roi_corners[3] = cv::Point2f( 7.0,8.0 );
通过声明具有初始大小的向量,您可以分配内存,该内存将用于store
和load
向量中的各个元素。现在,假设您不声明矢量的初始大小,而是使用push_back
随便添加元素:
//vector declaration with no initial size:
std::vector<cv::Point2f> roi_corners;
//store a new element into the vector:
roi_corners.push_back( cv::Point2f(1.0,2.0) );
很酷,您的向量存储了一个新元素,并且仅显示一项的容量。但是,您仍然可以这样做:
roi_corners[0] = cv::Point2f( 1.0,2.0 ); // data overwrite in position 0
roi_corners[1] = cv::Point2f( 3.0,4.0 ); // you haven't allocated memory for this yet!
Result: seg fault
推论:如果您有大小为N
的预定义矢量,则可以通过0
将元素从N
索引到std::vector<>::operator[]
,因为已分配内存以容纳所有N
元素。如果您尝试处理超出此范围的元素,则会看到seg fault
。
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