为了仔细掌握程明明CVPR 2014 oral文章:BING: Binarized Normed Gradients for Objectness Estimation at 300fps的代码,的好好学习opencv库啊,从基础走起!
(1)CV_Assert函数作用:
CV_Assert()若括号中的表达式值为false,则返回一个错误信息。
(2)Mat用法
1、使用准备:
using namespace cv;
2、Mat的声明
Mat m=Mat(rows, cols, type);
Mat m=Mat(Size(width,height), type);
Mat A=Mat(3,4,CV_32FC1);
Mat B=Mat(4,3,CV_32FC1);
3、Mat赋值
vector<Point3f>v;//suppose it is already full
Mat m1=Mat(v,true);//boolean value true is necessary in order to copy data from v to m1
CvMat *p1;
Mat m2=Mat(p1);
4、Mat之间运算
MatC=2*A*B;
Mat C=C.inv();//Now C is its own inverse matrix
Mat D=A.t();//D is the transposed matrix of A
Mat a=Mat(4,1, CV_32FC3);//a is 4x1, 3 channels
Mat b=a.reshape(1);//b is 4x3, 1 channel
5、单通道Mat元素读写
Mat a=Mat(4,3, CV_32FC1);
floatelem_a=a.at<float>(i,j);//access element aij, with i from 0 to rows-1 and j from 0 to cols-1
Point p=Point(x,y);
floatelem_a=a.at<float>(p);//Warning: y ranges from 0 to rows-1 and x from 0 to cols-1
6、多通道Mat元素读写
template<typename _Tp> _Tp& at(int y,int x); // cxcore.hpp (868)
template<typename _Tp>const _Tp& at(int y,int x)const; // cxcore.hpp (870)
template<typename _Tp> _Tp& at(Point pt); // cxcore.hpp (869)
template<typename _Tp>const _Tp& at(Point pt)const; // cxcore.hpp (871)
// defineded in cxmat.hpp (454-468)
typedefVec<float,2>Vec2f;// cxcore.hpp (254)
// we can access the element like this :
Mat m(Size(3,3), CV_32FC2 );
Vec2f& elem = m.at<Vec2f>( row , col );// or m.at<Vec2f>( Point(col,row) );
elem[0]=1212.0f;
elem[1]=326.0f;
float c1 = m.at<Vec2f>( row , col )[0];// or m.at<Vec2f>( Point(col,row) );
float c2 = m.at<Vec2f>( row , col )[1];
m.at<Vec2f>( row, col )[0]=1986.0f;
m.at<Vec2f>( row, col )[1]=326.0f;
7.选取Mat上指定区域方法
Mat src; Rect rect;
Mat dst = src(rect); 或者Mat dst(src,rect);
注意:cv::Mat A;
A.row(i) = A.row(j); // 错误
A.row(i) = A.row(j) + 0; // 正确
原文地址:http://blog.csdn.net/u013476464/article/details/40453399