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

opencv基础笔记(1)