记录：matlab 转C++和Opencv，用到的函数

Mat和vector的相互转化

转https://blog.csdn.net/guyuealian/article/details/80253066
/***************** Mat转vector **********************/
template
vector<_Tp> convertMat2Vector(const Mat &mat)
{
	return (vector<_Tp>)(mat.reshape(1, 1));//通道数不变，按行转为一行
}
 
/****************** vector转Mat *********************/
template
cv::Mat convertVector2Mat(vector<_Tp> v, int channels, int rows)
{
	cv::Mat mat = cv::Mat(v);//将vector变成单列的mat
	cv::Mat dest = mat.reshape(channels, rows).clone();//PS：必须clone()一份，否则返回出错
	return dest;
}
//velc.reshape(0, numelementsy);

vector 创建和初始化全为0

vector a(b.size(),0);
vector> a(b.size(), vector(c.size(), 0));
Mat:
Mat velcomp = Mat::zeros(numelementsy, numelementsx, CV_32F);

1、 repmat =repeat

Matlab： 
    x = repmat((min:step:max), num, 1)
Opencv:
    Mat x;
	vector xtemp,;
	for (int i = min; i < max+1;i=i+ step) {
		xtemp.push_back(i );
		x= Mat(xtemp).t();
	}
   x= repeat(x, num, 1);

2、fspecial（gaussian）=getGaussianKernel ，， imfilter=filter2D

Matlab：
        h=fspecial('gaussian',3,1);
        x=imfilter(x,h,'replicate');
Opencv：
		Mat kernel = getGaussianKernel(3, 1) * getGaussianKernel(3, 1).t();
		filter2D(x, x, -1, kernel, Point(-1, -1), 0.0, IPL_BORDER_REPLICATE);

3、interp2 =remap(三次样条插值)，这个不太对

Matlab：
    m=interp2(xold,yold,m,x,y,'*spline');
    用指定的算法method 计算二维插值：
    ’linear’：双线性插值算法(缺省算法);
    ’nearest’：最临近插值;
    ’spline’：三次样条插值;
    ’cubic’：双三次插值。
opencv:
    remap(m, m, x, y,INTER_CUBIC);
    INTER_NEAREST	最近邻插值
    INTER_LINEAR	双线性插值
    INTER_CUBIC	双三次插值

https://stackoverflow.com/questions/46692060/matlab-interp2-function-behaviour-differently-compared-with-opencv-remap

opencv需要减1，xold必须是0,1,2,3....，需要映射

4、padarray 填充

Matlab：
     x= padarray(x, [1,1], 'replicate');
    'replicate':边界，K：固定值
Opencv:
    //用K填充图像的边界RowPad上下扩充，ColPad左右扩充
    Mat PadArray(Mat Image, int RowPad, int ColPad,int K)
    {
	    int n = Image.rows;
	    int m = Image.cols;
	    Mat temp1 = Mat::zeros(n, m + ColPad * 2, Image.type());
	    Mat temp2 = Mat::zeros(n + RowPad * 2, m + ColPad * 2, Image.type());
	    Mat c1 = Mat(RowPad, m + ColPad * 2, CV_32F,K);
	    Mat c2 = Mat(n, ColPad, CV_32F,K);

	    Image.copyTo(temp1.colRange(ColPad, m + ColPad));
	    c2.copyTo(temp1.colRange(0, ColPad));
	    c2.copyTo(temp1.colRange(m + ColPad, m + ColPad * 2));

	    c1.copyTo(temp2.rowRange(0, RowPad));
	    temp1.copyTo(temp2.rowRange(RowPad, n + RowPad));
	    c1.copyTo(temp2.rowRange(n + RowPad, n + RowPad * 2));
        return temp2;
    }

5、interp1 分段线性插值

Matlab：
     firstlinex_intp=interp1(xold,y,xnew,'linear','extrap');
Opencv：
   void interp1(vector x, vector y, vector &x2, vector&y2) {
	int  n = x.size();
	int k = x2.size();
	for (int j = 0; j < k; j++) {
		for (int i = 1; i < n - 1; i++) {
			if (x[i] <= x2[j] && x2[j] < x[i + 1]) {
				double s = x2[j] - x[i];
				double delta = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
				y2.push_back(y[i] + s * delta);
				break;
			}
            //对溢出边界做处理
			else if(x2[j]<=x[0]){
				double s = x2[j] -x[0];
				double delta = (y[1] - y[0]) / (x[1] - x[0]);
				y2.push_back(y[0] + s * delta);
				break;
			}
            //对溢出边界做处理
			else if (x2[j] >= x[n - 2]) {
				double s = x2[j] - x[n-2];
				double delta = (y[n-1] - y[n-2]) / (x[n-1] - x[n-2]);
				y2.push_back(y[n-2] + s * delta);
				break;
			}
		}
	}
}
 

6、vector，赋值等差序列

		std::vector X1(100);
		std::iota(X1.begin(), X1.end(), 1);

先这样吧。。。