OpenCV保存的xml矩阵转换为MATLAB矩阵

最新推荐文章于 2023-06-28 17:03:21 发布

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本文介绍如何利用OpenCV的Mat类型在Matlab中进行图像处理操作。通过编写并编译C++源代码getMat.cpp，实现从XML文件读取OpenCV Mat对象，并将其转换为Matlab能识别的数据格式。此过程涉及动态库调用、编译配置及跨平台数据交换等关键技术。

OpenCV矩阵类型Mat属于core模块，故需要opencv_core249.dll动态库。先写好需要编译的cpp文件，命名getMat.cpp,如下内容：

#include "opencv2/opencv.hpp"
#include<iostream>
#include "mex.h"

void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
	if ((nrhs != 1) && (nlhs != 1))
	{
		mexErrMsgIdAndTxt("参数错误:",
			"输入参数和输出参数个数必须为1");
	}
	if (!mxIsChar(prhs[0]))
	{
		mexErrMsgIdAndTxt("输入参数错误:","输入参数必须为字符类型");
	}
	char *input_buf;
	input_buf = mxArrayToString(prhs[0]);//使用mxArrayToString将mxArray转换为c、c++字符串
	std::string xmlname = input_buf;
	cv::FileStorage fs(xmlname, cv::FileStorage::READ);
	cv::Mat currentFolderFeatures;
	fs["currentFolderFeatures"] >> currentFolderFeatures;// 注意！！！这里xml里面变量改成属于自己名字
	if (!currentFolderFeatures.data)
	{
		mexPrintf("输入参数xml必须是全路径的xml!");
		mexErrMsgIdAndTxt("输入参数错误:", "输入参数xml必须是全路径的xml!");
		return;
	}
		
	// 转换Mat
	int m = currentFolderFeatures.rows;
	int n = currentFolderFeatures.cols;
	plhs[0] = mxCreateDoubleMatrix(m, n, mxREAL);
	double *imgMat;
	imgMat = mxGetPr(plhs[0]);
	for (int i = 0; i < m; i++)
	for (int j = 0; j < n; j++)
		*(imgMat + i + j * m) = (double)currentFolderFeatures.at<float>(i, j);
}

注意好存储的xml矩阵的变量名字。写编译文件，make.m

%% -------------------------------------------------------------------  
%% get the architecture of this computer  
is_64bit = strcmp(computer,'MACI64') || strcmp(computer,'GLNXA64') || strcmp(computer,'PCWIN64');  
  
  
%% -------------------------------------------------------------------  
%% the configuration of compiler  
% You need to modify this configuration according to your own path of OpenCV  
% 注意：你的VS OpenCV平台一定要匹配Matlab 64位的！  
out_dir='./';% 当前目录  
CPPFLAGS = ' -g -IF:\opencv\mybuild\install\include -IF:\opencv\mybuild\install\include\opencv -IF:\opencv\mybuild\install\include\opencv2'; % your OpenCV "include" path  
LDFLAGS = ' -LF:\opencv\build\x64\vc12\lib'; % 用OpenCV release版本的"lib"路径  
LIBS = ' -lopencv_core249  -lopencv_imgproc249'; % release版本的lib，无后缀，系统会自动加上去  
if is_64bit  
    CPPFLAGS = [CPPFLAGS ' -largeArrayDims'];  
end  
%% add your files here!  
compile_files = [  
    % the list of your code files which need to be compiled  
    'F:/vs2013_work/mexFunctionDebug/mexFunctionDebug/getMat.cpp' % 你的cpp文件
    ];  
%-------------------------------------------------------------------  
%% compiling...  
str = compile_files;  
fprintf('compilation of: %s\n', str);  
str = [str ' -outdir ' out_dir CPPFLAGS LDFLAGS LIBS];  
args = regexp(str, '\s+', 'split');  
mex(args{:});  
  
fprintf('Congratulations, compilation successful!!!\n');

运行make.m文件就可以得到getMat.mexw64文件。然后把opencv安装目录x64下的opencv_core249.dll拷贝到当前目录下即可使用getMat函数。

Matlab里面导入xml测试：

xmlname = 'C:\faceSets\jpg_png_pts20171212_20171222/20000000012.xml'; %注意一定要输入全路径
A = getMat(xmlname); % 需要opencv_core249.dll ,getMat.mexw64

结果：

参考文件：

http://download.youkuaiyun.com/download/cuixing001/10207840