I have some MATLAB code that I want to migrate to OpenCV. The data that the MATLAB code uses is stored in a .mat file which is then loaded at run time.
I converted this .mat file into a .csv file and am then reading this data into OpenCV as a string using ifstream. I am having problems converting this string into a data-structure that I can then use in OpenCV.
Is there anyway that I can convert the .mat file / .csv file to a Mat data structure in OpenCV?
Edit: Based on the Answer I received, I was successful in reading MATLAB data into OpenCV using a YML file. This I did in a MAC environment. However, when I try to read the file with the same piece of code in a Windows environment, the file is not being read. Just wondering if anyone ran into such an issue. Below is my code snippet:
// OpenCVDemo.cpp : Defines the entry point for the console application.
// Created for build/install tutorial, Microsoft Visual Studio and OpenCV 2.4.0
#include "stdafx.h"
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>
#include <iostream>
using namespace cv;
using namespace std;
int _tmain(int argc, _TCHAR* argv[])
{
cout << "Loading the basis." << endl;
FileStorage fs1("basis.yml", FileStorage::READ);
cv::FileNode B = fs1["B"];
if (B.EMPTY)
{
cout << "File is empty or does not exist" << endl;
return 1;
}
fs1["B"] >> basis;
cout << basis.cols << endl;
fs1.release();
return 0;
}
You can use the XML/YAML file storages provided by the OpenCV class Filestorage.
As an example, if you have a yml file like this one, that I'll call demo.yml
%YAML:1.0
Variable1: !!opencv-matrix
rows: 4
cols: 5
dt: f
data: [ -1.60522782e-03, -5.93489595e-03, 2.92204670e-03,
1.14785777e-02, -1.57432575e-02, -2.17529312e-02, 4.05947529e-02,
6.56594411e-02, 1.24527821e-02, 3.19751091e-02, 5.41692637e-02,
4.04683389e-02, 2.59191263e-03, 1.15112308e-03, 1.11024221e-02,
4.03668173e-03, -3.19138430e-02, -9.40114353e-03, 4.93452176e-02,
5.73473945e-02 ]
Variable2: !!opencv-matrix
rows: 7
cols: 2
dt: f
data: [ -2.17529312e-02, 4.05947529e-02, 5.73473945e-02,
6.56594411e-02, 1.24527821e-02, 3.19751091e-02, 5.41692637e-02,
4.03668173e-03, -3.19138430e-02, -9.40114353e-03, 4.93452176e-02,
4.04683389e-02, 2.59191263e-03, 1.15112308e-03 ]
Then, you can use OpenCV FileStorage class to load the variables contained on this demo.yml file as:
#include <iostream>
#include <string>
#include <cv.h>
#include <highgui.h>
using namespace cv;
using namespace std;
int main (int argc, char * const argv[])
{
Mat var1;
Mat var2;
string demoFile = "demo.yml";
FileStorage fsDemo( demoFile, FileStorage::READ);
fsDemo["Variable1"] >> var1;
fsDemo["Variable2"] >> var2;
cout << "Print the contents of var1:" << endl;
cout << var1 << endl << endl;
cout << "Print the contents of var2:" << endl;
cout << var2 << endl;
fsDemo.release();
return 0;
}
Now, what you can do is writing your own Matlab parser, similarly to my matlab2opencv.m below:
function matlab2opencv( variable, fileName, flag)
[rows cols] = size(variable);
% Beware of Matlab's linear indexing
variable = variable';
% Write mode as default
if ( ~exist('flag','var') )
flag = 'w';
end
if ( ~exist(fileName,'file') || flag == 'w' )
% New file or write mode specified
file = fopen( fileName, 'w');
fprintf( file, '%%YAML:1.0\n');
else
% Append mode
file = fopen( fileName, 'a');
end
% Write variable header
fprintf( file, ' %s: !!opencv-matrix\n', inputname(1));
fprintf( file, ' rows: %d\n', rows);
fprintf( file, ' cols: %d\n', cols);
fprintf( file, ' dt: f\n');
fprintf( file, ' data: [ ');
% Write variable data
for i=1:rows*cols
fprintf( file, '%.6f', variable(i));
if (i == rows*cols), break, end
fprintf( file, ', ');
if mod(i+1,4) == 0
fprintf( file, '\n ');
end
end
fprintf( file, ']\n');
fclose(file);
So you could run something like:
varA = rand( 3, 6);
varB = rand( 7, 2);
matlab2opencv( varA, 'newStorageFile.yml');
matlab2opencv( varB, 'newStorageFile.yml', 'a'); % append mode passed by 'a' flag
obtaining newStorageFile.yml:
%YAML:1.0
varA: !!opencv-matrix
rows: 3
cols: 6
dt: f
data: [ 0.430207, 0.979748, 0.258065,
0.262212, 0.221747, 0.318778, 0.184816,
0.438870, 0.408720, 0.602843, 0.117418,
0.424167, 0.904881, 0.111119, 0.594896,
0.711216, 0.296676, 0.507858]
varB: !!opencv-matrix
rows: 7
cols: 2
dt: f
data: [ 0.085516, 0.578525, 0.262482,
0.237284, 0.801015, 0.458849, 0.029220,
0.963089, 0.928854, 0.546806, 0.730331,
0.521136, 0.488609, 0.231594]
from which you could read varA
and varB
as previously explained for Variable1
and Variable2
.
Hope it helps
You can use the Matlab bridge from opencv contrib. All you need from Opencv Contrib is to copy contrib/modules/matlab/include/opencv2/matlab folder into the include/opencv2 folder.
along with the Matlab Compiler Runtime (just libmx.lib, libmex.lib and libmat.lib).
MATFile *pmat = matOpen(filename, "r");
if (pmat == NULL)
{
cerr << "Error opening file " << filename << endl;
}
else
{
int numVars;
char** namePtr = matGetDir(pmat, &numVars);
cout << filename << " contains vars " << endl;
for (int idx = 0; idx < numVars; idx++)
{
std::cout << " " << namePtr[idx] << " ";
mxArray* m = matGetVariable(pmat, namePtr[idx]);
matlab::MxArray mArray(m);
cv::bridge::Bridge bridge(mArray);
cv::Mat mat = bridge.toMat();
// do something with opencv Mat
}
}
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