densematcher.cpp
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#include "densematcher.h"
DenseMatcher::DenseMatcher()
{
}
DenseMatcher::DenseMatcher(int method)
{
_method = method;
}
DenseMatcher::~DenseMatcher()
{
}
void DenseMatcher::calculateDisparityMap()
{
std::cout <<"Disparity calculation started... " <<endl;
if ( _lftIm == NULL || _rgtIm == NULL ){
std::cout<< "DenseMatcher module in not initialized: use denseMantcher->init command\n"<< endl;
return;
}
try{
cv::Ptr<cv::StereoSGBM> sgbm = cv::StereoSGBM::create( 16*_params.lowerBound,
16*_params.upperBound, //number of disparities
_params.blockSize);
sgbm->setMode(_method);
int cn = _lftIm->channels();
sgbm->setP1(8*cn*_params.blockSize*_params.blockSize);
sgbm->setP2(32*cn*_params.blockSize*_params.blockSize);
sgbm->compute( *_lftIm, *_rgtIm, _disp);
cv::Mat_<float> temp = _disp;
temp = temp / 16;
cv::bilateralFilter(temp,_dispValues,5,30,30); //use bilateral filter ?
//_dispValues = temp; // no filter
cout << "Done"<<endl;
}
catch(...){
cout << "DenseMatcher::Unexpected error\n"<<endl;
}
}
void DenseMatcher::plotDisparityMap()
{
if ( _dispValues.empty() ){
std::cout << "Disparity was not calculated yet\n"<< endl;
return;
}
cv::Mat disp8;
cv::normalize(_dispValues, disp8, 0, 225, cv::NORM_MINMAX, CV_8U);
//cout << _disp<<endl;
cv::imshow("Disparity", disp8);
cv::waitKey(0);
}
cv::Mat DenseMatcher::getDensePoint()
{
int nbRow=_dispValues.rows;
int nbCol=_dispValues.cols;
//creat meshgrid temp1 et temp2 present reference image
cv::Mat temp1=cv::Mat::zeros(nbRow,nbCol,CV_64F);
cv::Mat temp2=cv::Mat::zeros(nbRow,nbCol,CV_64F);
for(int i=0;i<nbRow;i++)
{
temp1.row(i)=double(i)*cv::Mat::ones(1,nbCol,temp1.type());
}
for(int j=0;j<nbCol;j++)
{
temp2.col(j)=double(j)*cv::Mat::ones(nbRow,1,temp2.type());
}
temp1=temp1.reshape(0,1);
temp2=temp2.reshape(0,1);
cv::Mat temp3;
_disp.convertTo(temp3,CV_64F);
temp3=temp3.reshape(0,1);
temp3=temp3/16;
//compute shift from first image to second image
cv::Mat temp4=temp1-temp3.reshape(0,1);
cv::Mat densePoint_temp;
cv::Mat densePoint;
densePoint_temp.push_back(temp1);
densePoint_temp.push_back(temp2);
densePoint_temp.push_back(temp4);
densePoint_temp.push_back(temp2);
//std::cout<<densePoint_temp.colRange(1,20)<<std::endl;
double min,max;
cv::minMaxLoc(temp3, &min, &max,0,0);
//cout<<"min"<< min<<endl;
temp3=temp3.reshape(0,1);
//cout<<temp3.at<double>(6)<<endl;
densePoint_temp=densePoint_temp.t();
//densePoint=densePoint_temp;
//remove the error colum which affect final result
for(int k=0;k<temp3.cols;k++)
{
if(ceil(temp3.at<double>(k))>min+1&&ceil(temp3.at<double>(k))<max-1)
{
densePoint.push_back(densePoint_temp.row(k));
}
}
densePoint=densePoint.t();
//cout<<"2"<<densePoint.size()<<endl;
//std::cout<<densePoint.colRange(1,20)<<std::endl;
return densePoint;
}
void DenseMatcher::filterDisparity(int newVal, int maxSpeckleSize, int maxDiff)
{
_paramsFilter.newVal = newVal;
_paramsFilter.maxSpeckleSize = maxSpeckleSize;
_paramsFilter.maxDiff = maxDiff;
std::cout << "Disparity filtering started... " << endl;
if ( ! _disp.empty() ){
_disp.copyTo(_dispFiltered);
cv::filterSpeckles( _dispFiltered, newVal, maxSpeckleSize, maxDiff);
cv::Mat_<float> temp = _dispFiltered;
temp = temp / 16;
_dispValues = temp;
}
else{
std::cout <<"Done\n"<<std::endl;
return;
}
std::cout <<"Done"<< std::endl;
}
cv::Mat DenseMatcher::getDisparityToDisplay() const
{
// if ( _disp.empty() )
// AR_Printf("Disparity was not calculated yet");
cv::Mat disp8 = _disp;
double minVal, maxVal;
minMaxLoc(disp8, &minVal, &maxVal); //find minimum and maximum intensities
cv::Mat draw;
disp8.convertTo(draw, CV_8UC1, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal));
//cv::imshow("image", draw);
return draw;
}
void DenseMatcher::plotDisparityFiltered()
{
if ( _dispFiltered.empty() ){
std::cout << "Disparity was not filtered yet\n" << endl;
return;
}
cv::Mat disp8;
cv::normalize(_dispFiltered, disp8, 0, 255, cv::NORM_MINMAX, CV_8U);
cv::imshow("Disparity", disp8);
}