Open Source Computer Vision Library https://opencv.org/
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#include "opencv2/core/core.hpp"
#include "opencv2/video/background_segm.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdio.h>
using namespace cv;
using namespace std;
void help()
{
printf("\nDo background segmentation, especially demonstrating the use of cvUpdateBGStatModel().\n"
" Learns the background at the start and then segments.\n"
" Learning is togged by the space key. Will read from file or camera\n"
"Usage: \n"
" ./bgfg_segm [--file_name]=<input file, camera as defautl>\n\n");
}
//this is a sample for foreground detection functions
int main(int argc, const char** argv)
{
help();
CommandLineParser parser(argc, argv);
string fileName = parser.get<string>("file_name", "0");
VideoCapture cap;
bool update_bg_model = true;
if(fileName == "0" )
cap.open(0);
else
cap.open(fileName.c_str());
if( !cap.isOpened() )
{
help();
printf("can not open camera or video file\n");
return -1;
}
namedWindow("image", CV_WINDOW_NORMAL);
namedWindow("foreground mask", CV_WINDOW_NORMAL);
namedWindow("foreground image", CV_WINDOW_NORMAL);
namedWindow("mean background image", CV_WINDOW_NORMAL);
BackgroundSubtractorMOG2 bg_model;
Mat img, fgmask, fgimg;
for(;;)
{
cap >> img;
if( img.empty() )
break;
if( fgimg.empty() )
fgimg.create(img.size(), img.type());
//update the model
bg_model(img, fgmask, update_bg_model ? -1 : 0);
fgimg = Scalar::all(0);
img.copyTo(fgimg, fgmask);
Mat bgimg;
bg_model.getBackgroundImage(bgimg);
imshow("image", img);
imshow("foreground mask", fgmask);
imshow("foreground image", fgimg);
if(!bgimg.empty())
imshow("mean background image", bgimg );
char k = (char)waitKey(30);
if( k == 27 ) break;
if( k == ' ' )
{
update_bg_model = !update_bg_model;
if(update_bg_model)
printf("Background update is on\n");
else
printf("Background update is off\n");
}
}
return 0;
}