#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "iostream"
using namespace cv;
using namespace std;
int main()
{
Mat img; vector<rect> found, found_filtered;
string namepic="street.png";
img = imread(namepic);
HOGDescriptor hog;
hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());
namedWindow("people detector", 1);
cout<<namepic<<endl; fflush(stdout);="" <="" p="">
// run the detector with default parameters. to get a higher hit-rate
// (and more false alarms, respectively), decrease the hitThreshold and
// groupThreshold (set groupThreshold to 0 to turn off the grouping completely).
hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2);
size_t i, j;
for( i = 0; i < found.size(); i++ )
{
Rect r = found[i];
for( j = 0; j < found.size(); j++ )
if( j != i && (r & found[j]) == r)
break;
if( j == found.size() )
found_filtered.push_back(r);
}
for( i = 0; i < found_filtered.size(); i++ )
{
Rect r = found_filtered[i];
// the HOG detector returns slightly larger rectangles than the real objects.
// so we slightly shrink the rectangles to get a nicer output.
r.x += cvRound(r.width0.1);
r.width = cvRound(r.width0.8);
r.y += cvRound(r.height0.07);
r.height = cvRound(r.height0.8);
rectangle(img, r.tl(), r.br(), cv::Scalar(0,255,0), 3);
}
imshow("people detector", img);
return 0;
}