OpenCV Humanoid Detection Hog

#include"iostream"#include"Queue"using namespacestd; #include"opencv2/opencv.hpp"#include"Windows.h"#include"opencv2/core/core.hpp"#include"opencv2/highgui/highgui.hpp"#include"opencv2/imgproc/imgproc.hpp"#include"opencv2/objdetect/objdetect.hpp"using namespaceCV;intMain () {Try{iplimage*pframe =NULL; Cvcapture*pcapture =NULL; //pcapture = cvcreatecameracapture (-1); //pcapture = Cvcapturefromcam (0);Pcapture = Cvcapturefromfile ("c:\\c_c++ Code\\photo and video\\textvideo2.flv"); //pcapture = Cvcapturefromfile ("c:\\c_c++ Code\\photo and video\\textvideo1.flv");        if(!pcapture) {cout<<"File opened fail ..."<<Endl; return-1;        } Mat img;        Hogdescriptor Hog;        Rect R; intNnum =0;        Hog.setsvmdetector (Hogdescriptor::getdefaultpeopledetector ()); Vector<Rect>Found,found1; intI, J; Charstr[ -];  while(Pframe =Cvqueryframe (pcapture)) {Nnum++; Mat img= Cvarrtomat (Pframe,0);//iplimage turn into Mat                        if(Nnum >=3)            {                //for testingHog.detectmultiscale (IMG, found);                Found1.clear (); //-------------------to remove nested rectangular boxes------------------------                 for(i =0; I < found.size (); i++) {R=Found[i];  for(j =0; J < Found.size (); J + +)                    {                        if(I! = J && ((r&found[j]) = =r)) { Break; }                    }                    if(J = =found.size ())                    {Found1.push_back (R); }                }                //Draw Rectangle box for people travelling                 for(i =0; I < found1.size (); i++) {R=Found1[i]; Rectangle (img, R, Scalar (0,255,0),1); } nnum=0; }                         for(inti =0; I < found1.size (); i++) {R=Found1[i]; Rectangle (img, R, Scalar (0,255,0),1); } sprintf (str,"The track count is:%d", Found1.size ()); Puttext (IMG, str, cvpoint ( -, -), Cv_font_hershey_plain,0.8, Cv_rgb (0,0, -),1,8); Imshow ("Track people", IMG); if(Cvwaitkey ( *) >=0)                 Break; }    }    Catch(Exception &e) {cout<< e.what () <<Endl; }    return 1;}

Effect:

Picture Humanoid test:

#include"iostream"#include"Queue"using namespacestd; #include"opencv2/opencv.hpp"#include"Windows.h"#include"opencv2/core/core.hpp"#include"opencv2/highgui/highgui.hpp"#include"opencv2/imgproc/imgproc.hpp"#include"opencv2/objdetect/objdetect.hpp"intMainintargcChar**argv)    {Mat img; Vector<Rect>found; IMG= Imread ("c:\\c_c++ Code\\photo and Video\\text006.jpg");    Hogdescriptor Defaulthog;    Defaulthog.setsvmdetector (Hogdescriptor::getdefaultpeopledetector ()); //for testingDefaulthog.detectmultiscale (IMG, found); //Draw Rectangle, frame traveler     for(inti =0; I < found.size (); i++) {Rect R=Found[i]; Rectangle (img, R, Scalar (0,255,0),1); } Namedwindow ("Detecting Pedestrians", cv_window_autosize); Imshow ("Detecting Pedestrians", IMG); Waitkey (0); return 0;}

Border nesting to remove weight:

intMainintargcChar**argv)    {Mat img; Vector<Rect>found, foundrect; IMG= Imread ("c:\\c_c++ Code\\photo and Video\\text007.jpg");    Hogdescriptor Defaulthog;    Defaulthog.setsvmdetector (Hogdescriptor::getdefaultpeopledetector ()); //for testingDefaulthog.detectmultiscale (IMG, found); //Traverse found to find rectangles that are not nested     for(inti =0; I < found.size (); i++) {Rect R=Found[i]; intj =0;  for(; J < Found.size (); j + +){            //Roll out loops if nested            if(J! = I && (R & found[j]) = =R) Break; }        if(J = =found.size ())        {Foundrect.push_back (R); }    }    //draw a rectangle, circle a pedestrian     for(inti =0; I < foundrect.size (); i++) {Rect R=Foundrect[i]; Rectangle (img, r.tl (), R.Br (), Scalar (0,0,255),3); } Namedwindow ("Detecting Pedestrians", cv_window_autosize); Imshow ("Detecting Pedestrians", IMG); Waitkey (0); return 0;}

intMain () {Mat image= Imread ("c:\\c_c++ Code\\photo and Video\\text007jpg"); Imshow ("Hog", image); if(Image.empty ()) {cout<<"Read image failed"<<Endl; }    //1. Defining Hog ObjectsHogdescriptor Hog (Size ( -, the), Size ( -, -), Size (8,8), Size (8,8),9); //2. Set up the SVM classifierHog.setsvmdetector (Hogdescriptor::getdaimlerpeopledetector ());//using a trained pedestrian detection classifier//3. Detecting pedestrian areas on the test imageStd::vector<cv::rect>regions; Hog.detectmultiscale (image, regions,0, Cv::size (8,8), Cv::size ( +, +),1.05,1); //Show     for(size_t i =0; I < regions.size (); i++{cv::rectangle (image, Regions[i], Cv::scalar (0,0,255),2); } cv::imshow ("Hog", image); Cv::waitkey (0); return 0;}

OpenCV Humanoid Detection Hog