#include <iostream>
#include <string>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/ml/ml.hpp>
using namespace std;
using namespace cv;
int main()
{
Mat src = imread("10.jpg");
HOGDescriptor hog;//HOG特征检测器
hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());//设置SVM分类器为默认参数
vector<Rect> found, found_filtered;//矩形框数组
hog.detectMultiScale(src, found, 0, Size(8,8), Size(32,32), 1.05, 2);//对图像进行多尺度检测,检测窗口移动步长为(8,8)
cout<<"矩形个数:"<<found.size()<<endl;
//找出所有没有嵌套的矩形框r,并放入found_filtered中,如果有嵌套的话,则取外面最大的那个矩形框放入found_filtered中
for(int i=0; i < found.size(); i++)
{
Rect r = found[i];
int j=0;
for(; j < found.size(); j++)
if(j != i && (r & found[j]) == r)
break;
if( j == found.size())
found_filtered.push_back(r);
}
cout<<"过滤后矩形的个数:"<<found_filtered.size()<<endl;
//画矩形框,因为hog检测出的矩形框比实际人体框要稍微大些,所以这里需要做一些调整
for(int i=0; i<found_filtered.size(); i++)
{
Rect r = found_filtered[i];
r.x += cvRound(r.width*0.1);
r.width = cvRound(r.width*0.8);
r.y += cvRound(r.height*0.07);
r.height = cvRound(r.height*0.8);
rectangle(src, r.tl(), r.br(), Scalar(0,255,0), 3);
}
imwrite("第三个结果图\\10.jpg",src);
namedWindow("src",0);
imshow("src",src);
waitKey(2000);//注意:imshow之后一定要加waitKey,否则无法显示图像
}
Demo3:视频人体检测
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转载自blog.csdn.net/u011473714/article/details/88244777
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