Opencv实现行人检测

Opencv实现行人检测

行人检测主要时通过Opencv的opencv2/objdetect/objdetect.hpp下的HOGDescriptor实现此功能。

效果图展示:

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需要声明一个文件，来存放我们需要识别的图片，文件名这里设置为posListINRIA.txt并存放在项目的目录下。

E:\PicSource\crowd_1.jpg
E:\PicSource\crowd_2.jpg
E:\PicSource\crowd_3.jpg

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主要实现代码为：

#include      
#include 
#include 
#include    
#include    
#include    
#include   

#include   
#include   
#include   

using namespace cv;
using namespace std;

void help()
{
    printf(
        "\nDemonstrate the use of the HoG descriptor using\n"
        "  HOGDescriptor::hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());\n"
        "Usage:\n"
        "./peopledetect ( | .txt)\n\n");
}

int main(int argc, char** argv)
{
    Mat img;
    FILE* f = 0;
    char _filename[1024];

    f = fopen("posListINRIA.txt", "rt");

    HOGDescriptor hog;
    hog.setSVMDetector(HOGDescriptor::getDefaultPeopleDetector());//得到检测器  
    namedWindow("people detector", 1);

    for (;;)
    {
        char* filename = _filename;
        if (f)
        {
            if (!fgets(filename, (int)sizeof(_filename) - 2, f))
                break;
            //while(*filename && isspace(*filename))  
            //  ++filename;  
            if (filename[0] == '#')
                continue;
            int l = strlen(filename);
            while (l > 0 && isspace(filename[l - 1]))
                --l;
            filename[l] = '\0';
            img = imread(filename);
        }
        printf("%s:\n", filename);
        if (!img.data)
            continue;

        fflush(stdout);
        vector found, found_filtered;
        double t = (double)getTickCount();
        // 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);
        t = (double)getTickCount() - t;
        printf("tdetection time = %gms\n", t*1000. / cv::getTickFrequency());
        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.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(img, r.tl(), r.br(), cv::Scalar(0, 255, 0), 3);
        }
        imshow("people detector", img);
        int c = waitKey(0) & 255;
        if (c == 'q' || c == 'Q' || !f)
            break;
    }
    if (f)
        fclose(f);
    return 0;
}

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