运行OpenCV HOG样例

Running OpenCV HOG Sample

本文关键字:样例 HOG OpenCV 运行      更新时间:2023-10-16

任何OpenCV专家?我对OpenCV有点陌生。我想运行包含在ocl文件夹下的hog.cpp。在msvc++ 9.0中编译文件时出现错误

1>------ Build started: Project: hog_ocl, Configuration: Debug Win32 ------
1>Linking...
1>hog.obj : error LNK2019: unresolved external symbol "public: void __thiscall cv::ocl::HOGDescriptor::detectMultiScale(class cv::ocl::oclMat const &,class std::vector<class cv::Rect_<int>,class std::allocator<class cv::Rect_<int> > > &,double,class cv::Size_<int>,class cv::Size_<int>,double,int)" (?detectMultiScale@HOGDescriptor@ocl@cv@@QAEXABVoclMat@23@AAV?$vector@V?$Rect_@H@cv@@V?$allocator@V?$Rect_@H@cv@@@std@@@std@@NV?$Size_@H@3@2NH@Z) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: void __thiscall cv::ocl::oclMat::upload(class cv::Mat const &)" (?upload@oclMat@ocl@cv@@QAEXABVMat@3@@Z) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: void __thiscall cv::ocl::HOGDescriptor::setSVMDetector(class std::vector<float,class std::allocator<float> > const &)" (?setSVMDetector@HOGDescriptor@ocl@cv@@QAEXABV?$vector@MV?$allocator@M@std@@@std@@@Z) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: __thiscall cv::ocl::HOGDescriptor::HOGDescriptor(class cv::Size_<int>,class cv::Size_<int>,class cv::Size_<int>,class cv::Size_<int>,int,double,double,bool,int)" (??0HOGDescriptor@ocl@cv@@QAE@V?$Size_@H@2@000HNN_NH@Z) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: static class std::vector<float,class std::allocator<float> > __cdecl cv::ocl::HOGDescriptor::getPeopleDetector48x96(void)" (?getPeopleDetector48x96@HOGDescriptor@ocl@cv@@SA?AV?$vector@MV?$allocator@M@std@@@std@@XZ) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: static class std::vector<float,class std::allocator<float> > __cdecl cv::ocl::HOGDescriptor::getPeopleDetector64x128(void)" (?getPeopleDetector64x128@HOGDescriptor@ocl@cv@@SA?AV?$vector@MV?$allocator@M@std@@@std@@XZ) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "int __cdecl cv::ocl::getDevice(class std::vector<class cv::ocl::Info,class std::allocator<class cv::ocl::Info> > &,int)" (?getDevice@ocl@cv@@YAHAAV?$vector@VInfo@ocl@cv@@V?$allocator@VInfo@ocl@cv@@@std@@@std@@H@Z) referenced in function "public: void __thiscall App::run(void)" (?run@App@@QAEXXZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: void __thiscall cv::ocl::oclMat::release(void)" (?release@oclMat@ocl@cv@@QAEXXZ) referenced in function "public: __thiscall cv::ocl::oclMat::~oclMat(void)" (??1oclMat@ocl@cv@@QAE@XZ)
1>hog.obj : error LNK2019: unresolved external symbol "public: __thiscall cv::ocl::Info::~Info(void)" (??1Info@ocl@cv@@QAE@XZ) referenced in function "public: void * __thiscall cv::ocl::Info::`scalar deleting destructor'(unsigned int)" (??_GInfo@ocl@cv@@QAEPAXI@Z)
1>C:UsersCTDocumentsVisual Studio 2008Projectshog_oclDebughog_ocl.exe : fatal error LNK1120: 9 unresolved externals
1>Build log was saved at "file://c:UsersCTDocumentsVisual Studio 2008Projectshog_oclhog_oclDebugBuildLog.htm"
1>hog_ocl - 10 error(s), 0 warning(s)
========== Build: 0 succeeded, 1 failed, 0 up-to-date, 0 skipped ==========

起初,我在project->config中包含了C:opencvbuildx86vc9lib中的所有库。属性->链接器->输入。不幸的是,它没有起作用。因此,通过尝试,我排除了不能最大限度地减少错误计数的库,并达到以下列表

opencv_imgproc244.lib
opencv_highgui244.lib
opencv_core244.lib
opencv_objdetect244.lib

仍然不起作用。我想知道我是不是一开始就拿错了样品,对我来说太高级了?

Add。信息:我按照手册安装OpenCV,甚至重建了库。希望我的程序是正确的。

代码(OpenCV 2.4.4):

#include <iostream>
#include <fstream>
#include <string>
#include <sstream>
#include <iomanip>
#include <stdexcept>
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
bool help_showed = false;
class Args
{
public:
    Args();
    static Args read(int argc, char** argv);
    string src;
    bool src_is_video;
    bool src_is_camera;
    int camera_id;
    bool write_video;
    string dst_video;
    double dst_video_fps;
    bool make_gray;
    bool resize_src;
    int width, height;
    double scale;
    int nlevels;
    int gr_threshold;
    double hit_threshold;
    bool hit_threshold_auto;
    int win_width;
    int win_stride_width, win_stride_height;
    bool gamma_corr;
};

class App
{
public:
    App(const Args& s);
    void run();
    void handleKey(char key);
    void hogWorkBegin();
    void hogWorkEnd();
    string hogWorkFps() const;
    void workBegin();
    void workEnd();
    string workFps() const;
    string message() const;
private:
    App operator=(App&);
    Args args;
    bool running;
    bool use_gpu;
    bool make_gray;
    double scale;
    int gr_threshold;
    int nlevels;
    double hit_threshold;
    bool gamma_corr;
    int64 hog_work_begin;
    double hog_work_fps;
    int64 work_begin;
    double work_fps;
};
static void printHelp()
{
    cout << "Histogram of Oriented Gradients descriptor and detector sample.n"
         << "nUsage: hog_gpun"
         << "  (<image>|--video <vide>|--camera <camera_id>) # frames sourcen"
         << "  [--make_gray <true/false>] # convert image to gray one or notn"
         << "  [--resize_src <true/false>] # do resize of the source image or notn"
         << "  [--width <int>] # resized image widthn"
         << "  [--height <int>] # resized image heightn"
         << "  [--hit_threshold <double>] # classifying plane distance threshold (0.0 usually)n"
         << "  [--scale <double>] # HOG window scale factorn"
         << "  [--nlevels <int>] # max number of HOG window scalesn"
         << "  [--win_width <int>] # width of the window (48 or 64)n"
         << "  [--win_stride_width <int>] # distance by OX axis between neighbour winsn"
         << "  [--win_stride_height <int>] # distance by OY axis between neighbour winsn"
         << "  [--gr_threshold <int>] # merging similar rects constantn"
         << "  [--gamma_correct <int>] # do gamma correction or notn"
         << "  [--write_video <bool>] # write video or notn"
         << "  [--dst_video <path>] # output video pathn"
         << "  [--dst_video_fps <double>] # output video fpsn";
    help_showed = true;
}
int main(int argc, char** argv)
{
    try
    {
        if (argc < 2)
            printHelp();
        Args args = Args::read(argc, argv);
        if (help_showed)
            return -1;
        App app(args);
        app.run();
    }
    catch (const Exception& e) { return cout << "error: "  << e.what() << endl, 1; }
    catch (const exception& e) { return cout << "error: "  << e.what() << endl, 1; }
    catch(...) { return cout << "unknown exception" << endl, 1; }
    return 0;
}

Args::Args()
{
    src_is_video = false;
    src_is_camera = false;
    camera_id = 0;
    write_video = false;
    dst_video_fps = 24.;
    make_gray = false;
    resize_src = false;
    width = 640;
    height = 480;
    scale = 1.05;
    nlevels = 13;
    gr_threshold = 8;
    hit_threshold = 1.4;
    hit_threshold_auto = true;
    win_width = 48;
    win_stride_width = 8;
    win_stride_height = 8;
    gamma_corr = true;
}

Args Args::read(int argc, char** argv)
{
    Args args;
    for (int i = 1; i < argc; i++)
    {
        if (string(argv[i]) == "--make_gray") args.make_gray = (string(argv[++i]) == "true");
        else if (string(argv[i]) == "--resize_src") args.resize_src = (string(argv[++i]) == "true");
        else if (string(argv[i]) == "--width") args.width = atoi(argv[++i]);
        else if (string(argv[i]) == "--height") args.height = atoi(argv[++i]);
        else if (string(argv[i]) == "--hit_threshold")
        {
            args.hit_threshold = atof(argv[++i]);
            args.hit_threshold_auto = false;
        }
        else if (string(argv[i]) == "--scale") args.scale = atof(argv[++i]);
        else if (string(argv[i]) == "--nlevels") args.nlevels = atoi(argv[++i]);
        else if (string(argv[i]) == "--win_width") args.win_width = atoi(argv[++i]);
        else if (string(argv[i]) == "--win_stride_width") args.win_stride_width = atoi(argv[++i]);
        else if (string(argv[i]) == "--win_stride_height") args.win_stride_height = atoi(argv[++i]);
        else if (string(argv[i]) == "--gr_threshold") args.gr_threshold = atoi(argv[++i]);
        else if (string(argv[i]) == "--gamma_correct") args.gamma_corr = (string(argv[++i]) == "true");
        else if (string(argv[i]) == "--write_video") args.write_video = (string(argv[++i]) == "true");
        else if (string(argv[i]) == "--dst_video") args.dst_video = argv[++i];
        else if (string(argv[i]) == "--dst_video_fps") args.dst_video_fps = atof(argv[++i]);
        else if (string(argv[i]) == "--help") printHelp();
        else if (string(argv[i]) == "--video") { args.src = argv[++i]; args.src_is_video = true; }
        else if (string(argv[i]) == "--camera") { args.camera_id = atoi(argv[++i]); args.src_is_camera = true; }
        else if (args.src.empty()) args.src = argv[i];
        else throw runtime_error((string("unknown key: ") + argv[i]));
    }
    return args;
}

App::App(const Args& s)
{
    args = s;
    cout << "nControls:n"
         << "tESC - exitn"
         << "tm - change mode GPU <-> CPUn"
         << "tg - convert image to gray or notn"
         << "t1/q - increase/decrease HOG scalen"
         << "t2/w - increase/decrease levels countn"
         << "t3/e - increase/decrease HOG group thresholdn"
         << "t4/r - increase/decrease hit thresholdn"
         << endl;
    use_gpu = true;
    make_gray = args.make_gray;
    scale = args.scale;
    gr_threshold = args.gr_threshold;
    nlevels = args.nlevels;
    if (args.hit_threshold_auto)
        args.hit_threshold = args.win_width == 48 ? 1.4 : 0.;
    hit_threshold = args.hit_threshold;
    gamma_corr = args.gamma_corr;
    if (args.win_width != 64 && args.win_width != 48)
        args.win_width = 64;
    cout << "Scale: " << scale << endl;
    if (args.resize_src)
        cout << "Resized source: (" << args.width << ", " << args.height << ")n";
    cout << "Group threshold: " << gr_threshold << endl;
    cout << "Levels number: " << nlevels << endl;
    cout << "Win width: " << args.win_width << endl;
    cout << "Win stride: (" << args.win_stride_width << ", " << args.win_stride_height << ")n";
    cout << "Hit threshold: " << hit_threshold << endl;
    cout << "Gamma correction: " << gamma_corr << endl;
    cout << endl;
}

void App::run()
{
    std::vector<ocl::Info> oclinfo;
    ocl::getDevice(oclinfo);
    running = true;
    cv::VideoWriter video_writer;
    Size win_size(args.win_width, args.win_width * 2); //(64, 128) or (48, 96)
    Size win_stride(args.win_stride_width, args.win_stride_height);
    // Create HOG descriptors and detectors here
    vector<float> detector;
    if (win_size == Size(64, 128))
        detector = cv::ocl::HOGDescriptor::getPeopleDetector64x128();
    else
        detector = cv::ocl::HOGDescriptor::getPeopleDetector48x96();
    cv::ocl::HOGDescriptor gpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9,
                                   cv::ocl::HOGDescriptor::DEFAULT_WIN_SIGMA, 0.2, gamma_corr,
                                   cv::ocl::HOGDescriptor::DEFAULT_NLEVELS);
    cv::HOGDescriptor cpu_hog(win_size, Size(16, 16), Size(8, 8), Size(8, 8), 9, 1, -1,
                              HOGDescriptor::L2Hys, 0.2, gamma_corr, cv::HOGDescriptor::DEFAULT_NLEVELS);
    gpu_hog.setSVMDetector(detector);
    cpu_hog.setSVMDetector(detector);
    while (running)
    {
        VideoCapture vc;
        Mat frame;
        if (args.src_is_video)
        {
            vc.open(args.src.c_str());
            if (!vc.isOpened())
                throw runtime_error(string("can't open video file: " + args.src));
            vc >> frame;
        }
        else if (args.src_is_camera)
        {
            vc.open(args.camera_id);
            if (!vc.isOpened())
            {
                stringstream msg;
                msg << "can't open camera: " << args.camera_id;
                throw runtime_error(msg.str());
            }
            vc >> frame;
        }
        else
        {
            frame = imread(args.src);
            if (frame.empty())
                throw runtime_error(string("can't open image file: " + args.src));
        }
        Mat img_aux, img, img_to_show;
        ocl::oclMat gpu_img;
        // Iterate over all frames
        while (running && !frame.empty())
        {
            workBegin();
            // Change format of the image
            if (make_gray) cvtColor(frame, img_aux, CV_BGR2GRAY);
            else if (use_gpu) cvtColor(frame, img_aux, CV_BGR2BGRA);
            else frame.copyTo(img_aux);
            // Resize image
            if (args.resize_src) resize(img_aux, img, Size(args.width, args.height));
            else img = img_aux;
            img_to_show = img;
            gpu_hog.nlevels = nlevels;
            cpu_hog.nlevels = nlevels;
            vector<Rect> found;
            // Perform HOG classification
            hogWorkBegin();
            if (use_gpu)
            {
                gpu_img.upload(img);
                gpu_hog.detectMultiScale(gpu_img, found, hit_threshold, win_stride,
                                         Size(0, 0), scale, gr_threshold);
            }
            else cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
                                          Size(0, 0), scale, gr_threshold);
            hogWorkEnd();
            // Draw positive classified windows
            for (size_t i = 0; i < found.size(); i++)
            {
                Rect r = found[i];
                rectangle(img_to_show, r.tl(), r.br(), CV_RGB(0, 255, 0), 3);
            }
            if (use_gpu)
                putText(img_to_show, "Mode: GPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
            else
                putText(img_to_show, "Mode: CPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
            putText(img_to_show, "FPS (HOG only): " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
            putText(img_to_show, "FPS (total): " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
            imshow("opencv_gpu_hog", img_to_show);
            if (args.src_is_video || args.src_is_camera) vc >> frame;
            workEnd();
            if (args.write_video)
            {
                if (!video_writer.isOpened())
                {
                    video_writer.open(args.dst_video, CV_FOURCC('x','v','i','d'), args.dst_video_fps,
                                      img_to_show.size(), true);
                    if (!video_writer.isOpened())
                        throw std::runtime_error("can't create video writer");
                }
                if (make_gray) cvtColor(img_to_show, img, CV_GRAY2BGR);
                else cvtColor(img_to_show, img, CV_BGRA2BGR);
                video_writer << img;
            }
            handleKey((char)waitKey(3));
        }
    }
}

void App::handleKey(char key)
{
    switch (key)
    {
    case 27:
        running = false;
        break;
    case 'm':
    case 'M':
        use_gpu = !use_gpu;
        cout << "Switched to " << (use_gpu ? "CUDA" : "CPU") << " moden";
        break;
    case 'g':
    case 'G':
        make_gray = !make_gray;
        cout << "Convert image to gray: " << (make_gray ? "YES" : "NO") << endl;
        break;
    case '1':
        scale *= 1.05;
        cout << "Scale: " << scale << endl;
        break;
    case 'q':
    case 'Q':
        scale /= 1.05;
        cout << "Scale: " << scale << endl;
        break;
    case '2':
        nlevels++;
        cout << "Levels number: " << nlevels << endl;
        break;
    case 'w':
    case 'W':
        nlevels = max(nlevels - 1, 1);
        cout << "Levels number: " << nlevels << endl;
        break;
    case '3':
        gr_threshold++;
        cout << "Group threshold: " << gr_threshold << endl;
        break;
    case 'e':
    case 'E':
        gr_threshold = max(0, gr_threshold - 1);
        cout << "Group threshold: " << gr_threshold << endl;
        break;
    case '4':
        hit_threshold+=0.25;
        cout << "Hit threshold: " << hit_threshold << endl;
        break;
    case 'r':
    case 'R':
        hit_threshold = max(0.0, hit_threshold - 0.25);
        cout << "Hit threshold: " << hit_threshold << endl;
        break;
    case 'c':
    case 'C':
        gamma_corr = !gamma_corr;
        cout << "Gamma correction: " << gamma_corr << endl;
        break;
    }
}

inline void App::hogWorkBegin() { hog_work_begin = getTickCount(); }
inline void App::hogWorkEnd()
{
    int64 delta = getTickCount() - hog_work_begin;
    double freq = getTickFrequency();
    hog_work_fps = freq / delta;
}
inline string App::hogWorkFps() const
{
    stringstream ss;
    ss << hog_work_fps;
    return ss.str();
}

inline void App::workBegin() { work_begin = getTickCount(); }
inline void App::workEnd()
{
    int64 delta = getTickCount() - work_begin;
    double freq = getTickFrequency();
    work_fps = freq / delta;
}
inline string App::workFps() const
{
    stringstream ss;
    ss << work_fps;
    return ss.str();
}

事实证明,运行此代码需要库opencv_ocl.lib, ocl文件夹下的其他示例也是如此。OpenCV必须使用CMake和C编译器在您的设备上构建(我使用MSVC 2010)。经过几天和长时间的试验,我成功地构建了它,构建/重建和OCL和GPU上的读数。我只是想知道为什么它不能像其他库一样预先构建并包含在包中,是因为硬件依赖吗?

然而,这是oclhog.cpp所需的库列表:

opencv_imgproc245.lib
opencv_highgui245.lib
opencv_core245.lib
opencv_objdetect245.lib
opencv_ocl245.lib

使用最新的OpenCV 2.4.5.

我认为你需要包含features2d库。