【AI】基于OpenCV开发自定义程序编译方法

基于OpenCV开发自定义程序编译方法

OpenCV自带的程序，编译均采用cmake统一编译。若我们要基于OpenCV开发自己的程序，如何快速编译？

本文以OpenCV库自带的facedetect.cpp程序作为模板，提供独立编译自定义程序的命令，和通用Makefile写法。

// 这是OpenCV库自带的sample程序，用于演示人脸/眼睛/鼻子侦测，我们将文件命名为facedetect.cpp
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include 

using namespace std;
using namespace cv;

static void help()
{
    cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
            "This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n"
            "It's most known use is for faces.\n"
            "Usage:\n"
            "./facedetect [--cascade= this is the primary trained classifier such as frontal face]\n"
               "   [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
               "   [--scale=]\n"
               "   [--try-flip]\n"
               "   [filename|camera_index]\n\n"
            "see facedetect.cmd for one call:\n"
            "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml\" --scale=1.3\n\n"
            "During execution:\n\tHit any key to quit.\n"
            "\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
}

void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                    CascadeClassifier& nestedCascade,
                    double scale, bool tryflip );

string cascadeName;
string nestedCascadeName;

int main( int argc, const char** argv )
{
    VideoCapture capture;
    Mat frame, image;
    string inputName;
    bool tryflip;
    CascadeClassifier cascade, nestedCascade;
    double scale;

    cv::CommandLineParser parser(argc, argv,
        "{help h||}"
        "{cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}"
        "{nested-cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}"
        "{scale|1|}{try-flip||}{@filename||}"
    );
    if (parser.has("help"))
    {
        help();
        return 0;
    }
    cascadeName = parser.get("cascade");
    nestedCascadeName = parser.get("nested-cascade");
    scale = parser.get("scale");
    if (scale < 1)
        scale = 1;
    tryflip = parser.has("try-flip");
    inputName = parser.get("@filename");
    if (!parser.check())
    {
        parser.printErrors();
        return 0;
    }
    if ( !nestedCascade.load( nestedCascadeName ) )
        cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
    if( !cascade.load( cascadeName ) )
    {
        cerr << "ERROR: Could not load classifier cascade" << endl;
        help();
        return -1;
    }
    if( inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1) )
    {
        int camera = inputName.empty() ? 0 : inputName[0] - '0';
        if(!capture.open(camera))
            cout << "Capture from camera #" <<  camera << " didn't work" << endl;
    }
    else if( inputName.size() )
    {
        image = imread( inputName, 1 );
        if( image.empty() )
        {
            if(!capture.open( inputName ))
                cout << "Could not read " << inputName << endl;
        }
    }
    else
    {
        image = imread( "../data/lena.jpg", 1 );
        if(image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
    }

    if( capture.isOpened() )
    {
        cout << "Video capturing has been started ..." << endl;

        for(;;)
        {
            capture >> frame;
            if( frame.empty() )
                break;

            Mat frame1 = frame.clone();
            detectAndDraw( frame1, cascade, nestedCascade, scale, tryflip );

            char c = (char)waitKey(10);
            if( c == 27 || c == 'q' || c == 'Q' )
                break;
        }
    }
    else
    {
        cout << "Detecting face(s) in " << inputName << endl;
        if( !image.empty() )
        {
            detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
            waitKey(0);
        }
        else if( !inputName.empty() )
        {
            /* assume it is a text file containing the
            list of the image filenames to be processed - one per line */
            FILE* f = fopen( inputName.c_str(), "rt" );
            if( f )
            {
                char buf[1000+1];
                while( fgets( buf, 1000, f ) )
                {
                    int len = (int)strlen(buf);
                    while( len > 0 && isspace(buf[len-1]) )
                        len--;
                    buf[len] = '\0';
                    cout << "file " << buf << endl;
                    image = imread( buf, 1 );
                    if( !image.empty() )
                    {
                        detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
                        char c = (char)waitKey(0);
                        if( c == 27 || c == 'q' || c == 'Q' )
                            break;
                    }
                    else
                    {
                        cerr << "Aw snap, couldn't read image " << buf << endl;
                    }
                }
                fclose(f);
            }
        }
    }

    return 0;
}

void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                    CascadeClassifier& nestedCascade,
                    double scale, bool tryflip )
{
    double t = 0;
    vector faces, faces2;
    const static Scalar colors[] =
    {
        Scalar(255,0,0),
        Scalar(255,128,0),
        Scalar(255,255,0),
        Scalar(0,255,0),
        Scalar(0,128,255),
        Scalar(0,255,255),
        Scalar(0,0,255),
        Scalar(255,0,255)
    };
    Mat gray, smallImg;

    cvtColor( img, gray, COLOR_BGR2GRAY );
    double fx = 1 / scale;
    resize( gray, smallImg, Size(), fx, fx, INTER_LINEAR );
    equalizeHist( smallImg, smallImg );

    t = (double)getTickCount();
    cascade.detectMultiScale( smallImg, faces,
        1.1, 2, 0
        //|CASCADE_FIND_BIGGEST_OBJECT
        //|CASCADE_DO_ROUGH_SEARCH
        |CASCADE_SCALE_IMAGE,
        Size(30, 30) );
    if( tryflip )
    {
        flip(smallImg, smallImg, 1);
        cascade.detectMultiScale( smallImg, faces2,
                                 1.1, 2, 0
                                 //|CASCADE_FIND_BIGGEST_OBJECT
                                 //|CASCADE_DO_ROUGH_SEARCH
                                 |CASCADE_SCALE_IMAGE,
                                 Size(30, 30) );
        for( vector::const_iterator r = faces2.begin(); r != faces2.end(); ++r )
        {
            faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
        }
    }
    t = (double)getTickCount() - t;
    printf( "detection time = %g ms\n", t*1000/getTickFrequency());
    for ( size_t i = 0; i < faces.size(); i++ )
    {
        Rect r = faces[i];
        Mat smallImgROI;
        vector nestedObjects;
        Point center;
        Scalar color = colors[i%8];
        int radius;

        double aspect_ratio = (double)r.width/r.height;
        if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
        {
            center.x = cvRound((r.x + r.width*0.5)*scale);
            center.y = cvRound((r.y + r.height*0.5)*scale);
            radius = cvRound((r.width + r.height)*0.25*scale);
            circle( img, center, radius, color, 3, 8, 0 );
        }
        else
            rectangle( img, cvPoint(cvRound(r.x*scale), cvRound(r.y*scale)),
                       cvPoint(cvRound((r.x + r.width-1)*scale), cvRound((r.y + r.height-1)*scale)),
                       color, 3, 8, 0);
        if( nestedCascade.empty() )
            continue;
        smallImgROI = smallImg( r );
        nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
            1.1, 2, 0
            //|CASCADE_FIND_BIGGEST_OBJECT
            //|CASCADE_DO_ROUGH_SEARCH
            //|CASCADE_DO_CANNY_PRUNING
            |CASCADE_SCALE_IMAGE,
            Size(30, 30) );
        for ( size_t j = 0; j < nestedObjects.size(); j++ )
        {
            Rect nr = nestedObjects[j];
            center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);
            center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);
            radius = cvRound((nr.width + nr.height)*0.25*scale);
            circle( img, center, radius, color, 3, 8, 0 );
        }
    }
    imshow( "result", img );
}

#命令行编译：
g++ facedetect.cpp -o facedetect `pkg-config --cflags --libs opencv`

#Makefile编译：

CFLAGS = `pkg-config --cflags opencv`
LIBS = `pkg-config --libs opencv`

APP_NAME = facedetect

OBJS = facedetect.o

$(APP_NAME) : $(OBJS)
        g++ $^ -o $(APP_NAME) $(LIBS)

%.o : %.cpp
        g++ $(CFLAGS) -c $^ -o $(OBJS)

clean:
        rm -rf *.o  $(APP_NAME)

#pkg-config解释，见man pkg-config说明：

NAME
       pkg-config - Return metainformation about installed libraries

SYNOPSIS
       pkg-config  [--modversion] [--help] [--print-errors] [--silence-errors] [--cflags] [--libs] [--libs-only-L] [--libs-only-l] [--cflags-only-I] [--variable=VARIABLENAME] [--define-variable=VARIABLENAME=VARIABLEVALUE] [--print-
       variables] [--uninstalled] [--exists] [--atleast-version=VERSION] [--exact-version=VERSION] [--max-version=VERSION] [--list-all] [LIBRARIES...]  [--print-provides] [--print-requires] [--print-requires-private] [LIBRARIES...]

DESCRIPTION
       The pkg-config program is used to retrieve information about installed libraries in the system.  It is typically used to compile and link against one or more libraries.  Here is a typical usage scenario in a Makefile:

       program: program.c
            cc program.c $(pkg-config --cflags --libs gnomeui)

       pkg-config retrieves information about packages from special metadata files. These files are named after the package, and has a .pc extension.  On most systems, pkg-config looks in  /usr/lib/pkgconfig,  /usr/share/pkgconfig,
       /usr/local/lib/pkgconfig  and  /usr/local/share/pkgconfig  for these files.  It will additionally look in the colon-separated (on Windows, semicolon-separated) list of directories specified by the PKG_CONFIG_PATH environment
       variable.

       The package name specified on the pkg-config command line is defined to be the name of the metadata file, minus the .pc extension. If a library can install multiple versions simultaneously, it must give each version its  own
       name (for example, GTK 1.2 might have the package name "gtk+" while GTK 2.0 has "gtk+-2.0").

       In addition to specifying a package name on the command line, the full path to a given .pc file may be given instead. This allows a user to directly query a particular .pc file.