opencv/modules/ocl/test/test_haar.cpp

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// @Authors
//    Jia Haipeng, jiahaipeng95@gmail.com
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#include "opencv2/objdetect/objdetect.hpp"
#include "precomp.hpp"

#ifdef HAVE_OPENCL

using namespace cvtest;
using namespace testing;
using namespace std;
using namespace cv;
extern string workdir;
struct getRect
{
    Rect operator ()(const CvAvgComp &e) const
    {
        return e.rect;
    }
};

PARAM_TEST_CASE(HaarTestBase, int, int)
{
    //std::vector<cv::ocl::Info> oclinfo;
    cv::ocl::OclCascadeClassifier cascade, nestedCascade;
    cv::CascadeClassifier cpucascade, cpunestedCascade;
    //    Mat img;

    double scale;
    int index;

    virtual void SetUp()
    {
        scale = 1.0;
        index = 0;
        string cascadeName = workdir + "../../data/haarcascades/haarcascade_frontalface_alt.xml";

        if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
        {
            cout << "ERROR: Could not load classifier cascade" << endl;
            return;
        }
        //int devnums = getDevice(oclinfo);
        //CV_Assert(devnums>0);
        ////if you want to use undefault device, set it here
        ////setDevice(oclinfo[0]);
        //cv::ocl::setBinpath("E:\\");
    }
};

////////////////////////////////faceDetect/////////////////////////////////////////////////

struct Haar : HaarTestBase {};

TEST_F(Haar, FaceDetect)
{
    string imgName = workdir + "lena.jpg";
    Mat img = imread( imgName, 1 );

    if(img.empty())
    {
        std::cout << "Couldn't read " << imgName << std::endl;
        return ;
    }

    //int i = 0;
    //double t = 0;
    vector<Rect> faces, oclfaces;

    const static Scalar colors[] =  { CV_RGB(0, 0, 255),
                                      CV_RGB(0, 128, 255),
                                      CV_RGB(0, 255, 255),
                                      CV_RGB(0, 255, 0),
                                      CV_RGB(255, 128, 0),
                                      CV_RGB(255, 255, 0),
                                      CV_RGB(255, 0, 0),
                                      CV_RGB(255, 0, 255)
                                    } ;

    Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
    MemStorage storage(cvCreateMemStorage(0));
    cvtColor( img, gray, CV_BGR2GRAY );
    resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
    equalizeHist( smallImg, smallImg );


    cv::ocl::oclMat image;
    CvSeq *_objects;
    image.upload(smallImg);
    _objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
               3, 0
               | CV_HAAR_SCALE_IMAGE
               , Size(30, 30), Size(0, 0) );
    vector<CvAvgComp> vecAvgComp;
    Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
    oclfaces.resize(vecAvgComp.size());
    std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());

    cpucascade.detectMultiScale( smallImg, faces,  1.1,
                                 3, 0
                                 | CV_HAAR_SCALE_IMAGE
                                 , Size(30, 30), Size(0, 0) );
    EXPECT_EQ(faces.size(), oclfaces.size());
    /*	for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
    {
    Mat smallImgROI;
    Point center;
    Scalar color = colors[i%8];
    int radius;
    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 );
    } */
    //namedWindow("result");
    //imshow("result",img);
    //waitKey(0);
    //destroyAllWindows();

}
#endif // HAVE_OPENCL