adding Haar & LBP cascades perf test using UMat, removing old incomplete test
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modules/objdetect/perf/opencl/perf_cascades.cpp
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53
modules/objdetect/perf/opencl/perf_cascades.cpp
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#include "perf_precomp.hpp"
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#include <opencv2/imgproc.hpp>
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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typedef std::tr1::tuple<std::string, std::string, int> Cascade_Image_MinSize_t;
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typedef perf::TestBaseWithParam<Cascade_Image_MinSize_t> Cascade_Image_MinSize;
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PERF_TEST_P( Cascade_Image_MinSize, CascadeClassifier_UMat,
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testing::Combine(
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testing::Values( string("cv/cascadeandhog/cascades/haarcascade_frontalface_alt.xml"),
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string("cv/cascadeandhog/cascades/lbpcascade_frontalface.xml") ),
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testing::Values( string("cv/shared/lena.png"),
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string("cv/cascadeandhog/images/bttf301.png"),
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string("cv/cascadeandhog/images/class57.png") ),
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testing::Values(30, 64, 90) ) )
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{
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const string cascasePath = get<0>(GetParam());
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const string imagePath = get<1>(GetParam());
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int min_size = get<2>(GetParam());
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Size minSize(min_size, min_size);
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CascadeClassifier cc( getDataPath(cascasePath) );
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if (cc.empty())
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FAIL() << "Can't load cascade file: " << getDataPath(cascasePath);
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Mat img = imread(getDataPath(imagePath), IMREAD_GRAYSCALE);
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if (img.empty())
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FAIL() << "Can't load source image: " << getDataPath(imagePath);
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vector<Rect> faces;
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equalizeHist(img, img);
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declare.in(img).time(60);
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UMat uimg = img.getUMat(ACCESS_READ);
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while(next())
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{
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faces.clear();
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startTimer();
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cc.detectMultiScale(uimg, faces, 1.1, 3, 0, minSize);
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stopTimer();
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}
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sort(faces.begin(), faces.end(), comparators::RectLess());
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SANITY_CHECK(faces, min_size/5);
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}
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#include "perf_precomp.hpp"
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#include <opencv2/imgproc.hpp>
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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typedef std::tr1::tuple<std::string, int> ImageName_MinSize_t;
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typedef perf::TestBaseWithParam<ImageName_MinSize_t> ImageName_MinSize;
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PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace,
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testing::Combine(testing::Values( std::string("cv/shared/lena.png"),
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std::string("cv/shared/1_itseez-0000289.png"),
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std::string("cv/shared/1_itseez-0000492.png"),
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std::string("cv/shared/1_itseez-0000573.png")),
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testing::Values(24, 30, 40, 50, 60, 70, 80, 90)
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)
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)
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{
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const string filename = get<0>(GetParam());
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int min_size = get<1>(GetParam());
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Size minSize(min_size, min_size);
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CascadeClassifier cc(getDataPath("cv/cascadeandhog/cascades/lbpcascade_frontalface.xml"));
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if (cc.empty())
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FAIL() << "Can't load cascade file";
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Mat img = imread(getDataPath(filename), 0);
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if (img.empty())
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FAIL() << "Can't load source image";
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vector<Rect> faces;
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equalizeHist(img, img);
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declare.in(img);
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while(next())
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{
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faces.clear();
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startTimer();
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cc.detectMultiScale(img, faces, 1.1, 3, 0, minSize);
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stopTimer();
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}
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// for some reason OpenCL version detects the face, which CPU version does not detect, we just remove it
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// TODO better solution: implement smart way of comparing two set of rectangles
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if( filename == "cv/shared/1_itseez-0000492.png" && faces.size() == (size_t)3 )
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{
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faces.erase(faces.begin());
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}
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std::sort(faces.begin(), faces.end(), comparators::RectLess());
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SANITY_CHECK(faces, 3.001 * faces.size());
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}
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