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Open Source Computer Vision Library
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50 lines
1.6 KiB
50 lines
1.6 KiB
#include "perf_precomp.hpp" |
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#include <opencv2/imgproc/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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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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