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Open Source Computer Vision Library
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61 lines
2.0 KiB
61 lines
2.0 KiB
#include "../perf_precomp.hpp" |
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#include <opencv2/imgproc.hpp> |
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#include "opencv2/ts/ocl_perf.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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#ifdef HAVE_OPENCL |
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OCL_PERF_TEST_P(Cascade_Image_MinSize, CascadeClassifier, |
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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/haarcascade_frontalface_alt2.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 cascadePath = 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(cascadePath) ); |
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if (cc.empty()) |
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FAIL() << "Can't load cascade file: " << getDataPath(cascadePath); |
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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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cvtest::ocl::perf::safeFinish(); |
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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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#endif //HAVE_OPENCL
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