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Open Source Computer Vision Library
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39 lines
1.3 KiB
39 lines
1.3 KiB
#include "perf_precomp.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<String, int, bool, std::tr1::tuple<double, double> > Img_Aperture_L2_thresholds_t; |
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typedef perf::TestBaseWithParam<Img_Aperture_L2_thresholds_t> Img_Aperture_L2_thresholds; |
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PERF_TEST_P( Img_Aperture_L2_thresholds, canny, |
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testing::Combine( |
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testing::Values( "cv/shared/lena.jpg", "stitching/b1.jpg", "cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png" ), |
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testing::Values( 3, 5 ), |
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testing::Bool(), |
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testing::Values( make_tuple(50.0, 100.0), make_tuple(0.0, 50.0), make_tuple(100.0, 120.0) ) |
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) |
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) |
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{ |
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String filename = getDataPath(get<0>(GetParam())); |
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int aperture = get<1>(GetParam()); |
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bool useL2 = get<2>(GetParam()); |
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double thresh_low = get<0>(get<3>(GetParam())); |
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double thresh_high = get<1>(get<3>(GetParam())); |
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Mat img = imread(filename, IMREAD_GRAYSCALE); |
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if (img.empty()) |
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FAIL() << "Unable to load source image " << filename; |
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Mat edges(img.size(), img.type()); |
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declare.in(img).out(edges); |
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TEST_CYCLE(100) { Canny(img, edges, thresh_low, thresh_high, aperture, useL2); } |
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SANITY_CHECK(edges); |
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}
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