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     11 //                For Open Source Computer Vision Library
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     42 
     43 #include "perf_precomp.hpp"
     44 
     45 using namespace std;
     46 using namespace testing;
     47 using namespace perf;
     48 
     49 //////////////////////////////////////////////////////////////////////
     50 // Canny
     51 
     52 DEF_PARAM_TEST(Image_AppertureSz_L2gradient, string, int, bool);
     53 
     54 PERF_TEST_P(Image_AppertureSz_L2gradient, Canny,
     55             Combine(Values("perf/800x600.png", "perf/1280x1024.png", "perf/1680x1050.png"),
     56                     Values(3, 5),
     57                     Bool()))
     58 {
     59     const string fileName = GET_PARAM(0);
     60     const int apperture_size = GET_PARAM(1);
     61     const bool useL2gradient = GET_PARAM(2);
     62 
     63     const cv::Mat image = readImage(fileName, cv::IMREAD_GRAYSCALE);
     64     ASSERT_FALSE(image.empty());
     65 
     66     const double low_thresh = 50.0;
     67     const double high_thresh = 100.0;
     68 
     69     if (PERF_RUN_CUDA())
     70     {
     71         const cv::cuda::GpuMat d_image(image);
     72         cv::cuda::GpuMat dst;
     73 
     74         cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
     75 
     76         TEST_CYCLE() canny->detect(d_image, dst);
     77 
     78         CUDA_SANITY_CHECK(dst);
     79     }
     80     else
     81     {
     82         cv::Mat dst;
     83 
     84         TEST_CYCLE() cv::Canny(image, dst, low_thresh, high_thresh, apperture_size, useL2gradient);
     85 
     86         CPU_SANITY_CHECK(dst);
     87     }
     88 }
     89