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Open Source Computer Vision Library
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66 lines
1.9 KiB
66 lines
1.9 KiB
#include "test_precomp.hpp" |
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#include <iomanip> |
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#include "opencv2/imgproc/imgproc_c.h" |
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#ifdef HAVE_OPENCL |
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using namespace cv; |
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using namespace cv::ocl; |
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using namespace cvtest; |
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using namespace testing; |
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using namespace std; |
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PARAM_TEST_CASE(MomentsTest, MatType, bool, bool) |
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{ |
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int type; |
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cv::Mat mat; |
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bool test_contours; |
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bool binaryImage; |
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virtual void SetUp() |
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{ |
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type = GET_PARAM(0); |
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test_contours = GET_PARAM(1); |
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cv::Size size(10 * MWIDTH, 10 * MHEIGHT); |
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mat = randomMat(size, type, 0, 256, false); |
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binaryImage = GET_PARAM(2); |
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} |
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void Compare(Moments& cpu, Moments& gpu) |
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{ |
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Mat gpu_dst, cpu_dst; |
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HuMoments(cpu, cpu_dst); |
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HuMoments(gpu, gpu_dst); |
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EXPECT_MAT_NEAR(gpu_dst,cpu_dst, 1e-3); |
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} |
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}; |
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OCL_TEST_P(MomentsTest, Mat) |
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{ |
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oclMat src_d(mat); |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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if(test_contours) |
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{ |
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Mat src = readImage( "cv/shared/pic3.png", IMREAD_GRAYSCALE ); |
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ASSERT_FALSE(src.empty()); |
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Mat canny_output; |
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vector<vector<Point> > contours; |
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vector<Vec4i> hierarchy; |
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Canny( src, canny_output, 100, 200, 3 ); |
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findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); |
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for( size_t i = 0; i < contours.size(); i++ ) |
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{ |
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Moments m = moments( contours[i], false ); |
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Moments dm = ocl::ocl_moments( contours[i]); |
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Compare(m, dm); |
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} |
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} |
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cv::Moments CvMom = cv::moments(mat, binaryImage); |
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cv::Moments oclMom = cv::ocl::ocl_moments(src_d, binaryImage); |
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Compare(CvMom, oclMom); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(OCL_ImgProc, MomentsTest, Combine( |
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Values(CV_8UC1, CV_16UC1, CV_16SC1, CV_32FC1, CV_64FC1), Values(false, true), Values(false, true))); |
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#endif // HAVE_OPENCL
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