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@ -116,6 +116,19 @@ PARAM_TEST_CASE(FilterTestBase, |
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gmat1 = mat1_roi; |
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} |
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void Init(int mat_type) |
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{ |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(size, mat_type, 5, 16); |
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dst = randomMat(size, mat_type, 5, 16); |
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} |
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void Near(double threshold) |
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{ |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, threshold, ""); |
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} |
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}; |
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/////////////////////////////////////////////////////////////////////////////////////////////////
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@ -131,12 +144,7 @@ struct Blur : FilterTestBase |
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type = GET_PARAM(0); |
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ksize = GET_PARAM(1); |
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bordertype = GET_PARAM(3); |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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Init(type); |
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} |
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}; |
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@ -145,20 +153,13 @@ TEST_P(Blur, Mat) |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::blur(mat1_roi, dst_roi, ksize, Point(-1, -1), bordertype); |
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cv::ocl::blur(gmat1, gdst, ksize, Point(-1, -1), bordertype); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, ""); |
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Near(1.0); |
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} |
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} |
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/////////////////////////////////////////////////////////////////////////////////////////////////
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//Laplacian
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struct Laplacian : FilterTestBase |
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@ -170,15 +171,8 @@ struct Laplacian : FilterTestBase |
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{ |
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type = GET_PARAM(0); |
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ksize = GET_PARAM(1); |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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Init(type); |
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} |
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}; |
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TEST_P(Laplacian, Accuracy) |
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@ -186,14 +180,9 @@ TEST_P(Laplacian, Accuracy) |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::Laplacian(mat1_roi, dst_roi, -1, ksize.width, 1); |
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cv::ocl::Laplacian(gmat1, gdst, -1, ksize.width, 1); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, ""); |
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Near(1e-5); |
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} |
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} |
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@ -213,45 +202,28 @@ struct ErodeDilate : FilterTestBase |
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{ |
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type = GET_PARAM(0); |
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iterations = GET_PARAM(3); |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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Init(type); |
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// rng.fill(kernel, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(3));
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kernel = randomMat(rng, Size(3, 3), CV_8UC1, 0, 3, false); |
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kernel = randomMat(Size(3, 3), CV_8UC1, 0, 3); |
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} |
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}; |
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// erode
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TEST_P(ErodeDilate, Mat) |
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{ |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::erode(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations); |
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cv::ocl::erode(gmat1, gdst, kernel, Point(-1, -1), iterations); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, ""); |
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Near(1e-5); |
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} |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::dilate(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations); |
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cv::ocl::dilate(gmat1, gdst, kernel, Point(-1, -1), iterations); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, ""); |
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Near(1e-5); |
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} |
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} |
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@ -272,15 +244,8 @@ struct Sobel : FilterTestBase |
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dx = s.width; |
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dy = s.height; |
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bordertype = GET_PARAM(3); |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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Init(type); |
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} |
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}; |
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TEST_P(Sobel, Mat) |
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@ -288,16 +253,10 @@ TEST_P(Sobel, Mat) |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::Sobel(mat1_roi, dst_roi, -1, dx, dy, ksize, /*scale*/0.00001,/*delta*/0, bordertype); |
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cv::ocl::Sobel(gmat1, gdst, -1, dx, dy, ksize,/*scale*/0.00001,/*delta*/0, bordertype); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1, ""); |
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Near(1); |
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} |
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} |
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@ -315,17 +274,8 @@ struct Scharr : FilterTestBase |
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dx = s.width; |
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dy = s.height; |
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bordertype = GET_PARAM(3); |
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dx = 1; |
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dy = 0; |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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Init(type); |
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} |
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}; |
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TEST_P(Scharr, Mat) |
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@ -333,14 +283,9 @@ TEST_P(Scharr, Mat) |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::Scharr(mat1_roi, dst_roi, -1, dx, dy, /*scale*/1,/*delta*/0, bordertype); |
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cv::ocl::Scharr(gmat1, gdst, -1, dx, dy,/*scale*/1,/*delta*/0, bordertype); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1, ""); |
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Near(1); |
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} |
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} |
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@ -360,18 +305,11 @@ struct GaussianBlur : FilterTestBase |
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type = GET_PARAM(0); |
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ksize = GET_PARAM(1); |
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bordertype = GET_PARAM(3); |
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Init(type); |
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cv::RNG &rng = TS::ptr()->get_rng(); |
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cv::Size size(MWIDTH, MHEIGHT); |
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sigma1 = rng.uniform(0.1, 1.0); |
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sigma2 = rng.uniform(0.1, 1.0); |
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mat1 = randomMat(rng, size, type, 5, 16, false); |
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dst = randomMat(rng, size, type, 5, 16, false); |
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} |
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}; |
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TEST_P(GaussianBlur, Mat) |
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@ -379,14 +317,9 @@ TEST_P(GaussianBlur, Mat) |
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for(int j = 0; j < LOOP_TIMES; j++) |
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{ |
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random_roi(); |
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cv::GaussianBlur(mat1_roi, dst_roi, ksize, sigma1, sigma2, bordertype); |
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cv::ocl::GaussianBlur(gmat1, gdst, ksize, sigma1, sigma2, bordertype); |
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cv::Mat cpu_dst; |
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gdst_whole.download(cpu_dst); |
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EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, ""); |
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Near(1); |
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} |
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} |
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@ -423,7 +356,7 @@ INSTANTIATE_TEST_CASE_P(Filter, Sobel, Combine( |
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INSTANTIATE_TEST_CASE_P(Filter, Scharr, Combine( |
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Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4), |
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Values(Size(0, 0)), //not use
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Values(Size(0, 0), Size(0, 1), Size(1, 0), Size(1, 1)),
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Values(Size(0, 1), Size(1, 0)),
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Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE))); |
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INSTANTIATE_TEST_CASE_P(Filter, GaussianBlur, Combine( |
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