Revert "call resetDevice if gpu test fails"

This reverts commit ab25fe9e37.

modules/gpu/test/nvidia/main_nvidia.cpp

@@ -276,8 +276,6 @@ static void devNullOutput(const std::string& msg)
     (void)msg;
 }
 
-}
-
 bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel)
 {
     path = test_data_path.c_str();
@@ -294,6 +292,8 @@ bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel
     return testListerII.invoke();
 }
 
+}
+
 bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel)
 {
     path = test_data_path;
@@ -439,4 +439,4 @@ bool nvidia_NCV_Visualization(const std::string& test_data_path, OutputLevel out
     return testListerVisualize.invoke();
 }
 
-#endif /* CUDA_DISABLER */
+#endif /* CUDA_DISABLER */

modules/gpu/test/test_calib3d.cpp

@@ -62,28 +62,20 @@ struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(StereoBM, Regression)
 {
-    try
-    {
-        cv::Mat left_image  = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
-        cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
-        cv::Mat disp_gold   = readImage("stereobm/aloe-disp.png", cv::IMREAD_GRAYSCALE);
+    cv::Mat left_image  = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
+    cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
+    cv::Mat disp_gold   = readImage("stereobm/aloe-disp.png", cv::IMREAD_GRAYSCALE);
 
-        ASSERT_FALSE(left_image.empty());
-        ASSERT_FALSE(right_image.empty());
-        ASSERT_FALSE(disp_gold.empty());
+    ASSERT_FALSE(left_image.empty());
+    ASSERT_FALSE(right_image.empty());
+    ASSERT_FALSE(disp_gold.empty());
 
-        cv::gpu::StereoBM_GPU bm(0, 128, 19);
-        cv::gpu::GpuMat disp;
+    cv::gpu::StereoBM_GPU bm(0, 128, 19);
+    cv::gpu::GpuMat disp;
 
-        bm(loadMat(left_image), loadMat(right_image), disp);
+    bm(loadMat(left_image), loadMat(right_image), disp);
 
-        EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBM, ALL_DEVICES);
@@ -105,31 +97,23 @@ struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(StereoBeliefPropagation, Regression)
 {
-    try
-    {
-        cv::Mat left_image  = readImage("stereobp/aloe-L.png");
-        cv::Mat right_image = readImage("stereobp/aloe-R.png");
-        cv::Mat disp_gold   = readImage("stereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
+    cv::Mat left_image  = readImage("stereobp/aloe-L.png");
+    cv::Mat right_image = readImage("stereobp/aloe-R.png");
+    cv::Mat disp_gold   = readImage("stereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
 
-        ASSERT_FALSE(left_image.empty());
-        ASSERT_FALSE(right_image.empty());
-        ASSERT_FALSE(disp_gold.empty());
+    ASSERT_FALSE(left_image.empty());
+    ASSERT_FALSE(right_image.empty());
+    ASSERT_FALSE(disp_gold.empty());
 
-        cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
-        cv::gpu::GpuMat disp;
+    cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
+    cv::gpu::GpuMat disp;
 
-        bp(loadMat(left_image), loadMat(right_image), disp);
+    bp(loadMat(left_image), loadMat(right_image), disp);
 
-        cv::Mat h_disp(disp);
-        h_disp.convertTo(h_disp, disp_gold.depth());
+    cv::Mat h_disp(disp);
+    h_disp.convertTo(h_disp, disp_gold.depth());
 
-        EXPECT_MAT_NEAR(disp_gold, h_disp, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(disp_gold, h_disp, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBeliefPropagation, ALL_DEVICES);
@@ -151,37 +135,29 @@ struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(StereoConstantSpaceBP, Regression)
 {
-    try
-    {
-        cv::Mat left_image  = readImage("csstereobp/aloe-L.png");
-        cv::Mat right_image = readImage("csstereobp/aloe-R.png");
+    cv::Mat left_image  = readImage("csstereobp/aloe-L.png");
+    cv::Mat right_image = readImage("csstereobp/aloe-R.png");
 
-        cv::Mat disp_gold;
+    cv::Mat disp_gold;
 
-        if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
-            disp_gold = readImage("csstereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
-        else
-            disp_gold = readImage("csstereobp/aloe-disp_CC1X.png", cv::IMREAD_GRAYSCALE);
+    if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
+        disp_gold = readImage("csstereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
+    else
+        disp_gold = readImage("csstereobp/aloe-disp_CC1X.png", cv::IMREAD_GRAYSCALE);
 
-        ASSERT_FALSE(left_image.empty());
-        ASSERT_FALSE(right_image.empty());
-        ASSERT_FALSE(disp_gold.empty());
+    ASSERT_FALSE(left_image.empty());
+    ASSERT_FALSE(right_image.empty());
+    ASSERT_FALSE(disp_gold.empty());
 
-        cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
-        cv::gpu::GpuMat disp;
+    cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
+    cv::gpu::GpuMat disp;
 
-        csbp(loadMat(left_image), loadMat(right_image), disp);
+    csbp(loadMat(left_image), loadMat(right_image), disp);
 
-        cv::Mat h_disp(disp);
-        h_disp.convertTo(h_disp, disp_gold.depth());
+    cv::Mat h_disp(disp);
+    h_disp.convertTo(h_disp, disp_gold.depth());
 
-        EXPECT_MAT_NEAR(disp_gold, h_disp, 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(disp_gold, h_disp, 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoConstantSpaceBP, ALL_DEVICES);
@@ -203,40 +179,32 @@ struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(TransformPoints, Accuracy)
 {
-    try
+    cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
+    cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+    cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+
+    cv::gpu::GpuMat dst;
+    cv::gpu::transformPoints(loadMat(src), rvec, tvec, dst);
+
+    ASSERT_EQ(src.size(), dst.size());
+    ASSERT_EQ(src.type(), dst.type());
+
+    cv::Mat h_dst(dst);
+
+    cv::Mat rot;
+    cv::Rodrigues(rvec, rot);
+
+    for (int i = 0; i < h_dst.cols; ++i)
     {
-        cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
-        cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
-        cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+        cv::Point3f res = h_dst.at<cv::Point3f>(0, i);
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::transformPoints(loadMat(src), rvec, tvec, dst);
+        cv::Point3f p = src.at<cv::Point3f>(0, i);
+        cv::Point3f res_gold(
+                rot.at<float>(0, 0) * p.x + rot.at<float>(0, 1) * p.y + rot.at<float>(0, 2) * p.z + tvec.at<float>(0, 0),
+                rot.at<float>(1, 0) * p.x + rot.at<float>(1, 1) * p.y + rot.at<float>(1, 2) * p.z + tvec.at<float>(0, 1),
+                rot.at<float>(2, 0) * p.x + rot.at<float>(2, 1) * p.y + rot.at<float>(2, 2) * p.z + tvec.at<float>(0, 2));
 
-        ASSERT_EQ(src.size(), dst.size());
-        ASSERT_EQ(src.type(), dst.type());
-
-        cv::Mat h_dst(dst);
-
-        cv::Mat rot;
-        cv::Rodrigues(rvec, rot);
-
-        for (int i = 0; i < h_dst.cols; ++i)
-        {
-            cv::Point3f res = h_dst.at<cv::Point3f>(0, i);
-
-            cv::Point3f p = src.at<cv::Point3f>(0, i);
-            cv::Point3f res_gold(
-                    rot.at<float>(0, 0) * p.x + rot.at<float>(0, 1) * p.y + rot.at<float>(0, 2) * p.z + tvec.at<float>(0, 0),
-                    rot.at<float>(1, 0) * p.x + rot.at<float>(1, 1) * p.y + rot.at<float>(1, 2) * p.z + tvec.at<float>(0, 1),
-                    rot.at<float>(2, 0) * p.x + rot.at<float>(2, 1) * p.y + rot.at<float>(2, 2) * p.z + tvec.at<float>(0, 2));
-
-            ASSERT_POINT3_NEAR(res_gold, res, 1e-5);
-        }
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        ASSERT_POINT3_NEAR(res_gold, res, 1e-5);
     }
 }
 
@@ -259,42 +227,34 @@ struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(ProjectPoints, Accuracy)
 {
-    try
+    cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
+    cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+    cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+    cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1);
+    camera_mat.at<float>(0, 1) = 0.f;
+    camera_mat.at<float>(1, 0) = 0.f;
+    camera_mat.at<float>(2, 0) = 0.f;
+    camera_mat.at<float>(2, 1) = 0.f;
+
+    cv::gpu::GpuMat dst;
+    cv::gpu::projectPoints(loadMat(src), rvec, tvec, camera_mat, cv::Mat(), dst);
+
+    ASSERT_EQ(1, dst.rows);
+    ASSERT_EQ(MatType(CV_32FC2), MatType(dst.type()));
+
+    std::vector<cv::Point2f> dst_gold;
+    cv::projectPoints(src, rvec, tvec, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), dst_gold);
+
+    ASSERT_EQ(dst_gold.size(), static_cast<size_t>(dst.cols));
+
+    cv::Mat h_dst(dst);
+
+    for (size_t i = 0; i < dst_gold.size(); ++i)
     {
-        cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
-        cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
-        cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
-        cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1);
-        camera_mat.at<float>(0, 1) = 0.f;
-        camera_mat.at<float>(1, 0) = 0.f;
-        camera_mat.at<float>(2, 0) = 0.f;
-        camera_mat.at<float>(2, 1) = 0.f;
+        cv::Point2f res = h_dst.at<cv::Point2f>(0, (int)i);
+        cv::Point2f res_gold = dst_gold[i];
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::projectPoints(loadMat(src), rvec, tvec, camera_mat, cv::Mat(), dst);
-
-        ASSERT_EQ(1, dst.rows);
-        ASSERT_EQ(MatType(CV_32FC2), MatType(dst.type()));
-
-        std::vector<cv::Point2f> dst_gold;
-        cv::projectPoints(src, rvec, tvec, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), dst_gold);
-
-        ASSERT_EQ(dst_gold.size(), static_cast<size_t>(dst.cols));
-
-        cv::Mat h_dst(dst);
-
-        for (size_t i = 0; i < dst_gold.size(); ++i)
-        {
-            cv::Point2f res = h_dst.at<cv::Point2f>(0, (int)i);
-            cv::Point2f res_gold = dst_gold[i];
-
-            ASSERT_LE(cv::norm(res_gold - res) / cv::norm(res_gold), 1e-3f);
-        }
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        ASSERT_LE(cv::norm(res_gold - res) / cv::norm(res_gold), 1e-3f);
     }
 }
 
@@ -317,36 +277,28 @@ struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(SolvePnPRansac, Accuracy)
 {
-    try
-    {
-        cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, 0, 100);
-        cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1);
-        camera_mat.at<float>(0, 1) = 0.f;
-        camera_mat.at<float>(1, 0) = 0.f;
-        camera_mat.at<float>(2, 0) = 0.f;
-        camera_mat.at<float>(2, 1) = 0.f;
+    cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, 0, 100);
+    cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1);
+    camera_mat.at<float>(0, 1) = 0.f;
+    camera_mat.at<float>(1, 0) = 0.f;
+    camera_mat.at<float>(2, 0) = 0.f;
+    camera_mat.at<float>(2, 1) = 0.f;
 
-        std::vector<cv::Point2f> image_vec;
-        cv::Mat rvec_gold;
-        cv::Mat tvec_gold;
-        rvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
-        tvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
-        cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), image_vec);
+    std::vector<cv::Point2f> image_vec;
+    cv::Mat rvec_gold;
+    cv::Mat tvec_gold;
+    rvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+    tvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
+    cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), image_vec);
 
-        cv::Mat rvec, tvec;
-        std::vector<int> inliers;
-        cv::gpu::solvePnPRansac(object, cv::Mat(1, (int)image_vec.size(), CV_32FC2, &image_vec[0]),
-                                camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)),
-                                rvec, tvec, false, 200, 2.f, 100, &inliers);
+    cv::Mat rvec, tvec;
+    std::vector<int> inliers;
+    cv::gpu::solvePnPRansac(object, cv::Mat(1, (int)image_vec.size(), CV_32FC2, &image_vec[0]),
+                            camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)),
+                            rvec, tvec, false, 200, 2.f, 100, &inliers);
 
-        ASSERT_LE(cv::norm(rvec - rvec_gold), 1e-3);
-        ASSERT_LE(cv::norm(tvec - tvec_gold), 1e-3);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_LE(cv::norm(rvec - rvec_gold), 1e-3);
+    ASSERT_LE(cv::norm(tvec - tvec_gold), 1e-3);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Calib3D, SolvePnPRansac, ALL_DEVICES);
@@ -374,24 +326,16 @@ PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, Use
 
 TEST_P(ReprojectImageTo3D, Accuracy)
 {
-    try
-    {
-        cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
-        cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
+    cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
+    cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::reprojectImageTo3D(loadMat(disp, useRoi), dst, Q, 3);
+    cv::gpu::GpuMat dst;
+    cv::gpu::reprojectImageTo3D(loadMat(disp, useRoi), dst, Q, 3);
 
-        cv::Mat dst_gold;
-        cv::reprojectImageTo3D(disp, dst_gold, Q, false);
+    cv::Mat dst_gold;
+    cv::reprojectImageTo3D(disp, dst_gold, Q, false);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ReprojectImageTo3D, testing::Combine(

modules/gpu/test/test_copy_make_border.cpp

@@ -71,24 +71,16 @@ PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border,
 
 TEST_P(CopyMakeBorder, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Scalar val = randomScalar(0, 255);
+    cv::Mat src = randomMat(size, type);
+    cv::Scalar val = randomScalar(0, 255);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size(size.width + 2 * border, size.height + 2 * border), type, useRoi);
-        cv::gpu::copyMakeBorder(loadMat(src, useRoi), dst, border, border, border, border, borderType, val);
+    cv::gpu::GpuMat dst = createMat(cv::Size(size.width + 2 * border, size.height + 2 * border), type, useRoi);
+    cv::gpu::copyMakeBorder(loadMat(src, useRoi), dst, border, border, border, border, borderType, val);
 
-        cv::Mat dst_gold;
-        cv::copyMakeBorder(src, dst_gold, border, border, border, border, borderType, val);
+    cv::Mat dst_gold;
+    cv::copyMakeBorder(src, dst_gold, border, border, border, border, borderType, val);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CopyMakeBorder, testing::Combine(

modules/gpu/test/test_denoising.cpp

@@ -71,25 +71,17 @@ PARAM_TEST_CASE(BilateralFilter, cv::gpu::DeviceInfo, cv::Size, MatType)
 
 TEST_P(BilateralFilter, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        src.convertTo(src, type);
-        cv::gpu::GpuMat dst;
+    src.convertTo(src, type);
+    cv::gpu::GpuMat dst;
 
-        cv::gpu::bilateralFilter(loadMat(src), dst, kernel_size, sigma_color, sigma_spatial);
+    cv::gpu::bilateralFilter(loadMat(src), dst, kernel_size, sigma_color, sigma_spatial);
 
-        cv::Mat dst_gold;
-        cv::bilateralFilter(src, dst_gold, kernel_size, sigma_color, sigma_spatial);
+    cv::Mat dst_gold;
+    cv::bilateralFilter(src, dst_gold, kernel_size, sigma_color, sigma_spatial);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Denoising, BilateralFilter, testing::Combine(
@@ -115,41 +107,35 @@ struct BruteForceNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(BruteForceNonLocalMeans, Regression)
 {
-    try
-    {
-        using cv::gpu::GpuMat;
+    using cv::gpu::GpuMat;
 
-        cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
-        ASSERT_FALSE(bgr.empty());
+    cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
+    ASSERT_FALSE(bgr.empty());
 
-        cv::Mat gray;
-        cv::cvtColor(bgr, gray, CV_BGR2GRAY);
+    cv::Mat gray;
+    cv::cvtColor(bgr, gray, CV_BGR2GRAY);
 
-        GpuMat dbgr, dgray;
-        cv::gpu::nonLocalMeans(GpuMat(bgr),  dbgr, 20);
-        cv::gpu::nonLocalMeans(GpuMat(gray), dgray, 20);
+    GpuMat dbgr, dgray;
+    cv::gpu::nonLocalMeans(GpuMat(bgr),  dbgr, 20);
+    cv::gpu::nonLocalMeans(GpuMat(gray), dgray, 20);
 
-    #if 0
-        dumpImage("denoising/nlm_denoised_lena_bgr.png", cv::Mat(dbgr));
-        dumpImage("denoising/nlm_denoised_lena_gray.png", cv::Mat(dgray));
-    #endif
+#if 0
+    dumpImage("denoising/nlm_denoised_lena_bgr.png", cv::Mat(dbgr));
+    dumpImage("denoising/nlm_denoised_lena_gray.png", cv::Mat(dgray));
+#endif
 
-        cv::Mat bgr_gold  = readImage("denoising/nlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
-        cv::Mat gray_gold  = readImage("denoising/nlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
+    cv::Mat bgr_gold  = readImage("denoising/nlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
+    cv::Mat gray_gold  = readImage("denoising/nlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
 
-        EXPECT_MAT_NEAR(bgr_gold, dbgr, 1e-4);
-        EXPECT_MAT_NEAR(gray_gold, dgray, 1e-4);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(bgr_gold, dbgr, 1e-4);
+    EXPECT_MAT_NEAR(gray_gold, dgray, 1e-4);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Denoising, BruteForceNonLocalMeans, ALL_DEVICES);
 
+
+
 ////////////////////////////////////////////////////////
 // Fast Force Non local means
 
@@ -166,41 +152,34 @@ struct FastNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(FastNonLocalMeans, Regression)
 {
-    try
-    {
-        using cv::gpu::GpuMat;
+    using cv::gpu::GpuMat;
 
-        cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
-        ASSERT_FALSE(bgr.empty());
+    cv::Mat bgr  = readImage("denoising/lena_noised_gaussian_sigma=20_multi_0.png", cv::IMREAD_COLOR);
+    ASSERT_FALSE(bgr.empty());
 
-        cv::Mat gray;
-        cv::cvtColor(bgr, gray, CV_BGR2GRAY);
+    cv::Mat gray;
+    cv::cvtColor(bgr, gray, CV_BGR2GRAY);
 
-        GpuMat dbgr, dgray;
-        cv::gpu::FastNonLocalMeansDenoising fnlmd;
+    GpuMat dbgr, dgray;
+    cv::gpu::FastNonLocalMeansDenoising fnlmd;
 
-        fnlmd.simpleMethod(GpuMat(gray),  dgray, 20);
-        fnlmd.labMethod(GpuMat(bgr),  dbgr, 20, 10);
+    fnlmd.simpleMethod(GpuMat(gray),  dgray, 20);
+    fnlmd.labMethod(GpuMat(bgr),  dbgr, 20, 10);
 
-    #if 0
-        //dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr));
-        //dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray));
-    #endif
+#if 0
+    //dumpImage("denoising/fnlm_denoised_lena_bgr.png", cv::Mat(dbgr));
+    //dumpImage("denoising/fnlm_denoised_lena_gray.png", cv::Mat(dgray));
+#endif
 
-        cv::Mat bgr_gold  = readImage("denoising/fnlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
-        cv::Mat gray_gold  = readImage("denoising/fnlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
+    cv::Mat bgr_gold  = readImage("denoising/fnlm_denoised_lena_bgr.png", cv::IMREAD_COLOR);
+    cv::Mat gray_gold  = readImage("denoising/fnlm_denoised_lena_gray.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(bgr_gold.empty() || gray_gold.empty());
 
-        EXPECT_MAT_NEAR(bgr_gold, dbgr, 1);
-        EXPECT_MAT_NEAR(gray_gold, dgray, 1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(bgr_gold, dbgr, 1);
+    EXPECT_MAT_NEAR(gray_gold, dgray, 1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Denoising, FastNonLocalMeans, ALL_DEVICES);
 
+
 #endif // HAVE_CUDA

modules/gpu/test/test_features2d.cpp

@@ -180,19 +180,31 @@ PARAM_TEST_CASE(SURF, cv::gpu::DeviceInfo, SURF_HessianThreshold, SURF_Octaves,
 
 TEST_P(SURF, Detector)
 {
-    try
+    cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(image.empty());
+
+    cv::gpu::SURF_GPU surf;
+    surf.hessianThreshold = hessianThreshold;
+    surf.nOctaves = nOctaves;
+    surf.nOctaveLayers = nOctaveLayers;
+    surf.extended = extended;
+    surf.upright = upright;
+    surf.keypointsRatio = 0.05f;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector<cv::KeyPoint> keypoints;
+            surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
     {
-        cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(image.empty());
-
-        cv::gpu::SURF_GPU surf;
-        surf.hessianThreshold = hessianThreshold;
-        surf.nOctaves = nOctaves;
-        surf.nOctaveLayers = nOctaveLayers;
-        surf.extended = extended;
-        surf.upright = upright;
-        surf.keypointsRatio = 0.05f;
-
         std::vector<cv::KeyPoint> keypoints;
         surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
 
@@ -212,31 +224,38 @@ TEST_P(SURF, Detector)
 
         EXPECT_GT(matchedRatio, 0.95);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 TEST_P(SURF, Detector_Masked)
 {
-    try
+    cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(image.empty());
+
+    cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
+    mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
+
+    cv::gpu::SURF_GPU surf;
+    surf.hessianThreshold = hessianThreshold;
+    surf.nOctaves = nOctaves;
+    surf.nOctaveLayers = nOctaveLayers;
+    surf.extended = extended;
+    surf.upright = upright;
+    surf.keypointsRatio = 0.05f;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector<cv::KeyPoint> keypoints;
+            surf(loadMat(image), loadMat(mask), keypoints);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
     {
-        cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(image.empty());
-
-        cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
-        mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
-
-        cv::gpu::SURF_GPU surf;
-        surf.hessianThreshold = hessianThreshold;
-        surf.nOctaves = nOctaves;
-        surf.nOctaveLayers = nOctaveLayers;
-        surf.extended = extended;
-        surf.upright = upright;
-        surf.keypointsRatio = 0.05f;
-
         std::vector<cv::KeyPoint> keypoints;
         surf(loadMat(image), loadMat(mask), keypoints);
 
@@ -256,35 +275,43 @@ TEST_P(SURF, Detector_Masked)
 
         EXPECT_GT(matchedRatio, 0.95);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 TEST_P(SURF, Descriptor)
 {
-    try
+    cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(image.empty());
+
+    cv::gpu::SURF_GPU surf;
+    surf.hessianThreshold = hessianThreshold;
+    surf.nOctaves = nOctaves;
+    surf.nOctaveLayers = nOctaveLayers;
+    surf.extended = extended;
+    surf.upright = upright;
+    surf.keypointsRatio = 0.05f;
+
+    cv::SURF surf_gold;
+    surf_gold.hessianThreshold = hessianThreshold;
+    surf_gold.nOctaves = nOctaves;
+    surf_gold.nOctaveLayers = nOctaveLayers;
+    surf_gold.extended = extended;
+    surf_gold.upright = upright;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector<cv::KeyPoint> keypoints;
+            cv::gpu::GpuMat descriptors;
+            surf(loadMat(image), cv::gpu::GpuMat(), keypoints, descriptors);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
     {
-        cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(image.empty());
-
-        cv::gpu::SURF_GPU surf;
-        surf.hessianThreshold = hessianThreshold;
-        surf.nOctaves = nOctaves;
-        surf.nOctaveLayers = nOctaveLayers;
-        surf.extended = extended;
-        surf.upright = upright;
-        surf.keypointsRatio = 0.05f;
-
-        cv::SURF surf_gold;
-        surf_gold.hessianThreshold = hessianThreshold;
-        surf_gold.nOctaves = nOctaves;
-        surf_gold.nOctaveLayers = nOctaveLayers;
-        surf_gold.extended = extended;
-        surf_gold.upright = upright;
-
         std::vector<cv::KeyPoint> keypoints;
         surf_gold(image, cv::noArray(), keypoints);
 
@@ -303,11 +330,6 @@ TEST_P(SURF, Descriptor)
 
         EXPECT_GT(matchedRatio, 0.6);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Features2D, SURF, testing::Combine(
@@ -342,14 +364,26 @@ PARAM_TEST_CASE(FAST, cv::gpu::DeviceInfo, FAST_Threshold, FAST_NonmaxSupression
 
 TEST_P(FAST, Accuracy)
 {
-    try
+    cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(image.empty());
+
+    cv::gpu::FAST_GPU fast(threshold);
+    fast.nonmaxSupression = nonmaxSupression;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector<cv::KeyPoint> keypoints;
+            fast(loadMat(image), cv::gpu::GpuMat(), keypoints);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
     {
-        cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(image.empty());
-
-        cv::gpu::FAST_GPU fast(threshold);
-        fast.nonmaxSupression = nonmaxSupression;
-
         std::vector<cv::KeyPoint> keypoints;
         fast(loadMat(image), cv::gpu::GpuMat(), keypoints);
 
@@ -358,11 +392,6 @@ TEST_P(FAST, Accuracy)
 
         ASSERT_KEYPOINTS_EQ(keypoints_gold, keypoints);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Features2D, FAST, testing::Combine(
@@ -416,17 +445,30 @@ PARAM_TEST_CASE(ORB, cv::gpu::DeviceInfo, ORB_FeaturesCount, ORB_ScaleFactor, OR
 
 TEST_P(ORB, Accuracy)
 {
-    try
+    cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(image.empty());
+
+    cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
+    mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
+
+    cv::gpu::ORB_GPU orb(nFeatures, scaleFactor, nLevels, edgeThreshold, firstLevel, WTA_K, scoreType, patchSize);
+    orb.blurForDescriptor = blurForDescriptor;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector<cv::KeyPoint> keypoints;
+            cv::gpu::GpuMat descriptors;
+            orb(loadMat(image), loadMat(mask), keypoints, descriptors);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
     {
-        cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(image.empty());
-
-        cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
-        mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
-
-        cv::gpu::ORB_GPU orb(nFeatures, scaleFactor, nLevels, edgeThreshold, firstLevel, WTA_K, scoreType, patchSize);
-        orb.blurForDescriptor = blurForDescriptor;
-
         std::vector<cv::KeyPoint> keypoints;
         cv::gpu::GpuMat descriptors;
         orb(loadMat(image), loadMat(mask), keypoints, descriptors);
@@ -446,11 +488,6 @@ TEST_P(ORB, Accuracy)
 
         EXPECT_GT(matchedRatio, 0.35);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Features2D, ORB,  testing::Combine(
@@ -533,156 +570,307 @@ PARAM_TEST_CASE(BruteForceMatcher, cv::gpu::DeviceInfo, NormCode, DescriptorSize
 
 TEST_P(BruteForceMatcher, Match_Single)
 {
-    try
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    cv::gpu::GpuMat mask;
+    if (useMask)
     {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
-
-        cv::gpu::GpuMat mask;
-        if (useMask)
-        {
-            mask.create(query.rows, train.rows, CV_8UC1);
-            mask.setTo(cv::Scalar::all(1));
-        }
-
-        std::vector<cv::DMatch> matches;
-        matcher.match(loadMat(query), loadMat(train), matches, mask);
-
-        ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-        int badCount = 0;
-        for (size_t i = 0; i < matches.size(); i++)
-        {
-            cv::DMatch match = matches[i];
-            if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor) || (match.imgIdx != 0))
-                badCount++;
-        }
-
-        ASSERT_EQ(0, badCount);
+        mask.create(query.rows, train.rows, CV_8UC1);
+        mask.setTo(cv::Scalar::all(1));
     }
-    catch (...)
+
+    std::vector<cv::DMatch> matches;
+    matcher.match(loadMat(query), loadMat(train), matches, mask);
+
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
+
+    int badCount = 0;
+    for (size_t i = 0; i < matches.size(); i++)
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::DMatch match = matches[i];
+        if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor) || (match.imgIdx != 0))
+            badCount++;
     }
+
+    ASSERT_EQ(0, badCount);
 }
 
 TEST_P(BruteForceMatcher, Match_Collection)
 {
-    try
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    cv::gpu::GpuMat d_train(train);
+
+    // make add() twice to test such case
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
+
+    // prepare masks (make first nearest match illegal)
+    std::vector<cv::gpu::GpuMat> masks(2);
+    for (int mi = 0; mi < 2; mi++)
     {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
+        masks[mi] = cv::gpu::GpuMat(query.rows, train.rows/2, CV_8UC1, cv::Scalar::all(1));
+        for (int di = 0; di < queryDescCount/2; di++)
+            masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+    }
 
-        cv::gpu::GpuMat d_train(train);
+    std::vector<cv::DMatch> matches;
+    if (useMask)
+        matcher.match(cv::gpu::GpuMat(query), matches, masks);
+    else
+        matcher.match(cv::gpu::GpuMat(query), matches);
 
-        // make add() twice to test such case
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
 
-        // prepare masks (make first nearest match illegal)
-        std::vector<cv::gpu::GpuMat> masks(2);
-        for (int mi = 0; mi < 2; mi++)
+    int badCount = 0;
+    int shift = useMask ? 1 : 0;
+    for (size_t i = 0; i < matches.size(); i++)
+    {
+        cv::DMatch match = matches[i];
+
+        if ((int)i < queryDescCount / 2)
         {
-            masks[mi] = cv::gpu::GpuMat(query.rows, train.rows/2, CV_8UC1, cv::Scalar::all(1));
-            for (int di = 0; di < queryDescCount/2; di++)
-                masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+            bool validQueryIdx = (match.queryIdx == (int)i);
+            bool validTrainIdx = (match.trainIdx == (int)i * countFactor + shift);
+            bool validImgIdx = (match.imgIdx == 0);
+            if (!validQueryIdx || !validTrainIdx || !validImgIdx)
+                badCount++;
         }
-
-        std::vector<cv::DMatch> matches;
-        if (useMask)
-            matcher.match(cv::gpu::GpuMat(query), matches, masks);
         else
-            matcher.match(cv::gpu::GpuMat(query), matches);
-
-        ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-        int badCount = 0;
-        int shift = useMask ? 1 : 0;
-        for (size_t i = 0; i < matches.size(); i++)
         {
-            cv::DMatch match = matches[i];
-
-            if ((int)i < queryDescCount / 2)
-            {
-                bool validQueryIdx = (match.queryIdx == (int)i);
-                bool validTrainIdx = (match.trainIdx == (int)i * countFactor + shift);
-                bool validImgIdx = (match.imgIdx == 0);
-                if (!validQueryIdx || !validTrainIdx || !validImgIdx)
-                    badCount++;
-            }
-            else
-            {
-                bool validQueryIdx = (match.queryIdx == (int)i);
-                bool validTrainIdx = (match.trainIdx == ((int)i - queryDescCount / 2) * countFactor + shift);
-                bool validImgIdx = (match.imgIdx == 1);
-                if (!validQueryIdx || !validTrainIdx || !validImgIdx)
-                    badCount++;
-            }
+            bool validQueryIdx = (match.queryIdx == (int)i);
+            bool validTrainIdx = (match.trainIdx == ((int)i - queryDescCount / 2) * countFactor + shift);
+            bool validImgIdx = (match.imgIdx == 1);
+            if (!validQueryIdx || !validTrainIdx || !validImgIdx)
+                badCount++;
         }
+    }
 
-        ASSERT_EQ(0, badCount);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_EQ(0, badCount);
 }
 
 TEST_P(BruteForceMatcher, KnnMatch_2_Single)
 {
-    try
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const int knn = 2;
+
+    cv::gpu::GpuMat mask;
+    if (useMask)
     {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
+        mask.create(query.rows, train.rows, CV_8UC1);
+        mask.setTo(cv::Scalar::all(1));
+    }
 
-        const int knn = 2;
+    std::vector< std::vector<cv::DMatch> > matches;
+    matcher.knnMatch(loadMat(query), loadMat(train), matches, knn, mask);
 
-        cv::gpu::GpuMat mask;
-        if (useMask)
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
+
+    int badCount = 0;
+    for (size_t i = 0; i < matches.size(); i++)
+    {
+        if ((int)matches[i].size() != knn)
+            badCount++;
+        else
         {
-            mask.create(query.rows, train.rows, CV_8UC1);
-            mask.setTo(cv::Scalar::all(1));
-        }
-
-        std::vector< std::vector<cv::DMatch> > matches;
-        matcher.knnMatch(loadMat(query), loadMat(train), matches, knn, mask);
-
-        ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-        int badCount = 0;
-        for (size_t i = 0; i < matches.size(); i++)
-        {
-            if ((int)matches[i].size() != knn)
-                badCount++;
-            else
+            int localBadCount = 0;
+            for (int k = 0; k < knn; k++)
             {
-                int localBadCount = 0;
-                for (int k = 0; k < knn; k++)
-                {
-                    cv::DMatch match = matches[i][k];
-                    if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
-                        localBadCount++;
-                }
-                badCount += localBadCount > 0 ? 1 : 0;
+                cv::DMatch match = matches[i][k];
+                if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
+                    localBadCount++;
             }
+            badCount += localBadCount > 0 ? 1 : 0;
         }
+    }
 
-        ASSERT_EQ(0, badCount);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_EQ(0, badCount);
 }
 
 TEST_P(BruteForceMatcher, KnnMatch_3_Single)
 {
-    try
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const int knn = 3;
+
+    cv::gpu::GpuMat mask;
+    if (useMask)
     {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
+        mask.create(query.rows, train.rows, CV_8UC1);
+        mask.setTo(cv::Scalar::all(1));
+    }
 
-        const int knn = 3;
+    std::vector< std::vector<cv::DMatch> > matches;
+    matcher.knnMatch(loadMat(query), loadMat(train), matches, knn, mask);
 
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
+
+    int badCount = 0;
+    for (size_t i = 0; i < matches.size(); i++)
+    {
+        if ((int)matches[i].size() != knn)
+            badCount++;
+        else
+        {
+            int localBadCount = 0;
+            for (int k = 0; k < knn; k++)
+            {
+                cv::DMatch match = matches[i][k];
+                if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
+                    localBadCount++;
+            }
+            badCount += localBadCount > 0 ? 1 : 0;
+        }
+    }
+
+    ASSERT_EQ(0, badCount);
+}
+
+TEST_P(BruteForceMatcher, KnnMatch_2_Collection)
+{
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const int knn = 2;
+
+    cv::gpu::GpuMat d_train(train);
+
+    // make add() twice to test such case
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
+
+    // prepare masks (make first nearest match illegal)
+    std::vector<cv::gpu::GpuMat> masks(2);
+    for (int mi = 0; mi < 2; mi++ )
+    {
+        masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
+        for (int di = 0; di < queryDescCount / 2; di++)
+            masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+    }
+
+    std::vector< std::vector<cv::DMatch> > matches;
+
+    if (useMask)
+        matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn, masks);
+    else
+        matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn);
+
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
+
+    int badCount = 0;
+    int shift = useMask ? 1 : 0;
+    for (size_t i = 0; i < matches.size(); i++)
+    {
+        if ((int)matches[i].size() != knn)
+            badCount++;
+        else
+        {
+            int localBadCount = 0;
+            for (int k = 0; k < knn; k++)
+            {
+                cv::DMatch match = matches[i][k];
+                {
+                    if ((int)i < queryDescCount / 2)
+                    {
+                        if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k + shift) || (match.imgIdx != 0) )
+                            localBadCount++;
+                    }
+                    else
+                    {
+                        if ((match.queryIdx != (int)i) || (match.trainIdx != ((int)i - queryDescCount / 2) * countFactor + k + shift) || (match.imgIdx != 1) )
+                            localBadCount++;
+                    }
+                }
+            }
+            badCount += localBadCount > 0 ? 1 : 0;
+        }
+    }
+
+    ASSERT_EQ(0, badCount);
+}
+
+TEST_P(BruteForceMatcher, KnnMatch_3_Collection)
+{
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const int knn = 3;
+
+    cv::gpu::GpuMat d_train(train);
+
+    // make add() twice to test such case
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
+
+    // prepare masks (make first nearest match illegal)
+    std::vector<cv::gpu::GpuMat> masks(2);
+    for (int mi = 0; mi < 2; mi++ )
+    {
+        masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
+        for (int di = 0; di < queryDescCount / 2; di++)
+            masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+    }
+
+    std::vector< std::vector<cv::DMatch> > matches;
+
+    if (useMask)
+        matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn, masks);
+    else
+        matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn);
+
+    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
+
+    int badCount = 0;
+    int shift = useMask ? 1 : 0;
+    for (size_t i = 0; i < matches.size(); i++)
+    {
+        if ((int)matches[i].size() != knn)
+            badCount++;
+        else
+        {
+            int localBadCount = 0;
+            for (int k = 0; k < knn; k++)
+            {
+                cv::DMatch match = matches[i][k];
+                {
+                    if ((int)i < queryDescCount / 2)
+                    {
+                        if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k + shift) || (match.imgIdx != 0) )
+                            localBadCount++;
+                    }
+                    else
+                    {
+                        if ((match.queryIdx != (int)i) || (match.trainIdx != ((int)i - queryDescCount / 2) * countFactor + k + shift) || (match.imgIdx != 1) )
+                            localBadCount++;
+                    }
+                }
+            }
+            badCount += localBadCount > 0 ? 1 : 0;
+        }
+    }
+
+    ASSERT_EQ(0, badCount);
+}
+
+TEST_P(BruteForceMatcher, RadiusMatch_Single)
+{
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const float radius = 1.f / countFactor;
+
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
+        {
+            std::vector< std::vector<cv::DMatch> > matches;
+            matcher.radiusMatch(loadMat(query), loadMat(train), matches, radius);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
+    {
         cv::gpu::GpuMat mask;
         if (useMask)
         {
@@ -691,258 +879,63 @@ TEST_P(BruteForceMatcher, KnnMatch_3_Single)
         }
 
         std::vector< std::vector<cv::DMatch> > matches;
-        matcher.knnMatch(loadMat(query), loadMat(train), matches, knn, mask);
+        matcher.radiusMatch(loadMat(query), loadMat(train), matches, radius, mask);
 
         ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
 
         int badCount = 0;
         for (size_t i = 0; i < matches.size(); i++)
         {
-            if ((int)matches[i].size() != knn)
+            if ((int)matches[i].size() != 1)
                 badCount++;
             else
             {
-                int localBadCount = 0;
-                for (int k = 0; k < knn; k++)
-                {
-                    cv::DMatch match = matches[i][k];
-                    if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
-                        localBadCount++;
-                }
-                badCount += localBadCount > 0 ? 1 : 0;
-            }
-        }
-
-        ASSERT_EQ(0, badCount);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
-}
-
-TEST_P(BruteForceMatcher, KnnMatch_2_Collection)
-{
-    try
-    {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
-
-        const int knn = 2;
-
-        cv::gpu::GpuMat d_train(train);
-
-        // make add() twice to test such case
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
-
-        // prepare masks (make first nearest match illegal)
-        std::vector<cv::gpu::GpuMat> masks(2);
-        for (int mi = 0; mi < 2; mi++ )
-        {
-            masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
-            for (int di = 0; di < queryDescCount / 2; di++)
-                masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
-        }
-
-        std::vector< std::vector<cv::DMatch> > matches;
-
-        if (useMask)
-            matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn, masks);
-        else
-            matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn);
-
-        ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-        int badCount = 0;
-        int shift = useMask ? 1 : 0;
-        for (size_t i = 0; i < matches.size(); i++)
-        {
-            if ((int)matches[i].size() != knn)
-                badCount++;
-            else
-            {
-                int localBadCount = 0;
-                for (int k = 0; k < knn; k++)
-                {
-                    cv::DMatch match = matches[i][k];
-                    {
-                        if ((int)i < queryDescCount / 2)
-                        {
-                            if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k + shift) || (match.imgIdx != 0) )
-                                localBadCount++;
-                        }
-                        else
-                        {
-                            if ((match.queryIdx != (int)i) || (match.trainIdx != ((int)i - queryDescCount / 2) * countFactor + k + shift) || (match.imgIdx != 1) )
-                                localBadCount++;
-                        }
-                    }
-                }
-                badCount += localBadCount > 0 ? 1 : 0;
-            }
-        }
-
-        ASSERT_EQ(0, badCount);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
-}
-
-TEST_P(BruteForceMatcher, KnnMatch_3_Collection)
-{
-    try
-    {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
-
-        const int knn = 3;
-
-        cv::gpu::GpuMat d_train(train);
-
-        // make add() twice to test such case
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
-
-        // prepare masks (make first nearest match illegal)
-        std::vector<cv::gpu::GpuMat> masks(2);
-        for (int mi = 0; mi < 2; mi++ )
-        {
-            masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
-            for (int di = 0; di < queryDescCount / 2; di++)
-                masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
-        }
-
-        std::vector< std::vector<cv::DMatch> > matches;
-
-        if (useMask)
-            matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn, masks);
-        else
-            matcher.knnMatch(cv::gpu::GpuMat(query), matches, knn);
-
-        ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-        int badCount = 0;
-        int shift = useMask ? 1 : 0;
-        for (size_t i = 0; i < matches.size(); i++)
-        {
-            if ((int)matches[i].size() != knn)
-                badCount++;
-            else
-            {
-                int localBadCount = 0;
-                for (int k = 0; k < knn; k++)
-                {
-                    cv::DMatch match = matches[i][k];
-                    {
-                        if ((int)i < queryDescCount / 2)
-                        {
-                            if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k + shift) || (match.imgIdx != 0) )
-                                localBadCount++;
-                        }
-                        else
-                        {
-                            if ((match.queryIdx != (int)i) || (match.trainIdx != ((int)i - queryDescCount / 2) * countFactor + k + shift) || (match.imgIdx != 1) )
-                                localBadCount++;
-                        }
-                    }
-                }
-                badCount += localBadCount > 0 ? 1 : 0;
-            }
-        }
-
-        ASSERT_EQ(0, badCount);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
-}
-
-TEST_P(BruteForceMatcher, RadiusMatch_Single)
-{
-    try
-    {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
-
-        const float radius = 1.f / countFactor;
-
-        if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
-        {
-            try
-            {
-                std::vector< std::vector<cv::DMatch> > matches;
-                matcher.radiusMatch(loadMat(query), loadMat(train), matches, radius);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsNotImplemented, e.code);
-            }
-        }
-        else
-        {
-            cv::gpu::GpuMat mask;
-            if (useMask)
-            {
-                mask.create(query.rows, train.rows, CV_8UC1);
-                mask.setTo(cv::Scalar::all(1));
-            }
-
-            std::vector< std::vector<cv::DMatch> > matches;
-            matcher.radiusMatch(loadMat(query), loadMat(train), matches, radius, mask);
-
-            ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());
-
-            int badCount = 0;
-            for (size_t i = 0; i < matches.size(); i++)
-            {
-                if ((int)matches[i].size() != 1)
+                cv::DMatch match = matches[i][0];
+                if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0))
                     badCount++;
-                else
-                {
-                    cv::DMatch match = matches[i][0];
-                    if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0))
-                        badCount++;
-                }
             }
-
-            ASSERT_EQ(0, badCount);
         }
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+
+        ASSERT_EQ(0, badCount);
     }
 }
 
 TEST_P(BruteForceMatcher, RadiusMatch_Collection)
 {
-    try
+    cv::gpu::BFMatcher_GPU matcher(normCode);
+
+    const int n = 3;
+    const float radius = 1.f / countFactor * n;
+
+    cv::gpu::GpuMat d_train(train);
+
+    // make add() twice to test such case
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
+    matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
+
+    // prepare masks (make first nearest match illegal)
+    std::vector<cv::gpu::GpuMat> masks(2);
+    for (int mi = 0; mi < 2; mi++)
     {
-        cv::gpu::BFMatcher_GPU matcher(normCode);
+        masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
+        for (int di = 0; di < queryDescCount / 2; di++)
+            masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+    }
 
-        const int n = 3;
-        const float radius = 1.f / countFactor * n;
-
-        cv::gpu::GpuMat d_train(train);
-
-        // make add() twice to test such case
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
-        matcher.add(std::vector<cv::gpu::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)));
-
-        // prepare masks (make first nearest match illegal)
-        std::vector<cv::gpu::GpuMat> masks(2);
-        for (int mi = 0; mi < 2; mi++)
+    if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
+    {
+        try
         {
-            masks[mi] = cv::gpu::GpuMat(query.rows, train.rows / 2, CV_8UC1, cv::Scalar::all(1));
-            for (int di = 0; di < queryDescCount / 2; di++)
-                masks[mi].col(di * countFactor).setTo(cv::Scalar::all(0));
+            std::vector< std::vector<cv::DMatch> > matches;
+            matcher.radiusMatch(cv::gpu::GpuMat(query), matches, radius, masks);
         }
-
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
+        }
+    }
+    else
+    {
         std::vector< std::vector<cv::DMatch> > matches;
 
         if (useMask)
@@ -984,11 +977,6 @@ TEST_P(BruteForceMatcher, RadiusMatch_Collection)
 
         ASSERT_EQ(0, badCount);
     }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Features2D, BruteForceMatcher, testing::Combine(

modules/gpu/test/test_filters.cpp

@@ -88,23 +88,15 @@ PARAM_TEST_CASE(Blur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, Use
 
 TEST_P(Blur, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::blur(loadMat(src, useRoi), dst, ksize, anchor);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::blur(loadMat(src, useRoi), dst, ksize, anchor);
 
-        cv::Mat dst_gold;
-        cv::blur(src, dst_gold, ksize, anchor);
+    cv::Mat dst_gold;
+    cv::blur(src, dst_gold, ksize, anchor);
 
-        EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Blur, testing::Combine(
@@ -158,23 +150,15 @@ TEST_P(Sobel, Accuracy)
     if (dx == 0 && dy == 0)
         return;
 
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::Sobel(loadMat(src, useRoi), dst, -1, dx, dy, ksize.width, 1.0, borderType);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::Sobel(loadMat(src, useRoi), dst, -1, dx, dy, ksize.width, 1.0, borderType);
 
-        cv::Mat dst_gold;
-        cv::Sobel(src, dst_gold, -1, dx, dy, ksize.width, 1.0, 0.0, borderType);
+    cv::Mat dst_gold;
+    cv::Sobel(src, dst_gold, -1, dx, dy, ksize.width, 1.0, 0.0, borderType);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
@@ -229,23 +213,15 @@ TEST_P(Scharr, Accuracy)
     if (dx + dy != 1)
         return;
 
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::Scharr(loadMat(src, useRoi), dst, -1, dx, dy, 1.0, borderType);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::Scharr(loadMat(src, useRoi), dst, -1, dx, dy, 1.0, borderType);
 
-        cv::Mat dst_gold;
-        cv::Scharr(src, dst_gold, -1, dx, dy, 1.0, 0.0, borderType);
+    cv::Mat dst_gold;
+    cv::Scharr(src, dst_gold, -1, dx, dy, 1.0, 0.0, borderType);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Scharr, testing::Combine(
@@ -294,39 +270,31 @@ PARAM_TEST_CASE(GaussianBlur, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels,
 
 TEST_P(GaussianBlur, Accuracy)
 {
-    try
+    cv::Mat src = randomMat(size, type);
+    double sigma1 = randomDouble(0.1, 1.0);
+    double sigma2 = randomDouble(0.1, 1.0);
+
+    if (ksize.height > 16 && !supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
     {
-        cv::Mat src = randomMat(size, type);
-        double sigma1 = randomDouble(0.1, 1.0);
-        double sigma2 = randomDouble(0.1, 1.0);
-
-        if (ksize.height > 16 && !supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
+        try
         {
-            try
-            {
-                cv::gpu::GpuMat dst;
-                cv::gpu::GaussianBlur(loadMat(src), dst, ksize, sigma1, sigma2, borderType);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsNotImplemented, e.code);
-            }
+            cv::gpu::GpuMat dst;
+            cv::gpu::GaussianBlur(loadMat(src), dst, ksize, sigma1, sigma2, borderType);
         }
-        else
+        catch (const cv::Exception& e)
         {
-            cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-            cv::gpu::GaussianBlur(loadMat(src, useRoi), dst, ksize, sigma1, sigma2, borderType);
-
-            cv::Mat dst_gold;
-            cv::GaussianBlur(src, dst_gold, ksize, sigma1, sigma2, borderType);
-
-            EXPECT_MAT_NEAR(dst_gold, dst, 4.0);
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+        cv::gpu::GaussianBlur(loadMat(src, useRoi), dst, ksize, sigma1, sigma2, borderType);
+
+        cv::Mat dst_gold;
+        cv::GaussianBlur(src, dst_gold, ksize, sigma1, sigma2, borderType);
+
+        EXPECT_MAT_NEAR(dst_gold, dst, 4.0);
     }
 }
 
@@ -381,23 +349,15 @@ PARAM_TEST_CASE(Laplacian, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, UseRoi
 
 TEST_P(Laplacian, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::Laplacian(loadMat(src, useRoi), dst, -1, ksize.width);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::Laplacian(loadMat(src, useRoi), dst, -1, ksize.width);
 
-        cv::Mat dst_gold;
-        cv::Laplacian(src, dst_gold, -1, ksize.width);
+    cv::Mat dst_gold;
+    cv::Laplacian(src, dst_gold, -1, ksize.width);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() < CV_32F ? 0.0 : 1e-3);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() < CV_32F ? 0.0 : 1e-3);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Laplacian, testing::Combine(
@@ -436,26 +396,18 @@ PARAM_TEST_CASE(Erode, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteration
 
 TEST_P(Erode, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::erode(loadMat(src, useRoi), dst, kernel, anchor, iterations);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::erode(loadMat(src, useRoi), dst, kernel, anchor, iterations);
 
-        cv::Mat dst_gold;
-        cv::erode(src, dst_gold, kernel, anchor, iterations);
+    cv::Mat dst_gold;
+    cv::erode(src, dst_gold, kernel, anchor, iterations);
 
-        cv::Size ksize = cv::Size(kernel.cols + iterations * (kernel.cols - 1), kernel.rows + iterations * (kernel.rows - 1));
+    cv::Size ksize = cv::Size(kernel.cols + iterations * (kernel.cols - 1), kernel.rows + iterations * (kernel.rows - 1));
 
-        EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Erode, testing::Combine(
@@ -493,26 +445,18 @@ PARAM_TEST_CASE(Dilate, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteratio
 
 TEST_P(Dilate, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::dilate(loadMat(src, useRoi), dst, kernel, anchor, iterations);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::dilate(loadMat(src, useRoi), dst, kernel, anchor, iterations);
 
-        cv::Mat dst_gold;
-        cv::dilate(src, dst_gold, kernel, anchor, iterations);
+    cv::Mat dst_gold;
+    cv::dilate(src, dst_gold, kernel, anchor, iterations);
 
-        cv::Size ksize = cv::Size(kernel.cols + iterations * (kernel.cols - 1), kernel.rows + iterations * (kernel.rows - 1));
+    cv::Size ksize = cv::Size(kernel.cols + iterations * (kernel.cols - 1), kernel.rows + iterations * (kernel.rows - 1));
 
-        EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Dilate, testing::Combine(
@@ -555,26 +499,18 @@ PARAM_TEST_CASE(MorphEx, cv::gpu::DeviceInfo, cv::Size, MatType, MorphOp, Anchor
 
 TEST_P(MorphEx, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::morphologyEx(loadMat(src, useRoi), dst, morphOp, kernel, anchor, iterations);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::morphologyEx(loadMat(src, useRoi), dst, morphOp, kernel, anchor, iterations);
 
-        cv::Mat dst_gold;
-        cv::morphologyEx(src, dst_gold, morphOp, kernel, anchor, iterations);
+    cv::Mat dst_gold;
+    cv::morphologyEx(src, dst_gold, morphOp, kernel, anchor, iterations);
 
-        cv::Size border = cv::Size(kernel.cols + (iterations + 1) * kernel.cols + 2, kernel.rows + (iterations + 1) * kernel.rows + 2);
+    cv::Size border = cv::Size(kernel.cols + (iterations + 1) * kernel.cols + 2, kernel.rows + (iterations + 1) * kernel.rows + 2);
 
-        EXPECT_MAT_NEAR(getInnerROI(dst_gold, border), getInnerROI(dst, border), 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, border), getInnerROI(dst, border), 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, MorphEx, testing::Combine(
@@ -617,24 +553,16 @@ PARAM_TEST_CASE(Filter2D, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor,
 
 TEST_P(Filter2D, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::filter2D(loadMat(src, useRoi), dst, -1, kernel, anchor, borderType);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::filter2D(loadMat(src, useRoi), dst, -1, kernel, anchor, borderType);
 
-        cv::Mat dst_gold;
-        cv::filter2D(src, dst_gold, -1, kernel, anchor, 0, borderType);
+    cv::Mat dst_gold;
+    cv::filter2D(src, dst_gold, -1, kernel, anchor, 0, borderType);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) == CV_32F ? 1e-1 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) == CV_32F ? 1e-1 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Filter2D, testing::Combine(

modules/gpu/test/test_global_motion.cpp

@@ -53,43 +53,35 @@ struct CompactPoints : testing::TestWithParam<gpu::DeviceInfo>
 
 TEST_P(CompactPoints, CanCompactizeSmallInput)
 {
-    try
-    {
-        Mat src0(1, 3, CV_32FC2);
-        src0.at<Point2f>(0,0) = Point2f(0,0);
-        src0.at<Point2f>(0,1) = Point2f(0,1);
-        src0.at<Point2f>(0,2) = Point2f(0,2);
+    Mat src0(1, 3, CV_32FC2);
+    src0.at<Point2f>(0,0) = Point2f(0,0);
+    src0.at<Point2f>(0,1) = Point2f(0,1);
+    src0.at<Point2f>(0,2) = Point2f(0,2);
 
-        Mat src1(1, 3, CV_32FC2);
-        src1.at<Point2f>(0,0) = Point2f(1,0);
-        src1.at<Point2f>(0,1) = Point2f(1,1);
-        src1.at<Point2f>(0,2) = Point2f(1,2);
+    Mat src1(1, 3, CV_32FC2);
+    src1.at<Point2f>(0,0) = Point2f(1,0);
+    src1.at<Point2f>(0,1) = Point2f(1,1);
+    src1.at<Point2f>(0,2) = Point2f(1,2);
 
-        Mat mask(1, 3, CV_8U);
-        mask.at<uchar>(0,0) = 1;
-        mask.at<uchar>(0,1) = 0;
-        mask.at<uchar>(0,2) = 1;
+    Mat mask(1, 3, CV_8U);
+    mask.at<uchar>(0,0) = 1;
+    mask.at<uchar>(0,1) = 0;
+    mask.at<uchar>(0,2) = 1;
 
-        gpu::GpuMat dsrc0(src0), dsrc1(src1), dmask(mask);
-        gpu::compactPoints(dsrc0, dsrc1, dmask);
+    gpu::GpuMat dsrc0(src0), dsrc1(src1), dmask(mask);
+    gpu::compactPoints(dsrc0, dsrc1, dmask);
 
-        dsrc0.download(src0);
-        dsrc1.download(src1);
+    dsrc0.download(src0);
+    dsrc1.download(src1);
 
-        ASSERT_EQ(2, src0.cols);
-        ASSERT_EQ(2, src1.cols);
+    ASSERT_EQ(2, src0.cols);
+    ASSERT_EQ(2, src1.cols);
 
-        ASSERT_TRUE(src0.at<Point2f>(0,0) == Point2f(0,0));
-        ASSERT_TRUE(src0.at<Point2f>(0,1) == Point2f(0,2));
+    ASSERT_TRUE(src0.at<Point2f>(0,0) == Point2f(0,0));
+    ASSERT_TRUE(src0.at<Point2f>(0,1) == Point2f(0,2));
 
-        ASSERT_TRUE(src1.at<Point2f>(0,0) == Point2f(1,0));
-        ASSERT_TRUE(src1.at<Point2f>(0,1) == Point2f(1,2));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(src1.at<Point2f>(0,0) == Point2f(1,0));
+    ASSERT_TRUE(src1.at<Point2f>(0,1) == Point2f(1,2));
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_GlobalMotion, CompactPoints, ALL_DEVICES);

modules/gpu/test/test_gpumat.cpp

@@ -69,122 +69,90 @@ PARAM_TEST_CASE(SetTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
 
 TEST_P(SetTo, Zero)
 {
-    try
-    {
-        cv::Scalar zero = cv::Scalar::all(0);
+    cv::Scalar zero = cv::Scalar::all(0);
 
-        cv::gpu::GpuMat mat = createMat(size, type, useRoi);
-        mat.setTo(zero);
+    cv::gpu::GpuMat mat = createMat(size, type, useRoi);
+    mat.setTo(zero);
 
-        EXPECT_MAT_NEAR(cv::Mat::zeros(size, type), mat, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(cv::Mat::zeros(size, type), mat, 0.0);
 }
 
 TEST_P(SetTo, SameVal)
 {
-    try
-    {
-        cv::Scalar val = cv::Scalar::all(randomDouble(0.0, 255.0));
+    cv::Scalar val = cv::Scalar::all(randomDouble(0.0, 255.0));
 
-        if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
-        {
-            try
-            {
-                cv::gpu::GpuMat mat = createMat(size, type, useRoi);
-                mat.setTo(val);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
-        }
-        else
+    if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+    {
+        try
         {
             cv::gpu::GpuMat mat = createMat(size, type, useRoi);
             mat.setTo(val);
-
-            EXPECT_MAT_NEAR(cv::Mat(size, type, val), mat, 0.0);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat mat = createMat(size, type, useRoi);
+        mat.setTo(val);
+
+        EXPECT_MAT_NEAR(cv::Mat(size, type, val), mat, 0.0);
     }
 }
 
 TEST_P(SetTo, DifferentVal)
 {
-    try
-    {
-        cv::Scalar val = randomScalar(0.0, 255.0);
+    cv::Scalar val = randomScalar(0.0, 255.0);
 
-        if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
-        {
-            try
-            {
-                cv::gpu::GpuMat mat = createMat(size, type, useRoi);
-                mat.setTo(val);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
-        }
-        else
+    if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+    {
+        try
         {
             cv::gpu::GpuMat mat = createMat(size, type, useRoi);
             mat.setTo(val);
-
-            EXPECT_MAT_NEAR(cv::Mat(size, type, val), mat, 0.0);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat mat = createMat(size, type, useRoi);
+        mat.setTo(val);
+
+        EXPECT_MAT_NEAR(cv::Mat(size, type, val), mat, 0.0);
     }
 }
 
 TEST_P(SetTo, Masked)
 {
-    try
+    cv::Scalar val = randomScalar(0.0, 255.0);
+    cv::Mat mat_gold = randomMat(size, type);
+    cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
+
+    if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
     {
-        cv::Scalar val = randomScalar(0.0, 255.0);
-        cv::Mat mat_gold = randomMat(size, type);
-        cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
-
-        if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+        try
         {
-            try
-            {
-                cv::gpu::GpuMat mat = createMat(size, type, useRoi);
-                mat.setTo(val, loadMat(mask));
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
+            cv::gpu::GpuMat mat = createMat(size, type, useRoi);
+            mat.setTo(val, loadMat(mask));
         }
-        else
+        catch (const cv::Exception& e)
         {
-            cv::gpu::GpuMat mat = loadMat(mat_gold, useRoi);
-            mat.setTo(val, loadMat(mask, useRoi));
-
-            mat_gold.setTo(val, mask);
-
-            EXPECT_MAT_NEAR(mat_gold, mat, 0.0);
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat mat = loadMat(mat_gold, useRoi);
+        mat.setTo(val, loadMat(mask, useRoi));
+
+        mat_gold.setTo(val, mask);
+
+        EXPECT_MAT_NEAR(mat_gold, mat, 0.0);
     }
 }
 
@@ -218,59 +186,43 @@ PARAM_TEST_CASE(CopyTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
 
 TEST_P(CopyTo, WithOutMask)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat d_src = loadMat(src, useRoi);
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        d_src.copyTo(dst);
+    cv::gpu::GpuMat d_src = loadMat(src, useRoi);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    d_src.copyTo(dst);
 
-        EXPECT_MAT_NEAR(src, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(src, dst, 0.0);
 }
 
 TEST_P(CopyTo, Masked)
 {
-    try
+    cv::Mat src = randomMat(size, type);
+    cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
+
+    if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
     {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
-
-        if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+        try
         {
-            try
-            {
-                cv::gpu::GpuMat d_src = loadMat(src);
-                cv::gpu::GpuMat dst;
-                d_src.copyTo(dst, loadMat(mask, useRoi));
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
-        }
-        else
-        {
-            cv::gpu::GpuMat d_src = loadMat(src, useRoi);
-            cv::gpu::GpuMat dst = loadMat(cv::Mat::zeros(size, type), useRoi);
+            cv::gpu::GpuMat d_src = loadMat(src);
+            cv::gpu::GpuMat dst;
             d_src.copyTo(dst, loadMat(mask, useRoi));
-
-            cv::Mat dst_gold = cv::Mat::zeros(size, type);
-            src.copyTo(dst_gold, mask);
-
-            EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat d_src = loadMat(src, useRoi);
+        cv::gpu::GpuMat dst = loadMat(cv::Mat::zeros(size, type), useRoi);
+        d_src.copyTo(dst, loadMat(mask, useRoi));
+
+        cv::Mat dst_gold = cv::Mat::zeros(size, type);
+        src.copyTo(dst_gold, mask);
+
+        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
     }
 }
 
@@ -305,79 +257,63 @@ PARAM_TEST_CASE(ConvertTo, cv::gpu::DeviceInfo, cv::Size, MatDepth, MatDepth, Us
 
 TEST_P(ConvertTo, WithOutScaling)
 {
-    try
+    cv::Mat src = randomMat(size, depth1);
+
+    if ((depth1 == CV_64F || depth2 == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
     {
-        cv::Mat src = randomMat(size, depth1);
-
-        if ((depth1 == CV_64F || depth2 == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+        try
         {
-            try
-            {
-                cv::gpu::GpuMat d_src = loadMat(src);
-                cv::gpu::GpuMat dst;
-                d_src.convertTo(dst, depth2);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
-        }
-        else
-        {
-            cv::gpu::GpuMat d_src = loadMat(src, useRoi);
-            cv::gpu::GpuMat dst = createMat(size, depth2, useRoi);
+            cv::gpu::GpuMat d_src = loadMat(src);
+            cv::gpu::GpuMat dst;
             d_src.convertTo(dst, depth2);
-
-            cv::Mat dst_gold;
-            src.convertTo(dst_gold, depth2);
-
-            EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat d_src = loadMat(src, useRoi);
+        cv::gpu::GpuMat dst = createMat(size, depth2, useRoi);
+        d_src.convertTo(dst, depth2);
+
+        cv::Mat dst_gold;
+        src.convertTo(dst_gold, depth2);
+
+        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
     }
 }
 
 TEST_P(ConvertTo, WithScaling)
 {
-    try
+    cv::Mat src = randomMat(size, depth1);
+    double a = randomDouble(0.0, 1.0);
+    double b = randomDouble(-10.0, 10.0);
+
+    if ((depth1 == CV_64F || depth2 == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
     {
-        cv::Mat src = randomMat(size, depth1);
-        double a = randomDouble(0.0, 1.0);
-        double b = randomDouble(-10.0, 10.0);
-
-        if ((depth1 == CV_64F || depth2 == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
+        try
         {
-            try
-            {
-                cv::gpu::GpuMat d_src = loadMat(src);
-                cv::gpu::GpuMat dst;
-                d_src.convertTo(dst, depth2, a, b);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
-            }
-        }
-        else
-        {
-            cv::gpu::GpuMat d_src = loadMat(src, useRoi);
-            cv::gpu::GpuMat dst = createMat(size, depth2, useRoi);
+            cv::gpu::GpuMat d_src = loadMat(src);
+            cv::gpu::GpuMat dst;
             d_src.convertTo(dst, depth2, a, b);
-
-            cv::Mat dst_gold;
-            src.convertTo(dst_gold, depth2, a, b);
-
-            EXPECT_MAT_NEAR(dst_gold, dst, depth2 < CV_32F ? 1.0 : 1e-4);
+        }
+        catch (const cv::Exception& e)
+        {
+            ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat d_src = loadMat(src, useRoi);
+        cv::gpu::GpuMat dst = createMat(size, depth2, useRoi);
+        d_src.convertTo(dst, depth2, a, b);
+
+        cv::Mat dst_gold;
+        src.convertTo(dst_gold, depth2, a, b);
+
+        EXPECT_MAT_NEAR(dst_gold, dst, depth2 < CV_32F ? 1.0 : 1e-4);
     }
 }
 
@@ -402,30 +338,22 @@ struct EnsureSizeIsEnough : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(EnsureSizeIsEnough, BufferReuse)
 {
-    try
-    {
-        cv::gpu::GpuMat buffer(100, 100, CV_8U);
-        cv::gpu::GpuMat old = buffer;
+    cv::gpu::GpuMat buffer(100, 100, CV_8U);
+    cv::gpu::GpuMat old = buffer;
 
-        // don't reallocate memory
-        cv::gpu::ensureSizeIsEnough(10, 20, CV_8U, buffer);
-        EXPECT_EQ(10, buffer.rows);
-        EXPECT_EQ(20, buffer.cols);
-        EXPECT_EQ(CV_8UC1, buffer.type());
-        EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
+    // don't reallocate memory
+    cv::gpu::ensureSizeIsEnough(10, 20, CV_8U, buffer);
+    EXPECT_EQ(10, buffer.rows);
+    EXPECT_EQ(20, buffer.cols);
+    EXPECT_EQ(CV_8UC1, buffer.type());
+    EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
 
-        // don't reallocate memory
-        cv::gpu::ensureSizeIsEnough(20, 30, CV_8U, buffer);
-        EXPECT_EQ(20, buffer.rows);
-        EXPECT_EQ(30, buffer.cols);
-        EXPECT_EQ(CV_8UC1, buffer.type());
-        EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    // don't reallocate memory
+    cv::gpu::ensureSizeIsEnough(20, 30, CV_8U, buffer);
+    EXPECT_EQ(20, buffer.rows);
+    EXPECT_EQ(30, buffer.cols);
+    EXPECT_EQ(CV_8UC1, buffer.type());
+    EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_GpuMat, EnsureSizeIsEnough, ALL_DEVICES);

modules/gpu/test/test_hough.cpp

@@ -81,36 +81,28 @@ PARAM_TEST_CASE(HoughLines, cv::gpu::DeviceInfo, cv::Size, UseRoi)
 
 TEST_P(HoughLines, Accuracy)
 {
-    try
-    {
-        const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
-        cv::gpu::setDevice(devInfo.deviceID());
-        const cv::Size size = GET_PARAM(1);
-        const bool useRoi = GET_PARAM(2);
+    const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
+    cv::gpu::setDevice(devInfo.deviceID());
+    const cv::Size size = GET_PARAM(1);
+    const bool useRoi = GET_PARAM(2);
 
-        const float rho = 1.0f;
-        const float theta = (float) (1.5 * CV_PI / 180.0);
-        const int threshold = 100;
+    const float rho = 1.0f;
+    const float theta = (float) (1.5 * CV_PI / 180.0);
+    onst int threshold = 100;
 
-        cv::Mat src(size, CV_8UC1);
-        generateLines(src);
+    cv::Mat src(size, CV_8UC1);
+    generateLines(src);
 
-        cv::gpu::GpuMat d_lines;
-        cv::gpu::HoughLines(loadMat(src, useRoi), d_lines, rho, theta, threshold);
+    cv::gpu::GpuMat d_lines;
+    cv::gpu::HoughLines(loadMat(src, useRoi), d_lines, rho, theta, threshold);
 
-        std::vector<cv::Vec2f> lines;
-        cv::gpu::HoughLinesDownload(d_lines, lines);
+    std::vector<cv::Vec2f> lines;
+    cv::gpu::HoughLinesDownload(d_lines, lines);
 
-        cv::Mat dst(size, CV_8UC1);
-        drawLines(dst, lines);
+    cv::Mat dst(size, CV_8UC1);
+    drawLines(dst, lines);
 
-        ASSERT_MAT_NEAR(src, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_MAT_NEAR(src, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HoughLines, testing::Combine(
@@ -134,61 +126,53 @@ PARAM_TEST_CASE(HoughCircles, cv::gpu::DeviceInfo, cv::Size, UseRoi)
 
 TEST_P(HoughCircles, Accuracy)
 {
-    try
+    const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
+    cv::gpu::setDevice(devInfo.deviceID());
+    const cv::Size size = GET_PARAM(1);
+    const bool useRoi = GET_PARAM(2);
+
+    const float dp = 2.0f;
+    const float minDist = 10.0f;
+    const int minRadius = 10;
+    const int maxRadius = 20;
+    const int cannyThreshold = 100;
+    const int votesThreshold = 20;
+
+    std::vector<cv::Vec3f> circles_gold(4);
+    circles_gold[0] = cv::Vec3i(20, 20, minRadius);
+    circles_gold[1] = cv::Vec3i(90, 87, minRadius + 3);
+    circles_gold[2] = cv::Vec3i(30, 70, minRadius + 8);
+    circles_gold[3] = cv::Vec3i(80, 10, maxRadius);
+
+    cv::Mat src(size, CV_8UC1);
+    drawCircles(src, circles_gold, true);
+
+    cv::gpu::GpuMat d_circles;
+    cv::gpu::HoughCircles(loadMat(src, useRoi), d_circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
+
+    std::vector<cv::Vec3f> circles;
+    cv::gpu::HoughCirclesDownload(d_circles, circles);
+
+    ASSERT_FALSE(circles.empty());
+
+    for (size_t i = 0; i < circles.size(); ++i)
     {
-        const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
-        cv::gpu::setDevice(devInfo.deviceID());
-        const cv::Size size = GET_PARAM(1);
-        const bool useRoi = GET_PARAM(2);
+        cv::Vec3f cur = circles[i];
 
-        const float dp = 2.0f;
-        const float minDist = 10.0f;
-        const int minRadius = 10;
-        const int maxRadius = 20;
-        const int cannyThreshold = 100;
-        const int votesThreshold = 20;
+        bool found = false;
 
-        std::vector<cv::Vec3f> circles_gold(4);
-        circles_gold[0] = cv::Vec3i(20, 20, minRadius);
-        circles_gold[1] = cv::Vec3i(90, 87, minRadius + 3);
-        circles_gold[2] = cv::Vec3i(30, 70, minRadius + 8);
-        circles_gold[3] = cv::Vec3i(80, 10, maxRadius);
-
-        cv::Mat src(size, CV_8UC1);
-        drawCircles(src, circles_gold, true);
-
-        cv::gpu::GpuMat d_circles;
-        cv::gpu::HoughCircles(loadMat(src, useRoi), d_circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
-
-        std::vector<cv::Vec3f> circles;
-        cv::gpu::HoughCirclesDownload(d_circles, circles);
-
-        ASSERT_FALSE(circles.empty());
-
-        for (size_t i = 0; i < circles.size(); ++i)
+        for (size_t j = 0; j < circles_gold.size(); ++j)
         {
-            cv::Vec3f cur = circles[i];
+            cv::Vec3f gold = circles_gold[j];
 
-            bool found = false;
-
-            for (size_t j = 0; j < circles_gold.size(); ++j)
+            if (std::fabs(cur[0] - gold[0]) < minDist && std::fabs(cur[1] - gold[1]) < minDist && std::fabs(cur[2] - gold[2]) < minDist)
             {
-                cv::Vec3f gold = circles_gold[j];
-
-                if (std::fabs(cur[0] - gold[0]) < minDist && std::fabs(cur[1] - gold[1]) < minDist && std::fabs(cur[2] - gold[2]) < minDist)
-                {
-                    found = true;
-                    break;
-                }
+                found = true;
+                break;
             }
-
-            ASSERT_TRUE(found);
         }
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+
+        ASSERT_TRUE(found);
     }
 }
 
@@ -206,68 +190,60 @@ PARAM_TEST_CASE(GeneralizedHough, cv::gpu::DeviceInfo, UseRoi)
 
 TEST_P(GeneralizedHough, POSITION)
 {
-    try
+    const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
+    cv::gpu::setDevice(devInfo.deviceID());
+    const bool useRoi = GET_PARAM(1);
+
+    cv::Mat templ = readImage("../cv/shared/templ.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(templ.empty());
+
+    cv::Point templCenter(templ.cols / 2, templ.rows / 2);
+
+    const size_t gold_count = 3;
+    cv::Point pos_gold[gold_count];
+    pos_gold[0] = cv::Point(templCenter.x + 10, templCenter.y + 10);
+    pos_gold[1] = cv::Point(2 * templCenter.x + 40, templCenter.y + 10);
+    pos_gold[2] = cv::Point(2 * templCenter.x + 40, 2 * templCenter.y + 40);
+
+    cv::Mat image(templ.rows * 3, templ.cols * 3, CV_8UC1, cv::Scalar::all(0));
+    for (size_t i = 0; i < gold_count; ++i)
     {
-        const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
-        cv::gpu::setDevice(devInfo.deviceID());
-        const bool useRoi = GET_PARAM(1);
-
-        cv::Mat templ = readImage("../cv/shared/templ.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(templ.empty());
-
-        cv::Point templCenter(templ.cols / 2, templ.rows / 2);
-
-        const size_t gold_count = 3;
-        cv::Point pos_gold[gold_count];
-        pos_gold[0] = cv::Point(templCenter.x + 10, templCenter.y + 10);
-        pos_gold[1] = cv::Point(2 * templCenter.x + 40, templCenter.y + 10);
-        pos_gold[2] = cv::Point(2 * templCenter.x + 40, 2 * templCenter.y + 40);
-
-        cv::Mat image(templ.rows * 3, templ.cols * 3, CV_8UC1, cv::Scalar::all(0));
-        for (size_t i = 0; i < gold_count; ++i)
-        {
-            cv::Rect rec(pos_gold[i].x - templCenter.x, pos_gold[i].y - templCenter.y, templ.cols, templ.rows);
-            cv::Mat imageROI = image(rec);
-            templ.copyTo(imageROI);
-        }
-
-        cv::Ptr<cv::gpu::GeneralizedHough_GPU> hough = cv::gpu::GeneralizedHough_GPU::create(cv::GHT_POSITION);
-        hough->set("votesThreshold", 200);
-
-        hough->setTemplate(loadMat(templ, useRoi));
-
-        cv::gpu::GpuMat d_pos;
-        hough->detect(loadMat(image, useRoi), d_pos);
-
-        std::vector<cv::Vec4f> pos;
-        hough->download(d_pos, pos);
-
-        ASSERT_EQ(gold_count, pos.size());
-
-        for (size_t i = 0; i < gold_count; ++i)
-        {
-            cv::Point gold = pos_gold[i];
-
-            bool found = false;
-
-            for (size_t j = 0; j < pos.size(); ++j)
-            {
-                cv::Point2f p(pos[j][0], pos[j][1]);
-
-                if (::fabs(p.x - gold.x) < 2 && ::fabs(p.y - gold.y) < 2)
-                {
-                    found = true;
-                    break;
-                }
-            }
-
-            ASSERT_TRUE(found);
-        }
+        cv::Rect rec(pos_gold[i].x - templCenter.x, pos_gold[i].y - templCenter.y, templ.cols, templ.rows);
+        cv::Mat imageROI = image(rec);
+        templ.copyTo(imageROI);
     }
-    catch (...)
+
+    cv::Ptr<cv::gpu::GeneralizedHough_GPU> hough = cv::gpu::GeneralizedHough_GPU::create(cv::GHT_POSITION);
+    hough->set("votesThreshold", 200);
+
+    hough->setTemplate(loadMat(templ, useRoi));
+
+    cv::gpu::GpuMat d_pos;
+    hough->detect(loadMat(image, useRoi), d_pos);
+
+    std::vector<cv::Vec4f> pos;
+    hough->download(d_pos, pos);
+
+    ASSERT_EQ(gold_count, pos.size());
+
+    for (size_t i = 0; i < gold_count; ++i)
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::Point gold = pos_gold[i];
+
+        bool found = false;
+
+        for (size_t j = 0; j < pos.size(); ++j)
+        {
+            cv::Point2f p(pos[j][0], pos[j][1]);
+
+            if (::fabs(p.x - gold.x) < 2 && ::fabs(p.y - gold.y) < 2)
+            {
+                found = true;
+                break;
+            }
+        }
+
+        ASSERT_TRUE(found);
     }
 }
 

modules/gpu/test/test_imgproc.cpp

@@ -66,23 +66,15 @@ PARAM_TEST_CASE(Integral, cv::gpu::DeviceInfo, cv::Size, UseRoi)
 
 TEST_P(Integral, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, CV_8UC1);
+    cv::Mat src = randomMat(size, CV_8UC1);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size(src.cols + 1, src.rows + 1), CV_32SC1, useRoi);
-        cv::gpu::integral(loadMat(src, useRoi), dst);
+    cv::gpu::GpuMat dst = createMat(cv::Size(src.cols + 1, src.rows + 1), CV_32SC1, useRoi);
+    cv::gpu::integral(loadMat(src, useRoi), dst);
 
-        cv::Mat dst_gold;
-        cv::integral(src, dst_gold, CV_32S);
+    cv::Mat dst_gold;
+    cv::integral(src, dst_gold, CV_32S);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Integral, testing::Combine(
@@ -107,40 +99,32 @@ struct HistEven : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(HistEven, Accuracy)
 {
-    try
-    {
-        cv::Mat img = readImage("stereobm/aloe-L.png");
-        ASSERT_FALSE(img.empty());
+    cv::Mat img = readImage("stereobm/aloe-L.png");
+    ASSERT_FALSE(img.empty());
 
-        cv::Mat hsv;
-        cv::cvtColor(img, hsv, CV_BGR2HSV);
+    cv::Mat hsv;
+    cv::cvtColor(img, hsv, CV_BGR2HSV);
 
-        int hbins = 30;
-        float hranges[] = {0.0f, 180.0f};
+    int hbins = 30;
+    float hranges[] = {0.0f, 180.0f};
 
-        std::vector<cv::gpu::GpuMat> srcs;
-        cv::gpu::split(loadMat(hsv), srcs);
+    std::vector<cv::gpu::GpuMat> srcs;
+    cv::gpu::split(loadMat(hsv), srcs);
 
-        cv::gpu::GpuMat hist;
-        cv::gpu::histEven(srcs[0], hist, hbins, (int)hranges[0], (int)hranges[1]);
+    cv::gpu::GpuMat hist;
+    cv::gpu::histEven(srcs[0], hist, hbins, (int)hranges[0], (int)hranges[1]);
 
-        cv::MatND histnd;
-        int histSize[] = {hbins};
-        const float* ranges[] = {hranges};
-        int channels[] = {0};
-        cv::calcHist(&hsv, 1, channels, cv::Mat(), histnd, 1, histSize, ranges);
+    cv::MatND histnd;
+    int histSize[] = {hbins};
+    const float* ranges[] = {hranges};
+    int channels[] = {0};
+    cv::calcHist(&hsv, 1, channels, cv::Mat(), histnd, 1, histSize, ranges);
 
-        cv::Mat hist_gold = histnd;
-        hist_gold = hist_gold.t();
-        hist_gold.convertTo(hist_gold, CV_32S);
+    cv::Mat hist_gold = histnd;
+    hist_gold = hist_gold.t();
+    hist_gold.convertTo(hist_gold, CV_32S);
 
-        EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HistEven, ALL_DEVICES);
@@ -180,23 +164,15 @@ PARAM_TEST_CASE(CalcHist, cv::gpu::DeviceInfo, cv::Size)
 
 TEST_P(CalcHist, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, CV_8UC1);
+    cv::Mat src = randomMat(size, CV_8UC1);
 
-        cv::gpu::GpuMat hist;
-        cv::gpu::calcHist(loadMat(src), hist);
+    cv::gpu::GpuMat hist;
+    cv::gpu::calcHist(loadMat(src), hist);
 
-        cv::Mat hist_gold;
-        calcHistGold(src, hist_gold);
+    cv::Mat hist_gold;
+    calcHistGold(src, hist_gold);
 
-        EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(hist_gold, hist, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CalcHist, testing::Combine(
@@ -222,23 +198,15 @@ PARAM_TEST_CASE(EqualizeHist, cv::gpu::DeviceInfo, cv::Size)
 
 TEST_P(EqualizeHist, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, CV_8UC1);
+    cv::Mat src = randomMat(size, CV_8UC1);
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::equalizeHist(loadMat(src), dst);
+    cv::gpu::GpuMat dst;
+    cv::gpu::equalizeHist(loadMat(src), dst);
 
-        cv::Mat dst_gold;
-        cv::equalizeHist(src, dst_gold);
+    cv::Mat dst_gold;
+    cv::equalizeHist(src, dst_gold);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 3.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 3.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, EqualizeHist, testing::Combine(
@@ -264,36 +232,28 @@ PARAM_TEST_CASE(ColumnSum, cv::gpu::DeviceInfo, cv::Size)
 
 TEST_P(ColumnSum, Accuracy)
 {
-    try
+    cv::Mat src = randomMat(size, CV_32FC1);
+
+    cv::gpu::GpuMat d_dst;
+    cv::gpu::columnSum(loadMat(src), d_dst);
+
+    cv::Mat dst(d_dst);
+
+    for (int j = 0; j < src.cols; ++j)
     {
-        cv::Mat src = randomMat(size, CV_32FC1);
-
-        cv::gpu::GpuMat d_dst;
-        cv::gpu::columnSum(loadMat(src), d_dst);
-
-        cv::Mat dst(d_dst);
+        float gold = src.at<float>(0, j);
+        float res = dst.at<float>(0, j);
+        ASSERT_NEAR(res, gold, 1e-5);
+    }
 
+    for (int i = 1; i < src.rows; ++i)
+    {
         for (int j = 0; j < src.cols; ++j)
         {
-            float gold = src.at<float>(0, j);
-            float res = dst.at<float>(0, j);
+            float gold = src.at<float>(i, j) += src.at<float>(i - 1, j);
+            float res = dst.at<float>(i, j);
             ASSERT_NEAR(res, gold, 1e-5);
         }
-
-        for (int i = 1; i < src.rows; ++i)
-        {
-            for (int j = 0; j < src.cols; ++j)
-            {
-                float gold = src.at<float>(i, j) += src.at<float>(i - 1, j);
-                float res = dst.at<float>(i, j);
-                ASSERT_NEAR(res, gold, 1e-5);
-            }
-        }
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
     }
 }
 
@@ -327,41 +287,33 @@ PARAM_TEST_CASE(Canny, cv::gpu::DeviceInfo, AppertureSize, L2gradient, UseRoi)
 
 TEST_P(Canny, Accuracy)
 {
-    try
+    cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
+    ASSERT_FALSE(img.empty());
+
+    double low_thresh = 50.0;
+    double high_thresh = 100.0;
+
+    if (!supportFeature(devInfo, cv::gpu::SHARED_ATOMICS))
     {
-        cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
-        ASSERT_FALSE(img.empty());
-
-        double low_thresh = 50.0;
-        double high_thresh = 100.0;
-
-        if (!supportFeature(devInfo, cv::gpu::SHARED_ATOMICS))
+        try
         {
-            try
-            {
-            cv::gpu::GpuMat edges;
-            cv::gpu::Canny(loadMat(img), edges, low_thresh, high_thresh, apperture_size, useL2gradient);
-            }
-            catch (const cv::Exception& e)
-            {
-                ASSERT_EQ(CV_StsNotImplemented, e.code);
-            }
+        cv::gpu::GpuMat edges;
+        cv::gpu::Canny(loadMat(img), edges, low_thresh, high_thresh, apperture_size, useL2gradient);
         }
-        else
+        catch (const cv::Exception& e)
         {
-            cv::gpu::GpuMat edges;
-            cv::gpu::Canny(loadMat(img, useRoi), edges, low_thresh, high_thresh, apperture_size, useL2gradient);
-
-            cv::Mat edges_gold;
-            cv::Canny(img, edges_gold, low_thresh, high_thresh, apperture_size, useL2gradient);
-
-            EXPECT_MAT_SIMILAR(edges_gold, edges, 2e-2);
+            ASSERT_EQ(CV_StsNotImplemented, e.code);
         }
     }
-    catch (...)
+    else
     {
-        cv::gpu::resetDevice();
-        throw;
+        cv::gpu::GpuMat edges;
+        cv::gpu::Canny(loadMat(img, useRoi), edges, low_thresh, high_thresh, apperture_size, useL2gradient);
+
+        cv::Mat edges_gold;
+        cv::Canny(img, edges_gold, low_thresh, high_thresh, apperture_size, useL2gradient);
+
+        EXPECT_MAT_SIMILAR(edges_gold, edges, 2e-2);
     }
 }
 
@@ -399,66 +351,50 @@ struct MeanShift : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(MeanShift, Filtering)
 {
-    try
-    {
-        cv::Mat img_template;
-        if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
-            img_template = readImage("meanshift/con_result.png");
-        else
-            img_template = readImage("meanshift/con_result_CC1X.png");
-        ASSERT_FALSE(img_template.empty());
+    cv::Mat img_template;
+    if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
+        img_template = readImage("meanshift/con_result.png");
+    else
+        img_template = readImage("meanshift/con_result_CC1X.png");
+    ASSERT_FALSE(img_template.empty());
 
-        cv::gpu::GpuMat d_dst;
-        cv::gpu::meanShiftFiltering(loadMat(img), d_dst, spatialRad, colorRad);
+    cv::gpu::GpuMat d_dst;
+    cv::gpu::meanShiftFiltering(loadMat(img), d_dst, spatialRad, colorRad);
 
-        ASSERT_EQ(CV_8UC4, d_dst.type());
+    ASSERT_EQ(CV_8UC4, d_dst.type());
 
-        cv::Mat dst(d_dst);
+    cv::Mat dst(d_dst);
 
-        cv::Mat result;
-        cv::cvtColor(dst, result, CV_BGRA2BGR);
+    cv::Mat result;
+    cv::cvtColor(dst, result, CV_BGRA2BGR);
 
-        EXPECT_MAT_NEAR(img_template, result, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(img_template, result, 0.0);
 }
 
 TEST_P(MeanShift, Proc)
 {
-    try
-    {
-        cv::FileStorage fs;
-        if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
-            fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap.yaml", cv::FileStorage::READ);
-        else
-            fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap_CC1X.yaml", cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
+    cv::FileStorage fs;
+    if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
+        fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap.yaml", cv::FileStorage::READ);
+    else
+        fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap_CC1X.yaml", cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
 
-        cv::Mat spmap_template;
-        fs["spmap"] >> spmap_template;
-        ASSERT_FALSE(spmap_template.empty());
+    cv::Mat spmap_template;
+    fs["spmap"] >> spmap_template;
+    ASSERT_FALSE(spmap_template.empty());
 
-        cv::gpu::GpuMat rmap_filtered;
-        cv::gpu::meanShiftFiltering(loadMat(img), rmap_filtered, spatialRad, colorRad);
+    cv::gpu::GpuMat rmap_filtered;
+    cv::gpu::meanShiftFiltering(loadMat(img), rmap_filtered, spatialRad, colorRad);
 
-        cv::gpu::GpuMat rmap;
-        cv::gpu::GpuMat spmap;
-        cv::gpu::meanShiftProc(loadMat(img), rmap, spmap, spatialRad, colorRad);
+    cv::gpu::GpuMat rmap;
+    cv::gpu::GpuMat spmap;
+    cv::gpu::meanShiftProc(loadMat(img), rmap, spmap, spatialRad, colorRad);
 
-        ASSERT_EQ(CV_8UC4, rmap.type());
+    ASSERT_EQ(CV_8UC4, rmap.type());
 
-        EXPECT_MAT_NEAR(rmap_filtered, rmap, 0.0);
-        EXPECT_MAT_NEAR(spmap_template, spmap, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(rmap_filtered, rmap, 0.0);
+    EXPECT_MAT_NEAR(spmap_template, spmap, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MeanShift, ALL_DEVICES);
@@ -484,33 +420,25 @@ PARAM_TEST_CASE(MeanShiftSegmentation, cv::gpu::DeviceInfo, MinSize)
 
 TEST_P(MeanShiftSegmentation, Regression)
 {
-    try
-    {
-        cv::Mat img = readImageType("meanshift/cones.png", CV_8UC4);
-        ASSERT_FALSE(img.empty());
+    cv::Mat img = readImageType("meanshift/cones.png", CV_8UC4);
+    ASSERT_FALSE(img.empty());
 
-        std::ostringstream path;
-        path << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
-        if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
-            path << ".png";
-        else
-            path << "_CC1X.png";
-        cv::Mat dst_gold = readImage(path.str());
-        ASSERT_FALSE(dst_gold.empty());
+    std::ostringstream path;
+    path << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
+    if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
+        path << ".png";
+    else
+        path << "_CC1X.png";
+    cv::Mat dst_gold = readImage(path.str());
+    ASSERT_FALSE(dst_gold.empty());
 
-        cv::Mat dst;
-        cv::gpu::meanShiftSegmentation(loadMat(img), dst, 10, 10, minsize);
+    cv::Mat dst;
+    cv::gpu::meanShiftSegmentation(loadMat(img), dst, 10, 10, minsize);
 
-        cv::Mat dst_rgb;
-        cv::cvtColor(dst, dst_rgb, CV_BGRA2BGR);
+    cv::Mat dst_rgb;
+    cv::cvtColor(dst, dst_rgb, CV_BGRA2BGR);
 
-        EXPECT_MAT_SIMILAR(dst_gold, dst_rgb, 1e-3);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_SIMILAR(dst_gold, dst_rgb, 1e-3);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MeanShiftSegmentation, testing::Combine(
@@ -564,31 +492,23 @@ PARAM_TEST_CASE(Blend, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
 
 TEST_P(Blend, Accuracy)
 {
-    try
-    {
-        int depth = CV_MAT_DEPTH(type);
+    int depth = CV_MAT_DEPTH(type);
 
-        cv::Mat img1 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
-        cv::Mat img2 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
-        cv::Mat weights1 = randomMat(size, CV_32F, 0, 1);
-        cv::Mat weights2 = randomMat(size, CV_32F, 0, 1);
+    cv::Mat img1 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
+    cv::Mat img2 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
+    cv::Mat weights1 = randomMat(size, CV_32F, 0, 1);
+    cv::Mat weights2 = randomMat(size, CV_32F, 0, 1);
 
-        cv::gpu::GpuMat result;
-        cv::gpu::blendLinear(loadMat(img1, useRoi), loadMat(img2, useRoi), loadMat(weights1, useRoi), loadMat(weights2, useRoi), result);
+    cv::gpu::GpuMat result;
+    cv::gpu::blendLinear(loadMat(img1, useRoi), loadMat(img2, useRoi), loadMat(weights1, useRoi), loadMat(weights2, useRoi), result);
 
-        cv::Mat result_gold;
-        if (depth == CV_8U)
-            blendLinearGold<uchar>(img1, img2, weights1, weights2, result_gold);
-        else
-            blendLinearGold<float>(img1, img2, weights1, weights2, result_gold);
+    cv::Mat result_gold;
+    if (depth == CV_8U)
+        blendLinearGold<uchar>(img1, img2, weights1, weights2, result_gold);
+    else
+        blendLinearGold<float>(img1, img2, weights1, weights2, result_gold);
 
-        EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1.0 : 1e-5);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1.0 : 1e-5);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Blend, testing::Combine(
@@ -662,24 +582,16 @@ PARAM_TEST_CASE(Convolve, cv::gpu::DeviceInfo, cv::Size, KSize, Ccorr)
 
 TEST_P(Convolve, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, CV_32FC1, 0.0, 100.0);
-        cv::Mat kernel = randomMat(cv::Size(ksize, ksize), CV_32FC1, 0.0, 1.0);
+    cv::Mat src = randomMat(size, CV_32FC1, 0.0, 100.0);
+    cv::Mat kernel = randomMat(cv::Size(ksize, ksize), CV_32FC1, 0.0, 1.0);
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::convolve(loadMat(src), loadMat(kernel), dst, ccorr);
+    cv::gpu::GpuMat dst;
+    cv::gpu::convolve(loadMat(src), loadMat(kernel), dst, ccorr);
 
-        cv::Mat dst_gold;
-        convolveDFT(src, kernel, dst_gold, ccorr);
+    cv::Mat dst_gold;
+    convolveDFT(src, kernel, dst_gold, ccorr);
 
-        EXPECT_MAT_NEAR(dst, dst_gold, 1e-1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst, dst_gold, 1e-1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Convolve, testing::Combine(
@@ -718,24 +630,16 @@ PARAM_TEST_CASE(MatchTemplate8U, cv::gpu::DeviceInfo, cv::Size, TemplateSize, Ch
 
 TEST_P(MatchTemplate8U, Accuracy)
 {
-    try
-    {
-        cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn));
-        cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_8U, cn));
+    cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn));
+    cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_8U, cn));
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::matchTemplate(loadMat(image), loadMat(templ), dst, method);
+    cv::gpu::GpuMat dst;
+    cv::gpu::matchTemplate(loadMat(image), loadMat(templ), dst, method);
 
-        cv::Mat dst_gold;
-        cv::matchTemplate(image, templ, dst_gold, method);
+    cv::Mat dst_gold;
+    cv::matchTemplate(image, templ, dst_gold, method);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, templ_size.area() * 1e-1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, templ_size.area() * 1e-1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U, testing::Combine(
@@ -772,24 +676,16 @@ PARAM_TEST_CASE(MatchTemplate32F, cv::gpu::DeviceInfo, cv::Size, TemplateSize, C
 
 TEST_P(MatchTemplate32F, Regression)
 {
-    try
-    {
-        cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn));
-        cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn));
+    cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn));
+    cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn));
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::matchTemplate(loadMat(image), loadMat(templ), dst, method);
+    cv::gpu::GpuMat dst;
+    cv::gpu::matchTemplate(loadMat(image), loadMat(templ), dst, method);
 
-        cv::Mat dst_gold;
-        cv::matchTemplate(image, templ, dst_gold, method);
+    cv::Mat dst_gold;
+    cv::matchTemplate(image, templ, dst_gold, method);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, templ_size.area() * 1e-1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, templ_size.area() * 1e-1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
@@ -818,32 +714,24 @@ PARAM_TEST_CASE(MatchTemplateBlackSource, cv::gpu::DeviceInfo, TemplateMethod)
 
 TEST_P(MatchTemplateBlackSource, Accuracy)
 {
-    try
-    {
-        cv::Mat image = readImage("matchtemplate/black.png");
-        ASSERT_FALSE(image.empty());
+    cv::Mat image = readImage("matchtemplate/black.png");
+    ASSERT_FALSE(image.empty());
 
-        cv::Mat pattern = readImage("matchtemplate/cat.png");
-        ASSERT_FALSE(pattern.empty());
+    cv::Mat pattern = readImage("matchtemplate/cat.png");
+    ASSERT_FALSE(pattern.empty());
 
-        cv::gpu::GpuMat d_dst;
-        cv::gpu::matchTemplate(loadMat(image), loadMat(pattern), d_dst, method);
+    cv::gpu::GpuMat d_dst;
+    cv::gpu::matchTemplate(loadMat(image), loadMat(pattern), d_dst, method);
 
-        cv::Mat dst(d_dst);
+    cv::Mat dst(d_dst);
 
-        double maxValue;
-        cv::Point maxLoc;
-        cv::minMaxLoc(dst, NULL, &maxValue, NULL, &maxLoc);
+    double maxValue;
+    cv::Point maxLoc;
+    cv::minMaxLoc(dst, NULL, &maxValue, NULL, &maxLoc);
 
-        cv::Point maxLocGold = cv::Point(284, 12);
+    cv::Point maxLocGold = cv::Point(284, 12);
 
-        ASSERT_EQ(maxLocGold, maxLoc);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_EQ(maxLocGold, maxLoc);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplateBlackSource, testing::Combine(
@@ -871,40 +759,32 @@ PARAM_TEST_CASE(MatchTemplate_CCOEF_NORMED, cv::gpu::DeviceInfo, std::pair<std::
 
 TEST_P(MatchTemplate_CCOEF_NORMED, Accuracy)
 {
-    try
-    {
-        cv::Mat image = readImage(imageName);
-        ASSERT_FALSE(image.empty());
+    cv::Mat image = readImage(imageName);
+    ASSERT_FALSE(image.empty());
 
-        cv::Mat pattern = readImage(patternName);
-        ASSERT_FALSE(pattern.empty());
+    cv::Mat pattern = readImage(patternName);
+    ASSERT_FALSE(pattern.empty());
 
-        cv::gpu::GpuMat d_dst;
-        cv::gpu::matchTemplate(loadMat(image), loadMat(pattern), d_dst, CV_TM_CCOEFF_NORMED);
+    cv::gpu::GpuMat d_dst;
+    cv::gpu::matchTemplate(loadMat(image), loadMat(pattern), d_dst, CV_TM_CCOEFF_NORMED);
 
-        cv::Mat dst(d_dst);
+    cv::Mat dst(d_dst);
 
-        cv::Point minLoc, maxLoc;
-        double minVal, maxVal;
-        cv::minMaxLoc(dst, &minVal, &maxVal, &minLoc, &maxLoc);
+    cv::Point minLoc, maxLoc;
+    double minVal, maxVal;
+    cv::minMaxLoc(dst, &minVal, &maxVal, &minLoc, &maxLoc);
 
-        cv::Mat dstGold;
-        cv::matchTemplate(image, pattern, dstGold, CV_TM_CCOEFF_NORMED);
+    cv::Mat dstGold;
+    cv::matchTemplate(image, pattern, dstGold, CV_TM_CCOEFF_NORMED);
 
-        double minValGold, maxValGold;
-        cv::Point minLocGold, maxLocGold;
-        cv::minMaxLoc(dstGold, &minValGold, &maxValGold, &minLocGold, &maxLocGold);
+    double minValGold, maxValGold;
+    cv::Point minLocGold, maxLocGold;
+    cv::minMaxLoc(dstGold, &minValGold, &maxValGold, &minLocGold, &maxLocGold);
 
-        ASSERT_EQ(minLocGold, minLoc);
-        ASSERT_EQ(maxLocGold, maxLoc);
-        ASSERT_LE(maxVal, 1.0);
-        ASSERT_GE(minVal, -1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_EQ(minLocGold, minLoc);
+    ASSERT_EQ(maxLocGold, maxLoc);
+    ASSERT_LE(maxVal, 1.0);
+    ASSERT_GE(minVal, -1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate_CCOEF_NORMED, testing::Combine(
@@ -928,63 +808,47 @@ struct MatchTemplate_CanFindBigTemplate : testing::TestWithParam<cv::gpu::Device
 
 TEST_P(MatchTemplate_CanFindBigTemplate, SQDIFF_NORMED)
 {
-    try
-    {
-        cv::Mat scene = readImage("matchtemplate/scene.png");
-        ASSERT_FALSE(scene.empty());
+    cv::Mat scene = readImage("matchtemplate/scene.png");
+    ASSERT_FALSE(scene.empty());
 
-        cv::Mat templ = readImage("matchtemplate/template.png");
-        ASSERT_FALSE(templ.empty());
+    cv::Mat templ = readImage("matchtemplate/template.png");
+    ASSERT_FALSE(templ.empty());
 
-        cv::gpu::GpuMat d_result;
-        cv::gpu::matchTemplate(loadMat(scene), loadMat(templ), d_result, CV_TM_SQDIFF_NORMED);
+    cv::gpu::GpuMat d_result;
+    cv::gpu::matchTemplate(loadMat(scene), loadMat(templ), d_result, CV_TM_SQDIFF_NORMED);
 
-        cv::Mat result(d_result);
+    cv::Mat result(d_result);
 
-        double minVal;
-        cv::Point minLoc;
-        cv::minMaxLoc(result, &minVal, 0, &minLoc, 0);
+    double minVal;
+    cv::Point minLoc;
+    cv::minMaxLoc(result, &minVal, 0, &minLoc, 0);
 
-        ASSERT_GE(minVal, 0);
-        ASSERT_LT(minVal, 1e-3);
-        ASSERT_EQ(344, minLoc.x);
-        ASSERT_EQ(0, minLoc.y);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_GE(minVal, 0);
+    ASSERT_LT(minVal, 1e-3);
+    ASSERT_EQ(344, minLoc.x);
+    ASSERT_EQ(0, minLoc.y);
 }
 
 TEST_P(MatchTemplate_CanFindBigTemplate, SQDIFF)
 {
-    try
-    {
-        cv::Mat scene = readImage("matchtemplate/scene.png");
-        ASSERT_FALSE(scene.empty());
+    cv::Mat scene = readImage("matchtemplate/scene.png");
+    ASSERT_FALSE(scene.empty());
 
-        cv::Mat templ = readImage("matchtemplate/template.png");
-        ASSERT_FALSE(templ.empty());
+    cv::Mat templ = readImage("matchtemplate/template.png");
+    ASSERT_FALSE(templ.empty());
 
-        cv::gpu::GpuMat d_result;
-        cv::gpu::matchTemplate(loadMat(scene), loadMat(templ), d_result, CV_TM_SQDIFF);
+    cv::gpu::GpuMat d_result;
+    cv::gpu::matchTemplate(loadMat(scene), loadMat(templ), d_result, CV_TM_SQDIFF);
 
-        cv::Mat result(d_result);
+    cv::Mat result(d_result);
 
-        double minVal;
-        cv::Point minLoc;
-        cv::minMaxLoc(result, &minVal, 0, &minLoc, 0);
+    double minVal;
+    cv::Point minLoc;
+    cv::minMaxLoc(result, &minVal, 0, &minLoc, 0);
 
-        ASSERT_GE(minVal, 0);
-        ASSERT_EQ(344, minLoc.x);
-        ASSERT_EQ(0, minLoc.y);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_GE(minVal, 0);
+    ASSERT_EQ(344, minLoc.x);
+    ASSERT_EQ(0, minLoc.y);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate_CanFindBigTemplate, ALL_DEVICES);
@@ -1017,43 +881,27 @@ PARAM_TEST_CASE(MulSpectrums, cv::gpu::DeviceInfo, cv::Size, DftFlags)
 
 TEST_P(MulSpectrums, Simple)
 {
-    try
-    {
-        cv::gpu::GpuMat c;
-        cv::gpu::mulSpectrums(loadMat(a), loadMat(b), c, flag, false);
+    cv::gpu::GpuMat c;
+    cv::gpu::mulSpectrums(loadMat(a), loadMat(b), c, flag, false);
 
-        cv::Mat c_gold;
-        cv::mulSpectrums(a, b, c_gold, flag, false);
+    cv::Mat c_gold;
+    cv::mulSpectrums(a, b, c_gold, flag, false);
 
-        EXPECT_MAT_NEAR(c_gold, c, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(c_gold, c, 1e-2);
 }
 
 TEST_P(MulSpectrums, Scaled)
 {
-    try
-    {
-        float scale = 1.f / size.area();
+    float scale = 1.f / size.area();
 
-        cv::gpu::GpuMat c;
-        cv::gpu::mulAndScaleSpectrums(loadMat(a), loadMat(b), c, flag, scale, false);
+    cv::gpu::GpuMat c;
+    cv::gpu::mulAndScaleSpectrums(loadMat(a), loadMat(b), c, flag, scale, false);
 
-        cv::Mat c_gold;
-        cv::mulSpectrums(a, b, c_gold, flag, false);
-        c_gold.convertTo(c_gold, c_gold.type(), scale);
+    cv::Mat c_gold;
+    cv::mulSpectrums(a, b, c_gold, flag, false);
+    c_gold.convertTo(c_gold, c_gold.type(), scale);
 
-        EXPECT_MAT_NEAR(c_gold, c, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(c_gold, c, 1e-2);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MulSpectrums, testing::Combine(
@@ -1102,34 +950,26 @@ void testC2C(const std::string& hint, int cols, int rows, int flags, bool inplac
 
 TEST_P(Dft, C2C)
 {
-    try
-    {
-        int cols = randomInt(2, 100);
-        int rows = randomInt(2, 100);
+    int cols = randomInt(2, 100);
+    int rows = randomInt(2, 100);
 
-        for (int i = 0; i < 2; ++i)
-        {
-            bool inplace = i != 0;
-
-            testC2C("no flags", cols, rows, 0, inplace);
-            testC2C("no flags 0 1", cols, rows + 1, 0, inplace);
-            testC2C("no flags 1 0", cols, rows + 1, 0, inplace);
-            testC2C("no flags 1 1", cols + 1, rows, 0, inplace);
-            testC2C("DFT_INVERSE", cols, rows, cv::DFT_INVERSE, inplace);
-            testC2C("DFT_ROWS", cols, rows, cv::DFT_ROWS, inplace);
-            testC2C("single col", 1, rows, 0, inplace);
-            testC2C("single row", cols, 1, 0, inplace);
-            testC2C("single col inversed", 1, rows, cv::DFT_INVERSE, inplace);
-            testC2C("single row inversed", cols, 1, cv::DFT_INVERSE, inplace);
-            testC2C("single row DFT_ROWS", cols, 1, cv::DFT_ROWS, inplace);
-            testC2C("size 1 2", 1, 2, 0, inplace);
-            testC2C("size 2 1", 2, 1, 0, inplace);
-        }
-    }
-    catch (...)
+    for (int i = 0; i < 2; ++i)
     {
-        cv::gpu::resetDevice();
-        throw;
+        bool inplace = i != 0;
+
+        testC2C("no flags", cols, rows, 0, inplace);
+        testC2C("no flags 0 1", cols, rows + 1, 0, inplace);
+        testC2C("no flags 1 0", cols, rows + 1, 0, inplace);
+        testC2C("no flags 1 1", cols + 1, rows, 0, inplace);
+        testC2C("DFT_INVERSE", cols, rows, cv::DFT_INVERSE, inplace);
+        testC2C("DFT_ROWS", cols, rows, cv::DFT_ROWS, inplace);
+        testC2C("single col", 1, rows, 0, inplace);
+        testC2C("single row", cols, 1, 0, inplace);
+        testC2C("single col inversed", 1, rows, cv::DFT_INVERSE, inplace);
+        testC2C("single row inversed", cols, 1, cv::DFT_INVERSE, inplace);
+        testC2C("single row DFT_ROWS", cols, 1, cv::DFT_ROWS, inplace);
+        testC2C("size 1 2", 1, 2, 0, inplace);
+        testC2C("size 2 1", 2, 1, 0, inplace);
     }
 }
 
@@ -1171,32 +1011,24 @@ void testR2CThenC2R(const std::string& hint, int cols, int rows, bool inplace)
 
 TEST_P(Dft, R2CThenC2R)
 {
-    try
-    {
-        int cols = randomInt(2, 100);
-        int rows = randomInt(2, 100);
+    int cols = randomInt(2, 100);
+    int rows = randomInt(2, 100);
 
-        testR2CThenC2R("sanity", cols, rows, false);
-        testR2CThenC2R("sanity 0 1", cols, rows + 1, false);
-        testR2CThenC2R("sanity 1 0", cols + 1, rows, false);
-        testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, false);
-        testR2CThenC2R("single col", 1, rows, false);
-        testR2CThenC2R("single col 1", 1, rows + 1, false);
-        testR2CThenC2R("single row", cols, 1, false);
-        testR2CThenC2R("single row 1", cols + 1, 1, false);
+    testR2CThenC2R("sanity", cols, rows, false);
+    testR2CThenC2R("sanity 0 1", cols, rows + 1, false);
+    testR2CThenC2R("sanity 1 0", cols + 1, rows, false);
+    testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, false);
+    testR2CThenC2R("single col", 1, rows, false);
+    testR2CThenC2R("single col 1", 1, rows + 1, false);
+    testR2CThenC2R("single row", cols, 1, false);
+    testR2CThenC2R("single row 1", cols + 1, 1, false);
 
-        testR2CThenC2R("sanity", cols, rows, true);
-        testR2CThenC2R("sanity 0 1", cols, rows + 1, true);
-        testR2CThenC2R("sanity 1 0", cols + 1, rows, true);
-        testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, true);
-        testR2CThenC2R("single row", cols, 1, true);
-        testR2CThenC2R("single row 1", cols + 1, 1, true);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    testR2CThenC2R("sanity", cols, rows, true);
+    testR2CThenC2R("sanity 0 1", cols, rows + 1, true);
+    testR2CThenC2R("sanity 1 0", cols + 1, rows, true);
+    testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, true);
+    testR2CThenC2R("single row", cols, 1, true);
+    testR2CThenC2R("single row 1", cols + 1, 1, true);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Dft, ALL_DEVICES);
@@ -1229,26 +1061,18 @@ PARAM_TEST_CASE(CornerHarris, cv::gpu::DeviceInfo, MatType, BorderType, BlockSiz
 
 TEST_P(CornerHarris, Accuracy)
 {
-    try
-    {
-        cv::Mat src = readImageType("stereobm/aloe-L.png", type);
-        ASSERT_FALSE(src.empty());
+    cv::Mat src = readImageType("stereobm/aloe-L.png", type);
+    ASSERT_FALSE(src.empty());
 
-        double k = randomDouble(0.1, 0.9);
+    double k = randomDouble(0.1, 0.9);
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::cornerHarris(loadMat(src), dst, blockSize, apertureSize, k, borderType);
+    cv::gpu::GpuMat dst;
+    cv::gpu::cornerHarris(loadMat(src), dst, blockSize, apertureSize, k, borderType);
 
-        cv::Mat dst_gold;
-        cv::cornerHarris(src, dst_gold, blockSize, apertureSize, k, borderType);
+    cv::Mat dst_gold;
+    cv::cornerHarris(src, dst_gold, blockSize, apertureSize, k, borderType);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CornerHarris, testing::Combine(
@@ -1283,24 +1107,16 @@ PARAM_TEST_CASE(CornerMinEigen, cv::gpu::DeviceInfo, MatType, BorderType, BlockS
 
 TEST_P(CornerMinEigen, Accuracy)
 {
-    try
-    {
-        cv::Mat src = readImageType("stereobm/aloe-L.png", type);
-        ASSERT_FALSE(src.empty());
+    cv::Mat src = readImageType("stereobm/aloe-L.png", type);
+    ASSERT_FALSE(src.empty());
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::cornerMinEigenVal(loadMat(src), dst, blockSize, apertureSize, borderType);
+    cv::gpu::GpuMat dst;
+    cv::gpu::cornerMinEigenVal(loadMat(src), dst, blockSize, apertureSize, borderType);
 
-        cv::Mat dst_gold;
-        cv::cornerMinEigenVal(src, dst_gold, blockSize, apertureSize, borderType);
+    cv::Mat dst_gold;
+    cv::cornerMinEigenVal(src, dst_gold, blockSize, apertureSize, borderType);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CornerMinEigen, testing::Combine(

modules/gpu/test/test_labeling.cpp

@@ -168,35 +168,27 @@ struct Labeling : testing::TestWithParam<cv::gpu::DeviceInfo>
 
 TEST_P(Labeling, ConnectedComponents)
 {
-    try
-    {
-        cv::Mat image;
-        cvtColor(loat_image(), image, CV_BGR2GRAY);
+    cv::Mat image;
+    cvtColor(loat_image(), image, CV_BGR2GRAY);
 
-        cv::threshold(image, image, 150, 255, CV_THRESH_BINARY);
+    cv::threshold(image, image, 150, 255, CV_THRESH_BINARY);
 
-        ASSERT_TRUE(image.type() == CV_8UC1);
+    ASSERT_TRUE(image.type() == CV_8UC1);
 
-        GreedyLabeling host(image);
-        host(host._labels);
+    GreedyLabeling host(image);
+    host(host._labels);
 
-        cv::gpu::GpuMat mask;
-        mask.create(image.rows, image.cols, CV_8UC1);
+    cv::gpu::GpuMat mask;
+    mask.create(image.rows, image.cols, CV_8UC1);
 
-        cv::gpu::GpuMat components;
-        components.create(image.rows, image.cols, CV_32SC1);
+    cv::gpu::GpuMat components;
+    components.create(image.rows, image.cols, CV_32SC1);
 
-        cv::gpu::connectivityMask(cv::gpu::GpuMat(image), mask, cv::Scalar::all(0), cv::Scalar::all(2));
+    cv::gpu::connectivityMask(cv::gpu::GpuMat(image), mask, cv::Scalar::all(0), cv::Scalar::all(2));
 
-        ASSERT_NO_THROW(cv::gpu::labelComponents(mask, components));
+    ASSERT_NO_THROW(cv::gpu::labelComponents(mask, components));
 
-        host.checkCorrectness(cv::Mat(components));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    host.checkCorrectness(cv::Mat(components));
 }
 
 INSTANTIATE_TEST_CASE_P(ConnectedComponents, Labeling, ALL_DEVICES);

modules/gpu/test/test_nvidia.cpp

@@ -69,169 +69,82 @@ struct NVidiaTest : TestWithParam<cv::gpu::DeviceInfo>
 struct NPPST : NVidiaTest {};
 struct NCV : NVidiaTest {};
 
-TEST_P(NPPST, Integral)
-{
-    try
-    {
-        bool res = nvidia_NPPST_Integral_Image(_path, nvidiaTestOutputLevel);
+//TEST_P(NPPST, Integral)
+//{
+//    bool res = nvidia_NPPST_Integral_Image(path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
-}
+//    ASSERT_TRUE(res);
+//}
 
 TEST_P(NPPST, SquaredIntegral)
 {
-    try
-    {
-        bool res = nvidia_NPPST_Squared_Integral_Image(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NPPST_Squared_Integral_Image(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NPPST, RectStdDev)
 {
-    try
-    {
-        bool res = nvidia_NPPST_RectStdDev(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NPPST_RectStdDev(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NPPST, Resize)
 {
-    try
-    {
-        bool res = nvidia_NPPST_Resize(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NPPST_Resize(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NPPST, VectorOperations)
 {
-    try
-    {
-        bool res = nvidia_NPPST_Vector_Operations(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NPPST_Vector_Operations(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NPPST, Transpose)
 {
-    try
-    {
-        bool res = nvidia_NPPST_Transpose(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NPPST_Transpose(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NCV, VectorOperations)
 {
-    try
-    {
-        bool res = nvidia_NCV_Vector_Operations(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NCV_Vector_Operations(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NCV, HaarCascadeLoader)
 {
-    try
-    {
-        bool res = nvidia_NCV_Haar_Cascade_Loader(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NCV_Haar_Cascade_Loader(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NCV, HaarCascadeApplication)
 {
-    try
-    {
-        bool res = nvidia_NCV_Haar_Cascade_Application(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NCV_Haar_Cascade_Application(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NCV, HypothesesFiltration)
 {
-    try
-    {
-        bool res = nvidia_NCV_Hypotheses_Filtration(_path, nvidiaTestOutputLevel);
+    bool res = nvidia_NCV_Hypotheses_Filtration(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 TEST_P(NCV, Visualization)
 {
-    try
-    {
-        bool res = nvidia_NCV_Visualization(_path, nvidiaTestOutputLevel);
+    // this functionality doesn't used in gpu module
+    bool res = nvidia_NCV_Visualization(_path, nvidiaTestOutputLevel);
 
-        ASSERT_TRUE(res);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(res);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_NVidia, NPPST, ALL_DEVICES);

modules/gpu/test/test_objdetect.cpp

@@ -175,129 +175,114 @@ struct HOG : testing::TestWithParam<cv::gpu::DeviceInfo>, cv::gpu::HOGDescriptor
     }
 };
 
-TEST_P(HOG, Detect)
+// desabled while resize does not fixed
+TEST_P(HOG, DISABLED_Detect)
 {
-    try
-    {
-        cv::Mat img_rgb = readImage("hog/road.png");
-        ASSERT_FALSE(img_rgb.empty());
+    cv::Mat img_rgb = readImage("hog/road.png");
+    ASSERT_FALSE(img_rgb.empty());
 
-    #ifdef DUMP
-        f.open((std::string(cvtest::TS::ptr()->get_data_path()) + "hog/expected_output.bin").c_str(), std::ios_base::binary);
-        ASSERT_TRUE(f.is_open());
-    #else
-        f.open((std::string(cvtest::TS::ptr()->get_data_path()) + "hog/expected_output.bin").c_str(), std::ios_base::binary);
-        ASSERT_TRUE(f.is_open());
-    #endif
+#ifdef DUMP
+    f.open((std::string(cvtest::TS::ptr()->get_data_path()) + "hog/expected_output.bin").c_str(), std::ios_base::binary);
+    ASSERT_TRUE(f.is_open());
+#else
+    f.open((std::string(cvtest::TS::ptr()->get_data_path()) + "hog/expected_output.bin").c_str(), std::ios_base::binary);
+    ASSERT_TRUE(f.is_open());
+#endif
 
-        // Test on color image
-        cv::Mat img;
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        testDetect(img);
+    // Test on color image
+    cv::Mat img;
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    testDetect(img);
 
-        // Test on gray image
-        cv::cvtColor(img_rgb, img, CV_BGR2GRAY);
-        testDetect(img);
+    // Test on gray image
+    cv::cvtColor(img_rgb, img, CV_BGR2GRAY);
+    testDetect(img);
 
-        f.close();
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    f.close();
 }
 
 TEST_P(HOG, GetDescriptors)
 {
-    try
+    // Load image (e.g. train data, composed from windows)
+    cv::Mat img_rgb = readImage("hog/train_data.png");
+    ASSERT_FALSE(img_rgb.empty());
+
+    // Convert to C4
+    cv::Mat img;
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+
+    cv::gpu::GpuMat d_img(img);
+
+    // Convert train images into feature vectors (train table)
+    cv::gpu::GpuMat descriptors, descriptors_by_cols;
+    getDescriptors(d_img, win_size, descriptors, DESCR_FORMAT_ROW_BY_ROW);
+    getDescriptors(d_img, win_size, descriptors_by_cols, DESCR_FORMAT_COL_BY_COL);
+
+    // Check size of the result train table
+    wins_per_img_x = 3;
+    wins_per_img_y = 2;
+    blocks_per_win_x = 7;
+    blocks_per_win_y = 15;
+    block_hist_size = 36;
+    cv::Size descr_size_expected = cv::Size(blocks_per_win_x * blocks_per_win_y * block_hist_size,
+                                            wins_per_img_x * wins_per_img_y);
+    ASSERT_EQ(descr_size_expected, descriptors.size());
+
+    // Check both formats of output descriptors are handled correctly
+    cv::Mat dr(descriptors);
+    cv::Mat dc(descriptors_by_cols);
+    for (int i = 0; i < wins_per_img_x * wins_per_img_y; ++i)
     {
-        // Load image (e.g. train data, composed from windows)
-        cv::Mat img_rgb = readImage("hog/train_data.png");
-        ASSERT_FALSE(img_rgb.empty());
-
-        // Convert to C4
-        cv::Mat img;
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-
-        cv::gpu::GpuMat d_img(img);
-
-        // Convert train images into feature vectors (train table)
-        cv::gpu::GpuMat descriptors, descriptors_by_cols;
-        getDescriptors(d_img, win_size, descriptors, DESCR_FORMAT_ROW_BY_ROW);
-        getDescriptors(d_img, win_size, descriptors_by_cols, DESCR_FORMAT_COL_BY_COL);
-
-        // Check size of the result train table
-        wins_per_img_x = 3;
-        wins_per_img_y = 2;
-        blocks_per_win_x = 7;
-        blocks_per_win_y = 15;
-        block_hist_size = 36;
-        cv::Size descr_size_expected = cv::Size(blocks_per_win_x * blocks_per_win_y * block_hist_size,
-                                                wins_per_img_x * wins_per_img_y);
-        ASSERT_EQ(descr_size_expected, descriptors.size());
-
-        // Check both formats of output descriptors are handled correctly
-        cv::Mat dr(descriptors);
-        cv::Mat dc(descriptors_by_cols);
-        for (int i = 0; i < wins_per_img_x * wins_per_img_y; ++i)
-        {
-            const float* l = dr.rowRange(i, i + 1).ptr<float>();
-            const float* r = dc.rowRange(i, i + 1).ptr<float>();
-            for (int y = 0; y < blocks_per_win_y; ++y)
-                for (int x = 0; x < blocks_per_win_x; ++x)
-                    for (int k = 0; k < block_hist_size; ++k)
-                        ASSERT_EQ(l[(y * blocks_per_win_x + x) * block_hist_size + k],
-                                  r[(x * blocks_per_win_y + y) * block_hist_size + k]);
-        }
-
-        /* Now we want to extract the same feature vectors, but from single images. NOTE: results will
-        be defferent, due to border values interpolation. Using of many small images is slower, however we
-        wont't call getDescriptors and will use computeBlockHistograms instead of. computeBlockHistograms
-        works good, it can be checked in the gpu_hog sample */
-
-        img_rgb = readImage("hog/positive1.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        // Everything is fine with interpolation for left top subimage
-        ASSERT_EQ(0.0, cv::norm((cv::Mat)block_hists, (cv::Mat)descriptors.rowRange(0, 1)));
-
-        img_rgb = readImage("hog/positive2.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(1, 2)));
-
-        img_rgb = readImage("hog/negative1.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(2, 3)));
-
-        img_rgb = readImage("hog/negative2.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(3, 4)));
-
-        img_rgb = readImage("hog/positive3.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(4, 5)));
-
-        img_rgb = readImage("hog/negative3.png");
-        ASSERT_TRUE(!img_rgb.empty());
-        cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
-        computeBlockHistograms(cv::gpu::GpuMat(img));
-        compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(5, 6)));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        const float* l = dr.rowRange(i, i + 1).ptr<float>();
+        const float* r = dc.rowRange(i, i + 1).ptr<float>();
+        for (int y = 0; y < blocks_per_win_y; ++y)
+            for (int x = 0; x < blocks_per_win_x; ++x)
+                for (int k = 0; k < block_hist_size; ++k)
+                    ASSERT_EQ(l[(y * blocks_per_win_x + x) * block_hist_size + k],
+                              r[(x * blocks_per_win_y + y) * block_hist_size + k]);
     }
+
+    /* Now we want to extract the same feature vectors, but from single images. NOTE: results will
+    be defferent, due to border values interpolation. Using of many small images is slower, however we
+    wont't call getDescriptors and will use computeBlockHistograms instead of. computeBlockHistograms
+    works good, it can be checked in the gpu_hog sample */
+
+    img_rgb = readImage("hog/positive1.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    // Everything is fine with interpolation for left top subimage
+    ASSERT_EQ(0.0, cv::norm((cv::Mat)block_hists, (cv::Mat)descriptors.rowRange(0, 1)));
+
+    img_rgb = readImage("hog/positive2.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(1, 2)));
+
+    img_rgb = readImage("hog/negative1.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(2, 3)));
+
+    img_rgb = readImage("hog/negative2.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(3, 4)));
+
+    img_rgb = readImage("hog/positive3.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(4, 5)));
+
+    img_rgb = readImage("hog/negative3.png");
+    ASSERT_TRUE(!img_rgb.empty());
+    cv::cvtColor(img_rgb, img, CV_BGR2BGRA);
+    computeBlockHistograms(cv::gpu::GpuMat(img));
+    compare_inner_parts(cv::Mat(block_hists), cv::Mat(descriptors.rowRange(5, 6)));
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, HOG, ALL_DEVICES);
@@ -320,35 +305,27 @@ struct CalTech : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::Device
 
 TEST_P(CalTech, HOG)
 {
-    try
+    cv::gpu::GpuMat d_img(img);
+    cv::Mat markedImage(img.clone());
+
+    cv::gpu::HOGDescriptor d_hog;
+    d_hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
+    d_hog.nlevels = d_hog.nlevels + 32;
+
+    std::vector<cv::Rect> found_locations;
+    d_hog.detectMultiScale(d_img, found_locations);
+
+#if defined (LOG_CASCADE_STATISTIC)
+    for (int i = 0; i < (int)found_locations.size(); i++)
     {
-        cv::gpu::GpuMat d_img(img);
-        cv::Mat markedImage(img.clone());
+        cv::Rect r = found_locations[i];
 
-        cv::gpu::HOGDescriptor d_hog;
-        d_hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
-        d_hog.nlevels = d_hog.nlevels + 32;
-
-        std::vector<cv::Rect> found_locations;
-        d_hog.detectMultiScale(d_img, found_locations);
-
-    #if defined (LOG_CASCADE_STATISTIC)
-        for (int i = 0; i < (int)found_locations.size(); i++)
-        {
-            cv::Rect r = found_locations[i];
-
-            std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
-            cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
-        }
-
-        cv::imshow("Res", markedImage); cv::waitKey();
-    #endif
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
+        cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
     }
+
+    cv::imshow("Res", markedImage); cv::waitKey();
+#endif
 }
 
 INSTANTIATE_TEST_CASE_P(detect, CalTech, testing::Combine(ALL_DEVICES,
@@ -375,17 +352,9 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
 
 TEST_P(LBP_Read_classifier, Accuracy)
 {
-    try
-    {
-        cv::gpu::CascadeClassifier_GPU classifier;
-        std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
-        ASSERT_TRUE(classifier.load(classifierXmlPath));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    cv::gpu::CascadeClassifier_GPU classifier;
+    std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
+    ASSERT_TRUE(classifier.load(classifierXmlPath));
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_Read_classifier,
@@ -405,57 +374,49 @@ PARAM_TEST_CASE(LBP_classify, cv::gpu::DeviceInfo, int)
 
 TEST_P(LBP_classify, Accuracy)
 {
-    try
+    std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
+    std::string imagePath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/er.png";
+
+    cv::CascadeClassifier cpuClassifier(classifierXmlPath);
+    ASSERT_FALSE(cpuClassifier.empty());
+
+    cv::Mat image = cv::imread(imagePath);
+    image = image.colRange(0, image.cols/2);
+    cv::Mat grey;
+    cvtColor(image, grey, CV_BGR2GRAY);
+    ASSERT_FALSE(image.empty());
+
+    std::vector<cv::Rect> rects;
+    cpuClassifier.detectMultiScale(grey, rects);
+    cv::Mat markedImage = image.clone();
+
+    std::vector<cv::Rect>::iterator it = rects.begin();
+    for (; it != rects.end(); ++it)
+        cv::rectangle(markedImage, *it, CV_RGB(0, 0, 255));
+
+    cv::gpu::CascadeClassifier_GPU gpuClassifier;
+    ASSERT_TRUE(gpuClassifier.load(classifierXmlPath));
+
+    cv::gpu::GpuMat gpu_rects;
+    cv::gpu::GpuMat tested(grey);
+    int count = gpuClassifier.detectMultiScale(tested, gpu_rects);
+
+#if defined (LOG_CASCADE_STATISTIC)
+    cv::Mat downloaded(gpu_rects);
+    const cv::Rect* faces = downloaded.ptr<cv::Rect>();
+    for (int i = 0; i < count; i++)
     {
-        std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
-        std::string imagePath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/er.png";
+        cv::Rect r = faces[i];
 
-        cv::CascadeClassifier cpuClassifier(classifierXmlPath);
-        ASSERT_FALSE(cpuClassifier.empty());
-
-        cv::Mat image = cv::imread(imagePath);
-        image = image.colRange(0, image.cols/2);
-        cv::Mat grey;
-        cvtColor(image, grey, CV_BGR2GRAY);
-        ASSERT_FALSE(image.empty());
-
-        std::vector<cv::Rect> rects;
-        cpuClassifier.detectMultiScale(grey, rects);
-        cv::Mat markedImage = image.clone();
-
-        std::vector<cv::Rect>::iterator it = rects.begin();
-        for (; it != rects.end(); ++it)
-            cv::rectangle(markedImage, *it, CV_RGB(0, 0, 255));
-
-        cv::gpu::CascadeClassifier_GPU gpuClassifier;
-        ASSERT_TRUE(gpuClassifier.load(classifierXmlPath));
-
-        cv::gpu::GpuMat gpu_rects;
-        cv::gpu::GpuMat tested(grey);
-        int count = gpuClassifier.detectMultiScale(tested, gpu_rects);
-
-    #if defined (LOG_CASCADE_STATISTIC)
-        cv::Mat downloaded(gpu_rects);
-        const cv::Rect* faces = downloaded.ptr<cv::Rect>();
-        for (int i = 0; i < count; i++)
-        {
-            cv::Rect r = faces[i];
-
-            std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
-            cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
-        }
-    #endif
-
-    #if defined (LOG_CASCADE_STATISTIC)
-        cv::imshow("Res", markedImage); cv::waitKey();
-    #endif
-        (void)count;
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        std::cout << r.x << " " << r.y  << " " << r.width << " " << r.height << std::endl;
+        cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
     }
+#endif
+
+#if defined (LOG_CASCADE_STATISTIC)
+    cv::imshow("Res", markedImage); cv::waitKey();
+#endif
+    (void)count;
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,

modules/gpu/test/test_opengl.cpp

@@ -70,402 +70,258 @@ PARAM_TEST_CASE(GlBuffer, cv::Size, MatType)
 
 TEST_P(GlBuffer, Constructor1)
 {
-    try
-    {
-        cv::GlBuffer buf(size.height, size.width, type, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(size.height, size.width, type, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_EQ(size.height, buf.rows());
-        EXPECT_EQ(size.width, buf.cols());
-        EXPECT_EQ(type, buf.type());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, buf.rows());
+    EXPECT_EQ(size.width, buf.cols());
+    EXPECT_EQ(type, buf.type());
 }
 
 TEST_P(GlBuffer, Constructor2)
 {
-    try
-    {
-        cv::GlBuffer buf(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_EQ(size.height, buf.rows());
-        EXPECT_EQ(size.width, buf.cols());
-        EXPECT_EQ(type, buf.type());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, buf.rows());
+    EXPECT_EQ(size.width, buf.cols());
+    EXPECT_EQ(type, buf.type());
 }
 
 TEST_P(GlBuffer, ConstructorFromMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, ConstructorFromGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
-        cv::gpu::GpuMat d_gold(gold);
+    cv::Mat gold = randomMat(size, type);
+    cv::gpu::GpuMat d_gold(gold);
 
-        cv::GlBuffer buf(d_gold, cv::GlBuffer::ARRAY_BUFFER);
+    cv::GlBuffer buf(d_gold, cv::GlBuffer::ARRAY_BUFFER);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, ConstructorFromGlBuffer)
 {
-    try
-    {
-        cv::GlBuffer buf_gold(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf_gold(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::GlBuffer buf(buf_gold);
+    cv::GlBuffer buf(buf_gold);
 
-        EXPECT_EQ(buf_gold.bufId(), buf.bufId());
-        EXPECT_EQ(buf_gold.rows(), buf.rows());
-        EXPECT_EQ(buf_gold.cols(), buf.cols());
-        EXPECT_EQ(buf_gold.type(), buf.type());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(buf_gold.bufId(), buf.bufId());
+    EXPECT_EQ(buf_gold.rows(), buf.rows());
+    EXPECT_EQ(buf_gold.cols(), buf.cols());
+    EXPECT_EQ(buf_gold.type(), buf.type());
 }
 
 TEST_P(GlBuffer, ConstructorFromGlTexture2D)
 {
-    try
-    {
-        const int depth = CV_MAT_DEPTH(type);
-        const int cn = CV_MAT_CN(type);
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
 
-        if (depth != CV_32F || cn == 2)
-            return;
+    if (depth != CV_32F || cn == 2)
+        return;
 
-        cv::Mat gold = randomMat(size, type, 0, 1.0);
-        cv::GlTexture2D tex_gold(gold, true);
+    cv::Mat gold = randomMat(size, type, 0, 1.0);
+    cv::GlTexture2D tex_gold(gold, true);
 
-        cv::GlBuffer buf(tex_gold, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
+    cv::GlBuffer buf(tex_gold, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 1e-2);
 }
 
 TEST_P(GlBuffer, Create)
 {
-    try
-    {
-        cv::GlBuffer buf;
-        buf.create(size.height, size.width, type, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf;
+    buf.create(size.height, size.width, type, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_EQ(size.height, buf.rows());
-        EXPECT_EQ(size.width, buf.cols());
-        EXPECT_EQ(type, buf.type());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, buf.rows());
+    EXPECT_EQ(size.width, buf.cols());
+    EXPECT_EQ(type, buf.type());
 }
 
 TEST_P(GlBuffer, CopyFromMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf;
-        buf.copyFrom(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf;
+    buf.copyFrom(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, CopyFromGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
-        cv::gpu::GpuMat d_gold(gold);
+    cv::Mat gold = randomMat(size, type);
+    cv::gpu::GpuMat d_gold(gold);
 
-        cv::GlBuffer buf;
-        buf.copyFrom(d_gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf;
+    buf.copyFrom(d_gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, CopyFromGlBuffer)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
-        cv::GlBuffer buf_gold(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::Mat gold = randomMat(size, type);
+    cv::GlBuffer buf_gold(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::GlBuffer buf;
-        buf.copyFrom(buf_gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf;
+    buf.copyFrom(buf_gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_NE(buf_gold.bufId(), buf.bufId());
+    EXPECT_NE(buf_gold.bufId(), buf.bufId());
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, CopyFromGlTexture2D)
 {
-    try
-    {
-        const int depth = CV_MAT_DEPTH(type);
-        const int cn = CV_MAT_CN(type);
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
 
-        if (depth != CV_32F || cn == 2)
-            return;
+    if (depth != CV_32F || cn == 2)
+        return;
 
-        cv::Mat gold = randomMat(size, type, 0, 1.0);
-        cv::GlTexture2D tex_gold(gold, true);
+    cv::Mat gold = randomMat(size, type, 0, 1.0);
+    cv::GlTexture2D tex_gold(gold, true);
 
-        cv::GlBuffer buf;
-        buf.copyFrom(tex_gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf;
+    buf.copyFrom(tex_gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 1e-2);
 }
 
 TEST_P(GlBuffer, CopyToGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::gpu::GpuMat dst;
-        buf.copyTo(dst);
+    cv::gpu::GpuMat dst;
+    buf.copyTo(dst);
 
-        EXPECT_MAT_NEAR(gold, dst, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, dst, 0);
 }
 
 TEST_P(GlBuffer, CopyToGlBuffer)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::GlBuffer dst;
-        buf.copyTo(dst, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer dst;
+    buf.copyTo(dst, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_NE(buf.bufId(), dst.bufId());
+    EXPECT_NE(buf.bufId(), dst.bufId());
 
-        cv::Mat bufData;
-        dst.copyTo(bufData);
+    cv::Mat bufData;
+    dst.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, CopyToGlTexture2D)
 {
-    try
-    {
-        const int depth = CV_MAT_DEPTH(type);
-        const int cn = CV_MAT_CN(type);
+    const int depth = CV_MAT_DEPTH(type);
+    const int cn = CV_MAT_CN(type);
 
-        if (depth != CV_32F || cn == 2)
-            return;
+    if (depth != CV_32F || cn == 2)
+        return;
 
-        cv::Mat gold = randomMat(size, type, 0, 1.0);
+    cv::Mat gold = randomMat(size, type, 0, 1.0);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
 
-        cv::GlTexture2D tex;
-        buf.copyTo(tex, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
+    cv::GlTexture2D tex;
+    buf.copyTo(tex, cv::GlBuffer::PIXEL_PACK_BUFFER, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData);
+    cv::Mat texData;
+    tex.copyTo(texData);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlBuffer, Clone)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::GlBuffer dst = buf.clone(cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer dst = buf.clone(cv::GlBuffer::ARRAY_BUFFER, true);
 
-        EXPECT_NE(buf.bufId(), dst.bufId());
+    EXPECT_NE(buf.bufId(), dst.bufId());
 
-        cv::Mat bufData;
-        dst.copyTo(bufData);
+    cv::Mat bufData;
+    dst.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, MapHostRead)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat dst = buf.mapHost(cv::GlBuffer::READ_ONLY);
+    cv::Mat dst = buf.mapHost(cv::GlBuffer::READ_ONLY);
 
-        EXPECT_MAT_NEAR(gold, dst, 0);
+    EXPECT_MAT_NEAR(gold, dst, 0);
 
-        buf.unmapHost();
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    buf.unmapHost();
 }
 
 TEST_P(GlBuffer, MapHostWrite)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(size, type, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::Mat dst = buf.mapHost(cv::GlBuffer::WRITE_ONLY);
-        gold.copyTo(dst);
-        buf.unmapHost();
-        dst.release();
+    cv::Mat dst = buf.mapHost(cv::GlBuffer::WRITE_ONLY);
+    gold.copyTo(dst);
+    buf.unmapHost();
+    dst.release();
 
-        cv::Mat bufData;
-        buf.copyTo(bufData);
+    cv::Mat bufData;
+    buf.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 0);
 }
 
 TEST_P(GlBuffer, MapDevice)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type);
+    cv::Mat gold = randomMat(size, type);
 
-        cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
+    cv::GlBuffer buf(gold, cv::GlBuffer::ARRAY_BUFFER, true);
 
-        cv::gpu::GpuMat dst = buf.mapDevice();
+    cv::gpu::GpuMat dst = buf.mapDevice();
 
-        EXPECT_MAT_NEAR(gold, dst, 0);
+    EXPECT_MAT_NEAR(gold, dst, 0);
 
-        buf.unmapDevice();
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    buf.unmapDevice();
 }
 
 INSTANTIATE_TEST_CASE_P(OpenGL, GlBuffer, testing::Combine(DIFFERENT_SIZES, ALL_TYPES));
@@ -504,243 +360,147 @@ PARAM_TEST_CASE(GlTexture2D, cv::Size, MatType)
 
 TEST_P(GlTexture2D, Constructor1)
 {
-    try
-    {
-        cv::GlTexture2D tex(size.height, size.width, format, true);
+    cv::GlTexture2D tex(size.height, size.width, format, true);
 
-        EXPECT_EQ(size.height, tex.rows());
-        EXPECT_EQ(size.width, tex.cols());
-        EXPECT_EQ(format, tex.format());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, tex.rows());
+    EXPECT_EQ(size.width, tex.cols());
+    EXPECT_EQ(format, tex.format());
 }
 
 TEST_P(GlTexture2D, Constructor2)
 {
-    try
-    {
-        cv::GlTexture2D tex(size, format, true);
+    cv::GlTexture2D tex(size, format, true);
 
-        EXPECT_EQ(size.height, tex.rows());
-        EXPECT_EQ(size.width, tex.cols());
-        EXPECT_EQ(format, tex.format());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, tex.rows());
+    EXPECT_EQ(size.width, tex.cols());
+    EXPECT_EQ(format, tex.format());
 }
 
 TEST_P(GlTexture2D, ConstructorFromMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
 
-        cv::GlTexture2D tex(gold, true);
+    cv::GlTexture2D tex(gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, ConstructorFromGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
-        cv::gpu::GpuMat d_gold(gold);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::gpu::GpuMat d_gold(gold);
 
-        cv::GlTexture2D tex(d_gold, true);
+    cv::GlTexture2D tex(d_gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, ConstructorFromGlBuffer)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
-        cv::GlBuffer buf_gold(gold, cv::GlBuffer::PIXEL_UNPACK_BUFFER, true);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::GlBuffer buf_gold(gold, cv::GlBuffer::PIXEL_UNPACK_BUFFER, true);
 
-        cv::GlTexture2D tex(buf_gold, true);
+    cv::GlTexture2D tex(buf_gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, ConstructorFromGlTexture2D)
 {
-    try
-    {
-        cv::GlTexture2D tex_gold(size, format, true);
-        cv::GlTexture2D tex(tex_gold);
+    cv::GlTexture2D tex_gold(size, format, true);
+    cv::GlTexture2D tex(tex_gold);
 
-        EXPECT_EQ(tex_gold.texId(), tex.texId());
-        EXPECT_EQ(tex_gold.rows(), tex.rows());
-        EXPECT_EQ(tex_gold.cols(), tex.cols());
-        EXPECT_EQ(tex_gold.format(), tex.format());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(tex_gold.texId(), tex.texId());
+    EXPECT_EQ(tex_gold.rows(), tex.rows());
+    EXPECT_EQ(tex_gold.cols(), tex.cols());
+    EXPECT_EQ(tex_gold.format(), tex.format());
 }
 
 TEST_P(GlTexture2D, Create)
 {
-    try
-    {
-        cv::GlTexture2D tex;
-        tex.create(size.height, size.width, format, true);
+    cv::GlTexture2D tex;
+    tex.create(size.height, size.width, format, true);
 
-        EXPECT_EQ(size.height, tex.rows());
-        EXPECT_EQ(size.width, tex.cols());
-        EXPECT_EQ(format, tex.format());
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_EQ(size.height, tex.rows());
+    EXPECT_EQ(size.width, tex.cols());
+    EXPECT_EQ(format, tex.format());
 }
 
 TEST_P(GlTexture2D, CopyFromMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
 
-        cv::GlTexture2D tex;
-        tex.copyFrom(gold, true);
+    cv::GlTexture2D tex;
+    tex.copyFrom(gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, CopyFromGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
-        cv::gpu::GpuMat d_gold(gold);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::gpu::GpuMat d_gold(gold);
 
-        cv::GlTexture2D tex;
-        tex.copyFrom(d_gold, true);
+    cv::GlTexture2D tex;
+    tex.copyFrom(d_gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, CopyFromGlBuffer)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
-        cv::GlBuffer buf_gold(gold, cv::GlBuffer::PIXEL_UNPACK_BUFFER, true);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::GlBuffer buf_gold(gold, cv::GlBuffer::PIXEL_UNPACK_BUFFER, true);
 
-        cv::GlTexture2D tex;
-        tex.copyFrom(buf_gold, true);
+    cv::GlTexture2D tex;
+    tex.copyFrom(buf_gold, true);
 
-        cv::Mat texData;
-        tex.copyTo(texData, depth);
+    cv::Mat texData;
+    tex.copyTo(texData, depth);
 
-        EXPECT_MAT_NEAR(gold, texData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, texData, 1e-2);
 }
 
 TEST_P(GlTexture2D, CopyToGpuMat)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
 
-        cv::GlTexture2D tex(gold, true);
+    cv::GlTexture2D tex(gold, true);
 
-        cv::gpu::GpuMat dst;
-        tex.copyTo(dst, depth);
+    cv::gpu::GpuMat dst;
+    tex.copyTo(dst, depth);
 
-        EXPECT_MAT_NEAR(gold, dst, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, dst, 1e-2);
 }
 
 TEST_P(GlTexture2D, CopyToGlBuffer)
 {
-    try
-    {
-        cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
+    cv::Mat gold = randomMat(size, type, 0, depth == CV_8U ? 255 : 1);
 
-        cv::GlTexture2D tex(gold, true);
+    cv::GlTexture2D tex(gold, true);
 
-        cv::GlBuffer dst;
-        tex.copyTo(dst, depth, true);
+    cv::GlBuffer dst;
+    tex.copyTo(dst, depth, true);
 
-        cv::Mat bufData;
-        dst.copyTo(bufData);
+    cv::Mat bufData;
+    dst.copyTo(bufData);
 
-        EXPECT_MAT_NEAR(gold, bufData, 1e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(gold, bufData, 1e-2);
 }
 
 INSTANTIATE_TEST_CASE_P(OpenGL, GlTexture2D, testing::Combine(DIFFERENT_SIZES, testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4)));

modules/gpu/test/test_pyramids.cpp

@@ -66,23 +66,15 @@ PARAM_TEST_CASE(PyrDown, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
 
 TEST_P(PyrDown, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size((size.width + 1) / 2, (size.height + 1) / 2), type, useRoi);
-        cv::gpu::pyrDown(loadMat(src, useRoi), dst);
+    cv::gpu::GpuMat dst = createMat(cv::Size((size.width + 1) / 2, (size.height + 1) / 2), type, useRoi);
+    cv::gpu::pyrDown(loadMat(src, useRoi), dst);
 
-        cv::Mat dst_gold;
-        cv::pyrDown(src, dst_gold);
+    cv::Mat dst_gold;
+    cv::pyrDown(src, dst_gold);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, PyrDown, testing::Combine(
@@ -114,23 +106,15 @@ PARAM_TEST_CASE(PyrUp, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
 
 TEST_P(PyrUp, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size(size.width * 2, size.height * 2), type, useRoi);
-        cv::gpu::pyrUp(loadMat(src, useRoi), dst);
+    cv::gpu::GpuMat dst = createMat(cv::Size(size.width * 2, size.height * 2), type, useRoi);
+    cv::gpu::pyrUp(loadMat(src, useRoi), dst);
 
-        cv::Mat dst_gold;
-        cv::pyrUp(src, dst_gold);
+    cv::Mat dst_gold;
+    cv::pyrUp(src, dst_gold);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, PyrUp, testing::Combine(

modules/gpu/test/test_remap.cpp

@@ -154,24 +154,16 @@ PARAM_TEST_CASE(Remap, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, Bo
 
 TEST_P(Remap, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Scalar val = randomScalar(0.0, 255.0);
+    cv::Mat src = randomMat(size, type);
+    cv::Scalar val = randomScalar(0.0, 255.0);
 
-        cv::gpu::GpuMat dst = createMat(xmap.size(), type, useRoi);
-        cv::gpu::remap(loadMat(src, useRoi), dst, loadMat(xmap, useRoi), loadMat(ymap, useRoi), interpolation, borderType, val);
+    cv::gpu::GpuMat dst = createMat(xmap.size(), type, useRoi);
+    cv::gpu::remap(loadMat(src, useRoi), dst, loadMat(xmap, useRoi), loadMat(ymap, useRoi), interpolation, borderType, val);
 
-        cv::Mat dst_gold;
-        remapGold(src, xmap, ymap, dst_gold, interpolation, borderType, val);
+    cv::Mat dst_gold;
+    remapGold(src, xmap, ymap, dst_gold, interpolation, borderType, val);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-3 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Remap, testing::Combine(

modules/gpu/test/test_resize.cpp

@@ -138,23 +138,15 @@ PARAM_TEST_CASE(Resize, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpol
 
 TEST_P(Resize, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
-        cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
+    cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
+    cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
 
-        cv::Mat dst_gold;
-        resizeGold(src, dst_gold, coeff, coeff, interpolation);
+    cv::Mat dst_gold;
+    resizeGold(src, dst_gold, coeff, coeff, interpolation);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
@@ -192,23 +184,15 @@ PARAM_TEST_CASE(ResizeSameAsHost, cv::gpu::DeviceInfo, cv::Size, MatType, double
 // downscaling only: used for classifiers
 TEST_P(ResizeSameAsHost, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
+    cv::Mat src = randomMat(size, type);
 
-        cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
-        cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
+    cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
+    cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
 
-        cv::Mat dst_gold;
-        cv::resize(src, dst_gold, cv::Size(), coeff, coeff, interpolation);
+    cv::Mat dst_gold;
+    cv::resize(src, dst_gold, cv::Size(), coeff, coeff, interpolation);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeSameAsHost, testing::Combine(
@@ -242,24 +226,16 @@ PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation)
 
 TEST_P(ResizeNPP, Accuracy)
 {
-    try
-    {
-        cv::Mat src = readImageType("stereobp/aloe-L.png", type);
-        ASSERT_FALSE(src.empty());
+    cv::Mat src = readImageType("stereobp/aloe-L.png", type);
+    ASSERT_FALSE(src.empty());
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::resize(loadMat(src), dst, cv::Size(), coeff, coeff, interpolation);
+    cv::gpu::GpuMat dst;
+    cv::gpu::resize(loadMat(src), dst, cv::Size(), coeff, coeff, interpolation);
 
-        cv::Mat dst_gold;
-        resizeGold(src, dst_gold, coeff, coeff, interpolation);
+    cv::Mat dst_gold;
+    resizeGold(src, dst_gold, coeff, coeff, interpolation);
 
-        EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-1);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeNPP, testing::Combine(

modules/gpu/test/test_softcascade.cpp

@@ -40,7 +40,7 @@
 //
 //M*/
 
-#include "test_precomp.hpp"
+#include <test_precomp.hpp>
 #include <time.h>
 
 #ifdef HAVE_CUDA
@@ -158,77 +158,62 @@ GPU_TEST_P(SCascadeTestRoi, detect,
         testing::Values(std::string("../cv/cascadeandhog/bahnhof/image_00000000_0.png")),
         testing::Range(0, 5)))
 {
-    try
+    cv::gpu::setDevice(GET_PARAM(0).deviceID());
+    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path() + GET_PARAM(2));
+    ASSERT_FALSE(coloredCpu.empty());
+
+    cv::gpu::SCascade cascade;
+
+    cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(1)), cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
+
+    ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
+
+    GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(colored.size(), CV_8UC1);
+    rois.setTo(0);
+
+    int nroi = GET_PARAM(3);
+    cv::Mat result(coloredCpu);
+    cv::RNG rng;
+    for (int i = 0; i < nroi; ++i)
     {
-        cv::gpu::setDevice(GET_PARAM(0).deviceID());
-        cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path() + GET_PARAM(2));
-        ASSERT_FALSE(coloredCpu.empty());
-
-        cv::gpu::SCascade cascade;
-
-        cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(1)), cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
-
-        ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
-
-        GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(colored.size(), CV_8UC1);
-        rois.setTo(0);
-
-        int nroi = GET_PARAM(3);
-        cv::Mat result(coloredCpu);
-        cv::RNG rng;
-        for (int i = 0; i < nroi; ++i)
-        {
-            cv::Rect r = getFromTable(rng(10));
-            GpuMat sub(rois, r);
-            sub.setTo(1);
-            cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1);
-        }
-        objectBoxes.setTo(0);
-
-        cascade.detect(colored, rois, objectBoxes);
-
-        cv::Mat dt(objectBoxes);
-        typedef cv::gpu::SCascade::Detection Detection;
-
-        Detection* dts = ((Detection*)dt.data) + 1;
-        int* count = dt.ptr<int>(0);
-
-        printTotal(std::cout, *count);
-
-        for (int i = 0; i  < *count; ++i)
-        {
-            Detection d = dts[i];
-            print(std::cout, d);
-            cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
-        }
-
-        SHOW(result);
+        cv::Rect r = getFromTable(rng(10));
+        GpuMat sub(rois, r);
+        sub.setTo(1);
+        cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1);
     }
-    catch (...)
+    objectBoxes.setTo(0);
+
+    cascade.detect(colored, rois, objectBoxes);
+
+    cv::Mat dt(objectBoxes);
+    typedef cv::gpu::SCascade::Detection Detection;
+
+    Detection* dts = ((Detection*)dt.data) + 1;
+    int* count = dt.ptr<int>(0);
+
+    printTotal(std::cout, *count);
+
+    for (int i = 0; i  < *count; ++i)
     {
-        cv::gpu::resetDevice();
-        throw;
+        Detection d = dts[i];
+        print(std::cout, d);
+        cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
     }
+
+    SHOW(result);
+
 }
 
 TEST(SCascadeTest, readCascade)
 {
-    try
-    {
-        std::string xml = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/icf-template.xml";
-        cv::gpu::SCascade cascade;
+    std::string xml = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/icf-template.xml";
+    cv::gpu::SCascade cascade;
 
-        cv::FileStorage fs(xml, cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
+    cv::FileStorage fs(xml, cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
 
-        ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 }
 
 typedef ::testing::TestWithParam<cv::gpu::DeviceInfo > SCascadeTestAll;
@@ -236,129 +221,105 @@ GPU_TEST_P(SCascadeTestAll, detect,
         ALL_DEVICES
         )
 {
-    try
-    {
-        cv::gpu::setDevice(GetParam().deviceID());
-        std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
-        cv::gpu::SCascade cascade;
+    cv::gpu::setDevice(GetParam().deviceID());
+    std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
+    cv::gpu::SCascade cascade;
 
-        cv::FileStorage fs(xml, cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
+    cv::FileStorage fs(xml, cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
 
-        ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
+    ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
-        cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path()
-            + "../cv/cascadeandhog/bahnhof/image_00000000_0.png");
-        ASSERT_FALSE(coloredCpu.empty());
+    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path()
+        + "../cv/cascadeandhog/bahnhof/image_00000000_0.png");
+    ASSERT_FALSE(coloredCpu.empty());
 
-        GpuMat colored(coloredCpu), objectBoxes, rois(colored.size(), CV_8UC1);
-        rois.setTo(0);
-        GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
-        sub.setTo(cv::Scalar::all(1));
+    GpuMat colored(coloredCpu), objectBoxes, rois(colored.size(), CV_8UC1);
+    rois.setTo(0);
+    GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
+    sub.setTo(cv::Scalar::all(1));
 
-        objectBoxes.setTo(0);
-        cascade.detect(colored, rois, objectBoxes);
+    objectBoxes.setTo(0);
+    cascade.detect(colored, rois, objectBoxes);
 
-        typedef cv::gpu::SCascade::Detection Detection;
-        cv::Mat detections(objectBoxes);
-        int a = *(detections.ptr<int>(0));
-        ASSERT_EQ(a, 2448);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    typedef cv::gpu::SCascade::Detection Detection;
+    cv::Mat detections(objectBoxes);
+    int a = *(detections.ptr<int>(0));
+    ASSERT_EQ(a ,2448);
 }
 
 GPU_TEST_P(SCascadeTestAll, detectOnIntegral,
         ALL_DEVICES
         )
 {
-    try
+    cv::gpu::setDevice(GetParam().deviceID());
+    std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
+    cv::gpu::SCascade cascade;
+
+    cv::FileStorage fs(xml, cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
+
+    ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
+
+    std::string intPath = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/integrals.xml";
+    cv::FileStorage fsi(intPath, cv::FileStorage::READ);
+    ASSERT_TRUE(fsi.isOpened());
+
+    GpuMat hogluv(121 * 10, 161, CV_32SC1);
+    for (int i = 0; i < 10; ++i)
     {
-        cv::gpu::setDevice(GetParam().deviceID());
-        std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
-        cv::gpu::SCascade cascade;
-
-        cv::FileStorage fs(xml, cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
-
-        ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
-
-        std::string intPath = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/integrals.xml";
-        cv::FileStorage fsi(intPath, cv::FileStorage::READ);
-        ASSERT_TRUE(fsi.isOpened());
-
-        GpuMat hogluv(121 * 10, 161, CV_32SC1);
-        for (int i = 0; i < 10; ++i)
-        {
-            cv::Mat channel;
-            fsi[std::string("channel") + itoa(i)] >> channel;
-            GpuMat gchannel(hogluv, cv::Rect(0, 121 * i, 161, 121));
-            gchannel.upload(channel);
-        }
-
-        GpuMat objectBoxes(1, 100000, CV_8UC1), rois(cv::Size(640, 480), CV_8UC1);
-        rois.setTo(1);
-
-        objectBoxes.setTo(0);
-        cascade.detect(hogluv, rois, objectBoxes);
-
-        typedef cv::gpu::SCascade::Detection Detection;
-        cv::Mat detections(objectBoxes);
-        int a = *(detections.ptr<int>(0));
-
-        ASSERT_EQ(a, 1024);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
+        cv::Mat channel;
+        fsi[std::string("channel") + itoa(i)] >> channel;
+        GpuMat gchannel(hogluv, cv::Rect(0, 121 * i, 161, 121));
+        gchannel.upload(channel);
     }
+
+    GpuMat objectBoxes(1, 100000, CV_8UC1), rois(cv::Size(640, 480), CV_8UC1);
+    rois.setTo(1);
+
+    objectBoxes.setTo(0);
+    cascade.detect(hogluv, rois, objectBoxes);
+
+    typedef cv::gpu::SCascade::Detection Detection;
+    cv::Mat detections(objectBoxes);
+    int a = *(detections.ptr<int>(0));
+
+    ASSERT_EQ( a ,1024);
 }
 
 GPU_TEST_P(SCascadeTestAll, detectStream,
         ALL_DEVICES
         )
 {
-    try
-    {
-        cv::gpu::setDevice(GetParam().deviceID());
-        std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
-        cv::gpu::SCascade cascade;
+    cv::gpu::setDevice(GetParam().deviceID());
+    std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
+    cv::gpu::SCascade cascade;
 
-        cv::FileStorage fs(xml, cv::FileStorage::READ);
-        ASSERT_TRUE(fs.isOpened());
+    cv::FileStorage fs(xml, cv::FileStorage::READ);
+    ASSERT_TRUE(fs.isOpened());
 
-        ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
+    ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode()));
 
-        cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path()
-            + "../cv/cascadeandhog/bahnhof/image_00000000_0.png");
-        ASSERT_FALSE(coloredCpu.empty());
+    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path()
+        + "../cv/cascadeandhog/bahnhof/image_00000000_0.png");
+    ASSERT_FALSE(coloredCpu.empty());
 
-        GpuMat colored(coloredCpu), objectBoxes(1, 100000, CV_8UC1), rois(colored.size(), CV_8UC1);
-        rois.setTo(0);
-        GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
-        sub.setTo(cv::Scalar::all(1));
+    GpuMat colored(coloredCpu), objectBoxes(1, 100000, CV_8UC1), rois(colored.size(), CV_8UC1);
+    rois.setTo(0);
+    GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
+    sub.setTo(cv::Scalar::all(1));
 
-        cv::gpu::Stream s;
+    cv::gpu::Stream s;
 
-        objectBoxes.setTo(0);
-        cascade.detect(colored, rois, objectBoxes, s);
-        s.waitForCompletion();
+    objectBoxes.setTo(0);
+    cascade.detect(colored, rois, objectBoxes, s);
+    s.waitForCompletion();
 
-        typedef cv::gpu::SCascade::Detection Detection;
-        cv::Mat detections(objectBoxes);
-        int a = *(detections.ptr<int>(0));
-        ASSERT_EQ(a, 2448);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    typedef cv::gpu::SCascade::Detection Detection;
+    cv::Mat detections(objectBoxes);
+    int a = *(detections.ptr<int>(0));
+    ASSERT_EQ(a ,2448);
 }
 
 
-#endif
+#endif

modules/gpu/test/test_threshold.cpp

@@ -68,25 +68,17 @@ PARAM_TEST_CASE(Threshold, cv::gpu::DeviceInfo, cv::Size, MatType, ThreshOp, Use
 
 TEST_P(Threshold, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        double maxVal = randomDouble(20.0, 127.0);
-        double thresh = randomDouble(0.0, maxVal);
+    cv::Mat src = randomMat(size, type);
+    double maxVal = randomDouble(20.0, 127.0);
+    double thresh = randomDouble(0.0, maxVal);
 
-        cv::gpu::GpuMat dst = createMat(src.size(), src.type(), useRoi);
-        cv::gpu::threshold(loadMat(src, useRoi), dst, thresh, maxVal, threshOp);
+    cv::gpu::GpuMat dst = createMat(src.size(), src.type(), useRoi);
+    cv::gpu::threshold(loadMat(src, useRoi), dst, thresh, maxVal, threshOp);
 
-        cv::Mat dst_gold;
-        cv::threshold(src, dst_gold, thresh, maxVal, threshOp);
+    cv::Mat dst_gold;
+    cv::threshold(src, dst_gold, thresh, maxVal, threshOp);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Threshold, testing::Combine(

modules/gpu/test/test_warp_affine.cpp

@@ -76,32 +76,24 @@ PARAM_TEST_CASE(BuildWarpAffineMaps, cv::gpu::DeviceInfo, cv::Size, Inverse)
 
 TEST_P(BuildWarpAffineMaps, Accuracy)
 {
-    try
-    {
-        cv::Mat M = createTransfomMatrix(size, CV_PI / 4);
-        cv::gpu::GpuMat xmap, ymap;
-        cv::gpu::buildWarpAffineMaps(M, inverse, size, xmap, ymap);
+    cv::Mat M = createTransfomMatrix(size, CV_PI / 4);
+    cv::gpu::GpuMat xmap, ymap;
+    cv::gpu::buildWarpAffineMaps(M, inverse, size, xmap, ymap);
 
-        int interpolation = cv::INTER_NEAREST;
-        int borderMode = cv::BORDER_CONSTANT;
+    int interpolation = cv::INTER_NEAREST;
+    int borderMode = cv::BORDER_CONSTANT;
 
-        cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1);
-        cv::Mat dst;
-        cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), interpolation, borderMode);
+    cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1);
+    cv::Mat dst;
+    cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), interpolation, borderMode);
 
-        int flags = interpolation;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
-        cv::Mat dst_gold;
-        cv::warpAffine(src, dst_gold, M, size, flags, borderMode);
+    int flags = interpolation;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
+    cv::Mat dst_gold;
+    cv::warpAffine(src, dst_gold, M, size, flags, borderMode);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, BuildWarpAffineMaps, testing::Combine(
@@ -209,28 +201,20 @@ PARAM_TEST_CASE(WarpAffine, cv::gpu::DeviceInfo, cv::Size, MatType, Inverse, Int
 
 TEST_P(WarpAffine, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat M = createTransfomMatrix(size, CV_PI / 3);
-        int flags = interpolation;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
-        cv::Scalar val = randomScalar(0.0, 255.0);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat M = createTransfomMatrix(size, CV_PI / 3);
+    int flags = interpolation;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
+    cv::Scalar val = randomScalar(0.0, 255.0);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::warpAffine(loadMat(src, useRoi), dst, M, size, flags, borderType, val);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::warpAffine(loadMat(src, useRoi), dst, M, size, flags, borderType, val);
 
-        cv::Mat dst_gold;
-        warpAffineGold(src, M, inverse, size, dst_gold, interpolation, borderType, val);
+    cv::Mat dst_gold;
+    warpAffineGold(src, M, inverse, size, dst_gold, interpolation, borderType, val);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpAffine, testing::Combine(
@@ -265,27 +249,19 @@ PARAM_TEST_CASE(WarpAffineNPP, cv::gpu::DeviceInfo, MatType, Inverse, Interpolat
 
 TEST_P(WarpAffineNPP, Accuracy)
 {
-    try
-    {
-        cv::Mat src = readImageType("stereobp/aloe-L.png", type);
-        cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4);
-        int flags = interpolation;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
+    cv::Mat src = readImageType("stereobp/aloe-L.png", type);
+    cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4);
+    int flags = interpolation;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::warpAffine(loadMat(src), dst, M, src.size(), flags);
+    cv::gpu::GpuMat dst;
+    cv::gpu::warpAffine(loadMat(src), dst, M, src.size(), flags);
 
-        cv::Mat dst_gold;
-        warpAffineGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0));
+    cv::Mat dst_gold;
+    warpAffineGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0));
 
-        EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpAffineNPP, testing::Combine(

modules/gpu/test/test_warp_perspective.cpp

@@ -77,29 +77,21 @@ PARAM_TEST_CASE(BuildWarpPerspectiveMaps, cv::gpu::DeviceInfo, cv::Size, Inverse
 
 TEST_P(BuildWarpPerspectiveMaps, Accuracy)
 {
-    try
-    {
-        cv::Mat M = createTransfomMatrix(size, CV_PI / 4);
-        cv::gpu::GpuMat xmap, ymap;
-        cv::gpu::buildWarpPerspectiveMaps(M, inverse, size, xmap, ymap);
+    cv::Mat M = createTransfomMatrix(size, CV_PI / 4);
+    cv::gpu::GpuMat xmap, ymap;
+    cv::gpu::buildWarpPerspectiveMaps(M, inverse, size, xmap, ymap);
 
-        cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1);
-        cv::Mat dst;
-        cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), cv::INTER_NEAREST, cv::BORDER_CONSTANT);
+    cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1);
+    cv::Mat dst;
+    cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), cv::INTER_NEAREST, cv::BORDER_CONSTANT);
 
-        int flags = cv::INTER_NEAREST;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
-        cv::Mat dst_gold;
-        cv::warpPerspective(src, dst_gold, M, size, flags, cv::BORDER_CONSTANT);
+    int flags = cv::INTER_NEAREST;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
+    cv::Mat dst_gold;
+    cv::warpPerspective(src, dst_gold, M, size, flags, cv::BORDER_CONSTANT);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, BuildWarpPerspectiveMaps, testing::Combine(
@@ -209,28 +201,20 @@ PARAM_TEST_CASE(WarpPerspective, cv::gpu::DeviceInfo, cv::Size, MatType, Inverse
 
 TEST_P(WarpPerspective, Accuracy)
 {
-    try
-    {
-        cv::Mat src = randomMat(size, type);
-        cv::Mat M = createTransfomMatrix(size, CV_PI / 3);
-        int flags = interpolation;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
-        cv::Scalar val = randomScalar(0.0, 255.0);
+    cv::Mat src = randomMat(size, type);
+    cv::Mat M = createTransfomMatrix(size, CV_PI / 3);
+    int flags = interpolation;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
+    cv::Scalar val = randomScalar(0.0, 255.0);
 
-        cv::gpu::GpuMat dst = createMat(size, type, useRoi);
-        cv::gpu::warpPerspective(loadMat(src, useRoi), dst, M, size, flags, borderType, val);
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::warpPerspective(loadMat(src, useRoi), dst, M, size, flags, borderType, val);
 
-        cv::Mat dst_gold;
-        warpPerspectiveGold(src, M, inverse, size, dst_gold, interpolation, borderType, val);
+    cv::Mat dst_gold;
+    warpPerspectiveGold(src, M, inverse, size, dst_gold, interpolation, borderType, val);
 
-        EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspective, testing::Combine(
@@ -265,27 +249,19 @@ PARAM_TEST_CASE(WarpPerspectiveNPP, cv::gpu::DeviceInfo, MatType, Inverse, Inter
 
 TEST_P(WarpPerspectiveNPP, Accuracy)
 {
-    try
-    {
-        cv::Mat src = readImageType("stereobp/aloe-L.png", type);
-        cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4);
-        int flags = interpolation;
-        if (inverse)
-            flags |= cv::WARP_INVERSE_MAP;
+    cv::Mat src = readImageType("stereobp/aloe-L.png", type);
+    cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4);
+    int flags = interpolation;
+    if (inverse)
+        flags |= cv::WARP_INVERSE_MAP;
 
-        cv::gpu::GpuMat dst;
-        cv::gpu::warpPerspective(loadMat(src), dst, M, src.size(), flags);
+    cv::gpu::GpuMat dst;
+    cv::gpu::warpPerspective(loadMat(src), dst, M, src.size(), flags);
 
-        cv::Mat dst_gold;
-        warpPerspectiveGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0));
+    cv::Mat dst_gold;
+    warpPerspectiveGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0));
 
-        EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2);
-    }
-    catch (...)
-    {
-        cv::gpu::resetDevice();
-        throw;
-    }
+    EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspectiveNPP, testing::Combine(