fixed tests (call resetDevice, if there was a gpu failure)

modules/gpu/perf/perf_imgproc.cpp

@@ -581,13 +581,12 @@ PERF_TEST_P(Sz, ImgProc_CalcHist, GPU_TYPICAL_MAT_SIZES)
     {
         cv::gpu::GpuMat d_src(src);
         cv::gpu::GpuMat d_hist;
-        cv::gpu::GpuMat d_buf;
 
-        cv::gpu::calcHist(d_src, d_hist, d_buf);
+        cv::gpu::calcHist(d_src, d_hist);
 
         TEST_CYCLE()
         {
-            cv::gpu::calcHist(d_src, d_hist, d_buf);
+            cv::gpu::calcHist(d_src, d_hist);
         }
 
         GPU_SANITY_CHECK(d_hist);
@@ -1706,10 +1705,30 @@ PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidGetLayer, Combine(GPU_TYPICAL_MAT_S
     }
 }
 
+namespace {
+    struct Vec3fComparator
+    {
+        bool operator()(const cv::Vec3f& a, const cv::Vec3f b) const
+        {
+            if(a[0] != b[0]) return a[0] < b[0];
+            else if(a[1] != b[1]) return a[1] < b[1];
+            else return a[2] < b[2];
+        }
+    };
+    struct Vec2fComparator
+    {
+        bool operator()(const cv::Vec2f& a, const cv::Vec2f b) const
+        {
+            if(a[0] != b[0]) return a[0] < b[0];
+            else return a[1] < b[1];
+        }
+    };
+}
+
 //////////////////////////////////////////////////////////////////////
 // HoughLines
 
-PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
+PERF_TEST_P(Sz, ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
 {
     declare.time(30.0);
 
@@ -1744,7 +1763,11 @@ PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
             cv::gpu::HoughLines(d_src, d_lines, d_buf, rho, theta, threshold);
         }
 
-        GPU_SANITY_CHECK(d_lines);
+        cv::Mat h_lines(d_lines);
+        cv::Vec2f* begin = (cv::Vec2f*)(h_lines.ptr<char>(0));
+        cv::Vec2f* end = (cv::Vec2f*)(h_lines.ptr<char>(0) + (h_lines.cols) * 2 * sizeof(float));
+        std::sort(begin, end, Vec2fComparator());
+        SANITY_CHECK(h_lines);
     }
     else
     {
@@ -1756,7 +1779,8 @@ PERF_TEST_P(Sz, DISABLED_ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
             cv::HoughLines(src, lines, rho, theta, threshold);
         }
 
-        CPU_SANITY_CHECK(lines);
+        std::sort(lines.begin(), lines.end(), Vec2fComparator());
+        SANITY_CHECK(lines);
     }
 }
 
@@ -1804,7 +1828,11 @@ PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles, Combine(GPU_TYPICAL_MAT_SIZES,
             cv::gpu::HoughCircles(d_src, d_circles, d_buf, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
         }
 
-        GPU_SANITY_CHECK(d_circles);
+        cv::Mat h_circles(d_circles);
+        cv::Vec3f* begin = (cv::Vec3f*)(h_circles.ptr<char>(0));
+        cv::Vec3f* end = (cv::Vec3f*)(h_circles.ptr<char>(0) + (h_circles.cols) * 3 * sizeof(float));
+        std::sort(begin, end, Vec3fComparator());
+        SANITY_CHECK(h_circles);
     }
     else
     {
@@ -1817,7 +1845,8 @@ PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles, Combine(GPU_TYPICAL_MAT_SIZES,
             cv::HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);
         }
 
-        CPU_SANITY_CHECK(circles);
+        std::sort(circles.begin(), circles.end(), Vec3fComparator());
+        SANITY_CHECK(circles);
     }
 }
 

modules/gpu/perf/perf_objdetect.cpp

@@ -89,7 +89,6 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
     SANITY_CHECK(found_locations);
 }
 
-
 ///////////////////////////////////////////////////////////////
 // HaarClassifier
 
@@ -181,4 +180,4 @@ PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
     }
 }
 
-} // namespace
+} // namespace
\ No newline at end of file

modules/gpu/test/interpolation.hpp

@@ -42,6 +42,9 @@
 #ifndef __OPENCV_TEST_INTERPOLATION_HPP__
 #define __OPENCV_TEST_INTERPOLATION_HPP__
 
+#include "opencv2/core/core.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
 template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
 {
     if (border_type == cv::BORDER_CONSTANT)
@@ -113,7 +116,7 @@ template <typename T> struct CubicInterpolator
             for (float cx = xmin; cx <= xmax; cx += 1.0f)
             {
                 const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
-                sum += w * readVal<T>(src, cvFloor(cy), cvFloor(cx), c, border_type, borderVal);
+                sum += w * readVal<T>(src, (int) floorf(cy), (int) floorf(cx), c, border_type, borderVal);
                 wsum += w;
             }
         }

modules/gpu/test/nvidia/TestHaarCascadeApplication.cpp

@@ -13,10 +13,50 @@
 
 #include <float.h>
 
-#if defined(__GNUC__) && !defined(__APPLE__)
+#if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
     #include <fpu_control.h>
 #endif
 
+namespace
+{
+    // http://www.christian-seiler.de/projekte/fpmath/
+    class FpuControl
+    {
+    public:
+        FpuControl();
+        ~FpuControl();
+
+    private:
+    #if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
+        fpu_control_t fpu_oldcw, fpu_cw;
+    #elif defined(_WIN32) && !defined(_WIN64)
+        unsigned int fpu_oldcw, fpu_cw;
+    #endif
+    };
+
+    FpuControl::FpuControl()
+    {
+    #if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
+        _FPU_GETCW(fpu_oldcw);
+        fpu_cw = (fpu_oldcw & ~_FPU_EXTENDED & ~_FPU_DOUBLE & ~_FPU_SINGLE) | _FPU_SINGLE;
+        _FPU_SETCW(fpu_cw);
+    #elif defined(_WIN32) && !defined(_WIN64)
+        _controlfp_s(&fpu_cw, 0, 0);
+        fpu_oldcw = fpu_cw;
+        _controlfp_s(&fpu_cw, _PC_24, _MCW_PC);
+    #endif
+    }
+
+    FpuControl::~FpuControl()
+    {
+    #if defined(__GNUC__) && !defined(__APPLE__) && !defined(__arm__)
+        _FPU_SETCW(fpu_oldcw);
+    #elif defined(_WIN32) && !defined(_WIN64)
+        _controlfp_s(&fpu_cw, fpu_oldcw, _MCW_PC);
+    #endif
+    }
+}
+
 #include "TestHaarCascadeApplication.h"
 #include "NCVHaarObjectDetection.hpp"
 
@@ -47,12 +87,8 @@ bool TestHaarCascadeApplication::init()
     return true;
 }
 
-
 bool TestHaarCascadeApplication::process()
 {
-#if defined(__APPLE)
-    return true;
-#endif
     NCVStatus ncvStat;
     bool rcode = false;
 
@@ -205,44 +241,19 @@ bool TestHaarCascadeApplication::process()
     }
     ncvAssertReturn(cudaSuccess == cudaStreamSynchronize(0), false);
 
-#if !defined(__APPLE__)
-
-#if defined(__GNUC__)
-    //http://www.christian-seiler.de/projekte/fpmath/
-
-    fpu_control_t fpu_oldcw, fpu_cw;
-    _FPU_GETCW(fpu_oldcw); // store old cw
-     fpu_cw = (fpu_oldcw & ~_FPU_EXTENDED & ~_FPU_DOUBLE & ~_FPU_SINGLE) | _FPU_SINGLE;
-    _FPU_SETCW(fpu_cw);
-
-    // calculations here
-    ncvStat = ncvApplyHaarClassifierCascade_host(
-        h_integralImage, h_rectStdDev, h_pixelMask,
-        detectionsOnThisScale_h,
-        haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
-        searchRoiU, 1, 1.0f);
-    ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
-
-    _FPU_SETCW(fpu_oldcw); // restore old cw
-#else
-#ifndef _WIN64
-    Ncv32u fpu_oldcw, fpu_cw;
-    _controlfp_s(&fpu_cw, 0, 0);
-    fpu_oldcw = fpu_cw;
-    _controlfp_s(&fpu_cw, _PC_24, _MCW_PC);
-#endif
-    ncvStat = ncvApplyHaarClassifierCascade_host(
-        h_integralImage, h_rectStdDev, h_pixelMask,
-        detectionsOnThisScale_h,
-        haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
-        searchRoiU, 1, 1.0f);
-    ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
-#ifndef _WIN64
-    _controlfp_s(&fpu_cw, fpu_oldcw, _MCW_PC);
-#endif
-#endif
+    {
+        // calculations here
+        FpuControl fpu;
+        (void) fpu;
+
+        ncvStat = ncvApplyHaarClassifierCascade_host(
+            h_integralImage, h_rectStdDev, h_pixelMask,
+            detectionsOnThisScale_h,
+            haar, h_HaarStages, h_HaarNodes, h_HaarFeatures, false,
+            searchRoiU, 1, 1.0f);
+        ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
+    }
 
-#endif
     NCV_SKIP_COND_END
 
     int devId;
@@ -302,4 +313,4 @@ bool TestHaarCascadeApplication::deinit()
     return true;
 }
 
-#endif /* CUDA_DISABLER */
+#endif /* CUDA_DISABLER */
\ No newline at end of file

modules/gpu/test/nvidia/main_nvidia.cpp

@@ -25,7 +25,7 @@
 #include "NCVAutoTestLister.hpp"
 #include "NCVTestSourceProvider.hpp"
 
-#include <main_test_nvidia.h>
+#include "main_test_nvidia.h"
 
 static std::string path;
 
@@ -97,7 +97,7 @@ void generateRectStdDevTests(NCVAutoTestLister &testLister, NCVTestSourceProvide
 template <class T>
 void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T> &src)
 {
-    for (Ncv32u i=1; i<480; i+=3)
+    for (Ncv32u i=2; i<10; ++i)
     {
         char testName[80];
         sprintf(testName, "TestResize_VGA_s%d", i);
@@ -105,7 +105,7 @@ void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T>
         testLister.add(new TestResize<T>(testName, src, 640, 480, i, false));
     }
 
-    for (Ncv32u i=1; i<1080; i+=5)
+    for (Ncv32u i=2; i<10; ++i)
     {
         char testName[80];
         sprintf(testName, "TestResize_1080_s%d", i);
@@ -117,7 +117,7 @@ void generateResizeTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<T>
 void generateNPPSTVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<Ncv32u> &src, Ncv32u maxLength)
 {
     //compaction
-    for (Ncv32f _i=256.0; _i<maxLength; _i*=1.1f)
+    for (Ncv32f _i=256.0; _i<maxLength; _i*=1.5f)
     {
         Ncv32u i = (Ncv32u)_i;
         char testName[80];
@@ -132,13 +132,13 @@ void generateNPPSTVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvid
         testLister.add(new TestCompact(testName, src, i, 0xC001C0DE, 0));
         testLister.add(new TestCompact(testName, src, i, 0xC001C0DE, 100));
     }
-    for (Ncv32u i=256*256-256; i<256*256+257; i++)
+    for (Ncv32u i=256*256-10; i<256*256+10; i++)
     {
         char testName[80];
         sprintf(testName, "Compaction%d", i);
         testLister.add(new TestCompact(testName, src, i, 0xFFFFFFFF, 40));
     }
-    for (Ncv32u i=256*256*256-10; i<256*256*256+10; i++)
+    for (Ncv32u i=256*256*256-2; i<256*256*256+2; i++)
     {
         char testName[80];
         sprintf(testName, "Compaction%d", i);
@@ -212,7 +212,7 @@ void generateDrawRectsTests(NCVAutoTestLister &testLister,
 void generateVectorTests(NCVAutoTestLister &testLister, NCVTestSourceProvider<Ncv32u> &src, Ncv32u maxLength)
 {
     //growth
-    for (Ncv32f _i=10.0; _i<maxLength; _i*=1.1f)
+    for (Ncv32f _i=10.0; _i<maxLength; _i*=1.5f)
     {
         Ncv32u i = (Ncv32u)_i;
         char testName[80];
@@ -253,16 +253,16 @@ void generateHaarApplicationTests(NCVAutoTestLister &testLister, NCVTestSourcePr
                                   Ncv32u maxWidth, Ncv32u maxHeight)
 {
     (void)maxHeight;
-    for (Ncv32u i=20; i<512; i+=11)
+    for (Ncv32u i=100; i<512; i+=41)
     {
-        for (Ncv32u j=20; j<128; j+=5)
+        for (Ncv32u j=100; j<128; j+=25)
         {
             char testName[80];
             sprintf(testName, "HaarAppl%d_%d", i, j);
             testLister.add(new TestHaarCascadeApplication(testName, src, path + "haarcascade_frontalface_alt.xml", j, i));
         }
     }
-    for (Ncv32f _i=20.0; _i<maxWidth; _i*=1.1f)
+    for (Ncv32f _i=20.0; _i<maxWidth; _i*=1.5f)
     {
         Ncv32u i = (Ncv32u)_i;
         char testName[80];
@@ -276,6 +276,8 @@ 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();
@@ -283,17 +285,15 @@ bool nvidia_NPPST_Integral_Image(const std::string& test_data_path, OutputLevel
 
     NCVAutoTestLister testListerII("NPPST Integral Image", outputLevel);
 
-    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
-    NCVTestSourceProvider<Ncv32f> testSrcRandom_32f(2010, -1.0f, 1.0f, 4096, 4096);
+    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
+    NCVTestSourceProvider<Ncv32f> testSrcRandom_32f(2010, -1.0f, 1.0f, 2048, 2048);
 
-    generateIntegralTests<Ncv8u, Ncv32u>(testListerII, testSrcRandom_8u, 4096, 4096);
-    generateIntegralTests<Ncv32f, Ncv32f>(testListerII, testSrcRandom_32f, 4096, 4096);
+    generateIntegralTests<Ncv8u, Ncv32u>(testListerII, testSrcRandom_8u, 2048, 2048);
+    generateIntegralTests<Ncv32f, Ncv32f>(testListerII, testSrcRandom_32f, 2048, 2048);
 
     return testListerII.invoke();
 }
 
-}
-
 bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, OutputLevel outputLevel)
 {
     path = test_data_path;
@@ -301,9 +301,9 @@ bool nvidia_NPPST_Squared_Integral_Image(const std::string& test_data_path, Outp
 
     NCVAutoTestLister testListerSII("NPPST Squared Integral Image", outputLevel);
 
-    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
+    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
 
-    generateSquaredIntegralTests(testListerSII, testSrcRandom_8u, 4096, 4096);
+    generateSquaredIntegralTests(testListerSII, testSrcRandom_8u, 2048, 2048);
 
     return testListerSII.invoke();
 }
@@ -315,9 +315,9 @@ bool nvidia_NPPST_RectStdDev(const std::string& test_data_path, OutputLevel outp
 
     NCVAutoTestLister testListerRStdDev("NPPST RectStdDev", outputLevel);
 
-    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
+    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
 
-    generateRectStdDevTests(testListerRStdDev, testSrcRandom_8u, 4096, 4096);
+    generateRectStdDevTests(testListerRStdDev, testSrcRandom_8u, 2048, 2048);
 
     return testListerRStdDev.invoke();
 }
@@ -329,8 +329,8 @@ bool nvidia_NPPST_Resize(const std::string& test_data_path, OutputLevel outputLe
 
     NCVAutoTestLister testListerResize("NPPST Resize", outputLevel);
 
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
-    NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 4096, 4096);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
+    NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 2048, 2048);
 
     generateResizeTests(testListerResize, testSrcRandom_32u);
     generateResizeTests(testListerResize, testSrcRandom_64u);
@@ -345,9 +345,9 @@ bool nvidia_NPPST_Vector_Operations(const std::string& test_data_path, OutputLev
 
     NCVAutoTestLister testListerNPPSTVectorOperations("NPPST Vector Operations", outputLevel);
 
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
 
-    generateNPPSTVectorTests(testListerNPPSTVectorOperations, testSrcRandom_32u, 4096*4096);
+    generateNPPSTVectorTests(testListerNPPSTVectorOperations, testSrcRandom_32u, 2048*2048);
 
     return testListerNPPSTVectorOperations.invoke();
 }
@@ -359,8 +359,8 @@ bool nvidia_NPPST_Transpose(const std::string& test_data_path, OutputLevel outpu
 
     NCVAutoTestLister testListerTranspose("NPPST Transpose", outputLevel);
 
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
-    NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 4096, 4096);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
+    NCVTestSourceProvider<Ncv64u> testSrcRandom_64u(2010, 0, -1, 2048, 2048);
 
     generateTransposeTests(testListerTranspose, testSrcRandom_32u);
     generateTransposeTests(testListerTranspose, testSrcRandom_64u);
@@ -375,9 +375,9 @@ bool nvidia_NCV_Vector_Operations(const std::string& test_data_path, OutputLevel
 
     NCVAutoTestLister testListerVectorOperations("Vector Operations", outputLevel);
 
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
 
-    generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 4096*4096);
+    generateVectorTests(testListerVectorOperations, testSrcRandom_32u, 2048*2048);
 
     return testListerVectorOperations.invoke();
 
@@ -404,7 +404,7 @@ bool nvidia_NCV_Haar_Cascade_Application(const std::string& test_data_path, Outp
 
     NCVTestSourceProvider<Ncv8u> testSrcFacesVGA_8u(path + "group_1_640x480_VGA.pgm");
 
-    generateHaarApplicationTests(testListerHaarAppl, testSrcFacesVGA_8u, 1280, 720);
+    generateHaarApplicationTests(testListerHaarAppl, testSrcFacesVGA_8u, 640, 480);
 
     return testListerHaarAppl.invoke();
 }
@@ -416,9 +416,9 @@ bool nvidia_NCV_Hypotheses_Filtration(const std::string& test_data_path, OutputL
 
     NCVAutoTestLister testListerHypFiltration("Hypotheses Filtration", outputLevel);
 
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 4096, 4096);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, 0xFFFFFFFF, 2048, 2048);
 
-    generateHypothesesFiltrationTests(testListerHypFiltration, testSrcRandom_32u, 1024);
+    generateHypothesesFiltrationTests(testListerHypFiltration, testSrcRandom_32u, 512);
 
     return testListerHypFiltration.invoke();
 }
@@ -430,13 +430,13 @@ bool nvidia_NCV_Visualization(const std::string& test_data_path, OutputLevel out
 
     NCVAutoTestLister testListerVisualize("Visualization", outputLevel);
 
-    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 4096, 4096);
-    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, RAND_MAX, 4096, 4096);
+    NCVTestSourceProvider<Ncv8u> testSrcRandom_8u(2010, 0, 255, 2048, 2048);
+    NCVTestSourceProvider<Ncv32u> testSrcRandom_32u(2010, 0, RAND_MAX, 2048, 2048);
 
-    generateDrawRectsTests(testListerVisualize, testSrcRandom_8u, testSrcRandom_32u, 4096, 4096);
-    generateDrawRectsTests(testListerVisualize, testSrcRandom_32u, testSrcRandom_32u, 4096, 4096);
+    generateDrawRectsTests(testListerVisualize, testSrcRandom_8u, testSrcRandom_32u, 2048, 2048);
+    generateDrawRectsTests(testListerVisualize, testSrcRandom_32u, testSrcRandom_32u, 2048, 2048);
 
     return testListerVisualize.invoke();
 }
 
-#endif /* CUDA_DISABLER */
+#endif /* CUDA_DISABLER */
\ No newline at end of file

modules/gpu/test/test_calib3d.cpp

@@ -43,8 +43,6 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
 //////////////////////////////////////////////////////////////////////////
 // StereoBM
 
@@ -60,7 +58,7 @@ struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(StereoBM, Regression)
+GPU_TEST_P(StereoBM, Regression)
 {
     cv::Mat left_image  = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
     cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
@@ -95,7 +93,7 @@ struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(StereoBeliefPropagation, Regression)
+GPU_TEST_P(StereoBeliefPropagation, Regression)
 {
     cv::Mat left_image  = readImage("stereobp/aloe-L.png");
     cv::Mat right_image = readImage("stereobp/aloe-R.png");
@@ -133,7 +131,7 @@ struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(StereoConstantSpaceBP, Regression)
+GPU_TEST_P(StereoConstantSpaceBP, Regression)
 {
     cv::Mat left_image  = readImage("csstereobp/aloe-L.png");
     cv::Mat right_image = readImage("csstereobp/aloe-R.png");
@@ -177,7 +175,7 @@ struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(TransformPoints, Accuracy)
+GPU_TEST_P(TransformPoints, Accuracy)
 {
     cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
     cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
@@ -225,7 +223,7 @@ struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(ProjectPoints, Accuracy)
+GPU_TEST_P(ProjectPoints, Accuracy)
 {
     cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10);
     cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1);
@@ -275,7 +273,7 @@ struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(SolvePnPRansac, Accuracy)
+GPU_TEST_P(SolvePnPRansac, Accuracy)
 {
     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);
@@ -324,7 +322,7 @@ PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, Use
     }
 };
 
-TEST_P(ReprojectImageTo3D, Accuracy)
+GPU_TEST_P(ReprojectImageTo3D, Accuracy)
 {
     cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
     cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
@@ -344,6 +342,4 @@ INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ReprojectImageTo3D, testing::Combine(
     testing::Values(MatDepth(CV_8U), MatDepth(CV_16S)),
     WHOLE_SUBMAT));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_copy_make_border.cpp

@@ -43,9 +43,10 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
-IMPLEMENT_PARAM_CLASS(Border, int)
+namespace
+{
+    IMPLEMENT_PARAM_CLASS(Border, int)
+}
 
 PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border, BorderType, UseRoi)
 {
@@ -69,7 +70,7 @@ PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border,
     }
 };
 
-TEST_P(CopyMakeBorder, Accuracy)
+GPU_TEST_P(CopyMakeBorder, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Scalar val = randomScalar(0, 255);
@@ -99,6 +100,4 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CopyMakeBorder, testing::Combine(
     ALL_BORDER_TYPES,
     WHOLE_SUBMAT));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_denoising.cpp

@@ -69,7 +69,7 @@ PARAM_TEST_CASE(BilateralFilter, cv::gpu::DeviceInfo, cv::Size, MatType)
     }
 };
 
-TEST_P(BilateralFilter, Accuracy)
+GPU_TEST_P(BilateralFilter, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -105,7 +105,7 @@ struct BruteForceNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(BruteForceNonLocalMeans, Regression)
+GPU_TEST_P(BruteForceNonLocalMeans, Regression)
 {
     using cv::gpu::GpuMat;
 
@@ -134,8 +134,6 @@ TEST_P(BruteForceNonLocalMeans, Regression)
 
 INSTANTIATE_TEST_CASE_P(GPU_Denoising, BruteForceNonLocalMeans, ALL_DEVICES);
 
-
-
 ////////////////////////////////////////////////////////
 // Fast Force Non local means
 
@@ -150,7 +148,7 @@ struct FastNonLocalMeans: testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(FastNonLocalMeans, Regression)
+GPU_TEST_P(FastNonLocalMeans, Regression)
 {
     using cv::gpu::GpuMat;
 
@@ -167,8 +165,8 @@ TEST_P(FastNonLocalMeans, Regression)
     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));
+    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);
@@ -181,5 +179,4 @@ TEST_P(FastNonLocalMeans, Regression)
 
 INSTANTIATE_TEST_CASE_P(GPU_Denoising, FastNonLocalMeans, ALL_DEVICES);
 
-
 #endif // HAVE_CUDA

modules/gpu/test/test_filters.cpp

@@ -43,27 +43,30 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
-IMPLEMENT_PARAM_CLASS(KSize, cv::Size)
-
-cv::Mat getInnerROI(cv::InputArray m_, cv::Size ksize)
+namespace
 {
-    cv::Mat m = getMat(m_);
-    cv::Rect roi(ksize.width, ksize.height, m.cols - 2 * ksize.width, m.rows - 2 * ksize.height);
-    return m(roi);
-}
+    IMPLEMENT_PARAM_CLASS(KSize, cv::Size)
+    IMPLEMENT_PARAM_CLASS(Anchor, cv::Point)
+    IMPLEMENT_PARAM_CLASS(Deriv_X, int)
+    IMPLEMENT_PARAM_CLASS(Deriv_Y, int)
+    IMPLEMENT_PARAM_CLASS(Iterations, int)
 
-cv::Mat getInnerROI(cv::InputArray m, int ksize)
-{
-    return getInnerROI(m, cv::Size(ksize, ksize));
+    cv::Mat getInnerROI(cv::InputArray m_, cv::Size ksize)
+    {
+        cv::Mat m = getMat(m_);
+        cv::Rect roi(ksize.width, ksize.height, m.cols - 2 * ksize.width, m.rows - 2 * ksize.height);
+        return m(roi);
+    }
+
+    cv::Mat getInnerROI(cv::InputArray m, int ksize)
+    {
+        return getInnerROI(m, cv::Size(ksize, ksize));
+    }
 }
 
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // Blur
 
-IMPLEMENT_PARAM_CLASS(Anchor, cv::Point)
-
 PARAM_TEST_CASE(Blur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
@@ -86,7 +89,7 @@ PARAM_TEST_CASE(Blur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor, Use
     }
 };
 
-TEST_P(Blur, Accuracy)
+GPU_TEST_P(Blur, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -110,36 +113,39 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Blur, testing::Combine(
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // Sobel
 
-IMPLEMENT_PARAM_CLASS(Deriv_X, int)
-IMPLEMENT_PARAM_CLASS(Deriv_Y, int)
-
-PARAM_TEST_CASE(Sobel, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Deriv_X, Deriv_Y, BorderType, UseRoi)
+PARAM_TEST_CASE(Sobel, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, KSize, Deriv_X, Deriv_Y, BorderType, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
     cv::Size size;
-    int type;
+    int depth;
+    int cn;
     cv::Size ksize;
     int dx;
     int dy;
     int borderType;
     bool useRoi;
 
+    int type;
+
     virtual void SetUp()
     {
         devInfo = GET_PARAM(0);
         size = GET_PARAM(1);
-        type = GET_PARAM(2);
-        ksize = GET_PARAM(3);
-        dx = GET_PARAM(4);
-        dy = GET_PARAM(5);
-        borderType = GET_PARAM(6);
-        useRoi = GET_PARAM(7);
+        depth = GET_PARAM(2);
+        cn = GET_PARAM(3);
+        ksize = GET_PARAM(4);
+        dx = GET_PARAM(5);
+        dy = GET_PARAM(6);
+        borderType = GET_PARAM(7);
+        useRoi = GET_PARAM(8);
 
         cv::gpu::setDevice(devInfo.deviceID());
+
+        type = CV_MAKE_TYPE(depth, cn);
     }
 };
 
-TEST_P(Sobel, Accuracy)
+GPU_TEST_P(Sobel, Accuracy)
 {
     if (dx == 0 && dy == 0)
         return;
@@ -152,13 +158,14 @@ TEST_P(Sobel, Accuracy)
     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);
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, ksize), getInnerROI(dst, ksize), CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
     ALL_DEVICES,
     DIFFERENT_SIZES,
-    testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
+    testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
+    IMAGE_CHANNELS,
     testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7))),
     testing::Values(Deriv_X(0), Deriv_X(1), Deriv_X(2)),
     testing::Values(Deriv_Y(0), Deriv_Y(1), Deriv_Y(2)),
@@ -171,31 +178,37 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // Scharr
 
-PARAM_TEST_CASE(Scharr, cv::gpu::DeviceInfo, cv::Size, MatType, Deriv_X, Deriv_Y, BorderType, UseRoi)
+PARAM_TEST_CASE(Scharr, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, Deriv_X, Deriv_Y, BorderType, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
     cv::Size size;
-    int type;
+    int depth;
+    int cn;
     int dx;
     int dy;
     int borderType;
     bool useRoi;
 
+    int type;
+
     virtual void SetUp()
     {
         devInfo = GET_PARAM(0);
         size = GET_PARAM(1);
-        type = GET_PARAM(2);
-        dx = GET_PARAM(3);
-        dy = GET_PARAM(4);
-        borderType = GET_PARAM(5);
-        useRoi = GET_PARAM(6);
+        depth = GET_PARAM(2);
+        cn = GET_PARAM(3);
+        dx = GET_PARAM(4);
+        dy = GET_PARAM(5);
+        borderType = GET_PARAM(6);
+        useRoi = GET_PARAM(7);
 
         cv::gpu::setDevice(devInfo.deviceID());
+
+        type = CV_MAKE_TYPE(depth, cn);
     }
 };
 
-TEST_P(Scharr, Accuracy)
+GPU_TEST_P(Scharr, Accuracy)
 {
     if (dx + dy != 1)
         return;
@@ -208,13 +221,14 @@ TEST_P(Scharr, Accuracy)
     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);
+    EXPECT_MAT_NEAR(getInnerROI(dst_gold, cv::Size(3, 3)), getInnerROI(dst, cv::Size(3, 3)), CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.1);
 }
 
 INSTANTIATE_TEST_CASE_P(GPU_Filter, Scharr, testing::Combine(
     ALL_DEVICES,
     DIFFERENT_SIZES,
-    testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
+    testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
+    IMAGE_CHANNELS,
     testing::Values(Deriv_X(0), Deriv_X(1)),
     testing::Values(Deriv_Y(0), Deriv_Y(1)),
     testing::Values(BorderType(cv::BORDER_REFLECT101),
@@ -226,29 +240,35 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Scharr, testing::Combine(
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // GaussianBlur
 
-PARAM_TEST_CASE(GaussianBlur, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, BorderType, UseRoi)
+PARAM_TEST_CASE(GaussianBlur, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, KSize, BorderType, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
     cv::Size size;
-    int type;
+    int depth;
+    int cn;
     cv::Size ksize;
     int borderType;
     bool useRoi;
 
+    int type;
+
     virtual void SetUp()
     {
         devInfo = GET_PARAM(0);
         size = GET_PARAM(1);
-        type = GET_PARAM(2);
-        ksize = GET_PARAM(3);
-        borderType = GET_PARAM(4);
-        useRoi = GET_PARAM(5);
+        depth = GET_PARAM(2);
+        cn = GET_PARAM(3);
+        ksize = GET_PARAM(4);
+        borderType = GET_PARAM(5);
+        useRoi = GET_PARAM(6);
 
         cv::gpu::setDevice(devInfo.deviceID());
+
+        type = CV_MAKE_TYPE(depth, cn);
     }
 };
 
-TEST_P(GaussianBlur, Accuracy)
+GPU_TEST_P(GaussianBlur, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     double sigma1 = randomDouble(0.1, 1.0);
@@ -281,7 +301,8 @@ TEST_P(GaussianBlur, Accuracy)
 INSTANTIATE_TEST_CASE_P(GPU_Filter, GaussianBlur, testing::Combine(
     ALL_DEVICES,
     DIFFERENT_SIZES,
-    testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
+    testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32F)),
+    IMAGE_CHANNELS,
     testing::Values(KSize(cv::Size(3, 3)),
                     KSize(cv::Size(5, 5)),
                     KSize(cv::Size(7, 7)),
@@ -326,7 +347,7 @@ PARAM_TEST_CASE(Laplacian, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, UseRoi
     }
 };
 
-TEST_P(Laplacian, Accuracy)
+GPU_TEST_P(Laplacian, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -349,8 +370,6 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Laplacian, testing::Combine(
 /////////////////////////////////////////////////////////////////////////////////////////////////
 // Erode
 
-IMPLEMENT_PARAM_CLASS(Iterations, int)
-
 PARAM_TEST_CASE(Erode, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iterations, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
@@ -373,7 +392,7 @@ PARAM_TEST_CASE(Erode, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteration
     }
 };
 
-TEST_P(Erode, Accuracy)
+GPU_TEST_P(Erode, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
@@ -422,7 +441,7 @@ PARAM_TEST_CASE(Dilate, cv::gpu::DeviceInfo, cv::Size, MatType, Anchor, Iteratio
     }
 };
 
-TEST_P(Dilate, Accuracy)
+GPU_TEST_P(Dilate, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
@@ -476,7 +495,7 @@ PARAM_TEST_CASE(MorphEx, cv::gpu::DeviceInfo, cv::Size, MatType, MorphOp, Anchor
     }
 };
 
-TEST_P(MorphEx, Accuracy)
+GPU_TEST_P(MorphEx, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Mat kernel = cv::Mat::ones(3, 3, CV_8U);
@@ -530,7 +549,7 @@ PARAM_TEST_CASE(Filter2D, cv::gpu::DeviceInfo, cv::Size, MatType, KSize, Anchor,
     }
 };
 
-TEST_P(Filter2D, Accuracy)
+GPU_TEST_P(Filter2D, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
@@ -553,6 +572,4 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Filter2D, testing::Combine(
     testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT)),
     WHOLE_SUBMAT));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_global_motion.cpp

@@ -51,7 +51,7 @@ struct CompactPoints : testing::TestWithParam<gpu::DeviceInfo>
     virtual void SetUp() { gpu::setDevice(GetParam().deviceID()); }
 };
 
-TEST_P(CompactPoints, CanCompactizeSmallInput)
+GPU_TEST_P(CompactPoints, CanCompactizeSmallInput)
 {
     Mat src0(1, 3, CV_32FC2);
     src0.at<Point2f>(0,0) = Point2f(0,0);

modules/gpu/test/test_gpumat.cpp

@@ -44,8 +44,6 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
 ////////////////////////////////////////////////////////////////////////////////
 // SetTo
 
@@ -67,7 +65,7 @@ PARAM_TEST_CASE(SetTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
     }
 };
 
-TEST_P(SetTo, Zero)
+GPU_TEST_P(SetTo, Zero)
 {
     cv::Scalar zero = cv::Scalar::all(0);
 
@@ -77,7 +75,7 @@ TEST_P(SetTo, Zero)
     EXPECT_MAT_NEAR(cv::Mat::zeros(size, type), mat, 0.0);
 }
 
-TEST_P(SetTo, SameVal)
+GPU_TEST_P(SetTo, SameVal)
 {
     cv::Scalar val = cv::Scalar::all(randomDouble(0.0, 255.0));
 
@@ -102,7 +100,7 @@ TEST_P(SetTo, SameVal)
     }
 }
 
-TEST_P(SetTo, DifferentVal)
+GPU_TEST_P(SetTo, DifferentVal)
 {
     cv::Scalar val = randomScalar(0.0, 255.0);
 
@@ -127,7 +125,7 @@ TEST_P(SetTo, DifferentVal)
     }
 }
 
-TEST_P(SetTo, Masked)
+GPU_TEST_P(SetTo, Masked)
 {
     cv::Scalar val = randomScalar(0.0, 255.0);
     cv::Mat mat_gold = randomMat(size, type);
@@ -184,7 +182,7 @@ PARAM_TEST_CASE(CopyTo, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
     }
 };
 
-TEST_P(CopyTo, WithOutMask)
+GPU_TEST_P(CopyTo, WithOutMask)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -195,7 +193,7 @@ TEST_P(CopyTo, WithOutMask)
     EXPECT_MAT_NEAR(src, dst, 0.0);
 }
 
-TEST_P(CopyTo, Masked)
+GPU_TEST_P(CopyTo, Masked)
 {
     cv::Mat src = randomMat(size, type);
     cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
@@ -255,7 +253,7 @@ PARAM_TEST_CASE(ConvertTo, cv::gpu::DeviceInfo, cv::Size, MatDepth, MatDepth, Us
     }
 };
 
-TEST_P(ConvertTo, WithOutScaling)
+GPU_TEST_P(ConvertTo, WithOutScaling)
 {
     cv::Mat src = randomMat(size, depth1);
 
@@ -285,7 +283,7 @@ TEST_P(ConvertTo, WithOutScaling)
     }
 }
 
-TEST_P(ConvertTo, WithScaling)
+GPU_TEST_P(ConvertTo, WithScaling)
 {
     cv::Mat src = randomMat(size, depth1);
     double a = randomDouble(0.0, 1.0);
@@ -324,6 +322,4 @@ INSTANTIATE_TEST_CASE_P(GPU_GpuMat, ConvertTo, testing::Combine(
     ALL_DEPTH,
     WHOLE_SUBMAT));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_hough.cpp

@@ -43,8 +43,6 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
 ///////////////////////////////////////////////////////////////////////////////////////////////////////
 // HoughLines
 
@@ -79,7 +77,7 @@ PARAM_TEST_CASE(HoughLines, cv::gpu::DeviceInfo, cv::Size, UseRoi)
     }
 };
 
-TEST_P(HoughLines, Accuracy)
+GPU_TEST_P(HoughLines, Accuracy)
 {
     const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
     cv::gpu::setDevice(devInfo.deviceID());
@@ -87,7 +85,7 @@ TEST_P(HoughLines, Accuracy)
     const bool useRoi = GET_PARAM(2);
 
     const float rho = 1.0f;
-    const float theta = 1.5f * CV_PI / 180.0f;
+    const float theta = (float) (1.5 * CV_PI / 180.0);
     const int threshold = 100;
 
     cv::Mat src(size, CV_8UC1);
@@ -124,7 +122,7 @@ PARAM_TEST_CASE(HoughCircles, cv::gpu::DeviceInfo, cv::Size, UseRoi)
     }
 };
 
-TEST_P(HoughCircles, Accuracy)
+GPU_TEST_P(HoughCircles, Accuracy)
 {
     const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
     cv::gpu::setDevice(devInfo.deviceID());
@@ -188,7 +186,7 @@ PARAM_TEST_CASE(GeneralizedHough, cv::gpu::DeviceInfo, UseRoi)
 {
 };
 
-TEST_P(GeneralizedHough, POSITION)
+GPU_TEST_P(GeneralizedHough, POSITION)
 {
     const cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
     cv::gpu::setDevice(devInfo.deviceID());
@@ -251,6 +249,4 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, GeneralizedHough, testing::Combine(
     ALL_DEVICES,
     WHOLE_SUBMAT));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_labeling.cpp

@@ -43,8 +43,8 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
+namespace
+{
     struct GreedyLabeling
     {
         struct dot
@@ -82,7 +82,7 @@ namespace {
             int cc = -1;
 
             int* dist_labels = (int*)labels.data;
-            int pitch = labels.step1();
+            int pitch = (int) labels.step1();
 
             unsigned char* source = (unsigned char*)image.data;
             int width = image.cols;
@@ -166,7 +166,7 @@ struct Labeling : testing::TestWithParam<cv::gpu::DeviceInfo>
     }
 };
 
-TEST_P(Labeling, ConnectedComponents)
+GPU_TEST_P(Labeling, DISABLED_ConnectedComponents)
 {
     cv::Mat image;
     cvtColor(loat_image(), image, CV_BGR2GRAY);
@@ -186,11 +186,11 @@ TEST_P(Labeling, ConnectedComponents)
 
     cv::gpu::connectivityMask(cv::gpu::GpuMat(image), mask, cv::Scalar::all(0), cv::Scalar::all(2));
 
-    ASSERT_NO_THROW(cv::gpu::labelComponents(mask, components));
+    cv::gpu::labelComponents(mask, components);
 
     host.checkCorrectness(cv::Mat(components));
 }
 
-INSTANTIATE_TEST_CASE_P(ConnectedComponents, Labeling, ALL_DEVICES);
+INSTANTIATE_TEST_CASE_P(GPU_ConnectedComponents, Labeling, ALL_DEVICES);
 
 #endif // HAVE_CUDA

modules/gpu/test/test_nvidia.cpp

@@ -41,11 +41,9 @@
 
 #include "test_precomp.hpp"
 
-#if defined HAVE_CUDA
-  OutputLevel nvidiaTestOutputLevel = OutputLevelNone;
-#endif
+#ifdef HAVE_CUDA
 
-#if defined HAVE_CUDA && !defined(CUDA_DISABLER)
+OutputLevel nvidiaTestOutputLevel = OutputLevelNone;
 
 using namespace cvtest;
 using namespace testing;
@@ -69,77 +67,77 @@ struct NVidiaTest : TestWithParam<cv::gpu::DeviceInfo>
 struct NPPST : NVidiaTest {};
 struct NCV : NVidiaTest {};
 
-//TEST_P(NPPST, Integral)
-//{
-//    bool res = nvidia_NPPST_Integral_Image(path, nvidiaTestOutputLevel);
+GPU_TEST_P(NPPST, Integral)
+{
+    bool res = nvidia_NPPST_Integral_Image(_path, nvidiaTestOutputLevel);
 
-//    ASSERT_TRUE(res);
-//}
+    ASSERT_TRUE(res);
+}
 
-TEST_P(NPPST, SquaredIntegral)
+GPU_TEST_P(NPPST, SquaredIntegral)
 {
     bool res = nvidia_NPPST_Squared_Integral_Image(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NPPST, RectStdDev)
+GPU_TEST_P(NPPST, RectStdDev)
 {
     bool res = nvidia_NPPST_RectStdDev(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NPPST, Resize)
+GPU_TEST_P(NPPST, Resize)
 {
     bool res = nvidia_NPPST_Resize(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NPPST, VectorOperations)
+GPU_TEST_P(NPPST, VectorOperations)
 {
     bool res = nvidia_NPPST_Vector_Operations(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NPPST, Transpose)
+GPU_TEST_P(NPPST, Transpose)
 {
     bool res = nvidia_NPPST_Transpose(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NCV, VectorOperations)
+GPU_TEST_P(NCV, VectorOperations)
 {
     bool res = nvidia_NCV_Vector_Operations(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NCV, HaarCascadeLoader)
+GPU_TEST_P(NCV, HaarCascadeLoader)
 {
     bool res = nvidia_NCV_Haar_Cascade_Loader(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NCV, HaarCascadeApplication)
+GPU_TEST_P(NCV, HaarCascadeApplication)
 {
     bool res = nvidia_NCV_Haar_Cascade_Application(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NCV, HypothesesFiltration)
+GPU_TEST_P(NCV, HypothesesFiltration)
 {
     bool res = nvidia_NCV_Hypotheses_Filtration(_path, nvidiaTestOutputLevel);
 
     ASSERT_TRUE(res);
 }
 
-TEST_P(NCV, Visualization)
+GPU_TEST_P(NCV, Visualization)
 {
     // this functionality doesn't used in gpu module
     bool res = nvidia_NCV_Visualization(_path, nvidiaTestOutputLevel);

modules/gpu/test/test_objdetect.cpp

@@ -43,8 +43,6 @@
 
 #ifdef HAVE_CUDA
 
-namespace {
-
 //#define DUMP
 
 struct HOG : testing::TestWithParam<cv::gpu::DeviceInfo>, cv::gpu::HOGDescriptor
@@ -176,7 +174,7 @@ struct HOG : testing::TestWithParam<cv::gpu::DeviceInfo>, cv::gpu::HOGDescriptor
 };
 
 // desabled while resize does not fixed
-TEST_P(HOG, DISABLED_Detect)
+GPU_TEST_P(HOG, Detect)
 {
     cv::Mat img_rgb = readImage("hog/road.png");
     ASSERT_FALSE(img_rgb.empty());
@@ -201,7 +199,7 @@ TEST_P(HOG, DISABLED_Detect)
     f.close();
 }
 
-TEST_P(HOG, GetDescriptors)
+GPU_TEST_P(HOG, GetDescriptors)
 {
     // Load image (e.g. train data, composed from windows)
     cv::Mat img_rgb = readImage("hog/train_data.png");
@@ -288,6 +286,7 @@ TEST_P(HOG, GetDescriptors)
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, HOG, ALL_DEVICES);
 
 //============== caltech hog tests =====================//
+
 struct CalTech : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::DeviceInfo, std::string> >
 {
     cv::gpu::DeviceInfo devInfo;
@@ -303,7 +302,7 @@ struct CalTech : public ::testing::TestWithParam<std::tr1::tuple<cv::gpu::Device
     }
 };
 
-TEST_P(CalTech, HOG)
+GPU_TEST_P(CalTech, HOG)
 {
     cv::gpu::GpuMat d_img(img);
     cv::Mat markedImage(img.clone());
@@ -350,7 +349,7 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
     }
 };
 
-TEST_P(LBP_Read_classifier, Accuracy)
+GPU_TEST_P(LBP_Read_classifier, Accuracy)
 {
     cv::gpu::CascadeClassifier_GPU classifier;
     std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
@@ -372,7 +371,7 @@ PARAM_TEST_CASE(LBP_classify, cv::gpu::DeviceInfo, int)
     }
 };
 
-TEST_P(LBP_classify, Accuracy)
+GPU_TEST_P(LBP_classify, Accuracy)
 {
     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";
@@ -422,6 +421,4 @@ TEST_P(LBP_classify, Accuracy)
 INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,
                         testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
 
-} // namespace
-
 #endif // HAVE_CUDA

modules/gpu/test/test_precomp.hpp

@@ -51,6 +51,7 @@
 #define __OPENCV_TEST_PRECOMP_HPP__
 
 #include <cmath>
+#include <ctime>
 #include <cstdio>
 #include <iostream>
 #include <fstream>

modules/gpu/test/test_pyramids.cpp

@@ -64,7 +64,7 @@ PARAM_TEST_CASE(PyrDown, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
     }
 };
 
-TEST_P(PyrDown, Accuracy)
+GPU_TEST_P(PyrDown, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -104,7 +104,7 @@ PARAM_TEST_CASE(PyrUp, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
     }
 };
 
-TEST_P(PyrUp, Accuracy)
+GPU_TEST_P(PyrUp, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 

modules/gpu/test/test_remap.cpp

@@ -152,7 +152,7 @@ PARAM_TEST_CASE(Remap, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, Bo
     }
 };
 
-TEST_P(Remap, Accuracy)
+GPU_TEST_P(Remap, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     cv::Scalar val = randomScalar(0.0, 255.0);

modules/gpu/test/test_resize.cpp

@@ -136,7 +136,7 @@ PARAM_TEST_CASE(Resize, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpol
     }
 };
 
-TEST_P(Resize, Accuracy)
+GPU_TEST_P(Resize, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -157,8 +157,8 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
     testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
     WHOLE_SUBMAT));
 
-
 /////////////////
+
 PARAM_TEST_CASE(ResizeSameAsHost, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi)
 {
     cv::gpu::DeviceInfo devInfo;
@@ -182,7 +182,7 @@ PARAM_TEST_CASE(ResizeSameAsHost, cv::gpu::DeviceInfo, cv::Size, MatType, double
 };
 
 // downscaling only: used for classifiers
-TEST_P(ResizeSameAsHost, Accuracy)
+GPU_TEST_P(ResizeSameAsHost, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
 
@@ -224,7 +224,7 @@ PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation)
     }
 };
 
-TEST_P(ResizeNPP, Accuracy)
+GPU_TEST_P(ResizeNPP, Accuracy)
 {
     cv::Mat src = readImageType("stereobp/aloe-L.png", type);
     ASSERT_FALSE(src.empty());

modules/gpu/test/test_threshold.cpp

@@ -66,7 +66,7 @@ PARAM_TEST_CASE(Threshold, cv::gpu::DeviceInfo, cv::Size, MatType, ThreshOp, Use
     }
 };
 
-TEST_P(Threshold, Accuracy)
+GPU_TEST_P(Threshold, Accuracy)
 {
     cv::Mat src = randomMat(size, type);
     double maxVal = randomDouble(20.0, 127.0);

modules/ts/include/opencv2/ts/ts.hpp

 #ifndef __OPENCV_GTESTCV_HPP__
 #define __OPENCV_GTESTCV_HPP__
 
-#if HAVE_CVCONFIG_H
+#ifdef HAVE_CVCONFIG_H
 #include "cvconfig.h"
 #endif
 #ifndef GTEST_CREATE_SHARED_LIBRARY

modules/ts/src/ts_perf.cpp

 #include "precomp.hpp"
 
+#ifdef HAVE_CUDA
+#include "opencv2/core/gpumat.hpp"
+#endif
+
 #ifdef ANDROID
 # include <sys/time.h>
 #endif
@@ -1160,6 +1164,10 @@ void TestBase::RunPerfTestBody()
     catch(cv::Exception e)
     {
         metrics.terminationReason = performance_metrics::TERM_EXCEPTION;
+        #ifdef HAVE_CUDA
+            if (e.code == CV_GpuApiCallError)
+                cv::gpu::resetDevice();
+        #endif
         FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n  Actual: it throws cv::Exception:\n  " << e.what();
     }
     catch(std::exception e)