Merge pull request #9692 from alalek:dnn_perf_net

modules/dnn/perf/perf_convolution.cpp

 #include "perf_precomp.hpp"
 #include <opencv2/dnn/shape_utils.hpp>
 
-namespace cvtest
+namespace
 {
 
-using std::tr1::tuple;
-using std::tr1::get;
-using std::tr1::make_tuple;
-using std::make_pair;
-using namespace perf;
-using namespace testing;
-using namespace cv;
-using namespace cv::dnn;
-
 enum {STRIDE_OFF = 1, STRIDE_ON = 2};
 CV_ENUM(StrideSize, STRIDE_OFF, STRIDE_ON);
 
 enum {GROUP_OFF = 1, GROUP_2 = 2};
 CV_ENUM(GroupSize, GROUP_OFF, GROUP_2);
 
-//Squared Size
-#define SSZ(n) cv::Size(n, n)
-
 typedef std::pair<MatShape, int> InpShapeNumOut;
 typedef tuple<Size, InpShapeNumOut, GroupSize, StrideSize> ConvParam; //kernel_size, inp shape, groups, stride
 typedef TestBaseWithParam<ConvParam> ConvolutionPerfTest;
@@ -77,11 +65,11 @@ PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
     Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp);
     std::vector<MatShape> inputShapes(1, shape(inpBlob)), outShapes, internals;
     layer->getMemoryShapes(inputShapes, 0, outShapes, internals);
-    for (int i = 0; i < outShapes.size(); i++)
+    for (size_t i = 0; i < outShapes.size(); i++)
     {
         outBlobs.push_back(Mat(outShapes[i], CV_32F));
     }
-    for (int i = 0; i < internals.size(); i++)
+    for (size_t i = 0; i < internals.size(); i++)
     {
         internalBlobs.push_back(Mat());
         if (total(internals[i]))
@@ -95,12 +83,13 @@ PERF_TEST_P( ConvolutionPerfTest, perf, Combine(
     Mat outBlob2D = outBlobs[0].reshape(1, outBlobs[0].size[0]);
     declare.in(inpBlob2D, wgtBlob2D, WARMUP_RNG).out(outBlob2D).tbb_threads(cv::getNumThreads());
 
-    TEST_CYCLE_N(10)
-    {
+    layer->forward(inpBlobs, outBlobs, internalBlobs); /// warmup
+
+    PERF_SAMPLE_BEGIN()
         layer->forward(inpBlobs, outBlobs, internalBlobs);
-    }
+    PERF_SAMPLE_END()
 
     SANITY_CHECK_NOTHING();
 }
 
-}
+} // namespace

modules/dnn/perf/perf_halide_net.cpp

-// This file is part of OpenCV project.
-// It is subject to the license terms in the LICENSE file found in the top-level directory
-// of this distribution and at http://opencv.org/license.html.
-//
-// Copyright (C) 2017, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-
-#include "perf_precomp.hpp"
-
-namespace cvtest
-{
-
-#ifdef HAVE_HALIDE
-using namespace cv;
-using namespace dnn;
-
-static void loadNet(std::string weights, std::string proto, std::string scheduler,
-                    int inWidth, int inHeight, const std::string& outputLayer,
-                    const std::string& framework, int targetId, Net* net)
-{
-    Mat input(inHeight, inWidth, CV_32FC3);
-    randu(input, 0.0f, 1.0f);
-
-    weights = findDataFile(weights, false);
-    if (!proto.empty())
-        proto = findDataFile(proto, false);
-    if (!scheduler.empty())
-        scheduler = findDataFile(scheduler, false);
-    if (framework == "caffe")
-    {
-        *net = cv::dnn::readNetFromCaffe(proto, weights);
-    }
-    else if (framework == "torch")
-    {
-        *net = cv::dnn::readNetFromTorch(weights);
-    }
-    else if (framework == "tensorflow")
-    {
-        *net = cv::dnn::readNetFromTensorflow(weights);
-    }
-    else
-        CV_Error(Error::StsNotImplemented, "Unknown framework " + framework);
-
-    net->setInput(blobFromImage(input, 1.0, Size(), Scalar(), false));
-    net->setPreferableBackend(DNN_BACKEND_HALIDE);
-    net->setPreferableTarget(targetId);
-    net->setHalideScheduler(scheduler);
-    net->forward(outputLayer);
-}
-
-////////////////////////////////////////////////////////////////////////////////
-// CPU target
-////////////////////////////////////////////////////////////////////////////////
-PERF_TEST(GoogLeNet, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt",
-            "", 224, 224, "prob", "caffe", DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(AlexNet, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/bvlc_alexnet.caffemodel", "dnn/bvlc_alexnet.prototxt",
-            "dnn/halide_scheduler_alexnet.yml", 227, 227, "prob", "caffe",
-            DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(ResNet50, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/ResNet-50-model.caffemodel", "dnn/ResNet-50-deploy.prototxt",
-            "dnn/halide_scheduler_resnet_50.yml", 224, 224, "prob", "caffe",
-            DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(SqueezeNet_v1_1, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/squeezenet_v1.1.caffemodel", "dnn/squeezenet_v1.1.prototxt",
-            "dnn/halide_scheduler_squeezenet_v1_1.yml", 227, 227, "prob",
-            "caffe", DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(Inception_5h, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/tensorflow_inception_graph.pb", "",
-            "dnn/halide_scheduler_inception_5h.yml",
-            224, 224, "softmax2", "tensorflow", DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward("softmax2");
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(ENet, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/Enet-model-best.net", "", "dnn/halide_scheduler_enet.yml",
-            512, 256, "l367_Deconvolution", "torch", DNN_TARGET_CPU, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-////////////////////////////////////////////////////////////////////////////////
-// OpenCL target
-////////////////////////////////////////////////////////////////////////////////
-PERF_TEST(GoogLeNet_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt",
-            "", 227, 227, "prob", "caffe", DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(AlexNet_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/bvlc_alexnet.caffemodel", "dnn/bvlc_alexnet.prototxt",
-            "dnn/halide_scheduler_opencl_alexnet.yml", 227, 227, "prob", "caffe",
-            DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(ResNet50_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/ResNet-50-model.caffemodel", "dnn/ResNet-50-deploy.prototxt",
-            "dnn/halide_scheduler_opencl_resnet_50.yml", 224, 224, "prob", "caffe",
-            DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-
-PERF_TEST(SqueezeNet_v1_1_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/squeezenet_v1.1.caffemodel", "dnn/squeezenet_v1.1.prototxt",
-            "dnn/halide_scheduler_opencl_squeezenet_v1_1.yml", 227, 227, "prob",
-            "caffe", DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(Inception_5h_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/tensorflow_inception_graph.pb", "",
-            "dnn/halide_scheduler_opencl_inception_5h.yml",
-            224, 224, "softmax2", "tensorflow", DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward("softmax2");
-    SANITY_CHECK_NOTHING();
-}
-
-PERF_TEST(ENet_opencl, HalidePerfTest)
-{
-    Net net;
-    loadNet("dnn/Enet-model-best.net", "", "dnn/halide_scheduler_opencl_enet.yml",
-            512, 256, "l367_Deconvolution", "torch", DNN_TARGET_OPENCL, &net);
-    TEST_CYCLE() net.forward();
-    SANITY_CHECK_NOTHING();
-}
-#endif  // HAVE_HALIDE
-
-}  // namespace cvtest

modules/dnn/perf/perf_net.cpp

+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+//
+// Copyright (C) 2017, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+
+#include "perf_precomp.hpp"
+#include "opencv2/core/ocl.hpp"
+
+#include "opencv2/dnn/shape_utils.hpp"
+
+namespace
+{
+
+#ifdef HAVE_HALIDE
+#define TEST_DNN_BACKEND DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE
+#else
+#define TEST_DNN_BACKEND DNN_BACKEND_DEFAULT
+#endif
+#define TEST_DNN_TARGET DNN_TARGET_CPU, DNN_TARGET_OPENCL
+
+CV_ENUM(DNNBackend, DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE)
+CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
+
+class DNNTestNetwork : public ::perf::TestBaseWithParam< tuple<DNNBackend, DNNTarget> >
+{
+public:
+    dnn::Backend backend;
+    dnn::Target target;
+
+    dnn::Net net;
+
+    void processNet(std::string weights, std::string proto, std::string halide_scheduler,
+                        int inWidth, int inHeight, const std::string& outputLayer,
+                        const std::string& framework)
+    {
+        backend = (dnn::Backend)(int)get<0>(GetParam());
+        target = (dnn::Target)(int)get<1>(GetParam());
+
+        if (backend == DNN_BACKEND_DEFAULT && target == DNN_TARGET_OPENCL)
+        {
+#if 0 //defined(HAVE_OPENCL)
+            if (!cv::ocl::useOpenCL())
+#endif
+            {
+                throw ::SkipTestException("OpenCL is not available/disabled in OpenCV");
+            }
+        }
+
+        Mat input(inHeight, inWidth, CV_32FC3);
+        randu(input, 0.0f, 1.0f);
+
+
+        weights = findDataFile(weights, false);
+        if (!proto.empty())
+            proto = findDataFile(proto, false);
+        if (!halide_scheduler.empty() && backend == DNN_BACKEND_HALIDE)
+            halide_scheduler = findDataFile(std::string("dnn/halide_scheduler_") + (target == DNN_TARGET_OPENCL ? "opencl_" : "") + halide_scheduler, true);
+        if (framework == "caffe")
+        {
+            net = cv::dnn::readNetFromCaffe(proto, weights);
+        }
+        else if (framework == "torch")
+        {
+            net = cv::dnn::readNetFromTorch(weights);
+        }
+        else if (framework == "tensorflow")
+        {
+            net = cv::dnn::readNetFromTensorflow(weights);
+        }
+        else
+            CV_Error(Error::StsNotImplemented, "Unknown framework " + framework);
+
+        net.setInput(blobFromImage(input, 1.0, Size(), Scalar(), false));
+        net.setPreferableBackend(backend);
+        net.setPreferableTarget(target);
+        if (backend == DNN_BACKEND_HALIDE)
+        {
+            net.setHalideScheduler(halide_scheduler);
+        }
+
+        MatShape netInputShape = shape(1, 3, inHeight, inWidth);
+        size_t weightsMemory = 0, blobsMemory = 0;
+        net.getMemoryConsumption(netInputShape, weightsMemory, blobsMemory);
+        int64 flops = net.getFLOPS(netInputShape);
+
+        net.forward(outputLayer); // warmup
+
+        std::cout << "Memory consumption:" << std::endl;
+        std::cout << "    Weights(parameters): " << divUp(weightsMemory, 1u<<20) << " Mb" << std::endl;
+        std::cout << "    Blobs: " << divUp(blobsMemory, 1u<<20) << " Mb" << std::endl;
+        std::cout << "Calculation complexity: " << flops * 1e-9 << " GFlops" << std::endl;
+
+        PERF_SAMPLE_BEGIN()
+            net.forward();
+        PERF_SAMPLE_END()
+
+        SANITY_CHECK_NOTHING();
+    }
+};
+
+
+PERF_TEST_P_(DNNTestNetwork, AlexNet)
+{
+    processNet("dnn/bvlc_alexnet.caffemodel", "dnn/bvlc_alexnet.prototxt",
+            "alexnet.yml", 227, 227, "prob", "caffe");
+}
+
+PERF_TEST_P_(DNNTestNetwork, GoogLeNet)
+{
+    processNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt",
+            "", 224, 224, "prob", "caffe");
+}
+
+PERF_TEST_P_(DNNTestNetwork, ResNet50)
+{
+    processNet("dnn/ResNet-50-model.caffemodel", "dnn/ResNet-50-deploy.prototxt",
+            "resnet_50.yml", 224, 224, "prob", "caffe");
+}
+
+PERF_TEST_P_(DNNTestNetwork, SqueezeNet_v1_1)
+{
+    processNet("dnn/squeezenet_v1.1.caffemodel", "dnn/squeezenet_v1.1.prototxt",
+            "squeezenet_v1_1.yml", 227, 227, "prob", "caffe");
+}
+
+PERF_TEST_P_(DNNTestNetwork, Inception_5h)
+{
+    processNet("dnn/tensorflow_inception_graph.pb", "",
+            "inception_5h.yml",
+            224, 224, "softmax2", "tensorflow");
+}
+
+PERF_TEST_P_(DNNTestNetwork, ENet)
+{
+    processNet("dnn/Enet-model-best.net", "", "enet.yml",
+            512, 256, "l367_Deconvolution", "torch");
+}
+
+
+INSTANTIATE_TEST_CASE_P(/*nothing*/, DNNTestNetwork,
+    testing::Combine(
+        ::testing::Values(TEST_DNN_BACKEND),
+        DNNTarget::all()
+    )
+);
+
+} // namespace

modules/dnn/perf/perf_precomp.hpp

-#ifdef __GNUC__
-#  pragma GCC diagnostic ignored "-Wmissing-declarations"
-#  if defined __clang__ || defined __APPLE__
-#    pragma GCC diagnostic ignored "-Wmissing-prototypes"
-#    pragma GCC diagnostic ignored "-Wextra"
-#  endif
-#endif
-
 #ifndef __OPENCV_PERF_PRECOMP_HPP__
 #define __OPENCV_PERF_PRECOMP_HPP__
 
@@ -14,4 +6,9 @@
 #include <opencv2/highgui.hpp>
 #include <opencv2/dnn.hpp>
 
+using namespace cvtest;
+using namespace perf;
+using namespace cv;
+using namespace dnn;
+
 #endif

modules/ts/include/opencv2/ts.hpp

@@ -58,8 +58,8 @@
 #  define GTEST_USES_POSIX_RE 0
 #endif
 
-#define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > >
-#define GET_PARAM(k) std::tr1::get< k >(GetParam())
+#define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< testing::tuple< __VA_ARGS__ > >
+#define GET_PARAM(k) testing::get< k >(GetParam())
 
 namespace cvtest
 {
@@ -70,6 +70,13 @@ using namespace cv;
 using testing::Values;
 using testing::Combine;
 
+// Tuple stuff from Google Tests
+using testing::get;
+using testing::make_tuple;
+using testing::tuple;
+using testing::tuple_size;
+using testing::tuple_element;
+
 
 class SkipTestException: public cv::Exception
 {

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

@@ -62,9 +62,9 @@ namespace perf
     #define CUDA_CHANNELS_1_3_4 testing::Values(MatCn(Gray), MatCn(BGR), MatCn(BGRA))
     #define CUDA_CHANNELS_1_3 testing::Values(MatCn(Gray), MatCn(BGR))
 
-    #define GET_PARAM(k) std::tr1::get< k >(GetParam())
+    #define GET_PARAM(k) testing::get< k >(GetParam())
 
-    #define DEF_PARAM_TEST(name, ...) typedef ::perf::TestBaseWithParam< std::tr1::tuple< __VA_ARGS__ > > name
+    #define DEF_PARAM_TEST(name, ...) typedef ::perf::TestBaseWithParam< testing::tuple< __VA_ARGS__ > > name
     #define DEF_PARAM_TEST_1(name, param_type) typedef ::perf::TestBaseWithParam< param_type > name
 
     DEF_PARAM_TEST_1(Sz, cv::Size);

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

@@ -52,9 +52,6 @@ namespace ocl {
 
 using namespace perf;
 
-using std::tr1::get;
-using std::tr1::tuple;
-
 #define OCL_PERF_STRATEGY PERF_STRATEGY_SIMPLE
 
 #define OCL_PERF_TEST(fixture, name) SIMPLE_PERF_TEST(fixture, name)

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

@@ -325,7 +325,7 @@ struct CV_EXPORTS TSTestWithParam : public TestUtils, public ::testing::TestWith
 };
 
 #undef PARAM_TEST_CASE
-#define PARAM_TEST_CASE(name, ...) struct name : public ::cvtest::ocl::TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
+#define PARAM_TEST_CASE(name, ...) struct name : public ::cvtest::ocl::TSTestWithParam< testing::tuple< __VA_ARGS__ > >
 
 #ifndef IMPLEMENT_PARAM_CLASS
 #define IMPLEMENT_PARAM_CLASS(name, type) \

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

@@ -12,17 +12,17 @@ namespace cvtest {
 void checkIppStatus();
 }
 
-#define CV_TEST_INIT \
+#define CV__TEST_INIT \
     cv::ipp::setIppStatus(0); \
     cv::theRNG().state = cvtest::param_seed;
-#define CV_TEST_CLEANUP ::cvtest::checkIppStatus();
-#define CV_TEST_BODY_IMPL(name) \
+#define CV__TEST_CLEANUP ::cvtest::checkIppStatus();
+#define CV__TEST_BODY_IMPL(name) \
     { \
        CV__TRACE_APP_FUNCTION_NAME(name); \
        try { \
-          CV_TEST_INIT \
+          CV__TEST_INIT \
           Body(); \
-          CV_TEST_CLEANUP \
+          CV__TEST_CLEANUP \
        } \
        catch (cvtest::SkipTestException& e) \
        { \
@@ -54,7 +54,7 @@ void checkIppStatus();
             ::testing::Test::TearDownTestCase, \
             new ::testing::internal::TestFactoryImpl<\
                 GTEST_TEST_CLASS_NAME_(test_case_name, test_name)>);\
-    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() CV_TEST_BODY_IMPL( #test_case_name "_" #test_name ) \
+    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() CV__TEST_BODY_IMPL( #test_case_name "_" #test_name ) \
     void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::Body()
 
 #undef TEST_F
@@ -80,17 +80,17 @@ void checkIppStatus();
             test_fixture::TearDownTestCase, \
             new ::testing::internal::TestFactoryImpl<\
                 GTEST_TEST_CLASS_NAME_(test_fixture, test_name)>);\
-    void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::TestBody() CV_TEST_BODY_IMPL( #test_fixture "_" #test_name ) \
+    void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::TestBody() CV__TEST_BODY_IMPL( #test_fixture "_" #test_name ) \
     void GTEST_TEST_CLASS_NAME_(test_fixture, test_name)::Body()
 
-#undef TEST_P
-#define TEST_P(test_case_name, test_name) \
+// Don't use directly
+#define CV__TEST_P(test_case_name, test_name, bodyMethodName, BODY_IMPL/*(name_str)*/) \
   class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \
       : public test_case_name { \
    public: \
     GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {} \
    private: \
-    virtual void Body(); \
+    virtual void bodyMethodName(); \
     virtual void TestBody(); \
     static int AddToRegistry() { \
       ::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
@@ -112,7 +112,10 @@ void checkIppStatus();
   int GTEST_TEST_CLASS_NAME_(test_case_name, \
                              test_name)::gtest_registering_dummy_ = \
       GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \
-    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() CV_TEST_BODY_IMPL( #test_case_name "_" #test_name ) \
-    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::Body()
+    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() BODY_IMPL( #test_case_name "_" #test_name ) \
+    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::bodyMethodName()
+
+#undef TEST_P
+#define TEST_P(test_case_name, test_name) CV__TEST_P(test_case_name, test_name, Body, CV__TEST_BODY_IMPL)
 
 #endif  // OPENCV_TS_EXT_HPP

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

@@ -27,40 +27,49 @@
 
 // declare major namespaces to avoid errors on unknown namespace
 namespace cv { namespace cuda {} namespace ocl {} }
+namespace cvtest { }
 
 namespace perf
 {
+
+// Tuple stuff from Google Tests
+using testing::get;
+using testing::make_tuple;
+using testing::tuple;
+using testing::tuple_size;
+using testing::tuple_element;
+
 class TestBase;
 
 /*****************************************************************************************\
 *                Predefined typical frame sizes and typical test parameters               *
 \*****************************************************************************************/
-const cv::Size szQVGA = cv::Size(320, 240);
-const cv::Size szVGA = cv::Size(640, 480);
-const cv::Size szSVGA = cv::Size(800, 600);
-const cv::Size szXGA = cv::Size(1024, 768);
-const cv::Size szSXGA = cv::Size(1280, 1024);
-const cv::Size szWQHD = cv::Size(2560, 1440);
-
-const cv::Size sznHD = cv::Size(640, 360);
-const cv::Size szqHD = cv::Size(960, 540);
-const cv::Size sz240p = szQVGA;
-const cv::Size sz720p = cv::Size(1280, 720);
-const cv::Size sz1080p = cv::Size(1920, 1080);
-const cv::Size sz1440p = szWQHD;
-const cv::Size sz2160p = cv::Size(3840, 2160);//UHDTV1 4K
-const cv::Size sz4320p = cv::Size(7680, 4320);//UHDTV2 8K
-
-const cv::Size sz3MP = cv::Size(2048, 1536);
-const cv::Size sz5MP = cv::Size(2592, 1944);
-const cv::Size sz2K = cv::Size(2048, 2048);
-
-const cv::Size szODD = cv::Size(127, 61);
-
-const cv::Size szSmall24 = cv::Size(24, 24);
-const cv::Size szSmall32 = cv::Size(32, 32);
-const cv::Size szSmall64 = cv::Size(64, 64);
-const cv::Size szSmall128 = cv::Size(128, 128);
+const static cv::Size szQVGA = cv::Size(320, 240);
+const static cv::Size szVGA = cv::Size(640, 480);
+const static cv::Size szSVGA = cv::Size(800, 600);
+const static cv::Size szXGA = cv::Size(1024, 768);
+const static cv::Size szSXGA = cv::Size(1280, 1024);
+const static cv::Size szWQHD = cv::Size(2560, 1440);
+
+const static cv::Size sznHD = cv::Size(640, 360);
+const static cv::Size szqHD = cv::Size(960, 540);
+const static cv::Size sz240p = szQVGA;
+const static cv::Size sz720p = cv::Size(1280, 720);
+const static cv::Size sz1080p = cv::Size(1920, 1080);
+const static cv::Size sz1440p = szWQHD;
+const static cv::Size sz2160p = cv::Size(3840, 2160);//UHDTV1 4K
+const static cv::Size sz4320p = cv::Size(7680, 4320);//UHDTV2 8K
+
+const static cv::Size sz3MP = cv::Size(2048, 1536);
+const static cv::Size sz5MP = cv::Size(2592, 1944);
+const static cv::Size sz2K = cv::Size(2048, 2048);
+
+const static cv::Size szODD = cv::Size(127, 61);
+
+const static cv::Size szSmall24 = cv::Size(24, 24);
+const static cv::Size szSmall32 = cv::Size(32, 32);
+const static cv::Size szSmall64 = cv::Size(64, 64);
+const static cv::Size szSmall128 = cv::Size(128, 128);
 
 #define SZ_ALL_VGA ::testing::Values(::perf::szQVGA, ::perf::szVGA, ::perf::szSVGA)
 #define SZ_ALL_GA  ::testing::Values(::perf::szQVGA, ::perf::szVGA, ::perf::szSVGA, ::perf::szXGA, ::perf::szSXGA)
@@ -492,7 +501,7 @@ public:
 
 template<typename T> class TestBaseWithParam: public TestBase, public ::testing::WithParamInterface<T> {};
 
-typedef std::tr1::tuple<cv::Size, MatType> Size_MatType_t;
+typedef tuple<cv::Size, MatType> Size_MatType_t;
 typedef TestBaseWithParam<Size_MatType_t> Size_MatType;
 
 /*****************************************************************************************\
@@ -514,6 +523,13 @@ CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
 /*****************************************************************************************\
 *                        Macro definitions for performance tests                          *
 \*****************************************************************************************/
+
+#define CV__PERF_TEST_BODY_IMPL(name) \
+    { \
+       CV__TRACE_APP_FUNCTION_NAME("PERF_TEST: " name); \
+       RunPerfTestBody(); \
+    }
+
 #define PERF_PROXY_NAMESPACE_NAME_(test_case_name, test_name) \
   test_case_name##_##test_name##_perf_namespace_proxy
 
@@ -538,7 +554,7 @@ CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
       protected:\
        virtual void PerfTestBody();\
      };\
-     TEST_F(test_case_name, test_name){ CV_TRACE_REGION("PERF_TEST: " #test_case_name "_" #test_name); RunPerfTestBody(); }\
+     TEST_F(test_case_name, test_name){ CV__PERF_TEST_BODY_IMPL(#test_case_name "_" #test_name); }\
     }\
     void PERF_PROXY_NAMESPACE_NAME_(test_case_name, test_name)::test_case_name::PerfTestBody()
 
@@ -576,12 +592,20 @@ CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
       protected:\
        virtual void PerfTestBody();\
      };\
-     TEST_F(fixture, testname){ CV_TRACE_REGION("PERF_TEST: " #fixture "_" #testname); RunPerfTestBody(); }\
+     TEST_F(fixture, testname){ CV__PERF_TEST_BODY_IMPL(#fixture "_" #testname); }\
     }\
     void PERF_PROXY_NAMESPACE_NAME_(fixture, testname)::fixture::PerfTestBody()
 
 // Defines a parametrized performance test.
 //
+// @Note PERF_TEST_P() below violates behavior of original Google Tests - there is no tests instantiation in original TEST_P()
+// This macro is intended for usage with separate INSTANTIATE_TEST_CASE_P macro
+#define PERF_TEST_P_(test_case_name, test_name) CV__TEST_P(test_case_name, test_name, PerfTestBody, CV__PERF_TEST_BODY_IMPL)
+
+// Defines a parametrized performance test.
+//
+// @Note Original TEST_P() macro doesn't instantiate tests with parameters. To keep original usage use PERF_TEST_P_() macro
+//
 // The first parameter is the name of the test fixture class, which
 // also doubles as the test case name.  The second parameter is the
 // name of the test within the test case.
@@ -609,7 +633,7 @@ CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
      protected:\
       virtual void PerfTestBody();\
     };\
-    TEST_P(fixture##_##name, name /*perf*/){ CV_TRACE_REGION("PERF_TEST: " #fixture "_" #name); RunPerfTestBody(); }\
+    CV__TEST_P(fixture##_##name, name, PerfTestBodyDummy, CV__PERF_TEST_BODY_IMPL){} \
     INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\
     void fixture##_##name::PerfTestBody()