From a0a3b8b56df52c07f436c8cb6e7c5dad2b51bd98 Mon Sep 17 00:00:00 2001
From: Konstantin Matskevich <konstantin.matskevich@itseez.com>
Date: Thu, 31 Oct 2013 16:25:13 +0400
Subject: [PATCH] Some tests for UMat

---
 modules/core/test/test_precomp.hpp | 123 ++++++++
 modules/core/test/test_umat.cpp    | 621 +++++++++++++++++++++++++------------
 2 files changed, 554 insertions(+), 190 deletions(-)

diff --git a/modules/core/test/test_precomp.hpp b/modules/core/test/test_precomp.hpp
index d981cea..ffd264f 100644
--- a/modules/core/test/test_precomp.hpp
+++ b/modules/core/test/test_precomp.hpp
@@ -15,4 +15,127 @@
 
 #include "opencv2/core/private.hpp"
 
+#define MWIDTH 256
+#define MHEIGHT 256
+
+#define MIN_VALUE 171
+#define MAX_VALUE 357
+
+#define RNG_SEED 123456
+
+template <typename T>
+struct TSTestWithParam : public ::testing::TestWithParam<T>
+{
+    cv::RNG rng;
+
+    TSTestWithParam()
+    {
+        rng = cv::RNG(RNG_SEED);
+    }
+
+    int randomInt(int minVal, int maxVal)
+    {
+        return rng.uniform(minVal, maxVal);
+    }
+
+    double randomDouble(double minVal, double maxVal)
+    {
+        return rng.uniform(minVal, maxVal);
+    }
+
+    double randomDoubleLog(double minVal, double maxVal)
+    {
+        double logMin = log((double)minVal + 1);
+        double logMax = log((double)maxVal + 1);
+        double pow = rng.uniform(logMin, logMax);
+        double v = exp(pow) - 1;
+        CV_Assert(v >= minVal && (v < maxVal || (v == minVal && v == maxVal)));
+        return v;
+    }
+
+    cv::Size randomSize(int minVal, int maxVal)
+    {
+#if 1
+        return cv::Size((int)randomDoubleLog(minVal, maxVal), (int)randomDoubleLog(minVal, maxVal));
+#else
+        return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
+#endif
+    }
+
+    cv::Size randomSize(int minValX, int maxValX, int minValY, int maxValY)
+    {
+#if 1
+        return cv::Size(randomDoubleLog(minValX, maxValX), randomDoubleLog(minValY, maxValY));
+#else
+        return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
+#endif
+    }
+
+    cv::Scalar randomScalar(double minVal, double maxVal)
+    {
+        return cv::Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
+    }
+
+    cv::Mat randomMat(cv::Size size, int type, double minVal, double maxVal, bool useRoi = false)
+    {
+        cv::RNG dataRng(rng.next());
+        return cvtest::randomMat(dataRng, size, type, minVal, maxVal, useRoi);
+    }
+
+};
+
+#define PARAM_TEST_CASE(name, ...) struct name : public TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
+
+#define GET_PARAM(k) std::tr1::get< k >(GetParam())
+
+#define UMAT_TEST_CHANNELS testing::Values(1, 2, 3, 4/*, 5*/)
+
+#define UMAT_TEST_SIZES testing::Values(cv::Size(1,1), cv::Size(1,128), cv::Size(128,1), cv::Size(128, 128), cv::Size(59, 113), cv::Size(640,480), cv::Size(751,373), cv::Size(2000, 2000))
+
+#define UMAT_TEST_DEPTH testing::Values(CV_8S, CV_8U, CV_16S, CV_16U, CV_32F, CV_32S, CV_64F)
+
+# define CORE_TEST_P(test_case_name, test_name) \
+    class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) : \
+        public test_case_name { \
+    public: \
+        GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() { } \
+        virtual void TestBody(); \
+        void CoreTestBody(); \
+    private: \
+        static int AddToRegistry() \
+        { \
+            ::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
+              GetTestCasePatternHolder<test_case_name>(\
+                  #test_case_name, __FILE__, __LINE__)->AddTestPattern(\
+                      #test_case_name, \
+                      #test_name, \
+                      new ::testing::internal::TestMetaFactory< \
+                          GTEST_TEST_CLASS_NAME_(test_case_name, test_name)>()); \
+            return 0; \
+        } \
+    \
+        static int gtest_registering_dummy_; \
+        GTEST_DISALLOW_COPY_AND_ASSIGN_(\
+            GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \
+    }; \
+    \
+    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() \
+    { \
+        try \
+        { \
+            CoreTestBody(); \
+        } \
+        catch (...) \
+        { \
+                std::cout << "Something wrong in CoreTestBody running" << std::endl; \
+                throw; \
+        } \
+    } \
+    \
+    void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::CoreTestBody()
+
 #endif
diff --git a/modules/core/test/test_umat.cpp b/modules/core/test/test_umat.cpp
index 765a631..e6fcbd1 100644
--- a/modules/core/test/test_umat.cpp
+++ b/modules/core/test/test_umat.cpp
@@ -40,257 +40,456 @@
 //M*/
 
 #include "test_precomp.hpp"
-
-#include <string>
-#include <iostream>
 #include "opencv2/core/ocl.hpp"
 
+using namespace cvtest;
+using namespace testing;
 using namespace cv;
-using namespace std;
 
-class CV_UMatTest :
-        public cvtest::BaseTest
-{
-public:
-    CV_UMatTest() {}
-    ~CV_UMatTest() {}
-protected:
-    void run(int);
+#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
+{ \
+   ASSERT_EQ(mat1.type(), mat2.type()); \
+   ASSERT_EQ(mat1.size(), mat2.size()); \
+   EXPECT_LE(cv::norm(mat1, mat2), eps); \
+}\
 
-    struct test_excep
-    {
-        test_excep(const string& _s=string("")) : s(_s) { }
-        string s;
-    };
+////////////////////////////////////////////////////////////// Basic Tests /////////////////////////////////////////////////////////////////////
 
-    bool TestUMat();
+PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
+{
+    Mat a, b, roi_a, roi_b;
+    UMat ua, ub, roi_ua, roi_ub;
+    int type;
+    int depth;
+    int cn;
+    Size size;
+    bool useRoi;
+    Size roi_size;
+    Rect roi;
+    virtual void SetUp()
+    {
+        depth = GET_PARAM(0);
+        cn = GET_PARAM(1);
+        size = GET_PARAM(2);
+        useRoi = GET_PARAM(3);
+        type = CV_MAKE_TYPE(depth, cn);
+        a = randomMat(size, type, -100, 100);
+        b = randomMat(size, type, -100, 100);
+        a.copyTo(ua);
+        b.copyTo(ub);
+        int roi_shift_x = randomInt(0, size.width-1);
+        int roi_shift_y = randomInt(0, size.height-1);
+        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+        roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+    }
+};
 
-    void checkDiff(const Mat& m1, const Mat& m2, const string& s)
+CORE_TEST_P(UMatBasicTests, createUMat)
+{
+    if(useRoi)
     {
-        if (norm(m1, m2, NORM_INF) != 0)
-            throw test_excep(s);
+        ua = UMat(ua, roi);
     }
-    void checkDiffF(const Mat& m1, const Mat& m2, const string& s)
+    int dims = randomInt(2,6);
+    int _sz[CV_MAX_DIM];
+    for( int i = 0; i<dims; i++)
     {
-        if (norm(m1, m2, NORM_INF) > 1e-5)
-            throw test_excep(s);
+        _sz[i] = randomInt(1,50);
     }
-};
-
-#define STR(a) STR2(a)
-#define STR2(a) #a
+    int *sz = _sz;
+    int new_depth = randomInt(CV_8S, CV_64F);
+    int new_cn = randomInt(1,4);
+    ua.create(dims, sz, CV_MAKE_TYPE(new_depth, new_cn));
 
-#define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ")  !=  (" #b ")  at l." STR(__LINE__))
-#define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ")  !=(eps)  (" #b ")  at l." STR(__LINE__))
+    for(int i = 0; i<dims; i++)
+    {
+        ASSERT_EQ(ua.size[i], sz[i]);
+    }
+    ASSERT_EQ(ua.dims, dims);
+    ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
+    Size new_size = randomSize(1, 1000);
+    ua.create(new_size, CV_MAKE_TYPE(new_depth, new_cn) );
+    ASSERT_EQ( ua.size(), new_size);
+    ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
+    ASSERT_EQ( ua.dims, 2);
+}
 
+CORE_TEST_P(UMatBasicTests, swap)
+{
+    if(useRoi)
+    {
+        ua = UMat(ua,roi);
+        ub = UMat(ub,roi);
+    }
+    UMat uc = ua, ud = ub;
+    swap(ua,ub);
+    EXPECT_MAT_NEAR(ub,uc, 0);
+    EXPECT_MAT_NEAR(ud, ua, 0);
+}
 
-bool CV_UMatTest::TestUMat()
+CORE_TEST_P(UMatBasicTests, base)
 {
-    try
+    if(useRoi)
     {
-        Mat a(100, 100, CV_16SC2), b, c;
-        randu(a, Scalar::all(-100), Scalar::all(100));
-        Rect roi(1, 3, 5, 4);
-        Mat ra(a, roi), rb, rc, rc0;
-        UMat ua, ura, ub, urb, uc, urc;
-        a.copyTo(ua);
-        ua.copyTo(b);
-        CHECK_DIFF(a, b);
+        ua = UMat(ua,roi);
+    }
+    ub = ua.clone();
+    EXPECT_MAT_NEAR(ub,ua,0);
+
+    ASSERT_EQ(ua.channels(), cn);
+    ASSERT_EQ(ua.depth(), depth);
+    ASSERT_EQ(ua.type(), type);
+    ASSERT_EQ(ua.elemSize(), a.elemSize());
+    ASSERT_EQ(ua.elemSize1(), a.elemSize1());
+    ASSERT_EQ(ub.empty(), ub.cols*ub.rows == 0);
+    ub.release();
+    ASSERT_TRUE( ub.empty() );
+    if(useRoi && a.size() != ua.size())
+    {
+        ASSERT_EQ(ua.isSubmatrix(), true);
+    }
+    else
+    {
+        ASSERT_EQ(ua.isSubmatrix(), false);
+    }
 
-        ura = ua(roi);
-        ura.copyTo(rb);
+    int dims = randomInt(2,6);
+    int sz[CV_MAX_DIM];
+    size_t total = 1;
+    for(int i = 0; i<dims; i++)
+    {
+        sz[i] = randomInt(1,45);
+        total *= (size_t)sz[i];
+    }
+    int new_type = CV_MAKE_TYPE(randomInt(CV_8S,CV_64F),randomInt(1,4));
+    ub = UMat(dims, sz, new_type);
+    ASSERT_EQ(ub.total(), total);
+}
 
-        CHECK_DIFF(ra, rb);
+CORE_TEST_P(UMatBasicTests, copyTo)
+{
+    if(useRoi)
+    {
+        roi_ua = UMat(ua, roi);
+        roi_a = Mat(a, roi);
+        roi_a.copyTo(roi_ua);
+        EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
+        roi_ua.copyTo(roi_a);
+        EXPECT_MAT_NEAR(roi_ua, roi_a, 0);
+        roi_ua.copyTo(ua);
+        EXPECT_MAT_NEAR(roi_ua, ua, 0);
+        ua.copyTo(a);
+        EXPECT_MAT_NEAR(ua, a, 0);
+    }
+    ua.copyTo(ub);
+    EXPECT_MAT_NEAR(ua, ub, 0);
+    int i = randomInt(0, ua.cols-1);
+    a.col(i).copyTo(ub);
+    EXPECT_MAT_NEAR(a.col(i), ub, 0);
+    ua.col(i).copyTo(ub);
+    EXPECT_MAT_NEAR(ua.col(i), ub, 0);
+    ua.col(i).copyTo(b);
+    EXPECT_MAT_NEAR(ua.col(i), b, 0);
+    i = randomInt(0, a.rows-1);
+    ua.row(i).copyTo(ub);
+    EXPECT_MAT_NEAR(ua.row(i), ub, 0);
+    a.row(i).copyTo(ub);
+    EXPECT_MAT_NEAR(a.row(i), ub, 0);
+    ua.row(i).copyTo(b);
+    EXPECT_MAT_NEAR(ua.row(i), b, 0);
+}
 
-        ra += Scalar::all(1.f);
-        {
-            Mat temp = ura.getMat(ACCESS_RW);
-            temp += Scalar::all(1.f);
-        }
-        ra.copyTo(rb);
-        CHECK_DIFF(ra, rb);
+CORE_TEST_P(UMatBasicTests, GetUMat)
+{
+    if(useRoi)
+    {
+        a = Mat(a, roi);
+        ua = UMat(ua,roi);
+    }
+    ub = a.getUMat(ACCESS_RW);
+    EXPECT_MAT_NEAR(ub, ua, 0);
+    b = a.getUMat(ACCESS_RW).getMat(ACCESS_RW);
+    EXPECT_MAT_NEAR(b, a, 0);
+    b.release();
+    b = ua.getMat(ACCESS_RW);
+    EXPECT_MAT_NEAR(b, a, 0);
+    b.release();
+    ub = ua.getMat(ACCESS_RW).getUMat(ACCESS_RW);
+    EXPECT_MAT_NEAR(ub, ua, 0);
+}
 
-        b = a.clone();
-        ra = a(roi);
-        rb = b(roi);
-        randu(b, Scalar::all(-100), Scalar::all(100));
-        b.copyTo(ub);
-        urb = ub(roi);
+INSTANTIATE_TEST_CASE_P(UMat, UMatBasicTests, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ) );
 
-        /*std::cout << "==============================================\nbefore op (CPU):\n";
-        std::cout << "ra: " << ra << std::endl;
-        std::cout << "rb: " << rb << std::endl;*/
+//////////////////////////////////////////////////////////////// Reshape ////////////////////////////////////////////////////////////////////////
 
-        ra.copyTo(ura);
-        rb.copyTo(urb);
-        ra.release();
-        rb.release();
-        ura.copyTo(ra);
-        urb.copyTo(rb);
+PARAM_TEST_CASE(UMatTestReshape,  int, int, Size, bool)
+{
+    Mat a;
+    UMat ua, ub;
+    int type;
+    int depth;
+    int cn;
+    Size size;
+    bool useRoi;
+    Size roi_size;
+    virtual void SetUp()
+    {
+        depth = GET_PARAM(0);
+        cn = GET_PARAM(1);
+        size = GET_PARAM(2);
+        useRoi = GET_PARAM(3);
+        type = CV_MAKE_TYPE(depth, cn);
+    }
+};
 
-        /*std::cout << "==============================================\nbefore op (GPU):\n";
-        std::cout << "ra: " << ra << std::endl;
-        std::cout << "rb: " << rb << std::endl;*/
+CORE_TEST_P(UMatTestReshape, reshape)
+{
+    a = randomMat(size,type, -100, 100);
+    a.copyTo(ua);
+    if(useRoi)
+    {
+        int roi_shift_x = randomInt(0, size.width-1);
+        int roi_shift_y = randomInt(0, size.height-1);
+        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+        ua = UMat(ua, roi).clone();
+        a = Mat(a, roi).clone();
+    }
 
-        cv::max(ra, rb, rc);
-        cv::max(ura, urb, urc);
-        urc.copyTo(rc0);
+    int nChannels = randomInt(1,4);
 
-        /*std::cout << "==============================================\nafter op:\n";
-        std::cout << "rc: " << rc << std::endl;
-        std::cout << "rc0: " << rc0 << std::endl;*/
+    if ((ua.cols*ua.channels()*ua.rows)%nChannels != 0)
+    {
+        EXPECT_ANY_THROW(ua.reshape(nChannels));
+    }
+    else
+    {
+        ub = ua.reshape(nChannels);
+        ASSERT_EQ(ub.channels(),nChannels);
+        ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
 
-        CHECK_DIFF(rc0, rc);
+        EXPECT_MAT_NEAR(ua.reshape(nChannels), a.reshape(nChannels), 0);
 
+        int new_rows = randomInt(1, INT_MAX);
+        if ( ((int)ua.total()*ua.channels())%(new_rows*nChannels) != 0)
         {
-            UMat tmp = rc0.getUMat(ACCESS_WRITE);
-            cv::max(ura, urb, tmp);
+            EXPECT_ANY_THROW (ua.reshape(nChannels, new_rows) );
         }
-        CHECK_DIFF(rc0, rc);
-
-        ura.copyTo(urc);
-        cv::max(urc, urb, urc);
-        urc.copyTo(rc0);
-        CHECK_DIFF(rc0, rc);
-
-        rc = ra ^ rb;
-        cv::bitwise_xor(ura, urb, urc);
-        urc.copyTo(rc0);
+        else
+        {
+            EXPECT_NO_THROW ( ub = ua.reshape(nChannels, new_rows) );
+            ASSERT_EQ(ub.channels(),nChannels);
+            ASSERT_EQ(ub.rows, new_rows);
+            ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
 
-        /*std::cout << "==============================================\nafter op:\n";
-        std::cout << "ra: " << rc0 << std::endl;
-        std::cout << "rc: " << rc << std::endl;*/
+            EXPECT_MAT_NEAR(ua.reshape(nChannels,new_rows), a.reshape(nChannels,new_rows), 0);
+        }
 
-        CHECK_DIFF(rc0, rc);
+        new_rows = (int)ua.total()*ua.channels()/(nChannels*randomInt(1, size.width*size.height));
+        if (new_rows == 0) new_rows = 1;
+        int new_cols = (int)ua.total()*ua.channels()/(new_rows*nChannels);
+        int sz[] = {new_rows, new_cols};
+        if( ((int)ua.total()*ua.channels()) % (new_rows*new_cols) != 0 )
+        {
+            EXPECT_ANY_THROW( ua.reshape(nChannels, ua.dims, sz) );
+        }
+        else
+        {
+            EXPECT_NO_THROW ( ub = ua.reshape(nChannels, ua.dims, sz) );
+            ASSERT_EQ(ub.channels(),nChannels);
+            ASSERT_EQ(ub.rows, new_rows);
+            ASSERT_EQ(ub.cols, new_cols);
+            ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
 
-        rc = ra + rb;
-        cv::add(ura, urb, urc);
-        urc.copyTo(rc0);
+            EXPECT_MAT_NEAR(ua.reshape(nChannels, ua.dims, sz), a.reshape(nChannels, a.dims, sz), 0);
+        }
+    }
+}
 
-        CHECK_DIFF(rc0, rc);
+INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
 
-        cv::subtract(ra, Scalar::all(5), rc);
-        cv::subtract(ura, Scalar::all(5), urc);
-        urc.copyTo(rc0);
+////////////////////////////////////////////////////////////////// ROI testing ///////////////////////////////////////////////////////////////
 
-        CHECK_DIFF(rc0, rc);
-    }
-    catch (const test_excep& e)
+PARAM_TEST_CASE(UMatTestRoi, int, int, Size)
+{
+    Mat a, roi_a;
+    UMat ua, roi_ua;
+    int type;
+    int depth;
+    int cn;
+    Size size;
+    Size roi_size;
+    virtual void SetUp()
     {
-        ts->printf(cvtest::TS::LOG, "%s\n", e.s.c_str());
-        ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
-        return false;
+        depth = GET_PARAM(0);
+        cn = GET_PARAM(1);
+        size = GET_PARAM(2);
+        type = CV_MAKE_TYPE(depth, cn);
     }
-    return true;
-}
+};
 
-void CV_UMatTest::run( int /* start_from */)
+CORE_TEST_P(UMatTestRoi, createRoi)
 {
-    printf("Use OpenCL: %s\nHave OpenCL: %s\n",
-           ocl::useOpenCL() ? "TRUE" : "FALSE",
-           ocl::haveOpenCL() ? "TRUE" : "FALSE" );
+    int roi_shift_x = randomInt(0, size.width-1);
+    int roi_shift_y = randomInt(0, size.height-1);
+    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+    a = randomMat(size, type, -100, 100);
+    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+    roi_a = Mat(a, roi);
+    a.copyTo(ua);
+    roi_ua = UMat(ua, roi);
+
+    EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
+}
 
-    if (!TestUMat())
-        return;
+CORE_TEST_P(UMatTestRoi, locateRoi)
+{
+    int roi_shift_x = randomInt(0, size.width-1);
+    int roi_shift_y = randomInt(0, size.height-1);
+    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+    a = randomMat(size, type, -100, 100);
+    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+    roi_a = Mat(a, roi);
+    a.copyTo(ua);
+    roi_ua = UMat(ua,roi);
+    Size sz, usz;
+    Point p, up;
+    roi_a.locateROI(sz, p);
+    roi_ua.locateROI(usz, up);
+    ASSERT_EQ(sz, usz);
+    ASSERT_EQ(p, up);
+}
 
-    ts->set_failed_test_info(cvtest::TS::OK);
+CORE_TEST_P(UMatTestRoi, adjustRoi)
+{
+    int roi_shift_x = randomInt(0, size.width-1);
+    int roi_shift_y = randomInt(0, size.height-1);
+    roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+    a = randomMat(size, type, -100, 100);
+    Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+    a.copyTo(ua);
+    roi_ua = UMat( ua, roi);
+    int adjLeft = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
+    int adjRight = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
+    int adjTop = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
+    int adjBot = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
+    roi_ua.adjustROI(adjTop, adjBot, adjLeft, adjRight);
+    roi_shift_x = max(0, roi.x-adjLeft);
+    roi_shift_y = max(0, roi.y-adjTop);
+    Rect new_roi( roi_shift_x, roi_shift_y, min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
+    UMat test_roi = UMat(ua, new_roi);
+    EXPECT_MAT_NEAR(roi_ua, test_roi, 0);
 }
 
-TEST(Core_UMat, base) { CV_UMatTest test; test.safe_run(); }
+INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES ));
+
+/////////////////////////////////////////////////////////////// Size ////////////////////////////////////////////////////////////////////
 
-TEST(Core_UMat, getUMat)
+PARAM_TEST_CASE(UMatTestSizeOperations, int, int, Size, bool)
 {
+    Mat a, b, roi_a, roi_b;
+    UMat ua, ub, roi_ua, roi_ub;
+    int type;
+    int depth;
+    int cn;
+    Size size;
+    Size roi_size;
+    bool useRoi;
+    virtual void SetUp()
     {
-        int a[3] = { 1, 2, 3 };
-        Mat m = Mat(1, 1, CV_32SC3, a);
-        UMat u = m.getUMat(ACCESS_READ);
-        EXPECT_NE((void*)NULL, u.u);
+        depth = GET_PARAM(0);
+        cn = GET_PARAM(1);
+        size = GET_PARAM(2);
+        useRoi = GET_PARAM(3);
+        type = CV_MAKE_TYPE(depth, cn);
     }
+};
 
+CORE_TEST_P(UMatTestSizeOperations, copySize)
+{
+    Size s = randomSize(1,300);
+    a = randomMat(size, type, -100, 100);
+    b = randomMat(s, type, -100, 100);
+    a.copyTo(ua);
+    b.copyTo(ub);
+    if(useRoi)
     {
-        Mat m(10, 10, CV_8UC1), ref;
-        for (int y = 0; y < m.rows; ++y)
-        {
-            uchar * const ptr = m.ptr<uchar>(y);
-            for (int x = 0; x < m.cols; ++x)
-                ptr[x] = (uchar)(x + y * 2);
-        }
+        int roi_shift_x = randomInt(0, size.width-1);
+        int roi_shift_y = randomInt(0, size.height-1);
+        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+        ua = UMat(ua,roi);
+
+        roi_shift_x = randomInt(0, s.width-1);
+        roi_shift_y = randomInt(0, s.height-1);
+        roi_size = Size(s.width - roi_shift_x, s.height - roi_shift_y);
+        roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+        ub = UMat(ub, roi);
+    }
+    ua.copySize(ub);
+    ASSERT_EQ(ua.size, ub.size);
+}
 
-        ref = m.clone();
-        Rect r(1, 1, 8, 8);
-        ref(r).setTo(17);
+INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
 
-        {
-            UMat um = m(r).getUMat(ACCESS_WRITE);
-            um.setTo(17);
-        }
+///////////////////////////////////////////////////////////////// UMat operations ////////////////////////////////////////////////////////////////////////////
 
-        double err = norm(m, ref, NORM_INF);
-        if (err > 0)
-        {
-            std::cout << "m: " << std::endl << m << std::endl;
-            std::cout << "ref: " << std::endl << ref << std::endl;
-        }
-        EXPECT_EQ(0., err);
+PARAM_TEST_CASE(UMatTestUMatOperations, int, int, Size, bool)
+{
+    Mat a, b;
+    UMat ua, ub;
+    int type;
+    int depth;
+    int cn;
+    Size size;
+    Size roi_size;
+    bool useRoi;
+    virtual void SetUp()
+    {
+        depth = GET_PARAM(0);
+        cn = GET_PARAM(1);
+        size = GET_PARAM(2);
+        useRoi = GET_PARAM(3);
+        type = CV_MAKE_TYPE(depth, cn);
     }
-}
+};
 
-TEST(UMat, Sync)
+CORE_TEST_P(UMatTestUMatOperations, diag)
 {
-    UMat um(10, 10, CV_8UC1);
-
+    a = randomMat(size, type, -100, 100);
+    a.copyTo(ua);
+    Mat new_diag;
+    if(useRoi)
     {
-        Mat m = um.getMat(ACCESS_WRITE);
-        m.setTo(cv::Scalar::all(17));
+        int roi_shift_x = randomInt(0, size.width-1);
+        int roi_shift_y = randomInt(0, size.height-1);
+        roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
+        Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
+        ua = UMat(ua,roi);
+        a = Mat(a, roi);
     }
-
-    um.setTo(cv::Scalar::all(19));
-
-    EXPECT_EQ(0, cv::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
+    int n = randomInt(0, ua.cols-1);
+    ub = ua.diag(n);
+    b = a.diag(n);
+    EXPECT_MAT_NEAR(b, ub, 0);
+    new_diag = randomMat(Size(ua.rows, 1), type, -100, 100);
+    new_diag.copyTo(ub);
+    ua = cv::UMat::diag(ub);
+    EXPECT_MAT_NEAR(ua.diag(), new_diag.t(), 0);
 }
 
-#define EXPECT_MAT_NEAR(m1, m2) ASSERT_EQ(0, cv::norm(m1, m1, cv::NORM_INF))
-
-TEST(UMat, setOpenCL)
+CORE_TEST_P(UMatTestUMatOperations, dotUMat)
 {
-    // save the current state
-    bool useOCL = ocl::useOpenCL();
-
-    Mat m = (Mat_<uchar>(3,3)<<0,1,2,3,4,5,6,7,8);
-
-    ocl::setUseOpenCL(true);
-    UMat um1;
-    m.copyTo(um1);
-
-    ocl::setUseOpenCL(false);
-    UMat um2;
-    m.copyTo(um2);
-
-    ocl::setUseOpenCL(true);
-    countNonZero(um1);
-    countNonZero(um2);
-
-    um1.copyTo(um2);
-    EXPECT_MAT_NEAR(um1, um2);
-    EXPECT_MAT_NEAR(um1, m);
-    um2.copyTo(um1);
-    EXPECT_MAT_NEAR(um1, m);
-    EXPECT_MAT_NEAR(um1, um2);
-
-    ocl::setUseOpenCL(false);
-    countNonZero(um1);
-    countNonZero(um2);
+    a = randomMat(size, type, -100, 100);
+    b = randomMat(size, type, -100, 100);
+    a.copyTo(ua);
+    b.copyTo(ub);
+    //ASSERT_EQ(ua.dot(ub), a.dot(b)); UMat::dot doesn't compiles
+}
 
-    um1.copyTo(um2);
-    EXPECT_MAT_NEAR(um1, um2);
-    EXPECT_MAT_NEAR(um1, m);
-    um2.copyTo(um1);
-    EXPECT_MAT_NEAR(um1, um2);
-    EXPECT_MAT_NEAR(um1, m);
+INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(UMAT_TEST_DEPTH, UMAT_TEST_CHANNELS, UMAT_TEST_SIZES, Bool() ));
 
-    // reset state to the previous one
-    ocl::setUseOpenCL(useOCL);
-}
+///////////////////////////////////////////////////////////////// OpenCL ////////////////////////////////////////////////////////////////////////////
 
 TEST(UMat, BufferPoolGrowing)
 {
@@ -300,7 +499,7 @@ TEST(UMat, BufferPoolGrowing)
     const int ITERATIONS = 200;
 #endif
     const Size sz(1920, 1080);
-    BufferPoolController* c = ocl::getOpenCLAllocator()->getBufferPoolController();
+    BufferPoolController* c = cv::ocl::getOpenCLAllocator()->getBufferPoolController();
     if (c)
     {
         size_t oldMaxReservedSize = c->getMaxReservedSize();
@@ -319,3 +518,45 @@ TEST(UMat, BufferPoolGrowing)
         std::cout << "Skipped, no OpenCL" << std::endl;
     }
 }
+
+TEST(UMat, setOpenCL)
+{
+    // save the current state
+    bool useOCL = cv::ocl::useOpenCL();
+
+    Mat m = (Mat_<uchar>(3,3)<<0,1,2,3,4,5,6,7,8);
+
+    cv::ocl::setUseOpenCL(true);
+    UMat um1;
+    m.copyTo(um1);
+
+    cv::ocl::setUseOpenCL(false);
+    UMat um2;
+    m.copyTo(um2);
+
+    cv::ocl::setUseOpenCL(true);
+    countNonZero(um1);
+    countNonZero(um2);
+
+    um1.copyTo(um2);
+    EXPECT_MAT_NEAR(um1, um2, 0);
+    EXPECT_MAT_NEAR(um1, m, 0);
+    um2.copyTo(um1);
+    EXPECT_MAT_NEAR(um1, m, 0);
+    EXPECT_MAT_NEAR(um1, um2, 0);
+
+    cv::ocl::setUseOpenCL(false);
+    countNonZero(um1);
+    countNonZero(um2);
+
+    um1.copyTo(um2);
+    EXPECT_MAT_NEAR(um1, um2, 0);
+    EXPECT_MAT_NEAR(um1, m, 0);
+    um2.copyTo(um1);
+    EXPECT_MAT_NEAR(um1, um2, 0);
+    EXPECT_MAT_NEAR(um1, m, 0);
+
+    // reset state to the previous one
+    cv::ocl::setUseOpenCL(useOCL);
+}
+
-- 
2.7.4