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     41 
     42 #ifndef __OPENCV_TS_OCL_TEST_HPP__
     43 #define __OPENCV_TS_OCL_TEST_HPP__
     44 
     45 #include "opencv2/opencv_modules.hpp"
     46 
     47 #include "opencv2/ts.hpp"
     48 
     49 #include "opencv2/imgcodecs.hpp"
     50 #include "opencv2/videoio.hpp"
     51 #include "opencv2/highgui.hpp"
     52 #include "opencv2/imgproc.hpp"
     53 #include "opencv2/imgproc/types_c.h"
     54 #include "opencv2/core/ocl.hpp"
     55 
     56 namespace cvtest {
     57 namespace ocl {
     58 
     59 using namespace cv;
     60 using namespace testing;
     61 
     62 inline std::vector<UMat> ToUMat(const std::vector<Mat>& src)
     63 {
     64     std::vector<UMat> dst;
     65     dst.resize(src.size());
     66     for (size_t i = 0; i < src.size(); ++i)
     67     {
     68         src[i].copyTo(dst[i]);
     69     }
     70     return dst;
     71 }
     72 
     73 inline UMat ToUMat(const Mat& src)
     74 {
     75     UMat dst;
     76     src.copyTo(dst);
     77     return dst;
     78 }
     79 
     80 inline UMat ToUMat(InputArray src)
     81 {
     82     UMat dst;
     83     src.getMat().copyTo(dst);
     84     return dst;
     85 }
     86 
     87 extern int test_loop_times;
     88 
     89 #define MAX_VALUE 357
     90 
     91 #define EXPECT_MAT_NORM(mat, eps) \
     92 do \
     93 { \
     94     EXPECT_LE(TestUtils::checkNorm1(mat), eps) \
     95 } while ((void)0, 0)
     96 
     97 #define EXPECT_MAT_NEAR(mat1, mat2, eps) \
     98 do \
     99 { \
    100     ASSERT_EQ(mat1.type(), mat2.type()); \
    101     ASSERT_EQ(mat1.size(), mat2.size()); \
    102     EXPECT_LE(TestUtils::checkNorm2(mat1, mat2), eps) \
    103         << "Size: " << mat1.size() << std::endl; \
    104 } while ((void)0, 0)
    105 
    106 #define EXPECT_MAT_NEAR_RELATIVE(mat1, mat2, eps) \
    107 do \
    108 { \
    109     ASSERT_EQ(mat1.type(), mat2.type()); \
    110     ASSERT_EQ(mat1.size(), mat2.size()); \
    111     EXPECT_LE(TestUtils::checkNormRelative(mat1, mat2), eps) \
    112         << "Size: " << mat1.size() << std::endl; \
    113 } while ((void)0, 0)
    114 
    115 #define EXPECT_MAT_N_DIFF(mat1, mat2, num) \
    116 do \
    117 { \
    118     ASSERT_EQ(mat1.type(), mat2.type()); \
    119     ASSERT_EQ(mat1.size(), mat2.size()); \
    120     Mat diff; \
    121     absdiff(mat1, mat2, diff); \
    122     EXPECT_LE(countNonZero(diff.reshape(1)), num) \
    123     << "Size: " << mat1.size() << std::endl; \
    124 } while ((void)0, 0)
    125 
    126 #define OCL_EXPECT_MATS_NEAR(name, eps) \
    127 do \
    128 { \
    129     ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
    130     ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
    131     EXPECT_LE(TestUtils::checkNorm2(name ## _roi, u ## name ## _roi), eps) \
    132         << "Size: " << name ## _roi.size() << std::endl; \
    133     Point _offset; \
    134     Size _wholeSize; \
    135     u ## name ## _roi.locateROI(_wholeSize, _offset); \
    136     Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
    137     _mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
    138     ASSERT_EQ(name.type(), u ## name.type()); \
    139     ASSERT_EQ(name.size(), u ## name.size()); \
    140     EXPECT_LE(TestUtils::checkNorm2(name, u ## name, _mask), eps) \
    141         << "Size: " << name ## _roi.size() << std::endl; \
    142 } while ((void)0, 0)
    143 
    144 #define OCL_EXPECT_MATS_NEAR_RELATIVE(name, eps) \
    145 do \
    146 { \
    147     ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
    148     ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
    149     EXPECT_LE(TestUtils::checkNormRelative(name ## _roi, u ## name ## _roi), eps) \
    150         << "Size: " << name ## _roi.size() << std::endl; \
    151     Point _offset; \
    152     Size _wholeSize; \
    153     name ## _roi.locateROI(_wholeSize, _offset); \
    154     Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
    155     _mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
    156     ASSERT_EQ(name.type(), u ## name.type()); \
    157     ASSERT_EQ(name.size(), u ## name.size()); \
    158     EXPECT_LE(TestUtils::checkNormRelative(name, u ## name, _mask), eps) \
    159         << "Size: " << name ## _roi.size() << std::endl; \
    160 } while ((void)0, 0)
    161 
    162 //for sparse matrix
    163 #define OCL_EXPECT_MATS_NEAR_RELATIVE_SPARSE(name, eps) \
    164 do \
    165 { \
    166     ASSERT_EQ(name ## _roi.type(), u ## name ## _roi.type()); \
    167     ASSERT_EQ(name ## _roi.size(), u ## name ## _roi.size()); \
    168     EXPECT_LE(TestUtils::checkNormRelativeSparse(name ## _roi, u ## name ## _roi), eps) \
    169         << "Size: " << name ## _roi.size() << std::endl; \
    170     Point _offset; \
    171     Size _wholeSize; \
    172     name ## _roi.locateROI(_wholeSize, _offset); \
    173     Mat _mask(name.size(), CV_8UC1, Scalar::all(255)); \
    174     _mask(Rect(_offset, name ## _roi.size())).setTo(Scalar::all(0)); \
    175     ASSERT_EQ(name.type(), u ## name.type()); \
    176     ASSERT_EQ(name.size(), u ## name.size()); \
    177     EXPECT_LE(TestUtils::checkNormRelativeSparse(name, u ## name, _mask), eps) \
    178         << "Size: " << name ## _roi.size() << std::endl; \
    179 } while ((void)0, 0)
    180 
    181 #define EXPECT_MAT_SIMILAR(mat1, mat2, eps) \
    182 do \
    183 { \
    184     ASSERT_EQ(mat1.type(), mat2.type()); \
    185     ASSERT_EQ(mat1.size(), mat2.size()); \
    186     EXPECT_LE(checkSimilarity(mat1, mat2), eps) \
    187         << "Size: " << mat1.size() << std::endl; \
    188 } while ((void)0, 0)
    189 
    190 using perf::MatDepth;
    191 using perf::MatType;
    192 
    193 #define OCL_RNG_SEED 123456
    194 
    195 struct CV_EXPORTS TestUtils
    196 {
    197     cv::RNG rng;
    198 
    199     TestUtils()
    200     {
    201         rng = cv::RNG(OCL_RNG_SEED);
    202     }
    203 
    204     int randomInt(int minVal, int maxVal)
    205     {
    206         return rng.uniform(minVal, maxVal);
    207     }
    208 
    209     double randomDouble(double minVal, double maxVal)
    210     {
    211         return rng.uniform(minVal, maxVal);
    212     }
    213 
    214     double randomDoubleLog(double minVal, double maxVal)
    215     {
    216         double logMin = log((double)minVal + 1);
    217         double logMax = log((double)maxVal + 1);
    218         double pow = rng.uniform(logMin, logMax);
    219         double v = exp(pow) - 1;
    220         CV_Assert(v >= minVal && (v < maxVal || (v == minVal && v == maxVal)));
    221         return v;
    222     }
    223 
    224     Size randomSize(int minVal, int maxVal)
    225     {
    226 #if 1
    227         return cv::Size((int)randomDoubleLog(minVal, maxVal), (int)randomDoubleLog(minVal, maxVal));
    228 #else
    229         return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
    230 #endif
    231     }
    232 
    233     Size randomSize(int minValX, int maxValX, int minValY, int maxValY)
    234     {
    235 #if 1
    236         return cv::Size((int)randomDoubleLog(minValX, maxValX), (int)randomDoubleLog(minValY, maxValY));
    237 #else
    238         return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
    239 #endif
    240     }
    241 
    242     Scalar randomScalar(double minVal, double maxVal)
    243     {
    244         return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
    245     }
    246 
    247     Mat randomMat(Size size, int type, double minVal, double maxVal, bool useRoi = false)
    248     {
    249         RNG dataRng(rng.next());
    250         return cvtest::randomMat(dataRng, size, type, minVal, maxVal, useRoi);
    251     }
    252 
    253     struct Border
    254     {
    255         int top, bot, lef, rig;
    256     };
    257 
    258     Border randomBorder(int minValue = 0, int maxValue = MAX_VALUE)
    259     {
    260         Border border = {
    261                 (int)randomDoubleLog(minValue, maxValue),
    262                 (int)randomDoubleLog(minValue, maxValue),
    263                 (int)randomDoubleLog(minValue, maxValue),
    264                 (int)randomDoubleLog(minValue, maxValue)
    265         };
    266         return border;
    267     }
    268 
    269     void randomSubMat(Mat& whole, Mat& subMat, const Size& roiSize, const Border& border, int type, double minVal, double maxVal)
    270     {
    271         Size wholeSize = Size(roiSize.width + border.lef + border.rig, roiSize.height + border.top + border.bot);
    272         whole = randomMat(wholeSize, type, minVal, maxVal, false);
    273         subMat = whole(Rect(border.lef, border.top, roiSize.width, roiSize.height));
    274     }
    275 
    276     // If the two vectors are not equal, it will return the difference in vector size
    277     // Else it will return (total diff of each 1 and 2 rects covered pixels)/(total 1 rects covered pixels)
    278     // The smaller, the better matched
    279     static double checkRectSimilarity(const cv::Size & sz, std::vector<cv::Rect>& ob1, std::vector<cv::Rect>& ob2);
    280 
    281     //! read image from testdata folder.
    282     static cv::Mat readImage(const String &fileName, int flags = cv::IMREAD_COLOR);
    283     static cv::Mat readImageType(const String &fname, int type);
    284 
    285     static double checkNorm1(InputArray m, InputArray mask = noArray());
    286     static double checkNorm2(InputArray m1, InputArray m2, InputArray mask = noArray());
    287     static double checkSimilarity(InputArray m1, InputArray m2);
    288     static void showDiff(InputArray _src, InputArray _gold, InputArray _actual, double eps, bool alwaysShow);
    289 
    290     static inline double checkNormRelative(InputArray m1, InputArray m2, InputArray mask = noArray())
    291     {
    292         return cvtest::norm(m1.getMat(), m2.getMat(), cv::NORM_INF, mask) /
    293                 std::max((double)std::numeric_limits<float>::epsilon(),
    294                          (double)std::max(cvtest::norm(m1.getMat(), cv::NORM_INF), cvtest::norm(m2.getMat(), cv::NORM_INF)));
    295     }
    296 
    297     static inline double checkNormRelativeSparse(InputArray m1, InputArray m2, InputArray mask = noArray())
    298     {
    299         double norm_inf = cvtest::norm(m1.getMat(), m2.getMat(), cv::NORM_INF, mask);
    300         double norm_rel = norm_inf /
    301                 std::max((double)std::numeric_limits<float>::epsilon(),
    302                          (double)std::max(cvtest::norm(m1.getMat(), cv::NORM_INF), cvtest::norm(m2.getMat(), cv::NORM_INF)));
    303         return std::min(norm_inf, norm_rel);
    304     }
    305 
    306 };
    307 
    308 #define TEST_DECLARE_INPUT_PARAMETER(name) Mat name, name ## _roi; UMat u ## name, u ## name ## _roi
    309 #define TEST_DECLARE_OUTPUT_PARAMETER(name) TEST_DECLARE_INPUT_PARAMETER(name)
    310 
    311 #define UMAT_UPLOAD_INPUT_PARAMETER(name) \
    312 do \
    313 { \
    314     name.copyTo(u ## name); \
    315     Size _wholeSize; Point ofs; name ## _roi.locateROI(_wholeSize, ofs); \
    316     u ## name ## _roi = u ## name(Rect(ofs.x, ofs.y, name ## _roi.size().width, name ## _roi.size().height)); \
    317 } while ((void)0, 0)
    318 
    319 #define UMAT_UPLOAD_OUTPUT_PARAMETER(name) UMAT_UPLOAD_INPUT_PARAMETER(name)
    320 
    321 template <typename T>
    322 struct CV_EXPORTS TSTestWithParam : public TestUtils, public ::testing::TestWithParam<T>
    323 {
    324 
    325 };
    326 
    327 #define PARAM_TEST_CASE(name, ...) struct name : public TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
    328 
    329 #define GET_PARAM(k) std::tr1::get< k >(GetParam())
    330 
    331 #ifndef IMPLEMENT_PARAM_CLASS
    332 #define IMPLEMENT_PARAM_CLASS(name, type) \
    333     class name \
    334     { \
    335     public: \
    336         name ( type arg = type ()) : val_(arg) {} \
    337         operator type () const {return val_;} \
    338     private: \
    339         type val_; \
    340     }; \
    341     inline void PrintTo( name param, std::ostream* os) \
    342     { \
    343         *os << #name <<  "(" << testing::PrintToString(static_cast< type >(param)) << ")"; \
    344     }
    345 
    346 IMPLEMENT_PARAM_CLASS(Channels, int)
    347 #endif // IMPLEMENT_PARAM_CLASS
    348 
    349 #define OCL_TEST_P TEST_P
    350 #define OCL_TEST_F(name, ...) typedef name OCL_##name; TEST_F(OCL_##name, __VA_ARGS__)
    351 #define OCL_TEST(name, ...) TEST(OCL_##name, __VA_ARGS__)
    352 
    353 #define OCL_OFF(fn) cv::ocl::setUseOpenCL(false); fn
    354 #define OCL_ON(fn) cv::ocl::setUseOpenCL(true); fn
    355 
    356 #define OCL_ALL_DEPTHS Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F)
    357 #define OCL_ALL_CHANNELS Values(1, 2, 3, 4)
    358 
    359 CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA)
    360 CV_ENUM(ThreshOp, THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV)
    361 CV_ENUM(BorderType, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT, BORDER_WRAP, BORDER_REFLECT_101)
    362 
    363 #define OCL_INSTANTIATE_TEST_CASE_P(prefix, test_case_name, generator) \
    364     INSTANTIATE_TEST_CASE_P(OCL_ ## prefix, test_case_name, generator)
    365 
    366 } } // namespace cvtest::ocl
    367 
    368 #endif // __OPENCV_TS_OCL_TEST_HPP__
    369