Merge remote-tracking branch 'upstream/2.4' into merge-2.4
* #1538 from StevenPuttemans:bugfix_3283 * #1545 from alalek:ocl_test_fix_rng * #1551 from alalek:cmake_install_win * #1570 from ilya-lavrenov:ipp_warn_fix * #1573 from alalek:perf_simple_strategy * #1574 from alalek:svm_workaround * #1576 from alalek:ocl_fix_cl_double * #1577 from ilya-lavrenov:ocl_setto_opencl12 * #1578 from asmorkalov:android_fd_cp_fix * #1579 from ilya-lavrenov:ocl_norm * #1582 from sperrholz:ocl-arithm-additions * #1586 from ilya-lavrenov:ocl_setto_win_fix * #1589 from ilya-lavrenov:pr1582_fix * #1591 from alalek:ocl_remove_cl_hpp_h * #1592 from alalek:ocl_program_cache_update * #1593 from ilya-lavrenov:ocl_war_on_double * #1594 from ilya-lavrenov:ocl_perf * #1595 from alalek:cl_code_cleanup * #1596 from alalek:test_fix_run_py * #1597 from alalek:ocl_fix_cleanup * #1598 from alalek:ocl_fix_build_mac * #1599 from ilya-lavrenov:ocl_mac_kernel_warnings * #1601 from ilya-lavrenov:ocl_fix_tvl1_and_sparse * #1602 from alalek:ocl_test_dump_info * #1603 from ilya-lavrenov:ocl_disable_svm_noblas * #1605 from alalek:ocl_fixes * #1606 from ilya-lavrenov:ocl_imgproc * #1607 from ilya-lavrenov:ocl_fft_cleanup * #1608 from alalek:fix_warn_upd_haar * #1609 from ilya-lavrenov:ocl_some_optimization * #1610 from alalek:ocl_fix_perf_kalman * #1612 from alalek:ocl_fix_string_info * #1614 from ilya-lavrenov:ocl_svm_misprint * #1616 from ilya-lavrenov:ocl_cvtColor * #1617 from ilya-lavrenov:ocl_info * #1622 from a0byte:2.4 * #1625 from ilya-lavrenov:to_string Conflicts: cmake/OpenCVConfig.cmake cmake/OpenCVDetectPython.cmake cmake/OpenCVGenConfig.cmake modules/core/CMakeLists.txt modules/nonfree/src/surf.ocl.cpp modules/ocl/include/opencv2/ocl/ocl.hpp modules/ocl/include/opencv2/ocl/private/util.hpp modules/ocl/perf/main.cpp modules/ocl/src/arithm.cpp modules/ocl/src/cl_operations.cpp modules/ocl/src/cl_programcache.cpp modules/ocl/src/color.cpp modules/ocl/src/fft.cpp modules/ocl/src/filtering.cpp modules/ocl/src/gemm.cpp modules/ocl/src/haar.cpp modules/ocl/src/imgproc.cpp modules/ocl/src/matrix_operations.cpp modules/ocl/src/pyrlk.cpp modules/ocl/src/split_merge.cpp modules/ocl/src/svm.cpp modules/ocl/test/main.cpp modules/ocl/test/test_fft.cpp modules/ocl/test/test_moments.cpp modules/ocl/test/test_objdetect.cpp modules/ocl/test/test_optflow.cpp modules/ocl/test/utility.hpp modules/python/CMakeLists.txt modules/ts/include/opencv2/ts.hpp modules/ts/src/ts_perf.cpp samples/android/face-detection/jni/DetectionBasedTracker_jni.cpp
This commit is contained in:
Alexander Alekhin
@@ -52,16 +52,12 @@
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#define MIN_VALUE 171
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#define MAX_VALUE 357
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//#define RANDOMROI
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int randomInt(int minVal, int maxVal);
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double randomDouble(double minVal, double maxVal);
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//std::string generateVarList(int first,...);
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std::string generateVarList(int &p1, int &p2);
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cv::Size randomSize(int minVal, int maxVal);
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cv::Scalar randomScalar(double minVal, double maxVal);
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cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal = 255.0);
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namespace cvtest {
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void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
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//void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
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cv::ocl::oclMat createMat_ocl(cv::RNG& rng, Size size, int type, bool useRoi);
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cv::ocl::oclMat loadMat_ocl(cv::RNG& rng, const Mat& m, bool useRoi);
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// This function test if gpu_rst matches cpu_rst.
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// If the two vectors are not equal, it will return the difference in vector size
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@@ -78,10 +74,6 @@ double checkNorm(const cv::Mat &m);
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double checkNorm(const cv::Mat &m1, const cv::Mat &m2);
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double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
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//oclMat create
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cv::ocl::oclMat createMat_ocl(cv::Size size, int type, bool useRoi = false);
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cv::ocl::oclMat loadMat_ocl(const cv::Mat& m, bool useRoi = false);
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#define EXPECT_MAT_NORM(mat, eps) \
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{ \
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EXPECT_LE(checkNorm(cv::Mat(mat)), eps) \
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@@ -101,13 +93,6 @@ cv::ocl::oclMat loadMat_ocl(const cv::Mat& m, bool useRoi = false);
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EXPECT_LE(checkSimilarity(cv::Mat(mat1), cv::Mat(mat2)), eps); \
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}
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namespace cv
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{
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namespace ocl
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{
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// void PrintTo(const DeviceInfo& info, std::ostream* os);
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}
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}
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using perf::MatDepth;
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using perf::MatType;
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@@ -134,80 +119,106 @@ private:
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void PrintTo(const Inverse &useRoi, std::ostream *os);
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enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
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CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
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#define OCL_RNG_SEED 123456
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CV_ENUM(CmpCode, CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE)
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CV_ENUM(NormCode, NORM_INF, NORM_L1, NORM_L2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX)
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CV_ENUM(ReduceOp, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN)
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CV_ENUM(MorphOp, MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT)
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CV_ENUM(ThreshOp, THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV)
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CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC)
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CV_ENUM(Border, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
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CV_ENUM(TemplateMethod, TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED)
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template <typename T>
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struct TSTestWithParam : public ::testing::TestWithParam<T>
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{
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cv::RNG rng;
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CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T);
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CV_FLAGS(WarpFlags, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
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CV_FLAGS(DftFlags, DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT)
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TSTestWithParam()
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{
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rng = cv::RNG(OCL_RNG_SEED);
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}
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void run_perf_test();
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int randomInt(int minVal, int maxVal)
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{
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return rng.uniform(minVal, maxVal);
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}
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#define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > >
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double randomDouble(double minVal, double maxVal)
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{
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return rng.uniform(minVal, maxVal);
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}
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double randomDoubleLog(double minVal, double maxVal)
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{
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double logMin = log((double)minVal + 1);
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double logMax = log((double)maxVal + 1);
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double pow = rng.uniform(logMin, logMax);
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double v = exp(pow) - 1;
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CV_Assert(v >= minVal && (v < maxVal || (v == minVal && v == maxVal)));
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return v;
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}
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Size randomSize(int minVal, int maxVal)
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{
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#if 1
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return cv::Size((int)randomDoubleLog(minVal, maxVal), (int)randomDoubleLog(minVal, maxVal));
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#else
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return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
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#endif
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}
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Size randomSize(int minValX, int maxValX, int minValY, int maxValY)
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{
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#if 1
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return cv::Size(randomDoubleLog(minValX, maxValX), randomDoubleLog(minValY, maxValY));
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#else
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return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal));
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#endif
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}
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Scalar randomScalar(double minVal, double maxVal)
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{
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return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal));
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}
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Mat randomMat(Size size, int type, double minVal, double maxVal, bool useRoi = false)
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{
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RNG dataRng(rng.next());
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return cvtest::randomMat(dataRng, size, type, minVal, maxVal, useRoi);
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}
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struct Border
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{
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int top, bot, lef, rig;
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};
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Border randomBorder(int minValue = 0, int maxValue = MAX_VALUE)
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{
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Border border = {
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(int)randomDoubleLog(minValue, maxValue),
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(int)randomDoubleLog(minValue, maxValue),
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(int)randomDoubleLog(minValue, maxValue),
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(int)randomDoubleLog(minValue, maxValue)
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};
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return border;
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}
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void randomSubMat(Mat& whole, Mat& subMat, const Size& roiSize, const Border& border, int type, double minVal, double maxVal)
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{
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Size wholeSize = Size(roiSize.width + border.lef + border.rig, roiSize.height + border.top + border.bot);
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whole = randomMat(wholeSize, type, minVal, maxVal, false);
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subMat = whole(Rect(border.lef, border.top, roiSize.width, roiSize.height));
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}
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void generateOclMat(cv::ocl::oclMat& whole, cv::ocl::oclMat& subMat, const Mat& wholeMat, const Size& roiSize, const Border& border)
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{
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whole = wholeMat;
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subMat = whole(Rect(border.lef, border.top, roiSize.width, roiSize.height));
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}
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};
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#define PARAM_TEST_CASE(name, ...) struct name : public TSTestWithParam< std::tr1::tuple< __VA_ARGS__ > >
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#define GET_PARAM(k) std::tr1::get< k >(GetParam())
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#define ALL_DEVICES testing::ValuesIn(devices())
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#define DEVICES(feature) testing::ValuesIn(devices(feature))
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#define ALL_TYPES testing::ValuesIn(all_types())
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#define TYPES(depth_start, depth_end, cn_start, cn_end) testing::ValuesIn(types(depth_start, depth_end, cn_start, cn_end))
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#define DIFFERENT_SIZES testing::Values(cv::Size(128, 128), cv::Size(113, 113), cv::Size(1300, 1300))
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#define DIRECT_INVERSE testing::Values(Inverse(false), Inverse(true))
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#ifndef ALL_DEPTH
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#define ALL_DEPTH testing::Values(MatDepth(CV_8U), MatDepth(CV_8S), MatDepth(CV_16U), MatDepth(CV_16S), MatDepth(CV_32S), MatDepth(CV_32F), MatDepth(CV_64F))
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#endif
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#define REPEAT 1000
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#define COUNT_U 0 // count the uploading execution time for ocl mat structures
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#define COUNT_D 0
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// the following macro section tests the target function (kernel) performance
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// upload is the code snippet for converting cv::mat to cv::ocl::oclMat
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// downloading is the code snippet for converting cv::ocl::oclMat back to cv::mat
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// change COUNT_U and COUNT_D to take downloading and uploading time into account
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#define P_TEST_FULL( upload, kernel_call, download ) \
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{ \
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std::cout<< "\n" #kernel_call "\n----------------------"; \
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{upload;} \
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R_TEST( kernel_call, 2 ); \
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double t = (double)cvGetTickCount(); \
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R_T( { \
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if( COUNT_U ) {upload;} \
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kernel_call; \
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if( COUNT_D ) {download;} \
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} ); \
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t = (double)cvGetTickCount() - t; \
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std::cout << "runtime is " << t/((double)cvGetTickFrequency()* 1000.) << "ms" << std::endl; \
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}
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#define R_T2( test ) \
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{ \
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std::cout<< "\n" #test "\n----------------------"; \
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R_TEST( test, 15 ) \
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clock_t st = clock(); \
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R_T( test ) \
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std::cout<< clock() - st << "ms\n"; \
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}
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#define R_T( test ) \
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R_TEST( test, REPEAT )
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#define R_TEST( test, repeat ) \
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try{ \
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for( int i = 0; i < repeat; i ++ ) { test; } \
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} catch( ... ) { std::cout << "||||| Exception catched! |||||\n"; return; }
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//////// Utility
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#define IMAGE_CHANNELS testing::Values(Channels(1), Channels(3), Channels(4))
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#ifndef IMPLEMENT_PARAM_CLASS
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#define IMPLEMENT_PARAM_CLASS(name, type) \
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@@ -227,4 +238,70 @@ void run_perf_test();
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IMPLEMENT_PARAM_CLASS(Channels, int)
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#endif // IMPLEMENT_PARAM_CLASS
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} // namespace cvtest
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enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
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CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
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CV_ENUM(CmpCode, CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE)
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CV_ENUM(NormCode, NORM_INF, NORM_L1, NORM_L2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX)
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CV_ENUM(ReduceOp, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN)
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CV_ENUM(MorphOp, MORPH_OPEN, MORPH_CLOSE, MORPH_GRADIENT, MORPH_TOPHAT, MORPH_BLACKHAT)
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CV_ENUM(ThreshOp, THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV)
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CV_ENUM(Interpolation, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC)
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CV_ENUM(Border, BORDER_REFLECT101, BORDER_REPLICATE, BORDER_CONSTANT, BORDER_REFLECT, BORDER_WRAP)
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CV_ENUM(TemplateMethod, TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED)
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CV_FLAGS(GemmFlags, GEMM_1_T, GEMM_2_T, GEMM_3_T);
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CV_FLAGS(WarpFlags, INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, WARP_INVERSE_MAP)
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CV_FLAGS(DftFlags, DFT_INVERSE, DFT_SCALE, DFT_ROWS, DFT_COMPLEX_OUTPUT, DFT_REAL_OUTPUT)
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# define OCL_TEST_P(test_case_name, test_name) \
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class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) : \
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public test_case_name { \
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public: \
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() { } \
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virtual void TestBody(); \
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void OCLTestBody(); \
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private: \
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static int AddToRegistry() \
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{ \
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::testing::UnitTest::GetInstance()->parameterized_test_registry(). \
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GetTestCasePatternHolder<test_case_name>(\
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#test_case_name, __FILE__, __LINE__)->AddTestPattern(\
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#test_case_name, \
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#test_name, \
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new ::testing::internal::TestMetaFactory< \
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)>()); \
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return 0; \
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} \
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\
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static int gtest_registering_dummy_; \
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GTEST_DISALLOW_COPY_AND_ASSIGN_(\
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \
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}; \
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\
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int GTEST_TEST_CLASS_NAME_(test_case_name, \
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test_name)::gtest_registering_dummy_ = \
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GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \
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\
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void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() \
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{ \
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try \
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{ \
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OCLTestBody(); \
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} \
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catch (const cv::Exception & ex) \
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{ \
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if (ex.code == cv::Error::OpenCLDoubleNotSupported)\
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std::cout << "Test skipped (selected device does not support double)" << std::endl; \
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else if (ex.code == cv::Error::OpenCLNoAMDBlasFft) \
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std::cout << "Test skipped (AMD Blas / Fft libraries are not available)" << std::endl; \
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else \
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throw; \
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} \
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} \
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\
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void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::OCLTestBody()
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#endif // __OPENCV_TEST_UTILITY_HPP__
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