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tests
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@ -60,15 +60,14 @@ OCL_PERF_TEST_P(LUTFixture, LUT,
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// getting params
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// getting params
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const Size_MatType_t params = GetParam();
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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const int type = get<1>(params), cn = CV_MAT_CN(type);
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// creating src data
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// creating src data
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Mat src(srcSize, CV_8UC1), lut(1, 256, type);
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Mat src(srcSize, CV_8UC(cn)), lut(1, 256, type);
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int dstType = CV_MAKETYPE(lut.depth(), src.channels());
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int dstType = CV_MAKETYPE(lut.depth(), src.channels());
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Mat dst(srcSize, dstType);
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Mat dst(srcSize, dstType);
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randu(lut, 0, 2);
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declare.in(src, lut, WARMUP_RNG).out(dst);
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declare.in(src, WARMUP_RNG).in(lut).out(dst);
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// select implementation
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// select implementation
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if (RUN_OCL_IMPL)
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if (RUN_OCL_IMPL)
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@ -564,158 +563,6 @@ OCL_PERF_TEST_P(FlipFixture, Flip,
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OCL_PERF_ELSE
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OCL_PERF_ELSE
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}
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}
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///////////// MinMax ////////////////////////
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typedef Size_MatType MinMaxFixture;
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PERF_TEST_P(MinMaxFixture, MinMax,
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::testing::Combine(OCL_TYPICAL_MAT_SIZES,
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OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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Mat src(srcSize, type);
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declare.in(src, WARMUP_RNG);
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double min_val = std::numeric_limits<double>::max(),
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max_val = std::numeric_limits<double>::min();
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc(src);
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OCL_TEST_CYCLE() cv::ocl::minMax(oclSrc, &min_val, &max_val);
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ASSERT_GE(max_val, min_val);
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SANITY_CHECK(min_val);
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SANITY_CHECK(max_val);
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}
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else if (RUN_PLAIN_IMPL)
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{
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Point min_loc, max_loc;
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TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
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ASSERT_GE(max_val, min_val);
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SANITY_CHECK(min_val);
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SANITY_CHECK(max_val);
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}
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else
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OCL_PERF_ELSE
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}
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///////////// MinMaxLoc ////////////////////////
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typedef Size_MatType MinMaxLocFixture;
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OCL_PERF_TEST_P(MinMaxLocFixture, MinMaxLoc,
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::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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Mat src(srcSize, type);
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randu(src, 0, 1);
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declare.in(src);
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double min_val = 0.0, max_val = 0.0;
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Point min_loc, max_loc;
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc(src);
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OCL_TEST_CYCLE() cv::ocl::minMaxLoc(oclSrc, &min_val, &max_val, &min_loc, &max_loc);
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ASSERT_GE(max_val, min_val);
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SANITY_CHECK(min_val);
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SANITY_CHECK(max_val);
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}
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else if (RUN_PLAIN_IMPL)
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{
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TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
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ASSERT_GE(max_val, min_val);
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SANITY_CHECK(min_val);
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SANITY_CHECK(max_val);
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}
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else
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OCL_PERF_ELSE
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}
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///////////// Sum ////////////////////////
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typedef Size_MatType SumFixture;
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OCL_PERF_TEST_P(SumFixture, Sum,
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::testing::Combine(OCL_TEST_SIZES,
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OCL_TEST_TYPES))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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Mat src(srcSize, type);
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Scalar result;
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randu(src, 0, 60);
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declare.in(src);
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc(src);
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OCL_TEST_CYCLE() result = cv::ocl::sum(oclSrc);
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SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
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}
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else if (RUN_PLAIN_IMPL)
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{
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TEST_CYCLE() result = cv::sum(src);
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SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
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}
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else
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OCL_PERF_ELSE
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}
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///////////// countNonZero ////////////////////////
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typedef Size_MatType CountNonZeroFixture;
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OCL_PERF_TEST_P(CountNonZeroFixture, CountNonZero,
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::testing::Combine(OCL_TEST_SIZES,
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OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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Mat src(srcSize, type);
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int result = 0;
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randu(src, 0, 256);
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declare.in(src);
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc(src);
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OCL_TEST_CYCLE() result = cv::ocl::countNonZero(oclSrc);
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SANITY_CHECK(result);
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}
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else if (RUN_PLAIN_IMPL)
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{
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TEST_CYCLE() result = cv::countNonZero(src);
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SANITY_CHECK(result);
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}
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else
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OCL_PERF_ELSE
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}
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///////////// Phase ////////////////////////
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///////////// Phase ////////////////////////
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typedef Size_MatType PhaseFixture;
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typedef Size_MatType PhaseFixture;
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@ -895,6 +742,41 @@ OCL_PERF_TEST_P(BitwiseNotFixture, Bitwise_not,
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OCL_PERF_ELSE
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OCL_PERF_ELSE
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}
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}
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///////////// SetIdentity ////////////////////////
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typedef Size_MatType SetIdentityFixture;
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OCL_PERF_TEST_P(SetIdentityFixture, SetIdentity,
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::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
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{
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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Mat src(srcSize, type);
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Scalar s = Scalar::all(17);
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declare.in(src, WARMUP_RNG).out(src);
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc(src);
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OCL_TEST_CYCLE() cv::ocl::setIdentity(oclSrc, s);
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oclSrc.download(src);
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SANITY_CHECK(src);
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}
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else if (RUN_PLAIN_IMPL)
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{
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TEST_CYCLE() cv::setIdentity(src, s);
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SANITY_CHECK(src);
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}
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else
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OCL_PERF_ELSE
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}
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///////////// compare////////////////////////
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///////////// compare////////////////////////
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CV_ENUM(CmpCode, CMP_LT, CMP_LE, CMP_EQ, CMP_NE, CMP_GE, CMP_GT)
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CV_ENUM(CmpCode, CMP_LT, CMP_LE, CMP_EQ, CMP_NE, CMP_GE, CMP_GT)
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@ -46,17 +46,22 @@
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#include "perf_precomp.hpp"
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#include "perf_precomp.hpp"
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using namespace perf;
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using namespace perf;
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using std::tr1::get;
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//////////////////// BruteForceMatch /////////////////
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//////////////////// BruteForceMatch /////////////////
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typedef TestBaseWithParam<Size> BruteForceMatcherFixture;
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typedef Size_MatType BruteForceMatcherFixture;
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OCL_PERF_TEST_P(BruteForceMatcherFixture, Match, OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3))
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OCL_PERF_TEST_P(BruteForceMatcherFixture, Match,
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::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
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OCL_PERF_ENUM(MatType(CV_32FC1))))
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{
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{
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const Size srcSize = GetParam();
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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vector<DMatch> matches;
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vector<DMatch> matches;
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Mat query(srcSize, CV_32FC1), train(srcSize, CV_32FC1);
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Mat query(srcSize, type), train(srcSize, type);
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declare.in(query, train);
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declare.in(query, train);
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randu(query, 0.0f, 1.0f);
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randu(query, 0.0f, 1.0f);
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randu(train, 0.0f, 1.0f);
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randu(train, 0.0f, 1.0f);
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@ -82,12 +87,16 @@ OCL_PERF_TEST_P(BruteForceMatcherFixture, Match, OCL_PERF_ENUM(OCL_SIZE_1, OCL_S
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OCL_PERF_ELSE
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OCL_PERF_ELSE
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}
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}
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OCL_PERF_TEST_P(BruteForceMatcherFixture, KnnMatch, OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3))
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OCL_PERF_TEST_P(BruteForceMatcherFixture, KnnMatch,
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::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
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OCL_PERF_ENUM(MatType(CV_32FC1))))
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{
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{
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const Size srcSize = GetParam();
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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vector<vector<DMatch> > matches(2);
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vector<vector<DMatch> > matches(2);
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Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
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Mat query(srcSize, type), train(srcSize, type);
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randu(query, 0.0f, 1.0f);
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randu(query, 0.0f, 1.0f);
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randu(train, 0.0f, 1.0f);
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randu(train, 0.0f, 1.0f);
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@ -121,13 +130,17 @@ OCL_PERF_TEST_P(BruteForceMatcherFixture, KnnMatch, OCL_PERF_ENUM(OCL_SIZE_1, OC
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OCL_PERF_ELSE
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OCL_PERF_ELSE
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}
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}
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OCL_PERF_TEST_P(BruteForceMatcherFixture, RadiusMatch, OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3))
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OCL_PERF_TEST_P(BruteForceMatcherFixture, RadiusMatch,
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::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
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OCL_PERF_ENUM(MatType(CV_32FC1))))
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{
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{
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const Size srcSize = GetParam();
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const Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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const float max_distance = 2.0f;
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const float max_distance = 2.0f;
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vector<vector<DMatch> > matches(2);
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vector<vector<DMatch> > matches(2);
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Mat query(srcSize, CV_32FC1), train(srcSize, CV_32FC1);
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Mat query(srcSize, type), train(srcSize, type);
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declare.in(query, train);
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declare.in(query, train);
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randu(query, 0.0f, 1.0f);
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randu(query, 0.0f, 1.0f);
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@ -71,9 +71,6 @@ OCL_PERF_TEST_P(DftFixture, Dft, ::testing::Combine(testing::Values(OCL_SIZE_1,
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randu(src, 0.0f, 1.0f);
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randu(src, 0.0f, 1.0f);
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declare.in(src);
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declare.in(src);
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if (srcSize == OCL_SIZE_4000)
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declare.time(7.4);
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if (RUN_OCL_IMPL)
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if (RUN_OCL_IMPL)
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{
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{
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ocl::oclMat oclSrc(src), oclDst;
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ocl::oclMat oclSrc(src), oclDst;
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@ -47,28 +47,32 @@
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using namespace perf;
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using namespace perf;
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using std::tr1::get;
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using std::tr1::get;
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using std::tr1::tuple;
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///////////// gemm ////////////////////////
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///////////// gemm ////////////////////////
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typedef Size_MatType GemmFixture;
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#ifdef HAVE_CLAMDBLAS
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#ifdef HAVE_CLAMDBLAS
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typedef tuple<Size, int> GemmParams;
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typedef TestBaseWithParam<GemmParams> GemmFixture;
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OCL_PERF_TEST_P(GemmFixture, Gemm, ::testing::Combine(
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OCL_PERF_TEST_P(GemmFixture, Gemm, ::testing::Combine(
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::testing::Values(Size(1000, 1000), Size(1500, 1500)),
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::testing::Values(Size(1000, 1000), Size(1500, 1500)),
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::testing::Values((int)cv::GEMM_1_T, (int)cv::GEMM_1_T | (int)cv::GEMM_2_T)))
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::testing::Values((int)cv::GEMM_1_T, (int)cv::GEMM_1_T | (int)cv::GEMM_2_T)))
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{
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{
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const Size_MatType_t params = GetParam();
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const GemmParams params = GetParam();
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const Size srcSize = get<0>(params);
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const Size srcSize = get<0>(params);
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const int type = get<1>(params);
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const int type = get<1>(params);
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Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
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Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
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src3(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
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src3(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
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declare.in(src1, src2, src3).out(dst).time(srcSize == OCL_SIZE_2000 ? 65 : 8);
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randu(src1, -10.0f, 10.0f);
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randu(src1, -10.0f, 10.0f);
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randu(src2, -10.0f, 10.0f);
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randu(src2, -10.0f, 10.0f);
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randu(src3, -10.0f, 10.0f);
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randu(src3, -10.0f, 10.0f);
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declare.in(src1, src2, src3).out(dst);
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if (RUN_OCL_IMPL)
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if (RUN_OCL_IMPL)
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{
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{
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ocl::oclMat oclSrc1(src1), oclSrc2(src2),
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ocl::oclMat oclSrc1(src1), oclSrc2(src2),
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@ -74,7 +74,7 @@ OCL_PERF_TEST(HOGFixture, HOG)
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ASSERT_TRUE(!src.empty()) << "can't open input image road.png";
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ASSERT_TRUE(!src.empty()) << "can't open input image road.png";
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vector<cv::Rect> found_locations;
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vector<cv::Rect> found_locations;
|
||||||
declare.in(src).time(5);
|
declare.in(src);
|
||||||
|
|
||||||
if (RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
|
@ -133,8 +133,7 @@ OCL_PERF_TEST_P(CornerMinEigenValFixture, CornerMinEigenVal,
|
|||||||
const int blockSize = 7, apertureSize = 1 + 2 * 3;
|
const int blockSize = 7, apertureSize = 1 + 2 * 3;
|
||||||
|
|
||||||
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
|
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
|
||||||
declare.in(src, WARMUP_RNG).out(dst)
|
declare.in(src, WARMUP_RNG).out(dst);
|
||||||
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
|
|
||||||
|
|
||||||
const int depth = CV_MAT_DEPTH(type);
|
const int depth = CV_MAT_DEPTH(type);
|
||||||
const ERROR_TYPE errorType = depth == CV_8U ? ERROR_ABSOLUTE : ERROR_RELATIVE;
|
const ERROR_TYPE errorType = depth == CV_8U ? ERROR_ABSOLUTE : ERROR_RELATIVE;
|
||||||
@ -172,8 +171,7 @@ OCL_PERF_TEST_P(CornerHarrisFixture, CornerHarris,
|
|||||||
|
|
||||||
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
|
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
|
||||||
randu(src, 0, 1);
|
randu(src, 0, 1);
|
||||||
declare.in(src).out(dst)
|
declare.in(src).out(dst);
|
||||||
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
|
|
||||||
|
|
||||||
if (RUN_OCL_IMPL)
|
if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
@ -469,9 +467,7 @@ PERF_TEST_P(MeanShiftFilteringFixture, MeanShiftFiltering,
|
|||||||
cv::TermCriteria crit(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1);
|
cv::TermCriteria crit(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1);
|
||||||
|
|
||||||
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
|
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
|
||||||
declare.in(src, WARMUP_RNG).out(dst)
|
declare.in(src, WARMUP_RNG).out(dst);
|
||||||
.time(srcSize == OCL_SIZE_4000 ?
|
|
||||||
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);
|
|
||||||
|
|
||||||
if (RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
@ -562,9 +558,7 @@ PERF_TEST_P(MeanShiftProcFixture, MeanShiftProc,
|
|||||||
|
|
||||||
Mat src(srcSize, CV_8UC4), dst1(srcSize, CV_8UC4),
|
Mat src(srcSize, CV_8UC4), dst1(srcSize, CV_8UC4),
|
||||||
dst2(srcSize, CV_16SC2);
|
dst2(srcSize, CV_16SC2);
|
||||||
declare.in(src, WARMUP_RNG).out(dst1, dst2)
|
declare.in(src, WARMUP_RNG).out(dst1, dst2);
|
||||||
.time(srcSize == OCL_SIZE_4000 ?
|
|
||||||
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);;
|
|
||||||
|
|
||||||
if (RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
@ -603,9 +597,6 @@ OCL_PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TEST_SIZES)
|
|||||||
const double clipLimit = 40.0;
|
const double clipLimit = 40.0;
|
||||||
declare.in(src, WARMUP_RNG);
|
declare.in(src, WARMUP_RNG);
|
||||||
|
|
||||||
if (srcSize == OCL_SIZE_4000)
|
|
||||||
declare.time(11);
|
|
||||||
|
|
||||||
if (RUN_OCL_IMPL)
|
if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
ocl::oclMat oclSrc(src), oclDst;
|
ocl::oclMat oclSrc(src), oclDst;
|
||||||
@ -649,9 +640,6 @@ PERF_TEST_P(ColumnSumFixture, ColumnSum, OCL_TYPICAL_MAT_SIZES)
|
|||||||
Mat src(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
|
Mat src(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
|
||||||
declare.in(src, WARMUP_RNG).out(dst);
|
declare.in(src, WARMUP_RNG).out(dst);
|
||||||
|
|
||||||
if (srcSize == OCL_SIZE_4000)
|
|
||||||
declare.time(5);
|
|
||||||
|
|
||||||
if (RUN_OCL_IMPL)
|
if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
|
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
|
||||||
|
@ -235,9 +235,6 @@ OCL_PERF_TEST_P(RemapFixture, Remap,
|
|||||||
Mat src(srcSize, type), dst(srcSize, type);
|
Mat src(srcSize, type), dst(srcSize, type);
|
||||||
declare.in(src, WARMUP_RNG).out(dst);
|
declare.in(src, WARMUP_RNG).out(dst);
|
||||||
|
|
||||||
if (srcSize == OCL_SIZE_4000 && interpolation == INTER_LINEAR)
|
|
||||||
declare.time(9);
|
|
||||||
|
|
||||||
Mat xmap, ymap;
|
Mat xmap, ymap;
|
||||||
xmap.create(srcSize, CV_32FC1);
|
xmap.create(srcSize, CV_32FC1);
|
||||||
ymap.create(srcSize, CV_32FC1);
|
ymap.create(srcSize, CV_32FC1);
|
||||||
|
@ -46,7 +46,7 @@
|
|||||||
|
|
||||||
#include "perf_precomp.hpp"
|
#include "perf_precomp.hpp"
|
||||||
|
|
||||||
#ifdef HAVE_CLAMDBLAS
|
//#ifdef HAVE_CLAMDBLAS
|
||||||
|
|
||||||
using namespace perf;
|
using namespace perf;
|
||||||
using namespace std;
|
using namespace std;
|
||||||
@ -100,4 +100,4 @@ PERF_TEST_P(KalmanFilterFixture, KalmanFilter,
|
|||||||
SANITY_CHECK(statePre_);
|
SANITY_CHECK(statePre_);
|
||||||
}
|
}
|
||||||
|
|
||||||
#endif // HAVE_CLAMDBLAS
|
//#endif // HAVE_CLAMDBLAS
|
||||||
|
@ -99,8 +99,7 @@ OCL_PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate,
|
|||||||
Mat src(srcSize, CV_8UC1), templ(templSize, CV_8UC1), dst;
|
Mat src(srcSize, CV_8UC1), templ(templSize, CV_8UC1), dst;
|
||||||
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
|
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
|
||||||
dst.create(dstSize, CV_8UC1);
|
dst.create(dstSize, CV_8UC1);
|
||||||
declare.in(src, templ, WARMUP_RNG).out(dst)
|
declare.in(src, templ, WARMUP_RNG).out(dst);
|
||||||
.time(srcSize == OCL_SIZE_2000 ? 10 : srcSize == OCL_SIZE_4000 ? 23 : 2);
|
|
||||||
|
|
||||||
if (RUN_OCL_IMPL)
|
if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
|
@ -55,7 +55,7 @@ static void genData(Mat& trainData, Size size, Mat& trainLabel = Mat().setTo(Sca
|
|||||||
trainData.create(size, CV_32FC1);
|
trainData.create(size, CV_32FC1);
|
||||||
randu(trainData, 1.0, 100.0);
|
randu(trainData, 1.0, 100.0);
|
||||||
|
|
||||||
if(nClasses != 0)
|
if (nClasses != 0)
|
||||||
{
|
{
|
||||||
trainLabel.create(size.height, 1, CV_8UC1);
|
trainLabel.create(size.height, 1, CV_8UC1);
|
||||||
randu(trainLabel, 0, nClasses - 1);
|
randu(trainLabel, 0, nClasses - 1);
|
||||||
@ -82,7 +82,7 @@ PERF_TEST_P(KNNFixture, KNN,
|
|||||||
genData(testData, size);
|
genData(testData, size);
|
||||||
Mat best_label;
|
Mat best_label;
|
||||||
|
|
||||||
if(RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
TEST_CYCLE()
|
TEST_CYCLE()
|
||||||
{
|
{
|
||||||
@ -90,7 +90,8 @@ PERF_TEST_P(KNNFixture, KNN,
|
|||||||
knn_cpu.train(trainData, trainLabels);
|
knn_cpu.train(trainData, trainLabels);
|
||||||
knn_cpu.find_nearest(testData, k, &best_label);
|
knn_cpu.find_nearest(testData, k, &best_label);
|
||||||
}
|
}
|
||||||
}else if(RUN_OCL_IMPL)
|
}
|
||||||
|
else if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
cv::ocl::oclMat best_label_ocl;
|
cv::ocl::oclMat best_label_ocl;
|
||||||
cv::ocl::oclMat testdata;
|
cv::ocl::oclMat testdata;
|
||||||
@ -103,7 +104,8 @@ PERF_TEST_P(KNNFixture, KNN,
|
|||||||
knn_ocl.find_nearest(testdata, k, best_label_ocl);
|
knn_ocl.find_nearest(testdata, k, best_label_ocl);
|
||||||
}
|
}
|
||||||
best_label_ocl.download(best_label);
|
best_label_ocl.download(best_label);
|
||||||
}else
|
}
|
||||||
|
else
|
||||||
OCL_PERF_ELSE
|
OCL_PERF_ELSE
|
||||||
SANITY_CHECK(best_label);
|
SANITY_CHECK(best_label);
|
||||||
}
|
}
|
||||||
@ -188,7 +190,7 @@ PERF_TEST_P(SVMFixture, DISABLED_SVM,
|
|||||||
CvMat samples_ = samples;
|
CvMat samples_ = samples;
|
||||||
CvMat results_ = results;
|
CvMat results_ = results;
|
||||||
|
|
||||||
if(RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
CvSVM svm;
|
CvSVM svm;
|
||||||
svm.train(trainData, labels, Mat(), Mat(), params);
|
svm.train(trainData, labels, Mat(), Mat(), params);
|
||||||
@ -197,7 +199,7 @@ PERF_TEST_P(SVMFixture, DISABLED_SVM,
|
|||||||
svm.predict(&samples_, &results_);
|
svm.predict(&samples_, &results_);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
else if(RUN_OCL_IMPL)
|
else if (RUN_OCL_IMPL)
|
||||||
{
|
{
|
||||||
CvSVM_OCL svm;
|
CvSVM_OCL svm;
|
||||||
svm.train(trainData, labels, Mat(), Mat(), params);
|
svm.train(trainData, labels, Mat(), Mat(), params);
|
||||||
|
@ -1,89 +0,0 @@
|
|||||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
||||||
//
|
|
||||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
||||||
//
|
|
||||||
// By downloading, copying, installing or using the software you agree to this license.
|
|
||||||
// If you do not agree to this license, do not download, install,
|
|
||||||
// copy or use the software.
|
|
||||||
//
|
|
||||||
//
|
|
||||||
// License Agreement
|
|
||||||
// For Open Source Computer Vision Library
|
|
||||||
//
|
|
||||||
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
|
|
||||||
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
|
|
||||||
// Third party copyrights are property of their respective owners.
|
|
||||||
//
|
|
||||||
// @Authors
|
|
||||||
// Fangfang Bai, fangfang@multicorewareinc.com
|
|
||||||
// Jin Ma, jin@multicorewareinc.com
|
|
||||||
//
|
|
||||||
// Redistribution and use in source and binary forms, with or without modification,
|
|
||||||
// are permitted provided that the following conditions are met:
|
|
||||||
//
|
|
||||||
// * Redistribution's of source code must retain the above copyright notice,
|
|
||||||
// this list of conditions and the following disclaimer.
|
|
||||||
//
|
|
||||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
||||||
// this list of conditions and the following disclaimer in the documentation
|
|
||||||
// and/or other materials provided with the distribution.
|
|
||||||
//
|
|
||||||
// * The name of the copyright holders may not be used to endorse or promote products
|
|
||||||
// derived from this software without specific prior written permission.
|
|
||||||
//
|
|
||||||
// This software is provided by the copyright holders and contributors as is and
|
|
||||||
// any express or implied warranties, including, but not limited to, the implied
|
|
||||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
||||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
||||||
// indirect, incidental, special, exemplary, or consequential damages
|
|
||||||
// (including, but not limited to, procurement of substitute goods or services;
|
|
||||||
// loss of use, data, or profits; or business interruption) however caused
|
|
||||||
// and on any theory of liability, whether in contract, strict liability,
|
|
||||||
// or tort (including negligence or otherwise) arising in any way out of
|
|
||||||
// the use of this software, even if advised of the possibility of such damage.
|
|
||||||
//
|
|
||||||
//M*/
|
|
||||||
#include "perf_precomp.hpp"
|
|
||||||
|
|
||||||
using namespace perf;
|
|
||||||
using std::tr1::tuple;
|
|
||||||
using std::tr1::get;
|
|
||||||
|
|
||||||
///////////// norm////////////////////////
|
|
||||||
|
|
||||||
CV_ENUM(NormType, NORM_INF, NORM_L1, NORM_L2)
|
|
||||||
|
|
||||||
typedef std::tr1::tuple<Size, MatType, NormType> NormParams;
|
|
||||||
typedef TestBaseWithParam<NormParams> NormFixture;
|
|
||||||
|
|
||||||
OCL_PERF_TEST_P(NormFixture, Norm,
|
|
||||||
::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
|
|
||||||
OCL_TEST_TYPES, NormType::all()))
|
|
||||||
{
|
|
||||||
const NormParams params = GetParam();
|
|
||||||
const Size srcSize = get<0>(params);
|
|
||||||
const int type = get<1>(params);
|
|
||||||
const int normType = get<2>(params);
|
|
||||||
perf::ERROR_TYPE errorType = type != NORM_INF ? ERROR_RELATIVE : ERROR_ABSOLUTE;
|
|
||||||
double eps = 1e-5, value;
|
|
||||||
|
|
||||||
Mat src1(srcSize, type), src2(srcSize, type);
|
|
||||||
declare.in(src1, src2, WARMUP_RNG);
|
|
||||||
|
|
||||||
if (RUN_OCL_IMPL)
|
|
||||||
{
|
|
||||||
ocl::oclMat oclSrc1(src1), oclSrc2(src2);
|
|
||||||
|
|
||||||
OCL_TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, normType);
|
|
||||||
|
|
||||||
SANITY_CHECK(value, eps, errorType);
|
|
||||||
}
|
|
||||||
else if (RUN_PLAIN_IMPL)
|
|
||||||
{
|
|
||||||
TEST_CYCLE() value = cv::norm(src1, src2, normType);
|
|
||||||
|
|
||||||
SANITY_CHECK(value, eps, errorType);
|
|
||||||
}
|
|
||||||
else
|
|
||||||
OCL_PERF_ELSE
|
|
||||||
}
|
|
@ -52,13 +52,12 @@ using std::tr1::get;
|
|||||||
using std::tr1::tuple;
|
using std::tr1::tuple;
|
||||||
using std::tr1::make_tuple;
|
using std::tr1::make_tuple;
|
||||||
|
|
||||||
typedef tuple<int> PyrLKOpticalFlowParamType;
|
typedef TestBaseWithParam<tuple<int> > PyrLKOpticalFlowFixture;
|
||||||
typedef TestBaseWithParam<int> PyrLKOpticalFlowFixture;
|
|
||||||
|
|
||||||
OCL_PERF_TEST_P(PyrLKOpticalFlowFixture,
|
OCL_PERF_TEST_P(PyrLKOpticalFlowFixture,
|
||||||
PyrLKOpticalFlow, ::testing::Values(1000, 2000, 4000))
|
PyrLKOpticalFlow, ::testing::Values(1000, 2000, 4000))
|
||||||
{
|
{
|
||||||
const int pointsCount = GetParam();
|
const int pointsCount = get<0>(GetParam());
|
||||||
|
|
||||||
const string fileName0 = "gpu/opticalflow/rubberwhale1.png",
|
const string fileName0 = "gpu/opticalflow/rubberwhale1.png",
|
||||||
fileName1 = "gpu/opticalflow/rubberwhale2.png";
|
fileName1 = "gpu/opticalflow/rubberwhale2.png";
|
||||||
@ -109,7 +108,7 @@ PERF_TEST(tvl1flowFixture, tvl1flow)
|
|||||||
const Size srcSize = frame0.size();
|
const Size srcSize = frame0.size();
|
||||||
const double eps = 1.2;
|
const double eps = 1.2;
|
||||||
Mat flow(srcSize, CV_32FC2), flow1(srcSize, CV_32FC1), flow2(srcSize, CV_32FC1);
|
Mat flow(srcSize, CV_32FC2), flow1(srcSize, CV_32FC1), flow2(srcSize, CV_32FC1);
|
||||||
declare.in(frame0, frame1).out(flow1, flow2).time(159);
|
declare.in(frame0, frame1).out(flow1, flow2);
|
||||||
|
|
||||||
if (RUN_PLAIN_IMPL)
|
if (RUN_PLAIN_IMPL)
|
||||||
{
|
{
|
||||||
|
276
modules/ocl/perf/perf_stat.cpp
Normal file
276
modules/ocl/perf/perf_stat.cpp
Normal file
@ -0,0 +1,276 @@
|
|||||||
|
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||||
|
//
|
||||||
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||||
|
//
|
||||||
|
// By downloading, copying, installing or using the software you agree to this license.
|
||||||
|
// If you do not agree to this license, do not download, install,
|
||||||
|
// copy or use the software.
|
||||||
|
//
|
||||||
|
//
|
||||||
|
// License Agreement
|
||||||
|
// For Open Source Computer Vision Library
|
||||||
|
//
|
||||||
|
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
|
||||||
|
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
|
||||||
|
// Third party copyrights are property of their respective owners.
|
||||||
|
//
|
||||||
|
// @Authors
|
||||||
|
// Fangfang Bai, fangfang@multicorewareinc.com
|
||||||
|
// Jin Ma, jin@multicorewareinc.com
|
||||||
|
//
|
||||||
|
// Redistribution and use in source and binary forms, with or without modification,
|
||||||
|
// are permitted provided that the following conditions are met:
|
||||||
|
//
|
||||||
|
// * Redistribution's of source code must retain the above copyright notice,
|
||||||
|
// this list of conditions and the following disclaimer.
|
||||||
|
//
|
||||||
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||||
|
// this list of conditions and the following disclaimer in the documentation
|
||||||
|
// and/or other materials provided with the distribution.
|
||||||
|
//
|
||||||
|
// * The name of the copyright holders may not be used to endorse or promote products
|
||||||
|
// derived from this software without specific prior written permission.
|
||||||
|
//
|
||||||
|
// This software is provided by the copyright holders and contributors as is and
|
||||||
|
// any express or implied warranties, including, but not limited to, the implied
|
||||||
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||||
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
||||||
|
// indirect, incidental, special, exemplary, or consequential damages
|
||||||
|
// (including, but not limited to, procurement of substitute goods or services;
|
||||||
|
// loss of use, data, or profits; or business interruption) however caused
|
||||||
|
// and on any theory of liability, whether in contract, strict liability,
|
||||||
|
// or tort (including negligence or otherwise) arising in any way out of
|
||||||
|
// the use of this software, even if advised of the possibility of such damage.
|
||||||
|
//
|
||||||
|
//M*/
|
||||||
|
#include "perf_precomp.hpp"
|
||||||
|
|
||||||
|
using namespace perf;
|
||||||
|
using std::tr1::tuple;
|
||||||
|
using std::tr1::get;
|
||||||
|
|
||||||
|
|
||||||
|
///////////// MinMax ////////////////////////
|
||||||
|
|
||||||
|
typedef Size_MatType MinMaxFixture;
|
||||||
|
|
||||||
|
PERF_TEST_P(MinMaxFixture, MinMax,
|
||||||
|
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
|
||||||
|
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
|
||||||
|
{
|
||||||
|
const Size_MatType_t params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
|
||||||
|
Mat src(srcSize, type);
|
||||||
|
declare.in(src, WARMUP_RNG);
|
||||||
|
|
||||||
|
double min_val = std::numeric_limits<double>::max(),
|
||||||
|
max_val = std::numeric_limits<double>::min();
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc(src);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() cv::ocl::minMax(oclSrc, &min_val, &max_val);
|
||||||
|
|
||||||
|
ASSERT_GE(max_val, min_val);
|
||||||
|
SANITY_CHECK(min_val);
|
||||||
|
SANITY_CHECK(max_val);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
Point min_loc, max_loc;
|
||||||
|
|
||||||
|
TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
|
||||||
|
|
||||||
|
ASSERT_GE(max_val, min_val);
|
||||||
|
SANITY_CHECK(min_val);
|
||||||
|
SANITY_CHECK(max_val);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
}
|
||||||
|
|
||||||
|
///////////// MinMaxLoc ////////////////////////
|
||||||
|
|
||||||
|
typedef Size_MatType MinMaxLocFixture;
|
||||||
|
|
||||||
|
OCL_PERF_TEST_P(MinMaxLocFixture, MinMaxLoc,
|
||||||
|
::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
|
||||||
|
{
|
||||||
|
const Size_MatType_t params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
|
||||||
|
Mat src(srcSize, type);
|
||||||
|
randu(src, 0, 1);
|
||||||
|
declare.in(src);
|
||||||
|
|
||||||
|
double min_val = 0.0, max_val = 0.0;
|
||||||
|
Point min_loc, max_loc;
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc(src);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() cv::ocl::minMaxLoc(oclSrc, &min_val, &max_val, &min_loc, &max_loc);
|
||||||
|
|
||||||
|
ASSERT_GE(max_val, min_val);
|
||||||
|
SANITY_CHECK(min_val);
|
||||||
|
SANITY_CHECK(max_val);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
TEST_CYCLE() cv::minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
|
||||||
|
|
||||||
|
ASSERT_GE(max_val, min_val);
|
||||||
|
SANITY_CHECK(min_val);
|
||||||
|
SANITY_CHECK(max_val);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
}
|
||||||
|
|
||||||
|
///////////// Sum ////////////////////////
|
||||||
|
|
||||||
|
typedef Size_MatType SumFixture;
|
||||||
|
|
||||||
|
OCL_PERF_TEST_P(SumFixture, Sum,
|
||||||
|
::testing::Combine(OCL_TEST_SIZES,
|
||||||
|
OCL_TEST_TYPES))
|
||||||
|
{
|
||||||
|
const Size_MatType_t params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
|
||||||
|
Mat src(srcSize, type);
|
||||||
|
Scalar result;
|
||||||
|
randu(src, 0, 60);
|
||||||
|
declare.in(src);
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc(src);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() result = cv::ocl::sum(oclSrc);
|
||||||
|
|
||||||
|
SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
TEST_CYCLE() result = cv::sum(src);
|
||||||
|
|
||||||
|
SANITY_CHECK(result, 1e-6, ERROR_RELATIVE);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
}
|
||||||
|
|
||||||
|
///////////// countNonZero ////////////////////////
|
||||||
|
|
||||||
|
typedef Size_MatType CountNonZeroFixture;
|
||||||
|
|
||||||
|
OCL_PERF_TEST_P(CountNonZeroFixture, CountNonZero,
|
||||||
|
::testing::Combine(OCL_TEST_SIZES,
|
||||||
|
OCL_PERF_ENUM(CV_8UC1, CV_32FC1)))
|
||||||
|
{
|
||||||
|
const Size_MatType_t params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
|
||||||
|
Mat src(srcSize, type);
|
||||||
|
int result = 0;
|
||||||
|
randu(src, 0, 256);
|
||||||
|
declare.in(src);
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc(src);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() result = cv::ocl::countNonZero(oclSrc);
|
||||||
|
|
||||||
|
SANITY_CHECK(result);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
TEST_CYCLE() result = cv::countNonZero(src);
|
||||||
|
|
||||||
|
SANITY_CHECK(result);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
}
|
||||||
|
|
||||||
|
///////////// meanStdDev ////////////////////////
|
||||||
|
|
||||||
|
typedef Size_MatType MeanStdDevFixture;
|
||||||
|
|
||||||
|
OCL_PERF_TEST_P(MeanStdDevFixture, MeanStdDev,
|
||||||
|
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
|
||||||
|
{
|
||||||
|
const Size_MatType_t params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
|
||||||
|
Mat src(srcSize, type);
|
||||||
|
Scalar mean, stddev;
|
||||||
|
randu(src, 0, 256);
|
||||||
|
declare.in(src);
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc(src);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() cv::ocl::meanStdDev(oclSrc, mean, stddev);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
TEST_CYCLE() cv::meanStdDev(src, mean, stddev);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
|
||||||
|
SANITY_CHECK_NOTHING();
|
||||||
|
// SANITY_CHECK(mean, 1e-6, ERROR_RELATIVE);
|
||||||
|
// SANITY_CHECK(stddev, 1e-6, ERROR_RELATIVE);
|
||||||
|
}
|
||||||
|
|
||||||
|
///////////// norm////////////////////////
|
||||||
|
|
||||||
|
CV_ENUM(NormType, NORM_INF, NORM_L1, NORM_L2)
|
||||||
|
|
||||||
|
typedef std::tr1::tuple<Size, MatType, NormType> NormParams;
|
||||||
|
typedef TestBaseWithParam<NormParams> NormFixture;
|
||||||
|
|
||||||
|
OCL_PERF_TEST_P(NormFixture, Norm,
|
||||||
|
::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3),
|
||||||
|
OCL_TEST_TYPES, NormType::all()))
|
||||||
|
{
|
||||||
|
const NormParams params = GetParam();
|
||||||
|
const Size srcSize = get<0>(params);
|
||||||
|
const int type = get<1>(params);
|
||||||
|
const int normType = get<2>(params);
|
||||||
|
perf::ERROR_TYPE errorType = type != NORM_INF ? ERROR_RELATIVE : ERROR_ABSOLUTE;
|
||||||
|
double eps = 1e-5, value;
|
||||||
|
|
||||||
|
Mat src1(srcSize, type), src2(srcSize, type);
|
||||||
|
declare.in(src1, src2, WARMUP_RNG);
|
||||||
|
|
||||||
|
if (RUN_OCL_IMPL)
|
||||||
|
{
|
||||||
|
ocl::oclMat oclSrc1(src1), oclSrc2(src2);
|
||||||
|
|
||||||
|
OCL_TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, normType);
|
||||||
|
|
||||||
|
SANITY_CHECK(value, eps, errorType);
|
||||||
|
}
|
||||||
|
else if (RUN_PLAIN_IMPL)
|
||||||
|
{
|
||||||
|
TEST_CYCLE() value = cv::norm(src1, src2, normType);
|
||||||
|
|
||||||
|
SANITY_CHECK(value, eps, errorType);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
OCL_PERF_ELSE
|
||||||
|
}
|
Loading…
Reference in New Issue
Block a user