2011-09-06 17:30:28 +02:00
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#include "perf_precomp.hpp"
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#include "opencv2/core/core_c.h"
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using namespace std;
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using namespace cv;
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using namespace perf;
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/*
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// Scalar sum(InputArray arr)
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*/
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PERF_TEST_P( Size_MatType, sum, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int type = std::tr1::get<1>(GetParam());
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Mat arr(sz, type);
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Scalar s;
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declare.in(arr, WARMUP_RNG);
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TEST_CYCLE(100) { s = sum(arr); }
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SANITY_CHECK(s);
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}
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/*
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// Scalar mean(InputArray src)
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*/
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PERF_TEST_P( Size_MatType, mean, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int type = std::tr1::get<1>(GetParam());
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Mat src(sz, type);
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Scalar s;
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declare.in(src, WARMUP_RNG);
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TEST_CYCLE(100) { s = mean(src); }
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SANITY_CHECK(s);
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}
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/*
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// Scalar mean(InputArray src, InputArray mask=noArray())
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*/
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PERF_TEST_P( Size_MatType, mean_mask, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int type = std::tr1::get<1>(GetParam());
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Mat src(sz, type);
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Mat mask = Mat::ones(src.size(), CV_8U);
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Scalar s;
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declare.in(src, WARMUP_RNG).in(mask);
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TEST_CYCLE(100) { s = mean(src, mask); }
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SANITY_CHECK(s);
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}
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CV_FLAGS(NormType, NORM_INF, NORM_L1, NORM_L2, NORM_TYPE_MASK, NORM_RELATIVE, NORM_MINMAX)
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typedef std::tr1::tuple<Size, MatType, NormType> Size_MatType_NormType_t;
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typedef perf::TestBaseWithParam<Size_MatType_NormType_t> Size_MatType_NormType;
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/*
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// double norm(InputArray src1, int normType=NORM_L2)
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*/
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PERF_TEST_P( Size_MatType_NormType, norm,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2 )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src1(sz, matType);
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double n;
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declare.in(src1, WARMUP_RNG);
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TEST_CYCLE(100) { n = norm(src1, normType); }
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SANITY_CHECK(n);
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}
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/*
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// double norm(InputArray src1, int normType=NORM_L2, InputArray mask=noArray())
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*/
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PERF_TEST_P( Size_MatType_NormType, norm_mask,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2 )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src1(sz, matType);
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Mat mask = Mat::ones(sz, CV_8U);
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double n;
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declare.in(src1, WARMUP_RNG).in(mask);
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TEST_CYCLE(100) { n = norm(src1, normType, mask); }
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SANITY_CHECK(n);
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}
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/*
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// double norm(InputArray src1, InputArray src2, int normType)
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*/
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PERF_TEST_P( Size_MatType_NormType, norm2,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2, (int)(NORM_RELATIVE+NORM_INF), (int)(NORM_RELATIVE+NORM_L1), (int)(NORM_RELATIVE+NORM_L2) )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src1(sz, matType);
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Mat src2(sz, matType);
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double n;
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declare.in(src1, src2, WARMUP_RNG);
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TEST_CYCLE(100) { n = norm(src1, src2, normType); }
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SANITY_CHECK(n);
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}
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/*
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// double norm(InputArray src1, InputArray src2, int normType, InputArray mask=noArray())
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*/
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PERF_TEST_P( Size_MatType_NormType, norm2_mask,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2, (int)(NORM_RELATIVE+NORM_INF), (int)(NORM_RELATIVE+NORM_L1), (int)(NORM_RELATIVE+NORM_L2) )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src1(sz, matType);
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Mat src2(sz, matType);
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Mat mask = Mat::ones(sz, CV_8U);
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double n;
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declare.in(src1, src2, WARMUP_RNG).in(mask);
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TEST_CYCLE(100) { n = norm(src1, src2, normType, mask); }
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SANITY_CHECK(n);
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}
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/*
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// void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2)
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*/
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PERF_TEST_P( Size_MatType_NormType, normalize,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2 )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src(sz, matType);
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Mat dst(sz, matType);
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double alpha = 100.;
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if(normType==NORM_L1) alpha = (double)src.total() * src.channels();
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if(normType==NORM_L2) alpha = (double)src.total()/10;
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declare.in(src, WARMUP_RNG).out(dst);
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TEST_CYCLE(100) { normalize(src, dst, alpha, 0., normType); }
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SANITY_CHECK(dst);
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}
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/*
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// void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2, int rtype=-1, InputArray mask=noArray())
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*/
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PERF_TEST_P( Size_MatType_NormType, normalize_mask,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2 )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src(sz, matType);
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Mat dst(sz, matType);
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Mat mask = Mat::ones(sz, CV_8U);
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double alpha = 100.;
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if(normType==NORM_L1) alpha = (double)src.total() * src.channels();
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if(normType==NORM_L2) alpha = (double)src.total()/10;
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declare.in(src, WARMUP_RNG).in(mask).out(dst);
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TEST_CYCLE(100) { normalize(src, dst, alpha, 0., normType, -1, mask); }
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SANITY_CHECK(dst);
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}
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/*
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// void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2, int rtype=-1)
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*/
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PERF_TEST_P( Size_MatType_NormType, normalize_32f,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
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testing::Values( (int)NORM_INF, (int)NORM_L1, (int)NORM_L2 )
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int normType = std::tr1::get<2>(GetParam());
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Mat src(sz, matType);
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Mat dst(sz, matType);
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double alpha = 100.;
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if(normType==NORM_L1) alpha = (double)src.total() * src.channels();
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if(normType==NORM_L2) alpha = (double)src.total()/10;
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declare.in(src, WARMUP_RNG).out(dst);
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TEST_CYCLE(100) { normalize(src, dst, alpha, 0., normType, CV_32F); }
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SANITY_CHECK(dst);
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}
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/*
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// void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2)
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*/
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PERF_TEST_P( Size_MatType, normalize_minmax, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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Mat src(sz, matType);
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randu(src, 0, 256);
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Mat dst(sz, matType);
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declare.in(src).out(dst);
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TEST_CYCLE(100) { normalize(src, dst, 20., 100., NORM_MINMAX); }
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SANITY_CHECK(dst);
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}
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/*
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// void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev)
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*/
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PERF_TEST_P( Size_MatType, meanStdDev, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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Mat src(sz, matType);
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Mat mean, dev;
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declare.in(src, WARMUP_RNG);
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TEST_CYCLE(100) { meanStdDev(src, mean, dev); }
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SANITY_CHECK(mean);
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SANITY_CHECK(dev);
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}
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/*
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// void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev, InputArray mask=noArray())
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*/
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PERF_TEST_P( Size_MatType, meanStdDev_mask, TYPICAL_MATS )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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Mat src(sz, matType);
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Mat mask = Mat::ones(sz, CV_8U);
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Mat mean, dev;
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declare.in(src, WARMUP_RNG).in(mask);
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TEST_CYCLE(100) { meanStdDev(src, mean, dev, mask); }
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SANITY_CHECK(mean);
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SANITY_CHECK(dev);
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}
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/*
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// int countNonZero(InputArray mtx)
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*/
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PERF_TEST_P( Size_MatType, countNonZero, TYPICAL_MATS_C1 )
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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Mat src(sz, matType);
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int cnt = 0;
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declare.in(src, WARMUP_RNG);
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TEST_CYCLE(100) { cnt = countNonZero(src); }
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SANITY_CHECK(cnt);
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}
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/*
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// void minMaxLoc(InputArray src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, InputArray mask=noArray())
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*/
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2011-09-14 18:20:10 +02:00
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PERF_TEST_P( Size_MatType, minMaxLoc, testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( CV_8UC1, CV_8SC1, CV_16UC1, CV_16SC1, CV_32SC1, CV_32FC1, CV_64FC1 ) ) )
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2011-09-06 17:30:28 +02:00
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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Mat src(sz, matType);
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double minVal, maxVal;
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Point minLoc, maxLoc;
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2011-09-14 18:20:10 +02:00
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// avoid early exit on 1 byte data
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if (matType == CV_8U)
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randu(src, 1, 254);
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else if (matType == CV_8S)
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randu(src, -127, 126);
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else
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warmup(src, WARMUP_RNG);
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declare.in(src);
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2011-09-06 17:30:28 +02:00
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TEST_CYCLE(100) { minMaxLoc(src, &minVal, &maxVal, &minLoc, &maxLoc); }
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SANITY_CHECK(minVal);
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SANITY_CHECK(maxVal);
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}
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CV_ENUM(ROp, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN)
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typedef std::tr1::tuple<Size, MatType, ROp> Size_MatType_ROp_t;
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typedef perf::TestBaseWithParam<Size_MatType_ROp_t> Size_MatType_ROp;
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/*
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// void reduce(InputArray mtx, OutputArray vec, int dim, int reduceOp, int dtype=-1)
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*/
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PERF_TEST_P( Size_MatType_ROp, reduceR,
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testing::Combine(
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testing::Values( TYPICAL_MAT_SIZES ),
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testing::Values( TYPICAL_MAT_TYPES ),
|
2011-11-01 16:41:43 +01:00
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testing::ValuesIn(ROp::all())
|
2011-09-06 17:30:28 +02:00
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)
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)
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{
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Size sz = std::tr1::get<0>(GetParam());
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int matType = std::tr1::get<1>(GetParam());
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int reduceOp = std::tr1::get<2>(GetParam());
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int ddepth = -1;
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if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG) )
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ddepth = CV_32S;
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Mat src(sz, matType);
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Mat vec;
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declare.in(src, WARMUP_RNG);
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TEST_CYCLE(100) { reduce(src, vec, 0, reduceOp, ddepth); }
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SANITY_CHECK(vec);
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}
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|
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|
|
|
/*
|
|
|
|
// void reduce(InputArray mtx, OutputArray vec, int dim, int reduceOp, int dtype=-1)
|
|
|
|
*/
|
|
|
|
PERF_TEST_P( Size_MatType_ROp, reduceC,
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|
|
|
testing::Combine(
|
|
|
|
testing::Values( TYPICAL_MAT_SIZES ),
|
|
|
|
testing::Values( TYPICAL_MAT_TYPES ),
|
2011-11-01 16:41:43 +01:00
|
|
|
testing::ValuesIn(ROp::all())
|
2011-09-06 17:30:28 +02:00
|
|
|
)
|
|
|
|
)
|
|
|
|
{
|
|
|
|
Size sz = std::tr1::get<0>(GetParam());
|
|
|
|
int matType = std::tr1::get<1>(GetParam());
|
|
|
|
int reduceOp = std::tr1::get<2>(GetParam());
|
|
|
|
|
|
|
|
int ddepth = -1;
|
|
|
|
if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG) )
|
|
|
|
ddepth = CV_32S;
|
|
|
|
Mat src(sz, matType);
|
|
|
|
Mat vec;
|
|
|
|
|
|
|
|
declare.in(src, WARMUP_RNG);
|
|
|
|
|
|
|
|
TEST_CYCLE(100) { reduce(src, vec, 1, reduceOp, ddepth); }
|
|
|
|
|
|
|
|
SANITY_CHECK(vec);
|
|
|
|
}
|