opencv/modules/cudaarithm/perf/perf_reductions.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// License Agreement
// For Open Source Computer Vision Library
//
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#include "perf_precomp.hpp"
using namespace std;
using namespace testing;
using namespace perf;
//////////////////////////////////////////////////////////////////////
// Norm
DEF_PARAM_TEST(Sz_Depth_Norm, cv::Size, MatDepth, NormType);
PERF_TEST_P(Sz_Depth_Norm, Norm,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32S, CV_32F),
Values(NormType(cv::NORM_INF), NormType(cv::NORM_L1), NormType(cv::NORM_L2))))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int normType = GET_PARAM(2);
cv::Mat src(size, depth);
if (depth == CV_8U)
cv::randu(src, 0, 254);
else
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::cuda::GpuMat d_buf;
double gpu_dst;
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TEST_CYCLE() gpu_dst = cv::cuda::norm(d_src, normType, d_buf);
SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE);
}
else
{
double cpu_dst;
TEST_CYCLE() cpu_dst = cv::norm(src, normType);
SANITY_CHECK(cpu_dst, 1e-6, ERROR_RELATIVE);
}
}
//////////////////////////////////////////////////////////////////////
// NormDiff
DEF_PARAM_TEST(Sz_Norm, cv::Size, NormType);
PERF_TEST_P(Sz_Norm, NormDiff,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(NormType(cv::NORM_INF), NormType(cv::NORM_L1), NormType(cv::NORM_L2))))
{
const cv::Size size = GET_PARAM(0);
const int normType = GET_PARAM(1);
cv::Mat src1(size, CV_8UC1);
declare.in(src1, WARMUP_RNG);
cv::Mat src2(size, CV_8UC1);
declare.in(src2, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src1(src1);
const cv::cuda::GpuMat d_src2(src2);
double gpu_dst;
TEST_CYCLE() gpu_dst = cv::cuda::norm(d_src1, d_src2, normType);
SANITY_CHECK(gpu_dst);
}
else
{
double cpu_dst;
TEST_CYCLE() cpu_dst = cv::norm(src1, src2, normType);
SANITY_CHECK(cpu_dst);
}
}
//////////////////////////////////////////////////////////////////////
// Sum
PERF_TEST_P(Sz_Depth_Cn, Sum,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
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CUDA_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::Scalar gpu_dst;
TEST_CYCLE() gpu_dst = cv::cuda::sum(d_src);
SANITY_CHECK(gpu_dst, 1e-5, ERROR_RELATIVE);
}
else
{
cv::Scalar cpu_dst;
TEST_CYCLE() cpu_dst = cv::sum(src);
SANITY_CHECK(cpu_dst, 1e-6, ERROR_RELATIVE);
}
}
//////////////////////////////////////////////////////////////////////
// SumAbs
PERF_TEST_P(Sz_Depth_Cn, SumAbs,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
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CUDA_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::Scalar gpu_dst;
TEST_CYCLE() gpu_dst = cv::cuda::absSum(d_src);
SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// SumSqr
PERF_TEST_P(Sz_Depth_Cn, SumSqr,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values<MatDepth>(CV_8U, CV_16U, CV_32F),
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CUDA_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::Scalar gpu_dst;
TEST_CYCLE() gpu_dst = cv::cuda::sqrSum(d_src);
SANITY_CHECK(gpu_dst, 1e-6, ERROR_RELATIVE);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// MinMax
PERF_TEST_P(Sz_Depth, MinMax,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F, CV_64F)))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
cv::Mat src(size, depth);
if (depth == CV_8U)
cv::randu(src, 0, 254);
else
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
double gpu_minVal, gpu_maxVal;
TEST_CYCLE() cv::cuda::minMax(d_src, &gpu_minVal, &gpu_maxVal, cv::cuda::GpuMat());
SANITY_CHECK(gpu_minVal, 1e-10);
SANITY_CHECK(gpu_maxVal, 1e-10);
}
else
{
double cpu_minVal, cpu_maxVal;
TEST_CYCLE() cv::minMaxLoc(src, &cpu_minVal, &cpu_maxVal);
SANITY_CHECK(cpu_minVal);
SANITY_CHECK(cpu_maxVal);
}
}
//////////////////////////////////////////////////////////////////////
// MinMaxLoc
PERF_TEST_P(Sz_Depth, MinMaxLoc,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F, CV_64F)))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
cv::Mat src(size, depth);
if (depth == CV_8U)
cv::randu(src, 0, 254);
else
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
double gpu_minVal, gpu_maxVal;
cv::Point gpu_minLoc, gpu_maxLoc;
TEST_CYCLE() cv::cuda::minMaxLoc(d_src, &gpu_minVal, &gpu_maxVal, &gpu_minLoc, &gpu_maxLoc);
SANITY_CHECK(gpu_minVal, 1e-10);
SANITY_CHECK(gpu_maxVal, 1e-10);
}
else
{
double cpu_minVal, cpu_maxVal;
cv::Point cpu_minLoc, cpu_maxLoc;
TEST_CYCLE() cv::minMaxLoc(src, &cpu_minVal, &cpu_maxVal, &cpu_minLoc, &cpu_maxLoc);
SANITY_CHECK(cpu_minVal);
SANITY_CHECK(cpu_maxVal);
}
}
//////////////////////////////////////////////////////////////////////
// CountNonZero
PERF_TEST_P(Sz_Depth, CountNonZero,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F, CV_64F)))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
cv::Mat src(size, depth);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
int gpu_dst = 0;
TEST_CYCLE() gpu_dst = cv::cuda::countNonZero(d_src);
SANITY_CHECK(gpu_dst);
}
else
{
int cpu_dst = 0;
TEST_CYCLE() cpu_dst = cv::countNonZero(src);
SANITY_CHECK(cpu_dst);
}
}
//////////////////////////////////////////////////////////////////////
// Reduce
CV_ENUM(ReduceCode, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN)
enum {Rows = 0, Cols = 1};
CV_ENUM(ReduceDim, Rows, Cols)
DEF_PARAM_TEST(Sz_Depth_Cn_Code_Dim, cv::Size, MatDepth, MatCn, ReduceCode, ReduceDim);
PERF_TEST_P(Sz_Depth_Cn_Code_Dim, Reduce,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_16S, CV_32F),
Values(1, 2, 3, 4),
ReduceCode::all(),
ReduceDim::all()))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int reduceOp = GET_PARAM(3);
const int dim = GET_PARAM(4);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::cuda::GpuMat dst;
TEST_CYCLE() cv::cuda::reduce(d_src, dst, dim, reduceOp, CV_32F);
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CUDA_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::reduce(src, dst, dim, reduceOp, CV_32F);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// Normalize
DEF_PARAM_TEST(Sz_Depth_NormType, cv::Size, MatDepth, NormType);
PERF_TEST_P(Sz_Depth_NormType, Normalize,
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Combine(CUDA_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F, CV_64F),
Values(NormType(cv::NORM_INF),
NormType(cv::NORM_L1),
NormType(cv::NORM_L2),
NormType(cv::NORM_MINMAX))))
{
const cv::Size size = GET_PARAM(0);
const int type = GET_PARAM(1);
const int norm_type = GET_PARAM(2);
const double alpha = 1;
const double beta = 0;
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::cuda::GpuMat dst;
TEST_CYCLE() cv::cuda::normalize(d_src, dst, alpha, beta, norm_type, type, cv::cuda::GpuMat());
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CUDA_SANITY_CHECK(dst, 1e-6);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::normalize(src, dst, alpha, beta, norm_type, type);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// MeanStdDev
PERF_TEST_P(Sz, MeanStdDev,
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CUDA_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
cv::Mat src(size, CV_8UC1);
declare.in(src, WARMUP_RNG);
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if (PERF_RUN_CUDA())
{
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const cv::cuda::GpuMat d_src(src);
cv::Scalar gpu_mean;
cv::Scalar gpu_stddev;
TEST_CYCLE() cv::cuda::meanStdDev(d_src, gpu_mean, gpu_stddev);
SANITY_CHECK(gpu_mean);
SANITY_CHECK(gpu_stddev);
}
else
{
cv::Scalar cpu_mean;
cv::Scalar cpu_stddev;
TEST_CYCLE() cv::meanStdDev(src, cpu_mean, cpu_stddev);
SANITY_CHECK(cpu_mean);
SANITY_CHECK(cpu_stddev);
}
}
//////////////////////////////////////////////////////////////////////
// Integral
PERF_TEST_P(Sz, Integral,
CUDA_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
cv::Mat src(size, CV_8UC1);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_src(src);
cv::cuda::GpuMat dst;
TEST_CYCLE() cv::cuda::integral(d_src, dst);
CUDA_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::integral(src, dst);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// IntegralSqr
PERF_TEST_P(Sz, IntegralSqr,
CUDA_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
cv::Mat src(size, CV_8UC1);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_CUDA())
{
const cv::cuda::GpuMat d_src(src);
cv::cuda::GpuMat dst;
TEST_CYCLE() cv::cuda::sqrIntegral(d_src, dst);
CUDA_SANITY_CHECK(dst);
}
else
{
FAIL_NO_CPU();
}
}