Commit 4c28a6f0 authored by ilya-lavrenov's avatar ilya-lavrenov

most of the performance tests was rewritten in google-test manner

parent 6c4ad9b5
......@@ -42,7 +42,7 @@
#include "perf_precomp.hpp"
int main(int argc, const char *argv[])
static int old_main(int argc, const char *argv[])
{
const char *keys =
"{ h | help | false | print help message }"
......@@ -162,3 +162,33 @@ END_DEV:
return 0;
}
const char * impls[] =
{
"ocl",
"plain",
#ifdef HAVE_OPENCV_GPU
"gpu"
#endif
};
int main(int argc, char **argv)
{
// temp solution: if no '--gtest_' and '--perf_' args switch to old behavior
bool useGTest = false;
for(int i=1; i<argc; i++)
{
std::string arg( argv[i] );
if( arg.find("--gtest_")==0 || arg.find("--perf_")==0 )
useGTest = true;
// if (arg == "--perf_verify_sanity")
// argv[i] = (char*)"--perf_no_verify_sanity";
}
if( !useGTest )
return old_main(argc, (const char**)argv);
CV_PERF_TEST_MAIN_INTERNALS(ocl, impls)
}
......@@ -45,1153 +45,1081 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::get;
using std::tr1::tuple;
///////////// Lut ////////////////////////
PERFTEST(lut)
{
Mat src, lut, dst, ocl_dst;
ocl::oclMat d_src, d_lut, d_dst;
int all_type[] = {CV_8UC1, CV_8UC3};
std::string type_name[] = {"CV_8UC1", "CV_8UC3"};
CV_ENUM(LUTMatTypes, CV_8UC1, CV_8UC3)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
typedef tuple<Size, LUTMatTypes> LUTParams;
typedef TestBaseWithParam<LUTParams> LUTFixture;
gen(src, size, size, all_type[j], 0, 256);
gen(lut, 1, 256, CV_8UC1, 0, 1);
PERF_TEST_P(LUTFixture, LUT,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
LUTMatTypes::all()))
{
// getting params
LUTParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
LUT(src, lut, dst);
const std::string impl = getSelectedImpl();
CPU_ON;
LUT(src, lut, dst);
CPU_OFF;
// creating src data
Mat src(srcSize, type), lut(1, 256, CV_8UC1);
int dstType = CV_MAKETYPE(lut.depth(), src.channels());
Mat dst(srcSize, dstType);
d_src.upload(src);
d_lut.upload(lut);
randu(lut, 0, 2);
declare.in(src, WARMUP_RNG).in(lut).out(dst);
WARMUP_ON;
ocl::LUT(d_src, d_lut, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclLut(lut), oclDst(srcSize, dstType);
GPU_ON;
ocl::LUT(d_src, d_lut, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::LUT(oclSrc, oclLut, oclDst);
GPU_FULL_ON;
d_src.upload(src);
d_lut.upload(lut);
ocl::LUT(d_src, d_lut, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::LUT(src, lut, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Exp ////////////////////////
PERFTEST(Exp)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; CV_32FC1";
typedef TestBaseWithParam<Size> ExpFixture;
PERF_TEST_P(ExpFixture, Exp, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
gen(src, size, size, CV_32FC1, 5, 16);
const std::string impl = getSelectedImpl();
exp(src, dst);
// creating src data
Mat src(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
declare.in(src).out(dst);
randu(src, 5, 16);
CPU_ON;
exp(src, dst);
CPU_OFF;
d_src.upload(src);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, src.type());
WARMUP_ON;
ocl::exp(d_src, d_dst);
WARMUP_OFF;
TEST_CYCLE() cv::ocl::exp(oclSrc, oclDst);
GPU_ON;
ocl::exp(d_src, d_dst);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src.upload(src);
ocl::exp(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
SANITY_CHECK(dst, 0.3);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::exp(src, dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 2);
SANITY_CHECK(dst, 0.3);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// LOG ////////////////////////
PERFTEST(Log)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; 32F";
typedef TestBaseWithParam<Size> LogFixture;
gen(src, size, size, CV_32F, 1, 10);
PERF_TEST_P(LogFixture, Log, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
log(src, dst);
// creating src data
Mat src(srcSize, CV_32F), dst(srcSize, src.type());
randu(src, 1, 10);
declare.in(src).out(dst);
CPU_ON;
log(src, dst);
CPU_OFF;
d_src.upload(src);
if (srcSize == OCL_SIZE_4000)
declare.time(3.6);
WARMUP_ON;
ocl::log(d_src, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, src.type());
GPU_ON;
ocl::log(d_src, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::log(oclSrc, oclDst);
GPU_FULL_ON;
d_src.upload(src);
ocl::log(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1);
SANITY_CHECK(dst);
}
}
///////////// Add ////////////////////////
PERFTEST(Add)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
else if (impl == "plain")
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
TEST_CYCLE() cv::log(src, dst);
gen(src1, size, size, all_type[j], 0, 1);
gen(src2, size, size, all_type[j], 0, 1);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
add(src1, src2, dst);
///////////// Add ////////////////////////
CPU_ON;
add(src1, src2, dst);
CPU_OFF;
CV_ENUM(AddMatTypes, CV_8UC1, CV_32FC1)
d_src1.upload(src1);
d_src2.upload(src2);
typedef tuple<Size, AddMatTypes> AddParams;
typedef TestBaseWithParam<AddParams> AddFixture;
WARMUP_ON;
ocl::add(d_src1, d_src2, d_dst);
WARMUP_OFF;
PERF_TEST_P(AddFixture, Add,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
AddMatTypes::all()))
{
// getting params
AddParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
randu(src1, 0, 1);
randu(src2, 0, 1);
declare.in(src1, src2).out(dst);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, type);
GPU_ON;
ocl::add(d_src1, d_src2, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::add(oclSrc1, oclSrc2, oclDst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::add(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::add(src1, src2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Mul ////////////////////////
PERFTEST(Mul)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
multiply(src1, src2, dst);
CV_ENUM(MulMatTypes, CV_8UC1, CV_8UC4)
CPU_ON;
multiply(src1, src2, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
typedef tuple<Size, MulMatTypes> MulParams;
typedef TestBaseWithParam<MulParams> MulFixture;
WARMUP_ON;
ocl::multiply(d_src1, d_src2, d_dst);
WARMUP_OFF;
PERF_TEST_P(MulFixture, Mul, ::testing::Combine(OCL_TYPICAL_MAT_SIZES,
MulMatTypes::all()))
{
// getting params
MulParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
randu(src1, 0, 256);
randu(src2, 0, 256);
declare.in(src1, src2).out(dst);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, type);
GPU_ON;
ocl::multiply(d_src1, d_src2, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::multiply(oclSrc1, oclSrc2, oclDst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::multiply(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::multiply(src1, src2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Div ////////////////////////
PERFTEST(Div)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
divide(src1, src2, dst);
CPU_ON;
divide(src1, src2, dst);
CPU_OFF;
typedef MulMatTypes DivMatTypes;
typedef tuple<Size, DivMatTypes> DivParams;
typedef TestBaseWithParam<DivParams> DivFixture;
d_src1.upload(src1);
d_src2.upload(src2);
WARMUP_ON;
ocl::divide(d_src1, d_src2, d_dst);
WARMUP_OFF;
PERF_TEST_P(DivFixture, Div, ::testing::Combine(OCL_TYPICAL_MAT_SIZES,
DivMatTypes::all()))
{
// getting params
DivParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
declare.in(src1, src2).out(dst);
randu(src1, 0, 256);
randu(src2, 0, 256);
if ((srcSize == OCL_SIZE_4000 && type == CV_8UC1) ||
(srcSize == OCL_SIZE_2000 && type == CV_8UC4))
declare.time(4.2);
else if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(16.6);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, type);
GPU_ON;
ocl::divide(d_src1, d_src2, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::divide(oclSrc1, oclSrc2, oclDst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::divide(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::divide(src1, src2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Absdiff ////////////////////////
PERFTEST(Absdiff)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
typedef MulMatTypes AbsDiffMatTypes;
typedef tuple<Size, AbsDiffMatTypes> AbsDiffParams;
typedef TestBaseWithParam<AbsDiffParams> AbsDiffFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(AbsDiffFixture, Absdiff, ::testing::Combine(OCL_TYPICAL_MAT_SIZES,
AbsDiffMatTypes::all()))
{
// getting params
AbsDiffParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
declare.in(src1, src2).in(dst);
randu(src1, 0, 256);
randu(src2, 0, 256);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
absdiff(src1, src2, dst);
CPU_ON;
absdiff(src1, src2, dst);
CPU_OFF;
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, type);
d_src1.upload(src1);
d_src2.upload(src2);
TEST_CYCLE() cv::ocl::absdiff(oclSrc1, oclSrc2, oclDst);
WARMUP_ON;
ocl::absdiff(d_src1, d_src2, d_dst);
WARMUP_OFF;
oclDst.download(dst);
GPU_ON;
ocl::absdiff(d_src1, d_src2, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::absdiff(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::absdiff(src1, src2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// CartToPolar ////////////////////////
PERFTEST(CartToPolar)
{
Mat src1, src2, dst, dst1, ocl_dst, ocl_dst1;
ocl::oclMat d_src1, d_src2, d_dst, d_dst1;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
typedef TestBaseWithParam<Size> CartToPolarFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(CartToPolarFixture, CartToPolar, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
dst1(srcSize, CV_32FC1), dst2(srcSize, CV_32FC1);
declare.in(src1, src2).out(dst1, dst2);
randu(src1, 0, 256);
randu(src2, 0, 256);
if (srcSize == OCL_SIZE_4000)
declare.time(3.6);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
gen(dst1, size, size, all_type[j], 0, 256);
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclDst1(srcSize, src1.type()), oclDst2(srcSize, src1.type());
TEST_CYCLE() cv::ocl::cartToPolar(oclSrc1, oclSrc2, oclDst1, oclDst2);
cartToPolar(src1, src2, dst, dst1, 1);
CPU_ON;
cartToPolar(src1, src2, dst, dst1, 1);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
WARMUP_ON;
ocl::cartToPolar(d_src1, d_src2, d_dst, d_dst1, 1);
WARMUP_OFF;
GPU_ON;
ocl::cartToPolar(d_src1, d_src2, d_dst, d_dst1, 1);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::cartToPolar(d_src1, d_src2, d_dst, d_dst1, 1);
d_dst.download(ocl_dst);
d_dst1.download(ocl_dst1);
GPU_FULL_OFF;
double diff1 = checkNorm(ocl_dst1, dst1);
double diff2 = checkNorm(ocl_dst, dst);
double max_diff = max(diff1, diff2);
TestSystem::instance().setAccurate(max_diff<=.5?1:0, max_diff);
oclDst1.download(dst1);
oclDst2.download(dst2);
SANITY_CHECK(dst1, 5e-3);
SANITY_CHECK(dst2, 5e-3);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::cartToPolar(src1, src2, dst1, dst2);
SANITY_CHECK(dst1, 5e-3);
SANITY_CHECK(dst2, 5e-3);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// PolarToCart ////////////////////////
PERFTEST(PolarToCart)
{
Mat src1, src2, dst, dst1, ocl_dst, ocl_dst1;
ocl::oclMat d_src1, d_src2, d_dst, d_dst1;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
typedef TestBaseWithParam<Size> PolarToCartFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(PolarToCartFixture, PolarToCart, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
dst1(srcSize, CV_32FC1), dst2(srcSize, CV_32FC1);
declare.in(src1, src2).out(dst1, dst2);
randu(src1, 0, 256);
randu(src2, 0, 256);
if (srcSize == OCL_SIZE_4000)
declare.time(5.4);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
gen(dst1, size, size, all_type[j], 0, 256);
polarToCart(src1, src2, dst, dst1, 1);
CPU_ON;
polarToCart(src1, src2, dst, dst1, 1);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
WARMUP_ON;
ocl::polarToCart(d_src1, d_src2, d_dst, d_dst1, 1);
WARMUP_OFF;
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclDst1(srcSize, src1.type()), oclDst2(srcSize, src1.type());
GPU_ON;
ocl::polarToCart(d_src1, d_src2, d_dst, d_dst1, 1);
GPU_OFF;
TEST_CYCLE() cv::ocl::polarToCart(oclSrc1, oclSrc2, oclDst1, oclDst2);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::polarToCart(d_src1, d_src2, d_dst, d_dst1, 1);
d_dst.download(ocl_dst);
d_dst1.download(ocl_dst1);
GPU_FULL_OFF;
double diff1 = checkNorm(ocl_dst1, dst1);
double diff2 = checkNorm(ocl_dst, dst);
double max_diff = max(diff1, diff2);
TestSystem::instance().setAccurate(max_diff<=.5?1:0, max_diff);
oclDst1.download(dst1);
oclDst2.download(dst2);
SANITY_CHECK(dst1, 5e-5);
SANITY_CHECK(dst2, 5e-5);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::polarToCart(src1, src2, dst1, dst2);
SANITY_CHECK(dst1, 5e-5);
SANITY_CHECK(dst2, 5e-5);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Magnitude ////////////////////////
PERFTEST(magnitude)
{
Mat x, y, mag, ocl_mag;
ocl::oclMat d_x, d_y, d_mag;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
typedef TestBaseWithParam<Size> MagnitudeFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(MagnitudeFixture, Magnitude, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
dst(srcSize, CV_32FC1);
randu(src1, 0, 1);
randu(src2, 0, 1);
declare.in(src1, src2).out(dst);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
gen(x, size, size, all_type[j], 0, 1);
gen(y, size, size, all_type[j], 0, 1);
magnitude(x, y, mag);
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclDst(srcSize, src1.type());
CPU_ON;
magnitude(x, y, mag);
CPU_OFF;
d_x.upload(x);
d_y.upload(y);
TEST_CYCLE() cv::ocl::magnitude(oclSrc1, oclSrc2, oclDst);
WARMUP_ON;
ocl::magnitude(d_x, d_y, d_mag);
WARMUP_OFF;
oclDst.download(dst);
GPU_ON;
ocl::magnitude(d_x, d_y, d_mag);
GPU_OFF;
GPU_FULL_ON;
d_x.upload(x);
d_y.upload(y);
ocl::magnitude(d_x, d_y, d_mag);
d_mag.download(ocl_mag);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_mag, mag, 1e-5);
SANITY_CHECK(dst, 1e-6);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::magnitude(src1, src2, dst);
SANITY_CHECK(dst, 1e-6);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Transpose ////////////////////////
PERFTEST(Transpose)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
typedef MulMatTypes TransposeMatTypes;
typedef tuple<Size, TransposeMatTypes> TransposeParams;
typedef TestBaseWithParam<TransposeParams> TransposeFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(TransposeFixture, Transpose,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
TransposeMatTypes::all()))
{
// getting params
TransposeParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
gen(src, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
transpose(src, dst);
TEST_CYCLE() cv::ocl::transpose(oclSrc, oclDst);
CPU_ON;
transpose(src, dst);
CPU_OFF;
d_src.upload(src);
oclDst.download(dst);
WARMUP_ON;
ocl::transpose(d_src, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::transpose(d_src, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::transpose(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::transpose(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Flip ////////////////////////
PERFTEST(Flip)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
typedef MulMatTypes FlipMatTypes;
typedef tuple<Size, FlipMatTypes> FlipParams;
typedef TestBaseWithParam<FlipParams> FlipFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(FlipFixture, Flip,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
FlipMatTypes::all()))
{
// getting params
TransposeParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " ; FLIP_BOTH";
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
gen(src, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
TEST_CYCLE() cv::ocl::flip(oclSrc, oclDst, 0);
flip(src, dst, 0);
oclDst.download(dst);
CPU_ON;
flip(src, dst, 0);
CPU_OFF;
d_src.upload(src);
WARMUP_ON;
ocl::flip(d_src, d_dst, 0);
WARMUP_OFF;
GPU_ON;
ocl::flip(d_src, d_dst, 0);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::flip(d_src, d_dst, 0);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::flip(src, dst, 0);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// minMax ////////////////////////
PERFTEST(minMax)
{
Mat src;
ocl::oclMat d_src;
double min_val = 0.0, max_val = 0.0;
double min_val_ = 0.0, max_val_ = 0.0;
Point min_loc, max_loc;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
typedef AddMatTypes minMaxMatTypes;
typedef tuple<Size, minMaxMatTypes> minMaxParams;
typedef TestBaseWithParam<minMaxParams> minMaxFixture;
gen(src, size, size, all_type[j], 0, 256);
CPU_ON;
minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
CPU_OFF;
d_src.upload(src);
PERF_TEST_P(minMaxFixture, minMax,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
minMaxMatTypes::all()))
{
// getting params
minMaxParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
WARMUP_ON;
ocl::minMax(d_src, &min_val_, &max_val_);
WARMUP_OFF;
// creating src data
Mat src(srcSize, type);
declare.in(src, WARMUP_RNG);
if(EeceptDoubleEQ<double>(max_val_, max_val) && EeceptDoubleEQ<double>(min_val_, min_val))
TestSystem::instance().setAccurate(1, max(fabs(max_val_-max_val), fabs(min_val_-min_val)));
else
TestSystem::instance().setAccurate(0, max(fabs(max_val_-max_val), fabs(min_val_-min_val)));
double min_val = 0.0, max_val = 0.0;
GPU_ON;
ocl::minMax(d_src, &min_val, &max_val);
GPU_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src);
GPU_FULL_ON;
d_src.upload(src);
ocl::minMax(d_src, &min_val, &max_val);
GPU_FULL_OFF;
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 (impl == "plain")
{
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);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// minMaxLoc ////////////////////////
PERFTEST(minMaxLoc)
typedef AddMatTypes minMaxLocMatTypes;
typedef tuple<Size, minMaxMatTypes> minMaxLocParams;
typedef TestBaseWithParam<minMaxLocParams> minMaxLocFixture;
PERF_TEST_P(minMaxLocFixture, minMaxLoc,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
minMaxLocMatTypes::all()))
{
Mat src;
ocl::oclMat d_src;
// getting params
minMaxLocParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type);
randu(src, 0, 1);
declare.in(src);
double min_val = 0.0, max_val = 0.0;
double min_val_ = 0.0, max_val_ = 0.0;
Point min_loc, max_loc;
Point min_loc_, max_loc_;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 1);
CPU_ON;
minMaxLoc(src, &min_val, &max_val, &min_loc, &max_loc);
CPU_OFF;
d_src.upload(src);
ocl::oclMat oclSrc(src);
WARMUP_ON;
ocl::minMaxLoc(d_src, &min_val_, &max_val_, &min_loc_, &max_loc_);
WARMUP_OFF;
TEST_CYCLE() cv::ocl::minMaxLoc(oclSrc, &min_val, &max_val, &min_loc, &max_loc);
double error0 = 0., error1 = 0., minlocVal = 0., minlocVal_ = 0., maxlocVal = 0., maxlocVal_ = 0.;
if(src.depth() == 0)
{
minlocVal = src.at<unsigned char>(min_loc);
minlocVal_ = src.at<unsigned char>(min_loc_);
maxlocVal = src.at<unsigned char>(max_loc);
maxlocVal_ = src.at<unsigned char>(max_loc_);
}
if(src.depth() == 1)
{
minlocVal = src.at<signed char>(min_loc);
minlocVal_ = src.at<signed char>(min_loc_);
maxlocVal = src.at<signed char>(max_loc);
maxlocVal_ = src.at<signed char>(max_loc_);
}
if(src.depth() == 2)
{
minlocVal = src.at<unsigned short>(min_loc);
minlocVal_ = src.at<unsigned short>(min_loc_);
maxlocVal = src.at<unsigned short>(max_loc);
maxlocVal_ = src.at<unsigned short>(max_loc_);
}
if(src.depth() == 3)
{
minlocVal = src.at<signed short>(min_loc);
minlocVal_ = src.at<signed short>(min_loc_);
maxlocVal = src.at<signed short>(max_loc);
maxlocVal_ = src.at<signed short>(max_loc_);
}
if(src.depth() == 4)
{
minlocVal = src.at<int>(min_loc);
minlocVal_ = src.at<int>(min_loc_);
maxlocVal = src.at<int>(max_loc);
maxlocVal_ = src.at<int>(max_loc_);
}
if(src.depth() == 5)
{
minlocVal = src.at<float>(min_loc);
minlocVal_ = src.at<float>(min_loc_);
maxlocVal = src.at<float>(max_loc);
maxlocVal_ = src.at<float>(max_loc_);
ASSERT_GE(max_val, min_val);
SANITY_CHECK(min_val);
SANITY_CHECK(max_val);
}
if(src.depth() == 6)
else if (impl == "plain")
{
minlocVal = src.at<double>(min_loc);
minlocVal_ = src.at<double>(min_loc_);
maxlocVal = src.at<double>(max_loc);
maxlocVal_ = src.at<double>(max_loc_);
}
error0 = ::abs(minlocVal_ - minlocVal);
error1 = ::abs(maxlocVal_ - maxlocVal);
if( EeceptDoubleEQ<double>(maxlocVal_, maxlocVal)
&&EeceptDoubleEQ<double>(minlocVal_, minlocVal)
&&EeceptDoubleEQ<double>(max_val_, max_val)
&&EeceptDoubleEQ<double>(min_val_, min_val))
TestSystem::instance().setAccurate(1, 0.);
else
TestSystem::instance().setAccurate(0, max(error0, error1));
GPU_ON;
ocl::minMaxLoc(d_src, &min_val, &max_val, &min_loc, &max_loc);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::minMaxLoc(d_src, &min_val, &max_val, &min_loc, &max_loc);
GPU_FULL_OFF;
}
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);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Sum ////////////////////////
PERFTEST(Sum)
{
Mat src;
Scalar cpures, gpures;
ocl::oclMat d_src;
int all_type[] = {CV_8UC1, CV_32SC1};
std::string type_name[] = {"CV_8UC1", "CV_32SC1"};
CV_ENUM(SumMatTypes, CV_8UC1, CV_32SC1)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef tuple<Size, SumMatTypes> SumParams;
typedef TestBaseWithParam<SumParams> SumFixture;
gen(src, size, size, all_type[j], 0, 60);
cpures = sum(src);
CPU_ON;
cpures = sum(src);
CPU_OFF;
d_src.upload(src);
WARMUP_ON;
gpures = ocl::sum(d_src);
WARMUP_OFF;
vector<double> diffs(4);
diffs[3] = fabs(cpures[3] - gpures[3]);
diffs[2] = fabs(cpures[2] - gpures[2]);
diffs[1] = fabs(cpures[1] - gpures[1]);
diffs[0] = fabs(cpures[0] - gpures[0]);
double max_diff = *max_element(diffs.begin(), diffs.end());
TestSystem::instance().setAccurate(max_diff<0.1?1:0, max_diff);
PERF_TEST_P(SumFixture, Sum,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
SumMatTypes::all()))
{
// getting params
SumParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type);
Scalar result;
randu(src, 0, 60);
declare.in(src);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src);
GPU_ON;
gpures = ocl::sum(d_src);
GPU_OFF;
TEST_CYCLE() result = cv::ocl::sum(oclSrc);
GPU_FULL_ON;
d_src.upload(src);
gpures = ocl::sum(d_src);
GPU_FULL_OFF;
SANITY_CHECK(result);
}
else if (impl == "plain")
{
TEST_CYCLE() result = cv::sum(src);
SANITY_CHECK(result);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// countNonZero ////////////////////////
PERFTEST(countNonZero)
{
Mat src;
ocl::oclMat d_src;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
countNonZero(src);
CV_ENUM(countNonZeroMatTypes, CV_8UC1, CV_32FC1)
int cpures = 0, gpures = 0;
CPU_ON;
cpures = countNonZero(src);
CPU_OFF;
d_src.upload(src);
typedef tuple<Size, countNonZeroMatTypes> countNonZeroParams;
typedef TestBaseWithParam<countNonZeroParams> countNonZeroFixture;
WARMUP_ON;
gpures = ocl::countNonZero(d_src);
WARMUP_OFF;
int diff = abs(cpures - gpures);
if(diff == 0)
TestSystem::instance().setAccurate(1, 0);
else
TestSystem::instance().setAccurate(0, diff);
PERF_TEST_P(countNonZeroFixture, countNonZero,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
countNonZeroMatTypes::all()))
{
// getting params
countNonZeroParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type);
int result = 0;
randu(src, 0, 256);
declare.in(src);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src);
GPU_ON;
ocl::countNonZero(d_src);
GPU_OFF;
TEST_CYCLE() result = cv::ocl::countNonZero(oclSrc);
GPU_FULL_ON;
d_src.upload(src);
ocl::countNonZero(d_src);
GPU_FULL_OFF;
SANITY_CHECK(result);
}
else if (impl == "plain")
{
TEST_CYCLE() result = cv::countNonZero(src);
SANITY_CHECK(result);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Phase ////////////////////////
PERFTEST(Phase)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
typedef TestBaseWithParam<Size> PhaseFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(PhaseFixture, Phase, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
dst(srcSize, CV_32FC1);
declare.in(src1, src2).out(dst);
randu(src1, 0, 256);
randu(src2, 0, 256);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclDst(srcSize, src1.type());
phase(src1, src2, dst, 1);
TEST_CYCLE() cv::ocl::phase(oclSrc1, oclSrc2, oclDst, 1);
CPU_ON;
phase(src1, src2, dst, 1);
CPU_OFF;
oclDst.download(dst);
d_src1.upload(src1);
d_src2.upload(src2);
WARMUP_ON;
ocl::phase(d_src1, d_src2, d_dst, 1);
WARMUP_OFF;
GPU_ON;
ocl::phase(d_src1, d_src2, d_dst, 1);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::phase(d_src1, d_src2, d_dst, 1);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-2);
SANITY_CHECK(dst, 1e-2);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::phase(src1, src2, dst, 1);
SANITY_CHECK(dst, 1e-2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// bitwise_and////////////////////////
PERFTEST(bitwise_and)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_8UC1, CV_32SC1};
std::string type_name[] = {"CV_8UC1", "CV_32SC1"};
typedef SumMatTypes BitwiseAndMatTypes;
typedef tuple<Size, BitwiseAndMatTypes> BitwiseAndParams;
typedef TestBaseWithParam<BitwiseAndParams> BitwiseAndFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(BitwiseAndFixture, bitwise_and,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
BitwiseAndMatTypes::all()))
{
// getting params
BitwiseAndParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
declare.in(src1, src2).out(dst);
randu(src1, 0, 256);
randu(src2, 0, 256);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
bitwise_and(src1, src2, dst);
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, src1.type());
CPU_ON;
bitwise_and(src1, src2, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
TEST_CYCLE() cv::ocl::bitwise_and(oclSrc1, oclSrc2, oclDst);
WARMUP_ON;
ocl::bitwise_and(d_src1, d_src2, d_dst);
WARMUP_OFF;
oclDst.download(dst);
GPU_ON;
ocl::bitwise_and(d_src1, d_src2, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::bitwise_and(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::bitwise_and(src1, src2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// bitwise_not////////////////////////
PERFTEST(bitwise_not)
{
Mat src1, dst, ocl_dst;
ocl::oclMat d_src1, d_dst;
int all_type[] = {CV_8UC1, CV_32SC1};
std::string type_name[] = {"CV_8UC1", "CV_32SC1"};
typedef SumMatTypes BitwiseNotMatTypes;
typedef tuple<Size, BitwiseNotMatTypes> BitwiseNotParams;
typedef TestBaseWithParam<BitwiseNotParams> BitwiseNotFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(BitwiseAndFixture, bitwise_not,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
BitwiseAndMatTypes::all()))
{
// getting params
BitwiseNotParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
bitwise_not(src1, dst);
TEST_CYCLE() cv::ocl::bitwise_not(oclSrc, oclDst);
CPU_ON;
bitwise_not(src1, dst);
CPU_OFF;
d_src1.upload(src1);
oclDst.download(dst);
WARMUP_ON;
ocl::bitwise_not(d_src1, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::bitwise_not(d_src1, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
ocl::bitwise_not(d_src1, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::bitwise_not(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// compare////////////////////////
PERFTEST(compare)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int CMP_EQ = 0;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
typedef countNonZeroMatTypes CompareMatTypes;
typedef tuple<Size, CompareMatTypes> CompareParams;
typedef TestBaseWithParam<CompareParams> CompareFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
PERF_TEST_P(CompareFixture, compare,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
CompareMatTypes::all()))
{
// getting params
CompareParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, CV_8UC1);
declare.in(src1, src2, WARMUP_RNG).out(dst);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
compare(src1, src2, dst, CMP_EQ);
CPU_ON;
compare(src1, src2, dst, CMP_EQ);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, CV_8UC1);
WARMUP_ON;
ocl::compare(d_src1, d_src2, d_dst, CMP_EQ);
WARMUP_OFF;
TEST_CYCLE() cv::ocl::compare(oclSrc1, oclSrc2, oclDst, CMP_EQ);
GPU_ON;
ocl::compare(d_src1, d_src2, d_dst, CMP_EQ);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::compare(d_src1, d_src2, d_dst, CMP_EQ);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::compare(src1, src2, dst, CMP_EQ);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// pow ////////////////////////
PERFTEST(pow)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 5, 16);
typedef TestBaseWithParam<Size> PowFixture;
pow(src, -2.0, dst);
PERF_TEST_P(PowFixture, pow, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
CPU_ON;
pow(src, -2.0, dst);
CPU_OFF;
d_src.upload(src);
d_dst.upload(dst);
// creating src data
Mat src(srcSize, CV_32F), dst(srcSize, CV_32F);
declare.in(src, WARMUP_RNG).out(dst);
WARMUP_ON;
ocl::pow(d_src, -2.0, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, src.type());
GPU_ON;
ocl::pow(d_src, -2.0, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::pow(oclSrc, -2.0, oclDst);
GPU_FULL_ON;
d_src.upload(src);
ocl::pow(d_src, -2.0, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1.0);
SANITY_CHECK(dst, 5e-2);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::pow(src, -2.0, dst);
SANITY_CHECK(dst, 5e-2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// MagnitudeSqr////////////////////////
PERFTEST(MagnitudeSqr)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
int all_type[] = {CV_32FC1};
std::string type_name[] = {"CV_32FC1"};
typedef TestBaseWithParam<Size> MagnitudeSqrFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t t = 0; t < sizeof(all_type) / sizeof(int); t++)
{
SUBTEST << size << 'x' << size << "; " << type_name[t];
PERF_TEST_P(MagnitudeSqrFixture, MagnitudeSqr, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
gen(src1, size, size, all_type[t], 0, 256);
gen(src2, size, size, all_type[t], 0, 256);
gen(dst, size, size, all_type[t], 0, 256);
// creating src data
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
dst(srcSize, CV_32FC1);
declare.in(src1, src2, WARMUP_RNG).out(dst);
CPU_ON;
for (int i = 0; i < src1.rows; ++i)
for (int j = 0; j < src1.cols; ++j)
// select implementation
if (impl == "ocl")
{
float val1 = src1.at<float>(i, j);
float val2 = src2.at<float>(i, j);
((float *)(dst.data))[i * dst.step / 4 + j] = val1 * val1 + val2 * val2;
}
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, src1.type());
WARMUP_ON;
ocl::magnitudeSqr(d_src1, d_src2, d_dst);
WARMUP_OFF;
TEST_CYCLE() cv::ocl::magnitudeSqr(oclSrc1, oclSrc2, oclDst);
GPU_ON;
ocl::magnitudeSqr(d_src1, d_src2, d_dst);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::magnitudeSqr(d_src1, d_src2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
SANITY_CHECK(dst, 1e-6, ERROR_RELATIVE);
}
else if (impl == "plain")
{
ASSERT_EQ(1, src1.channels());
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1.0);
TEST_CYCLE()
{
for (int y = 0; y < srcSize.height; ++y)
{
const float * const src1Data = reinterpret_cast<float *>(src1.data + src1.step * y);
const float * const src2Data = reinterpret_cast<float *>(src2.data + src2.step * y);
float * const dstData = reinterpret_cast<float *>(dst.data + dst.step * y);
for (int x = 0; x < srcSize.width; ++x)
{
float t0 = src1Data[x] * src1Data[x];
float t1 = src2Data[x] * src2Data[x];
dstData[x] = t0 + t1;
}
}
}
SANITY_CHECK(dst, 1e-6, ERROR_RELATIVE);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// AddWeighted////////////////////////
PERFTEST(AddWeighted)
{
Mat src1, src2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_dst;
typedef countNonZeroMatTypes AddWeightedMatTypes;
typedef tuple<Size, AddWeightedMatTypes> AddWeightedParams;
typedef TestBaseWithParam<AddWeightedParams> AddWeightedFixture;
PERF_TEST_P(AddWeightedFixture, AddWeighted,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
AddWeightedMatTypes::all()))
{
// getting params
AddWeightedParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src1(srcSize, type), src2(srcSize, type), dst(srcSize, type);
declare.in(src1, src2, WARMUP_RNG).out(dst);
double alpha = 2.0, beta = 1.0, gama = 3.0;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst(srcSize, type);
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
TEST_CYCLE() cv::ocl::addWeighted(oclSrc1, alpha, oclSrc2, beta, gama, oclDst);
oclDst.download(dst);
addWeighted(src1, alpha, src2, beta, gama, dst);
CPU_ON;
addWeighted(src1, alpha, src2, beta, gama, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
WARMUP_ON;
ocl::addWeighted(d_src1, alpha, d_src2, beta, gama, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::addWeighted(d_src1, alpha, d_src2, beta, gama, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::addWeighted(d_src1, alpha, d_src2, beta, gama, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::addWeighted(src1, alpha, src2, beta, gama, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,9 +45,15 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
///////////// blend ////////////////////////
template <typename T>
void blendLinearGold(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &weights1, const cv::Mat &weights2, cv::Mat &result_gold)
static void blendLinearGold(const cv::Mat &img1, const cv::Mat &img2,
const cv::Mat &weights1, const cv::Mat &weights2,
cv::Mat &result_gold)
{
result_gold.create(img1.size(), img1.type());
......@@ -63,60 +69,54 @@ void blendLinearGold(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &we
for (int x = 0; x < img1.cols * cn; ++x)
{
float w1 = weights1_row[x / cn];
float w2 = weights2_row[x / cn];
result_gold_row[x] = static_cast<T>((img1_row[x] * w1 + img2_row[x] * w2) / (w1 + w2 + 1e-5f));
int x1 = x * cn;
float w1 = weights1_row[x];
float w2 = weights2_row[x];
result_gold_row[x] = static_cast<T>((img1_row[x1] * w1
+ img2_row[x1] * w2) / (w1 + w2 + 1e-5f));
}
}
}
PERFTEST(blend)
typedef TestBaseWithParam<Size> blendLinearFixture;
PERF_TEST_P(blendLinearFixture, blendLinear, OCL_TYPICAL_MAT_SIZES)
{
Mat src1, src2, weights1, weights2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_weights1, d_weights2, d_dst;
// getting params
const Size srcSize = GetParam();
const int type = CV_8UC1;
const std::string impl = getSelectedImpl();
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
// creating src data
Mat src1(srcSize, type), src2(srcSize, CV_8UC1), dst;
Mat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
declare.in(src1, src2, WARMUP_RNG);
randu(weights1, 0.0f, 1.0f);
randu(weights2, 0.0f, 1.0f);
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " and CV_32FC1";
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(weights1, size, size, CV_32FC1, 0, 1);
gen(weights2, size, size, CV_32FC1, 0, 1);
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_ON;
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
WARMUP_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.f);
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst;
ocl::oclMat oclWeights1(weights1), oclWeights2(weights2);
TEST_CYCLE() cv::ocl::blendLinear(oclSrc1, oclSrc2, oclWeights1, oclWeights2, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,123 +45,242 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
#define OCL_BFMATCHER_TYPICAL_MAT_SIZES ::testing::Values(cv::Size(128, 500), cv::Size(128, 1000), cv::Size(128, 2000))
//////////////////// BruteForceMatch /////////////////
PERFTEST(BruteForceMatcher)
typedef TestBaseWithParam<Size> BruteForceMatcherFixture;
PERF_TEST_P(BruteForceMatcherFixture, match,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
{
Mat trainIdx_cpu;
Mat distance_cpu;
Mat allDist_cpu;
Mat nMatches_cpu;
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
// Init CPU matcher
int desc_len = 64;
vector<DMatch> matches;
Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
declare.in(query, train).time(srcSize.height == 2000 ? 8 : 4 );
randu(query, 0.0f, 1.0f);
randu(train, 0.0f, 1.0f);
if (impl == "plain")
{
BFMatcher matcher(NORM_L2);
TEST_CYCLE() matcher.match(query, train, matches);
Mat query;
gen(query, size, desc_len, CV_32F, 0, 1);
Mat train;
gen(train, size, desc_len, CV_32F, 0, 1);
// Output
vector< vector<DMatch> > matches(2);
vector< vector<DMatch> > d_matches(2);
SANITY_CHECK_MATCHES(matches);
}
else if (impl == "ocl")
{
// Init GPU matcher
ocl::BruteForceMatcher_OCL_base d_matcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
ocl::oclMat oclQuery(query), oclTrain(train);
ocl::oclMat d_query(query);
ocl::oclMat d_train(train);
TEST_CYCLE() oclMatcher.match(oclQuery, oclTrain, matches);
ocl::oclMat d_trainIdx, d_distance, d_allDist, d_nMatches;
SANITY_CHECK_MATCHES(matches);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
SUBTEST << size << "; match";
//PERF_TEST_P(BruteForceMatcherFixture, matchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
matcher.match(query, train, matches[0]);
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance;
CPU_ON;
matcher.match(query, train, matches[0]);
CPU_OFF;
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
WARMUP_ON;
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance);
WARMUP_OFF;
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance;
GPU_ON;
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance);
GPU_OFF;
// TEST_CYCLE() oclMatcher->matchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance);
GPU_FULL_ON;
d_query.upload(query);
d_train.upload(train);
d_matcher.match(d_query, d_train, d_matches[0]);
GPU_FULL_OFF;
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
int diff = abs((int)d_matches[0].size() - (int)matches[0].size());
if(diff == 0)
TestSystem::instance().setAccurate(1, 0);
else
TestSystem::instance().setAccurate(0, diff);
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
SUBTEST << size << "; knnMatch";
PERF_TEST_P(BruteForceMatcherFixture, knnMatch,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
matcher.knnMatch(query, train, matches, 2);
vector<vector<DMatch> > matches(2);
Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
randu(query, 0.0f, 1.0f);
randu(train, 0.0f, 1.0f);
CPU_ON;
matcher.knnMatch(query, train, matches, 2);
CPU_OFF;
declare.in(query, train);
if (srcSize.height == 2000)
declare.time(8);
WARMUP_ON;
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2);
WARMUP_OFF;
if (impl == "plain")
{
BFMatcher matcher (NORM_L2);
TEST_CYCLE() matcher.knnMatch(query, train, matches, 2);
GPU_ON;
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2);
GPU_OFF;
std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
else if (impl == "ocl")
{
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
ocl::oclMat oclQuery(query), oclTrain(train);
GPU_FULL_ON;
d_query.upload(query);
d_train.upload(train);
d_matcher.knnMatch(d_query, d_train, d_matches, 2);
GPU_FULL_OFF;
TEST_CYCLE() oclMatcher.knnMatch(oclQuery, oclTrain, matches, 2);
diff = abs((int)d_matches[0].size() - (int)matches[0].size());
if(diff == 0)
TestSystem::instance().setAccurate(1, 0);
std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
TestSystem::instance().setAccurate(0, diff);
CV_TEST_FAIL_NO_IMPL();
}
SUBTEST << size << "; radiusMatch";
//PERF_TEST_P(BruteForceMatcherFixture, knnMatchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
float max_distance = 2.0f;
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance, allDist;
matcher.radiusMatch(query, train, matches, max_distance);
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
CPU_ON;
matcher.radiusMatch(query, train, matches, max_distance);
CPU_OFF;
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance, oclAllDist;
d_trainIdx.release();
// TEST_CYCLE() oclMatcher->knnMatchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance, oclAllDist, 2);
WARMUP_ON;
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance);
WARMUP_OFF;
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
// oclAllDist.download(allDist);
GPU_ON;
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance);
GPU_OFF;
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// SANITY_CHECK(allDist);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
GPU_FULL_ON;
d_query.upload(query);
d_train.upload(train);
d_matcher.radiusMatch(d_query, d_train, d_matches, max_distance);
GPU_FULL_OFF;
PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch,
OCL_BFMATCHER_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
diff = abs((int)d_matches[0].size() - (int)matches[0].size());
if(diff == 0)
TestSystem::instance().setAccurate(1, 0);
else
TestSystem::instance().setAccurate(0, diff);
const float max_distance = 2.0f;
vector<vector<DMatch> > matches(2);
Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
declare.in(query, train);
Mat trainIdx, distance, allDist;
randu(query, 0.0f, 1.0f);
randu(train, 0.0f, 1.0f);
if (impl == "plain")
{
BFMatcher matcher (NORM_L2);
TEST_CYCLE() matcher.radiusMatch(query, matches, max_distance);
std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
else if (impl == "ocl")
{
ocl::oclMat oclQuery(query), oclTrain(train);
ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist);
TEST_CYCLE() oclMatcher.radiusMatch(oclQuery, oclTrain, matches, max_distance);
std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0);
SANITY_CHECK_MATCHES(matches1);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
//PERF_TEST_P(BruteForceMatcherFixture, radiusMatchSingle,
// OCL_BFMATCHER_TYPICAL_MAT_SIZES)
//{
// const Size srcSize = GetParam();
// const string impl = getSelectedImpl();
// const float max_distance = 2.0f;
// Mat query(srcSize, CV_32F), train(srcSize, CV_32F);
// Mat trainIdx, distance, nMatches;
// randu(query, 0.0f, 1.0f);
// randu(train, 0.0f, 1.0f);
// if (impl == "plain")
// CV_TEST_FAIL_NO_IMPL();
// else if (impl == "ocl")
// {
// ocl::oclMat oclQuery(query), oclTrain(train), oclTrainIdx, oclDistance, oclNMatches;
// TEST_CYCLE() oclMatcher->radiusMatchSingle(oclQuery, oclTrain, oclTrainIdx, oclDistance, oclNMatches, max_distance);
// oclTrainIdx.download(trainIdx);
// oclDistance.download(distance);
// oclNMatches.download(nMatches);
// SANITY_CHECK(trainIdx);
// SANITY_CHECK(distance);
// SANITY_CHECK(nMatches);
// }
//#ifdef HAVE_OPENCV_GPU
// else if (impl == "gpu")
// CV_TEST_FAIL_NO_IMPL();
//#endif
// else
// CV_TEST_FAIL_NO_IMPL();
//}
#undef OCL_BFMATCHER_TYPICAL_MAT_SIZES
......@@ -45,48 +45,49 @@
//M*/
#include "perf_precomp.hpp"
///////////// StereoMatchBM ////////////////////////
PERFTEST(StereoMatchBM)
PERF_TEST(StereoMatchBMFixture, DISABLED_StereoMatchBM)
{
Mat left_image = imread(abspath("aloeL.jpg"), cv::IMREAD_GRAYSCALE);
Mat right_image = imread(abspath("aloeR.jpg"), cv::IMREAD_GRAYSCALE);
Mat disp,dst;
ocl::oclMat d_left, d_right,d_disp;
int n_disp= 128;
int winSize =19;
Mat left_image = imread(getDataPath("gpu/stereobm/aloe-L.png"), cv::IMREAD_GRAYSCALE);
Mat right_image = imread(getDataPath("gpu/stereobm/aloe-R.png"), cv::IMREAD_GRAYSCALE);
SUBTEST << left_image.cols << 'x' << left_image.rows << "; aloeL.jpg ;"<< right_image.cols << 'x' << right_image.rows << "; aloeR.jpg ";
ASSERT_TRUE(!left_image.empty()) << "no input image";
ASSERT_TRUE(!right_image.empty()) << "no input image";
ASSERT_TRUE(right_image.size() == left_image.size());
ASSERT_TRUE(right_image.size() == left_image.size());
StereoBM bm(0, n_disp, winSize);
bm(left_image, right_image, dst);
const std::string impl = getSelectedImpl();
const int n_disp = 128, winSize = 19;
Mat disp(left_image.size(), CV_16SC1);
CPU_ON;
bm(left_image, right_image, dst);
CPU_OFF;
declare.in(left_image, right_image).out(disp);
d_left.upload(left_image);
d_right.upload(right_image);
if (impl == "ocl")
{
ocl::oclMat oclLeft(left_image), oclRight(right_image),
oclDisp(left_image.size(), CV_16SC1);
ocl::StereoBM_OCL oclBM(0, n_disp, winSize);
ocl::StereoBM_OCL d_bm(0, n_disp, winSize);
TEST_CYCLE() oclBM(oclLeft, oclRight, oclDisp);
WARMUP_ON;
d_bm(d_left, d_right, d_disp);
WARMUP_OFF;
oclDisp.download(disp);
cv::Mat ocl_mat;
d_disp.download(ocl_mat);
ocl_mat.convertTo(ocl_mat, dst.type());
GPU_ON;
d_bm(d_left, d_right, d_disp);
GPU_OFF;
SANITY_CHECK(disp);
}
else if (impl == "plain")
{
StereoBM bm(0, n_disp, winSize);
GPU_FULL_ON;
d_left.upload(left_image);
d_right.upload(right_image);
d_bm(d_left, d_right, d_disp);
d_disp.download(disp);
GPU_FULL_OFF;
TEST_CYCLE() bm(left_image, right_image, disp);
TestSystem::instance().setAccurate(-1, 0.);
SANITY_CHECK(disp);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,41 +45,38 @@
//M*/
#include "perf_precomp.hpp"
///////////// Canny ////////////////////////
PERFTEST(Canny)
{
Mat img = imread(abspath("aloeL.jpg"), CV_LOAD_IMAGE_GRAYSCALE);
if (img.empty())
{
throw runtime_error("can't open aloeL.jpg");
}
SUBTEST << img.cols << 'x' << img.rows << "; aloeL.jpg" << "; edges" << "; CV_8UC1";
using namespace perf;
Mat edges(img.size(), CV_8UC1), ocl_edges;
///////////// Canny ////////////////////////
CPU_ON;
Canny(img, edges, 50.0, 100.0);
CPU_OFF;
PERF_TEST(CannyFixture, Canny)
{
Mat img = imread(getDataPath("gpu/stereobm/aloe-L.png"), cv::IMREAD_GRAYSCALE),
edges(img.size(), CV_8UC1);
ASSERT_TRUE(!img.empty()) << "can't open aloeL.jpg";
ocl::oclMat d_img(img);
ocl::oclMat d_edges;
ocl::CannyBuf d_buf;
const std::string impl = getSelectedImpl();
declare.in(img).out(edges);
WARMUP_ON;
ocl::Canny(d_img, d_buf, d_edges, 50.0, 100.0);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclImg(img), oclEdges(img.size(), CV_8UC1);
GPU_ON;
ocl::Canny(d_img, d_buf, d_edges, 50.0, 100.0);
GPU_OFF;
TEST_CYCLE() Canny(oclImg, oclEdges, 50.0, 100.0);
oclEdges.download(edges);
GPU_FULL_ON;
d_img.upload(img);
ocl::Canny(d_img, d_buf, d_edges, 50.0, 100.0);
d_edges.download(ocl_edges);
GPU_FULL_OFF;
SANITY_CHECK(edges);
}
else if (impl == "plain")
{
TEST_CYCLE() Canny(img, edges, 50.0, 100.0);
TestSystem::instance().ExceptedMatSimilar(edges, ocl_edges, 2e-2);
SANITY_CHECK(edges);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,49 +45,39 @@
//M*/
#include "perf_precomp.hpp"
///////////// cvtColor////////////////////////
PERFTEST(cvtColor)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
using namespace perf;
int all_type[] = {CV_8UC4};
std::string type_name[] = {"CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
gen(src, size, size, all_type[j], 0, 256);
SUBTEST << size << "x" << size << "; " << type_name[j] << " ; CV_RGBA2GRAY";
cvtColor(src, dst, CV_RGBA2GRAY, 4);
///////////// cvtColor////////////////////////
CPU_ON;
cvtColor(src, dst, CV_RGBA2GRAY, 4);
CPU_OFF;
typedef TestBaseWithParam<Size> cvtColorFixture;
d_src.upload(src);
PERF_TEST_P(cvtColorFixture, cvtColor, OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
WARMUP_ON;
ocl::cvtColor(d_src, d_dst, CV_RGBA2GRAY, 4);
WARMUP_OFF;
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
declare.in(src).out(dst);
GPU_ON;
ocl::cvtColor(d_src, d_dst, CV_RGBA2GRAY, 4);
GPU_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(src.size(), CV_8UC4);
GPU_FULL_ON;
d_src.upload(src);
ocl::cvtColor(d_src, d_dst, CV_RGBA2GRAY, 4);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TEST_CYCLE() ocl::cvtColor(oclSrc, oclDst, CV_RGBA2GRAY, 4);
oclDst.download(dst);
TestSystem::instance().ExceptedMatSimilar(dst, ocl_dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::cvtColor(src, dst, CV_RGBA2GRAY, 4);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,47 +45,43 @@
//M*/
#include "perf_precomp.hpp"
///////////// dft ////////////////////////
PERFTEST(dft)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_32FC2};
std::string type_name[] = {"CV_32FC2"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " ; complex-to-complex";
using namespace perf;
gen(src, size, size, all_type[j], Scalar::all(0), Scalar::all(1));
///////////// dft ////////////////////////
dft(src, dst);
typedef TestBaseWithParam<Size> dftFixture;
CPU_ON;
dft(src, dst);
CPU_OFF;
PERF_TEST_P(dftFixture, DISABLED_dft, OCL_TYPICAL_MAT_SIZES)
{
const std::string impl = getSelectedImpl();
Size srcSize = GetParam();
d_src.upload(src);
Mat src(srcSize, CV_32FC2), dst;
randu(src, 0.0f, 1.0f);
declare.in(src);
WARMUP_ON;
ocl::dft(d_src, d_dst, Size(size, size));
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst;
GPU_ON;
ocl::dft(d_src, d_dst, Size(size, size));
GPU_OFF;
EXPECT_NO_THROW({
TEST_CYCLE() cv::ocl::dft(oclSrc, oclDst);
});
GPU_FULL_ON;
d_src.upload(src);
ocl::dft(d_src, d_dst, Size(size, size));
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, src.size().area() * 1e-4);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::dft(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,333 +45,344 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::get;
using std::tr1::tuple;
///////////// Blur////////////////////////
PERFTEST(Blur)
{
Mat src1, dst, ocl_dst;
ocl::oclMat d_src1, d_dst;
Size ksize = Size(3, 3);
int bordertype = BORDER_CONSTANT;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
CV_ENUM(BlurMatType, CV_8UC1, CV_8UC4)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef tuple<Size, BlurMatType> BlurParams;
typedef TestBaseWithParam<BlurParams> BlurFixture;
gen(src1, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
PERF_TEST_P(BlurFixture, Blur,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
BlurMatType::all()))
{
// getting params
BlurParams params = GetParam();
const Size srcSize = get<0>(params), ksize(3, 3);
const int type = get<1>(params), bordertype = BORDER_CONSTANT;
blur(src1, dst, ksize, Point(-1, -1), bordertype);
const std::string impl = getSelectedImpl();
CPU_ON;
blur(src1, dst, ksize, Point(-1, -1), bordertype);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
d_src1.upload(src1);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(5);
WARMUP_ON;
ocl::blur(d_src1, d_dst, ksize, Point(-1, -1), bordertype);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::blur(d_src1, d_dst, ksize, Point(-1, -1), bordertype);
GPU_OFF;
TEST_CYCLE() cv::ocl::blur(oclSrc, oclDst, ksize, Point(-1, -1), bordertype);
GPU_FULL_ON;
d_src1.upload(src1);
ocl::blur(d_src1, d_dst, ksize, Point(-1, -1), bordertype);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1.0);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::blur(src, dst, ksize, Point(-1, -1), bordertype);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Laplacian////////////////////////
PERFTEST(Laplacian)
{
Mat src1, dst, ocl_dst;
ocl::oclMat d_src1, d_dst;
int ksize = 3;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
typedef BlurMatType LaplacianMatType;
typedef tuple<Size, LaplacianMatType> LaplacianParams;
typedef TestBaseWithParam<LaplacianParams> LaplacianFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src1, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
PERF_TEST_P(LaplacianFixture, Laplacian,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
LaplacianMatType::all()))
{
// getting params
LaplacianParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
Laplacian(src1, dst, -1, ksize, 1);
const std::string impl = getSelectedImpl();
CPU_ON;
Laplacian(src1, dst, -1, ksize, 1);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
d_src1.upload(src1);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(6);
WARMUP_ON;
ocl::Laplacian(d_src1, d_dst, -1, ksize, 1);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::Laplacian(d_src1, d_dst, -1, ksize, 1);
GPU_OFF;
TEST_CYCLE() cv::ocl::Laplacian(oclSrc, oclDst, -1, ksize, 1);
GPU_FULL_ON;
d_src1.upload(src1);
ocl::Laplacian(d_src1, d_dst, -1, ksize, 1);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::Laplacian(src, dst, -1, ksize, 1);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Erode ////////////////////
PERFTEST(Erode)
{
Mat src, dst, ker, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4", "CV_32FC1", "CV_32FC4"};
CV_ENUM(ErodeMatType, CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef tuple<Size, ErodeMatType> ErodeParams;
typedef TestBaseWithParam<ErodeParams> ErodeFixture;
gen(src, size, size, all_type[j], Scalar::all(0), Scalar::all(256));
ker = getStructuringElement(MORPH_RECT, Size(3, 3));
PERF_TEST_P(ErodeFixture, Erode,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ErodeMatType::all()))
{
// getting params
ErodeParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
const Mat ker = getStructuringElement(MORPH_RECT, Size(ksize, ksize));
erode(src, dst, ker);
const std::string impl = getSelectedImpl();
CPU_ON;
erode(src, dst, ker);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst).in(ker);
d_src.upload(src);
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(5);
WARMUP_ON;
ocl::erode(d_src, d_dst, ker);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type), oclKer(ker);
GPU_ON;
ocl::erode(d_src, d_dst, ker);
GPU_OFF;
TEST_CYCLE() cv::ocl::erode(oclSrc, oclDst, oclKer);
GPU_FULL_ON;
d_src.upload(src);
ocl::erode(d_src, d_dst, ker);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::erode(src, dst, ker);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Sobel ////////////////////////
PERFTEST(Sobel)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int dx = 1;
int dy = 1;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef BlurMatType SobelMatType;
typedef tuple<Size, SobelMatType> SobelMatParams;
typedef TestBaseWithParam<SobelMatParams> SobelFixture;
gen(src, size, size, all_type[j], 0, 256);
PERF_TEST_P(SobelFixture, Sobel,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
SobelMatType::all()))
{
// getting params
SobelMatParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), dx = 1, dy = 1;
Sobel(src, dst, -1, dx, dy);
const std::string impl = getSelectedImpl();
CPU_ON;
Sobel(src, dst, -1, dx, dy);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
d_src.upload(src);
if ((srcSize == OCL_SIZE_2000 && type == CV_8UC4) ||
(srcSize == OCL_SIZE_4000 && type == CV_8UC1))
declare.time(5.5);
else if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(20);
WARMUP_ON;
ocl::Sobel(d_src, d_dst, -1, dx, dy);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::Sobel(d_src, d_dst, -1, dx, dy);
GPU_OFF;
TEST_CYCLE() cv::ocl::Sobel(oclSrc, oclDst, -1, dx, dy);
GPU_FULL_ON;
d_src.upload(src);
ocl::Sobel(d_src, d_dst, -1, dx, dy);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::Sobel(src, dst, -1, dx, dy);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Scharr ////////////////////////
PERFTEST(Scharr)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int dx = 1;
int dy = 0;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
typedef BlurMatType ScharrMatType;
typedef tuple<Size, ScharrMatType> ScharrParams;
typedef TestBaseWithParam<ScharrParams> ScharrFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
PERF_TEST_P(ScharrFixture, Scharr,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ScharrMatType::all()))
{
// getting params
ScharrParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), dx = 1, dy = 0;
Scharr(src, dst, -1, dx, dy);
const std::string impl = getSelectedImpl();
CPU_ON;
Scharr(src, dst, -1, dx, dy);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
d_src.upload(src);
if ((srcSize == OCL_SIZE_2000 && type == CV_8UC4) ||
(srcSize == OCL_SIZE_4000 && type == CV_8UC1))
declare.time(5.5);
else if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(21);
WARMUP_ON;
ocl::Scharr(d_src, d_dst, -1, dx, dy);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::Scharr(d_src, d_dst, -1, dx, dy);
GPU_OFF;
TEST_CYCLE() cv::ocl::Scharr(oclSrc, oclDst, -1, dx, dy);
GPU_FULL_ON;
d_src.upload(src);
ocl::Scharr(d_src, d_dst, -1, dx, dy);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::Scharr(src, dst, -1, dx, dy);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// GaussianBlur ////////////////////////
PERFTEST(GaussianBlur)
{
Mat src, dst, ocl_dst;
int all_type[] = {CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4", "CV_32FC1", "CV_32FC4"};
const int ksize = 7;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef ErodeMatType GaussianBlurMatType;
typedef tuple<Size, GaussianBlurMatType> GaussianBlurParams;
typedef TestBaseWithParam<GaussianBlurParams> GaussianBlurFixture;
gen(src, size, size, all_type[j], 0, 256);
PERF_TEST_P(GaussianBlurFixture, GaussianBlur,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
GaussianBlurMatType::all()))
{
// getting params
GaussianBlurParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 7;
GaussianBlur(src, dst, Size(ksize, ksize), 0);
const std::string impl = getSelectedImpl();
CPU_ON;
GaussianBlur(src, dst, Size(ksize, ksize), 0);
CPU_OFF;
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
ocl::oclMat d_src(src);
ocl::oclMat d_dst;
const double eps = src.depth() == CV_8U ? 1 + DBL_EPSILON : 3e-4;
WARMUP_ON;
ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
WARMUP_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
GPU_OFF;
TEST_CYCLE() cv::ocl::GaussianBlur(oclSrc, oclDst, Size(ksize, ksize), 0);
GPU_FULL_ON;
d_src.upload(src);
ocl::GaussianBlur(d_src, d_dst, Size(ksize, ksize), 0);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1.0);
SANITY_CHECK(dst, eps);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::GaussianBlur(src, dst, Size(ksize, ksize), 0);
SANITY_CHECK(dst, eps);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// filter2D////////////////////////
PERFTEST(filter2D)
{
Mat src;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
gen(src, size, size, all_type[j], 0, 256);
const int ksize = 3;
SUBTEST << "ksize = " << ksize << "; " << size << 'x' << size << "; " << type_name[j] ;
typedef BlurMatType filter2DMatType;
typedef tuple<Size, filter2DMatType> filter2DParams;
typedef TestBaseWithParam<filter2DParams> filter2DFixture;
Mat kernel;
gen(kernel, ksize, ksize, CV_32SC1, -3.0, 3.0);
Mat dst, ocl_dst;
cv::filter2D(src, dst, -1, kernel);
PERF_TEST_P(filter2DFixture, filter2D,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
filter2DMatType::all()))
{
// getting params
filter2DParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), ksize = 3;
CPU_ON;
cv::filter2D(src, dst, -1, kernel);
CPU_OFF;
const std::string impl = getSelectedImpl();
ocl::oclMat d_src(src), d_dst;
Mat src(srcSize, type), dst(srcSize, type), kernel(ksize, ksize, CV_32SC1);
declare.in(src, WARMUP_RNG).in(kernel).out(dst);
randu(kernel, -3.0, 3.0);
WARMUP_ON;
ocl::filter2D(d_src, d_dst, -1, kernel);
WARMUP_OFF;
if (srcSize == OCL_SIZE_4000 && type == CV_8UC4)
declare.time(8);
GPU_ON;
ocl::filter2D(d_src, d_dst, -1, kernel);
GPU_OFF;
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type), oclKernel(kernel);
GPU_FULL_ON;
d_src.upload(src);
ocl::filter2D(d_src, d_dst, -1, kernel);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TEST_CYCLE() cv::ocl::filter2D(oclSrc, oclDst, -1, oclKernel);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, 1e-5);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::filter2D(src, dst, -1, kernel);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,46 +45,46 @@
//M*/
#include "perf_precomp.hpp"
///////////// gemm ////////////////////////
PERFTEST(gemm)
{
Mat src1, src2, src3, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_src3, d_dst;
using namespace perf;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size;
///////////// gemm ////////////////////////
gen(src1, size, size, CV_32FC1, Scalar::all(-10), Scalar::all(10));
gen(src2, size, size, CV_32FC1, Scalar::all(-10), Scalar::all(10));
gen(src3, size, size, CV_32FC1, Scalar::all(-10), Scalar::all(10));
typedef TestBaseWithParam<Size> gemmFixture;
gemm(src1, src2, 1.0, src3, 1.0, dst);
PERF_TEST_P(gemmFixture, DISABLED_gemm, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
CPU_ON;
gemm(src1, src2, 1.0, src3, 1.0, dst);
CPU_OFF;
Mat src1(srcSize, CV_32FC1), src2(srcSize, CV_32FC1),
src3(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
declare.in(src1, src2, src3).out(dst);
randu(src1, -10.0f, 10.0f);
randu(src2, -10.0f, 10.0f);
randu(src3, -10.0f, 10.0f);
d_src1.upload(src1);
d_src2.upload(src2);
d_src3.upload(src3);
if (impl == "ocl")
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2),
oclSrc3(src3), oclDst(srcSize, CV_32FC1);
WARMUP_ON;
ocl::gemm(d_src1, d_src2, 1.0, d_src3, 1.0, d_dst);
WARMUP_OFF;
TEST_CYCLE() cv::ocl::gemm(oclSrc1, oclSrc2, 1.0, oclSrc3, 1.0, oclDst);
GPU_ON;
ocl::gemm(d_src1, d_src2, 1.0, d_src3, 1.0, d_dst);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
d_src3.upload(src3);
ocl::gemm(d_src1, d_src2, 1.0, d_src3, 1.0, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::gemm(src1, src2, 1.0, src3, 1.0, dst);
TestSystem::instance().ExpectedMatNear(ocl_dst, dst, src1.cols * src1.rows * 1e-4);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -46,56 +46,54 @@
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
///////////// GoodFeaturesToTrack ////////////////////////
PERFTEST(GoodFeaturesToTrack)
{
using namespace cv;
int maxCorners = 2000;
double qualityLevel = 0.01;
typedef tuple<string, double> GoodFeaturesToTrackParams;
typedef TestBaseWithParam<GoodFeaturesToTrackParams> GoodFeaturesToTrackFixture;
std::string images[] = { "rubberwhale1.png", "aloeL.jpg" };
PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrack,
::testing::Combine(::testing::Values(string("gpu/opticalflow/rubberwhale1.png"),
string("gpu/stereobm/aloe-L.png")),
::testing::Range(0.0, 4.0, 3.0)))
{
std::vector<cv::Point2f> pts_gold;
std::vector<cv::Point2f> pts_gold, pts_ocl;
// getting params
GoodFeaturesToTrackParams param = GetParam();
const string fileName = getDataPath(get<0>(param)), impl = getSelectedImpl();
const int maxCorners = 2000;
const double qualityLevel = 0.01, minDistance = get<1>(param);
for(size_t imgIdx = 0; imgIdx < (sizeof(images)/sizeof(std::string)); ++imgIdx)
{
Mat frame = imread(abspath(images[imgIdx]), IMREAD_GRAYSCALE);
CV_Assert(!frame.empty());
Mat frame = imread(fileName, IMREAD_GRAYSCALE);
declare.in(frame);
ASSERT_TRUE(!frame.empty()) << "no input image";
for(float minDistance = 0; minDistance < 4; minDistance += 3.0)
if (impl == "ocl")
{
SUBTEST << "image = " << images[imgIdx] << "; ";
SUBTEST << "minDistance = " << minDistance << "; ";
cv::goodFeaturesToTrack(frame, pts_gold, maxCorners, qualityLevel, minDistance);
CPU_ON;
cv::goodFeaturesToTrack(frame, pts_gold, maxCorners, qualityLevel, minDistance);
CPU_OFF;
ocl::oclMat oclFrame(frame), pts_oclmat;
cv::ocl::GoodFeaturesToTrackDetector_OCL detector(maxCorners, qualityLevel, minDistance);
ocl::oclMat frame_ocl(frame), pts_oclmat;
WARMUP_ON;
detector(frame_ocl, pts_oclmat);
WARMUP_OFF;
detector.downloadPoints(pts_oclmat, pts_ocl);
TEST_CYCLE() detector(oclFrame, pts_oclmat);
double diff = abs(static_cast<float>(pts_gold.size() - pts_ocl.size()));
TestSystem::instance().setAccurate(diff == 0.0, diff);
detector.downloadPoints(pts_oclmat, pts_gold);
GPU_ON;
detector(frame_ocl, pts_oclmat);
GPU_OFF;
GPU_FULL_ON;
frame_ocl.upload(frame);
detector(frame_ocl, pts_oclmat);
detector.downloadPoints(pts_oclmat, pts_ocl);
GPU_FULL_OFF;
SANITY_CHECK(pts_gold);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::goodFeaturesToTrack(frame, pts_gold,
maxCorners, qualityLevel, minDistance);
SANITY_CHECK(pts_gold);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,6 +45,8 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
///////////// Haar ////////////////////////
namespace cv
{
......@@ -83,61 +85,45 @@ public:
}
}
PERFTEST(Haar)
{
Mat img = imread(abspath("basketball1.png"), CV_LOAD_IMAGE_GRAYSCALE);
if (img.empty())
{
throw runtime_error("can't open basketball1.png");
}
PERF_TEST(HaarFixture, Haar)
{
const std::string impl = getSelectedImpl();
vector<Rect> faces;
CascadeClassifier faceCascadeCPU;
Mat img = imread(getDataPath("gpu/haarcascade/basketball1.png"), CV_LOAD_IMAGE_GRAYSCALE);
ASSERT_TRUE(!img.empty()) << "can't open basketball1.png";
declare.in(img);
if (!faceCascadeCPU.load(abspath("haarcascade_frontalface_alt.xml")))
if (impl == "plain")
{
throw runtime_error("can't load haarcascade_frontalface_alt.xml");
}
vector<Rect> faces;
CascadeClassifier faceCascade;
ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))
<< "can't load haarcascade_frontalface_alt.xml";
SUBTEST << img.cols << "x" << img.rows << "; scale image";
CPU_ON;
faceCascadeCPU.detectMultiScale(img, faces,
TEST_CYCLE() faceCascade.detectMultiScale(img, faces,
1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
CPU_OFF;
vector<Rect> oclfaces;
ocl::CascadeClassifier_GPU faceCascade;
if (!faceCascade.load(abspath("haarcascade_frontalface_alt.xml")))
{
throw runtime_error("can't load haarcascade_frontalface_alt.xml");
SANITY_CHECK(faces, 4 + 1e-4);
}
else if (impl == "ocl")
{
ocl::CascadeClassifier_GPU faceCascade;
ocl::oclMat oclImg(img);
ocl::oclMat d_img(img);
ASSERT_TRUE(faceCascade.load(getDataPath("gpu/haarcascade/haarcascade_frontalface_alt.xml")))
<< "can't load haarcascade_frontalface_alt.xml";
WARMUP_ON;
faceCascade.detectMultiScale(d_img, oclfaces,
TEST_CYCLE() faceCascade.detectMultiScale(oclImg, faces,
1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
WARMUP_OFF;
if(faces.size() == oclfaces.size())
TestSystem::instance().setAccurate(1, 0);
else
TestSystem::instance().setAccurate(0, abs((int)faces.size() - (int)oclfaces.size()));
faces.clear();
GPU_ON;
faceCascade.detectMultiScale(d_img, oclfaces,
1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
GPU_OFF;
SANITY_CHECK(faces, 4 + 1e-4);
}
GPU_FULL_ON;
d_img.upload(img);
faceCascade.detectMultiScale(d_img, oclfaces,
1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));
GPU_FULL_OFF;
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,50 +45,42 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
///////////// HOG////////////////////////
PERFTEST(HOG)
PERF_TEST(HOGFixture, HOG)
{
Mat src = imread(abspath("road.png"), cv::IMREAD_GRAYSCALE);
Mat src = imread(getDataPath("gpu/hog/road.png"), cv::IMREAD_GRAYSCALE);
ASSERT_TRUE(!src.empty()) << "can't open input image road.png";
if (src.empty())
{
throw runtime_error("can't open road.png");
}
const std::string impl = getSelectedImpl();
std::vector<cv::Rect> found_locations;
declare.in(src).time(5);
if (impl == "plain")
{
cv::HOGDescriptor hog;
hog.setSVMDetector(hog.getDefaultPeopleDetector());
std::vector<cv::Rect> found_locations;
std::vector<cv::Rect> d_found_locations;
SUBTEST << src.cols << 'x' << src.rows << "; road.png";
hog.detectMultiScale(src, found_locations);
CPU_ON;
hog.detectMultiScale(src, found_locations);
CPU_OFF;
TEST_CYCLE() hog.detectMultiScale(src, found_locations);
SANITY_CHECK(found_locations, 1 + DBL_EPSILON);
}
else if (impl == "ocl")
{
cv::ocl::HOGDescriptor ocl_hog;
ocl_hog.setSVMDetector(ocl_hog.getDefaultPeopleDetector());
ocl::oclMat d_src;
d_src.upload(src);
ocl::oclMat oclSrc(src);
WARMUP_ON;
ocl_hog.detectMultiScale(d_src, d_found_locations);
WARMUP_OFF;
TEST_CYCLE() ocl_hog.detectMultiScale(oclSrc, found_locations);
if(d_found_locations.size() == found_locations.size())
TestSystem::instance().setAccurate(1, 0);
SANITY_CHECK(found_locations, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
TestSystem::instance().setAccurate(0, abs((int)found_locations.size() - (int)d_found_locations.size()));
GPU_ON;
ocl_hog.detectMultiScale(d_src, found_locations);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl_hog.detectMultiScale(d_src, found_locations);
GPU_FULL_OFF;
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,295 +45,299 @@
//M*/
#include "perf_precomp.hpp"
///////////// equalizeHist ////////////////////////
PERFTEST(equalizeHist)
{
Mat src, dst, ocl_dst;
int all_type[] = {CV_8UC1};
std::string type_name[] = {"CV_8UC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
gen(src, size, size, all_type[j], 0, 256);
///////////// equalizeHist ////////////////////////
equalizeHist(src, dst);
typedef TestBaseWithParam<Size> equalizeHistFixture;
CPU_ON;
equalizeHist(src, dst);
CPU_OFF;
PERF_TEST_P(equalizeHistFixture, equalizeHist, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
ocl::oclMat d_src(src);
ocl::oclMat d_dst;
ocl::oclMat d_hist;
ocl::oclMat d_buf;
// creating src data
Mat src(srcSize, CV_8UC1), dst(srcSize, CV_8UC1);
declare.in(src, WARMUP_RNG).out(dst);
WARMUP_ON;
ocl::equalizeHist(d_src, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, src.type());
GPU_ON;
ocl::equalizeHist(d_src, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::equalizeHist(oclSrc, oclDst);
GPU_FULL_ON;
d_src.upload(src);
ocl::equalizeHist(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.1);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::equalizeHist(src, dst);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
/////////// CopyMakeBorder //////////////////////
PERFTEST(CopyMakeBorder)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_dst;
int bordertype = BORDER_CONSTANT;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
/////////// CopyMakeBorder //////////////////////
gen(src, size, size, all_type[j], 0, 256);
CV_ENUM(CopyMakeBorderMatType, CV_8UC1, CV_8UC4)
copyMakeBorder(src, dst, 7, 5, 5, 7, bordertype, cv::Scalar(1.0));
typedef tuple<Size, CopyMakeBorderMatType> CopyMakeBorderParams;
typedef TestBaseWithParam<CopyMakeBorderParams> CopyMakeBorderFixture;
CPU_ON;
copyMakeBorder(src, dst, 7, 5, 5, 7, bordertype, cv::Scalar(1.0));
CPU_OFF;
PERF_TEST_P(CopyMakeBorderFixture, CopyMakeBorder,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
CopyMakeBorderMatType::all()))
{
// getting params
CopyMakeBorderParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_CONSTANT;
const string impl = getSelectedImpl();
ocl::oclMat d_src(src);
// creating src data
Mat src(srcSize, type), dst;
const Size dstSize = srcSize + Size(12, 12);
dst.create(dstSize, type);
declare.in(src, WARMUP_RNG).out(dst);
WARMUP_ON;
ocl::copyMakeBorder(d_src, d_dst, 7, 5, 5, 7, bordertype, cv::Scalar(1.0));
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
GPU_ON;
ocl::copyMakeBorder(d_src, d_dst, 7, 5, 5, 7, bordertype, cv::Scalar(1.0));
GPU_OFF;
TEST_CYCLE() cv::ocl::copyMakeBorder(oclSrc, oclDst, 7, 5, 5, 7, borderType, cv::Scalar(1.0));
GPU_FULL_ON;
d_src.upload(src);
ocl::copyMakeBorder(d_src, d_dst, 7, 5, 5, 7, bordertype, cv::Scalar(1.0));
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::copyMakeBorder(src, dst, 7, 5, 5, 7, borderType, cv::Scalar(1.0));
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// cornerMinEigenVal ////////////////////////
PERFTEST(cornerMinEigenVal)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_dst;
int blockSize = 7, apertureSize = 1 + 2 * (rand() % 4);
int borderType = BORDER_REFLECT;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
CV_ENUM(cornerMinEigenValMatType, CV_8UC1, CV_32FC1)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
typedef tuple<Size, cornerMinEigenValMatType> cornerMinEigenValParams;
typedef TestBaseWithParam<cornerMinEigenValParams> cornerMinEigenValFixture;
gen(src, size, size, all_type[j], 0, 256);
PERF_TEST_P(cornerMinEigenValFixture, cornerMinEigenVal,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
cornerMinEigenValMatType::all()))
{
// getting params
cornerMinEigenValParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_REFLECT;
const int blockSize = 7, apertureSize = 1 + 2 * 3;
cornerMinEigenVal(src, dst, blockSize, apertureSize, borderType);
const string impl = getSelectedImpl();
CPU_ON;
cornerMinEigenVal(src, dst, blockSize, apertureSize, borderType);
CPU_OFF;
// creating src data
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
declare.in(src, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
ocl::oclMat d_src(src);
const int depth = CV_MAT_DEPTH(type);
const ERROR_TYPE errorType = depth == CV_8U ? ERROR_ABSOLUTE : ERROR_RELATIVE;
WARMUP_ON;
ocl::cornerMinEigenVal(d_src, d_dst, blockSize, apertureSize, borderType);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
GPU_ON;
ocl::cornerMinEigenVal(d_src, d_dst, blockSize, apertureSize, borderType);
GPU_OFF;
TEST_CYCLE() cv::ocl::cornerMinEigenVal(oclSrc, oclDst, blockSize, apertureSize, borderType);
GPU_FULL_ON;
d_src.upload(src);
ocl::cornerMinEigenVal(d_src, d_dst, blockSize, apertureSize, borderType);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst, 1e-6, errorType);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::cornerMinEigenVal(src, dst, blockSize, apertureSize, borderType);
SANITY_CHECK(dst, 1e-6, errorType);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// cornerHarris ////////////////////////
PERFTEST(cornerHarris)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " ; BORDER_REFLECT";
///////////// cornerHarris ////////////////////////
gen(src, size, size, all_type[j], 0, 1);
typedef cornerMinEigenValMatType cornerHarrisMatType;
typedef tuple<Size, cornerHarrisMatType> cornerHarrisParams;
typedef TestBaseWithParam<cornerHarrisParams> cornerHarrisFixture;
cornerHarris(src, dst, 5, 7, 0.1, BORDER_REFLECT);
PERF_TEST_P(cornerHarrisFixture, cornerHarris,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
cornerHarrisMatType::all()))
{
// getting params
cornerHarrisParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), borderType = BORDER_REFLECT;
CPU_ON;
cornerHarris(src, dst, 5, 7, 0.1, BORDER_REFLECT);
CPU_OFF;
const string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, type), dst(srcSize, CV_32FC1);
randu(src, 0, 1);
declare.in(src).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 20 : srcSize == OCL_SIZE_2000 ? 5 : 3);
WARMUP_ON;
ocl::cornerHarris(d_src, d_dst, 5, 7, 0.1, BORDER_REFLECT);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
GPU_ON;
ocl::cornerHarris(d_src, d_dst, 5, 7, 0.1, BORDER_REFLECT);
GPU_OFF;
TEST_CYCLE() cv::ocl::cornerHarris(oclSrc, oclDst, 5, 7, 0.1, borderType);
GPU_FULL_ON;
d_src.upload(src);
ocl::cornerHarris(d_src, d_dst, 5, 7, 0.1, BORDER_REFLECT);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst, 3e-5);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::cornerHarris(src, dst, 5, 7, 0.1, borderType);
SANITY_CHECK(dst, 3e-5);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// integral ////////////////////////
PERFTEST(integral)
{
Mat src, sum, ocl_sum;
ocl::oclMat d_src, d_sum, d_buf;
int all_type[] = {CV_8UC1};
std::string type_name[] = {"CV_8UC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
integral(src, sum);
///////////// integral ////////////////////////
CPU_ON;
integral(src, sum);
CPU_OFF;
typedef TestBaseWithParam<Size> integralFixture;
d_src.upload(src);
PERF_TEST_P(integralFixture, DISABLED_integral, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
WARMUP_ON;
ocl::integral(d_src, d_sum);
WARMUP_OFF;
// creating src data
Mat src(srcSize, CV_8UC1), dst;
declare.in(src, WARMUP_RNG);
GPU_ON;
ocl::integral(d_src, d_sum);
GPU_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst;
GPU_FULL_ON;
d_src.upload(src);
ocl::integral(d_src, d_sum);
d_sum.download(ocl_sum);
GPU_FULL_OFF;
TEST_CYCLE() cv::ocl::integral(oclSrc, oclDst);
if(sum.type() == ocl_sum.type()) //we won't test accuracy when cpu function overlow
TestSystem::instance().ExpectedMatNear(sum, ocl_sum, 0.0);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::integral(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// WarpAffine ////////////////////////
PERFTEST(WarpAffine)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
typedef CopyMakeBorderMatType WarpAffineMatType;
typedef tuple<Size, WarpAffineMatType> WarpAffineParams;
typedef TestBaseWithParam<WarpAffineParams> WarpAffineFixture;
PERF_TEST_P(WarpAffineFixture, WarpAffine,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
WarpAffineMatType::all()))
{
static const double coeffs[2][3] =
{
{cos(CV_PI / 6), -sin(CV_PI / 6), 100.0},
{sin(CV_PI / 6), cos(CV_PI / 6), -100.0}
{ cos(CV_PI / 6), -sin(CV_PI / 6), 100.0 },
{ sin(CV_PI / 6), cos(CV_PI / 6), -100.0 }
};
Mat M(2, 3, CV_64F, (void *)coeffs);
int interpolation = INTER_NEAREST;
const int interpolation = INTER_NEAREST;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
// getting params
WarpAffineParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
// select implementation
if (impl == "ocl")
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
Size size1 = Size(size, size);
warpAffine(src, dst, M, size1, interpolation);
CPU_ON;
warpAffine(src, dst, M, size1, interpolation);
CPU_OFF;
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
d_src.upload(src);
TEST_CYCLE() cv::ocl::warpAffine(oclSrc, oclDst, M, srcSize, interpolation);
WARMUP_ON;
ocl::warpAffine(d_src, d_dst, M, size1, interpolation);
WARMUP_OFF;
oclDst.download(dst);
GPU_ON;
ocl::warpAffine(d_src, d_dst, M, size1, interpolation);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::warpAffine(d_src, d_dst, M, size1, interpolation);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::warpAffine(src, dst, M, srcSize, interpolation);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// WarpPerspective ////////////////////////
PERFTEST(WarpPerspective)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
typedef CopyMakeBorderMatType WarpPerspectiveMatType;
typedef tuple<Size, WarpPerspectiveMatType> WarpPerspectiveParams;
typedef TestBaseWithParam<WarpPerspectiveParams> WarpPerspectiveFixture;
PERF_TEST_P(WarpPerspectiveFixture, WarpPerspective,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
WarpPerspectiveMatType::all()))
{
static const double coeffs[3][3] =
{
{cos(CV_PI / 6), -sin(CV_PI / 6), 100.0},
......@@ -341,199 +345,154 @@ PERFTEST(WarpPerspective)
{0.0, 0.0, 1.0}
};
Mat M(3, 3, CV_64F, (void *)coeffs);
int interpolation = INTER_LINEAR;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
gen(dst, size, size, all_type[j], 0, 256);
Size size1 = Size(size, size);
warpPerspective(src, dst, M, size1, interpolation);
const int interpolation = INTER_LINEAR;
CPU_ON;
warpPerspective(src, dst, M, size1, interpolation);
CPU_OFF;
// getting params
WarpPerspectiveParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_4000 ? 18 : srcSize == OCL_SIZE_2000 ? 5 : 2);
WARMUP_ON;
ocl::warpPerspective(d_src, d_dst, M, size1, interpolation);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
ocl::warpPerspective(d_src, d_dst, M, size1, interpolation);
GPU_OFF;
TEST_CYCLE() cv::ocl::warpPerspective(oclSrc, oclDst, M, srcSize, interpolation);
GPU_FULL_ON;
d_src.upload(src);
ocl::warpPerspective(d_src, d_dst, M, size1, interpolation);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::warpPerspective(src, dst, M, srcSize, interpolation);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// resize ////////////////////////
PERFTEST(resize)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " ; up";
gen(src, size, size, all_type[j], 0, 256);
resize(src, dst, Size(), 2.0, 2.0);
CPU_ON;
resize(src, dst, Size(), 2.0, 2.0);
CPU_OFF;
d_src.upload(src);
WARMUP_ON;
ocl::resize(d_src, d_dst, Size(), 2.0, 2.0);
WARMUP_OFF;
GPU_ON;
ocl::resize(d_src, d_dst, Size(), 2.0, 2.0);
GPU_OFF;
CV_ENUM(resizeInterType, INTER_NEAREST, INTER_LINEAR)
GPU_FULL_ON;
d_src.upload(src);
ocl::resize(d_src, d_dst, Size(), 2.0, 2.0);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
typedef CopyMakeBorderMatType resizeMatType;
typedef tuple<Size, resizeMatType, resizeInterType, double> resizeParams;
typedef TestBaseWithParam<resizeParams> resizeFixture;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
}
PERF_TEST_P(resizeFixture, resize,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
resizeMatType::all(),
resizeInterType::all(),
::testing::Values(0.5, 2.0)))
{
// getting params
resizeParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), interType = get<2>(params);
double scale = get<3>(params);
const string impl = getSelectedImpl();
}
// creating src data
Mat src(srcSize, type), dst;
const Size dstSize(cvRound(srcSize.width * scale), cvRound(srcSize.height * scale));
dst.create(dstSize, type);
declare.in(src, WARMUP_RNG).out(dst);
if (interType == INTER_LINEAR && type == CV_8UC4 && OCL_SIZE_4000 == srcSize)
declare.time(11);
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
// select implementation
if (impl == "ocl")
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " ; down";
gen(src, size, size, all_type[j], 0, 256);
resize(src, dst, Size(), 0.5, 0.5);
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
CPU_ON;
resize(src, dst, Size(), 0.5, 0.5);
CPU_OFF;
TEST_CYCLE() cv::ocl::resize(oclSrc, oclDst, Size(), scale, scale, interType);
d_src.upload(src);
oclDst.download(dst);
WARMUP_ON;
ocl::resize(d_src, d_dst, Size(), 0.5, 0.5);
WARMUP_OFF;
GPU_ON;
ocl::resize(d_src, d_dst, Size(), 0.5, 0.5);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::resize(d_src, d_dst, Size(), 0.5, 0.5);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::resize(src, dst, Size(), scale, scale, interType);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// threshold////////////////////////
PERFTEST(threshold)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; 8UC1; THRESH_BINARY";
///////////// threshold////////////////////////
gen(src, size, size, CV_8U, 0, 100);
CV_ENUM(ThreshType, THRESH_BINARY, THRESH_TRUNC)
threshold(src, dst, 50.0, 0.0, THRESH_BINARY);
typedef tuple<Size, ThreshType> ThreshParams;
typedef TestBaseWithParam<ThreshParams> ThreshFixture;
CPU_ON;
threshold(src, dst, 50.0, 0.0, THRESH_BINARY);
CPU_OFF;
PERF_TEST_P(ThreshFixture, threshold,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ThreshType::all()))
{
// getting params
ThreshParams params = GetParam();
const Size srcSize = get<0>(params);
const int threshType = get<1>(params);
const string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, CV_8U), dst(srcSize, CV_8U);
randu(src, 0, 100);
declare.in(src).out(dst);
WARMUP_ON;
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_BINARY);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_8U);
GPU_ON;
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_BINARY);
GPU_OFF;
TEST_CYCLE() cv::ocl::threshold(oclSrc, oclDst, 50.0, 0.0, threshType);
GPU_FULL_ON;
d_src.upload(src);
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_BINARY);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst);
}
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
else if (impl == "plain")
{
SUBTEST << size << 'x' << size << "; 32FC1; THRESH_TRUNC [NPP]";
gen(src, size, size, CV_32FC1, 0, 100);
threshold(src, dst, 50.0, 0.0, THRESH_TRUNC);
CPU_ON;
threshold(src, dst, 50.0, 0.0, THRESH_TRUNC);
CPU_OFF;
d_src.upload(src);
WARMUP_ON;
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_TRUNC);
WARMUP_OFF;
TEST_CYCLE() cv::threshold(src, dst, 50.0, 0.0, threshType);
GPU_ON;
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_TRUNC);
GPU_OFF;
GPU_FULL_ON;
d_src.upload(src);
ocl::threshold(d_src, d_dst, 50.0, 0.0, THRESH_TRUNC);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// meanShiftFiltering////////////////////////
COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, cv::Size size, int sp, int sr, int maxIter, float eps, int *tab)
typedef struct
{
short x;
short y;
} COOR;
static COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep, cv::Size size, int sp, int sr, int maxIter, float eps, int *tab)
{
int isr2 = sr * sr;
......@@ -715,48 +674,46 @@ static void meanShiftFiltering_(const Mat &src_roi, Mat &dst_roi, int sp, int sr
}
}
PERFTEST(meanShiftFiltering)
{
int sp = 5, sr = 6;
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; 8UC3 vs 8UC4";
gen(src, size, size, CV_8UC4, Scalar::all(0), Scalar::all(256));
typedef TestBaseWithParam<Size> meanShiftFilteringFixture;
PERF_TEST_P(meanShiftFilteringFixture, meanShiftFiltering,
OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const int sp = 5, sr = 6;
const string impl = getSelectedImpl();
cv::TermCriteria crit(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 5, 1);
meanShiftFiltering_(src, dst, sp, sr, crit);
CPU_ON;
meanShiftFiltering_(src, dst, sp, sr, crit);
CPU_OFF;
Mat src(srcSize, CV_8UC4), dst(srcSize, CV_8UC4);
declare.in(src, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_4000 ?
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);
d_src.upload(src);
if (impl == "plain")
{
TEST_CYCLE() meanShiftFiltering_(src, dst, sp, sr, crit);
WARMUP_ON;
ocl::meanShiftFiltering(d_src, d_dst, sp, sr, crit);
WARMUP_OFF;
SANITY_CHECK(dst);
}
else if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_8UC4);
GPU_ON;
ocl::meanShiftFiltering(d_src, d_dst, sp, sr, crit);
GPU_OFF;
TEST_CYCLE() ocl::meanShiftFiltering(oclSrc, oclDst, sp, sr, crit);
GPU_FULL_ON;
d_src.upload(src);
ocl::meanShiftFiltering(d_src, d_dst, sp, sr, crit);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 0.0);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, cv::TermCriteria crit)
static void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp, int sr, cv::TermCriteria crit)
{
if (src_roi.empty())
{
......@@ -814,200 +771,213 @@ void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi, int sp,
}
}
PERFTEST(meanShiftProc)
{
Mat src;
vector<Mat> dst(2), ocl_dst(2);
ocl::oclMat d_src, d_dst, d_dstCoor;
TermCriteria crit(TermCriteria::COUNT + TermCriteria::EPS, 5, 1);
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; 8UC4 and CV_16SC2 ";
gen(src, size, size, CV_8UC4, Scalar::all(0), Scalar::all(256));
typedef TestBaseWithParam<Size> meanShiftProcFixture;
meanShiftProc_(src, dst[0], dst[1], 5, 6, crit);
PERF_TEST_P(meanShiftProcFixture, meanShiftProc,
OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
TermCriteria crit(TermCriteria::COUNT + TermCriteria::EPS, 5, 1);
CPU_ON;
meanShiftProc_(src, dst[0], dst[1], 5, 6, crit);
CPU_OFF;
Mat src(srcSize, CV_8UC4), dst1(srcSize, CV_8UC4),
dst2(srcSize, CV_16SC2);
declare.in(src, WARMUP_RNG).out(dst1, dst2)
.time(srcSize == OCL_SIZE_4000 ?
56 : srcSize == OCL_SIZE_2000 ? 15 : 3.8);;
d_src.upload(src);
if (impl == "plain")
{
TEST_CYCLE() meanShiftProc_(src, dst1, dst2, 5, 6, crit);
WARMUP_ON;
ocl::meanShiftProc(d_src, d_dst, d_dstCoor, 5, 6, crit);
WARMUP_OFF;
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
else if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst1(srcSize, CV_8UC4),
oclDst2(srcSize, CV_16SC2);
GPU_ON;
ocl::meanShiftProc(d_src, d_dst, d_dstCoor, 5, 6, crit);
GPU_OFF;
TEST_CYCLE() ocl::meanShiftProc(oclSrc, oclDst1, oclDst2, 5, 6, crit);
GPU_FULL_ON;
d_src.upload(src);
ocl::meanShiftProc(d_src, d_dst, d_dstCoor, 5, 6, crit);
d_dst.download(ocl_dst[0]);
d_dstCoor.download(ocl_dst[1]);
GPU_FULL_OFF;
oclDst1.download(dst1);
oclDst2.download(dst2);
vector<double> eps(2, 0.);
TestSystem::instance().ExpectMatsNear(dst, ocl_dst, eps);
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// remap////////////////////////
PERFTEST(remap)
{
Mat src, dst, xmap, ymap, ocl_dst;
ocl::oclMat d_src, d_dst, d_xmap, d_ymap;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
CV_ENUM(RemapInterType, INTER_NEAREST, INTER_LINEAR)
int interpolation = INTER_LINEAR;
int borderMode = BORDER_CONSTANT;
typedef CopyMakeBorderMatType remapMatType;
typedef tuple<Size, remapMatType, RemapInterType> remapParams;
typedef TestBaseWithParam<remapParams> remapFixture;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t t = 0; t < sizeof(all_type) / sizeof(int); t++)
{
SUBTEST << size << 'x' << size << "; src " << type_name[t] << "; map CV_32FC1";
PERF_TEST_P(remapFixture, remap,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
remapMatType::all(),
RemapInterType::all()))
{
// getting params
remapParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params), interpolation = get<2>(params);
const string impl = getSelectedImpl();
gen(src, size, size, all_type[t], 0, 256);
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
xmap.create(size, size, CV_32FC1);
dst.create(size, size, CV_32FC1);
ymap.create(size, size, CV_32FC1);
if (srcSize == OCL_SIZE_4000 && interpolation == INTER_LINEAR)
declare.time(9);
for (int i = 0; i < size; ++i)
Mat xmap, ymap;
xmap.create(srcSize, CV_32FC1);
ymap.create(srcSize, CV_32FC1);
for (int i = 0; i < srcSize.height; ++i)
{
float *xmap_row = xmap.ptr<float>(i);
float *ymap_row = ymap.ptr<float>(i);
float * const xmap_row = xmap.ptr<float>(i);
float * const ymap_row = ymap.ptr<float>(i);
for (int j = 0; j < size; ++j)
for (int j = 0; j < srcSize.width; ++j)
{
xmap_row[j] = (j - size * 0.5f) * 0.75f + size * 0.5f;
ymap_row[j] = (i - size * 0.5f) * 0.75f + size * 0.5f;
xmap_row[j] = (j - srcSize.width * 0.5f) * 0.75f + srcSize.width * 0.5f;
ymap_row[j] = (i - srcSize.height * 0.5f) * 0.75f + srcSize.height * 0.5f;
}
}
remap(src, dst, xmap, ymap, interpolation, borderMode);
CPU_ON;
remap(src, dst, xmap, ymap, interpolation, borderMode);
CPU_OFF;
d_src.upload(src);
d_dst.upload(dst);
d_xmap.upload(xmap);
d_ymap.upload(ymap);
const int borderMode = BORDER_CONSTANT;
WARMUP_ON;
ocl::remap(d_src, d_dst, d_xmap, d_ymap, interpolation, borderMode);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
ocl::oclMat oclXMap(xmap), oclYMap(ymap);
GPU_ON;
ocl::remap(d_src, d_dst, d_xmap, d_ymap, interpolation, borderMode);
GPU_OFF;
TEST_CYCLE() cv::ocl::remap(oclSrc, oclDst, oclXMap, oclYMap, interpolation, borderMode);
GPU_FULL_ON;
d_src.upload(src);
ocl::remap(d_src, d_dst, d_xmap, d_ymap, interpolation, borderMode);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 2.0);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::remap(src, dst, xmap, ymap, interpolation, borderMode);
SANITY_CHECK(dst, 1 + DBL_EPSILON);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// CLAHE ////////////////////////
PERFTEST(CLAHE)
{
Mat src, dst, ocl_dst;
cv::ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1};
std::string type_name[] = {"CV_8UC1"};
double clipLimit = 40.0;
cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(clipLimit);
cv::Ptr<cv::CLAHE> d_clahe = cv::ocl::createCLAHE(clipLimit);
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
///////////// CLAHE ////////////////////////
gen(src, size, size, all_type[j], 0, 256);
typedef TestBaseWithParam<Size> CLAHEFixture;
CPU_ON;
clahe->apply(src, dst);
CPU_OFF;
PERF_TEST_P(CLAHEFixture, CLAHE, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, CV_8UC1), dst;
const double clipLimit = 40.0;
declare.in(src, WARMUP_RNG);
WARMUP_ON;
d_clahe->apply(d_src, d_dst);
WARMUP_OFF;
if (srcSize == OCL_SIZE_4000)
declare.time(11);
ocl_dst = d_dst;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst;
cv::Ptr<cv::CLAHE> oclClahe = cv::ocl::createCLAHE(clipLimit);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.0);
TEST_CYCLE() oclClahe->apply(oclSrc, oclDst);
GPU_ON;
d_clahe->apply(d_src, d_dst);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src.upload(src);
d_clahe->apply(d_src, d_dst);
d_dst.download(dst);
GPU_FULL_OFF;
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(clipLimit);
TEST_CYCLE() clahe->apply(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// columnSum////////////////////////
PERFTEST(columnSum)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; CV_32FC1";
gen(src, size, size, CV_32FC1, 0, 256);
typedef TestBaseWithParam<Size> columnSumFixture;
CPU_ON;
dst.create(src.size(), src.type());
static void columnSumPerfTest(const Mat & src, Mat & dst)
{
for (int j = 0; j < src.cols; j++)
dst.at<float>(0, j) = src.at<float>(0, j);
for (int i = 1; i < src.rows; ++i)
for (int j = 0; j < src.cols; ++j)
dst.at<float>(i, j) = dst.at<float>(i - 1 , j) + src.at<float>(i , j);
CPU_OFF;
}
PERF_TEST_P(columnSumFixture, columnSum, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_32FC1), dst(srcSize, CV_32FC1);
declare.in(src, WARMUP_RNG).out(dst);
d_src.upload(src);
if (srcSize == OCL_SIZE_4000)
declare.time(5);
WARMUP_ON;
ocl::columnSum(d_src, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, CV_32FC1);
TEST_CYCLE() cv::ocl::columnSum(oclSrc, oclDst);
GPU_ON;
ocl::columnSum(d_src, d_dst);
GPU_OFF;
oclDst.download(dst);
GPU_FULL_ON;
d_src.upload(src);
ocl::columnSum(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() columnSumPerfTest(src, dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 5e-1);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,101 +45,97 @@
//M*/
#include "perf_precomp.hpp"
/////////// matchTemplate ////////////////////////
//void InitMatchTemplate()
//{
// Mat src; gen(src, 500, 500, CV_32F, 0, 1);
// Mat templ; gen(templ, 500, 500, CV_32F, 0, 1);
// ocl::oclMat d_src(src), d_templ(templ), d_dst;
// ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
//}
PERFTEST(matchTemplate)
{
//InitMatchTemplate();
Mat src, templ, dst, ocl_dst;
int templ_size = 5;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
int all_type[] = {CV_32FC1, CV_32FC4};
std::string type_name[] = {"CV_32FC1", "CV_32FC4"};
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
for(templ_size = 5; templ_size <= 5; templ_size *= 5)
{
gen(src, size, size, all_type[j], 0, 1);
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
SUBTEST << src.cols << 'x' << src.rows << "; " << type_name[j] << "; templ " << templ_size << 'x' << templ_size << "; CCORR";
gen(templ, templ_size, templ_size, all_type[j], 0, 1);
matchTemplate(src, templ, dst, CV_TM_CCORR);
/////////// matchTemplate ////////////////////////
CPU_ON;
matchTemplate(src, templ, dst, CV_TM_CCORR);
CPU_OFF;
CV_ENUM(CV_TM_CCORRMatType, CV_32FC1, CV_32FC4)
ocl::oclMat d_src(src), d_templ(templ), d_dst;
typedef tuple<Size, CV_TM_CCORRMatType> CV_TM_CCORRParams;
typedef TestBaseWithParam<CV_TM_CCORRParams> CV_TM_CCORRFixture;
WARMUP_ON;
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
WARMUP_OFF;
PERF_TEST_P(CV_TM_CCORRFixture, matchTemplate,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
CV_TM_CCORRMatType::all()))
{
// getting params
CV_TM_CCORRParams params = GetParam();
const Size srcSize = get<0>(params), templSize(5, 5);
const int type = get<1>(params);
std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, type), templ(templSize, type);
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
Mat dst(dstSize, CV_32F);
randu(src, 0.0f, 1.0f);
randu(templ, 0.0f, 1.0f);
declare.time(srcSize == OCL_SIZE_2000 ? 20 : 6).in(src, templ).out(dst);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_32F);
GPU_ON;
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
GPU_OFF;
TEST_CYCLE() cv::ocl::matchTemplate(oclSrc, oclTempl, oclDst, CV_TM_CCORR);
GPU_FULL_ON;
d_src.upload(src);
d_templ.upload(templ);
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, templ.rows * templ.cols * 1e-1);
}
SANITY_CHECK(dst, 1e-4);
}
int all_type_8U[] = {CV_8UC1};
std::string type_name_8U[] = {"CV_8UC1"};
for (size_t j = 0; j < sizeof(all_type_8U) / sizeof(int); j++)
else if (impl == "plain")
{
for(templ_size = 5; templ_size <= 5; templ_size *= 5)
{
SUBTEST << src.cols << 'x' << src.rows << "; " << type_name_8U[j] << "; templ " << templ_size << 'x' << templ_size << "; CCORR_NORMED";
gen(src, size, size, all_type_8U[j], 0, 255);
TEST_CYCLE() cv::matchTemplate(src, templ, dst, CV_TM_CCORR);
gen(templ, templ_size, templ_size, all_type_8U[j], 0, 255);
matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
CPU_ON;
matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
CPU_OFF;
SANITY_CHECK(dst, 1e-4);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
ocl::oclMat d_src(src);
ocl::oclMat d_templ(templ), d_dst;
typedef TestBaseWithParam<Size> CV_TM_CCORR_NORMEDFixture;
WARMUP_ON;
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR_NORMED);
WARMUP_OFF;
PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam(), templSize(5, 5);
const std::string impl = getSelectedImpl();
// creating src data
Mat src(srcSize, CV_8UC1), templ(templSize, CV_8UC1), dst;
const Size dstSize(src.cols - templ.cols + 1, src.rows - templ.rows + 1);
dst.create(dstSize, CV_8UC1);
declare.in(src, templ, WARMUP_RNG).out(dst)
.time(srcSize == OCL_SIZE_2000 ? 10 : srcSize == OCL_SIZE_4000 ? 23 : 2);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_8UC1);
GPU_ON;
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR_NORMED);
GPU_OFF;
TEST_CYCLE() cv::ocl::matchTemplate(oclSrc, oclTempl, oclDst, CV_TM_CCORR_NORMED);
GPU_FULL_ON;
d_src.upload(src);
d_templ.upload(templ);
ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR_NORMED);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, templ.rows * templ.cols * 1e-1);
}
SANITY_CHECK(dst, 2e-2);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
SANITY_CHECK(dst, 2e-2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,142 +45,147 @@
//M*/
#include "perf_precomp.hpp"
///////////// ConvertTo////////////////////////
PERFTEST(ConvertTo)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " to 32FC1";
///////////// ConvertTo////////////////////////
gen(src, size, size, all_type[j], 0, 256);
//gen(dst, size, size, all_type[j], 0, 256);
CV_ENUM(ConvertToMatType, CV_8UC1, CV_8UC4)
//d_dst.upload(dst);
typedef tuple<Size, ConvertToMatType> ConvertToParams;
typedef TestBaseWithParam<ConvertToParams> ConvertToFixture;
src.convertTo(dst, CV_32FC1);
PERF_TEST_P(ConvertToFixture, ConvertTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
ConvertToMatType::all()))
{
// getting params
ConvertToParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
CPU_ON;
src.convertTo(dst, CV_32FC1);
CPU_OFF;
std::string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, type), dst;
const int dstType = CV_MAKE_TYPE(CV_32F, src.channels());
dst.create(srcSize, dstType);
declare.in(src, WARMUP_RNG).out(dst);
WARMUP_ON;
d_src.convertTo(d_dst, CV_32FC1);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, dstType);
GPU_ON;
d_src.convertTo(d_dst, CV_32FC1);
GPU_OFF;
TEST_CYCLE() oclSrc.convertTo(oclDst, dstType);
GPU_FULL_ON;
d_src.upload(src);
d_src.convertTo(d_dst, CV_32FC1);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() src.convertTo(dst, dstType);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// copyTo////////////////////////
PERFTEST(copyTo)
{
Mat src, dst, ocl_dst;
ocl::oclMat d_src, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
//gen(dst, size, size, all_type[j], 0, 256);
///////////// copyTo////////////////////////
//d_dst.upload(dst);
typedef ConvertToMatType copyToMatType;
typedef tuple<Size, copyToMatType> copyToParams;
typedef TestBaseWithParam<copyToParams> copyToFixture;
src.copyTo(dst);
PERF_TEST_P(copyToFixture, copyTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
copyToMatType::all()))
{
// getting params
copyToParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
CPU_ON;
src.copyTo(dst);
CPU_OFF;
std::string impl = getSelectedImpl();
d_src.upload(src);
// creating src data
Mat src(srcSize, type), dst(srcSize, type);
declare.in(src, WARMUP_RNG).out(dst);
WARMUP_ON;
d_src.copyTo(d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(srcSize, type);
GPU_ON;
d_src.copyTo(d_dst);
GPU_OFF;
TEST_CYCLE() oclSrc.copyTo(oclDst);
GPU_FULL_ON;
d_src.upload(src);
d_src.copyTo(d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() src.copyTo(dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// setTo////////////////////////
PERFTEST(setTo)
{
Mat src, ocl_src;
Scalar val(1, 2, 3, 4);
ocl::oclMat d_src;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
///////////// setTo////////////////////////
src.setTo(val);
typedef ConvertToMatType setToMatType;
typedef tuple<Size, setToMatType> setToParams;
typedef TestBaseWithParam<setToParams> setToFixture;
CPU_ON;
src.setTo(val);
CPU_OFF;
PERF_TEST_P(setToFixture, setTo,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
setToMatType::all()))
{
// getting params
setToParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
const Scalar val(1, 2, 3, 4);
d_src.upload(src);
std::string impl = getSelectedImpl();
WARMUP_ON;
d_src.setTo(val);
WARMUP_OFF;
// creating src data
Mat src(srcSize, type);
declare.in(src);
d_src.download(ocl_src);
TestSystem::instance().ExpectedMatNear(src, ocl_src, 1.0);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(srcSize, type);
GPU_ON;;
d_src.setTo(val);
GPU_OFF;
TEST_CYCLE() oclSrc.setTo(val);
oclSrc.download(src);
GPU_FULL_ON;
d_src.upload(src);
d_src.setTo(val);
GPU_FULL_OFF;
SANITY_CHECK(src);
}
else if (impl == "plain")
{
TEST_CYCLE() src.setTo(val);
SANITY_CHECK(src);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -43,50 +43,59 @@
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
///////////// Moments ////////////////////////
PERFTEST(Moments)
{
Mat src;
bool binaryImage = 0;
int all_type[] = {CV_8UC1, CV_16SC1, CV_32FC1, CV_64FC1};
std::string type_name[] = {"CV_8UC1", "CV_16SC1", "CV_32FC1", "CV_64FC1"};
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
///////////// Moments ////////////////////////
gen(src, size, size, all_type[j], 0, 256);
CV_ENUM(MomentsMatType, CV_8UC1, CV_16SC1, CV_32FC1, CV_64FC1)
cv::Moments CvMom = moments(src, binaryImage);
typedef tuple<Size, MomentsMatType> MomentsParams;
typedef TestBaseWithParam<MomentsParams> MomentsFixture;
CPU_ON;
moments(src, binaryImage);
CPU_OFF;
PERF_TEST_P(MomentsFixture, DISABLED_Moments,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
MomentsMatType::all()))
{
// getting params
MomentsParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
cv::Moments oclMom;
WARMUP_ON;
oclMom = ocl::ocl_moments(src, binaryImage);
WARMUP_OFF;
std::string impl = getSelectedImpl();
Mat gpu_dst, cpu_dst;
HuMoments(CvMom, cpu_dst);
HuMoments(oclMom, gpu_dst);
// creating src data
Mat src(srcSize, type), dst(7, 1, CV_64F);
const bool binaryImage = false;
cv::Moments mom;
GPU_ON;
ocl::ocl_moments(src, binaryImage);
GPU_OFF;
declare.in(src, WARMUP_RNG).out(dst);
GPU_FULL_ON;
ocl::ocl_moments(src, binaryImage);
GPU_FULL_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src);
TestSystem::instance().ExpectedMatNear(gpu_dst, cpu_dst, .5);
TEST_CYCLE() mom = cv::ocl::ocl_moments(oclSrc, binaryImage);
cv::HuMoments(mom, dst);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() mom = cv::moments(src, binaryImage);
cv::HuMoments(mom, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,43 +45,46 @@
//M*/
#include "perf_precomp.hpp"
///////////// norm////////////////////////
PERFTEST(norm)
{
Mat src1, src2, ocl_src1;
ocl::oclMat d_src1, d_src2;
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
SUBTEST << size << 'x' << size << "; CV_8UC1; NORM_INF";
gen(src1, size, size, CV_8UC1, Scalar::all(0), Scalar::all(1));
gen(src2, size, size, CV_8UC1, Scalar::all(0), Scalar::all(1));
///////////// norm////////////////////////
norm(src1, src2, NORM_INF);
typedef TestBaseWithParam<Size> normFixture;
CPU_ON;
norm(src1, src2, NORM_INF);
CPU_OFF;
PERF_TEST_P(normFixture, DISABLED_norm, OCL_TYPICAL_MAT_SIZES)
{
// getting params
const Size srcSize = GetParam();
const std::string impl = getSelectedImpl();
double value = 0.0;
d_src1.upload(src1);
d_src2.upload(src2);
// creating src data
Mat src1(srcSize, CV_8UC1), src2(srcSize, CV_8UC1);
declare.in(src1, src2);
randu(src1, 0, 1);
randu(src2, 0, 1);
WARMUP_ON;
ocl::norm(d_src1, d_src2, NORM_INF);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2);
d_src1.download(ocl_src1);
TestSystem::instance().ExpectedMatNear(src1, ocl_src1, .5);
TEST_CYCLE() value = cv::ocl::norm(oclSrc1, oclSrc2, NORM_INF);
GPU_ON;
ocl::norm(d_src1, d_src2, NORM_INF);
GPU_OFF;
SANITY_CHECK(value);
}
else if (impl == "plain")
{
TEST_CYCLE() value = cv::norm(src1, src2, NORM_INF);
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
ocl::norm(d_src1, d_src2, NORM_INF);
GPU_FULL_OFF;
SANITY_CHECK(value);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -46,117 +46,130 @@
#include "perf_precomp.hpp"
///////////// PyrLKOpticalFlow ////////////////////////
PERFTEST(PyrLKOpticalFlow)
{
std::string images1[] = {"rubberwhale1.png", "aloeL.jpg"};
std::string images2[] = {"rubberwhale2.png", "aloeR.jpg"};
for (size_t i = 0; i < sizeof(images1) / sizeof(std::string); i++)
{
Mat frame0 = imread(abspath(images1[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
if (frame0.empty())
{
std::string errstr = "can't open " + images1[i];
throw runtime_error(errstr);
}
Mat frame1 = imread(abspath(images2[i]), i == 0 ? IMREAD_COLOR : IMREAD_GRAYSCALE);
using namespace perf;
using std::tr1::get;
using std::tr1::tuple;
using std::tr1::make_tuple;
if (frame1.empty())
{
std::string errstr = "can't open " + images2[i];
throw runtime_error(errstr);
}
template <typename T>
static vector<T> & MatToVector(const ocl::oclMat & oclSrc, vector<T> & instance)
{
Mat src;
oclSrc.download(src);
Mat gray_frame;
for (int i = 0; i < src.cols; ++i)
instance.push_back(src.at<T>(0, i));
if (i == 0)
{
cvtColor(frame0, gray_frame, COLOR_BGR2GRAY);
}
return instance;
}
for (int points = Min_Size; points <= Max_Size; points *= Multiple)
{
if (i == 0)
SUBTEST << frame0.cols << "x" << frame0.rows << "; color; " << points << " points";
CV_ENUM(LoadMode, IMREAD_GRAYSCALE, IMREAD_COLOR)
typedef tuple<int, tuple<string, string, LoadMode> > PyrLKOpticalFlowParamType;
typedef TestBaseWithParam<PyrLKOpticalFlowParamType> PyrLKOpticalFlowFixture;
PERF_TEST_P(PyrLKOpticalFlowFixture,
PyrLKOpticalFlow,
::testing::Combine(
::testing::Values(1000, 2000, 4000),
::testing::Values(
make_tuple<string, string, LoadMode>
(
string("gpu/opticalflow/rubberwhale1.png"),
string("gpu/opticalflow/rubberwhale1.png"),
LoadMode(IMREAD_COLOR)
)
// , make_tuple<string, string, LoadMode>
// (
// string("gpu/stereobm/aloe-L.png"),
// string("gpu/stereobm/aloe-R.png"),
// LoadMode(IMREAD_GRAYSCALE)
// )
)
)
)
{
PyrLKOpticalFlowParamType params = GetParam();
tuple<string, string, LoadMode> fileParam = get<1>(params);
const int pointsCount = get<0>(params);
const int openMode = static_cast<int>(get<2>(fileParam));
const string fileName0 = get<0>(fileParam), fileName1 = get<1>(fileParam);
Mat frame0 = imread(getDataPath(fileName0), openMode);
Mat frame1 = imread(getDataPath(fileName1), openMode);
const string impl = getSelectedImpl();
ASSERT_FALSE(frame0.empty()) << "can't load " << fileName0;
ASSERT_FALSE(frame1.empty()) << "can't load " << fileName1;
Mat grayFrame;
if (openMode == IMREAD_COLOR)
cvtColor(frame0, grayFrame, COLOR_BGR2GRAY);
else
SUBTEST << frame0.cols << "x" << frame0.rows << "; gray; " << points << " points";
Mat ocl_nextPts;
Mat ocl_status;
grayFrame = frame0;
vector<Point2f> pts;
goodFeaturesToTrack(i == 0 ? gray_frame : frame0, pts, points, 0.01, 0.0);
vector<Point2f> nextPts;
// initialization
vector<Point2f> pts, nextPts;
vector<unsigned char> status;
vector<float> err;
goodFeaturesToTrack(grayFrame, pts, pointsCount, 0.01, 0.0);
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
CPU_ON;
calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
CPU_OFF;
ocl::PyrLKOpticalFlow d_pyrLK;
ocl::oclMat d_frame0(frame0);
ocl::oclMat d_frame1(frame1);
ocl::oclMat d_pts;
Mat pts_mat(1, (int)pts.size(), CV_32FC2, (void *)&pts[0]);
d_pts.upload(pts_mat);
ocl::oclMat d_nextPts;
ocl::oclMat d_status;
ocl::oclMat d_err;
WARMUP_ON;
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
WARMUP_OFF;
GPU_ON;
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
GPU_OFF;
// selecting implementation
if (impl == "plain")
{
TEST_CYCLE()
cv::calcOpticalFlowPyrLK(frame0, frame1, pts, nextPts, status, err);
GPU_FULL_ON;
d_frame0.upload(frame0);
d_frame1.upload(frame1);
d_pts.upload(pts_mat);
d_pyrLK.sparse(d_frame0, d_frame1, d_pts, d_nextPts, d_status, &d_err);
SANITY_CHECK(nextPts);
SANITY_CHECK(status);
SANITY_CHECK(err);
}
else if (impl == "ocl")
{
ocl::PyrLKOpticalFlow oclPyrLK;
ocl::oclMat oclFrame0(frame0), oclFrame1(frame1);
ocl::oclMat oclPts(1, static_cast<int>(pts.size()), CV_32FC2, (void *)&pts[0]);
ocl::oclMat oclNextPts, oclStatus, oclErr;
if (!d_nextPts.empty())
d_nextPts.download(ocl_nextPts);
TEST_CYCLE()
oclPyrLK.sparse(oclFrame0, oclFrame1, oclPts, oclNextPts, oclStatus, &oclErr);
if (!d_status.empty())
d_status.download(ocl_status);
GPU_FULL_OFF;
MatToVector(oclNextPts, nextPts);
MatToVector(oclStatus, status);
MatToVector(oclErr, err);
size_t mismatch = 0;
for (int i = 0; i < (int)nextPts.size(); ++i)
{
if(status[i] != ocl_status.at<unsigned char>(0, i))
{
mismatch++;
continue;
SANITY_CHECK(nextPts);
SANITY_CHECK(status);
SANITY_CHECK(err);
}
if(status[i])
{
Point2f gpu_rst = ocl_nextPts.at<Point2f>(0, i);
Point2f cpu_rst = nextPts[i];
if(fabs(gpu_rst.x - cpu_rst.x) >= 1. || fabs(gpu_rst.y - cpu_rst.y) >= 1.)
mismatch++;
}
}
double ratio = (double)mismatch / (double)nextPts.size();
if(ratio < .02)
TestSystem::instance().setAccurate(1, ratio);
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
TestSystem::instance().setAccurate(0, ratio);
}
}
CV_TEST_FAIL_NO_IMPL();
// size_t mismatch = 0;
// for (int i = 0; i < (int)nextPts.size(); ++i)
// {
// if(status[i] != ocl_status.at<unsigned char>(0, i))
// {
// mismatch++;
// continue;
// }
// if(status[i])
// {
// Point2f gpu_rst = ocl_nextPts.at<Point2f>(0, i);
// Point2f cpu_rst = nextPts[i];
// if(fabs(gpu_rst.x - cpu_rst.x) >= 1. || fabs(gpu_rst.y - cpu_rst.y) >= 1.)
// mismatch++;
// }
// }
// double ratio = (double)mismatch / (double)nextPts.size();
// if(ratio < .02)
// TestSystem::instance().setAccurate(1, ratio);
// else
// TestSystem::instance().setAccurate(0, ratio);
}
......
......@@ -40,6 +40,15 @@
//
//M*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# pragma GCC diagnostic ignored "-Wunused-function"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
......@@ -50,6 +59,7 @@
#include <cstdio>
#include <vector>
#include <numeric>
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
......@@ -59,9 +69,12 @@
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/ocl/ocl.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/ts/ts_gtest.h"
#define OCL_SIZE_1000 cv::Size(1000, 1000)
#define OCL_SIZE_2000 cv::Size(2000, 2000)
#define OCL_SIZE_4000 cv::Size(4000, 4000)
#define OCL_TYPICAL_MAT_SIZES ::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000, OCL_SIZE_4000)
#define Min_Size 1000
#define Max_Size 4000
......@@ -76,15 +89,15 @@ void gen(Mat &mat, int rows, int cols, int type, int low, int high, int n);
string abspath(const string &relpath);
int CV_CDECL cvErrorCallback(int, const char *, const char *, const char *, int, void *);
typedef struct
{
short x;
short y;
} COOR;
COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep,
cv::Size size, int sp, int sr, int maxIter, float eps, int *tab);
void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi,
int sp, int sr, cv::TermCriteria crit);
//typedef struct
//{
// short x;
// short y;
//} COOR;
//COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep,
// cv::Size size, int sp, int sr, int maxIter, float eps, int *tab);
//void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi,
// int sp, int sr, cv::TermCriteria crit);
template<class T1, class T2>
......
......@@ -45,88 +45,103 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
///////////// pyrDown //////////////////////
PERFTEST(pyrDown)
{
Mat src, dst, ocl_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
CV_ENUM(pyrDownMatType, CV_8UC1, CV_8UC4)
gen(src, size, size, all_type[j], 0, 256);
typedef tuple<Size, pyrDownMatType> pyrDownParams;
typedef TestBaseWithParam<pyrDownParams> pyrDownFixture;
pyrDown(src, dst);
PERF_TEST_P(pyrDownFixture, pyrDown,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
pyrDownMatType::all()))
{
// getting params
pyrDownParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
CPU_ON;
pyrDown(src, dst);
CPU_OFF;
std::string impl = getSelectedImpl();
ocl::oclMat d_src(src);
ocl::oclMat d_dst;
// creating src data
Mat src(srcSize, type), dst;
Size dstSize((srcSize.height + 1) >> 1, (srcSize.width + 1) >> 1);
dst.create(dstSize, type);
declare.in(src).out(dst);
WARMUP_ON;
ocl::pyrDown(d_src, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
GPU_ON;
ocl::pyrDown(d_src, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::pyrDown(oclSrc, oclDst);
GPU_FULL_ON;
d_src.upload(src);
ocl::pyrDown(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, dst.depth() == CV_32F ? 1e-4f : 1.0f);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::pyrDown(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// pyrUp ////////////////////////
PERFTEST(pyrUp)
{
Mat src, dst, ocl_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = 500; size <= 2000; size *= 2)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
gen(src, size, size, all_type[j], 0, 256);
typedef pyrDownMatType pyrUpMatType;
typedef tuple<Size, pyrUpMatType> pyrUpParams;
typedef TestBaseWithParam<pyrUpParams> pyrUpFixture;
pyrUp(src, dst);
PERF_TEST_P(pyrUpFixture, pyrUp,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
pyrUpMatType::all()))
{
// getting params
pyrUpParams params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
CPU_ON;
pyrUp(src, dst);
CPU_OFF;
std::string impl = getSelectedImpl();
ocl::oclMat d_src(src);
ocl::oclMat d_dst;
// creating src data
Mat src(srcSize, type), dst;
Size dstSize(srcSize.height << 1, srcSize.width << 1);
dst.create(dstSize, type);
declare.in(src).out(dst);
WARMUP_ON;
ocl::pyrUp(d_src, d_dst);
WARMUP_OFF;
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src), oclDst(dstSize, type);
GPU_ON;
ocl::pyrUp(d_src, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::pyrDown(oclSrc, oclDst);
GPU_FULL_ON;
d_src.upload(src);
ocl::pyrUp(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, (src.depth() == CV_32F ? 1e-4f : 1.0));
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::pyrDown(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
......@@ -45,110 +45,120 @@
//M*/
#include "perf_precomp.hpp"
using namespace perf;
using std::tr1::tuple;
using std::tr1::get;
///////////// Merge////////////////////////
PERFTEST(Merge)
{
Mat dst, ocl_dst;
ocl::oclMat d_dst;
int channels = 4;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
CV_ENUM(MergeMatType, CV_8U, CV_32F)
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] ;
Size size1 = Size(size, size);
std::vector<Mat> src(channels);
typedef tuple<Size, MergeMatType> MergeParams;
typedef TestBaseWithParam<MergeParams> MergeFixture;
for (int i = 0; i < channels; ++i)
PERF_TEST_P(MergeFixture, Merge,
::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
MergeMatType::all()))
{
// getting params
MergeParams params = GetParam();
const Size srcSize = get<0>(params);
const int depth = get<1>(params), channels = 3;
std::string impl = getSelectedImpl();
// creating src data
const int dstType = CV_MAKE_TYPE(depth, channels);
Mat dst(srcSize, dstType);
vector<Mat> src(channels);
for (vector<Mat>::iterator i = src.begin(), end = src.end(); i != end; ++i)
{
src[i] = Mat(size1, all_type[j], cv::Scalar::all(i));
i->create(srcSize, CV_MAKE_TYPE(depth, 1));
declare.in(*i, WARMUP_RNG);
}
declare.out(dst);
merge(src, dst);
CPU_ON;
merge(src, dst);
CPU_OFF;
std::vector<ocl::oclMat> d_src(channels);
for (int i = 0; i < channels; ++i)
// select implementation
if (impl == "ocl")
{
d_src[i] = ocl::oclMat(size1, all_type[j], cv::Scalar::all(i));
}
WARMUP_ON;
ocl::merge(d_src, d_dst);
WARMUP_OFF;
ocl::oclMat oclDst(srcSize, dstType);
vector<ocl::oclMat> oclSrc(src.size());
for (vector<ocl::oclMat>::size_type i = 0, end = src.size(); i < end; ++i)
oclSrc[i] = src[i];
GPU_ON;
ocl::merge(d_src, d_dst);
GPU_OFF;
TEST_CYCLE() cv::ocl::merge(oclSrc, oclDst);
GPU_FULL_ON;
for (int i = 0; i < channels; ++i)
{
d_src[i] = ocl::oclMat(size1, all_type[j], cv::Scalar::all(i));
}
ocl::merge(d_src, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
oclDst.download(dst);
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 0.0);
SANITY_CHECK(dst);
}
else if (impl == "plain")
{
TEST_CYCLE() cv::merge(src, dst);
SANITY_CHECK(dst);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
///////////// Split////////////////////////
PERFTEST(Split)
{
//int channels = 4;
int all_type[] = {CV_8UC1, CV_32FC1};
std::string type_name[] = {"CV_8UC1", "CV_32FC1"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j];
Size size1 = Size(size, size);
Mat src(size1, CV_MAKE_TYPE(all_type[j], 4), cv::Scalar(1, 2, 3, 4));
std::vector<cv::Mat> dst, ocl_dst(4);
split(src, dst);
typedef MergeMatType SplitMatType;
typedef tuple<Size, SplitMatType> SplitParams;
typedef TestBaseWithParam<SplitParams> SplitFixture;
CPU_ON;
split(src, dst);
CPU_OFF;
ocl::oclMat d_src(size1, CV_MAKE_TYPE(all_type[j], 4), cv::Scalar(1, 2, 3, 4));
std::vector<cv::ocl::oclMat> d_dst;
WARMUP_ON;
ocl::split(d_src, d_dst);
WARMUP_OFF;
PERF_TEST_P(SplitFixture, Split,
::testing::Combine(OCL_TYPICAL_MAT_SIZES,
SplitMatType::all()))
{
// getting params
MergeParams params = GetParam();
const Size srcSize = get<0>(params);
const int depth = get<1>(params), channels = 3;
GPU_ON;
ocl::split(d_src, d_dst);
GPU_OFF;
std::string impl = getSelectedImpl();
GPU_FULL_ON;
d_src.upload(src);
ocl::split(d_src, d_dst);
for(size_t i = 0; i < dst.size(); i++)
d_dst[i].download(ocl_dst[i]);
GPU_FULL_OFF;
// creating src data
Mat src(srcSize, CV_MAKE_TYPE(depth, channels));
declare.in(src, WARMUP_RNG);
vector<double> eps(4, 0.);
TestSystem::instance().ExpectMatsNear(dst, ocl_dst, eps);
// select implementation
if (impl == "ocl")
{
ocl::oclMat oclSrc(src);
vector<ocl::oclMat> oclDst(channels, ocl::oclMat(srcSize, CV_MAKE_TYPE(depth, 1)));
TEST_CYCLE() cv::ocl::split(oclSrc, oclDst);
AssertEQ(channels, 3);
Mat dst0, dst1, dst2;
oclDst[0].download(dst0);
oclDst[1].download(dst1);
oclDst[2].download(dst2);
SANITY_CHECK(dst0);
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
else if (impl == "plain")
{
vector<Mat> dst(channels, Mat(srcSize, CV_MAKE_TYPE(depth, 1)));
TEST_CYCLE() cv::split(src, dst);
AssertEQ(channels, 3);
Mat & dst0 = dst[0], & dst1 = dst[1], & dst2 = dst[2];
SANITY_CHECK(dst0);
SANITY_CHECK(dst1);
SANITY_CHECK(dst2);
}
#ifdef HAVE_OPENCV_GPU
else if (impl == "gpu")
CV_TEST_FAIL_NO_IMPL();
#endif
else
CV_TEST_FAIL_NO_IMPL();
}
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