//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
-// and/or other oclMaterials provided with the distribution.
+// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//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);
-
- SUBTEST << src.cols << 'x' << src.rows << "; " << type_name[j] << "; templ " << templ_size << 'x' << templ_size << "; CCORR";
+using namespace perf;
+using std::tr1::tuple;
+using std::tr1::get;
- gen(templ, templ_size, templ_size, all_type[j], 0, 1);
-
- matchTemplate(src, templ, dst, CV_TM_CCORR);
-
- CPU_ON;
- matchTemplate(src, templ, dst, CV_TM_CCORR);
- CPU_OFF;
-
- ocl::oclMat d_src(src), d_templ(templ), d_dst;
-
- WARMUP_ON;
- ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
- WARMUP_OFF;
+/////////// matchTemplate ////////////////////////
- GPU_ON;
- ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR);
- GPU_OFF;
+typedef Size_MatType CV_TM_CCORRFixture;
- 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;
+PERF_TEST_P(CV_TM_CCORRFixture, matchTemplate,
+ ::testing::Combine(::testing::Values(OCL_SIZE_1000, OCL_SIZE_2000),
+ OCL_PERF_ENUM(CV_32FC1, CV_32FC4)))
+{
+ const Size_MatType_t params = GetParam();
+ const Size srcSize = get<0>(params), templSize(5, 5);
+ const int type = get<1>(params);
+
+ 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);
+
+ if (RUN_OCL_IMPL)
+ {
+ ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_32F);
- TestSystem::instance().ExpectedMatNear(dst, ocl_dst, templ.rows * templ.cols * 1e-1);
- }
- }
+ OCL_TEST_CYCLE() cv::ocl::matchTemplate(oclSrc, oclTempl, oclDst, TM_CCORR);
- int all_type_8U[] = {CV_8UC1};
- std::string type_name_8U[] = {"CV_8UC1"};
+ oclDst.download(dst);
- for (size_t j = 0; j < sizeof(all_type_8U) / sizeof(int); j++)
- {
- 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";
+ SANITY_CHECK(dst, 1e-4);
+ }
+ else if (RUN_PLAIN_IMPL)
+ {
+ TEST_CYCLE() cv::matchTemplate(src, templ, dst, TM_CCORR);
- gen(src, size, size, all_type_8U[j], 0, 255);
+ SANITY_CHECK(dst, 1e-4);
+ }
+ else
+ OCL_PERF_ELSE
+}
- gen(templ, templ_size, templ_size, all_type_8U[j], 0, 255);
+typedef TestBaseWithParam<Size> CV_TM_CCORR_NORMEDFixture;
- matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
+PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate, OCL_TYPICAL_MAT_SIZES)
+{
+ const Size srcSize = GetParam(), templSize(5, 5);
- CPU_ON;
- matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
- CPU_OFF;
+ 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);
- ocl::oclMat d_src(src);
- ocl::oclMat d_templ(templ), d_dst;
+ if (RUN_OCL_IMPL)
+ {
+ ocl::oclMat oclSrc(src), oclTempl(templ), oclDst(dstSize, CV_8UC1);
- WARMUP_ON;
- ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR_NORMED);
- WARMUP_OFF;
+ OCL_TEST_CYCLE() cv::ocl::matchTemplate(oclSrc, oclTempl, oclDst, TM_CCORR_NORMED);
- GPU_ON;
- ocl::matchTemplate(d_src, d_templ, d_dst, CV_TM_CCORR_NORMED);
- GPU_OFF;
+ oclDst.download(dst);
- 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;
+ SANITY_CHECK(dst, 3e-2);
+ }
+ else if (RUN_PLAIN_IMPL)
+ {
+ TEST_CYCLE() cv::matchTemplate(src, templ, dst, TM_CCORR_NORMED);
- TestSystem::instance().ExpectedMatNear(dst, ocl_dst, templ.rows * templ.cols * 1e-1);
- }
- }
+ SANITY_CHECK(dst, 3e-2);
}
+ else
+ OCL_PERF_ELSE
}
projects / profile / ivi / opencv.git / blobdiff