Open Source Computer Vision Library https://opencv.org/
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#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using namespace testing;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(MatrixType, CV_16UC1, CV_16SC1, CV_32FC1)
CV_ENUM(MapType, CV_16SC2, CV_32FC1, CV_32FC2)
CV_ENUM(InterType, INTER_LINEAR, INTER_CUBIC, INTER_LANCZOS4, INTER_NEAREST)
typedef TestBaseWithParam< tr1::tuple<Size, MatrixType, MapType, InterType> > TestRemap;
PERF_TEST_P( TestRemap, Remap,
Combine(
Values( szVGA, sz1080p ),
ValuesIn( MatrixType::all() ),
ValuesIn( MapType::all() ),
ValuesIn( InterType::all() )
)
)
{
Size sz;
int src_type, map1_type, inter_type;
sz = get<0>(GetParam());
src_type = get<1>(GetParam());
map1_type = get<2>(GetParam());
inter_type = get<3>(GetParam());
Mat src(sz, src_type);
Mat map1(sz, map1_type);
Mat dst(sz, src_type);
Mat map2(map1_type == CV_32FC1 ? sz : Size(), CV_32FC1);
RNG rng;
rng.fill(src, RNG::UNIFORM, 0, 256);
for (int j = 0; j < map1.rows; ++j)
for (int i = 0; i < map1.cols; ++i)
switch (map1_type)
{
case CV_32FC1:
map1.at<float>(j, i) = src.cols - i;
map2.at<float>(j, i) = j;
break;
case CV_32FC2:
map1.at<Vec2f>(j, i)[0] = src.cols - i;
map1.at<Vec2f>(j, i)[1] = j;
break;
case CV_16SC2:
map1.at<Vec2s>(j, i)[0] = src.cols - i;
map1.at<Vec2s>(j, i)[1] = j;
break;
default:
CV_Assert(0);
}
declare.in(src, WARMUP_RNG).out(dst).time(20);
TEST_CYCLE() remap(src, dst, map1, map2, inter_type);
SANITY_CHECK(dst);
}