OpenCV_4.2.0/opencv_contrib-4.2.0/modules/cudaimgproc/test/test_mean_shift.cpp

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#include "test_precomp.hpp"
#ifdef HAVE_CUDA
namespace opencv_test { namespace {
////////////////////////////////////////////////////////////////////////////////
// MeanShift
struct MeanShift : testing::TestWithParam<cv::cuda::DeviceInfo>
{
cv::cuda::DeviceInfo devInfo;
cv::Mat img;
int spatialRad;
int colorRad;
virtual void SetUp()
{
devInfo = GetParam();
cv::cuda::setDevice(devInfo.deviceID());
img = readImageType("meanshift/cones.png", CV_8UC4);
ASSERT_FALSE(img.empty());
spatialRad = 30;
colorRad = 30;
}
};
CUDA_TEST_P(MeanShift, Filtering)
{
cv::Mat img_template;
if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
img_template = readImage("meanshift/con_result.png");
else
img_template = readImage("meanshift/con_result_CC1X.png");
ASSERT_FALSE(img_template.empty());
cv::cuda::GpuMat d_dst;
cv::cuda::meanShiftFiltering(loadMat(img), d_dst, spatialRad, colorRad);
ASSERT_EQ(CV_8UC4, d_dst.type());
cv::Mat dst(d_dst);
cv::Mat result;
cv::cvtColor(dst, result, cv::COLOR_BGRA2BGR);
EXPECT_MAT_NEAR(img_template, result, 0.0);
}
CUDA_TEST_P(MeanShift, Proc)
{
cv::FileStorage fs;
if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap.yaml", cv::FileStorage::READ);
else
fs.open(std::string(cvtest::TS::ptr()->get_data_path()) + "meanshift/spmap_CC1X.yaml", cv::FileStorage::READ);
ASSERT_TRUE(fs.isOpened());
cv::Mat spmap_template;
fs["spmap"] >> spmap_template;
ASSERT_FALSE(spmap_template.empty());
cv::cuda::GpuMat rmap_filtered;
cv::cuda::meanShiftFiltering(loadMat(img), rmap_filtered, spatialRad, colorRad);
cv::cuda::GpuMat rmap;
cv::cuda::GpuMat spmap;
cv::cuda::meanShiftProc(loadMat(img), rmap, spmap, spatialRad, colorRad);
ASSERT_EQ(CV_8UC4, rmap.type());
EXPECT_MAT_NEAR(rmap_filtered, rmap, 0.0);
EXPECT_MAT_NEAR(spmap_template, spmap, 0.0);
}
INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, MeanShift, ALL_DEVICES);
////////////////////////////////////////////////////////////////////////////////
// MeanShiftSegmentation
namespace
{
IMPLEMENT_PARAM_CLASS(MinSize, int);
}
PARAM_TEST_CASE(MeanShiftSegmentation, cv::cuda::DeviceInfo, MinSize)
{
cv::cuda::DeviceInfo devInfo;
int minsize;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
minsize = GET_PARAM(1);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(MeanShiftSegmentation, Regression)
{
cv::Mat img = readImageType("meanshift/cones.png", CV_8UC4);
ASSERT_FALSE(img.empty());
std::ostringstream path;
path << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
if (supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_20))
path << ".png";
else
path << "_CC1X.png";
cv::Mat dst_gold = readImage(path.str());
ASSERT_FALSE(dst_gold.empty());
cv::Mat dst;
cv::cuda::meanShiftSegmentation(loadMat(img), dst, 10, 10, minsize);
cv::Mat dst_rgb;
cv::cvtColor(dst, dst_rgb, cv::COLOR_BGRA2BGR);
EXPECT_MAT_SIMILAR(dst_gold, dst_rgb, 1e-3);
}
INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, MeanShiftSegmentation, testing::Combine(
ALL_DEVICES,
testing::Values(MinSize(0), MinSize(4), MinSize(20), MinSize(84), MinSize(340), MinSize(1364))));
}} // namespace
#endif // HAVE_CUDA