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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "test_precomp.hpp"
namespace opencv_test { namespace {
static string getOpenCVExtraDir()
{
return cvtest::TS::ptr()->get_data_path();
}
CV_ENUM(SupportedTypes, CV_8UC1, CV_8UC3, CV_32FC1); // reduced set
CV_ENUM(ModeType, DTF_NC, DTF_IC, DTF_RF)
typedef tuple<Size, ModeType, SupportedTypes, SupportedTypes> DTParams;
Mat convertTypeAndSize(Mat src, int dstType, Size dstSize)
{
Mat dst;
CV_Assert(src.channels() == 3);
int dstChannels = CV_MAT_CN(dstType);
if (dstChannels == 1)
{
cvtColor(src, dst, COLOR_BGR2GRAY);
}
else if (dstChannels == 2)
{
Mat srcCn[3];
split(src, srcCn);
merge(srcCn, 2, dst);
}
else if (dstChannels == 3)
{
dst = src.clone();
}
else if (dstChannels == 4)
{
Mat srcCn[4];
split(src, srcCn);
srcCn[3] = srcCn[0].clone();
merge(srcCn, 4, dst);
}
dst.convertTo(dst, dstType);
resize(dst, dst, dstSize, 0, 0, dstType == CV_32FC1 ? INTER_LINEAR : INTER_LINEAR_EXACT);
return dst;
}
TEST(DomainTransformTest, SplatSurfaceAccuracy)
{
static int dtModes[] = {DTF_NC, DTF_RF, DTF_IC};
RNG rnd(0);
for (int i = 0; i < 15; i++)
{
Size sz(rnd.uniform(512, 1024), rnd.uniform(512, 1024));
int guideCn = rnd.uniform(1, 4);
Mat guide(sz, CV_MAKE_TYPE(CV_32F, guideCn));
randu(guide, 0, 255);
Scalar surfaceValue;
int srcCn = rnd.uniform(1, 4);
rnd.fill(surfaceValue, RNG::UNIFORM, 0, 255);
Mat src(sz, CV_MAKE_TYPE(CV_8U, srcCn), surfaceValue);
double sigma_s = rnd.uniform(1.0, 100.0);
double sigma_r = rnd.uniform(1.0, 100.0);
int mode = dtModes[i%3];
Mat res;
dtFilter(guide, src, res, sigma_s, sigma_r, mode, 1);
double normL1 = cvtest::norm(src, res, NORM_L1)/src.total()/src.channels();
EXPECT_LE(normL1, 1.0/64);
}
}
typedef TestWithParam<DTParams> DomainTransformTest;
TEST_P(DomainTransformTest, MultiThreadReproducibility)
{
if (cv::getNumberOfCPUs() == 1)
return;
double MAX_DIF = 1.0;
double MAX_MEAN_DIF = 1.0 / 256.0;
int loopsCount = 2;
RNG rng(0);
DTParams params = GetParam();
Size size = get<0>(params);
int mode = get<1>(params);
int guideType = get<2>(params);
int srcType = get<3>(params);
Mat original = imread(getOpenCVExtraDir() + "cv/edgefilter/statue.png");
Mat guide = convertTypeAndSize(original, guideType, size);
Mat src = convertTypeAndSize(original, srcType, size);
int nThreads = cv::getNumThreads();
if (nThreads == 1)
throw SkipTestException("Single thread environment");
for (int iter = 0; iter <= loopsCount; iter++)
{
double ss = rng.uniform(0.0, 100.0);
double sc = rng.uniform(0.0, 100.0);
cv::setNumThreads(nThreads);
Mat resMultithread;
dtFilter(guide, src, resMultithread, ss, sc, mode);
cv::setNumThreads(1);
Mat resSingleThread;
dtFilter(guide, src, resSingleThread, ss, sc, mode);
EXPECT_LE(cv::norm(resSingleThread, resMultithread, NORM_INF), MAX_DIF);
EXPECT_LE(cv::norm(resSingleThread, resMultithread, NORM_L1), MAX_MEAN_DIF*src.total());
}
}
INSTANTIATE_TEST_CASE_P(FullSet, DomainTransformTest,
Combine(Values(szODD, szQVGA), ModeType::all(), SupportedTypes::all(), SupportedTypes::all())
);
template<typename SrcVec>
Mat getChessMat1px(Size sz, double whiteIntensity = 255)
{
typedef typename DataType<SrcVec>::channel_type SrcType;
Mat dst(sz, traits::Type<SrcVec>::value);
SrcVec black = SrcVec::all(0);
SrcVec white = SrcVec::all((SrcType)whiteIntensity);
for (int i = 0; i < dst.rows; i++)
for (int j = 0; j < dst.cols; j++)
dst.at<SrcVec>(i, j) = ((i + j) % 2) ? white : black;
return dst;
}
TEST(DomainTransformTest, ChessBoard_NC_accuracy)
{
RNG rng(0);
double MAX_DIF = 1;
Size sz = szVGA;
double ss = 80;
double sc = 60;
Mat srcb = randomMat(rng, sz, CV_8UC4, 0, 255, true);
Mat srcf = randomMat(rng, sz, CV_32FC4, 0, 255, true);
Mat chessb = getChessMat1px<Vec3b>(sz);
Mat dstb, dstf;
dtFilter(chessb, srcb.clone(), dstb, ss, sc, DTF_NC);
dtFilter(chessb, srcf.clone(), dstf, ss, sc, DTF_NC);
EXPECT_LE(cv::norm(srcb, dstb, NORM_INF), MAX_DIF);
EXPECT_LE(cv::norm(srcf, dstf, NORM_INF), MAX_DIF);
}
TEST(DomainTransformTest, BoxFilter_NC_accuracy)
{
double MAX_DIF = 1;
int radius = 5;
double sc = 1.0;
double ss = 1.01*radius / sqrt(3.0);
Mat src = imread(getOpenCVExtraDir() + "cv/edgefilter/statue.png");
ASSERT_TRUE(!src.empty());
Mat1b guide(src.size(), 200);
Mat res_dt, res_box;
blur(src, res_box, Size(2 * radius + 1, 2 * radius + 1));
dtFilter(guide, src, res_dt, ss, sc, DTF_NC, 1);
EXPECT_LE(cv::norm(res_dt, res_box, NORM_L2), MAX_DIF*src.total());
}
TEST(DomainTransformTest, AuthorReferenceAccuracy)
{
string dir = getOpenCVExtraDir() + "cv/edgefilter";
double ss = 30;
double sc = 0.2 * 255;
Mat src = imread(dir + "/statue.png");
Mat ref_NC = imread(dir + "/dt/authors_statue_NC_ss30_sc0.2.png");
Mat ref_IC = imread(dir + "/dt/authors_statue_IC_ss30_sc0.2.png");
Mat ref_RF = imread(dir + "/dt/authors_statue_RF_ss30_sc0.2.png");
ASSERT_FALSE(src.empty());
ASSERT_FALSE(ref_NC.empty());
ASSERT_FALSE(ref_IC.empty());
ASSERT_FALSE(ref_RF.empty());
Mat res_NC, res_IC, res_RF;
dtFilter(src, src, res_NC, ss, sc, DTF_NC);
dtFilter(src, src, res_IC, ss, sc, DTF_IC);
dtFilter(src, src, res_RF, ss, sc, DTF_RF);
double totalMaxError = 1.0/64.0*src.total();
EXPECT_LE(cvtest::norm(res_NC, ref_NC, NORM_L2), totalMaxError);
EXPECT_LE(cvtest::norm(res_NC, ref_NC, NORM_INF), 1);
EXPECT_LE(cvtest::norm(res_IC, ref_IC, NORM_L2), totalMaxError);
EXPECT_LE(cvtest::norm(res_IC, ref_IC, NORM_INF), 1);
EXPECT_LE(cvtest::norm(res_RF, ref_RF, NORM_L2), totalMaxError);
EXPECT_LE(cvtest::norm(res_IC, ref_IC, NORM_INF), 1);
}
}} // namespace
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