cameracv/libs/opencv/modules/stitching/test/test_exposure_compensate.cpp
2023-05-18 21:39:43 +03:00

70 lines
2.2 KiB
C++

// 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 {
double minPSNR(UMat src1, UMat src2)
{
std::vector<UMat> src1_channels, src2_channels;
split(src1, src1_channels);
split(src2, src2_channels);
double psnr = cvtest::PSNR(src1_channels[0], src2_channels[0]);
psnr = std::min(psnr, cvtest::PSNR(src1_channels[1], src2_channels[1]));
return std::min(psnr, cvtest::PSNR(src1_channels[2], src2_channels[2]));
}
TEST(ExposureCompensate, SimilarityThreshold)
{
UMat source;
imread(cvtest::TS::ptr()->get_data_path() + "stitching/s1.jpg").copyTo(source);
UMat image1 = source.clone();
UMat image2 = source.clone();
// Add a big artifact
image2(Rect(150, 150, 100, 100)).setTo(Scalar(0, 0, 255));
UMat mask(image1.size(), CV_8U);
mask.setTo(255);
detail::BlocksChannelsCompensator compensator;
compensator.setNrGainsFilteringIterations(0); // makes it more clear
// Feed the compensator, image 1 and 2 are perfectly
// identical, except for the red artifact in image 2
// Apart from that artifact, there is no exposure to compensate
compensator.setSimilarityThreshold(1);
uchar xff = 255;
compensator.feed(
{{}, {}},
{image1, image2},
{{mask, xff}, {mask, xff}}
);
// Verify that the artifact in image 2 did create
// an artifact in image1 during the exposure compensation
UMat image1_result = image1.clone();
compensator.apply(0, {}, image1_result, mask);
double psnr_no_similarity_mask = minPSNR(image1, image1_result);
EXPECT_LT(psnr_no_similarity_mask, 45);
// Add a similarity threshold and verify that
// the artifact in image1 is gone
compensator.setSimilarityThreshold(0.1);
compensator.feed(
{{}, {}},
{image1, image2},
{{mask, xff}, {mask, xff}}
);
image1_result = image1.clone();
compensator.apply(0, {}, image1_result, mask);
double psnr_similarity_mask = minPSNR(image1, image1_result);
EXPECT_GT(psnr_similarity_mask, 300);
}
} // namespace
} // namespace opencv_test