mirror of
https://github.com/opencv/opencv.git
synced 2024-12-16 10:29:11 +08:00
ea1e3fb90d
* support similarity masks * add test for similarity threshold * short license in test * use UMat in buildSimilarityMask * fix win32 warnings * fix test indentation * fix umat/mat sync * no in-place argument for erode/dilate
71 lines
2.2 KiB
C++
71 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
|