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Implementation of bit-exact resize. Internal calls to linear resize updated to use bit-exact version. (#9468)

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This commit is contained in:
Vitaly Tuzov
2017-12-13 15:00:38 +03:00
committed by Vadim Pisarevsky
parent 84ee4d701a
commit 51cb56ef2c
57 changed files with 1300 additions and 112 deletions
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modules/stitching/perf/perf_estimators.cpp
+2 -2
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@@ -24,8 +24,8 @@ PERF_TEST_P(bundleAdjuster, affine, testing::Combine(TEST_DETECTORS, AFFINE_FUNC
Mat img2, img2_full = imread(getDataPath("stitching/s2.jpg"));
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
resize(img1_full, img1, Size(), scale1, scale1, INTER_LINEAR_EXACT);
resize(img2_full, img2, Size(), scale2, scale2, INTER_LINEAR_EXACT);
string detector = get<0>(GetParam());
string affine_fun = get<1>(GetParam());
modules/stitching/perf/perf_matchers.cpp
+8 -8
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@@ -64,8 +64,8 @@ PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
Mat img2, img2_full = imread( getDataPath("stitching/boat2.jpg") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
resize(img1_full, img1, Size(), scale1, scale1, INTER_LINEAR_EXACT);
resize(img2_full, img2, Size(), scale2, scale2, INTER_LINEAR_EXACT);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
@@ -117,8 +117,8 @@ PERF_TEST_P( matchVector, bestOf2NearestVectorFeatures, testing::Combine(
Mat img2, img2_full = imread( getDataPath("stitching/boat2.jpg") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
resize(img1_full, img1, Size(), scale1, scale1, INTER_LINEAR_EXACT);
resize(img2_full, img2, Size(), scale2, scale2, INTER_LINEAR_EXACT);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
@@ -182,8 +182,8 @@ PERF_TEST_P( match, affineBestOf2Nearest, TEST_DETECTORS)
Mat img2, img2_full = imread( getDataPath("stitching/s2.jpg") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
resize(img1_full, img1, Size(), scale1, scale1, INTER_LINEAR_EXACT);
resize(img2_full, img2, Size(), scale2, scale2, INTER_LINEAR_EXACT);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
@@ -241,8 +241,8 @@ PERF_TEST_P( matchVector, affineBestOf2NearestVectorFeatures, testing::Combine(
Mat img2, img2_full = imread( getDataPath("stitching/s2.jpg") );
float scale1 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img1_full.total()));
float scale2 = (float)std::min(1.0, sqrt(WORK_MEGAPIX * 1e6 / img2_full.total()));
resize(img1_full, img1, Size(), scale1, scale1);
resize(img2_full, img2, Size(), scale2, scale2);
resize(img1_full, img1, Size(), scale1, scale1, INTER_LINEAR_EXACT);
resize(img2_full, img2, Size(), scale2, scale2, INTER_LINEAR_EXACT);
Ptr<detail::FeaturesFinder> finder;
Ptr<detail::FeaturesMatcher> matcher;
modules/stitching/src/stitcher.cpp
+5 -5
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@@ -173,7 +173,7 @@ Stitcher::Status Stitcher::composePanorama(InputArrayOfArrays images, OutputArra
for (size_t i = 0; i < imgs.size(); ++i)
{
imgs_[i] = imgs[i];
resize(imgs[i], img, Size(), seam_scale_, seam_scale_);
resize(imgs[i], img, Size(), seam_scale_, seam_scale_, INTER_LINEAR_EXACT);
seam_est_imgs_[i] = img.clone();
}
@@ -315,7 +315,7 @@ Stitcher::Status Stitcher::composePanorama(InputArrayOfArrays images, OutputArra
#if ENABLE_LOG
int64 resize_t = getTickCount();
#endif
resize(full_img, img, Size(), compose_scale, compose_scale);
resize(full_img, img, Size(), compose_scale, compose_scale, INTER_LINEAR_EXACT);
LOGLN(" resize time: " << ((getTickCount() - resize_t) / getTickFrequency()) << " sec");
}
else
@@ -361,7 +361,7 @@ Stitcher::Status Stitcher::composePanorama(InputArrayOfArrays images, OutputArra
// Make sure seam mask has proper size
dilate(masks_warped[img_idx], dilated_mask, Mat());
resize(dilated_mask, seam_mask, mask_warped.size());
resize(dilated_mask, seam_mask, mask_warped.size(), 0, 0, INTER_LINEAR_EXACT);
bitwise_and(seam_mask, mask_warped, mask_warped);
@@ -471,7 +471,7 @@ Stitcher::Status Stitcher::matchImages()
work_scale_ = std::min(1.0, std::sqrt(registr_resol_ * 1e6 / full_img.size().area()));
is_work_scale_set = true;
}
resize(full_img, img, Size(), work_scale_, work_scale_);
resize(full_img, img, Size(), work_scale_, work_scale_, INTER_LINEAR_EXACT);
}
if (!is_seam_scale_set)
{
@@ -496,7 +496,7 @@ Stitcher::Status Stitcher::matchImages()
features_[i].img_idx = (int)i;
LOGLN("Features in image #" << i+1 << ": " << features_[i].keypoints.size());
resize(full_img, img, Size(), seam_scale_, seam_scale_);
resize(full_img, img, Size(), seam_scale_, seam_scale_, INTER_LINEAR_EXACT);
seam_est_imgs_[i] = img.clone();
}