init - 初始化项目

2022-05-06 01:58:53 +08:00
commit 90a5cc7cb6
6772 changed files with 2837787 additions and 0 deletions
--- a/modules/stitching/test/test_exposure_compensate.cpp
+++ b/modules/stitching/test/test_exposure_compensate.cpp
@@ -0,0 +1,70 @@
+// 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