Merge pull request #11531 from alalek:issue_11518

modules/photo/src/seamless_cloning_impl.cpp

@@ -251,13 +251,15 @@ void Cloning::initVariables(const Mat &destination, const Mat &binaryMask)
     //init of the filters used in the dst
     const int w = destination.cols;
     filter_X.resize(w - 2);
+    double scale = CV_PI / (w - 1);
     for(int i = 0 ; i < w-2 ; ++i)
-        filter_X[i] = 2.0f * std::cos(static_cast<float>(CV_PI) * (i + 1) / (w - 1));
+        filter_X[i] = 2.0f * (float)std::cos(scale * (i + 1));
 
     const int h  = destination.rows;
     filter_Y.resize(h - 2);
+    scale = CV_PI / (h - 1);
     for(int j = 0 ; j < h - 2 ; ++j)
-        filter_Y[j] = 2.0f * std::cos(static_cast<float>(CV_PI) * (j + 1) / (h - 1));
+        filter_Y[j] = 2.0f * (float)std::cos(scale * (j + 1));
 }
 
 void Cloning::computeDerivatives(const Mat& destination, const Mat &patch, const Mat &binaryMask)

modules/photo/test/test_cloning.cpp

@@ -53,7 +53,7 @@ namespace opencv_test { namespace {
 #define SAVE(x)
 #endif
 
-static const double numerical_precision = 1000.;
+static const double numerical_precision = 0.05; // 95% of pixels should have exact values
 
 TEST(Photo_SeamlessClone_normal, regression)
 {
@@ -82,8 +82,10 @@ TEST(Photo_SeamlessClone_normal, regression)
 
     SAVE(result);
 
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 TEST(Photo_SeamlessClone_mixed, regression)
@@ -113,9 +115,10 @@ TEST(Photo_SeamlessClone_mixed, regression)
     Mat reference = imread(reference_path);
     ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path;
 
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
-
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 TEST(Photo_SeamlessClone_featureExchange, regression)
@@ -145,9 +148,10 @@ TEST(Photo_SeamlessClone_featureExchange, regression)
     Mat reference = imread(reference_path);
     ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path;
 
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
-
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 TEST(Photo_SeamlessClone_colorChange, regression)
@@ -171,9 +175,10 @@ TEST(Photo_SeamlessClone_colorChange, regression)
     Mat reference = imread(reference_path);
     ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path;
 
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
-
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 TEST(Photo_SeamlessClone_illuminationChange, regression)
@@ -195,9 +200,12 @@ TEST(Photo_SeamlessClone_illuminationChange, regression)
     SAVE(result);
 
     Mat reference = imread(reference_path);
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
+    ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path;
 
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 TEST(Photo_SeamlessClone_textureFlattening, regression)
@@ -221,9 +229,10 @@ TEST(Photo_SeamlessClone_textureFlattening, regression)
     Mat reference = imread(reference_path);
     ASSERT_FALSE(reference.empty()) << "Could not load reference image " << reference_path;
 
-    double error = cvtest::norm(reference, result, NORM_L1);
-    EXPECT_LE(error, numerical_precision);
-
+    double errorINF = cvtest::norm(reference, result, NORM_INF);
+    EXPECT_LE(errorINF, 1);
+    double errorL1 = cvtest::norm(reference, result, NORM_L1);
+    EXPECT_LE(errorL1, reference.total() * numerical_precision) << "size=" << reference.size();
 }
 
 }} // namespace