Correct tolerance value for sanity checks with ERROR_RELATIVE

Use min/max bounds instead of local value to calculate acceptance threshold.
Threshold based on local values somethimes does not work because cancellation
of big values may produce error bigger than local value.

diff --git a/modules/ts/src/ts_perf.cpp b/modules/ts/src/ts_perf.cpp
index 0a94fcc19ca62d0a6cde820552a32a0e08fe624f..cd82d73ef3744f985036e03cc37e264e48923bd4 100644 (file)
--- a/modules/ts/src/ts_perf.cpp
+++ b/modules/ts/src/ts_perf.cpp
@@ -334,29 +334,21 @@ void Regression::write(cv::Mat m)
     write() << "val" << getElem(m, y, x, cn) << "}";
 }
 
-static double evalEps(double expected, double actual, double _eps, ERROR_TYPE err)
-{
-    if (err == ERROR_ABSOLUTE)
-        return _eps;
-    else if (err == ERROR_RELATIVE)
-        return std::max(std::abs(expected), std::abs(actual)) * _eps;
-    return 0;
-}
-
-void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::string argname, ERROR_TYPE err)
+void Regression::verify(cv::FileNode node, cv::Mat actual, double eps, std::string argname, ERROR_TYPE err)
 {
     if (!actual.empty() && actual.dims < 2) return;
 
+    double expect_min = (double)node["min"];
+    double expect_max = (double)node["max"];
+
+    if (err == ERROR_RELATIVE)
+        eps *= std::max(std::abs(expect_min), std::abs(expect_max));
+
     double actual_min, actual_max;
     cv::minMaxIdx(actual, &actual_min, &actual_max);
 
-    double expect_min = (double)node["min"];
-    double eps = evalEps(expect_min, actual_min, _eps, err);
     ASSERT_NEAR(expect_min, actual_min, eps)
             << argname << " has unexpected minimal value" << std::endl;
-
-    double expect_max = (double)node["max"];
-    eps = evalEps(expect_max, actual_max, _eps, err);
     ASSERT_NEAR(expect_max, actual_max, eps)
             << argname << " has unexpected maximal value" << std::endl;
 
@@ -370,7 +362,6 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
             << argname << " has unexpected number of rows" << std::endl;
 
     double expect_last = (double)last["val"];
-    eps = evalEps(expect_last, actual_last, _eps, err);
     ASSERT_NEAR(expect_last, actual_last, eps)
             << argname << " has unexpected value of the last element" << std::endl;
 
@@ -384,7 +375,6 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
     // verified that mat size is the same as recorded
     double actual_rng1 = getElem(actual, y1, x1, cn1);
 
-    eps = evalEps(expect_rng1, actual_rng1, _eps, err);
     ASSERT_NEAR(expect_rng1, actual_rng1, eps)
             << argname << " has unexpected value of the ["<< x1 << ":" << y1 << ":" << cn1 <<"] element" << std::endl;
 
@@ -396,7 +386,6 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
     double expect_rng2 = (double)rng2["val"];
     double actual_rng2 = getElem(actual, y2, x2, cn2);
 
-    eps = evalEps(expect_rng2, actual_rng2, _eps, err);
     ASSERT_NEAR(expect_rng2, actual_rng2, eps)
             << argname << " has unexpected value of the ["<< x2 << ":" << y2 << ":" << cn2 <<"] element" << std::endl;
 }