Improve performance tests failures formatting

diff --git a/modules/ts/src/ts_perf.cpp b/modules/ts/src/ts_perf.cpp
index d0194ed..6e14422 100644 (file)
--- a/modules/ts/src/ts_perf.cpp
+++ b/modules/ts/src/ts_perf.cpp
@@ -326,42 +326,53 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
     double actual_min, actual_max;
     cv::minMaxLoc(actual, &actual_min, &actual_max);
 
-    double eps = evalEps((double)node["min"], actual_min, _eps, err);
-    ASSERT_NEAR((double)node["min"], actual_min, eps)
-            << "  " << argname << " has unexpected minimal value";
+    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;
 
-    eps = evalEps((double)node["max"], actual_max, _eps, err);
-    ASSERT_NEAR((double)node["max"], actual_max, eps)
-            << "  " << argname << " has unexpected maximal value";
+    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;
 
     cv::FileNode last = node["last"];
-    double actualLast = getElem(actual, actual.rows - 1, actual.cols - 1, actual.channels() - 1);
-    ASSERT_EQ((int)last["x"], actual.cols - 1)
-            << "  " << argname << " has unexpected number of columns";
-    ASSERT_EQ((int)last["y"], actual.rows - 1)
-            << "  " << argname << " has unexpected number of rows";
-
-    eps = evalEps((double)last["val"], actualLast, _eps, err);
-    ASSERT_NEAR((double)last["val"], actualLast, eps)
-            << "  " << argname << " has unexpected value of last element";
+    double actual_last = getElem(actual, actual.rows - 1, actual.cols - 1, actual.channels() - 1);
+    int expect_cols = (int)last["x"] + 1;
+    int expect_rows = (int)last["y"] + 1;
+    ASSERT_EQ(expect_cols, actual.cols)
+            << argname << " has unexpected number of columns" << std::endl;
+    ASSERT_EQ(expect_rows, actual.rows)
+            << 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;
 
     cv::FileNode rng1 = node["rng1"];
     int x1 = rng1["x"];
     int y1 = rng1["y"];
     int cn1 = rng1["cn"];
 
-    eps = evalEps((double)rng1["val"], getElem(actual, y1, x1, cn1), _eps, err);
-    ASSERT_NEAR((double)rng1["val"], getElem(actual, y1, x1, cn1), eps)
-            << "  " << argname << " has unexpected value of ["<< x1 << ":" << y1 << ":" << cn1 <<"] element";
+    double expect_rng1 = (double)rng1["val"];
+    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;
 
     cv::FileNode rng2 = node["rng2"];
     int x2 = rng2["x"];
     int y2 = rng2["y"];
     int cn2 = rng2["cn"];
 
-    eps = evalEps((double)rng2["val"], getElem(actual, y2, x2, cn2), _eps, err);
-    ASSERT_NEAR((double)rng2["val"], getElem(actual, y2, x2, cn2), eps)
-            << "  " << argname << " has unexpected value of ["<< x2 << ":" << y2 << ":" << cn2 <<"] element";
+    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;
 }
 
 void Regression::write(cv::InputArray array)
@@ -417,13 +428,16 @@ static int countViolations(const cv::Mat& expected, const cv::Mat& actual, const
 
 void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERROR_TYPE err)
 {
-    ASSERT_EQ((int)node["kind"], array.kind()) << "  Argument \"" << node.name() << "\" has unexpected kind";
-    ASSERT_EQ((int)node["type"], array.type()) << "  Argument \"" << node.name() << "\" has unexpected type";
+    int expected_kind = (int)node["kind"];
+    int expected_type = (int)node["type"];
+    ASSERT_EQ(expected_kind, array.kind()) << "  Argument \"" << node.name() << "\" has unexpected kind";
+    ASSERT_EQ(expected_type, array.type()) << "  Argument \"" << node.name() << "\" has unexpected type";
 
     cv::FileNode valnode = node["val"];
     if (isVector(array))
     {
-        ASSERT_EQ((int)node["len"], (int)array.total()) << "  Vector \"" << node.name() << "\" has unexpected length";
+        int expected_length = (int)node["len"];
+        ASSERT_EQ(expected_length, (int)array.total()) << "  Vector \"" << node.name() << "\" has unexpected length";
         int idx = node["idx"];
 
         cv::Mat actual = array.getMat(idx);
@@ -485,7 +499,7 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
         {
             ASSERT_LE((size_t)26, array.total() * (size_t)array.channels())
                     << "  Argument \"" << node.name() << "\" has unexpected number of elements";
-            verify(node, array.getMat(), eps, "Argument " + node.name(), err);
+            verify(node, array.getMat(), eps, "Argument \"" + node.name() + "\"", err);
         }
         else
         {
@@ -537,6 +551,9 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
 
 Regression& Regression::operator() (const std::string& name, cv::InputArray array, double eps, ERROR_TYPE err)
 {
+    // exit if current test is already failed
+    if(::testing::UnitTest::GetInstance()->current_test_info()->result()->Failed()) return *this;
+
     if(!array.empty() && array.depth() == CV_USRTYPE1)
     {
         ADD_FAILURE() << "  Can not check regression for CV_USRTYPE1 data type for " << name;