tests: add "bigdata" tests

modules/core/test/test_io.cpp

@@ -522,33 +522,23 @@ protected:
 
 TEST(Core_InputOutput, misc) { CV_MiscIOTest test; test.safe_run(); }
 
-/*class CV_BigMatrixIOTest : public cvtest::BaseTest
+#if 0 // 4+ GB of data, 40+ GB of estimated result size, it is very slow
+BIGDATA_TEST(Core_InputOutput, huge)
 {
-public:
+    RNG& rng = theRNG();
-    CV_BigMatrixIOTest() {}
+    int N = 1000, M = 1200000;
-    ~CV_BigMatrixIOTest() {}
+    std::cout << "Allocating..." << std::endl;
-protected:
+    Mat mat(M, N, CV_32F);
-    void run(int)
+    std::cout << "Initializing..." << std::endl;
+    rng.fill(mat, RNG::UNIFORM, 0, 1);
+    std::cout << "Writing..." << std::endl;
     {
-        try
+        FileStorage fs(cv::tempfile(".xml"), FileStorage::WRITE);
-        {
+        fs << "mat" << mat;
-            RNG& rng = theRNG();
+        fs.release();
-            int N = 1000, M = 1200000;
-            Mat mat(M, N, CV_32F);
-            rng.fill(mat, RNG::UNIFORM, 0, 1);
-            FileStorage fs(cv::tempfile(".xml"), FileStorage::WRITE);
-            fs << "mat" << mat;
-            fs.release();
-        }
-        catch(...)
-        {
-            ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
-        }
     }
-};
+}
-
+#endif
-TEST(Core_InputOutput, huge) { CV_BigMatrixIOTest test; test.safe_run(); }
-*/
 
 TEST(Core_globbing, accuracy)
 {

modules/core/test/test_mat.cpp

@@ -1776,4 +1776,26 @@ TEST(Mat_, template_based_ptr)
 
 #endif
 
+
+BIGDATA_TEST(Mat, push_back_regression_4158)  // memory usage: ~10.6 Gb
+{
+    Mat result;
+
+    Mat tail(100, 500000, CV_32FC2, Scalar(1, 2));
+
+    tail.copyTo(result);
+    for (int i = 1; i < 15; i++)
+    {
+        result.push_back(tail);
+        std::cout << "i = " << i << "  result = " << result.size() << "   used = " << (uint64)result.total()*result.elemSize()*(1.0 / (1 << 20)) << " Mb"
+            << "   allocated=" << (uint64)(result.datalimit - result.datastart)*(1.0 / (1 << 20)) << " Mb" << std::endl;
+    }
+    for (int i = 0; i < 15; i++)
+    {
+        Rect roi(0, tail.rows * i, tail.cols, tail.rows);
+        int nz = countNonZero(result(roi).reshape(1) == 2);
+        EXPECT_EQ(tail.total(), (size_t)nz) << "i=" << i;
+    }
+}
+
 }} // namespace

modules/imgproc/test/test_thresh.cpp

@@ -420,34 +420,18 @@ void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ )
 
 TEST(Imgproc_Threshold, accuracy) { CV_ThreshTest test; test.safe_run(); }
 
-#if defined(_M_X64) || defined(__x86_64__)
+BIGDATA_TEST(Imgproc_Threshold, huge)
-TEST(Imgproc_Threshold, huge) /* since the test needs a lot of memory, enable it only on 64-bit Intel/AMD platforms, otherwise it may take a lot of time because of heavy swapping */
-#else
-TEST(DISABLED_Imgproc_Threshold, huge)
-#endif
 {
-    Mat m;
+    Mat m(65000, 40000, CV_8U);
-    try
+    ASSERT_FALSE(m.isContinuous());
-    {
-        m.create(65000, 40000, CV_8U);
-    }
-    catch(...)
-    {
-    }
 
-    if( !m.empty() )
+    uint64 i, n = (uint64)m.rows*m.cols;
-    {
+    for( i = 0; i < n; i++ )
-        ASSERT_FALSE(m.isContinuous());
+        m.data[i] = (uchar)(i & 255);
 
-        uint64 i, n = (uint64)m.rows*m.cols;
+    cv::threshold(m, m, 127, 255, cv::THRESH_BINARY);
-        for( i = 0; i < n; i++ )
+    int nz = cv::countNonZero(m);  // FIXIT 'int' is not enough here (overflow is possible with other inputs)
-            m.data[i] = (uchar)(i & 255);
+    ASSERT_EQ((uint64)nz, n / 2);
-
-        cv::threshold(m, m, 127, 255, cv::THRESH_BINARY);
-        int nz = cv::countNonZero(m);
-        ASSERT_EQ(nz, (int)(n/2));
-    }
-    // just skip the test if there is no enough memory
 }
 
 }} // namespace