Merge pull request #365 from ivan-korolev:fix_HoughLines_segfault

modules/imgproc/test/test_houghLines.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
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+//                For Open Source Computer Vision Library
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+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
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+//M*/
+
+#include "test_precomp.hpp"
+
+using namespace cv;
+using namespace std;
+
+class CV_HoughLinesTest : public cvtest::BaseTest
+{
+public:
+    enum {STANDART = 0, PROBABILISTIC};
+    CV_HoughLinesTest() {}
+    ~CV_HoughLinesTest() {}
+protected:
+    void run_test(int type);
+};
+
+class CV_StandartHoughLinesTest : public CV_HoughLinesTest
+{
+public:
+    CV_StandartHoughLinesTest() {}
+    ~CV_StandartHoughLinesTest() {}
+    virtual void run(int);
+};
+
+class CV_ProbabilisticHoughLinesTest : public CV_HoughLinesTest
+{
+public:
+    CV_ProbabilisticHoughLinesTest() {}
+    ~CV_ProbabilisticHoughLinesTest() {}
+    virtual void run(int);
+};
+
+void CV_StandartHoughLinesTest::run(int)
+{
+    run_test(STANDART);
+}
+
+void CV_ProbabilisticHoughLinesTest::run(int)
+{
+    run_test(PROBABILISTIC);
+}
+
+void CV_HoughLinesTest::run_test(int type)
+{
+    Mat src = imread(string(ts->get_data_path()) + "shared/pic1.png");
+    if (src.empty())
+    {
+        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
+        return;
+    }
+
+    string xml;
+    if (type == STANDART)
+        xml = string(ts->get_data_path()) + "imgproc/HoughLines.xml";
+    else if (type == PROBABILISTIC)
+        xml = string(ts->get_data_path()) + "imgproc/HoughLinesP.xml";
+    else
+    {
+        ts->printf(cvtest::TS::LOG, "Error: unknown HoughLines algorithm type.\n");
+        ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
+        return;
+    }
+
+    Mat dst;
+    Canny(src, dst, 50, 200, 3);
+
+    Mat lines;
+    if (type == STANDART)
+        HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0);
+    else if (type == PROBABILISTIC)
+        HoughLinesP(dst, lines, 1, CV_PI/180, 100, 0, 0);
+
+    FileStorage fs(xml, FileStorage::READ);
+    if (!fs.isOpened())
+    {
+        fs.open(xml, FileStorage::WRITE);
+        if (!fs.isOpened())
+        {
+            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
+            return;
+        }
+        fs << "exp_lines" << lines;
+        fs.release();
+        fs.open(xml, FileStorage::READ);
+        if (!fs.isOpened())
+        {
+            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
+            return;
+        }
+    }
+
+    Mat exp_lines;
+    read( fs["exp_lines"], exp_lines, Mat() );
+    fs.release();
+
+    if ( exp_lines.size != lines.size || norm(exp_lines, lines, NORM_INF) > 1e-4 )
+    {
+        ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
+        return;
+    }
+
+    ts->set_failed_test_info(cvtest::TS::OK);
+}
+
+TEST(Imgproc_HoughLines, regression) { CV_StandartHoughLinesTest test; test.safe_run(); }
+
+TEST(Imgproc_HoughLinesP, regression) { CV_ProbabilisticHoughLinesTest test; test.safe_run(); }
+