opencv/modules/imgproc/test/test_houghLines.cpp
Ilya Lavrenov aa5326c231 cv::norm -> cvtest::norm in tests
Conflicts:

	modules/core/src/stat.cpp
2014-04-08 14:49:20 +04:00

152 lines
4.8 KiB
C++

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#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 )
transpose(lines, lines);
if ( exp_lines.size != lines.size || cvtest::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(); }