mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
352 lines
12 KiB
352 lines
12 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
|
// Copyright (C) 2014, Itseez, Inc, all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other materials provided with the distribution. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (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, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#include "test_precomp.hpp" |
|
|
|
//#define GENERATE_DATA // generate data in debug mode via CPU code path (without IPP / OpenCL and other accelerators) |
|
|
|
namespace opencv_test { namespace { |
|
|
|
template<typename T> |
|
struct SimilarWith |
|
{ |
|
T value; |
|
float theta_eps; |
|
float rho_eps; |
|
SimilarWith<T>(T val, float e, float r_e): value(val), theta_eps(e), rho_eps(r_e) { }; |
|
bool operator()(const T& other); |
|
}; |
|
|
|
template<> |
|
bool SimilarWith<Vec2f>::operator()(const Vec2f& other) |
|
{ |
|
return std::abs(other[0] - value[0]) < rho_eps && std::abs(other[1] - value[1]) < theta_eps; |
|
} |
|
|
|
template<> |
|
bool SimilarWith<Vec3f>::operator()(const Vec3f& other) |
|
{ |
|
return std::abs(other[0] - value[0]) < rho_eps && std::abs(other[1] - value[1]) < theta_eps; |
|
} |
|
|
|
template<> |
|
bool SimilarWith<Vec4i>::operator()(const Vec4i& other) |
|
{ |
|
return cv::norm(value, other) < theta_eps; |
|
} |
|
|
|
template <typename T> |
|
int countMatIntersection(const Mat& expect, const Mat& actual, float eps, float rho_eps) |
|
{ |
|
int count = 0; |
|
if (!expect.empty() && !actual.empty()) |
|
{ |
|
for (MatConstIterator_<T> it=expect.begin<T>(); it!=expect.end<T>(); it++) |
|
{ |
|
MatConstIterator_<T> f = std::find_if(actual.begin<T>(), actual.end<T>(), SimilarWith<T>(*it, eps, rho_eps)); |
|
if (f != actual.end<T>()) |
|
count++; |
|
} |
|
} |
|
return count; |
|
} |
|
|
|
String getTestCaseName(String filename) |
|
{ |
|
string temp(filename); |
|
size_t pos = temp.find_first_of("\\/."); |
|
while ( pos != string::npos ) { |
|
temp.replace( pos, 1, "_" ); |
|
pos = temp.find_first_of("\\/."); |
|
} |
|
return String(temp); |
|
} |
|
|
|
class BaseHoughLineTest |
|
{ |
|
public: |
|
enum {STANDART = 0, PROBABILISTIC}; |
|
protected: |
|
template<typename LinesType, typename LineType> |
|
void run_test(int type, const char* xml_name); |
|
|
|
string picture_name; |
|
double rhoStep; |
|
double thetaStep; |
|
int threshold; |
|
int minLineLength; |
|
int maxGap; |
|
}; |
|
|
|
typedef tuple<string, double, double, int> Image_RhoStep_ThetaStep_Threshold_t; |
|
class StandartHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_t> |
|
{ |
|
public: |
|
StandartHoughLinesTest() |
|
{ |
|
picture_name = get<0>(GetParam()); |
|
rhoStep = get<1>(GetParam()); |
|
thetaStep = get<2>(GetParam()); |
|
threshold = get<3>(GetParam()); |
|
minLineLength = 0; |
|
maxGap = 0; |
|
} |
|
}; |
|
|
|
typedef tuple<string, double, double, int, int, int> Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t; |
|
class ProbabilisticHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t> |
|
{ |
|
public: |
|
ProbabilisticHoughLinesTest() |
|
{ |
|
picture_name = get<0>(GetParam()); |
|
rhoStep = get<1>(GetParam()); |
|
thetaStep = get<2>(GetParam()); |
|
threshold = get<3>(GetParam()); |
|
minLineLength = get<4>(GetParam()); |
|
maxGap = get<5>(GetParam()); |
|
} |
|
}; |
|
|
|
typedef tuple<double, double, double, double> HoughLinesPointSetInput_t; |
|
class HoughLinesPointSetTest : public testing::TestWithParam<HoughLinesPointSetInput_t> |
|
{ |
|
protected: |
|
void run_test(); |
|
double Rho; |
|
double Theta; |
|
double rhoMin, rhoMax, rhoStep; |
|
double thetaMin, thetaMax, thetaStep; |
|
public: |
|
HoughLinesPointSetTest() |
|
{ |
|
rhoMin = get<0>(GetParam()); |
|
rhoMax = get<1>(GetParam()); |
|
rhoStep = (rhoMax - rhoMin) / 360.0f; |
|
thetaMin = get<2>(GetParam()); |
|
thetaMax = get<3>(GetParam()); |
|
thetaStep = CV_PI / 180.0f; |
|
Rho = 320.00000; |
|
Theta = 1.04719; |
|
} |
|
}; |
|
|
|
template<typename LinesType, typename LineType> |
|
void BaseHoughLineTest::run_test(int type, const char* xml_name) |
|
{ |
|
string filename = cvtest::TS::ptr()->get_data_path() + picture_name; |
|
Mat src = imread(filename, IMREAD_GRAYSCALE); |
|
ASSERT_FALSE(src.empty()) << "Invalid test image: " << filename; |
|
|
|
string xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/" + xml_name; |
|
|
|
Mat dst; |
|
Canny(src, dst, 100, 150, 3); |
|
ASSERT_FALSE(dst.empty()) << "Failed Canny edge detector"; |
|
|
|
LinesType lines; |
|
if (type == STANDART) |
|
HoughLines(dst, lines, rhoStep, thetaStep, threshold, 0, 0); |
|
else if (type == PROBABILISTIC) |
|
HoughLinesP(dst, lines, rhoStep, thetaStep, threshold, minLineLength, maxGap); |
|
|
|
String test_case_name = format("lines_%s_%.0f_%.2f_%d_%d_%d", picture_name.c_str(), rhoStep, thetaStep, |
|
threshold, minLineLength, maxGap); |
|
test_case_name = getTestCaseName(test_case_name); |
|
|
|
#ifdef GENERATE_DATA |
|
{ |
|
FileStorage fs(xml, FileStorage::READ); |
|
ASSERT_TRUE(!fs.isOpened() || fs[test_case_name].empty()); |
|
} |
|
{ |
|
FileStorage fs(xml, FileStorage::APPEND); |
|
EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml; |
|
fs << test_case_name << Mat(lines); |
|
} |
|
#else |
|
FileStorage fs(xml, FileStorage::READ); |
|
FileNode node = fs[test_case_name]; |
|
ASSERT_FALSE(node.empty()) << "Missing test data: " << test_case_name << std::endl << "XML: " << xml; |
|
|
|
Mat exp_lines_; |
|
read(fs[test_case_name], exp_lines_, Mat()); |
|
fs.release(); |
|
LinesType exp_lines; |
|
exp_lines_.copyTo(exp_lines); |
|
|
|
int count = -1; |
|
if (type == STANDART) |
|
count = countMatIntersection<LineType>(Mat(exp_lines), Mat(lines), (float) thetaStep + FLT_EPSILON, (float) rhoStep + FLT_EPSILON); |
|
else if (type == PROBABILISTIC) |
|
count = countMatIntersection<LineType>(Mat(exp_lines), Mat(lines), 1e-4f, 0.f); |
|
|
|
#if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH |
|
EXPECT_LE(std::abs((double)count - Mat(exp_lines).total()), Mat(exp_lines).total() * 0.25) |
|
<< "count=" << count << " expected=" << Mat(exp_lines).total(); |
|
#else |
|
EXPECT_EQ(count, (int)Mat(exp_lines).total()); |
|
#endif |
|
#endif // GENERATE_DATA |
|
} |
|
|
|
void HoughLinesPointSetTest::run_test(void) |
|
{ |
|
Mat lines_f, lines_i; |
|
vector<Point2f> pointf; |
|
vector<Point2i> pointi; |
|
vector<Vec3d> line_polar_f, line_polar_i; |
|
const float Points[20][2] = { |
|
{ 0.0f, 369.0f }, { 10.0f, 364.0f }, { 20.0f, 358.0f }, { 30.0f, 352.0f }, |
|
{ 40.0f, 346.0f }, { 50.0f, 341.0f }, { 60.0f, 335.0f }, { 70.0f, 329.0f }, |
|
{ 80.0f, 323.0f }, { 90.0f, 318.0f }, { 100.0f, 312.0f }, { 110.0f, 306.0f }, |
|
{ 120.0f, 300.0f }, { 130.0f, 295.0f }, { 140.0f, 289.0f }, { 150.0f, 284.0f }, |
|
{ 160.0f, 277.0f }, { 170.0f, 271.0f }, { 180.0f, 266.0f }, { 190.0f, 260.0f } |
|
}; |
|
|
|
// Float |
|
for (int i = 0; i < 20; i++) |
|
{ |
|
pointf.push_back(Point2f(Points[i][0],Points[i][1])); |
|
} |
|
|
|
HoughLinesPointSet(pointf, lines_f, 20, 1, |
|
rhoMin, rhoMax, rhoStep, |
|
thetaMin, thetaMax, thetaStep); |
|
|
|
lines_f.copyTo( line_polar_f ); |
|
|
|
// Integer |
|
for( int i = 0; i < 20; i++ ) |
|
{ |
|
pointi.push_back( Point2i( (int)Points[i][0], (int)Points[i][1] ) ); |
|
} |
|
|
|
HoughLinesPointSet( pointi, lines_i, 20, 1, |
|
rhoMin, rhoMax, rhoStep, |
|
thetaMin, thetaMax, thetaStep ); |
|
|
|
lines_i.copyTo( line_polar_i ); |
|
|
|
EXPECT_EQ((int)(line_polar_f.at(0).val[1] * 100000.0f), (int)(Rho * 100000.0f)); |
|
EXPECT_EQ((int)(line_polar_f.at(0).val[2] * 100000.0f), (int)(Theta * 100000.0f)); |
|
EXPECT_EQ((int)(line_polar_i.at(0).val[1] * 100000.0f), (int)(Rho * 100000.0f)); |
|
EXPECT_EQ((int)(line_polar_i.at(0).val[2] * 100000.0f), (int)(Theta * 100000.0f)); |
|
} |
|
|
|
TEST_P(StandartHoughLinesTest, regression) |
|
{ |
|
run_test<Mat, Vec2f>(STANDART, "HoughLines.xml"); |
|
} |
|
|
|
TEST_P(ProbabilisticHoughLinesTest, regression) |
|
{ |
|
run_test<Mat, Vec4i>(PROBABILISTIC, "HoughLinesP.xml"); |
|
} |
|
|
|
TEST_P(StandartHoughLinesTest, regression_Vec2f) |
|
{ |
|
run_test<std::vector<Vec2f>, Vec2f>(STANDART, "HoughLines2f.xml"); |
|
} |
|
|
|
TEST_P(StandartHoughLinesTest, regression_Vec3f) |
|
{ |
|
run_test<std::vector<Vec3f>, Vec3f>(STANDART, "HoughLines3f.xml"); |
|
} |
|
|
|
TEST_P(HoughLinesPointSetTest, regression) |
|
{ |
|
run_test(); |
|
} |
|
|
|
TEST(HoughLinesPointSet, regression_21029) |
|
{ |
|
std::vector<Point2f> points; |
|
points.push_back(Point2f(100, 100)); |
|
points.push_back(Point2f(1000, 1000)); |
|
points.push_back(Point2f(10000, 10000)); |
|
points.push_back(Point2f(100000, 100000)); |
|
|
|
double rhoMin = 0; |
|
double rhoMax = 10; |
|
double rhoStep = 0.1; |
|
|
|
double thetaMin = 85 * CV_PI / 180.0; |
|
double thetaMax = 95 * CV_PI / 180.0; |
|
double thetaStep = 1 * CV_PI / 180.0; |
|
|
|
int lines_max = 5; |
|
int threshold = 100; |
|
|
|
Mat lines; |
|
|
|
HoughLinesPointSet(points, lines, |
|
lines_max, threshold, |
|
rhoMin, rhoMax, rhoStep, |
|
thetaMin, thetaMax, thetaStep |
|
); |
|
|
|
EXPECT_TRUE(lines.empty()); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ), |
|
testing::Values( 1, 10 ), |
|
testing::Values( 0.05, 0.1 ), |
|
testing::Values( 80, 150 ) |
|
)); |
|
|
|
INSTANTIATE_TEST_CASE_P( ImgProc, ProbabilisticHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "shared/pic1.png" ), |
|
testing::Values( 5, 10 ), |
|
testing::Values( 0.05, 0.1 ), |
|
testing::Values( 75, 150 ), |
|
testing::Values( 0, 10 ), |
|
testing::Values( 0, 4 ) |
|
)); |
|
|
|
INSTANTIATE_TEST_CASE_P( Imgproc, HoughLinesPointSetTest, testing::Combine(testing::Values( 0.0f, 120.0f ), |
|
testing::Values( 360.0f, 480.0f ), |
|
testing::Values( 0.0f, (CV_PI / 18.0f) ), |
|
testing::Values( (CV_PI / 2.0f), (CV_PI * 5.0f / 12.0f) ) |
|
)); |
|
|
|
}} // namespace
|
|
|