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11 // For Open Source Computer Vision Library
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43
44 #include "test_precomp.hpp"
45
46 using namespace cv;
47 using namespace std;
48
49 template<typename T>
50 struct SimilarWith
51 {
52 T value;
53 float theta_eps;
54 float rho_eps;
SimilarWithSimilarWith55 SimilarWith<T>(T val, float e, float r_e): value(val), theta_eps(e), rho_eps(r_e) { };
56 bool operator()(T other);
57 };
58
59 template<>
operator ()(Vec2f other)60 bool SimilarWith<Vec2f>::operator()(Vec2f other)
61 {
62 return abs(other[0] - value[0]) < rho_eps && abs(other[1] - value[1]) < theta_eps;
63 }
64
65 template<>
operator ()(Vec4i other)66 bool SimilarWith<Vec4i>::operator()(Vec4i other)
67 {
68 return norm(value, other) < theta_eps;
69 }
70
71 template <typename T>
countMatIntersection(Mat expect,Mat actual,float eps,float rho_eps)72 int countMatIntersection(Mat expect, Mat actual, float eps, float rho_eps)
73 {
74 int count = 0;
75 if (!expect.empty() && !actual.empty())
76 {
77 for (MatIterator_<T> it=expect.begin<T>(); it!=expect.end<T>(); it++)
78 {
79 MatIterator_<T> f = std::find_if(actual.begin<T>(), actual.end<T>(), SimilarWith<T>(*it, eps, rho_eps));
80 if (f != actual.end<T>())
81 count++;
82 }
83 }
84 return count;
85 }
86
getTestCaseName(String filename)87 String getTestCaseName(String filename)
88 {
89 string temp(filename);
90 size_t pos = temp.find_first_of("\\/.");
91 while ( pos != string::npos ) {
92 temp.replace( pos, 1, "_" );
93 pos = temp.find_first_of("\\/.");
94 }
95 return String(temp);
96 }
97
98 class BaseHoughLineTest
99 {
100 public:
101 enum {STANDART = 0, PROBABILISTIC};
102 protected:
103 void run_test(int type);
104
105 string picture_name;
106 double rhoStep;
107 double thetaStep;
108 int threshold;
109 int minLineLength;
110 int maxGap;
111 };
112
113 typedef std::tr1::tuple<string, double, double, int> Image_RhoStep_ThetaStep_Threshold_t;
114 class StandartHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_t>
115 {
116 public:
StandartHoughLinesTest()117 StandartHoughLinesTest()
118 {
119 picture_name = std::tr1::get<0>(GetParam());
120 rhoStep = std::tr1::get<1>(GetParam());
121 thetaStep = std::tr1::get<2>(GetParam());
122 threshold = std::tr1::get<3>(GetParam());
123 minLineLength = 0;
124 maxGap = 0;
125 }
126 };
127
128 typedef std::tr1::tuple<string, double, double, int, int, int> Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t;
129 class ProbabilisticHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t>
130 {
131 public:
ProbabilisticHoughLinesTest()132 ProbabilisticHoughLinesTest()
133 {
134 picture_name = std::tr1::get<0>(GetParam());
135 rhoStep = std::tr1::get<1>(GetParam());
136 thetaStep = std::tr1::get<2>(GetParam());
137 threshold = std::tr1::get<3>(GetParam());
138 minLineLength = std::tr1::get<4>(GetParam());
139 maxGap = std::tr1::get<5>(GetParam());
140 }
141 };
142
run_test(int type)143 void BaseHoughLineTest::run_test(int type)
144 {
145 string filename = cvtest::TS::ptr()->get_data_path() + picture_name;
146 Mat src = imread(filename, IMREAD_GRAYSCALE);
147 EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename;
148
149 string xml;
150 if (type == STANDART)
151 xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLines.xml";
152 else if (type == PROBABILISTIC)
153 xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLinesP.xml";
154
155 Mat dst;
156 Canny(src, dst, 100, 150, 3);
157 EXPECT_FALSE(dst.empty()) << "Failed Canny edge detector";
158
159 Mat lines;
160 if (type == STANDART)
161 HoughLines(dst, lines, rhoStep, thetaStep, threshold, 0, 0);
162 else if (type == PROBABILISTIC)
163 HoughLinesP(dst, lines, rhoStep, thetaStep, threshold, minLineLength, maxGap);
164
165 String test_case_name = format("lines_%s_%.0f_%.2f_%d_%d_%d", picture_name.c_str(), rhoStep, thetaStep,
166 threshold, minLineLength, maxGap);
167 test_case_name = getTestCaseName(test_case_name);
168
169 FileStorage fs(xml, FileStorage::READ);
170 FileNode node = fs[test_case_name];
171 if (node.empty())
172 {
173 fs.release();
174 fs.open(xml, FileStorage::APPEND);
175 EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
176 fs << test_case_name << lines;
177 fs.release();
178 fs.open(xml, FileStorage::READ);
179 EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
180 }
181
182 Mat exp_lines;
183 read( fs[test_case_name], exp_lines, Mat() );
184 fs.release();
185
186 int count = -1;
187 if (type == STANDART)
188 count = countMatIntersection<Vec2f>(exp_lines, lines, (float) thetaStep + FLT_EPSILON, (float) rhoStep + FLT_EPSILON);
189 else if (type == PROBABILISTIC)
190 count = countMatIntersection<Vec4i>(exp_lines, lines, 1e-4f, 0.f);
191
192 #if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
193 EXPECT_GE( count, (int) (exp_lines.total() * 0.8) );
194 #else
195 EXPECT_EQ( count, (int) exp_lines.total());
196 #endif
197 }
198
TEST_P(StandartHoughLinesTest,regression)199 TEST_P(StandartHoughLinesTest, regression)
200 {
201 run_test(STANDART);
202 }
203
TEST_P(ProbabilisticHoughLinesTest,regression)204 TEST_P(ProbabilisticHoughLinesTest, regression)
205 {
206 run_test(PROBABILISTIC);
207 }
208
209 INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ),
210 testing::Values( 1, 10 ),
211 testing::Values( 0.05, 0.1 ),
212 testing::Values( 80, 150 )
213 ));
214
215 INSTANTIATE_TEST_CASE_P( ImgProc, ProbabilisticHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "shared/pic1.png" ),
216 testing::Values( 5, 10 ),
217 testing::Values( 0.05, 0.1 ),
218 testing::Values( 75, 150 ),
219 testing::Values( 0, 10 ),
220 testing::Values( 0, 4 )
221 ));
222