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41 #include "test_precomp.hpp"
42 
43 using namespace cv;
44 using namespace std;
45 
46 #define OCL_TUNING_MODE 0
47 #if OCL_TUNING_MODE
48 #define OCL_TUNING_MODE_ONLY(code) code
49 #else
50 #define OCL_TUNING_MODE_ONLY(code)
51 #endif
52 
53 // image moments
54 class CV_MomentsTest : public cvtest::ArrayTest
55 {
56 public:
57     CV_MomentsTest();
58 
59 protected:
60 
61     enum { MOMENT_COUNT = 25 };
62     int prepare_test_case( int test_case_idx );
63     void prepare_to_validation( int /*test_case_idx*/ );
64     void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
65     void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high );
66     double get_success_error_level( int test_case_idx, int i, int j );
67     void run_func();
68     int coi;
69     bool is_binary;
70     bool try_umat;
71 };
72 
73 
CV_MomentsTest()74 CV_MomentsTest::CV_MomentsTest()
75 {
76     test_array[INPUT].push_back(NULL);
77     test_array[OUTPUT].push_back(NULL);
78     test_array[REF_OUTPUT].push_back(NULL);
79     coi = -1;
80     is_binary = false;
81     OCL_TUNING_MODE_ONLY(test_case_count = 10);
82     //element_wise_relative_error = false;
83 }
84 
85 
get_minmax_bounds(int i,int j,int type,Scalar & low,Scalar & high)86 void CV_MomentsTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high )
87 {
88     cvtest::ArrayTest::get_minmax_bounds( i, j, type, low, high );
89     int depth = CV_MAT_DEPTH(type);
90 
91     if( depth == CV_16U )
92     {
93         low = Scalar::all(0);
94         high = Scalar::all(1000);
95     }
96     else if( depth == CV_16S )
97     {
98         low = Scalar::all(-1000);
99         high = Scalar::all(1000);
100     }
101     else if( depth == CV_32F )
102     {
103         low = Scalar::all(-1);
104         high = Scalar::all(1);
105     }
106 }
107 
get_test_array_types_and_sizes(int test_case_idx,vector<vector<Size>> & sizes,vector<vector<int>> & types)108 void CV_MomentsTest::get_test_array_types_and_sizes( int test_case_idx,
109                                                 vector<vector<Size> >& sizes, vector<vector<int> >& types )
110 {
111     RNG& rng = ts->get_rng();
112     cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
113     int cn = (cvtest::randInt(rng) % 4) + 1;
114     int depth = cvtest::randInt(rng) % 4;
115     depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : depth == 2 ? CV_16S : CV_32F;
116 
117     is_binary = cvtest::randInt(rng) % 2 != 0;
118     if( depth == 0 && !is_binary )
119         try_umat = cvtest::randInt(rng) % 5 != 0;
120     else
121         try_umat = cvtest::randInt(rng) % 2 != 0;
122 
123     if( cn == 2 || try_umat )
124         cn = 1;
125 
126     OCL_TUNING_MODE_ONLY(
127     cn = 1;
128     depth = CV_8U;
129     try_umat = true;
130     is_binary = false;
131     sizes[INPUT][0] = Size(1024,768)
132     );
133 
134     types[INPUT][0] = CV_MAKETYPE(depth, cn);
135     types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
136     sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(MOMENT_COUNT,1);
137     if(CV_MAT_DEPTH(types[INPUT][0])>=CV_32S)
138         sizes[INPUT][0].width = MAX(sizes[INPUT][0].width, 3);
139 
140     coi = 0;
141     cvmat_allowed = true;
142     if( cn > 1 )
143     {
144         coi = cvtest::randInt(rng) % cn;
145         cvmat_allowed = false;
146     }
147 }
148 
149 
get_success_error_level(int,int,int)150 double CV_MomentsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
151 {
152     int depth = test_mat[INPUT][0].depth();
153     return depth != CV_32F ? FLT_EPSILON*10 : FLT_EPSILON*100;
154 }
155 
prepare_test_case(int test_case_idx)156 int CV_MomentsTest::prepare_test_case( int test_case_idx )
157 {
158     int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
159     if( code > 0 )
160     {
161         int cn = test_mat[INPUT][0].channels();
162         if( cn > 1 )
163             cvSetImageCOI( (IplImage*)test_array[INPUT][0], coi + 1 );
164     }
165 
166     return code;
167 }
168 
169 
run_func()170 void CV_MomentsTest::run_func()
171 {
172     CvMoments* m = (CvMoments*)test_mat[OUTPUT][0].ptr<double>();
173     double* others = (double*)(m + 1);
174     if( try_umat )
175     {
176         UMat u;
177         test_mat[INPUT][0].clone().copyTo(u);
178         OCL_TUNING_MODE_ONLY(
179             static double ttime = 0;
180             static int ncalls = 0;
181             moments(u, is_binary != 0);
182             double t = (double)getTickCount());
183         Moments new_m = moments(u, is_binary != 0);
184         OCL_TUNING_MODE_ONLY(
185             ttime += (double)getTickCount() - t;
186             ncalls++;
187             printf("%g\n", ttime/ncalls/u.total()));
188         *m = new_m;
189     }
190     else
191         cvMoments( test_array[INPUT][0], m, is_binary );
192 
193     others[0] = cvGetNormalizedCentralMoment( m, 2, 0 );
194     others[1] = cvGetNormalizedCentralMoment( m, 1, 1 );
195     others[2] = cvGetNormalizedCentralMoment( m, 0, 2 );
196     others[3] = cvGetNormalizedCentralMoment( m, 3, 0 );
197     others[4] = cvGetNormalizedCentralMoment( m, 2, 1 );
198     others[5] = cvGetNormalizedCentralMoment( m, 1, 2 );
199     others[6] = cvGetNormalizedCentralMoment( m, 0, 3 );
200 }
201 
202 
prepare_to_validation(int)203 void CV_MomentsTest::prepare_to_validation( int /*test_case_idx*/ )
204 {
205     Mat& src = test_mat[INPUT][0];
206     CvMoments m;
207     double* mdata = test_mat[REF_OUTPUT][0].ptr<double>();
208     int depth = src.depth();
209     int cn = src.channels();
210     int i, y, x, cols = src.cols;
211     double xc = 0., yc = 0.;
212 
213     memset( &m, 0, sizeof(m));
214 
215     for( y = 0; y < src.rows; y++ )
216     {
217         double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
218         uchar* ptr = src.ptr(y);
219         for( x = 0; x < cols; x++ )
220         {
221             double val;
222             if( depth == CV_8U )
223                 val = ptr[x*cn + coi];
224             else if( depth == CV_16U )
225                 val = ((ushort*)ptr)[x*cn + coi];
226             else if( depth == CV_16S )
227                 val = ((short*)ptr)[x*cn + coi];
228             else
229                 val = ((float*)ptr)[x*cn + coi];
230 
231             if( is_binary )
232                 val = val != 0;
233 
234             s0 += val;
235             s1 += val*x;
236             s2 += val*x*x;
237             s3 += ((val*x)*x)*x;
238         }
239 
240         m.m00 += s0;
241         m.m01 += s0*y;
242         m.m02 += (s0*y)*y;
243         m.m03 += ((s0*y)*y)*y;
244 
245         m.m10 += s1;
246         m.m11 += s1*y;
247         m.m12 += (s1*y)*y;
248 
249         m.m20 += s2;
250         m.m21 += s2*y;
251 
252         m.m30 += s3;
253     }
254 
255     if( m.m00 != 0 )
256     {
257         xc = m.m10/m.m00, yc = m.m01/m.m00;
258         m.inv_sqrt_m00 = 1./sqrt(fabs(m.m00));
259     }
260 
261     for( y = 0; y < src.rows; y++ )
262     {
263         double s0 = 0, s1 = 0, s2 = 0, s3 = 0, y1 = y - yc;
264         uchar* ptr = src.ptr(y);
265         for( x = 0; x < cols; x++ )
266         {
267             double val, x1 = x - xc;
268             if( depth == CV_8U )
269                 val = ptr[x*cn + coi];
270             else if( depth == CV_16U )
271                 val = ((ushort*)ptr)[x*cn + coi];
272             else if( depth == CV_16S )
273                 val = ((short*)ptr)[x*cn + coi];
274             else
275                 val = ((float*)ptr)[x*cn + coi];
276 
277             if( is_binary )
278                 val = val != 0;
279 
280             s0 += val;
281             s1 += val*x1;
282             s2 += val*x1*x1;
283             s3 += ((val*x1)*x1)*x1;
284         }
285 
286         m.mu02 += s0*y1*y1;
287         m.mu03 += ((s0*y1)*y1)*y1;
288 
289         m.mu11 += s1*y1;
290         m.mu12 += (s1*y1)*y1;
291 
292         m.mu20 += s2;
293         m.mu21 += s2*y1;
294 
295         m.mu30 += s3;
296     }
297 
298     memcpy( mdata, &m, sizeof(m));
299     mdata += sizeof(m)/sizeof(m.m00);
300 
301     /* calc normalized moments */
302     {
303         double inv_m00 = m.inv_sqrt_m00*m.inv_sqrt_m00;
304         double s2 = inv_m00*inv_m00; /* 1./(m00 ^ (2/2 + 1)) */
305         double s3 = s2*m.inv_sqrt_m00; /* 1./(m00 ^ (3/2 + 1)) */
306 
307         mdata[0] = m.mu20 * s2;
308         mdata[1] = m.mu11 * s2;
309         mdata[2] = m.mu02 * s2;
310 
311         mdata[3] = m.mu30 * s3;
312         mdata[4] = m.mu21 * s3;
313         mdata[5] = m.mu12 * s3;
314         mdata[6] = m.mu03 * s3;
315     }
316 
317     double* a = test_mat[REF_OUTPUT][0].ptr<double>();
318     double* b = test_mat[OUTPUT][0].ptr<double>();
319     for( i = 0; i < MOMENT_COUNT; i++ )
320     {
321         if( fabs(a[i]) < 1e-3 )
322             a[i] = 0;
323         if( fabs(b[i]) < 1e-3 )
324             b[i] = 0;
325     }
326 }
327 
328 
329 // Hu invariants
330 class CV_HuMomentsTest : public cvtest::ArrayTest
331 {
332 public:
333     CV_HuMomentsTest();
334 
335 protected:
336 
337     enum { MOMENT_COUNT = 18, HU_MOMENT_COUNT = 7 };
338 
339     int prepare_test_case( int test_case_idx );
340     void prepare_to_validation( int /*test_case_idx*/ );
341     void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
342     void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high );
343     double get_success_error_level( int test_case_idx, int i, int j );
344     void run_func();
345 };
346 
347 
CV_HuMomentsTest()348 CV_HuMomentsTest::CV_HuMomentsTest()
349 {
350     test_array[INPUT].push_back(NULL);
351     test_array[OUTPUT].push_back(NULL);
352     test_array[REF_OUTPUT].push_back(NULL);
353 }
354 
355 
get_minmax_bounds(int i,int j,int type,Scalar & low,Scalar & high)356 void CV_HuMomentsTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high )
357 {
358     cvtest::ArrayTest::get_minmax_bounds( i, j, type, low, high );
359     low = Scalar::all(-10000);
360     high = Scalar::all(10000);
361 }
362 
363 
get_test_array_types_and_sizes(int test_case_idx,vector<vector<Size>> & sizes,vector<vector<int>> & types)364 void CV_HuMomentsTest::get_test_array_types_and_sizes( int test_case_idx,
365                                                 vector<vector<Size> >& sizes, vector<vector<int> >& types )
366 {
367     cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
368     types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
369     sizes[INPUT][0] = cvSize(MOMENT_COUNT,1);
370     sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(HU_MOMENT_COUNT,1);
371 }
372 
373 
get_success_error_level(int,int,int)374 double CV_HuMomentsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
375 {
376     return FLT_EPSILON;
377 }
378 
379 
380 
prepare_test_case(int test_case_idx)381 int CV_HuMomentsTest::prepare_test_case( int test_case_idx )
382 {
383     int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
384     if( code > 0 )
385     {
386         // ...
387     }
388 
389     return code;
390 }
391 
392 
run_func()393 void CV_HuMomentsTest::run_func()
394 {
395     cvGetHuMoments( test_mat[INPUT][0].ptr<CvMoments>(),
396                     test_mat[OUTPUT][0].ptr<CvHuMoments>() );
397 }
398 
399 
prepare_to_validation(int)400 void CV_HuMomentsTest::prepare_to_validation( int /*test_case_idx*/ )
401 {
402     CvMoments* m = test_mat[INPUT][0].ptr<CvMoments>();
403     CvHuMoments* hu = test_mat[REF_OUTPUT][0].ptr<CvHuMoments>();
404 
405     double inv_m00 = m->inv_sqrt_m00*m->inv_sqrt_m00;
406     double s2 = inv_m00*inv_m00; /* 1./(m00 ^ (2/2 + 1)) */
407     double s3 = s2*m->inv_sqrt_m00; /* 1./(m00 ^ (3/2 + 1)) */
408 
409     double nu20 = m->mu20 * s2;
410     double nu11 = m->mu11 * s2;
411     double nu02 = m->mu02 * s2;
412 
413     double nu30 = m->mu30 * s3;
414     double nu21 = m->mu21 * s3;
415     double nu12 = m->mu12 * s3;
416     double nu03 = m->mu03 * s3;
417 
418     #undef sqr
419     #define sqr(a) ((a)*(a))
420 
421     hu->hu1 = nu20 + nu02;
422     hu->hu2 = sqr(nu20 - nu02) + 4*sqr(nu11);
423     hu->hu3 = sqr(nu30 - 3*nu12) + sqr(3*nu21 - nu03);
424     hu->hu4 = sqr(nu30 + nu12) + sqr(nu21 + nu03);
425     hu->hu5 = (nu30 - 3*nu12)*(nu30 + nu12)*(sqr(nu30 + nu12) - 3*sqr(nu21 + nu03)) +
426             (3*nu21 - nu03)*(nu21 + nu03)*(3*sqr(nu30 + nu12) - sqr(nu21 + nu03));
427     hu->hu6 = (nu20 - nu02)*(sqr(nu30 + nu12) - sqr(nu21 + nu03)) +
428             4*nu11*(nu30 + nu12)*(nu21 + nu03);
429     hu->hu7 = (3*nu21 - nu03)*(nu30 + nu12)*(sqr(nu30 + nu12) - 3*sqr(nu21 + nu03)) +
430             (3*nu12 - nu30)*(nu21 + nu03)*(3*sqr(nu30 + nu12) - sqr(nu21 + nu03));
431 }
432 
433 
TEST(Imgproc_Moments,accuracy)434 TEST(Imgproc_Moments, accuracy) { CV_MomentsTest test; test.safe_run(); }
TEST(Imgproc_HuMoments,accuracy)435 TEST(Imgproc_HuMoments, accuracy) { CV_HuMomentsTest test; test.safe_run(); }
436 
437 class CV_SmallContourMomentTest : public cvtest::BaseTest
438 {
439 public:
CV_SmallContourMomentTest()440     CV_SmallContourMomentTest() {}
~CV_SmallContourMomentTest()441     ~CV_SmallContourMomentTest() {}
442 protected:
run(int)443     void run(int)
444     {
445         try
446         {
447             vector<Point> points;
448             points.push_back(Point(50, 56));
449             points.push_back(Point(53, 53));
450             points.push_back(Point(46, 54));
451             points.push_back(Point(49, 51));
452 
453             Moments m = moments(points, false);
454             double area = contourArea(points);
455 
456             CV_Assert( m.m00 == 0 && m.m01 == 0 && m.m10 == 0 && area == 0 );
457         }
458         catch(...)
459         {
460             ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
461         }
462     }
463 };
464 
TEST(Imgproc_ContourMoment,small)465 TEST(Imgproc_ContourMoment, small) { CV_SmallContourMomentTest test; test.safe_run(); }
466