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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