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41
42 #include "test_precomp.hpp"
43 #include "opencv2/core/core_c.h"
44 #include "opencv2/calib3d/calib3d_c.h"
45
46 namespace cvtest {
47
cvTsRodrigues(const CvMat * src,CvMat * dst,CvMat * jacobian)48 static int cvTsRodrigues( const CvMat* src, CvMat* dst, CvMat* jacobian )
49 {
50 int depth;
51 int i;
52 float Jf[27];
53 double J[27];
54 CvMat _Jf, matJ = cvMat( 3, 9, CV_64F, J );
55
56 depth = CV_MAT_DEPTH(src->type);
57
58 if( jacobian )
59 {
60 assert( (jacobian->rows == 9 && jacobian->cols == 3) ||
61 (jacobian->rows == 3 && jacobian->cols == 9) );
62 }
63
64 if( src->cols == 1 || src->rows == 1 )
65 {
66 double r[3], theta;
67 CvMat _r = cvMat( src->rows, src->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(src->type)), r);
68
69 assert( dst->rows == 3 && dst->cols == 3 );
70
71 cvConvert( src, &_r );
72
73 theta = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);
74 if( theta < DBL_EPSILON )
75 {
76 cvSetIdentity( dst );
77
78 if( jacobian )
79 {
80 memset( J, 0, sizeof(J) );
81 J[5] = J[15] = J[19] = 1;
82 J[7] = J[11] = J[21] = -1;
83 }
84 }
85 else
86 {
87 // omega = r/theta (~[w1, w2, w3])
88 double itheta = 1./theta;
89 double w1 = r[0]*itheta, w2 = r[1]*itheta, w3 = r[2]*itheta;
90 double alpha = cos(theta);
91 double beta = sin(theta);
92 double gamma = 1 - alpha;
93 double omegav[] =
94 {
95 0, -w3, w2,
96 w3, 0, -w1,
97 -w2, w1, 0
98 };
99 double A[] =
100 {
101 w1*w1, w1*w2, w1*w3,
102 w2*w1, w2*w2, w2*w3,
103 w3*w1, w3*w2, w3*w3
104 };
105 double R[9];
106 CvMat _omegav = cvMat(3, 3, CV_64F, omegav);
107 CvMat matA = cvMat(3, 3, CV_64F, A);
108 CvMat matR = cvMat(3, 3, CV_64F, R);
109
110 cvSetIdentity( &matR, cvRealScalar(alpha) );
111 cvScaleAdd( &_omegav, cvRealScalar(beta), &matR, &matR );
112 cvScaleAdd( &matA, cvRealScalar(gamma), &matR, &matR );
113 cvConvert( &matR, dst );
114
115 if( jacobian )
116 {
117 // m3 = [r, theta]
118 double dm3din[] =
119 {
120 1, 0, 0,
121 0, 1, 0,
122 0, 0, 1,
123 w1, w2, w3
124 };
125 // m2 = [omega, theta]
126 double dm2dm3[] =
127 {
128 itheta, 0, 0, -w1*itheta,
129 0, itheta, 0, -w2*itheta,
130 0, 0, itheta, -w3*itheta,
131 0, 0, 0, 1
132 };
133 double t0[9*4];
134 double dm1dm2[21*4];
135 double dRdm1[9*21];
136 CvMat _dm3din = cvMat( 4, 3, CV_64FC1, dm3din );
137 CvMat _dm2dm3 = cvMat( 4, 4, CV_64FC1, dm2dm3 );
138 CvMat _dm1dm2 = cvMat( 21, 4, CV_64FC1, dm1dm2 );
139 CvMat _dRdm1 = cvMat( 9, 21, CV_64FC1, dRdm1 );
140 CvMat _dRdm1_part;
141 CvMat _t0 = cvMat( 9, 4, CV_64FC1, t0 );
142 CvMat _t1 = cvMat( 9, 4, CV_64FC1, dRdm1 );
143
144 // m1 = [alpha, beta, gamma, omegav; A]
145 memset( dm1dm2, 0, sizeof(dm1dm2) );
146 dm1dm2[3] = -beta;
147 dm1dm2[7] = alpha;
148 dm1dm2[11] = beta;
149
150 // dm1dm2(4:12,1:3) = [0 0 0 0 0 1 0 -1 0;
151 // 0 0 -1 0 0 0 1 0 0;
152 // 0 1 0 -1 0 0 0 0 0]'
153 // -------------------
154 // 0 0 0 0 0 0 0 0 0
155 dm1dm2[12 + 6] = dm1dm2[12 + 20] = dm1dm2[12 + 25] = 1;
156 dm1dm2[12 + 9] = dm1dm2[12 + 14] = dm1dm2[12 + 28] = -1;
157
158 double dm1dw[] =
159 {
160 2*w1, w2, w3, w2, 0, 0, w3, 0, 0,
161 0, w1, 0, w1, 2*w2, w3, 0, w3, 0,
162 0, 0, w1, 0, 0, w2, w1, w2, 2*w3
163 };
164
165 CvMat _dm1dw = cvMat( 3, 9, CV_64FC1, dm1dw );
166 CvMat _dm1dm2_part;
167
168 cvGetSubRect( &_dm1dm2, &_dm1dm2_part, cvRect(0,12,3,9) );
169 cvTranspose( &_dm1dw, &_dm1dm2_part );
170
171 memset( dRdm1, 0, sizeof(dRdm1) );
172 dRdm1[0*21] = dRdm1[4*21] = dRdm1[8*21] = 1;
173
174 cvGetCol( &_dRdm1, &_dRdm1_part, 1 );
175 cvTranspose( &_omegav, &_omegav );
176 cvReshape( &_omegav, &_omegav, 1, 1 );
177 cvTranspose( &_omegav, &_dRdm1_part );
178
179 cvGetCol( &_dRdm1, &_dRdm1_part, 2 );
180 cvReshape( &matA, &matA, 1, 1 );
181 cvTranspose( &matA, &_dRdm1_part );
182
183 cvGetSubRect( &_dRdm1, &_dRdm1_part, cvRect(3,0,9,9) );
184 cvSetIdentity( &_dRdm1_part, cvScalarAll(beta) );
185
186 cvGetSubRect( &_dRdm1, &_dRdm1_part, cvRect(12,0,9,9) );
187 cvSetIdentity( &_dRdm1_part, cvScalarAll(gamma) );
188
189 matJ = cvMat( 9, 3, CV_64FC1, J );
190
191 cvMatMul( &_dRdm1, &_dm1dm2, &_t0 );
192 cvMatMul( &_t0, &_dm2dm3, &_t1 );
193 cvMatMul( &_t1, &_dm3din, &matJ );
194
195 _t0 = cvMat( 3, 9, CV_64FC1, t0 );
196 cvTranspose( &matJ, &_t0 );
197
198 for( i = 0; i < 3; i++ )
199 {
200 _t1 = cvMat( 3, 3, CV_64FC1, t0 + i*9 );
201 cvTranspose( &_t1, &_t1 );
202 }
203
204 cvTranspose( &_t0, &matJ );
205 }
206 }
207 }
208 else if( src->cols == 3 && src->rows == 3 )
209 {
210 double R[9], A[9], I[9], r[3], W[3], U[9], V[9];
211 double tr, alpha, beta, theta;
212 CvMat matR = cvMat( 3, 3, CV_64F, R );
213 CvMat matA = cvMat( 3, 3, CV_64F, A );
214 CvMat matI = cvMat( 3, 3, CV_64F, I );
215 CvMat _r = cvMat( dst->rows, dst->cols, CV_MAKETYPE(CV_64F, CV_MAT_CN(dst->type)), r );
216 CvMat matW = cvMat( 1, 3, CV_64F, W );
217 CvMat matU = cvMat( 3, 3, CV_64F, U );
218 CvMat matV = cvMat( 3, 3, CV_64F, V );
219
220 cvConvert( src, &matR );
221 cvSVD( &matR, &matW, &matU, &matV, CV_SVD_MODIFY_A + CV_SVD_U_T + CV_SVD_V_T );
222 cvGEMM( &matU, &matV, 1, 0, 0, &matR, CV_GEMM_A_T );
223
224 cvMulTransposed( &matR, &matA, 0 );
225 cvSetIdentity( &matI );
226
227 if( cvNorm( &matA, &matI, CV_C ) > 1e-3 ||
228 fabs( cvDet(&matR) - 1 ) > 1e-3 )
229 return 0;
230
231 tr = (cvTrace(&matR).val[0] - 1.)*0.5;
232 tr = tr > 1. ? 1. : tr < -1. ? -1. : tr;
233 theta = acos(tr);
234 alpha = cos(theta);
235 beta = sin(theta);
236
237 if( beta >= 1e-5 )
238 {
239 double dtheta_dtr = -1./sqrt(1 - tr*tr);
240 double vth = 1/(2*beta);
241
242 // om1 = [R(3,2) - R(2,3), R(1,3) - R(3,1), R(2,1) - R(1,2)]'
243 double om1[] = { R[7] - R[5], R[2] - R[6], R[3] - R[1] };
244 // om = om1*vth
245 // r = om*theta
246 double d3 = vth*theta;
247
248 r[0] = om1[0]*d3; r[1] = om1[1]*d3; r[2] = om1[2]*d3;
249 cvConvert( &_r, dst );
250
251 if( jacobian )
252 {
253 // var1 = [vth;theta]
254 // var = [om1;var1] = [om1;vth;theta]
255 double dvth_dtheta = -vth*alpha/beta;
256 double d1 = 0.5*dvth_dtheta*dtheta_dtr;
257 double d2 = 0.5*dtheta_dtr;
258 // dvar1/dR = dvar1/dtheta*dtheta/dR = [dvth/dtheta; 1] * dtheta/dtr * dtr/dR
259 double dvardR[5*9] =
260 {
261 0, 0, 0, 0, 0, 1, 0, -1, 0,
262 0, 0, -1, 0, 0, 0, 1, 0, 0,
263 0, 1, 0, -1, 0, 0, 0, 0, 0,
264 d1, 0, 0, 0, d1, 0, 0, 0, d1,
265 d2, 0, 0, 0, d2, 0, 0, 0, d2
266 };
267 // var2 = [om;theta]
268 double dvar2dvar[] =
269 {
270 vth, 0, 0, om1[0], 0,
271 0, vth, 0, om1[1], 0,
272 0, 0, vth, om1[2], 0,
273 0, 0, 0, 0, 1
274 };
275 double domegadvar2[] =
276 {
277 theta, 0, 0, om1[0]*vth,
278 0, theta, 0, om1[1]*vth,
279 0, 0, theta, om1[2]*vth
280 };
281
282 CvMat _dvardR = cvMat( 5, 9, CV_64FC1, dvardR );
283 CvMat _dvar2dvar = cvMat( 4, 5, CV_64FC1, dvar2dvar );
284 CvMat _domegadvar2 = cvMat( 3, 4, CV_64FC1, domegadvar2 );
285 double t0[3*5];
286 CvMat _t0 = cvMat( 3, 5, CV_64FC1, t0 );
287
288 cvMatMul( &_domegadvar2, &_dvar2dvar, &_t0 );
289 cvMatMul( &_t0, &_dvardR, &matJ );
290 }
291 }
292 else if( tr > 0 )
293 {
294 cvZero( dst );
295 if( jacobian )
296 {
297 memset( J, 0, sizeof(J) );
298 J[5] = J[15] = J[19] = 0.5;
299 J[7] = J[11] = J[21] = -0.5;
300 }
301 }
302 else
303 {
304 r[0] = theta*sqrt((R[0] + 1)*0.5);
305 r[1] = theta*sqrt((R[4] + 1)*0.5)*(R[1] >= 0 ? 1 : -1);
306 r[2] = theta*sqrt((R[8] + 1)*0.5)*(R[2] >= 0 ? 1 : -1);
307 cvConvert( &_r, dst );
308
309 if( jacobian )
310 memset( J, 0, sizeof(J) );
311 }
312
313 if( jacobian )
314 {
315 for( i = 0; i < 3; i++ )
316 {
317 CvMat t = cvMat( 3, 3, CV_64F, J + i*9 );
318 cvTranspose( &t, &t );
319 }
320 }
321 }
322 else
323 {
324 assert(0);
325 return 0;
326 }
327
328 if( jacobian )
329 {
330 if( depth == CV_32F )
331 {
332 if( jacobian->rows == matJ.rows )
333 cvConvert( &matJ, jacobian );
334 else
335 {
336 _Jf = cvMat( matJ.rows, matJ.cols, CV_32FC1, Jf );
337 cvConvert( &matJ, &_Jf );
338 cvTranspose( &_Jf, jacobian );
339 }
340 }
341 else if( jacobian->rows == matJ.rows )
342 cvCopy( &matJ, jacobian );
343 else
344 cvTranspose( &matJ, jacobian );
345 }
346
347 return 1;
348 }
349
350
Rodrigues(const Mat & src,Mat & dst,Mat * jac)351 /*extern*/ void Rodrigues(const Mat& src, Mat& dst, Mat* jac)
352 {
353 if(src.rows == 1 || src.cols == 1)
354 dst.create(3, 3, src.depth());
355 else
356 dst.create(3, 1, src.depth());
357 CvMat _src = cvMat(src), _dst = cvMat(dst), _jac;
358 if( jac )
359 _jac = cvMat(*jac);
360 cvTsRodrigues(&_src, &_dst, jac ? &_jac : 0);
361 }
362
363 } // namespace
364 namespace opencv_test {
365
test_convertHomogeneous(const Mat & _src,Mat & _dst)366 static void test_convertHomogeneous( const Mat& _src, Mat& _dst )
367 {
368 Mat src = _src, dst = _dst;
369 int i, count, sdims, ddims;
370 int sstep1, sstep2, dstep1, dstep2;
371
372 if( src.depth() != CV_64F )
373 _src.convertTo(src, CV_64F);
374
375 if( dst.depth() != CV_64F )
376 dst.create(dst.size(), CV_MAKETYPE(CV_64F, _dst.channels()));
377
378 if( src.rows > src.cols )
379 {
380 count = src.rows;
381 sdims = src.channels()*src.cols;
382 sstep1 = (int)(src.step/sizeof(double));
383 sstep2 = 1;
384 }
385 else
386 {
387 count = src.cols;
388 sdims = src.channels()*src.rows;
389 if( src.rows == 1 )
390 {
391 sstep1 = sdims;
392 sstep2 = 1;
393 }
394 else
395 {
396 sstep1 = 1;
397 sstep2 = (int)(src.step/sizeof(double));
398 }
399 }
400
401 if( dst.rows > dst.cols )
402 {
403 CV_Assert( count == dst.rows );
404 ddims = dst.channels()*dst.cols;
405 dstep1 = (int)(dst.step/sizeof(double));
406 dstep2 = 1;
407 }
408 else
409 {
410 assert( count == dst.cols );
411 ddims = dst.channels()*dst.rows;
412 if( dst.rows == 1 )
413 {
414 dstep1 = ddims;
415 dstep2 = 1;
416 }
417 else
418 {
419 dstep1 = 1;
420 dstep2 = (int)(dst.step/sizeof(double));
421 }
422 }
423
424 double* s = src.ptr<double>();
425 double* d = dst.ptr<double>();
426
427 if( sdims <= ddims )
428 {
429 int wstep = dstep2*(ddims - 1);
430
431 for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
432 {
433 double x = s[0];
434 double y = s[sstep2];
435
436 d[wstep] = 1;
437 d[0] = x;
438 d[dstep2] = y;
439
440 if( sdims >= 3 )
441 {
442 d[dstep2*2] = s[sstep2*2];
443 if( sdims == 4 )
444 d[dstep2*3] = s[sstep2*3];
445 }
446 }
447 }
448 else
449 {
450 int wstep = sstep2*(sdims - 1);
451
452 for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
453 {
454 double w = s[wstep];
455 double x = s[0];
456 double y = s[sstep2];
457
458 w = w ? 1./w : 1;
459
460 d[0] = x*w;
461 d[dstep2] = y*w;
462
463 if( ddims == 3 )
464 d[dstep2*2] = s[sstep2*2]*w;
465 }
466 }
467
468 if( dst.data != _dst.data )
469 dst.convertTo(_dst, _dst.depth());
470 }
471
472 namespace {
473
474 void
test_projectPoints(const Mat & _3d,const Mat & Rt,const Mat & A,Mat & _2d,RNG * rng,double sigma)475 test_projectPoints( const Mat& _3d, const Mat& Rt, const Mat& A, Mat& _2d, RNG* rng, double sigma )
476 {
477 CV_Assert( _3d.isContinuous() );
478
479 double p[12];
480 Mat P( 3, 4, CV_64F, p );
481 gemm(A, Rt, 1, Mat(), 0, P);
482
483 int i, count = _3d.cols;
484
485 Mat noise;
486 if( rng )
487 {
488 if( sigma == 0 )
489 rng = 0;
490 else
491 {
492 noise.create( 1, _3d.cols, CV_64FC2 );
493 rng->fill(noise, RNG::NORMAL, Scalar::all(0), Scalar::all(sigma) );
494 }
495 }
496
497 Mat temp( 1, count, CV_64FC3 );
498
499 for( i = 0; i < count; i++ )
500 {
501 const double* M = _3d.ptr<double>() + i*3;
502 double* m = temp.ptr<double>() + i*3;
503 double X = M[0], Y = M[1], Z = M[2];
504 double u = p[0]*X + p[1]*Y + p[2]*Z + p[3];
505 double v = p[4]*X + p[5]*Y + p[6]*Z + p[7];
506 double s = p[8]*X + p[9]*Y + p[10]*Z + p[11];
507
508 if( !noise.empty() )
509 {
510 u += noise.at<Point2d>(i).x*s;
511 v += noise.at<Point2d>(i).y*s;
512 }
513
514 m[0] = u;
515 m[1] = v;
516 m[2] = s;
517 }
518
519 test_convertHomogeneous( temp, _2d );
520 }
521
522
523 /********************************** Rodrigues transform ********************************/
524
525 class CV_RodriguesTest : public cvtest::ArrayTest
526 {
527 public:
528 CV_RodriguesTest();
529
530 protected:
531 int read_params( const cv::FileStorage& fs );
532 void fill_array( int test_case_idx, int i, int j, Mat& arr );
533 int prepare_test_case( int test_case_idx );
534 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
535 double get_success_error_level( int test_case_idx, int i, int j );
536 void run_func();
537 void prepare_to_validation( int );
538
539 bool calc_jacobians;
540 bool test_cpp;
541 };
542
543
CV_RodriguesTest()544 CV_RodriguesTest::CV_RodriguesTest()
545 {
546 test_array[INPUT].push_back(NULL); // rotation vector
547 test_array[OUTPUT].push_back(NULL); // rotation matrix
548 test_array[OUTPUT].push_back(NULL); // jacobian (J)
549 test_array[OUTPUT].push_back(NULL); // rotation vector (backward transform result)
550 test_array[OUTPUT].push_back(NULL); // inverse transform jacobian (J1)
551 test_array[OUTPUT].push_back(NULL); // J*J1 (or J1*J) == I(3x3)
552 test_array[REF_OUTPUT].push_back(NULL);
553 test_array[REF_OUTPUT].push_back(NULL);
554 test_array[REF_OUTPUT].push_back(NULL);
555 test_array[REF_OUTPUT].push_back(NULL);
556 test_array[REF_OUTPUT].push_back(NULL);
557
558 element_wise_relative_error = false;
559 calc_jacobians = false;
560
561 test_cpp = false;
562 }
563
564
read_params(const cv::FileStorage & fs)565 int CV_RodriguesTest::read_params( const cv::FileStorage& fs )
566 {
567 int code = cvtest::ArrayTest::read_params( fs );
568 return code;
569 }
570
571
get_test_array_types_and_sizes(int,vector<vector<Size>> & sizes,vector<vector<int>> & types)572 void CV_RodriguesTest::get_test_array_types_and_sizes(
573 int /*test_case_idx*/, vector<vector<Size> >& sizes, vector<vector<int> >& types )
574 {
575 RNG& rng = ts->get_rng();
576 int depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
577 int i, code;
578
579 code = cvtest::randInt(rng) % 3;
580 types[INPUT][0] = CV_MAKETYPE(depth, 1);
581
582 if( code == 0 )
583 {
584 sizes[INPUT][0] = cvSize(1,1);
585 types[INPUT][0] = CV_MAKETYPE(depth, 3);
586 }
587 else if( code == 1 )
588 sizes[INPUT][0] = cvSize(3,1);
589 else
590 sizes[INPUT][0] = cvSize(1,3);
591
592 sizes[OUTPUT][0] = cvSize(3, 3);
593 types[OUTPUT][0] = CV_MAKETYPE(depth, 1);
594
595 types[OUTPUT][1] = CV_MAKETYPE(depth, 1);
596
597 if( cvtest::randInt(rng) % 2 )
598 sizes[OUTPUT][1] = cvSize(3,9);
599 else
600 sizes[OUTPUT][1] = cvSize(9,3);
601
602 types[OUTPUT][2] = types[INPUT][0];
603 sizes[OUTPUT][2] = sizes[INPUT][0];
604
605 types[OUTPUT][3] = types[OUTPUT][1];
606 sizes[OUTPUT][3] = cvSize(sizes[OUTPUT][1].height, sizes[OUTPUT][1].width);
607
608 types[OUTPUT][4] = types[OUTPUT][1];
609 sizes[OUTPUT][4] = cvSize(3,3);
610
611 calc_jacobians = cvtest::randInt(rng) % 3 != 0;
612 if( !calc_jacobians )
613 sizes[OUTPUT][1] = sizes[OUTPUT][3] = sizes[OUTPUT][4] = cvSize(0,0);
614
615 for( i = 0; i < 5; i++ )
616 {
617 types[REF_OUTPUT][i] = types[OUTPUT][i];
618 sizes[REF_OUTPUT][i] = sizes[OUTPUT][i];
619 }
620 test_cpp = (cvtest::randInt(rng) & 256) == 0;
621 }
622
623
get_success_error_level(int,int,int j)624 double CV_RodriguesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )
625 {
626 return j == 4 ? 1e-2 : 1e-2;
627 }
628
629
fill_array(int test_case_idx,int i,int j,Mat & arr)630 void CV_RodriguesTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
631 {
632 if( i == INPUT && j == 0 )
633 {
634 double r[3], theta0, theta1, f;
635 Mat _r( arr.rows, arr.cols, CV_MAKETYPE(CV_64F,arr.channels()), r );
636 RNG& rng = ts->get_rng();
637
638 r[0] = cvtest::randReal(rng)*CV_PI*2;
639 r[1] = cvtest::randReal(rng)*CV_PI*2;
640 r[2] = cvtest::randReal(rng)*CV_PI*2;
641
642 theta0 = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);
643 theta1 = fmod(theta0, CV_PI*2);
644
645 if( theta1 > CV_PI )
646 theta1 = -(CV_PI*2 - theta1);
647
648 f = theta1/(theta0 ? theta0 : 1);
649 r[0] *= f;
650 r[1] *= f;
651 r[2] *= f;
652
653 cvtest::convert( _r, arr, arr.type() );
654 }
655 else
656 cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
657 }
658
659
prepare_test_case(int test_case_idx)660 int CV_RodriguesTest::prepare_test_case( int test_case_idx )
661 {
662 int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
663 return code;
664 }
665
666
run_func()667 void CV_RodriguesTest::run_func()
668 {
669 cv::Mat v = test_mat[INPUT][0], M = test_mat[OUTPUT][0], v2 = test_mat[OUTPUT][2];
670 cv::Mat M0 = M, v2_0 = v2;
671 if( !calc_jacobians )
672 {
673 cv::Rodrigues(v, M);
674 cv::Rodrigues(M, v2);
675 }
676 else
677 {
678 cv::Mat J1 = test_mat[OUTPUT][1], J2 = test_mat[OUTPUT][3];
679 cv::Mat J1_0 = J1, J2_0 = J2;
680 cv::Rodrigues(v, M, J1);
681 cv::Rodrigues(M, v2, J2);
682 if( J1.data != J1_0.data )
683 {
684 if( J1.size() != J1_0.size() )
685 J1 = J1.t();
686 J1.convertTo(J1_0, J1_0.type());
687 }
688 if( J2.data != J2_0.data )
689 {
690 if( J2.size() != J2_0.size() )
691 J2 = J2.t();
692 J2.convertTo(J2_0, J2_0.type());
693 }
694 }
695 if( M.data != M0.data )
696 M.reshape(M0.channels(), M0.rows).convertTo(M0, M0.type());
697 if( v2.data != v2_0.data )
698 v2.reshape(v2_0.channels(), v2_0.rows).convertTo(v2_0, v2_0.type());
699 }
700
701
prepare_to_validation(int)702 void CV_RodriguesTest::prepare_to_validation( int /*test_case_idx*/ )
703 {
704 const Mat& vec = test_mat[INPUT][0];
705 Mat& m = test_mat[REF_OUTPUT][0];
706 Mat& vec2 = test_mat[REF_OUTPUT][2];
707 Mat* v2m_jac = 0, *m2v_jac = 0;
708 double theta0, theta1;
709
710 if( calc_jacobians )
711 {
712 v2m_jac = &test_mat[REF_OUTPUT][1];
713 m2v_jac = &test_mat[REF_OUTPUT][3];
714 }
715
716
717 cvtest::Rodrigues( vec, m, v2m_jac );
718 cvtest::Rodrigues( m, vec2, m2v_jac );
719 cvtest::copy( vec, vec2 );
720
721 theta0 = cvtest::norm( vec2, CV_L2 );
722 theta1 = fmod( theta0, CV_PI*2 );
723
724 if( theta1 > CV_PI )
725 theta1 = -(CV_PI*2 - theta1);
726 vec2 *= theta1/(theta0 ? theta0 : 1);
727
728 if( calc_jacobians )
729 {
730 //cvInvert( v2m_jac, m2v_jac, CV_SVD );
731 double nrm = cvtest::norm(test_mat[REF_OUTPUT][3], CV_C);
732 if( FLT_EPSILON < nrm && nrm < 1000 )
733 {
734 gemm( test_mat[OUTPUT][1], test_mat[OUTPUT][3],
735 1, Mat(), 0, test_mat[OUTPUT][4],
736 v2m_jac->rows == 3 ? 0 : CV_GEMM_A_T + CV_GEMM_B_T );
737 }
738 else
739 {
740 setIdentity(test_mat[OUTPUT][4], Scalar::all(1.));
741 cvtest::copy( test_mat[REF_OUTPUT][2], test_mat[OUTPUT][2] );
742 }
743 setIdentity(test_mat[REF_OUTPUT][4], Scalar::all(1.));
744 }
745 }
746
747
748 /********************************** fundamental matrix *********************************/
749
750 class CV_FundamentalMatTest : public cvtest::ArrayTest
751 {
752 public:
753 CV_FundamentalMatTest();
754
755 protected:
756 int read_params( const cv::FileStorage& fs );
757 void fill_array( int test_case_idx, int i, int j, Mat& arr );
758 int prepare_test_case( int test_case_idx );
759 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
760 double get_success_error_level( int test_case_idx, int i, int j );
761 void run_func();
762 void prepare_to_validation( int );
763
764 int method;
765 int img_size;
766 int cube_size;
767 int dims;
768 int f_result;
769 double min_f, max_f;
770 double sigma;
771 bool test_cpp;
772 };
773
774
CV_FundamentalMatTest()775 CV_FundamentalMatTest::CV_FundamentalMatTest()
776 {
777 // input arrays:
778 // 0, 1 - arrays of 2d points that are passed to %func%.
779 // Can have different data type, layout, be stored in homogeneous coordinates or not.
780 // 2 - array of 3d points that are projected to both view planes
781 // 3 - [R|t] matrix for the second view plane (for the first one it is [I|0]
782 // 4, 5 - intrinsic matrices
783 test_array[INPUT].push_back(NULL);
784 test_array[INPUT].push_back(NULL);
785 test_array[INPUT].push_back(NULL);
786 test_array[INPUT].push_back(NULL);
787 test_array[INPUT].push_back(NULL);
788 test_array[INPUT].push_back(NULL);
789 test_array[TEMP].push_back(NULL);
790 test_array[TEMP].push_back(NULL);
791 test_array[OUTPUT].push_back(NULL);
792 test_array[OUTPUT].push_back(NULL);
793 test_array[REF_OUTPUT].push_back(NULL);
794 test_array[REF_OUTPUT].push_back(NULL);
795
796 element_wise_relative_error = false;
797
798 method = 0;
799 img_size = 10;
800 cube_size = 10;
801 dims = 0;
802 min_f = 1;
803 max_f = 3;
804 sigma = 0;//0.1;
805 f_result = 0;
806
807 test_cpp = false;
808 }
809
810
read_params(const cv::FileStorage & fs)811 int CV_FundamentalMatTest::read_params( const cv::FileStorage& fs )
812 {
813 int code = cvtest::ArrayTest::read_params( fs );
814 return code;
815 }
816
817
get_test_array_types_and_sizes(int,vector<vector<Size>> & sizes,vector<vector<int>> & types)818 void CV_FundamentalMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
819 vector<vector<Size> >& sizes, vector<vector<int> >& types )
820 {
821 RNG& rng = ts->get_rng();
822 int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
823 double pt_count_exp = cvtest::randReal(rng)*6 + 1;
824 int pt_count = cvRound(exp(pt_count_exp));
825
826 dims = cvtest::randInt(rng) % 2 + 2;
827 method = 1 << (cvtest::randInt(rng) % 4);
828
829 if( method == CV_FM_7POINT )
830 pt_count = 7;
831 else
832 {
833 pt_count = MAX( pt_count, 8 + (method == CV_FM_8POINT) );
834 if( pt_count >= 8 && cvtest::randInt(rng) % 2 )
835 method |= CV_FM_8POINT;
836 }
837
838 types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
839
840 sizes[INPUT][0] = cvSize(dims, pt_count);
841 if( cvtest::randInt(rng) % 2 )
842 {
843 types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
844 if( cvtest::randInt(rng) % 2 )
845 sizes[INPUT][0] = cvSize(pt_count, 1);
846 else
847 sizes[INPUT][0] = cvSize(1, pt_count);
848 }
849
850 sizes[INPUT][1] = sizes[INPUT][0];
851 types[INPUT][1] = types[INPUT][0];
852
853 sizes[INPUT][2] = cvSize(pt_count, 1 );
854 types[INPUT][2] = CV_64FC3;
855
856 sizes[INPUT][3] = cvSize(4,3);
857 types[INPUT][3] = CV_64FC1;
858
859 sizes[INPUT][4] = sizes[INPUT][5] = cvSize(3,3);
860 types[INPUT][4] = types[INPUT][5] = CV_MAKETYPE(CV_64F, 1);
861
862 sizes[TEMP][0] = cvSize(3,3);
863 types[TEMP][0] = CV_64FC1;
864 sizes[TEMP][1] = cvSize(pt_count,1);
865 types[TEMP][1] = CV_8UC1;
866
867 sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,1);
868 types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
869 sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(pt_count,1);
870 types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
871
872 test_cpp = (cvtest::randInt(rng) & 256) == 0;
873 }
874
875
get_success_error_level(int,int,int)876 double CV_FundamentalMatTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
877 {
878 return 1e-2;
879 }
880
881
fill_array(int test_case_idx,int i,int j,Mat & arr)882 void CV_FundamentalMatTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
883 {
884 double t[12]={0};
885 RNG& rng = ts->get_rng();
886
887 if( i != INPUT )
888 {
889 cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
890 return;
891 }
892
893 switch( j )
894 {
895 case 0:
896 case 1:
897 return; // fill them later in prepare_test_case
898 case 2:
899 {
900 double* p = arr.ptr<double>();
901 for( i = 0; i < arr.cols*3; i += 3 )
902 {
903 p[i] = cvtest::randReal(rng)*cube_size;
904 p[i+1] = cvtest::randReal(rng)*cube_size;
905 p[i+2] = cvtest::randReal(rng)*cube_size + cube_size;
906 }
907 }
908 break;
909 case 3:
910 {
911 double r[3];
912 Mat rot_vec( 3, 1, CV_64F, r );
913 Mat rot_mat( 3, 3, CV_64F, t, 4*sizeof(t[0]) );
914 r[0] = cvtest::randReal(rng)*CV_PI*2;
915 r[1] = cvtest::randReal(rng)*CV_PI*2;
916 r[2] = cvtest::randReal(rng)*CV_PI*2;
917
918 cvtest::Rodrigues( rot_vec, rot_mat );
919 t[3] = cvtest::randReal(rng)*cube_size;
920 t[7] = cvtest::randReal(rng)*cube_size;
921 t[11] = cvtest::randReal(rng)*cube_size;
922 Mat( 3, 4, CV_64F, t ).convertTo(arr, arr.type());
923 }
924 break;
925 case 4:
926 case 5:
927 t[0] = t[4] = cvtest::randReal(rng)*(max_f - min_f) + min_f;
928 t[2] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[0];
929 t[5] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[4];
930 t[8] = 1.;
931 Mat( 3, 3, CV_64F, t ).convertTo( arr, arr.type() );
932 break;
933 }
934 }
935
936
prepare_test_case(int test_case_idx)937 int CV_FundamentalMatTest::prepare_test_case( int test_case_idx )
938 {
939 int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
940 if( code > 0 )
941 {
942 const Mat& _3d = test_mat[INPUT][2];
943 RNG& rng = ts->get_rng();
944 double Idata[] = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 };
945 Mat I( 3, 4, CV_64F, Idata );
946 int k;
947
948 for( k = 0; k < 2; k++ )
949 {
950 const Mat& Rt = k == 0 ? I : test_mat[INPUT][3];
951 const Mat& A = test_mat[INPUT][k == 0 ? 4 : 5];
952 Mat& _2d = test_mat[INPUT][k];
953
954 test_projectPoints( _3d, Rt, A, _2d, &rng, sigma );
955 }
956 }
957
958 return code;
959 }
960
run_func()961 void CV_FundamentalMatTest::run_func()
962 {
963 // cvFindFundamentalMat calls cv::findFundamentalMat
964 cv::Mat _input0 = test_mat[INPUT][0], _input1 = test_mat[INPUT][1];
965 cv::Mat& F = test_mat[TEMP][0], &mask = test_mat[TEMP][1];
966 F = cv::findFundamentalMat( _input0, _input1, method, MAX(sigma*3, 0.01), 0, mask );
967 f_result = !F.empty();
968 }
969
prepare_to_validation(int test_case_idx)970 void CV_FundamentalMatTest::prepare_to_validation( int test_case_idx )
971 {
972 const Mat& Rt = test_mat[INPUT][3];
973 const Mat& A1 = test_mat[INPUT][4];
974 const Mat& A2 = test_mat[INPUT][5];
975 double f0[9], f[9];
976 Mat F0(3, 3, CV_64FC1, f0), F(3, 3, CV_64F, f);
977
978 Mat invA1, invA2, R=Rt.colRange(0, 3), T;
979
980 cv::invert(A1, invA1, CV_SVD);
981 cv::invert(A2, invA2, CV_SVD);
982
983 double tx = Rt.at<double>(0, 3);
984 double ty = Rt.at<double>(1, 3);
985 double tz = Rt.at<double>(2, 3);
986
987 double _t_x[] = { 0, -tz, ty, tz, 0, -tx, -ty, tx, 0 };
988
989 // F = (A2^-T)*[t]_x*R*(A1^-1)
990 cv::gemm( invA2, Mat( 3, 3, CV_64F, _t_x ), 1, Mat(), 0, T, CV_GEMM_A_T );
991 cv::gemm( R, invA1, 1, Mat(), 0, invA2 );
992 cv::gemm( T, invA2, 1, Mat(), 0, F0 );
993 F0 *= 1./f0[8];
994
995 uchar* status = test_mat[TEMP][1].ptr();
996 double err_level = get_success_error_level( test_case_idx, OUTPUT, 1 );
997 uchar* mtfm1 = test_mat[REF_OUTPUT][1].ptr();
998 uchar* mtfm2 = test_mat[OUTPUT][1].ptr();
999 double* f_prop1 = test_mat[REF_OUTPUT][0].ptr<double>();
1000 double* f_prop2 = test_mat[OUTPUT][0].ptr<double>();
1001
1002 int i, pt_count = test_mat[INPUT][2].cols;
1003 Mat p1( 1, pt_count, CV_64FC2 );
1004 Mat p2( 1, pt_count, CV_64FC2 );
1005
1006 test_convertHomogeneous( test_mat[INPUT][0], p1 );
1007 test_convertHomogeneous( test_mat[INPUT][1], p2 );
1008
1009 Mat Fsrc = test_mat[TEMP][0];
1010 if( Fsrc.rows > 3 )
1011 Fsrc = Fsrc.rowRange(0, 3);
1012
1013 cvtest::convert(Fsrc, F, F.type());
1014
1015 if( method <= CV_FM_8POINT )
1016 memset( status, 1, pt_count );
1017
1018 for( i = 0; i < pt_count; i++ )
1019 {
1020 double x1 = p1.at<Point2d>(i).x;
1021 double y1 = p1.at<Point2d>(i).y;
1022 double x2 = p2.at<Point2d>(i).x;
1023 double y2 = p2.at<Point2d>(i).y;
1024 double n1 = 1./sqrt(x1*x1 + y1*y1 + 1);
1025 double n2 = 1./sqrt(x2*x2 + y2*y2 + 1);
1026 double t0 = fabs(f0[0]*x2*x1 + f0[1]*x2*y1 + f0[2]*x2 +
1027 f0[3]*y2*x1 + f0[4]*y2*y1 + f0[5]*y2 +
1028 f0[6]*x1 + f0[7]*y1 + f0[8])*n1*n2;
1029 double t = fabs(f[0]*x2*x1 + f[1]*x2*y1 + f[2]*x2 +
1030 f[3]*y2*x1 + f[4]*y2*y1 + f[5]*y2 +
1031 f[6]*x1 + f[7]*y1 + f[8])*n1*n2;
1032 mtfm1[i] = 1;
1033 mtfm2[i] = !status[i] || t0 > err_level || t < err_level;
1034 }
1035
1036 f_prop1[0] = 1;
1037 f_prop1[1] = 1;
1038 f_prop1[2] = 0;
1039
1040 f_prop2[0] = f_result != 0;
1041 f_prop2[1] = f[8];
1042 f_prop2[2] = cv::determinant( F );
1043 }
1044 /******************************* find essential matrix ***********************************/
1045 class CV_EssentialMatTest : public cvtest::ArrayTest
1046 {
1047 public:
1048 CV_EssentialMatTest();
1049
1050 protected:
1051 int read_params( const cv::FileStorage& fs );
1052 void fill_array( int test_case_idx, int i, int j, Mat& arr );
1053 int prepare_test_case( int test_case_idx );
1054 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
1055 double get_success_error_level( int test_case_idx, int i, int j );
1056 void run_func();
1057 void prepare_to_validation( int );
1058
1059 #if 0
1060 double sampson_error(const double* f, double x1, double y1, double x2, double y2);
1061 #endif
1062
1063 int method;
1064 int img_size;
1065 int cube_size;
1066 int dims;
1067 double min_f, max_f;
1068 double sigma;
1069 };
1070
1071
CV_EssentialMatTest()1072 CV_EssentialMatTest::CV_EssentialMatTest()
1073 {
1074 // input arrays:
1075 // 0, 1 - arrays of 2d points that are passed to %func%.
1076 // Can have different data type, layout, be stored in homogeneous coordinates or not.
1077 // 2 - array of 3d points that are projected to both view planes
1078 // 3 - [R|t] matrix for the second view plane (for the first one it is [I|0]
1079 // 4 - intrinsic matrix for both camera
1080 test_array[INPUT].push_back(NULL);
1081 test_array[INPUT].push_back(NULL);
1082 test_array[INPUT].push_back(NULL);
1083 test_array[INPUT].push_back(NULL);
1084 test_array[INPUT].push_back(NULL);
1085 test_array[TEMP].push_back(NULL);
1086 test_array[TEMP].push_back(NULL);
1087 test_array[TEMP].push_back(NULL);
1088 test_array[TEMP].push_back(NULL);
1089 test_array[TEMP].push_back(NULL);
1090 test_array[OUTPUT].push_back(NULL); // Essential Matrix singularity
1091 test_array[OUTPUT].push_back(NULL); // Inliers mask
1092 test_array[OUTPUT].push_back(NULL); // Translation error
1093 test_array[OUTPUT].push_back(NULL); // Positive depth count
1094 test_array[REF_OUTPUT].push_back(NULL);
1095 test_array[REF_OUTPUT].push_back(NULL);
1096 test_array[REF_OUTPUT].push_back(NULL);
1097 test_array[REF_OUTPUT].push_back(NULL);
1098
1099 element_wise_relative_error = false;
1100
1101 method = 0;
1102 img_size = 10;
1103 cube_size = 10;
1104 dims = 0;
1105 min_f = 1;
1106 max_f = 3;
1107 sigma = 0;
1108 }
1109
1110
read_params(const cv::FileStorage & fs)1111 int CV_EssentialMatTest::read_params( const cv::FileStorage& fs )
1112 {
1113 int code = cvtest::ArrayTest::read_params( fs );
1114 return code;
1115 }
1116
1117
get_test_array_types_and_sizes(int,vector<vector<Size>> & sizes,vector<vector<int>> & types)1118 void CV_EssentialMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
1119 vector<vector<Size> >& sizes, vector<vector<int> >& types )
1120 {
1121 RNG& rng = ts->get_rng();
1122 int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
1123 double pt_count_exp = cvtest::randReal(rng)*6 + 1;
1124 int pt_count = MAX(5, cvRound(exp(pt_count_exp)));
1125
1126 dims = cvtest::randInt(rng) % 2 + 2;
1127 dims = 2;
1128 method = CV_LMEDS << (cvtest::randInt(rng) % 2);
1129
1130 types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
1131
1132 sizes[INPUT][0] = cvSize(dims, pt_count);
1133 if( cvtest::randInt(rng) % 2 )
1134 {
1135 types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
1136 if( cvtest::randInt(rng) % 2 )
1137 sizes[INPUT][0] = cvSize(pt_count, 1);
1138 else
1139 sizes[INPUT][0] = cvSize(1, pt_count);
1140 }
1141
1142 sizes[INPUT][1] = sizes[INPUT][0];
1143 types[INPUT][1] = types[INPUT][0];
1144
1145 sizes[INPUT][2] = cvSize(pt_count, 1 );
1146 types[INPUT][2] = CV_64FC3;
1147
1148 sizes[INPUT][3] = cvSize(4,3);
1149 types[INPUT][3] = CV_64FC1;
1150
1151 sizes[INPUT][4] = cvSize(3,3);
1152 types[INPUT][4] = CV_MAKETYPE(CV_64F, 1);
1153
1154 sizes[TEMP][0] = cvSize(3,3);
1155 types[TEMP][0] = CV_64FC1;
1156 sizes[TEMP][1] = cvSize(pt_count,1);
1157 types[TEMP][1] = CV_8UC1;
1158 sizes[TEMP][2] = cvSize(3,3);
1159 types[TEMP][2] = CV_64FC1;
1160 sizes[TEMP][3] = cvSize(3, 1);
1161 types[TEMP][3] = CV_64FC1;
1162 sizes[TEMP][4] = cvSize(pt_count,1);
1163 types[TEMP][4] = CV_8UC1;
1164
1165 sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,1);
1166 types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
1167 sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(pt_count,1);
1168 types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
1169 sizes[OUTPUT][2] = sizes[REF_OUTPUT][2] = cvSize(1,1);
1170 types[OUTPUT][2] = types[REF_OUTPUT][2] = CV_64FC1;
1171 sizes[OUTPUT][3] = sizes[REF_OUTPUT][3] = cvSize(1,1);
1172 types[OUTPUT][3] = types[REF_OUTPUT][3] = CV_8UC1;
1173
1174 }
1175
1176
get_success_error_level(int,int,int)1177 double CV_EssentialMatTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
1178 {
1179 return 1e-2;
1180 }
1181
1182
fill_array(int test_case_idx,int i,int j,Mat & arr)1183 void CV_EssentialMatTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
1184 {
1185 double t[12]={0};
1186 RNG& rng = ts->get_rng();
1187
1188 if( i != INPUT )
1189 {
1190 cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
1191 return;
1192 }
1193
1194 switch( j )
1195 {
1196 case 0:
1197 case 1:
1198 return; // fill them later in prepare_test_case
1199 case 2:
1200 {
1201 double* p = arr.ptr<double>();
1202 for( i = 0; i < arr.cols*3; i += 3 )
1203 {
1204 p[i] = cvtest::randReal(rng)*cube_size;
1205 p[i+1] = cvtest::randReal(rng)*cube_size;
1206 p[i+2] = cvtest::randReal(rng)*cube_size + cube_size;
1207 }
1208 }
1209 break;
1210 case 3:
1211 {
1212 double r[3];
1213 Mat rot_vec( 3, 1, CV_64F, r );
1214 Mat rot_mat( 3, 3, CV_64F, t, 4*sizeof(t[0]) );
1215 r[0] = cvtest::randReal(rng)*CV_PI*2;
1216 r[1] = cvtest::randReal(rng)*CV_PI*2;
1217 r[2] = cvtest::randReal(rng)*CV_PI*2;
1218
1219 cvtest::Rodrigues( rot_vec, rot_mat );
1220 t[3] = cvtest::randReal(rng)*cube_size;
1221 t[7] = cvtest::randReal(rng)*cube_size;
1222 t[11] = cvtest::randReal(rng)*cube_size;
1223 Mat( 3, 4, CV_64F, t ).convertTo(arr, arr.type());
1224 }
1225 break;
1226 case 4:
1227 t[0] = t[4] = cvtest::randReal(rng)*(max_f - min_f) + min_f;
1228 t[2] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[0];
1229 t[5] = (img_size*0.5 + cvtest::randReal(rng)*4. - 2.)*t[4];
1230 t[8] = 1.;
1231 Mat( 3, 3, CV_64F, t ).convertTo( arr, arr.type() );
1232 break;
1233 }
1234 }
1235
1236
prepare_test_case(int test_case_idx)1237 int CV_EssentialMatTest::prepare_test_case( int test_case_idx )
1238 {
1239 int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
1240 if( code > 0 )
1241 {
1242 const Mat& _3d = test_mat[INPUT][2];
1243 RNG& rng = ts->get_rng();
1244 double Idata[] = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 };
1245 Mat I( 3, 4, CV_64F, Idata );
1246 int k;
1247
1248 for( k = 0; k < 2; k++ )
1249 {
1250 const Mat& Rt = k == 0 ? I : test_mat[INPUT][3];
1251 const Mat& A = test_mat[INPUT][4];
1252 Mat& _2d = test_mat[INPUT][k];
1253
1254 test_projectPoints( _3d, Rt, A, _2d, &rng, sigma );
1255 }
1256 }
1257
1258 return code;
1259 }
1260
1261
run_func()1262 void CV_EssentialMatTest::run_func()
1263 {
1264 Mat _input0(test_mat[INPUT][0]), _input1(test_mat[INPUT][1]);
1265 Mat K(test_mat[INPUT][4]);
1266 double focal(K.at<double>(0, 0));
1267 cv::Point2d pp(K.at<double>(0, 2), K.at<double>(1, 2));
1268
1269 RNG& rng = ts->get_rng();
1270 Mat E, mask1(test_mat[TEMP][1]);
1271 E = cv::findEssentialMat( _input0, _input1, focal, pp, method, 0.99, MAX(sigma*3, 0.0001), mask1 );
1272 if (E.rows > 3)
1273 {
1274 int count = E.rows / 3;
1275 int row = (cvtest::randInt(rng) % count) * 3;
1276 E = E.rowRange(row, row + 3) * 1.0;
1277 }
1278
1279 E.copyTo(test_mat[TEMP][0]);
1280
1281 Mat R, t, mask2;
1282 recoverPose( E, _input0, _input1, R, t, focal, pp, mask2 );
1283 R.copyTo(test_mat[TEMP][2]);
1284 t.copyTo(test_mat[TEMP][3]);
1285 mask2.copyTo(test_mat[TEMP][4]);
1286 }
1287
1288 #if 0
1289 double CV_EssentialMatTest::sampson_error(const double * f, double x1, double y1, double x2, double y2)
1290 {
1291 double Fx1[3] = {
1292 f[0] * x1 + f[1] * y1 + f[2],
1293 f[3] * x1 + f[4] * y1 + f[5],
1294 f[6] * x1 + f[7] * y1 + f[8]
1295 };
1296 double Ftx2[3] = {
1297 f[0] * x2 + f[3] * y2 + f[6],
1298 f[1] * x2 + f[4] * y2 + f[7],
1299 f[2] * x2 + f[5] * y2 + f[8]
1300 };
1301 double x2tFx1 = Fx1[0] * x2 + Fx1[1] * y2 + Fx1[2];
1302
1303 double error = x2tFx1 * x2tFx1 / (Fx1[0] * Fx1[0] + Fx1[1] * Fx1[1] + Ftx2[0] * Ftx2[0] + Ftx2[1] * Ftx2[1]);
1304 error = sqrt(error);
1305 return error;
1306 }
1307 #endif
1308
prepare_to_validation(int test_case_idx)1309 void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
1310 {
1311 const Mat& Rt0 = test_mat[INPUT][3];
1312 const Mat& A = test_mat[INPUT][4];
1313 double f0[9], f[9], e[9];
1314 Mat F0(3, 3, CV_64FC1, f0), F(3, 3, CV_64F, f);
1315 Mat E(3, 3, CV_64F, e);
1316
1317 Mat invA, R=Rt0.colRange(0, 3), T1, T2;
1318
1319 cv::invert(A, invA, CV_SVD);
1320
1321 double tx = Rt0.at<double>(0, 3);
1322 double ty = Rt0.at<double>(1, 3);
1323 double tz = Rt0.at<double>(2, 3);
1324
1325 double _t_x[] = { 0, -tz, ty, tz, 0, -tx, -ty, tx, 0 };
1326
1327 // F = (A2^-T)*[t]_x*R*(A1^-1)
1328 cv::gemm( invA, Mat( 3, 3, CV_64F, _t_x ), 1, Mat(), 0, T1, CV_GEMM_A_T );
1329 cv::gemm( R, invA, 1, Mat(), 0, T2 );
1330 cv::gemm( T1, T2, 1, Mat(), 0, F0 );
1331 F0 *= 1./f0[8];
1332
1333 uchar* status = test_mat[TEMP][1].ptr();
1334 double err_level = get_success_error_level( test_case_idx, OUTPUT, 1 );
1335 uchar* mtfm1 = test_mat[REF_OUTPUT][1].ptr();
1336 uchar* mtfm2 = test_mat[OUTPUT][1].ptr();
1337 double* e_prop1 = test_mat[REF_OUTPUT][0].ptr<double>();
1338 double* e_prop2 = test_mat[OUTPUT][0].ptr<double>();
1339 Mat E_prop2 = Mat(3, 1, CV_64F, e_prop2);
1340
1341 int i, pt_count = test_mat[INPUT][2].cols;
1342 Mat p1( 1, pt_count, CV_64FC2 );
1343 Mat p2( 1, pt_count, CV_64FC2 );
1344
1345 test_convertHomogeneous( test_mat[INPUT][0], p1 );
1346 test_convertHomogeneous( test_mat[INPUT][1], p2 );
1347
1348 cvtest::convert(test_mat[TEMP][0], E, E.type());
1349 cv::gemm( invA, E, 1, Mat(), 0, T1, CV_GEMM_A_T );
1350 cv::gemm( T1, invA, 1, Mat(), 0, F );
1351
1352 for( i = 0; i < pt_count; i++ )
1353 {
1354 double x1 = p1.at<Point2d>(i).x;
1355 double y1 = p1.at<Point2d>(i).y;
1356 double x2 = p2.at<Point2d>(i).x;
1357 double y2 = p2.at<Point2d>(i).y;
1358 // double t0 = sampson_error(f0, x1, y1, x2, y2);
1359 // double t = sampson_error(f, x1, y1, x2, y2);
1360 double n1 = 1./sqrt(x1*x1 + y1*y1 + 1);
1361 double n2 = 1./sqrt(x2*x2 + y2*y2 + 1);
1362 double t0 = fabs(f0[0]*x2*x1 + f0[1]*x2*y1 + f0[2]*x2 +
1363 f0[3]*y2*x1 + f0[4]*y2*y1 + f0[5]*y2 +
1364 f0[6]*x1 + f0[7]*y1 + f0[8])*n1*n2;
1365 double t = fabs(f[0]*x2*x1 + f[1]*x2*y1 + f[2]*x2 +
1366 f[3]*y2*x1 + f[4]*y2*y1 + f[5]*y2 +
1367 f[6]*x1 + f[7]*y1 + f[8])*n1*n2;
1368 mtfm1[i] = 1;
1369 mtfm2[i] = !status[i] || t0 > err_level || t < err_level;
1370 }
1371
1372 e_prop1[0] = sqrt(0.5);
1373 e_prop1[1] = sqrt(0.5);
1374 e_prop1[2] = 0;
1375
1376 e_prop2[0] = 0;
1377 e_prop2[1] = 0;
1378 e_prop2[2] = 0;
1379 SVD::compute(E, E_prop2);
1380
1381
1382
1383 double* pose_prop1 = test_mat[REF_OUTPUT][2].ptr<double>();
1384 double* pose_prop2 = test_mat[OUTPUT][2].ptr<double>();
1385 double terr1 = cvtest::norm(Rt0.col(3) / cvtest::norm(Rt0.col(3), NORM_L2) + test_mat[TEMP][3], NORM_L2);
1386 double terr2 = cvtest::norm(Rt0.col(3) / cvtest::norm(Rt0.col(3), NORM_L2) - test_mat[TEMP][3], NORM_L2);
1387 Mat rvec(3, 1, CV_32F);
1388 cvtest::Rodrigues(Rt0.colRange(0, 3), rvec);
1389 pose_prop1[0] = 0;
1390 // No check for CV_LMeDS on translation. Since it
1391 // involves with some degraded problem, when data is exact inliers.
1392 pose_prop2[0] = method == CV_LMEDS || pt_count == 5 ? 0 : MIN(terr1, terr2);
1393
1394
1395 // int inliers_count = countNonZero(test_mat[TEMP][1]);
1396 // int good_count = countNonZero(test_mat[TEMP][4]);
1397 test_mat[OUTPUT][3] = true; //good_count >= inliers_count / 2;
1398 test_mat[REF_OUTPUT][3] = true;
1399
1400
1401 }
1402
1403
1404 /********************************** convert homogeneous *********************************/
1405
1406 class CV_ConvertHomogeneousTest : public cvtest::ArrayTest
1407 {
1408 public:
1409 CV_ConvertHomogeneousTest();
1410
1411 protected:
1412 int read_params( const cv::FileStorage& fs );
1413 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
1414 void fill_array( int test_case_idx, int i, int j, Mat& arr );
1415 double get_success_error_level( int test_case_idx, int i, int j );
1416 void run_func();
1417 void prepare_to_validation( int );
1418
1419 int dims1, dims2;
1420 int pt_count;
1421 };
1422
1423
CV_ConvertHomogeneousTest()1424 CV_ConvertHomogeneousTest::CV_ConvertHomogeneousTest()
1425 {
1426 test_array[INPUT].push_back(NULL);
1427 test_array[OUTPUT].push_back(NULL);
1428 test_array[REF_OUTPUT].push_back(NULL);
1429 element_wise_relative_error = false;
1430
1431 pt_count = dims1 = dims2 = 0;
1432 }
1433
1434
read_params(const cv::FileStorage & fs)1435 int CV_ConvertHomogeneousTest::read_params( const cv::FileStorage& fs )
1436 {
1437 int code = cvtest::ArrayTest::read_params( fs );
1438 return code;
1439 }
1440
1441
get_test_array_types_and_sizes(int,vector<vector<Size>> & sizes,vector<vector<int>> & types)1442 void CV_ConvertHomogeneousTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
1443 vector<vector<Size> >& sizes, vector<vector<int> >& types )
1444 {
1445 RNG& rng = ts->get_rng();
1446 int pt_depth1 = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
1447 int pt_depth2 = pt_depth1;//cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
1448 double pt_count_exp = cvtest::randReal(rng)*6 + 1;
1449 int t;
1450
1451 pt_count = cvRound(exp(pt_count_exp));
1452 pt_count = MAX( pt_count, 5 );
1453
1454 dims1 = 2 + (cvtest::randInt(rng) % 2);
1455 dims2 = dims1 + 1;
1456
1457 if( cvtest::randInt(rng) % 2 )
1458 CV_SWAP( dims1, dims2, t );
1459
1460 types[INPUT][0] = CV_MAKETYPE(pt_depth1, 1);
1461
1462 sizes[INPUT][0] = cvSize(dims1, pt_count);
1463 if( cvtest::randInt(rng) % 2 )
1464 {
1465 types[INPUT][0] = CV_MAKETYPE(pt_depth1, dims1);
1466 if( cvtest::randInt(rng) % 2 )
1467 sizes[INPUT][0] = cvSize(pt_count, 1);
1468 else
1469 sizes[INPUT][0] = cvSize(1, pt_count);
1470 }
1471
1472 types[OUTPUT][0] = CV_MAKETYPE(pt_depth2, dims2);
1473 sizes[OUTPUT][0] = cvSize(1, pt_count);
1474
1475 types[REF_OUTPUT][0] = types[OUTPUT][0];
1476 sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
1477 }
1478
1479
get_success_error_level(int,int,int)1480 double CV_ConvertHomogeneousTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
1481 {
1482 return 1e-5;
1483 }
1484
1485
fill_array(int,int,int,Mat & arr)1486 void CV_ConvertHomogeneousTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, Mat& arr )
1487 {
1488 Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims1) );
1489 RNG& rng = ts->get_rng();
1490 CvScalar low = cvScalarAll(0), high = cvScalarAll(10);
1491
1492 if( dims1 > dims2 )
1493 low.val[dims1-1] = 1.;
1494
1495 cvtest::randUni( rng, temp, low, high );
1496 test_convertHomogeneous( temp, arr );
1497 }
1498
1499
run_func()1500 void CV_ConvertHomogeneousTest::run_func()
1501 {
1502 cv::Mat _input = test_mat[INPUT][0], &_output = test_mat[OUTPUT][0];
1503 if( dims1 > dims2 )
1504 cv::convertPointsFromHomogeneous(_input, _output);
1505 else
1506 cv::convertPointsToHomogeneous(_input, _output);
1507 }
1508
1509
prepare_to_validation(int)1510 void CV_ConvertHomogeneousTest::prepare_to_validation( int /*test_case_idx*/ )
1511 {
1512 test_convertHomogeneous( test_mat[INPUT][0], test_mat[REF_OUTPUT][0] );
1513 }
1514
1515
1516 /************************** compute corresponding epipolar lines ************************/
1517
1518 class CV_ComputeEpilinesTest : public cvtest::ArrayTest
1519 {
1520 public:
1521 CV_ComputeEpilinesTest();
1522
1523 protected:
1524 int read_params( const cv::FileStorage& fs );
1525 void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
1526 void fill_array( int test_case_idx, int i, int j, Mat& arr );
1527 double get_success_error_level( int test_case_idx, int i, int j );
1528 void run_func();
1529 void prepare_to_validation( int );
1530
1531 int which_image;
1532 int dims;
1533 int pt_count;
1534 };
1535
1536
CV_ComputeEpilinesTest()1537 CV_ComputeEpilinesTest::CV_ComputeEpilinesTest()
1538 {
1539 test_array[INPUT].push_back(NULL);
1540 test_array[INPUT].push_back(NULL);
1541 test_array[OUTPUT].push_back(NULL);
1542 test_array[REF_OUTPUT].push_back(NULL);
1543 element_wise_relative_error = false;
1544
1545 pt_count = dims = which_image = 0;
1546 }
1547
1548
read_params(const cv::FileStorage & fs)1549 int CV_ComputeEpilinesTest::read_params( const cv::FileStorage& fs )
1550 {
1551 int code = cvtest::ArrayTest::read_params( fs );
1552 return code;
1553 }
1554
1555
get_test_array_types_and_sizes(int,vector<vector<Size>> & sizes,vector<vector<int>> & types)1556 void CV_ComputeEpilinesTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
1557 vector<vector<Size> >& sizes, vector<vector<int> >& types )
1558 {
1559 RNG& rng = ts->get_rng();
1560 int fm_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
1561 int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
1562 int ln_depth = pt_depth;
1563 double pt_count_exp = cvtest::randReal(rng)*6;
1564
1565 which_image = 1 + (cvtest::randInt(rng) % 2);
1566
1567 pt_count = cvRound(exp(pt_count_exp));
1568 pt_count = MAX( pt_count, 1 );
1569 bool few_points = pt_count < 5;
1570
1571 dims = 2 + (cvtest::randInt(rng) % 2);
1572
1573 types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
1574
1575 sizes[INPUT][0] = cvSize(dims, pt_count);
1576 if( cvtest::randInt(rng) % 2 || few_points )
1577 {
1578 types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
1579 if( cvtest::randInt(rng) % 2 )
1580 sizes[INPUT][0] = cvSize(pt_count, 1);
1581 else
1582 sizes[INPUT][0] = cvSize(1, pt_count);
1583 }
1584
1585 types[INPUT][1] = CV_MAKETYPE(fm_depth, 1);
1586 sizes[INPUT][1] = cvSize(3, 3);
1587
1588 types[OUTPUT][0] = CV_MAKETYPE(ln_depth, 3);
1589 sizes[OUTPUT][0] = cvSize(1, pt_count);
1590
1591 types[REF_OUTPUT][0] = types[OUTPUT][0];
1592 sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
1593 }
1594
1595
get_success_error_level(int,int,int)1596 double CV_ComputeEpilinesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
1597 {
1598 return 1e-5;
1599 }
1600
1601
fill_array(int test_case_idx,int i,int j,Mat & arr)1602 void CV_ComputeEpilinesTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
1603 {
1604 RNG& rng = ts->get_rng();
1605
1606 if( i == INPUT && j == 0 )
1607 {
1608 Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims) );
1609 cvtest::randUni( rng, temp, cvScalar(0,0,1), cvScalarAll(10) );
1610 test_convertHomogeneous( temp, arr );
1611 }
1612 else if( i == INPUT && j == 1 )
1613 cvtest::randUni( rng, arr, cvScalarAll(0), cvScalarAll(10) );
1614 else
1615 cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
1616 }
1617
1618
run_func()1619 void CV_ComputeEpilinesTest::run_func()
1620 {
1621 cv::Mat _points = test_mat[INPUT][0], _F = test_mat[INPUT][1], &_lines = test_mat[OUTPUT][0];
1622 cv::computeCorrespondEpilines( _points, which_image, _F, _lines );
1623 }
1624
1625
prepare_to_validation(int)1626 void CV_ComputeEpilinesTest::prepare_to_validation( int /*test_case_idx*/ )
1627 {
1628 Mat pt( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
1629 Mat lines( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
1630 double f[9];
1631 Mat F( 3, 3, CV_64F, f );
1632
1633 test_convertHomogeneous( test_mat[INPUT][0], pt );
1634 test_mat[INPUT][1].convertTo(F, CV_64F);
1635 if( which_image == 2 )
1636 cv::transpose( F, F );
1637
1638 for( int i = 0; i < pt_count; i++ )
1639 {
1640 double* p = pt.ptr<double>() + i*3;
1641 double* l = lines.ptr<double>() + i*3;
1642 double t0 = f[0]*p[0] + f[1]*p[1] + f[2]*p[2];
1643 double t1 = f[3]*p[0] + f[4]*p[1] + f[5]*p[2];
1644 double t2 = f[6]*p[0] + f[7]*p[1] + f[8]*p[2];
1645 double d = sqrt(t0*t0 + t1*t1);
1646 d = d ? 1./d : 1.;
1647 l[0] = t0*d; l[1] = t1*d; l[2] = t2*d;
1648 }
1649
1650 test_convertHomogeneous( lines, test_mat[REF_OUTPUT][0] );
1651 }
1652
TEST(Calib3d_Rodrigues,accuracy)1653 TEST(Calib3d_Rodrigues, accuracy) { CV_RodriguesTest test; test.safe_run(); }
TEST(Calib3d_FindFundamentalMat,accuracy)1654 TEST(Calib3d_FindFundamentalMat, accuracy) { CV_FundamentalMatTest test; test.safe_run(); }
TEST(Calib3d_ConvertHomogeneoous,accuracy)1655 TEST(Calib3d_ConvertHomogeneoous, accuracy) { CV_ConvertHomogeneousTest test; test.safe_run(); }
TEST(Calib3d_ComputeEpilines,accuracy)1656 TEST(Calib3d_ComputeEpilines, accuracy) { CV_ComputeEpilinesTest test; test.safe_run(); }
TEST(Calib3d_FindEssentialMat,accuracy)1657 TEST(Calib3d_FindEssentialMat, accuracy) { CV_EssentialMatTest test; test.safe_run(); }
1658
TEST(Calib3d_FindFundamentalMat,correctMatches)1659 TEST(Calib3d_FindFundamentalMat, correctMatches)
1660 {
1661 double fdata[] = {0, 0, 0, 0, 0, -1, 0, 1, 0};
1662 double p1data[] = {200, 0, 1};
1663 double p2data[] = {170, 0, 1};
1664
1665 Mat F(3, 3, CV_64F, fdata);
1666 Mat p1(1, 1, CV_64FC2, p1data);
1667 Mat p2(1, 1, CV_64FC2, p2data);
1668 Mat np1, np2;
1669
1670 correctMatches(F, p1, p2, np1, np2);
1671
1672 cout << np1 << endl;
1673 cout << np2 << endl;
1674 }
1675
1676 }} // namespace
1677 /* End of file. */
1678