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Merge pull request #26259 from Kumataro:fix26258
core: C-API cleanup: RNG algorithms in core(4.x) #26259 - replace CV_RAND_UNI and NORMAL to cv::RNG::UNIFORM and cv::RNG::NORMAL. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
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@ -409,7 +409,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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(((_param2.rows == 1 || _param2.cols == 1) &&
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(_param2.rows + _param2.cols - 1 == cn || _param2.rows + _param2.cols - 1 == 1 ||
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(_param1.size() == Size(1, 4) && _param1.type() == CV_64F && cn <= 4))) ||
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(_param2.rows == cn && _param2.cols == cn && disttype == NORMAL)));
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(_param2.rows == cn && _param2.cols == cn && disttype == RNG::NORMAL)));
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Vec2i* ip = 0;
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Vec2d* dp = 0;
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@ -421,7 +421,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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int n1 = (int)_param1.total();
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int n2 = (int)_param2.total();
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if( disttype == UNIFORM )
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if( disttype == RNG::UNIFORM )
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{
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_parambuf.allocate(cn*8 + n1 + n2);
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double* parambuf = _parambuf.data();
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@ -535,7 +535,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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}
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CV_Assert( func != 0 );
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}
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else if( disttype == CV_RAND_NORMAL )
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else if( disttype == RNG::NORMAL )
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{
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_parambuf.allocate(MAX(n1, cn) + MAX(n2, cn));
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double* parambuf = _parambuf.data();
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@ -586,7 +586,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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float* nbuf = 0;
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float* tmpbuf = 0;
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if( disttype == UNIFORM )
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if( disttype == RNG::UNIFORM )
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{
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buf.allocate(blockSize*cn*4);
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param = (uchar*)(double*)buf.data();
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@ -637,7 +637,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
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{
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int len = std::min(total - j, blockSize);
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if( disttype == CV_RAND_UNI )
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if( disttype == RNG::UNIFORM )
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func( ptr, len*cn, &state, param, tmpbuf, smallFlag );
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else
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{
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@ -753,12 +753,31 @@ void cv::randShuffle( InputOutputArray _dst, double iterFactor, RNG* _rng )
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#ifndef OPENCV_EXCLUDE_C_API
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// Related with https://github.com/opencv/opencv/issues/26258
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// To suppress cast-user-defined warning for casting CvRNG to cv::RNG& with GCC14.
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// ( CvRNG is uint64, and cv::RNG has only status member which is uint64. )
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#if defined(__GNUC__) && __GNUC__ >= 14
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#define CV_IGNORE_CAST_USER_DEFINED_WARNING
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#endif
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CV_IMPL void
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cvRandArr( CvRNG* _rng, CvArr* arr, int disttype, CvScalar param1, CvScalar param2 )
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{
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cv::Mat mat = cv::cvarrToMat(arr);
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#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#pragma GCC diagnostic push
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#pragma GCC diagnostic ignored "-Wcast-user-defined"
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#endif
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// !!! this will only work for current 64-bit MWC RNG !!!
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cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG();
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#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#pragma GCC diagnostic pop
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#endif
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rng.fill(mat, disttype == CV_RAND_NORMAL ?
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cv::RNG::NORMAL : cv::RNG::UNIFORM, cv::Scalar(param1), cv::Scalar(param2) );
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}
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@ -766,10 +785,25 @@ cvRandArr( CvRNG* _rng, CvArr* arr, int disttype, CvScalar param1, CvScalar para
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CV_IMPL void cvRandShuffle( CvArr* arr, CvRNG* _rng, double iter_factor )
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{
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cv::Mat dst = cv::cvarrToMat(arr);
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#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#pragma GCC diagnostic push
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#pragma GCC diagnostic ignored "-Wcast-user-defined"
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#endif
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cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG();
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#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#pragma GCC diagnostic pop
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#endif
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cv::randShuffle( dst, iter_factor, &rng );
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}
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#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#undef CV_IGNORE_CAST_USER_DEFINED_WARNING
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#endif
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#endif // OPENCV_EXCLUDE_C_API
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@ -118,12 +118,12 @@ protected:
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int cn = cvtest::randInt(rng) % 4 + 1;
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Mat test_mat(cvtest::randInt(rng)%30+1, cvtest::randInt(rng)%30+1, CV_MAKETYPE(depth, cn));
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rng0.fill(test_mat, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
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rng0.fill(test_mat, RNG::UNIFORM, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
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if( depth >= CV_32F )
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{
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exp(test_mat, test_mat);
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Mat test_mat_scale(test_mat.size(), test_mat.type());
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rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
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rng0.fill(test_mat_scale, RNG::UNIFORM, Scalar::all(-1), Scalar::all(1));
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cv::multiply(test_mat, test_mat_scale, test_mat);
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}
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@ -136,12 +136,12 @@ protected:
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};
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MatND test_mat_nd(3, sz, CV_MAKETYPE(depth, cn));
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rng0.fill(test_mat_nd, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
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rng0.fill(test_mat_nd, RNG::UNIFORM, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
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if( depth >= CV_32F )
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{
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exp(test_mat_nd, test_mat_nd);
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MatND test_mat_scale(test_mat_nd.dims, test_mat_nd.size, test_mat_nd.type());
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rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1));
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rng0.fill(test_mat_scale, RNG::UNIFORM, Scalar::all(-1), Scalar::all(1));
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cv::multiply(test_mat_nd, test_mat_scale, test_mat_nd);
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}
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@ -650,8 +650,8 @@ void Core_ArrayOpTest::run( int /* start_from */)
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MatND A(3, sz3, CV_32F), B(3, sz3, CV_16SC4);
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CvMatND matA = cvMatND(A), matB = cvMatND(B);
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RNG rng;
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rng.fill(A, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
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rng.fill(B, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10));
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rng.fill(A, RNG::UNIFORM, Scalar::all(-10), Scalar::all(10));
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rng.fill(B, RNG::UNIFORM, Scalar::all(-10), Scalar::all(10));
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int idx0[] = {3,4,5}, idx1[] = {0, 9, 7};
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float val0 = 130;
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@ -807,7 +807,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
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all_vals.resize(nz0);
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all_vals2.resize(nz0);
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Mat_<double> _all_vals(all_vals), _all_vals2(all_vals2);
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rng.fill(_all_vals, CV_RAND_UNI, Scalar(-1000), Scalar(1000));
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rng.fill(_all_vals, RNG::UNIFORM, Scalar(-1000), Scalar(1000));
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if( depth == CV_32F )
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{
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Mat _all_vals_f;
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@ -48,7 +48,7 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
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sum += H[i];
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CV_Assert( fabs(1./sum - scale) < FLT_EPSILON );
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if( dist_type == CV_RAND_UNI )
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if( dist_type == RNG::UNIFORM )
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{
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float scale0 = (float)(1./hsz);
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for( i = 0; i < hsz; i++ )
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@ -79,7 +79,7 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
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}
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realval = chi2;
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double chi2_pval = chi2_p95(hsz - 1 - (dist_type == CV_RAND_NORMAL ? 2 : 0));
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double chi2_pval = chi2_p95(hsz - 1 - (dist_type == RNG::NORMAL ? 2 : 0));
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refval = chi2_pval*0.01;
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return realval <= refval;
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}
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@ -108,7 +108,7 @@ void Core_RandTest::run( int )
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int depth = cvtest::randInt(rng) % (CV_64F+1);
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int c, cn = (cvtest::randInt(rng) % 4) + 1;
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int type = CV_MAKETYPE(depth, cn);
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int dist_type = cvtest::randInt(rng) % (CV_RAND_NORMAL+1);
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int dist_type = cvtest::randInt(rng) % (RNG::NORMAL+1);
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int i, k, SZ = N/cn;
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Scalar A, B;
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@ -116,18 +116,18 @@ void Core_RandTest::run( int )
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if (depth == CV_64F)
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eps = 1.e-7;
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bool do_sphere_test = dist_type == CV_RAND_UNI;
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bool do_sphere_test = dist_type == RNG::UNIFORM;
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Mat arr[2], hist[4];
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int W[] = {0,0,0,0};
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arr[0].create(1, SZ, type);
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arr[1].create(1, SZ, type);
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bool fast_algo = dist_type == CV_RAND_UNI && depth < CV_32F;
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bool fast_algo = dist_type == RNG::UNIFORM && depth < CV_32F;
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for( c = 0; c < cn; c++ )
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{
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int a, b, hsz;
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if( dist_type == CV_RAND_UNI )
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if( dist_type == RNG::UNIFORM )
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{
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a = (int)(cvtest::randInt(rng) % (_ranges[depth][1] -
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_ranges[depth][0])) + _ranges[depth][0];
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@ -188,8 +188,8 @@ void Core_RandTest::run( int )
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const uchar* data = arr[0].ptr();
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int* H = hist[c].ptr<int>();
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int HSZ = hist[c].cols;
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double minVal = dist_type == CV_RAND_UNI ? A[c] : A[c] - B[c]*4;
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double maxVal = dist_type == CV_RAND_UNI ? B[c] : A[c] + B[c]*4;
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double minVal = dist_type == RNG::UNIFORM ? A[c] : A[c] - B[c]*4;
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double maxVal = dist_type == RNG::UNIFORM ? B[c] : A[c] + B[c]*4;
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double scale = HSZ/(maxVal - minVal);
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double delta = -minVal*scale;
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@ -210,7 +210,7 @@ void Core_RandTest::run( int )
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H[ival]++;
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W[c]++;
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}
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else if( dist_type == CV_RAND_UNI )
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else if( dist_type == RNG::UNIFORM )
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{
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if( (minVal <= val && val < maxVal) || (depth >= CV_32F && val == maxVal) )
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{
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@ -224,14 +224,14 @@ void Core_RandTest::run( int )
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}
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}
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if( dist_type == CV_RAND_UNI && W[c] != SZ )
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if( dist_type == RNG::UNIFORM && W[c] != SZ )
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{
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ts->printf( cvtest::TS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n",
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A[c], B[c], c, cn);
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
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return;
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}
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if( dist_type == CV_RAND_NORMAL && W[c] < SZ*.90)
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if( dist_type == RNG::NORMAL && W[c] < SZ*.90)
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{
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ts->printf( cvtest::TS::LOG, "Normal RNG gave too many values out of the range (%g+4*%g,%g+4*%g) on channel %d/%d\n",
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A[c], B[c], A[c], B[c], c, cn);
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angle = cvtest::randReal(rng)*360;
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scale = ((double)dst.rows/src.rows + (double)dst.cols/src.cols)*0.5;
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getRotationMatrix2D(center, angle, scale).convertTo(mat, mat.depth());
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rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(1.), Scalar::all(0.01) );
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rng.fill( tmp, RNG::NORMAL, Scalar::all(1.), Scalar::all(0.01) );
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cv::max(tmp, 0.9, tmp);
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cv::min(tmp, 1.1, tmp);
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cv::multiply(tmp, mat, mat, 1.);
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@ -673,7 +673,7 @@ int CV_WarpPerspectiveTest::prepare_test_case( int test_case_idx )
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float bufer[16];
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Mat tmp( 1, 16, CV_32FC1, bufer );
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rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(0.), Scalar::all(0.1) );
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rng.fill( tmp, RNG::NORMAL, Scalar::all(0.), Scalar::all(0.1) );
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for( i = 0; i < 4; i++ )
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{
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