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Merge pull request #26259 from Kumataro:fix26258

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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
pull/26284/head
Kumataro 2 months ago committed by GitHub
parent 28efc21530
commit 40428d919d
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5 changed files with 59 additions and 25 deletions
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  1. 44
      modules/core/src/rand.cpp
  2. 8
      modules/core/test/test_io.cpp
  3. 6
      modules/core/test/test_mat.cpp
  4. 22
      modules/core/test/test_rand.cpp
  5. 4
      modules/imgproc/test/test_imgwarp.cpp

44
modules/core/src/rand.cpp
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@ -409,7 +409,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
(((_param2.rows == 1 || _param2.cols == 1) && (((_param2.rows == 1 || _param2.cols == 1) &&
(_param2.rows + _param2.cols - 1 == cn || _param2.rows + _param2.cols - 1 == 1 || (_param2.rows + _param2.cols - 1 == cn || _param2.rows + _param2.cols - 1 == 1 ||
(_param1.size() == Size(1, 4) && _param1.type() == CV_64F && cn <= 4))) || (_param1.size() == Size(1, 4) && _param1.type() == CV_64F && cn <= 4))) ||
(_param2.rows == cn && _param2.cols == cn && disttype == NORMAL))); (_param2.rows == cn && _param2.cols == cn && disttype == RNG::NORMAL)));
Vec2i* ip = 0; Vec2i* ip = 0;
Vec2d* dp = 0; Vec2d* dp = 0;
@ -421,7 +421,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
int n1 = (int)_param1.total(); int n1 = (int)_param1.total();
int n2 = (int)_param2.total(); int n2 = (int)_param2.total();
if( disttype == UNIFORM ) if( disttype == RNG::UNIFORM )
{ {
_parambuf.allocate(cn*8 + n1 + n2); _parambuf.allocate(cn*8 + n1 + n2);
double* parambuf = _parambuf.data(); double* parambuf = _parambuf.data();
@ -535,7 +535,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
} }
CV_Assert( func != 0 ); CV_Assert( func != 0 );
} }
else if( disttype == CV_RAND_NORMAL ) else if( disttype == RNG::NORMAL )
{ {
_parambuf.allocate(MAX(n1, cn) + MAX(n2, cn)); _parambuf.allocate(MAX(n1, cn) + MAX(n2, cn));
double* parambuf = _parambuf.data(); double* parambuf = _parambuf.data();
@ -586,7 +586,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
float* nbuf = 0; float* nbuf = 0;
float* tmpbuf = 0; float* tmpbuf = 0;
if( disttype == UNIFORM ) if( disttype == RNG::UNIFORM )
{ {
buf.allocate(blockSize*cn*4); buf.allocate(blockSize*cn*4);
param = (uchar*)(double*)buf.data(); param = (uchar*)(double*)buf.data();
@ -637,7 +637,7 @@ void RNG::fill( InputOutputArray _mat, int disttype,
{ {
int len = std::min(total - j, blockSize); int len = std::min(total - j, blockSize);
if( disttype == CV_RAND_UNI ) if( disttype == RNG::UNIFORM )
func( ptr, len*cn, &state, param, tmpbuf, smallFlag ); func( ptr, len*cn, &state, param, tmpbuf, smallFlag );
else else
{ {
@ -753,12 +753,31 @@ void cv::randShuffle( InputOutputArray _dst, double iterFactor, RNG* _rng )
#ifndef OPENCV_EXCLUDE_C_API #ifndef OPENCV_EXCLUDE_C_API
// Related with https://github.com/opencv/opencv/issues/26258
// To suppress cast-user-defined warning for casting CvRNG to cv::RNG& with GCC14.
// ( CvRNG is uint64, and cv::RNG has only status member which is uint64. )
#if defined(__GNUC__) && __GNUC__ >= 14
#define CV_IGNORE_CAST_USER_DEFINED_WARNING
#endif
CV_IMPL void CV_IMPL void
cvRandArr( CvRNG* _rng, CvArr* arr, int disttype, CvScalar param1, CvScalar param2 ) cvRandArr( CvRNG* _rng, CvArr* arr, int disttype, CvScalar param1, CvScalar param2 )
{ {
cv::Mat mat = cv::cvarrToMat(arr); cv::Mat mat = cv::cvarrToMat(arr);
#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wcast-user-defined"
#endif
// !!! this will only work for current 64-bit MWC RNG !!! // !!! this will only work for current 64-bit MWC RNG !!!
cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG(); cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG();
#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
#pragma GCC diagnostic pop
#endif
rng.fill(mat, disttype == CV_RAND_NORMAL ? rng.fill(mat, disttype == CV_RAND_NORMAL ?
cv::RNG::NORMAL : cv::RNG::UNIFORM, cv::Scalar(param1), cv::Scalar(param2) ); cv::RNG::NORMAL : cv::RNG::UNIFORM, cv::Scalar(param1), cv::Scalar(param2) );
} }
@ -766,10 +785,25 @@ cvRandArr( CvRNG* _rng, CvArr* arr, int disttype, CvScalar param1, CvScalar para
CV_IMPL void cvRandShuffle( CvArr* arr, CvRNG* _rng, double iter_factor ) CV_IMPL void cvRandShuffle( CvArr* arr, CvRNG* _rng, double iter_factor )
{ {
cv::Mat dst = cv::cvarrToMat(arr); cv::Mat dst = cv::cvarrToMat(arr);
#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wcast-user-defined"
#endif
cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG(); cv::RNG& rng = _rng ? (cv::RNG&)*_rng : cv::theRNG();
#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
#pragma GCC diagnostic pop
#endif
cv::randShuffle( dst, iter_factor, &rng ); cv::randShuffle( dst, iter_factor, &rng );
} }
#ifdef CV_IGNORE_CAST_USER_DEFINED_WARNING
#undef CV_IGNORE_CAST_USER_DEFINED_WARNING
#endif
#endif // OPENCV_EXCLUDE_C_API #endif // OPENCV_EXCLUDE_C_API

8
modules/core/test/test_io.cpp
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@ -118,12 +118,12 @@ protected:
int cn = cvtest::randInt(rng) % 4 + 1; int cn = cvtest::randInt(rng) % 4 + 1;
Mat test_mat(cvtest::randInt(rng)%30+1, cvtest::randInt(rng)%30+1, CV_MAKETYPE(depth, cn)); Mat test_mat(cvtest::randInt(rng)%30+1, cvtest::randInt(rng)%30+1, CV_MAKETYPE(depth, cn));
rng0.fill(test_mat, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1])); rng0.fill(test_mat, RNG::UNIFORM, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
if( depth >= CV_32F ) if( depth >= CV_32F )
{ {
exp(test_mat, test_mat); exp(test_mat, test_mat);
Mat test_mat_scale(test_mat.size(), test_mat.type()); Mat test_mat_scale(test_mat.size(), test_mat.type());
rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1)); rng0.fill(test_mat_scale, RNG::UNIFORM, Scalar::all(-1), Scalar::all(1));
cv::multiply(test_mat, test_mat_scale, test_mat); cv::multiply(test_mat, test_mat_scale, test_mat);
} }
@ -136,12 +136,12 @@ protected:
}; };
MatND test_mat_nd(3, sz, CV_MAKETYPE(depth, cn)); MatND test_mat_nd(3, sz, CV_MAKETYPE(depth, cn));
rng0.fill(test_mat_nd, CV_RAND_UNI, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1])); rng0.fill(test_mat_nd, RNG::UNIFORM, Scalar::all(ranges[depth][0]), Scalar::all(ranges[depth][1]));
if( depth >= CV_32F ) if( depth >= CV_32F )
{ {
exp(test_mat_nd, test_mat_nd); exp(test_mat_nd, test_mat_nd);
MatND test_mat_scale(test_mat_nd.dims, test_mat_nd.size, test_mat_nd.type()); MatND test_mat_scale(test_mat_nd.dims, test_mat_nd.size, test_mat_nd.type());
rng0.fill(test_mat_scale, CV_RAND_UNI, Scalar::all(-1), Scalar::all(1)); rng0.fill(test_mat_scale, RNG::UNIFORM, Scalar::all(-1), Scalar::all(1));
cv::multiply(test_mat_nd, test_mat_scale, test_mat_nd); cv::multiply(test_mat_nd, test_mat_scale, test_mat_nd);
} }

6
modules/core/test/test_mat.cpp
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@ -650,8 +650,8 @@ void Core_ArrayOpTest::run( int /* start_from */)
MatND A(3, sz3, CV_32F), B(3, sz3, CV_16SC4); MatND A(3, sz3, CV_32F), B(3, sz3, CV_16SC4);
CvMatND matA = cvMatND(A), matB = cvMatND(B); CvMatND matA = cvMatND(A), matB = cvMatND(B);
RNG rng; RNG rng;
rng.fill(A, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10)); rng.fill(A, RNG::UNIFORM, Scalar::all(-10), Scalar::all(10));
rng.fill(B, CV_RAND_UNI, Scalar::all(-10), Scalar::all(10)); rng.fill(B, RNG::UNIFORM, Scalar::all(-10), Scalar::all(10));
int idx0[] = {3,4,5}, idx1[] = {0, 9, 7}; int idx0[] = {3,4,5}, idx1[] = {0, 9, 7};
float val0 = 130; float val0 = 130;
@ -807,7 +807,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
all_vals.resize(nz0); all_vals.resize(nz0);
all_vals2.resize(nz0); all_vals2.resize(nz0);
Mat_<double> _all_vals(all_vals), _all_vals2(all_vals2); Mat_<double> _all_vals(all_vals), _all_vals2(all_vals2);
rng.fill(_all_vals, CV_RAND_UNI, Scalar(-1000), Scalar(1000)); rng.fill(_all_vals, RNG::UNIFORM, Scalar(-1000), Scalar(1000));
if( depth == CV_32F ) if( depth == CV_32F )
{ {
Mat _all_vals_f; Mat _all_vals_f;

22
modules/core/test/test_rand.cpp
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@ -48,7 +48,7 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
sum += H[i]; sum += H[i];
CV_Assert( fabs(1./sum - scale) < FLT_EPSILON ); CV_Assert( fabs(1./sum - scale) < FLT_EPSILON );
if( dist_type == CV_RAND_UNI ) if( dist_type == RNG::UNIFORM )
{ {
float scale0 = (float)(1./hsz); float scale0 = (float)(1./hsz);
for( i = 0; i < hsz; i++ ) for( i = 0; i < hsz; i++ )
@ -79,7 +79,7 @@ bool Core_RandTest::check_pdf(const Mat& hist, double scale,
} }
realval = chi2; realval = chi2;
double chi2_pval = chi2_p95(hsz - 1 - (dist_type == CV_RAND_NORMAL ? 2 : 0)); double chi2_pval = chi2_p95(hsz - 1 - (dist_type == RNG::NORMAL ? 2 : 0));
refval = chi2_pval*0.01; refval = chi2_pval*0.01;
return realval <= refval; return realval <= refval;
} }
@ -108,7 +108,7 @@ void Core_RandTest::run( int )
int depth = cvtest::randInt(rng) % (CV_64F+1); int depth = cvtest::randInt(rng) % (CV_64F+1);
int c, cn = (cvtest::randInt(rng) % 4) + 1; int c, cn = (cvtest::randInt(rng) % 4) + 1;
int type = CV_MAKETYPE(depth, cn); int type = CV_MAKETYPE(depth, cn);
int dist_type = cvtest::randInt(rng) % (CV_RAND_NORMAL+1); int dist_type = cvtest::randInt(rng) % (RNG::NORMAL+1);
int i, k, SZ = N/cn; int i, k, SZ = N/cn;
Scalar A, B; Scalar A, B;
@ -116,18 +116,18 @@ void Core_RandTest::run( int )
if (depth == CV_64F) if (depth == CV_64F)
eps = 1.e-7; eps = 1.e-7;
bool do_sphere_test = dist_type == CV_RAND_UNI; bool do_sphere_test = dist_type == RNG::UNIFORM;
Mat arr[2], hist[4]; Mat arr[2], hist[4];
int W[] = {0,0,0,0}; int W[] = {0,0,0,0};
arr[0].create(1, SZ, type); arr[0].create(1, SZ, type);
arr[1].create(1, SZ, type); arr[1].create(1, SZ, type);
bool fast_algo = dist_type == CV_RAND_UNI && depth < CV_32F; bool fast_algo = dist_type == RNG::UNIFORM && depth < CV_32F;
for( c = 0; c < cn; c++ ) for( c = 0; c < cn; c++ )
{ {
int a, b, hsz; int a, b, hsz;
if( dist_type == CV_RAND_UNI ) if( dist_type == RNG::UNIFORM )
{ {
a = (int)(cvtest::randInt(rng) % (_ranges[depth][1] - a = (int)(cvtest::randInt(rng) % (_ranges[depth][1] -
_ranges[depth][0])) + _ranges[depth][0]; _ranges[depth][0])) + _ranges[depth][0];
@ -188,8 +188,8 @@ void Core_RandTest::run( int )
const uchar* data = arr[0].ptr(); const uchar* data = arr[0].ptr();
int* H = hist[c].ptr<int>(); int* H = hist[c].ptr<int>();
int HSZ = hist[c].cols; int HSZ = hist[c].cols;
double minVal = dist_type == CV_RAND_UNI ? A[c] : A[c] - B[c]*4; double minVal = dist_type == RNG::UNIFORM ? A[c] : A[c] - B[c]*4;
double maxVal = dist_type == CV_RAND_UNI ? B[c] : A[c] + B[c]*4; double maxVal = dist_type == RNG::UNIFORM ? B[c] : A[c] + B[c]*4;
double scale = HSZ/(maxVal - minVal); double scale = HSZ/(maxVal - minVal);
double delta = -minVal*scale; double delta = -minVal*scale;
@ -210,7 +210,7 @@ void Core_RandTest::run( int )
H[ival]++; H[ival]++;
W[c]++; W[c]++;
} }
else if( dist_type == CV_RAND_UNI ) else if( dist_type == RNG::UNIFORM )
{ {
if( (minVal <= val && val < maxVal) || (depth >= CV_32F && val == maxVal) ) if( (minVal <= val && val < maxVal) || (depth >= CV_32F && val == maxVal) )
{ {
@ -224,14 +224,14 @@ void Core_RandTest::run( int )
} }
} }
if( dist_type == CV_RAND_UNI && W[c] != SZ ) if( dist_type == RNG::UNIFORM && W[c] != SZ )
{ {
ts->printf( cvtest::TS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n", ts->printf( cvtest::TS::LOG, "Uniform RNG gave values out of the range [%g,%g) on channel %d/%d\n",
A[c], B[c], c, cn); A[c], B[c], c, cn);
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT ); ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return; return;
} }
if( dist_type == CV_RAND_NORMAL && W[c] < SZ*.90) if( dist_type == RNG::NORMAL && W[c] < SZ*.90)
{ {
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", 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",
A[c], B[c], A[c], B[c], c, cn); A[c], B[c], A[c], B[c], c, cn);

4
modules/imgproc/test/test_imgwarp.cpp
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@ -558,7 +558,7 @@ int CV_WarpAffineTest::prepare_test_case( int test_case_idx )
angle = cvtest::randReal(rng)*360; angle = cvtest::randReal(rng)*360;
scale = ((double)dst.rows/src.rows + (double)dst.cols/src.cols)*0.5; scale = ((double)dst.rows/src.rows + (double)dst.cols/src.cols)*0.5;
getRotationMatrix2D(center, angle, scale).convertTo(mat, mat.depth()); getRotationMatrix2D(center, angle, scale).convertTo(mat, mat.depth());
rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(1.), Scalar::all(0.01) ); rng.fill( tmp, RNG::NORMAL, Scalar::all(1.), Scalar::all(0.01) );
cv::max(tmp, 0.9, tmp); cv::max(tmp, 0.9, tmp);
cv::min(tmp, 1.1, tmp); cv::min(tmp, 1.1, tmp);
cv::multiply(tmp, mat, mat, 1.); cv::multiply(tmp, mat, mat, 1.);
@ -673,7 +673,7 @@ int CV_WarpPerspectiveTest::prepare_test_case( int test_case_idx )
float bufer[16]; float bufer[16];
Mat tmp( 1, 16, CV_32FC1, bufer ); Mat tmp( 1, 16, CV_32FC1, bufer );
rng.fill( tmp, CV_RAND_NORMAL, Scalar::all(0.), Scalar::all(0.1) ); rng.fill( tmp, RNG::NORMAL, Scalar::all(0.), Scalar::all(0.1) );
for( i = 0; i < 4; i++ ) for( i = 0; i < 4; i++ )
{ {

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