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Merge pull request #9293 from sovrasov:assert_improvement

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pull/9581/head
Vadim Pisarevsky 7 years ago
parent 4970a56341 9a10bdbae5
commit d25cbaaba8
2 changed files with 40 additions and 25 deletions
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  1. 17
      modules/core/include/opencv2/core/base.hpp
  2. 48
      modules/core/src/matmul.cpp

17
modules/core/include/opencv2/core/base.hpp
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@ -424,7 +424,22 @@ The macros CV_Assert (and CV_DbgAssert(expr)) evaluate the specified expression.
raise an error (see cv::error). The macro CV_Assert checks the condition in both Debug and Release
configurations while CV_DbgAssert is only retained in the Debug configuration.
*/
#define CV_Assert( expr ) if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ )
#define CV_VA_NUM_ARGS_HELPER(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N
#define CV_VA_NUM_ARGS(...) CV_VA_NUM_ARGS_HELPER(__VA_ARGS__, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1)
#define CV_Assert_1( expr ) if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ )
#define CV_Assert_2( expr1, expr2 ) CV_Assert_1(expr1); CV_Assert_1(expr2)
#define CV_Assert_3( expr1, expr2, expr3 ) CV_Assert_2(expr1, expr2); CV_Assert_1(expr3)
#define CV_Assert_4( expr1, expr2, expr3, expr4 ) CV_Assert_3(expr1, expr2, expr3); CV_Assert_1(expr4)
#define CV_Assert_5( expr1, expr2, expr3, expr4, expr5 ) CV_Assert_4(expr1, expr2, expr3, expr4); CV_Assert_1(expr5)
#define CV_Assert_6( expr1, expr2, expr3, expr4, expr5, expr6 ) CV_Assert_5(expr1, expr2, expr3, expr4, expr5); CV_Assert_1(expr6)
#define CV_Assert_7( expr1, expr2, expr3, expr4, expr5, expr6, expr7 ) CV_Assert_6(expr1, expr2, expr3, expr4, expr5, expr6 ); CV_Assert_1(expr7)
#define CV_Assert_8( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ) CV_Assert_7(expr1, expr2, expr3, expr4, expr5, expr6, expr7 ); CV_Assert_1(expr8)
#define CV_Assert_9( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ) CV_Assert_8(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ); CV_Assert_1(expr9)
#define CV_Assert_10( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9, expr10 ) CV_Assert_9(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ); CV_Assert_1(expr10)
#define CV_Assert(...) CVAUX_CONCAT(CV_Assert_, CV_VA_NUM_ARGS(__VA_ARGS__)) (__VA_ARGS__)
/** same as CV_Error(code,msg), but does not return */
#define CV_ErrorNoReturn( code, msg ) cv::errorNoReturn( code, msg, CV_Func, __FILE__, __LINE__ )

48
modules/core/src/matmul.cpp
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@ -796,7 +796,7 @@ static bool ocl_gemm( InputArray matA, InputArray matB, double alpha,
int depth = matA.depth(), cn = matA.channels();
int type = CV_MAKETYPE(depth, cn);
CV_Assert( type == matB.type() && (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
CV_Assert( type == matB.type(), (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
const ocl::Device & dev = ocl::Device::getDefault();
bool doubleSupport = dev.doubleFPConfig() > 0;
@ -1555,7 +1555,7 @@ void cv::gemm( InputArray matA, InputArray matB, double alpha,
Size a_size = A.size(), d_size;
int len = 0, type = A.type();
CV_Assert( type == B.type() && (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
CV_Assert( type == B.type(), (type == CV_32FC1 || type == CV_64FC1 || type == CV_32FC2 || type == CV_64FC2) );
switch( flags & (GEMM_1_T|GEMM_2_T) )
{
@ -1583,7 +1583,7 @@ void cv::gemm( InputArray matA, InputArray matB, double alpha,
if( !C.empty() )
{
CV_Assert( C.type() == type &&
CV_Assert( C.type() == type,
(((flags&GEMM_3_T) == 0 && C.rows == d_size.height && C.cols == d_size.width) ||
((flags&GEMM_3_T) != 0 && C.rows == d_size.width && C.cols == d_size.height)));
}
@ -2537,7 +2537,7 @@ void cv::calcCovarMatrix( const Mat* data, int nsamples, Mat& covar, Mat& _mean,
{
CV_INSTRUMENT_REGION()
CV_Assert( data && nsamples > 0 );
CV_Assert( data, nsamples > 0 );
Size size = data[0].size();
int sz = size.width * size.height, esz = (int)data[0].elemSize();
int type = data[0].type();
@ -2560,7 +2560,7 @@ void cv::calcCovarMatrix( const Mat* data, int nsamples, Mat& covar, Mat& _mean,
for( int i = 0; i < nsamples; i++ )
{
CV_Assert( data[i].size() == size && data[i].type() == type );
CV_Assert( data[i].size() == size, data[i].type() == type );
if( data[i].isContinuous() )
memcpy( _data.ptr(i), data[i].ptr(), sz*esz );
else
@ -2596,7 +2596,7 @@ void cv::calcCovarMatrix( InputArray _src, OutputArray _covar, InputOutputArray
int i = 0;
for(std::vector<cv::Mat>::iterator each = src.begin(); each != src.end(); ++each, ++i )
{
CV_Assert( (*each).size() == size && (*each).type() == type );
CV_Assert( (*each).size() == size, (*each).type() == type );
Mat dataRow(size.height, size.width, type, _data.ptr(i));
(*each).copyTo(dataRow);
}
@ -2675,8 +2675,8 @@ double cv::Mahalanobis( InputArray _v1, InputArray _v2, InputArray _icovar )
AutoBuffer<double> buf(len);
double result = 0;
CV_Assert( type == v2.type() && type == icovar.type() &&
sz == v2.size() && len == icovar.rows && len == icovar.cols );
CV_Assert( type == v2.type(), type == icovar.type(),
sz == v2.size(), len == icovar.rows && len == icovar.cols );
sz.width *= v1.channels();
if( v1.isContinuous() && v2.isContinuous() )
@ -2968,8 +2968,8 @@ void cv::mulTransposed( InputArray _src, OutputArray _dst, bool ata,
if( !delta.empty() )
{
CV_Assert( delta.channels() == 1 &&
(delta.rows == src.rows || delta.rows == 1) &&
CV_Assert( delta.channels() == 1,
(delta.rows == src.rows || delta.rows == 1),
(delta.cols == src.cols || delta.cols == 1));
if( delta.type() != dtype )
delta.convertTo(delta, dtype);
@ -3380,7 +3380,7 @@ double Mat::dot(InputArray _mat) const
Mat mat = _mat.getMat();
int cn = channels();
DotProdFunc func = getDotProdFunc(depth());
CV_Assert( mat.type() == type() && mat.size == size && func != 0 );
CV_Assert( mat.type() == type(), mat.size == size, func != 0 );
if( isContinuous() && mat.isContinuous() )
{
@ -3416,8 +3416,8 @@ CV_IMPL void cvGEMM( const CvArr* Aarr, const CvArr* Barr, double alpha,
if( Carr )
C = cv::cvarrToMat(Carr);
CV_Assert( (D.rows == ((flags & CV_GEMM_A_T) == 0 ? A.rows : A.cols)) &&
(D.cols == ((flags & CV_GEMM_B_T) == 0 ? B.cols : B.rows)) &&
CV_Assert( (D.rows == ((flags & CV_GEMM_A_T) == 0 ? A.rows : A.cols)),
(D.cols == ((flags & CV_GEMM_B_T) == 0 ? B.cols : B.rows)),
D.type() == A.type() );
gemm( A, B, alpha, C, beta, D, flags );
@ -3439,7 +3439,7 @@ cvTransform( const CvArr* srcarr, CvArr* dstarr,
m = _m;
}
CV_Assert( dst.depth() == src.depth() && dst.channels() == m.rows );
CV_Assert( dst.depth() == src.depth(), dst.channels() == m.rows );
cv::transform( src, dst, m );
}
@ -3449,7 +3449,7 @@ cvPerspectiveTransform( const CvArr* srcarr, CvArr* dstarr, const CvMat* mat )
{
cv::Mat m = cv::cvarrToMat(mat), src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( dst.type() == src.type() && dst.channels() == m.rows-1 );
CV_Assert( dst.type() == src.type(), dst.channels() == m.rows-1 );
cv::perspectiveTransform( src, dst, m );
}
@ -3459,7 +3459,7 @@ CV_IMPL void cvScaleAdd( const CvArr* srcarr1, CvScalar scale,
{
cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
CV_Assert( src1.size == dst.size, src1.type() == dst.type() );
cv::scaleAdd( src1, scale.val[0], cv::cvarrToMat(srcarr2), dst );
}
@ -3469,7 +3469,7 @@ cvCalcCovarMatrix( const CvArr** vecarr, int count,
CvArr* covarr, CvArr* avgarr, int flags )
{
cv::Mat cov0 = cv::cvarrToMat(covarr), cov = cov0, mean0, mean;
CV_Assert( vecarr != 0 && count >= 1 );
CV_Assert( vecarr != 0, count >= 1 );
if( avgarr )
mean = mean0 = cv::cvarrToMat(avgarr);
@ -3549,9 +3549,9 @@ cvCalcPCA( const CvArr* data_arr, CvArr* avg_arr, CvArr* eigenvals, CvArr* eigen
int ecount0 = evals0.cols + evals0.rows - 1;
int ecount = evals.cols + evals.rows - 1;
CV_Assert( (evals0.cols == 1 || evals0.rows == 1) &&
ecount0 <= ecount &&
evects0.cols == evects.cols &&
CV_Assert( (evals0.cols == 1 || evals0.rows == 1),
ecount0 <= ecount,
evects0.cols == evects.cols,
evects0.rows == ecount0 );
cv::Mat temp = evals0;
@ -3580,12 +3580,12 @@ cvProjectPCA( const CvArr* data_arr, const CvArr* avg_arr,
int n;
if( mean.rows == 1 )
{
CV_Assert(dst.cols <= evects.rows && dst.rows == data.rows);
CV_Assert(dst.cols <= evects.rows, dst.rows == data.rows);
n = dst.cols;
}
else
{
CV_Assert(dst.rows <= evects.rows && dst.cols == data.cols);
CV_Assert(dst.rows <= evects.rows, dst.cols == data.cols);
n = dst.rows;
}
pca.eigenvectors = evects.rowRange(0, n);
@ -3611,12 +3611,12 @@ cvBackProjectPCA( const CvArr* proj_arr, const CvArr* avg_arr,
int n;
if( mean.rows == 1 )
{
CV_Assert(data.cols <= evects.rows && dst.rows == data.rows);
CV_Assert(data.cols <= evects.rows, dst.rows == data.rows);
n = data.cols;
}
else
{
CV_Assert(data.rows <= evects.rows && dst.cols == data.cols);
CV_Assert(data.rows <= evects.rows, dst.cols == data.cols);
n = data.rows;
}
pca.eigenvectors = evects.rowRange(0, n);

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