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