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# include "test_precomp.hpp"
using namespace cv ;
using namespace std ;
class Core_ReduceTest : public cvtest : : BaseTest
{
public :
Core_ReduceTest ( ) { } ;
protected :
void run ( int ) ;
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int checkOp ( const Mat & src , int dstType , int opType , const Mat & opRes , int dim ) ;
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int checkCase ( int srcType , int dstType , int dim , Size sz ) ;
int checkDim ( int dim , Size sz ) ;
int checkSize ( Size sz ) ;
} ;
template < class Type >
void testReduce ( const Mat & src , Mat & sum , Mat & avg , Mat & max , Mat & min , int dim )
{
assert ( src . channels ( ) = = 1 ) ;
if ( dim = = 0 ) // row
{
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sum . create ( 1 , src . cols , CV_64FC1 ) ;
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max . create ( 1 , src . cols , CV_64FC1 ) ;
min . create ( 1 , src . cols , CV_64FC1 ) ;
}
else
{
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sum . create ( src . rows , 1 , CV_64FC1 ) ;
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max . create ( src . rows , 1 , CV_64FC1 ) ;
min . create ( src . rows , 1 , CV_64FC1 ) ;
}
sum . setTo ( Scalar ( 0 ) ) ;
max . setTo ( Scalar ( - DBL_MAX ) ) ;
min . setTo ( Scalar ( DBL_MAX ) ) ;
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const Mat_ < Type > & src_ = src ;
Mat_ < double > & sum_ = ( Mat_ < double > & ) sum ;
Mat_ < double > & min_ = ( Mat_ < double > & ) min ;
Mat_ < double > & max_ = ( Mat_ < double > & ) max ;
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if ( dim = = 0 )
{
for ( int ri = 0 ; ri < src . rows ; ri + + )
{
for ( int ci = 0 ; ci < src . cols ; ci + + )
{
sum_ ( 0 , ci ) + = src_ ( ri , ci ) ;
max_ ( 0 , ci ) = std : : max ( max_ ( 0 , ci ) , ( double ) src_ ( ri , ci ) ) ;
min_ ( 0 , ci ) = std : : min ( min_ ( 0 , ci ) , ( double ) src_ ( ri , ci ) ) ;
}
}
}
else
{
for ( int ci = 0 ; ci < src . cols ; ci + + )
{
for ( int ri = 0 ; ri < src . rows ; ri + + )
{
sum_ ( ri , 0 ) + = src_ ( ri , ci ) ;
max_ ( ri , 0 ) = std : : max ( max_ ( ri , 0 ) , ( double ) src_ ( ri , ci ) ) ;
min_ ( ri , 0 ) = std : : min ( min_ ( ri , 0 ) , ( double ) src_ ( ri , ci ) ) ;
}
}
}
sum . convertTo ( avg , CV_64FC1 ) ;
avg = avg * ( 1.0 / ( dim = = 0 ? ( double ) src . rows : ( double ) src . cols ) ) ;
}
void getMatTypeStr ( int type , string & str )
{
str = type = = CV_8UC1 ? " CV_8UC1 " :
type = = CV_8SC1 ? " CV_8SC1 " :
type = = CV_16UC1 ? " CV_16UC1 " :
type = = CV_16SC1 ? " CV_16SC1 " :
type = = CV_32SC1 ? " CV_32SC1 " :
type = = CV_32FC1 ? " CV_32FC1 " :
type = = CV_64FC1 ? " CV_64FC1 " : " unsupported matrix type " ;
}
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int Core_ReduceTest : : checkOp ( const Mat & src , int dstType , int opType , const Mat & opRes , int dim )
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{
int srcType = src . type ( ) ;
bool support = false ;
if ( opType = = CV_REDUCE_SUM | | opType = = CV_REDUCE_AVG )
{
if ( srcType = = CV_8U & & ( dstType = = CV_32S | | dstType = = CV_32F | | dstType = = CV_64F ) )
support = true ;
if ( srcType = = CV_16U & & ( dstType = = CV_32F | | dstType = = CV_64F ) )
support = true ;
if ( srcType = = CV_16S & & ( dstType = = CV_32F | | dstType = = CV_64F ) )
support = true ;
if ( srcType = = CV_32F & & ( dstType = = CV_32F | | dstType = = CV_64F ) )
support = true ;
if ( srcType = = CV_64F & & dstType = = CV_64F )
support = true ;
}
else if ( opType = = CV_REDUCE_MAX )
{
if ( srcType = = CV_8U & & dstType = = CV_8U )
support = true ;
if ( srcType = = CV_32F & & dstType = = CV_32F )
support = true ;
if ( srcType = = CV_64F & & dstType = = CV_64F )
support = true ;
}
else if ( opType = = CV_REDUCE_MIN )
{
if ( srcType = = CV_8U & & dstType = = CV_8U )
support = true ;
if ( srcType = = CV_32F & & dstType = = CV_32F )
support = true ;
if ( srcType = = CV_64F & & dstType = = CV_64F )
support = true ;
}
if ( ! support )
return cvtest : : TS : : OK ;
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double eps = 0.0 ;
if ( opType = = CV_REDUCE_SUM | | opType = = CV_REDUCE_AVG )
{
if ( dstType = = CV_32F )
eps = 1.e-5 ;
else if ( dstType = = CV_64F )
eps = 1.e-8 ;
else if ( dstType = = CV_32S )
eps = 0.6 ;
}
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assert ( opRes . type ( ) = = CV_64FC1 ) ;
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Mat _dst , dst , diff ;
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reduce ( src , _dst , dim , opType , dstType ) ;
_dst . convertTo ( dst , CV_64FC1 ) ;
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absdiff ( opRes , dst , diff ) ;
bool check = false ;
if ( dstType = = CV_32F | | dstType = = CV_64F )
check = countNonZero ( diff > eps * dst ) > 0 ;
else
check = countNonZero ( diff > eps ) > 0 ;
if ( check )
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{
char msg [ 100 ] ;
const char * opTypeStr = opType = = CV_REDUCE_SUM ? " CV_REDUCE_SUM " :
opType = = CV_REDUCE_AVG ? " CV_REDUCE_AVG " :
opType = = CV_REDUCE_MAX ? " CV_REDUCE_MAX " :
opType = = CV_REDUCE_MIN ? " CV_REDUCE_MIN " : " unknown operation type " ;
string srcTypeStr , dstTypeStr ;
getMatTypeStr ( src . type ( ) , srcTypeStr ) ;
getMatTypeStr ( dstType , dstTypeStr ) ;
const char * dimStr = dim = = 0 ? " ROWS " : " COLS " ;
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sprintf ( msg , " bad accuracy with srcType = %s, dstType = %s, opType = %s, dim = %s " ,
srcTypeStr . c_str ( ) , dstTypeStr . c_str ( ) , opTypeStr , dimStr ) ;
ts - > printf ( cvtest : : TS : : LOG , msg ) ;
return cvtest : : TS : : FAIL_BAD_ACCURACY ;
}
return cvtest : : TS : : OK ;
}
int Core_ReduceTest : : checkCase ( int srcType , int dstType , int dim , Size sz )
{
int code = cvtest : : TS : : OK , tempCode ;
Mat src , sum , avg , max , min ;
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src . create ( sz , srcType ) ;
randu ( src , Scalar ( 0 ) , Scalar ( 100 ) ) ;
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if ( srcType = = CV_8UC1 )
testReduce < uchar > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_8SC1 )
testReduce < char > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_16UC1 )
testReduce < unsigned short int > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_16SC1 )
testReduce < short int > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_32SC1 )
testReduce < int > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_32FC1 )
testReduce < float > ( src , sum , avg , max , min , dim ) ;
else if ( srcType = = CV_64FC1 )
testReduce < double > ( src , sum , avg , max , min , dim ) ;
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else
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assert ( 0 ) ;
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// 1. sum
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tempCode = checkOp ( src , dstType , CV_REDUCE_SUM , sum , dim ) ;
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code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// 2. avg
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tempCode = checkOp ( src , dstType , CV_REDUCE_AVG , avg , dim ) ;
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code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// 3. max
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tempCode = checkOp ( src , dstType , CV_REDUCE_MAX , max , dim ) ;
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code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// 4. min
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tempCode = checkOp ( src , dstType , CV_REDUCE_MIN , min , dim ) ;
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code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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return code ;
}
int Core_ReduceTest : : checkDim ( int dim , Size sz )
{
int code = cvtest : : TS : : OK , tempCode ;
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// CV_8UC1
tempCode = checkCase ( CV_8UC1 , CV_8UC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_8UC1 , CV_32SC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_8UC1 , CV_32FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_8UC1 , CV_64FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// CV_16UC1
tempCode = checkCase ( CV_16UC1 , CV_32FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_16UC1 , CV_64FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// CV_16SC1
tempCode = checkCase ( CV_16SC1 , CV_32FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_16SC1 , CV_64FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// CV_32FC1
tempCode = checkCase ( CV_32FC1 , CV_32FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkCase ( CV_32FC1 , CV_64FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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// CV_64FC1
tempCode = checkCase ( CV_64FC1 , CV_64FC1 , dim , sz ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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return code ;
}
int Core_ReduceTest : : checkSize ( Size sz )
{
int code = cvtest : : TS : : OK , tempCode ;
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tempCode = checkDim ( 0 , sz ) ; // rows
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkDim ( 1 , sz ) ; // cols
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code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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return code ;
}
void Core_ReduceTest : : run ( int )
{
int code = cvtest : : TS : : OK , tempCode ;
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tempCode = checkSize ( Size ( 1 , 1 ) ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkSize ( Size ( 1 , 100 ) ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkSize ( Size ( 100 , 1 ) ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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tempCode = checkSize ( Size ( 1000 , 500 ) ) ;
code = tempCode ! = cvtest : : TS : : OK ? tempCode : code ;
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ts - > set_failed_test_info ( code ) ;
}
# define CHECK_C
class Core_PCATest : public cvtest : : BaseTest
{
public :
Core_PCATest ( ) { }
protected :
void run ( int )
{
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const Size sz ( 200 , 500 ) ;
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double diffPrjEps , diffBackPrjEps ,
prjEps , backPrjEps ,
evalEps , evecEps ;
int maxComponents = 100 ;
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double retainedVariance = 0.95 ;
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Mat rPoints ( sz , CV_32FC1 ) , rTestPoints ( sz , CV_32FC1 ) ;
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RNG & rng = ts - > get_rng ( ) ;
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rng . fill ( rPoints , RNG : : UNIFORM , Scalar : : all ( 0.0 ) , Scalar : : all ( 1.0 ) ) ;
rng . fill ( rTestPoints , RNG : : UNIFORM , Scalar : : all ( 0.0 ) , Scalar : : all ( 1.0 ) ) ;
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PCA rPCA ( rPoints , Mat ( ) , CV_PCA_DATA_AS_ROW , maxComponents ) , cPCA ;
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// 1. check C++ PCA & ROW
Mat rPrjTestPoints = rPCA . project ( rTestPoints ) ;
Mat rBackPrjTestPoints = rPCA . backProject ( rPrjTestPoints ) ;
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Mat avg ( 1 , sz . width , CV_32FC1 ) ;
reduce ( rPoints , avg , 0 , CV_REDUCE_AVG ) ;
Mat Q = rPoints - repeat ( avg , rPoints . rows , 1 ) , Qt = Q . t ( ) , eval , evec ;
Q = Qt * Q ;
Q = Q / ( float ) rPoints . rows ;
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eigen ( Q , eval , evec ) ;
/*SVD svd(Q);
evec = svd . vt ;
eval = svd . w ; */
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Mat subEval ( maxComponents , 1 , eval . type ( ) , eval . data ) ,
subEvec ( maxComponents , evec . cols , evec . type ( ) , evec . data ) ;
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# ifdef CHECK_C
Mat prjTestPoints , backPrjTestPoints , cPoints = rPoints . t ( ) , cTestPoints = rTestPoints . t ( ) ;
CvMat _points , _testPoints , _avg , _eval , _evec , _prjTestPoints , _backPrjTestPoints ;
# endif
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// check eigen()
double eigenEps = 1e-6 ;
double err ;
for ( int i = 0 ; i < Q . rows ; i + + )
{
Mat v = evec . row ( i ) . t ( ) ;
Mat Qv = Q * v ;
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Mat lv = eval . at < float > ( i , 0 ) * v ;
err = norm ( Qv , lv ) ;
if ( err > eigenEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of eigen(); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
}
// check pca eigenvalues
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evalEps = 1e-6 , evecEps = 1e-3 ;
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err = norm ( rPCA . eigenvalues , subEval ) ;
if ( err > evalEps )
{
ts - > printf ( cvtest : : TS : : LOG , " pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
// check pca eigenvectors
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for ( int i = 0 ; i < subEvec . rows ; i + + )
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{
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Mat r0 = rPCA . eigenvectors . row ( i ) ;
Mat r1 = subEvec . row ( i ) ;
err = norm ( r0 , r1 , CV_L2 ) ;
if ( err > evecEps )
{
r1 * = - 1 ;
double err2 = norm ( r0 , r1 , CV_L2 ) ;
if ( err2 > evecEps )
{
Mat tmp ;
absdiff ( rPCA . eigenvectors , subEvec , tmp ) ;
double mval = 0 ; Point mloc ;
minMaxLoc ( tmp , 0 , & mval , 0 , & mloc ) ;
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ts - > printf ( cvtest : : TS : : LOG , " pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
ts - > printf ( cvtest : : TS : : LOG , " max diff is %g at (i=%d, j=%d) (%g vs %g) \n " ,
mval , mloc . y , mloc . x , rPCA . eigenvectors . at < float > ( mloc . y , mloc . x ) ,
subEvec . at < float > ( mloc . y , mloc . x ) ) ;
ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
}
}
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}
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prjEps = 1.265 , backPrjEps = 1.265 ;
for ( int i = 0 ; i < rTestPoints . rows ; i + + )
{
// check pca project
Mat subEvec_t = subEvec . t ( ) ;
Mat prj = rTestPoints . row ( i ) - avg ; prj * = subEvec_t ;
err = norm ( rPrjTestPoints . row ( i ) , prj , CV_RELATIVE_L2 ) ;
if ( err > prjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
// check pca backProject
Mat backPrj = rPrjTestPoints . row ( i ) * subEvec + avg ;
err = norm ( rBackPrjTestPoints . row ( i ) , backPrj , CV_RELATIVE_L2 ) ;
if ( err > backPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
}
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// 2. check C++ PCA & COL
cPCA ( rPoints . t ( ) , Mat ( ) , CV_PCA_DATA_AS_COL , maxComponents ) ;
diffPrjEps = 1 , diffBackPrjEps = 1 ;
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Mat ocvPrjTestPoints = cPCA . project ( rTestPoints . t ( ) ) ;
err = norm ( cv : : abs ( ocvPrjTestPoints ) , cv : : abs ( rPrjTestPoints . t ( ) ) , CV_RELATIVE_L2 ) ;
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if ( err > diffPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
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err = norm ( cPCA . backProject ( ocvPrjTestPoints ) , rBackPrjTestPoints . t ( ) , CV_RELATIVE_L2 ) ;
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if ( err > diffBackPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
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// 3. check C++ PCA w/retainedVariance
cPCA ( rPoints . t ( ) , Mat ( ) , CV_PCA_DATA_AS_COL , retainedVariance ) ;
diffPrjEps = 1 , diffBackPrjEps = 1 ;
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Mat rvPrjTestPoints = cPCA . project ( rTestPoints . t ( ) ) ;
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if ( cPCA . eigenvectors . rows > maxComponents )
err = norm ( cv : : abs ( rvPrjTestPoints . rowRange ( 0 , maxComponents ) ) , cv : : abs ( rPrjTestPoints . t ( ) ) , CV_RELATIVE_L2 ) ;
else
err = norm ( cv : : abs ( rvPrjTestPoints ) , cv : : abs ( rPrjTestPoints . colRange ( 0 , cPCA . eigenvectors . rows ) . t ( ) ) , CV_RELATIVE_L2 ) ;
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if ( err > diffPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of project() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f \n " , err ) ;
ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
}
err = norm ( cPCA . backProject ( rvPrjTestPoints ) , rBackPrjTestPoints . t ( ) , CV_RELATIVE_L2 ) ;
if ( err > diffBackPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of backProject() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f \n " , err ) ;
ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
}
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# ifdef CHECK_C
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// 4. check C PCA & ROW
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_points = rPoints ;
_testPoints = rTestPoints ;
_avg = avg ;
_eval = eval ;
_evec = evec ;
prjTestPoints . create ( rTestPoints . rows , maxComponents , rTestPoints . type ( ) ) ;
backPrjTestPoints . create ( rPoints . size ( ) , rPoints . type ( ) ) ;
_prjTestPoints = prjTestPoints ;
_backPrjTestPoints = backPrjTestPoints ;
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cvCalcPCA ( & _points , & _avg , & _eval , & _evec , CV_PCA_DATA_AS_ROW ) ;
cvProjectPCA ( & _testPoints , & _avg , & _evec , & _prjTestPoints ) ;
cvBackProjectPCA ( & _prjTestPoints , & _avg , & _evec , & _backPrjTestPoints ) ;
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err = norm ( prjTestPoints , rPrjTestPoints , CV_RELATIVE_L2 ) ;
if ( err > diffPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
err = norm ( backPrjTestPoints , rBackPrjTestPoints , CV_RELATIVE_L2 ) ;
if ( err > diffBackPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
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// 5. check C PCA & COL
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_points = cPoints ;
_testPoints = cTestPoints ;
avg = avg . t ( ) ; _avg = avg ;
eval = eval . t ( ) ; _eval = eval ;
evec = evec . t ( ) ; _evec = evec ;
prjTestPoints = prjTestPoints . t ( ) ; _prjTestPoints = prjTestPoints ;
backPrjTestPoints = backPrjTestPoints . t ( ) ; _backPrjTestPoints = backPrjTestPoints ;
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cvCalcPCA ( & _points , & _avg , & _eval , & _evec , CV_PCA_DATA_AS_COL ) ;
cvProjectPCA ( & _testPoints , & _avg , & _evec , & _prjTestPoints ) ;
cvBackProjectPCA ( & _prjTestPoints , & _avg , & _evec , & _backPrjTestPoints ) ;
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err = norm ( cv : : abs ( prjTestPoints ) , cv : : abs ( rPrjTestPoints . t ( ) ) , CV_RELATIVE_L2 ) ;
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if ( err > diffPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
err = norm ( backPrjTestPoints , rBackPrjTestPoints . t ( ) , CV_RELATIVE_L2 ) ;
if ( err > diffBackPrjEps )
{
ts - > printf ( cvtest : : TS : : LOG , " bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f \n " , err ) ;
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ts - > set_failed_test_info ( cvtest : : TS : : FAIL_BAD_ACCURACY ) ;
return ;
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}
# endif
}
} ;
class Core_ArrayOpTest : public cvtest : : BaseTest
{
public :
Core_ArrayOpTest ( ) ;
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~ Core_ArrayOpTest ( ) ;
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protected :
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void run ( int ) ;
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} ;
Core_ArrayOpTest : : Core_ArrayOpTest ( )
{
}
Core_ArrayOpTest : : ~ Core_ArrayOpTest ( ) { }
static string idx2string ( const int * idx , int dims )
{
char buf [ 256 ] ;
char * ptr = buf ;
for ( int k = 0 ; k < dims ; k + + )
{
sprintf ( ptr , " %4d " , idx [ k ] ) ;
ptr + = strlen ( ptr ) ;
}
ptr [ - 1 ] = ' \0 ' ;
return string ( buf ) ;
}
static const int * string2idx ( const string & s , int * idx , int dims )
{
const char * ptr = s . c_str ( ) ;
for ( int k = 0 ; k < dims ; k + + )
{
int n = 0 ;
sscanf ( ptr , " %d%n " , idx + k , & n ) ;
ptr + = n ;
}
return idx ;
}
static double getValue ( SparseMat & M , const int * idx , RNG & rng )
{
int d = M . dims ( ) ;
size_t hv = 0 , * phv = 0 ;
if ( ( unsigned ) rng % 2 )
{
hv = d = = 2 ? M . hash ( idx [ 0 ] , idx [ 1 ] ) :
d = = 3 ? M . hash ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] ) : M . hash ( idx ) ;
phv = & hv ;
}
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const uchar * ptr = d = = 2 ? M . ptr ( idx [ 0 ] , idx [ 1 ] , false , phv ) :
d = = 3 ? M . ptr ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] , false , phv ) :
M . ptr ( idx , false , phv ) ;
return ! ptr ? 0 : M . type ( ) = = CV_32F ? * ( float * ) ptr : M . type ( ) = = CV_64F ? * ( double * ) ptr : 0 ;
}
static double getValue ( const CvSparseMat * M , const int * idx )
{
int type = 0 ;
const uchar * ptr = cvPtrND ( M , idx , & type , 0 ) ;
return ! ptr ? 0 : type = = CV_32F ? * ( float * ) ptr : type = = CV_64F ? * ( double * ) ptr : 0 ;
}
static void eraseValue ( SparseMat & M , const int * idx , RNG & rng )
{
int d = M . dims ( ) ;
size_t hv = 0 , * phv = 0 ;
if ( ( unsigned ) rng % 2 )
{
hv = d = = 2 ? M . hash ( idx [ 0 ] , idx [ 1 ] ) :
d = = 3 ? M . hash ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] ) : M . hash ( idx ) ;
phv = & hv ;
}
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if ( d = = 2 )
M . erase ( idx [ 0 ] , idx [ 1 ] , phv ) ;
else if ( d = = 3 )
M . erase ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] , phv ) ;
else
M . erase ( idx , phv ) ;
}
static void eraseValue ( CvSparseMat * M , const int * idx )
{
cvClearND ( M , idx ) ;
}
static void setValue ( SparseMat & M , const int * idx , double value , RNG & rng )
{
int d = M . dims ( ) ;
size_t hv = 0 , * phv = 0 ;
if ( ( unsigned ) rng % 2 )
{
hv = d = = 2 ? M . hash ( idx [ 0 ] , idx [ 1 ] ) :
d = = 3 ? M . hash ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] ) : M . hash ( idx ) ;
phv = & hv ;
}
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uchar * ptr = d = = 2 ? M . ptr ( idx [ 0 ] , idx [ 1 ] , true , phv ) :
d = = 3 ? M . ptr ( idx [ 0 ] , idx [ 1 ] , idx [ 2 ] , true , phv ) :
M . ptr ( idx , true , phv ) ;
if ( M . type ( ) = = CV_32F )
* ( float * ) ptr = ( float ) value ;
else if ( M . type ( ) = = CV_64F )
* ( double * ) ptr = value ;
else
CV_Error ( CV_StsUnsupportedFormat , " " ) ;
}
void Core_ArrayOpTest : : run ( int /* start_from */ )
{
int errcount = 0 ;
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// dense matrix operations
{
int sz3 [ ] = { 5 , 10 , 15 } ;
MatND A ( 3 , sz3 , CV_32F ) , B ( 3 , sz3 , CV_16SC4 ) ;
CvMatND matA = A , matB = B ;
RNG rng ;
rng . fill ( A , CV_RAND_UNI , Scalar : : all ( - 10 ) , Scalar : : all ( 10 ) ) ;
rng . fill ( B , CV_RAND_UNI , Scalar : : all ( - 10 ) , Scalar : : all ( 10 ) ) ;
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int idx0 [ ] = { 3 , 4 , 5 } , idx1 [ ] = { 0 , 9 , 7 } ;
float val0 = 130 ;
Scalar val1 ( - 1000 , 30 , 3 , 8 ) ;
cvSetRealND ( & matA , idx0 , val0 ) ;
cvSetReal3D ( & matA , idx1 [ 0 ] , idx1 [ 1 ] , idx1 [ 2 ] , - val0 ) ;
cvSetND ( & matB , idx0 , val1 ) ;
cvSet3D ( & matB , idx1 [ 0 ] , idx1 [ 1 ] , idx1 [ 2 ] , - val1 ) ;
Ptr < CvMatND > matC = cvCloneMatND ( & matB ) ;
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if ( A . at < float > ( idx0 [ 0 ] , idx0 [ 1 ] , idx0 [ 2 ] ) ! = val0 | |
A . at < float > ( idx1 [ 0 ] , idx1 [ 1 ] , idx1 [ 2 ] ) ! = - val0 | |
cvGetReal3D ( & matA , idx0 [ 0 ] , idx0 [ 1 ] , idx0 [ 2 ] ) ! = val0 | |
cvGetRealND ( & matA , idx1 ) ! = - val0 | |
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Scalar ( B . at < Vec4s > ( idx0 [ 0 ] , idx0 [ 1 ] , idx0 [ 2 ] ) ) ! = val1 | |
Scalar ( B . at < Vec4s > ( idx1 [ 0 ] , idx1 [ 1 ] , idx1 [ 2 ] ) ) ! = - val1 | |
Scalar ( cvGet3D ( matC , idx0 [ 0 ] , idx0 [ 1 ] , idx0 [ 2 ] ) ) ! = val1 | |
Scalar ( cvGetND ( matC , idx1 ) ) ! = - val1 )
{
ts - > printf ( cvtest : : TS : : LOG , " one of cvSetReal3D, cvSetRealND, cvSet3D, cvSetND "
" or the corresponding *Get* functions is not correct \n " ) ;
errcount + + ;
}
}
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RNG rng ;
const int MAX_DIM = 5 , MAX_DIM_SZ = 10 ;
// sparse matrix operations
for ( int si = 0 ; si < 10 ; si + + )
{
int depth = ( unsigned ) rng % 2 = = 0 ? CV_32F : CV_64F ;
int dims = ( ( unsigned ) rng % MAX_DIM ) + 1 ;
int i , k , size [ MAX_DIM ] = { 0 } , idx [ MAX_DIM ] = { 0 } ;
vector < string > all_idxs ;
vector < double > all_vals ;
vector < double > all_vals2 ;
string sidx , min_sidx , max_sidx ;
double min_val = 0 , max_val = 0 ;
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int p = 1 ;
for ( k = 0 ; k < dims ; k + + )
{
size [ k ] = ( ( unsigned ) rng % MAX_DIM_SZ ) + 1 ;
p * = size [ k ] ;
}
SparseMat M ( dims , size , depth ) ;
map < string , double > M0 ;
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int nz0 = ( unsigned ) rng % max ( p / 5 , 10 ) ;
nz0 = min ( max ( nz0 , 1 ) , p ) ;
all_vals . resize ( nz0 ) ;
all_vals2 . resize ( nz0 ) ;
Mat_ < double > _all_vals ( all_vals ) , _all_vals2 ( all_vals2 ) ;
rng . fill ( _all_vals , CV_RAND_UNI , Scalar ( - 1000 ) , Scalar ( 1000 ) ) ;
if ( depth = = CV_32F )
{
Mat _all_vals_f ;
_all_vals . convertTo ( _all_vals_f , CV_32F ) ;
_all_vals_f . convertTo ( _all_vals , CV_64F ) ;
}
_all_vals . convertTo ( _all_vals2 , _all_vals2 . type ( ) , 2 ) ;
if ( depth = = CV_32F )
{
Mat _all_vals2_f ;
_all_vals2 . convertTo ( _all_vals2_f , CV_32F ) ;
_all_vals2_f . convertTo ( _all_vals2 , CV_64F ) ;
}
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minMaxLoc ( _all_vals , & min_val , & max_val ) ;
double _norm0 = norm ( _all_vals , CV_C ) ;
double _norm1 = norm ( _all_vals , CV_L1 ) ;
double _norm2 = norm ( _all_vals , CV_L2 ) ;
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for ( i = 0 ; i < nz0 ; i + + )
{
for ( ; ; )
{
for ( k = 0 ; k < dims ; k + + )
idx [ k ] = ( unsigned ) rng % size [ k ] ;
sidx = idx2string ( idx , dims ) ;
if ( M0 . count ( sidx ) = = 0 )
break ;
}
all_idxs . push_back ( sidx ) ;
M0 [ sidx ] = all_vals [ i ] ;
if ( all_vals [ i ] = = min_val )
min_sidx = sidx ;
if ( all_vals [ i ] = = max_val )
max_sidx = sidx ;
setValue ( M , idx , all_vals [ i ] , rng ) ;
double v = getValue ( M , idx , rng ) ;
if ( v ! = all_vals [ i ] )
{
ts - > printf ( cvtest : : TS : : LOG , " %d. immediately after SparseMat[%s]=%.20g the current value is %.20g \n " ,
i , sidx . c_str ( ) , all_vals [ i ] , v ) ;
errcount + + ;
break ;
}
}
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Ptr < CvSparseMat > M2 = ( CvSparseMat * ) M ;
MatND Md ;
M . copyTo ( Md ) ;
SparseMat M3 ; SparseMat ( Md ) . convertTo ( M3 , Md . type ( ) , 2 ) ;
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int nz1 = ( int ) M . nzcount ( ) , nz2 = ( int ) M3 . nzcount ( ) ;
double norm0 = norm ( M , CV_C ) ;
double norm1 = norm ( M , CV_L1 ) ;
double norm2 = norm ( M , CV_L2 ) ;
double eps = depth = = CV_32F ? FLT_EPSILON * 100 : DBL_EPSILON * 1000 ;
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if ( nz1 ! = nz0 | | nz2 ! = nz0 )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " %d: The number of non-zero elements before/after converting to/from dense matrix is not correct: %d/%d (while it should be %d) \n " ,
si , nz1 , nz2 , nz0 ) ;
break ;
}
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if ( fabs ( norm0 - _norm0 ) > fabs ( _norm0 ) * eps | |
fabs ( norm1 - _norm1 ) > fabs ( _norm1 ) * eps | |
fabs ( norm2 - _norm2 ) > fabs ( _norm2 ) * eps )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " %d: The norms are different: %.20g/%.20g/%.20g vs %.20g/%.20g/%.20g \n " ,
si , norm0 , norm1 , norm2 , _norm0 , _norm1 , _norm2 ) ;
break ;
}
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int n = ( unsigned ) rng % max ( p / 5 , 10 ) ;
n = min ( max ( n , 1 ) , p ) + nz0 ;
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for ( i = 0 ; i < n ; i + + )
{
double val1 , val2 , val3 , val0 ;
if ( i < nz0 )
{
sidx = all_idxs [ i ] ;
string2idx ( sidx , idx , dims ) ;
val0 = all_vals [ i ] ;
}
else
{
for ( k = 0 ; k < dims ; k + + )
idx [ k ] = ( unsigned ) rng % size [ k ] ;
sidx = idx2string ( idx , dims ) ;
val0 = M0 [ sidx ] ;
}
val1 = getValue ( M , idx , rng ) ;
val2 = getValue ( M2 , idx ) ;
val3 = getValue ( M3 , idx , rng ) ;
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if ( val1 ! = val0 | | val2 ! = val0 | | fabs ( val3 - val0 * 2 ) > fabs ( val0 * 2 ) * FLT_EPSILON )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " SparseMat M[%s] = %g/%g/%g (while it should be %g) \n " , sidx . c_str ( ) , val1 , val2 , val3 , val0 ) ;
break ;
}
}
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for ( i = 0 ; i < n ; i + + )
{
double val1 , val2 ;
if ( i < nz0 )
{
sidx = all_idxs [ i ] ;
string2idx ( sidx , idx , dims ) ;
}
else
{
for ( k = 0 ; k < dims ; k + + )
idx [ k ] = ( unsigned ) rng % size [ k ] ;
sidx = idx2string ( idx , dims ) ;
}
eraseValue ( M , idx , rng ) ;
eraseValue ( M2 , idx ) ;
val1 = getValue ( M , idx , rng ) ;
val2 = getValue ( M2 , idx ) ;
if ( val1 ! = 0 | | val2 ! = 0 )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " SparseMat: after deleting M[%s], it is =%g/%g (while it should be 0) \n " , sidx . c_str ( ) , val1 , val2 ) ;
break ;
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}
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}
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int nz = ( int ) M . nzcount ( ) ;
if ( nz ! = 0 )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " The number of non-zero elements after removing all the elements = %d (while it should be 0) \n " , nz ) ;
break ;
}
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int idx1 [ MAX_DIM ] , idx2 [ MAX_DIM ] ;
double val1 = 0 , val2 = 0 ;
M3 = SparseMat ( Md ) ;
minMaxLoc ( M3 , & val1 , & val2 , idx1 , idx2 ) ;
string s1 = idx2string ( idx1 , dims ) , s2 = idx2string ( idx2 , dims ) ;
if ( val1 ! = min_val | | val2 ! = max_val | | s1 ! = min_sidx | | s2 ! = max_sidx )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " %d. Sparse: The value and positions of minimum/maximum elements are different from the reference values and positions: \n \t "
" (%g, %g, %s, %s) vs (%g, %g, %s, %s) \n " , si , val1 , val2 , s1 . c_str ( ) , s2 . c_str ( ) ,
min_val , max_val , min_sidx . c_str ( ) , max_sidx . c_str ( ) ) ;
break ;
}
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minMaxIdx ( Md , & val1 , & val2 , idx1 , idx2 ) ;
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s1 = idx2string ( idx1 , dims ) , s2 = idx2string ( idx2 , dims ) ;
if ( ( min_val < 0 & & ( val1 ! = min_val | | s1 ! = min_sidx ) ) | |
( max_val > 0 & & ( val2 ! = max_val | | s2 ! = max_sidx ) ) )
{
errcount + + ;
ts - > printf ( cvtest : : TS : : LOG , " %d. Dense: The value and positions of minimum/maximum elements are different from the reference values and positions: \n \t "
" (%g, %g, %s, %s) vs (%g, %g, %s, %s) \n " , si , val1 , val2 , s1 . c_str ( ) , s2 . c_str ( ) ,
min_val , max_val , min_sidx . c_str ( ) , max_sidx . c_str ( ) ) ;
break ;
}
}
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ts - > set_failed_test_info ( errcount = = 0 ? cvtest : : TS : : OK : cvtest : : TS : : FAIL_INVALID_OUTPUT ) ;
}
TEST ( Core_PCA , accuracy ) { Core_PCATest test ; test . safe_run ( ) ; }
TEST ( Core_Reduce , accuracy ) { Core_ReduceTest test ; test . safe_run ( ) ; }
TEST ( Core_Array , basic_operations ) { Core_ArrayOpTest test ; test . safe_run ( ) ; }
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TEST ( Core_IOArray , submat_assignment )
{
Mat1f A = Mat1f : : zeros ( 2 , 2 ) ;
Mat1f B = Mat1f : : ones ( 1 , 3 ) ;
EXPECT_THROW ( B . colRange ( 0 , 3 ) . copyTo ( A . row ( 0 ) ) , cv : : Exception ) ;
EXPECT_NO_THROW ( B . colRange ( 0 , 2 ) . copyTo ( A . row ( 0 ) ) ) ;
EXPECT_EQ ( 1.0f , A ( 0 , 0 ) ) ;
EXPECT_EQ ( 1.0f , A ( 0 , 1 ) ) ;
}
void OutputArray_create1 ( OutputArray m ) { m . create ( 1 , 2 , CV_32S ) ; }
void OutputArray_create2 ( OutputArray m ) { m . create ( 1 , 3 , CV_32F ) ; }
TEST ( Core_IOArray , submat_create )
{
Mat1f A = Mat1f : : zeros ( 2 , 2 ) ;
EXPECT_THROW ( OutputArray_create1 ( A . row ( 0 ) ) , cv : : Exception ) ;
EXPECT_THROW ( OutputArray_create2 ( A . row ( 0 ) ) , cv : : Exception ) ;
}
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TEST ( Core_Mat , reshape_1942 )
{
cv : : Mat A = ( cv : : Mat_ < float > ( 2 , 3 ) < < 3.4884074 , 1.4159607 , 0.78737736 , 2.3456569 , - 0.88010466 , 0.3009364 ) ;
int cn = 0 ;
ASSERT_NO_THROW (
cv : : Mat_ < float > M = A . reshape ( 3 ) ;
cn = M . channels ( ) ;
) ;
ASSERT_EQ ( 1 , cn ) ;
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}