static void
icxLogicSM( const void* srcarr, CxScalar* scalar, void* dstarr,
const void* maskarr, CxArithmUniMaskFunc2D func )
{
CX_FUNCNAME( "icxLogicSM" );
__BEGIN__;
double buf[12];
int coi1 = 0, coi2 = 0;
CxMat srcstub, *src = (CxMat*)srcarr;
CxMat dststub, *dst = (CxMat*)dstarr;
CxMat maskstub, *mask = (CxMat*)maskarr;
int pix_size, type;
int dst_step, mask_step;
CxSize size;
if( !CX_IS_MAT(src))
CX_CALL( src = cxGetMat( src, &srcstub, &coi1 ));
if( !CX_IS_MAT(dst))
CX_CALL( dst = cxGetMat( dst, &dststub ));
if( coi1 != 0 || coi2 != 0 )
CX_ERROR( CX_BadCOI, "" );
CX_CALL( mask = cxGetMat( mask, &maskstub ));
if( !CX_IS_MASK_ARR(mask) )
CX_ERROR_FROM_CODE( CX_StsBadMask );
if( !CX_ARE_SIZES_EQ( mask, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
if( src->data.ptr != dst->data.ptr )
{
CX_CALL( cxCopy( src, dst, mask ));
}
size = cxGetMatSize( dst );
dst_step = dst->step;
mask_step = mask->step;
if( CX_IS_MAT_CONT( mask->type & dst->type ))
{
size.width *= size.height;
dst_step = mask_step = CX_STUB_STEP;
size.height = 1;
}
type = CX_MAT_TYPE( src->type );
pix_size = icxPixSize[type];
CX_CALL( cxScalarToRawData( scalar, buf, type, 0 ));
IPPI_CALL( func( dst->data.ptr, dst_step, mask->data.ptr,
mask_step, size, buf, pix_size ));
__END__;
}
CX_IMPL void
cxMinMaxLoc( const void* img, double* minVal, double* maxVal,
CxPoint* minLoc, CxPoint* maxLoc, const void* mask )
{
static CxFuncTable minmax_tab, minmaxcoi_tab;
static CxFuncTable minmaxmask_tab, minmaxmaskcoi_tab;
static int inittab = 0;
CX_FUNCNAME("cxMinMaxLoc");
__BEGIN__;
int type, depth, cn, coi = 0;
int mat_step, mask_step = 0;
CxSize size;
CxMat stub, maskstub, *mat = (CxMat*)img, *matmask = (CxMat*)mask;
if( !inittab )
{
icxInitMinMaxIndxC1RTable( &minmax_tab );
icxInitMinMaxIndxCnCRTable( &minmaxcoi_tab );
icxInitMinMaxIndxC1MRTable( &minmaxmask_tab );
icxInitMinMaxIndxCnCMRTable( &minmaxmaskcoi_tab );
inittab = 1;
}
CX_CALL( mat = cxGetMat( mat, &stub, &coi ));
type = CX_MAT_TYPE( mat->type );
depth = CX_MAT_DEPTH( type );
cn = CX_MAT_CN( type );
size = cxGetMatSize( mat );
if( cn > 1 && coi == 0 )
CX_ERROR( CX_StsBadArg, "" );
mat_step = mat->step;
if( !mask )
{
if( size.height == 1 )
mat_step = CX_STUB_STEP;
if( CX_MAT_CN(type) == 1 || coi == 0 )
{
CxFunc2D_1A4P func = (CxFunc2D_1A4P)(minmax_tab.fn_2d[depth]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, size,
minVal, maxVal, minLoc, maxLoc ));
}
else
{
CxFunc2DnC_1A4P func = (CxFunc2DnC_1A4P)(minmaxcoi_tab.fn_2d[depth]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, size, cn, coi,
minVal, maxVal, minLoc, maxLoc ));
}
}
else
{
CX_CALL( matmask = cxGetMat( matmask, &maskstub ));
if( !CX_IS_MASK_ARR( matmask ))
CX_ERROR( CX_StsBadMask, "" );
if( !CX_ARE_SIZES_EQ( mat, matmask ))
CX_ERROR( CX_StsUnmatchedSizes, "" );
mask_step = matmask->step;
if( size.height == 1 )
mat_step = mask_step = CX_STUB_STEP;
if( CX_MAT_CN(type) == 1 || coi == 0 )
{
CxFunc2D_2A4P func = (CxFunc2D_2A4P)(minmaxmask_tab.fn_2d[depth]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, matmask->data.ptr,
mask_step, size,
minVal, maxVal, minLoc, maxLoc ));
}
else
{
CxFunc2DnC_2A4P func = (CxFunc2DnC_2A4P)(minmaxmaskcoi_tab.fn_2d[depth]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step,
matmask->data.ptr, mask_step, size, cn, coi,
minVal, maxVal, minLoc, maxLoc ));
}
}
if( depth < CX_32S || depth == CX_32F )
{
if( minVal )
*minVal = *(float*)minVal;
if( maxVal )
*maxVal = *(float*)maxVal;
}
__END__;
}
CX_IMPL void
icxLogicM( const void* srcimg1, const void* srcimg2,
void* dstarr, const void* maskarr,
CxArithmBinMaskFunc2D func )
{
CX_FUNCNAME( "icxLogicM" );
__BEGIN__;
int coi1 = 0, coi2 = 0, coi3 = 0;
CxMat srcstub1, *src1 = (CxMat*)srcimg1;
CxMat srcstub2, *src2 = (CxMat*)srcimg2;
CxMat dststub, *dst = (CxMat*)dstarr;
CxMat maskstub, *mask = (CxMat*)maskarr;
int src_step, dst_step, mask_step;
int pix_size;
CxSize size;
CX_CALL( src1 = cxGetMat( src1, &srcstub1, &coi1 ));
CX_CALL( src2 = cxGetMat( src2, &srcstub2, &coi2 ));
CX_CALL( dst = cxGetMat( dst, &dststub, &coi3 ));
CX_CALL( mask = cxGetMat( mask, &maskstub ));
if( coi1 != 0 || coi2 != 0 || coi3 != 0 )
CX_ERROR( CX_BadCOI, "" );
if( !CX_IS_MASK_ARR(mask) )
CX_ERROR_FROM_CODE( CX_StsBadMask );
if( !CX_ARE_SIZES_EQ( mask, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
if( !CX_ARE_SIZES_EQ( src1, src2 ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
size = cxGetMatSize( src1 );
pix_size = icxPixSize[CX_MAT_TYPE(src1->type)];
if( src2->data.ptr != dst->data.ptr )
{
if( src1->data.ptr != dst->data.ptr )
{
CX_CALL( cxCopy( src2, dst, mask ));
}
else
src1 = src2;
}
if( !CX_ARE_TYPES_EQ( src1, dst ))
CX_ERROR_FROM_CODE( CX_StsUnmatchedFormats );
if( !CX_ARE_SIZES_EQ( src1, dst ))
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
src_step = src1->step;
dst_step = dst->step;
mask_step = mask->step;
if( CX_IS_MAT_CONT( src1->type & dst->type & mask->type ))
{
size.width *= size.height;
src_step = dst_step = mask_step = CX_STUB_STEP;
size.height = 1;
}
IPPI_CALL( func( src1->data.ptr, src_step, mask->data.ptr, mask_step,
dst->data.ptr, dst_step, size, pix_size ));
__END__;
}
static void
icxLogic( const void* srcimg1, const void* srcimg2,
void* dstarr, CxFunc2D_3A fn_2d )
{
CX_FUNCNAME( "icxLogic" );
__BEGIN__;
int coi1 = 0, coi2 = 0, coi3 = 0;
int is_nd = 0;
CxMat srcstub1, *src1 = (CxMat*)srcimg1;
CxMat srcstub2, *src2 = (CxMat*)srcimg2;
CxMat dststub, *dst = (CxMat*)dstarr;
int src1_step, src2_step, dst_step;
CxSize size;
if( !CX_IS_MAT(src1))
{
if( CX_IS_MATND(src1) )
is_nd = 1;
else
CX_CALL( src1 = cxGetMat( src1, &srcstub1, &coi1 ));
}
if( !CX_IS_MAT(src2))
{
if( CX_IS_MATND(src2) )
is_nd = 1;
else
CX_CALL( src2 = cxGetMat( src2, &srcstub2, &coi2 ));
}
if( !CX_IS_MAT(dst))
{
if( CX_IS_MATND(dst) )
is_nd = 1;
else
CX_CALL( dst = cxGetMat( dst, &dststub, &coi3 ));
}
if( is_nd )
{
CxArr* arrs[] = { src1, src2, dst };
CxMatND stubs[3];
CxNArrayIterator iterator;
int type;
CX_CALL( cxInitNArrayIterator( 3, arrs, 0, stubs, &iterator ));
type = CX_MAT_TYPE(iterator.hdr[0]->type);
iterator.size.width *= icxPixSize[type];
do
{
IPPI_CALL( fn_2d( iterator.ptr[0], CX_STUB_STEP,
iterator.ptr[1], CX_STUB_STEP,
iterator.ptr[2], CX_STUB_STEP,
iterator.size ));
}
while( cxNextNArraySlice( &iterator ));
EXIT;
}
if( coi1 != 0 || coi2 != 0 || coi3 != 0 )
CX_ERROR_FROM_CODE( CX_BadCOI );
if( !CX_ARE_TYPES_EQ( src1, src2 ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedFormats );
if( !CX_ARE_SIZES_EQ( src1, src2 ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
size = cxGetMatSize( src1 );
if( !CX_ARE_TYPES_EQ( src1, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedFormats );
if( !CX_ARE_SIZES_EQ( src1, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
src1_step = src1->step;
src2_step = src2->step;
dst_step = dst->step;
if( CX_IS_MAT_CONT( src1->type & src2->type & dst->type ))
{
size.width *= size.height;
src1_step = src2_step = dst_step = CX_STUB_STEP;
size.height = 1;
}
size.width *= icxPixSize[CX_MAT_TYPE(src1->type)];
IPPI_CALL( fn_2d( src1->data.ptr, src1_step, src2->data.ptr, src2_step,
dst->data.ptr, dst_step, size ));
__END__;
}
static void
icxLogicS( const void* srcarr, CxScalar* scalar,
void* dstarr, CxFunc2D_2A1P1I fn_2d )
{
CX_FUNCNAME( "icxLogicS" );
__BEGIN__;
CxMat srcstub, *src = (CxMat*)srcarr;
CxMat dststub, *dst = (CxMat*)dstarr;
int coi1 = 0, coi2 = 0;
int is_nd = 0;
int pix_size, type;
double buf[12];
CxSize size;
int src_step, dst_step;
if( !CX_IS_MAT(src))
{
if( CX_IS_MATND(src) )
is_nd = 1;
else
CX_CALL( src = cxGetMat( src, &srcstub, &coi1 ));
}
if( !CX_IS_MAT(dst))
{
if( CX_IS_MATND(dst) )
is_nd = 1;
else
CX_CALL( dst = cxGetMat( dst, &dststub, &coi2 ));
}
if( is_nd )
{
CxArr* arrs[] = { src, dst };
CxMatND stubs[2];
CxNArrayIterator iterator;
CX_CALL( cxInitNArrayIterator( 2, arrs, 0, stubs, &iterator ));
type = CX_MAT_TYPE(iterator.hdr[0]->type);
iterator.size.width *= icxPixSize[type];
pix_size = icxPixSize[type & CX_MAT_DEPTH_MASK];
CX_CALL( cxScalarToRawData( scalar, buf, type, 1 ));
do
{
IPPI_CALL( fn_2d( iterator.ptr[0], CX_STUB_STEP,
iterator.ptr[1], CX_STUB_STEP,
iterator.size, buf, pix_size ));
}
while( cxNextNArraySlice( &iterator ));
EXIT;
}
if( coi1 != 0 || coi2 != 0 )
CX_ERROR( CX_BadCOI, "" );
if( !CX_ARE_TYPES_EQ( src, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedFormats );
if( !CX_ARE_SIZES_EQ( src, dst ) )
CX_ERROR_FROM_CODE( CX_StsUnmatchedSizes );
size = cxGetMatSize( src );
src_step = src->step;
dst_step = dst->step;
if( CX_IS_MAT_CONT( src->type & dst->type ))
{
size.width *= size.height;
src_step = dst_step = CX_STUB_STEP;
size.height = 1;
}
type = CX_MAT_TYPE( src->type );
size.width *= icxPixSize[type];
pix_size = icxPixSize[type & CX_MAT_DEPTH_MASK];
CX_CALL( cxScalarToRawData( scalar, buf, type, 1 ));
IPPI_CALL( fn_2d( src->data.ptr, src_step, dst->data.ptr, dst_step,
size, buf, pix_size ));
__END__;
}
CX_IMPL void
cxAvgSdv( const void* img, CxScalar* _mean, CxScalar* _sdv, const void* mask )
{
CxScalar mean = {{0,0,0,0}};
CxScalar sdv = {{0,0,0,0}};
static CxBigFuncTable meansdv_tab;
static CxFuncTable meansdvcoi_tab;
static CxBigFuncTable meansdvmask_tab;
static CxFuncTable meansdvmaskcoi_tab;
static int inittab = 0;
CX_FUNCNAME("cxMean_StdDev");
__BEGIN__;
int type, coi = 0;
int mat_step, mask_step = 0;
CxSize size;
CxMat stub, maskstub, *mat = (CxMat*)img, *matmask = (CxMat*)mask;
if( !inittab )
{
icxInitMean_StdDevRTable( &meansdv_tab );
icxInitMean_StdDevCnCRTable( &meansdvcoi_tab );
icxInitMean_StdDevMRTable( &meansdvmask_tab );
icxInitMean_StdDevCnCMRTable( &meansdvmaskcoi_tab );
inittab = 1;
}
CX_CALL( mat = cxGetMat( mat, &stub, &coi ));
type = CX_MAT_TYPE( mat->type );
size = cxGetMatSize( mat );
mat_step = mat->step;
if( !mask )
{
if( CX_IS_MAT_CONT( mat->type ))
{
size.width *= size.height;
size.height = 1;
mat_step = CX_STUB_STEP;
}
if( CX_MAT_CN(type) == 1 || coi == 0 )
{
CxFunc2D_1A2P func = (CxFunc2D_1A2P)(meansdv_tab.fn_2d[type]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, size, mean.val, sdv.val ));
}
else
{
CxFunc2DnC_1A2P func = (CxFunc2DnC_1A2P)
(meansdvcoi_tab.fn_2d[CX_MAT_DEPTH(type)]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, size,
CX_MAT_CN(type), coi, mean.val, sdv.val ));
}
}
else
{
CX_CALL( matmask = cxGetMat( matmask, &maskstub ));
mask_step = matmask->step;
if( !CX_IS_MASK_ARR( matmask ))
CX_ERROR( CX_StsBadMask, "" );
if( !CX_ARE_SIZES_EQ( mat, matmask ))
CX_ERROR( CX_StsUnmatchedSizes, "" );
if( CX_IS_MAT_CONT( mat->type & matmask->type ))
{
size.width *= size.height;
size.height = 1;
mat_step = mask_step = CX_STUB_STEP;
}
if( CX_MAT_CN(type) == 1 || coi == 0 )
{
CxFunc2D_2A2P func = (CxFunc2D_2A2P)(meansdvmask_tab.fn_2d[type]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step, matmask->data.ptr,
mask_step, size, mean.val, sdv.val ));
}
else
{
CxFunc2DnC_2A2P func = (CxFunc2DnC_2A2P)
(meansdvmaskcoi_tab.fn_2d[CX_MAT_DEPTH(type)]);
if( !func )
CX_ERROR( CX_StsBadArg, cxUnsupportedFormat );
IPPI_CALL( func( mat->data.ptr, mat_step,
matmask->data.ptr, mask_step,
size, CX_MAT_CN(type), coi, mean.val, sdv.val ));
}
}
__END__;
if( _mean )
*_mean = mean;
if( _sdv )
*_sdv = sdv;
}
CX_IMPL void
cxKMeans2( const CxArr* samples_arr, int cluster_count,
CxArr* labels_arr, CxTermCriteria termcrit )
{
CxMat* centers = 0;
CxMat* old_centers = 0;
CxMat* counters = 0;
CX_FUNCNAME( "cxKMeans2" );
__BEGIN__;
CxMat samples_stub, *samples = (CxMat*)samples_arr;
CxMat cluster_idx_stub, *labels = (CxMat*)labels_arr;
CxMat* temp = 0;
CxRandState rng;
int i, k, sample_count, dims;
int ids_delta, iter;
double max_dist;
int pix_size;
if( !CX_IS_MAT( samples ))
CX_CALL( samples = cxGetMat( samples, &samples_stub ));
if( !CX_IS_MAT( labels ))
CX_CALL( labels = cxGetMat( labels, &cluster_idx_stub ));
if( cluster_count < 1 )
CX_ERROR( CX_StsOutOfRange, "Number of clusters should be positive" );
if( CX_MAT_DEPTH(samples->type) != CX_32F || CX_MAT_TYPE(labels->type) != CX_32SC1 )
CX_ERROR( CX_StsUnsupportedFormat,
"samples should be floating-point matrix, cluster_idx - integer vector" );
pix_size = CX_ELEM_SIZE(samples->type);
if( labels->rows != 1 && labels->cols != 1 || labels->rows + labels->cols - 1 != samples->rows )
CX_ERROR( CX_StsUnmatchedSizes,
"cluster_idx should be 1D vector of the same number of elements as samples' number of rows" );
switch( termcrit.type )
{
case CX_TERMCRIT_EPS:
if( termcrit.epsilon < 0 )
termcrit.epsilon = 0;
termcrit.maxIter = 100;
break;
case CX_TERMCRIT_ITER:
if( termcrit.maxIter < 1 )
termcrit.maxIter = 1;
termcrit.epsilon = 1e-6;
break;
case CX_TERMCRIT_EPS|CX_TERMCRIT_ITER:
if( termcrit.epsilon < 0 )
termcrit.epsilon = 0;
if( termcrit.maxIter < 1 )
termcrit.maxIter = 1;
break;
default:
CX_ERROR( CX_StsBadArg, "Invalid termination criteria" );
}
termcrit.epsilon *= termcrit.epsilon;
sample_count = samples->rows;
if( cluster_count > sample_count )
cluster_count = sample_count;
dims = samples->cols*CX_MAT_CN(samples->type);
ids_delta = labels->step ? labels->step/(int)sizeof(int) : 1;
cxRandInit( &rng, 0, 1, -1, CX_RAND_UNI );
CX_CALL( centers = cxCreateMat( cluster_count, dims, CX_64FC1 ));
CX_CALL( old_centers = cxCreateMat( cluster_count, dims, CX_64FC1 ));
// samples_count >= cluster_count, <samples_count>
// elements are used during initialization
#if 0
CX_CALL( counters = cxCreateMat( 1, sample_count, CX_32SC1 ));
cxZero( counters );
// init centers
for( i = 0; i < cluster_count; i++ )
{
int j, idx;
double* c = (double*)(centers->data.ptr + i*centers->step);
float* s;
do
idx = cxRandNext( &rng ) % cluster_count;
while( counters->data.i[idx] != 0 );
counters->data.i[idx] = 1;
s = (float*)(samples->data.ptr + idx*samples->step);
for( j = 0; j < samples->cols; j++ )
c[j] = s[j];
}
counters->cols = cluster_count;
#else
CX_CALL( counters = cxCreateMat( 1, cluster_count, CX_32SC1 ));
// init centers
for( i = 0, k = 0; i < sample_count; i++ )
{
labels->data.i[i] = k;
k = k < cluster_count-1 ? k+1 : 0;
}
#endif
counters->cols = cluster_count; // cut down counters
max_dist = termcrit.epsilon*2;
for( iter = 0; iter < termcrit.maxIter; iter++ )
{
int i, j, k;
// computer centers
cxZero( centers );
cxZero( counters );
for( i = 0; i < sample_count; i++ )
{
float* s = (float*)(samples->data.ptr + i*samples->step);
int k = labels->data.i[i*ids_delta];
double* c = (double*)(centers->data.ptr + k*centers->step);
j = 0;
for( ; j <= dims - 4; j += 4 )
{
double t0 = c[j] + s[j];
double t1 = c[j+1] + s[j+1];
c[j] = t0;
c[j+1] = t1;
t0 = c[j+2] + s[j+2];
t1 = c[j+3] + s[j+3];
c[j+2] = t0;
c[j+3] = t1;
}
for( ; j < dims; j++ )
c[j] += s[j];
counters->data.i[k]++;
}
if( iter > 0 )
max_dist = 0;
for( k = 0; k < cluster_count; k++ )
{
double* c = (double*)(centers->data.ptr + k*centers->step);
if( counters->data.i[k] != 0 )
{
double scale = 1./counters->data.i[k];
for( j = 0; j < dims; j++ )
c[j] *= scale;
}
else
{
int i = cxRandNext( &rng ) % sample_count;
float* s = (float*)(samples->data.ptr + i*samples->step);
for( j = 0; j < dims; j++ )
c[j] = s[j];
}
if( iter > 0 )
{
double dist = 0;
double* c_o = (double*)(old_centers->data.ptr + k*old_centers->step);
for( j = 0; j < dims; j++ )
{
double t = c[j] - c_o[j];
dist += t*t;
}
if( max_dist < dist )
max_dist = dist;
}
}
// assign labels
for( i = 0; i < sample_count; i++ )
{
float* s = (float*)(samples->data.ptr + i*samples->step);
int k_best = 0;
double min_dist = DBL_MAX;
for( k = 0; k < cluster_count; k++ )
{
double* c = (double*)(centers->data.ptr + k*centers->step);
double dist = 0;
j = 0;
for( ; j <= dims - 4; j += 4 )
{
double t0 = c[j] - s[j];
double t1 = c[j+1] - s[j+1];
dist += t0*t0 + t1*t1;
t0 = c[j+2] - s[j+2];
t1 = c[j+3] - s[j+3];
dist += t0*t0 + t1*t1;
}
for( ; j < dims; j++ )
{
double t = c[j] - s[j];
dist += t*t;
}
if( min_dist > dist )
{
min_dist = dist;
k_best = k;
}
}
labels->data.i[i*ids_delta] = k_best;
}
if( max_dist < termcrit.epsilon )
break;
CX_SWAP( centers, old_centers, temp );
}
__END__;
cxReleaseMat( ¢ers );
cxReleaseMat( &old_centers );
cxReleaseMat( &counters );
}