\r
if (TBB_FOUND)\r
set(HAVE_TBB 1)\r
- if(NOT "${TBB_INCLUDE_DIRS}" STREQUAL "")\r
- include_directories("${TBB_INCLUDE_DIRS}")\r
+ if(NOT ${TBB_INCLUDE_DIRS} STREQUAL "")\r
+ include_directories(${TBB_INCLUDE_DIRS})\r
endif()\r
- link_directories("${TBB_LIBRARY_DIRS}")\r
+ link_directories(${TBB_LIBRARY_DIRS})\r
set(OPENCV_LINKER_LIBS ${OPENCV_LINKER_LIBS} ${TBB_LIBRARIES})\r
else()\r
set(TBB_DEFAULT_INCLUDE_DIRS\r
AutoBuffer<double> buffer(nb);
CV_Assert( u.data && vt.data && w.data );
- if( rhs.data )
- CV_Assert( rhs.type() == type && rhs.rows == m );
+ CV_Assert( rhs.data == 0 || (rhs.type() == type && rhs.rows == m) );
dst.create( n, nb, type );
if( type == CV_32F )
{
Mat mat = cvarrToMat(arr, false, true, 1);
ch.create(mat.dims, mat.size, mat.depth());
- if(coi < 0)
- CV_Assert( CV_IS_IMAGE(arr) && (coi = cvGetImageCOI((const IplImage*)arr)-1) >= 0 );
+ if(coi < 0)
+ {
+ CV_Assert( CV_IS_IMAGE(arr) );
+ coi = cvGetImageCOI((const IplImage*)arr)-1;
+ }
CV_Assert(0 <= coi && coi < mat.channels());
int _pairs[] = { coi, 0 };
mixChannels( &mat, 1, &ch, 1, _pairs, 1 );
void insertImageCOI(const Mat& ch, CvArr* arr, int coi)
{
Mat mat = cvarrToMat(arr, false, true, 1);
- if(coi < 0)
- CV_Assert( CV_IS_IMAGE(arr) && (coi = cvGetImageCOI((const IplImage*)arr)-1) >= 0 );
+ if(coi < 0)
+ {
+ CV_Assert( CV_IS_IMAGE(arr) );
+ coi = cvGetImageCOI((const IplImage*)arr)-1;
+ }
CV_Assert(ch.size == mat.size && ch.depth() == mat.depth() && 0 <= coi && coi < mat.channels());
int _pairs[] = { 0, coi };
mixChannels( &ch, 1, &mat, 1, _pairs, 1 );
{
CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
- if( mask.data )
- CV_Assert( mask.type() == CV_8UC1 && mask.size() == image.size() );
+ CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) );
Mat eig, tmp;
if( useHarrisDetector )
Size& imsize, vector<double>& uniranges )
{
int i, j, c;
- if(!channels)
- CV_Assert( nimages == dims );
+ CV_Assert( channels != 0 || nimages == dims );
imsize = images[0].size();
int depth = images[0].depth(), esz1 = (int)images[0].elemSize1();
{
if(!(_results->data && (_results->type() == CV_32F ||
(_results->type() == CV_32S && regression)) &&
- (_results->cols == 1 || _results->rows == 1) ||
+ (_results->cols == 1 || _results->rows == 1) &&
_results->cols + _results->rows - 1 == _samples.rows) )
_results->create(_samples.rows, 1, CV_32F);
presults = &(results = *_results);
void allocate(int dims, const int* sizes, int type, int*& refcount,
uchar*& datastart, uchar*& data, size_t* step)
{
- static int ncalls = 0;
-
int depth = CV_MAT_DEPTH(type);
int cn = CV_MAT_CN(type);
const int f = (int)(sizeof(size_t)/8);
void deallocate(int* refcount, uchar* datastart, uchar* data)
{
- static int ncalls = 0;
-
if( !refcount )
return;
PyObject* o = pyObjectFromRefcount(refcount);
static int pyopencv_to(const PyObject* o, Mat& m, const char* name = "<unknown>", bool allowND=true)
{
- static int call_idx = 0;
-
if(!o || o == Py_None)
{
if( !m.data )