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opencv/modules/core/src/matrix_wrap.cpp
Alexander Alekhin cbfd38bd41 core: rework code locality 
- to reduce binaries size of FFmpeg Windows wrapper
- MinGW linker doesn't support -ffunction-sections (used for FFmpeg Windows wrapper)
- move code to improve locality with its used dependencies
- move UMat::dot() to matmul.dispatch.cpp (Mat::dot() is already there)
- move UMat::inv() to lapack.cpp
- move UMat::mul() to arithm.cpp
- move UMat:eye() to matrix_operations.cpp (near setIdentity() implementation)
- move normalize(): convert_scale.cpp => norm.cpp
- move convertAndUnrollScalar(): arithm.cpp => copy.cpp
- move scalarToRawData(): array.cpp => copy.cpp
- move transpose(): matrix_operations.cpp => matrix_transform.cpp
- move flip(), rotate(): copy.cpp => matrix_transform.cpp (rotate90 uses flip and transpose)
- add 'OPENCV_CORE_EXCLUDE_C_API' CMake variable to exclude compilation of C-API functions from the core module
- matrix_wrap.cpp: add compile-time checks for CUDA/OpenGL calls
- the steps above allow to reduce FFmpeg wrapper size for ~1.5Mb (initial size of OpenCV part is about 3Mb)

backport is done to improve merge experience (less conflicts)
backport of commit: 65eb946756
2021-03-02 23:24:28 +00:00

2061 lines
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencv2/core/mat.hpp"
namespace cv {
/*************************************************************************************************\
Input/Output Array
\*************************************************************************************************/
Mat _InputArray::getMat_(int i) const
{
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == MAT )
{
const Mat* m = (const Mat*)obj;
if( i < 0 )
return *m;
return m->row(i);
}
if( k == UMAT )
{
const UMat* m = (const UMat*)obj;
if( i < 0 )
return m->getMat(accessFlags);
return m->getMat(accessFlags).row(i);
}
if (k == MATX)
{
CV_Assert( i < 0 );
return Mat(sz, flags, obj);
}
if( k == STD_VECTOR )
{
CV_Assert( i < 0 );
int t = CV_MAT_TYPE(flags);
const std::vector<uchar>& v = *(const std::vector<uchar>*)obj;
return !v.empty() ? Mat(size(), t, (void*)&v[0]) : Mat();
}
if( k == STD_BOOL_VECTOR )
{
CV_Assert( i < 0 );
int t = CV_8U;
const std::vector<bool>& v = *(const std::vector<bool>*)obj;
int j, n = (int)v.size();
if( n == 0 )
return Mat();
Mat m(1, n, t);
uchar* dst = m.data;
for( j = 0; j < n; j++ )
dst[j] = (uchar)v[j];
return m;
}
if( k == NONE )
return Mat();
if( k == STD_VECTOR_VECTOR )
{
int t = type(i);
const std::vector<std::vector<uchar> >& vv = *(const std::vector<std::vector<uchar> >*)obj;
CV_Assert( 0 <= i && i < (int)vv.size() );
const std::vector<uchar>& v = vv[i];
return !v.empty() ? Mat(size(i), t, (void*)&v[0]) : Mat();
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& v = *(const std::vector<Mat>*)obj;
CV_Assert( 0 <= i && i < (int)v.size() );
return v[i];
}
if( k == STD_ARRAY_MAT )
{
const Mat* v = (const Mat*)obj;
CV_Assert( 0 <= i && i < sz.height );
return v[i];
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& v = *(const std::vector<UMat>*)obj;
CV_Assert( 0 <= i && i < (int)v.size() );
return v[i].getMat(accessFlags);
}
if( k == OPENGL_BUFFER )
{
CV_Assert( i < 0 );
CV_Error(cv::Error::StsNotImplemented, "You should explicitly call mapHost/unmapHost methods for ogl::Buffer object");
}
if( k == CUDA_GPU_MAT )
{
CV_Assert( i < 0 );
CV_Error(cv::Error::StsNotImplemented, "You should explicitly call download method for cuda::GpuMat object");
}
if( k == CUDA_HOST_MEM )
{
CV_Assert( i < 0 );
const cuda::HostMem* cuda_mem = (const cuda::HostMem*)obj;
return cuda_mem->createMatHeader();
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
UMat _InputArray::getUMat(int i) const
{
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == UMAT )
{
const UMat* m = (const UMat*)obj;
if( i < 0 )
return *m;
return m->row(i);
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& v = *(const std::vector<UMat>*)obj;
CV_Assert( 0 <= i && i < (int)v.size() );
return v[i];
}
if( k == MAT )
{
const Mat* m = (const Mat*)obj;
if( i < 0 )
return m->getUMat(accessFlags);
return m->row(i).getUMat(accessFlags);
}
return getMat(i).getUMat(accessFlags);
}
void _InputArray::getMatVector(std::vector<Mat>& mv) const
{
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == MAT )
{
const Mat& m = *(const Mat*)obj;
int n = (int)m.size[0];
mv.resize(n);
for( int i = 0; i < n; i++ )
mv[i] = m.dims == 2 ? Mat(1, m.cols, m.type(), (void*)m.ptr(i)) :
Mat(m.dims-1, &m.size[1], m.type(), (void*)m.ptr(i), &m.step[1]);
return;
}
if (k == MATX)
{
size_t n = sz.height, esz = CV_ELEM_SIZE(flags);
mv.resize(n);
for( size_t i = 0; i < n; i++ )
mv[i] = Mat(1, sz.width, CV_MAT_TYPE(flags), (uchar*)obj + esz*sz.width*i);
return;
}
if( k == STD_VECTOR )
{
const std::vector<uchar>& v = *(const std::vector<uchar>*)obj;
size_t n = size().width, esz = CV_ELEM_SIZE(flags);
int t = CV_MAT_DEPTH(flags), cn = CV_MAT_CN(flags);
mv.resize(n);
for( size_t i = 0; i < n; i++ )
mv[i] = Mat(1, cn, t, (void*)(&v[0] + esz*i));
return;
}
if( k == NONE )
{
mv.clear();
return;
}
if( k == STD_VECTOR_VECTOR )
{
const std::vector<std::vector<uchar> >& vv = *(const std::vector<std::vector<uchar> >*)obj;
int n = (int)vv.size();
int t = CV_MAT_TYPE(flags);
mv.resize(n);
for( int i = 0; i < n; i++ )
{
const std::vector<uchar>& v = vv[i];
mv[i] = Mat(size(i), t, (void*)&v[0]);
}
return;
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& v = *(const std::vector<Mat>*)obj;
size_t n = v.size();
mv.resize(n);
for( size_t i = 0; i < n; i++ )
mv[i] = v[i];
return;
}
if( k == STD_ARRAY_MAT )
{
const Mat* v = (const Mat*)obj;
size_t n = sz.height;
mv.resize(n);
for( size_t i = 0; i < n; i++ )
mv[i] = v[i];
return;
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& v = *(const std::vector<UMat>*)obj;
size_t n = v.size();
mv.resize(n);
for( size_t i = 0; i < n; i++ )
mv[i] = v[i].getMat(accessFlags);
return;
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
void _InputArray::getUMatVector(std::vector<UMat>& umv) const
{
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == NONE )
{
umv.clear();
return;
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& v = *(const std::vector<Mat>*)obj;
size_t n = v.size();
umv.resize(n);
for( size_t i = 0; i < n; i++ )
umv[i] = v[i].getUMat(accessFlags);
return;
}
if( k == STD_ARRAY_MAT )
{
const Mat* v = (const Mat*)obj;
size_t n = sz.height;
umv.resize(n);
for( size_t i = 0; i < n; i++ )
umv[i] = v[i].getUMat(accessFlags);
return;
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& v = *(const std::vector<UMat>*)obj;
size_t n = v.size();
umv.resize(n);
for( size_t i = 0; i < n; i++ )
umv[i] = v[i];
return;
}
if( k == UMAT )
{
UMat& v = *(UMat*)obj;
umv.resize(1);
umv[0] = v;
return;
}
if( k == MAT )
{
Mat& v = *(Mat*)obj;
umv.resize(1);
umv[0] = v.getUMat(accessFlags);
return;
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
cuda::GpuMat _InputArray::getGpuMat() const
{
#ifdef HAVE_CUDA
_InputArray::KindFlag k = kind();
if (k == CUDA_GPU_MAT)
{
const cuda::GpuMat* d_mat = (const cuda::GpuMat*)obj;
return *d_mat;
}
if (k == CUDA_HOST_MEM)
{
const cuda::HostMem* cuda_mem = (const cuda::HostMem*)obj;
return cuda_mem->createGpuMatHeader();
}
if (k == OPENGL_BUFFER)
{
CV_Error(cv::Error::StsNotImplemented, "You should explicitly call mapDevice/unmapDevice methods for ogl::Buffer object");
}
if (k == NONE)
return cuda::GpuMat();
CV_Error(cv::Error::StsNotImplemented, "getGpuMat is available only for cuda::GpuMat and cuda::HostMem");
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
void _InputArray::getGpuMatVector(std::vector<cuda::GpuMat>& gpumv) const
{
#ifdef HAVE_CUDA
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
gpumv = *(std::vector<cuda::GpuMat>*)obj;
}
#else
CV_UNUSED(gpumv);
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
ogl::Buffer _InputArray::getOGlBuffer() const
{
_InputArray::KindFlag k = kind();
CV_Assert(k == OPENGL_BUFFER);
const ogl::Buffer* gl_buf = (const ogl::Buffer*)obj;
return *gl_buf;
}
_InputArray::KindFlag _InputArray::kind() const
{
KindFlag k = flags & KIND_MASK;
#if CV_VERSION_MAJOR < 5
CV_DbgAssert(k != EXPR);
CV_DbgAssert(k != STD_ARRAY);
#endif
return k;
}
int _InputArray::rows(int i) const
{
return size(i).height;
}
int _InputArray::cols(int i) const
{
return size(i).width;
}
Size _InputArray::size(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert( i < 0 );
return ((const Mat*)obj)->size();
}
if( k == UMAT )
{
CV_Assert( i < 0 );
return ((const UMat*)obj)->size();
}
if (k == MATX)
{
CV_Assert( i < 0 );
return sz;
}
if( k == STD_VECTOR )
{
CV_Assert( i < 0 );
const std::vector<uchar>& v = *(const std::vector<uchar>*)obj;
const std::vector<int>& iv = *(const std::vector<int>*)obj;
size_t szb = v.size(), szi = iv.size();
return szb == szi ? Size((int)szb, 1) : Size((int)(szb/CV_ELEM_SIZE(flags)), 1);
}
if( k == STD_BOOL_VECTOR )
{
CV_Assert( i < 0 );
const std::vector<bool>& v = *(const std::vector<bool>*)obj;
return Size((int)v.size(), 1);
}
if( k == NONE )
return Size();
if( k == STD_VECTOR_VECTOR )
{
const std::vector<std::vector<uchar> >& vv = *(const std::vector<std::vector<uchar> >*)obj;
if( i < 0 )
return vv.empty() ? Size() : Size((int)vv.size(), 1);
CV_Assert( i < (int)vv.size() );
const std::vector<std::vector<int> >& ivv = *(const std::vector<std::vector<int> >*)obj;
size_t szb = vv[i].size(), szi = ivv[i].size();
return szb == szi ? Size((int)szb, 1) : Size((int)(szb/CV_ELEM_SIZE(flags)), 1);
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
if( i < 0 )
return vv.empty() ? Size() : Size((int)vv.size(), 1);
CV_Assert( i < (int)vv.size() );
return vv[i].size();
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
if( i < 0 )
return sz.height==0 ? Size() : Size(sz.height, 1);
CV_Assert( i < sz.height );
return vv[i].size();
}
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
#ifdef HAVE_CUDA
const std::vector<cuda::GpuMat>& vv = *(const std::vector<cuda::GpuMat>*)obj;
if (i < 0)
return vv.empty() ? Size() : Size((int)vv.size(), 1);
CV_Assert(i < (int)vv.size());
return vv[i].size();
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
if( i < 0 )
return vv.empty() ? Size() : Size((int)vv.size(), 1);
CV_Assert( i < (int)vv.size() );
return vv[i].size();
}
if( k == OPENGL_BUFFER )
{
CV_Assert( i < 0 );
const ogl::Buffer* buf = (const ogl::Buffer*)obj;
return buf->size();
}
if( k == CUDA_GPU_MAT )
{
CV_Assert( i < 0 );
const cuda::GpuMat* d_mat = (const cuda::GpuMat*)obj;
return d_mat->size();
}
if( k == CUDA_HOST_MEM )
{
CV_Assert( i < 0 );
const cuda::HostMem* cuda_mem = (const cuda::HostMem*)obj;
return cuda_mem->size();
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
int _InputArray::sizend(int* arrsz, int i) const
{
int j, d = 0;
_InputArray::KindFlag k = kind();
if( k == NONE )
;
else if( k == MAT )
{
CV_Assert( i < 0 );
const Mat& m = *(const Mat*)obj;
d = m.dims;
if(arrsz)
for(j = 0; j < d; j++)
arrsz[j] = m.size.p[j];
}
else if( k == UMAT )
{
CV_Assert( i < 0 );
const UMat& m = *(const UMat*)obj;
d = m.dims;
if(arrsz)
for(j = 0; j < d; j++)
arrsz[j] = m.size.p[j];
}
else if( k == STD_VECTOR_MAT && i >= 0 )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
CV_Assert( i < (int)vv.size() );
const Mat& m = vv[i];
d = m.dims;
if(arrsz)
for(j = 0; j < d; j++)
arrsz[j] = m.size.p[j];
}
else if( k == STD_ARRAY_MAT && i >= 0 )
{
const Mat* vv = (const Mat*)obj;
CV_Assert( i < sz.height );
const Mat& m = vv[i];
d = m.dims;
if(arrsz)
for(j = 0; j < d; j++)
arrsz[j] = m.size.p[j];
}
else if( k == STD_VECTOR_UMAT && i >= 0 )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
CV_Assert( i < (int)vv.size() );
const UMat& m = vv[i];
d = m.dims;
if(arrsz)
for(j = 0; j < d; j++)
arrsz[j] = m.size.p[j];
}
else
{
CV_CheckLE(dims(i), 2, "Not supported");
Size sz2d = size(i);
d = 2;
if(arrsz)
{
arrsz[0] = sz2d.height;
arrsz[1] = sz2d.width;
}
}
return d;
}
bool _InputArray::sameSize(const _InputArray& arr) const
{
_InputArray::KindFlag k1 = kind(), k2 = arr.kind();
Size sz1;
if( k1 == MAT )
{
const Mat* m = ((const Mat*)obj);
if( k2 == MAT )
return m->size == ((const Mat*)arr.obj)->size;
if( k2 == UMAT )
return m->size == ((const UMat*)arr.obj)->size;
if( m->dims > 2 )
return false;
sz1 = m->size();
}
else if( k1 == UMAT )
{
const UMat* m = ((const UMat*)obj);
if( k2 == MAT )
return m->size == ((const Mat*)arr.obj)->size;
if( k2 == UMAT )
return m->size == ((const UMat*)arr.obj)->size;
if( m->dims > 2 )
return false;
sz1 = m->size();
}
else
sz1 = size();
if( arr.dims() > 2 )
return false;
return sz1 == arr.size();
}
int _InputArray::dims(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert( i < 0 );
return ((const Mat*)obj)->dims;
}
if( k == UMAT )
{
CV_Assert( i < 0 );
return ((const UMat*)obj)->dims;
}
if (k == MATX)
{
CV_Assert( i < 0 );
return 2;
}
if( k == STD_VECTOR || k == STD_BOOL_VECTOR )
{
CV_Assert( i < 0 );
return 2;
}
if( k == NONE )
return 0;
if( k == STD_VECTOR_VECTOR )
{
const std::vector<std::vector<uchar> >& vv = *(const std::vector<std::vector<uchar> >*)obj;
if( i < 0 )
return 1;
CV_Assert( i < (int)vv.size() );
return 2;
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
if( i < 0 )
return 1;
CV_Assert( i < (int)vv.size() );
return vv[i].dims;
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
if( i < 0 )
return 1;
CV_Assert( i < sz.height );
return vv[i].dims;
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
if( i < 0 )
return 1;
CV_Assert( i < (int)vv.size() );
return vv[i].dims;
}
if( k == OPENGL_BUFFER )
{
CV_Assert( i < 0 );
return 2;
}
if( k == CUDA_GPU_MAT )
{
CV_Assert( i < 0 );
return 2;
}
if( k == CUDA_HOST_MEM )
{
CV_Assert( i < 0 );
return 2;
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
size_t _InputArray::total(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert( i < 0 );
return ((const Mat*)obj)->total();
}
if( k == UMAT )
{
CV_Assert( i < 0 );
return ((const UMat*)obj)->total();
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
if( i < 0 )
return vv.size();
CV_Assert( i < (int)vv.size() );
return vv[i].total();
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
if( i < 0 )
return sz.height;
CV_Assert( i < sz.height );
return vv[i].total();
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
if( i < 0 )
return vv.size();
CV_Assert( i < (int)vv.size() );
return vv[i].total();
}
return size(i).area();
}
int _InputArray::type(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
return ((const Mat*)obj)->type();
if( k == UMAT )
return ((const UMat*)obj)->type();
if( k == MATX || k == STD_VECTOR || k == STD_VECTOR_VECTOR || k == STD_BOOL_VECTOR )
return CV_MAT_TYPE(flags);
if( k == NONE )
return -1;
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
if( vv.empty() )
{
CV_Assert((flags & FIXED_TYPE) != 0);
return CV_MAT_TYPE(flags);
}
CV_Assert( i < (int)vv.size() );
return vv[i >= 0 ? i : 0].type();
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
if( vv.empty() )
{
CV_Assert((flags & FIXED_TYPE) != 0);
return CV_MAT_TYPE(flags);
}
CV_Assert( i < (int)vv.size() );
return vv[i >= 0 ? i : 0].type();
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
if( sz.height == 0 )
{
CV_Assert((flags & FIXED_TYPE) != 0);
return CV_MAT_TYPE(flags);
}
CV_Assert( i < sz.height );
return vv[i >= 0 ? i : 0].type();
}
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
#ifdef HAVE_CUDA
const std::vector<cuda::GpuMat>& vv = *(const std::vector<cuda::GpuMat>*)obj;
if (vv.empty())
{
CV_Assert((flags & FIXED_TYPE) != 0);
return CV_MAT_TYPE(flags);
}
CV_Assert(i < (int)vv.size());
return vv[i >= 0 ? i : 0].type();
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == OPENGL_BUFFER )
return ((const ogl::Buffer*)obj)->type();
if( k == CUDA_GPU_MAT )
return ((const cuda::GpuMat*)obj)->type();
if( k == CUDA_HOST_MEM )
return ((const cuda::HostMem*)obj)->type();
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
int _InputArray::depth(int i) const
{
return CV_MAT_DEPTH(type(i));
}
int _InputArray::channels(int i) const
{
return CV_MAT_CN(type(i));
}
bool _InputArray::empty() const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
return ((const Mat*)obj)->empty();
if( k == UMAT )
return ((const UMat*)obj)->empty();
if (k == MATX)
return false;
if( k == STD_VECTOR )
{
const std::vector<uchar>& v = *(const std::vector<uchar>*)obj;
return v.empty();
}
if( k == STD_BOOL_VECTOR )
{
const std::vector<bool>& v = *(const std::vector<bool>*)obj;
return v.empty();
}
if( k == NONE )
return true;
if( k == STD_VECTOR_VECTOR )
{
const std::vector<std::vector<uchar> >& vv = *(const std::vector<std::vector<uchar> >*)obj;
return vv.empty();
}
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
return vv.empty();
}
if( k == STD_ARRAY_MAT )
{
return sz.height == 0;
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
return vv.empty();
}
if( k == OPENGL_BUFFER )
return ((const ogl::Buffer*)obj)->empty();
if( k == CUDA_GPU_MAT )
return ((const cuda::GpuMat*)obj)->empty();
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
const std::vector<cuda::GpuMat>& vv = *(const std::vector<cuda::GpuMat>*)obj;
return vv.empty();
}
if( k == CUDA_HOST_MEM )
return ((const cuda::HostMem*)obj)->empty();
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
bool _InputArray::isContinuous(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
return i < 0 ? ((const Mat*)obj)->isContinuous() : true;
if( k == UMAT )
return i < 0 ? ((const UMat*)obj)->isContinuous() : true;
if( k == MATX || k == STD_VECTOR ||
k == NONE || k == STD_VECTOR_VECTOR || k == STD_BOOL_VECTOR )
return true;
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].isContinuous();
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
CV_Assert(i >= 0 && i < sz.height);
return vv[i].isContinuous();
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].isContinuous();
}
if( k == CUDA_GPU_MAT )
return i < 0 ? ((const cuda::GpuMat*)obj)->isContinuous() : true;
CV_Error(CV_StsNotImplemented, "Unknown/unsupported array type");
}
bool _InputArray::isSubmatrix(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
return i < 0 ? ((const Mat*)obj)->isSubmatrix() : false;
if( k == UMAT )
return i < 0 ? ((const UMat*)obj)->isSubmatrix() : false;
if( k == MATX || k == STD_VECTOR ||
k == NONE || k == STD_VECTOR_VECTOR || k == STD_BOOL_VECTOR )
return false;
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].isSubmatrix();
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
CV_Assert(i >= 0 && i < sz.height);
return vv[i].isSubmatrix();
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].isSubmatrix();
}
CV_Error(CV_StsNotImplemented, "");
}
size_t _InputArray::offset(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert( i < 0 );
const Mat * const m = ((const Mat*)obj);
return (size_t)(m->ptr() - m->datastart);
}
if( k == UMAT )
{
CV_Assert( i < 0 );
return ((const UMat*)obj)->offset;
}
if( k == MATX || k == STD_VECTOR ||
k == NONE || k == STD_VECTOR_VECTOR || k == STD_BOOL_VECTOR )
return 0;
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
CV_Assert( i >= 0 && i < (int)vv.size() );
return (size_t)(vv[i].ptr() - vv[i].datastart);
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
CV_Assert( i >= 0 && i < sz.height );
return (size_t)(vv[i].ptr() - vv[i].datastart);
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].offset;
}
if( k == CUDA_GPU_MAT )
{
CV_Assert( i < 0 );
const cuda::GpuMat * const m = ((const cuda::GpuMat*)obj);
return (size_t)(m->data - m->datastart);
}
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
const std::vector<cuda::GpuMat>& vv = *(const std::vector<cuda::GpuMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return (size_t)(vv[i].data - vv[i].datastart);
}
CV_Error(Error::StsNotImplemented, "");
}
size_t _InputArray::step(int i) const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert( i < 0 );
return ((const Mat*)obj)->step;
}
if( k == UMAT )
{
CV_Assert( i < 0 );
return ((const UMat*)obj)->step;
}
if( k == MATX || k == STD_VECTOR ||
k == NONE || k == STD_VECTOR_VECTOR || k == STD_BOOL_VECTOR )
return 0;
if( k == STD_VECTOR_MAT )
{
const std::vector<Mat>& vv = *(const std::vector<Mat>*)obj;
CV_Assert( i >= 0 && i < (int)vv.size() );
return vv[i].step;
}
if( k == STD_ARRAY_MAT )
{
const Mat* vv = (const Mat*)obj;
CV_Assert( i >= 0 && i < sz.height );
return vv[i].step;
}
if( k == STD_VECTOR_UMAT )
{
const std::vector<UMat>& vv = *(const std::vector<UMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].step;
}
if( k == CUDA_GPU_MAT )
{
CV_Assert( i < 0 );
return ((const cuda::GpuMat*)obj)->step;
}
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
const std::vector<cuda::GpuMat>& vv = *(const std::vector<cuda::GpuMat>*)obj;
CV_Assert(i >= 0 && (size_t)i < vv.size());
return vv[i].step;
}
CV_Error(Error::StsNotImplemented, "");
}
void _InputArray::copyTo(const _OutputArray& arr) const
{
_InputArray::KindFlag k = kind();
if( k == NONE )
arr.release();
else if( k == MAT || k == MATX || k == STD_VECTOR || k == STD_BOOL_VECTOR )
{
Mat m = getMat();
m.copyTo(arr);
}
else if( k == UMAT )
((UMat*)obj)->copyTo(arr);
#ifdef HAVE_CUDA
else if (k == CUDA_GPU_MAT)
((cuda::GpuMat*)obj)->copyTo(arr);
#endif
else
CV_Error(Error::StsNotImplemented, "");
}
void _InputArray::copyTo(const _OutputArray& arr, const _InputArray & mask) const
{
_InputArray::KindFlag k = kind();
if( k == NONE )
arr.release();
else if( k == MAT || k == MATX || k == STD_VECTOR || k == STD_BOOL_VECTOR )
{
Mat m = getMat();
m.copyTo(arr, mask);
}
else if( k == UMAT )
((UMat*)obj)->copyTo(arr, mask);
#ifdef HAVE_CUDA
else if (k == CUDA_GPU_MAT)
((cuda::GpuMat*)obj)->copyTo(arr, mask);
#endif
else
CV_Error(Error::StsNotImplemented, "");
}
bool _OutputArray::fixedSize() const
{
return (flags & FIXED_SIZE) == FIXED_SIZE;
}
bool _OutputArray::fixedType() const
{
return (flags & FIXED_TYPE) == FIXED_TYPE;
}
void _OutputArray::create(Size _sz, int mtype, int i, bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
_InputArray::KindFlag k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == _sz);
CV_Assert(!fixedType() || ((Mat*)obj)->type() == mtype);
((Mat*)obj)->create(_sz, mtype);
return;
}
if( k == UMAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((UMat*)obj)->size.operator()() == _sz);
CV_Assert(!fixedType() || ((UMat*)obj)->type() == mtype);
((UMat*)obj)->create(_sz, mtype);
return;
}
if( k == CUDA_GPU_MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((cuda::GpuMat*)obj)->size() == _sz);
CV_Assert(!fixedType() || ((cuda::GpuMat*)obj)->type() == mtype);
#ifdef HAVE_CUDA
((cuda::GpuMat*)obj)->create(_sz, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == OPENGL_BUFFER && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((ogl::Buffer*)obj)->size() == _sz);
CV_Assert(!fixedType() || ((ogl::Buffer*)obj)->type() == mtype);
#ifdef HAVE_OPENGL
((ogl::Buffer*)obj)->create(_sz, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "OpenGL support is not enabled in this OpenCV build (missing HAVE_OPENGL)");
#endif
}
if( k == CUDA_HOST_MEM && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((cuda::HostMem*)obj)->size() == _sz);
CV_Assert(!fixedType() || ((cuda::HostMem*)obj)->type() == mtype);
#ifdef HAVE_CUDA
((cuda::HostMem*)obj)->create(_sz, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
int sizes[] = {_sz.height, _sz.width};
create(2, sizes, mtype, i, allowTransposed, fixedDepthMask);
}
void _OutputArray::create(int _rows, int _cols, int mtype, int i, bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
_InputArray::KindFlag k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == Size(_cols, _rows));
CV_Assert(!fixedType() || ((Mat*)obj)->type() == mtype);
((Mat*)obj)->create(_rows, _cols, mtype);
return;
}
if( k == UMAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((UMat*)obj)->size.operator()() == Size(_cols, _rows));
CV_Assert(!fixedType() || ((UMat*)obj)->type() == mtype);
((UMat*)obj)->create(_rows, _cols, mtype);
return;
}
if( k == CUDA_GPU_MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((cuda::GpuMat*)obj)->size() == Size(_cols, _rows));
CV_Assert(!fixedType() || ((cuda::GpuMat*)obj)->type() == mtype);
#ifdef HAVE_CUDA
((cuda::GpuMat*)obj)->create(_rows, _cols, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == OPENGL_BUFFER && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((ogl::Buffer*)obj)->size() == Size(_cols, _rows));
CV_Assert(!fixedType() || ((ogl::Buffer*)obj)->type() == mtype);
#ifdef HAVE_OPENGL
((ogl::Buffer*)obj)->create(_rows, _cols, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "OpenGL support is not enabled in this OpenCV build (missing HAVE_OPENGL)");
#endif
}
if( k == CUDA_HOST_MEM && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((cuda::HostMem*)obj)->size() == Size(_cols, _rows));
CV_Assert(!fixedType() || ((cuda::HostMem*)obj)->type() == mtype);
#ifdef HAVE_CUDA
((cuda::HostMem*)obj)->create(_rows, _cols, mtype);
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
int sizes[] = {_rows, _cols};
create(2, sizes, mtype, i, allowTransposed, fixedDepthMask);
}
void _OutputArray::create(int d, const int* sizes, int mtype, int i,
bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
int sizebuf[2];
if(d == 1)
{
d = 2;
sizebuf[0] = sizes[0];
sizebuf[1] = 1;
sizes = sizebuf;
}
_InputArray::KindFlag k = kind();
mtype = CV_MAT_TYPE(mtype);
if( k == MAT )
{
CV_Assert( i < 0 );
Mat& m = *(Mat*)obj;
CV_Assert(!(m.empty() && fixedType() && fixedSize()) && "Can't reallocate empty Mat with locked layout (probably due to misused 'const' modifier)");
if (allowTransposed && !m.empty() &&
d == 2 && m.dims == 2 &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] &&
m.isContinuous())
{
return;
}
if(fixedType())
{
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_CheckTypeEQ(m.type(), CV_MAT_TYPE(mtype), "Can't reallocate Mat with locked type (probably due to misused 'const' modifier)");
}
if(fixedSize())
{
CV_CheckEQ(m.dims, d, "Can't reallocate Mat with locked size (probably due to misused 'const' modifier)");
for(int j = 0; j < d; ++j)
CV_CheckEQ(m.size[j], sizes[j], "Can't reallocate Mat with locked size (probably due to misused 'const' modifier)");
}
m.create(d, sizes, mtype);
return;
}
if( k == UMAT )
{
CV_Assert( i < 0 );
UMat& m = *(UMat*)obj;
CV_Assert(!(m.empty() && fixedType() && fixedSize()) && "Can't reallocate empty UMat with locked layout (probably due to misused 'const' modifier)");
if (allowTransposed && !m.empty() &&
d == 2 && m.dims == 2 &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] &&
m.isContinuous())
{
return;
}
if(fixedType())
{
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_CheckTypeEQ(m.type(), CV_MAT_TYPE(mtype), "Can't reallocate UMat with locked type (probably due to misused 'const' modifier)");
}
if(fixedSize())
{
CV_CheckEQ(m.dims, d, "Can't reallocate UMat with locked size (probably due to misused 'const' modifier)");
for(int j = 0; j < d; ++j)
CV_CheckEQ(m.size[j], sizes[j], "Can't reallocate UMat with locked size (probably due to misused 'const' modifier)");
}
m.create(d, sizes, mtype);
return;
}
if( k == MATX )
{
CV_Assert( i < 0 );
int type0 = CV_MAT_TYPE(flags);
CV_Assert( mtype == type0 || (CV_MAT_CN(mtype) == 1 && ((1 << type0) & fixedDepthMask) != 0) );
CV_CheckLE(d, 2, "");
Size requested_size(d == 2 ? sizes[1] : 1, d >= 1 ? sizes[0] : 1);
if (sz.width == 1 || sz.height == 1)
{
// NB: 1D arrays assume allowTransposed=true (see #4159)
int total_1d = std::max(sz.width, sz.height);
CV_Check(requested_size, std::max(requested_size.width, requested_size.height) == total_1d, "");
}
else
{
if (!allowTransposed)
{
CV_CheckEQ(requested_size, sz, "");
}
else
{
CV_Check(requested_size,
(requested_size == sz || (requested_size.height == sz.width && requested_size.width == sz.height)),
"");
}
}
return;
}
if( k == STD_VECTOR || k == STD_VECTOR_VECTOR )
{
CV_Assert( d == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0;
std::vector<uchar>* v = (std::vector<uchar>*)obj;
if( k == STD_VECTOR_VECTOR )
{
std::vector<std::vector<uchar> >& vv = *(std::vector<std::vector<uchar> >*)obj;
if( i < 0 )
{
CV_Assert(!fixedSize() || len == vv.size());
vv.resize(len);
return;
}
CV_Assert( i < (int)vv.size() );
v = &vv[i];
}
else
CV_Assert( i < 0 );
int type0 = CV_MAT_TYPE(flags);
CV_Assert( mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0) );
int esz = CV_ELEM_SIZE(type0);
CV_Assert(!fixedSize() || len == ((std::vector<uchar>*)v)->size() / esz);
switch( esz )
{
case 1:
((std::vector<uchar>*)v)->resize(len);
break;
case 2:
((std::vector<Vec2b>*)v)->resize(len);
break;
case 3:
((std::vector<Vec3b>*)v)->resize(len);
break;
case 4:
((std::vector<int>*)v)->resize(len);
break;
case 6:
((std::vector<Vec3s>*)v)->resize(len);
break;
case 8:
((std::vector<Vec2i>*)v)->resize(len);
break;
case 12:
((std::vector<Vec3i>*)v)->resize(len);
break;
case 16:
((std::vector<Vec4i>*)v)->resize(len);
break;
case 20:
((std::vector<Vec<int, 5> >*)v)->resize(len);
break;
case 24:
((std::vector<Vec6i>*)v)->resize(len);
break;
case 28:
((std::vector<Vec<int, 7> >*)v)->resize(len);
break;
case 32:
((std::vector<Vec8i>*)v)->resize(len);
break;
case 36:
((std::vector<Vec<int, 9> >*)v)->resize(len);
break;
case 40:
((std::vector<Vec<int, 10> >*)v)->resize(len);
break;
case 44:
((std::vector<Vec<int, 11> >*)v)->resize(len);
break;
case 48:
((std::vector<Vec<int, 12> >*)v)->resize(len);
break;
case 52:
((std::vector<Vec<int, 13> >*)v)->resize(len);
break;
case 56:
((std::vector<Vec<int, 14> >*)v)->resize(len);
break;
case 60:
((std::vector<Vec<int, 15> >*)v)->resize(len);
break;
case 64:
((std::vector<Vec<int, 16> >*)v)->resize(len);
break;
case 128:
((std::vector<Vec<int, 32> >*)v)->resize(len);
break;
case 256:
((std::vector<Vec<int, 64> >*)v)->resize(len);
break;
case 512:
((std::vector<Vec<int, 128> >*)v)->resize(len);
break;
default:
CV_Error_(CV_StsBadArg, ("Vectors with element size %d are not supported. Please, modify OutputArray::create()\n", esz));
}
return;
}
if( k == NONE )
{
CV_Error(CV_StsNullPtr, "create() called for the missing output array" );
}
if( k == STD_VECTOR_MAT )
{
std::vector<Mat>& v = *(std::vector<Mat>*)obj;
if( i < 0 )
{
CV_Assert( d == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0, len0 = v.size();
CV_Assert(!fixedSize() || len == len0);
v.resize(len);
if( fixedType() )
{
int _type = CV_MAT_TYPE(flags);
for( size_t j = len0; j < len; j++ )
{
if( v[j].type() == _type )
continue;
CV_Assert( v[j].empty() );
v[j].flags = (v[j].flags & ~CV_MAT_TYPE_MASK) | _type;
}
}
return;
}
CV_Assert( i < (int)v.size() );
Mat& m = v[i];
if( allowTransposed )
{
if( !m.isContinuous() )
{
CV_Assert(!fixedType() && !fixedSize());
m.release();
}
if( d == 2 && m.dims == 2 && m.data &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
if(fixedType())
{
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
}
if(fixedSize())
{
CV_Assert(m.dims == d);
for(int j = 0; j < d; ++j)
CV_Assert(m.size[j] == sizes[j]);
}
m.create(d, sizes, mtype);
return;
}
if( k == STD_ARRAY_MAT )
{
Mat* v = (Mat*)obj;
if( i < 0 )
{
CV_Assert( d == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0, len0 = sz.height;
CV_Assert(len == len0);
if( fixedType() )
{
int _type = CV_MAT_TYPE(flags);
for( size_t j = len0; j < len; j++ )
{
if( v[j].type() == _type )
continue;
CV_Assert( v[j].empty() );
v[j].flags = (v[j].flags & ~CV_MAT_TYPE_MASK) | _type;
}
}
return;
}
CV_Assert( i < sz.height );
Mat& m = v[i];
if( allowTransposed )
{
if( !m.isContinuous() )
{
CV_Assert(!fixedType() && !fixedSize());
m.release();
}
if( d == 2 && m.dims == 2 && m.data &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
if(fixedType())
{
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
}
if(fixedSize())
{
CV_Assert(m.dims == d);
for(int j = 0; j < d; ++j)
CV_Assert(m.size[j] == sizes[j]);
}
m.create(d, sizes, mtype);
return;
}
if( k == STD_VECTOR_UMAT )
{
std::vector<UMat>& v = *(std::vector<UMat>*)obj;
if( i < 0 )
{
CV_Assert( d == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) );
size_t len = sizes[0]*sizes[1] > 0 ? sizes[0] + sizes[1] - 1 : 0, len0 = v.size();
CV_Assert(!fixedSize() || len == len0);
v.resize(len);
if( fixedType() )
{
int _type = CV_MAT_TYPE(flags);
for( size_t j = len0; j < len; j++ )
{
if( v[j].type() == _type )
continue;
CV_Assert( v[j].empty() );
v[j].flags = (v[j].flags & ~CV_MAT_TYPE_MASK) | _type;
}
}
return;
}
CV_Assert( i < (int)v.size() );
UMat& m = v[i];
if( allowTransposed )
{
if( !m.isContinuous() )
{
CV_Assert(!fixedType() && !fixedSize());
m.release();
}
if( d == 2 && m.dims == 2 && m.u &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
if(fixedType())
{
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
}
if(fixedSize())
{
CV_Assert(m.dims == d);
for(int j = 0; j < d; ++j)
CV_Assert(m.size[j] == sizes[j]);
}
m.create(d, sizes, mtype);
return;
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
void _OutputArray::createSameSize(const _InputArray& arr, int mtype) const
{
int arrsz[CV_MAX_DIM], d = arr.sizend(arrsz);
create(d, arrsz, mtype);
}
void _OutputArray::release() const
{
CV_Assert(!fixedSize());
_InputArray::KindFlag k = kind();
if( k == MAT )
{
((Mat*)obj)->release();
return;
}
if( k == UMAT )
{
((UMat*)obj)->release();
return;
}
if( k == CUDA_GPU_MAT )
{
#ifdef HAVE_CUDA
((cuda::GpuMat*)obj)->release();
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == CUDA_HOST_MEM )
{
#ifdef HAVE_CUDA
((cuda::HostMem*)obj)->release();
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
if( k == OPENGL_BUFFER )
{
#ifdef HAVE_OPENGL
((ogl::Buffer*)obj)->release();
return;
#else
CV_Error(Error::StsNotImplemented, "OpenGL support is not enabled in this OpenCV build (missing HAVE_OPENGL)");
#endif
}
if( k == NONE )
return;
if( k == STD_VECTOR )
{
create(Size(), CV_MAT_TYPE(flags));
return;
}
if( k == STD_VECTOR_VECTOR )
{
((std::vector<std::vector<uchar> >*)obj)->clear();
return;
}
if( k == STD_VECTOR_MAT )
{
((std::vector<Mat>*)obj)->clear();
return;
}
if( k == STD_VECTOR_UMAT )
{
((std::vector<UMat>*)obj)->clear();
return;
}
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
#ifdef HAVE_CUDA
((std::vector<cuda::GpuMat>*)obj)->clear();
return;
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
}
void _OutputArray::clear() const
{
_InputArray::KindFlag k = kind();
if( k == MAT )
{
CV_Assert(!fixedSize());
((Mat*)obj)->resize(0);
return;
}
release();
}
bool _OutputArray::needed() const
{
return kind() != NONE;
}
Mat& _OutputArray::getMatRef(int i) const
{
_InputArray::KindFlag k = kind();
if( i < 0 )
{
CV_Assert( k == MAT );
return *(Mat*)obj;
}
CV_Assert( k == STD_VECTOR_MAT || k == STD_ARRAY_MAT );
if( k == STD_VECTOR_MAT )
{
std::vector<Mat>& v = *(std::vector<Mat>*)obj;
CV_Assert( i < (int)v.size() );
return v[i];
}
else
{
Mat* v = (Mat*)obj;
CV_Assert( 0 <= i && i < sz.height );
return v[i];
}
}
UMat& _OutputArray::getUMatRef(int i) const
{
_InputArray::KindFlag k = kind();
if( i < 0 )
{
CV_Assert( k == UMAT );
return *(UMat*)obj;
}
else
{
CV_Assert( k == STD_VECTOR_UMAT );
std::vector<UMat>& v = *(std::vector<UMat>*)obj;
CV_Assert( i < (int)v.size() );
return v[i];
}
}
cuda::GpuMat& _OutputArray::getGpuMatRef() const
{
_InputArray::KindFlag k = kind();
CV_Assert( k == CUDA_GPU_MAT );
return *(cuda::GpuMat*)obj;
}
std::vector<cuda::GpuMat>& _OutputArray::getGpuMatVecRef() const
{
_InputArray::KindFlag k = kind();
CV_Assert(k == STD_VECTOR_CUDA_GPU_MAT);
return *(std::vector<cuda::GpuMat>*)obj;
}
ogl::Buffer& _OutputArray::getOGlBufferRef() const
{
_InputArray::KindFlag k = kind();
CV_Assert( k == OPENGL_BUFFER );
return *(ogl::Buffer*)obj;
}
cuda::HostMem& _OutputArray::getHostMemRef() const
{
_InputArray::KindFlag k = kind();
CV_Assert( k == CUDA_HOST_MEM );
return *(cuda::HostMem*)obj;
}
void _OutputArray::setTo(const _InputArray& arr, const _InputArray & mask) const
{
_InputArray::KindFlag k = kind();
if( k == NONE )
;
else if (k == MAT || k == MATX || k == STD_VECTOR)
{
Mat m = getMat();
m.setTo(arr, mask);
}
else if( k == UMAT )
((UMat*)obj)->setTo(arr, mask);
else if( k == CUDA_GPU_MAT )
{
#ifdef HAVE_CUDA
Mat value = arr.getMat();
CV_Assert( checkScalar(value, type(), arr.kind(), _InputArray::CUDA_GPU_MAT) );
((cuda::GpuMat*)obj)->setTo(Scalar(Vec<double, 4>(value.ptr<double>())), mask);
#else
CV_Error(Error::StsNotImplemented, "CUDA support is not enabled in this OpenCV build (missing HAVE_CUDA)");
#endif
}
else
CV_Error(Error::StsNotImplemented, "");
}
void _OutputArray::assign(const UMat& u) const
{
_InputArray::KindFlag k = kind();
if (k == UMAT)
{
*(UMat*)obj = u;
}
else if (k == MAT)
{
u.copyTo(*(Mat*)obj); // TODO check u.getMat()
}
else if (k == MATX)
{
u.copyTo(getMat()); // TODO check u.getMat()
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
void _OutputArray::assign(const Mat& m) const
{
_InputArray::KindFlag k = kind();
if (k == UMAT)
{
m.copyTo(*(UMat*)obj); // TODO check m.getUMat()
}
else if (k == MAT)
{
*(Mat*)obj = m;
}
else if (k == MATX)
{
m.copyTo(getMat());
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
void _OutputArray::move(UMat& u) const
{
if (fixedSize())
{
// TODO Performance warning
assign(u);
return;
}
int k = kind();
if (k == UMAT)
{
#ifdef CV_CXX11
*(UMat*)obj = std::move(u);
#else
*(UMat*)obj = u;
u.release();
#endif
}
else if (k == MAT)
{
u.copyTo(*(Mat*)obj); // TODO check u.getMat()
u.release();
}
else if (k == MATX)
{
u.copyTo(getMat()); // TODO check u.getMat()
u.release();
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
void _OutputArray::move(Mat& m) const
{
if (fixedSize())
{
// TODO Performance warning
assign(m);
return;
}
int k = kind();
if (k == UMAT)
{
m.copyTo(*(UMat*)obj); // TODO check m.getUMat()
m.release();
}
else if (k == MAT)
{
#ifdef CV_CXX11
*(Mat*)obj = std::move(m);
#else
*(Mat*)obj = m;
m.release();
#endif
}
else if (k == MATX)
{
m.copyTo(getMat());
m.release();
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
void _OutputArray::assign(const std::vector<UMat>& v) const
{
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_UMAT)
{
std::vector<UMat>& this_v = *(std::vector<UMat>*)obj;
CV_Assert(this_v.size() == v.size());
for (size_t i = 0; i < v.size(); i++)
{
const UMat& m = v[i];
UMat& this_m = this_v[i];
if (this_m.u != NULL && this_m.u == m.u)
continue; // same object (see dnn::Layer::forward_fallback)
m.copyTo(this_m);
}
}
else if (k == STD_VECTOR_MAT)
{
std::vector<Mat>& this_v = *(std::vector<Mat>*)obj;
CV_Assert(this_v.size() == v.size());
for (size_t i = 0; i < v.size(); i++)
{
const UMat& m = v[i];
Mat& this_m = this_v[i];
if (this_m.u != NULL && this_m.u == m.u)
continue; // same object (see dnn::Layer::forward_fallback)
m.copyTo(this_m);
}
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
void _OutputArray::assign(const std::vector<Mat>& v) const
{
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_UMAT)
{
std::vector<UMat>& this_v = *(std::vector<UMat>*)obj;
CV_Assert(this_v.size() == v.size());
for (size_t i = 0; i < v.size(); i++)
{
const Mat& m = v[i];
UMat& this_m = this_v[i];
if (this_m.u != NULL && this_m.u == m.u)
continue; // same object (see dnn::Layer::forward_fallback)
m.copyTo(this_m);
}
}
else if (k == STD_VECTOR_MAT)
{
std::vector<Mat>& this_v = *(std::vector<Mat>*)obj;
CV_Assert(this_v.size() == v.size());
for (size_t i = 0; i < v.size(); i++)
{
const Mat& m = v[i];
Mat& this_m = this_v[i];
if (this_m.u != NULL && this_m.u == m.u)
continue; // same object (see dnn::Layer::forward_fallback)
m.copyTo(this_m);
}
}
else
{
CV_Error(Error::StsNotImplemented, "");
}
}
static _InputOutputArray _none;
InputOutputArray noArray() { return _none; }
} // cv::
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