opencv/modules/core/src/convert_c.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

138 lines
4.0 KiB
C++

// 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"
#ifndef OPENCV_EXCLUDE_C_API
CV_IMPL void
cvSplit( const void* srcarr, void* dstarr0, void* dstarr1, void* dstarr2, void* dstarr3 )
{
void* dptrs[] = { dstarr0, dstarr1, dstarr2, dstarr3 };
cv::Mat src = cv::cvarrToMat(srcarr);
int i, j, nz = 0;
for( i = 0; i < 4; i++ )
nz += dptrs[i] != 0;
CV_Assert( nz > 0 );
std::vector<cv::Mat> dvec(nz);
std::vector<int> pairs(nz*2);
for( i = j = 0; i < 4; i++ )
{
if( dptrs[i] != 0 )
{
dvec[j] = cv::cvarrToMat(dptrs[i]);
CV_Assert( dvec[j].size() == src.size() );
CV_Assert( dvec[j].depth() == src.depth() );
CV_Assert( dvec[j].channels() == 1 );
CV_Assert( i < src.channels() );
pairs[j*2] = i;
pairs[j*2+1] = j;
j++;
}
}
if( nz == src.channels() )
cv::split( src, dvec );
else
{
cv::mixChannels( &src, 1, &dvec[0], nz, &pairs[0], nz );
}
}
CV_IMPL void
cvMerge( const void* srcarr0, const void* srcarr1, const void* srcarr2,
const void* srcarr3, void* dstarr )
{
const void* sptrs[] = { srcarr0, srcarr1, srcarr2, srcarr3 };
cv::Mat dst = cv::cvarrToMat(dstarr);
int i, j, nz = 0;
for( i = 0; i < 4; i++ )
nz += sptrs[i] != 0;
CV_Assert( nz > 0 );
std::vector<cv::Mat> svec(nz);
std::vector<int> pairs(nz*2);
for( i = j = 0; i < 4; i++ )
{
if( sptrs[i] != 0 )
{
svec[j] = cv::cvarrToMat(sptrs[i]);
CV_Assert( svec[j].size == dst.size &&
svec[j].depth() == dst.depth() &&
svec[j].channels() == 1 && i < dst.channels() );
pairs[j*2] = j;
pairs[j*2+1] = i;
j++;
}
}
if( nz == dst.channels() )
cv::merge( svec, dst );
else
{
cv::mixChannels( &svec[0], nz, &dst, 1, &pairs[0], nz );
}
}
CV_IMPL void
cvMixChannels( const CvArr** src, int src_count,
CvArr** dst, int dst_count,
const int* from_to, int pair_count )
{
cv::AutoBuffer<cv::Mat> buf(src_count + dst_count);
int i;
for( i = 0; i < src_count; i++ )
buf[i] = cv::cvarrToMat(src[i]);
for( i = 0; i < dst_count; i++ )
buf[i+src_count] = cv::cvarrToMat(dst[i]);
cv::mixChannels(&buf[0], src_count, &buf[src_count], dst_count, from_to, pair_count);
}
CV_IMPL void
cvConvertScaleAbs( const void* srcarr, void* dstarr,
double scale, double shift )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size == dst.size && dst.type() == CV_8UC(src.channels()));
cv::convertScaleAbs( src, dst, scale, shift );
}
CV_IMPL void
cvConvertScale( const void* srcarr, void* dstarr,
double scale, double shift )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
CV_Assert( src.size == dst.size && src.channels() == dst.channels() );
src.convertTo(dst, dst.type(), scale, shift);
}
CV_IMPL void cvLUT( const void* srcarr, void* dstarr, const void* lutarr )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), lut = cv::cvarrToMat(lutarr);
CV_Assert( dst.size() == src.size() && dst.type() == CV_MAKETYPE(lut.depth(), src.channels()) );
cv::LUT( src, lut, dst );
}
CV_IMPL void cvNormalize( const CvArr* srcarr, CvArr* dstarr,
double a, double b, int norm_type, const CvArr* maskarr )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask;
if( maskarr )
mask = cv::cvarrToMat(maskarr);
CV_Assert( dst.size() == src.size() && src.channels() == dst.channels() );
cv::normalize( src, dst, a, b, norm_type, dst.type(), mask );
}
#endif // OPENCV_EXCLUDE_C_API