Open Source Computer Vision Library https://opencv.org/
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#include "precomp.hpp"
#include <vector>
using namespace std;
#if !defined (HAVE_CUDA)
void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/) { throw_nogpu(); }
void cv::gpu::merge(const vector<GpuMat>& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
void cv::gpu::merge(const GpuMat* /*src*/, size_t /*count*/, GpuMat& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
void cv::gpu::merge(const vector<GpuMat>& /*src*/, GpuMat& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/) { throw_nogpu(); }
void cv::gpu::split(const GpuMat& /*src*/, vector<GpuMat>& /*dst*/) { throw_nogpu(); }
void cv::gpu::split(const GpuMat& /*src*/, GpuMat* /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
void cv::gpu::split(const GpuMat& /*src*/, vector<GpuMat>& /*dst*/, const Stream& /*stream*/) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace split_merge
{
extern "C" void merge_caller(const DevMem2D* src, DevMem2D& dst,
int total_channels, int elem_size,
const cudaStream_t& stream);
extern "C" void split_caller(const DevMem2D& src, DevMem2D* dst,
int num_channels, int elem_size1,
const cudaStream_t& stream);
void merge(const GpuMat* src, size_t n, GpuMat& dst, const cudaStream_t& stream)
{
CV_Assert(src);
CV_Assert(n > 0);
int depth = src[0].depth();
Size size = src[0].size();
bool single_channel_only = true;
int total_channels = 0;
for (size_t i = 0; i < n; ++i)
{
CV_Assert(src[i].size() == size);
CV_Assert(src[i].depth() == depth);
single_channel_only = single_channel_only && src[i].channels() == 1;
total_channels += src[i].channels();
}
CV_Assert(single_channel_only);
CV_Assert(total_channels <= 4);
if (total_channels == 1)
src[0].copyTo(dst);
else
{
dst.create(size, CV_MAKETYPE(depth, total_channels));
DevMem2D src_as_devmem[4];
for(size_t i = 0; i < n; ++i)
src_as_devmem[i] = src[i];
split_merge::merge_caller(src_as_devmem, (DevMem2D)dst,
total_channels, CV_ELEM_SIZE(depth),
stream);
}
}
void split(const GpuMat& src, GpuMat* dst, const cudaStream_t& stream)
{
CV_Assert(dst);
int depth = src.depth();
int num_channels = src.channels();
Size size = src.size();
if (num_channels == 1)
{
src.copyTo(dst[0]);
return;
}
for (int i = 0; i < num_channels; ++i)
dst[i].create(src.size(), depth);
CV_Assert(num_channels <= 4);
DevMem2D dst_as_devmem[4];
for (int i = 0; i < num_channels; ++i)
dst_as_devmem[i] = dst[i];
split_merge::split_caller((DevMem2D)src, dst_as_devmem,
num_channels, src.elemSize1(),
stream);
}
}}}
void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst)
{
split_merge::merge(src, n, dst, 0);
}
void cv::gpu::merge(const vector<GpuMat>& src, GpuMat& dst)
{
split_merge::merge(&src[0], src.size(), dst, 0);
}
void cv::gpu::merge(const GpuMat* src, size_t n, GpuMat& dst, const Stream& stream)
{
split_merge::merge(src, n, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::merge(const vector<GpuMat>& src, GpuMat& dst, const Stream& stream)
{
split_merge::merge(&src[0], src.size(), dst, StreamAccessor::getStream(stream));
}
void cv::gpu::split(const GpuMat& src, GpuMat* dst)
{
split_merge::split(src, dst, 0);
}
void cv::gpu::split(const GpuMat& src, vector<GpuMat>& dst)
{
dst.resize(src.channels());
if(src.channels() > 0)
split_merge::split(src, &dst[0], 0);
}
void cv::gpu::split(const GpuMat& src, GpuMat* dst, const Stream& stream)
{
split_merge::split(src, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::split(const GpuMat& src, vector<GpuMat>& dst, const Stream& stream)
{
dst.resize(src.channels());
if(src.channels() > 0)
split_merge::split(src, &dst[0], StreamAccessor::getStream(stream));
}
#endif /* !defined (HAVE_CUDA) */