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refactoring: moved gpu reduction-based functions into separated file

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This commit is contained in:
Alexey Spizhevoy
2010-12-20 09:51:25 +00:00
parent 1922e50f19
commit df8529377b
7 changed files with 2377 additions and 2260 deletions
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508
modules/gpu/src/arithm.cpp
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@@ -49,20 +49,7 @@ using namespace std;
#if !defined (HAVE_CUDA)
void cv::gpu::transpose(const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); }
double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sqrSum(const GpuMat&) { throw_nogpu(); return Scalar(); }
Scalar cv::gpu::sqrSum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_nogpu(); }
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_nogpu(); }
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
int cv::gpu::countNonZero(const GpuMat&) { throw_nogpu(); return 0; }
int cv::gpu::countNonZero(const GpuMat&, GpuMat&) { throw_nogpu(); return 0; }
void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::exp(const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::log(const GpuMat&, GpuMat&) { throw_nogpu(); }
@@ -78,14 +65,6 @@ void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool)
void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool) { throw_nogpu(); }
void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
void cv::gpu::min(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
@@ -118,54 +97,6 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
}
}
////////////////////////////////////////////////////////////////////////
// meanStdDev
void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
{
CV_Assert(src.type() == CV_8UC1);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, mean.val, stddev.val) );
}
////////////////////////////////////////////////////////////////////////
// norm
double cv::gpu::norm(const GpuMat& src1, int normType)
{
return norm(src1, GpuMat(src1.size(), src1.type(), Scalar::all(0.0)), normType);
}
double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
{
CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(src1.type() == CV_8UC1);
CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2);
typedef NppStatus (*npp_norm_diff_func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2,
NppiSize oSizeROI, Npp64f* pRetVal);
static const npp_norm_diff_func_t npp_norm_diff_func[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
NppiSize sz;
sz.width = src1.cols;
sz.height = src1.rows;
int funcIdx = normType >> 1;
double retVal;
nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step,
src2.ptr<Npp8u>(), src2.step,
sz, &retVal) );
return retVal;
}
////////////////////////////////////////////////////////////////////////
// flip
@@ -193,305 +124,6 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
}
}
////////////////////////////////////////////////////////////////////////
// sum
namespace cv { namespace gpu { namespace mathfunc
{
template <typename T>
void sum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
template <typename T>
void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
template <typename T>
void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
template <typename T>
void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
namespace sum
{
void get_buf_size_required(int cols, int rows, int cn, int& bufcols, int& bufrows);
}
}}}
Scalar cv::gpu::sum(const GpuMat& src)
{
GpuMat buf;
return sum(src, buf);
}
Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
{
using namespace mathfunc;
typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
static const Caller callers[2][7] =
{ { sum_multipass_caller<unsigned char>, sum_multipass_caller<char>,
sum_multipass_caller<unsigned short>, sum_multipass_caller<short>,
sum_multipass_caller<int>, sum_multipass_caller<float>, 0 },
{ sum_caller<unsigned char>, sum_caller<char>,
sum_caller<unsigned short>, sum_caller<short>,
sum_caller<int>, sum_caller<float>, 0 } };
Size bufSize;
sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
buf.create(bufSize, CV_8U);
Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
if (!caller) CV_Error(CV_StsBadArg, "sum: unsupported type");
double result[4];
caller(src, buf, result, src.channels());
return Scalar(result[0], result[1], result[2], result[3]);
}
Scalar cv::gpu::sqrSum(const GpuMat& src)
{
GpuMat buf;
return sqrSum(src, buf);
}
Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
{
using namespace mathfunc;
typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
static const Caller callers[2][7] =
{ { sqsum_multipass_caller<unsigned char>, sqsum_multipass_caller<char>,
sqsum_multipass_caller<unsigned short>, sqsum_multipass_caller<short>,
sqsum_multipass_caller<int>, sqsum_multipass_caller<float>, 0 },
{ sqsum_caller<unsigned char>, sqsum_caller<char>,
sqsum_caller<unsigned short>, sqsum_caller<short>,
sqsum_caller<int>, sqsum_caller<float>, 0 } };
Size bufSize;
sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
buf.create(bufSize, CV_8U);
Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
if (!caller) CV_Error(CV_StsBadArg, "sqrSum: unsupported type");
double result[4];
caller(src, buf, result, src.channels());
return Scalar(result[0], result[1], result[2], result[3]);
}
////////////////////////////////////////////////////////////////////////
// minMax
namespace cv { namespace gpu { namespace mathfunc { namespace minmax {
void get_buf_size_required(int cols, int rows, int elem_size, int& bufcols, int& bufrows);
template <typename T>
void min_max_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
template <typename T>
void min_max_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
template <typename T>
void min_max_multipass_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
template <typename T>
void min_max_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
}}}}
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask)
{
GpuMat buf;
minMax(src, minVal, maxVal, mask, buf);
}
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
{
using namespace mathfunc::minmax;
typedef void (*Caller)(const DevMem2D, double*, double*, PtrStep);
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, PtrStep);
static const Caller callers[2][7] =
{ { min_max_multipass_caller<unsigned char>, min_max_multipass_caller<char>,
min_max_multipass_caller<unsigned short>, min_max_multipass_caller<short>,
min_max_multipass_caller<int>, min_max_multipass_caller<float>, 0 },
{ min_max_caller<unsigned char>, min_max_caller<char>,
min_max_caller<unsigned short>, min_max_caller<short>,
min_max_caller<int>, min_max_caller<float>, min_max_caller<double> } };
static const MaskedCaller masked_callers[2][7] =
{ { min_max_mask_multipass_caller<unsigned char>, min_max_mask_multipass_caller<char>,
min_max_mask_multipass_caller<unsigned short>, min_max_mask_multipass_caller<short>,
min_max_mask_multipass_caller<int>, min_max_mask_multipass_caller<float>, 0 },
{ min_max_mask_caller<unsigned char>, min_max_mask_caller<char>,
min_max_mask_caller<unsigned short>, min_max_mask_caller<short>,
min_max_mask_caller<int>, min_max_mask_caller<float>,
min_max_mask_caller<double> } };
CV_Assert(src.channels() == 1);
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
double minVal_; if (!minVal) minVal = &minVal_;
double maxVal_; if (!maxVal) maxVal = &maxVal_;
Size bufSize;
get_buf_size_required(src.cols, src.rows, src.elemSize(), bufSize.width, bufSize.height);
buf.create(bufSize, CV_8U);
if (mask.empty())
{
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
caller(src, minVal, maxVal, buf);
}
else
{
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
caller(src, mask, minVal, maxVal, buf);
}
}
////////////////////////////////////////////////////////////////////////
// minMaxLoc
namespace cv { namespace gpu { namespace mathfunc { namespace minmaxloc {
void get_buf_size_required(int cols, int rows, int elem_size, int& b1cols,
int& b1rows, int& b2cols, int& b2rows);
template <typename T>
void min_max_loc_caller(const DevMem2D src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
template <typename T>
void min_max_loc_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
template <typename T>
void min_max_loc_multipass_caller(const DevMem2D src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
template <typename T>
void min_max_loc_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
}}}}
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask)
{
GpuMat valbuf, locbuf;
minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask, valbuf, locbuf);
}
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf)
{
using namespace mathfunc::minmaxloc;
typedef void (*Caller)(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
static const Caller callers[2][7] =
{ { min_max_loc_multipass_caller<unsigned char>, min_max_loc_multipass_caller<char>,
min_max_loc_multipass_caller<unsigned short>, min_max_loc_multipass_caller<short>,
min_max_loc_multipass_caller<int>, min_max_loc_multipass_caller<float>, 0 },
{ min_max_loc_caller<unsigned char>, min_max_loc_caller<char>,
min_max_loc_caller<unsigned short>, min_max_loc_caller<short>,
min_max_loc_caller<int>, min_max_loc_caller<float>, min_max_loc_caller<double> } };
static const MaskedCaller masked_callers[2][7] =
{ { min_max_loc_mask_multipass_caller<unsigned char>, min_max_loc_mask_multipass_caller<char>,
min_max_loc_mask_multipass_caller<unsigned short>, min_max_loc_mask_multipass_caller<short>,
min_max_loc_mask_multipass_caller<int>, min_max_loc_mask_multipass_caller<float>, 0 },
{ min_max_loc_mask_caller<unsigned char>, min_max_loc_mask_caller<char>,
min_max_loc_mask_caller<unsigned short>, min_max_loc_mask_caller<short>,
min_max_loc_mask_caller<int>, min_max_loc_mask_caller<float>, min_max_loc_mask_caller<double> } };
CV_Assert(src.channels() == 1);
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
double minVal_; if (!minVal) minVal = &minVal_;
double maxVal_; if (!maxVal) maxVal = &maxVal_;
int minLoc_[2];
int maxLoc_[2];
Size valbuf_size, locbuf_size;
get_buf_size_required(src.cols, src.rows, src.elemSize(), valbuf_size.width,
valbuf_size.height, locbuf_size.width, locbuf_size.height);
valbuf.create(valbuf_size, CV_8U);
locbuf.create(locbuf_size, CV_8U);
if (mask.empty())
{
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
caller(src, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
}
else
{
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
caller(src, mask, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
}
if (minLoc) { minLoc->x = minLoc_[0]; minLoc->y = minLoc_[1]; }
if (maxLoc) { maxLoc->x = maxLoc_[0]; maxLoc->y = maxLoc_[1]; }
}
////////////////////////////////////////////////////////////////////////
// Count non zero
namespace cv { namespace gpu { namespace mathfunc { namespace countnonzero {
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows);
template <typename T>
int count_non_zero_caller(const DevMem2D src, PtrStep buf);
template <typename T>
int count_non_zero_multipass_caller(const DevMem2D src, PtrStep buf);
}}}}
int cv::gpu::countNonZero(const GpuMat& src)
{
GpuMat buf;
return countNonZero(src, buf);
}
int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf)
{
using namespace mathfunc::countnonzero;
typedef int (*Caller)(const DevMem2D src, PtrStep buf);
static const Caller callers[2][7] =
{ { count_non_zero_multipass_caller<unsigned char>, count_non_zero_multipass_caller<char>,
count_non_zero_multipass_caller<unsigned short>, count_non_zero_multipass_caller<short>,
count_non_zero_multipass_caller<int>, count_non_zero_multipass_caller<float>, 0},
{ count_non_zero_caller<unsigned char>, count_non_zero_caller<char>,
count_non_zero_caller<unsigned short>, count_non_zero_caller<short>,
count_non_zero_caller<int>, count_non_zero_caller<float>, count_non_zero_caller<double> } };
CV_Assert(src.channels() == 1);
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
Size buf_size;
get_buf_size_required(src.cols, src.rows, buf_size.width, buf_size.height);
buf.create(buf_size, CV_8U);
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
if (!caller) CV_Error(CV_StsBadArg, "countNonZero: unsupported type");
return caller(src, buf);
}
////////////////////////////////////////////////////////////////////////
// LUT
@@ -711,144 +343,4 @@ void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat&
}
//////////////////////////////////////////////////////////////////////////////
// min/max
namespace cv { namespace gpu { namespace mathfunc
{
template <typename T>
void min_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
template <typename T>
void max_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
template <typename T>
void min_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
template <typename T>
void max_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
}}}
namespace
{
template <typename T>
void min_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
mathfunc::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
}
template <typename T>
void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
{
dst.create(src1.size(), src1.type());
mathfunc::min_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
}
template <typename T>
void max_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
mathfunc::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
}
template <typename T>
void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
{
dst.create(src1.size(), src1.type());
mathfunc::max_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
}
}
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
min_caller<float>, min_caller<double>
};
funcs[src1.depth()](src1, src2, dst, 0);
}
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
min_caller<float>, min_caller<double>
};
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst)
{
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
min_caller<float>, min_caller<double>
};
funcs[src1.depth()](src1, src2, dst, 0);
}
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
{
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
min_caller<float>, min_caller<double>
};
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
max_caller<float>, max_caller<double>
};
funcs[src1.depth()](src1, src2, dst, 0);
}
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
max_caller<float>, max_caller<double>
};
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst)
{
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
max_caller<float>, max_caller<double>
};
funcs[src1.depth()](src1, src2, dst, 0);
}
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
{
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[] =
{
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
max_caller<float>, max_caller<double>
};
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
}
#endif /* !defined (HAVE_CUDA) */