opencv/modules/cudaarithm/src/cuda/minmax_mat.cu
2013-10-01 12:18:36 +04:00

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#include "opencv2/opencv_modules.hpp"
#ifndef HAVE_OPENCV_CUDEV
#error "opencv_cudev is required"
#else
#include "opencv2/cudev.hpp"
using namespace cv::cudev;
void minMaxMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& stream, int op);
void minMaxScalar(const GpuMat& src, cv::Scalar value, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int op);
///////////////////////////////////////////////////////////////////////
/// minMaxMat
namespace
{
template <template <typename> class Op, typename T>
void minMaxMat_v1(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
gridTransformBinary(globPtr<T>(src1), globPtr<T>(src2), globPtr<T>(dst), Op<T>(), stream);
}
struct MinOp2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmin2(a, b);
}
};
struct MaxOp2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmax2(a, b);
}
};
template <class Op2>
void minMaxMat_v2(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
const int vcols = src1.cols >> 1;
GlobPtrSz<uint> src1_ = globPtr((uint*) src1.data, src1.step, src1.rows, vcols);
GlobPtrSz<uint> src2_ = globPtr((uint*) src2.data, src2.step, src1.rows, vcols);
GlobPtrSz<uint> dst_ = globPtr((uint*) dst.data, dst.step, src1.rows, vcols);
gridTransformBinary(src1_, src2_, dst_, Op2(), stream);
}
struct MinOp4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmin4(a, b);
}
};
struct MaxOp4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmax4(a, b);
}
};
template <class Op4>
void minMaxMat_v4(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream)
{
const int vcols = src1.cols >> 2;
GlobPtrSz<uint> src1_ = globPtr((uint*) src1.data, src1.step, src1.rows, vcols);
GlobPtrSz<uint> src2_ = globPtr((uint*) src2.data, src2.step, src1.rows, vcols);
GlobPtrSz<uint> dst_ = globPtr((uint*) dst.data, dst.step, src1.rows, vcols);
gridTransformBinary(src1_, src2_, dst_, Op4(), stream);
}
}
void minMaxMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& stream, int op)
{
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream);
static const func_t funcs_v1[2][7] =
{
{
minMaxMat_v1<minimum, uchar>,
minMaxMat_v1<minimum, schar>,
minMaxMat_v1<minimum, ushort>,
minMaxMat_v1<minimum, short>,
minMaxMat_v1<minimum, int>,
minMaxMat_v1<minimum, float>,
minMaxMat_v1<minimum, double>
},
{
minMaxMat_v1<maximum, uchar>,
minMaxMat_v1<maximum, schar>,
minMaxMat_v1<maximum, ushort>,
minMaxMat_v1<maximum, short>,
minMaxMat_v1<maximum, int>,
minMaxMat_v1<maximum, float>,
minMaxMat_v1<maximum, double>
}
};
static const func_t funcs_v2[2] =
{
minMaxMat_v2<MinOp2>, minMaxMat_v2<MaxOp2>
};
static const func_t funcs_v4[2] =
{
minMaxMat_v4<MinOp4>, minMaxMat_v4<MaxOp4>
};
const int depth = src1.depth();
CV_DbgAssert( depth <= CV_64F );
GpuMat src1_ = src1.reshape(1);
GpuMat src2_ = src2.reshape(1);
GpuMat dst_ = dst.reshape(1);
if (depth == CV_8U || depth == CV_16U)
{
const intptr_t src1ptr = reinterpret_cast<intptr_t>(src1_.data);
const intptr_t src2ptr = reinterpret_cast<intptr_t>(src2_.data);
const intptr_t dstptr = reinterpret_cast<intptr_t>(dst_.data);
const bool isAllAligned = (src1ptr & 31) == 0 && (src2ptr & 31) == 0 && (dstptr & 31) == 0;
if (isAllAligned)
{
if (depth == CV_8U && (src1_.cols & 3) == 0)
{
funcs_v4[op](src1_, src2_, dst_, stream);
return;
}
else if (depth == CV_16U && (src1_.cols & 1) == 0)
{
funcs_v2[op](src1_, src2_, dst_, stream);
return;
}
}
}
const func_t func = funcs_v1[op][depth];
func(src1_, src2_, dst_, stream);
}
///////////////////////////////////////////////////////////////////////
/// minMaxScalar
namespace
{
template <template <typename> class Op, typename T>
void minMaxScalar(const GpuMat& src, double value, GpuMat& dst, Stream& stream)
{
gridTransformUnary(globPtr<T>(src), globPtr<T>(dst), bind2nd(Op<T>(), cv::saturate_cast<T>(value)), stream);
}
}
void minMaxScalar(const GpuMat& src, cv::Scalar value, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int op)
{
typedef void (*func_t)(const GpuMat& src, double value, GpuMat& dst, Stream& stream);
static const func_t funcs[2][7] =
{
{
minMaxScalar<minimum, uchar>,
minMaxScalar<minimum, schar>,
minMaxScalar<minimum, ushort>,
minMaxScalar<minimum, short>,
minMaxScalar<minimum, int>,
minMaxScalar<minimum, float>,
minMaxScalar<minimum, double>
},
{
minMaxScalar<maximum, uchar>,
minMaxScalar<maximum, schar>,
minMaxScalar<maximum, ushort>,
minMaxScalar<maximum, short>,
minMaxScalar<maximum, int>,
minMaxScalar<maximum, float>,
minMaxScalar<maximum, double>
}
};
const int depth = src.depth();
CV_DbgAssert( depth <= CV_64F );
CV_DbgAssert( src.channels() == 1 );
funcs[op][depth](src, value[0], dst, stream);
}
#endif