提交 cc34a8ac 编写于 作者: V Vladislav Vinogradov

new implementation for GpuMat::setTo (without constant memory)

上级 69be49ba
......@@ -44,42 +44,33 @@
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/type_traits.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "matrix_operations.hpp"
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct shift_and_sizeof;
template <> struct shift_and_sizeof<signed char> { enum { shift = 0 }; };
template <> struct shift_and_sizeof<unsigned char> { enum { shift = 0 }; };
template <> struct shift_and_sizeof<short> { enum { shift = 1 }; };
template <> struct shift_and_sizeof<unsigned short> { enum { shift = 1 }; };
template <> struct shift_and_sizeof<int> { enum { shift = 2 }; };
template <> struct shift_and_sizeof<float> { enum { shift = 2 }; };
template <> struct shift_and_sizeof<double> { enum { shift = 3 }; };
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// CopyTo /////////////////////////////////
///////////////////////////////////////////////////////////////////////////
// copyWithMask
template <typename T>
void copyWithMask(PtrStepSzb src, PtrStepSzb dst, int cn, PtrStepSzb mask, bool multiChannelMask, cudaStream_t stream)
{
if (multiChannelMask)
cv::gpu::cudev::transform((PtrStepSz<T>)src, (PtrStepSz<T>)dst, identity<T>(), SingleMask(mask), stream);
cv::gpu::cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, identity<T>(), SingleMask(mask), stream);
else
cv::gpu::cudev::transform((PtrStepSz<T>)src, (PtrStepSz<T>)dst, identity<T>(), SingleMaskChannels(mask, cn), stream);
cv::gpu::cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, identity<T>(), SingleMaskChannels(mask, cn), stream);
}
void copyWithMask(PtrStepSzb src, PtrStepSzb dst, size_t elemSize1, int cn, PtrStepSzb mask, bool multiChannelMask, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, int cn, PtrStepSzb mask, bool multiChannelMask, cudaStream_t stream);
static func_t tab[] =
static const func_t tab[] =
{
0,
copyWithMask<unsigned char>,
copyWithMask<unsigned short>,
copyWithMask<uchar>,
copyWithMask<ushort>,
0,
copyWithMask<int>,
0,
......@@ -88,81 +79,39 @@ namespace cv { namespace gpu { namespace cudev
copyWithMask<double>
};
tab[elemSize1](src, dst, cn, mask, multiChannelMask, stream);
const func_t func = tab[elemSize1];
CV_DbgAssert( func != 0 );
func(src, dst, cn, mask, multiChannelMask, stream);
}
///////////////////////////////////////////////////////////////////////////
////////////////////////////////// SetTo //////////////////////////////////
///////////////////////////////////////////////////////////////////////////
// set
__constant__ uchar scalar_8u[4];
__constant__ schar scalar_8s[4];
__constant__ ushort scalar_16u[4];
__constant__ short scalar_16s[4];
__constant__ int scalar_32s[4];
__constant__ float scalar_32f[4];
__constant__ double scalar_64f[4];
template <typename T> __device__ __forceinline__ T readScalar(int i);
template <> __device__ __forceinline__ uchar readScalar<uchar>(int i) {return scalar_8u[i];}
template <> __device__ __forceinline__ schar readScalar<schar>(int i) {return scalar_8s[i];}
template <> __device__ __forceinline__ ushort readScalar<ushort>(int i) {return scalar_16u[i];}
template <> __device__ __forceinline__ short readScalar<short>(int i) {return scalar_16s[i];}
template <> __device__ __forceinline__ int readScalar<int>(int i) {return scalar_32s[i];}
template <> __device__ __forceinline__ float readScalar<float>(int i) {return scalar_32f[i];}
template <> __device__ __forceinline__ double readScalar<double>(int i) {return scalar_64f[i];}
static inline void writeScalar(const uchar* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_8u, vals, sizeof(uchar) * 4) );
}
static inline void writeScalar(const schar* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_8s, vals, sizeof(schar) * 4) );
}
static inline void writeScalar(const ushort* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_16u, vals, sizeof(ushort) * 4) );
}
static inline void writeScalar(const short* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_16s, vals, sizeof(short) * 4) );
}
static inline void writeScalar(const int* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_32s, vals, sizeof(int) * 4) );
}
static inline void writeScalar(const float* vals)
template<typename T, class Mask>
__global__ void set(PtrStepSz<T> mat, const Mask mask, const int channels, const typename TypeVec<T, 4>::vec_type value)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_32f, vals, sizeof(float) * 4) );
}
static inline void writeScalar(const double* vals)
{
cudaSafeCall( cudaMemcpyToSymbol(scalar_64f, vals, sizeof(double) * 4) );
}
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
template<typename T>
__global__ void set(T* mat, int cols, int rows, size_t step, int channels)
{
size_t x = blockIdx.x * blockDim.x + threadIdx.x;
size_t y = blockIdx.y * blockDim.y + threadIdx.y;
if (x >= mat.cols * channels || y >= mat.rows)
return;
if ((x < cols * channels ) && (y < rows))
{
size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
mat[idx] = readScalar<T>(x % channels);
}
const T scalar[4] = {value.x, value.y, value.z, value.w};
if (mask(y, x / channels))
mat(y, x) = scalar[x % channels];
}
template <typename T>
void set(PtrStepSz<T> mat, const T* scalar, int channels, cudaStream_t stream)
{
writeScalar(scalar);
typedef typename TypeVec<T, 4>::vec_type scalar_t;
dim3 threadsPerBlock(32, 8, 1);
dim3 numBlocks(mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
dim3 block(32, 8);
dim3 grid(divUp(mat.cols * channels, block.x), divUp(mat.rows, block.y));
set<T><<<numBlocks, threadsPerBlock, 0, stream>>>(mat.data, mat.cols, mat.rows, mat.step, channels);
set<T><<<grid, block, 0, stream>>>(mat, WithOutMask(), channels, VecTraits<scalar_t>::make(scalar));
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
......@@ -177,29 +126,15 @@ namespace cv { namespace gpu { namespace cudev
template void set<float >(PtrStepSz<float > mat, const float* scalar, int channels, cudaStream_t stream);
template void set<double>(PtrStepSz<double> mat, const double* scalar, int channels, cudaStream_t stream);
template<typename T>
__global__ void set(T* mat, const uchar* mask, int cols, int rows, size_t step, int channels, size_t step_mask)
{
size_t x = blockIdx.x * blockDim.x + threadIdx.x;
size_t y = blockIdx.y * blockDim.y + threadIdx.y;
if ((x < cols * channels ) && (y < rows))
if (mask[y * step_mask + x / channels] != 0)
{
size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
mat[idx] = readScalar<T>(x % channels);
}
}
template <typename T>
void set(PtrStepSz<T> mat, const T* scalar, PtrStepSzb mask, int channels, cudaStream_t stream)
{
writeScalar(scalar);
typedef typename TypeVec<T, 4>::vec_type scalar_t;
dim3 threadsPerBlock(32, 8, 1);
dim3 numBlocks(mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
dim3 block(32, 8);
dim3 grid(divUp(mat.cols * channels, block.x), divUp(mat.rows, block.y));
set<T><<<numBlocks, threadsPerBlock, 0, stream>>>(mat.data, mask.data, mat.cols, mat.rows, mat.step, channels, mask.step);
set<T><<<grid, block, 0, stream>>>(mat, SingleMask(mask), channels, VecTraits<scalar_t>::make(scalar));
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
......@@ -215,8 +150,7 @@ namespace cv { namespace gpu { namespace cudev
template void set<double>(PtrStepSz<double> mat, const double* scalar, PtrStepSzb mask, int channels, cudaStream_t stream);
///////////////////////////////////////////////////////////////////////////
//////////////////////////////// ConvertTo ////////////////////////////////
///////////////////////////////////////////////////////////////////////////
// convert
template <typename T, typename D, typename S> struct Convertor : unary_function<T, D>
{
......@@ -281,8 +215,6 @@ namespace cv { namespace gpu { namespace cudev
template<typename T, typename D, typename S>
void cvt_(PtrStepSzb src, PtrStepSzb dst, double alpha, double beta, cudaStream_t stream)
{
cudaSafeCall( cudaSetDoubleForDevice(&alpha) );
cudaSafeCall( cudaSetDoubleForDevice(&beta) );
Convertor<T, D, S> op(static_cast<S>(alpha), static_cast<S>(beta));
cv::gpu::cudev::transform((PtrStepSz<T>)src, (PtrStepSz<D>)dst, op, WithOutMask(), stream);
}
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册