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Commit e62bf3a2 authored by Alexey Spizhevoy's avatar Alexey Spizhevoy
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updated gpu bitwise operations

parent 0f30fe08
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Showing with 182 additions and 207 deletions
modules/gpu/src/arithm.cpp
View file @ e62bf3a2
......@@ -1002,18 +1002,25 @@ void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat&
namespace cv { namespace gpu { namespace mathfunc
{
void bitwise_not_caller(int rows, int cols, const PtrStep src, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_not_caller(int rows, int cols, const PtrStep src, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
template <int opid, typename Mask>
void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst, int elem_size, Mask mask, cudaStream_t stream);
void bitwise_not_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src, PtrStep dst, cudaStream_t stream);
template <typename T>
void bitwise_mask_not_caller(int rows, int cols, int cn, const PtrStep src, const PtrStep mask, PtrStep dst, cudaStream_t stream);
void bitwise_or_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream);
template <typename T>
void bitwise_mask_or_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream);
void bitwise_and_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream);
template <typename T>
void bitwise_mask_and_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream);
void bitwise_xor_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream);
template <typename T>
void bitwise_mask_xor_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream);
}}}
namespace
......@@ -1021,60 +1028,123 @@ namespace
void bitwise_not_caller(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
dst.create(src.size(), src.type());
mathfunc::bitwise_not_caller(src.rows, src.cols, src, src.elemSize(), dst, stream);
cv::gpu::mathfunc::bitwise_not_caller(src.rows, src.cols, src.elemSize1(),
dst.channels(), src, dst, stream);
}
void bitwise_not_caller(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwise_mask_not_caller<unsigned char>, mathfunc::bitwise_mask_not_caller<unsigned char>,
mathfunc::bitwise_mask_not_caller<unsigned short>, mathfunc::bitwise_mask_not_caller<unsigned short>,
mathfunc::bitwise_mask_not_caller<unsigned int>, mathfunc::bitwise_mask_not_caller<unsigned int>,
mathfunc::bitwise_mask_not_caller<unsigned int>};
CV_Assert(mask.type() == CV_8U && mask.size() == src.size());
dst.create(src.size(), src.type());
mathfunc::bitwise_not_caller(src.rows, src.cols, src, src.elemSize(), dst, mask, stream);
Caller caller = callers[src.depth()];
CV_Assert(caller);
int cn = src.depth() != CV_64F ? src.channels() : src.channels() * (sizeof(double) / sizeof(unsigned int));
caller(src.rows, src.cols, cn, src, mask, dst, stream);
}
void bitwise_or_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::bitwise_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
cv::gpu::mathfunc::bitwise_or_caller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
void bitwise_or_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwise_mask_or_caller<unsigned char>, mathfunc::bitwise_mask_or_caller<unsigned char>,
mathfunc::bitwise_mask_or_caller<unsigned short>, mathfunc::bitwise_mask_or_caller<unsigned short>,
mathfunc::bitwise_mask_or_caller<unsigned int>, mathfunc::bitwise_mask_or_caller<unsigned int>,
mathfunc::bitwise_mask_or_caller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
mathfunc::bitwise_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
Caller caller = callers[src1.depth()];
CV_Assert(caller);
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
caller(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
void bitwise_and_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::bitwise_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
cv::gpu::mathfunc::bitwise_and_caller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
void bitwise_and_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwise_mask_and_caller<unsigned char>, mathfunc::bitwise_mask_and_caller<unsigned char>,
mathfunc::bitwise_mask_and_caller<unsigned short>, mathfunc::bitwise_mask_and_caller<unsigned short>,
mathfunc::bitwise_mask_and_caller<unsigned int>, mathfunc::bitwise_mask_and_caller<unsigned int>,
mathfunc::bitwise_mask_and_caller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
mathfunc::bitwise_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
Caller caller = callers[src1.depth()];
CV_Assert(caller);
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
caller(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
void bitwise_xor_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
{
CV_Assert(src1.size() == src2.size());
CV_Assert(src1.type() == src2.type());
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
cv::gpu::mathfunc::bitwise_xor_caller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
void bitwise_xor_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwise_mask_xor_caller<unsigned char>, mathfunc::bitwise_mask_xor_caller<unsigned char>,
mathfunc::bitwise_mask_xor_caller<unsigned short>, mathfunc::bitwise_mask_xor_caller<unsigned short>,
mathfunc::bitwise_mask_xor_caller<unsigned int>, mathfunc::bitwise_mask_xor_caller<unsigned int>,
mathfunc::bitwise_mask_xor_caller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
dst.create(src1.size(), src1.type());
mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
Caller caller = callers[src1.depth()];
CV_Assert(caller);
int cn = dst.depth() != CV_64F ? dst.channels() : dst.channels() * (sizeof(double) / sizeof(unsigned int));
caller(dst.rows, dst.cols, cn, src1, src2, mask, dst, stream);
}
}
......
modules/gpu/src/cuda/mathfunc.cu
View file @ e62bf3a2
......@@ -299,18 +299,12 @@ namespace cv { namespace gpu { namespace mathfunc
template <typename T>
struct UnOp<T, UN_OP_NOT>
{
typedef typename TypeVec<T, 2>::vec_t Vec2;
typedef typename TypeVec<T, 3>::vec_t Vec3;
typedef typename TypeVec<T, 4>::vec_t Vec4;
static __device__ T call(T v) { return ~v; }
static __device__ Vec2 call(Vec2 v) { return VecTraits<Vec2>::make(~v.x, ~v.y); }
static __device__ Vec3 call(Vec3 v) { return VecTraits<Vec3>::make(~v.x, ~v.y, ~v.z); }
static __device__ Vec4 call(Vec4 v) { return VecTraits<Vec4>::make(~v.x, ~v.y, ~v.z, ~v.w); }
};
template <int opid>
__global__ void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst)
__global__ void bitwise_un_op_kernel(int rows, int width, const PtrStep src, PtrStep dst)
{
const int x = (blockDim.x * blockIdx.x + threadIdx.x) * 4;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
......@@ -319,13 +313,13 @@ namespace cv { namespace gpu { namespace mathfunc
{
uchar* dst_ptr = dst.ptr(y) + x;
const uchar* src_ptr = src.ptr(y) + x;
if (x + sizeof(uint) - 1 < cols)
if (x + sizeof(uint) - 1 < width)
{
*(uint*)dst_ptr = UnOp<uint, opid>::call(*(uint*)src_ptr);
}
else
{
const uchar* src_end = src.ptr(y) + cols;
const uchar* src_end = src.ptr(y) + width;
while (src_ptr < src_end)
{
*dst_ptr++ = UnOp<uchar, opid>::call(*src_ptr++);
......@@ -335,105 +329,65 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T, int cn, int opid>
__global__ void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, const PtrStep mask)
template <int opid>
void bitwise_un_op(int rows, int width, const PtrStep src, PtrStep dst, cudaStream_t stream)
{
typedef typename TypeVec<T, cn>::vec_t Type;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
dim3 threads(16, 16);
dim3 grid(divUp(width, threads.x * sizeof(uint)),
divUp(rows, threads.y));
if (x < cols && y < rows && mask.ptr(y)[x])
{
Type* dst_row = (Type*)dst.ptr(y);
const Type* src_row = (const Type*)src.ptr(y);
dst_row[x] = UnOp<T, opid>::call(src_row[x]);
}
bitwise_un_op_kernel<opid><<<grid, threads>>>(rows, width, src, dst);
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
template <typename T, int cn, int opid>
__global__ void bitwise_un_op_two_loads(int rows, int cols, const PtrStep src, PtrStep dst, const PtrStep mask)
template <typename T, int opid>
__global__ void bitwise_un_op_kernel(int rows, int cols, int cn, const PtrStep src, const PtrStep mask, PtrStep dst)
{
typedef typename TypeVec<T, cn>::vec_t Type;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < cols && y < rows && mask.ptr(y)[x])
if (x < cols && y < rows && mask.ptr(y)[x / cn])
{
Type* dst_row = (Type*)dst.ptr(y);
const Type* src_row = (const Type*)src.ptr(y);
dst_row[2 * x] = UnOp<T, opid>::call(src_row[2 * x]);
dst_row[2 * x + 1] = UnOp<T, opid>::call(src_row[2 * x + 1]);
T* dst_row = (T*)dst.ptr(y);
const T* src_row = (const T*)src.ptr(y);
dst_row[x] = UnOp<T, opid>::call(src_row[x]);
}
}
template <int opid>
void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, int elem_size, cudaStream_t stream)
template <typename T, int opid>
void bitwise_un_op(int rows, int cols, int cn, const PtrStep src, const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
dim3 threads(16, 16);
dim3 grid(divUp(cols * elem_size, threads.x * sizeof(uint)),
divUp(rows, threads.y));
bitwise_un_op<opid><<<grid, threads>>>(rows, cols * elem_size, src, dst);
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
bitwise_un_op_kernel<T, opid><<<grid, threads>>>(rows, cols, cn, src, mask, dst);
template <int opid>
void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, int elem_size, const PtrStep mask, cudaStream_t stream)
{
dim3 threads(16, 16);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
switch (elem_size)
{
case 1:
bitwise_un_op<uchar, 1, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 2:
bitwise_un_op<ushort, 1, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 3:
bitwise_un_op<uchar, 3, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 4:
bitwise_un_op<uint, 1, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 6:
bitwise_un_op<ushort, 3, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 8:
bitwise_un_op<uint, 2, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 12:
bitwise_un_op<uint, 3, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 16:
bitwise_un_op<uint, 4, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 24:
bitwise_un_op_two_loads<uint, 3, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
case 32:
bitwise_un_op_two_loads<uint, 4, opid><<<grid, threads>>>(rows, cols, src, dst, mask);
break;
}
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
void bitwise_not_caller(int rows, int cols, const PtrStep src, int elem_size, PtrStep dst, cudaStream_t stream)
void bitwise_not_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src, PtrStep dst, cudaStream_t stream)
{
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, stream);
bitwise_un_op<UN_OP_NOT>(rows, cols * elem_size1 * cn, src, dst, stream);
}
void bitwise_not_caller(int rows, int cols,const PtrStep src, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
template <typename T>
void bitwise_mask_not_caller(int rows, int cols, int cn, const PtrStep src, const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, mask, stream);
bitwise_un_op<T, UN_OP_NOT>(rows, cols * cn, cn, src, mask, dst, stream);
}
template void bitwise_mask_not_caller<uchar>(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_not_caller<ushort>(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_not_caller<uint>(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
//------------------------------------------------------------------------
// Binary operations
......@@ -445,43 +399,25 @@ namespace cv { namespace gpu { namespace mathfunc
template <typename T>
struct BinOp<T, BIN_OP_OR>
{
typedef typename TypeVec<T, 2>::vec_t Vec2;
typedef typename TypeVec<T, 3>::vec_t Vec3;
typedef typename TypeVec<T, 4>::vec_t Vec4;
static __device__ T call(T a, T b) { return a | b; }
static __device__ Vec2 call(Vec2 a, Vec2 b) { return VecTraits<Vec2>::make(a.x | b.x, a.y | b.y); }
static __device__ Vec3 call(Vec3 a, Vec3 b) { return VecTraits<Vec3>::make(a.x | b.x, a.y | b.y, a.z | b.z); }
static __device__ Vec4 call(Vec4 a, Vec4 b) { return VecTraits<Vec4>::make(a.x | b.x, a.y | b.y, a.z | b.z, a.w | b.w); }
};
template <typename T>
struct BinOp<T, BIN_OP_AND>
{
typedef typename TypeVec<T, 2>::vec_t Vec2;
typedef typename TypeVec<T, 3>::vec_t Vec3;
typedef typename TypeVec<T, 4>::vec_t Vec4;
static __device__ T call(T a, T b) { return a & b; }
static __device__ Vec2 call(Vec2 a, Vec2 b) { return VecTraits<Vec2>::make(a.x & b.x, a.y & b.y); }
static __device__ Vec3 call(Vec3 a, Vec3 b) { return VecTraits<Vec3>::make(a.x & b.x, a.y & b.y, a.z & b.z); }
static __device__ Vec4 call(Vec4 a, Vec4 b) { return VecTraits<Vec4>::make(a.x & b.x, a.y & b.y, a.z & b.z, a.w & b.w); }
};
template <typename T>
struct BinOp<T, BIN_OP_XOR>
{
typedef typename TypeVec<T, 2>::vec_t Vec2;
typedef typename TypeVec<T, 3>::vec_t Vec3;
typedef typename TypeVec<T, 4>::vec_t Vec4;
static __device__ T call(T a, T b) { return a ^ b; }
static __device__ Vec2 call(Vec2 a, Vec2 b) { return VecTraits<Vec2>::make(a.x ^ b.x, a.y ^ b.y); }
static __device__ Vec3 call(Vec3 a, Vec3 b) { return VecTraits<Vec3>::make(a.x ^ b.x, a.y ^ b.y, a.z ^ b.z); }
static __device__ Vec4 call(Vec4 a, Vec4 b) { return VecTraits<Vec4>::make(a.x ^ b.x, a.y ^ b.y, a.z ^ b.z, a.w ^ b.w); }
};
template <int opid>
__global__ void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst)
__global__ void bitwise_bin_op_kernel(int rows, int width, const PtrStep src1, const PtrStep src2, PtrStep dst)
{
const int x = (blockDim.x * blockIdx.x + threadIdx.x) * 4;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
......@@ -491,13 +427,14 @@ namespace cv { namespace gpu { namespace mathfunc
uchar* dst_ptr = dst.ptr(y) + x;
const uchar* src1_ptr = src1.ptr(y) + x;
const uchar* src2_ptr = src2.ptr(y) + x;
if (x + sizeof(uint) - 1 < cols)
if (x + sizeof(uint) - 1 < width)
{
*(uint*)dst_ptr = BinOp<uint, opid>::call(*(uint*)src1_ptr, *(uint*)src2_ptr);
}
else
{
const uchar* src1_end = src1.ptr(y) + cols;
const uchar* src1_end = src1.ptr(y) + width;
while (src1_ptr < src1_end)
{
*dst_ptr++ = BinOp<uchar, opid>::call(*src1_ptr++, *src2_ptr++);
......@@ -507,135 +444,103 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T, int cn, int opid>
__global__ void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2,
PtrStep dst, const PtrStep mask)
template <int opid>
void bitwise_bin_op(int rows, int width, const PtrStep src1, const PtrStep src2, PtrStep dst,
cudaStream_t stream)
{
typedef typename TypeVec<T, cn>::vec_t Type;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
dim3 threads(16, 16);
dim3 grid(divUp(width, threads.x * sizeof(uint)), divUp(rows, threads.y));
if (x < cols && y < rows && mask.ptr(y)[x])
{
Type* dst_row = (Type*)dst.ptr(y);
const Type* src1_row = (const Type*)src1.ptr(y);
const Type* src2_row = (const Type*)src2.ptr(y);
dst_row[x] = BinOp<T, opid>::call(src1_row[x], src2_row[x]);
}
bitwise_bin_op_kernel<opid><<<grid, threads>>>(rows, width, src1, src2, dst);
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
template <typename T, int cn, int opid>
__global__ void bitwise_bin_op_two_loads(int rows, int cols, const PtrStep src1, const PtrStep src2,
PtrStep dst, const PtrStep mask)
template <typename T, int opid>
__global__ void bitwise_bin_op_kernel(
int rows, int cols, int cn, const PtrStep src1, const PtrStep src2,
const PtrStep mask, PtrStep dst)
{
typedef typename TypeVec<T, cn>::vec_t Type;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < cols && y < rows && mask.ptr(y)[x])
if (x < cols && y < rows && mask.ptr(y)[x / cn])
{
Type* dst_row = (Type*)dst.ptr(y);
const Type* src1_row = (const Type*)src1.ptr(y);
const Type* src2_row = (const Type*)src2.ptr(y);
dst_row[2 * x] = BinOp<T, opid>::call(src1_row[2 * x], src2_row[2 * x]);
dst_row[2 * x + 1] = BinOp<T, opid>::call(src1_row[2 * x + 1], src2_row[2 * x + 1]);
T* dst_row = (T*)dst.ptr(y);
const T* src1_row = (const T*)src1.ptr(y);
const T* src2_row = (const T*)src2.ptr(y);
dst_row[x] = BinOp<T, opid>::call(src1_row[x], src2_row[x]);
}
}
template <int opid>
void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst,
int elem_size, cudaStream_t stream)
template <typename T, int opid>
void bitwise_bin_op(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2,
const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
dim3 threads(16, 16);
dim3 grid(divUp(cols * elem_size, threads.x * sizeof(uint)),
divUp(rows, threads.y));
bitwise_bin_op<opid><<<grid, threads>>>(rows, cols * elem_size, src1, src2, dst);
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
bitwise_bin_op_kernel<T, opid><<<grid, threads>>>(rows, cols, cn, src1, src2, mask, dst);
template <int opid>
void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst,
int elem_size, const PtrStep mask, cudaStream_t stream)
{
dim3 threads(16, 16);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
switch (elem_size)
{
case 1:
bitwise_bin_op<uchar, 1, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 2:
bitwise_bin_op<ushort, 1, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 3:
bitwise_bin_op<uchar, 3, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 4:
bitwise_bin_op<uint, 1, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 6:
bitwise_bin_op<ushort, 3, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 8:
bitwise_bin_op<uint, 2, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 12:
bitwise_bin_op<uint, 3, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 16:
bitwise_bin_op<uint, 4, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 24:
bitwise_bin_op_two_loads<uint, 3, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
case 32:
bitwise_bin_op_two_loads<uint, 4, opid><<<grid, threads>>>(rows, cols, src1, src2, dst, mask);
break;
}
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
void bitwise_or_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, stream);
bitwise_bin_op<BIN_OP_OR>(rows, cols * elem_size1 * cn, src1, src2, dst, stream);
}
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
template <typename T>
void bitwise_mask_or_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, mask, stream);
bitwise_bin_op<T, BIN_OP_OR>(rows, cols * cn, cn, src1, src2, mask, dst, stream);
}
template void bitwise_mask_or_caller<uchar>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_or_caller<ushort>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_or_caller<uint>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
void bitwise_and_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, stream);
bitwise_bin_op<BIN_OP_AND>(rows, cols * elem_size1 * cn, src1, src2, dst, stream);
}
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
template <typename T>
void bitwise_mask_and_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, mask, stream);
bitwise_bin_op<T, BIN_OP_AND>(rows, cols * cn, cn, src1, src2, mask, dst, stream);
}
template void bitwise_mask_and_caller<uchar>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_and_caller<ushort>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_and_caller<uint>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
void bitwise_xor_caller(int rows, int cols, int elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, stream);
bitwise_bin_op<BIN_OP_XOR>(rows, cols * elem_size1 * cn, src1, src2, dst, stream);
}
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
template <typename T>
void bitwise_mask_xor_caller(int rows, int cols, int cn, const PtrStep src1, const PtrStep src2, const PtrStep mask, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, mask, stream);
bitwise_bin_op<T, BIN_OP_XOR>(rows, cols * cn, cn, src1, src2, mask, dst, stream);
}
template void bitwise_mask_xor_caller<uchar>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_xor_caller<ushort>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
template void bitwise_mask_xor_caller<uint>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
//////////////////////////////////////////////////////////////////////////////
......
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