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Commit 732bd621 authored by Alexey Spizhevoy's avatar Alexey Spizhevoy
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added masks support for bitwise operations on GPU

parent 3163cfb8
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Showing with 284 additions and 125 deletions
modules/gpu/include/opencv2/gpu/gpu.hpp
View file @ 732bd621
......@@ -474,53 +474,53 @@ namespace cv
//! computes magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
//! Async version
//! async version
CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
//! computes squared magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
//! Async version
//! async version
CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
//! computes angle (angle(i)) of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false);
//! Async version
//! async version
CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, const Stream& stream);
//! converts Cartesian coordinates to polar
//! supports only floating-point source
CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false);
//! Async version
//! async version
CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees, const Stream& stream);
//! converts polar coordinates to Cartesian
//! supports only floating-point source
CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false);
//! Async version
//! async version
CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, const Stream& stream);
//! Perfroms per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst);
//! Async version
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const Stream& stream);
//! perfroms per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat());
//! async version
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream);
//! Calculates per-element bit-wise disjunction of two arrays
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
//! Async version
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
//! calculates per-element bit-wise disjunction of two arrays
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
//! async version
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
//! Calculates per-element bit-wise conjunction of two arrays
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
//! Async version
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
//! calculates per-element bit-wise conjunction of two arrays
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
//! async version
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
//! Calculates per-element bit-wise "exclusive or" operation
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
//! Async version
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
//! calculates per-element bit-wise "exclusive or" operation
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
//! async version
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
//! Logical operators
CV_EXPORTS GpuMat operator ~ (const GpuMat& src);
......@@ -551,7 +551,7 @@ namespace cv
//! Supported types of input disparity: CV_8U, CV_16S.
//! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp);
//! Async version
//! async version
CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, const Stream& stream);
//! Reprojects disparity image to 3D space.
......@@ -560,12 +560,12 @@ namespace cv
//! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
//! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q);
//! Async version
//! async version
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream);
//! converts image from one color space to another
CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0);
//! Async version
//! async version
CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, const Stream& stream);
//! applies fixed threshold to the image.
......@@ -821,7 +821,7 @@ namespace cv
//! Output disparity has CV_8U type.
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Async version
//! async version
void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream);
//! Some heuristics that tries to estmate
......@@ -876,7 +876,7 @@ namespace cv
//! if disparity is empty output type will be CV_16S else output type will be disparity.type().
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Async version
//! async version
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
......@@ -935,7 +935,7 @@ namespace cv
//! if disparity is empty output type will be CV_16S else output type will be disparity.type().
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Async version
//! async version
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
int ndisp;
......@@ -991,7 +991,7 @@ namespace cv
//! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst);
//! Async version
//! async version
void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream);
private:
......
modules/gpu/src/arithm.cpp
View file @ 732bd621
......@@ -81,14 +81,14 @@ 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::bitwise_not(const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
cv::gpu::GpuMat cv::gpu::operator ~ (const GpuMat&) { throw_nogpu(); return GpuMat(); }
cv::gpu::GpuMat cv::gpu::operator | (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
cv::gpu::GpuMat cv::gpu::operator & (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
......@@ -873,10 +873,18 @@ void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat&
namespace cv { namespace gpu { namespace mathfunc
{
void bitwise_not_caller(const DevMem2D src, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_or_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_and_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
void bitwise_xor_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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);
}}}
namespace
......@@ -884,75 +892,126 @@ namespace
void bitwise_not_caller(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
{
dst.create(src.size(), src.type());
mathfunc::bitwise_not_caller(src, src.elemSize(), dst, stream);
mathfunc::bitwise_not_caller(src.rows, src.cols, src, src.elemSize(), dst, stream);
}
void bitwise_not_caller(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
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);
}
void bitwise_or_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_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
}
void bitwise_or_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
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.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
mathfunc::bitwise_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
}
void bitwise_and_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_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
}
void bitwise_and_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
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.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
mathfunc::bitwise_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, 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());
dst.create(src1.size(), src1.type());
mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
}
void bitwise_xor_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
{
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.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
}
}
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst)
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask)
{
::bitwise_not_caller(src, dst, 0);
if (mask.empty())
::bitwise_not_caller(src, dst, 0);
else
::bitwise_not_caller(src, dst, mask, 0);
}
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const Stream& stream)
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream)
{
::bitwise_not_caller(src, dst, StreamAccessor::getStream(stream));
if (mask.empty())
::bitwise_not_caller(src, dst, StreamAccessor::getStream(stream));
else
::bitwise_not_caller(src, dst, mask, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
{
::bitwise_or_caller(src1, src2, dst, 0);
if (mask.empty())
::bitwise_or_caller(src1, src2, dst, 0);
else
::bitwise_or_caller(src1, src2, dst, mask, 0);
}
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
{
::bitwise_or_caller(src1, src2, dst, StreamAccessor::getStream(stream));
if (mask.empty())
::bitwise_or_caller(src1, src2, dst, StreamAccessor::getStream(stream));
else
::bitwise_or_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
{
::bitwise_and_caller(src1, src2, dst, 0);
if (mask.empty())
::bitwise_and_caller(src1, src2, dst, 0);
else
::bitwise_and_caller(src1, src2, dst, mask, 0);
}
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
{
::bitwise_and_caller(src1, src2, dst, StreamAccessor::getStream(stream));
if (mask.empty())
::bitwise_and_caller(src1, src2, dst, StreamAccessor::getStream(stream));
else
::bitwise_and_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
{
::bitwise_xor_caller(src1, src2, dst, 0);
if (mask.empty())
::bitwise_xor_caller(src1, src2, dst, 0);
else
::bitwise_xor_caller(src1, src2, dst, mask, 0);
}
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
{
::bitwise_xor_caller(src1, src2, dst, StreamAccessor::getStream(stream));
if (mask.empty())
::bitwise_xor_caller(src1, src2, dst, StreamAccessor::getStream(stream));
else
::bitwise_xor_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
}
cv::gpu::GpuMat cv::gpu::operator ~ (const GpuMat& src)
......
modules/gpu/src/cuda/mathfunc.cu
View file @ 732bd621
......@@ -243,100 +243,154 @@ namespace cv { namespace gpu { namespace mathfunc
//////////////////////////////////////////////////////////////////////////////
// Per-element bit-wise logical matrix operations
__global__ void bitwise_not_kernel(int cols, int rows, const PtrStep src, PtrStep dst)
struct Mask8U
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < cols && y < rows)
{
dst.ptr(y)[x] = ~src.ptr(y)[x];
}
}
explicit Mask8U(PtrStep mask): mask(mask) {}
__device__ bool operator()(int y, int x) { return mask.ptr(y)[x]; }
PtrStep mask;
};
struct MaskTrue { __device__ bool operator()(int y, int x) { return true; } };
void bitwise_not_caller(const DevMem2D src, int elemSize, PtrStep dst, cudaStream_t stream)
{
dim3 threads(16, 16, 1);
dim3 grid(divUp(src.cols * elemSize, threads.x), divUp(src.rows, threads.y), 1);
// Unary operations
bitwise_not_kernel<<<grid, threads, 0, stream>>>(src.cols * elemSize, src.rows, src, dst);
enum { UN_OP_NOT };
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
template <typename T, int opid>
struct UnOp { __device__ T operator()(T lhs, T rhs); };
template <typename T>
struct UnOp<T, UN_OP_NOT>{ __device__ T operator()(T x) { return ~x; } };
__global__ void bitwise_or_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
template <typename T, int cn, typename UnOp, typename Mask>
__global__ void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, UnOp op, Mask mask)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < cols && y < rows)
if (x < cols && y < rows && mask(y, x))
{
dst.ptr(y)[x] = src1.ptr(y)[x] | src2.ptr(y)[x];
T* dsty = (T*)dst.ptr(y);
const T* srcy = (const T*)src.ptr(y);
#pragma unroll
for (int i = 0; i < cn; ++i)
dsty[cn * x + i] = op(srcy[cn * x + i]);
}
}
void bitwise_or_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream)
template <int opid, typename Mask>
void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, int elem_size, Mask mask, cudaStream_t stream)
{
dim3 threads(16, 16, 1);
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
bitwise_or_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
dim3 threads(16, 16);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
switch (elem_size)
{
case 1: bitwise_un_op<unsigned char, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned char, opid>(), mask); break;
case 2: bitwise_un_op<unsigned short, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned short, opid>(), mask); break;
case 3: bitwise_un_op<unsigned char, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned char, opid>(), mask); break;
case 4: bitwise_un_op<unsigned int, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
case 6: bitwise_un_op<unsigned short, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned short, opid>(), mask); break;
case 8: bitwise_un_op<unsigned int, 2><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
case 12: bitwise_un_op<unsigned int, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
case 16: bitwise_un_op<unsigned int, 4><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
case 24: bitwise_un_op<unsigned int, 6><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
case 32: bitwise_un_op<unsigned int, 8><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
}
if (stream == 0) cudaSafeCall(cudaThreadSynchronize());
}
__global__ void bitwise_and_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
void bitwise_not_caller(int rows, int cols,const PtrStep src, int elem_size, PtrStep dst, cudaStream_t stream)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, MaskTrue(), stream);
}
if (x < cols && y < rows)
{
dst.ptr(y)[x] = src1.ptr(y)[x] & src2.ptr(y)[x];
}
void bitwise_not_caller(int rows, int cols,const PtrStep src, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
{
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, Mask8U(mask), stream);
}
// Binary operations
void bitwise_and_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream)
{
dim3 threads(16, 16, 1);
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
enum { BIN_OP_OR, BIN_OP_AND, BIN_OP_XOR };
bitwise_and_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
template <typename T, int opid>
struct BinOp { __device__ T operator()(T lhs, T rhs); };
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
template <typename T>
struct BinOp<T, BIN_OP_OR>{ __device__ T operator()(T lhs, T rhs) { return lhs | rhs; } };
template <typename T>
struct BinOp<T, BIN_OP_AND>{ __device__ T operator()(T lhs, T rhs) { return lhs & rhs; } };
template <typename T>
struct BinOp<T, BIN_OP_XOR>{ __device__ T operator()(T lhs, T rhs) { return lhs ^ rhs; } };
__global__ void bitwise_xor_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
template <typename T, int cn, typename BinOp, typename Mask>
__global__ void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst, BinOp op, Mask mask)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < cols && y < rows)
if (x < cols && y < rows && mask(y, x))
{
dst.ptr(y)[x] = src1.ptr(y)[x] ^ src2.ptr(y)[x];
T* dsty = (T*)dst.ptr(y);
const T* src1y = (const T*)src1.ptr(y);
const T* src2y = (const T*)src2.ptr(y);
#pragma unroll
for (int i = 0; i < cn; ++i)
dsty[cn * x + i] = op(src1y[cn * x + i], src2y[cn * x + i]);
}
}
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)
{
dim3 threads(16, 16);
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
switch (elem_size)
{
case 1: bitwise_bin_op<unsigned char, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned char, opid>(), mask); break;
case 2: bitwise_bin_op<unsigned short, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned short, opid>(), mask); break;
case 3: bitwise_bin_op<unsigned char, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned char, opid>(), mask); break;
case 4: bitwise_bin_op<unsigned int, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
case 6: bitwise_bin_op<unsigned short, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned short, opid>(), mask); break;
case 8: bitwise_bin_op<unsigned int, 2><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
case 12: bitwise_bin_op<unsigned int, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
case 16: bitwise_bin_op<unsigned int, 4><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
case 24: bitwise_bin_op<unsigned int, 6><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
case 32: bitwise_bin_op<unsigned int, 8><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
}
if (stream == 0) cudaSafeCall(cudaThreadSynchronize());
}
void bitwise_xor_caller(int cols, int rows, 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 elem_size, PtrStep dst, cudaStream_t stream)
{
dim3 threads(16, 16, 1);
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), stream);
}
bitwise_xor_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
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)
{
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
}
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), 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)
{
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
}
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
{
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), 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)
{
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
}
}}}
tests/gpu/src/bitwise_oper.cpp
View file @ 732bd621
......@@ -60,7 +60,7 @@ struct CV_GpuBitwiseTest: public CvTest
int rows, cols;
for (int depth = CV_8U; depth <= CV_64F; ++depth)
for (int cn = 1; cn <= 4; ++cn)
for (int attempt = 0; attempt < 5; ++attempt)
for (int attempt = 0; attempt < 3; ++attempt)
{
rows = 1 + rand() % 100;
cols = 1 + rand() % 100;
......@@ -83,7 +83,12 @@ struct CV_GpuBitwiseTest: public CvTest
}
Mat dst_gold = ~src;
gpu::GpuMat dst = ~gpu::GpuMat(src);
gpu::GpuMat mask(src.size(), CV_8U);
mask.setTo(Scalar(1));
gpu::GpuMat dst;
gpu::bitwise_not(gpu::GpuMat(src), dst, mask);
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
......@@ -112,10 +117,23 @@ struct CV_GpuBitwiseTest: public CvTest
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
Mat dsth(dst);
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
Mat mask(src1.size(), CV_8U);
randu(mask, Scalar(0), Scalar(255));
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
bitwise_or(src1, src2, dst_gold2, mask);
gpu::bitwise_or(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
dsth = dst2;
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
}
void test_bitwise_and(int rows, int cols, int type)
......@@ -138,10 +156,24 @@ struct CV_GpuBitwiseTest: public CvTest
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
Mat dsth(dst);
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
Mat mask(src1.size(), CV_8U);
randu(mask, Scalar(0), Scalar(255));
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
bitwise_and(src1, src2, dst_gold2, mask);
gpu::bitwise_and(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
dsth = dst2;
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
}
void test_bitwise_xor(int rows, int cols, int type)
......@@ -164,10 +196,24 @@ struct CV_GpuBitwiseTest: public CvTest
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
Mat dsth(dst);
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
Mat mask(src1.size(), CV_8U);
randu(mask, Scalar(0), Scalar(255));
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
bitwise_xor(src1, src2, dst_gold2, mask);
gpu::bitwise_xor(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
dsth = dst2;
for (int i = 0; i < dst_gold.rows; ++i)
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
}
} gpu_bitwise_test;
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