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Commit d81f54db authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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switched to Input/Output Array in bitwise logical operations

parent 04a1a6dd
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Showing with 91 additions and 197 deletions
modules/gpuarithm/include/opencv2/gpuarithm.hpp
View file @ d81f54db
......@@ -95,6 +95,18 @@ CV_EXPORTS void pow(InputArray src, double power, OutputArray dst, Stream& strea
//! compares elements of two arrays (dst = src1 <cmpop> src2)
CV_EXPORTS void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop, Stream& stream = Stream::Null());
//! performs per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of two arrays
CV_EXPORTS void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of two arrays
CV_EXPORTS void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" operation
CV_EXPORTS void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
//! computes the weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)
CV_EXPORTS void addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst,
int dtype = -1, Stream& stream = Stream::Null());
......@@ -105,27 +117,6 @@ static inline void scaleAdd(const GpuMat& src1, double alpha, const GpuMat& src2
addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
}
//! performs per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! 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(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_or(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! 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(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_and(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! 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(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! pixel by pixel right shift of an image by a constant value
//! supports 1, 3 and 4 channels images with integers elements
CV_EXPORTS void rshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream = Stream::Null());
......
modules/gpuarithm/src/element_operations.cpp
View file @ d81f54db
......@@ -71,16 +71,13 @@ void cv::gpu::pow(InputArray, double, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::compare(InputArray, InputArray, OutputArray, int, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_not(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_or(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_or(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_and(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_and(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_xor(const GpuMat&, const Scalar&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_xor(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::rshift(const GpuMat&, Scalar_<int>, GpuMat&, Stream&) { throw_no_cuda(); }
......@@ -1889,25 +1886,29 @@ void cv::gpu::compare(InputArray src1, InputArray src2, OutputArray dst, int cmp
}
//////////////////////////////////////////////////////////////////////////////
// Unary bitwise logical operations
// bitwise_not
namespace arithm
{
template <typename T> void bitMatNot(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, Stream& s)
void cv::gpu::bitwise_not(InputArray _src, OutputArray _dst, InputArray _mask, Stream& _stream)
{
using namespace arithm;
GpuMat src = _src.getGpuMat();
GpuMat mask = _mask.getGpuMat();
const int depth = src.depth();
CV_Assert( depth <= CV_64F );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src.size()) );
dst.create(src.size(), src.type());
_dst.create(src.size(), src.type());
GpuMat dst = _dst.getGpuMat();
cudaStream_t stream = StreamAccessor::getStream(s);
cudaStream_t stream = StreamAccessor::getStream(_stream);
const int bcols = (int) (src.cols * src.elemSize());
......@@ -1941,6 +1942,16 @@ void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, St
//////////////////////////////////////////////////////////////////////////////
// Binary bitwise logical operations
namespace
{
enum
{
BIT_OP_AND,
BIT_OP_OR,
BIT_OP_XOR
};
}
namespace arithm
{
template <typename T> void bitMatAnd(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
......@@ -1948,113 +1959,31 @@ namespace arithm
template <typename T> void bitMatXor(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& s)
{
using namespace arithm;
const int depth = src1.depth();
CV_Assert( depth <= CV_64F );
CV_Assert( src2.size() == src1.size() && src2.type() == src1.type() );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src1.size()) );
dst.create(src1.size(), src1.type());
cudaStream_t stream = StreamAccessor::getStream(s);
const int bcols = (int) (src1.cols * src1.elemSize());
if ((bcols & 3) == 0)
{
const int vcols = bcols >> 2;
bitMatAnd<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
}
else if ((bcols & 1) == 0)
{
const int vcols = bcols >> 1;
bitMatAnd<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
}
else
{
bitMatAnd<unsigned int>(
PtrStepSzb(src1.rows, bcols, src1.data, src1.step),
PtrStepSzb(src1.rows, bcols, src2.data, src2.step),
PtrStepSzb(src1.rows, bcols, dst.data, dst.step),
mask, stream);
}
}
void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& s)
static void bitMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, double, Stream& _stream, int op)
{
using namespace arithm;
const int depth = src1.depth();
CV_Assert( depth <= CV_64F );
CV_Assert( src2.size() == src1.size() && src2.type() == src1.type() );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src1.size()) );
dst.create(src1.size(), src1.type());
cudaStream_t stream = StreamAccessor::getStream(s);
const int bcols = (int) (src1.cols * src1.elemSize());
if ((bcols & 3) == 0)
typedef void (*func_t)(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
static const func_t funcs32[] =
{
const int vcols = bcols >> 2;
bitMatOr<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
}
else if ((bcols & 1) == 0)
bitMatAnd<uint>,
bitMatOr<uint>,
bitMatXor<uint>
};
static const func_t funcs16[] =
{
const int vcols = bcols >> 1;
bitMatOr<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
}
else
bitMatAnd<ushort>,
bitMatOr<ushort>,
bitMatXor<ushort>
};
static const func_t funcs8[] =
{
bitMatAnd<uchar>,
bitMatOr<uchar>,
bitMatXor<uchar>
};
bitMatOr<unsigned int>(
PtrStepSzb(src1.rows, bcols, src1.data, src1.step),
PtrStepSzb(src1.rows, bcols, src2.data, src2.step),
PtrStepSzb(src1.rows, bcols, dst.data, dst.step),
mask, stream);
}
}
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, Stream& s)
{
using namespace arithm;
const int depth = src1.depth();
CV_Assert( depth <= CV_64F );
CV_Assert( src2.size() == src1.size() && src2.type() == src1.type() );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == src1.size()) );
dst.create(src1.size(), src1.type());
cudaStream_t stream = StreamAccessor::getStream(s);
cudaStream_t stream = StreamAccessor::getStream(_stream);
const int bcols = (int) (src1.cols * src1.elemSize());
......@@ -2062,8 +1991,7 @@ void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
{
const int vcols = bcols >> 2;
bitMatXor<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
funcs32[op](PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
......@@ -2072,8 +2000,7 @@ void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
{
const int vcols = bcols >> 1;
bitMatXor<unsigned int>(
PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
funcs16[op](PtrStepSzb(src1.rows, vcols, src1.data, src1.step),
PtrStepSzb(src1.rows, vcols, src2.data, src2.step),
PtrStepSzb(src1.rows, vcols, dst.data, dst.step),
mask, stream);
......@@ -2081,17 +2008,13 @@ void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
else
{
bitMatXor<unsigned int>(
PtrStepSzb(src1.rows, bcols, src1.data, src1.step),
PtrStepSzb(src1.rows, bcols, src2.data, src2.step),
PtrStepSzb(src1.rows, bcols, dst.data, dst.step),
mask, stream);
funcs8[op](PtrStepSzb(src1.rows, bcols, src1.data, src1.step),
PtrStepSzb(src1.rows, bcols, src2.data, src2.step),
PtrStepSzb(src1.rows, bcols, dst.data, dst.step),
mask, stream);
}
}
//////////////////////////////////////////////////////////////////////////////
// Binary bitwise logical operations with scalars
namespace arithm
{
template <typename T> void bitScalarAnd(PtrStepSzb src1, unsigned int src2, PtrStepSzb dst, cudaStream_t stream);
......@@ -2179,18 +2102,34 @@ namespace
};
}
void cv::gpu::bitwise_and(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
static void bitScalar(const GpuMat& src, Scalar val, bool, GpuMat& dst, const GpuMat& mask, double, Stream& stream, int op)
{
using namespace arithm;
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
static const func_t funcs[3][5][4] =
{
{BitScalar<unsigned char, bitScalarAnd<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiAndC_8u_C3R >::call, BitScalar4< bitScalarAnd<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarAnd<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiAndC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiAndC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarAnd<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiAndC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiAndC_32s_C4R>::call}
{
{BitScalar<unsigned char, bitScalarAnd<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiAndC_8u_C3R >::call, BitScalar4< bitScalarAnd<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarAnd<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiAndC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiAndC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarAnd<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiAndC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiAndC_32s_C4R>::call}
},
{
{BitScalar<unsigned char, bitScalarOr<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiOrC_8u_C3R >::call, BitScalar4< bitScalarOr<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarOr<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiOrC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiOrC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarOr<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiOrC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiOrC_32s_C4R>::call}
},
{
{BitScalar<unsigned char, bitScalarXor<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiXorC_8u_C3R >::call, BitScalar4< bitScalarXor<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarXor<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiXorC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiXorC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarXor<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiXorC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiXorC_32s_C4R>::call}
}
};
const int depth = src.depth();
......@@ -2198,60 +2137,24 @@ void cv::gpu::bitwise_and(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stre
CV_Assert( depth == CV_8U || depth == CV_16U || depth == CV_32S );
CV_Assert( cn == 1 || cn == 3 || cn == 4 );
CV_Assert( mask.empty() );
dst.create(src.size(), src.type());
funcs[depth][cn - 1](src, sc, dst, StreamAccessor::getStream(stream));
funcs[op][depth][cn - 1](src, val, dst, StreamAccessor::getStream(stream));
}
void cv::gpu::bitwise_or(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
void cv::gpu::bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask, Stream& stream)
{
using namespace arithm;
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{BitScalar<unsigned char, bitScalarOr<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiOrC_8u_C3R >::call, BitScalar4< bitScalarOr<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarOr<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiOrC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiOrC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarOr<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiOrC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiOrC_32s_C4R>::call}
};
const int depth = src.depth();
const int cn = src.channels();
CV_Assert( depth == CV_8U || depth == CV_16U || depth == CV_32S );
CV_Assert( cn == 1 || cn == 3 || cn == 4 );
dst.create(src.size(), src.type());
funcs[depth][cn - 1](src, sc, dst, StreamAccessor::getStream(stream));
arithm_op(src1, src2, dst, mask, 1.0, -1, stream, bitMat, bitScalar, BIT_OP_OR);
}
void cv::gpu::bitwise_xor(const GpuMat& src, const Scalar& sc, GpuMat& dst, Stream& stream)
void cv::gpu::bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask, Stream& stream)
{
using namespace arithm;
typedef void (*func_t)(const GpuMat& src, Scalar sc, GpuMat& dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{BitScalar<unsigned char, bitScalarXor<unsigned char> >::call , 0, NppBitwiseC<CV_8U , 3, nppiXorC_8u_C3R >::call, BitScalar4< bitScalarXor<unsigned int> >::call},
{0,0,0,0},
{BitScalar<unsigned short, bitScalarXor<unsigned short> >::call, 0, NppBitwiseC<CV_16U, 3, nppiXorC_16u_C3R>::call, NppBitwiseC<CV_16U, 4, nppiXorC_16u_C4R>::call},
{0,0,0,0},
{BitScalar<int, bitScalarXor<int> >::call , 0, NppBitwiseC<CV_32S, 3, nppiXorC_32s_C3R>::call, NppBitwiseC<CV_32S, 4, nppiXorC_32s_C4R>::call}
};
const int depth = src.depth();
const int cn = src.channels();
CV_Assert( depth == CV_8U || depth == CV_16U || depth == CV_32S );
CV_Assert( cn == 1 || cn == 3 || cn == 4 );
dst.create(src.size(), src.type());
arithm_op(src1, src2, dst, mask, 1.0, -1, stream, bitMat, bitScalar, BIT_OP_AND);
}
funcs[depth][cn - 1](src, sc, dst, StreamAccessor::getStream(stream));
void cv::gpu::bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask, Stream& stream)
{
arithm_op(src1, src2, dst, mask, 1.0, -1, stream, bitMat, bitScalar, BIT_OP_XOR);
}
//////////////////////////////////////////////////////////////////////////////
......
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