Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

switched to Input/Output Array in min/max operations

Browse Source
pull/978/head
Vladislav Vinogradov 12 years ago
parent f2aa6ebe15
commit ec70282bf7
4 changed files with 82 additions and 187 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 18
      modules/gpuarithm/include/opencv2/gpuarithm.hpp
  2. 247
      modules/gpuarithm/src/element_operations.cpp
  3. 2
      modules/gpuimgproc/src/hough.cpp
  4. 2
      modules/nonfree/src/surf_gpu.cpp

18
modules/gpuarithm/include/opencv2/gpuarithm.hpp
Unescape View File

@ -115,6 +115,12 @@ CV_EXPORTS void rshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void lshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream& stream = Stream::Null());
//! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS void min(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
//! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS void max(InputArray src1, InputArray src2, OutputArray dst, 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());
@ -125,18 +131,6 @@ static inline void scaleAdd(const GpuMat& src1, double alpha, const GpuMat& src2
addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
}
//! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element minimum of array and scalar (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of array and scalar (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
//! implements generalized matrix product algorithm GEMM from BLAS
CV_EXPORTS void gemm(const GpuMat& src1, const GpuMat& src2, double alpha,
const GpuMat& src3, double beta, GpuMat& dst, int flags = 0, Stream& stream = Stream::Null());

247
modules/gpuarithm/src/element_operations.cpp
Unescape View File

@ -48,46 +48,30 @@ using namespace cv::gpu;
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
void cv::gpu::add(InputArray, InputArray, OutputArray, InputArray, int, Stream&) { throw_no_cuda(); }
void cv::gpu::subtract(InputArray, InputArray, OutputArray, InputArray, int, Stream&) { throw_no_cuda(); }
void cv::gpu::multiply(InputArray, InputArray, OutputArray, double, int, Stream&) { throw_no_cuda(); }
void cv::gpu::divide(InputArray, InputArray, OutputArray, double, int, Stream&) { throw_no_cuda(); }
void cv::gpu::absdiff(InputArray, InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::abs(InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::sqr(InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::sqrt(InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::exp(InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::log(InputArray, OutputArray, Stream&) { throw_no_cuda(); }
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(InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_or(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_and(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::bitwise_xor(InputArray, InputArray, OutputArray, InputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::rshift(InputArray, Scalar_<int>, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::lshift(InputArray, Scalar_<int>, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::min(const GpuMat&, double, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::min(InputArray, InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::max(InputArray, InputArray, OutputArray, Stream&) { throw_no_cuda(); }
void cv::gpu::addWeighted(const GpuMat&, double, const GpuMat&, double, double, GpuMat&, int, Stream&) { throw_no_cuda(); }
@ -2262,6 +2246,15 @@ void cv::gpu::lshift(InputArray _src, Scalar_<int> val, OutputArray _dst, Stream
//////////////////////////////////////////////////////////////////////////////
// Minimum and maximum operations
namespace
{
enum
{
MIN_OP,
MAX_OP
};
}
namespace arithm
{
void minMat_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
@ -2275,116 +2268,49 @@ namespace arithm
template <typename T> void maxScalar(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
}
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s)
void minMaxMat(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat&, double, Stream& _stream, int op)
{
using namespace arithm;
typedef void (*func_t)(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
static const func_t funcs[2][7] =
{
minMat<unsigned char>,
minMat<signed char>,
minMat<unsigned short>,
minMat<short>,
minMat<int>,
minMat<float>,
minMat<double>
};
const int depth = src1.depth();
const int cn = src1.channels();
CV_Assert( depth <= CV_64F );
CV_Assert( src2.type() == src1.type() && src2.size() == src1.size() );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
cudaStream_t stream = StreamAccessor::getStream(s);
PtrStepSzb src1_(src1.rows, src1.cols * cn, src1.data, src1.step);
PtrStepSzb src2_(src1.rows, src1.cols * cn, src2.data, src2.step);
PtrStepSzb dst_(src1.rows, src1.cols * cn, dst.data, dst.step);
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)
{
const int vcols = src1_.cols >> 2;
minMat_v4(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
return;
}
else if (depth == CV_16U && (src1_.cols & 1) == 0)
{
const int vcols = src1_.cols >> 1;
minMat_v2(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
return;
}
minMat<unsigned char>,
minMat<signed char>,
minMat<unsigned short>,
minMat<short>,
minMat<int>,
minMat<float>,
minMat<double>
},
{
maxMat<unsigned char>,
maxMat<signed char>,
maxMat<unsigned short>,
maxMat<short>,
maxMat<int>,
maxMat<float>,
maxMat<double>
}
}
const func_t func = funcs[depth];
if (!func)
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");
func(src1_, src2_, dst_, stream);
}
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s)
{
using namespace arithm;
};
typedef void (*func_t)(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
typedef void (*opt_func_t)(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
static const opt_func_t funcs_v4[2] =
{
minMat_v4, maxMat_v4
};
static const opt_func_t funcs_v2[2] =
{
maxMat<unsigned char>,
maxMat<signed char>,
maxMat<unsigned short>,
maxMat<short>,
maxMat<int>,
maxMat<float>,
maxMat<double>
minMat_v2, maxMat_v2
};
const int depth = src1.depth();
const int cn = src1.channels();
CV_Assert( depth <= CV_64F );
CV_Assert( src2.type() == src1.type() && src2.size() == src1.size() );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src1.size(), src1.type());
cudaStream_t stream = StreamAccessor::getStream(s);
cudaStream_t stream = StreamAccessor::getStream(_stream);
PtrStepSzb src1_(src1.rows, src1.cols * cn, src1.data, src1.step);
PtrStepSzb src2_(src1.rows, src1.cols * cn, src2.data, src2.step);
@ -2404,10 +2330,10 @@ void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s
{
const int vcols = src1_.cols >> 2;
maxMat_v4(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
funcs_v4[op](PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
return;
}
@ -2415,17 +2341,17 @@ void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s
{
const int vcols = src1_.cols >> 1;
maxMat_v2(PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
funcs_v2[op](PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src1_.data, src1_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) src2_.data, src2_.step),
PtrStepSz<unsigned int>(src1_.rows, vcols, (unsigned int*) dst_.data, dst_.step),
stream);
return;
}
}
}
const func_t func = funcs[depth];
const func_t func = funcs[op][depth];
if (!func)
CV_Error(cv::Error::StsUnsupportedFormat, "Unsupported combination of source and destination types");
@ -2441,20 +2367,31 @@ namespace
}
}
void cv::gpu::min(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
void minMaxScalar(const GpuMat& src, Scalar val, bool, GpuMat& dst, const GpuMat&, double, Stream& stream, int op)
{
using namespace arithm;
typedef void (*func_t)(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
static const func_t funcs[2][7] =
{
minScalar<unsigned char>,
minScalar<signed char>,
minScalar<unsigned short>,
minScalar<short>,
minScalar<int>,
minScalar<float>,
minScalar<double>
{
minScalar<unsigned char>,
minScalar<signed char>,
minScalar<unsigned short>,
minScalar<short>,
minScalar<int>,
minScalar<float>,
minScalar<double>
},
{
maxScalar<unsigned char>,
maxScalar<signed char>,
maxScalar<unsigned short>,
maxScalar<short>,
maxScalar<int>,
maxScalar<float>,
maxScalar<double>
}
};
typedef double (*cast_func_t)(double sc);
@ -2468,53 +2405,17 @@ void cv::gpu::min(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
CV_Assert( depth <= CV_64F );
CV_Assert( src.channels() == 1 );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
funcs[depth](src, cast_func[depth](val), dst, StreamAccessor::getStream(stream));
funcs[op][depth](src, cast_func[depth](val[0]), dst, StreamAccessor::getStream(stream));
}
void cv::gpu::max(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
void cv::gpu::min(InputArray src1, InputArray src2, OutputArray dst, Stream& stream)
{
using namespace arithm;
typedef void (*func_t)(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
maxScalar<unsigned char>,
maxScalar<signed char>,
maxScalar<unsigned short>,
maxScalar<short>,
maxScalar<int>,
maxScalar<float>,
maxScalar<double>
};
typedef double (*cast_func_t)(double sc);
static const cast_func_t cast_func[] =
{
castScalar<unsigned char>, castScalar<signed char>, castScalar<unsigned short>, castScalar<short>, castScalar<int>, castScalar<float>, castScalar<double>
};
const int depth = src.depth();
CV_Assert( depth <= CV_64F );
CV_Assert( src.channels() == 1 );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
arithm_op(src1, src2, dst, noArray(), 1.0, -1, stream, minMaxMat, minMaxScalar, MIN_OP);
}
funcs[depth](src, cast_func[depth](val), dst, StreamAccessor::getStream(stream));
void cv::gpu::max(InputArray src1, InputArray src2, OutputArray dst, Stream& stream)
{
arithm_op(src1, src2, dst, noArray(), 1.0, -1, stream, minMaxMat, minMaxScalar, MAX_OP);
}
////////////////////////////////////////////////////////////////////////

2
modules/gpuimgproc/src/hough.cpp
Unescape View File

@ -761,7 +761,7 @@ namespace
{
buildRTable_gpu(edgePointList.ptr<unsigned int>(0), edgePointList.ptr<float>(1), edgePointList.cols,
r_table, r_sizes.ptr<int>(), make_short2(templCenter.x, templCenter.y), levels);
min(r_sizes, maxSize, r_sizes);
gpu::min(r_sizes, maxSize, r_sizes);
}
}

2
modules/nonfree/src/surf_gpu.cpp
Unescape View File

@ -147,7 +147,7 @@ namespace
if (use_mask)
{
min(mask, 1.0, surf_.mask1);
gpu::min(mask, 1.0, surf_.mask1);
gpu::integralBuffered(surf_.mask1, surf_.maskSum, surf_.intBuffer);
maskOffset = bindMaskSumTex(surf_.maskSum);
}

Write Preview
Loading…
Cancel
Save