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Commit e8f9762e authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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matrix reduction

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modules/gpu/src/cuda/matrix_reductions.cu
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modules/gpu/src/matrix_reductions.cpp
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...@@ -204,34 +204,19 @@ double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType) ...@@ -204,34 +204,19 @@ double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
//////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////
// Sum // Sum
namespace cv { namespace gpu { namespace device namespace sum
{ {
namespace matrix_reductions void getBufSize(int cols, int rows, int cn, int& bufcols, int& bufrows);
{
namespace sum
{
template <typename T>
void sumCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn);
template <typename T>
void sumMultipassCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn);
template <typename T>
void absSumCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn);
template <typename T> template <typename T, int cn>
void absSumMultipassCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn); void run(PtrStepSzb src, void* buf, double* sum);
template <typename T> template <typename T, int cn>
void sqrSumCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn); void runAbs(PtrStepSzb src, void* buf, double* sum);
template <typename T> template <typename T, int cn>
void sqrSumMultipassCaller(const PtrStepSzb src, PtrStepb buf, double* sum, int cn); void runSqr(PtrStepSzb src, void* buf, double* sum);
}
void getBufSizeRequired(int cols, int rows, int cn, int& bufcols, int& bufrows);
}
}
}}}
Scalar cv::gpu::sum(const GpuMat& src) Scalar cv::gpu::sum(const GpuMat& src)
{ {
...@@ -239,159 +224,115 @@ Scalar cv::gpu::sum(const GpuMat& src) ...@@ -239,159 +224,115 @@ Scalar cv::gpu::sum(const GpuMat& src)
return sum(src, buf); return sum(src, buf);
} }
Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf) Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
{ {
using namespace cv::gpu::device::matrix_reductions::sum; typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum);
static const func_t funcs[7][5] =
typedef void (*Caller)(const PtrStepSzb, PtrStepb, double*, int);
static Caller multipass_callers[] =
{ {
sumMultipassCaller<unsigned char>, sumMultipassCaller<char>, {0, ::sum::run<uchar , 1>, ::sum::run<uchar , 2>, ::sum::run<uchar , 3>, ::sum::run<uchar , 4>},
sumMultipassCaller<unsigned short>, sumMultipassCaller<short>, {0, ::sum::run<schar , 1>, ::sum::run<schar , 2>, ::sum::run<schar , 3>, ::sum::run<schar , 4>},
sumMultipassCaller<int>, sumMultipassCaller<float> {0, ::sum::run<ushort, 1>, ::sum::run<ushort, 2>, ::sum::run<ushort, 3>, ::sum::run<ushort, 4>},
{0, ::sum::run<short , 1>, ::sum::run<short , 2>, ::sum::run<short , 3>, ::sum::run<short , 4>},
{0, ::sum::run<int , 1>, ::sum::run<int , 2>, ::sum::run<int , 3>, ::sum::run<int , 4>},
{0, ::sum::run<float , 1>, ::sum::run<float , 2>, ::sum::run<float , 3>, ::sum::run<float , 4>},
{0, ::sum::run<double, 1>, ::sum::run<double, 2>, ::sum::run<double, 3>, ::sum::run<double, 4>}
}; };
static Caller singlepass_callers[] = { if (src.depth() == CV_64F)
sumCaller<unsigned char>, sumCaller<char>, {
sumCaller<unsigned short>, sumCaller<short>, if (!TargetArchs::builtWith(NATIVE_DOUBLE) || !DeviceInfo().supports(NATIVE_DOUBLE))
sumCaller<int>, sumCaller<float> CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
}; }
CV_Assert(src.depth() <= CV_32F);
Size buf_size; Size buf_size;
getBufSizeRequired(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); ::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf); ensureSizeIsEnough(buf_size, CV_8U, buf);
buf.setTo(Scalar::all(0));
Caller* callers = multipass_callers; const func_t func = funcs[src.depth()][src.channels()];
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Caller caller = callers[src.depth()];
double result[4]; double result[4];
caller(src, buf, result, src.channels()); func(src, buf.data, result);
return Scalar(result[0], result[1], result[2], result[3]); return Scalar(result[0], result[1], result[2], result[3]);
} }
Scalar cv::gpu::absSum(const GpuMat& src) Scalar cv::gpu::absSum(const GpuMat& src)
{ {
GpuMat buf; GpuMat buf;
return absSum(src, buf); return absSum(src, buf);
} }
Scalar cv::gpu::absSum(const GpuMat& src, GpuMat& buf) Scalar cv::gpu::absSum(const GpuMat& src, GpuMat& buf)
{ {
using namespace cv::gpu::device::matrix_reductions::sum; typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum);
static const func_t funcs[7][5] =
typedef void (*Caller)(const PtrStepSzb, PtrStepb, double*, int);
static Caller multipass_callers[] =
{
absSumMultipassCaller<unsigned char>, absSumMultipassCaller<char>,
absSumMultipassCaller<unsigned short>, absSumMultipassCaller<short>,
absSumMultipassCaller<int>, absSumMultipassCaller<float>
};
static Caller singlepass_callers[] =
{ {
absSumCaller<unsigned char>, absSumCaller<char>, {0, ::sum::runAbs<uchar , 1>, ::sum::runAbs<uchar , 2>, ::sum::runAbs<uchar , 3>, ::sum::runAbs<uchar , 4>},
absSumCaller<unsigned short>, absSumCaller<short>, {0, ::sum::runAbs<schar , 1>, ::sum::runAbs<schar , 2>, ::sum::runAbs<schar , 3>, ::sum::runAbs<schar , 4>},
absSumCaller<int>, absSumCaller<float> {0, ::sum::runAbs<ushort, 1>, ::sum::runAbs<ushort, 2>, ::sum::runAbs<ushort, 3>, ::sum::runAbs<ushort, 4>},
{0, ::sum::runAbs<short , 1>, ::sum::runAbs<short , 2>, ::sum::runAbs<short , 3>, ::sum::runAbs<short , 4>},
{0, ::sum::runAbs<int , 1>, ::sum::runAbs<int , 2>, ::sum::runAbs<int , 3>, ::sum::runAbs<int , 4>},
{0, ::sum::runAbs<float , 1>, ::sum::runAbs<float , 2>, ::sum::runAbs<float , 3>, ::sum::runAbs<float , 4>},
{0, ::sum::runAbs<double, 1>, ::sum::runAbs<double, 2>, ::sum::runAbs<double, 3>, ::sum::runAbs<double, 4>}
}; };
CV_Assert(src.depth() <= CV_32F);
Size buf_size; Size buf_size;
getBufSizeRequired(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); ::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf); ensureSizeIsEnough(buf_size, CV_8U, buf);
buf.setTo(Scalar::all(0));
Caller* callers = multipass_callers; const func_t func = funcs[src.depth()][src.channels()];
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Caller caller = callers[src.depth()];
double result[4]; double result[4];
caller(src, buf, result, src.channels()); func(src, buf.data, result);
return Scalar(result[0], result[1], result[2], result[3]); return Scalar(result[0], result[1], result[2], result[3]);
} }
Scalar cv::gpu::sqrSum(const GpuMat& src) Scalar cv::gpu::sqrSum(const GpuMat& src)
{ {
GpuMat buf; GpuMat buf;
return sqrSum(src, buf); return sqrSum(src, buf);
} }
Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf) Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
{ {
using namespace cv::gpu::device::matrix_reductions::sum; typedef void (*func_t)(PtrStepSzb src, void* buf, double* sum);
static const func_t funcs[7][5] =
typedef void (*Caller)(const PtrStepSzb, PtrStepb, double*, int);
static Caller multipass_callers[] =
{ {
sqrSumMultipassCaller<unsigned char>, sqrSumMultipassCaller<char>, {0, ::sum::runSqr<uchar , 1>, ::sum::runSqr<uchar , 2>, ::sum::runSqr<uchar , 3>, ::sum::runSqr<uchar , 4>},
sqrSumMultipassCaller<unsigned short>, sqrSumMultipassCaller<short>, {0, ::sum::runSqr<schar , 1>, ::sum::runSqr<schar , 2>, ::sum::runSqr<schar , 3>, ::sum::runSqr<schar , 4>},
sqrSumMultipassCaller<int>, sqrSumMultipassCaller<float> {0, ::sum::runSqr<ushort, 1>, ::sum::runSqr<ushort, 2>, ::sum::runSqr<ushort, 3>, ::sum::runSqr<ushort, 4>},
{0, ::sum::runSqr<short , 1>, ::sum::runSqr<short , 2>, ::sum::runSqr<short , 3>, ::sum::runSqr<short , 4>},
{0, ::sum::runSqr<int , 1>, ::sum::runSqr<int , 2>, ::sum::runSqr<int , 3>, ::sum::runSqr<int , 4>},
{0, ::sum::runSqr<float , 1>, ::sum::runSqr<float , 2>, ::sum::runSqr<float , 3>, ::sum::runSqr<float , 4>},
{0, ::sum::runSqr<double, 1>, ::sum::runSqr<double, 2>, ::sum::runSqr<double, 3>, ::sum::runSqr<double, 4>}
}; };
static Caller singlepass_callers[7] =
{
sqrSumCaller<unsigned char>, sqrSumCaller<char>,
sqrSumCaller<unsigned short>, sqrSumCaller<short>,
sqrSumCaller<int>, sqrSumCaller<float>
};
CV_Assert(src.depth() <= CV_32F);
Caller* callers = multipass_callers;
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Size buf_size; Size buf_size;
getBufSizeRequired(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height); ::sum::getBufSize(src.cols, src.rows, src.channels(), buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf); ensureSizeIsEnough(buf_size, CV_8U, buf);
buf.setTo(Scalar::all(0));
Caller caller = callers[src.depth()]; const func_t func = funcs[src.depth()][src.channels()];
double result[4]; double result[4];
caller(src, buf, result, src.channels()); func(src, buf.data, result);
return Scalar(result[0], result[1], result[2], result[3]); return Scalar(result[0], result[1], result[2], result[3]);
} }
//////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////
// Find min or max // minMax
namespace cv { namespace gpu { namespace device namespace minMax
{ {
namespace matrix_reductions void getBufSize(int cols, int rows, int& bufcols, int& bufrows);
{
namespace minmax
{
void getBufSizeRequired(int cols, int rows, int elem_size, int& bufcols, int& bufrows);
template <typename T>
void minMaxCaller(const PtrStepSzb src, double* minval, double* maxval, PtrStepb buf);
template <typename T>
void minMaxMaskCaller(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template <typename T>
void minMaxMultipassCaller(const PtrStepSzb src, double* minval, double* maxval, PtrStepb buf);
template <typename T>
void minMaxMaskMultipassCaller(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
}
}
}}}
template <typename T>
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
}
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask) void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask)
{ {
...@@ -399,45 +340,22 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const Gp ...@@ -399,45 +340,22 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const Gp
minMax(src, minVal, maxVal, mask, buf); minMax(src, minVal, maxVal, mask, buf);
} }
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf) void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
{ {
using namespace ::cv::gpu::device::matrix_reductions::minmax; typedef void (*func_t)(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
static const func_t funcs[] =
typedef void (*Caller)(const PtrStepSzb, double*, double*, PtrStepb);
typedef void (*MaskedCaller)(const PtrStepSzb, const PtrStepb, double*, double*, PtrStepb);
static Caller multipass_callers[] =
{
minMaxMultipassCaller<unsigned char>, minMaxMultipassCaller<char>,
minMaxMultipassCaller<unsigned short>, minMaxMultipassCaller<short>,
minMaxMultipassCaller<int>, minMaxMultipassCaller<float>, 0
};
static Caller singlepass_callers[] =
{
minMaxCaller<unsigned char>, minMaxCaller<char>,
minMaxCaller<unsigned short>, minMaxCaller<short>,
minMaxCaller<int>, minMaxCaller<float>, minMaxCaller<double>
};
static MaskedCaller masked_multipass_callers[] =
{
minMaxMaskMultipassCaller<unsigned char>, minMaxMaskMultipassCaller<char>,
minMaxMaskMultipassCaller<unsigned short>, minMaxMaskMultipassCaller<short>,
minMaxMaskMultipassCaller<int>, minMaxMaskMultipassCaller<float>, 0
};
static MaskedCaller masked_singlepass_callers[] =
{ {
minMaxMaskCaller<unsigned char>, minMaxMaskCaller<char>, ::minMax::run<uchar>,
minMaxMaskCaller<unsigned short>, minMaxMaskCaller<short>, ::minMax::run<schar>,
minMaxMaskCaller<int>, minMaxMaskCaller<float>, minMaxMaskCaller<double> ::minMax::run<ushort>,
::minMax::run<short>,
::minMax::run<int>,
::minMax::run<float>,
::minMax::run<double>
}; };
CV_Assert(src.depth() <= CV_64F); CV_Assert( src.channels() == 1 );
CV_Assert(src.channels() == 1); CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) );
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
if (src.depth() == CV_64F) if (src.depth() == CV_64F)
{ {
...@@ -445,66 +363,26 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const Gp ...@@ -445,66 +363,26 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const Gp
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
} }
double minVal_; if (!minVal) minVal = &minVal_;
double maxVal_; if (!maxVal) maxVal = &maxVal_;
Size buf_size; Size buf_size;
getBufSizeRequired(src.cols, src.rows, static_cast<int>(src.elemSize()), buf_size.width, buf_size.height); ::minMax::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf); ensureSizeIsEnough(buf_size, CV_8U, buf);
if (mask.empty()) const func_t func = funcs[src.depth()];
{
Caller* callers = multipass_callers;
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Caller caller = callers[src.type()];
CV_Assert(caller != 0);
caller(src, minVal, maxVal, buf);
}
else
{
MaskedCaller* callers = masked_multipass_callers;
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = masked_singlepass_callers;
MaskedCaller caller = callers[src.type()]; double temp1, temp2;
CV_Assert(caller != 0); func(src, mask, minVal ? minVal : &temp1, maxVal ? maxVal : &temp2, buf);
caller(src, mask, minVal, maxVal, buf);
}
} }
//////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////
// Locate min and max // minMaxLoc
namespace cv { namespace gpu { namespace device namespace minMaxLoc
{ {
namespace matrix_reductions void getBufSize(int cols, int rows, size_t elem_size, int& b1cols, int& b1rows, int& b2cols, int& b2rows);
{
namespace minmaxloc
{
void getBufSizeRequired(int cols, int rows, int elem_size, int& b1cols,
int& b1rows, int& b2cols, int& b2rows);
template <typename T>
void minMaxLocCaller(const PtrStepSzb src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStepb valBuf, PtrStepb locBuf);
template <typename T>
void minMaxLocMaskCaller(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStepb valBuf, PtrStepb locBuf);
template <typename T>
void minMaxLocMultipassCaller(const PtrStepSzb src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStepb valBuf, PtrStepb locBuf);
template <typename T> template <typename T>
void minMaxLocMaskMultipassCaller(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
int minloc[2], int maxloc[2], PtrStepb valBuf, PtrStepb locBuf); }
}
}
}}}
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask) void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask)
{ {
...@@ -515,42 +393,20 @@ void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point ...@@ -515,42 +393,20 @@ void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
const GpuMat& mask, GpuMat& valBuf, GpuMat& locBuf) const GpuMat& mask, GpuMat& valBuf, GpuMat& locBuf)
{ {
using namespace ::cv::gpu::device::matrix_reductions::minmaxloc; typedef void (*func_t)(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
static const func_t funcs[] =
typedef void (*Caller)(const PtrStepSzb, double*, double*, int[2], int[2], PtrStepb, PtrStepb);
typedef void (*MaskedCaller)(const PtrStepSzb, const PtrStepb, double*, double*, int[2], int[2], PtrStepb, PtrStepb);
static Caller multipass_callers[] =
{
minMaxLocMultipassCaller<unsigned char>, minMaxLocMultipassCaller<char>,
minMaxLocMultipassCaller<unsigned short>, minMaxLocMultipassCaller<short>,
minMaxLocMultipassCaller<int>, minMaxLocMultipassCaller<float>, 0
};
static Caller singlepass_callers[] =
{ {
minMaxLocCaller<unsigned char>, minMaxLocCaller<char>, ::minMaxLoc::run<uchar>,
minMaxLocCaller<unsigned short>, minMaxLocCaller<short>, ::minMaxLoc::run<schar>,
minMaxLocCaller<int>, minMaxLocCaller<float>, minMaxLocCaller<double> ::minMaxLoc::run<ushort>,
::minMaxLoc::run<short>,
::minMaxLoc::run<int>,
::minMaxLoc::run<float>,
::minMaxLoc::run<double>
}; };
static MaskedCaller masked_multipass_callers[] = CV_Assert( src.channels() == 1 );
{ CV_Assert( mask.empty() || (mask.size() == src.size() && mask.type() == CV_8U) );
minMaxLocMaskMultipassCaller<unsigned char>, minMaxLocMaskMultipassCaller<char>,
minMaxLocMaskMultipassCaller<unsigned short>, minMaxLocMaskMultipassCaller<short>,
minMaxLocMaskMultipassCaller<int>, minMaxLocMaskMultipassCaller<float>, 0
};
static MaskedCaller masked_singlepass_callers[] =
{
minMaxLocMaskCaller<unsigned char>, minMaxLocMaskCaller<char>,
minMaxLocMaskCaller<unsigned short>, minMaxLocMaskCaller<short>,
minMaxLocMaskCaller<int>, minMaxLocMaskCaller<float>, minMaxLocMaskCaller<double>
};
CV_Assert(src.depth() <= CV_64F);
CV_Assert(src.channels() == 1);
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
if (src.depth() == CV_64F) if (src.depth() == CV_64F)
{ {
...@@ -558,61 +414,28 @@ void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point ...@@ -558,61 +414,28 @@ void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point
CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double"); CV_Error(CV_StsUnsupportedFormat, "The device doesn't support double");
} }
double minVal_; if (!minVal) minVal = &minVal_;
double maxVal_; if (!maxVal) maxVal = &maxVal_;
int minLoc_[2];
int maxLoc_[2];
Size valbuf_size, locbuf_size; Size valbuf_size, locbuf_size;
getBufSizeRequired(src.cols, src.rows, static_cast<int>(src.elemSize()), valbuf_size.width, ::minMaxLoc::getBufSize(src.cols, src.rows, src.elemSize(), valbuf_size.width, valbuf_size.height, locbuf_size.width, locbuf_size.height);
valbuf_size.height, locbuf_size.width, locbuf_size.height);
ensureSizeIsEnough(valbuf_size, CV_8U, valBuf); ensureSizeIsEnough(valbuf_size, CV_8U, valBuf);
ensureSizeIsEnough(locbuf_size, CV_8U, locBuf); ensureSizeIsEnough(locbuf_size, CV_8U, locBuf);
if (mask.empty()) const func_t func = funcs[src.depth()];
{
Caller* callers = multipass_callers;
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Caller caller = callers[src.type()];
CV_Assert(caller != 0);
caller(src, minVal, maxVal, minLoc_, maxLoc_, valBuf, locBuf);
}
else
{
MaskedCaller* callers = masked_multipass_callers;
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = masked_singlepass_callers;
MaskedCaller caller = callers[src.type()];
CV_Assert(caller != 0);
caller(src, mask, minVal, maxVal, minLoc_, maxLoc_, valBuf, locBuf);
}
if (minLoc) { minLoc->x = minLoc_[0]; minLoc->y = minLoc_[1]; } double temp1, temp2;
if (maxLoc) { maxLoc->x = maxLoc_[0]; maxLoc->y = maxLoc_[1]; } Point temp3, temp4;
func(src, mask, minVal ? minVal : &temp1, maxVal ? maxVal : &temp2, minLoc ? &minLoc->x : &temp3.x, maxLoc ? &maxLoc->x : &temp4.x, valBuf, locBuf);
} }
////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////
// Count non-zero elements // countNonZero
namespace cv { namespace gpu { namespace device namespace countNonZero
{ {
namespace matrix_reductions void getBufSize(int cols, int rows, int& bufcols, int& bufrows);
{
namespace countnonzero
{
void getBufSizeRequired(int cols, int rows, int& bufcols, int& bufrows);
template <typename T> template <typename T>
int countNonZeroCaller(const PtrStepSzb src, PtrStepb buf); int run(const PtrStepSzb src, PtrStep<unsigned int> buf);
}
template <typename T>
int countNonZeroMultipassCaller(const PtrStepSzb src, PtrStepb buf);
}
}
}}}
int cv::gpu::countNonZero(const GpuMat& src) int cv::gpu::countNonZero(const GpuMat& src)
{ {
...@@ -620,27 +443,20 @@ int cv::gpu::countNonZero(const GpuMat& src) ...@@ -620,27 +443,20 @@ int cv::gpu::countNonZero(const GpuMat& src)
return countNonZero(src, buf); return countNonZero(src, buf);
} }
int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf) int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf)
{ {
using namespace ::cv::gpu::device::matrix_reductions::countnonzero; typedef int (*func_t)(const PtrStepSzb src, PtrStep<unsigned int> buf);
static const func_t funcs[] =
typedef int (*Caller)(const PtrStepSzb src, PtrStepb buf);
static Caller multipass_callers[7] =
{ {
countNonZeroMultipassCaller<unsigned char>, countNonZeroMultipassCaller<char>, ::countNonZero::run<uchar>,
countNonZeroMultipassCaller<unsigned short>, countNonZeroMultipassCaller<short>, ::countNonZero::run<schar>,
countNonZeroMultipassCaller<int>, countNonZeroMultipassCaller<float>, 0 ::countNonZero::run<ushort>,
::countNonZero::run<short>,
::countNonZero::run<int>,
::countNonZero::run<float>,
::countNonZero::run<double>
}; };
static Caller singlepass_callers[7] =
{
countNonZeroCaller<unsigned char>, countNonZeroCaller<char>,
countNonZeroCaller<unsigned short>, countNonZeroCaller<short>,
countNonZeroCaller<int>, countNonZeroCaller<float>, countNonZeroCaller<double> };
CV_Assert(src.depth() <= CV_64F);
CV_Assert(src.channels() == 1); CV_Assert(src.channels() == 1);
if (src.depth() == CV_64F) if (src.depth() == CV_64F)
...@@ -650,168 +466,190 @@ int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf) ...@@ -650,168 +466,190 @@ int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf)
} }
Size buf_size; Size buf_size;
getBufSizeRequired(src.cols, src.rows, buf_size.width, buf_size.height); ::countNonZero::getBufSize(src.cols, src.rows, buf_size.width, buf_size.height);
ensureSizeIsEnough(buf_size, CV_8U, buf); ensureSizeIsEnough(buf_size, CV_8U, buf);
Caller* callers = multipass_callers; const func_t func = funcs[src.depth()];
if (TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS))
callers = singlepass_callers;
Caller caller = callers[src.type()]; return func(src, buf);
CV_Assert(caller != 0);
return caller(src, buf);
} }
////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////
// reduce // reduce
namespace cv { namespace gpu { namespace device namespace reduce
{ {
namespace matrix_reductions template <typename T, typename S, typename D>
{ void rows(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template <typename T, typename S, typename D> void reduceRows_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int reduceOp, cudaStream_t stream);
template <typename T, typename S, typename D> void reduceCols_gpu(const PtrStepSzb& src, int cn, const PtrStepSzb& dst, int reduceOp, cudaStream_t stream); template <typename T, typename S, typename D>
} void cols(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
}}} }
void cv::gpu::reduce(const GpuMat& src, GpuMat& dst, int dim, int reduceOp, int dtype, Stream& stream) void cv::gpu::reduce(const GpuMat& src, GpuMat& dst, int dim, int reduceOp, int dtype, Stream& stream)
{ {
using namespace ::cv::gpu::device::matrix_reductions; CV_Assert( src.channels() <= 4 );
CV_Assert( dim == 0 || dim == 1 );
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4 && dtype <= CV_32F); CV_Assert( reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG || reduceOp == CV_REDUCE_MAX || reduceOp == CV_REDUCE_MIN );
CV_Assert(dim == 0 || dim == 1);
CV_Assert(reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG || reduceOp == CV_REDUCE_MAX || reduceOp == CV_REDUCE_MIN);
if (dtype < 0) if (dtype < 0)
dtype = src.depth(); dtype = src.depth();
dst.create(1, dim == 0 ? src.cols : src.rows, CV_MAKETYPE(dtype, src.channels())); dst.create(1, dim == 0 ? src.cols : src.rows, CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()));
if (dim == 0) if (dim == 0)
{ {
typedef void (*caller_t)(const PtrStepSzb& src, const PtrStepSzb& dst, int reduceOp, cudaStream_t stream); typedef void (*func_t)(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
static const func_t funcs[7][7] =
static const caller_t callers[6][6] =
{ {
{ {
reduceRows_gpu<unsigned char, int, unsigned char>, ::reduce::rows<unsigned char, int, unsigned char>,
0/*reduceRows_gpu<unsigned char, int, signed char>*/, 0/*::reduce::rows<unsigned char, int, signed char>*/,
0/*reduceRows_gpu<unsigned char, int, unsigned short>*/, 0/*::reduce::rows<unsigned char, int, unsigned short>*/,
0/*reduceRows_gpu<unsigned char, int, short>*/, 0/*::reduce::rows<unsigned char, int, short>*/,
reduceRows_gpu<unsigned char, int, int>, ::reduce::rows<unsigned char, int, int>,
reduceRows_gpu<unsigned char, int, float> ::reduce::rows<unsigned char, float, float>,
::reduce::rows<unsigned char, double, double>
},
{
0/*::reduce::rows<signed char, int, unsigned char>*/,
0/*::reduce::rows<signed char, int, signed char>*/,
0/*::reduce::rows<signed char, int, unsigned short>*/,
0/*::reduce::rows<signed char, int, short>*/,
0/*::reduce::rows<signed char, int, int>*/,
0/*::reduce::rows<signed char, float, float>*/,
0/*::reduce::rows<signed char, double, double>*/
}, },
{ {
0/*reduceRows_gpu<signed char, int, unsigned char>*/, 0/*::reduce::rows<unsigned short, int, unsigned char>*/,
0/*reduceRows_gpu<signed char, int, signed char>*/, 0/*::reduce::rows<unsigned short, int, signed char>*/,
0/*reduceRows_gpu<signed char, int, unsigned short>*/, ::reduce::rows<unsigned short, int, unsigned short>,
0/*reduceRows_gpu<signed char, int, short>*/, 0/*::reduce::rows<unsigned short, int, short>*/,
0/*reduceRows_gpu<signed char, int, int>*/, ::reduce::rows<unsigned short, int, int>,
0/*reduceRows_gpu<signed char, int, float>*/ ::reduce::rows<unsigned short, float, float>,
::reduce::rows<unsigned short, double, double>
}, },
{ {
0/*reduceRows_gpu<unsigned short, int, unsigned char>*/, 0/*::reduce::rows<short, int, unsigned char>*/,
0/*reduceRows_gpu<unsigned short, int, signed char>*/, 0/*::reduce::rows<short, int, signed char>*/,
reduceRows_gpu<unsigned short, int, unsigned short>, 0/*::reduce::rows<short, int, unsigned short>*/,
0/*reduceRows_gpu<unsigned short, int, short>*/, ::reduce::rows<short, int, short>,
reduceRows_gpu<unsigned short, int, int>, ::reduce::rows<short, int, int>,
reduceRows_gpu<unsigned short, int, float> ::reduce::rows<short, float, float>,
::reduce::rows<short, double, double>
}, },
{ {
0/*reduceRows_gpu<short, int, unsigned char>*/, 0/*::reduce::rows<int, int, unsigned char>*/,
0/*reduceRows_gpu<short, int, signed char>*/, 0/*::reduce::rows<int, int, signed char>*/,
0/*reduceRows_gpu<short, int, unsigned short>*/, 0/*::reduce::rows<int, int, unsigned short>*/,
reduceRows_gpu<short, int, short>, 0/*::reduce::rows<int, int, short>*/,
reduceRows_gpu<short, int, int>, ::reduce::rows<int, int, int>,
reduceRows_gpu<short, int, float> ::reduce::rows<int, float, float>,
::reduce::rows<int, double, double>
}, },
{ {
0/*reduceRows_gpu<int, int, unsigned char>*/, 0/*::reduce::rows<float, float, unsigned char>*/,
0/*reduceRows_gpu<int, int, signed char>*/, 0/*::reduce::rows<float, float, signed char>*/,
0/*reduceRows_gpu<int, int, unsigned short>*/, 0/*::reduce::rows<float, float, unsigned short>*/,
0/*reduceRows_gpu<int, int, short>*/, 0/*::reduce::rows<float, float, short>*/,
reduceRows_gpu<int, int, int>, 0/*::reduce::rows<float, float, int>*/,
reduceRows_gpu<int, int, float> ::reduce::rows<float, float, float>,
::reduce::rows<float, double, double>
}, },
{ {
0/*reduceRows_gpu<float, float, unsigned char>*/, 0/*::reduce::rows<double, double, unsigned char>*/,
0/*reduceRows_gpu<float, float, signed char>*/, 0/*::reduce::rows<double, double, signed char>*/,
0/*reduceRows_gpu<float, float, unsigned short>*/, 0/*::reduce::rows<double, double, unsigned short>*/,
0/*reduceRows_gpu<float, float, short>*/, 0/*::reduce::rows<double, double, short>*/,
0/*reduceRows_gpu<float, float, int>*/, 0/*::reduce::rows<double, double, int>*/,
reduceRows_gpu<float, float, float> 0/*::reduce::rows<double, double, float>*/,
::reduce::rows<double, double, double>
} }
}; };
const caller_t func = callers[src.depth()][dst.depth()]; const func_t func = funcs[src.depth()][dst.depth()];
if (!func) if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats"); CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats");
func(src.reshape(1), dst.reshape(1), reduceOp, StreamAccessor::getStream(stream)); func(src.reshape(1), dst.data, reduceOp, StreamAccessor::getStream(stream));
} }
else else
{ {
typedef void (*caller_t)(const PtrStepSzb& src, int cn, const PtrStepSzb& dst, int reduceOp, cudaStream_t stream); typedef void (*func_t)(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
static const func_t funcs[7][7] =
static const caller_t callers[6][6] =
{ {
{ {
reduceCols_gpu<unsigned char, int, unsigned char>, ::reduce::cols<unsigned char, int, unsigned char>,
0/*reduceCols_gpu<unsigned char, int, signed char>*/, 0/*::reduce::cols<unsigned char, int, signed char>*/,
0/*reduceCols_gpu<unsigned char, int, unsigned short>*/, 0/*::reduce::cols<unsigned char, int, unsigned short>*/,
0/*reduceCols_gpu<unsigned char, int, short>*/, 0/*::reduce::cols<unsigned char, int, short>*/,
reduceCols_gpu<unsigned char, int, int>, ::reduce::cols<unsigned char, int, int>,
reduceCols_gpu<unsigned char, int, float> ::reduce::cols<unsigned char, float, float>,
::reduce::cols<unsigned char, double, double>
},
{
0/*::reduce::cols<signed char, int, unsigned char>*/,
0/*::reduce::cols<signed char, int, signed char>*/,
0/*::reduce::cols<signed char, int, unsigned short>*/,
0/*::reduce::cols<signed char, int, short>*/,
0/*::reduce::cols<signed char, int, int>*/,
0/*::reduce::cols<signed char, float, float>*/,
0/*::reduce::cols<signed char, double, double>*/
}, },
{ {
0/*reduceCols_gpu<signed char, int, unsigned char>*/, 0/*::reduce::cols<unsigned short, int, unsigned char>*/,
0/*reduceCols_gpu<signed char, int, signed char>*/, 0/*::reduce::cols<unsigned short, int, signed char>*/,
0/*reduceCols_gpu<signed char, int, unsigned short>*/, ::reduce::cols<unsigned short, int, unsigned short>,
0/*reduceCols_gpu<signed char, int, short>*/, 0/*::reduce::cols<unsigned short, int, short>*/,
0/*reduceCols_gpu<signed char, int, int>*/, ::reduce::cols<unsigned short, int, int>,
0/*reduceCols_gpu<signed char, int, float>*/ ::reduce::cols<unsigned short, float, float>,
::reduce::cols<unsigned short, double, double>
}, },
{ {
0/*reduceCols_gpu<unsigned short, int, unsigned char>*/, 0/*::reduce::cols<short, int, unsigned char>*/,
0/*reduceCols_gpu<unsigned short, int, signed char>*/, 0/*::reduce::cols<short, int, signed char>*/,
reduceCols_gpu<unsigned short, int, unsigned short>, 0/*::reduce::cols<short, int, unsigned short>*/,
0/*reduceCols_gpu<unsigned short, int, short>*/, ::reduce::cols<short, int, short>,
reduceCols_gpu<unsigned short, int, int>, ::reduce::cols<short, int, int>,
reduceCols_gpu<unsigned short, int, float> ::reduce::cols<short, float, float>,
::reduce::cols<short, double, double>
}, },
{ {
0/*reduceCols_gpu<short, int, unsigned char>*/, 0/*::reduce::cols<int, int, unsigned char>*/,
0/*reduceCols_gpu<short, int, signed char>*/, 0/*::reduce::cols<int, int, signed char>*/,
0/*reduceCols_gpu<short, int, unsigned short>*/, 0/*::reduce::cols<int, int, unsigned short>*/,
reduceCols_gpu<short, int, short>, 0/*::reduce::cols<int, int, short>*/,
reduceCols_gpu<short, int, int>, ::reduce::cols<int, int, int>,
reduceCols_gpu<short, int, float> ::reduce::cols<int, float, float>,
::reduce::cols<int, double, double>
}, },
{ {
0/*reduceCols_gpu<int, int, unsigned char>*/, 0/*::reduce::cols<float, float, unsigned char>*/,
0/*reduceCols_gpu<int, int, signed char>*/, 0/*::reduce::cols<float, float, signed char>*/,
0/*reduceCols_gpu<int, int, unsigned short>*/, 0/*::reduce::cols<float, float, unsigned short>*/,
0/*reduceCols_gpu<int, int, short>*/, 0/*::reduce::cols<float, float, short>*/,
reduceCols_gpu<int, int, int>, 0/*::reduce::cols<float, float, int>*/,
reduceCols_gpu<int, int, float> ::reduce::cols<float, float, float>,
::reduce::cols<float, double, double>
}, },
{ {
0/*reduceCols_gpu<float, unsigned char>*/, 0/*::reduce::cols<double, double, unsigned char>*/,
0/*reduceCols_gpu<float, signed char>*/, 0/*::reduce::cols<double, double, signed char>*/,
0/*reduceCols_gpu<float, unsigned short>*/, 0/*::reduce::cols<double, double, unsigned short>*/,
0/*reduceCols_gpu<float, short>*/, 0/*::reduce::cols<double, double, short>*/,
0/*reduceCols_gpu<float, int>*/, 0/*::reduce::cols<double, double, int>*/,
reduceCols_gpu<float, float, float> 0/*::reduce::cols<double, double, float>*/,
::reduce::cols<double, double, double>
} }
}; };
const caller_t func = callers[src.depth()][dst.depth()]; const func_t func = funcs[src.depth()][dst.depth()];
if (!func) if (!func)
CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats"); CV_Error(CV_StsUnsupportedFormat, "Unsupported combination of input and output array formats");
func(src, src.channels(), dst, reduceOp, StreamAccessor::getStream(stream)); func(src, dst.data, src.channels(), reduceOp, StreamAccessor::getStream(stream));
} }
} }
......
modules/gpu/test/test_core.cpp
View file @ e8f9762e
...@@ -2982,7 +2982,7 @@ TEST_P(Sum, Sqr) ...@@ -2982,7 +2982,7 @@ TEST_P(Sum, Sqr)
INSTANTIATE_TEST_CASE_P(GPU_Core, Sum, testing::Combine( INSTANTIATE_TEST_CASE_P(GPU_Core, Sum, testing::Combine(
ALL_DEVICES, ALL_DEVICES,
DIFFERENT_SIZES, DIFFERENT_SIZES,
TYPES(CV_8U, CV_32F, 1, 4), TYPES(CV_8U, CV_64F, 1, 4),
WHOLE_SUBMAT)); WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////////////
...@@ -3351,7 +3351,14 @@ PARAM_TEST_CASE(Reduce, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, Reduc ...@@ -3351,7 +3351,14 @@ PARAM_TEST_CASE(Reduce, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, Reduc
cv::gpu::setDevice(devInfo.deviceID()); cv::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, channels); type = CV_MAKE_TYPE(depth, channels);
dst_depth = (reduceOp == CV_REDUCE_MAX || reduceOp == CV_REDUCE_MIN) ? depth : CV_32F;
if (reduceOp == CV_REDUCE_MAX || reduceOp == CV_REDUCE_MIN)
dst_depth = depth;
else if (reduceOp == CV_REDUCE_SUM)
dst_depth = depth == CV_8U ? CV_32S : depth < CV_64F ? CV_32F : depth;
else
dst_depth = depth < CV_32F ? CV_32F : depth;
dst_type = CV_MAKE_TYPE(dst_depth, channels); dst_type = CV_MAKE_TYPE(dst_depth, channels);
} }
...@@ -3392,7 +3399,8 @@ INSTANTIATE_TEST_CASE_P(GPU_Core, Reduce, testing::Combine( ...@@ -3392,7 +3399,8 @@ INSTANTIATE_TEST_CASE_P(GPU_Core, Reduce, testing::Combine(
testing::Values(MatDepth(CV_8U), testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U), MatDepth(CV_16U),
MatDepth(CV_16S), MatDepth(CV_16S),
MatDepth(CV_32F)), MatDepth(CV_32F),
MatDepth(CV_64F)),
ALL_CHANNELS, ALL_CHANNELS,
ALL_REDUCE_CODES, ALL_REDUCE_CODES,
WHOLE_SUBMAT)); WHOLE_SUBMAT));
......
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