generic-library/opencv
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added TransformFunctorTraits, optimized some functions that use transform

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This commit is contained in:
Vladislav Vinogradov
2011-08-17 11:32:24 +00:00
parent 6ce2277cc7
commit 5e9ae6b19f
11 changed files with 591 additions and 312 deletions
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107
modules/gpu/src/element_operations.cpp
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@@ -67,7 +67,6 @@ void cv::gpu::min(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, Stream&) {throw_nogpu(); return 0.0;}
void cv::gpu::pow(const GpuMat&, double, GpuMat&, Stream&) { throw_nogpu(); }
#else
@@ -180,7 +179,7 @@ void cv::gpu::add(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& s
nppArithmCaller(src1, src2, dst, nppiAdd_8u_C1RSfs, nppiAdd_8u_C4RSfs, nppiAdd_32s_C1R, nppiAdd_32f_C1R, StreamAccessor::getStream(stream));
}
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
template <typename T>
void subtractCaller(const DevMem2D src1, const DevMem2D src2, DevMem2D dst, cudaStream_t stream);
@@ -192,7 +191,7 @@ void cv::gpu::subtract(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stre
{
CV_Assert(src1.size() == src2.size());
dst.create(src1.size(), src1.type());
mathfunc::subtractCaller<short>(src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
device::subtractCaller<short>(src1.reshape(1), src2.reshape(1), dst.reshape(1), StreamAccessor::getStream(stream));
}
else
nppArithmCaller(src2, src1, dst, nppiSub_8u_C1RSfs, nppiSub_8u_C4RSfs, nppiSub_32s_C1R, nppiSub_32f_C1R, StreamAccessor::getStream(stream));
@@ -338,7 +337,7 @@ void cv::gpu::absdiff(const GpuMat& src1, const Scalar& src2, GpuMat& dst, Strea
//////////////////////////////////////////////////////////////////////////////
// Comparison of two matrixes
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
void compare_ne_8uc4(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
void compare_ne_32f(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
@@ -375,7 +374,7 @@ void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int c
}
else
{
mathfunc::compare_ne_8uc4(src1, src2, dst, stream);
device::compare_ne_8uc4(src1, src2, dst, stream);
}
}
else
@@ -393,7 +392,7 @@ void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int c
}
else
{
mathfunc::compare_ne_32f(src1, src2, dst, stream);
device::compare_ne_32f(src1, src2, dst, stream);
}
}
}
@@ -402,7 +401,7 @@ void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int c
//////////////////////////////////////////////////////////////////////////////
// Unary bitwise logical operations
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
void bitwiseNotCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStep src, PtrStep dst, cudaStream_t stream);
@@ -416,7 +415,7 @@ namespace
{
dst.create(src.size(), src.type());
cv::gpu::mathfunc::bitwiseNotCaller(src.rows, src.cols, src.elemSize1(),
cv::gpu::device::bitwiseNotCaller(src.rows, src.cols, src.elemSize1(),
dst.channels(), src, dst, stream);
}
@@ -426,10 +425,10 @@ namespace
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwiseMaskNotCaller<unsigned char>, mathfunc::bitwiseMaskNotCaller<unsigned char>,
mathfunc::bitwiseMaskNotCaller<unsigned short>, mathfunc::bitwiseMaskNotCaller<unsigned short>,
mathfunc::bitwiseMaskNotCaller<unsigned int>, mathfunc::bitwiseMaskNotCaller<unsigned int>,
mathfunc::bitwiseMaskNotCaller<unsigned int>};
static Caller callers[] = {device::bitwiseMaskNotCaller<unsigned char>, device::bitwiseMaskNotCaller<unsigned char>,
device::bitwiseMaskNotCaller<unsigned short>, device::bitwiseMaskNotCaller<unsigned short>,
device::bitwiseMaskNotCaller<unsigned int>, device::bitwiseMaskNotCaller<unsigned int>,
device::bitwiseMaskNotCaller<unsigned int>};
CV_Assert(mask.type() == CV_8U && mask.size() == src.size());
dst.create(src.size(), src.type());
@@ -456,7 +455,7 @@ void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, St
//////////////////////////////////////////////////////////////////////////////
// Binary bitwise logical operations
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
void bitwiseOrCaller(int rows, int cols, size_t elem_size1, int cn, const PtrStep src1, const PtrStep src2, PtrStep dst, cudaStream_t stream);
@@ -482,7 +481,7 @@ namespace
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::mathfunc::bitwiseOrCaller(dst.rows, dst.cols, dst.elemSize1(),
cv::gpu::device::bitwiseOrCaller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
@@ -492,10 +491,10 @@ namespace
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwiseMaskOrCaller<unsigned char>, mathfunc::bitwiseMaskOrCaller<unsigned char>,
mathfunc::bitwiseMaskOrCaller<unsigned short>, mathfunc::bitwiseMaskOrCaller<unsigned short>,
mathfunc::bitwiseMaskOrCaller<unsigned int>, mathfunc::bitwiseMaskOrCaller<unsigned int>,
mathfunc::bitwiseMaskOrCaller<unsigned int>};
static Caller callers[] = {device::bitwiseMaskOrCaller<unsigned char>, device::bitwiseMaskOrCaller<unsigned char>,
device::bitwiseMaskOrCaller<unsigned short>, device::bitwiseMaskOrCaller<unsigned short>,
device::bitwiseMaskOrCaller<unsigned int>, device::bitwiseMaskOrCaller<unsigned int>,
device::bitwiseMaskOrCaller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
@@ -513,7 +512,7 @@ namespace
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::mathfunc::bitwiseAndCaller(dst.rows, dst.cols, dst.elemSize1(),
cv::gpu::device::bitwiseAndCaller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
@@ -523,10 +522,10 @@ namespace
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwiseMaskAndCaller<unsigned char>, mathfunc::bitwiseMaskAndCaller<unsigned char>,
mathfunc::bitwiseMaskAndCaller<unsigned short>, mathfunc::bitwiseMaskAndCaller<unsigned short>,
mathfunc::bitwiseMaskAndCaller<unsigned int>, mathfunc::bitwiseMaskAndCaller<unsigned int>,
mathfunc::bitwiseMaskAndCaller<unsigned int>};
static Caller callers[] = {device::bitwiseMaskAndCaller<unsigned char>, device::bitwiseMaskAndCaller<unsigned char>,
device::bitwiseMaskAndCaller<unsigned short>, device::bitwiseMaskAndCaller<unsigned short>,
device::bitwiseMaskAndCaller<unsigned int>, device::bitwiseMaskAndCaller<unsigned int>,
device::bitwiseMaskAndCaller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
@@ -544,7 +543,7 @@ namespace
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
cv::gpu::mathfunc::bitwiseXorCaller(dst.rows, dst.cols, dst.elemSize1(),
cv::gpu::device::bitwiseXorCaller(dst.rows, dst.cols, dst.elemSize1(),
dst.channels(), src1, src2, dst, stream);
}
@@ -554,10 +553,10 @@ namespace
using namespace cv::gpu;
typedef void (*Caller)(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
static Caller callers[] = {mathfunc::bitwiseMaskXorCaller<unsigned char>, mathfunc::bitwiseMaskXorCaller<unsigned char>,
mathfunc::bitwiseMaskXorCaller<unsigned short>, mathfunc::bitwiseMaskXorCaller<unsigned short>,
mathfunc::bitwiseMaskXorCaller<unsigned int>, mathfunc::bitwiseMaskXorCaller<unsigned int>,
mathfunc::bitwiseMaskXorCaller<unsigned int>};
static Caller callers[] = {device::bitwiseMaskXorCaller<unsigned char>, device::bitwiseMaskXorCaller<unsigned char>,
device::bitwiseMaskXorCaller<unsigned short>, device::bitwiseMaskXorCaller<unsigned short>,
device::bitwiseMaskXorCaller<unsigned int>, device::bitwiseMaskXorCaller<unsigned int>,
device::bitwiseMaskXorCaller<unsigned int>};
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
@@ -601,7 +600,7 @@ void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
//////////////////////////////////////////////////////////////////////////////
// Minimum and maximum operations
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
template <typename T>
void min_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
@@ -623,14 +622,14 @@ namespace
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
mathfunc::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
device::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
}
template <typename T>
void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
{
dst.create(src1.size(), src1.type());
mathfunc::min_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream);
device::min_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream);
}
template <typename T>
@@ -638,14 +637,14 @@ namespace
{
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
dst.create(src1.size(), src1.type());
mathfunc::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
device::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
}
template <typename T>
void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
{
dst.create(src1.size(), src1.type());
mathfunc::max_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream);
device::max_gpu<T>(src1.reshape(1), saturate_cast<T>(src2), dst.reshape(1), stream);
}
}
@@ -709,7 +708,7 @@ void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream)
////////////////////////////////////////////////////////////////////////
// threshold
namespace cv { namespace gpu { namespace mathfunc
namespace cv { namespace gpu { namespace device
{
template <typename T>
void threshold_gpu(const DevMem2D& src, const DevMem2D& dst, T thresh, T maxVal, int type,
@@ -718,24 +717,25 @@ namespace cv { namespace gpu { namespace mathfunc
namespace
{
template <typename T>
void threshold_caller(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type,
cudaStream_t stream)
template <typename T> void threshold_caller(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, cudaStream_t stream)
{
mathfunc::threshold_gpu<T>(src, dst, saturate_cast<T>(thresh), saturate_cast<T>(maxVal), type, stream);
device::threshold_gpu<T>(src, dst, saturate_cast<T>(thresh), saturate_cast<T>(maxVal), type, stream);
}
}
double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& s)
{
CV_Assert(src.channels() == 1 && src.depth() <= CV_64F);
CV_Assert(type <= THRESH_TOZERO_INV);
dst.create(src.size(), src.type());
cudaStream_t stream = StreamAccessor::getStream(s);
if (src.type() == CV_32FC1 && type == THRESH_TRUNC)
{
NppStreamHandler h(stream);
dst.create(src.size(), src.type());
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
@@ -761,12 +761,7 @@ double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double
threshold_caller<int>, threshold_caller<float>, threshold_caller<double>
};
CV_Assert(src.channels() == 1 && src.depth() <= CV_64F);
CV_Assert(type <= THRESH_TOZERO_INV);
dst.create(src.size(), src.type());
if (src.depth() != CV_32F)
if (src.depth() != CV_32F && src.depth() != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
@@ -781,17 +776,11 @@ double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double
////////////////////////////////////////////////////////////////////////
// pow
namespace cv
namespace cv { namespace gpu { namespace device
{
namespace gpu
{
namespace mathfunc
{
template<typename T>
void pow_caller(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);
}
}
}
template<typename T>
void pow_caller(const DevMem2D& src, float power, DevMem2D dst, cudaStream_t stream);
}}}
void cv::gpu::pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream)
{
@@ -802,9 +791,9 @@ void cv::gpu::pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream)
static const caller_t callers[] =
{
mathfunc::pow_caller<unsigned char>, mathfunc::pow_caller<signed char>,
mathfunc::pow_caller<unsigned short>, mathfunc::pow_caller<short>,
mathfunc::pow_caller<int>, mathfunc::pow_caller<float>
device::pow_caller<unsigned char>, device::pow_caller<signed char>,
device::pow_caller<unsigned short>, device::pow_caller<short>,
device::pow_caller<int>, device::pow_caller<float>
};
callers[src.depth()](src.reshape(1), (float)power, dst.reshape(1), StreamAccessor::getStream(stream));