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fixed gpu::pyrUp (now it matches cpu analog)

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fixed several warnings
This commit is contained in:
Vladislav Vinogradov
2012-03-19 09:27:06 +00:00
parent 484fe1d598
commit 6397fa5b38
11 changed files with 648 additions and 597 deletions
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338
modules/gpu/src/imgproc.cpp
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@@ -87,8 +87,6 @@ void cv::gpu::dft(const GpuMat&, GpuMat&, Size, int, Stream&) { throw_nogpu(); }
void cv::gpu::ConvolveBuf::create(Size, Size) { throw_nogpu(); }
void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool) { throw_nogpu(); }
void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool, ConvolveBuf&, Stream&) { throw_nogpu(); }
void cv::gpu::pyrDown(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::pyrUp(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::Canny(const GpuMat&, GpuMat&, double, double, int, bool) { throw_nogpu(); }
void cv::gpu::Canny(const GpuMat&, CannyBuf&, GpuMat&, double, double, int, bool) { throw_nogpu(); }
void cv::gpu::Canny(const GpuMat&, const GpuMat&, GpuMat&, double, double, bool) { throw_nogpu(); }
@@ -96,17 +94,15 @@ void cv::gpu::Canny(const GpuMat&, const GpuMat&, CannyBuf&, GpuMat&, double, do
cv::gpu::CannyBuf::CannyBuf(const GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::CannyBuf::create(const Size&, int) { throw_nogpu(); }
void cv::gpu::CannyBuf::release() { throw_nogpu(); }
void cv::gpu::ImagePyramid::build(const GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::ImagePyramid::getLayer(GpuMat&, Size, Stream&) const { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
////////////////////////////////////////////////////////////////////////
// meanShiftFiltering_GPU
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void meanShiftFiltering_gpu(const DevMem2Db& src, DevMem2Db dst, int sp, int sr, int maxIter, float eps, cudaStream_t stream);
}
@@ -140,9 +136,9 @@ void cv::gpu::meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
////////////////////////////////////////////////////////////////////////
// meanShiftProc_GPU
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void meanShiftProc_gpu(const DevMem2Db& src, DevMem2Db dstr, DevMem2Db dstsp, int sp, int sr, int maxIter, float eps, cudaStream_t stream);
}
@@ -177,9 +173,9 @@ void cv::gpu::meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int
////////////////////////////////////////////////////////////////////////
// drawColorDisp
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void drawColorDisp_gpu(const DevMem2Db& src, const DevMem2Db& dst, int ndisp, const cudaStream_t& stream);
void drawColorDisp_gpu(const DevMem2D_<short>& src, const DevMem2Db& dst, int ndisp, const cudaStream_t& stream);
@@ -213,9 +209,9 @@ void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, Stream& s
////////////////////////////////////////////////////////////////////////
// reprojectImageTo3D
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void reprojectImageTo3D_gpu(const DevMem2Db& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
void reprojectImageTo3D_gpu(const DevMem2D_<short>& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
@@ -249,9 +245,9 @@ void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q,
////////////////////////////////////////////////////////////////////////
// copyMakeBorder
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
template <typename T, int cn> void copyMakeBorder_gpu(const DevMem2Db& src, const DevMem2Db& dst, int top, int left, int borderMode, const T* borderValue, cudaStream_t stream);
}
@@ -329,7 +325,7 @@ void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom
else
{
typedef void (*caller_t)(const DevMem2Db& src, const DevMem2Db& dst, int top, int left, int borderType, const Scalar& value, cudaStream_t stream);
static const caller_t callers[6][4] =
static const caller_t callers[6][4] =
{
{ copyMakeBorder_caller<uchar, 1> , 0/*copyMakeBorder_caller<uchar, 2>*/ , copyMakeBorder_caller<uchar, 3> , copyMakeBorder_caller<uchar, 4>},
{0/*copyMakeBorder_caller<schar, 1>*/, 0/*copyMakeBorder_caller<schar, 2>*/ , 0/*copyMakeBorder_caller<schar, 3>*/, 0/*copyMakeBorder_caller<schar, 4>*/},
@@ -352,9 +348,9 @@ void cv::gpu::copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom
//////////////////////////////////////////////////////////////////////////////
// buildWarpPlaneMaps
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void buildWarpPlaneMaps(int tl_u, int tl_v, DevMem2Df map_x, DevMem2Df map_y,
const float k_rinv[9], const float r_kinv[9], const float t[3], float scale,
@@ -362,7 +358,7 @@ namespace cv { namespace gpu { namespace device
}
}}}
void cv::gpu::buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, const Mat &T,
void cv::gpu::buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, const Mat &T,
float scale, GpuMat& map_x, GpuMat& map_y, Stream& stream)
{
using namespace ::cv::gpu::device::imgproc;
@@ -378,16 +374,16 @@ void cv::gpu::buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, cons
map_x.create(dst_roi.size(), CV_32F);
map_y.create(dst_roi.size(), CV_32F);
buildWarpPlaneMaps(dst_roi.tl().x, dst_roi.tl().y, map_x, map_y, K_Rinv.ptr<float>(), R_Kinv.ptr<float>(),
buildWarpPlaneMaps(dst_roi.tl().x, dst_roi.tl().y, map_x, map_y, K_Rinv.ptr<float>(), R_Kinv.ptr<float>(),
T.ptr<float>(), scale, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// buildWarpCylyndricalMaps
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void buildWarpCylindricalMaps(int tl_u, int tl_v, DevMem2Df map_x, DevMem2Df map_y,
const float k_rinv[9], const float r_kinv[9], float scale,
@@ -417,9 +413,9 @@ void cv::gpu::buildWarpCylindricalMaps(Size src_size, Rect dst_roi, const Mat &K
//////////////////////////////////////////////////////////////////////////////
// buildWarpSphericalMaps
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void buildWarpSphericalMaps(int tl_u, int tl_v, DevMem2Df map_x, DevMem2Df map_y,
const float k_rinv[9], const float r_kinv[9], float scale,
@@ -449,7 +445,7 @@ void cv::gpu::buildWarpSphericalMaps(Size src_size, Rect dst_roi, const Mat &K,
// rotate
namespace
{
{
template<int DEPTH> struct NppTypeTraits;
template<> struct NppTypeTraits<CV_8U> { typedef Npp8u npp_t; };
template<> struct NppTypeTraits<CV_8S> { typedef Npp8s npp_t; };
@@ -463,7 +459,7 @@ namespace
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI,
typedef NppStatus (*func_t)(const npp_t* pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI,
npp_t* pDst, int nDstStep, NppiRect oDstROI,
double nAngle, double nShiftX, double nShiftY, int eInterpolation);
};
@@ -503,7 +499,7 @@ void cv::gpu::rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, d
{
typedef void (*func_t)(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift, double yShift, int interpolation, cudaStream_t stream);
static const func_t funcs[6][4] =
static const func_t funcs[6][4] =
{
{NppRotate<CV_8U, nppiRotate_8u_C1R>::call, 0, NppRotate<CV_8U, nppiRotate_8u_C3R>::call, NppRotate<CV_8U, nppiRotate_8u_C4R>::call},
{0,0,0,0},
@@ -536,13 +532,13 @@ void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, S
CV_Assert(src.type() == CV_8UC1);
sum.create(src.rows + 1, src.cols + 1, CV_32S);
NcvSize32u roiSize;
roiSize.width = src.cols;
roiSize.height = src.rows;
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
Ncv32u bufSize;
ncvSafeCall( nppiStIntegralGetSize_8u32u(roiSize, &bufSize, prop) );
@@ -552,7 +548,7 @@ void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, S
NppStStreamHandler h(stream);
ncvSafeCall( nppiStIntegral_8u32u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>()), static_cast<int>(src.step),
ncvSafeCall( nppiStIntegral_8u32u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>()), static_cast<int>(src.step),
sum.ptr<Ncv32u>(), static_cast<int>(sum.step), roiSize, buffer.ptr<Ncv8u>(), bufSize, prop) );
if (stream == 0)
@@ -570,11 +566,11 @@ void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& s)
roiSize.width = src.cols;
roiSize.height = src.rows;
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, cv::gpu::getDevice()) );
Ncv32u bufSize;
ncvSafeCall(nppiStSqrIntegralGetSize_8u64u(roiSize, &bufSize, prop));
ncvSafeCall(nppiStSqrIntegralGetSize_8u64u(roiSize, &bufSize, prop));
GpuMat buf(1, bufSize, CV_8U);
cudaStream_t stream = StreamAccessor::getStream(s);
@@ -582,7 +578,7 @@ void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& s)
NppStStreamHandler h(stream);
sqsum.create(src.rows + 1, src.cols + 1, CV_64F);
ncvSafeCall(nppiStSqrIntegral_8u64u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>(0)), static_cast<int>(src.step),
ncvSafeCall(nppiStSqrIntegral_8u64u_C1R(const_cast<Ncv8u*>(src.ptr<Ncv8u>(0)), static_cast<int>(src.step),
sqsum.ptr<Ncv64u>(0), static_cast<int>(sqsum.step), roiSize, buf.ptr<Ncv8u>(0), bufSize, prop));
if (stream == 0)
@@ -592,7 +588,7 @@ void cv::gpu::sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& s)
//////////////////////////////////////////////////////////////////////////////
// columnSum
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
@@ -651,8 +647,8 @@ namespace
{
typedef typename NppTypeTraits<SDEPTH>::npp_t src_t;
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, NppiSize oSizeROI, Npp32s * pHist,
int nLevels, Npp32s nLowerLevel, Npp32s nUpperLevel, Npp8u * pBuffer);
typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, NppiSize oSizeROI, Npp32s * pHist,
int nLevels, Npp32s nLowerLevel, Npp32s nUpperLevel, Npp8u * pBuffer);
};
template<int SDEPTH> struct NppHistogramEvenFuncC4
{
@@ -779,7 +775,7 @@ namespace
int buf_size;
get_buf_size(sz, levels.cols, &buf_size);
ensureSizeIsEnough(1, buf_size, CV_8U, buffer);
NppStreamHandler h(stream);
@@ -931,7 +927,7 @@ void cv::gpu::histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4
hist_callers[src.depth()](src, hist, levels, buf, StreamAccessor::getStream(stream));
}
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace hist
{
@@ -1002,7 +998,7 @@ void cv::gpu::equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat&
NppStreamHandler h(stream);
nppSafeCall( nppsIntegral_32s(hist.ptr<Npp32s>(), lut.ptr<Npp32s>(), 256, intBuf.ptr<Npp8u>()) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
@@ -1012,22 +1008,22 @@ void cv::gpu::equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat&
////////////////////////////////////////////////////////////////////////
// cornerHarris & minEgenVal
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void cornerHarris_gpu(int block_size, float k, DevMem2Df Dx, DevMem2Df Dy, DevMem2Df dst, int border_type, cudaStream_t stream);
void cornerMinEigenVal_gpu(int block_size, DevMem2Df Dx, DevMem2Df Dy, DevMem2Df dst, int border_type, cudaStream_t stream);
}
}}}
namespace
namespace
{
void extractCovData(const GpuMat& src, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, int borderType, Stream& stream)
{
double scale = static_cast<double>(1 << ((ksize > 0 ? ksize : 3) - 1)) * blockSize;
if (ksize < 0)
if (ksize < 0)
scale *= 2.;
if (src.depth() == CV_8U)
@@ -1105,7 +1101,7 @@ void cv::gpu::cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& D
}
void cv::gpu::cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType)
{
{
GpuMat Dx, Dy;
cornerMinEigenVal(src, dst, Dx, Dy, blockSize, ksize, borderType);
}
@@ -1117,7 +1113,7 @@ void cv::gpu::cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuM
}
void cv::gpu::cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, int borderType, Stream& stream)
{
{
using namespace ::cv::gpu::device::imgproc;
CV_Assert(borderType == cv::BORDER_REFLECT101 || borderType == cv::BORDER_REPLICATE || borderType == cv::BORDER_REFLECT);
@@ -1125,7 +1121,7 @@ void cv::gpu::cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuM
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderType, gpuBorderType));
extractCovData(src, Dx, Dy, buf, blockSize, ksize, borderType, stream);
extractCovData(src, Dx, Dy, buf, blockSize, ksize, borderType, stream);
dst.create(src.size(), CV_32F);
@@ -1135,9 +1131,9 @@ void cv::gpu::cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuM
//////////////////////////////////////////////////////////////////////////////
// mulSpectrums
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void mulSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, DevMem2D_<cufftComplex> c, cudaStream_t stream);
@@ -1145,7 +1141,7 @@ namespace cv { namespace gpu { namespace device
}
}}}
void cv::gpu::mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, bool conjB, Stream& stream)
void cv::gpu::mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, bool conjB, Stream& stream)
{
using namespace ::cv::gpu::device::imgproc;
@@ -1165,9 +1161,9 @@ void cv::gpu::mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flag
//////////////////////////////////////////////////////////////////////////////
// mulAndScaleSpectrums
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace imgproc
namespace imgproc
{
void mulAndScaleSpectrums(const PtrStep<cufftComplex> a, const PtrStep<cufftComplex> b, float scale, DevMem2D_<cufftComplex> c, cudaStream_t stream);
@@ -1175,7 +1171,7 @@ namespace cv { namespace gpu { namespace device
}
}}}
void cv::gpu::mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, float scale, bool conjB, Stream& stream)
void cv::gpu::mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, float scale, bool conjB, Stream& stream)
{
using namespace ::cv::gpu::device::imgproc;
@@ -1225,7 +1221,7 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags, Stre
GpuMat src_data;
// Make sure here we work with the continuous input,
// Make sure here we work with the continuous input,
// as CUFFT can't handle gaps
src_data = src;
createContinuous(src.rows, src.cols, src.type(), src_data);
@@ -1241,7 +1237,7 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags, Stre
}
cufftType dft_type = CUFFT_R2C;
if (is_complex_input)
if (is_complex_input)
dft_type = is_complex_output ? CUFFT_C2C : CUFFT_C2R;
CV_Assert(dft_size_opt.width > 1);
@@ -1304,7 +1300,7 @@ void cv::gpu::ConvolveBuf::create(Size image_size, Size templ_size)
void cv::gpu::ConvolveBuf::create(Size image_size, Size templ_size, Size block_size)
{
result_size = Size(image_size.width - templ_size.width + 1,
image_size.height - templ_size.height + 1);
image_size.height - templ_size.height + 1);
this->block_size = block_size;
@@ -1377,10 +1373,10 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
cufftSafeCall( cufftSetStream(planC2R, StreamAccessor::getStream(stream)) );
GpuMat templ_roi(templ.size(), CV_32F, templ.data, templ.step);
copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0,
templ_block.cols - templ_roi.cols, 0, Scalar(), stream);
cufftSafeCall(cufftExecR2C(planR2C, templ_block.ptr<cufftReal>(),
cufftSafeCall(cufftExecR2C(planR2C, templ_block.ptr<cufftReal>(),
templ_spect.ptr<cufftComplex>()));
// Process all blocks of the result matrix
@@ -1390,23 +1386,23 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
{
Size image_roi_size(std::min(x + dft_size.width, image.cols) - x,
std::min(y + dft_size.height, image.rows) - y);
GpuMat image_roi(image_roi_size, CV_32F, (void*)(image.ptr<float>(y) + x),
GpuMat image_roi(image_roi_size, CV_32F, (void*)(image.ptr<float>(y) + x),
image.step);
copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows,
0, image_block.cols - image_roi.cols, 0, Scalar(), stream);
cufftSafeCall(cufftExecR2C(planR2C, image_block.ptr<cufftReal>(),
cufftSafeCall(cufftExecR2C(planR2C, image_block.ptr<cufftReal>(),
image_spect.ptr<cufftComplex>()));
mulAndScaleSpectrums(image_spect, templ_spect, result_spect, 0,
1.f / dft_size.area(), ccorr, stream);
cufftSafeCall(cufftExecC2R(planC2R, result_spect.ptr<cufftComplex>(),
cufftSafeCall(cufftExecC2R(planC2R, result_spect.ptr<cufftComplex>(),
result_data.ptr<cufftReal>()));
Size result_roi_size(std::min(x + block_size.width, result.cols) - x,
std::min(y + block_size.height, result.rows) - y);
GpuMat result_roi(result_roi_size, result.type(),
GpuMat result_roi(result_roi_size, result.type(),
(void*)(result.ptr<float>(y) + x), result.step);
GpuMat result_block(result_roi_size, result_data.type(),
GpuMat result_block(result_roi_size, result_data.type(),
result_data.ptr(), result_data.step);
if (stream)
@@ -1421,83 +1417,6 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
#endif
}
//////////////////////////////////////////////////////////////////////////////
// pyrDown
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
template <typename T, int cn> void pyrDown_gpu(const DevMem2Db& src, const DevMem2Db& dst, int borderType, cudaStream_t stream);
}
}}}
void cv::gpu::pyrDown(const GpuMat& src, GpuMat& dst, int borderType, Stream& stream)
{
using namespace ::cv::gpu::device::imgproc;
typedef void (*func_t)(const DevMem2Db& src, const DevMem2Db& dst, int borderType, cudaStream_t stream);
static const func_t funcs[6][4] =
{
{pyrDown_gpu<uchar, 1>, pyrDown_gpu<uchar, 2>, pyrDown_gpu<uchar, 3>, pyrDown_gpu<uchar, 4>},
{pyrDown_gpu<schar, 1>, pyrDown_gpu<schar, 2>, pyrDown_gpu<schar, 3>, pyrDown_gpu<schar, 4>},
{pyrDown_gpu<ushort, 1>, pyrDown_gpu<ushort, 2>, pyrDown_gpu<ushort, 3>, pyrDown_gpu<ushort, 4>},
{pyrDown_gpu<short, 1>, pyrDown_gpu<short, 2>, pyrDown_gpu<short, 3>, pyrDown_gpu<short, 4>},
{pyrDown_gpu<int, 1>, pyrDown_gpu<int, 2>, pyrDown_gpu<int, 3>, pyrDown_gpu<int, 4>},
{pyrDown_gpu<float, 1>, pyrDown_gpu<float, 2>, pyrDown_gpu<float, 3>, pyrDown_gpu<float, 4>},
};
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(borderType == BORDER_REFLECT101 || borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT || borderType == BORDER_REFLECT || borderType == BORDER_WRAP);
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderType, gpuBorderType));
dst.create((src.rows + 1) / 2, (src.cols + 1) / 2, src.type());
funcs[src.depth()][src.channels() - 1](src, dst, gpuBorderType, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// pyrUp
namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
template <typename T, int cn> void pyrUp_gpu(const DevMem2Db& src, const DevMem2Db& dst, int borderType, cudaStream_t stream);
}
}}}
void cv::gpu::pyrUp(const GpuMat& src, GpuMat& dst, int borderType, Stream& stream)
{
using namespace ::cv::gpu::device::imgproc;
typedef void (*func_t)(const DevMem2Db& src, const DevMem2Db& dst, int borderType, cudaStream_t stream);
static const func_t funcs[6][4] =
{
{pyrUp_gpu<uchar, 1>, pyrUp_gpu<uchar, 2>, pyrUp_gpu<uchar, 3>, pyrUp_gpu<uchar, 4>},
{pyrUp_gpu<schar, 1>, pyrUp_gpu<schar, 2>, pyrUp_gpu<schar, 3>, pyrUp_gpu<schar, 4>},
{pyrUp_gpu<ushort, 1>, pyrUp_gpu<ushort, 2>, pyrUp_gpu<ushort, 3>, pyrUp_gpu<ushort, 4>},
{pyrUp_gpu<short, 1>, pyrUp_gpu<short, 2>, pyrUp_gpu<short, 3>, pyrUp_gpu<short, 4>},
{pyrUp_gpu<int, 1>, pyrUp_gpu<int, 2>, pyrUp_gpu<int, 3>, pyrUp_gpu<int, 4>},
{pyrUp_gpu<float, 1>, pyrUp_gpu<float, 2>, pyrUp_gpu<float, 3>, pyrUp_gpu<float, 4>},
};
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(borderType == BORDER_REFLECT101 || borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT || borderType == BORDER_REFLECT || borderType == BORDER_WRAP);
int gpuBorderType;
CV_Assert(tryConvertToGpuBorderType(borderType, gpuBorderType));
dst.create(src.rows*2, src.cols*2, src.type());
funcs[src.depth()][src.channels() - 1](src, dst, gpuBorderType, StreamAccessor::getStream(stream));
}
//////////////////////////////////////////////////////////////////////////////
// Canny
@@ -1544,9 +1463,9 @@ void cv::gpu::CannyBuf::release()
trackBuf2.release();
}
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace canny
namespace canny
{
void calcSobelRowPass_gpu(PtrStepb src, PtrStepi dx_buf, PtrStepi dy_buf, int rows, int cols);
@@ -1554,7 +1473,7 @@ namespace cv { namespace gpu { namespace device
void calcMagnitude_gpu(PtrStepi dx, PtrStepi dy, PtrStepf mag, int rows, int cols, bool L2Grad);
void calcMap_gpu(PtrStepi dx, PtrStepi dy, PtrStepf mag, PtrStepi map, int rows, int cols, float low_thresh, float high_thresh);
void edgesHysteresisLocal_gpu(PtrStepi map, ushort2* st1, int rows, int cols);
void edgesHysteresisGlobal_gpu(PtrStepi map, ushort2* st1, ushort2* st2, int rows, int cols);
@@ -1570,11 +1489,11 @@ namespace
using namespace ::cv::gpu::device::canny;
calcMap_gpu(buf.dx, buf.dy, buf.edgeBuf, buf.edgeBuf, dst.rows, dst.cols, low_thresh, high_thresh);
edgesHysteresisLocal_gpu(buf.edgeBuf, buf.trackBuf1.ptr<ushort2>(), dst.rows, dst.cols);
edgesHysteresisGlobal_gpu(buf.edgeBuf, buf.trackBuf1.ptr<ushort2>(), buf.trackBuf2.ptr<ushort2>(), dst.rows, dst.cols);
getEdges_gpu(buf.edgeBuf, dst, dst.rows, dst.cols);
}
}
@@ -1597,7 +1516,7 @@ void cv::gpu::Canny(const GpuMat& src, CannyBuf& buf, GpuMat& dst, double low_th
dst.create(src.size(), CV_8U);
dst.setTo(Scalar::all(0));
buf.create(src.size(), apperture_size);
buf.edgeBuf.setTo(Scalar::all(0));
@@ -1636,7 +1555,7 @@ void cv::gpu::Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& d
dst.create(dx.size(), CV_8U);
dst.setTo(Scalar::all(0));
buf.dx = dx; buf.dy = dy;
buf.create(dx.size(), -1);
buf.edgeBuf.setTo(Scalar::all(0));
@@ -1646,129 +1565,6 @@ void cv::gpu::Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& d
CannyCaller(buf, dst, static_cast<float>(low_thresh), static_cast<float>(high_thresh));
}
//////////////////////////////////////////////////////////////////////////////
// ImagePyramid
namespace cv { namespace gpu { namespace device
{
namespace pyramid
{
template <typename T> void kernelDownsampleX2_gpu(DevMem2Db src, DevMem2Db dst, cudaStream_t stream);
template <typename T> void kernelInterpolateFrom1_gpu(DevMem2Db src, DevMem2Db dst, cudaStream_t stream);
}
}}}
void cv::gpu::ImagePyramid::build(const GpuMat& img, int numLayers, Stream& stream)
{
using namespace cv::gpu::device::pyramid;
typedef void (*func_t)(DevMem2Db src, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[7][4] =
{
{kernelDownsampleX2_gpu<uchar1>, /*kernelDownsampleX2_gpu<uchar2>*/ 0, kernelDownsampleX2_gpu<uchar3>, kernelDownsampleX2_gpu<uchar4>},
{/*kernelDownsampleX2_gpu<char1>*/0, /*kernelDownsampleX2_gpu<char2>*/ 0, /*kernelDownsampleX2_gpu<char3>*/ 0, /*kernelDownsampleX2_gpu<char4>*/ 0},
{kernelDownsampleX2_gpu<ushort1>, /*kernelDownsampleX2_gpu<ushort2>*/ 0, kernelDownsampleX2_gpu<ushort3>, kernelDownsampleX2_gpu<ushort4>},
{/*kernelDownsampleX2_gpu<short1>*/ 0, /*kernelDownsampleX2_gpu<short2>*/ 0, /*kernelDownsampleX2_gpu<short3>*/ 0, /*kernelDownsampleX2_gpu<short4>*/ 0},
{/*kernelDownsampleX2_gpu<int1>*/ 0, /*kernelDownsampleX2_gpu<int2>*/ 0, /*kernelDownsampleX2_gpu<int3>*/ 0, /*kernelDownsampleX2_gpu<int4>*/ 0},
{kernelDownsampleX2_gpu<float1>, /*kernelDownsampleX2_gpu<float2>*/ 0, kernelDownsampleX2_gpu<float3>, kernelDownsampleX2_gpu<float4>},
{/*kernelDownsampleX2_gpu<double1>*/ 0, /*kernelDownsampleX2_gpu<double2>*/ 0, /*kernelDownsampleX2_gpu<double3>*/ 0, /*kernelDownsampleX2_gpu<double4>*/ 0}
};
CV_Assert(img.channels() == 1 || img.channels() == 3 || img.channels() == 4);
CV_Assert(img.depth() == CV_8U || img.depth() == CV_16U || img.depth() == CV_32F);
layer0_ = img;
Size szLastLayer = img.size();
nLayers_ = 1;
if (numLayers <= 0)
numLayers = 255; //it will cut-off when any of the dimensions goes 1
pyramid_.resize(numLayers);
for (int i = 0; i < numLayers - 1; ++i)
{
Size szCurLayer(szLastLayer.width / 2, szLastLayer.height / 2);
if (szCurLayer.width == 0 || szCurLayer.height == 0)
break;
ensureSizeIsEnough(szCurLayer, img.type(), pyramid_[i]);
nLayers_++;
const GpuMat& prevLayer = i == 0 ? layer0_ : pyramid_[i - 1];
func_t func = funcs[img.depth()][img.channels() - 1];
CV_Assert(func != 0);
func(prevLayer, pyramid_[i], StreamAccessor::getStream(stream));
szLastLayer = szCurLayer;
}
}
void cv::gpu::ImagePyramid::getLayer(GpuMat& outImg, Size outRoi, Stream& stream) const
{
using namespace cv::gpu::device::pyramid;
typedef void (*func_t)(DevMem2Db src, DevMem2Db dst, cudaStream_t stream);
static const func_t funcs[7][4] =
{
{kernelInterpolateFrom1_gpu<uchar1>, /*kernelInterpolateFrom1_gpu<uchar2>*/ 0, kernelInterpolateFrom1_gpu<uchar3>, kernelInterpolateFrom1_gpu<uchar4>},
{/*kernelInterpolateFrom1_gpu<char1>*/0, /*kernelInterpolateFrom1_gpu<char2>*/ 0, /*kernelInterpolateFrom1_gpu<char3>*/ 0, /*kernelInterpolateFrom1_gpu<char4>*/ 0},
{kernelInterpolateFrom1_gpu<ushort1>, /*kernelInterpolateFrom1_gpu<ushort2>*/ 0, kernelInterpolateFrom1_gpu<ushort3>, kernelInterpolateFrom1_gpu<ushort4>},
{/*kernelInterpolateFrom1_gpu<short1>*/ 0, /*kernelInterpolateFrom1_gpu<short2>*/ 0, /*kernelInterpolateFrom1_gpu<short3>*/ 0, /*kernelInterpolateFrom1_gpu<short4>*/ 0},
{/*kernelInterpolateFrom1_gpu<int1>*/ 0, /*kernelInterpolateFrom1_gpu<int2>*/ 0, /*kernelInterpolateFrom1_gpu<int3>*/ 0, /*kernelInterpolateFrom1_gpu<int4>*/ 0},
{kernelInterpolateFrom1_gpu<float1>, /*kernelInterpolateFrom1_gpu<float2>*/ 0, kernelInterpolateFrom1_gpu<float3>, kernelInterpolateFrom1_gpu<float4>},
{/*kernelInterpolateFrom1_gpu<double1>*/ 0, /*kernelInterpolateFrom1_gpu<double2>*/ 0, /*kernelInterpolateFrom1_gpu<double3>*/ 0, /*kernelInterpolateFrom1_gpu<double4>*/ 0}
};
CV_Assert(outRoi.width <= layer0_.cols && outRoi.height <= layer0_.rows && outRoi.width > 0 && outRoi.height > 0);
ensureSizeIsEnough(outRoi, layer0_.type(), outImg);
if (outRoi.width == layer0_.cols && outRoi.height == layer0_.rows)
{
if (stream)
stream.enqueueCopy(layer0_, outImg);
else
layer0_.copyTo(outImg);
}
float lastScale = 1.0f;
float curScale;
GpuMat lastLayer = layer0_;
GpuMat curLayer;
for (int i = 0; i < nLayers_ - 1; ++i)
{
curScale = lastScale * 0.5f;
curLayer = pyramid_[i];
if (outRoi.width == curLayer.cols && outRoi.height == curLayer.rows)
{
if (stream)
stream.enqueueCopy(curLayer, outImg);
else
curLayer.copyTo(outImg);
}
if (outRoi.width >= curLayer.cols && outRoi.height >= curLayer.rows)
break;
lastScale = curScale;
lastLayer = curLayer;
}
func_t func = funcs[outImg.depth()][outImg.channels() - 1];
CV_Assert(func != 0);
func(lastLayer, outImg, StreamAccessor::getStream(stream));
}
#endif /* !defined (HAVE_CUDA) */