/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, all rights reserved. // Copyright (C) 2014, Itseez, Inc, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of Intel Corporation may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" #include "opencl_kernels_imgproc.hpp" #include "opencv2/core/openvx/ovx_defs.hpp" #include "filter.hpp" /****************************************************************************************\ Sobel & Scharr Derivative Filters \****************************************************************************************/ namespace cv { static void getScharrKernels( OutputArray _kx, OutputArray _ky, int dx, int dy, bool normalize, int ktype ) { const int ksize = 3; CV_Assert( ktype == CV_32F || ktype == CV_64F ); _kx.create(ksize, 1, ktype, -1, true); _ky.create(ksize, 1, ktype, -1, true); Mat kx = _kx.getMat(); Mat ky = _ky.getMat(); CV_Assert( dx >= 0 && dy >= 0 && dx+dy == 1 ); for( int k = 0; k < 2; k++ ) { Mat* kernel = k == 0 ? &kx : &ky; int order = k == 0 ? dx : dy; int kerI[3]; if( order == 0 ) kerI[0] = 3, kerI[1] = 10, kerI[2] = 3; else if( order == 1 ) kerI[0] = -1, kerI[1] = 0, kerI[2] = 1; Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]); double scale = !normalize || order == 1 ? 1. : 1./32; temp.convertTo(*kernel, ktype, scale); } } static void getSobelKernels( OutputArray _kx, OutputArray _ky, int dx, int dy, int _ksize, bool normalize, int ktype ) { int i, j, ksizeX = _ksize, ksizeY = _ksize; if( ksizeX == 1 && dx > 0 ) ksizeX = 3; if( ksizeY == 1 && dy > 0 ) ksizeY = 3; CV_Assert( ktype == CV_32F || ktype == CV_64F ); _kx.create(ksizeX, 1, ktype, -1, true); _ky.create(ksizeY, 1, ktype, -1, true); Mat kx = _kx.getMat(); Mat ky = _ky.getMat(); if( _ksize % 2 == 0 || _ksize > 31 ) CV_Error( cv::Error::StsOutOfRange, "The kernel size must be odd and not larger than 31" ); std::vector kerI(std::max(ksizeX, ksizeY) + 1); CV_Assert( dx >= 0 && dy >= 0 && dx+dy > 0 ); for( int k = 0; k < 2; k++ ) { Mat* kernel = k == 0 ? &kx : &ky; int order = k == 0 ? dx : dy; int ksize = k == 0 ? ksizeX : ksizeY; CV_Assert( ksize > order ); if( ksize == 1 ) kerI[0] = 1; else if( ksize == 3 ) { if( order == 0 ) kerI[0] = 1, kerI[1] = 2, kerI[2] = 1; else if( order == 1 ) kerI[0] = -1, kerI[1] = 0, kerI[2] = 1; else kerI[0] = 1, kerI[1] = -2, kerI[2] = 1; } else { int oldval, newval; kerI[0] = 1; for( i = 0; i < ksize; i++ ) kerI[i+1] = 0; for( i = 0; i < ksize - order - 1; i++ ) { oldval = kerI[0]; for( j = 1; j <= ksize; j++ ) { newval = kerI[j]+kerI[j-1]; kerI[j-1] = oldval; oldval = newval; } } for( i = 0; i < order; i++ ) { oldval = -kerI[0]; for( j = 1; j <= ksize; j++ ) { newval = kerI[j-1] - kerI[j]; kerI[j-1] = oldval; oldval = newval; } } } Mat temp(kernel->rows, kernel->cols, CV_32S, &kerI[0]); double scale = !normalize ? 1. : 1./(1 << (ksize-order-1)); temp.convertTo(*kernel, ktype, scale); } } } void cv::getDerivKernels( OutputArray kx, OutputArray ky, int dx, int dy, int ksize, bool normalize, int ktype ) { if( ksize <= 0 ) getScharrKernels( kx, ky, dx, dy, normalize, ktype ); else getSobelKernels( kx, ky, dx, dy, ksize, normalize, ktype ); } cv::Ptr cv::createDerivFilter(int srcType, int dstType, int dx, int dy, int ksize, int borderType ) { Mat kx, ky; getDerivKernels( kx, ky, dx, dy, ksize, false, CV_32F ); return createSeparableLinearFilter(srcType, dstType, kx, ky, Point(-1,-1), 0, borderType ); } #ifdef HAVE_OPENVX namespace cv { namespace ovx { template <> inline bool skipSmallImages(int w, int h) { return w*h < 320 * 240; } } static bool openvx_sobel(InputArray _src, OutputArray _dst, int dx, int dy, int ksize, double scale, double delta, int borderType) { if (_src.type() != CV_8UC1 || _dst.type() != CV_16SC1 || ksize != 3 || scale != 1.0 || delta != 0.0 || (dx | dy) != 1 || (dx + dy) != 1 || _src.cols() < ksize || _src.rows() < ksize || ovx::skipSmallImages(_src.cols(), _src.rows()) ) return false; Mat src = _src.getMat(); Mat dst = _dst.getMat(); if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix()) return false; //Process isolated borders only vx_enum border; switch (borderType & ~BORDER_ISOLATED) { case BORDER_CONSTANT: border = VX_BORDER_CONSTANT; break; case BORDER_REPLICATE: // border = VX_BORDER_REPLICATE; // break; default: return false; } try { ivx::Context ctx = ovx::getOpenVXContext(); //if ((vx_size)ksize > ctx.convolutionMaxDimension()) // return false; Mat a; if (dst.data != src.data) a = src; else src.copyTo(a); ivx::Image ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8, ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data), ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_S16, ivx::Image::createAddressing(dst.cols, dst.rows, 2, (vx_int32)(dst.step)), dst.data); //ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments //since OpenVX standard says nothing about thread-safety for now ivx::border_t prevBorder = ctx.immediateBorder(); ctx.setImmediateBorder(border, (vx_uint8)(0)); if(dx) ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, ib, NULL)); else ivx::IVX_CHECK_STATUS(vxuSobel3x3(ctx, ia, NULL, ib)); ctx.setImmediateBorder(prevBorder); } catch (const ivx::RuntimeError & e) { VX_DbgThrow(e.what()); } catch (const ivx::WrapperError & e) { VX_DbgThrow(e.what()); } return true; } } #endif #if 0 //defined HAVE_IPP namespace cv { static bool ipp_Deriv(InputArray _src, OutputArray _dst, int dx, int dy, int ksize, double scale, double delta, int borderType) { #ifdef HAVE_IPP_IW CV_INSTRUMENT_REGION_IPP(); ::ipp::IwiSize size(_src.size().width, _src.size().height); IppDataType srcType = ippiGetDataType(_src.depth()); IppDataType dstType = ippiGetDataType(_dst.depth()); int channels = _src.channels(); bool useScale = false; bool useScharr = false; if(channels != _dst.channels() || channels > 1) return false; if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON) useScale = true; if(ksize <= 0) { ksize = 3; useScharr = true; } IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize); if((int)maskSize < 0) return false; #if IPP_VERSION_X100 <= 201703 // Bug with mirror wrap if(borderType == BORDER_REFLECT_101 && (ksize/2+1 > size.width || ksize/2+1 > size.height)) return false; #endif IwiDerivativeType derivType = ippiGetDerivType(dx, dy, (useScharr)?false:true); if((int)derivType < 0) return false; // Acquire data and begin processing try { Mat src = _src.getMat(); Mat dst = _dst.getMat(); ::ipp::IwiImage iwSrc = ippiGetImage(src); ::ipp::IwiImage iwDst = ippiGetImage(dst); ::ipp::IwiImage iwSrcProc = iwSrc; ::ipp::IwiImage iwDstProc = iwDst; ::ipp::IwiBorderSize borderSize(maskSize); ::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize)); if(!ippBorder) return false; if(srcType == ipp8u && dstType == ipp8u) { iwDstProc.Alloc(iwDst.m_size, ipp16s, channels); useScale = true; } else if(srcType == ipp8u && dstType == ipp32f) { iwSrc -= borderSize; iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels); CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0, ::ipp::IwiScaleParams(ippAlgHintFast)); iwSrcProc += borderSize; } if(useScharr) CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterScharr, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder); else CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterSobel, iwSrcProc, iwDstProc, derivType, maskSize, ::ipp::IwDefault(), ippBorder); if(useScale) CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta, ::ipp::IwiScaleParams(ippAlgHintFast)); } catch (const ::ipp::IwException &) { return false; } return true; #else CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(dx); CV_UNUSED(dy); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType); return false; #endif } } #endif #ifdef HAVE_OPENCL namespace cv { static bool ocl_sepFilter3x3_8UC1(InputArray _src, OutputArray _dst, int ddepth, InputArray _kernelX, InputArray _kernelY, double delta, int borderType) { const ocl::Device & dev = ocl::Device::getDefault(); int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) && (_src.offset() == 0) && (_src.step() % 4 == 0) && (_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) ) return false; Mat kernelX = _kernelX.getMat().reshape(1, 1); if (kernelX.cols % 2 != 1) return false; Mat kernelY = _kernelY.getMat().reshape(1, 1); if (kernelY.cols % 2 != 1) return false; if (ddepth < 0) ddepth = sdepth; Size size = _src.size(); size_t globalsize[2] = { 0, 0 }; size_t localsize[2] = { 0, 0 }; globalsize[0] = size.width / 16; globalsize[1] = size.height / 2; const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" }; char build_opts[1024]; snprintf(build_opts, sizeof(build_opts), "-D %s %s%s", borderMap[borderType], ocl::kernelToStr(kernelX, CV_32F, "KERNEL_MATRIX_X").c_str(), ocl::kernelToStr(kernelY, CV_32F, "KERNEL_MATRIX_Y").c_str()); ocl::Kernel kernel("sepFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::sepFilter3x3_oclsrc, build_opts); if (kernel.empty()) return false; UMat src = _src.getUMat(); _dst.create(size, CV_MAKETYPE(ddepth, cn)); if (!(_dst.offset() == 0 && _dst.step() % 4 == 0)) return false; UMat dst = _dst.getUMat(); int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src)); idxArg = kernel.set(idxArg, (int)src.step); idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst)); idxArg = kernel.set(idxArg, (int)dst.step); idxArg = kernel.set(idxArg, (int)dst.rows); idxArg = kernel.set(idxArg, (int)dst.cols); idxArg = kernel.set(idxArg, static_cast(delta)); return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false); } } #endif void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType ) { CV_INSTRUMENT_REGION(); CV_Assert(!_src.empty()); int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); if (ddepth < 0) ddepth = sdepth; int dtype = CV_MAKE_TYPE(ddepth, cn); _dst.create( _src.size(), dtype ); int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); Mat kx, ky; getDerivKernels( kx, ky, dx, dy, ksize, false, ktype ); if( scale != 1 ) { // usually the smoothing part is the slowest to compute, // so try to scale it instead of the faster differentiating part if( dx == 0 ) kx *= scale; else ky *= scale; } CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && ksize == 3 && (size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(), ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType)); CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(), ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType)) Mat src = _src.getMat(); Mat dst = _dst.getMat(); Point ofs; Size wsz(src.cols, src.rows); if(!(borderType & BORDER_ISOLATED)) src.locateROI( wsz, ofs ); CALL_HAL(sobel, cv_hal_sobel, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn, ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, ksize, scale, delta, borderType&~BORDER_ISOLATED); CV_OVX_RUN(true, openvx_sobel(src, dst, dx, dy, ksize, scale, delta, borderType)) //CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, ksize, scale, delta, borderType)); sepFilter2D(src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType ); } void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy, double scale, double delta, int borderType ) { CV_INSTRUMENT_REGION(); CV_Assert(!_src.empty()); int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); if (ddepth < 0) ddepth = sdepth; int dtype = CV_MAKETYPE(ddepth, cn); _dst.create( _src.size(), dtype ); int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); Mat kx, ky; getScharrKernels( kx, ky, dx, dy, false, ktype ); if( scale != 1 ) { // usually the smoothing part is the slowest to compute, // so try to scale it instead of the faster differentiating part if( dx == 0 ) kx *= scale; else ky *= scale; } CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > ky.total() && (size_t)_src.cols() > kx.total(), ocl_sepFilter3x3_8UC1(_src, _dst, ddepth, kx, ky, delta, borderType)); CV_OCL_RUN(ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(), ocl_sepFilter2D(_src, _dst, ddepth, kx, ky, Point(-1, -1), delta, borderType)) Mat src = _src.getMat(); Mat dst = _dst.getMat(); Point ofs; Size wsz(src.cols, src.rows); if(!(borderType & BORDER_ISOLATED)) src.locateROI( wsz, ofs ); CALL_HAL(scharr, cv_hal_scharr, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn, ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, dx, dy, scale, delta, borderType&~BORDER_ISOLATED); //CV_IPP_RUN_FAST(ipp_Deriv(src, dst, dx, dy, 0, scale, delta, borderType)); sepFilter2D( src, dst, ddepth, kx, ky, Point(-1, -1), delta, borderType ); } #ifdef HAVE_OPENCL namespace cv { #define LAPLACIAN_LOCAL_MEM(tileX, tileY, ksize, elsize) (((tileX) + 2 * (int)((ksize) / 2)) * (3 * (tileY) + 2 * (int)((ksize) / 2)) * elsize) static bool ocl_Laplacian5(InputArray _src, OutputArray _dst, const Mat & kd, const Mat & ks, double scale, double delta, int borderType, int depth, int ddepth) { const size_t tileSizeX = 16; const size_t tileSizeYmin = 8; const ocl::Device dev = ocl::Device::getDefault(); int stype = _src.type(); int sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype), esz = CV_ELEM_SIZE(stype); bool doubleSupport = dev.doubleFPConfig() > 0; if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) return false; Mat kernelX = kd.reshape(1, 1); if (kernelX.cols % 2 != 1) return false; Mat kernelY = ks.reshape(1, 1); if (kernelY.cols % 2 != 1) return false; CV_Assert(kernelX.cols == kernelY.cols); size_t wgs = dev.maxWorkGroupSize(); size_t lmsz = dev.localMemSize(); size_t src_step = _src.step(), src_offset = _src.offset(); const size_t tileSizeYmax = wgs / tileSizeX; CV_Assert(src_step != 0 && esz != 0); // workaround for NVIDIA: 3 channel vector type takes 4*elem_size in local memory int loc_mem_cn = dev.vendorID() == ocl::Device::VENDOR_NVIDIA && cn == 3 ? 4 : cn; if (((src_offset % src_step) % esz == 0) && ( (borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE) || ((borderType == BORDER_REFLECT || borderType == BORDER_WRAP || borderType == BORDER_REFLECT_101) && (_src.cols() >= (int) (kernelX.cols + tileSizeX) && _src.rows() >= (int) (kernelY.cols + tileSizeYmax))) ) && (tileSizeX * tileSizeYmin <= wgs) && (LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeYmin, kernelX.cols, loc_mem_cn * 4) <= lmsz) && OCL_PERFORMANCE_CHECK(!dev.isAMD()) // TODO FIXIT 2018: Problem with AMDGPU on Linux (2482.3) ) { Size size = _src.size(), wholeSize; Point origin; int dtype = CV_MAKE_TYPE(ddepth, cn); int wdepth = CV_32F; size_t tileSizeY = tileSizeYmax; while ((tileSizeX * tileSizeY > wgs) || (LAPLACIAN_LOCAL_MEM(tileSizeX, tileSizeY, kernelX.cols, loc_mem_cn * 4) > lmsz)) { tileSizeY /= 2; } size_t lt2[2] = { tileSizeX, tileSizeY}; size_t gt2[2] = { lt2[0] * (1 + (size.width - 1) / lt2[0]), lt2[1] }; char cvt[2][50]; const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", "BORDER_WRAP", "BORDER_REFLECT_101" }; String opts = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUS=%d%s%s" " -D CONVERT_TO_WT=%s -D CONVERT_TO_DT=%s" " -D %s -D SRC_T1=%s -D DST_T1=%s -D WT1=%s" " -D SRC_T=%s -D DST_T=%s -D WT=%s" " -D CN=%d ", (int)lt2[0], (int)lt2[1], kernelX.cols / 2, ocl::kernelToStr(kernelX, wdepth, "KERNEL_MATRIX_X").c_str(), ocl::kernelToStr(kernelY, wdepth, "KERNEL_MATRIX_Y").c_str(), ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0], sizeof(cvt[0])), ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1], sizeof(cvt[1])), borderMap[borderType], ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), ocl::typeToStr(wdepth), ocl::typeToStr(CV_MAKETYPE(sdepth, cn)), ocl::typeToStr(CV_MAKETYPE(ddepth, cn)), ocl::typeToStr(CV_MAKETYPE(wdepth, cn)), cn); ocl::Kernel k("laplacian", ocl::imgproc::laplacian5_oclsrc, opts); if (k.empty()) return false; UMat src = _src.getUMat(); _dst.create(size, dtype); UMat dst = _dst.getUMat(); int src_offset_x = static_cast((src_offset % src_step) / esz); int src_offset_y = static_cast(src_offset / src_step); src.locateROI(wholeSize, origin); k.args(ocl::KernelArg::PtrReadOnly(src), (int)src_step, src_offset_x, src_offset_y, wholeSize.height, wholeSize.width, ocl::KernelArg::WriteOnly(dst), static_cast(scale), static_cast(delta)); return k.run(2, gt2, lt2, false); } int iscale = cvRound(scale), idelta = cvRound(delta); bool floatCoeff = std::fabs(delta - idelta) > DBL_EPSILON || std::fabs(scale - iscale) > DBL_EPSILON; int wdepth = std::max(depth, floatCoeff ? CV_32F : CV_32S), kercn = 1; if (!doubleSupport && wdepth == CV_64F) return false; char cvt[2][50]; ocl::Kernel k("sumConvert", ocl::imgproc::laplacian5_oclsrc, format("-D ONLY_SUM_CONVERT " "-D SRC_T=%s -D WT=%s -D DST_T=%s -D COEFF_T=%s -D WDEPTH=%d " "-D CONVERT_TO_WT=%s -D CONVERT_TO_DT=%s%s", ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)), ocl::typeToStr(CV_MAKE_TYPE(ddepth, kercn)), ocl::typeToStr(wdepth), wdepth, ocl::convertTypeStr(depth, wdepth, kercn, cvt[0], sizeof(cvt[0])), ocl::convertTypeStr(wdepth, ddepth, kercn, cvt[1], sizeof(cvt[1])), doubleSupport ? " -D DOUBLE_SUPPORT" : "")); if (k.empty()) return false; UMat d2x, d2y; sepFilter2D(_src, d2x, depth, kd, ks, Point(-1, -1), 0, borderType); sepFilter2D(_src, d2y, depth, ks, kd, Point(-1, -1), 0, borderType); UMat dst = _dst.getUMat(); ocl::KernelArg d2xarg = ocl::KernelArg::ReadOnlyNoSize(d2x), d2yarg = ocl::KernelArg::ReadOnlyNoSize(d2y), dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn); if (wdepth >= CV_32F) k.args(d2xarg, d2yarg, dstarg, (float)scale, (float)delta); else k.args(d2xarg, d2yarg, dstarg, iscale, idelta); size_t globalsize[] = { (size_t)dst.cols * cn / kercn, (size_t)dst.rows }; return k.run(2, globalsize, NULL, false); } static bool ocl_Laplacian3_8UC1(InputArray _src, OutputArray _dst, int ddepth, InputArray _kernel, double delta, int borderType) { const ocl::Device & dev = ocl::Device::getDefault(); int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) && (borderType != BORDER_WRAP) && (_src.offset() == 0) && (_src.step() % 4 == 0) && (_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) ) return false; Mat kernel = _kernel.getMat().reshape(1, 1); if (ddepth < 0) ddepth = sdepth; Size size = _src.size(); size_t globalsize[2] = { 0, 0 }; size_t localsize[2] = { 0, 0 }; globalsize[0] = size.width / 16; globalsize[1] = size.height / 2; const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" }; char build_opts[1024]; snprintf(build_opts, sizeof(build_opts), "-D %s %s", borderMap[borderType], ocl::kernelToStr(kernel, CV_32F, "KERNEL_MATRIX").c_str()); ocl::Kernel k("laplacian3_8UC1_cols16_rows2", cv::ocl::imgproc::laplacian3_oclsrc, build_opts); if (k.empty()) return false; UMat src = _src.getUMat(); _dst.create(size, CV_MAKETYPE(ddepth, cn)); if (!(_dst.offset() == 0 && _dst.step() % 4 == 0)) return false; UMat dst = _dst.getUMat(); int idxArg = k.set(0, ocl::KernelArg::PtrReadOnly(src)); idxArg = k.set(idxArg, (int)src.step); idxArg = k.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst)); idxArg = k.set(idxArg, (int)dst.step); idxArg = k.set(idxArg, (int)dst.rows); idxArg = k.set(idxArg, (int)dst.cols); idxArg = k.set(idxArg, static_cast(delta)); return k.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false); } } #endif #if defined(HAVE_IPP) namespace cv { static bool ipp_Laplacian(InputArray _src, OutputArray _dst, int ksize, double scale, double delta, int borderType) { #ifdef HAVE_IPP_IW CV_INSTRUMENT_REGION_IPP(); ::ipp::IwiSize size(_src.size().width, _src.size().height); IppDataType srcType = ippiGetDataType(_src.depth()); IppDataType dstType = ippiGetDataType(_dst.depth()); int channels = _src.channels(); bool useScale = false; if(channels != _dst.channels() || channels > 1) return false; if(fabs(delta) > FLT_EPSILON || fabs(scale-1) > FLT_EPSILON) useScale = true; IppiMaskSize maskSize = ippiGetMaskSize(ksize, ksize); if((int)maskSize < 0) return false; // Acquire data and begin processing try { Mat src = _src.getMat(); Mat dst = _dst.getMat(); ::ipp::IwiImage iwSrc = ippiGetImage(src); ::ipp::IwiImage iwDst = ippiGetImage(dst); ::ipp::IwiImage iwSrcProc = iwSrc; ::ipp::IwiImage iwDstProc = iwDst; ::ipp::IwiBorderSize borderSize(maskSize); ::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize)); if(!ippBorder) return false; if(srcType == ipp8u && dstType == ipp8u) { iwDstProc.Alloc(iwDst.m_size, ipp16s, channels); useScale = true; } else if(srcType == ipp8u && dstType == ipp32f) { iwSrc -= borderSize; iwSrcProc.Alloc(iwSrc.m_size, ipp32f, channels); CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwSrc, iwSrcProc, 1, 0); iwSrcProc += borderSize; } CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterLaplacian, iwSrcProc, iwDstProc, maskSize, ::ipp::IwDefault(), ippBorder); if(useScale) CV_INSTRUMENT_FUN_IPP(::ipp::iwiScale, iwDstProc, iwDst, scale, delta); } catch (const ::ipp::IwException &) { return false; } return true; #else CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(scale); CV_UNUSED(delta); CV_UNUSED(borderType); return false; #endif } } #endif void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize, double scale, double delta, int borderType ) { CV_INSTRUMENT_REGION(); CV_Assert(!_src.empty()); int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype); if (ddepth < 0) ddepth = sdepth; _dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) ); if( ksize == 1 || ksize == 3 ) { float K[2][9] = { { 0, 1, 0, 1, -4, 1, 0, 1, 0 }, { 2, 0, 2, 0, -8, 0, 2, 0, 2 } }; Mat kernel(3, 3, CV_32F, K[ksize == 3]); if( scale != 1 ) kernel *= scale; CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2, ocl_Laplacian3_8UC1(_src, _dst, ddepth, kernel, delta, borderType)); } CV_IPP_RUN(!(cv::ocl::isOpenCLActivated() && _dst.isUMat()), ipp_Laplacian(_src, _dst, ksize, scale, delta, borderType)); if( ksize == 1 || ksize == 3 ) { float K[2][9] = { { 0, 1, 0, 1, -4, 1, 0, 1, 0 }, { 2, 0, 2, 0, -8, 0, 2, 0, 2 } }; Mat kernel(3, 3, CV_32F, K[ksize == 3]); if( scale != 1 ) kernel *= scale; filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType ); } else { int ktype = std::max(CV_32F, std::max(ddepth, sdepth)); int wdepth = sdepth == CV_8U && ksize <= 5 ? CV_16S : sdepth <= CV_32F ? CV_32F : CV_64F; int wtype = CV_MAKETYPE(wdepth, cn); Mat kd, ks; getSobelKernels( kd, ks, 2, 0, ksize, false, ktype ); CV_OCL_RUN(_dst.isUMat(), ocl_Laplacian5(_src, _dst, kd, ks, scale, delta, borderType, wdepth, ddepth)) Mat src = _src.getMat(), dst = _dst.getMat(); Point ofs; Size wsz(src.cols, src.rows); if(!(borderType&BORDER_ISOLATED)) src.locateROI( wsz, ofs ); borderType = (borderType&~BORDER_ISOLATED); const size_t STRIPE_SIZE = 1 << 14; Ptr fx = createSeparableLinearFilter(stype, wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() ); Ptr fy = createSeparableLinearFilter(stype, wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() ); int y = fx->start(src, wsz, ofs), dsty = 0, dy = 0; fy->start(src, wsz, ofs); const uchar* sptr = src.ptr() + src.step[0] * y; int dy0 = std::min(std::max((int)(STRIPE_SIZE/(CV_ELEM_SIZE(stype)*src.cols)), 1), src.rows); Mat d2x( dy0 + kd.rows - 1, src.cols, wtype ); Mat d2y( dy0 + kd.rows - 1, src.cols, wtype ); for( ; dsty < src.rows; sptr += dy0*src.step, dsty += dy ) { fx->proceed( sptr, (int)src.step, dy0, d2x.ptr(), (int)d2x.step ); dy = fy->proceed( sptr, (int)src.step, dy0, d2y.ptr(), (int)d2y.step ); if( dy > 0 ) { Mat dstripe = dst.rowRange(dsty, dsty + dy); d2x.rows = d2y.rows = dy; // modify the headers, which should work d2x += d2y; d2x.convertTo( dstripe, ddepth, scale, delta ); } } } } ///////////////////////////////////////////////////////////////////////////////////////// CV_IMPL void cvSobel( const void* srcarr, void* dstarr, int dx, int dy, int aperture_size ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() ); cv::Sobel( src, dst, dst.depth(), dx, dy, aperture_size, 1, 0, cv::BORDER_REPLICATE ); if( CV_IS_IMAGE(srcarr) && ((IplImage*)srcarr)->origin && dy % 2 != 0 ) dst *= -1; } CV_IMPL void cvLaplace( const void* srcarr, void* dstarr, int aperture_size ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); CV_Assert( src.size() == dst.size() && src.channels() == dst.channels() ); cv::Laplacian( src, dst, dst.depth(), aperture_size, 1, 0, cv::BORDER_REPLICATE ); } /* End of file. */