// This file is part of OpenCV project. // It is subject to the license terms in the LICENSE file found in the top-level directory // of this distribution and at http://opencv.org/license.html #include "precomp.hpp" #include "opencl_kernels_core.hpp" #include "convert_scale.simd.hpp" #include "convert_scale.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content namespace cv { static BinaryFunc getCvtScaleAbsFunc(int depth) { CV_INSTRUMENT_REGION(); CV_CPU_DISPATCH(getCvtScaleAbsFunc, (depth), CV_CPU_DISPATCH_MODES_ALL); } BinaryFunc getConvertScaleFunc(int sdepth, int ddepth) { CV_INSTRUMENT_REGION(); CV_CPU_DISPATCH(getConvertScaleFunc, (sdepth, ddepth), CV_CPU_DISPATCH_MODES_ALL); } #ifdef HAVE_OPENCL static bool ocl_convertScaleAbs( InputArray _src, OutputArray _dst, double alpha, double beta ) { const ocl::Device & d = ocl::Device::getDefault(); int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); bool doubleSupport = d.doubleFPConfig() > 0; if (!doubleSupport && depth == CV_64F) return false; _dst.create(_src.size(), CV_8UC(cn)); int kercn = 1; if (d.isIntel()) { static const int vectorWidths[] = {4, 4, 4, 4, 4, 4, 4, -1}; kercn = ocl::checkOptimalVectorWidth( vectorWidths, _src, _dst, noArray(), noArray(), noArray(), noArray(), noArray(), noArray(), noArray(), ocl::OCL_VECTOR_MAX); } else kercn = ocl::predictOptimalVectorWidthMax(_src, _dst); int rowsPerWI = d.isIntel() ? 4 : 1; char cvt[2][50]; int wdepth = std::max(depth, CV_32F); String build_opt = format("-D OP_CONVERT_SCALE_ABS -D UNARY_OP -D dstT=%s -D DEPTH_dst=%d -D srcT1=%s" " -D workT=%s -D wdepth=%d -D convertToWT1=%s -D convertToDT=%s" " -D workT1=%s -D rowsPerWI=%d%s", ocl::typeToStr(CV_8UC(kercn)), CV_8U, ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)), wdepth, ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]), ocl::convertTypeStr(wdepth, CV_8U, kercn, cvt[1]), ocl::typeToStr(wdepth), rowsPerWI, doubleSupport ? " -D DOUBLE_SUPPORT" : ""); ocl::Kernel k("KF", ocl::core::arithm_oclsrc, build_opt); if (k.empty()) return false; UMat src = _src.getUMat(); UMat dst = _dst.getUMat(); ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src), dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn); if (wdepth == CV_32F) k.args(srcarg, dstarg, (float)alpha, (float)beta); else if (wdepth == CV_64F) k.args(srcarg, dstarg, alpha, beta); size_t globalsize[2] = { (size_t)src.cols * cn / kercn, ((size_t)src.rows + rowsPerWI - 1) / rowsPerWI }; return k.run(2, globalsize, NULL, false); } #endif void convertScaleAbs(InputArray _src, OutputArray _dst, double alpha, double beta) { CV_INSTRUMENT_REGION(); CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(), ocl_convertScaleAbs(_src, _dst, alpha, beta)) Mat src = _src.getMat(); int cn = src.channels(); double scale[] = {alpha, beta}; _dst.create( src.dims, src.size, CV_8UC(cn) ); Mat dst = _dst.getMat(); BinaryFunc func = getCvtScaleAbsFunc(src.depth()); CV_Assert( func != 0 ); if( src.dims <= 2 ) { Size sz = getContinuousSize2D(src, dst, cn); func( src.ptr(), src.step, 0, 0, dst.ptr(), dst.step, sz, scale ); } else { const Mat* arrays[] = {&src, &dst, 0}; uchar* ptrs[2] = {}; NAryMatIterator it(arrays, ptrs); Size sz((int)it.size*cn, 1); for( size_t i = 0; i < it.nplanes; i++, ++it ) func( ptrs[0], 0, 0, 0, ptrs[1], 0, sz, scale ); } } //================================================================================================== #ifdef HAVE_OPENCL static bool ocl_normalize( InputArray _src, InputOutputArray _dst, InputArray _mask, int dtype, double scale, double delta ) { UMat src = _src.getUMat(); if( _mask.empty() ) src.convertTo( _dst, dtype, scale, delta ); else if (src.channels() <= 4) { const ocl::Device & dev = ocl::Device::getDefault(); int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype), ddepth = CV_MAT_DEPTH(dtype), wdepth = std::max(CV_32F, std::max(sdepth, ddepth)), rowsPerWI = dev.isIntel() ? 4 : 1; float fscale = static_cast(scale), fdelta = static_cast(delta); bool haveScale = std::fabs(scale - 1) > DBL_EPSILON, haveZeroScale = !(std::fabs(scale) > DBL_EPSILON), haveDelta = std::fabs(delta) > DBL_EPSILON, doubleSupport = dev.doubleFPConfig() > 0; if (!haveScale && !haveDelta && stype == dtype) { _src.copyTo(_dst, _mask); return true; } if (haveZeroScale) { _dst.setTo(Scalar(delta), _mask); return true; } if ((sdepth == CV_64F || ddepth == CV_64F) && !doubleSupport) return false; char cvt[2][40]; String opts = format("-D srcT=%s -D dstT=%s -D convertToWT=%s -D cn=%d -D rowsPerWI=%d" " -D convertToDT=%s -D workT=%s%s%s%s -D srcT1=%s -D dstT1=%s", ocl::typeToStr(stype), ocl::typeToStr(dtype), ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]), cn, rowsPerWI, ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]), ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)), doubleSupport ? " -D DOUBLE_SUPPORT" : "", haveScale ? " -D HAVE_SCALE" : "", haveDelta ? " -D HAVE_DELTA" : "", ocl::typeToStr(sdepth), ocl::typeToStr(ddepth)); ocl::Kernel k("normalizek", ocl::core::normalize_oclsrc, opts); if (k.empty()) return false; UMat mask = _mask.getUMat(), dst = _dst.getUMat(); ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src), maskarg = ocl::KernelArg::ReadOnlyNoSize(mask), dstarg = ocl::KernelArg::ReadWrite(dst); if (haveScale) { if (haveDelta) k.args(srcarg, maskarg, dstarg, fscale, fdelta); else k.args(srcarg, maskarg, dstarg, fscale); } else { if (haveDelta) k.args(srcarg, maskarg, dstarg, fdelta); else k.args(srcarg, maskarg, dstarg); } size_t globalsize[2] = { (size_t)src.cols, ((size_t)src.rows + rowsPerWI - 1) / rowsPerWI }; return k.run(2, globalsize, NULL, false); } else { UMat temp; src.convertTo( temp, dtype, scale, delta ); temp.copyTo( _dst, _mask ); } return true; } #endif void normalize(InputArray _src, InputOutputArray _dst, double a, double b, int norm_type, int rtype, InputArray _mask) { CV_INSTRUMENT_REGION(); double scale = 1, shift = 0; int type = _src.type(), depth = CV_MAT_DEPTH(type); if( rtype < 0 ) rtype = _dst.fixedType() ? _dst.depth() : depth; if( norm_type == CV_MINMAX ) { double smin = 0, smax = 0; double dmin = MIN( a, b ), dmax = MAX( a, b ); minMaxIdx( _src, &smin, &smax, 0, 0, _mask ); scale = (dmax - dmin)*(smax - smin > DBL_EPSILON ? 1./(smax - smin) : 0); if( rtype == CV_32F ) { scale = (float)scale; shift = (float)dmin - (float)(smin*scale); } else shift = dmin - smin*scale; } else if( norm_type == CV_L2 || norm_type == CV_L1 || norm_type == CV_C ) { scale = norm( _src, norm_type, _mask ); scale = scale > DBL_EPSILON ? a/scale : 0.; shift = 0; } else CV_Error( CV_StsBadArg, "Unknown/unsupported norm type" ); CV_OCL_RUN(_dst.isUMat(), ocl_normalize(_src, _dst, _mask, rtype, scale, shift)) Mat src = _src.getMat(); if( _mask.empty() ) src.convertTo( _dst, rtype, scale, shift ); else { Mat temp; src.convertTo( temp, rtype, scale, shift ); temp.copyTo( _dst, _mask ); } } } // namespace