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