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// 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.
// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
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#include "precomp.hpp"
#ifndef __OPENCV_FAST_NLMEANS_DENOISING_OPENCL_HPP__
#define __OPENCV_FAST_NLMEANS_DENOISING_OPENCL_HPP__
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#include "opencl_kernels_photo.hpp"
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#ifdef HAVE_OPENCL
namespace cv {
enum
{
BLOCK_ROWS = 32,
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BLOCK_COLS = 32,
CTA_SIZE_INTEL = 64,
CTA_SIZE_DEFAULT = 256
};
static int divUp(int a, int b)
{
return (a + b - 1) / b;
}
template <typename FT, typename ST, typename WT>
static bool ocl_calcAlmostDist2Weight(UMat & almostDist2Weight, int searchWindowSize, int templateWindowSize, FT h, int cn,
int & almostTemplateWindowSizeSqBinShift, bool abs)
{
const WT maxEstimateSumValue = searchWindowSize * searchWindowSize *
std::numeric_limits<ST>::max();
int fixedPointMult = (int)std::min<WT>(std::numeric_limits<WT>::max() / maxEstimateSumValue,
std::numeric_limits<int>::max());
int depth = DataType<FT>::depth;
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
if (depth == CV_64F && !doubleSupport)
return false;
// precalc weight for every possible l2 dist between blocks
// additional optimization of precalced weights to replace division(averaging) by binary shift
CV_Assert(templateWindowSize <= 46340); // sqrt(INT_MAX)
int templateWindowSizeSq = templateWindowSize * templateWindowSize;
almostTemplateWindowSizeSqBinShift = getNearestPowerOf2(templateWindowSizeSq);
FT almostDist2ActualDistMultiplier = (FT)(1 << almostTemplateWindowSizeSqBinShift) / templateWindowSizeSq;
const FT WEIGHT_THRESHOLD = 1e-3f;
int maxDist = abs ? std::numeric_limits<ST>::max() * cn :
std::numeric_limits<ST>::max() * std::numeric_limits<ST>::max() * cn;
int almostMaxDist = (int)(maxDist / almostDist2ActualDistMultiplier + 1);
FT den = 1.0f / (h * h * cn);
almostDist2Weight.create(1, almostMaxDist, CV_32SC1);
ocl::Kernel k("calcAlmostDist2Weight", ocl::photo::nlmeans_oclsrc,
format("-D OP_CALC_WEIGHTS -D FT=%s%s%s", ocl::typeToStr(depth),
doubleSupport ? " -D DOUBLE_SUPPORT" : "", abs ? " -D ABS" : ""));
if (k.empty())
return false;
k.args(ocl::KernelArg::PtrWriteOnly(almostDist2Weight), almostMaxDist,
almostDist2ActualDistMultiplier, fixedPointMult, den, WEIGHT_THRESHOLD);
size_t globalsize[1] = { almostMaxDist };
return k.run(1, globalsize, NULL, false);
}
static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, float h,
int templateWindowSize, int searchWindowSize, bool abs)
{
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int ctaSize = ocl::Device::getDefault().isIntel() ? CTA_SIZE_INTEL : CTA_SIZE_DEFAULT;
Size size = _src.size();
if (cn != 1 && cn != 2 && cn != 3 && depth != CV_8U && (!abs || depth != CV_16U))
return false;
int templateWindowHalfWize = templateWindowSize / 2;
int searchWindowHalfSize = searchWindowSize / 2;
templateWindowSize = templateWindowHalfWize * 2 + 1;
searchWindowSize = searchWindowHalfSize * 2 + 1;
int nblocksx = divUp(size.width, BLOCK_COLS), nblocksy = divUp(size.height, BLOCK_ROWS);
int almostTemplateWindowSizeSqBinShift = -1;
char buf[4][40];
String opts = format("-D OP_CALC_FASTNLMEANS -D TEMPLATE_SIZE=%d -D SEARCH_SIZE=%d"
" -D sample_t=%s -D pixel_t=%s -D int_t=%s"
" -D weight_t=%s -D sum_t=%s -D convert_sum_t=%s"
" -D BLOCK_COLS=%d -D BLOCK_ROWS=%d"
" -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d"
" -D convert_int_t=%s -D cn=%d -D convert_pixel_t=%s%s",
templateWindowSize, searchWindowSize,
ocl::typeToStr(depth), ocl::typeToStr(type), ocl::typeToStr(CV_32SC(cn)),
depth == CV_8U ? ocl::typeToStr(CV_32S) : "long",
depth == CV_8U ? ocl::typeToStr(CV_32SC(cn)) :
(sprintf(buf[0], "long%d", cn), buf[0]),
depth == CV_8U ? ocl::convertTypeStr(depth, CV_32S, cn, buf[1]) :
(sprintf(buf[1], "convert_long%d", cn), buf[1]),
BLOCK_COLS, BLOCK_ROWS,
ctaSize, templateWindowHalfWize, searchWindowHalfSize,
ocl::convertTypeStr(depth, CV_32S, cn, buf[2]), cn == 3 ? 4 : cn,
ocl::convertTypeStr(CV_32S, depth, cn, buf[3]), abs ? " -D ABS" : "");
ocl::Kernel k("fastNlMeansDenoising", ocl::photo::nlmeans_oclsrc, opts);
if (k.empty())
return false;
UMat almostDist2Weight;
if ((depth == CV_8U &&
!ocl_calcAlmostDist2Weight<float, uchar, int>(almostDist2Weight,
searchWindowSize, templateWindowSize,
h, cn,
almostTemplateWindowSizeSqBinShift,
abs)) ||
(depth == CV_16U &&
!ocl_calcAlmostDist2Weight<float, ushort, int64>(almostDist2Weight,
searchWindowSize, templateWindowSize,
h, cn,
almostTemplateWindowSizeSqBinShift,
abs)))
return false;
CV_Assert(almostTemplateWindowSizeSqBinShift >= 0);
UMat srcex;
int borderSize = searchWindowHalfSize + templateWindowHalfWize;
if (cn == 3) {
UMat tmp(size, CV_MAKE_TYPE(depth, 4));
int from_to[] = { 0,0, 1,1, 2,2 };
mixChannels(std::vector<UMat>(1, _src.getUMat()), std::vector<UMat>(1, tmp), from_to, 3);
copyMakeBorder(tmp, srcex, borderSize, borderSize, borderSize, borderSize, BORDER_DEFAULT);
}
else
copyMakeBorder(_src, srcex, borderSize, borderSize, borderSize, borderSize, BORDER_DEFAULT);
_dst.create(size, type);
UMat dst;
if (cn == 3)
dst.create(size, CV_MAKE_TYPE(depth, 4));
else
dst = _dst.getUMat();
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int searchWindowSizeSq = searchWindowSize * searchWindowSize;
Size upColSumSize(size.width, searchWindowSizeSq * nblocksy);
Size colSumSize(nblocksx * templateWindowSize, searchWindowSizeSq * nblocksy);
UMat buffer(upColSumSize + colSumSize, CV_32SC(cn));
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srcex = srcex(Rect(Point(borderSize, borderSize), size));
k.args(ocl::KernelArg::ReadOnlyNoSize(srcex), ocl::KernelArg::WriteOnly(dst),
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ocl::KernelArg::PtrReadOnly(almostDist2Weight),
ocl::KernelArg::PtrReadOnly(buffer), almostTemplateWindowSizeSqBinShift);
size_t globalsize[2] = { nblocksx * ctaSize, nblocksy }, localsize[2] = { ctaSize, 1 };
if (!k.run(2, globalsize, localsize, false)) return false;
if (cn == 3) {
int from_to[] = { 0,0, 1,1, 2,2 };
mixChannels(std::vector<UMat>(1, dst), std::vector<UMat>(1, _dst.getUMat()), from_to, 3);
}
return true;
}
static bool ocl_fastNlMeansDenoisingColored( InputArray _src, OutputArray _dst,
float h, float hForColorComponents,
int templateWindowSize, int searchWindowSize)
{
UMat src = _src.getUMat();
_dst.create(src.size(), src.type());
UMat dst = _dst.getUMat();
UMat src_lab;
cvtColor(src, src_lab, COLOR_LBGR2Lab);
UMat l(src.size(), CV_8U);
UMat ab(src.size(), CV_8UC2);
std::vector<UMat> l_ab(2), l_ab_denoised(2);
l_ab[0] = l;
l_ab[1] = ab;
l_ab_denoised[0].create(src.size(), CV_8U);
l_ab_denoised[1].create(src.size(), CV_8UC2);
int from_to[] = { 0,0, 1,1, 2,2 };
mixChannels(std::vector<UMat>(1, src_lab), l_ab, from_to, 3);
fastNlMeansDenoising(l_ab[0], l_ab_denoised[0], h, templateWindowSize, searchWindowSize);
fastNlMeansDenoising(l_ab[1], l_ab_denoised[1], hForColorComponents, templateWindowSize, searchWindowSize);
UMat dst_lab(src.size(), CV_8UC3);
mixChannels(l_ab_denoised, std::vector<UMat>(1, dst_lab), from_to, 3);
cvtColor(dst_lab, dst, COLOR_Lab2LBGR, src.channels());
return true;
}
}
#endif
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#endif