Added OpenCL support for FastNlMeansDenoisingAbs
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@ -51,7 +51,7 @@ void cv::fastNlMeansDenoising( InputArray _src, OutputArray _dst, float h,
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Size src_size = _src.size();
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CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
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src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
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ocl_fastNlMeansDenoising(_src, _dst, h, templateWindowSize, searchWindowSize))
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ocl_fastNlMeansDenoising(_src, _dst, h, templateWindowSize, searchWindowSize, false))
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Mat src = _src.getMat();
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_dst.create(src_size, src.type());
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@ -88,6 +88,10 @@ void cv::fastNlMeansDenoisingAbs( InputArray _src, OutputArray _dst, float h,
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int templateWindowSize, int searchWindowSize)
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{
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Size src_size = _src.size();
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CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()) &&
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src_size.width > 5 && src_size.height > 5, // low accuracy on small sizes
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ocl_fastNlMeansDenoising(_src, _dst, h, templateWindowSize, searchWindowSize, true))
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Mat src = _src.getMat();
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_dst.create(src_size, src.type());
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Mat dst = _dst.getMat();
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@ -30,7 +30,7 @@ static int divUp(int a, int b)
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template <typename FT>
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static bool ocl_calcAlmostDist2Weight(UMat & almostDist2Weight, int searchWindowSize, int templateWindowSize, FT h, int cn,
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int & almostTemplateWindowSizeSqBinShift)
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int & almostTemplateWindowSizeSqBinShift, bool abs)
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{
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const int maxEstimateSumValue = searchWindowSize * searchWindowSize * 255;
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int fixedPointMult = std::numeric_limits<int>::max() / maxEstimateSumValue;
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@ -48,15 +48,15 @@ static bool ocl_calcAlmostDist2Weight(UMat & almostDist2Weight, int searchWindow
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FT almostDist2ActualDistMultiplier = (FT)(1 << almostTemplateWindowSizeSqBinShift) / templateWindowSizeSq;
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const FT WEIGHT_THRESHOLD = 1e-3f;
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int maxDist = 255 * 255 * cn;
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int maxDist = abs ? 255 * cn : 255 * 255 * cn;
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int almostMaxDist = (int)(maxDist / almostDist2ActualDistMultiplier + 1);
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FT den = 1.0f / (h * h * cn);
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almostDist2Weight.create(1, almostMaxDist, CV_32SC1);
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ocl::Kernel k("calcAlmostDist2Weight", ocl::photo::nlmeans_oclsrc,
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format("-D OP_CALC_WEIGHTS -D FT=%s%s", ocl::typeToStr(depth),
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doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
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format("-D OP_CALC_WEIGHTS -D FT=%s%s%s", ocl::typeToStr(depth),
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doubleSupport ? " -D DOUBLE_SUPPORT" : "", abs ? " -D ABS" : ""));
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if (k.empty())
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return false;
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@ -68,7 +68,7 @@ static bool ocl_calcAlmostDist2Weight(UMat & almostDist2Weight, int searchWindow
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}
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static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, float h,
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int templateWindowSize, int searchWindowSize)
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int templateWindowSize, int searchWindowSize, bool abs)
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{
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int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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int ctaSize = ocl::Device::getDefault().isIntel() ? CTA_SIZE_INTEL : CTA_SIZE_DEFAULT;
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@ -89,21 +89,21 @@ static bool ocl_fastNlMeansDenoising(InputArray _src, OutputArray _dst, float h,
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" -D sample_t=%s -D pixel_t=%s -D int_t=%s"
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" -D BLOCK_COLS=%d -D BLOCK_ROWS=%d"
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" -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d"
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" -D convert_int_t=%s -D cn=%d -D convert_pixel_t=%s",
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" -D convert_int_t=%s -D cn=%d -D convert_pixel_t=%s%s",
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templateWindowSize, searchWindowSize,
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ocl::typeToStr(depth), ocl::typeToStr(type), ocl::typeToStr(CV_32SC(cn)),
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BLOCK_COLS, BLOCK_ROWS,
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ctaSize, templateWindowHalfWize, searchWindowHalfSize,
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ocl::convertTypeStr(CV_8U, CV_32S, cn, cvt[0]), type == CV_8UC3 ? 4 : cn,
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ocl::convertTypeStr(CV_32S, CV_8U, cn, cvt[1]));
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ocl::convertTypeStr(CV_32S, CV_8U, cn, cvt[1]), abs ? " -D ABS" : "");
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ocl::Kernel k("fastNlMeansDenoising", ocl::photo::nlmeans_oclsrc, opts);
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if (k.empty())
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return false;
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UMat almostDist2Weight;
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if (!ocl_calcAlmostDist2Weight<float>(almostDist2Weight, searchWindowSize, templateWindowSize, h, cn,
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almostTemplateWindowSizeSqBinShift))
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if (!ocl_calcAlmostDist2Weight<float>(almostDist2Weight, searchWindowSize, templateWindowSize,
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h, cn, almostTemplateWindowSizeSqBinShift, abs))
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return false;
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CV_Assert(almostTemplateWindowSizeSqBinShift >= 0);
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