added perf test for cv::goodFeaturesToTrack
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modules/imgproc/perf/opencl/perf_gftt.cpp
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87
modules/imgproc/perf/opencl/perf_gftt.cpp
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///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "perf_precomp.hpp"
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#include "opencv2/ts/ocl_perf.hpp"
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#include <sstream>
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#ifdef HAVE_OPENCL
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namespace cvtest {
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namespace ocl {
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//////////////////////////// GoodFeaturesToTrack //////////////////////////
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typedef tuple<String, double, bool> GoodFeaturesToTrackParams;
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typedef TestBaseWithParam<GoodFeaturesToTrackParams> GoodFeaturesToTrackFixture;
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OCL_PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrack,
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::testing::Combine(OCL_PERF_ENUM(String("gpu/opticalflow/rubberwhale1.png")),
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OCL_PERF_ENUM(0.0, 3.0), Bool()))
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{
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GoodFeaturesToTrackParams params = GetParam();
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const String fileName = get<0>(params);
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const double minDistance = get<1>(params), qualityLevel = 0.01;
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const bool harrisDetector = get<2>(params);
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const int maxCorners = 1000;
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Mat img = imread(getDataPath(fileName), cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty()) << "could not load " << fileName;
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checkDeviceMaxMemoryAllocSize(img.size(), img.type());
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UMat src(img.size(), img.type()), dst(1, maxCorners, CV_32FC2);
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img.copyTo(src);
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declare.in(src, WARMUP_READ).out(dst);
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OCL_TEST_CYCLE() cv::goodFeaturesToTrack(src, dst, maxCorners, qualityLevel,
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minDistance, noArray(), 3, harrisDetector, 0.04);
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SANITY_CHECK(dst);
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}
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} } // namespace cvtest::ocl
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#endif
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@ -96,7 +96,7 @@ static bool ocl_goodFeaturesToTrack( InputArray _image, OutputArray _corners,
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return false;
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return false;
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UMat counter(1, 1, CV_32SC1, Scalar::all(0)),
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UMat counter(1, 1, CV_32SC1, Scalar::all(0)),
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corners(1, possibleCornersCount * sizeof(Corner), CV_8UC1);
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corners(1, (int)(possibleCornersCount * sizeof(Corner)), CV_8UC1);
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ocl::KernelArg eigarg = ocl::KernelArg::ReadOnlyNoSize(eig),
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ocl::KernelArg eigarg = ocl::KernelArg::ReadOnlyNoSize(eig),
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tmparg = ocl::KernelArg::ReadOnlyNoSize(tmp),
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tmparg = ocl::KernelArg::ReadOnlyNoSize(tmp),
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cornersarg = ocl::KernelArg::PtrWriteOnly(corners),
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cornersarg = ocl::KernelArg::PtrWriteOnly(corners),
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@ -117,7 +117,7 @@ static bool ocl_goodFeaturesToTrack( InputArray _image, OutputArray _corners,
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return false;
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return false;
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total = counter.getMat(ACCESS_READ).at<int>(0, 0);
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total = counter.getMat(ACCESS_READ).at<int>(0, 0);
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size_t totalb = sizeof(Corner) * total;
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int totalb = (int)(sizeof(Corner) * total);
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tmpCorners.resize(total);
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tmpCorners.resize(total);
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Mat mcorners(1, totalb, CV_8UC1, &tmpCorners[0]);
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Mat mcorners(1, totalb, CV_8UC1, &tmpCorners[0]);
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@ -221,12 +221,10 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
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CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
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CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
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CV_Assert( _mask.empty() || (_mask.type() == CV_8UC1 && _mask.sameSize(_image)) );
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CV_Assert( _mask.empty() || (_mask.type() == CV_8UC1 && _mask.sameSize(_image)) );
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if (ocl::useOpenCL() && _image.dims() <= 2 && _image.isUMat())
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if (ocl::useOpenCL() && _image.dims() <= 2 && _image.isUMat() &&
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{
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ocl_goodFeaturesToTrack(_image, _corners, maxCorners, qualityLevel, minDistance,
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CV_Assert(ocl_goodFeaturesToTrack(_image, _corners, maxCorners, qualityLevel, minDistance,
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_mask, blockSize, useHarrisDetector, harrisK))
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_mask, blockSize, useHarrisDetector, harrisK));
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return;
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return;
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}
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Mat image = _image.getMat(), eig, tmp;
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Mat image = _image.getMat(), eig, tmp;
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if( useHarrisDetector )
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if( useHarrisDetector )
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@ -74,7 +74,7 @@ __kernel void findCorners(__global const uchar * eigptr, int eig_step, int eig_o
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#endif
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#endif
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)
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)
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{
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{
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__global float2 * corners = (cornersptr + (int)sizeof(float2) * atomic_inc(counter));
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__global float2 * corners = (__global float2 *)(cornersptr + (int)sizeof(float2) * atomic_inc(counter));
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corners[0] = (float2)(val, as_float( (x<<16) | y ));
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corners[0] = (float2)(val, as_float( (x<<16) | y ));
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}
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}
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}
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}
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@ -196,7 +196,6 @@ void cv::ocl::GoodFeaturesToTrackDetector_OCL::operator ()(const oclMat& image,
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// sort detected corners on cpu side.
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// sort detected corners on cpu side.
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tmp.resize(total);
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tmp.resize(total);
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printf("total: %d\n", total);
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std::sort(tmp.begin(), tmp.end(), DefCornerCompare());
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std::sort(tmp.begin(), tmp.end(), DefCornerCompare());
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// estimate maximal size of final output array
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// estimate maximal size of final output array
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@ -389,6 +389,7 @@ CV_EXPORTS void PrintTo(const MatType& t, std::ostream* os);
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namespace cv
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namespace cv
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{
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{
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CV_EXPORTS void PrintTo(const String& str, ::std::ostream* os);
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CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
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CV_EXPORTS void PrintTo(const Size& sz, ::std::ostream* os);
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} //namespace cv
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} //namespace cv
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@ -1199,7 +1199,7 @@ void TestBase::validateMetrics()
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double mean = metrics.mean * 1000.0f / metrics.frequency;
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double mean = metrics.mean * 1000.0f / metrics.frequency;
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double stddev = metrics.stddev * 1000.0f / metrics.frequency;
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double stddev = metrics.stddev * 1000.0f / metrics.frequency;
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double percents = stddev / mean * 100.f;
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double percents = stddev / mean * 100.f;
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printf(" samples = %d, mean = %.2f, stddev = %.2f (%.1f%%)\n", (int)metrics.samples, mean, stddev, percents);
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printf("[ PERFSTAT ] (samples = %d, mean = %.2f, stddev = %.2f (%.1f%%))\n", (int)metrics.samples, mean, stddev, percents);
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}
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}
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else
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else
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{
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{
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@ -1611,6 +1611,11 @@ void PrintTo(const MatType& t, ::std::ostream* os)
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\*****************************************************************************************/
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\*****************************************************************************************/
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namespace cv {
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namespace cv {
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void PrintTo(const String& str, ::std::ostream* os)
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{
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*os << str;
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}
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void PrintTo(const Size& sz, ::std::ostream* os)
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void PrintTo(const Size& sz, ::std::ostream* os)
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{
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{
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*os << /*"Size:" << */sz.width << "x" << sz.height;
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*os << /*"Size:" << */sz.width << "x" << sz.height;
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