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209 lines
6.8 KiB
209 lines
6.8 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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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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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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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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// |
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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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// indirect, incidental, special, exemplary, or consequential damages |
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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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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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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 "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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class CV_Affine3D_EstTest : public cvtest::BaseTest |
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{ |
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public: |
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CV_Affine3D_EstTest(); |
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~CV_Affine3D_EstTest(); |
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protected: |
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void run(int); |
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bool test4Points(); |
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bool testNPoints(); |
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}; |
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CV_Affine3D_EstTest::CV_Affine3D_EstTest() |
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{ |
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} |
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CV_Affine3D_EstTest::~CV_Affine3D_EstTest() {} |
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float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); } |
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struct WrapAff |
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{ |
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const double *F; |
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WrapAff(const Mat& aff) : F(aff.ptr<double>()) {} |
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Point3f operator()(const Point3f& p) |
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{ |
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return Point3f( (float)(p.x * F[0] + p.y * F[1] + p.z * F[2] + F[3]), |
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(float)(p.x * F[4] + p.y * F[5] + p.z * F[6] + F[7]), |
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(float)(p.x * F[8] + p.y * F[9] + p.z * F[10] + F[11]) ); |
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} |
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}; |
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bool CV_Affine3D_EstTest::test4Points() |
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{ |
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Mat aff(3, 4, CV_64F); |
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cv::randu(aff, Scalar(1), Scalar(3)); |
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// setting points that are no in the same line |
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Mat fpts(1, 4, CV_32FC3); |
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Mat tpts(1, 4, CV_32FC3); |
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fpts.ptr<Point3f>()[0] = Point3f( rngIn(1,2), rngIn(1,2), rngIn(5, 6) ); |
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fpts.ptr<Point3f>()[1] = Point3f( rngIn(3,4), rngIn(3,4), rngIn(5, 6) ); |
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fpts.ptr<Point3f>()[2] = Point3f( rngIn(1,2), rngIn(3,4), rngIn(5, 6) ); |
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fpts.ptr<Point3f>()[3] = Point3f( rngIn(3,4), rngIn(1,2), rngIn(5, 6) ); |
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std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + 4, tpts.ptr<Point3f>(), WrapAff(aff)); |
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Mat aff_est; |
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vector<uchar> outliers; |
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estimateAffine3D(fpts, tpts, aff_est, outliers); |
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const double thres = 1e-3; |
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if (cvtest::norm(aff_est, aff, NORM_INF) > thres) |
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{ |
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//cout << cvtest::norm(aff_est, aff, NORM_INF) << endl; |
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
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return false; |
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} |
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return true; |
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} |
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struct Noise |
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{ |
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float l; |
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Noise(float level) : l(level) {} |
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Point3f operator()(const Point3f& p) |
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{ |
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RNG& rng = theRNG(); |
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return Point3f( p.x + l * (float)rng, p.y + l * (float)rng, p.z + l * (float)rng); |
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} |
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}; |
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bool CV_Affine3D_EstTest::testNPoints() |
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{ |
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Mat aff(3, 4, CV_64F); |
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cv::randu(aff, Scalar(-2), Scalar(2)); |
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// setting points that are no in the same line |
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const int n = 100; |
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const int m = 3*n/5; |
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const Point3f shift_outl = Point3f(15, 15, 15); |
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const float noise_level = 20.f; |
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Mat fpts(1, n, CV_32FC3); |
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Mat tpts(1, n, CV_32FC3); |
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randu(fpts, Scalar::all(0), Scalar::all(100)); |
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std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + n, tpts.ptr<Point3f>(), WrapAff(aff)); |
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/* adding noise*/ |
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#ifdef CV_CXX11 |
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std::transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, |
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[=] (const Point3f& pt) -> Point3f { return Noise(noise_level)(pt + shift_outl); }); |
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#else |
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std::transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, std::bind2nd(std::plus<Point3f>(), shift_outl)); |
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std::transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, Noise(noise_level)); |
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#endif |
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Mat aff_est; |
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vector<uchar> outl; |
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int res = estimateAffine3D(fpts, tpts, aff_est, outl); |
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if (!res) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
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return false; |
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} |
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const double thres = 1e-4; |
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if (cvtest::norm(aff_est, aff, NORM_INF) > thres) |
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{ |
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cout << "aff est: " << aff_est << endl; |
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cout << "aff ref: " << aff << endl; |
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
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return false; |
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} |
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bool outl_good = count(outl.begin(), outl.end(), 1) == m && |
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m == accumulate(outl.begin(), outl.begin() + m, 0); |
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if (!outl_good) |
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{ |
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ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH); |
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return false; |
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} |
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return true; |
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} |
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void CV_Affine3D_EstTest::run( int /* start_from */) |
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{ |
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cvtest::DefaultRngAuto dra; |
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if (!test4Points()) |
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return; |
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if (!testNPoints()) |
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return; |
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ts->set_failed_test_info(cvtest::TS::OK); |
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} |
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TEST(Calib3d_EstimateAffine3D, accuracy) { CV_Affine3D_EstTest test; test.safe_run(); } |
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TEST(Calib3d_EstimateAffine3D, regression_16007) |
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{ |
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std::vector<cv::Point3f> m1, m2; |
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m1.push_back(Point3f(1.0f, 0.0f, 0.0f)); m2.push_back(Point3f(1.0f, 1.0f, 0.0f)); |
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m1.push_back(Point3f(1.0f, 0.0f, 1.0f)); m2.push_back(Point3f(1.0f, 1.0f, 1.0f)); |
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m1.push_back(Point3f(0.5f, 0.0f, 0.5f)); m2.push_back(Point3f(0.5f, 1.0f, 0.5f)); |
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m1.push_back(Point3f(2.5f, 0.0f, 2.5f)); m2.push_back(Point3f(2.5f, 1.0f, 2.5f)); |
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m1.push_back(Point3f(2.0f, 0.0f, 1.0f)); m2.push_back(Point3f(2.0f, 1.0f, 1.0f)); |
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cv::Mat m3D, inl; |
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int res = cv::estimateAffine3D(m1, m2, m3D, inl); |
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EXPECT_EQ(1, res); |
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} |
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}} // namespace
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