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https://github.com/opencv/opencv.git
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54279523a3
* trying to fix the custom AVX2 builder test failures (false alarms) * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * fixed compile error with CPU_BASELINE=AVX2 on x86; raised tolerance thresholds in a couple of tests * seemingly disabled false alarm warning in surf.cpp; increased tolerance thresholds in the tests for SolvePnP and in DNN/ENet
110 lines
4.0 KiB
C++
110 lines
4.0 KiB
C++
/*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) 2008-2013, 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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#include "opencv2/core/affine.hpp"
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namespace opencv_test { namespace {
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TEST(Calib3d_Affine3f, accuracy)
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{
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const double eps = 1e-5;
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cv::Vec3d rvec(0.2, 0.5, 0.3);
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cv::Affine3d affine(rvec);
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cv::Mat expected;
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cv::Rodrigues(rvec, expected);
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ASSERT_LE(cvtest::norm(cv::Mat(affine.matrix, false).colRange(0, 3).rowRange(0, 3), expected, cv::NORM_L2), eps);
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ASSERT_LE(cvtest::norm(cv::Mat(affine.linear()), expected, cv::NORM_L2), eps);
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cv::Matx33d R = cv::Matx33d::eye();
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double angle = 50;
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R.val[0] = R.val[4] = std::cos(CV_PI*angle/180.0);
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R.val[3] = std::sin(CV_PI*angle/180.0);
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R.val[1] = -R.val[3];
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cv::Affine3d affine1(cv::Mat(cv::Vec3d(0.2, 0.5, 0.3)).reshape(1, 1), cv::Vec3d(4, 5, 6));
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cv::Affine3d affine2(R, cv::Vec3d(1, 1, 0.4));
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cv::Affine3d result = affine1.inv() * affine2;
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expected = cv::Mat(affine1.matrix.inv(cv::DECOMP_SVD)) * cv::Mat(affine2.matrix, false);
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cv::Mat diff;
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cv::absdiff(expected, result.matrix, diff);
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ASSERT_LT(cvtest::norm(diff, cv::NORM_INF), 1e-15);
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}
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TEST(Calib3d_Affine3f, accuracy_rvec)
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{
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cv::RNG rng;
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typedef float T;
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cv::Affine3<T>::Vec3 w;
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cv::Affine3<T>::Mat3 u, vt, R;
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for(int i = 0; i < 100; ++i)
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{
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rng.fill(R, cv::RNG::UNIFORM, -10, 10, true);
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cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A);
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R = u * vt;
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//double s = (double)cv::getTickCount();
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cv::Affine3<T>::Vec3 va = cv::Affine3<T>(R).rvec();
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//std::cout << "M:" <<(cv::getTickCount() - s)*1000/cv::getTickFrequency() << std::endl;
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cv::Affine3<T>::Vec3 vo;
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//s = (double)cv::getTickCount();
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cv::Rodrigues(R, vo);
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//std::cout << "O:" <<(cv::getTickCount() - s)*1000/cv::getTickFrequency() << std::endl;
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ASSERT_LT(cvtest::norm(va, vo, cv::NORM_L2), 1e-9);
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}
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}
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}} // namespace
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