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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2008-2013, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
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// this list of conditions and the following disclaimer in the documentation
// 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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// This software is provided by the copyright holders and contributors "as is" and
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// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
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//M*/
#include "test_precomp.hpp"
#include "opencv2/core/affine.hpp"
namespace opencv_test { namespace {
TEST(Calib3d_Affine3f, accuracy)
{
const double eps = 1e-5;
cv::Vec3d rvec(0.2, 0.5, 0.3);
cv::Affine3d affine(rvec);
cv::Mat expected;
cv::Rodrigues(rvec, expected);
ASSERT_LE(cvtest::norm(cv::Mat(affine.matrix, false).colRange(0, 3).rowRange(0, 3), expected, cv::NORM_L2), eps);
ASSERT_LE(cvtest::norm(cv::Mat(affine.linear()), expected, cv::NORM_L2), eps);
cv::Matx33d R = cv::Matx33d::eye();
double angle = 50;
R.val[0] = R.val[4] = std::cos(CV_PI*angle/180.0);
R.val[3] = std::sin(CV_PI*angle/180.0);
R.val[1] = -R.val[3];
cv::Affine3d affine1(cv::Mat(cv::Vec3d(0.2, 0.5, 0.3)).reshape(1, 1), cv::Vec3d(4, 5, 6));
cv::Affine3d affine2(R, cv::Vec3d(1, 1, 0.4));
cv::Affine3d result = affine1.inv() * affine2;
expected = cv::Mat(affine1.matrix.inv(cv::DECOMP_SVD)) * cv::Mat(affine2.matrix, false);
cv::Mat diff;
cv::absdiff(expected, result.matrix, diff);
ASSERT_LT(cvtest::norm(diff, cv::NORM_INF), 1e-15);
}
TEST(Calib3d_Affine3f, accuracy_rvec)
{
cv::RNG rng;
typedef float T;
cv::Affine3<T>::Vec3 w;
cv::Affine3<T>::Mat3 u, vt, R;
for(int i = 0; i < 100; ++i)
{
rng.fill(R, cv::RNG::UNIFORM, -10, 10, true);
cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A);
R = u * vt;
//double s = (double)cv::getTickCount();
cv::Affine3<T>::Vec3 va = cv::Affine3<T>(R).rvec();
//std::cout << "M:" <<(cv::getTickCount() - s)*1000/cv::getTickFrequency() << std::endl;
cv::Affine3<T>::Vec3 vo;
//s = (double)cv::getTickCount();
cv::Rodrigues(R, vo);
//std::cout << "O:" <<(cv::getTickCount() - s)*1000/cv::getTickFrequency() << std::endl;
ASSERT_LT(cvtest::norm(va, vo, cv::NORM_L2), 1e-9);
}
}
}} // namespace
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