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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) 2009, 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.
- //
- // * Redistribution's in binary form must reproduce the above copyright notice,
- // this list of conditions and the following disclaimer in the documentation
- // and/or other materials provided with the distribution.
- //
- // * The name of the copyright holders may not be used to endorse or promote products
- // derived from this software without specific prior written permission.
- //
- // This software is provided by the copyright holders and contributors "as is" and
- // any express or implied warranties, including, but not limited to, the implied
- // warranties of merchantability and fitness for a particular purpose are disclaimed.
- // In no event shall the Intel Corporation or contributors be liable for any direct,
- // indirect, incidental, special, exemplary, or consequential damages
- // (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,
- // or tort (including negligence or otherwise) arising in any way out of
- // the use of this software, even if advised of the possibility of such damage.
- //
- //M*/
- #include "test_precomp.hpp"
- namespace opencv_test { namespace {
- class CV_Affine3D_EstTest : public cvtest::BaseTest
- {
- public:
- CV_Affine3D_EstTest();
- ~CV_Affine3D_EstTest();
- protected:
- void run(int);
- bool test4Points();
- bool testNPoints();
- };
- CV_Affine3D_EstTest::CV_Affine3D_EstTest()
- {
- }
- CV_Affine3D_EstTest::~CV_Affine3D_EstTest() {}
- float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
- struct WrapAff
- {
- const double *F;
- WrapAff(const Mat& aff) : F(aff.ptr<double>()) {}
- Point3f operator()(const Point3f& p)
- {
- return Point3f( (float)(p.x * F[0] + p.y * F[1] + p.z * F[2] + F[3]),
- (float)(p.x * F[4] + p.y * F[5] + p.z * F[6] + F[7]),
- (float)(p.x * F[8] + p.y * F[9] + p.z * F[10] + F[11]) );
- }
- };
- bool CV_Affine3D_EstTest::test4Points()
- {
- Mat aff(3, 4, CV_64F);
- cv::randu(aff, Scalar(1), Scalar(3));
- // setting points that are no in the same line
- Mat fpts(1, 4, CV_32FC3);
- Mat tpts(1, 4, CV_32FC3);
- fpts.ptr<Point3f>()[0] = Point3f( rngIn(1,2), rngIn(1,2), rngIn(5, 6) );
- fpts.ptr<Point3f>()[1] = Point3f( rngIn(3,4), rngIn(3,4), rngIn(5, 6) );
- fpts.ptr<Point3f>()[2] = Point3f( rngIn(1,2), rngIn(3,4), rngIn(5, 6) );
- fpts.ptr<Point3f>()[3] = Point3f( rngIn(3,4), rngIn(1,2), rngIn(5, 6) );
- std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + 4, tpts.ptr<Point3f>(), WrapAff(aff));
- Mat aff_est;
- vector<uchar> outliers;
- estimateAffine3D(fpts, tpts, aff_est, outliers);
- const double thres = 1e-3;
- if (cvtest::norm(aff_est, aff, NORM_INF) > thres)
- {
- //cout << cvtest::norm(aff_est, aff, NORM_INF) << endl;
- ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
- return false;
- }
- return true;
- }
- struct Noise
- {
- float l;
- Noise(float level) : l(level) {}
- Point3f operator()(const Point3f& p)
- {
- RNG& rng = theRNG();
- return Point3f( p.x + l * (float)rng, p.y + l * (float)rng, p.z + l * (float)rng);
- }
- };
- bool CV_Affine3D_EstTest::testNPoints()
- {
- Mat aff(3, 4, CV_64F);
- cv::randu(aff, Scalar(-2), Scalar(2));
- // setting points that are no in the same line
- const int n = 100;
- const int m = 3*n/5;
- const Point3f shift_outl = Point3f(15, 15, 15);
- const float noise_level = 20.f;
- Mat fpts(1, n, CV_32FC3);
- Mat tpts(1, n, CV_32FC3);
- randu(fpts, Scalar::all(0), Scalar::all(100));
- std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + n, tpts.ptr<Point3f>(), WrapAff(aff));
- /* adding noise*/
- std::transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m,
- [=] (const Point3f& pt) -> Point3f { return Noise(noise_level)(pt + shift_outl); });
- Mat aff_est;
- vector<uchar> outl;
- int res = estimateAffine3D(fpts, tpts, aff_est, outl);
- if (!res)
- {
- ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
- return false;
- }
- const double thres = 1e-4;
- if (cvtest::norm(aff_est, aff, NORM_INF) > thres)
- {
- cout << "aff est: " << aff_est << endl;
- cout << "aff ref: " << aff << endl;
- ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
- return false;
- }
- bool outl_good = count(outl.begin(), outl.end(), 1) == m &&
- m == accumulate(outl.begin(), outl.begin() + m, 0);
- if (!outl_good)
- {
- ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
- return false;
- }
- return true;
- }
- void CV_Affine3D_EstTest::run( int /* start_from */)
- {
- cvtest::DefaultRngAuto dra;
- if (!test4Points())
- return;
- if (!testNPoints())
- return;
- ts->set_failed_test_info(cvtest::TS::OK);
- }
- TEST(Calib3d_EstimateAffine3D, accuracy) { CV_Affine3D_EstTest test; test.safe_run(); }
- TEST(Calib3d_EstimateAffine3D, regression_16007)
- {
- std::vector<cv::Point3f> m1, m2;
- m1.push_back(Point3f(1.0f, 0.0f, 0.0f)); m2.push_back(Point3f(1.0f, 1.0f, 0.0f));
- m1.push_back(Point3f(1.0f, 0.0f, 1.0f)); m2.push_back(Point3f(1.0f, 1.0f, 1.0f));
- m1.push_back(Point3f(0.5f, 0.0f, 0.5f)); m2.push_back(Point3f(0.5f, 1.0f, 0.5f));
- m1.push_back(Point3f(2.5f, 0.0f, 2.5f)); m2.push_back(Point3f(2.5f, 1.0f, 2.5f));
- m1.push_back(Point3f(2.0f, 0.0f, 1.0f)); m2.push_back(Point3f(2.0f, 1.0f, 1.0f));
- cv::Mat m3D, inl;
- int res = cv::estimateAffine3D(m1, m2, m3D, inl);
- EXPECT_EQ(1, res);
- }
- TEST(Calib3d_EstimateAffine3D, umeyama_3_pt)
- {
- std::vector<cv::Vec3d> points = {{{0.80549149, 0.8225781, 0.79949521},
- {0.28906756, 0.57158557, 0.9864789},
- {0.58266182, 0.65474983, 0.25078834}}};
- cv::Mat R = (cv::Mat_<double>(3,3) << 0.9689135, -0.0232753, 0.2463025,
- 0.0236362, 0.9997195, 0.0014915,
- -0.2462682, 0.0043765, 0.9691918);
- cv::Vec3d t(1., 2., 3.);
- cv::Affine3d transform(R, t);
- std::vector<cv::Vec3d> transformed_points(points.size());
- std::transform(points.begin(), points.end(), transformed_points.begin(), [transform](const cv::Vec3d v){return transform * v;});
- double scale;
- cv::Mat trafo_est = estimateAffine3D(points, transformed_points, &scale);
- Mat R_est(trafo_est(Rect(0, 0, 3, 3)));
- EXPECT_LE(cvtest::norm(R_est, R, NORM_INF), 1e-6);
- Vec3d t_est = trafo_est.col(3);
- EXPECT_LE(cvtest::norm(t_est, t, NORM_INF), 1e-6);
- EXPECT_NEAR(scale, 1.0, 1e-6);
- }
- }} // namespace
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