184 lines
5.9 KiB
C++
184 lines
5.9 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) 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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// this is test for a deprecated function. let's ignore deprecated warnings in this file
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#if defined(__clang__)
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#pragma clang diagnostic ignored "-Wdeprecated-declarations"
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#elif defined(__GNUC__)
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#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
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#elif defined(_MSC_VER)
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#pragma warning( disable : 4996)
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#endif
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namespace opencv_test { namespace {
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class CV_RigidTransform_Test : public cvtest::BaseTest
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{
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public:
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CV_RigidTransform_Test();
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~CV_RigidTransform_Test();
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protected:
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void run(int);
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bool testNPoints(int);
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bool testImage();
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};
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CV_RigidTransform_Test::CV_RigidTransform_Test()
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{
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}
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CV_RigidTransform_Test::~CV_RigidTransform_Test() {}
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struct WrapAff2D
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{
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const double *F;
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WrapAff2D(const Mat& aff) : F(aff.ptr<double>()) {}
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Point2f operator()(const Point2f& p)
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{
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return Point2f( (float)(p.x * F[0] + p.y * F[1] + F[2]),
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(float)(p.x * F[3] + p.y * F[4] + F[5]) );
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}
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};
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bool CV_RigidTransform_Test::testNPoints(int from)
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{
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cv::RNG rng = ts->get_rng();
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int progress = 0;
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int k, ntests = 10000;
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for( k = from; k < ntests; k++ )
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{
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ts->update_context( this, k, true );
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progress = update_progress(progress, k, ntests, 0);
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Mat aff(2, 3, CV_64F);
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rng.fill(aff, RNG::UNIFORM, Scalar(-2), Scalar(2));
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int n = (unsigned)rng % 100 + 10;
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Mat fpts(1, n, CV_32FC2);
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Mat tpts(1, n, CV_32FC2);
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rng.fill(fpts, RNG::UNIFORM, Scalar(0,0), Scalar(10,10));
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std::transform(fpts.ptr<Point2f>(), fpts.ptr<Point2f>() + n, tpts.ptr<Point2f>(), WrapAff2D(aff));
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Mat noise(1, n, CV_32FC2);
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rng.fill(noise, RNG::NORMAL, Scalar::all(0), Scalar::all(0.001*(n<=7 ? 0 : n <= 30 ? 1 : 10)));
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tpts += noise;
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Mat aff_est = estimateRigidTransform(fpts, tpts, true);
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double thres = 0.1*cvtest::norm(aff, NORM_L2);
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double d = cvtest::norm(aff_est, aff, NORM_L2);
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if (d > thres)
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{
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double dB=0, nB=0;
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if (n <= 4)
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{
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Mat A = fpts.reshape(1, 3);
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Mat B = A - repeat(A.row(0), 3, 1), Bt = B.t();
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B = Bt*B;
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dB = cv::determinant(B);
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nB = cvtest::norm(B, NORM_L2);
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if( fabs(dB) < 0.01*nB )
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continue;
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}
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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ts->printf( cvtest::TS::LOG, "Threshold = %f, norm of difference = %f", thres, d );
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return false;
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}
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}
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return true;
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}
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bool CV_RigidTransform_Test::testImage()
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{
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Mat img;
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Mat testImg = imread( string(ts->get_data_path()) + "shared/graffiti.png", 1);
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if (testImg.empty())
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{
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ts->printf( ts->LOG, "test image can not be read");
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ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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return false;
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}
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pyrDown(testImg, img);
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Mat aff = cv::getRotationMatrix2D(Point(img.cols/2, img.rows/2), 1, 0.99);
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aff.ptr<double>()[2]+=3;
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aff.ptr<double>()[5]+=3;
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Mat rotated;
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warpAffine(img, rotated, aff, img.size());
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Mat aff_est = estimateRigidTransform(img, rotated, true);
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const double thres = 0.033;
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if (cvtest::norm(aff_est, aff, NORM_INF) > thres)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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ts->printf( cvtest::TS::LOG, "Threshold = %f, norm of difference = %f", thres,
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cvtest::norm(aff_est, aff, NORM_INF) );
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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_RigidTransform_Test::run( int start_from )
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{
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cvtest::DefaultRngAuto dra;
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if (!testNPoints(start_from))
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return;
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if (!testImage())
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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(Video_RigidFlow, accuracy) { CV_RigidTransform_Test test; test.safe_run(); }
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}} // namespace
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