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284 lines
8.1 KiB
284 lines
8.1 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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// Copyright (C) 2013, Alfonso Sanchez-Beato, 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/imgcodecs.hpp> |
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#include <opencv2/core.hpp> |
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#include "opencv2/reg/mapaffine.hpp" |
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#include "opencv2/reg/mapshift.hpp" |
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#include "opencv2/reg/mapprojec.hpp" |
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#include "opencv2/reg/mappergradshift.hpp" |
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#include "opencv2/reg/mappergradeuclid.hpp" |
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#include "opencv2/reg/mappergradsimilar.hpp" |
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#include "opencv2/reg/mappergradaffine.hpp" |
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#include "opencv2/reg/mappergradproj.hpp" |
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#include "opencv2/reg/mapperpyramid.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace cv::reg; |
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class RegTest : public testing::Test |
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{ |
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public: |
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void loadImage(); |
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void testShift(); |
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void testEuclidean(); |
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void testSimilarity(); |
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void testAffine(); |
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void testProjective(); |
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private: |
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Mat img1; |
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}; |
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void RegTest::testShift() |
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{ |
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Mat img2; |
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// Warp original image |
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Vec<double, 2> shift(5., 5.); |
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MapShift mapTest(shift); |
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mapTest.warp(img1, img2); |
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// Register |
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MapperGradShift mapper; |
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MapperPyramid mappPyr(mapper); |
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Ptr<Map> mapPtr; |
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mappPyr.calculate(img1, img2, mapPtr); |
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// Print result |
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MapShift* mapShift = dynamic_cast<MapShift*>(mapPtr.get()); |
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cout << endl << "--- Testing shift mapper ---" << endl; |
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cout << Mat(shift) << endl; |
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cout << Mat(mapShift->getShift()) << endl; |
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// Check accuracy |
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Ptr<Map> mapInv(mapShift->inverseMap()); |
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mapTest.compose(*mapInv.get()); |
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double shNorm = norm(mapTest.getShift()); |
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EXPECT_LE(shNorm, 0.1); |
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} |
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void RegTest::testEuclidean() |
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{ |
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Mat img2; |
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// Warp original image |
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double theta = 3*CV_PI/180; |
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double cosT = cos(theta); |
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double sinT = sin(theta); |
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Matx<double, 2, 2> linTr(cosT, -sinT, sinT, cosT); |
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Vec<double, 2> shift(5., 5.); |
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MapAffine mapTest(linTr, shift); |
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mapTest.warp(img1, img2); |
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// Register |
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MapperGradEuclid mapper; |
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MapperPyramid mappPyr(mapper); |
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Ptr<Map> mapPtr; |
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mappPyr.calculate(img1, img2, mapPtr); |
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// Print result |
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MapAffine* mapAff = dynamic_cast<MapAffine*>(mapPtr.get()); |
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cout << endl << "--- Testing Euclidean mapper ---" << endl; |
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cout << Mat(linTr) << endl; |
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cout << Mat(shift) << endl; |
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cout << Mat(mapAff->getLinTr()) << endl; |
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cout << Mat(mapAff->getShift()) << endl; |
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// Check accuracy |
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Ptr<Map> mapInv(mapAff->inverseMap()); |
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mapTest.compose(*mapInv.get()); |
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double shNorm = norm(mapTest.getShift()); |
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EXPECT_LE(shNorm, 0.1); |
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double linTrNorm = norm(mapTest.getLinTr()); |
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EXPECT_LE(linTrNorm, sqrt(2.) + 0.01); |
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EXPECT_GE(linTrNorm, sqrt(2.) - 0.01); |
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} |
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void RegTest::testSimilarity() |
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{ |
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Mat img2; |
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// Warp original image |
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double theta = 3*CV_PI/180; |
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double scale = 0.95; |
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double a = scale*cos(theta); |
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double b = scale*sin(theta); |
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Matx<double, 2, 2> linTr(a, -b, b, a); |
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Vec<double, 2> shift(5., 5.); |
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MapAffine mapTest(linTr, shift); |
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mapTest.warp(img1, img2); |
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// Register |
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MapperGradSimilar mapper; |
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MapperPyramid mappPyr(mapper); |
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Ptr<Map> mapPtr; |
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mappPyr.calculate(img1, img2, mapPtr); |
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// Print result |
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MapAffine* mapAff = dynamic_cast<MapAffine*>(mapPtr.get()); |
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cout << endl << "--- Testing similarity mapper ---" << endl; |
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cout << Mat(linTr) << endl; |
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cout << Mat(shift) << endl; |
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cout << Mat(mapAff->getLinTr()) << endl; |
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cout << Mat(mapAff->getShift()) << endl; |
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// Check accuracy |
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Ptr<Map> mapInv(mapAff->inverseMap()); |
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mapTest.compose(*mapInv.get()); |
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double shNorm = norm(mapTest.getShift()); |
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EXPECT_LE(shNorm, 0.1); |
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double linTrNorm = norm(mapTest.getLinTr()); |
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EXPECT_LE(linTrNorm, sqrt(2.) + 0.01); |
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EXPECT_GE(linTrNorm, sqrt(2.) - 0.01); |
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} |
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void RegTest::testAffine() |
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{ |
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Mat img2; |
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// Warp original image |
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Matx<double, 2, 2> linTr(1., 0.1, -0.01, 1.); |
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Vec<double, 2> shift(1., 1.); |
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MapAffine mapTest(linTr, shift); |
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mapTest.warp(img1, img2); |
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// Register |
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MapperGradAffine mapper; |
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MapperPyramid mappPyr(mapper); |
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Ptr<Map> mapPtr; |
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mappPyr.calculate(img1, img2, mapPtr); |
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// Print result |
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MapAffine* mapAff = dynamic_cast<MapAffine*>(mapPtr.get()); |
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cout << endl << "--- Testing affine mapper ---" << endl; |
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cout << Mat(linTr) << endl; |
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cout << Mat(shift) << endl; |
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cout << Mat(mapAff->getLinTr()) << endl; |
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cout << Mat(mapAff->getShift()) << endl; |
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// Check accuracy |
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Ptr<Map> mapInv(mapAff->inverseMap()); |
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mapTest.compose(*mapInv.get()); |
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double shNorm = norm(mapTest.getShift()); |
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EXPECT_LE(shNorm, 0.1); |
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double linTrNorm = norm(mapTest.getLinTr()); |
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EXPECT_LE(linTrNorm, sqrt(2.) + 0.01); |
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EXPECT_GE(linTrNorm, sqrt(2.) - 0.01); |
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} |
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void RegTest::testProjective() |
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{ |
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Mat img2; |
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// Warp original image |
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Matx<double, 3, 3> projTr(1., 0., 0., 0., 1., 0., 0.0001, 0.0001, 1); |
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MapProjec mapTest(projTr); |
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mapTest.warp(img1, img2); |
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// Register |
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MapperGradProj mapper; |
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MapperPyramid mappPyr(mapper); |
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Ptr<Map> mapPtr; |
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mappPyr.calculate(img1, img2, mapPtr); |
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// Print result |
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MapProjec* mapProj = dynamic_cast<MapProjec*>(mapPtr.get()); |
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mapProj->normalize(); |
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cout << endl << "--- Testing projective transformation mapper ---" << endl; |
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cout << Mat(projTr) << endl; |
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cout << Mat(mapProj->getProjTr()) << endl; |
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// Check accuracy |
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Ptr<Map> mapInv(mapProj->inverseMap()); |
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mapTest.compose(*mapInv.get()); |
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double projNorm = norm(mapTest.getProjTr()); |
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EXPECT_LE(projNorm, sqrt(3.) + 0.01); |
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EXPECT_GE(projNorm, sqrt(3.) - 0.01); |
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} |
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void RegTest::loadImage() |
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{ |
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const string imageName = cvtest::TS::ptr()->get_data_path() + "reg/home.png"; |
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img1 = imread(imageName, -1); |
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ASSERT_TRUE(img1.data != 0); |
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// Convert to double, 3 channels |
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img1.convertTo(img1, CV_64FC3); |
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} |
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TEST_F(RegTest, shift) |
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{ |
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loadImage(); |
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testShift(); |
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} |
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TEST_F(RegTest, euclidean) |
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{ |
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loadImage(); |
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testEuclidean(); |
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} |
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TEST_F(RegTest, similarity) |
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{ |
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loadImage(); |
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testSimilarity(); |
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} |
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TEST_F(RegTest, affine) |
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{ |
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loadImage(); |
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testAffine(); |
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} |
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TEST_F(RegTest, projective) |
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{ |
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loadImage(); |
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testProjective(); |
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}
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