289 lines
8.1 KiB
C++
289 lines
8.1 KiB
C++
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/*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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namespace opencv_test { namespace {
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#define REG_DEBUG_OUTPUT 0
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class RegTest : public testing::Test
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{
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public:
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void loadImage(int dstDataType = CV_32FC3);
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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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Ptr<Mapper> mapper = makePtr<MapperGradShift>();
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MapperPyramid mappPyr(mapper);
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Ptr<Map> mapPtr = mappPyr.calculate(img1, img2);
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// Print result
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Ptr<MapShift> mapShift = MapTypeCaster::toShift(mapPtr);
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#if REG_DEBUG_OUTPUT
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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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#endif
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// Check accuracy
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Ptr<Map> mapInv(mapShift->inverseMap());
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mapTest.compose(mapInv);
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double shNorm = cv::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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Ptr<Mapper> mapper = makePtr<MapperGradEuclid>();
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MapperPyramid mappPyr(mapper);
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Ptr<Map> mapPtr = mappPyr.calculate(img1, img2);
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// Print result
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Ptr<MapAffine> mapAff = MapTypeCaster::toAffine(mapPtr);
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#if REG_DEBUG_OUTPUT
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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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#endif
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// Check accuracy
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Ptr<Map> mapInv(mapAff->inverseMap());
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mapTest.compose(mapInv);
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double shNorm = cv::norm(mapTest.getShift());
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EXPECT_LE(shNorm, 0.1);
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double linTrNorm = cv::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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Ptr<Mapper> mapper = makePtr<MapperGradSimilar>();
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MapperPyramid mappPyr(mapper);
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Ptr<Map> mapPtr = mappPyr.calculate(img1, img2);
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// Print result
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Ptr<MapAffine> mapAff = MapTypeCaster::toAffine(mapPtr);
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#if REG_DEBUG_OUTPUT
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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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#endif
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// Check accuracy
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Ptr<Map> mapInv(mapAff->inverseMap());
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mapTest.compose(mapInv);
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double shNorm = cv::norm(mapTest.getShift());
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EXPECT_LE(shNorm, 0.1);
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double linTrNorm = cv::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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Ptr<Mapper> mapper = makePtr<MapperGradAffine>();
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MapperPyramid mappPyr(mapper);
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Ptr<Map> mapPtr = mappPyr.calculate(img1, img2);
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// Print result
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Ptr<MapAffine> mapAff = MapTypeCaster::toAffine(mapPtr);
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#if REG_DEBUG_OUTPUT
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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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#endif
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// Check accuracy
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Ptr<Map> mapInv(mapAff->inverseMap());
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mapTest.compose(mapInv);
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double shNorm = cv::norm(mapTest.getShift());
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EXPECT_LE(shNorm, 0.1);
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double linTrNorm = cv::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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Ptr<Mapper> mapper = makePtr<MapperGradProj>();
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MapperPyramid mappPyr(mapper);
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Ptr<Map> mapPtr = mappPyr.calculate(img1, img2);
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// Print result
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Ptr<MapProjec> mapProj = MapTypeCaster::toProjec(mapPtr);
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mapProj->normalize();
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#if REG_DEBUG_OUTPUT
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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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#endif
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// Check accuracy
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Ptr<Map> mapInv(mapProj->inverseMap());
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mapTest.compose(mapInv);
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double projNorm = cv::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(int dstDataType)
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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.empty());
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img1.convertTo(img1, dstDataType);
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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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TEST_F(RegTest, projective_dt64fc3)
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{
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loadImage(CV_64FC3);
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testProjective();
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}
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TEST_F(RegTest, projective_dt64fc1)
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{
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loadImage(CV_64FC1);
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testProjective();
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}
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}} // namespace
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