197 lines
6.2 KiB
C++
197 lines
6.2 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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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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// (3-clause BSD License)
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//
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// Copyright (C) 2015-2016, OpenCV Foundation, 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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// * Redistributions 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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// * Redistributions 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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// * Neither the names of the copyright holders nor the names of the contributors
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// may be used to endorse or promote products derived from this software
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// 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 copyright holders 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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CV_ENUM(Method, RANSAC, LMEDS)
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typedef TestWithParam<Method> EstimateAffine2D;
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static float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
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TEST_P(EstimateAffine2D, test3Points)
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{
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// try more transformations
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for (size_t i = 0; i < 500; ++i)
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{
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Mat aff(2, 3, CV_64F);
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cv::randu(aff, 1., 3.);
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Mat fpts(1, 3, CV_32FC2);
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Mat tpts(1, 3, CV_32FC2);
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// setting points that are not in the same line
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fpts.at<Point2f>(0) = Point2f( rngIn(1,2), rngIn(5,6) );
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fpts.at<Point2f>(1) = Point2f( rngIn(3,4), rngIn(3,4) );
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fpts.at<Point2f>(2) = Point2f( rngIn(1,2), rngIn(3,4) );
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transform(fpts, tpts, aff);
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vector<uchar> inliers;
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Mat aff_est = estimateAffine2D(fpts, tpts, inliers, GetParam() /* method */);
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EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-3);
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// all must be inliers
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EXPECT_EQ(countNonZero(inliers), 3);
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}
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}
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TEST_P(EstimateAffine2D, testNPoints)
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{
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// try more transformations
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for (size_t i = 0; i < 500; ++i)
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{
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Mat aff(2, 3, CV_64F);
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cv::randu(aff, -2., 2.);
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const int method = GetParam();
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const int n = 100;
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int m;
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// LMEDS can't handle more than 50% outliers (by design)
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if (method == LMEDS)
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m = 3*n/5;
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else
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m = 2*n/5;
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const float shift_outl = 15.f;
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const float noise_level = 20.f;
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Mat fpts(1, n, CV_32FC2);
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Mat tpts(1, n, CV_32FC2);
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randu(fpts, 0., 100.);
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transform(fpts, tpts, aff);
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/* adding noise to some points */
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Mat outliers = tpts.colRange(m, n);
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outliers.reshape(1) += shift_outl;
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Mat noise (outliers.size(), outliers.type());
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randu(noise, 0., noise_level);
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outliers += noise;
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vector<uchar> inliers;
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Mat aff_est = estimateAffine2D(fpts, tpts, inliers, method);
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EXPECT_FALSE(aff_est.empty()) << "estimation failed, unable to estimate transform";
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EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-4);
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bool inliers_good = count(inliers.begin(), inliers.end(), 1) == m &&
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m == accumulate(inliers.begin(), inliers.begin() + m, 0);
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EXPECT_TRUE(inliers_good);
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}
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}
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// test conversion from other datatypes than float
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TEST_P(EstimateAffine2D, testConversion)
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{
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Mat aff(2, 3, CV_32S);
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cv::randu(aff, 1., 3.);
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std::vector<Point> fpts(3);
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std::vector<Point> tpts(3);
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// setting points that are not in the same line
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fpts[0] = Point2f( rngIn(1,2), rngIn(5,6) );
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fpts[1] = Point2f( rngIn(3,4), rngIn(3,4) );
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fpts[2] = Point2f( rngIn(1,2), rngIn(3,4) );
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transform(fpts, tpts, aff);
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vector<uchar> inliers;
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Mat aff_est = estimateAffine2D(fpts, tpts, inliers, GetParam() /* method */);
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ASSERT_FALSE(aff_est.empty());
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aff.convertTo(aff, CV_64F); // need to convert before compare
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EXPECT_NEAR(0., cvtest::norm(aff_est, aff, NORM_INF), 1e-3);
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// all must be inliers
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EXPECT_EQ(countNonZero(inliers), 3);
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}
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INSTANTIATE_TEST_CASE_P(Calib3d, EstimateAffine2D, Method::all());
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// https://github.com/opencv/opencv/issues/14259
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TEST(EstimateAffine2D, issue_14259_dont_change_inputs)
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{
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/*const static*/ float pts0_[10] = {
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0.0f, 0.0f,
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0.0f, 8.0f,
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4.0f, 0.0f, // outlier
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8.0f, 8.0f,
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8.0f, 0.0f
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};
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/*const static*/ float pts1_[10] = {
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0.1f, 0.1f,
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0.1f, 8.1f,
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0.0f, 4.0f, // outlier
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8.1f, 8.1f,
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8.1f, 0.1f
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};
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Mat pts0(Size(1, 5), CV_32FC2, (void*)pts0_);
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Mat pts1(Size(1, 5), CV_32FC2, (void*)pts1_);
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Mat pts0_copy = pts0.clone();
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Mat pts1_copy = pts1.clone();
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Mat inliers;
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cv::Mat A = cv::estimateAffine2D(pts0, pts1, inliers);
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for(int i = 0; i < pts0.rows; ++i)
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{
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EXPECT_EQ(pts0_copy.at<Vec2f>(i), pts0.at<Vec2f>(i)) << "pts0: i=" << i;
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}
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for(int i = 0; i < pts1.rows; ++i)
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{
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EXPECT_EQ(pts1_copy.at<Vec2f>(i), pts1.at<Vec2f>(i)) << "pts1: i=" << i;
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}
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EXPECT_EQ(0, (int)inliers.at<uchar>(2));
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}
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}} // namespace
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