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