mirror of
https://github.com/opencv/opencv.git
synced 2024-12-13 16:09:23 +08:00
207 lines
6.7 KiB
C++
207 lines
6.7 KiB
C++
/*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> EstimateAffinePartial2D;
|
|
|
|
static float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
|
|
|
|
// get random matrix of affine transformation limited to combinations of translation,
|
|
// rotation, and uniform scaling
|
|
static Mat rngPartialAffMat() {
|
|
double theta = rngIn(0, (float)CV_PI*2.f);
|
|
double scale = rngIn(0, 3);
|
|
double tx = rngIn(-2, 2);
|
|
double ty = rngIn(-2, 2);
|
|
double aff[2*3] = { std::cos(theta) * scale, -std::sin(theta) * scale, tx,
|
|
std::sin(theta) * scale, std::cos(theta) * scale, ty };
|
|
return Mat(2, 3, CV_64F, aff).clone();
|
|
}
|
|
|
|
TEST_P(EstimateAffinePartial2D, test2Points)
|
|
{
|
|
// try more transformations
|
|
for (size_t i = 0; i < 500; ++i)
|
|
{
|
|
Mat aff = rngPartialAffMat();
|
|
|
|
// setting points that are no in the same line
|
|
Mat fpts(1, 2, CV_32FC2);
|
|
Mat tpts(1, 2, CV_32FC2);
|
|
|
|
fpts.at<Point2f>(0) = Point2f( rngIn(1,2), rngIn(5,6) );
|
|
fpts.at<Point2f>(1) = Point2f( rngIn(3,4), rngIn(3,4) );
|
|
|
|
transform(fpts, tpts, aff);
|
|
|
|
vector<uchar> inliers;
|
|
Mat aff_est = estimateAffinePartial2D(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), 2);
|
|
}
|
|
}
|
|
|
|
TEST_P(EstimateAffinePartial2D, testNPoints)
|
|
{
|
|
// try more transformations
|
|
for (size_t i = 0; i < 500; ++i)
|
|
{
|
|
Mat aff = rngPartialAffMat();
|
|
|
|
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 = estimateAffinePartial2D(fpts, tpts, inliers, method);
|
|
|
|
EXPECT_FALSE(aff_est.empty());
|
|
|
|
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(EstimateAffinePartial2D, testConversion)
|
|
{
|
|
Mat aff = rngPartialAffMat();
|
|
aff.convertTo(aff, CV_32S); // convert to int to transform ints properly
|
|
|
|
std::vector<Point> fpts(3);
|
|
std::vector<Point> tpts(3);
|
|
|
|
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 = estimateAffinePartial2D(fpts, tpts, inliers, GetParam() /* method */);
|
|
|
|
ASSERT_FALSE(aff_est.empty());
|
|
|
|
aff.convertTo(aff, CV_64F); // need to convert back 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, EstimateAffinePartial2D, Method::all());
|
|
|
|
|
|
// https://github.com/opencv/opencv/issues/14259
|
|
TEST(EstimateAffinePartial2D, 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::estimateAffinePartial2D(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
|