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Merge pull request #21841 from victor1234:calib3d-undistortPoints-tests

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Add distort/undistort test for fisheye::undistortPoints()

* Add distort/undistort test for fisheye::undistortPoints()

Lack of test has allowed error described in 19138 to be unnoticed.
In addition to random points, four corners and principal center
added to point set

* Add random distortion coefficients set

* Move undistortPoints test to google test, refactor

* Add fisheye::undistortPoints() perf test

* Add negative distortion coefficients to undistortPoints test, increase value

* Move to theRNG()

* Change test check from cvtest::norm(L2) to EXPECT_MAT_NEAR()

* Layout fix

* Add points number parameters, comments
This commit is contained in:
Victor 2022-04-19 21:07:34 +03:00 committed by GitHub
parent 9cd5a0a1e6
commit 5cc154147f
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3 changed files with 124 additions and 41 deletions
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36
modules/calib3d/perf/perf_undistort.cpp
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@ -27,4 +27,40 @@ PERF_TEST(Undistort, DISABLED_InitInverseRectificationMap)
SANITY_CHECK_NOTHING();
}
using PerfIntType = perf::TestBaseWithParam<std::tuple<int>>;
PERF_TEST_P(PerfIntType, fisheye_undistortPoints,
(testing::Values(1e2, 1e3, 1e4)))
{
const cv::Size imageSize(1280, 800);
/* Set camera matrix */
const cv::Matx33d K(558.478087865323, 0, 620.458515360843,
0, 560.506767351568, 381.939424848348,
0, 0, 1);
/* Set distortion coefficients */
Mat D(1, 4, CV_64F);
theRNG().fill(D, RNG::UNIFORM, -1.e-5, 1.e-5);
int pointsNumber = std::get<0>(GetParam());
/* Create two-channel points matrix */
cv::Mat xy[2] = {};
xy[0].create(pointsNumber, 1, CV_64F);
theRNG().fill(xy[0], cv::RNG::UNIFORM, 0, imageSize.width); // x
xy[1].create(pointsNumber, 1, CV_64F);
theRNG().fill(xy[1], cv::RNG::UNIFORM, 0, imageSize.height); // y
cv::Mat points;
merge(xy, 2, points);
/* Set fixed iteration number to check only c++ code, not algo convergence */
TermCriteria termCriteria(TermCriteria::MAX_ITER, 10, 0);
Mat undistortedPoints;
TEST_CYCLE() fisheye::undistortPoints(points, undistortedPoints, K, D, noArray(), noArray(), termCriteria);
SANITY_CHECK_NOTHING();
}
} // namespace

49
modules/calib3d/test/test_fisheye.cpp
View File

@ -101,6 +101,55 @@ TEST_F(fisheyeTest, projectPoints)
EXPECT_MAT_NEAR(distorted0, distorted2, 1e-10);
}
TEST_F(fisheyeTest, distortUndistortPoints)
{
int width = imageSize.width;
int height = imageSize.height;
/* Create test points */
std::vector<cv::Point2d> points0Vector;
cv::Mat principalPoints = (cv::Mat_<double>(5, 2) << K(0, 2), K(1, 2), // (cx, cy)
/* Image corners */
0, 0,
0, height,
width, 0,
width, height
);
/* Random points inside image */
cv::Mat xy[2] = {};
xy[0].create(100, 1, CV_64F);
theRNG().fill(xy[0], cv::RNG::UNIFORM, 0, width); // x
xy[1].create(100, 1, CV_64F);
theRNG().fill(xy[1], cv::RNG::UNIFORM, 0, height); // y
cv::Mat randomPoints;
merge(xy, 2, randomPoints);
cv::Mat points0;
cv::vconcat(principalPoints.reshape(2), randomPoints, points0);
/* Test with random D set */
for (size_t i = 0; i < 10; ++i) {
cv::Mat D(1, 4, CV_64F);
theRNG().fill(D, cv::RNG::UNIFORM, -0.00001, 0.00001);
/* Distort -> Undistort */
cv::Mat distortedPoints;
cv::fisheye::distortPoints(points0, distortedPoints, K, D);
cv::Mat undistortedPoints;
cv::fisheye::undistortPoints(distortedPoints, undistortedPoints, K, D);
EXPECT_MAT_NEAR(points0, undistortedPoints, 1e-8);
/* Undistort -> Distort */
cv::fisheye::undistortPoints(points0, undistortedPoints, K, D);
cv::fisheye::distortPoints(undistortedPoints, distortedPoints, K, D);
EXPECT_MAT_NEAR(points0, distortedPoints, 1e-8);
}
}
TEST_F(fisheyeTest, undistortImage)
{
cv::Matx33d theK = this->K;

80
modules/calib3d/test/test_undistort_points.cpp
View File

@ -1,34 +1,24 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include <opencv2/ts/cuda_test.hpp> // EXPECT_MAT_NEAR
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class CV_UndistortTest : public cvtest::BaseTest
class UndistortPointsTest : public ::testing::Test
{
public:
CV_UndistortTest();
~CV_UndistortTest();
protected:
void run(int);
private:
void generate3DPointCloud(vector<Point3f>& points, Point3f pmin = Point3f(-1,
-1, 5), Point3f pmax = Point3f(1, 1, 10));
void generateCameraMatrix(Mat& cameraMatrix);
void generateDistCoeffs(Mat& distCoeffs, int count);
double thresh;
RNG rng;
double thresh = 1.0e-2;
};
CV_UndistortTest::CV_UndistortTest()
{
thresh = 1.0e-2;
}
CV_UndistortTest::~CV_UndistortTest() {}
void CV_UndistortTest::generate3DPointCloud(vector<Point3f>& points, Point3f pmin, Point3f pmax)
void UndistortPointsTest::generate3DPointCloud(vector<Point3f>& points, Point3f pmin, Point3f pmax)
{
RNG rng_Point = cv::theRNG(); // fix the seed to use "fixed" input 3D points
for (size_t i = 0; i < points.size(); i++)
@ -39,31 +29,35 @@ void CV_UndistortTest::generate3DPointCloud(vector<Point3f>& points, Point3f pmi
points[i] = Point3f(_x, _y, _z);
}
}
void CV_UndistortTest::generateCameraMatrix(Mat& cameraMatrix)
void UndistortPointsTest::generateCameraMatrix(Mat& cameraMatrix)
{
const double fcMinVal = 1e-3;
const double fcMaxVal = 100;
cameraMatrix.create(3, 3, CV_64FC1);
cameraMatrix.setTo(Scalar(0));
cameraMatrix.at<double>(0,0) = rng.uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(1,1) = rng.uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(0,2) = rng.uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(1,2) = rng.uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(0,0) = theRNG().uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(1,1) = theRNG().uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(0,2) = theRNG().uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(1,2) = theRNG().uniform(fcMinVal, fcMaxVal);
cameraMatrix.at<double>(2,2) = 1;
}
void CV_UndistortTest::generateDistCoeffs(Mat& distCoeffs, int count)
void UndistortPointsTest::generateDistCoeffs(Mat& distCoeffs, int count)
{
distCoeffs = Mat::zeros(count, 1, CV_64FC1);
for (int i = 0; i < count; i++)
distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-3);
distCoeffs.at<double>(i,0) = theRNG().uniform(-0.1, 0.1);
}
void CV_UndistortTest::run(int /* start_from */)
TEST_F(UndistortPointsTest, accuracy)
{
Mat intrinsics, distCoeffs;
generateCameraMatrix(intrinsics);
vector<Point3f> points(500);
generate3DPointCloud(points);
vector<Point2f> projectedPoints;
projectedPoints.resize(points.size());
@ -71,10 +65,15 @@ void CV_UndistortTest::run(int /* start_from */)
for (int idx = 0; idx < 3; idx++)
{
generateDistCoeffs(distCoeffs, modelMembersCount[idx]);
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, distCoeffs, projectedPoints);
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1),
Mat::zeros(3,1,CV_64FC1), intrinsics,
distCoeffs, projectedPoints);
vector<Point2f> realUndistortedPoints;
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, Mat::zeros(4,1,CV_64FC1), realUndistortedPoints);
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1),
Mat::zeros(3,1,CV_64FC1), intrinsics,
Mat::zeros(4,1,CV_64FC1), realUndistortedPoints);
Mat undistortedPoints;
undistortPoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs);
@ -82,44 +81,43 @@ void CV_UndistortTest::run(int /* start_from */)
Mat p;
perspectiveTransform(undistortedPoints, p, intrinsics);
undistortedPoints = p;
double diff = cvtest::norm(Mat(realUndistortedPoints), undistortedPoints, NORM_L2);
if (diff > thresh)
{
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
ts->set_failed_test_info(cvtest::TS::OK);
EXPECT_MAT_NEAR(realUndistortedPoints, undistortedPoints.t(), thresh);
}
}
TEST(Calib3d_Undistort, accuracy) { CV_UndistortTest test; test.safe_run(); }
TEST(Calib3d_Undistort, stop_criteria)
TEST_F(UndistortPointsTest, stop_criteria)
{
Mat cameraMatrix = (Mat_<double>(3,3,CV_64F) << 857.48296979, 0, 968.06224829,
0, 876.71824265, 556.37145899,
0, 0, 1);
Mat distCoeffs = (Mat_<double>(5,1,CV_64F) <<
-2.57614020e-01, 8.77086999e-02, -2.56970803e-04, -5.93390389e-04, -1.52194091e-02);
RNG rng(2);
Point2d pt_distorted(rng.uniform(0.0, 1920.0), rng.uniform(0.0, 1080.0));
Point2d pt_distorted(theRNG().uniform(0.0, 1920.0), theRNG().uniform(0.0, 1080.0));
std::vector<Point2d> pt_distorted_vec;
pt_distorted_vec.push_back(pt_distorted);
const double maxError = 1e-6;
TermCriteria criteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 100, maxError);
std::vector<Point2d> pt_undist_vec;
undistortPoints(pt_distorted_vec, pt_undist_vec, cameraMatrix, distCoeffs, noArray(), noArray(), criteria);
std::vector<Point2d> pt_redistorted_vec;
std::vector<Point3d> pt_undist_vec_homogeneous;
pt_undist_vec_homogeneous.push_back( Point3d(pt_undist_vec[0].x, pt_undist_vec[0].y, 1.0) );
projectPoints(pt_undist_vec_homogeneous, Mat::zeros(3,1,CV_64F), Mat::zeros(3,1,CV_64F), cameraMatrix, distCoeffs, pt_redistorted_vec);
pt_undist_vec_homogeneous.emplace_back(pt_undist_vec[0].x, pt_undist_vec[0].y, 1.0 );
std::vector<Point2d> pt_redistorted_vec;
projectPoints(pt_undist_vec_homogeneous, Mat::zeros(3,1,CV_64F),
Mat::zeros(3,1,CV_64F), cameraMatrix, distCoeffs, pt_redistorted_vec);
const double obtainedError = sqrt( pow(pt_distorted.x - pt_redistorted_vec[0].x, 2) + pow(pt_distorted.y - pt_redistorted_vec[0].y, 2) );
ASSERT_LE(obtainedError, maxError);
}
TEST(undistortPoints, regression_14583)
TEST_F(UndistortPointsTest, regression_14583)
{
const int col = 720;
// const int row = 540;