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// 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 "opencv2/core/types.hpp"
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class UndistortPointsTest : public ::testing::Test
{
protected:
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);
cv::Mat generateRotationVector();
double thresh = 1.0e-2;
};
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++)
{
float _x = rng_Point.uniform(pmin.x, pmax.x);
float _y = rng_Point.uniform(pmin.y, pmax.y);
float _z = rng_Point.uniform(pmin.z, pmax.z);
points[i] = Point3f(_x, _y, _z);
}
}
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) = 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 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) = theRNG().uniform(-0.1, 0.1);
}
cv::Mat UndistortPointsTest::generateRotationVector()
{
Mat rvec(1, 3, CV_64F);
theRNG().fill(rvec, RNG::UNIFORM, -0.2, 0.2);
return rvec;
}
TEST_F(UndistortPointsTest, accuracy)
{
Mat intrinsics, distCoeffs;
generateCameraMatrix(intrinsics);
vector<Point3f> points(500);
generate3DPointCloud(points);
Mat rvec = generateRotationVector();
Mat R;
cv::Rodrigues(rvec, R);
int modelMembersCount[] = {4,5,8};
for (int idx = 0; idx < 3; idx++)
{
generateDistCoeffs(distCoeffs, modelMembersCount[idx]);
/* Project points with distortion */
vector<Point2f> projectedPoints;
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1),
Mat::zeros(3,1,CV_64FC1), intrinsics,
distCoeffs, projectedPoints);
/* Project points without distortion */
vector<Point2f> realUndistortedPoints;
projectPoints(Mat(points), rvec,
Mat::zeros(3,1,CV_64FC1), intrinsics,
Mat::zeros(4,1,CV_64FC1), realUndistortedPoints);
/* Undistort points */
Mat undistortedPoints;
undistortPoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs, R, intrinsics);
EXPECT_MAT_NEAR(realUndistortedPoints, undistortedPoints.t(), thresh);
}
}
TEST_F(UndistortPointsTest, undistortImagePointsAccuracy)
{
Mat intrinsics, distCoeffs;
generateCameraMatrix(intrinsics);
vector<Point3f> points(500);
generate3DPointCloud(points);
int modelMembersCount[] = {4,5,8};
for (int idx = 0; idx < 3; idx++)
{
generateDistCoeffs(distCoeffs, modelMembersCount[idx]);
/* Project points with distortion */
vector<Point2f> projectedPoints;
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1),
Mat::zeros(3,1,CV_64FC1), intrinsics,
distCoeffs, projectedPoints);
/* Project points without distortion */
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);
/* Undistort points */
Mat undistortedPoints;
TermCriteria termCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, thresh / 2);
undistortImagePoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs,
termCriteria);
EXPECT_MAT_NEAR(realUndistortedPoints, undistortedPoints.t(), thresh);
}
}
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);
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;
Mat rVec = Mat(Matx31d(0.1, -0.2, 0.2));
Mat R;
cv::Rodrigues(rVec, R);
undistortPoints(pt_distorted_vec, pt_undist_vec, cameraMatrix, distCoeffs, R, noArray(), criteria);
std::vector<Point3d> pt_undist_vec_homogeneous;
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, -rVec,
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_F(UndistortPointsTest, regression_14583)
{
const int col = 720;
// const int row = 540;
float camera_matrix_value[] = {
437.8995f, 0.0f, 342.9241f,
0.0f, 438.8216f, 273.7163f,
0.0f, 0.0f, 1.0f
};
cv::Mat camera_interior(3, 3, CV_32F, camera_matrix_value);
float camera_distort_value[] = {-0.34329f, 0.11431f, 0.0f, 0.0f, -0.017375f};
cv::Mat camera_distort(1, 5, CV_32F, camera_distort_value);
float distort_points_value[] = {col, 0.};
cv::Mat distort_pt(1, 1, CV_32FC2, distort_points_value);
cv::Mat undistort_pt;
cv::undistortPoints(distort_pt, undistort_pt, camera_interior,
camera_distort, cv::Mat(), camera_interior);
EXPECT_NEAR(distort_pt.at<Vec2f>(0)[0], undistort_pt.at<Vec2f>(0)[0], col / 2)
<< "distort point: " << distort_pt << std::endl
<< "undistort point: " << undistort_pt;
}
}} // namespace
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