148 lines
5.5 KiB
C++
148 lines
5.5 KiB
C++
// 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 "test_precomp.hpp"
|
|
|
|
namespace opencv_test { namespace {
|
|
|
|
class CV_UndistortTest : public cvtest::BaseTest
|
|
{
|
|
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;
|
|
};
|
|
|
|
CV_UndistortTest::CV_UndistortTest()
|
|
{
|
|
thresh = 1.0e-2;
|
|
}
|
|
CV_UndistortTest::~CV_UndistortTest() {}
|
|
|
|
void CV_UndistortTest::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 CV_UndistortTest::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>(2,2) = 1;
|
|
}
|
|
void CV_UndistortTest::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);
|
|
}
|
|
|
|
void CV_UndistortTest::run(int /* start_from */)
|
|
{
|
|
Mat intrinsics, distCoeffs;
|
|
generateCameraMatrix(intrinsics);
|
|
vector<Point3f> points(500);
|
|
generate3DPointCloud(points);
|
|
vector<Point2f> projectedPoints;
|
|
projectedPoints.resize(points.size());
|
|
|
|
int modelMembersCount[] = {4,5,8};
|
|
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);
|
|
|
|
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);
|
|
|
|
Mat undistortedPoints;
|
|
undistortPoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs);
|
|
|
|
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);
|
|
}
|
|
}
|
|
|
|
TEST(Calib3d_Undistort, accuracy) { CV_UndistortTest test; test.safe_run(); }
|
|
|
|
TEST(Calib3d_Undistort, 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));
|
|
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);
|
|
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)
|
|
{
|
|
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
|