mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
199 lines
6.8 KiB
199 lines
6.8 KiB
// 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
|
|
|