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120 lines
4.4 KiB
C++
120 lines
4.4 KiB
C++
#include "test_precomp.hpp"
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#include <string>
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using namespace cv;
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using namespace std;
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class CV_UndistortTest : public cvtest::BaseTest
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{
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public:
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CV_UndistortTest();
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~CV_UndistortTest();
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protected:
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void run(int);
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private:
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void generate3DPointCloud(vector<Point3f>& points, Point3f pmin = Point3f(-1,
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-1, 5), Point3f pmax = Point3f(1, 1, 10));
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void generateCameraMatrix(Mat& cameraMatrix);
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void generateDistCoeffs(Mat& distCoeffs, int count);
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double thresh;
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RNG rng;
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};
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CV_UndistortTest::CV_UndistortTest()
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{
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thresh = 1.0e-2;
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}
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CV_UndistortTest::~CV_UndistortTest() {}
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void CV_UndistortTest::generate3DPointCloud(vector<Point3f>& points, Point3f pmin, Point3f pmax)
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{
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RNG rng_Point = ::theRNG(); // fix the seed to use "fixed" input 3D points
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for (size_t i = 0; i < points.size(); i++)
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{
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float _x = rng_Point.uniform(pmin.x, pmax.x);
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float _y = rng_Point.uniform(pmin.y, pmax.y);
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float _z = rng_Point.uniform(pmin.z, pmax.z);
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points[i] = Point3f(_x, _y, _z);
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}
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}
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void CV_UndistortTest::generateCameraMatrix(Mat& cameraMatrix)
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{
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const double fcMinVal = 1e-3;
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const double fcMaxVal = 100;
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cameraMatrix.create(3, 3, CV_64FC1);
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cameraMatrix.setTo(Scalar(0));
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cameraMatrix.at<double>(0,0) = rng.uniform(fcMinVal, fcMaxVal);
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cameraMatrix.at<double>(1,1) = rng.uniform(fcMinVal, fcMaxVal);
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cameraMatrix.at<double>(0,2) = rng.uniform(fcMinVal, fcMaxVal);
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cameraMatrix.at<double>(1,2) = rng.uniform(fcMinVal, fcMaxVal);
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cameraMatrix.at<double>(2,2) = 1;
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}
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void CV_UndistortTest::generateDistCoeffs(Mat& distCoeffs, int count)
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{
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distCoeffs = Mat::zeros(count, 1, CV_64FC1);
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for (int i = 0; i < count; i++)
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distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-3);
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}
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void CV_UndistortTest::run(int /* start_from */)
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{
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Mat intrinsics, distCoeffs;
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generateCameraMatrix(intrinsics);
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vector<Point3f> points(500);
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generate3DPointCloud(points);
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vector<Point2f> projectedPoints;
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projectedPoints.resize(points.size());
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int modelMembersCount[] = {4,5,8};
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for (int idx = 0; idx < 3; idx++)
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{
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generateDistCoeffs(distCoeffs, modelMembersCount[idx]);
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projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, distCoeffs, projectedPoints);
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vector<Point2f> realUndistortedPoints;
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projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, Mat::zeros(4,1,CV_64FC1), realUndistortedPoints);
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Mat undistortedPoints;
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undistortPoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs);
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Mat p;
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perspectiveTransform(undistortedPoints, p, intrinsics);
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undistortedPoints = p;
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double diff = cvtest::norm(Mat(realUndistortedPoints), undistortedPoints, NORM_L2);
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if (diff > thresh)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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return;
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}
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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}
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TEST(Calib3d_Undistort, accuracy) { CV_UndistortTest test; test.safe_run(); }
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TEST(Calib3d_Undistort, stop_criteria)
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{
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Mat cameraMatrix = (Mat_<double>(3,3,CV_64F) << 857.48296979, 0, 968.06224829,
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0, 876.71824265, 556.37145899,
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0, 0, 1);
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Mat distCoeffs = (Mat_<double>(5,1,CV_64F) <<
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-2.57614020e-01, 8.77086999e-02, -2.56970803e-04, -5.93390389e-04, -1.52194091e-02);
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RNG rng(2);
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Point2d pt_distorted(rng.uniform(0.0, 1920.0), rng.uniform(0.0, 1080.0));
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std::vector<Point2d> pt_distorted_vec;
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pt_distorted_vec.push_back(pt_distorted);
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const double maxError = 1e-6;
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TermCriteria criteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 100, maxError);
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std::vector<Point2d> pt_undist_vec;
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undistortPoints(pt_distorted_vec, pt_undist_vec, cameraMatrix, distCoeffs, noArray(), noArray(), criteria);
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std::vector<Point2d> pt_redistorted_vec;
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std::vector<Point3d> pt_undist_vec_homogeneous;
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pt_undist_vec_homogeneous.push_back( Point3d(pt_undist_vec[0].x, pt_undist_vec[0].y, 1.0) );
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projectPoints(pt_undist_vec_homogeneous, Mat::zeros(3,1,CV_64F), Mat::zeros(3,1,CV_64F), cameraMatrix, distCoeffs, pt_redistorted_vec);
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const double obtainedError = sqrt( pow(pt_distorted.x - pt_redistorted_vec[0].x, 2) + pow(pt_distorted.y - pt_redistorted_vec[0].y, 2) );
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ASSERT_LE(obtainedError, maxError);
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}
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