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Open Source Computer Vision Library
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148 lines
5.5 KiB
148 lines
5.5 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html. |
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#include "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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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 = cv::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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TEST(undistortPoints, regression_14583) |
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{ |
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const int col = 720; |
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// const int row = 540; |
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float camera_matrix_value[] = { |
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437.8995f, 0.0f, 342.9241f, |
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0.0f, 438.8216f, 273.7163f, |
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0.0f, 0.0f, 1.0f |
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}; |
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cv::Mat camera_interior(3, 3, CV_32F, camera_matrix_value); |
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float camera_distort_value[] = {-0.34329f, 0.11431f, 0.0f, 0.0f, -0.017375f}; |
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cv::Mat camera_distort(1, 5, CV_32F, camera_distort_value); |
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float distort_points_value[] = {col, 0.}; |
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cv::Mat distort_pt(1, 1, CV_32FC2, distort_points_value); |
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cv::Mat undistort_pt; |
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cv::undistortPoints(distort_pt, undistort_pt, camera_interior, |
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camera_distort, cv::Mat(), camera_interior); |
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EXPECT_NEAR(distort_pt.at<Vec2f>(0)[0], undistort_pt.at<Vec2f>(0)[0], col / 2) |
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<< "distort point: " << distort_pt << std::endl |
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<< "undistort point: " << undistort_pt; |
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} |
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}} // namespace
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