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Open Source Computer Vision Library
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97 lines
3.0 KiB
97 lines
3.0 KiB
#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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const Point3f delta = pmax - pmin; |
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for (size_t i = 0; i < points.size(); i++) |
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{ |
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Point3f p(float(rand()) / RAND_MAX, float(rand()) / RAND_MAX, |
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float(rand()) / RAND_MAX); |
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p.x *= delta.x; |
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p.y *= delta.y; |
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p.z *= delta.z; |
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p = p + pmin; |
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points[i] = p; |
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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 = norm(Mat(realUndistortedPoints), undistortedPoints); |
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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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