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Open Source Computer Vision Library
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97 lines
3.1 KiB
97 lines
3.1 KiB
13 years ago
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#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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