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241 lines
8.6 KiB
241 lines
8.6 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "test_precomp.hpp" |
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using namespace cv; |
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using namespace std; |
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class CV_solvePnPRansac_Test : public cvtest::BaseTest |
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{ |
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public: |
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CV_solvePnPRansac_Test() |
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{ |
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eps[CV_ITERATIVE] = 1.0e-2; |
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eps[CV_EPNP] = 1.0e-2; |
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eps[CV_P3P] = 1.0e-2; |
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totalTestsCount = 10; |
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} |
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~CV_solvePnPRansac_Test() {} |
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protected: |
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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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{ |
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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 generateCameraMatrix(Mat& cameraMatrix, RNG& rng) |
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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 generateDistCoeffs(Mat& distCoeffs, RNG& rng) |
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{ |
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distCoeffs = Mat::zeros(4, 1, CV_64FC1); |
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for (int i = 0; i < 3; i++) |
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distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-6); |
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} |
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void generatePose(Mat& rvec, Mat& tvec, RNG& rng) |
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{ |
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const double minVal = 1.0e-3; |
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const double maxVal = 1.0; |
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rvec.create(3, 1, CV_64FC1); |
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tvec.create(3, 1, CV_64FC1); |
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for (int i = 0; i < 3; i++) |
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{ |
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rvec.at<double>(i,0) = rng.uniform(minVal, maxVal); |
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tvec.at<double>(i,0) = rng.uniform(minVal, maxVal/10); |
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} |
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} |
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virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* eps, double& maxError) |
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{ |
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Mat rvec, tvec; |
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vector<int> inliers; |
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Mat trueRvec, trueTvec; |
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Mat intrinsics, distCoeffs; |
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generateCameraMatrix(intrinsics, rng); |
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if (mode == 0) |
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distCoeffs = Mat::zeros(4, 1, CV_64FC1); |
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else |
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generateDistCoeffs(distCoeffs, rng); |
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generatePose(trueRvec, trueTvec, rng); |
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vector<Point2f> projectedPoints; |
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projectedPoints.resize(points.size()); |
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projectPoints(Mat(points), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints); |
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for (size_t i = 0; i < projectedPoints.size(); i++) |
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{ |
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if (i % 20 == 0) |
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{ |
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projectedPoints[i] = projectedPoints[rng.uniform(0,points.size()-1)]; |
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} |
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} |
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solvePnPRansac(points, projectedPoints, intrinsics, distCoeffs, rvec, tvec, |
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false, 500, 0.5, -1, inliers, method); |
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bool isTestSuccess = inliers.size() >= points.size()*0.95; |
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double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec); |
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isTestSuccess = isTestSuccess && rvecDiff < eps[method] && tvecDiff < eps[method]; |
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double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff; |
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//cout << error << " " << inliers.size() << " " << eps[method] << endl; |
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if (error > maxError) |
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maxError = error; |
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return isTestSuccess; |
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} |
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void run(int) |
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{ |
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cvtest::TS& ts = *this->ts; |
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ts.set_failed_test_info(cvtest::TS::OK); |
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vector<Point3f> points; |
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const int pointsCount = 500; |
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points.resize(pointsCount); |
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generate3DPointCloud(points); |
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const int methodsCount = 3; |
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RNG rng = ts.get_rng(); |
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for (int mode = 0; mode < 2; mode++) |
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{ |
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for (int method = 0; method < methodsCount; method++) |
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{ |
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double maxError = 0; |
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int successfulTestsCount = 0; |
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for (int testIndex = 0; testIndex < totalTestsCount; testIndex++) |
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{ |
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if (runTest(rng, mode, method, points, eps, maxError)) |
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successfulTestsCount++; |
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} |
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//cout << maxError << " " << successfulTestsCount << endl; |
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if (successfulTestsCount < 0.7*totalTestsCount) |
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{ |
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ts.printf( cvtest::TS::LOG, "Invalid accuracy for method %d, failed %d tests from %d, maximum error equals %f, distortion mode equals %d\n", |
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method, totalTestsCount - successfulTestsCount, totalTestsCount, maxError, mode); |
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ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); |
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} |
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} |
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} |
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} |
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double eps[3]; |
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int totalTestsCount; |
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}; |
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class CV_solvePnP_Test : public CV_solvePnPRansac_Test |
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{ |
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public: |
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CV_solvePnP_Test() |
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{ |
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eps[CV_ITERATIVE] = 1.0e-6; |
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eps[CV_EPNP] = 1.0e-6; |
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eps[CV_P3P] = 1.0e-4; |
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totalTestsCount = 1000; |
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} |
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~CV_solvePnP_Test() {} |
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protected: |
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virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* eps, double& maxError) |
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{ |
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Mat rvec, tvec; |
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Mat trueRvec, trueTvec; |
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Mat intrinsics, distCoeffs; |
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generateCameraMatrix(intrinsics, rng); |
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if (mode == 0) |
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distCoeffs = Mat::zeros(4, 1, CV_64FC1); |
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else |
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generateDistCoeffs(distCoeffs, rng); |
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generatePose(trueRvec, trueTvec, rng); |
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std::vector<Point3f> opoints; |
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if (method == 2) |
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{ |
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opoints = std::vector<Point3f>(points.begin(), points.begin()+4); |
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} |
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else |
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opoints = points; |
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vector<Point2f> projectedPoints; |
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projectedPoints.resize(opoints.size()); |
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projectPoints(Mat(opoints), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints); |
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solvePnP(opoints, projectedPoints, intrinsics, distCoeffs, rvec, tvec, |
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false, method); |
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double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec); |
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bool isTestSuccess = rvecDiff < eps[method] && tvecDiff < eps[method]; |
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double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff; |
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if (error > maxError) |
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maxError = error; |
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return isTestSuccess; |
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} |
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}; |
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TEST(Calib3d_SolvePnPRansac, accuracy) { CV_solvePnPRansac_Test test; test.safe_run(); } |
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TEST(Calib3d_SolvePnP, accuracy) { CV_solvePnP_Test test; test.safe_run(); } |
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