151 lines
4.2 KiB
C++
151 lines
4.2 KiB
C++
#include "perf_precomp.hpp"
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namespace opencv_test
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{
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using namespace perf;
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CV_ENUM(pnpAlgo, SOLVEPNP_ITERATIVE, SOLVEPNP_EPNP, SOLVEPNP_P3P, SOLVEPNP_DLS, SOLVEPNP_UPNP)
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typedef tuple<int, pnpAlgo> PointsNum_Algo_t;
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typedef perf::TestBaseWithParam<PointsNum_Algo_t> PointsNum_Algo;
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typedef perf::TestBaseWithParam<int> PointsNum;
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PERF_TEST_P(PointsNum_Algo, solvePnP,
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testing::Combine( //When non planar, DLT needs at least 6 points for SOLVEPNP_ITERATIVE flag
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testing::Values(6, 3*9, 7*13), //TODO: find why results on 4 points are too unstable
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testing::Values((int)SOLVEPNP_ITERATIVE, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_UPNP, (int)SOLVEPNP_DLS)
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)
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)
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{
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int pointsNum = get<0>(GetParam());
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pnpAlgo algo = get<1>(GetParam());
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vector<Point2f> points2d(pointsNum);
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vector<Point3f> points3d(pointsNum);
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Mat rvec = Mat::zeros(3, 1, CV_32FC1);
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Mat tvec = Mat::zeros(3, 1, CV_32FC1);
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Mat distortion = Mat::zeros(5, 1, CV_32FC1);
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Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
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intrinsics.at<float> (0, 0) = 400.0;
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intrinsics.at<float> (1, 1) = 400.0;
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intrinsics.at<float> (0, 2) = 640 / 2;
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intrinsics.at<float> (1, 2) = 480 / 2;
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warmup(points3d, WARMUP_RNG);
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warmup(rvec, WARMUP_RNG);
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warmup(tvec, WARMUP_RNG);
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projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
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//add noise
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Mat noise(1, (int)points2d.size(), CV_32FC2);
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randu(noise, 0, 0.01);
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cv::add(points2d, noise, points2d);
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declare.in(points3d, points2d);
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declare.time(100);
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TEST_CYCLE_N(1000)
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{
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cv::solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
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}
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SANITY_CHECK(rvec, 1e-4);
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SANITY_CHECK(tvec, 1e-4);
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}
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PERF_TEST_P(PointsNum_Algo, solvePnPSmallPoints,
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testing::Combine(
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testing::Values(5),
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testing::Values((int)SOLVEPNP_P3P, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_DLS, (int)SOLVEPNP_UPNP)
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)
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)
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{
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int pointsNum = get<0>(GetParam());
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pnpAlgo algo = get<1>(GetParam());
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if( algo == SOLVEPNP_P3P )
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pointsNum = 4;
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vector<Point2f> points2d(pointsNum);
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vector<Point3f> points3d(pointsNum);
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Mat rvec = Mat::zeros(3, 1, CV_32FC1);
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Mat tvec = Mat::zeros(3, 1, CV_32FC1);
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Mat distortion = Mat::zeros(5, 1, CV_32FC1);
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Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
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intrinsics.at<float> (0, 0) = 400.0f;
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intrinsics.at<float> (1, 1) = 400.0f;
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intrinsics.at<float> (0, 2) = 640 / 2;
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intrinsics.at<float> (1, 2) = 480 / 2;
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warmup(points3d, WARMUP_RNG);
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warmup(rvec, WARMUP_RNG);
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warmup(tvec, WARMUP_RNG);
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// normalize Rodrigues vector
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Mat rvec_tmp = Mat::eye(3, 3, CV_32F);
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cv::Rodrigues(rvec, rvec_tmp);
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cv::Rodrigues(rvec_tmp, rvec);
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cv::projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
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//add noise
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Mat noise(1, (int)points2d.size(), CV_32FC2);
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randu(noise, -0.001, 0.001);
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cv::add(points2d, noise, points2d);
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declare.in(points3d, points2d);
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declare.time(100);
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TEST_CYCLE_N(1000)
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{
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cv::solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
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}
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SANITY_CHECK(rvec, 1e-1);
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SANITY_CHECK(tvec, 1e-2);
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}
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PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(5, 3*9, 7*13))
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{
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int count = GetParam();
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Mat object(1, count, CV_32FC3);
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randu(object, -100, 100);
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Mat camera_mat(3, 3, CV_32FC1);
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randu(camera_mat, 0.5, 1);
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camera_mat.at<float>(0, 1) = 0.f;
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camera_mat.at<float>(1, 0) = 0.f;
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camera_mat.at<float>(2, 0) = 0.f;
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camera_mat.at<float>(2, 1) = 0.f;
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Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));
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vector<cv::Point2f> image_vec;
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Mat rvec_gold(1, 3, CV_32FC1);
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randu(rvec_gold, 0, 1);
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Mat tvec_gold(1, 3, CV_32FC1);
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randu(tvec_gold, 0, 1);
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projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);
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Mat image(1, count, CV_32FC2, &image_vec[0]);
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Mat rvec;
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Mat tvec;
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TEST_CYCLE()
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{
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cv::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
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}
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SANITY_CHECK(rvec, 1e-6);
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SANITY_CHECK(tvec, 1e-6);
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}
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} // namespace
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