141 lines
3.8 KiB
C++
141 lines
3.8 KiB
C++
#include "perf_precomp.hpp"
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#include "opencv2/core/internal.hpp"
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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CV_ENUM(pnpAlgo, CV_ITERATIVE, CV_EPNP /*, CV_P3P*/)
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typedef std::tr1::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(
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testing::Values(/*4,*/ 3*9, 7*13), //TODO: find why results on 4 points are too unstable
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testing::Values((int)CV_ITERATIVE, (int)CV_EPNP)
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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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add(points2d, noise, points2d);
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declare.in(points3d, points2d);
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TEST_CYCLE_N(1000)
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{
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solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
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}
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SANITY_CHECK(rvec, 1e-6);
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SANITY_CHECK(tvec, 1e-3);
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}
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PERF_TEST(PointsNum_Algo, solveP3P)
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{
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int 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) = 400.0;
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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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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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solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, CV_P3P);
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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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PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(4, 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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#ifdef HAVE_TBB
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// limit concurrency to get deterministic result
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cv::Ptr<tbb::task_scheduler_init> one_thread = new tbb::task_scheduler_init(1);
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#endif
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TEST_CYCLE()
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{
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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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