Open Source Computer Vision Library https://opencv.org/
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#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(pnpAlgo, CV_ITERATIVE, CV_EPNP /*, CV_P3P*/)
typedef std::tr1::tuple<int, pnpAlgo> PointsNum_Algo_t;
typedef perf::TestBaseWithParam<PointsNum_Algo_t> PointsNum_Algo;
PERF_TEST_P(PointsNum_Algo, solvePnP,
testing::Combine(
testing::Values(4, 3*9, 7*13),
testing::Values((int)CV_ITERATIVE, (int)CV_EPNP)
)
)
{
int pointsNum = get<0>(GetParam());
pnpAlgo algo = get<1>(GetParam());
vector<Point2f> points2d(pointsNum);
vector<Point3f> points3d(pointsNum);
Mat rvec = Mat::zeros(3, 1, CV_32FC1);
Mat tvec = Mat::zeros(3, 1, CV_32FC1);
Mat distortion = Mat::zeros(5, 1, CV_32FC1);
Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
intrinsics.at<float> (0, 0) = 400.0;
intrinsics.at<float> (1, 1) = 400.0;
intrinsics.at<float> (0, 2) = 640 / 2;
intrinsics.at<float> (1, 2) = 480 / 2;
warmup(points3d, WARMUP_RNG);
warmup(rvec, WARMUP_RNG);
warmup(tvec, WARMUP_RNG);
projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
Mat noise(1, (int)points2d.size(), CV_32FC2);
randu(noise, 0, 0.01);
add(points2d, noise, points2d);
declare.in(points3d, points2d);
TEST_CYCLE_N(1000) solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
}
PERF_TEST(PointsNum_Algo, solveP3P)
{
int pointsNum = 4;
vector<Point2f> points2d(pointsNum);
vector<Point3f> points3d(pointsNum);
Mat rvec = Mat::zeros(3, 1, CV_32FC1);
Mat tvec = Mat::zeros(3, 1, CV_32FC1);
Mat distortion = Mat::zeros(5, 1, CV_32FC1);
Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
intrinsics.at<float> (0, 0) = 400.0;
intrinsics.at<float> (1, 1) = 400.0;
intrinsics.at<float> (0, 2) = 640 / 2;
intrinsics.at<float> (1, 2) = 480 / 2;
warmup(points3d, WARMUP_RNG);
warmup(rvec, WARMUP_RNG);
warmup(tvec, WARMUP_RNG);
projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
Mat noise(1, (int)points2d.size(), CV_32FC2);
randu(noise, 0, 0.01);
add(points2d, noise, points2d);
declare.in(points3d, points2d);
TEST_CYCLE_N(1000) solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, CV_P3P);
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
}