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#include "perf_precomp.hpp"
#ifdef HAVE_TBB
#include "tbb/task_scheduler_init.h"
#endif
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(pnpAlgo, SOLVEPNP_ITERATIVE, SOLVEPNP_EPNP, SOLVEPNP_P3P, SOLVEPNP_DLS, SOLVEPNP_UPNP)
typedef std::tr1::tuple<int, pnpAlgo> PointsNum_Algo_t;
typedef perf::TestBaseWithParam<PointsNum_Algo_t> PointsNum_Algo;
typedef perf::TestBaseWithParam<int> PointsNum;
PERF_TEST_P(PointsNum_Algo, solvePnP,
testing::Combine(
testing::Values(5, 3*9, 7*13), //TODO: find why results on 4 points are too unstable
testing::Values((int)SOLVEPNP_ITERATIVE, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_UPNP, (int)SOLVEPNP_DLS)
)
)
{
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);
declare.time(100);
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_P(PointsNum_Algo, solvePnPSmallPoints,
testing::Combine(
testing::Values(5),
testing::Values((int)SOLVEPNP_P3P, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_DLS, (int)SOLVEPNP_UPNP)
)
)
{
int pointsNum = get<0>(GetParam());
pnpAlgo algo = get<1>(GetParam());
if( algo == SOLVEPNP_P3P )
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) = 400.0f;
intrinsics.at<float> (1, 1) = 400.0f;
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);
// normalize Rodrigues vector
Mat rvec_tmp = Mat::eye(3, 3, CV_32F);
Rodrigues(rvec, rvec_tmp);
Rodrigues(rvec_tmp, rvec);
projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
Mat noise(1, (int)points2d.size(), CV_32FC2);
randu(noise, -0.001, 0.001);
add(points2d, noise, points2d);
declare.in(points3d, points2d);
declare.time(100);
TEST_CYCLE_N(1000)
{
solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
}
SANITY_CHECK(rvec, 1e-1);
SANITY_CHECK(tvec, 1e-2);
}
PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(5, 3*9, 7*13))
{
int count = GetParam();
Mat object(1, count, CV_32FC3);
randu(object, -100, 100);
Mat camera_mat(3, 3, CV_32FC1);
randu(camera_mat, 0.5, 1);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));
vector<cv::Point2f> image_vec;
Mat rvec_gold(1, 3, CV_32FC1);
randu(rvec_gold, 0, 1);
Mat tvec_gold(1, 3, CV_32FC1);
randu(tvec_gold, 0, 1);
projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);
Mat image(1, count, CV_32FC2, &image_vec[0]);
Mat rvec;
Mat tvec;
#ifdef HAVE_TBB
// limit concurrency to get deterministic result
tbb::task_scheduler_init one_thread(1);
#endif
TEST_CYCLE()
{
solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
}
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
}
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