opencv/modules/3d/perf/perf_pnp.cpp
Vadim Pisarevsky 416bf3253d
attempt to add 0d/1d mat support to OpenCV (#23473)
* attempt to add 0d/1d mat support to OpenCV

* revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1.

* a step towards 'green' tests

* another little step towards 'green' tests

* calib test failures seem to be fixed now

* more fixes _core & _dnn

* another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported!

* * fixed strange bug in aruco/charuco detector, not sure why it did not work
* also fixed a few remaining failures (hopefully) in dnn & core

* disabled failing GAPI tests - too complex to dig into this compiler pipeline

* hopefully fixed java tests

* trying to fix some more tests

* quick followup fix

* continue to fix test failures and warnings

* quick followup fix

* trying to fix some more tests

* partly fixed support for 0D/scalar UMat's

* use updated parseReduce() from upstream

* trying to fix the remaining test failures

* fixed [ch]aruco tests in Python

* still trying to fix tests

* revert "fix" in dnn's CUDA tensor

* trying to fix dnn+CUDA test failures

* fixed 1D umat creation

* hopefully fixed remaining cuda test failures

* removed training whitespaces
2023-09-21 18:24:38 +03:00

154 lines
4.3 KiB
C++

#include "perf_precomp.hpp"
namespace opencv_test
{
using namespace perf;
CV_ENUM(pnpAlgo, SOLVEPNP_ITERATIVE, SOLVEPNP_EPNP, SOLVEPNP_P3P, SOLVEPNP_DLS, SOLVEPNP_UPNP)
typedef 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( //When non planar, DLT needs at least 6 points for SOLVEPNP_ITERATIVE flag
testing::Values(6, 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
int sz = (int)points2d.size();
Mat noise(1, &sz, CV_32FC2);
randu(noise, 0, 0.01);
cv::add(points2d, noise, points2d);
declare.in(points3d, points2d);
declare.time(100);
TEST_CYCLE_N(1000)
{
cv::solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
}
SANITY_CHECK(rvec, 1e-4);
// the check is relaxed from 1e-4 to 2e-2 after LevMarq replacement
SANITY_CHECK(tvec, 2e-2);
}
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);
cv::Rodrigues(rvec, rvec_tmp);
cv::Rodrigues(rvec_tmp, rvec);
cv::projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
int npoints = (int)points2d.size();
Mat noise(1, &npoints, CV_32FC2);
randu(noise, -0.001, 0.001);
cv::add(points2d, noise, points2d);
declare.in(points3d, points2d);
declare.time(100);
TEST_CYCLE_N(1000)
{
cv::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;
TEST_CYCLE()
{
cv::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
}
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
}
} // namespace