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Merge pull request #24005 from ivashmak:merge_usac_5.x

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Merge usac to 5.x #24005

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake


Base branch is PR #23979. Merging PR #23078, 23900 and PR #23806  to 5.x
This commit is contained in:
Maksym Ivashechkin
2023-07-27 15:51:16 +01:00
committed by GitHub
parent 4d695cd2f4
commit 0e8748746f
26 changed files with 4758 additions and 2586 deletions
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modules/3d/test/test_usac.cpp
+6 -9
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@@ -181,12 +181,9 @@ static double getError (TestSolver test_case, int pt_idx, const cv::Mat &pts1, c
if (test_case == TestSolver::Fundam || test_case == TestSolver::Essen) {
cv::Mat l2 = model * pt1;
cv::Mat l1 = model.t() * pt2;
if (test_case == TestSolver::Fundam) // sampson error
return fabs(pt2.dot(l2)) / sqrt(pow(l1.at<double>(0), 2) + pow(l1.at<double>(1), 2) +
pow(l2.at<double>(0), 2) + pow(l2.at<double>(1), 2));
else // symmetric geometric distance
return sqrt(pow(pt1.dot(l1),2) / (pow(l1.at<double>(0),2) + pow(l1.at<double>(1),2)) +
pow(pt2.dot(l2),2) / (pow(l2.at<double>(0),2) + pow(l2.at<double>(1),2)));
// Sampson error
return fabs(pt2.dot(l2)) / sqrt(pow(l1.at<double>(0), 2) + pow(l1.at<double>(1), 2) +
pow(l2.at<double>(0), 2) + pow(l2.at<double>(1), 2));
} else
if (test_case == TestSolver::PnP) { // PnP, reprojection error
cv::Mat img_pt = model * pt2; img_pt /= img_pt.at<double>(2);
@@ -340,7 +337,7 @@ TEST_P(usac_Essential, maxiters) {
cv::Mat K1 = cv::Mat(cv::Matx33d(1, 0, 0,
0, 1, 0,
0, 0, 1.));
const double conf = 0.99, thr = 0.5;
const double conf = 0.99, thr = 0.25;
int roll_results_sum = 0;
for (int iters = 0; iters < 10; iters++) {
@@ -361,8 +358,8 @@ TEST_P(usac_Essential, maxiters) {
FAIL() << "Essential matrix estimation failed!\n";
else continue;
}
EXPECT_NE(roll_results_sum, 0);
}
EXPECT_NE(roll_results_sum, 0);
}
INSTANTIATE_TEST_CASE_P(Calib3d, usac_Essential, UsacMethod::all());
@@ -416,7 +413,7 @@ TEST (usac_Affine2D, accuracy) {
TEST(usac_testUsacParams, accuracy) {
std::vector<int> gt_inliers;
const int pts_size = 150000;
const int pts_size = 1500;
cv::RNG &rng = cv::theRNG();
const cv::UsacParams usac_params = cv::UsacParams();
cv::Mat pts1, pts2, K1, K2, mask, model, rvec, tvec, R;