Merge pull request #22986 from AleksandrPanov:move_contrib_charuco_to_main_objdetect

merge with https://github.com/opencv/opencv_contrib/pull/3394

move Charuco API from contrib to main repo:

- add CharucoDetector:
```
CharucoDetector::detectBoard(InputArray image, InputOutputArrayOfArrays markerCorners, InputOutputArray markerIds, 
                             OutputArray charucoCorners, OutputArray charucoIds) const // detect charucoCorners and/or markerCorners
CharucoDetector::detectDiamonds(InputArray image, InputOutputArrayOfArrays _markerCorners,
                                InputOutputArrayOfArrays _markerIds, OutputArrayOfArrays _diamondCorners,
                                OutputArray _diamondIds) const
```

- add `matchImagePoints()` for `CharucoBoard`
- remove contrib aruco dependencies from interactive-calibration tool
- move almost all aruco tests to objdetect

### 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
This commit is contained in:
Alexander Panov
2022-12-28 17:28:59 +03:00
committed by GitHub
parent 9627ab9462
commit 121034876d
21 changed files with 2721 additions and 499 deletions
@@ -105,6 +105,26 @@ using a Boosted Cascade of Simple Features. IEEE CVPR, 2001. The paper is availa
@defgroup objdetect_dnn_face DNN-based face detection and recognition
Check @ref tutorial_dnn_face "the corresponding tutorial" for more details.
@defgroup objdetect_common Common functions and classes
@defgroup objdetect_aruco ArUco markers and boards detection for robust camera pose estimation
@{
ArUco Marker Detection
Square fiducial markers (also known as Augmented Reality Markers) are useful for easy,
fast and robust camera pose estimation.
The main functionality of ArucoDetector class is detection of markers in an image. If the markers are grouped
as a board, then you can try to recover the missing markers with ArucoDetector::refineDetectedMarkers().
ArUco markers can also be used for advanced chessboard corner finding. To do this, group the markers in the
CharucoBoard and find the corners of the chessboard with the CharucoDetector::detectBoard().
The implementation is based on the ArUco Library by R. Muñoz-Salinas and S. Garrido-Jurado @cite Aruco2014.
Markers can also be detected based on the AprilTag 2 @cite wang2016iros fiducial detection method.
@sa @cite Aruco2014
This code has been originally developed by Sergio Garrido-Jurado as a project
for Google Summer of Code 2015 (GSoC 15).
@}
@}
*/
@@ -852,5 +872,6 @@ protected:
#include "opencv2/objdetect/detection_based_tracker.hpp"
#include "opencv2/objdetect/face.hpp"
#include "opencv2/objdetect/aruco_detector.hpp"
#include "opencv2/objdetect/charuco_detector.hpp"
#endif