Merge pull request #26669 from GouMinghao:4.x

solvePnPRansac implementation for Fisheye camera model #26669

Related: https://github.com/opencv/opencv/pull/25028

### 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
- [ ] There is a reference to the original bug report and related work
- [ ] 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

modules/calib3d/include/opencv2/calib3d.hpp

@@ -4075,6 +4075,40 @@ optimization. It is the \f$max(width,height)/\pi\f$ or the provided \f$f_x\f$, \
     the provided rvec and tvec values as initial approximations of the rotation and translation
     vectors, respectively, and further optimizes them.
     @param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
+    @param criteria Termination criteria for internal undistortPoints call.
+    The function interally undistorts points with @ref undistortPoints and call @ref cv::solvePnP,
+    thus the input are very similar. More information about Perspective-n-Points is described in @ref calib3d_solvePnP
+    for more information.
+    */
+    CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
+                                InputArray cameraMatrix, InputArray distCoeffs,
+                                OutputArray rvec, OutputArray tvec,
+                                bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE,
+                                TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8)
+                              );
+
+    /**
+    @brief Finds an object pose from 3D-2D point correspondences using the RANSAC scheme for fisheye camera moodel.
+
+    @param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+    1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+    @param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+    where N is the number of points. vector\<Point2d\> can be also passed here.
+    @param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+    @param distCoeffs Input vector of distortion coefficients (4x1/1x4).
+    @param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+    the model coordinate system to the camera coordinate system.
+    @param tvec Output translation vector.
+    @param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses
+    the provided rvec and tvec values as initial approximations of the rotation and translation
+    vectors, respectively, and further optimizes them.
+    @param iterationsCount Number of iterations.
+    @param reprojectionError Inlier threshold value used by the RANSAC procedure. The parameter value
+    is the maximum allowed distance between the observed and computed point projections to consider it
+    an inlier.
+    @param confidence The probability that the algorithm produces a useful result.
+    @param inliers Output vector that contains indices of inliers in objectPoints and imagePoints .
+    @param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
     This function returns the rotation and the translation vectors that transform a 3D point expressed in the object
     coordinate frame to the camera coordinate frame, using different methods:
     - P3P methods (@ref SOLVEPNP_P3P, @ref SOLVEPNP_AP3P): need 4 input points to return a unique solution.
@@ -4091,12 +4125,14 @@ optimization. It is the \f$max(width,height)/\pi\f$ or the provided \f$f_x\f$, \
     thus the input are very similar. More information about Perspective-n-Points is described in @ref calib3d_solvePnP
     for more information.
     */
-    CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
-                                InputArray cameraMatrix, InputArray distCoeffs,
-                                OutputArray rvec, OutputArray tvec,
-                                bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE,
-                                TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8)
-                              );
+    CV_EXPORTS_W bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
+                                      InputArray cameraMatrix, InputArray distCoeffs,
+                                      OutputArray rvec, OutputArray tvec,
+                                      bool useExtrinsicGuess = false, int iterationsCount = 100,
+                                      float reprojectionError = 8.0, double confidence = 0.99,
+                                      OutputArray inliers = noArray(), int flags = SOLVEPNP_ITERATIVE,
+                                      TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8)
+                                    );
 
 //! @} calib3d_fisheye
 } // end namespace fisheye