opencv
diff --git a/‎modules/calib3d/include/opencv2/calib3d.hpp
Copy file name to clipboard
+9-6Lines changed: 9 additions & 6 deletions b/‎modules/calib3d/include/opencv2/calib3d.hpp
Copy file name to clipboard
+9-6Lines changed: 9 additions & 6 deletions
diff --git a/‎modules/calib3d/src/five-point.cpp
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions b/‎modules/calib3d/src/five-point.cpp
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions
diff --git a/‎modules/calib3d/src/fundam.cpp
Copy file name to clipboard
+4-4Lines changed: 4 additions & 4 deletions b/‎modules/calib3d/src/fundam.cpp
Copy file name to clipboard
+4-4Lines changed: 4 additions & 4 deletions
diff --git a/‎modules/calib3d/src/ptsetreg.cpp
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions b/‎modules/calib3d/src/ptsetreg.cpp
Copy file name to clipboard
+2-2Lines changed: 2 additions & 2 deletions
diff --git a/‎modules/calib3d/src/solvepnp.cpp
Copy file name to clipboard
+1-16Lines changed: 1 addition & 16 deletions b/‎modules/calib3d/src/solvepnp.cpp
Copy file name to clipboard
+1-16Lines changed: 1 addition & 16 deletions
@@ -548,12 +548,13 @@ enum RobotWorldHandEyeCalibrationMethod
     CALIB_ROBOT_WORLD_HAND_EYE_LI   = 1  //!< Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product @cite Li2010SimultaneousRA
 };
 
-enum SamplingMethod { SAMPLING_UNIFORM, SAMPLING_PROGRESSIVE_NAPSAC, SAMPLING_NAPSAC,
-        SAMPLING_PROSAC };
-enum LocalOptimMethod {LOCAL_OPTIM_NULL, LOCAL_OPTIM_INNER_LO, LOCAL_OPTIM_INNER_AND_ITER_LO,
-        LOCAL_OPTIM_GC, LOCAL_OPTIM_SIGMA};
-enum ScoreMethod {SCORE_METHOD_RANSAC, SCORE_METHOD_MSAC, SCORE_METHOD_MAGSAC, SCORE_METHOD_LMEDS};
-enum NeighborSearchMethod { NEIGH_FLANN_KNN, NEIGH_GRID, NEIGH_FLANN_RADIUS };
+enum SamplingMethod { SAMPLING_UNIFORM=0, SAMPLING_PROGRESSIVE_NAPSAC=1, SAMPLING_NAPSAC=2,
+        SAMPLING_PROSAC=3 };
+enum LocalOptimMethod {LOCAL_OPTIM_NULL=0, LOCAL_OPTIM_INNER_LO=1, LOCAL_OPTIM_INNER_AND_ITER_LO=2,
+        LOCAL_OPTIM_GC=3, LOCAL_OPTIM_SIGMA=4};
+enum ScoreMethod {SCORE_METHOD_RANSAC=0, SCORE_METHOD_MSAC=1, SCORE_METHOD_MAGSAC=2, SCORE_METHOD_LMEDS=3};
+enum NeighborSearchMethod { NEIGH_FLANN_KNN=0, NEIGH_GRID=1, NEIGH_FLANN_RADIUS=2 };
+enum PolishingMethod { NONE_POLISHER=0, LSQ_POLISHER=1, MAGSAC=2, COV_POLISHER=3 };
 
 struct CV_EXPORTS_W_SIMPLE UsacParams
 { // in alphabetical order
@@ -569,6 +570,8 @@ struct CV_EXPORTS_W_SIMPLE UsacParams
     CV_PROP_RW SamplingMethod sampler;
     CV_PROP_RW ScoreMethod score;
     CV_PROP_RW double threshold;
+    CV_PROP_RW PolishingMethod final_polisher;
+    CV_PROP_RW int final_polisher_iterations;
 };
 
 /** @brief Converts a rotation matrix to a rotation vector or vice versa.
 
@@ -522,9 +522,9 @@ cv::Mat cv::findEssentialMat( InputArray points1, InputArray points2,
                       InputArray cameraMatrix1, InputArray cameraMatrix2,
                       InputArray dist_coeff1, InputArray dist_coeff2, OutputArray mask, const UsacParams &params) {
     Ptr<usac::Model> model;
-    usac::setParameters(model, usac::EstimationMethod::Essential, params, mask.needed());
+    usac::setParameters(model, usac::EstimationMethod::ESSENTIAL, params, mask.needed());
     Ptr<usac::RansacOutput> ransac_output;
-    if (usac::run(model, points1, points2, model->getRandomGeneratorState(),
+    if (usac::run(model, points1, points2,
             ransac_output, cameraMatrix1, cameraMatrix2, dist_coeff1, dist_coeff2)) {
         usac::saveMask(mask, ransac_output->getInliersMask());
         return ransac_output->getModel();
 
@@ -451,9 +451,9 @@ cv::Mat cv::findHomography( InputArray _points1, InputArray _points2,
 cv::Mat cv::findHomography(InputArray srcPoints, InputArray dstPoints, OutputArray mask,
                    const UsacParams &params) {
     Ptr<usac::Model> model;
-    usac::setParameters(model, usac::EstimationMethod::Homography, params, mask.needed());
+    usac::setParameters(model, usac::EstimationMethod::HOMOGRAPHY, params, mask.needed());
     Ptr<usac::RansacOutput> ransac_output;
-    if (usac::run(model, srcPoints, dstPoints, model->getRandomGeneratorState(),
+    if (usac::run(model, srcPoints, dstPoints,
             ransac_output, noArray(), noArray(), noArray(), noArray())) {
         usac::saveMask(mask, ransac_output->getInliersMask());
         return ransac_output->getModel() / ransac_output->getModel().at<double>(2,2);
@@ -913,10 +913,10 @@ cv::Mat cv::findFundamentalMat( cv::InputArray points1, cv::InputArray points2,
 cv::Mat cv::findFundamentalMat( InputArray points1, InputArray points2,
                         OutputArray mask, const UsacParams &params) {
     Ptr<usac::Model> model;
-    setParameters(model, usac::EstimationMethod::Fundamental, params, mask.needed());
+    setParameters(model, usac::EstimationMethod::FUNDAMENTAL, params, mask.needed());
     CV_Assert(model);
     Ptr<usac::RansacOutput> ransac_output;
-    if (usac::run(model, points1, points2, model->getRandomGeneratorState(),
+    if (usac::run(model, points1, points2,
             ransac_output, noArray(), noArray(), noArray(), noArray())) {
         usac::saveMask(mask, ransac_output->getInliersMask());
         return ransac_output->getModel();
 
@@ -1086,9 +1086,9 @@ Mat estimateAffine2D(InputArray _from, InputArray _to, OutputArray _inliers,
 Mat estimateAffine2D(InputArray _from, InputArray _to, OutputArray inliers,
                      const UsacParams &params) {
     Ptr<usac::Model> model;
-    usac::setParameters(model, usac::EstimationMethod::Affine, params, inliers.needed());
+    usac::setParameters(model, usac::EstimationMethod::AFFINE, params, inliers.needed());
     Ptr<usac::RansacOutput> ransac_output;
-    if (usac::run(model, _from, _to, model->getRandomGeneratorState(),
+    if (usac::run(model, _from, _to,
             ransac_output, noArray(), noArray(), noArray(), noArray())) {
         usac::saveMask(inliers, ransac_output->getInliersMask());
         return ransac_output->getModel().rowRange(0,2);
 
@@ -199,21 +199,6 @@ class PnPRansacCallback CV_FINAL : public PointSetRegistrator::Callback
     Mat tvec;
 };
 
-UsacParams::UsacParams()
-{
-    confidence = 0.99;
-    isParallel = false;
-    loIterations = 5;
-    loMethod = LocalOptimMethod::LOCAL_OPTIM_INNER_LO;
-    loSampleSize = 14;
-    maxIterations = 5000;
-    neighborsSearch = NeighborSearchMethod::NEIGH_GRID;
-    randomGeneratorState = 0;
-    sampler = SamplingMethod::SAMPLING_UNIFORM;
-    score = ScoreMethod::SCORE_METHOD_MSAC;
-    threshold = 1.5;
-}
-
 bool solvePnPRansac(InputArray _opoints, InputArray _ipoints,
                     InputArray _cameraMatrix, InputArray _distCoeffs,
                     OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
@@ -407,7 +392,7 @@ bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
     usac::setParameters(model_params, cameraMatrix.empty() ? usac::EstimationMethod::P6P :
         usac::EstimationMethod::P3P, params, inliers.needed());
     Ptr<usac::RansacOutput> ransac_output;
-    if (usac::run(model_params, imagePoints, objectPoints, model_params->getRandomGeneratorState(),
+    if (usac::run(model_params, imagePoints, objectPoints,
             ransac_output, cameraMatrix, noArray(), distCoeffs, noArray())) {
         if (inliers.needed()) {
             const auto &inliers_mask = ransac_output->getInliersMask();