Merge branch '4.x' into remap_relative

Author: chacha21

.github/workflows/PR-4.x.yaml

@@ -15,6 +15,9 @@ jobs:
   Ubuntu2204-x64:
     uses: opencv/ci-gha-workflow/.github/workflows/OCV-Contrib-PR-4.x-U22.yaml@main
 
+  Ubuntu2404-x64:
+    uses: opencv/ci-gha-workflow/.github/workflows/OCV-Contrib-PR-4.x-U24.yaml@main
+
   Ubuntu2004-x64-CUDA:
     uses: opencv/ci-gha-workflow/.github/workflows/OCV-Contrib-PR-4.x-U20-Cuda.yaml@main
 

modules/alphamat/README.md

@@ -1,9 +1,14 @@
 # Computer Vision based Alpha Matting
 
+![Trimap Alphamat Example from Askoy et al 2017](https://github.com/opencv/opencv_contrib/assets/810997/5cafae51-18e1-4e75-9035-6b40c9a064cb)
+
+
+
 This project was part of the Google Summer of Code 2019.
 
-####Student: Muskaan Kularia
-####Mentor: Sunita Nayak
+#### Student: Muskaan Kularia
+#### Mentor: Sunita Nayak
+
 ***
 Alphamatting is the problem of extracting the foreground from an image. Given the input of an image and its corresponding trimap, we try to extract the foreground from the background.
 
@@ -20,4 +25,4 @@ This project is implementation of "[Designing Effective Inter-Pixel Information
 
 [4] Qifeng Chen, Dingzeyu Li, Chi-Keung Tang, "[KNN Matting](http://dingzeyu.li/files/knn-matting-tpami.pdf)", IEEE TPAMI, 2013.
 
-[5] Yagiz Aksoy, "[Affinity Based Matting Toolbox](https://github.com/yaksoy/AffinityBasedMattingToolbox)".
+[5] Yagiz Aksoy, "[Affinity Based Matting Toolbox](https://github.com/yaksoy/AffinityBasedMattingToolbox)".

modules/aruco/CMakeLists.txt

@@ -1,31 +1,2 @@
 set(the_description "ArUco Marker Detection")
 ocv_define_module(aruco opencv_core opencv_imgproc opencv_calib3d opencv_objdetect WRAP python java objc js)
-ocv_include_directories(${CMAKE_CURRENT_BINARY_DIR})
-
-ocv_add_testdata(samples/ contrib/aruco
-    FILES_MATCHING PATTERN "*yml"
-)
-
-ocv_add_testdata(tutorials/aruco_detection/images/ contrib/aruco
-    FILES_MATCHING PATTERN "singlemarkersoriginal.jpg"
-)
-
-ocv_add_testdata(tutorials/aruco_board_detection/images/ contrib/aruco
-    FILES_MATCHING PATTERN "gboriginal.png"
-)
-
-ocv_add_testdata(tutorials/charuco_detection/images/ contrib/aruco
-    FILES_MATCHING PATTERN "choriginal.jpg"
-)
-
-ocv_add_testdata(tutorials/charuco_detection/images/ contrib/aruco
-    FILES_MATCHING PATTERN "chocclusion_original.jpg"
-)
-
-ocv_add_testdata(tutorials/charuco_diamond_detection/images/ contrib/aruco
-    FILES_MATCHING PATTERN "diamondmarkers.png"
-)
-
-ocv_add_testdata(tutorials/aruco_calibration/images/ contrib/aruco
-    FILES_MATCHING REGEX "img_[0-9]+.jpg"
-)

modules/aruco/README.md

@@ -3,10 +3,15 @@ ArUco Marker Detection
 
 **ArUco**
 
+![markers](https://github.com/opencv/opencv_contrib/assets/810997/8d587456-f27f-49e4-9540-28a0477d43fc)
+
 ArUco markers are easy to detect pattern grids that yield up to 1024 different patterns. They were built for augmented reality and later used for camera calibration. Since the grid uniquely orients the square, the detection algorithm can determing the pose of the grid.
 
 **ChArUco**
 
+![screen_charuco](https://github.com/opencv/opencv_contrib/assets/810997/64610da1-ee06-406c-a19b-006b02ac44fd)
+
+
 ArUco markers were improved by interspersing them inside a checkerboard called ChArUco. Checkerboard corner intersections provide more stable corners because the edge location bias on one square is countered by the opposite edge orientation in the connecting square. By interspersing ArUco markers inside the checkerboard, each checkerboard corner gets a label which enables it to be used in complex calibration or pose scenarios where you cannot see all the corners of the checkerboard.
 
-The smallest ChArUco board is 5 checkers and 4 markers called a "Diamond Marker".
+The smallest ChArUco board is 5 checkers and 4 markers called a "Diamond Marker".

modules/aruco/include/opencv2/aruco.hpp

@@ -52,7 +52,7 @@ CV_EXPORTS_W void getBoardObjectAndImagePoints(const Ptr<Board> &board, InputArr
                                                InputArray detectedIds, OutputArray objPoints, OutputArray imgPoints);
 
 
-/** @deprecated Use cv::solvePnP
+/** @deprecated Use Board::matchImagePoints and cv::solvePnP
  */
 CV_EXPORTS_W int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, const Ptr<Board> &board,
                                    InputArray cameraMatrix, InputArray distCoeffs, InputOutputArray rvec,
@@ -75,6 +75,7 @@ CV_EXPORTS_W int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, c
  * This function estimates a Charuco board pose from some detected corners.
  * The function checks if the input corners are enough and valid to perform pose estimation.
  * If pose estimation is valid, returns true, else returns false.
+ * @deprecated Use CharucoBoard::matchImagePoints and cv::solvePnP
  * @sa use cv::drawFrameAxes to get world coordinate system axis for object points
  */
 CV_EXPORTS_W bool estimatePoseCharucoBoard(InputArray charucoCorners, InputArray charucoIds,

modules/aruco/include/opencv2/aruco/aruco_calib.hpp

@@ -16,17 +16,17 @@ namespace aruco {
  * PatternPositionType defines center this system and axes direction.
  * Axis X (red color) - first coordinate, axis Y (green color) - second coordinate,
  * axis Z (blue color) - third coordinate.
- * @sa estimatePoseSingleMarkers(), check tutorial_aruco_detection in aruco contrib
+ *
+ * @deprecated Use Board::matchImagePoints and cv::solvePnP
+ *
+ * @sa estimatePoseSingleMarkers()
  */
 enum PatternPositionType {
     /** @brief The marker coordinate system is centered on the middle of the marker.
      *
      * The coordinates of the four corners (CCW order) of the marker in its own coordinate system are:
      * (-markerLength/2, markerLength/2, 0), (markerLength/2, markerLength/2, 0),
      * (markerLength/2, -markerLength/2, 0), (-markerLength/2, -markerLength/2, 0).
-     *
-     * These pattern points define this coordinate system:
-     * ![Image with axes drawn](tutorials/images/singlemarkersaxes2.jpg)
      */
     ARUCO_CCW_CENTER,
     /** @brief The marker coordinate system is centered on the top-left corner of the marker.
@@ -35,9 +35,6 @@ enum PatternPositionType {
      * (0, 0, 0), (markerLength, 0, 0),
      * (markerLength, markerLength, 0), (0, markerLength, 0).
      *
-     * These pattern points define this coordinate system:
-     * ![Image with axes drawn](tutorials/images/singlemarkersaxes.jpg)
-     *
      * These pattern dots are convenient to use with a chessboard/ChArUco board.
      */
     ARUCO_CW_TOP_LEFT_CORNER
@@ -50,7 +47,10 @@ enum PatternPositionType {
  * rvec and tvec values as initial approximations of the rotation and translation vectors, respectively, and further
  * optimizes them (default false).
  * @param solvePnPMethod Method for solving a PnP problem: see @ref calib3d_solvePnP_flags (default SOLVEPNP_ITERATIVE).
- * @sa PatternPositionType, solvePnP(), check tutorial_aruco_detection in aruco contrib
+ *
+ * @deprecated Use Board::matchImagePoints and cv::solvePnP
+ *
+ * @sa PatternPositionType, solvePnP()
  */
 struct CV_EXPORTS_W_SIMPLE EstimateParameters {
     CV_PROP_RW PatternPositionType pattern;
@@ -95,6 +95,8 @@ struct CV_EXPORTS_W_SIMPLE EstimateParameters {
  * This function calibrates a camera using an Aruco Board. The function receives a list of
  * detected markers from several views of the Board. The process is similar to the chessboard
  * calibration in calibrateCamera(). The function returns the final re-projection error.
+ *
+ * @deprecated Use Board::matchImagePoints and cv::solvePnP
  */
 CV_EXPORTS_AS(calibrateCameraArucoExtended)
 double calibrateCameraAruco(InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr<Board> &board,
@@ -105,6 +107,7 @@ double calibrateCameraAruco(InputArrayOfArrays corners, InputArray ids, InputArr
 
 /** @overload
  * @brief It's the same function as #calibrateCameraAruco but without calibration error estimation.
+ * @deprecated Use Board::matchImagePoints and cv::solvePnP
  */
 CV_EXPORTS_W double calibrateCameraAruco(InputArrayOfArrays corners, InputArray ids, InputArray counter,
                                          const Ptr<Board> &board, Size imageSize, InputOutputArray cameraMatrix,
@@ -147,6 +150,8 @@ CV_EXPORTS_W double calibrateCameraAruco(InputArrayOfArrays corners, InputArray
  * This function calibrates a camera using a set of corners of a  Charuco Board. The function
  * receives a list of detected corners and its identifiers from several views of the Board.
  * The function returns the final re-projection error.
+ *
+ * @deprecated Use CharucoBoard::matchImagePoints and cv::solvePnP
  */
 CV_EXPORTS_AS(calibrateCameraCharucoExtended)
 double calibrateCameraCharuco(InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds,
@@ -158,6 +163,8 @@ double calibrateCameraCharuco(InputArrayOfArrays charucoCorners, InputArrayOfArr
 
 /**
  * @brief It's the same function as #calibrateCameraCharuco but without calibration error estimation.
+ *
+ * @deprecated Use CharucoBoard::matchImagePoints and cv::solvePnP
  */
 CV_EXPORTS_W double calibrateCameraCharuco(InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds,
                                            const Ptr<CharucoBoard> &board, Size imageSize,

modules/aruco/include/opencv2/aruco/charuco.hpp

@@ -96,6 +96,8 @@ CV_EXPORTS_W void detectCharucoDiamond(InputArray image, InputArrayOfArrays mark
  * @param borderBits width of the marker borders.
  *
  * This function return the image of a ChArUco marker, ready to be printed.
+ *
+ * @deprecated Use CharucoBoard::generateImage()
  */
 CV_EXPORTS_W void drawCharucoDiamond(const Ptr<Dictionary> &dictionary, Vec4i ids, int squareLength,
                                      int markerLength, OutputArray img, int marginSize = 0,