diff --git a/.gitattributes b/.gitattributes index b27c18f8..401887ac 100644 --- a/.gitattributes +++ b/.gitattributes @@ -3,3 +3,4 @@ roslib.js linguist-vendored eventemitter2.js linguist-vendored ros3d.js linguist-vendored three.min.js linguist-vendored +aruco_pose/vendor/* linguist-vendored diff --git a/.markdownlint.json b/.markdownlint.json index e005271f..73ae30ee 100644 --- a/.markdownlint.json +++ b/.markdownlint.json @@ -20,6 +20,7 @@ "MAVLink", "ROS", "ROS Kinetic", + "ROS Melodic", "OpenCV", "Gazebo", "GitHub", diff --git a/.travis.yml b/.travis.yml index 18db1ee2..7b2bcd31 100644 --- a/.travis.yml +++ b/.travis.yml @@ -50,6 +50,22 @@ jobs: tags: true draft: true name: ${TRAVIS_TAG} + - stage: Build + name: "Native Kinetic build" + env: + - NATIVE_DOCKER=ros:kinetic-ros-base + before_script: + - docker pull ${NATIVE_DOCKER} + script: + - docker run --rm -v $(pwd):/root/catkin_ws/src/clever ${NATIVE_DOCKER} /root/catkin_ws/src/clever/builder/standalone-install.sh + - stage: Build + name: "Native Melodic build" + env: + - NATIVE_DOCKER=ros:melodic-ros-base + before_script: + - docker pull ${NATIVE_DOCKER} + script: + - docker run --rm -v $(pwd):/root/catkin_ws/src/clever ${NATIVE_DOCKER} /root/catkin_ws/src/clever/builder/standalone-install.sh - stage: Build name: "Documentation" language: node_js @@ -93,7 +109,7 @@ jobs: - wget https://github.com/okalachev/editorconfig-checker/releases/download/1.2.1-disable-spaces-amount/ec-linux-amd64 - chmod +x ec-linux-amd64 script: - - ./ec-linux-amd64 -spaces-after-tabs -e "roslib.js|ros3d.js|eventemitter2.js|draw.cpp|BinUtils.swift|\.idea|apps/android/app|Assets.xcassets|test_parser_pass.txt|test_node_failure.txt|\.stl|\.dxf" + - ./ec-linux-amd64 -spaces-after-tabs -e "roslib.js|ros3d.js|eventemitter2.js|draw.cpp|BinUtils.swift|\.idea|apps/android/app|Assets.xcassets|test_parser_pass.txt|test_node_failure.txt|aruco_pose/vendor|\.stl|\.dxf" stages: - Build - Annotate diff --git a/README.md b/README.md index 70e49855..3d2cdd7d 100644 --- a/README.md +++ b/README.md @@ -18,8 +18,8 @@ Use it to learn how to assemble, configure, pilot and program autonomous CLEVER Image includes: -* Raspbian Stretch -* ROS Kinetic +* Raspbian Buster +* ROS Melodic * Configured networking * OpenCV * mavros @@ -30,7 +30,7 @@ API description (in Russian) for autonomous flights is available [on GitBook](ht ## Manual installation -Install ROS Kinetic according to the [documentation](http://wiki.ros.org/kinetic/Installation), then [create a Catkin workspace](http://wiki.ros.org/catkin/Tutorials/create_a_workspace). +Install ROS Melodic according to the [documentation](http://wiki.ros.org/melodic/Installation), then [create a Catkin workspace](http://wiki.ros.org/catkin/Tutorials/create_a_workspace). Clone this repo to directory `~/catkin_ws/src/clever`: diff --git a/aruco_pose/CMakeLists.txt b/aruco_pose/CMakeLists.txt index 1644710d..30061a9b 100644 --- a/aruco_pose/CMakeLists.txt +++ b/aruco_pose/CMakeLists.txt @@ -1,4 +1,4 @@ -cmake_minimum_required(VERSION 2.8.3) +cmake_minimum_required(VERSION 3.0) project(aruco_pose) add_definitions(-std=c++11 -Wall -g) @@ -23,7 +23,16 @@ find_package(catkin REQUIRED COMPONENTS message_generation ) -find_package(OpenCV 3 REQUIRED) +find_package(OpenCV 3 REQUIRED COMPONENTS core imgproc calib3d) +if ("${OpenCV_VERSION_MINOR}" LESS "3") + message(STATUS "OpenCV version too low, using vendored ArUco package") + include(vendor/VendorOpenCV.cmake) +else() + message(STATUS "Using system OpenCV ArUco package") + find_package(OpenCV 3 REQUIRED COMPONENTS aruco) +endif() +message(STATUS "OpenCV include dirs: ${OpenCV_INCLUDE_DIRS}") +message(STATUS "OpenCV libraries: ${OpenCV_LIBRARIES}") ## System dependencies are found with CMake's conventions # find_package(Boost REQUIRED COMPONENTS system) diff --git a/aruco_pose/package.xml b/aruco_pose/package.xml index 3d0fb50a..f028a81a 100644 --- a/aruco_pose/package.xml +++ b/aruco_pose/package.xml @@ -18,7 +18,8 @@ tf2 tf2_ros tf2_geometry_msgs - opencv3 + + cv_bridge image_transport message_generation diff --git a/aruco_pose/vendor/VendorOpenCV.cmake b/aruco_pose/vendor/VendorOpenCV.cmake new file mode 100644 index 00000000..fc0bac5f --- /dev/null +++ b/aruco_pose/vendor/VendorOpenCV.cmake @@ -0,0 +1,33 @@ +# There should be a better way to add ArUco libraries, +# but I have not found it yet. +# -- sfalexrog, 2019.09.11 +if (NOT OpenCV_LIBRARIES OR NOT OpenCV_INCLUDE_DIRS) + message(FATAL_ERROR "OpenCV was not found - cannot continue") +endif() + +message(STATUS "Adding vendored aruco_pose OpenCV module") +add_library(_opencv_aruco STATIC + vendor/aruco/src/aruco.cpp + vendor/aruco/src/charuco.cpp + vendor/aruco/src/dictionary.cpp + vendor/aruco/src/zmaxheap.cpp + ) + +target_include_directories(_opencv_aruco PRIVATE + ${OpenCV_INCLUDE_DIRS} +) +target_link_libraries(_opencv_aruco PRIVATE + ${OpenCV_LIBRARIES} +) +target_compile_definitions(_opencv_aruco PRIVATE + CV_OVERRIDE=override +) +target_compile_options(_opencv_aruco PRIVATE + -fpic -fPIC +) + +target_include_directories(_opencv_aruco PUBLIC + vendor/aruco/include +) + +set(OpenCV_LIBRARIES "_opencv_aruco;${OpenCV_LIBRARIES}") diff --git a/aruco_pose/vendor/aruco/CMakeLists.txt b/aruco_pose/vendor/aruco/CMakeLists.txt new file mode 100644 index 00000000..568a10a1 --- /dev/null +++ b/aruco_pose/vendor/aruco/CMakeLists.txt @@ -0,0 +1,2 @@ +set(the_description "ArUco Marker Detection") +ocv_define_module(aruco opencv_core opencv_imgproc opencv_calib3d WRAP python java) diff --git a/aruco_pose/vendor/aruco/README.md b/aruco_pose/vendor/aruco/README.md new file mode 100644 index 00000000..d40ae78f --- /dev/null +++ b/aruco_pose/vendor/aruco/README.md @@ -0,0 +1,12 @@ +ArUco Marker Detection +====================== + +**ArUco** + +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** + +ArUco markers were improved by interspersing them inside a checkerboard called ChArUco. Checkerboard corner intersectionsa 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". diff --git a/aruco_pose/vendor/aruco/include/opencv2/aruco.hpp b/aruco_pose/vendor/aruco/include/opencv2/aruco.hpp new file mode 100644 index 00000000..56bfe982 --- /dev/null +++ b/aruco_pose/vendor/aruco/include/opencv2/aruco.hpp @@ -0,0 +1,604 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#ifndef __OPENCV_ARUCO_HPP__ +#define __OPENCV_ARUCO_HPP__ + +#include +#include +#include "opencv2/aruco/dictionary.hpp" + +/** + * @defgroup aruco ArUco Marker Detection + * This module is dedicated to square fiducial markers (also known as Augmented Reality Markers) + * These markers are useful for easy, fast and robust camera pose estimation.ç + * + * The main functionalities are: + * - Detection of markers in an image + * - Pose estimation from a single marker or from a board/set of markers + * - Detection of ChArUco board for high subpixel accuracy + * - Camera calibration from both, ArUco boards and ChArUco boards. + * - Detection of ChArUco diamond markers + * The samples directory includes easy examples of how to use the module. + * + * 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 S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez. 2014. + * "Automatic generation and detection of highly reliable fiducial markers under occlusion". + * Pattern Recogn. 47, 6 (June 2014), 2280-2292. DOI=10.1016/j.patcog.2014.01.005 + * + * @sa http://www.uco.es/investiga/grupos/ava/node/26 + * + * This module has been originally developed by Sergio Garrido-Jurado as a project + * for Google Summer of Code 2015 (GSoC 15). + * + * +*/ + +namespace cv { +namespace aruco { + +//! @addtogroup aruco +//! @{ + +enum CornerRefineMethod{ + CORNER_REFINE_NONE, ///< Tag and corners detection based on the ArUco approach + CORNER_REFINE_SUBPIX, ///< ArUco approach and refine the corners locations using corner subpixel accuracy + CORNER_REFINE_CONTOUR, ///< ArUco approach and refine the corners locations using the contour-points line fitting + CORNER_REFINE_APRILTAG, ///< Tag and corners detection based on the AprilTag 2 approach @cite wang2016iros +}; + +/** + * @brief Parameters for the detectMarker process: + * - adaptiveThreshWinSizeMin: minimum window size for adaptive thresholding before finding + * contours (default 3). + * - adaptiveThreshWinSizeMax: maximum window size for adaptive thresholding before finding + * contours (default 23). + * - adaptiveThreshWinSizeStep: increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax + * during the thresholding (default 10). + * - adaptiveThreshConstant: constant for adaptive thresholding before finding contours (default 7) + * - minMarkerPerimeterRate: determine minimum perimeter for marker contour to be detected. This + * is defined as a rate respect to the maximum dimension of the input image (default 0.03). + * - maxMarkerPerimeterRate: determine maximum perimeter for marker contour to be detected. This + * is defined as a rate respect to the maximum dimension of the input image (default 4.0). + * - polygonalApproxAccuracyRate: minimum accuracy during the polygonal approximation process to + * determine which contours are squares. + * - minCornerDistanceRate: minimum distance between corners for detected markers relative to its + * perimeter (default 0.05) + * - minDistanceToBorder: minimum distance of any corner to the image border for detected markers + * (in pixels) (default 3) + * - minMarkerDistanceRate: minimum mean distance beetween two marker corners to be considered + * similar, so that the smaller one is removed. The rate is relative to the smaller perimeter + * of the two markers (default 0.05). + * - cornerRefinementMethod: corner refinement method. (CORNER_REFINE_NONE, no refinement. + * CORNER_REFINE_SUBPIX, do subpixel refinement. CORNER_REFINE_CONTOUR use contour-Points, + * CORNER_REFINE_APRILTAG use the AprilTag2 approach) + * - cornerRefinementWinSize: window size for the corner refinement process (in pixels) (default 5). + * - cornerRefinementMaxIterations: maximum number of iterations for stop criteria of the corner + * refinement process (default 30). + * - cornerRefinementMinAccuracy: minimum error for the stop cristeria of the corner refinement + * process (default: 0.1) + * - markerBorderBits: number of bits of the marker border, i.e. marker border width (default 1). + * - perspectiveRemovePixelPerCell: number of bits (per dimension) for each cell of the marker + * when removing the perspective (default 8). + * - perspectiveRemoveIgnoredMarginPerCell: width of the margin of pixels on each cell not + * considered for the determination of the cell bit. Represents the rate respect to the total + * size of the cell, i.e. perspectiveRemovePixelPerCell (default 0.13) + * - maxErroneousBitsInBorderRate: maximum number of accepted erroneous bits in the border (i.e. + * number of allowed white bits in the border). Represented as a rate respect to the total + * number of bits per marker (default 0.35). + * - minOtsuStdDev: minimun standard deviation in pixels values during the decodification step to + * apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher + * than 128 or not) (default 5.0) + * - errorCorrectionRate error correction rate respect to the maximun error correction capability + * for each dictionary. (default 0.6). + * - aprilTagMinClusterPixels: reject quads containing too few pixels. + * - aprilTagMaxNmaxima: how many corner candidates to consider when segmenting a group of pixels into a quad. + * - aprilTagCriticalRad: Reject quads where pairs of edges have angles that are close to straight or close to + * 180 degrees. Zero means that no quads are rejected. (In radians). + * - aprilTagMaxLineFitMse: When fitting lines to the contours, what is the maximum mean squared error + * allowed? This is useful in rejecting contours that are far from being quad shaped; rejecting + * these quads "early" saves expensive decoding processing. + * - aprilTagMinWhiteBlackDiff: When we build our model of black & white pixels, we add an extra check that + * the white model must be (overall) brighter than the black model. How much brighter? (in pixel values, [0,255]). + * - aprilTagDeglitch: should the thresholded image be deglitched? Only useful for very noisy images + * - aprilTagQuadDecimate: Detection of quads can be done on a lower-resolution image, improving speed at a + * cost of pose accuracy and a slight decrease in detection rate. Decoding the binary payload is still + * done at full resolution. + * - aprilTagQuadSigma: What Gaussian blur should be applied to the segmented image (used for quad detection?) + * Parameter is the standard deviation in pixels. Very noisy images benefit from non-zero values (e.g. 0.8). + * - detectInvertedMarker: to check if there is a white marker. In order to generate a "white" marker just + * invert a normal marker by using a tilde, ~markerImage. (default false) + */ +struct CV_EXPORTS_W DetectorParameters { + + DetectorParameters(); + + CV_WRAP static Ptr create(); + + CV_PROP_RW int adaptiveThreshWinSizeMin; + CV_PROP_RW int adaptiveThreshWinSizeMax; + CV_PROP_RW int adaptiveThreshWinSizeStep; + CV_PROP_RW double adaptiveThreshConstant; + CV_PROP_RW double minMarkerPerimeterRate; + CV_PROP_RW double maxMarkerPerimeterRate; + CV_PROP_RW double polygonalApproxAccuracyRate; + CV_PROP_RW double minCornerDistanceRate; + CV_PROP_RW int minDistanceToBorder; + CV_PROP_RW double minMarkerDistanceRate; + CV_PROP_RW int cornerRefinementMethod; + CV_PROP_RW int cornerRefinementWinSize; + CV_PROP_RW int cornerRefinementMaxIterations; + CV_PROP_RW double cornerRefinementMinAccuracy; + CV_PROP_RW int markerBorderBits; + CV_PROP_RW int perspectiveRemovePixelPerCell; + CV_PROP_RW double perspectiveRemoveIgnoredMarginPerCell; + CV_PROP_RW double maxErroneousBitsInBorderRate; + CV_PROP_RW double minOtsuStdDev; + CV_PROP_RW double errorCorrectionRate; + + // April :: User-configurable parameters. + CV_PROP_RW float aprilTagQuadDecimate; + CV_PROP_RW float aprilTagQuadSigma; + + // April :: Internal variables + CV_PROP_RW int aprilTagMinClusterPixels; + CV_PROP_RW int aprilTagMaxNmaxima; + CV_PROP_RW float aprilTagCriticalRad; + CV_PROP_RW float aprilTagMaxLineFitMse; + CV_PROP_RW int aprilTagMinWhiteBlackDiff; + CV_PROP_RW int aprilTagDeglitch; + + // to detect white (inverted) markers + CV_PROP_RW bool detectInvertedMarker; +}; + + + +/** + * @brief Basic marker detection + * + * @param image input image + * @param dictionary indicates the type of markers that will be searched + * @param corners vector of detected marker corners. For each marker, its four corners + * are provided, (e.g std::vector > ). For N detected markers, + * the dimensions of this array is Nx4. The order of the corners is clockwise. + * @param ids vector of identifiers of the detected markers. The identifier is of type int + * (e.g. std::vector). For N detected markers, the size of ids is also N. + * The identifiers have the same order than the markers in the imgPoints array. + * @param parameters marker detection parameters + * @param rejectedImgPoints contains the imgPoints of those squares whose inner code has not a + * correct codification. Useful for debugging purposes. + * @param cameraMatrix optional input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeff optional vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * + * Performs marker detection in the input image. Only markers included in the specific dictionary + * are searched. For each detected marker, it returns the 2D position of its corner in the image + * and its corresponding identifier. + * Note that this function does not perform pose estimation. + * @sa estimatePoseSingleMarkers, estimatePoseBoard + * + */ +CV_EXPORTS_W void detectMarkers(InputArray image, const Ptr &dictionary, OutputArrayOfArrays corners, + OutputArray ids, const Ptr ¶meters = DetectorParameters::create(), + OutputArrayOfArrays rejectedImgPoints = noArray(), InputArray cameraMatrix= noArray(), InputArray distCoeff= noArray()); + + + +/** + * @brief Pose estimation for single markers + * + * @param corners vector of already detected markers corners. For each marker, its four corners + * are provided, (e.g std::vector > ). For N detected markers, + * the dimensions of this array should be Nx4. The order of the corners should be clockwise. + * @sa detectMarkers + * @param markerLength the length of the markers' side. The returning translation vectors will + * be in the same unit. Normally, unit is meters. + * @param cameraMatrix input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvecs array of output rotation vectors (@sa Rodrigues) (e.g. std::vector). + * Each element in rvecs corresponds to the specific marker in imgPoints. + * @param tvecs array of output translation vectors (e.g. std::vector). + * Each element in tvecs corresponds to the specific marker in imgPoints. + * @param _objPoints array of object points of all the marker corners + * + * This function receives the detected markers and returns their pose estimation respect to + * the camera individually. So for each marker, one rotation and translation vector is returned. + * The returned transformation is the one that transforms points from each marker coordinate system + * to the camera coordinate system. + * The marker corrdinate system is centered on the middle of the marker, with the Z axis + * perpendicular to the marker plane. + * The coordinates of the four corners 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) + */ +CV_EXPORTS_W void estimatePoseSingleMarkers(InputArrayOfArrays corners, float markerLength, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArray rvecs, OutputArray tvecs, OutputArray _objPoints = noArray()); + + + +/** + * @brief Board of markers + * + * A board is a set of markers in the 3D space with a common coordinate system. + * The common form of a board of marker is a planar (2D) board, however any 3D layout can be used. + * A Board object is composed by: + * - The object points of the marker corners, i.e. their coordinates respect to the board system. + * - The dictionary which indicates the type of markers of the board + * - The identifier of all the markers in the board. + */ +class CV_EXPORTS_W Board { + + public: + /** + * @brief Provide way to create Board by passing necessary data. Specially needed in Python. + * + * @param objPoints array of object points of all the marker corners in the board + * @param dictionary the dictionary of markers employed for this board + * @param ids vector of the identifiers of the markers in the board + * + */ + CV_WRAP static Ptr create(InputArrayOfArrays objPoints, const Ptr &dictionary, InputArray ids); + /// array of object points of all the marker corners in the board + /// each marker include its 4 corners in CCW order. For M markers, the size is Mx4. + CV_PROP std::vector< std::vector< Point3f > > objPoints; + + /// the dictionary of markers employed for this board + CV_PROP Ptr dictionary; + + /// vector of the identifiers of the markers in the board (same size than objPoints) + /// The identifiers refers to the board dictionary + CV_PROP std::vector< int > ids; +}; + + + +/** + * @brief Planar board with grid arrangement of markers + * More common type of board. All markers are placed in the same plane in a grid arrangement. + * The board can be drawn using drawPlanarBoard() function (@sa drawPlanarBoard) + */ +class CV_EXPORTS_W GridBoard : public Board { + + public: + /** + * @brief Draw a GridBoard + * + * @param outSize size of the output image in pixels. + * @param img output image with the board. The size of this image will be outSize + * and the board will be on the center, keeping the board proportions. + * @param marginSize minimum margins (in pixels) of the board in the output image + * @param borderBits width of the marker borders. + * + * This function return the image of the GridBoard, ready to be printed. + */ + CV_WRAP void draw(Size outSize, OutputArray img, int marginSize = 0, int borderBits = 1); + + + /** + * @brief Create a GridBoard object + * + * @param markersX number of markers in X direction + * @param markersY number of markers in Y direction + * @param markerLength marker side length (normally in meters) + * @param markerSeparation separation between two markers (same unit as markerLength) + * @param dictionary dictionary of markers indicating the type of markers + * @param firstMarker id of first marker in dictionary to use on board. + * @return the output GridBoard object + * + * This functions creates a GridBoard object given the number of markers in each direction and + * the marker size and marker separation. + */ + CV_WRAP static Ptr create(int markersX, int markersY, float markerLength, + float markerSeparation, const Ptr &dictionary, int firstMarker = 0); + + /** + * + */ + CV_WRAP Size getGridSize() const { return Size(_markersX, _markersY); } + + /** + * + */ + CV_WRAP float getMarkerLength() const { return _markerLength; } + + /** + * + */ + CV_WRAP float getMarkerSeparation() const { return _markerSeparation; } + + + private: + // number of markers in X and Y directions + int _markersX, _markersY; + + // marker side lenght (normally in meters) + float _markerLength; + + // separation between markers in the grid + float _markerSeparation; +}; + + + +/** + * @brief Pose estimation for a board of markers + * + * @param corners vector of already detected markers corners. For each marker, its four corners + * are provided, (e.g std::vector > ). For N detected markers, the + * dimensions of this array should be Nx4. The order of the corners should be clockwise. + * @param ids list of identifiers for each marker in corners + * @param board layout of markers in the board. The layout is composed by the marker identifiers + * and the positions of each marker corner in the board reference system. + * @param cameraMatrix input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvec Output vector (e.g. cv::Mat) corresponding to the rotation vector of the board + * (see cv::Rodrigues). Used as initial guess if not empty. + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * @param useExtrinsicGuess defines whether initial guess for \b rvec and \b tvec will be used or not. + * Used as initial guess if not empty. + * + * This function receives the detected markers and returns the pose of a marker board composed + * by those markers. + * A Board of marker has a single world coordinate system which is defined by the board layout. + * The returned transformation is the one that transforms points from the board coordinate system + * to the camera coordinate system. + * Input markers that are not included in the board layout are ignored. + * The function returns the number of markers from the input employed for the board pose estimation. + * Note that returning a 0 means the pose has not been estimated. + */ +CV_EXPORTS_W int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, const Ptr &board, + InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, + OutputArray tvec, bool useExtrinsicGuess = false); + + + + +/** + * @brief Refind not detected markers based on the already detected and the board layout + * + * @param image input image + * @param board layout of markers in the board. + * @param detectedCorners vector of already detected marker corners. + * @param detectedIds vector of already detected marker identifiers. + * @param rejectedCorners vector of rejected candidates during the marker detection process. + * @param cameraMatrix optional input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs optional vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param minRepDistance minimum distance between the corners of the rejected candidate and the + * reprojected marker in order to consider it as a correspondence. + * @param errorCorrectionRate rate of allowed erroneous bits respect to the error correction + * capability of the used dictionary. -1 ignores the error correction step. + * @param checkAllOrders Consider the four posible corner orders in the rejectedCorners array. + * If it set to false, only the provided corner order is considered (default true). + * @param recoveredIdxs Optional array to returns the indexes of the recovered candidates in the + * original rejectedCorners array. + * @param parameters marker detection parameters + * + * This function tries to find markers that were not detected in the basic detecMarkers function. + * First, based on the current detected marker and the board layout, the function interpolates + * the position of the missing markers. Then it tries to find correspondence between the reprojected + * markers and the rejected candidates based on the minRepDistance and errorCorrectionRate + * parameters. + * If camera parameters and distortion coefficients are provided, missing markers are reprojected + * using projectPoint function. If not, missing marker projections are interpolated using global + * homography, and all the marker corners in the board must have the same Z coordinate. + */ +CV_EXPORTS_W void refineDetectedMarkers( + InputArray image,const Ptr &board, InputOutputArrayOfArrays detectedCorners, + InputOutputArray detectedIds, InputOutputArrayOfArrays rejectedCorners, + InputArray cameraMatrix = noArray(), InputArray distCoeffs = noArray(), + float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true, + OutputArray recoveredIdxs = noArray(), const Ptr ¶meters = DetectorParameters::create()); + + + +/** + * @brief Draw detected markers in image + * + * @param image input/output image. It must have 1 or 3 channels. The number of channels is not + * altered. + * @param corners positions of marker corners on input image. + * (e.g std::vector > ). For N detected markers, the dimensions of + * this array should be Nx4. The order of the corners should be clockwise. + * @param ids vector of identifiers for markers in markersCorners . + * Optional, if not provided, ids are not painted. + * @param borderColor color of marker borders. Rest of colors (text color and first corner color) + * are calculated based on this one to improve visualization. + * + * Given an array of detected marker corners and its corresponding ids, this functions draws + * the markers in the image. The marker borders are painted and the markers identifiers if provided. + * Useful for debugging purposes. + */ +CV_EXPORTS_W void drawDetectedMarkers(InputOutputArray image, InputArrayOfArrays corners, + InputArray ids = noArray(), + Scalar borderColor = Scalar(0, 255, 0)); + + + +/** + * @brief Draw coordinate system axis from pose estimation + * + * @param image input/output image. It must have 1 or 3 channels. The number of channels is not + * altered. + * @param cameraMatrix input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvec rotation vector of the coordinate system that will be drawn. (@sa Rodrigues). + * @param tvec translation vector of the coordinate system that will be drawn. + * @param length length of the painted axis in the same unit than tvec (usually in meters) + * + * Given the pose estimation of a marker or board, this function draws the axis of the world + * coordinate system, i.e. the system centered on the marker/board. Useful for debugging purposes. + * + * @deprecated use cv::drawFrameAxes + */ +CV_EXPORTS_W void drawAxis(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, + InputArray rvec, InputArray tvec, float length); + + + +/** + * @brief Draw a canonical marker image + * + * @param dictionary dictionary of markers indicating the type of markers + * @param id identifier of the marker that will be returned. It has to be a valid id + * in the specified dictionary. + * @param sidePixels size of the image in pixels + * @param img output image with the marker + * @param borderBits width of the marker border. + * + * This function returns a marker image in its canonical form (i.e. ready to be printed) + */ +CV_EXPORTS_W void drawMarker(const Ptr &dictionary, int id, int sidePixels, OutputArray img, + int borderBits = 1); + + + +/** + * @brief Draw a planar board + * @sa _drawPlanarBoardImpl + * + * @param board layout of the board that will be drawn. The board should be planar, + * z coordinate is ignored + * @param outSize size of the output image in pixels. + * @param img output image with the board. The size of this image will be outSize + * and the board will be on the center, keeping the board proportions. + * @param marginSize minimum margins (in pixels) of the board in the output image + * @param borderBits width of the marker borders. + * + * This function return the image of a planar board, ready to be printed. It assumes + * the Board layout specified is planar by ignoring the z coordinates of the object points. + */ +CV_EXPORTS_W void drawPlanarBoard(const Ptr &board, Size outSize, OutputArray img, + int marginSize = 0, int borderBits = 1); + + + +/** + * @brief Implementation of drawPlanarBoard that accepts a raw Board pointer. + */ +void _drawPlanarBoardImpl(Board *board, Size outSize, OutputArray img, + int marginSize = 0, int borderBits = 1); + + + +/** + * @brief Calibrate a camera using aruco markers + * + * @param corners vector of detected marker corners in all frames. + * The corners should have the same format returned by detectMarkers (see #detectMarkers). + * @param ids list of identifiers for each marker in corners + * @param counter number of markers in each frame so that corners and ids can be split + * @param board Marker Board layout + * @param imageSize Size of the image used only to initialize the intrinsic camera matrix. + * @param cameraMatrix Output 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . If CV\_CALIB\_USE\_INTRINSIC\_GUESS + * and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be + * initialized before calling the function. + * @param distCoeffs Output vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view + * (e.g. std::vector>). That is, each k-th rotation vector together with the corresponding + * k-th translation vector (see the next output parameter description) brings the board pattern + * from the model coordinate space (in which object points are specified) to the world coordinate + * space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1). + * @param tvecs Output vector of translation vectors estimated for each pattern view. + * @param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters. + * Order of deviations values: + * \f$(f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, + * s_4, \tau_x, \tau_y)\f$ If one of parameters is not estimated, it's deviation is equals to zero. + * @param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters. + * Order of deviations values: \f$(R_1, T_1, \dotsc , R_M, T_M)\f$ where M is number of pattern views, + * \f$R_i, T_i\f$ are concatenated 1x3 vectors. + * @param perViewErrors Output vector of average re-projection errors estimated for each pattern view. + * @param flags flags Different flags for the calibration process (see #calibrateCamera for details). + * @param criteria Termination criteria for the iterative optimization algorithm. + * + * 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. + */ +CV_EXPORTS_AS(calibrateCameraArucoExtended) double calibrateCameraAruco( + InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr &board, + Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, + OutputArray perViewErrors, int flags = 0, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON)); + + +/** @brief It's the same function as #calibrateCameraAruco but without calibration error estimation. + */ +CV_EXPORTS_W double calibrateCameraAruco( + InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr &board, + Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs = noArray(), OutputArrayOfArrays tvecs = noArray(), int flags = 0, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON)); + + +/** + * @brief Given a board configuration and a set of detected markers, returns the corresponding + * image points and object points to call solvePnP + * + * @param board Marker board layout. + * @param detectedCorners List of detected marker corners of the board. + * @param detectedIds List of identifiers for each marker. + * @param objPoints Vector of vectors of board marker points in the board coordinate space. + * @param imgPoints Vector of vectors of the projections of board marker corner points. +*/ +CV_EXPORTS_W void getBoardObjectAndImagePoints(const Ptr &board, InputArrayOfArrays detectedCorners, + InputArray detectedIds, OutputArray objPoints, OutputArray imgPoints); + + +//! @} +} +} + +#endif diff --git a/aruco_pose/vendor/aruco/include/opencv2/aruco/charuco.hpp b/aruco_pose/vendor/aruco/include/opencv2/aruco/charuco.hpp new file mode 100644 index 00000000..be535c76 --- /dev/null +++ b/aruco_pose/vendor/aruco/include/opencv2/aruco/charuco.hpp @@ -0,0 +1,343 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#ifndef __OPENCV_CHARUCO_HPP__ +#define __OPENCV_CHARUCO_HPP__ + +#include +#include +#include + + +namespace cv { +namespace aruco { + +//! @addtogroup aruco +//! @{ + + +/** + * @brief ChArUco board + * Specific class for ChArUco boards. A ChArUco board is a planar board where the markers are placed + * inside the white squares of a chessboard. The benefits of ChArUco boards is that they provide + * both, ArUco markers versatility and chessboard corner precision, which is important for + * calibration and pose estimation. + * This class also allows the easy creation and drawing of ChArUco boards. + */ +class CV_EXPORTS_W CharucoBoard : public Board { + + public: + // vector of chessboard 3D corners precalculated + CV_PROP std::vector< Point3f > chessboardCorners; + + // for each charuco corner, nearest marker id and nearest marker corner id of each marker + CV_PROP std::vector< std::vector< int > > nearestMarkerIdx; + CV_PROP std::vector< std::vector< int > > nearestMarkerCorners; + + /** + * @brief Draw a ChArUco board + * + * @param outSize size of the output image in pixels. + * @param img output image with the board. The size of this image will be outSize + * and the board will be on the center, keeping the board proportions. + * @param marginSize minimum margins (in pixels) of the board in the output image + * @param borderBits width of the marker borders. + * + * This function return the image of the ChArUco board, ready to be printed. + */ + CV_WRAP void draw(Size outSize, OutputArray img, int marginSize = 0, int borderBits = 1); + + + /** + * @brief Create a CharucoBoard object + * + * @param squaresX number of chessboard squares in X direction + * @param squaresY number of chessboard squares in Y direction + * @param squareLength chessboard square side length (normally in meters) + * @param markerLength marker side length (same unit than squareLength) + * @param dictionary dictionary of markers indicating the type of markers. + * The first markers in the dictionary are used to fill the white chessboard squares. + * @return the output CharucoBoard object + * + * This functions creates a CharucoBoard object given the number of squares in each direction + * and the size of the markers and chessboard squares. + */ + CV_WRAP static Ptr create(int squaresX, int squaresY, float squareLength, + float markerLength, const Ptr &dictionary); + + /** + * + */ + CV_WRAP Size getChessboardSize() const { return Size(_squaresX, _squaresY); } + + /** + * + */ + CV_WRAP float getSquareLength() const { return _squareLength; } + + /** + * + */ + CV_WRAP float getMarkerLength() const { return _markerLength; } + + private: + void _getNearestMarkerCorners(); + + // number of markers in X and Y directions + int _squaresX, _squaresY; + + // size of chessboard squares side (normally in meters) + float _squareLength; + + // marker side lenght (normally in meters) + float _markerLength; +}; + + + + +/** + * @brief Interpolate position of ChArUco board corners + * @param markerCorners vector of already detected markers corners. For each marker, its four + * corners are provided, (e.g std::vector > ). For N detected markers, the + * dimensions of this array should be Nx4. The order of the corners should be clockwise. + * @param markerIds list of identifiers for each marker in corners + * @param image input image necesary for corner refinement. Note that markers are not detected and + * should be sent in corners and ids parameters. + * @param board layout of ChArUco board. + * @param charucoCorners interpolated chessboard corners + * @param charucoIds interpolated chessboard corners identifiers + * @param cameraMatrix optional 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs optional vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param minMarkers number of adjacent markers that must be detected to return a charuco corner + * + * This function receives the detected markers and returns the 2D position of the chessboard corners + * from a ChArUco board using the detected Aruco markers. If camera parameters are provided, + * the process is based in an approximated pose estimation, else it is based on local homography. + * Only visible corners are returned. For each corner, its corresponding identifier is + * also returned in charucoIds. + * The function returns the number of interpolated corners. + */ +CV_EXPORTS_W int interpolateCornersCharuco(InputArrayOfArrays markerCorners, InputArray markerIds, + InputArray image, const Ptr &board, + OutputArray charucoCorners, OutputArray charucoIds, + InputArray cameraMatrix = noArray(), + InputArray distCoeffs = noArray(), int minMarkers = 2); + + + + +/** + * @brief Pose estimation for a ChArUco board given some of their corners + * @param charucoCorners vector of detected charuco corners + * @param charucoIds list of identifiers for each corner in charucoCorners + * @param board layout of ChArUco board. + * @param cameraMatrix input 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ + * @param distCoeffs vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvec Output vector (e.g. cv::Mat) corresponding to the rotation vector of the board + * (see cv::Rodrigues). + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * @param useExtrinsicGuess defines whether initial guess for \b rvec and \b tvec will be used or not. + * + * 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. + */ +CV_EXPORTS_W bool estimatePoseCharucoBoard(InputArray charucoCorners, InputArray charucoIds, + const Ptr &board, InputArray cameraMatrix, + InputArray distCoeffs, OutputArray rvec, OutputArray tvec, + bool useExtrinsicGuess = false); + + + + +/** + * @brief Draws a set of Charuco corners + * @param image input/output image. It must have 1 or 3 channels. The number of channels is not + * altered. + * @param charucoCorners vector of detected charuco corners + * @param charucoIds list of identifiers for each corner in charucoCorners + * @param cornerColor color of the square surrounding each corner + * + * This function draws a set of detected Charuco corners. If identifiers vector is provided, it also + * draws the id of each corner. + */ +CV_EXPORTS_W void drawDetectedCornersCharuco(InputOutputArray image, InputArray charucoCorners, + InputArray charucoIds = noArray(), + Scalar cornerColor = Scalar(255, 0, 0)); + + + +/** + * @brief Calibrate a camera using Charuco corners + * + * @param charucoCorners vector of detected charuco corners per frame + * @param charucoIds list of identifiers for each corner in charucoCorners per frame + * @param board Marker Board layout + * @param imageSize input image size + * @param cameraMatrix Output 3x3 floating-point camera matrix + * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . If CV\_CALIB\_USE\_INTRINSIC\_GUESS + * and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be + * initialized before calling the function. + * @param distCoeffs Output vector of distortion coefficients + * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements + * @param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view + * (e.g. std::vector>). That is, each k-th rotation vector together with the corresponding + * k-th translation vector (see the next output parameter description) brings the board pattern + * from the model coordinate space (in which object points are specified) to the world coordinate + * space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1). + * @param tvecs Output vector of translation vectors estimated for each pattern view. + * @param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters. + * Order of deviations values: + * \f$(f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, + * s_4, \tau_x, \tau_y)\f$ If one of parameters is not estimated, it's deviation is equals to zero. + * @param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters. + * Order of deviations values: \f$(R_1, T_1, \dotsc , R_M, T_M)\f$ where M is number of pattern views, + * \f$R_i, T_i\f$ are concatenated 1x3 vectors. + * @param perViewErrors Output vector of average re-projection errors estimated for each pattern view. + * @param flags flags Different flags for the calibration process (see #calibrateCamera for details). + * @param criteria Termination criteria for the iterative optimization algorithm. + * + * 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. + */ +CV_EXPORTS_AS(calibrateCameraCharucoExtended) double calibrateCameraCharuco( + InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const Ptr &board, + Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics, + OutputArray perViewErrors, int flags = 0, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON)); + +/** @brief It's the same function as #calibrateCameraCharuco but without calibration error estimation. +*/ +CV_EXPORTS_W double calibrateCameraCharuco( + InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const Ptr &board, + Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs = noArray(), OutputArrayOfArrays tvecs = noArray(), int flags = 0, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON)); + + + +/** + * @brief Detect ChArUco Diamond markers + * + * @param image input image necessary for corner subpixel. + * @param markerCorners list of detected marker corners from detectMarkers function. + * @param markerIds list of marker ids in markerCorners. + * @param squareMarkerLengthRate rate between square and marker length: + * squareMarkerLengthRate = squareLength/markerLength. The real units are not necessary. + * @param diamondCorners output list of detected diamond corners (4 corners per diamond). The order + * is the same than in marker corners: top left, top right, bottom right and bottom left. Similar + * format than the corners returned by detectMarkers (e.g std::vector > ). + * @param diamondIds ids of the diamonds in diamondCorners. The id of each diamond is in fact of + * type Vec4i, so each diamond has 4 ids, which are the ids of the aruco markers composing the + * diamond. + * @param cameraMatrix Optional camera calibration matrix. + * @param distCoeffs Optional camera distortion coefficients. + * + * This function detects Diamond markers from the previous detected ArUco markers. The diamonds + * are returned in the diamondCorners and diamondIds parameters. If camera calibration parameters + * are provided, the diamond search is based on reprojection. If not, diamond search is based on + * homography. Homography is faster than reprojection but can slightly reduce the detection rate. + */ +CV_EXPORTS_W void detectCharucoDiamond(InputArray image, InputArrayOfArrays markerCorners, + InputArray markerIds, float squareMarkerLengthRate, + OutputArrayOfArrays diamondCorners, OutputArray diamondIds, + InputArray cameraMatrix = noArray(), + InputArray distCoeffs = noArray()); + + + +/** + * @brief Draw a set of detected ChArUco Diamond markers + * + * @param image input/output image. It must have 1 or 3 channels. The number of channels is not + * altered. + * @param diamondCorners positions of diamond corners in the same format returned by + * detectCharucoDiamond(). (e.g std::vector > ). For N detected markers, + * the dimensions of this array should be Nx4. The order of the corners should be clockwise. + * @param diamondIds vector of identifiers for diamonds in diamondCorners, in the same format + * returned by detectCharucoDiamond() (e.g. std::vector). + * Optional, if not provided, ids are not painted. + * @param borderColor color of marker borders. Rest of colors (text color and first corner color) + * are calculated based on this one. + * + * Given an array of detected diamonds, this functions draws them in the image. The marker borders + * are painted and the markers identifiers if provided. + * Useful for debugging purposes. + */ +CV_EXPORTS_W void drawDetectedDiamonds(InputOutputArray image, InputArrayOfArrays diamondCorners, + InputArray diamondIds = noArray(), + Scalar borderColor = Scalar(0, 0, 255)); + + + + +/** + * @brief Draw a ChArUco Diamond marker + * + * @param dictionary dictionary of markers indicating the type of markers. + * @param ids list of 4 ids for each ArUco marker in the ChArUco marker. + * @param squareLength size of the chessboard squares in pixels. + * @param markerLength size of the markers in pixels. + * @param img output image with the marker. The size of this image will be + * 3*squareLength + 2*marginSize,. + * @param marginSize minimum margins (in pixels) of the marker in the output image + * @param borderBits width of the marker borders. + * + * This function return the image of a ChArUco marker, ready to be printed. + */ +// TODO cannot be exported yet; conversion from/to Vec4i is not wrapped in core +CV_EXPORTS void drawCharucoDiamond(const Ptr &dictionary, Vec4i ids, int squareLength, + int markerLength, OutputArray img, int marginSize = 0, + int borderBits = 1); + + + + +//! @} +} +} + +#endif diff --git a/aruco_pose/vendor/aruco/include/opencv2/aruco/dictionary.hpp b/aruco_pose/vendor/aruco/include/opencv2/aruco/dictionary.hpp new file mode 100644 index 00000000..27c7e5dd --- /dev/null +++ b/aruco_pose/vendor/aruco/include/opencv2/aruco/dictionary.hpp @@ -0,0 +1,212 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#ifndef __OPENCV_DICTIONARY_HPP__ +#define __OPENCV_DICTIONARY_HPP__ + +#include + +namespace cv { +namespace aruco { + +//! @addtogroup aruco +//! @{ + + +/** + * @brief Dictionary/Set of markers. It contains the inner codification + * + * bytesList contains the marker codewords where + * - bytesList.rows is the dictionary size + * - each marker is encoded using `nbytes = ceil(markerSize*markerSize/8.)` + * - each row contains all 4 rotations of the marker, so its length is `4*nbytes` + * + * `bytesList.ptr(i)[k*nbytes + j]` is then the j-th byte of i-th marker, in its k-th rotation. + */ +class CV_EXPORTS_W Dictionary { + + public: + CV_PROP_RW Mat bytesList; // marker code information + CV_PROP_RW int markerSize; // number of bits per dimension + CV_PROP_RW int maxCorrectionBits; // maximum number of bits that can be corrected + + + /** + */ + Dictionary(const Mat &_bytesList = Mat(), int _markerSize = 0, int _maxcorr = 0); + + + /** + Dictionary(const Dictionary &_dictionary); + */ + + + /** + */ + Dictionary(const Ptr &_dictionary); + + + /** + * @see generateCustomDictionary + */ + CV_WRAP_AS(create) static Ptr create(int nMarkers, int markerSize, int randomSeed=0); + + + /** + * @see generateCustomDictionary + */ + CV_WRAP_AS(create_from) static Ptr create(int nMarkers, int markerSize, + const Ptr &baseDictionary, int randomSeed=0); + + /** + * @see getPredefinedDictionary + */ + CV_WRAP static Ptr get(int dict); + + /** + * @brief Given a matrix of bits. Returns whether if marker is identified or not. + * It returns by reference the correct id (if any) and the correct rotation + */ + bool identify(const Mat &onlyBits, int &idx, int &rotation, double maxCorrectionRate) const; + + /** + * @brief Returns the distance of the input bits to the specific id. If allRotations is true, + * the four posible bits rotation are considered + */ + int getDistanceToId(InputArray bits, int id, bool allRotations = true) const; + + + /** + * @brief Draw a canonical marker image + */ + CV_WRAP void drawMarker(int id, int sidePixels, OutputArray _img, int borderBits = 1) const; + + + /** + * @brief Transform matrix of bits to list of bytes in the 4 rotations + */ + CV_WRAP static Mat getByteListFromBits(const Mat &bits); + + + /** + * @brief Transform list of bytes to matrix of bits + */ + CV_WRAP static Mat getBitsFromByteList(const Mat &byteList, int markerSize); +}; + + + + +/** + * @brief Predefined markers dictionaries/sets + * Each dictionary indicates the number of bits and the number of markers contained + * - DICT_ARUCO_ORIGINAL: standard ArUco Library Markers. 1024 markers, 5x5 bits, 0 minimum + distance + */ +enum PREDEFINED_DICTIONARY_NAME { + DICT_4X4_50 = 0, + DICT_4X4_100, + DICT_4X4_250, + DICT_4X4_1000, + DICT_5X5_50, + DICT_5X5_100, + DICT_5X5_250, + DICT_5X5_1000, + DICT_6X6_50, + DICT_6X6_100, + DICT_6X6_250, + DICT_6X6_1000, + DICT_7X7_50, + DICT_7X7_100, + DICT_7X7_250, + DICT_7X7_1000, + DICT_ARUCO_ORIGINAL, + DICT_APRILTAG_16h5, ///< 4x4 bits, minimum hamming distance between any two codes = 5, 30 codes + DICT_APRILTAG_25h9, ///< 5x5 bits, minimum hamming distance between any two codes = 9, 35 codes + DICT_APRILTAG_36h10, ///< 6x6 bits, minimum hamming distance between any two codes = 10, 2320 codes + DICT_APRILTAG_36h11 ///< 6x6 bits, minimum hamming distance between any two codes = 11, 587 codes +}; + + +/** + * @brief Returns one of the predefined dictionaries defined in PREDEFINED_DICTIONARY_NAME + */ +CV_EXPORTS Ptr getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name); + + +/** + * @brief Returns one of the predefined dictionaries referenced by DICT_*. + */ +CV_EXPORTS_W Ptr getPredefinedDictionary(int dict); + + +/** + * @see generateCustomDictionary + */ +CV_EXPORTS_AS(custom_dictionary) Ptr generateCustomDictionary( + int nMarkers, + int markerSize, + int randomSeed=0); + + +/** + * @brief Generates a new customizable marker dictionary + * + * @param nMarkers number of markers in the dictionary + * @param markerSize number of bits per dimension of each markers + * @param baseDictionary Include the markers in this dictionary at the beginning (optional) + * @param randomSeed a user supplied seed for theRNG() + * + * This function creates a new dictionary composed by nMarkers markers and each markers composed + * by markerSize x markerSize bits. If baseDictionary is provided, its markers are directly + * included and the rest are generated based on them. If the size of baseDictionary is higher + * than nMarkers, only the first nMarkers in baseDictionary are taken and no new marker is added. + */ +CV_EXPORTS_AS(custom_dictionary_from) Ptr generateCustomDictionary( + int nMarkers, + int markerSize, + const Ptr &baseDictionary, + int randomSeed=0); + + + +//! @} +} +} + +#endif diff --git a/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.cpp b/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.cpp new file mode 100644 index 00000000..fc75a384 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.cpp @@ -0,0 +1,1570 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. + +// limitation: image size must be <32768 in width and height. This is +// because we use a fixed-point 16 bit integer representation with one +// fractional bit. + +#include "precomp.hpp" +#include "apriltag_quad_thresh.hpp" + +//#define APRIL_DEBUG +#ifdef APRIL_DEBUG + #include "opencv2/imgcodecs.hpp" + #include +#endif + +namespace cv { +namespace aruco { + +static void ptsort_(struct pt *pts, int sz); // forward delaration + +static inline +void ptsort(struct pt *pts, int sz) +{ +#define MAYBE_SWAP(arr,apos,bpos) \ + if (arr[apos].theta > arr[bpos].theta) { \ + tmp = arr[apos]; arr[apos] = arr[bpos]; arr[bpos] = tmp; \ + }; + + if (sz <= 1) + return; + + if (sz == 2) { + struct pt tmp; + MAYBE_SWAP(pts, 0, 1); + return; + } + + // NB: Using less-branch-intensive sorting networks here on the + // hunch that it's better for performance. + if (sz == 3) { // 3 element bubble sort is optimal + struct pt tmp; + MAYBE_SWAP(pts, 0, 1); + MAYBE_SWAP(pts, 1, 2); + MAYBE_SWAP(pts, 0, 1); + return; + } + + if (sz == 4) { // 4 element optimal sorting network. + struct pt tmp; + MAYBE_SWAP(pts, 0, 1); // sort each half, like a merge sort + MAYBE_SWAP(pts, 2, 3); + MAYBE_SWAP(pts, 0, 2); // minimum value is now at 0. + MAYBE_SWAP(pts, 1, 3); // maximum value is now at end. + MAYBE_SWAP(pts, 1, 2); // that only leaves the middle two. + return; + } + + if (sz == 5) { + // this 9-step swap is optimal for a sorting network, but two + // steps slower than a generic sort. + struct pt tmp; + MAYBE_SWAP(pts, 0, 1); // sort each half (3+2), like a merge sort + MAYBE_SWAP(pts, 3, 4); + MAYBE_SWAP(pts, 1, 2); + MAYBE_SWAP(pts, 0, 1); + MAYBE_SWAP(pts, 0, 3); // minimum element now at 0 + MAYBE_SWAP(pts, 2, 4); // maximum element now at end + MAYBE_SWAP(pts, 1, 2); // now resort the three elements 1-3. + MAYBE_SWAP(pts, 2, 3); + MAYBE_SWAP(pts, 1, 2); + return; + } + +#undef MAYBE_SWAP + + ptsort_(pts, sz); +} + +void ptsort_(struct pt *pts, int sz) +{ + // a merge sort with temp storage. + + // Use stack storage if it's not too big. + cv::AutoBuffer _tmp_stack(sz); + memcpy(_tmp_stack.data(), pts, sizeof(struct pt) * sz); + + int asz = sz/2; + int bsz = sz - asz; + + struct pt *as = &_tmp_stack[0]; + struct pt *bs = &_tmp_stack[asz]; + + ptsort(as, asz); + ptsort(bs, bsz); + +#define MERGE(apos,bpos) \ + if (as[apos].theta < bs[bpos].theta) \ + pts[outpos++] = as[apos++]; \ + else \ + pts[outpos++] = bs[bpos++]; + + int apos = 0, bpos = 0, outpos = 0; + while (apos + 8 < asz && bpos + 8 < bsz) { + MERGE(apos,bpos); MERGE(apos,bpos); MERGE(apos,bpos); MERGE(apos,bpos); + MERGE(apos,bpos); MERGE(apos,bpos); MERGE(apos,bpos); MERGE(apos,bpos); + } + + while (apos < asz && bpos < bsz) { + MERGE(apos,bpos); + } + + if (apos < asz) + memcpy(&pts[outpos], &as[apos], (asz-apos)*sizeof(struct pt)); + if (bpos < bsz) + memcpy(&pts[outpos], &bs[bpos], (bsz-bpos)*sizeof(struct pt)); + +#undef MERGE +} + +/** + * lfps contains *cumulative* moments for N points, with + * index j reflecting points [0,j] (inclusive). + * fit a line to the points [i0, i1] (inclusive). i0, i1 are both (0, sz) + * if i1 < i0, we treat this as a wrap around. + */ +void fit_line(struct line_fit_pt *lfps, int sz, int i0, int i1, double *lineparm, double *err, double *mse){ + CV_Assert(i0 != i1); + CV_Assert(i0 >= 0 && i1 >= 0 && i0 < sz && i1 < sz); + + double Mx, My, Mxx, Myy, Mxy, W; + int N; // how many points are included in the set? + + if (i0 < i1) { + N = i1 - i0 + 1; + + Mx = lfps[i1].Mx; + My = lfps[i1].My; + Mxx = lfps[i1].Mxx; + Mxy = lfps[i1].Mxy; + Myy = lfps[i1].Myy; + W = lfps[i1].W; + + if (i0 > 0) { + Mx -= lfps[i0-1].Mx; + My -= lfps[i0-1].My; + Mxx -= lfps[i0-1].Mxx; + Mxy -= lfps[i0-1].Mxy; + Myy -= lfps[i0-1].Myy; + W -= lfps[i0-1].W; + } + + } else { + // i0 > i1, e.g. [15, 2]. Wrap around. + CV_Assert(i0 > 0); + + Mx = lfps[sz-1].Mx - lfps[i0-1].Mx; + My = lfps[sz-1].My - lfps[i0-1].My; + Mxx = lfps[sz-1].Mxx - lfps[i0-1].Mxx; + Mxy = lfps[sz-1].Mxy - lfps[i0-1].Mxy; + Myy = lfps[sz-1].Myy - lfps[i0-1].Myy; + W = lfps[sz-1].W - lfps[i0-1].W; + + Mx += lfps[i1].Mx; + My += lfps[i1].My; + Mxx += lfps[i1].Mxx; + Mxy += lfps[i1].Mxy; + Myy += lfps[i1].Myy; + W += lfps[i1].W; + + N = sz - i0 + i1 + 1; + } + + CV_Assert(N >= 2); + + double Ex = Mx / W; + double Ey = My / W; + double Cxx = Mxx / W - Ex*Ex; + double Cxy = Mxy / W - Ex*Ey; + double Cyy = Myy / W - Ey*Ey; + + double nx, ny; + + if (1) { + // on iOS about 5% of total CPU spent in these trig functions. + // 85 ms per frame on 5S, example.pnm + // + // XXX this was using the double-precision atan2. Was there a case where + // we needed that precision? Seems doubtful. + float normal_theta = float(.5f * (CV_PI / 180)) * cv::fastAtan2((float)(-2*Cxy), (float)(Cyy - Cxx)); + nx = cosf(normal_theta); + ny = sinf(normal_theta); + } else { + // 73.5 ms per frame on 5S, example.pnm + double ty = -2*Cxy; + double tx = (Cyy - Cxx); + double mag = ty*ty + tx*tx; + + if (mag == 0) { + nx = 1; + ny = 0; + } else { + float norm = sqrtf((float)(ty*ty + tx*tx)); + tx /= norm; + + // ty is now sin(2theta) + // tx is now cos(2theta). We want sin(theta) and cos(theta) + + // due to precision err, tx could still have slightly too large magnitude. + if (tx > 1) { + ny = 0; + nx = 1; + } else if (tx < -1) { + ny = 1; + nx = 0; + } else { + // half angle formula + ny = sqrtf((1.0f - (float)tx)*0.5f); + nx = sqrtf((1.0f + (float)tx)*0.5f); + + // pick a consistent branch cut + if (ty < 0) + ny = - ny; + } + } + } + + if (lineparm) { + lineparm[0] = Ex; + lineparm[1] = Ey; + lineparm[2] = nx; + lineparm[3] = ny; + } + + // sum of squared errors = + // + // SUM_i ((p_x - ux)*nx + (p_y - uy)*ny)^2 + // SUM_i nx*nx*(p_x - ux)^2 + 2nx*ny(p_x -ux)(p_y-uy) + ny*ny*(p_y-uy)*(p_y-uy) + // nx*nx*SUM_i((p_x -ux)^2) + 2nx*ny*SUM_i((p_x-ux)(p_y-uy)) + ny*ny*SUM_i((p_y-uy)^2) + // + // nx*nx*N*Cxx + 2nx*ny*N*Cxy + ny*ny*N*Cyy + + // sum of squared errors + if (err) + *err = nx*nx*N*Cxx + 2*nx*ny*N*Cxy + ny*ny*N*Cyy; + + // mean squared error + if (mse) + *mse = nx*nx*Cxx + 2*nx*ny*Cxy + ny*ny*Cyy; +} + +int err_compare_descending(const void *_a, const void *_b){ + const double *a = (const double*)_a; + const double *b = (const double*)_b; + + return ((*a) < (*b)) ? 1 : -1; +} + +/** + 1. Identify A) white points near a black point and B) black points near a white point. + + 2. Find the connected components within each of the classes above, + yielding clusters of "white-near-black" and + "black-near-white". (These two classes are kept separate). Each + segment has a unique id. + + 3. For every pair of "white-near-black" and "black-near-white" + clusters, find the set of points that are in one and adjacent to the + other. In other words, a "boundary" layer between the two + clusters. (This is actually performed by iterating over the pixels, + rather than pairs of clusters.) Critically, this helps keep nearby + edges from becoming connected. + **/ +int quad_segment_maxima(const Ptr &td, int sz, struct line_fit_pt *lfps, int indices[4]){ + + // ksz: when fitting points, how many points on either side do we consider? + // (actual "kernel" width is 2ksz). + // + // This value should be about: 0.5 * (points along shortest edge). + // + // If all edges were equally-sized, that would give a value of + // sz/8. We make it somewhat smaller to account for tags at high + // aspects. + + // XXX Tunable. Maybe make a multiple of JPEG block size to increase robustness + // to JPEG compression artifacts? + //int ksz = imin(20, sz / 12); + int ksz = 20 < (sz/12)? 20: (sz/12); + + // can't fit a quad if there are too few points. + if (ksz < 2) + return 0; + + // printf("sz %5d, ksz %3d\n", sz, ksz); + + std::vector errs(sz); + + for (int i = 0; i < sz; i++) { + fit_line(lfps, sz, (i + sz - ksz) % sz, (i + ksz) % sz, NULL, &errs[i], NULL); + } + + // apply a low-pass filter to errs + if (1) { + std::vector y(sz); + + // how much filter to apply? + + // XXX Tunable + double sigma = 1; // was 3 + + // cutoff = exp(-j*j/(2*sigma*sigma)); + // log(cutoff) = -j*j / (2*sigma*sigma) + // log(cutoff)*2*sigma*sigma = -j*j; + + // how big a filter should we use? We make our kernel big + // enough such that we represent any values larger than + // 'cutoff'. + + // XXX Tunable (though not super useful to change) + double cutoff = 0.05; + int fsz = cvFloor(sqrt(-log(cutoff)*2*sigma*sigma)) + 1; + fsz = 2*fsz + 1; + + // For default values of cutoff = 0.05, sigma = 3, + // we have fsz = 17. + std::vector f(fsz); + + for (int i = 0; i < fsz; i++) { + int j = i - fsz / 2; + f[i] = (float)exp(-j*j/(2*sigma*sigma)); + } + + for (int iy = 0; iy < sz; iy++) { + double acc = 0; + + for (int i = 0; i < fsz; i++) { + acc += errs[(iy + i - fsz / 2 + sz) % sz] * f[i]; + } + y[iy] = acc; + } + copy(y.begin(), y.end(), errs.begin()); + } + + std::vector maxima(sz); + std::vector maxima_errs(sz); + int nmaxima = 0; + + for (int i = 0; i < sz; i++) { + if (errs[i] > errs[(i+1)%sz] && errs[i] > errs[(i+sz-1)%sz]) { + maxima[nmaxima] = i; + maxima_errs[nmaxima] = errs[i]; + nmaxima++; + } + } + // if we didn't get at least 4 maxima, we can't fit a quad. + if (nmaxima < 4) + return 0; + + // select only the best maxima if we have too many + int max_nmaxima = td->aprilTagMaxNmaxima; + + if (nmaxima > max_nmaxima) { + std::vector maxima_errs_copy(maxima_errs.begin(), maxima_errs.begin()+nmaxima); + + // throw out all but the best handful of maxima. Sorts descending. + qsort(maxima_errs_copy.data(), nmaxima, sizeof(double), err_compare_descending); + + double maxima_thresh = maxima_errs_copy[max_nmaxima]; + int out = 0; + for (int in = 0; in < nmaxima; in++) { + if (maxima_errs[in] <= maxima_thresh) + continue; + maxima[out++] = maxima[in]; + } + nmaxima = out; + } + + int best_indices[4]; + double best_error = HUGE_VALF; + + double err01, err12, err23, err30; + double mse01, mse12, mse23, mse30; + double params01[4], params12[4], params23[4], params30[4]; + + // disallow quads where the angle is less than a critical value. + double max_dot = cos(td->aprilTagCriticalRad); //25*M_PI/180); + + for (int m0 = 0; m0 < nmaxima - 3; m0++) { + int i0 = maxima[m0]; + + for (int m1 = m0+1; m1 < nmaxima - 2; m1++) { + int i1 = maxima[m1]; + + fit_line(lfps, sz, i0, i1, params01, &err01, &mse01); + + if (mse01 > td->aprilTagMaxLineFitMse) + continue; + + for (int m2 = m1+1; m2 < nmaxima - 1; m2++) { + int i2 = maxima[m2]; + + fit_line(lfps, sz, i1, i2, params12, &err12, &mse12); + if (mse12 > td->aprilTagMaxLineFitMse) + continue; + + double dot = params01[2]*params12[2] + params01[3]*params12[3]; + if (fabs(dot) > max_dot) + continue; + + for (int m3 = m2+1; m3 < nmaxima; m3++) { + int i3 = maxima[m3]; + + fit_line(lfps, sz, i2, i3, params23, &err23, &mse23); + if (mse23 > td->aprilTagMaxLineFitMse) + continue; + + fit_line(lfps, sz, i3, i0, params30, &err30, &mse30); + if (mse30 > td->aprilTagMaxLineFitMse) + continue; + + double err = err01 + err12 + err23 + err30; + if (err < best_error) { + best_error = err; + best_indices[0] = i0; + best_indices[1] = i1; + best_indices[2] = i2; + best_indices[3] = i3; + } + } + } + } + } + + if (best_error == HUGE_VALF) + return 0; + + for (int i = 0; i < 4; i++) + indices[i] = best_indices[i]; + + if (best_error / sz < td->aprilTagMaxLineFitMse) + return 1; + return 0; +} + +/** + * returns 0 if the cluster looks bad. + */ +int quad_segment_agg(int sz, struct line_fit_pt *lfps, int indices[4]){ + //int sz = zarray_size(cluster); + + zmaxheap_t *heap = zmaxheap_create(sizeof(struct remove_vertex*)); + + // We will initially allocate sz rvs. We then have two types of + // iterations: some iterations that are no-ops in terms of + // allocations, and those that remove a vertex and allocate two + // more children. This will happen at most (sz-4) times. Thus we + // need: sz + 2*(sz-4) entries. + + int rvalloc_pos = 0; + int rvalloc_size = 3*sz; + cv::AutoBuffer rvalloc_(std::max(1, rvalloc_size)); + memset(rvalloc_.data(), 0, sizeof(rvalloc_[0]) * rvalloc_.size()); // TODO Add AutoBuffer zero fill + struct remove_vertex *rvalloc = rvalloc_.data(); + cv::AutoBuffer segs_(std::max(1, sz)); // TODO Add AutoBuffer zero fill + memset(segs_.data(), 0, sizeof(segs_[0]) * segs_.size()); + struct segment *segs = segs_.data(); + + // populate with initial entries + for (int i = 0; i < sz; i++) { + struct remove_vertex *rv = &rvalloc[rvalloc_pos++]; + rv->i = i; + if (i == 0) { + rv->left = sz-1; + rv->right = 1; + } else { + rv->left = i-1; + rv->right = (i+1) % sz; + } + + fit_line(lfps, sz, rv->left, rv->right, NULL, NULL, &rv->err); + + //TODO is finite CV_Assert(): + CV_DbgAssert (!cvIsNaN(-rv->err) && "zmaxheap_add: Trying to add non-finite number to heap. NaN's prohibited, could allow INF with testing"); + zmaxheap_add(heap, &rv, (float)-rv->err); + + segs[i].left = rv->left; + segs[i].right = rv->right; + segs[i].is_vertex = 1; + } + + int nvertices = sz; + + while (nvertices > 4) { + CV_Assert(rvalloc_pos < rvalloc_size); + + struct remove_vertex *rv; + float err; + + int res = zmaxheap_remove_max(heap, &rv, &err); + if (!res) + return 0; + CV_Assert(res); + + // is this remove_vertex valid? (Or has one of the left/right + // vertices changes since we last looked?) + if (!segs[rv->i].is_vertex || + !segs[rv->left].is_vertex || + !segs[rv->right].is_vertex) { + continue; + } + + // we now merge. + CV_Assert(segs[rv->i].is_vertex); + + segs[rv->i].is_vertex = 0; + segs[rv->left].right = rv->right; + segs[rv->right].left = rv->left; + + // create the join to the left + if (1) { + struct remove_vertex *child = &rvalloc[rvalloc_pos++]; + child->i = rv->left; + child->left = segs[rv->left].left; + child->right = rv->right; + + fit_line(lfps, sz, child->left, child->right, NULL, NULL, &child->err); + + //TODO is finite CV_Assert(): + CV_DbgAssert (!cvIsNaN(-child->err) && "zmaxheap_add: Trying to add non-finite number to heap. NaN's prohibited, could allow INF with testing"); + zmaxheap_add(heap, &child, (float)-child->err); + } + + // create the join to the right + if (1) { + struct remove_vertex *child = &rvalloc[rvalloc_pos++]; + child->i = rv->right; + child->left = rv->left; + child->right = segs[rv->right].right; + + fit_line(lfps, sz, child->left, child->right, NULL, NULL, &child->err); + + //TODO is finite CV_Assert(): + CV_DbgAssert (!cvIsNaN(-child->err) && "zmaxheap_add: Trying to add non-finite number to heap. NaN's prohibited, could allow INF with testing"); + zmaxheap_add(heap, &child, (float)-child->err); + } + + // we now have one less vertex + nvertices--; + } + + zmaxheap_destroy(heap); + + int idx = 0; + for (int i = 0; i < sz; i++) { + if (segs[i].is_vertex) { + indices[idx++] = i; + } + } + + return 1; +} + +#define DO_UNIONFIND(dx, dy) if (im.data[y*s + dy*s + x + dx] == v) unionfind_connect(uf, y*w + x, y*w + dy*w + x + dx); +static void do_unionfind_line(unionfind_t *uf, Mat &im, int w, int s, int y){ + CV_Assert(y+1 < im.rows); + CV_Assert(!im.empty()); + + for (int x = 1; x < w - 1; x++) { + uint8_t v = im.data[y*s + x]; + + if (v == 127) + continue; + + // (dx,dy) pairs for 8 connectivity: + // (REFERENCE) (1, 0) + // (-1, 1) (0, 1) (1, 1) + // + DO_UNIONFIND(1, 0); + DO_UNIONFIND(0, 1); + if (v == 255) { + DO_UNIONFIND(-1, 1); + DO_UNIONFIND(1, 1); + } + } +} +#undef DO_UNIONFIND + +/** + * return 1 if the quad looks okay, 0 if it should be discarded + * quad + **/ +int fit_quad(const Ptr &_params, const Mat im, zarray_t *cluster, struct sQuad *quad){ + CV_Assert(cluster != NULL); + + int res = 0; + + int sz = _zarray_size(cluster); + if (sz < 4) // can't fit a quad to less than 4 points + return 0; + + ///////////////////////////////////////////////////////////// + // Step 1. Sort points so they wrap around the center of the + // quad. We will constrain our quad fit to simply partition this + // ordered set into 4 groups. + + // compute a bounding box so that we can order the points + // according to their angle WRT the center. + int32_t xmax = 0, xmin = INT32_MAX, ymax = 0, ymin = INT32_MAX; + + for (int pidx = 0; pidx < sz; pidx++) { + struct pt *p; + _zarray_get_volatile(cluster, pidx, &p); + + //(a > b) ? a : b; + //xmax = imax(xmax, p->x); + //xmin = imin(xmin, p->x); + //ymax = imax(ymax, p->y); + //ymin = imin(ymin, p->y); + + xmax = xmax > p->x? xmax : p->x; + xmin = xmin < p->x? xmin : p->x; + + ymax = ymax > p->y? ymax : p->y; + ymin = ymin < p->y? ymin : p->y; + } + + // add some noise to (cx,cy) so that pixels get a more diverse set + // of theta estimates. This will help us remove more points. + // (Only helps a small amount. The actual noise values here don't + // matter much at all, but we want them [-1, 1]. (XXX with + // fixed-point, should range be bigger?) + double cx = (xmin + xmax) * 0.5 + 0.05118; + double cy = (ymin + ymax) * 0.5 + -0.028581; + + double dot = 0; + + for (int pidx = 0; pidx < sz; pidx++) { + struct pt *p; + _zarray_get_volatile(cluster, pidx, &p); + + double dx = p->x - cx; + double dy = p->y - cy; + + p->theta = cv::fastAtan2((float)dy, (float)dx) * (float)(CV_PI/180); + + dot += dx*p->gx + dy*p->gy; + } + + // Ensure that the black border is inside the white border. + if (dot < 0) + return 0; + + // we now sort the points according to theta. This is a prepatory + // step for segmenting them into four lines. + if (1) { + // zarray_sort(cluster, pt_compare_theta); + ptsort((struct pt*) cluster->data, sz); + + // remove duplicate points. (A byproduct of our segmentation system.) + if (1) { + int outpos = 1; + + struct pt *last; + _zarray_get_volatile(cluster, 0, &last); + + for (int i = 1; i < sz; i++) { + + struct pt *p; + _zarray_get_volatile(cluster, i, &p); + + if (p->x != last->x || p->y != last->y) { + + if (i != outpos) { + struct pt *out; + _zarray_get_volatile(cluster, outpos, &out); + memcpy(out, p, sizeof(struct pt)); + } + + outpos++; + } + + last = p; + } + + cluster->size = outpos; + sz = outpos; + } + + } else { + // This is a counting sort in which we retain at most one + // point for every bucket; the bucket index is computed from + // theta. Since a good quad completes a complete revolution, + // there's reason to think that we should get a good + // distribution of thetas. We might "lose" a few points due + // to collisions, but this shouldn't affect quality very much. + + // XXX tunable. Increase to reduce the likelihood of "losing" + // points due to collisions. + int nbuckets = 4*sz; + +#define ASSOC 2 + std::vector > v(nbuckets, std::vector(ASSOC)); + + // put each point into a bucket. + for (int i = 0; i < sz; i++) { + struct pt *p; + _zarray_get_volatile(cluster, i, &p); + + CV_Assert(p->theta >= -CV_PI && p->theta <= CV_PI); + + int bucket = cvFloor((nbuckets - 1) * (p->theta + CV_PI) / (2*CV_PI)); + CV_Assert(bucket >= 0 && bucket < nbuckets); + + for (int j = 0; j < ASSOC; j++) { + if (v[bucket][j].theta == 0) { + v[bucket][j] = *p; + break; + } + } + } + + // collect the points from the buckets and put them back into the array. + int outsz = 0; + for (int i = 0; i < nbuckets; i++) { + for (int j = 0; j < ASSOC; j++) { + if (v[i][j].theta != 0) { + _zarray_set(cluster, outsz, &v[i][j], NULL); + outsz++; + } + } + } + + _zarray_truncate(cluster, outsz); + sz = outsz; + } + + if (sz < 4) + return 0; + + ///////////////////////////////////////////////////////////// + // Step 2. Precompute statistics that allow line fit queries to be + // efficiently computed for any contiguous range of indices. + + cv::AutoBuffer lfps_(sz); + memset(lfps_.data(), 0, sizeof(lfps_[0]) * lfps_.size()); // TODO Add AutoBuffer zero fill + struct line_fit_pt *lfps = lfps_.data(); + + for (int i = 0; i < sz; i++) { + struct pt *p; + _zarray_get_volatile(cluster, i, &p); + + if (i > 0) { + memcpy(&lfps[i], &lfps[i-1], sizeof(struct line_fit_pt)); + } + + if (0) { + // we now undo our fixed-point arithmetic. + double delta = 0.5; + double x = p->x * .5 + delta; + double y = p->y * .5 + delta; + double W; + + for (int dy = -1; dy <= 1; dy++) { + int iy = cvFloor(y + dy); + + if (iy < 0 || iy + 1 >= im.rows) + continue; + + for (int dx = -1; dx <= 1; dx++) { + int ix = cvFloor(x + dx); + + if (ix < 0 || ix + 1 >= im.cols) + continue; + + int grad_x = im.data[iy * im.cols + ix + 1] - + im.data[iy * im.cols + ix - 1]; + + int grad_y = im.data[(iy+1) * im.cols + ix] - + im.data[(iy-1) * im.cols + ix]; + + W = sqrtf(float(grad_x*grad_x + grad_y*grad_y)) + 1; + + // double fx = x + dx, fy = y + dy; + double fx = ix + .5, fy = iy + .5; + lfps[i].Mx += W * fx; + lfps[i].My += W * fy; + lfps[i].Mxx += W * fx * fx; + lfps[i].Mxy += W * fx * fy; + lfps[i].Myy += W * fy * fy; + lfps[i].W += W; + } + } + } else { + // we now undo our fixed-point arithmetic. + double delta = 0.5; // adjust for pixel center bias + double x = p->x * .5 + delta; + double y = p->y * .5 + delta; + int ix = cvFloor(x), iy = cvFloor(y); + double W = 1; + + if (ix > 0 && ix+1 < im.cols && iy > 0 && iy+1 < im.rows) { + int grad_x = im.data[iy * im.cols + ix + 1] - + im.data[iy * im.cols + ix - 1]; + + int grad_y = im.data[(iy+1) * im.cols + ix] - + im.data[(iy-1) * im.cols + ix]; + + // XXX Tunable. How to shape the gradient magnitude? + W = sqrt(grad_x*grad_x + grad_y*grad_y) + 1; + } + + double fx = x, fy = y; + lfps[i].Mx += W * fx; + lfps[i].My += W * fy; + lfps[i].Mxx += W * fx * fx; + lfps[i].Mxy += W * fx * fy; + lfps[i].Myy += W * fy * fy; + lfps[i].W += W; + } + } + + int indices[4]; + if (1) { + if (!quad_segment_maxima(_params, _zarray_size(cluster), lfps, indices)) + goto finish; + } else { + if (!quad_segment_agg(sz, lfps, indices)) + goto finish; + } + + // printf("%d %d %d %d\n", indices[0], indices[1], indices[2], indices[3]); + + if (0) { + // no refitting here; just use those points as the vertices. + // Note, this is useful for debugging, but pretty bad in + // practice since this code path also omits several + // plausibility checks that save us tons of time in quad + // decoding. + for (int i = 0; i < 4; i++) { + struct pt *p; + _zarray_get_volatile(cluster, indices[i], &p); + + quad->p[i][0] = (float)(.5*p->x); // undo fixed-point arith. + quad->p[i][1] = (float)(.5*p->y); + } + + res = 1; + + } else { + double lines[4][4]; + + for (int i = 0; i < 4; i++) { + int i0 = indices[i]; + int i1 = indices[(i+1)&3]; + + if (0) { + // if there are enough points, skip the points near the corners + // (because those tend not to be very good.) + if (i1-i0 > 8) { + int t = (i1-i0)/6; + if (t < 0) + t = -t; + + i0 = (i0 + t) % sz; + i1 = (i1 + sz - t) % sz; + } + } + + double err; + fit_line(lfps, sz, i0, i1, lines[i], NULL, &err); + + if (err > _params->aprilTagMaxLineFitMse) { + res = 0; + goto finish; + } + } + + for (int i = 0; i < 4; i++) { + // solve for the intersection of lines (i) and (i+1)&3. + // p0 + lambda0*u0 = p1 + lambda1*u1, where u0 and u1 + // are the line directions. + // + // lambda0*u0 - lambda1*u1 = (p1 - p0) + // + // rearrange (solve for lambdas) + // + // [u0_x -u1_x ] [lambda0] = [ p1_x - p0_x ] + // [u0_y -u1_y ] [lambda1] [ p1_y - p0_y ] + // + // remember that lines[i][0,1] = p, lines[i][2,3] = NORMAL vector. + // We want the unit vector, so we need the perpendiculars. Thus, below + // we have swapped the x and y components and flipped the y components. + + const int i1 = (i + 1) & 3; + double A00 = lines[i][3], A01 = -lines[i1][3]; + double A10 = -lines[i][2], A11 = lines[i1][2]; + double B0 = -lines[i][0] + lines[i1][0]; + double B1 = -lines[i][1] + lines[i1][1]; + + double det = A00 * A11 - A10 * A01; + if (fabs(det) < 0.001) { + res = 0; + goto finish; + } + + // inverse. + double det_inv = 1.0 / det; + double W00 = A11 * det_inv, W01 = -A01 * det_inv; + + // solve + double L0 = W00*B0 + W01*B1; + + // compute intersection + quad->p[i][0] = (float)(lines[i][0] + L0*A00); + quad->p[i][1] = (float)(lines[i][1] + L0*A10); + +#if !defined(NDEBUG) + { + // we should get the same intersection starting + // from point p1 and moving L1*u1. + double W10 = -A10 * det_inv, W11 = A00 * det_inv; + double L1 = W10*B0 + W11*B1; + + double x = lines[i1][0] - L1*A01; + double y = lines[i1][1] - L1*A11; + + CV_Assert(fabs(x - quad->p[i][0]) < 0.001); + CV_Assert(fabs(y - quad->p[i][1]) < 0.001); + } +#endif // NDEBUG + + res = 1; + } + } + + // reject quads that are too small + if (1) { + double area = 0; + + // get area of triangle formed by points 0, 1, 2, 0 + double length[3], p; + for (int i = 0; i < 3; i++) { + int idxa = i; // 0, 1, 2, + int idxb = (i+1) % 3; // 1, 2, 0 + //length[i] = sqrt( + // sq(quad->p[idxb][0] - quad->p[idxa][0]) + // + sq(quad->p[idxb][1] - quad->p[idxa][1])); + double sq1 = quad->p[idxb][0] - quad->p[idxa][0]; + sq1 = sq1 * sq1; + double sq2 = quad->p[idxb][1] - quad->p[idxa][1]; + sq2 = sq2 * sq2; + length[i] = sqrt(sq1 + sq2); + } + p = (length[0] + length[1] + length[2]) / 2; + + area += sqrt(p*(p-length[0])*(p-length[1])*(p-length[2])); + + // get area of triangle formed by points 2, 3, 0, 2 + for (int i = 0; i < 3; i++) { + int idxs[] = { 2, 3, 0, 2 }; + int idxa = idxs[i]; + int idxb = idxs[i+1]; + //length[i] = sqrt( + // sq(quad->p[idxb][0] - quad->p[idxa][0]) + // + sq(quad->p[idxb][1] - quad->p[idxa][1])); + double sq1 = quad->p[idxb][0] - quad->p[idxa][0]; + sq1 = sq1 * sq1; + double sq2 = quad->p[idxb][1] - quad->p[idxa][1]; + sq2 = sq2 * sq2; + length[i] = sqrt(sq1 + sq2); + } + p = (length[0] + length[1] + length[2]) / 2; + + area += sqrt(p*(p-length[0])*(p-length[1])*(p-length[2])); + + // we don't actually know the family yet (quad detection is generic.) + // This threshold is based on a 6x6 tag (which is actually 8x8) + // int d = fam->d + fam->black_border*2; + int d = 8; + if (area < d*d) { + res = 0; + goto finish; + } + } + + // reject quads whose cumulative angle change isn't equal to 2PI + if(1){ + double total = 0; + + for (int i = 0; i < 4; i++) { + int i0 = i, i1 = (i+1)&3, i2 = (i+2)&3; + + double theta0 = atan2f(quad->p[i0][1] - quad->p[i1][1], + quad->p[i0][0] - quad->p[i1][0]); + double theta1 = atan2f(quad->p[i2][1] - quad->p[i1][1], + quad->p[i2][0] - quad->p[i1][0]); + + double dtheta = theta0 - theta1; + if (dtheta < 0) + dtheta += 2*CV_PI; + + if (dtheta < _params->aprilTagCriticalRad || dtheta > (CV_PI - _params->aprilTagCriticalRad)) + res = 0; + + total += dtheta; + } + + // looking for 2PI + if (total < 6.2 || total > 6.4) { + res = 0; + goto finish; + } + } + + finish: + + return res; +} + +/** + * + * @param nCidx0 + * @param nCidx1 + * @param nClusters + * @param nW + * @param nH + * @param nquads + * @param td + * @param im + */ +static void do_quad(int nCidx0, int nCidx1, zarray_t &nClusters, int nW, int nH, zarray_t *nquads, const Ptr &td, const Mat im){ + + CV_Assert(nquads != NULL); + + //struct quad_task *task = (struct quad_task*) p; + + //zarray_t *clusters = nClusters; + zarray_t *quads = nquads; + int w = nW, h = nH; + + for (int cidx = nCidx0; cidx < nCidx1; cidx++) { + + zarray_t *cluster; + _zarray_get(&nClusters, cidx, &cluster); + + if (_zarray_size(cluster) < td->aprilTagMinClusterPixels) + continue; + + // a cluster should contain only boundary points around the + // tag. it cannot be bigger than the whole screen. (Reject + // large connected blobs that will be prohibitively slow to + // fit quads to.) A typical point along an edge is added three + // times (because it has 3 neighbors). The maximum perimeter + // is 2w+2h. + if (_zarray_size(cluster) > 3*(2*w+2*h)) { + continue; + } + + struct sQuad quad; + memset(&quad, 0, sizeof(struct sQuad)); + + if (fit_quad(td, im, cluster, &quad)) { + //pthread_mutex_lock(&td.mutex); + _zarray_add(quads, &quad); + //pthread_mutex_unlock(&td.mutex); + } + } +} + +/** + * + * @param mIm + * @param parameters + * @param mThresh + */ +void threshold(const Mat mIm, const Ptr ¶meters, Mat& mThresh){ + int w = mIm.cols, h = mIm.rows; + int s = (unsigned) mIm.step; + CV_Assert(w < 32768); + CV_Assert(h < 32768); + + CV_Assert(mThresh.step == (unsigned)s); + + // The idea is to find the maximum and minimum values in a + // window around each pixel. If it's a contrast-free region + // (max-min is small), don't try to binarize. Otherwise, + // threshold according to (max+min)/2. + // + // Mark low-contrast regions with value 127 so that we can skip + // future work on these areas too. + + // however, computing max/min around every pixel is needlessly + // expensive. We compute max/min for tiles. To avoid artifacts + // that arise when high-contrast features appear near a tile + // edge (and thus moving from one tile to another results in a + // large change in max/min value), the max/min values used for + // any pixel are computed from all 3x3 surrounding tiles. Thus, + // the max/min sampling area for nearby pixels overlap by at least + // one tile. + // + // The important thing is that the windows be large enough to + // capture edge transitions; the tag does not need to fit into + // a tile. + + // XXX Tunable. Generally, small tile sizes--- so long as they're + // large enough to span a single tag edge--- seem to be a winner. + const int tilesz = 4; + + // the last (possibly partial) tiles along each row and column will + // just use the min/max value from the last full tile. + int tw = w / tilesz; + int th = h / tilesz; + + uint8_t *im_max = (uint8_t*)calloc(tw*th, sizeof(uint8_t)); + uint8_t *im_min = (uint8_t*)calloc(tw*th, sizeof(uint8_t)); + + + // first, collect min/max statistics for each tile + for (int ty = 0; ty < th; ty++) { + for (int tx = 0; tx < tw; tx++) { + uint8_t max = 0, min = 255; + + for (int dy = 0; dy < tilesz; dy++) { + + for (int dx = 0; dx < tilesz; dx++) { + + uint8_t v = mIm.data[(ty*tilesz+dy)*s + tx*tilesz + dx]; + if (v < min) + min = v; + if (v > max) + max = v; + } + } + im_max[ty*tw+tx] = max; + im_min[ty*tw+tx] = min; + } + } + + // second, apply 3x3 max/min convolution to "blur" these values + // over larger areas. This reduces artifacts due to abrupt changes + // in the threshold value. + uint8_t *im_max_tmp = (uint8_t*)calloc(tw*th, sizeof(uint8_t)); + uint8_t *im_min_tmp = (uint8_t*)calloc(tw*th, sizeof(uint8_t)); + + for (int ty = 0; ty < th; ty++) { + for (int tx = 0; tx < tw; tx++) { + uint8_t max = 0, min = 255; + + for (int dy = -1; dy <= 1; dy++) { + if (ty+dy < 0 || ty+dy >= th) + continue; + for (int dx = -1; dx <= 1; dx++) { + if (tx+dx < 0 || tx+dx >= tw) + continue; + + uint8_t m = im_max[(ty+dy)*tw+tx+dx]; + if (m > max) + max = m; + m = im_min[(ty+dy)*tw+tx+dx]; + if (m < min) + min = m; + } + } + + im_max_tmp[ty*tw + tx] = max; + im_min_tmp[ty*tw + tx] = min; + } + } + free(im_max); + free(im_min); + im_max = im_max_tmp; + im_min = im_min_tmp; + + for (int ty = 0; ty < th; ty++) { + for (int tx = 0; tx < tw; tx++) { + + int min_ = im_min[ty*tw + tx]; + int max_ = im_max[ty*tw + tx]; + + // low contrast region? (no edges) + if (max_ - min_ < parameters->aprilTagMinWhiteBlackDiff) { + for (int dy = 0; dy < tilesz; dy++) { + int y = ty*tilesz + dy; + + for (int dx = 0; dx < tilesz; dx++) { + int x = tx*tilesz + dx; + + //threshim->buf[y*s+x] = 127; + mThresh.data[y*s+x] = 127; + } + } + continue; + } + + // otherwise, actually threshold this tile. + + // argument for biasing towards dark; specular highlights + // can be substantially brighter than white tag parts + uint8_t thresh = saturate_cast((max_ + min_) / 2); + + for (int dy = 0; dy < tilesz; dy++) { + int y = ty*tilesz + dy; + + for (int dx = 0; dx < tilesz; dx++) { + int x = tx*tilesz + dx; + + uint8_t v = mIm.data[y*s+x]; + mThresh.data[y*s+x] = (v > thresh) ? 255 : 0; + } + } + } + } + + // we skipped over the non-full-sized tiles above. Fix those now. + for (int y = 0; y < h; y++) { + + // what is the first x coordinate we need to process in this row? + + int x0; + + if (y >= th*tilesz) { + x0 = 0; // we're at the bottom; do the whole row. + } else { + x0 = tw*tilesz; // we only need to do the right most part. + } + + // compute tile coordinates and clamp. + int ty = y / tilesz; + if (ty >= th) + ty = th - 1; + + for (int x = x0; x < w; x++) { + int tx = x / tilesz; + if (tx >= tw) + tx = tw - 1; + + int max = im_max[ty*tw + tx]; + int min = im_min[ty*tw + tx]; + int thresh = min + (max - min) / 2; + + uint8_t v = mIm.data[y*s+x]; + if (v > thresh){ + mThresh.data[y*s+x] = 255; + } + else{ + mThresh.data[y*s+x] = 0; + } + } + } + free(im_min); + free(im_max); + + // this is a dilate/erode deglitching scheme that does not improve + // anything as far as I can tell. + if (parameters->aprilTagDeglitch) { + Mat tmp(h,w, mIm.type()); + for (int y = 1; y + 1 < h; y++) { + for (int x = 1; x + 1 < w; x++) { + uint8_t max = 0; + for (int dy = -1; dy <= 1; dy++) { + for (int dx = -1; dx <= 1; dx++) { + uint8_t v = mThresh.data[(y+dy)*s + x + dx]; + if (v > max) + max = v; + } + } + tmp.data[y*s+x] = max; + } + } + + for (int y = 1; y + 1 < h; y++) { + for (int x = 1; x + 1 < w; x++) { + uint8_t min = 255; + for (int dy = -1; dy <= 1; dy++) { + for (int dx = -1; dx <= 1; dx++) { + uint8_t v = tmp.data[(y+dy)*s + x + dx]; + if (v < min) + min = v; + } + } + mThresh.data[y*s+x] = min; + } + } + } + +} + +#ifdef APRIL_DEBUG +static void _darken(const Mat &im){ + for (int y = 0; y < im.rows; y++) { + for (int x = 0; x < im.cols; x++) { + im.data[im.cols*y+x] /= 2; + } + } +} +#endif + +/** + * + * @param parameters + * @param mImg + * @param contours + * @return + */ +zarray_t *apriltag_quad_thresh(const Ptr ¶meters, const Mat & mImg, std::vector< std::vector< Point > > &contours){ + + //////////////////////////////////////////////////////// + // step 1. threshold the image, creating the edge image. + + int w = mImg.cols, h = mImg.rows; + + Mat thold(h, w, mImg.type()); + threshold(mImg, parameters, thold); + + int ts = thold.cols; + +#ifdef APRIL_DEBUG + imwrite("2.2 debug_threshold.pnm", thold); +#endif + + //////////////////////////////////////////////////////// + // step 2. find connected components. + + unionfind_t *uf = unionfind_create(w * h); + + // TODO PARALLELIZE + for (int y = 0; y < h - 1; y++) { + do_unionfind_line(uf, thold, w, ts, y); + } + + // XXX sizing?? + int nclustermap = 2*w*h - 1; + + struct uint64_zarray_entry **clustermap = (struct uint64_zarray_entry**)calloc(nclustermap, sizeof(struct uint64_zarray_entry*)); + + for (int y = 1; y < h-1; y++) { + for (int x = 1; x < w-1; x++) { + + uint8_t v0 = thold.data[y*ts + x]; + if (v0 == 127) + continue; + + // XXX don't query this until we know we need it? + uint64_t rep0 = unionfind_get_representative(uf, y*w + x); + + // whenever we find two adjacent pixels such that one is + // white and the other black, we add the point half-way + // between them to a cluster associated with the unique + // ids of the white and black regions. + // + // We additionally compute the gradient direction (i.e., which + // direction was the white pixel?) Note: if (v1-v0) == 255, then + // (dx,dy) points towards the white pixel. if (v1-v0) == -255, then + // (dx,dy) points towards the black pixel. p.gx and p.gy will thus + // be -255, 0, or 255. + // + // Note that any given pixel might be added to multiple + // different clusters. But in the common case, a given + // pixel will be added multiple times to the same cluster, + // which increases the size of the cluster and thus the + // computational costs. + // + // A possible optimization would be to combine entries + // within the same cluster. + +#define DO_CONN(dx, dy) \ + if (1) { \ + uint8_t v1 = thold.data[y*ts + dy*ts + x + dx]; \ + \ + if (v0 + v1 == 255) { \ + uint64_t rep1 = unionfind_get_representative(uf, y*w + dy*w + x + dx); \ + uint64_t clusterid; \ + if (rep0 < rep1) \ + clusterid = (rep1 << 32) + rep0; \ + else \ + clusterid = (rep0 << 32) + rep1; \ + \ + /* XXX lousy hash function */ \ + uint32_t clustermap_bucket = u64hash_2(clusterid) % nclustermap; \ + struct uint64_zarray_entry *entry = clustermap[clustermap_bucket]; \ + while (entry && entry->id != clusterid) { \ + entry = entry->next; \ + } \ + \ + if (!entry) { \ + entry = (struct uint64_zarray_entry*)calloc(1, sizeof(struct uint64_zarray_entry)); \ + entry->id = clusterid; \ + entry->cluster = _zarray_create(sizeof(struct pt)); \ + entry->next = clustermap[clustermap_bucket]; \ + clustermap[clustermap_bucket] = entry; \ + } \ + \ + struct pt p; \ + p.x = saturate_cast(2*x + dx); \ + p.y = saturate_cast(2*y + dy); \ + p.gx = saturate_cast(dx*((int) v1-v0)); \ + p.gy = saturate_cast(dy*((int) v1-v0)); \ + _zarray_add(entry->cluster, &p); \ + } \ + } + + // do 4 connectivity. NB: Arguments must be [-1, 1] or we'll overflow .gx, .gy + DO_CONN(1, 0); + DO_CONN(0, 1); + + // do 8 connectivity + DO_CONN(-1, 1); + DO_CONN(1, 1); +} +} +#undef DO_CONN + +#ifdef APRIL_DEBUG +Mat out = Mat::zeros(h, w, CV_8UC3); + +uint32_t *colors = (uint32_t*) calloc(w*h, sizeof(*colors)); + +for (int y = 0; y < h; y++) { + for (int x = 0; x < w; x++) { + uint32_t v = unionfind_get_representative(uf, y*w+x); + + if (unionfind_get_set_size(uf, v) < parameters->aprilTagMinClusterPixels) + continue; + + uint32_t color = colors[v]; + uint8_t r = color >> 16, + g = color >> 8, + b = color; + + if (color == 0) { + const int bias = 50; + r = bias + (random() % (200-bias)); + g = bias + (random() % (200-bias)); + b = bias + (random() % (200-bias)); + colors[v] = (r << 16) | (g << 8) | b; + } + out.at(y, x)[0]=b; + out.at(y, x)[1]=g; + out.at(y, x)[2]=r; + } +} +free(colors); +imwrite("2.3 debug_segmentation.pnm", out); +out = Mat::zeros(h, w, CV_8UC3); +#endif + + //////////////////////////////////////////////////////// + // step 3. process each connected component. + zarray_t *clusters = _zarray_create(sizeof(zarray_t*)); //, uint64_zarray_hash_size(clustermap)); + CV_Assert(clusters != NULL); + + for (int i = 0; i < nclustermap; i++) { + for (struct uint64_zarray_entry *entry = clustermap[i]; entry; entry = entry->next) { + // XXX reject clusters here? + _zarray_add(clusters, &entry->cluster); + } + } + +#ifdef APRIL_DEBUG +for (int i = 0; i < _zarray_size(clusters); i++) { + zarray_t *cluster; + _zarray_get(clusters, i, &cluster); + + uint32_t r, g, b; + + const int bias = 50; + r = bias + (random() % (200-bias)); + g = bias + (random() % (200-bias)); + b = bias + (random() % (200-bias)); + + for (int j = 0; j < _zarray_size(cluster); j++) { + struct pt *p; + _zarray_get_volatile(cluster, j, &p); + + int x = p->x / 2; + int y = p->y / 2; + out.at(y, x)[0]=b; + out.at(y, x)[1]=g; + out.at(y, x)[2]=r; + } +} + +imwrite("2.4 debug_clusters.pnm", out); +out = Mat::zeros(h, w, CV_8UC3); +#endif + + for (int i = 0; i < _zarray_size(clusters); i++) { + zarray_t *cluster; + _zarray_get(clusters, i, &cluster); + + std::vector< Point > cnt; + for (int j = 0; j < _zarray_size(cluster); j++) { + struct pt *p; + _zarray_get_volatile(cluster, j, &p); + + Point pnt(p->x, p->y); + cnt.push_back(pnt); + } + contours.push_back(cnt); + } + + for (int i = 0; i < nclustermap; i++) { + struct uint64_zarray_entry *entry = clustermap[i]; + while (entry) { + struct uint64_zarray_entry *tmp = entry->next; + free(entry); + entry = tmp; + } + } + free(clustermap); + + zarray_t *quads = _zarray_create(sizeof(struct sQuad)); + + //int chunksize = 1 + sz / (APRILTAG_TASKS_PER_THREAD_TARGET * numberOfThreads); + int chunksize = h / (10 * getNumThreads()); + int sz = _zarray_size(clusters); + + // TODO PARALLELIZE + for (int i = 0; i < sz; i += chunksize) { + int min = sz < (i+chunksize)? sz: (i+chunksize); + do_quad(i, min, *clusters, w, h, quads, parameters, mImg); + } + +#ifdef APRIL_DEBUG +mImg.copyTo(out); +_darken(out); +_darken(out); +srandom(0); + +for (int i = 0; i < _zarray_size(quads); i++) { + struct sQuad *quad; + _zarray_get_volatile(quads, i, &quad); + + float rgb[3]; + int bias = 100; + + for (int i = 0; i < 3; i++) + rgb[i] = bias + (random() % (255-bias)); + + line(out, Point(quad->p[0][0], quad->p[0][1]), Point(quad->p[1][0], quad->p[1][1]), rgb[i]); + line(out, Point(quad->p[1][0], quad->p[1][1]), Point(quad->p[2][0], quad->p[2][1]), rgb[i]); + line(out, Point(quad->p[2][0], quad->p[2][1]), Point(quad->p[3][0], quad->p[3][1]), rgb[i]); + line(out, Point(quad->p[3][0], quad->p[3][1]), Point(quad->p[0][0], quad->p[0][1]), rgb[i]); +} +imwrite("2.5 debug_lines.pnm", out); +#endif + + unionfind_destroy(uf); + + for (int i = 0; i < _zarray_size(clusters); i++) { + zarray_t *cluster; + _zarray_get(clusters, i, &cluster); + _zarray_destroy(cluster); + } + _zarray_destroy(clusters); + return quads; +} + +}} diff --git a/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.hpp b/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.hpp new file mode 100644 index 00000000..fd392c84 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/apriltag_quad_thresh.hpp @@ -0,0 +1,125 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. + +// limitation: image size must be <32768 in width and height. This is +// because we use a fixed-point 16 bit integer representation with one +// fractional bit. + +#ifndef _OPENCV_APRIL_QUAD_THRESH_HPP_ +#define _OPENCV_APRIL_QUAD_THRESH_HPP_ + +#include "opencv2/aruco.hpp" +#include "unionfind.hpp" +#include "zmaxheap.hpp" +#include "zarray.hpp" + +namespace cv { +namespace aruco { + +static inline uint32_t u64hash_2(uint64_t x) { + return uint32_t((2654435761UL * x) >> 32); +} + +struct uint64_zarray_entry{ + uint64_t id; + zarray_t *cluster; + + struct uint64_zarray_entry *next; +}; + +struct pt{ + // Note: these represent 2*actual value. + uint16_t x, y; + float theta; + int16_t gx, gy; +}; + +struct remove_vertex{ + int i; // which vertex to remove? + int left, right; // left vertex, right vertex + + double err; +}; + +struct segment{ + int is_vertex; + + // always greater than zero, but right can be > size, which denotes + // a wrap around back to the beginning of the points. and left < right. + int left, right; +}; + +struct line_fit_pt{ + double Mx, My; + double Mxx, Myy, Mxy; + double W; // total weight +}; + +/** + * lfps contains *cumulative* moments for N points, with + * index j reflecting points [0,j] (inclusive). + * fit a line to the points [i0, i1] (inclusive). i0, i1 are both (0, sz) + * if i1 < i0, we treat this as a wrap around. + */ +void fit_line(struct line_fit_pt *lfps, int sz, int i0, int i1, double *lineparm, double *err, double *mse); + +int err_compare_descending(const void *_a, const void *_b); + +/** + 1. Identify A) white points near a black point and B) black points near a white point. + + 2. Find the connected components within each of the classes above, + yielding clusters of "white-near-black" and + "black-near-white". (These two classes are kept separate). Each + segment has a unique id. + + 3. For every pair of "white-near-black" and "black-near-white" + clusters, find the set of points that are in one and adjacent to the + other. In other words, a "boundary" layer between the two + clusters. (This is actually performed by iterating over the pixels, + rather than pairs of clusters.) Critically, this helps keep nearby + edges from becoming connected. + **/ +int quad_segment_maxima(const Ptr &td, int sz, struct line_fit_pt *lfps, int indices[4]); + +/** + * returns 0 if the cluster looks bad. + */ +int quad_segment_agg(int sz, struct line_fit_pt *lfps, int indices[4]); + +/** + * return 1 if the quad looks okay, 0 if it should be discarded + * quad + **/ +int fit_quad(const Ptr &_params, const Mat im, zarray_t *cluster, struct sQuad *quad); + +/** + * + * @param mIm + * @param parameters + * @param mThresh + */ +void threshold(const Mat mIm, const Ptr ¶meters, Mat& mThresh); + +/** + * + * @param parameters + * @param mImg + * @param contours + * @return + */ +zarray_t *apriltag_quad_thresh(const Ptr ¶meters, const Mat & mImg, std::vector< std::vector< Point > > &contours); + +}} +#endif diff --git a/aruco_pose/vendor/aruco/src/aruco.cpp b/aruco_pose/vendor/aruco/src/aruco.cpp new file mode 100644 index 00000000..dfbff73e --- /dev/null +++ b/aruco_pose/vendor/aruco/src/aruco.cpp @@ -0,0 +1,1916 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#include "precomp.hpp" +#include "opencv2/aruco.hpp" +#include +#include + +#include "apriltag_quad_thresh.hpp" +#include "zarray.hpp" + +//#define APRIL_DEBUG +#ifdef APRIL_DEBUG +#include "opencv2/imgcodecs.hpp" +#endif + +namespace cv { +namespace aruco { + +using namespace std; + + +/** + * + */ +DetectorParameters::DetectorParameters() + : adaptiveThreshWinSizeMin(3), + adaptiveThreshWinSizeMax(23), + adaptiveThreshWinSizeStep(10), + adaptiveThreshConstant(7), + minMarkerPerimeterRate(0.03), + maxMarkerPerimeterRate(4.), + polygonalApproxAccuracyRate(0.03), + minCornerDistanceRate(0.05), + minDistanceToBorder(3), + minMarkerDistanceRate(0.05), + cornerRefinementMethod(CORNER_REFINE_NONE), + cornerRefinementWinSize(5), + cornerRefinementMaxIterations(30), + cornerRefinementMinAccuracy(0.1), + markerBorderBits(1), + perspectiveRemovePixelPerCell(4), + perspectiveRemoveIgnoredMarginPerCell(0.13), + maxErroneousBitsInBorderRate(0.35), + minOtsuStdDev(5.0), + errorCorrectionRate(0.6), + aprilTagQuadDecimate(0.0), + aprilTagQuadSigma(0.0), + aprilTagMinClusterPixels(5), + aprilTagMaxNmaxima(10), + aprilTagCriticalRad( (float)(10* CV_PI /180) ), + aprilTagMaxLineFitMse(10.0), + aprilTagMinWhiteBlackDiff(5), + aprilTagDeglitch(0), + detectInvertedMarker(false){} + + +/** + * @brief Create a new set of DetectorParameters with default values. + */ +Ptr DetectorParameters::create() { + Ptr params = makePtr(); + return params; +} + + +/** + * @brief Convert input image to gray if it is a 3-channels image + */ +static void _convertToGrey(InputArray _in, OutputArray _out) { + + CV_Assert(_in.type() == CV_8UC1 || _in.type() == CV_8UC3); + + if(_in.type() == CV_8UC3) + cvtColor(_in, _out, COLOR_BGR2GRAY); + else + _in.copyTo(_out); +} + + +/** + * @brief Threshold input image using adaptive thresholding + */ +static void _threshold(InputArray _in, OutputArray _out, int winSize, double constant) { + + CV_Assert(winSize >= 3); + if(winSize % 2 == 0) winSize++; // win size must be odd + adaptiveThreshold(_in, _out, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY_INV, winSize, constant); +} + + +/** + * @brief Given a tresholded image, find the contours, calculate their polygonal approximation + * and take those that accomplish some conditions + */ +static void _findMarkerContours(InputArray _in, vector< vector< Point2f > > &candidates, + vector< vector< Point > > &contoursOut, double minPerimeterRate, + double maxPerimeterRate, double accuracyRate, + double minCornerDistanceRate, int minDistanceToBorder) { + + CV_Assert(minPerimeterRate > 0 && maxPerimeterRate > 0 && accuracyRate > 0 && + minCornerDistanceRate >= 0 && minDistanceToBorder >= 0); + + // calculate maximum and minimum sizes in pixels + unsigned int minPerimeterPixels = + (unsigned int)(minPerimeterRate * max(_in.getMat().cols, _in.getMat().rows)); + unsigned int maxPerimeterPixels = + (unsigned int)(maxPerimeterRate * max(_in.getMat().cols, _in.getMat().rows)); + + Mat contoursImg; + _in.getMat().copyTo(contoursImg); + vector< vector< Point > > contours; + findContours(contoursImg, contours, RETR_LIST, CHAIN_APPROX_NONE); + // now filter list of contours + for(unsigned int i = 0; i < contours.size(); i++) { + // check perimeter + if(contours[i].size() < minPerimeterPixels || contours[i].size() > maxPerimeterPixels) + continue; + + // check is square and is convex + vector< Point > approxCurve; + approxPolyDP(contours[i], approxCurve, double(contours[i].size()) * accuracyRate, true); + if(approxCurve.size() != 4 || !isContourConvex(approxCurve)) continue; + + // check min distance between corners + double minDistSq = + max(contoursImg.cols, contoursImg.rows) * max(contoursImg.cols, contoursImg.rows); + for(int j = 0; j < 4; j++) { + double d = (double)(approxCurve[j].x - approxCurve[(j + 1) % 4].x) * + (double)(approxCurve[j].x - approxCurve[(j + 1) % 4].x) + + (double)(approxCurve[j].y - approxCurve[(j + 1) % 4].y) * + (double)(approxCurve[j].y - approxCurve[(j + 1) % 4].y); + minDistSq = min(minDistSq, d); + } + double minCornerDistancePixels = double(contours[i].size()) * minCornerDistanceRate; + if(minDistSq < minCornerDistancePixels * minCornerDistancePixels) continue; + + // check if it is too near to the image border + bool tooNearBorder = false; + for(int j = 0; j < 4; j++) { + if(approxCurve[j].x < minDistanceToBorder || approxCurve[j].y < minDistanceToBorder || + approxCurve[j].x > contoursImg.cols - 1 - minDistanceToBorder || + approxCurve[j].y > contoursImg.rows - 1 - minDistanceToBorder) + tooNearBorder = true; + } + if(tooNearBorder) continue; + + // if it passes all the test, add to candidates vector + vector< Point2f > currentCandidate; + currentCandidate.resize(4); + for(int j = 0; j < 4; j++) { + currentCandidate[j] = Point2f((float)approxCurve[j].x, (float)approxCurve[j].y); + } + candidates.push_back(currentCandidate); + contoursOut.push_back(contours[i]); + } +} + + +/** + * @brief Assure order of candidate corners is clockwise direction + */ +static void _reorderCandidatesCorners(vector< vector< Point2f > > &candidates) { + + for(unsigned int i = 0; i < candidates.size(); i++) { + double dx1 = candidates[i][1].x - candidates[i][0].x; + double dy1 = candidates[i][1].y - candidates[i][0].y; + double dx2 = candidates[i][2].x - candidates[i][0].x; + double dy2 = candidates[i][2].y - candidates[i][0].y; + double crossProduct = (dx1 * dy2) - (dy1 * dx2); + + if(crossProduct < 0.0) { // not clockwise direction + swap(candidates[i][1], candidates[i][3]); + } + } +} + + +/** + * @brief Check candidates that are too close to each other and remove the smaller one + */ +static void _filterTooCloseCandidates(const vector< vector< Point2f > > &candidatesIn, + vector< vector< Point2f > > &candidatesOut, + const vector< vector< Point > > &contoursIn, + vector< vector< Point > > &contoursOut, + double minMarkerDistanceRate) { + + CV_Assert(minMarkerDistanceRate >= 0); + + vector< pair< int, int > > nearCandidates; + for(unsigned int i = 0; i < candidatesIn.size(); i++) { + for(unsigned int j = i + 1; j < candidatesIn.size(); j++) { + + int minimumPerimeter = min((int)contoursIn[i].size(), (int)contoursIn[j].size() ); + + // fc is the first corner considered on one of the markers, 4 combinations are possible + for(int fc = 0; fc < 4; fc++) { + double distSq = 0; + for(int c = 0; c < 4; c++) { + // modC is the corner considering first corner is fc + int modC = (c + fc) % 4; + distSq += (candidatesIn[i][modC].x - candidatesIn[j][c].x) * + (candidatesIn[i][modC].x - candidatesIn[j][c].x) + + (candidatesIn[i][modC].y - candidatesIn[j][c].y) * + (candidatesIn[i][modC].y - candidatesIn[j][c].y); + } + distSq /= 4.; + + // if mean square distance is too low, remove the smaller one of the two markers + double minMarkerDistancePixels = double(minimumPerimeter) * minMarkerDistanceRate; + if(distSq < minMarkerDistancePixels * minMarkerDistancePixels) { + nearCandidates.push_back(pair< int, int >(i, j)); + break; + } + } + } + } + + // mark smaller one in pairs to remove + vector< bool > toRemove(candidatesIn.size(), false); + for(unsigned int i = 0; i < nearCandidates.size(); i++) { + // if one of the marker has been already markerd to removed, dont need to do anything + if(toRemove[nearCandidates[i].first] || toRemove[nearCandidates[i].second]) continue; + size_t perimeter1 = contoursIn[nearCandidates[i].first].size(); + size_t perimeter2 = contoursIn[nearCandidates[i].second].size(); + if(perimeter1 > perimeter2) + toRemove[nearCandidates[i].second] = true; + else + toRemove[nearCandidates[i].first] = true; + } + + // remove extra candidates + candidatesOut.clear(); + unsigned long totalRemaining = 0; + for(unsigned int i = 0; i < toRemove.size(); i++) + if(!toRemove[i]) totalRemaining++; + candidatesOut.resize(totalRemaining); + contoursOut.resize(totalRemaining); + for(unsigned int i = 0, currIdx = 0; i < candidatesIn.size(); i++) { + if(toRemove[i]) continue; + candidatesOut[currIdx] = candidatesIn[i]; + contoursOut[currIdx] = contoursIn[i]; + currIdx++; + } +} + + +/** + * ParallelLoopBody class for the parallelization of the basic candidate detections using + * different threhold window sizes. Called from function _detectInitialCandidates() + */ +class DetectInitialCandidatesParallel : public ParallelLoopBody { + public: + DetectInitialCandidatesParallel(const Mat *_grey, + vector< vector< vector< Point2f > > > *_candidatesArrays, + vector< vector< vector< Point > > > *_contoursArrays, + const Ptr &_params) + : grey(_grey), candidatesArrays(_candidatesArrays), contoursArrays(_contoursArrays), + params(_params) {} + + void operator()(const Range &range) const CV_OVERRIDE { + const int begin = range.start; + const int end = range.end; + + for(int i = begin; i < end; i++) { + int currScale = + params->adaptiveThreshWinSizeMin + i * params->adaptiveThreshWinSizeStep; + // threshold + Mat thresh; + _threshold(*grey, thresh, currScale, params->adaptiveThreshConstant); + + // detect rectangles + _findMarkerContours(thresh, (*candidatesArrays)[i], (*contoursArrays)[i], + params->minMarkerPerimeterRate, params->maxMarkerPerimeterRate, + params->polygonalApproxAccuracyRate, params->minCornerDistanceRate, + params->minDistanceToBorder); + } + } + + private: + DetectInitialCandidatesParallel &operator=(const DetectInitialCandidatesParallel &); + + const Mat *grey; + vector< vector< vector< Point2f > > > *candidatesArrays; + vector< vector< vector< Point > > > *contoursArrays; + const Ptr ¶ms; +}; + + +/** + * @brief Initial steps on finding square candidates + */ +static void _detectInitialCandidates(const Mat &grey, vector< vector< Point2f > > &candidates, + vector< vector< Point > > &contours, + const Ptr ¶ms) { + + CV_Assert(params->adaptiveThreshWinSizeMin >= 3 && params->adaptiveThreshWinSizeMax >= 3); + CV_Assert(params->adaptiveThreshWinSizeMax >= params->adaptiveThreshWinSizeMin); + CV_Assert(params->adaptiveThreshWinSizeStep > 0); + + // number of window sizes (scales) to apply adaptive thresholding + int nScales = (params->adaptiveThreshWinSizeMax - params->adaptiveThreshWinSizeMin) / + params->adaptiveThreshWinSizeStep + 1; + + vector< vector< vector< Point2f > > > candidatesArrays((size_t) nScales); + vector< vector< vector< Point > > > contoursArrays((size_t) nScales); + + ////for each value in the interval of thresholding window sizes + // for(int i = 0; i < nScales; i++) { + // int currScale = params.adaptiveThreshWinSizeMin + i*params.adaptiveThreshWinSizeStep; + // // treshold + // Mat thresh; + // _threshold(grey, thresh, currScale, params.adaptiveThreshConstant); + // // detect rectangles + // _findMarkerContours(thresh, candidatesArrays[i], contoursArrays[i], + // params.minMarkerPerimeterRate, + // params.maxMarkerPerimeterRate, params.polygonalApproxAccuracyRate, + // params.minCornerDistance, params.minDistanceToBorder); + //} + + // this is the parallel call for the previous commented loop (result is equivalent) + parallel_for_(Range(0, nScales), DetectInitialCandidatesParallel(&grey, &candidatesArrays, + &contoursArrays, params)); + + // join candidates + for(int i = 0; i < nScales; i++) { + for(unsigned int j = 0; j < candidatesArrays[i].size(); j++) { + candidates.push_back(candidatesArrays[i][j]); + contours.push_back(contoursArrays[i][j]); + } + } +} + + +/** + * @brief Detect square candidates in the input image + */ +static void _detectCandidates(InputArray _image, vector< vector< Point2f > >& candidatesOut, + vector< vector< Point > >& contoursOut, const Ptr &_params) { + + Mat image = _image.getMat(); + CV_Assert(image.total() != 0); + + /// 1. CONVERT TO GRAY + Mat grey; + _convertToGrey(image, grey); + + vector< vector< Point2f > > candidates; + vector< vector< Point > > contours; + /// 2. DETECT FIRST SET OF CANDIDATES + _detectInitialCandidates(grey, candidates, contours, _params); + + /// 3. SORT CORNERS + _reorderCandidatesCorners(candidates); + + /// 4. FILTER OUT NEAR CANDIDATE PAIRS + _filterTooCloseCandidates(candidates, candidatesOut, contours, contoursOut, + _params->minMarkerDistanceRate); +} + + +/** + * @brief Given an input image and candidate corners, extract the bits of the candidate, including + * the border bits + */ +static Mat _extractBits(InputArray _image, InputArray _corners, int markerSize, + int markerBorderBits, int cellSize, double cellMarginRate, + double minStdDevOtsu) { + + CV_Assert(_image.getMat().channels() == 1); + CV_Assert(_corners.total() == 4); + CV_Assert(markerBorderBits > 0 && cellSize > 0 && cellMarginRate >= 0 && cellMarginRate <= 1); + CV_Assert(minStdDevOtsu >= 0); + + // number of bits in the marker + int markerSizeWithBorders = markerSize + 2 * markerBorderBits; + int cellMarginPixels = int(cellMarginRate * cellSize); + + Mat resultImg; // marker image after removing perspective + int resultImgSize = markerSizeWithBorders * cellSize; + Mat resultImgCorners(4, 1, CV_32FC2); + resultImgCorners.ptr< Point2f >(0)[0] = Point2f(0, 0); + resultImgCorners.ptr< Point2f >(0)[1] = Point2f((float)resultImgSize - 1, 0); + resultImgCorners.ptr< Point2f >(0)[2] = + Point2f((float)resultImgSize - 1, (float)resultImgSize - 1); + resultImgCorners.ptr< Point2f >(0)[3] = Point2f(0, (float)resultImgSize - 1); + + // remove perspective + Mat transformation = getPerspectiveTransform(_corners, resultImgCorners); + warpPerspective(_image, resultImg, transformation, Size(resultImgSize, resultImgSize), + INTER_NEAREST); + + // output image containing the bits + Mat bits(markerSizeWithBorders, markerSizeWithBorders, CV_8UC1, Scalar::all(0)); + + // check if standard deviation is enough to apply Otsu + // if not enough, it probably means all bits are the same color (black or white) + Mat mean, stddev; + // Remove some border just to avoid border noise from perspective transformation + Mat innerRegion = resultImg.colRange(cellSize / 2, resultImg.cols - cellSize / 2) + .rowRange(cellSize / 2, resultImg.rows - cellSize / 2); + meanStdDev(innerRegion, mean, stddev); + if(stddev.ptr< double >(0)[0] < minStdDevOtsu) { + // all black or all white, depending on mean value + if(mean.ptr< double >(0)[0] > 127) + bits.setTo(1); + else + bits.setTo(0); + return bits; + } + + // now extract code, first threshold using Otsu + threshold(resultImg, resultImg, 125, 255, THRESH_BINARY | THRESH_OTSU); + + // for each cell + for(int y = 0; y < markerSizeWithBorders; y++) { + for(int x = 0; x < markerSizeWithBorders; x++) { + int Xstart = x * (cellSize) + cellMarginPixels; + int Ystart = y * (cellSize) + cellMarginPixels; + Mat square = resultImg(Rect(Xstart, Ystart, cellSize - 2 * cellMarginPixels, + cellSize - 2 * cellMarginPixels)); + // count white pixels on each cell to assign its value + size_t nZ = (size_t) countNonZero(square); + if(nZ > square.total() / 2) bits.at< unsigned char >(y, x) = 1; + } + } + + return bits; +} + + + +/** + * @brief Return number of erroneous bits in border, i.e. number of white bits in border. + */ +static int _getBorderErrors(const Mat &bits, int markerSize, int borderSize) { + + int sizeWithBorders = markerSize + 2 * borderSize; + + CV_Assert(markerSize > 0 && bits.cols == sizeWithBorders && bits.rows == sizeWithBorders); + + int totalErrors = 0; + for(int y = 0; y < sizeWithBorders; y++) { + for(int k = 0; k < borderSize; k++) { + if(bits.ptr< unsigned char >(y)[k] != 0) totalErrors++; + if(bits.ptr< unsigned char >(y)[sizeWithBorders - 1 - k] != 0) totalErrors++; + } + } + for(int x = borderSize; x < sizeWithBorders - borderSize; x++) { + for(int k = 0; k < borderSize; k++) { + if(bits.ptr< unsigned char >(k)[x] != 0) totalErrors++; + if(bits.ptr< unsigned char >(sizeWithBorders - 1 - k)[x] != 0) totalErrors++; + } + } + return totalErrors; +} + + +/** + * @brief Tries to identify one candidate given the dictionary + */ +static bool _identifyOneCandidate(const Ptr& dictionary, InputArray _image, + vector& _corners, int& idx, + const Ptr& params) +{ + CV_Assert(_corners.size() == 4); + CV_Assert(_image.getMat().total() != 0); + CV_Assert(params->markerBorderBits > 0); + + // get bits + Mat candidateBits = + _extractBits(_image, _corners, dictionary->markerSize, params->markerBorderBits, + params->perspectiveRemovePixelPerCell, + params->perspectiveRemoveIgnoredMarginPerCell, params->minOtsuStdDev); + + // analyze border bits + int maximumErrorsInBorder = + int(dictionary->markerSize * dictionary->markerSize * params->maxErroneousBitsInBorderRate); + int borderErrors = + _getBorderErrors(candidateBits, dictionary->markerSize, params->markerBorderBits); + + // check if it is a white marker + if(params->detectInvertedMarker){ + // to get from 255 to 1 + Mat invertedImg = ~candidateBits-254; + int invBError = _getBorderErrors(invertedImg, dictionary->markerSize, params->markerBorderBits); + // white marker + if(invBError maximumErrorsInBorder) return false; + + // take only inner bits + Mat onlyBits = + candidateBits.rowRange(params->markerBorderBits, + candidateBits.rows - params->markerBorderBits) + .colRange(params->markerBorderBits, candidateBits.rows - params->markerBorderBits); + + // try to indentify the marker + int rotation; + if(!dictionary->identify(onlyBits, idx, rotation, params->errorCorrectionRate)) + return false; + + // shift corner positions to the correct rotation + if(rotation != 0) { + std::rotate(_corners.begin(), _corners.begin() + 4 - rotation, _corners.end()); + } + return true; +} + + +/** + * ParallelLoopBody class for the parallelization of the marker identification step + * Called from function _identifyCandidates() + */ +class IdentifyCandidatesParallel : public ParallelLoopBody { + public: + IdentifyCandidatesParallel(const Mat& _grey, vector< vector< Point2f > >& _candidates, + const Ptr &_dictionary, + vector< int >& _idsTmp, vector< char >& _validCandidates, + const Ptr &_params) + : grey(_grey), candidates(_candidates), dictionary(_dictionary), + idsTmp(_idsTmp), validCandidates(_validCandidates), params(_params) {} + + void operator()(const Range &range) const CV_OVERRIDE { + const int begin = range.start; + const int end = range.end; + + for(int i = begin; i < end; i++) { + int currId; + if(_identifyOneCandidate(dictionary, grey, candidates[i], currId, params)) { + validCandidates[i] = 1; + idsTmp[i] = currId; + } + } + } + + private: + IdentifyCandidatesParallel &operator=(const IdentifyCandidatesParallel &); // to quiet MSVC + + const Mat &grey; + vector< vector< Point2f > >& candidates; + const Ptr &dictionary; + vector< int > &idsTmp; + vector< char > &validCandidates; + const Ptr ¶ms; +}; + + + +/** + * @brief Copy the contents of a corners vector to an OutputArray, settings its size. + */ +static void _copyVector2Output(vector< vector< Point2f > > &vec, OutputArrayOfArrays out) { + out.create((int)vec.size(), 1, CV_32FC2); + + if(out.isMatVector()) { + for (unsigned int i = 0; i < vec.size(); i++) { + out.create(4, 1, CV_32FC2, i); + Mat &m = out.getMatRef(i); + Mat(Mat(vec[i]).t()).copyTo(m); + } + } + else if(out.isUMatVector()) { + for (unsigned int i = 0; i < vec.size(); i++) { + out.create(4, 1, CV_32FC2, i); + UMat &m = out.getUMatRef(i); + Mat(Mat(vec[i]).t()).copyTo(m); + } + } + else if(out.kind() == _OutputArray::STD_VECTOR_VECTOR){ + for (unsigned int i = 0; i < vec.size(); i++) { + out.create(4, 1, CV_32FC2, i); + Mat m = out.getMat(i); + Mat(Mat(vec[i]).t()).copyTo(m); + } + } + else { + CV_Error(cv::Error::StsNotImplemented, + "Only Mat vector, UMat vector, and vector OutputArrays are currently supported."); + } +} + + + +/** + * @brief Identify square candidates according to a marker dictionary + */ +static void _identifyCandidates(InputArray _image, vector< vector< Point2f > >& _candidates, + vector< vector >& _contours, const Ptr &_dictionary, + vector< vector< Point2f > >& _accepted, vector< int >& ids, + const Ptr ¶ms, + OutputArrayOfArrays _rejected = noArray()) { + + int ncandidates = (int)_candidates.size(); + + vector< vector< Point2f > > accepted; + vector< vector< Point2f > > rejected; + + vector< vector< Point > > contours; + + CV_Assert(_image.getMat().total() != 0); + + Mat grey; + _convertToGrey(_image.getMat(), grey); + + vector< int > idsTmp(ncandidates, -1); + vector< char > validCandidates(ncandidates, 0); + + //// Analyze each of the candidates + // for (int i = 0; i < ncandidates; i++) { + // int currId = i; + // Mat currentCandidate = _candidates.getMat(i); + // if (_identifyOneCandidate(dictionary, grey, currentCandidate, currId, params)) { + // validCandidates[i] = 1; + // idsTmp[i] = currId; + // } + //} + + // this is the parallel call for the previous commented loop (result is equivalent) + parallel_for_(Range(0, ncandidates), + IdentifyCandidatesParallel(grey, _candidates, _dictionary, idsTmp, + validCandidates, params)); + + for(int i = 0; i < ncandidates; i++) { + if(validCandidates[i] == 1) { + accepted.push_back(_candidates[i]); + ids.push_back(idsTmp[i]); + + contours.push_back(_contours[i]); + + } else { + rejected.push_back(_candidates[i]); + } + } + + // parse output + _accepted = accepted; + + _contours= contours; + + if(_rejected.needed()) { + _copyVector2Output(rejected, _rejected); + } +} + + +/** + * @brief Final filter of markers after its identification + */ +static void _filterDetectedMarkers(vector< vector< Point2f > >& _corners, vector< int >& _ids, vector< vector< Point> >& _contours) { + + CV_Assert(_corners.size() == _ids.size()); + if(_corners.empty()) return; + + // mark markers that will be removed + vector< bool > toRemove(_corners.size(), false); + bool atLeastOneRemove = false; + + // remove repeated markers with same id, if one contains the other (doble border bug) + for(unsigned int i = 0; i < _corners.size() - 1; i++) { + for(unsigned int j = i + 1; j < _corners.size(); j++) { + if(_ids[i] != _ids[j]) continue; + + // check if first marker is inside second + bool inside = true; + for(unsigned int p = 0; p < 4; p++) { + Point2f point = _corners[j][p]; + if(pointPolygonTest(_corners[i], point, false) < 0) { + inside = false; + break; + } + } + if(inside) { + toRemove[j] = true; + atLeastOneRemove = true; + continue; + } + + // check the second marker + inside = true; + for(unsigned int p = 0; p < 4; p++) { + Point2f point = _corners[i][p]; + if(pointPolygonTest(_corners[j], point, false) < 0) { + inside = false; + break; + } + } + if(inside) { + toRemove[i] = true; + atLeastOneRemove = true; + continue; + } + } + } + + // parse output + if(atLeastOneRemove) { + vector< vector< Point2f > >::iterator filteredCorners = _corners.begin(); + vector< int >::iterator filteredIds = _ids.begin(); + + vector< vector< Point > >::iterator filteredContours = _contours.begin(); + + for(unsigned int i = 0; i < toRemove.size(); i++) { + if(!toRemove[i]) { + *filteredCorners++ = _corners[i]; + *filteredIds++ = _ids[i]; + + *filteredContours++ = _contours[i]; + } + } + + _ids.erase(filteredIds, _ids.end()); + _corners.erase(filteredCorners, _corners.end()); + + _contours.erase(filteredContours, _contours.end()); + } +} + + + +/** + * @brief Return object points for the system centered in a single marker, given the marker length + */ +static void _getSingleMarkerObjectPoints(float markerLength, OutputArray _objPoints) { + + CV_Assert(markerLength > 0); + + _objPoints.create(4, 1, CV_32FC3); + Mat objPoints = _objPoints.getMat(); + // set coordinate system in the middle of the marker, with Z pointing out + objPoints.ptr< Vec3f >(0)[0] = Vec3f(-markerLength / 2.f, markerLength / 2.f, 0); + objPoints.ptr< Vec3f >(0)[1] = Vec3f(markerLength / 2.f, markerLength / 2.f, 0); + objPoints.ptr< Vec3f >(0)[2] = Vec3f(markerLength / 2.f, -markerLength / 2.f, 0); + objPoints.ptr< Vec3f >(0)[3] = Vec3f(-markerLength / 2.f, -markerLength / 2.f, 0); +} + + + + +/** + * ParallelLoopBody class for the parallelization of the marker corner subpixel refinement + * Called from function detectMarkers() + */ +class MarkerSubpixelParallel : public ParallelLoopBody { + public: + MarkerSubpixelParallel(const Mat *_grey, OutputArrayOfArrays _corners, + const Ptr &_params) + : grey(_grey), corners(_corners), params(_params) {} + + void operator()(const Range &range) const CV_OVERRIDE { + const int begin = range.start; + const int end = range.end; + + for(int i = begin; i < end; i++) { + cornerSubPix(*grey, corners.getMat(i), + Size(params->cornerRefinementWinSize, params->cornerRefinementWinSize), + Size(-1, -1), TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS, + params->cornerRefinementMaxIterations, + params->cornerRefinementMinAccuracy)); + } + } + + private: + MarkerSubpixelParallel &operator=(const MarkerSubpixelParallel &); // to quiet MSVC + + const Mat *grey; + OutputArrayOfArrays corners; + const Ptr ¶ms; +}; + +/** + * Line fitting A * B = C :: Called from function refineCandidateLines + * @param nContours, contour-container + */ +static Point3f _interpolate2Dline(const std::vector& nContours){ + float minX, minY, maxX, maxY; + minX = maxX = nContours[0].x; + minY = maxY = nContours[0].y; + + for(unsigned int i = 0; i< nContours.size(); i++){ + minX = nContours[i].x < minX ? nContours[i].x : minX; + minY = nContours[i].y < minY ? nContours[i].y : minY; + maxX = nContours[i].x > maxX ? nContours[i].x : maxX; + maxY = nContours[i].y > maxY ? nContours[i].y : maxY; + } + + Mat A = Mat::ones((int)nContours.size(), 2, CV_32F); // Coefficient Matrix (N x 2) + Mat B((int)nContours.size(), 1, CV_32F); // Variables Matrix (N x 1) + Mat C; // Constant + + if(maxX - minX > maxY - minY){ + for(unsigned int i =0; i < nContours.size(); i++){ + A.at(i,0)= nContours[i].x; + B.at(i,0)= nContours[i].y; + } + + solve(A, B, C, DECOMP_NORMAL); + + return Point3f(C.at(0, 0), -1., C.at(1, 0)); + } + else{ + for(unsigned int i =0; i < nContours.size(); i++){ + A.at(i,0)= nContours[i].y; + B.at(i,0)= nContours[i].x; + } + + solve(A, B, C, DECOMP_NORMAL); + + return Point3f(-1., C.at(0, 0), C.at(1, 0)); + } + +} + +/** + * Find the Point where the lines crosses :: Called from function refineCandidateLines + * @param nLine1 + * @param nLine2 + * @return Crossed Point + */ +static Point2f _getCrossPoint(Point3f nLine1, Point3f nLine2){ + Matx22f A(nLine1.x, nLine1.y, nLine2.x, nLine2.y); + Vec2f B(-nLine1.z, -nLine2.z); + return Vec2f(A.solve(B).val); +} + +static void _distortPoints(vector& in, const Mat& camMatrix, const Mat& distCoeff) { + // trivial extrinsics + Matx31f Rvec(0,0,0); + Matx31f Tvec(0,0,0); + + // calculate 3d points and then reproject, so opencv makes the distortion internally + vector cornersPoints3d; + for (unsigned int i = 0; i < in.size(); i++){ + float x= (in[i].x - float(camMatrix.at(0, 2))) / float(camMatrix.at(0, 0)); + float y= (in[i].y - float(camMatrix.at(1, 2))) / float(camMatrix.at(1, 1)); + cornersPoints3d.push_back(Point3f(x,y,1)); + } + cv::projectPoints(cornersPoints3d, Rvec, Tvec, camMatrix, distCoeff, in); +} + +/** + * Refine Corners using the contour vector :: Called from function detectMarkers + * @param nContours, contour-container + * @param nCorners, candidate Corners + * @param camMatrix, cameraMatrix input 3x3 floating-point camera matrix + * @param distCoeff, distCoeffs vector of distortion coefficient + */ +static void _refineCandidateLines(std::vector& nContours, std::vector& nCorners, const Mat& camMatrix, const Mat& distCoeff){ + vector contour2f(nContours.begin(), nContours.end()); + + if(!camMatrix.empty() && !distCoeff.empty()){ + undistortPoints(contour2f, contour2f, camMatrix, distCoeff); + } + + /* 5 groups :: to group the edges + * 4 - classified by its corner + * extra group - (temporary) if contours do not begin with a corner + */ + vector cntPts[5]; + int cornerIndex[4]={-1}; + int group=4; + + for ( unsigned int i =0; i < nContours.size(); i++ ) { + for(unsigned int j=0; j<4; j++){ + if ( nCorners[j] == contour2f[i] ){ + cornerIndex[j] = i; + group=j; + } + } + cntPts[group].push_back(contour2f[i]); + } + + // saves extra group into corresponding + if( !cntPts[4].empty() ){ + for( unsigned int i=0; i < cntPts[4].size() ; i++ ) + cntPts[group].push_back(cntPts[4].at(i)); + cntPts[4].clear(); + } + + //Evaluate contour direction :: using the position of the detected corners + int inc=1; + + inc = ( (cornerIndex[0] > cornerIndex[1]) && (cornerIndex[3] > cornerIndex[0]) ) ? -1:inc; + inc = ( (cornerIndex[2] > cornerIndex[3]) && (cornerIndex[1] > cornerIndex[2]) ) ? -1:inc; + + // calculate the line :: who passes through the grouped points + Point3f lines[4]; + for(int i=0; i<4; i++){ + lines[i]=_interpolate2Dline(cntPts[i]); + } + + /* + * calculate the corner :: where the lines crosses to each other + * clockwise direction no clockwise direction + * 0 1 + * .---. 1 .---. 2 + * | | | | + * 3 .___. 0 .___. + * 2 3 + */ + for(int i=0; i < 4; i++){ + if(inc<0) + nCorners[i] = _getCrossPoint(lines[ i ], lines[ (i+1)%4 ]); // 01 12 23 30 + else + nCorners[i] = _getCrossPoint(lines[ i ], lines[ (i+3)%4 ]); // 30 01 12 23 + } + + if(!camMatrix.empty() && !distCoeff.empty()){ + _distortPoints(nCorners, camMatrix, distCoeff); + } +} + + +/** + * ParallelLoopBody class for the parallelization of the marker corner contour refinement + * Called from function detectMarkers() + */ +class MarkerContourParallel : public ParallelLoopBody { + public: + MarkerContourParallel( vector< vector< Point > >& _contours, vector< vector< Point2f > >& _candidates, const Mat& _camMatrix, const Mat& _distCoeff) + : contours(_contours), candidates(_candidates), camMatrix(_camMatrix), distCoeff(_distCoeff){} + + void operator()(const Range &range) const CV_OVERRIDE { + + for(int i = range.start; i < range.end; i++) { + _refineCandidateLines(contours[i], candidates[i], camMatrix, distCoeff); + } + } + + private: + MarkerContourParallel &operator=(const MarkerContourParallel &){ + return *this; + } + + vector< vector< Point > >& contours; + vector< vector< Point2f > >& candidates; + const Mat& camMatrix; + const Mat& distCoeff; +}; + +#ifdef APRIL_DEBUG +static void _darken(const Mat &im){ + for (int y = 0; y < im.rows; y++) { + for (int x = 0; x < im.cols; x++) { + im.data[im.cols*y+x] /= 2; + } + } +} +#endif + +/** + * + * @param im_orig + * @param _params + * @param candidates + * @param contours + */ +static void _apriltag(Mat im_orig, const Ptr & _params, std::vector< std::vector< Point2f > > &candidates, + std::vector< std::vector< Point > > &contours){ + + /////////////////////////////////////////////////////////// + /// Step 1. Detect quads according to requested image decimation + /// and blurring parameters. + Mat quad_im; + im_orig.copyTo(quad_im); + + if (_params->aprilTagQuadDecimate > 1){ + resize(im_orig, quad_im, Size(), 1/_params->aprilTagQuadDecimate, 1/_params->aprilTagQuadDecimate, INTER_AREA ); + } + + // Apply a Blur + if (_params->aprilTagQuadSigma != 0) { + // compute a reasonable kernel width by figuring that the + // kernel should go out 2 std devs. + // + // max sigma ksz + // 0.499 1 (disabled) + // 0.999 3 + // 1.499 5 + // 1.999 7 + + float sigma = fabsf((float) _params->aprilTagQuadSigma); + + int ksz = cvFloor(4 * sigma); // 2 std devs in each direction + ksz |= 1; // make odd number + + if (ksz > 1) { + if (_params->aprilTagQuadSigma > 0) + GaussianBlur(quad_im, quad_im, Size(ksz, ksz), sigma, sigma, BORDER_REPLICATE); + else { + Mat orig; + quad_im.copyTo(orig); + GaussianBlur(quad_im, quad_im, Size(ksz, ksz), sigma, sigma, BORDER_REPLICATE); + + // SHARPEN the image by subtracting the low frequency components. + for (int y = 0; y < orig.rows; y++) { + for (int x = 0; x < orig.cols; x++) { + int vorig = orig.data[y*orig.step + x]; + int vblur = quad_im.data[y*quad_im.step + x]; + + int v = 2*vorig - vblur; + if (v < 0) + v = 0; + if (v > 255) + v = 255; + + quad_im.data[y*quad_im.step + x] = (uint8_t) v; + } + } + } + } + } + +#ifdef APRIL_DEBUG + imwrite("1.1 debug_preprocess.pnm", quad_im); +#endif + + /////////////////////////////////////////////////////////// + /// Step 2. do the Threshold :: get the set of candidate quads + zarray_t *quads = apriltag_quad_thresh(_params, quad_im, contours); + + CV_Assert(quads != NULL); + + // adjust centers of pixels so that they correspond to the + // original full-resolution image. + if (_params->aprilTagQuadDecimate > 1) { + for (int i = 0; i < _zarray_size(quads); i++) { + struct sQuad *q; + _zarray_get_volatile(quads, i, &q); + for (int j = 0; j < 4; j++) { + q->p[j][0] *= _params->aprilTagQuadDecimate; + q->p[j][1] *= _params->aprilTagQuadDecimate; + } + } + } + +#ifdef APRIL_DEBUG + Mat im_quads = im_orig.clone(); + im_quads = im_quads*0.5; + srandom(0); + + for (int i = 0; i < _zarray_size(quads); i++) { + struct sQuad *quad; + _zarray_get_volatile(quads, i, &quad); + + const int bias = 100; + int color = bias + (random() % (255-bias)); + + line(im_quads, Point(quad->p[0][0], quad->p[0][1]), Point(quad->p[1][0], quad->p[1][1]), color, 1); + line(im_quads, Point(quad->p[1][0], quad->p[1][1]), Point(quad->p[2][0], quad->p[2][1]), color, 1); + line(im_quads, Point(quad->p[2][0], quad->p[2][1]), Point(quad->p[3][0], quad->p[3][1]), color, 1); + line(im_quads, Point(quad->p[3][0], quad->p[3][1]), Point(quad->p[0][0], quad->p[0][1]), color, 1); + } + imwrite("1.2 debug_quads_raw.pnm", im_quads); +#endif + + //////////////////////////////////////////////////////////////// + /// Step 3. Save the output :: candidate corners + for (int i = 0; i < _zarray_size(quads); i++) { + struct sQuad *quad; + _zarray_get_volatile(quads, i, &quad); + + std::vector< Point2f > corners; + corners.push_back(Point2f(quad->p[3][0], quad->p[3][1])); //pA + corners.push_back(Point2f(quad->p[0][0], quad->p[0][1])); //pB + corners.push_back(Point2f(quad->p[1][0], quad->p[1][1])); //pC + corners.push_back(Point2f(quad->p[2][0], quad->p[2][1])); //pD + + candidates.push_back(corners); + } + + _zarray_destroy(quads); +} + + +/** + */ +void detectMarkers(InputArray _image, const Ptr &_dictionary, OutputArrayOfArrays _corners, + OutputArray _ids, const Ptr &_params, + OutputArrayOfArrays _rejectedImgPoints, InputArrayOfArrays camMatrix, InputArrayOfArrays distCoeff) { + + CV_Assert(!_image.empty()); + + Mat grey; + _convertToGrey(_image.getMat(), grey); + + /// STEP 1: Detect marker candidates + vector< vector< Point2f > > candidates; + vector< vector< Point > > contours; + vector< int > ids; + + /// STEP 1.a Detect marker candidates :: using AprilTag + if(_params->cornerRefinementMethod == CORNER_REFINE_APRILTAG) + _apriltag(grey, _params, candidates, contours); + + /// STEP 1.b Detect marker candidates :: traditional way + else + _detectCandidates(grey, candidates, contours, _params); + + /// STEP 2: Check candidate codification (identify markers) + _identifyCandidates(grey, candidates, contours, _dictionary, candidates, ids, _params, + _rejectedImgPoints); + + /// STEP 3: Filter detected markers; + _filterDetectedMarkers(candidates, ids, contours); + + // copy to output arrays + _copyVector2Output(candidates, _corners); + Mat(ids).copyTo(_ids); + + /// STEP 4: Corner refinement :: use corner subpix + if( _params->cornerRefinementMethod == CORNER_REFINE_SUBPIX ) { + CV_Assert(_params->cornerRefinementWinSize > 0 && _params->cornerRefinementMaxIterations > 0 && + _params->cornerRefinementMinAccuracy > 0); + + //// do corner refinement for each of the detected markers + // for (unsigned int i = 0; i < _corners.cols(); i++) { + // cornerSubPix(grey, _corners.getMat(i), + // Size(params.cornerRefinementWinSize, params.cornerRefinementWinSize), + // Size(-1, -1), TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS, + // params.cornerRefinementMaxIterations, + // params.cornerRefinementMinAccuracy)); + //} + + // this is the parallel call for the previous commented loop (result is equivalent) + parallel_for_(Range(0, _corners.cols()), + MarkerSubpixelParallel(&grey, _corners, _params)); + } + + /// STEP 4, Optional : Corner refinement :: use contour container + if( _params->cornerRefinementMethod == CORNER_REFINE_CONTOUR){ + + if(! _ids.empty()){ + + // do corner refinement using the contours for each detected markers + parallel_for_(Range(0, _corners.cols()), MarkerContourParallel(contours, candidates, camMatrix.getMat(), distCoeff.getMat())); + + // copy the corners to the output array + _copyVector2Output(candidates, _corners); + } + } +} + + + +/** + * ParallelLoopBody class for the parallelization of the single markers pose estimation + * Called from function estimatePoseSingleMarkers() + */ +class SinglePoseEstimationParallel : public ParallelLoopBody { + public: + SinglePoseEstimationParallel(Mat& _markerObjPoints, InputArrayOfArrays _corners, + InputArray _cameraMatrix, InputArray _distCoeffs, + Mat& _rvecs, Mat& _tvecs) + : markerObjPoints(_markerObjPoints), corners(_corners), cameraMatrix(_cameraMatrix), + distCoeffs(_distCoeffs), rvecs(_rvecs), tvecs(_tvecs) {} + + void operator()(const Range &range) const CV_OVERRIDE { + const int begin = range.start; + const int end = range.end; + + for(int i = begin; i < end; i++) { + solvePnP(markerObjPoints, corners.getMat(i), cameraMatrix, distCoeffs, + rvecs.at(i), tvecs.at(i)); + } + } + + private: + SinglePoseEstimationParallel &operator=(const SinglePoseEstimationParallel &); // to quiet MSVC + + Mat& markerObjPoints; + InputArrayOfArrays corners; + InputArray cameraMatrix, distCoeffs; + Mat& rvecs, tvecs; +}; + + + + +/** + */ +void estimatePoseSingleMarkers(InputArrayOfArrays _corners, float markerLength, + InputArray _cameraMatrix, InputArray _distCoeffs, + OutputArray _rvecs, OutputArray _tvecs, OutputArray _objPoints) { + + CV_Assert(markerLength > 0); + + Mat markerObjPoints; + _getSingleMarkerObjectPoints(markerLength, markerObjPoints); + int nMarkers = (int)_corners.total(); + _rvecs.create(nMarkers, 1, CV_64FC3); + _tvecs.create(nMarkers, 1, CV_64FC3); + + Mat rvecs = _rvecs.getMat(), tvecs = _tvecs.getMat(); + + //// for each marker, calculate its pose + // for (int i = 0; i < nMarkers; i++) { + // solvePnP(markerObjPoints, _corners.getMat(i), _cameraMatrix, _distCoeffs, + // _rvecs.getMat(i), _tvecs.getMat(i)); + //} + + // this is the parallel call for the previous commented loop (result is equivalent) + parallel_for_(Range(0, nMarkers), + SinglePoseEstimationParallel(markerObjPoints, _corners, _cameraMatrix, + _distCoeffs, rvecs, tvecs)); + if(_objPoints.needed()){ + markerObjPoints.convertTo(_objPoints, -1); + } +} + + + +void getBoardObjectAndImagePoints(const Ptr &board, InputArrayOfArrays detectedCorners, + InputArray detectedIds, OutputArray objPoints, OutputArray imgPoints) { + + CV_Assert(board->ids.size() == board->objPoints.size()); + CV_Assert(detectedIds.total() == detectedCorners.total()); + + size_t nDetectedMarkers = detectedIds.total(); + + vector< Point3f > objPnts; + objPnts.reserve(nDetectedMarkers); + + vector< Point2f > imgPnts; + imgPnts.reserve(nDetectedMarkers); + + // look for detected markers that belong to the board and get their information + for(unsigned int i = 0; i < nDetectedMarkers; i++) { + int currentId = detectedIds.getMat().ptr< int >(0)[i]; + for(unsigned int j = 0; j < board->ids.size(); j++) { + if(currentId == board->ids[j]) { + for(int p = 0; p < 4; p++) { + objPnts.push_back(board->objPoints[j][p]); + imgPnts.push_back(detectedCorners.getMat(i).ptr< Point2f >(0)[p]); + } + } + } + } + + // create output + Mat(objPnts).copyTo(objPoints); + Mat(imgPnts).copyTo(imgPoints); +} + + + +/** + * Project board markers that are not included in the list of detected markers + */ +static void _projectUndetectedMarkers(const Ptr &_board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, InputArray _cameraMatrix, + InputArray _distCoeffs, + vector< vector< Point2f > >& _undetectedMarkersProjectedCorners, + OutputArray _undetectedMarkersIds) { + + // first estimate board pose with the current avaible markers + Mat rvec, tvec; + int boardDetectedMarkers; + boardDetectedMarkers = aruco::estimatePoseBoard(_detectedCorners, _detectedIds, _board, + _cameraMatrix, _distCoeffs, rvec, tvec); + + // at least one marker from board so rvec and tvec are valid + if(boardDetectedMarkers == 0) return; + + // search undetected markers and project them using the previous pose + vector< vector< Point2f > > undetectedCorners; + vector< int > undetectedIds; + for(unsigned int i = 0; i < _board->ids.size(); i++) { + int foundIdx = -1; + for(unsigned int j = 0; j < _detectedIds.total(); j++) { + if(_board->ids[i] == _detectedIds.getMat().ptr< int >()[j]) { + foundIdx = j; + break; + } + } + + // not detected + if(foundIdx == -1) { + undetectedCorners.push_back(vector< Point2f >()); + undetectedIds.push_back(_board->ids[i]); + projectPoints(_board->objPoints[i], rvec, tvec, _cameraMatrix, _distCoeffs, + undetectedCorners.back()); + } + } + + + // parse output + Mat(undetectedIds).copyTo(_undetectedMarkersIds); + _undetectedMarkersProjectedCorners = undetectedCorners; +} + + + +/** + * Interpolate board markers that are not included in the list of detected markers using + * global homography + */ +static void _projectUndetectedMarkers(const Ptr &_board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, + vector< vector< Point2f > >& _undetectedMarkersProjectedCorners, + OutputArray _undetectedMarkersIds) { + + + // check board points are in the same plane, if not, global homography cannot be applied + CV_Assert(_board->objPoints.size() > 0); + CV_Assert(_board->objPoints[0].size() > 0); + float boardZ = _board->objPoints[0][0].z; + for(unsigned int i = 0; i < _board->objPoints.size(); i++) { + for(unsigned int j = 0; j < _board->objPoints[i].size(); j++) { + CV_Assert(boardZ == _board->objPoints[i][j].z); + } + } + + vector< Point2f > detectedMarkersObj2DAll; // Object coordinates (without Z) of all the detected + // marker corners in a single vector + vector< Point2f > imageCornersAll; // Image corners of all detected markers in a single vector + vector< vector< Point2f > > undetectedMarkersObj2D; // Object coordinates (without Z) of all + // missing markers in different vectors + vector< int > undetectedMarkersIds; // ids of missing markers + // find markers included in board, and missing markers from board. Fill the previous vectors + for(unsigned int j = 0; j < _board->ids.size(); j++) { + bool found = false; + for(unsigned int i = 0; i < _detectedIds.total(); i++) { + if(_detectedIds.getMat().ptr< int >()[i] == _board->ids[j]) { + for(int c = 0; c < 4; c++) { + imageCornersAll.push_back(_detectedCorners.getMat(i).ptr< Point2f >()[c]); + detectedMarkersObj2DAll.push_back( + Point2f(_board->objPoints[j][c].x, _board->objPoints[j][c].y)); + } + found = true; + break; + } + } + if(!found) { + undetectedMarkersObj2D.push_back(vector< Point2f >()); + for(int c = 0; c < 4; c++) { + undetectedMarkersObj2D.back().push_back( + Point2f(_board->objPoints[j][c].x, _board->objPoints[j][c].y)); + } + undetectedMarkersIds.push_back(_board->ids[j]); + } + } + if(imageCornersAll.size() == 0) return; + + // get homography from detected markers + Mat transformation = findHomography(detectedMarkersObj2DAll, imageCornersAll); + + _undetectedMarkersProjectedCorners.resize(undetectedMarkersIds.size()); + + // for each undetected marker, apply transformation + for(unsigned int i = 0; i < undetectedMarkersObj2D.size(); i++) { + perspectiveTransform(undetectedMarkersObj2D[i], _undetectedMarkersProjectedCorners[i], transformation); + } + + Mat(undetectedMarkersIds).copyTo(_undetectedMarkersIds); +} + + + +/** + */ +void refineDetectedMarkers(InputArray _image, const Ptr &_board, + InputOutputArrayOfArrays _detectedCorners, InputOutputArray _detectedIds, + InputOutputArrayOfArrays _rejectedCorners, InputArray _cameraMatrix, + InputArray _distCoeffs, float minRepDistance, float errorCorrectionRate, + bool checkAllOrders, OutputArray _recoveredIdxs, + const Ptr &_params) { + + CV_Assert(minRepDistance > 0); + + if(_detectedIds.total() == 0 || _rejectedCorners.total() == 0) return; + + DetectorParameters ¶ms = *_params; + + // get projections of missing markers in the board + vector< vector< Point2f > > undetectedMarkersCorners; + vector< int > undetectedMarkersIds; + if(_cameraMatrix.total() != 0) { + // reproject based on camera projection model + _projectUndetectedMarkers(_board, _detectedCorners, _detectedIds, _cameraMatrix, _distCoeffs, + undetectedMarkersCorners, undetectedMarkersIds); + + } else { + // reproject based on global homography + _projectUndetectedMarkers(_board, _detectedCorners, _detectedIds, undetectedMarkersCorners, + undetectedMarkersIds); + } + + // list of missing markers indicating if they have been assigned to a candidate + vector< bool > alreadyIdentified(_rejectedCorners.total(), false); + + // maximum bits that can be corrected + Dictionary &dictionary = *(_board->dictionary); + int maxCorrectionRecalculated = + int(double(dictionary.maxCorrectionBits) * errorCorrectionRate); + + Mat grey; + _convertToGrey(_image, grey); + + // vector of final detected marker corners and ids + vector< Mat > finalAcceptedCorners; + vector< int > finalAcceptedIds; + // fill with the current markers + finalAcceptedCorners.resize(_detectedCorners.total()); + finalAcceptedIds.resize(_detectedIds.total()); + for(unsigned int i = 0; i < _detectedIds.total(); i++) { + finalAcceptedCorners[i] = _detectedCorners.getMat(i).clone(); + finalAcceptedIds[i] = _detectedIds.getMat().ptr< int >()[i]; + } + vector< int > recoveredIdxs; // original indexes of accepted markers in _rejectedCorners + + // for each missing marker, try to find a correspondence + for(unsigned int i = 0; i < undetectedMarkersIds.size(); i++) { + + // best match at the moment + int closestCandidateIdx = -1; + double closestCandidateDistance = minRepDistance * minRepDistance + 1; + Mat closestRotatedMarker; + + for(unsigned int j = 0; j < _rejectedCorners.total(); j++) { + if(alreadyIdentified[j]) continue; + + // check distance + double minDistance = closestCandidateDistance + 1; + bool valid = false; + int validRot = 0; + for(int c = 0; c < 4; c++) { // first corner in rejected candidate + double currentMaxDistance = 0; + for(int k = 0; k < 4; k++) { + Point2f rejCorner = _rejectedCorners.getMat(j).ptr< Point2f >()[(c + k) % 4]; + Point2f distVector = undetectedMarkersCorners[i][k] - rejCorner; + double cornerDist = distVector.x * distVector.x + distVector.y * distVector.y; + currentMaxDistance = max(currentMaxDistance, cornerDist); + } + // if distance is better than current best distance + if(currentMaxDistance < closestCandidateDistance) { + valid = true; + validRot = c; + minDistance = currentMaxDistance; + } + if(!checkAllOrders) break; + } + + if(!valid) continue; + + // apply rotation + Mat rotatedMarker; + if(checkAllOrders) { + rotatedMarker = Mat(4, 1, CV_32FC2); + for(int c = 0; c < 4; c++) + rotatedMarker.ptr< Point2f >()[c] = + _rejectedCorners.getMat(j).ptr< Point2f >()[(c + 4 + validRot) % 4]; + } + else rotatedMarker = _rejectedCorners.getMat(j); + + // last filter, check if inner code is close enough to the assigned marker code + int codeDistance = 0; + // if errorCorrectionRate, dont check code + if(errorCorrectionRate >= 0) { + + // extract bits + Mat bits = _extractBits( + grey, rotatedMarker, dictionary.markerSize, params.markerBorderBits, + params.perspectiveRemovePixelPerCell, + params.perspectiveRemoveIgnoredMarginPerCell, params.minOtsuStdDev); + + Mat onlyBits = + bits.rowRange(params.markerBorderBits, bits.rows - params.markerBorderBits) + .colRange(params.markerBorderBits, bits.rows - params.markerBorderBits); + + codeDistance = + dictionary.getDistanceToId(onlyBits, undetectedMarkersIds[i], false); + } + + // if everythin is ok, assign values to current best match + if(errorCorrectionRate < 0 || codeDistance < maxCorrectionRecalculated) { + closestCandidateIdx = j; + closestCandidateDistance = minDistance; + closestRotatedMarker = rotatedMarker; + } + } + + // if at least one good match, we have rescue the missing marker + if(closestCandidateIdx >= 0) { + + // subpixel refinement + if(_params->cornerRefinementMethod == CORNER_REFINE_SUBPIX) { + CV_Assert(params.cornerRefinementWinSize > 0 && + params.cornerRefinementMaxIterations > 0 && + params.cornerRefinementMinAccuracy > 0); + cornerSubPix(grey, closestRotatedMarker, + Size(params.cornerRefinementWinSize, params.cornerRefinementWinSize), + Size(-1, -1), TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS, + params.cornerRefinementMaxIterations, + params.cornerRefinementMinAccuracy)); + } + + // remove from rejected + alreadyIdentified[closestCandidateIdx] = true; + + // add to detected + finalAcceptedCorners.push_back(closestRotatedMarker); + finalAcceptedIds.push_back(undetectedMarkersIds[i]); + + // add the original index of the candidate + recoveredIdxs.push_back(closestCandidateIdx); + } + } + + // parse output + if(finalAcceptedIds.size() != _detectedIds.total()) { + _detectedCorners.clear(); + _detectedIds.clear(); + + // parse output + Mat(finalAcceptedIds).copyTo(_detectedIds); + + _detectedCorners.create((int)finalAcceptedCorners.size(), 1, CV_32FC2); + for(unsigned int i = 0; i < finalAcceptedCorners.size(); i++) { + _detectedCorners.create(4, 1, CV_32FC2, i, true); + for(int j = 0; j < 4; j++) { + _detectedCorners.getMat(i).ptr< Point2f >()[j] = + finalAcceptedCorners[i].ptr< Point2f >()[j]; + } + } + + // recalculate _rejectedCorners based on alreadyIdentified + vector< Mat > finalRejected; + for(unsigned int i = 0; i < alreadyIdentified.size(); i++) { + if(!alreadyIdentified[i]) { + finalRejected.push_back(_rejectedCorners.getMat(i).clone()); + } + } + + _rejectedCorners.clear(); + _rejectedCorners.create((int)finalRejected.size(), 1, CV_32FC2); + for(unsigned int i = 0; i < finalRejected.size(); i++) { + _rejectedCorners.create(4, 1, CV_32FC2, i, true); + for(int j = 0; j < 4; j++) { + _rejectedCorners.getMat(i).ptr< Point2f >()[j] = + finalRejected[i].ptr< Point2f >()[j]; + } + } + + if(_recoveredIdxs.needed()) { + Mat(recoveredIdxs).copyTo(_recoveredIdxs); + } + } +} + + + + +/** + */ +int estimatePoseBoard(InputArrayOfArrays _corners, InputArray _ids, const Ptr &board, + InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, + OutputArray _tvec, bool useExtrinsicGuess) { + + CV_Assert(_corners.total() == _ids.total()); + + // get object and image points for the solvePnP function + Mat objPoints, imgPoints; + getBoardObjectAndImagePoints(board, _corners, _ids, objPoints, imgPoints); + + CV_Assert(imgPoints.total() == objPoints.total()); + + if(objPoints.total() == 0) // 0 of the detected markers in board + return 0; + + solvePnP(objPoints, imgPoints, _cameraMatrix, _distCoeffs, _rvec, _tvec, useExtrinsicGuess); + + // divide by four since all the four corners are concatenated in the array for each marker + return (int)objPoints.total() / 4; +} + + + + +/** + */ +void GridBoard::draw(Size outSize, OutputArray _img, int marginSize, int borderBits) { + _drawPlanarBoardImpl(this, outSize, _img, marginSize, borderBits); +} + + +/** +*/ +Ptr Board::create(InputArrayOfArrays objPoints, const Ptr &dictionary, InputArray ids) { + + CV_Assert(objPoints.total() == ids.total()); + CV_Assert(objPoints.type() == CV_32FC3 || objPoints.type() == CV_32FC1); + + std::vector< std::vector< Point3f > > obj_points_vector; + for (unsigned int i = 0; i < objPoints.total(); i++) { + std::vector corners; + Mat corners_mat = objPoints.getMat(i); + + if(corners_mat.type() == CV_32FC1) + corners_mat = corners_mat.reshape(3); + CV_Assert(corners_mat.total() == 4); + + for (int j = 0; j < 4; j++) { + corners.push_back(corners_mat.at(j)); + } + obj_points_vector.push_back(corners); + } + + Ptr res = makePtr(); + ids.copyTo(res->ids); + res->objPoints = obj_points_vector; + res->dictionary = cv::makePtr(dictionary); + return res; +} + +/** + */ +Ptr GridBoard::create(int markersX, int markersY, float markerLength, float markerSeparation, + const Ptr &dictionary, int firstMarker) { + + CV_Assert(markersX > 0 && markersY > 0 && markerLength > 0 && markerSeparation > 0); + + Ptr res = makePtr(); + + res->_markersX = markersX; + res->_markersY = markersY; + res->_markerLength = markerLength; + res->_markerSeparation = markerSeparation; + res->dictionary = dictionary; + + size_t totalMarkers = (size_t) markersX * markersY; + res->ids.resize(totalMarkers); + res->objPoints.reserve(totalMarkers); + + // fill ids with first identifiers + for(unsigned int i = 0; i < totalMarkers; i++) { + res->ids[i] = i + firstMarker; + } + + // calculate Board objPoints + float maxY = (float)markersY * markerLength + (markersY - 1) * markerSeparation; + for(int y = 0; y < markersY; y++) { + for(int x = 0; x < markersX; x++) { + vector< Point3f > corners; + corners.resize(4); + corners[0] = Point3f(x * (markerLength + markerSeparation), + maxY - y * (markerLength + markerSeparation), 0); + corners[1] = corners[0] + Point3f(markerLength, 0, 0); + corners[2] = corners[0] + Point3f(markerLength, -markerLength, 0); + corners[3] = corners[0] + Point3f(0, -markerLength, 0); + res->objPoints.push_back(corners); + } + } + + return res; +} + + + +/** + */ +void drawDetectedMarkers(InputOutputArray _image, InputArrayOfArrays _corners, + InputArray _ids, Scalar borderColor) { + + + CV_Assert(_image.getMat().total() != 0 && + (_image.getMat().channels() == 1 || _image.getMat().channels() == 3)); + CV_Assert((_corners.total() == _ids.total()) || _ids.total() == 0); + + // calculate colors + Scalar textColor, cornerColor; + textColor = cornerColor = borderColor; + swap(textColor.val[0], textColor.val[1]); // text color just sawp G and R + swap(cornerColor.val[1], cornerColor.val[2]); // corner color just sawp G and B + + int nMarkers = (int)_corners.total(); + for(int i = 0; i < nMarkers; i++) { + Mat currentMarker = _corners.getMat(i); + CV_Assert(currentMarker.total() == 4 && currentMarker.type() == CV_32FC2); + + // draw marker sides + for(int j = 0; j < 4; j++) { + Point2f p0, p1; + p0 = currentMarker.ptr< Point2f >(0)[j]; + p1 = currentMarker.ptr< Point2f >(0)[(j + 1) % 4]; + line(_image, p0, p1, borderColor, 1); + } + // draw first corner mark + rectangle(_image, currentMarker.ptr< Point2f >(0)[0] - Point2f(3, 3), + currentMarker.ptr< Point2f >(0)[0] + Point2f(3, 3), cornerColor, 1, LINE_AA); + + // draw ID + if(_ids.total() != 0) { + Point2f cent(0, 0); + for(int p = 0; p < 4; p++) + cent += currentMarker.ptr< Point2f >(0)[p]; + cent = cent / 4.; + stringstream s; + s << "id=" << _ids.getMat().ptr< int >(0)[i]; + putText(_image, s.str(), cent, FONT_HERSHEY_SIMPLEX, 0.5, textColor, 2); + } + } +} + + + +/** + */ +void drawAxis(InputOutputArray _image, InputArray _cameraMatrix, InputArray _distCoeffs, InputArray _rvec, + InputArray _tvec, float length) +{ + /* no-op since we're using our own _drawAxis routine */ + /*drawFrameAxes(_image, _cameraMatrix, _distCoeffs, _rvec, _tvec, length, 3);*/ +} + +/** + */ +void drawMarker(const Ptr &dictionary, int id, int sidePixels, OutputArray _img, int borderBits) { + dictionary->drawMarker(id, sidePixels, _img, borderBits); +} + + + +void _drawPlanarBoardImpl(Board *_board, Size outSize, OutputArray _img, int marginSize, + int borderBits) { + + /* NOTE: OpenCV v<3.3 does not have .empty() as a Size member */ + CV_Assert(outSize.height > 0 && outSize.width > 0); + CV_Assert(marginSize >= 0); + + _img.create(outSize, CV_8UC1); + Mat out = _img.getMat(); + out.setTo(Scalar::all(255)); + out.adjustROI(-marginSize, -marginSize, -marginSize, -marginSize); + + // calculate max and min values in XY plane + CV_Assert(_board->objPoints.size() > 0); + float minX, maxX, minY, maxY; + minX = maxX = _board->objPoints[0][0].x; + minY = maxY = _board->objPoints[0][0].y; + + for(unsigned int i = 0; i < _board->objPoints.size(); i++) { + for(int j = 0; j < 4; j++) { + minX = min(minX, _board->objPoints[i][j].x); + maxX = max(maxX, _board->objPoints[i][j].x); + minY = min(minY, _board->objPoints[i][j].y); + maxY = max(maxY, _board->objPoints[i][j].y); + } + } + + float sizeX = maxX - minX; + float sizeY = maxY - minY; + + // proportion transformations + float xReduction = sizeX / float(out.cols); + float yReduction = sizeY / float(out.rows); + + // determine the zone where the markers are placed + if(xReduction > yReduction) { + int nRows = int(sizeY / xReduction); + int rowsMargins = (out.rows - nRows) / 2; + out.adjustROI(-rowsMargins, -rowsMargins, 0, 0); + } else { + int nCols = int(sizeX / yReduction); + int colsMargins = (out.cols - nCols) / 2; + out.adjustROI(0, 0, -colsMargins, -colsMargins); + } + + // now paint each marker + Dictionary &dictionary = *(_board->dictionary); + Mat marker; + Point2f outCorners[3]; + Point2f inCorners[3]; + for(unsigned int m = 0; m < _board->objPoints.size(); m++) { + // transform corners to markerZone coordinates + for(int j = 0; j < 3; j++) { + Point2f pf = Point2f(_board->objPoints[m][j].x, _board->objPoints[m][j].y); + // move top left to 0, 0 + pf -= Point2f(minX, minY); + pf.x = pf.x / sizeX * float(out.cols); + pf.y = (1.0f - pf.y / sizeY) * float(out.rows); + outCorners[j] = pf; + } + + // get marker + Size dst_sz(outCorners[2] - outCorners[0]); // assuming CCW order + dst_sz.width = dst_sz.height = std::min(dst_sz.width, dst_sz.height); //marker should be square + dictionary.drawMarker(_board->ids[m], dst_sz.width, marker, borderBits); + + if((outCorners[0].y == outCorners[1].y) && (outCorners[1].x == outCorners[2].x)) { + // marker is aligned to image axes + marker.copyTo(out(Rect(outCorners[0], dst_sz))); + continue; + } + + // interpolate tiny marker to marker position in markerZone + inCorners[0] = Point2f(-0.5f, -0.5f); + inCorners[1] = Point2f(marker.cols - 0.5f, -0.5f); + inCorners[2] = Point2f(marker.cols - 0.5f, marker.rows - 0.5f); + + // remove perspective + Mat transformation = getAffineTransform(inCorners, outCorners); + warpAffine(marker, out, transformation, out.size(), INTER_LINEAR, + BORDER_TRANSPARENT); + } +} + + + +/** + */ +void drawPlanarBoard(const Ptr &_board, Size outSize, OutputArray _img, int marginSize, + int borderBits) { + _drawPlanarBoardImpl(_board, outSize, _img, marginSize, borderBits); +} + + + +/** + */ +double calibrateCameraAruco(InputArrayOfArrays _corners, InputArray _ids, InputArray _counter, + const Ptr &board, Size imageSize, InputOutputArray _cameraMatrix, + InputOutputArray _distCoeffs, OutputArrayOfArrays _rvecs, + OutputArrayOfArrays _tvecs, + OutputArray _stdDeviationsIntrinsics, + OutputArray _stdDeviationsExtrinsics, + OutputArray _perViewErrors, + int flags, TermCriteria criteria) { + + // for each frame, get properly processed imagePoints and objectPoints for the calibrateCamera + // function + vector< Mat > processedObjectPoints, processedImagePoints; + size_t nFrames = _counter.total(); + int markerCounter = 0; + for(size_t frame = 0; frame < nFrames; frame++) { + int nMarkersInThisFrame = _counter.getMat().ptr< int >()[frame]; + vector< Mat > thisFrameCorners; + vector< int > thisFrameIds; + + CV_Assert(nMarkersInThisFrame > 0); + + thisFrameCorners.reserve((size_t) nMarkersInThisFrame); + thisFrameIds.reserve((size_t) nMarkersInThisFrame); + for(int j = markerCounter; j < markerCounter + nMarkersInThisFrame; j++) { + thisFrameCorners.push_back(_corners.getMat(j)); + thisFrameIds.push_back(_ids.getMat().ptr< int >()[j]); + } + markerCounter += nMarkersInThisFrame; + Mat currentImgPoints, currentObjPoints; + getBoardObjectAndImagePoints(board, thisFrameCorners, thisFrameIds, currentObjPoints, + currentImgPoints); + if(currentImgPoints.total() > 0 && currentObjPoints.total() > 0) { + processedImagePoints.push_back(currentImgPoints); + processedObjectPoints.push_back(currentObjPoints); + } + } + + return calibrateCamera(processedObjectPoints, processedImagePoints, imageSize, _cameraMatrix, + _distCoeffs, _rvecs, _tvecs, _stdDeviationsIntrinsics, _stdDeviationsExtrinsics, + _perViewErrors, flags, criteria); +} + + + +/** + */ +double calibrateCameraAruco(InputArrayOfArrays _corners, InputArray _ids, InputArray _counter, + const Ptr &board, Size imageSize, InputOutputArray _cameraMatrix, + InputOutputArray _distCoeffs, OutputArrayOfArrays _rvecs, + OutputArrayOfArrays _tvecs, int flags, TermCriteria criteria) { + return calibrateCameraAruco(_corners, _ids, _counter, board, imageSize, _cameraMatrix, _distCoeffs, _rvecs, _tvecs, + noArray(), noArray(), noArray(), flags, criteria); +} + + + +} +} diff --git a/aruco_pose/vendor/aruco/src/charuco.cpp b/aruco_pose/vendor/aruco/src/charuco.cpp new file mode 100644 index 00000000..ec0323f0 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/charuco.cpp @@ -0,0 +1,934 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#include "precomp.hpp" +#include "opencv2/aruco/charuco.hpp" +#include +#include + + +namespace cv { +namespace aruco { + +using namespace std; + + + +/** + */ +void CharucoBoard::draw(Size outSize, OutputArray _img, int marginSize, int borderBits) { + + /* NOTE: OpenCV v<3.3 does not have .empty() as a Size member */ + CV_Assert(outSize.height > 0 && outSize.width > 0); + CV_Assert(marginSize >= 0); + + _img.create(outSize, CV_8UC1); + _img.setTo(255); + Mat out = _img.getMat(); + Mat noMarginsImg = + out.colRange(marginSize, out.cols - marginSize).rowRange(marginSize, out.rows - marginSize); + + double totalLengthX, totalLengthY; + totalLengthX = _squareLength * _squaresX; + totalLengthY = _squareLength * _squaresY; + + // proportional transformation + double xReduction = totalLengthX / double(noMarginsImg.cols); + double yReduction = totalLengthY / double(noMarginsImg.rows); + + // determine the zone where the chessboard is placed + Mat chessboardZoneImg; + if(xReduction > yReduction) { + int nRows = int(totalLengthY / xReduction); + int rowsMargins = (noMarginsImg.rows - nRows) / 2; + chessboardZoneImg = noMarginsImg.rowRange(rowsMargins, noMarginsImg.rows - rowsMargins); + } else { + int nCols = int(totalLengthX / yReduction); + int colsMargins = (noMarginsImg.cols - nCols) / 2; + chessboardZoneImg = noMarginsImg.colRange(colsMargins, noMarginsImg.cols - colsMargins); + } + + // determine the margins to draw only the markers + // take the minimum just to be sure + double squareSizePixels = min(double(chessboardZoneImg.cols) / double(_squaresX), + double(chessboardZoneImg.rows) / double(_squaresY)); + + double diffSquareMarkerLength = (_squareLength - _markerLength) / 2; + int diffSquareMarkerLengthPixels = + int(diffSquareMarkerLength * squareSizePixels / _squareLength); + + // draw markers + Mat markersImg; + aruco::_drawPlanarBoardImpl(this, chessboardZoneImg.size(), markersImg, + diffSquareMarkerLengthPixels, borderBits); + + markersImg.copyTo(chessboardZoneImg); + + // now draw black squares + for(int y = 0; y < _squaresY; y++) { + for(int x = 0; x < _squaresX; x++) { + + if(y % 2 != x % 2) continue; // white corner, dont do anything + + double startX, startY; + startX = squareSizePixels * double(x); + startY = double(chessboardZoneImg.rows) - squareSizePixels * double(y + 1); + + Mat squareZone = chessboardZoneImg.rowRange(int(startY), int(startY + squareSizePixels)) + .colRange(int(startX), int(startX + squareSizePixels)); + + squareZone.setTo(0); + } + } +} + + + +/** + */ +Ptr CharucoBoard::create(int squaresX, int squaresY, float squareLength, + float markerLength, const Ptr &dictionary) { + + CV_Assert(squaresX > 1 && squaresY > 1 && markerLength > 0 && squareLength > markerLength); + Ptr res = makePtr(); + + res->_squaresX = squaresX; + res->_squaresY = squaresY; + res->_squareLength = squareLength; + res->_markerLength = markerLength; + res->dictionary = dictionary; + + float diffSquareMarkerLength = (squareLength - markerLength) / 2; + + // calculate Board objPoints + for(int y = squaresY - 1; y >= 0; y--) { + for(int x = 0; x < squaresX; x++) { + + if(y % 2 == x % 2) continue; // black corner, no marker here + + vector< Point3f > corners; + corners.resize(4); + corners[0] = Point3f(x * squareLength + diffSquareMarkerLength, + y * squareLength + diffSquareMarkerLength + markerLength, 0); + corners[1] = corners[0] + Point3f(markerLength, 0, 0); + corners[2] = corners[0] + Point3f(markerLength, -markerLength, 0); + corners[3] = corners[0] + Point3f(0, -markerLength, 0); + res->objPoints.push_back(corners); + // first ids in dictionary + int nextId = (int)res->ids.size(); + res->ids.push_back(nextId); + } + } + + // now fill chessboardCorners + for(int y = 0; y < squaresY - 1; y++) { + for(int x = 0; x < squaresX - 1; x++) { + Point3f corner; + corner.x = (x + 1) * squareLength; + corner.y = (y + 1) * squareLength; + corner.z = 0; + res->chessboardCorners.push_back(corner); + } + } + + res->_getNearestMarkerCorners(); + + return res; +} + + + +/** + * Fill nearestMarkerIdx and nearestMarkerCorners arrays + */ +void CharucoBoard::_getNearestMarkerCorners() { + + nearestMarkerIdx.resize(chessboardCorners.size()); + nearestMarkerCorners.resize(chessboardCorners.size()); + + unsigned int nMarkers = (unsigned int)ids.size(); + unsigned int nCharucoCorners = (unsigned int)chessboardCorners.size(); + for(unsigned int i = 0; i < nCharucoCorners; i++) { + double minDist = -1; // distance of closest markers + Point3f charucoCorner = chessboardCorners[i]; + for(unsigned int j = 0; j < nMarkers; j++) { + // calculate distance from marker center to charuco corner + Point3f center = Point3f(0, 0, 0); + for(unsigned int k = 0; k < 4; k++) + center += objPoints[j][k]; + center /= 4.; + double sqDistance; + Point3f distVector = charucoCorner - center; + sqDistance = distVector.x * distVector.x + distVector.y * distVector.y; + if(j == 0 || fabs(sqDistance - minDist) < cv::pow(0.01 * _squareLength, 2)) { + // if same minimum distance (or first iteration), add to nearestMarkerIdx vector + nearestMarkerIdx[i].push_back(j); + minDist = sqDistance; + } else if(sqDistance < minDist) { + // if finding a closest marker to the charuco corner + nearestMarkerIdx[i].clear(); // remove any previous added marker + nearestMarkerIdx[i].push_back(j); // add the new closest marker index + minDist = sqDistance; + } + } + + // for each of the closest markers, search the marker corner index closer + // to the charuco corner + for(unsigned int j = 0; j < nearestMarkerIdx[i].size(); j++) { + nearestMarkerCorners[i].resize(nearestMarkerIdx[i].size()); + double minDistCorner = -1; + for(unsigned int k = 0; k < 4; k++) { + double sqDistance; + Point3f distVector = charucoCorner - objPoints[nearestMarkerIdx[i][j]][k]; + sqDistance = distVector.x * distVector.x + distVector.y * distVector.y; + if(k == 0 || sqDistance < minDistCorner) { + // if this corner is closer to the charuco corner, assing its index + // to nearestMarkerCorners + minDistCorner = sqDistance; + nearestMarkerCorners[i][j] = k; + } + } + } + } +} + + +/** + * Remove charuco corners if any of their minMarkers closest markers has not been detected + */ +static int _filterCornersWithoutMinMarkers(const Ptr &_board, + InputArray _allCharucoCorners, + InputArray _allCharucoIds, + InputArray _allArucoIds, int minMarkers, + OutputArray _filteredCharucoCorners, + OutputArray _filteredCharucoIds) { + + CV_Assert(minMarkers >= 0 && minMarkers <= 2); + + vector< Point2f > filteredCharucoCorners; + vector< int > filteredCharucoIds; + // for each charuco corner + for(unsigned int i = 0; i < _allCharucoIds.getMat().total(); i++) { + int currentCharucoId = _allCharucoIds.getMat().at< int >(i); + int totalMarkers = 0; // nomber of closest marker detected + // look for closest markers + for(unsigned int m = 0; m < _board->nearestMarkerIdx[currentCharucoId].size(); m++) { + int markerId = _board->ids[_board->nearestMarkerIdx[currentCharucoId][m]]; + bool found = false; + for(unsigned int k = 0; k < _allArucoIds.getMat().total(); k++) { + if(_allArucoIds.getMat().at< int >(k) == markerId) { + found = true; + break; + } + } + if(found) totalMarkers++; + } + // if enough markers detected, add the charuco corner to the final list + if(totalMarkers >= minMarkers) { + filteredCharucoIds.push_back(currentCharucoId); + filteredCharucoCorners.push_back(_allCharucoCorners.getMat().at< Point2f >(i)); + } + } + + // parse output + Mat(filteredCharucoCorners).copyTo(_filteredCharucoCorners); + Mat(filteredCharucoIds).copyTo(_filteredCharucoIds); + return (int)_filteredCharucoIds.total(); +} + + +/** + * ParallelLoopBody class for the parallelization of the charuco corners subpixel refinement + * Called from function _selectAndRefineChessboardCorners() + */ +class CharucoSubpixelParallel : public ParallelLoopBody { + public: + CharucoSubpixelParallel(const Mat *_grey, vector< Point2f > *_filteredChessboardImgPoints, + vector< Size > *_filteredWinSizes, const Ptr &_params) + : grey(_grey), filteredChessboardImgPoints(_filteredChessboardImgPoints), + filteredWinSizes(_filteredWinSizes), params(_params) {} + + void operator()(const Range &range) const CV_OVERRIDE { + const int begin = range.start; + const int end = range.end; + + for(int i = begin; i < end; i++) { + vector< Point2f > in; + in.push_back((*filteredChessboardImgPoints)[i]); + Size winSize = (*filteredWinSizes)[i]; + if(winSize.height == -1 || winSize.width == -1) + winSize = Size(params->cornerRefinementWinSize, params->cornerRefinementWinSize); + + cornerSubPix(*grey, in, winSize, Size(), + TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS, + params->cornerRefinementMaxIterations, + params->cornerRefinementMinAccuracy)); + + (*filteredChessboardImgPoints)[i] = in[0]; + } + } + + private: + CharucoSubpixelParallel &operator=(const CharucoSubpixelParallel &); // to quiet MSVC + + const Mat *grey; + vector< Point2f > *filteredChessboardImgPoints; + vector< Size > *filteredWinSizes; + const Ptr ¶ms; +}; + + + + +/** + * @brief From all projected chessboard corners, select those inside the image and apply subpixel + * refinement. Returns number of valid corners. + */ +static int _selectAndRefineChessboardCorners(InputArray _allCorners, InputArray _image, + OutputArray _selectedCorners, + OutputArray _selectedIds, + const vector< Size > &winSizes) { + + const int minDistToBorder = 2; // minimum distance of the corner to the image border + // remaining corners, ids and window refinement sizes after removing corners outside the image + vector< Point2f > filteredChessboardImgPoints; + vector< Size > filteredWinSizes; + vector< int > filteredIds; + + // filter corners outside the image + Rect innerRect(minDistToBorder, minDistToBorder, _image.getMat().cols - 2 * minDistToBorder, + _image.getMat().rows - 2 * minDistToBorder); + for(unsigned int i = 0; i < _allCorners.getMat().total(); i++) { + if(innerRect.contains(_allCorners.getMat().at< Point2f >(i))) { + filteredChessboardImgPoints.push_back(_allCorners.getMat().at< Point2f >(i)); + filteredIds.push_back(i); + filteredWinSizes.push_back(winSizes[i]); + } + } + + // if none valid, return 0 + if(filteredChessboardImgPoints.size() == 0) return 0; + + // corner refinement, first convert input image to grey + Mat grey; + if(_image.type() == CV_8UC3) + cvtColor(_image, grey, COLOR_BGR2GRAY); + else + _image.copyTo(grey); + + const Ptr params = DetectorParameters::create(); // use default params for corner refinement + + //// For each of the charuco corners, apply subpixel refinement using its correspondind winSize + // for(unsigned int i=0; i in; + // in.push_back(filteredChessboardImgPoints[i]); + // Size winSize = filteredWinSizes[i]; + // if(winSize.height == -1 || winSize.width == -1) + // winSize = Size(params.cornerRefinementWinSize, params.cornerRefinementWinSize); + // cornerSubPix(grey, in, winSize, Size(), + // TermCriteria(TermCriteria::MAX_ITER | TermCriteria::EPS, + // params->cornerRefinementMaxIterations, + // params->cornerRefinementMinAccuracy)); + // filteredChessboardImgPoints[i] = in[0]; + //} + + // this is the parallel call for the previous commented loop (result is equivalent) + parallel_for_( + Range(0, (int)filteredChessboardImgPoints.size()), + CharucoSubpixelParallel(&grey, &filteredChessboardImgPoints, &filteredWinSizes, params)); + + // parse output + Mat(filteredChessboardImgPoints).copyTo(_selectedCorners); + Mat(filteredIds).copyTo(_selectedIds); + return (int)filteredChessboardImgPoints.size(); +} + + +/** + * Calculate the maximum window sizes for corner refinement for each charuco corner based on the + * distance to their closest markers + */ +static void _getMaximumSubPixWindowSizes(InputArrayOfArrays markerCorners, InputArray markerIds, + InputArray charucoCorners, const Ptr &board, + vector< Size > &sizes) { + + unsigned int nCharucoCorners = (unsigned int)charucoCorners.getMat().total(); + sizes.resize(nCharucoCorners, Size(-1, -1)); + + for(unsigned int i = 0; i < nCharucoCorners; i++) { + if(charucoCorners.getMat().at< Point2f >(i) == Point2f(-1, -1)) continue; + if(board->nearestMarkerIdx[i].size() == 0) continue; + + double minDist = -1; + int counter = 0; + + // calculate the distance to each of the closest corner of each closest marker + for(unsigned int j = 0; j < board->nearestMarkerIdx[i].size(); j++) { + // find marker + int markerId = board->ids[board->nearestMarkerIdx[i][j]]; + int markerIdx = -1; + for(unsigned int k = 0; k < markerIds.getMat().total(); k++) { + if(markerIds.getMat().at< int >(k) == markerId) { + markerIdx = k; + break; + } + } + if(markerIdx == -1) continue; + Point2f markerCorner = + markerCorners.getMat(markerIdx).at< Point2f >(board->nearestMarkerCorners[i][j]); + Point2f charucoCorner = charucoCorners.getMat().at< Point2f >(i); + double dist = norm(markerCorner - charucoCorner); + if(minDist == -1) minDist = dist; // if first distance, just assign it + minDist = min(dist, minDist); + counter++; + } + + // if this is the first closest marker, dont do anything + if(counter == 0) + continue; + else { + // else, calculate the maximum window size + int winSizeInt = int(minDist - 2); // remove 2 pixels for safety + if(winSizeInt < 1) winSizeInt = 1; // minimum size is 1 + if(winSizeInt > 10) winSizeInt = 10; // maximum size is 10 + sizes[i] = Size(winSizeInt, winSizeInt); + } + } +} + + + +/** + * Interpolate charuco corners using approximated pose estimation + */ +static int _interpolateCornersCharucoApproxCalib(InputArrayOfArrays _markerCorners, + InputArray _markerIds, InputArray _image, + const Ptr &_board, + InputArray _cameraMatrix, InputArray _distCoeffs, + OutputArray _charucoCorners, + OutputArray _charucoIds) { + + CV_Assert(_image.getMat().channels() == 1 || _image.getMat().channels() == 3); + CV_Assert(_markerCorners.total() == _markerIds.getMat().total() && + _markerIds.getMat().total() > 0); + + // approximated pose estimation using marker corners + Mat approximatedRvec, approximatedTvec; + int detectedBoardMarkers; + Ptr _b = _board.staticCast(); + detectedBoardMarkers = + aruco::estimatePoseBoard(_markerCorners, _markerIds, _b, + _cameraMatrix, _distCoeffs, approximatedRvec, approximatedTvec); + + if(detectedBoardMarkers == 0) return 0; + + // project chessboard corners + vector< Point2f > allChessboardImgPoints; + + projectPoints(_board->chessboardCorners, approximatedRvec, approximatedTvec, _cameraMatrix, + _distCoeffs, allChessboardImgPoints); + + + // calculate maximum window sizes for subpixel refinement. The size is limited by the distance + // to the closes marker corner to avoid erroneous displacements to marker corners + vector< Size > subPixWinSizes; + _getMaximumSubPixWindowSizes(_markerCorners, _markerIds, allChessboardImgPoints, _board, + subPixWinSizes); + + // filter corners outside the image and subpixel-refine charuco corners + return _selectAndRefineChessboardCorners(allChessboardImgPoints, _image, _charucoCorners, + _charucoIds, subPixWinSizes); +} + + + +/** + * Interpolate charuco corners using local homography + */ +static int _interpolateCornersCharucoLocalHom(InputArrayOfArrays _markerCorners, + InputArray _markerIds, InputArray _image, + const Ptr &_board, + OutputArray _charucoCorners, + OutputArray _charucoIds) { + + CV_Assert(_image.getMat().channels() == 1 || _image.getMat().channels() == 3); + CV_Assert(_markerCorners.total() == _markerIds.getMat().total() && + _markerIds.getMat().total() > 0); + + unsigned int nMarkers = (unsigned int)_markerIds.getMat().total(); + + // calculate local homographies for each marker + vector< Mat > transformations; + transformations.resize(nMarkers); + for(unsigned int i = 0; i < nMarkers; i++) { + vector< Point2f > markerObjPoints2D; + int markerId = _markerIds.getMat().at< int >(i); + vector< int >::const_iterator it = find(_board->ids.begin(), _board->ids.end(), markerId); + if(it == _board->ids.end()) continue; + int boardIdx = (int)std::distance::const_iterator>(_board->ids.begin(), it); + markerObjPoints2D.resize(4); + for(unsigned int j = 0; j < 4; j++) + markerObjPoints2D[j] = + Point2f(_board->objPoints[boardIdx][j].x, _board->objPoints[boardIdx][j].y); + + transformations[i] = getPerspectiveTransform(markerObjPoints2D, _markerCorners.getMat(i)); + } + + unsigned int nCharucoCorners = (unsigned int)_board->chessboardCorners.size(); + vector< Point2f > allChessboardImgPoints(nCharucoCorners, Point2f(-1, -1)); + + // for each charuco corner, calculate its interpolation position based on the closest markers + // homographies + for(unsigned int i = 0; i < nCharucoCorners; i++) { + Point2f objPoint2D = Point2f(_board->chessboardCorners[i].x, _board->chessboardCorners[i].y); + + vector< Point2f > interpolatedPositions; + for(unsigned int j = 0; j < _board->nearestMarkerIdx[i].size(); j++) { + int markerId = _board->ids[_board->nearestMarkerIdx[i][j]]; + int markerIdx = -1; + for(unsigned int k = 0; k < _markerIds.getMat().total(); k++) { + if(_markerIds.getMat().at< int >(k) == markerId) { + markerIdx = k; + break; + } + } + if(markerIdx != -1) { + vector< Point2f > in, out; + in.push_back(objPoint2D); + perspectiveTransform(in, out, transformations[markerIdx]); + interpolatedPositions.push_back(out[0]); + } + } + + // none of the closest markers detected + if(interpolatedPositions.size() == 0) continue; + + // more than one closest marker detected, take middle point + if(interpolatedPositions.size() > 1) { + allChessboardImgPoints[i] = (interpolatedPositions[0] + interpolatedPositions[1]) / 2.; + } + // a single closest marker detected + else allChessboardImgPoints[i] = interpolatedPositions[0]; + } + + // calculate maximum window sizes for subpixel refinement. The size is limited by the distance + // to the closes marker corner to avoid erroneous displacements to marker corners + vector< Size > subPixWinSizes; + _getMaximumSubPixWindowSizes(_markerCorners, _markerIds, allChessboardImgPoints, _board, + subPixWinSizes); + + + // filter corners outside the image and subpixel-refine charuco corners + return _selectAndRefineChessboardCorners(allChessboardImgPoints, _image, _charucoCorners, + _charucoIds, subPixWinSizes); +} + + + +/** + */ +int interpolateCornersCharuco(InputArrayOfArrays _markerCorners, InputArray _markerIds, + InputArray _image, const Ptr &_board, + OutputArray _charucoCorners, OutputArray _charucoIds, + InputArray _cameraMatrix, InputArray _distCoeffs, int minMarkers) { + + // if camera parameters are avaible, use approximated calibration + if(_cameraMatrix.total() != 0) { + _interpolateCornersCharucoApproxCalib(_markerCorners, _markerIds, _image, _board, + _cameraMatrix, _distCoeffs, _charucoCorners, + _charucoIds); + } + // else use local homography + else { + _interpolateCornersCharucoLocalHom(_markerCorners, _markerIds, _image, _board, + _charucoCorners, _charucoIds); + } + + // to return a charuco corner, its closest aruco markers should have been detected + return _filterCornersWithoutMinMarkers(_board, _charucoCorners, _charucoIds, _markerIds, + minMarkers, _charucoCorners, _charucoIds); +} + + + +/** + */ +void drawDetectedCornersCharuco(InputOutputArray _image, InputArray _charucoCorners, + InputArray _charucoIds, Scalar cornerColor) { + + CV_Assert(_image.getMat().total() != 0 && + (_image.getMat().channels() == 1 || _image.getMat().channels() == 3)); + CV_Assert((_charucoCorners.getMat().total() == _charucoIds.getMat().total()) || + _charucoIds.getMat().total() == 0); + + unsigned int nCorners = (unsigned int)_charucoCorners.getMat().total(); + for(unsigned int i = 0; i < nCorners; i++) { + Point2f corner = _charucoCorners.getMat().at< Point2f >(i); + + // draw first corner mark + rectangle(_image, corner - Point2f(3, 3), corner + Point2f(3, 3), cornerColor, 1, LINE_AA); + + // draw ID + if(_charucoIds.total() != 0) { + int id = _charucoIds.getMat().at< int >(i); + stringstream s; + s << "id=" << id; + putText(_image, s.str(), corner + Point2f(5, -5), FONT_HERSHEY_SIMPLEX, 0.5, + cornerColor, 2); + } + } +} + + +/** + * Check if a set of 3d points are enough for calibration. Z coordinate is ignored. + * Only axis paralel lines are considered + */ +static bool _arePointsEnoughForPoseEstimation(const vector< Point3f > &points) { + + if(points.size() < 4) return false; + + vector< double > sameXValue; // different x values in points + vector< int > sameXCounter; // number of points with the x value in sameXValue + for(unsigned int i = 0; i < points.size(); i++) { + bool found = false; + for(unsigned int j = 0; j < sameXValue.size(); j++) { + if(sameXValue[j] == points[i].x) { + found = true; + sameXCounter[j]++; + } + } + if(!found) { + sameXValue.push_back(points[i].x); + sameXCounter.push_back(1); + } + } + + // count how many x values has more than 2 points + int moreThan2 = 0; + for(unsigned int i = 0; i < sameXCounter.size(); i++) { + if(sameXCounter[i] >= 2) moreThan2++; + } + + // if we have more than 1 two xvalues with more than 2 points, calibration is ok + if(moreThan2 > 1) + return true; + else + return false; +} + + +/** + */ +bool estimatePoseCharucoBoard(InputArray _charucoCorners, InputArray _charucoIds, + const Ptr &_board, InputArray _cameraMatrix, InputArray _distCoeffs, + OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess) { + + CV_Assert((_charucoCorners.getMat().total() == _charucoIds.getMat().total())); + + // need, at least, 4 corners + if(_charucoIds.getMat().total() < 4) return false; + + vector< Point3f > objPoints; + objPoints.reserve(_charucoIds.getMat().total()); + for(unsigned int i = 0; i < _charucoIds.getMat().total(); i++) { + int currId = _charucoIds.getMat().at< int >(i); + CV_Assert(currId >= 0 && currId < (int)_board->chessboardCorners.size()); + objPoints.push_back(_board->chessboardCorners[currId]); + } + + // points need to be in different lines, check if detected points are enough + if(!_arePointsEnoughForPoseEstimation(objPoints)) return false; + + solvePnP(objPoints, _charucoCorners, _cameraMatrix, _distCoeffs, _rvec, _tvec, useExtrinsicGuess); + + return true; +} + + + + +/** + */ +double calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds, + const Ptr &_board, Size imageSize, + InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, + OutputArray _stdDeviationsIntrinsics, + OutputArray _stdDeviationsExtrinsics, + OutputArray _perViewErrors, + int flags, TermCriteria criteria) { + + CV_Assert(_charucoIds.total() > 0 && (_charucoIds.total() == _charucoCorners.total())); + + // Join object points of charuco corners in a single vector for calibrateCamera() function + vector< vector< Point3f > > allObjPoints; + allObjPoints.resize(_charucoIds.total()); + for(unsigned int i = 0; i < _charucoIds.total(); i++) { + unsigned int nCorners = (unsigned int)_charucoIds.getMat(i).total(); + CV_Assert(nCorners > 0 && nCorners == _charucoCorners.getMat(i).total()); + allObjPoints[i].reserve(nCorners); + + for(unsigned int j = 0; j < nCorners; j++) { + int pointId = _charucoIds.getMat(i).at< int >(j); + CV_Assert(pointId >= 0 && pointId < (int)_board->chessboardCorners.size()); + allObjPoints[i].push_back(_board->chessboardCorners[pointId]); + } + } + + return calibrateCamera(allObjPoints, _charucoCorners, imageSize, _cameraMatrix, _distCoeffs, + _rvecs, _tvecs, _stdDeviationsIntrinsics, _stdDeviationsExtrinsics, + _perViewErrors, flags, criteria); +} + + + +/** + */ +double calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds, + const Ptr &_board, Size imageSize, + InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags, + TermCriteria criteria) { + return calibrateCameraCharuco(_charucoCorners, _charucoIds, _board, imageSize, _cameraMatrix, _distCoeffs, _rvecs, + _tvecs, noArray(), noArray(), noArray(), flags, criteria); +} + + +/** + */ +void detectCharucoDiamond(InputArray _image, InputArrayOfArrays _markerCorners, + InputArray _markerIds, float squareMarkerLengthRate, + OutputArrayOfArrays _diamondCorners, OutputArray _diamondIds, + InputArray _cameraMatrix, InputArray _distCoeffs) { + + CV_Assert(_markerIds.total() > 0 && _markerIds.total() == _markerCorners.total()); + + const float minRepDistanceRate = 1.302455f; + + // create Charuco board layout for diamond (3x3 layout) + Ptr dict = getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME(0)); + Ptr _charucoDiamondLayout = CharucoBoard::create(3, 3, squareMarkerLengthRate, 1., dict); + + + vector< vector< Point2f > > diamondCorners; + vector< Vec4i > diamondIds; + + // stores if the detected markers have been assigned or not to a diamond + vector< bool > assigned(_markerIds.total(), false); + if(_markerIds.total() < 4) return; // a diamond need at least 4 markers + + // convert input image to grey + Mat grey; + if(_image.type() == CV_8UC3) + cvtColor(_image, grey, COLOR_BGR2GRAY); + else + _image.copyTo(grey); + + // for each of the detected markers, try to find a diamond + for(unsigned int i = 0; i < _markerIds.total(); i++) { + if(assigned[i]) continue; + + // calculate marker perimeter + float perimeterSq = 0; + Mat corners = _markerCorners.getMat(i); + for(int c = 0; c < 4; c++) { + Point2f edge = corners.at< Point2f >(c) - corners.at< Point2f >((c + 1) % 4); + perimeterSq += edge.x*edge.x + edge.y*edge.y; + } + // maximum reprojection error relative to perimeter + float minRepDistance = sqrt(perimeterSq) * minRepDistanceRate; + + int currentId = _markerIds.getMat().at< int >(i); + + // prepare data to call refineDetectedMarkers() + // detected markers (only the current one) + vector< Mat > currentMarker; + vector< int > currentMarkerId; + currentMarker.push_back(_markerCorners.getMat(i)); + currentMarkerId.push_back(currentId); + + // marker candidates (the rest of markers if they have not been assigned) + vector< Mat > candidates; + vector< int > candidatesIdxs; + for(unsigned int k = 0; k < assigned.size(); k++) { + if(k == i) continue; + if(!assigned[k]) { + candidates.push_back(_markerCorners.getMat(k)); + candidatesIdxs.push_back(k); + } + } + if(candidates.size() < 3) break; // we need at least 3 free markers + + // modify charuco layout id to make sure all the ids are different than current id + for(int k = 1; k < 4; k++) + _charucoDiamondLayout->ids[k] = currentId + 1 + k; + // current id is assigned to [0], so it is the marker on the top + _charucoDiamondLayout->ids[0] = currentId; + + // try to find the rest of markers in the diamond + vector< int > acceptedIdxs; + Ptr _b = _charucoDiamondLayout.staticCast(); + aruco::refineDetectedMarkers(grey, _b, + currentMarker, currentMarkerId, + candidates, noArray(), noArray(), minRepDistance, -1, false, + acceptedIdxs); + + // if found, we have a diamond + if(currentMarker.size() == 4) { + + assigned[i] = true; + + // calculate diamond id, acceptedIdxs array indicates the markers taken from candidates + // array + Vec4i markerId; + markerId[0] = currentId; + for(int k = 1; k < 4; k++) { + int currentMarkerIdx = candidatesIdxs[acceptedIdxs[k - 1]]; + markerId[k] = _markerIds.getMat().at< int >(currentMarkerIdx); + assigned[currentMarkerIdx] = true; + } + + // interpolate the charuco corners of the diamond + vector< Point2f > currentMarkerCorners; + Mat aux; + interpolateCornersCharuco(currentMarker, currentMarkerId, grey, _charucoDiamondLayout, + currentMarkerCorners, aux, _cameraMatrix, _distCoeffs); + + // if everything is ok, save the diamond + if(currentMarkerCorners.size() > 0) { + // reorder corners + vector< Point2f > currentMarkerCornersReorder; + currentMarkerCornersReorder.resize(4); + currentMarkerCornersReorder[0] = currentMarkerCorners[2]; + currentMarkerCornersReorder[1] = currentMarkerCorners[3]; + currentMarkerCornersReorder[2] = currentMarkerCorners[1]; + currentMarkerCornersReorder[3] = currentMarkerCorners[0]; + + diamondCorners.push_back(currentMarkerCornersReorder); + diamondIds.push_back(markerId); + } + } + } + + + if(diamondIds.size() > 0) { + // parse output + Mat(diamondIds).copyTo(_diamondIds); + + _diamondCorners.create((int)diamondCorners.size(), 1, CV_32FC2); + for(unsigned int i = 0; i < diamondCorners.size(); i++) { + _diamondCorners.create(4, 1, CV_32FC2, i, true); + for(int j = 0; j < 4; j++) { + _diamondCorners.getMat(i).at< Point2f >(j) = diamondCorners[i][j]; + } + } + } +} + + + + +/** + */ +void drawCharucoDiamond(const Ptr &dictionary, Vec4i ids, int squareLength, int markerLength, + OutputArray _img, int marginSize, int borderBits) { + + CV_Assert(squareLength > 0 && markerLength > 0 && squareLength > markerLength); + CV_Assert(marginSize >= 0 && borderBits > 0); + + // create a charuco board similar to a charuco marker and print it + Ptr board = + CharucoBoard::create(3, 3, (float)squareLength, (float)markerLength, dictionary); + + // assign the charuco marker ids + for(int i = 0; i < 4; i++) + board->ids[i] = ids[i]; + + Size outSize(3 * squareLength + 2 * marginSize, 3 * squareLength + 2 * marginSize); + board->draw(outSize, _img, marginSize, borderBits); +} + + +/** + */ +void drawDetectedDiamonds(InputOutputArray _image, InputArrayOfArrays _corners, + InputArray _ids, Scalar borderColor) { + + + CV_Assert(_image.getMat().total() != 0 && + (_image.getMat().channels() == 1 || _image.getMat().channels() == 3)); + CV_Assert((_corners.total() == _ids.total()) || _ids.total() == 0); + + // calculate colors + Scalar textColor, cornerColor; + textColor = cornerColor = borderColor; + swap(textColor.val[0], textColor.val[1]); // text color just sawp G and R + swap(cornerColor.val[1], cornerColor.val[2]); // corner color just sawp G and B + + int nMarkers = (int)_corners.total(); + for(int i = 0; i < nMarkers; i++) { + Mat currentMarker = _corners.getMat(i); + CV_Assert(currentMarker.total() == 4 && currentMarker.type() == CV_32FC2); + + // draw marker sides + for(int j = 0; j < 4; j++) { + Point2f p0, p1; + p0 = currentMarker.at< Point2f >(j); + p1 = currentMarker.at< Point2f >((j + 1) % 4); + line(_image, p0, p1, borderColor, 1); + } + + // draw first corner mark + rectangle(_image, currentMarker.at< Point2f >(0) - Point2f(3, 3), + currentMarker.at< Point2f >(0) + Point2f(3, 3), cornerColor, 1, LINE_AA); + + // draw id composed by four numbers + if(_ids.total() != 0) { + Point2f cent(0, 0); + for(int p = 0; p < 4; p++) + cent += currentMarker.at< Point2f >(p); + cent = cent / 4.; + stringstream s; + s << "id=" << _ids.getMat().at< Vec4i >(i); + putText(_image, s.str(), cent, FONT_HERSHEY_SIMPLEX, 0.5, textColor, 2); + } + } +} +} +} diff --git a/aruco_pose/vendor/aruco/src/dictionary.cpp b/aruco_pose/vendor/aruco/src/dictionary.cpp new file mode 100644 index 00000000..62faf2a6 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/dictionary.cpp @@ -0,0 +1,494 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +#include "precomp.hpp" +#include "opencv2/aruco/dictionary.hpp" +#include +#include +#include "predefined_dictionaries.hpp" +#include "predefined_dictionaries_apriltag.hpp" +#include "opencv2/core/hal/hal.hpp" + +namespace cv { +namespace aruco { + +using namespace std; + + +/** + */ +Dictionary::Dictionary(const Ptr &_dictionary) { + markerSize = _dictionary->markerSize; + maxCorrectionBits = _dictionary->maxCorrectionBits; + bytesList = _dictionary->bytesList.clone(); +} + + +/** + */ +Dictionary::Dictionary(const Mat &_bytesList, int _markerSize, int _maxcorr) { + markerSize = _markerSize; + maxCorrectionBits = _maxcorr; + bytesList = _bytesList; +} + + +/** + */ +Ptr Dictionary::create(int nMarkers, int markerSize, int randomSeed) { + const Ptr baseDictionary = makePtr(); + return create(nMarkers, markerSize, baseDictionary, randomSeed); +} + + +/** + */ +Ptr Dictionary::create(int nMarkers, int markerSize, + const Ptr &baseDictionary, int randomSeed) { + + return generateCustomDictionary(nMarkers, markerSize, baseDictionary, randomSeed); +} + + +/** + */ +Ptr Dictionary::get(int dict) { + return getPredefinedDictionary(dict); +} + + +/** + */ +bool Dictionary::identify(const Mat &onlyBits, int &idx, int &rotation, + double maxCorrectionRate) const { + + CV_Assert(onlyBits.rows == markerSize && onlyBits.cols == markerSize); + + int maxCorrectionRecalculed = int(double(maxCorrectionBits) * maxCorrectionRate); + + // get as a byte list + Mat candidateBytes = getByteListFromBits(onlyBits); + + idx = -1; // by default, not found + + // search closest marker in dict + for(int m = 0; m < bytesList.rows; m++) { + int currentMinDistance = markerSize * markerSize + 1; + int currentRotation = -1; + for(unsigned int r = 0; r < 4; r++) { + int currentHamming = cv::hal::normHamming( + bytesList.ptr(m)+r*candidateBytes.cols, + candidateBytes.ptr(), + candidateBytes.cols); + + if(currentHamming < currentMinDistance) { + currentMinDistance = currentHamming; + currentRotation = r; + } + } + + // if maxCorrection is fullfilled, return this one + if(currentMinDistance <= maxCorrectionRecalculed) { + idx = m; + rotation = currentRotation; + break; + } + } + + return idx != -1; +} + + +/** + */ +int Dictionary::getDistanceToId(InputArray bits, int id, bool allRotations) const { + + CV_Assert(id >= 0 && id < bytesList.rows); + + unsigned int nRotations = 4; + if(!allRotations) nRotations = 1; + + Mat candidateBytes = getByteListFromBits(bits.getMat()); + int currentMinDistance = int(bits.total() * bits.total()); + for(unsigned int r = 0; r < nRotations; r++) { + int currentHamming = cv::hal::normHamming( + bytesList.ptr(id) + r*candidateBytes.cols, + candidateBytes.ptr(), + candidateBytes.cols); + + if(currentHamming < currentMinDistance) { + currentMinDistance = currentHamming; + } + } + return currentMinDistance; +} + + + +/** + * @brief Draw a canonical marker image + */ +void Dictionary::drawMarker(int id, int sidePixels, OutputArray _img, int borderBits) const { + + CV_Assert(sidePixels >= (markerSize + 2*borderBits)); + CV_Assert(id < bytesList.rows); + CV_Assert(borderBits > 0); + + _img.create(sidePixels, sidePixels, CV_8UC1); + + // create small marker with 1 pixel per bin + Mat tinyMarker(markerSize + 2 * borderBits, markerSize + 2 * borderBits, CV_8UC1, + Scalar::all(0)); + Mat innerRegion = tinyMarker.rowRange(borderBits, tinyMarker.rows - borderBits) + .colRange(borderBits, tinyMarker.cols - borderBits); + // put inner bits + Mat bits = 255 * getBitsFromByteList(bytesList.rowRange(id, id + 1), markerSize); + CV_Assert(innerRegion.total() == bits.total()); + bits.copyTo(innerRegion); + + // resize tiny marker to output size + cv::resize(tinyMarker, _img.getMat(), _img.getMat().size(), 0, 0, INTER_NEAREST); +} + + + + +/** + * @brief Transform matrix of bits to list of bytes in the 4 rotations + */ +Mat Dictionary::getByteListFromBits(const Mat &bits) { + // integer ceil + int nbytes = (bits.cols * bits.rows + 8 - 1) / 8; + + Mat candidateByteList(1, nbytes, CV_8UC4, Scalar::all(0)); + unsigned char currentBit = 0; + int currentByte = 0; + + // the 4 rotations + uchar* rot0 = candidateByteList.ptr(); + uchar* rot1 = candidateByteList.ptr() + 1*nbytes; + uchar* rot2 = candidateByteList.ptr() + 2*nbytes; + uchar* rot3 = candidateByteList.ptr() + 3*nbytes; + + for(int row = 0; row < bits.rows; row++) { + for(int col = 0; col < bits.cols; col++) { + // circular shift + rot0[currentByte] <<= 1; + rot1[currentByte] <<= 1; + rot2[currentByte] <<= 1; + rot3[currentByte] <<= 1; + // set bit + rot0[currentByte] |= bits.at(row, col); + rot1[currentByte] |= bits.at(col, bits.cols - 1 - row); + rot2[currentByte] |= bits.at(bits.rows - 1 - row, bits.cols - 1 - col); + rot3[currentByte] |= bits.at(bits.rows - 1 - col, row); + currentBit++; + if(currentBit == 8) { + // next byte + currentBit = 0; + currentByte++; + } + } + } + return candidateByteList; +} + + + +/** + * @brief Transform list of bytes to matrix of bits + */ +Mat Dictionary::getBitsFromByteList(const Mat &byteList, int markerSize) { + CV_Assert(byteList.total() > 0 && + byteList.total() >= (unsigned int)markerSize * markerSize / 8 && + byteList.total() <= (unsigned int)markerSize * markerSize / 8 + 1); + Mat bits(markerSize, markerSize, CV_8UC1, Scalar::all(0)); + + unsigned char base2List[] = { 128, 64, 32, 16, 8, 4, 2, 1 }; + int currentByteIdx = 0; + // we only need the bytes in normal rotation + unsigned char currentByte = byteList.ptr()[0]; + int currentBit = 0; + for(int row = 0; row < bits.rows; row++) { + for(int col = 0; col < bits.cols; col++) { + if(currentByte >= base2List[currentBit]) { + bits.at< unsigned char >(row, col) = 1; + currentByte -= base2List[currentBit]; + } + currentBit++; + if(currentBit == 8) { + currentByteIdx++; + currentByte = byteList.ptr()[currentByteIdx]; + // if not enough bits for one more byte, we are in the end + // update bit position accordingly + if(8 * (currentByteIdx + 1) > (int)bits.total()) + currentBit = 8 * (currentByteIdx + 1) - (int)bits.total(); + else + currentBit = 0; // ok, bits enough for next byte + } + } + } + return bits; +} + + + + +// DictionaryData constructors calls +const Dictionary DICT_ARUCO_DATA = Dictionary(Mat(1024, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_ARUCO_BYTES), 5, 0); + +const Dictionary DICT_4X4_50_DATA = Dictionary(Mat(50, (4*4 + 7)/8, CV_8UC4, (uchar*)DICT_4X4_1000_BYTES), 4, 1); +const Dictionary DICT_4X4_100_DATA = Dictionary(Mat(100, (4*4 + 7)/8, CV_8UC4, (uchar*)DICT_4X4_1000_BYTES), 4, 1); +const Dictionary DICT_4X4_250_DATA = Dictionary(Mat(250, (4*4 + 7)/8, CV_8UC4, (uchar*)DICT_4X4_1000_BYTES), 4, 1); +const Dictionary DICT_4X4_1000_DATA = Dictionary(Mat(1000, (4*4 + 7)/8, CV_8UC4, (uchar*)DICT_4X4_1000_BYTES), 4, 0); + +const Dictionary DICT_5X5_50_DATA = Dictionary(Mat(50, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_5X5_1000_BYTES), 5, 3); +const Dictionary DICT_5X5_100_DATA = Dictionary(Mat(100, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_5X5_1000_BYTES), 5, 3); +const Dictionary DICT_5X5_250_DATA = Dictionary(Mat(250, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_5X5_1000_BYTES), 5, 2); +const Dictionary DICT_5X5_1000_DATA = Dictionary(Mat(1000, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_5X5_1000_BYTES), 5, 2); + +const Dictionary DICT_6X6_50_DATA = Dictionary(Mat(50, (6*6 + 7)/8 ,CV_8UC4, (uchar*)DICT_6X6_1000_BYTES), 6, 6); +const Dictionary DICT_6X6_100_DATA = Dictionary(Mat(100, (6*6 + 7)/8 ,CV_8UC4, (uchar*)DICT_6X6_1000_BYTES), 6, 5); +const Dictionary DICT_6X6_250_DATA = Dictionary(Mat(250, (6*6 + 7)/8 ,CV_8UC4, (uchar*)DICT_6X6_1000_BYTES), 6, 5); +const Dictionary DICT_6X6_1000_DATA = Dictionary(Mat(1000, (6*6 + 7)/8 ,CV_8UC4, (uchar*)DICT_6X6_1000_BYTES), 6, 4); + +const Dictionary DICT_7X7_50_DATA = Dictionary(Mat(50, (7*7 + 7)/8 ,CV_8UC4, (uchar*)DICT_7X7_1000_BYTES), 7, 9); +const Dictionary DICT_7X7_100_DATA = Dictionary(Mat(100, (7*7 + 7)/8 ,CV_8UC4, (uchar*)DICT_7X7_1000_BYTES), 7, 8); +const Dictionary DICT_7X7_250_DATA = Dictionary(Mat(250, (7*7 + 7)/8 ,CV_8UC4, (uchar*)DICT_7X7_1000_BYTES), 7, 8); +const Dictionary DICT_7X7_1000_DATA = Dictionary(Mat(1000, (7*7 + 7)/8 ,CV_8UC4, (uchar*)DICT_7X7_1000_BYTES), 7, 6); + +const Dictionary DICT_APRILTAG_16h5_DATA = Dictionary(Mat(30, (4*4 + 7)/8, CV_8UC4, (uchar*)DICT_APRILTAG_16h5_BYTES), 4, 0); +const Dictionary DICT_APRILTAG_25h9_DATA = Dictionary(Mat(35, (5*5 + 7)/8, CV_8UC4, (uchar*)DICT_APRILTAG_25h9_BYTES), 5, 0); +const Dictionary DICT_APRILTAG_36h10_DATA = Dictionary(Mat(2320, (6*6 + 7)/8, CV_8UC4, (uchar*)DICT_APRILTAG_36h10_BYTES), 6, 0); +const Dictionary DICT_APRILTAG_36h11_DATA = Dictionary(Mat(587, (6*6 + 7)/8, CV_8UC4, (uchar*)DICT_APRILTAG_36h11_BYTES), 6, 0); + + +Ptr getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name) { + switch(name) { + + case DICT_ARUCO_ORIGINAL: + return makePtr(DICT_ARUCO_DATA); + + case DICT_4X4_50: + return makePtr(DICT_4X4_50_DATA); + case DICT_4X4_100: + return makePtr(DICT_4X4_100_DATA); + case DICT_4X4_250: + return makePtr(DICT_4X4_250_DATA); + case DICT_4X4_1000: + return makePtr(DICT_4X4_1000_DATA); + + case DICT_5X5_50: + return makePtr(DICT_5X5_50_DATA); + case DICT_5X5_100: + return makePtr(DICT_5X5_100_DATA); + case DICT_5X5_250: + return makePtr(DICT_5X5_250_DATA); + case DICT_5X5_1000: + return makePtr(DICT_5X5_1000_DATA); + + case DICT_6X6_50: + return makePtr(DICT_6X6_50_DATA); + case DICT_6X6_100: + return makePtr(DICT_6X6_100_DATA); + case DICT_6X6_250: + return makePtr(DICT_6X6_250_DATA); + case DICT_6X6_1000: + return makePtr(DICT_6X6_1000_DATA); + + case DICT_7X7_50: + return makePtr(DICT_7X7_50_DATA); + case DICT_7X7_100: + return makePtr(DICT_7X7_100_DATA); + case DICT_7X7_250: + return makePtr(DICT_7X7_250_DATA); + case DICT_7X7_1000: + return makePtr(DICT_7X7_1000_DATA); + + case DICT_APRILTAG_16h5: + return makePtr(DICT_APRILTAG_16h5_DATA); + case DICT_APRILTAG_25h9: + return makePtr(DICT_APRILTAG_25h9_DATA); + case DICT_APRILTAG_36h10: + return makePtr(DICT_APRILTAG_36h10_DATA); + case DICT_APRILTAG_36h11: + return makePtr(DICT_APRILTAG_36h11_DATA); + + } + return makePtr(DICT_4X4_50_DATA); +} + + +Ptr getPredefinedDictionary(int dict) { + return getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME(dict)); +} + + +/** + * @brief Generates a random marker Mat of size markerSize x markerSize + */ +static Mat _generateRandomMarker(int markerSize, RNG &rng) { + Mat marker(markerSize, markerSize, CV_8UC1, Scalar::all(0)); + for(int i = 0; i < markerSize; i++) { + for(int j = 0; j < markerSize; j++) { + unsigned char bit = (unsigned char) (rng.uniform(0,2)); + marker.at< unsigned char >(i, j) = bit; + } + } + return marker; +} + +/** + * @brief Calculate selfDistance of the codification of a marker Mat. Self distance is the Hamming + * distance of the marker to itself in the other rotations. + * See S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez. 2014. + * "Automatic generation and detection of highly reliable fiducial markers under occlusion". + * Pattern Recogn. 47, 6 (June 2014), 2280-2292. DOI=10.1016/j.patcog.2014.01.005 + */ +static int _getSelfDistance(const Mat &marker) { + Mat bytes = Dictionary::getByteListFromBits(marker); + int minHamming = (int)marker.total() + 1; + for(int r = 1; r < 4; r++) { + int currentHamming = cv::hal::normHamming(bytes.ptr(), bytes.ptr() + bytes.cols*r, bytes.cols); + if(currentHamming < minHamming) minHamming = currentHamming; + } + return minHamming; +} + +/** + */ +Ptr generateCustomDictionary(int nMarkers, int markerSize, + const Ptr &baseDictionary, int randomSeed) { + RNG rng((uint64)(randomSeed)); + + Ptr out = makePtr(); + out->markerSize = markerSize; + + // theoretical maximum intermarker distance + // See S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez. 2014. + // "Automatic generation and detection of highly reliable fiducial markers under occlusion". + // Pattern Recogn. 47, 6 (June 2014), 2280-2292. DOI=10.1016/j.patcog.2014.01.005 + int C = (int)std::floor(float(markerSize * markerSize) / 4.f); + int tau = 2 * (int)std::floor(float(C) * 4.f / 3.f); + + // if baseDictionary is provided, calculate its intermarker distance + if(baseDictionary->bytesList.rows > 0) { + CV_Assert(baseDictionary->markerSize == markerSize); + out->bytesList = baseDictionary->bytesList.clone(); + + int minDistance = markerSize * markerSize + 1; + for(int i = 0; i < out->bytesList.rows; i++) { + Mat markerBytes = out->bytesList.rowRange(i, i + 1); + Mat markerBits = Dictionary::getBitsFromByteList(markerBytes, markerSize); + minDistance = min(minDistance, _getSelfDistance(markerBits)); + for(int j = i + 1; j < out->bytesList.rows; j++) { + minDistance = min(minDistance, out->getDistanceToId(markerBits, j)); + } + } + tau = minDistance; + } + + // current best option + int bestTau = 0; + Mat bestMarker; + + // after these number of unproductive iterations, the best option is accepted + const int maxUnproductiveIterations = 5000; + int unproductiveIterations = 0; + + while(out->bytesList.rows < nMarkers) { + Mat currentMarker = _generateRandomMarker(markerSize, rng); + + int selfDistance = _getSelfDistance(currentMarker); + int minDistance = selfDistance; + + // if self distance is better or equal than current best option, calculate distance + // to previous accepted markers + if(selfDistance >= bestTau) { + for(int i = 0; i < out->bytesList.rows; i++) { + int currentDistance = out->getDistanceToId(currentMarker, i); + minDistance = min(currentDistance, minDistance); + if(minDistance <= bestTau) { + break; + } + } + } + + // if distance is high enough, accept the marker + if(minDistance >= tau) { + unproductiveIterations = 0; + bestTau = 0; + Mat bytes = Dictionary::getByteListFromBits(currentMarker); + out->bytesList.push_back(bytes); + } else { + unproductiveIterations++; + + // if distance is not enough, but is better than the current best option + if(minDistance > bestTau) { + bestTau = minDistance; + bestMarker = currentMarker; + } + + // if number of unproductive iterarions has been reached, accept the current best option + if(unproductiveIterations == maxUnproductiveIterations) { + unproductiveIterations = 0; + tau = bestTau; + bestTau = 0; + Mat bytes = Dictionary::getByteListFromBits(bestMarker); + out->bytesList.push_back(bytes); + } + } + } + + // update the maximum number of correction bits for the generated dictionary + out->maxCorrectionBits = (tau - 1) / 2; + + return out; +} + + +/** + */ +Ptr generateCustomDictionary(int nMarkers, int markerSize, int randomSeed) { + Ptr baseDictionary = makePtr(); + return generateCustomDictionary(nMarkers, markerSize, baseDictionary, randomSeed); +} + + +} +} diff --git a/aruco_pose/vendor/aruco/src/precomp.hpp b/aruco_pose/vendor/aruco/src/precomp.hpp new file mode 100644 index 00000000..b45771a6 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/precomp.hpp @@ -0,0 +1,49 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// + // + // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. + // + // By downloading, copying, installing or using the software you agree to this license. + // If you do not agree to this license, do not download, install, + // copy or use the software. + // + // + // License Agreement + // For Open Source Computer Vision Library + // + // Copyright (C) 2014, OpenCV Foundation, all rights reserved. + // Third party copyrights are property of their respective owners. + // + // Redistribution and use in source and binary forms, with or without modification, + // are permitted provided that the following conditions are met: + // + // * Redistribution's of source code must retain the above copyright notice, + // this list of conditions and the following disclaimer. + // + // * Redistribution's in binary form must reproduce the above copyright notice, + // this list of conditions and the following disclaimer in the documentation + // and/or other materials provided with the distribution. + // + // * The name of the copyright holders may not be used to endorse or promote products + // derived from this software without specific prior written permission. + // + // This software is provided by the copyright holders and contributors "as is" and + // any express or implied warranties, including, but not limited to, the implied + // warranties of merchantability and fitness for a particular purpose are disclaimed. + // In no event shall the Intel Corporation or contributors be liable for any direct, + // indirect, incidental, special, exemplary, or consequential damages + // (including, but not limited to, procurement of substitute goods or services; + // loss of use, data, or profits; or business interruption) however caused + // and on any theory of liability, whether in contract, strict liability, + // or tort (including negligence or otherwise) arising in any way out of + // the use of this software, even if advised of the possibility of such damage. + // + //M*/ + +#ifndef __OPENCV_CCALIB_PRECOMP__ +#define __OPENCV_CCALIB_PRECOMP__ + +#include +#include +#include + +#endif diff --git a/aruco_pose/vendor/aruco/src/predefined_dictionaries.hpp b/aruco_pose/vendor/aruco/src/predefined_dictionaries.hpp new file mode 100644 index 00000000..ce2db459 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/predefined_dictionaries.hpp @@ -0,0 +1,20161 @@ +/* +By downloading, copying, installing or using the software you agree to this +license. If you do not agree to this license, do not download, install, +copy or use the software. + + License Agreement + For Open Source Computer Vision Library + (3-clause BSD License) + +Copyright (C) 2013, OpenCV Foundation, all rights reserved. +Third party copyrights are property of their respective owners. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + * Neither the names of the copyright holders nor the names of the contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + +This software is provided by the copyright holders and contributors "as is" and +any express or implied warranties, including, but not limited to, the implied +warranties of merchantability and fitness for a particular purpose are +disclaimed. In no event shall copyright holders or contributors be liable for +any direct, indirect, incidental, special, exemplary, or consequential damages +(including, but not limited to, procurement of substitute goods or services; +loss of use, data, or profits; or business interruption) however caused +and on any theory of liability, whether in contract, strict liability, +or tort (including negligence or otherwise) arising in any way out of +the use of this software, even if advised of the possibility of such damage. +*/ + +namespace { + + + +/** + * Dictionaries are stored as a list of bytes in its four rotations + * On each rotation, the marker is divided in bytes assuming a row-major order + * This format allows a faster marker identification. + * For a dictionary composed by M markers of NxN bits, the structure dimensions should be: + * const char name[nMarkers][4rotations][nBytes], or more specifically: + * const char name[M][4][ceil(NxN/8)] + * The element [i][j][k] represents the k-th byte of the i-th marker in the dictionary + * in its j-th rotation. + * Each rotation implies a 90 degree rotation of the marker in anticlockwise direction. + */ + +static unsigned char DICT_ARUCO_BYTES[][4][4] = { + { { 132, 33, 8, 0 }, + { 0, 0, 15, 1 }, + { 8, 66, 16, 1 }, + { 248, 0, 0, 0 }, }, + { { 132, 33, 11, 1 }, + { 8, 66, 15, 1 }, + { 232, 66, 16, 1 }, + { 248, 33, 8, 0 }, }, + { { 132, 33, 4, 1 }, + { 8, 0, 31, 0 }, + { 144, 66, 16, 1 }, + { 124, 0, 8, 0 }, }, + { { 132, 33, 7, 0 }, + { 0, 66, 31, 0 }, + { 112, 66, 16, 1 }, + { 124, 33, 0, 0 }, }, + { { 132, 33, 120, 0 }, + { 16, 132, 15, 1 }, + { 15, 66, 16, 1 }, + { 248, 16, 132, 0 }, }, + { { 132, 33, 123, 1 }, + { 24, 198, 15, 1 }, + { 239, 66, 16, 1 }, + { 248, 49, 140, 0 }, }, + { { 132, 33, 116, 1 }, + { 24, 132, 31, 0 }, + { 151, 66, 16, 1 }, + { 124, 16, 140, 0 }, }, + { { 132, 33, 119, 0 }, + { 16, 198, 31, 0 }, + { 119, 66, 16, 1 }, + { 124, 49, 132, 0 }, }, + { { 132, 32, 152, 0 }, + { 16, 0, 46, 1 }, + { 12, 130, 16, 1 }, + { 186, 0, 4, 0 }, }, + { { 132, 32, 155, 1 }, + { 24, 66, 46, 1 }, + { 236, 130, 16, 1 }, + { 186, 33, 12, 0 }, }, + { { 132, 32, 148, 1 }, + { 24, 0, 62, 0 }, + { 148, 130, 16, 1 }, + { 62, 0, 12, 0 }, }, + { { 132, 32, 151, 0 }, + { 16, 66, 62, 0 }, + { 116, 130, 16, 1 }, + { 62, 33, 4, 0 }, }, + { { 132, 32, 232, 0 }, + { 0, 132, 46, 1 }, + { 11, 130, 16, 1 }, + { 186, 16, 128, 0 }, }, + { { 132, 32, 235, 1 }, + { 8, 198, 46, 1 }, + { 235, 130, 16, 1 }, + { 186, 49, 136, 0 }, }, + { { 132, 32, 228, 1 }, + { 8, 132, 62, 0 }, + { 147, 130, 16, 1 }, + { 62, 16, 136, 0 }, }, + { { 132, 32, 231, 0 }, + { 0, 198, 62, 0 }, + { 115, 130, 16, 1 }, + { 62, 49, 128, 0 }, }, + { { 132, 47, 8, 0 }, + { 33, 8, 15, 1 }, + { 8, 122, 16, 1 }, + { 248, 8, 66, 0 }, }, + { { 132, 47, 11, 1 }, + { 41, 74, 15, 1 }, + { 232, 122, 16, 1 }, + { 248, 41, 74, 0 }, }, + { { 132, 47, 4, 1 }, + { 41, 8, 31, 0 }, + { 144, 122, 16, 1 }, + { 124, 8, 74, 0 }, }, + { { 132, 47, 7, 0 }, + { 33, 74, 31, 0 }, + { 112, 122, 16, 1 }, + { 124, 41, 66, 0 }, }, + { { 132, 47, 120, 0 }, + { 49, 140, 15, 1 }, + { 15, 122, 16, 1 }, + { 248, 24, 198, 0 }, }, + { { 132, 47, 123, 1 }, + { 57, 206, 15, 1 }, + { 239, 122, 16, 1 }, + { 248, 57, 206, 0 }, }, + { { 132, 47, 116, 1 }, + { 57, 140, 31, 0 }, + { 151, 122, 16, 1 }, + { 124, 24, 206, 0 }, }, + { { 132, 47, 119, 0 }, + { 49, 206, 31, 0 }, + { 119, 122, 16, 1 }, + { 124, 57, 198, 0 }, }, + { { 132, 46, 152, 0 }, + { 49, 8, 46, 1 }, + { 12, 186, 16, 1 }, + { 186, 8, 70, 0 }, }, + { { 132, 46, 155, 1 }, + { 57, 74, 46, 1 }, + { 236, 186, 16, 1 }, + { 186, 41, 78, 0 }, }, + { { 132, 46, 148, 1 }, + { 57, 8, 62, 0 }, + { 148, 186, 16, 1 }, + { 62, 8, 78, 0 }, }, + { { 132, 46, 151, 0 }, + { 49, 74, 62, 0 }, + { 116, 186, 16, 1 }, + { 62, 41, 70, 0 }, }, + { { 132, 46, 232, 0 }, + { 33, 140, 46, 1 }, + { 11, 186, 16, 1 }, + { 186, 24, 194, 0 }, }, + { { 132, 46, 235, 1 }, + { 41, 206, 46, 1 }, + { 235, 186, 16, 1 }, + { 186, 57, 202, 0 }, }, + { { 132, 46, 228, 1 }, + { 41, 140, 62, 0 }, + { 147, 186, 16, 1 }, + { 62, 24, 202, 0 }, }, + { { 132, 46, 231, 0 }, + { 33, 206, 62, 0 }, + { 115, 186, 16, 1 }, + { 62, 57, 194, 0 }, }, + { { 132, 19, 8, 0 }, + { 32, 0, 77, 1 }, + { 8, 100, 16, 1 }, + { 217, 0, 2, 0 }, }, + { { 132, 19, 11, 1 }, + { 40, 66, 77, 1 }, + { 232, 100, 16, 1 }, + { 217, 33, 10, 0 }, }, + { { 132, 19, 4, 1 }, + { 40, 0, 93, 0 }, + { 144, 100, 16, 1 }, + { 93, 0, 10, 0 }, }, + { { 132, 19, 7, 0 }, + { 32, 66, 93, 0 }, + { 112, 100, 16, 1 }, + { 93, 33, 2, 0 }, }, + { { 132, 19, 120, 0 }, + { 48, 132, 77, 1 }, + { 15, 100, 16, 1 }, + { 217, 16, 134, 0 }, }, + { { 132, 19, 123, 1 }, + { 56, 198, 77, 1 }, + { 239, 100, 16, 1 }, + { 217, 49, 142, 0 }, }, + { { 132, 19, 116, 1 }, + { 56, 132, 93, 0 }, + { 151, 100, 16, 1 }, + { 93, 16, 142, 0 }, }, + { { 132, 19, 119, 0 }, + { 48, 198, 93, 0 }, + { 119, 100, 16, 1 }, + { 93, 49, 134, 0 }, }, + { { 132, 18, 152, 0 }, + { 48, 0, 108, 1 }, + { 12, 164, 16, 1 }, + { 155, 0, 6, 0 }, }, + { { 132, 18, 155, 1 }, + { 56, 66, 108, 1 }, + { 236, 164, 16, 1 }, + { 155, 33, 14, 0 }, }, + { { 132, 18, 148, 1 }, + { 56, 0, 124, 0 }, + { 148, 164, 16, 1 }, + { 31, 0, 14, 0 }, }, + { { 132, 18, 151, 0 }, + { 48, 66, 124, 0 }, + { 116, 164, 16, 1 }, + { 31, 33, 6, 0 }, }, + { { 132, 18, 232, 0 }, + { 32, 132, 108, 1 }, + { 11, 164, 16, 1 }, + { 155, 16, 130, 0 }, }, + { { 132, 18, 235, 1 }, + { 40, 198, 108, 1 }, + { 235, 164, 16, 1 }, + { 155, 49, 138, 0 }, }, + { { 132, 18, 228, 1 }, + { 40, 132, 124, 0 }, + { 147, 164, 16, 1 }, + { 31, 16, 138, 0 }, }, + { { 132, 18, 231, 0 }, + { 32, 198, 124, 0 }, + { 115, 164, 16, 1 }, + { 31, 49, 130, 0 }, }, + { { 132, 29, 8, 0 }, + { 1, 8, 77, 1 }, + { 8, 92, 16, 1 }, + { 217, 8, 64, 0 }, }, + { { 132, 29, 11, 1 }, + { 9, 74, 77, 1 }, + { 232, 92, 16, 1 }, + { 217, 41, 72, 0 }, }, + { { 132, 29, 4, 1 }, + { 9, 8, 93, 0 }, + { 144, 92, 16, 1 }, + { 93, 8, 72, 0 }, }, + { { 132, 29, 7, 0 }, + { 1, 74, 93, 0 }, + { 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+ { 209, 111, 121, 0 }, }, + { { 117, 221, 4, 1 }, + { 79, 57, 85, 0 }, + { 144, 93, 215, 0 }, + { 85, 78, 121, 0 }, }, + { { 117, 221, 7, 0 }, + { 71, 123, 85, 0 }, + { 112, 93, 215, 0 }, + { 85, 111, 113, 0 }, }, + { { 117, 221, 120, 0 }, + { 87, 189, 69, 1 }, + { 15, 93, 215, 0 }, + { 209, 94, 245, 0 }, }, + { { 117, 221, 123, 1 }, + { 95, 255, 69, 1 }, + { 239, 93, 215, 0 }, + { 209, 127, 253, 0 }, }, + { { 117, 221, 116, 1 }, + { 95, 189, 85, 0 }, + { 151, 93, 215, 0 }, + { 85, 94, 253, 0 }, }, + { { 117, 221, 119, 0 }, + { 87, 255, 85, 0 }, + { 119, 93, 215, 0 }, + { 85, 127, 245, 0 }, }, + { { 117, 220, 152, 0 }, + { 87, 57, 100, 1 }, + { 12, 157, 215, 0 }, + { 147, 78, 117, 0 }, }, + { { 117, 220, 155, 1 }, + { 95, 123, 100, 1 }, + { 236, 157, 215, 0 }, + { 147, 111, 125, 0 }, }, + { { 117, 220, 148, 1 }, + { 95, 57, 116, 0 }, + { 148, 157, 215, 0 }, + { 23, 78, 125, 0 }, }, + { { 117, 220, 151, 0 }, + { 87, 123, 116, 0 }, + { 116, 157, 215, 0 }, + { 23, 111, 117, 0 }, }, + { { 117, 220, 232, 0 }, + { 71, 189, 100, 1 }, + { 11, 157, 215, 0 }, + { 147, 94, 241, 0 }, }, + { { 117, 220, 235, 1 }, + { 79, 255, 100, 1 }, + { 235, 157, 215, 0 }, + { 147, 127, 249, 0 }, }, + { { 117, 220, 228, 1 }, + { 79, 189, 116, 0 }, + { 147, 157, 215, 0 }, + { 23, 94, 249, 0 }, }, + { { 117, 220, 231, 0 }, + { 71, 255, 116, 0 }, + { 115, 157, 215, 0 }, + { 23, 127, 241, 0 }, }, + { { 114, 97, 8, 0 }, + { 68, 33, 131, 1 }, + { 8, 67, 39, 0 }, + { 224, 194, 17, 0 }, }, + { { 114, 97, 11, 1 }, + { 76, 99, 131, 1 }, + { 232, 67, 39, 0 }, + { 224, 227, 25, 0 }, }, + { { 114, 97, 4, 1 }, + { 76, 33, 147, 0 }, + { 144, 67, 39, 0 }, + { 100, 194, 25, 0 }, }, + { { 114, 97, 7, 0 }, + { 68, 99, 147, 0 }, + { 112, 67, 39, 0 }, + { 100, 227, 17, 0 }, }, + { { 114, 97, 120, 0 }, + { 84, 165, 131, 1 }, + { 15, 67, 39, 0 }, + { 224, 210, 149, 0 }, }, + { { 114, 97, 123, 1 }, + { 92, 231, 131, 1 }, + { 239, 67, 39, 0 }, + { 224, 243, 157, 0 }, }, + { { 114, 97, 116, 1 }, + { 92, 165, 147, 0 }, + { 151, 67, 39, 0 }, + { 100, 210, 157, 0 }, }, + { { 114, 97, 119, 0 }, + { 84, 231, 147, 0 }, + { 119, 67, 39, 0 }, + { 100, 243, 149, 0 }, }, + { { 114, 96, 152, 0 }, + { 84, 33, 162, 1 }, + { 12, 131, 39, 0 }, + { 162, 194, 21, 0 }, }, + { { 114, 96, 155, 1 }, + { 92, 99, 162, 1 }, + { 236, 131, 39, 0 }, + { 162, 227, 29, 0 }, }, + { { 114, 96, 148, 1 }, + { 92, 33, 178, 0 }, + { 148, 131, 39, 0 }, + { 38, 194, 29, 0 }, }, + { { 114, 96, 151, 0 }, + { 84, 99, 178, 0 }, + { 116, 131, 39, 0 }, + { 38, 227, 21, 0 }, }, + { { 114, 96, 232, 0 }, + { 68, 165, 162, 1 }, + { 11, 131, 39, 0 }, + { 162, 210, 145, 0 }, }, + { { 114, 96, 235, 1 }, + { 76, 231, 162, 1 }, + { 235, 131, 39, 0 }, + { 162, 243, 153, 0 }, }, + { { 114, 96, 228, 1 }, + { 76, 165, 178, 0 }, + { 147, 131, 39, 0 }, + { 38, 210, 153, 0 }, }, + { { 114, 96, 231, 0 }, + { 68, 231, 178, 0 }, + { 115, 131, 39, 0 }, + { 38, 243, 145, 0 }, }, + { { 114, 111, 8, 0 }, + { 101, 41, 131, 1 }, + { 8, 123, 39, 0 }, + { 224, 202, 83, 0 }, }, + { { 114, 111, 11, 1 }, + { 109, 107, 131, 1 }, + { 232, 123, 39, 0 }, + { 224, 235, 91, 0 }, }, + { { 114, 111, 4, 1 }, + { 109, 41, 147, 0 }, + { 144, 123, 39, 0 }, + { 100, 202, 91, 0 }, }, + { { 114, 111, 7, 0 }, + { 101, 107, 147, 0 }, + { 112, 123, 39, 0 }, + { 100, 235, 83, 0 }, }, + { { 114, 111, 120, 0 }, + { 117, 173, 131, 1 }, + { 15, 123, 39, 0 }, + { 224, 218, 215, 0 }, }, + { { 114, 111, 123, 1 }, + { 125, 239, 131, 1 }, + { 239, 123, 39, 0 }, + { 224, 251, 223, 0 }, }, + { { 114, 111, 116, 1 }, + { 125, 173, 147, 0 }, + { 151, 123, 39, 0 }, + { 100, 218, 223, 0 }, }, + { { 114, 111, 119, 0 }, + { 117, 239, 147, 0 }, + { 119, 123, 39, 0 }, + { 100, 251, 215, 0 }, }, + { { 114, 110, 152, 0 }, + { 117, 41, 162, 1 }, + { 12, 187, 39, 0 }, + { 162, 202, 87, 0 }, }, + { { 114, 110, 155, 1 }, + { 125, 107, 162, 1 }, + { 236, 187, 39, 0 }, + { 162, 235, 95, 0 }, }, + { { 114, 110, 148, 1 }, + { 125, 41, 178, 0 }, + { 148, 187, 39, 0 }, + { 38, 202, 95, 0 }, }, + { { 114, 110, 151, 0 }, + { 117, 107, 178, 0 }, + { 116, 187, 39, 0 }, + { 38, 235, 87, 0 }, }, + { { 114, 110, 232, 0 }, + { 101, 173, 162, 1 }, + { 11, 187, 39, 0 }, + { 162, 218, 211, 0 }, }, + { { 114, 110, 235, 1 }, + { 109, 239, 162, 1 }, + { 235, 187, 39, 0 }, + { 162, 251, 219, 0 }, }, + { { 114, 110, 228, 1 }, + { 109, 173, 178, 0 }, + { 147, 187, 39, 0 }, + { 38, 218, 219, 0 }, }, + { { 114, 110, 231, 0 }, + { 101, 239, 178, 0 }, + { 115, 187, 39, 0 }, + { 38, 251, 211, 0 }, }, + { { 114, 83, 8, 0 }, + { 100, 33, 193, 1 }, + { 8, 101, 39, 0 }, + { 193, 194, 19, 0 }, }, + { { 114, 83, 11, 1 }, + { 108, 99, 193, 1 }, + { 232, 101, 39, 0 }, + { 193, 227, 27, 0 }, }, + { { 114, 83, 4, 1 }, + { 108, 33, 209, 0 }, + { 144, 101, 39, 0 }, + { 69, 194, 27, 0 }, }, + { { 114, 83, 7, 0 }, + { 100, 99, 209, 0 }, + { 112, 101, 39, 0 }, + { 69, 227, 19, 0 }, }, + { { 114, 83, 120, 0 }, + { 116, 165, 193, 1 }, + { 15, 101, 39, 0 }, + { 193, 210, 151, 0 }, }, + { { 114, 83, 123, 1 }, + { 124, 231, 193, 1 }, + { 239, 101, 39, 0 }, + { 193, 243, 159, 0 }, }, + { { 114, 83, 116, 1 }, + { 124, 165, 209, 0 }, + { 151, 101, 39, 0 }, + { 69, 210, 159, 0 }, }, + { { 114, 83, 119, 0 }, + { 116, 231, 209, 0 }, + { 119, 101, 39, 0 }, + { 69, 243, 151, 0 }, }, + { { 114, 82, 152, 0 }, + { 116, 33, 224, 1 }, + { 12, 165, 39, 0 }, + { 131, 194, 23, 0 }, }, + { { 114, 82, 155, 1 }, + { 124, 99, 224, 1 }, + { 236, 165, 39, 0 }, + { 131, 227, 31, 0 }, }, + { { 114, 82, 148, 1 }, + { 124, 33, 240, 0 }, + { 148, 165, 39, 0 }, + { 7, 194, 31, 0 }, }, + { { 114, 82, 151, 0 }, + { 116, 99, 240, 0 }, + { 116, 165, 39, 0 }, + { 7, 227, 23, 0 }, }, + { { 114, 82, 232, 0 }, + { 100, 165, 224, 1 }, + { 11, 165, 39, 0 }, + { 131, 210, 147, 0 }, }, + { { 114, 82, 235, 1 }, + { 108, 231, 224, 1 }, + { 235, 165, 39, 0 }, + { 131, 243, 155, 0 }, }, + { { 114, 82, 228, 1 }, + { 108, 165, 240, 0 }, + { 147, 165, 39, 0 }, + { 7, 210, 155, 0 }, }, + { { 114, 82, 231, 0 }, + { 100, 231, 240, 0 }, + { 115, 165, 39, 0 }, + { 7, 243, 147, 0 }, }, + { { 114, 93, 8, 0 }, + { 69, 41, 193, 1 }, + { 8, 93, 39, 0 }, + { 193, 202, 81, 0 }, }, + { { 114, 93, 11, 1 }, + { 77, 107, 193, 1 }, + { 232, 93, 39, 0 }, + { 193, 235, 89, 0 }, }, + { { 114, 93, 4, 1 }, + { 77, 41, 209, 0 }, + { 144, 93, 39, 0 }, + { 69, 202, 89, 0 }, }, + { { 114, 93, 7, 0 }, + { 69, 107, 209, 0 }, + { 112, 93, 39, 0 }, + { 69, 235, 81, 0 }, }, + { { 114, 93, 120, 0 }, + { 85, 173, 193, 1 }, + { 15, 93, 39, 0 }, + { 193, 218, 213, 0 }, }, + { { 114, 93, 123, 1 }, + { 93, 239, 193, 1 }, + { 239, 93, 39, 0 }, + { 193, 251, 221, 0 }, }, + { { 114, 93, 116, 1 }, + { 93, 173, 209, 0 }, + { 151, 93, 39, 0 }, + { 69, 218, 221, 0 }, }, + { { 114, 93, 119, 0 }, + { 85, 239, 209, 0 }, + { 119, 93, 39, 0 }, + { 69, 251, 213, 0 }, }, + { { 114, 92, 152, 0 }, + { 85, 41, 224, 1 }, + { 12, 157, 39, 0 }, + { 131, 202, 85, 0 }, }, + { { 114, 92, 155, 1 }, + { 93, 107, 224, 1 }, + { 236, 157, 39, 0 }, + { 131, 235, 93, 0 }, }, + { { 114, 92, 148, 1 }, + { 93, 41, 240, 0 }, + { 148, 157, 39, 0 }, + { 7, 202, 93, 0 }, }, + { { 114, 92, 151, 0 }, + { 85, 107, 240, 0 }, + { 116, 157, 39, 0 }, + { 7, 235, 85, 0 }, }, + { { 114, 92, 232, 0 }, + { 69, 173, 224, 1 }, + { 11, 157, 39, 0 }, + { 131, 218, 209, 0 }, }, + { { 114, 92, 235, 1 }, + { 77, 239, 224, 1 }, + { 235, 157, 39, 0 }, + { 131, 251, 217, 0 }, }, + { { 114, 92, 228, 1 }, + { 77, 173, 240, 0 }, + { 147, 157, 39, 0 }, + { 7, 218, 217, 0 }, }, + { { 114, 92, 231, 0 }, + { 69, 239, 240, 0 }, + { 115, 157, 39, 0 }, + { 7, 251, 209, 0 }, }, + { { 115, 161, 8, 0 }, + { 6, 49, 131, 1 }, + { 8, 66, 231, 0 }, + { 224, 198, 48, 0 }, }, + { { 115, 161, 11, 1 }, + { 14, 115, 131, 1 }, + { 232, 66, 231, 0 }, + { 224, 231, 56, 0 }, }, + { { 115, 161, 4, 1 }, + { 14, 49, 147, 0 }, + { 144, 66, 231, 0 }, + { 100, 198, 56, 0 }, }, + { { 115, 161, 7, 0 }, + { 6, 115, 147, 0 }, + { 112, 66, 231, 0 }, + { 100, 231, 48, 0 }, }, + { { 115, 161, 120, 0 }, + { 22, 181, 131, 1 }, + { 15, 66, 231, 0 }, + { 224, 214, 180, 0 }, }, + { { 115, 161, 123, 1 }, + { 30, 247, 131, 1 }, + { 239, 66, 231, 0 }, + { 224, 247, 188, 0 }, }, + { { 115, 161, 116, 1 }, + { 30, 181, 147, 0 }, + { 151, 66, 231, 0 }, + { 100, 214, 188, 0 }, }, + { { 115, 161, 119, 0 }, + { 22, 247, 147, 0 }, + { 119, 66, 231, 0 }, + { 100, 247, 180, 0 }, }, + { { 115, 160, 152, 0 }, + { 22, 49, 162, 1 }, + { 12, 130, 231, 0 }, + { 162, 198, 52, 0 }, }, + { { 115, 160, 155, 1 }, + { 30, 115, 162, 1 }, + { 236, 130, 231, 0 }, + { 162, 231, 60, 0 }, }, + { { 115, 160, 148, 1 }, + { 30, 49, 178, 0 }, + { 148, 130, 231, 0 }, + { 38, 198, 60, 0 }, }, + { { 115, 160, 151, 0 }, + { 22, 115, 178, 0 }, + { 116, 130, 231, 0 }, + { 38, 231, 52, 0 }, }, + { { 115, 160, 232, 0 }, + { 6, 181, 162, 1 }, + { 11, 130, 231, 0 }, + { 162, 214, 176, 0 }, }, + { { 115, 160, 235, 1 }, + { 14, 247, 162, 1 }, + { 235, 130, 231, 0 }, + { 162, 247, 184, 0 }, }, + { { 115, 160, 228, 1 }, + { 14, 181, 178, 0 }, + { 147, 130, 231, 0 }, + { 38, 214, 184, 0 }, }, + { { 115, 160, 231, 0 }, + { 6, 247, 178, 0 }, + { 115, 130, 231, 0 }, + { 38, 247, 176, 0 }, }, + { { 115, 175, 8, 0 }, + { 39, 57, 131, 1 }, + { 8, 122, 231, 0 }, + { 224, 206, 114, 0 }, }, + { { 115, 175, 11, 1 }, + { 47, 123, 131, 1 }, + { 232, 122, 231, 0 }, + { 224, 239, 122, 0 }, }, + { { 115, 175, 4, 1 }, + { 47, 57, 147, 0 }, + { 144, 122, 231, 0 }, + { 100, 206, 122, 0 }, }, + { { 115, 175, 7, 0 }, + { 39, 123, 147, 0 }, + { 112, 122, 231, 0 }, + { 100, 239, 114, 0 }, }, + { { 115, 175, 120, 0 }, + { 55, 189, 131, 1 }, + { 15, 122, 231, 0 }, + { 224, 222, 246, 0 }, }, + { { 115, 175, 123, 1 }, + { 63, 255, 131, 1 }, + { 239, 122, 231, 0 }, + { 224, 255, 254, 0 }, }, + { { 115, 175, 116, 1 }, + { 63, 189, 147, 0 }, + { 151, 122, 231, 0 }, + { 100, 222, 254, 0 }, }, + { { 115, 175, 119, 0 }, + { 55, 255, 147, 0 }, + { 119, 122, 231, 0 }, + { 100, 255, 246, 0 }, }, + { { 115, 174, 152, 0 }, + { 55, 57, 162, 1 }, + { 12, 186, 231, 0 }, + { 162, 206, 118, 0 }, }, + { { 115, 174, 155, 1 }, + { 63, 123, 162, 1 }, + { 236, 186, 231, 0 }, + { 162, 239, 126, 0 }, }, + { { 115, 174, 148, 1 }, + { 63, 57, 178, 0 }, + { 148, 186, 231, 0 }, + { 38, 206, 126, 0 }, }, + { { 115, 174, 151, 0 }, + { 55, 123, 178, 0 }, + { 116, 186, 231, 0 }, + { 38, 239, 118, 0 }, }, + { { 115, 174, 232, 0 }, + { 39, 189, 162, 1 }, + { 11, 186, 231, 0 }, + { 162, 222, 242, 0 }, }, + { { 115, 174, 235, 1 }, + { 47, 255, 162, 1 }, + { 235, 186, 231, 0 }, + { 162, 255, 250, 0 }, }, + { { 115, 174, 228, 1 }, + { 47, 189, 178, 0 }, + { 147, 186, 231, 0 }, + { 38, 222, 250, 0 }, }, + { { 115, 174, 231, 0 }, + { 39, 255, 178, 0 }, + { 115, 186, 231, 0 }, + { 38, 255, 242, 0 }, }, + { { 115, 147, 8, 0 }, + { 38, 49, 193, 1 }, + { 8, 100, 231, 0 }, + { 193, 198, 50, 0 }, }, + { { 115, 147, 11, 1 }, + { 46, 115, 193, 1 }, + { 232, 100, 231, 0 }, + { 193, 231, 58, 0 }, }, + { { 115, 147, 4, 1 }, + { 46, 49, 209, 0 }, + { 144, 100, 231, 0 }, + { 69, 198, 58, 0 }, }, + { { 115, 147, 7, 0 }, + { 38, 115, 209, 0 }, + { 112, 100, 231, 0 }, + { 69, 231, 50, 0 }, }, + { { 115, 147, 120, 0 }, + { 54, 181, 193, 1 }, + { 15, 100, 231, 0 }, + { 193, 214, 182, 0 }, }, + { { 115, 147, 123, 1 }, + { 62, 247, 193, 1 }, + { 239, 100, 231, 0 }, + { 193, 247, 190, 0 }, }, + { { 115, 147, 116, 1 }, + { 62, 181, 209, 0 }, + { 151, 100, 231, 0 }, + { 69, 214, 190, 0 }, }, + { { 115, 147, 119, 0 }, + { 54, 247, 209, 0 }, + { 119, 100, 231, 0 }, + { 69, 247, 182, 0 }, }, + { { 115, 146, 152, 0 }, + { 54, 49, 224, 1 }, + { 12, 164, 231, 0 }, + { 131, 198, 54, 0 }, }, + { { 115, 146, 155, 1 }, + { 62, 115, 224, 1 }, + { 236, 164, 231, 0 }, + { 131, 231, 62, 0 }, }, + { { 115, 146, 148, 1 }, + { 62, 49, 240, 0 }, + { 148, 164, 231, 0 }, + { 7, 198, 62, 0 }, }, + { { 115, 146, 151, 0 }, + { 54, 115, 240, 0 }, + { 116, 164, 231, 0 }, + { 7, 231, 54, 0 }, }, + { { 115, 146, 232, 0 }, + { 38, 181, 224, 1 }, + { 11, 164, 231, 0 }, + { 131, 214, 178, 0 }, }, + { { 115, 146, 235, 1 }, + { 46, 247, 224, 1 }, + { 235, 164, 231, 0 }, + { 131, 247, 186, 0 }, }, + { { 115, 146, 228, 1 }, + { 46, 181, 240, 0 }, + { 147, 164, 231, 0 }, + { 7, 214, 186, 0 }, }, + { { 115, 146, 231, 0 }, + { 38, 247, 240, 0 }, + { 115, 164, 231, 0 }, + { 7, 247, 178, 0 }, }, + { { 115, 157, 8, 0 }, + { 7, 57, 193, 1 }, + { 8, 92, 231, 0 }, + { 193, 206, 112, 0 }, }, + { { 115, 157, 11, 1 }, + { 15, 123, 193, 1 }, + { 232, 92, 231, 0 }, + { 193, 239, 120, 0 }, }, + { { 115, 157, 4, 1 }, + { 15, 57, 209, 0 }, + { 144, 92, 231, 0 }, + { 69, 206, 120, 0 }, }, + { { 115, 157, 7, 0 }, + { 7, 123, 209, 0 }, + { 112, 92, 231, 0 }, + { 69, 239, 112, 0 }, }, + { { 115, 157, 120, 0 }, + { 23, 189, 193, 1 }, + { 15, 92, 231, 0 }, + { 193, 222, 244, 0 }, }, + { { 115, 157, 123, 1 }, + { 31, 255, 193, 1 }, + { 239, 92, 231, 0 }, + { 193, 255, 252, 0 }, }, + { { 115, 157, 116, 1 }, + { 31, 189, 209, 0 }, + { 151, 92, 231, 0 }, + { 69, 222, 252, 0 }, }, + { { 115, 157, 119, 0 }, + { 23, 255, 209, 0 }, + { 119, 92, 231, 0 }, + { 69, 255, 244, 0 }, }, + { { 115, 156, 152, 0 }, + { 23, 57, 224, 1 }, + { 12, 156, 231, 0 }, + { 131, 206, 116, 0 }, }, + { { 115, 156, 155, 1 }, + { 31, 123, 224, 1 }, + { 236, 156, 231, 0 }, + { 131, 239, 124, 0 }, }, + { { 115, 156, 148, 1 }, + { 31, 57, 240, 0 }, + { 148, 156, 231, 0 }, + { 7, 206, 124, 0 }, }, + { { 115, 156, 151, 0 }, + { 23, 123, 240, 0 }, + { 116, 156, 231, 0 }, + { 7, 239, 116, 0 }, }, + { { 115, 156, 232, 0 }, + { 7, 189, 224, 1 }, + { 11, 156, 231, 0 }, + { 131, 222, 240, 0 }, }, + { { 115, 156, 235, 1 }, + { 15, 255, 224, 1 }, + { 235, 156, 231, 0 }, + { 131, 255, 248, 0 }, }, + { { 115, 156, 228, 1 }, + { 15, 189, 240, 0 }, + { 147, 156, 231, 0 }, + { 7, 222, 248, 0 }, }, + { { 115, 156, 231, 0 }, + { 7, 255, 240, 0 }, + { 115, 156, 231, 0 }, + { 7, 255, 240, 0 }, }, +}; + +static unsigned char DICT_4X4_1000_BYTES[][4][2] = + { { { 181, 50 }, + { 235, 72 }, + { 76, 173 }, + { 18, 215 }, }, + { { 15, 154 }, + { 101, 71 }, + { 89, 240 }, + { 226, 166 }, }, + { { 51, 45 }, + { 222, 17 }, + { 180, 204 }, + { 136, 123 }, }, + { { 153, 70 }, + { 193, 60 }, + { 98, 153 }, + { 60, 131 }, }, + { { 84, 158 }, + { 161, 211 }, + { 121, 42 }, + { 203, 133 }, }, + { { 121, 205 }, + { 216, 183 }, + { 179, 158 }, + { 237, 27 }, }, + { { 158, 46 }, + { 135, 93 }, + { 116, 121 }, + { 186, 225 }, }, + { { 196, 242 }, + { 35, 234 }, + { 79, 35 }, + { 87, 196 }, }, + { { 254, 218 }, + { 173, 239 }, + { 91, 127 }, + { 247, 181 }, }, + { { 207, 86 }, + { 101, 252 }, + { 106, 243 }, + { 63, 166 }, }, + { { 249, 145 }, + { 248, 142 }, + { 137, 159 }, + { 113, 31 }, }, + { { 17, 167 }, + { 211, 18 }, + { 229, 136 }, + { 72, 203 }, }, + { { 14, 183 }, + { 55, 86 }, + { 237, 112 }, + { 106, 236 }, }, + { { 42, 15 }, + { 29, 21 }, + { 240, 84 }, + { 168, 184 }, }, + { { 36, 177 }, + { 58, 66 }, + { 141, 36 }, + { 66, 92 }, }, + { { 38, 62 }, + { 47, 81 }, + { 124, 100 }, + { 138, 244 }, }, + { { 70, 101 }, + { 22, 240 }, + { 166, 98 }, + { 15, 104 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{ 153, 33 }, }, + { { 218, 9 }, + { 148, 141 }, + { 144, 91 }, + { 177, 41 }, }, + { { 208, 48 }, + { 162, 136 }, + { 12, 11 }, + { 17, 69 }, }, + { { 216, 148 }, + { 160, 158 }, + { 41, 27 }, + { 121, 5 }, }, + { { 208, 58 }, + { 163, 137 }, + { 92, 11 }, + { 145, 197 }, }, + { { 208, 182 }, + { 163, 154 }, + { 109, 11 }, + { 89, 197 }, }, + { { 208, 117 }, + { 178, 184 }, + { 174, 11 }, + { 29, 77 }, }, + { { 210, 118 }, + { 167, 184 }, + { 110, 75 }, + { 29, 229 }, }, + { { 218, 93 }, + { 180, 189 }, + { 186, 91 }, + { 189, 45 }, }, + { { 218, 53 }, + { 182, 156 }, + { 172, 91 }, + { 57, 109 }, }, + { { 210, 23 }, + { 181, 152 }, + { 232, 75 }, + { 25, 173 }, }, + { { 217, 2 }, + { 193, 140 }, + { 64, 155 }, + { 49, 131 }, }, + { { 211, 232 }, + { 198, 171 }, + { 23, 203 }, + { 213, 99 }, }, + { { 211, 229 }, + { 214, 186 }, + { 167, 203 }, + { 93, 107 }, }, + { { 209, 154 }, + { 225, 139 }, + { 89, 139 }, + { 209, 135 }, }, + { { 209, 246 }, + { 227, 186 }, + { 111, 139 }, + { 93, 199 }, }, + { { 209, 81 }, + { 240, 168 }, + { 138, 139 }, + { 21, 15 }, }, + { { 219, 20 }, + { 228, 156 }, + { 40, 219 }, + { 57, 39 }, }, + { { 211, 62 }, + { 231, 153 }, + { 124, 203 }, + { 153, 231 }, }, + { { 211, 211 }, + { 245, 170 }, + { 203, 203 }, + { 85, 175 }, }, + { { 196, 96 }, + { 2, 232 }, + { 6, 35 }, + { 23, 64 }, }, + { { 204, 167 }, + { 19, 222 }, + { 229, 51 }, + { 123, 200 }, }, + { { 198, 66 }, + { 5, 232 }, + { 66, 99 }, + { 23, 160 }, }, + { { 198, 71 }, + { 21, 248 }, + { 226, 99 }, + { 31, 168 }, }, + { { 206, 231 }, + { 23, 254 }, + { 231, 115 }, + { 127, 232 }, }, + { { 196, 92 }, + { 32, 249 }, + { 58, 35 }, + { 159, 4 }, }, + { { 204, 29 }, + { 48, 221 }, + { 184, 51 }, + { 187, 12 }, }, + { { 204, 53 }, + { 50, 220 }, + { 172, 51 }, + { 59, 76 }, }, + { { 198, 188 }, + { 38, 219 }, + { 61, 99 }, + { 219, 100 }, }, + { { 205, 168 }, + { 66, 207 }, + { 21, 179 }, + { 243, 66 }, }, + { { 197, 12 }, + { 64, 217 }, + { 48, 163 }, + { 155, 2 }, }, + { { 197, 228 }, + { 66, 250 }, + { 39, 163 }, + { 95, 66 }, }, + { { 197, 194 }, + { 65, 234 }, + { 67, 163 }, + { 87, 130 }, }, + { { 205, 45 }, + { 82, 221 }, + { 180, 179 }, + { 187, 74 }, }, + { { 205, 89 }, + { 112, 237 }, + { 154, 179 }, + { 183, 14 }, }, + { { 205, 149 }, + { 112, 222 }, + { 169, 179 }, + { 123, 14 }, }, + { { 197, 147 }, + { 113, 202 }, + { 201, 163 }, + { 83, 142 }, }, + { { 199, 95 }, + { 117, 249 }, + { 250, 227 }, + { 159, 174 }, }, + { { 212, 197 }, + { 144, 250 }, + { 163, 43 }, + { 95, 9 }, }, + { { 222, 136 }, + { 132, 207 }, + { 17, 123 }, + { 243, 33 }, }, + { { 214, 36 }, + { 134, 216 }, + { 36, 107 }, + { 27, 97 }, }, + { { 222, 236 }, + { 134, 255 }, + { 55, 123 }, + { 255, 97 }, }, + { { 214, 226 }, + { 135, 234 }, + { 71, 107 }, + { 87, 225 }, }, + { { 222, 198 }, + { 133, 254 }, + { 99, 123 }, + { 127, 161 }, }, + { { 222, 35 }, + { 151, 204 }, + { 196, 123 }, + { 51, 233 }, }, + { { 220, 220 }, + { 160, 255 }, + { 59, 59 }, + { 255, 5 }, }, + { { 220, 26 }, + { 161, 205 }, + { 88, 59 }, + { 179, 133 }, }, + { { 212, 17 }, + { 176, 200 }, + { 136, 43 }, + { 19, 13 }, }, + { { 222, 84 }, + { 164, 252 }, + { 42, 123 }, + { 63, 37 }, }, + { { 214, 148 }, + { 164, 218 }, + { 41, 107 }, + { 91, 37 }, }, + { { 222, 157 }, + { 180, 223 }, + { 185, 123 }, + { 251, 45 }, }, + { { 221, 129 }, + { 208, 206 }, + { 129, 187 }, + { 115, 11 }, }, + { { 213, 165 }, + { 210, 218 }, + { 165, 171 }, + { 91, 75 }, }, + { { 215, 172 }, + { 198, 219 }, + { 53, 235 }, + { 219, 99 }, }, + { { 215, 102 }, + { 199, 248 }, + { 102, 235 }, + { 31, 227 }, }, + { { 223, 169 }, + { 214, 207 }, + { 149, 251 }, + { 243, 107 }, }, + { { 213, 220 }, + { 224, 251 }, + { 59, 171 }, + { 223, 7 }, }, + { { 221, 31 }, + { 241, 221 }, + { 248, 187 }, + { 187, 143 }, }, + { { 223, 240 }, + { 230, 238 }, + { 15, 251 }, + { 119, 103 }, }, + { { 226, 72 }, + { 12, 169 }, + { 18, 71 }, + { 149, 48 }, }, + { { 226, 232 }, + { 14, 171 }, + { 23, 71 }, + { 213, 112 }, }, + { { 226, 7 }, + { 29, 152 }, + { 224, 71 }, + { 25, 184 }, }, + { { 224, 93 }, + { 56, 185 }, + { 186, 7 }, + { 157, 28 }, }, + { { 234, 245 }, + { 62, 190 }, + { 175, 87 }, + { 125, 124 }, }, + { { 235, 38 }, + { 79, 156 }, + { 100, 215 }, + { 57, 242 }, }, + { { 235, 237 }, + { 94, 191 }, + { 183, 215 }, + { 253, 122 }, }, + { { 225, 82 }, + { 105, 168 }, + { 74, 135 }, + { 21, 150 }, }, + { { 225, 126 }, + { 107, 185 }, + { 126, 135 }, + { 157, 214 }, }, + { { 233, 219 }, + { 121, 175 }, + { 219, 151 }, + { 245, 158 }, }, + { { 248, 6 }, + { 137, 156 }, + { 96, 31 }, + { 57, 145 }, }, + { { 240, 238 }, + { 139, 187 }, + { 119, 15 }, + { 221, 209 }, }, + { { 248, 161 }, + { 154, 142 }, + { 133, 31 }, + { 113, 89 }, }, + { { 250, 0 }, + { 140, 140 }, + { 0, 95 }, + { 49, 49 }, }, + { { 250, 194 }, + { 141, 174 }, + { 67, 95 }, + { 117, 177 }, }, + { { 240, 155 }, + { 185, 139 }, + { 217, 15 }, + { 209, 157 }, }, + { { 250, 244 }, + { 174, 190 }, + { 47, 95 }, + { 125, 117 }, }, + { { 250, 60 }, + { 174, 157 }, + { 60, 95 }, + { 185, 117 }, }, + { { 242, 252 }, + { 174, 187 }, + { 63, 79 }, + { 221, 117 }, }, + { { 242, 189 }, + { 190, 155 }, + { 189, 79 }, + { 217, 125 }, }, + { { 242, 147 }, + { 189, 138 }, + { 201, 79 }, + { 81, 189 }, }, + { { 241, 96 }, + { 202, 168 }, + { 6, 143 }, + { 21, 83 }, }, + { { 249, 236 }, + { 202, 191 }, + { 55, 159 }, + { 253, 83 }, }, + { { 241, 70 }, + { 201, 184 }, + { 98, 143 }, + { 29, 147 }, }, + { { 249, 225 }, + { 218, 174 }, + { 135, 159 }, + { 117, 91 }, }, + { { 243, 72 }, + { 204, 169 }, + { 18, 207 }, + { 149, 51 }, }, + { { 243, 174 }, + { 207, 155 }, + { 117, 207 }, + { 217, 243 }, }, + { { 243, 193 }, + { 220, 170 }, + { 131, 207 }, + { 85, 59 }, }, + { { 243, 139 }, + { 221, 139 }, + { 209, 207 }, + { 209, 187 }, }, + { { 243, 167 }, + { 223, 154 }, + { 229, 207 }, + { 89, 251 }, }, + { { 241, 115 }, + { 251, 168 }, + { 206, 143 }, + { 21, 223 }, }, + { { 241, 151 }, + { 249, 154 }, + { 233, 143 }, + { 89, 159 }, }, + { { 243, 244 }, + { 238, 186 }, + { 47, 207 }, + { 93, 119 }, }, + { { 251, 50 }, + { 239, 140 }, + { 76, 223 }, + { 49, 247 }, }, + { { 228, 7 }, + { 25, 216 }, + { 224, 39 }, + { 27, 152 }, }, + { { 230, 77 }, + { 28, 249 }, + { 178, 103 }, + { 159, 56 }, }, + { { 236, 85 }, + { 56, 252 }, + { 170, 55 }, + { 63, 28 }, }, + { { 237, 192 }, + { 72, 238 }, + { 3, 183 }, + { 119, 18 }, }, + { { 237, 133 }, + { 88, 222 }, + { 161, 183 }, + { 123, 26 }, }, + { { 239, 162 }, + { 79, 206 }, + { 69, 247 }, + { 115, 242 }, }, + { { 231, 78 }, + { 77, 249 }, + { 114, 231 }, + { 159, 178 }, }, + { { 229, 213 }, + { 120, 250 }, + { 171, 167 }, + { 95, 30 }, }, + { { 239, 80 }, + { 108, 236 }, + { 10, 247 }, + { 55, 54 }, }, + { { 244, 34 }, + { 139, 200 }, + { 68, 47 }, + { 19, 209 }, }, + { { 244, 137 }, + { 152, 203 }, + { 145, 47 }, + { 211, 25 }, }, + { { 244, 41 }, + { 154, 201 }, + { 148, 47 }, + { 147, 89 }, }, + { { 246, 106 }, + { 143, 233 }, + { 86, 111 }, + { 151, 241 }, }, + { { 254, 11 }, + { 157, 205 }, + { 208, 127 }, + { 179, 185 }, }, + { { 254, 111 }, + { 159, 253 }, + { 246, 127 }, + { 191, 249 }, }, + { { 244, 149 }, + { 184, 218 }, + { 169, 47 }, + { 91, 29 }, }, + { { 244, 53 }, + { 186, 216 }, + { 172, 47 }, + { 27, 93 }, }, + { { 244, 31 }, + { 185, 217 }, + { 248, 47 }, + { 155, 157 }, }, + { { 246, 176 }, + { 174, 202 }, + { 13, 111 }, + { 83, 117 }, }, + { { 245, 232 }, + { 202, 235 }, + { 23, 175 }, + { 215, 83 }, }, + { { 245, 197 }, + { 216, 250 }, + { 163, 175 }, + { 95, 27 }, }, + { { 253, 35 }, + { 219, 204 }, + { 196, 191 }, + { 51, 219 }, }, + { { 255, 192 }, + { 204, 238 }, + { 3, 255 }, + { 119, 51 }, }, + { { 247, 204 }, + { 204, 251 }, + { 51, 239 }, + { 223, 51 }, }, + { { 247, 233 }, + { 222, 235 }, + { 151, 239 }, + { 215, 123 }, }, + { { 245, 188 }, + { 234, 219 }, + { 61, 175 }, + { 219, 87 }, }, + { { 253, 246 }, + { 235, 254 }, + { 111, 191 }, + { 127, 215 }, }, + { { 245, 217 }, + { 248, 235 }, + { 155, 175 }, + { 215, 31 }, }, + { { 253, 151 }, + { 249, 222 }, + { 233, 191 }, + { 123, 159 }, }, + { { 253, 63 }, + { 251, 221 }, + { 252, 191 }, + { 187, 223 }, }, + { { 255, 156 }, + { 236, 223 }, + { 57, 255 }, + { 251, 55 }, }, + { { 255, 90 }, + { 237, 237 }, + { 90, 255 }, + { 183, 183 }, }, + { { 247, 254 }, + { 239, 251 }, + { 127, 239 }, + { 223, 247 }, }, + { { 255, 17 }, + { 252, 204 }, + { 136, 255 }, + { 51, 63 }, }, + { { 247, 191 }, + { 255, 219 }, + { 253, 239 }, + { 219, 255 }, }, }; + +static unsigned char DICT_5X5_1000_BYTES[][4][4] = + { { { 162, 217, 94, 0 }, + { 82, 46, 217, 1 }, + { 61, 77, 162, 1 }, + { 205, 186, 37, 0 }, }, + { { 14, 3, 115, 0 }, + { 176, 198, 133, 0 }, + { 103, 96, 56, 0 }, + { 80, 177, 134, 1 }, }, + { { 215, 135, 110, 1 }, + { 47, 151, 157, 1 }, + { 187, 112, 245, 1 }, + { 220, 244, 250, 0 }, }, + { { 129, 202, 251, 1 }, + { 122, 222, 40, 1 }, + { 239, 169, 192, 1 }, + { 138, 61, 175, 0 }, }, + { { 215, 90, 146, 0 }, + { 116, 27, 236, 0 }, + { 36, 173, 117, 1 }, + { 27, 236, 23, 0 }, }, + { { 234, 4, 22, 1 }, + { 153, 35, 152, 0 }, + { 180, 16, 43, 1 }, + { 12, 226, 76, 1 }, }, + { { 105, 235, 246, 0 }, + { 242, 191, 51, 0 }, + { 55, 235, 203, 0 }, + { 102, 126, 167, 1 }, }, + { { 113, 10, 53, 1 }, + { 60, 249, 16, 0 }, + { 214, 40, 71, 0 }, + { 4, 79, 158, 0 }, }, + { { 134, 176, 153, 0 }, + { 18, 64, 238, 1 }, + { 76, 134, 176, 1 }, + { 187, 129, 36, 0 }, }, + { { 152, 159, 210, 1 }, + { 191, 14, 105, 0 }, + { 165, 252, 140, 1 }, + { 75, 56, 126, 1 }, }, + { { 158, 119, 1, 1 }, + { 237, 64, 207, 0 }, + { 192, 119, 60, 1 }, + { 121, 129, 91, 1 }, }, + { { 209, 109, 96, 0 }, + { 69, 157, 11, 0 }, + { 3, 91, 69, 1 }, + { 104, 92, 209, 0 }, }, + { { 243, 21, 136, 1 }, + { 13, 49, 233, 1 }, + { 136, 212, 103, 1 }, + { 203, 198, 88, 0 }, }, + { { 47, 56, 179, 0 }, + { 144, 250, 230, 0 }, + { 102, 142, 122, 0 }, + { 51, 175, 132, 1 }, }, + { { 254, 126, 84, 0 }, + { 245, 45, 222, 0 }, + { 21, 63, 63, 1 }, + { 61, 218, 87, 1 }, }, + { { 40, 241, 191, 1 }, + { 218, 226, 115, 1 }, + { 254, 199, 138, 0 }, + { 231, 35, 173, 1 }, }, + { { 75, 211, 172, 0 }, + { 226, 145, 241, 1 }, + { 26, 229, 233, 0 }, + { 199, 196, 163, 1 }, }, + { { 95, 81, 55, 1 }, + { 220, 211, 213, 0 }, + { 246, 69, 125, 0 }, + { 85, 229, 157, 1 }, }, + { { 123, 38, 226, 0 }, + { 165, 183, 162, 0 }, + { 35, 178, 111, 0 }, + { 34, 246, 210, 1 }, }, + { { 131, 14, 244, 0 }, + { 49, 156, 184, 0 }, + { 23, 184, 96, 1 }, + { 14, 156, 198, 0 }, }, + { { 150, 237, 58, 1 }, + { 95, 138, 143, 1 }, + { 174, 91, 180, 1 }, + { 248, 168, 253, 0 }, }, + { { 168, 114, 32, 0 }, + { 224, 160, 74, 0 }, + { 2, 39, 10, 1 }, + { 41, 2, 131, 1 }, }, + { { 181, 134, 80, 1 }, + { 63, 52, 12, 0 }, + { 133, 48, 214, 1 }, + { 24, 22, 126, 0 }, }, + { { 93, 9, 111, 0 }, + { 132, 223, 21, 1 }, + { 123, 72, 93, 0 }, + { 212, 125, 144, 1 }, }, + { { 206, 104, 17, 1 }, + { 216, 73, 142, 0 }, + { 196, 11, 57, 1 }, + { 56, 201, 13, 1 }, }, + { { 210, 204, 185, 0 }, + { 87, 201, 168, 1 }, + { 78, 153, 165, 1 }, + { 138, 201, 245, 0 }, }, + { { 225, 231, 69, 1 }, + { 107, 117, 27, 0 }, + { 209, 115, 195, 1 }, + { 108, 87, 107, 0 }, }, + { { 17, 33, 35, 0 }, + { 4, 210, 3, 0 }, + { 98, 66, 68, 0 }, + { 96, 37, 144, 0 }, }, + { { 29, 203, 57, 0 }, + { 246, 216, 5, 1 }, + { 78, 105, 220, 0 }, + { 208, 13, 183, 1 }, }, + { { 18, 17, 29, 1 }, + { 28, 64, 209, 1 }, + { 220, 68, 36, 0 }, + { 197, 129, 28, 0 }, }, + { { 19, 155, 183, 0 }, + { 54, 218, 241, 0 }, + { 118, 236, 228, 0 }, + { 71, 173, 182, 0 }, }, + { { 27, 68, 57, 1 }, + { 221, 208, 128, 1 }, + { 206, 17, 108, 0 }, + { 128, 133, 221, 1 }, }, + { { 32, 104, 103, 0 }, + { 64, 238, 18, 0 }, + { 115, 11, 2, 0 }, + { 36, 59, 129, 0 }, }, + { { 37, 85, 100, 0 }, + { 65, 180, 85, 0 }, + { 19, 85, 82, 0 }, + { 85, 22, 193, 0 }, }, + { { 35, 33, 221, 0 }, + { 16, 116, 179, 1 }, + { 93, 194, 98, 0 }, + { 230, 151, 4, 0 }, }, + { { 61, 55, 245, 0 }, + { 181, 244, 119, 0 }, + { 87, 246, 94, 0 }, + { 119, 23, 214, 1 }, }, + { { 76, 197, 86, 0 }, + { 211, 7, 21, 0 }, + { 53, 81, 153, 0 }, + { 84, 112, 101, 1 }, }, + { { 65, 104, 128, 1 }, + { 72, 25, 34, 0 }, + { 128, 139, 65, 0 }, + { 34, 76, 9, 0 }, }, + { { 77, 86, 142, 1 }, + { 233, 19, 116, 1 }, + { 184, 181, 89, 0 }, + { 151, 100, 75, 1 }, }, + { { 67, 30, 57, 0 }, + { 49, 217, 192, 1 }, + { 78, 60, 97, 0 }, + { 129, 205, 198, 0 }, }, + { { 86, 148, 18, 1 }, + { 31, 3, 196, 0 }, + { 164, 20, 181, 0 }, + { 17, 224, 124, 0 }, }, + { { 82, 151, 207, 0 }, + { 39, 71, 241, 1 }, + { 121, 244, 165, 0 }, + { 199, 241, 114, 0 }, }, + { { 108, 36, 251, 1 }, + { 153, 231, 38, 1 }, + { 239, 146, 27, 0 }, + { 178, 115, 204, 1 }, }, + { { 97, 132, 236, 1 }, + { 11, 181, 48, 1 }, + { 155, 144, 195, 0 }, + { 134, 86, 232, 0 }, }, + { { 109, 63, 24, 1 }, + { 185, 57, 71, 1 }, + { 140, 126, 91, 0 }, + { 241, 78, 78, 1 }, }, + { { 116, 177, 61, 0 }, + { 22, 225, 87, 1 }, + { 94, 70, 151, 0 }, + { 245, 67, 180, 0 }, }, + { { 116, 220, 203, 1 }, + { 79, 111, 100, 1 }, + { 233, 157, 151, 0 }, + { 147, 123, 121, 0 }, }, + { { 124, 164, 3, 0 }, + { 135, 99, 6, 0 }, + { 96, 18, 159, 0 }, + { 48, 99, 112, 1 }, }, + { { 122, 200, 146, 1 }, + { 222, 43, 160, 0 }, + { 164, 137, 175, 0 }, + { 2, 234, 61, 1 }, }, + { { 123, 91, 235, 1 }, + { 236, 255, 225, 1 }, + { 235, 237, 111, 0 }, + { 195, 255, 155, 1 }, }, + { { 141, 172, 114, 0 }, + { 147, 158, 14, 0 }, + { 39, 26, 216, 1 }, + { 56, 60, 228, 1 }, }, + { { 141, 105, 60, 1 }, + { 216, 152, 31, 1 }, + { 158, 75, 88, 1 }, + { 252, 12, 141, 1 }, }, + { { 143, 28, 5, 1 }, + { 137, 88, 220, 0 }, + { 208, 28, 120, 1 }, + { 29, 141, 72, 1 }, }, + { { 139, 74, 34, 1 }, + { 232, 154, 136, 0 }, + { 162, 41, 104, 1 }, + { 8, 172, 139, 1 }, }, + { { 151, 253, 165, 0 }, + { 71, 216, 255, 0 }, + { 82, 223, 244, 1 }, + { 127, 141, 241, 0 }, }, + { { 172, 101, 198, 1 }, + { 201, 38, 63, 0 }, + { 177, 211, 26, 1 }, + { 126, 50, 73, 1 }, }, + { { 172, 195, 248, 0 }, + { 242, 164, 45, 1 }, + { 15, 225, 154, 1 }, + { 218, 18, 167, 1 }, }, + { { 161, 23, 239, 1 }, + { 41, 246, 121, 1 }, + { 251, 244, 66, 1 }, + { 207, 55, 202, 0 }, }, + { { 167, 9, 19, 1 }, + { 24, 122, 141, 0 }, + { 228, 72, 114, 1 }, + { 88, 175, 12, 0 }, }, + { { 171, 111, 145, 0 }, + { 241, 120, 171, 0 }, + { 68, 251, 106, 1 }, + { 106, 143, 71, 1 }, }, + { { 185, 237, 248, 1 }, + { 223, 188, 43, 1 }, + { 143, 219, 206, 1 }, + { 234, 30, 253, 1 }, }, + { { 178, 100, 158, 0 }, + { 85, 34, 186, 1 }, + { 60, 147, 38, 1 }, + { 174, 162, 85, 0 }, }, + { { 190, 93, 195, 0 }, + { 197, 110, 237, 0 }, + { 97, 221, 62, 1 }, + { 91, 187, 81, 1 }, }, + { { 196, 5, 67, 1 }, + { 9, 71, 13, 0 }, + { 225, 80, 17, 1 }, + { 88, 113, 72, 0 }, }, + { { 200, 163, 238, 1 }, + { 170, 135, 59, 1 }, + { 187, 226, 137, 1 }, + { 238, 112, 170, 1 }, }, + { { 194, 117, 197, 0 }, + { 65, 69, 251, 0 }, + { 81, 215, 33, 1 }, + { 111, 209, 65, 0 }, }, + { { 198, 194, 214, 1 }, + { 122, 7, 188, 0 }, + { 181, 161, 177, 1 }, + { 30, 240, 47, 0 }, }, + { { 217, 102, 212, 1 }, + { 253, 21, 58, 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23, 25, 1 }, + { 57, 65, 69, 1 }, }, + { { 193, 8, 90, 1 }, + { 24, 31, 8, 1 }, + { 173, 8, 65, 1 }, + { 136, 124, 12, 0 }, }, + { { 193, 47, 130, 1 }, + { 41, 27, 43, 0 }, + { 160, 250, 65, 1 }, + { 106, 108, 74, 0 }, }, + { { 193, 35, 120, 0 }, + { 48, 149, 11, 1 }, + { 15, 98, 65, 1 }, + { 232, 84, 134, 0 }, }, + { { 198, 52, 219, 1 }, + { 25, 71, 238, 1 }, + { 237, 150, 49, 1 }, + { 187, 241, 76, 0 }, }, + { { 198, 164, 244, 1 }, + { 27, 133, 190, 0 }, + { 151, 146, 177, 1 }, + { 62, 208, 236, 0 }, }, + { { 194, 228, 25, 0 }, + { 83, 65, 138, 1 }, + { 76, 19, 161, 1 }, + { 168, 193, 101, 0 }, }, + { { 195, 29, 35, 0 }, + { 1, 219, 201, 0 }, + { 98, 92, 97, 1 }, + { 73, 237, 192, 0 }, }, + { { 195, 242, 196, 1 }, + { 106, 21, 250, 0 }, + { 145, 167, 225, 1 }, + { 47, 212, 43, 0 }, }, + { { 199, 95, 223, 0 }, + { 113, 95, 253, 1 }, + { 125, 253, 113, 1 }, + { 223, 253, 71, 0 }, }, + { { 203, 101, 189, 0 }, + { 209, 209, 187, 1 }, + { 94, 211, 105, 1 }, + { 238, 197, 197, 1 }, }, + { { 203, 199, 15, 1 }, + { 235, 83, 153, 1 }, + { 248, 113, 233, 1 }, + { 204, 229, 107, 1 }, }, + { { 207, 246, 185, 0 }, + { 243, 209, 238, 1 }, + { 78, 183, 249, 1 }, + { 187, 197, 231, 1 }, }, + { { 212, 84, 239, 0 }, + { 69, 199, 124, 1 }, + { 123, 149, 21, 1 }, + { 159, 113, 209, 0 }, }, + { { 212, 251, 220, 0 }, + { 118, 13, 127, 1 }, + { 29, 239, 149, 1 }, + { 255, 88, 55, 0 }, }, + { { 220, 232, 84, 0 }, + { 214, 13, 30, 0 }, + { 21, 11, 157, 1 }, + { 60, 88, 53, 1 }, }, + { { 213, 177, 150, 0 }, + { 22, 19, 127, 0 }, + { 52, 198, 213, 1 }, + { 127, 100, 52, 0 }, }, + { { 209, 159, 7, 1 }, + { 47, 91, 89, 0 }, + { 240, 124, 197, 1 }, + { 77, 109, 122, 0 }, }, + { { 209, 93, 126, 1 }, + { 93, 159, 89, 1 }, + { 191, 93, 69, 1 }, + { 205, 124, 221, 0 }, }, + { { 217, 164, 134, 1 }, + { 143, 19, 58, 0 }, + { 176, 146, 205, 1 }, + { 46, 100, 120, 1 }, }, + { { 221, 9, 48, 1 }, + { 156, 153, 13, 0 }, + { 134, 72, 93, 1 }, + { 88, 76, 156, 1 }, }, + { { 217, 180, 57, 1 }, + { 159, 209, 74, 1 }, + { 206, 22, 205, 1 }, + { 169, 69, 252, 1 }, }, + { { 221, 171, 105, 1 }, + { 174, 221, 15, 1 }, + { 203, 106, 221, 1 }, + { 248, 93, 186, 1 }, }, + { { 217, 203, 66, 0 }, + { 230, 31, 9, 0 }, + { 33, 105, 205, 1 }, + { 72, 124, 51, 1 }, }, + { { 210, 33, 13, 0 }, + { 4, 65, 155, 1 }, + { 88, 66, 37, 1 }, + { 236, 193, 16, 0 }, }, + { { 214, 73, 4, 0 }, + { 68, 9, 157, 0 }, + { 16, 73, 53, 1 }, + { 92, 200, 17, 0 }, }, + { { 210, 216, 219, 0 }, + { 86, 79, 232, 1 }, + { 109, 141, 165, 1 }, + { 139, 249, 53, 0 }, }, + { { 218, 63, 69, 1 }, + { 173, 77, 219, 0 }, + { 209, 126, 45, 1 }, + { 109, 217, 90, 1 }, }, + { { 218, 125, 218, 0 }, + { 213, 15, 235, 1 }, + { 45, 223, 45, 1 }, + { 235, 248, 85, 1 }, }, + { { 218, 211, 230, 0 }, + { 230, 135, 249, 0 }, + { 51, 229, 173, 1 }, + { 79, 240, 179, 1 }, }, + { { 211, 51, 189, 0 }, + { 52, 209, 251, 1 }, + { 94, 230, 101, 1 }, + { 239, 197, 150, 0 }, }, + { { 215, 225, 237, 1 }, + { 78, 213, 191, 1 }, + { 219, 195, 245, 1 }, + { 254, 213, 185, 0 }, }, + { { 219, 197, 122, 0 }, + { 215, 151, 137, 1 }, + { 47, 81, 237, 1 }, + { 200, 244, 245, 1 }, }, + { { 224, 128, 59, 1 }, + { 26, 227, 8, 1 }, + { 238, 0, 131, 1 }, + { 136, 99, 172, 0 }, }, + { { 224, 207, 105, 1 }, + { 107, 237, 9, 1 }, + { 203, 121, 131, 1 }, + { 200, 91, 235, 0 }, }, + { { 228, 71, 48, 1 }, + { 121, 161, 13, 0 }, + { 134, 113, 19, 1 }, + { 88, 66, 207, 0 }, }, + { { 232, 29, 86, 1 }, + { 153, 47, 89, 0 }, + { 181, 92, 11, 1 }, + { 77, 122, 76, 1 }, }, + { { 232, 243, 72, 1 }, + { 234, 37, 75, 1 }, + { 137, 103, 139, 1 }, + { 233, 82, 43, 1 }, }, + { { 232, 254, 175, 0 }, + { 227, 235, 122, 1 }, + { 122, 191, 139, 1 }, + { 175, 107, 227, 1 }, }, + { { 236, 231, 159, 0 }, + { 243, 99, 63, 1 }, + { 124, 243, 155, 1 }, + { 254, 99, 103, 1 }, }, + { { 225, 60, 212, 1 }, + { 25, 61, 122, 0 }, + { 149, 158, 67, 1 }, + { 47, 94, 76, 0 }, }, + { { 229, 204, 106, 1 }, + { 75, 191, 12, 1 }, + { 171, 25, 211, 1 }, + { 152, 126, 233, 0 }, }, + { { 233, 175, 154, 0 }, + { 179, 59, 43, 1 }, + { 44, 250, 203, 1 }, + { 234, 110, 102, 1 }, }, + { { 227, 0, 237, 0 }, + { 0, 245, 184, 1 }, + { 91, 128, 99, 1 }, + { 142, 215, 128, 0 }, }, + { { 231, 177, 14, 0 }, + { 2, 51, 223, 1 }, + { 56, 70, 243, 1 }, + { 253, 230, 32, 0 }, }, + { { 227, 192, 126, 0 }, + { 82, 183, 152, 1 }, + { 63, 1, 227, 1 }, + { 140, 246, 165, 0 }, }, + { { 235, 140, 163, 0 }, + { 131, 251, 168, 0 }, + { 98, 152, 235, 1 }, + { 10, 239, 224, 1 }, }, + { { 235, 159, 109, 1 }, + { 171, 253, 217, 1 }, + { 219, 124, 235, 1 }, + { 205, 223, 234, 1 }, }, + { { 239, 65, 11, 0 }, + { 192, 115, 141, 1 }, + { 104, 65, 123, 1 }, + { 216, 231, 1, 1 }, }, + { { 239, 194, 195, 0 }, + { 226, 119, 172, 0 }, + { 97, 161, 251, 1 }, + { 26, 247, 35, 1 }, }, + { { 240, 168, 32, 0 }, + { 6, 169, 10, 0 }, + { 2, 10, 135, 1 }, + { 40, 74, 176, 0 }, }, + { { 244, 25, 211, 0 }, + { 20, 111, 109, 0 }, + { 101, 204, 23, 1 }, + { 91, 123, 20, 0 }, }, + { { 244, 133, 191, 1 }, + { 31, 227, 61, 1 }, + { 254, 208, 151, 1 }, + { 222, 99, 252, 0 }, }, + { { 240, 106, 204, 0 }, + { 100, 45, 58, 1 }, + { 25, 171, 7, 1 }, + { 174, 90, 19, 0 }, }, + { { 240, 123, 107, 1 }, + { 108, 239, 75, 1 }, + { 235, 111, 7, 1 }, + { 233, 123, 155, 0 }, }, + { { 244, 251, 170, 0 }, + { 102, 171, 111, 1 }, + { 42, 239, 151, 1 }, + { 251, 106, 179, 0 }, }, + { { 252, 198, 47, 0 }, + { 231, 227, 28, 1 }, + { 122, 49, 159, 1 }, + { 156, 99, 243, 1 }, }, + { { 248, 111, 16, 0 }, + { 245, 41, 11, 0 }, + { 4, 123, 15, 1 }, + { 104, 74, 87, 1 }, }, + { { 252, 127, 120, 1 }, + { 253, 173, 79, 1 }, + { 143, 127, 31, 1 }, + { 249, 90, 223, 1 }, }, + { { 241, 171, 217, 0 }, + { 54, 125, 43, 1 }, + { 77, 234, 199, 1 }, + { 234, 95, 54, 0 }, }, + { { 245, 81, 143, 1 }, + { 76, 115, 125, 1 }, + { 248, 197, 87, 1 }, + { 223, 103, 25, 0 }, }, + { { 241, 248, 166, 1 }, + { 78, 187, 122, 0 }, + { 178, 143, 199, 1 }, + { 47, 110, 185, 0 }, }, + { { 241, 86, 24, 0 }, + { 117, 49, 72, 1 }, + { 12, 53, 71, 1 }, + { 137, 70, 87, 0 }, }, + { { 253, 132, 196, 0 }, + { 135, 53, 60, 0 }, + { 17, 144, 223, 1 }, + { 30, 86, 112, 1 }, }, + { { 249, 141, 114, 1 }, + { 159, 191, 9, 0 }, + { 167, 88, 207, 1 }, + { 72, 126, 252, 1 }, }, + { { 253, 15, 85, 1 }, + { 189, 125, 29, 0 }, + { 213, 120, 95, 1 }, + { 92, 95, 94, 1 }, }, + { { 242, 156, 111, 1 }, + { 15, 239, 216, 1 }, + { 251, 28, 167, 1 }, + { 141, 251, 248, 0 }, }, + { { 246, 136, 24, 1 }, + { 30, 41, 140, 1 }, + { 140, 8, 183, 1 }, + { 152, 202, 60, 0 }, }, + { { 246, 7, 197, 0 }, + { 37, 101, 189, 0 }, + { 81, 240, 55, 1 }, + { 94, 211, 82, 0 }, }, + { { 242, 65, 215, 0 }, + { 84, 103, 185, 0 }, + { 117, 193, 39, 1 }, + { 78, 243, 21, 0 }, }, + { { 246, 241, 27, 0 }, + { 86, 99, 207, 1 }, + { 108, 71, 183, 1 }, + { 249, 227, 53, 0 }, }, + { { 242, 230, 203, 1 }, + { 111, 103, 170, 1 }, + { 233, 179, 167, 1 }, + { 170, 243, 123, 0 }, }, + { { 250, 213, 32, 1 }, + { 207, 161, 201, 0 }, + { 130, 85, 175, 1 }, + { 73, 194, 249, 1 }, }, + { { 254, 67, 233, 0 }, + { 228, 229, 173, 1 }, + { 75, 225, 63, 1 }, + { 218, 211, 147, 1 }, }, + { { 243, 251, 142, 0 }, + { 102, 59, 251, 1 }, + { 56, 239, 231, 1 }, + { 239, 238, 51, 0 }, }, + { { 255, 187, 218, 0 }, + { 182, 63, 239, 1 }, + { 45, 238, 255, 1 }, + { 251, 254, 54, 1 }, }, + { { 251, 201, 14, 1 }, + { 206, 59, 153, 1 }, + { 184, 73, 239, 1 }, + { 204, 238, 57, 1 }, }, }; + +static unsigned char DICT_6X6_1000_BYTES[][4][5] = + { { { 30, 61, 216, 42, 6 }, + { 227, 186, 70, 49, 9 }, + { 101, 65, 187, 199, 8 }, + { 152, 198, 37, 220, 7 }, }, + { { 14, 251, 163, 137, 1 }, + { 215, 230, 24, 5, 14 }, + { 137, 28, 93, 247, 0 }, + { 122, 1, 134, 126, 11 }, }, + { { 21, 144, 126, 172, 13 }, + { 236, 105, 87, 80, 6 }, + { 179, 87, 224, 154, 8 }, + { 96, 174, 169, 99, 7 }, }, + { { 201, 27, 48, 105, 14 }, + { 66, 50, 75, 222, 12 }, + { 121, 96, 205, 137, 3 }, + { 55, 189, 36, 196, 2 }, }, + { { 214, 7, 214, 225, 5 }, + { 164, 203, 74, 191, 2 }, + { 168, 118, 190, 6, 11 }, + { 79, 213, 45, 50, 5 }, }, + { { 216, 232, 224, 230, 8 }, + { 43, 140, 19, 138, 15 }, + { 22, 112, 113, 113, 11 }, + { 245, 28, 131, 29, 4 }, }, + { { 66, 104, 180, 31, 5 }, + { 13, 165, 192, 149, 13 }, + { 175, 130, 209, 100, 2 }, + { 186, 144, 58, 91, 0 }, }, + { { 136, 165, 15, 41, 10 }, + { 19, 115, 23, 38, 0 }, + { 89, 79, 10, 81, 1 }, + { 6, 78, 140, 236, 8 }, }, + { { 48, 125, 82, 79, 13 }, + { 109, 110, 97, 60, 9 }, + { 191, 36, 171, 224, 12 }, + { 147, 200, 103, 107, 6 }, }, + { { 60, 47, 52, 179, 12 }, + { 131, 11, 235, 52, 15 }, + { 60, 210, 207, 67, 12 }, + { 242, 205, 125, 12, 1 }, }, + { { 69, 223, 199, 78, 3 }, + { 252, 247, 24, 232, 9 }, + { 199, 46, 63, 186, 2 }, + { 145, 113, 142, 243, 15 }, }, + { { 72, 216, 91, 37, 7 }, + { 126, 84, 86, 148, 8 }, + { 234, 77, 161, 177, 2 }, + { 18, 150, 162, 167, 14 }, }, + { { 113, 5, 88, 252, 6 }, + { 40, 58, 230, 248, 2 }, + { 99, 241, 170, 8, 14 }, + { 65, 246, 117, 193, 4 }, }, + { { 134, 220, 250, 208, 7 }, + { 228, 212, 212, 59, 14 }, + { 224, 181, 243, 182, 1 }, + { 125, 194, 178, 178, 7 }, }, + { { 141, 114, 169, 63, 6 }, + { 219, 180, 206, 70, 5 }, + { 111, 201, 84, 235, 1 }, + { 166, 39, 50, 221, 11 }, }, + { { 162, 184, 157, 205, 14 }, + { 89, 177, 117, 31, 10 }, + { 123, 59, 145, 212, 5 }, + { 95, 138, 232, 217, 10 }, }, + { { 9, 253, 30, 156, 4 }, + { 75, 103, 212, 112, 10 }, + { 35, 151, 139, 249, 0 }, + { 80, 226, 190, 109, 2 }, }, + { { 21, 77, 189, 24, 15 }, + { 148, 191, 197, 112, 12 }, + { 241, 139, 219, 42, 8 }, + { 48, 234, 63, 210, 9 }, }, + { { 48, 10, 49, 14, 2 }, + { 24, 56, 40, 16, 13 }, + { 71, 8, 197, 0, 12 }, + { 176, 129, 65, 193, 8 }, }, + { { 72, 7, 239, 175, 13 }, + { 62, 227, 79, 164, 7 }, + { 191, 95, 126, 1, 2 }, + { 226, 95, 44, 119, 12 }, }, + { { 86, 223, 17, 219, 6 }, + { 208, 62, 216, 189, 11 }, + { 109, 184, 143, 182, 10 }, + { 219, 209, 183, 192, 11 }, }, + { { 102, 136, 50, 116, 12 }, + { 136, 64, 243, 153, 12 }, + { 50, 228, 193, 22, 6 }, + { 57, 156, 240, 33, 1 }, }, + { { 118, 232, 203, 120, 1 }, + { 181, 236, 182, 137, 8 }, + { 129, 237, 49, 118, 14 }, + { 25, 22, 211, 122, 13 }, }, + { { 154, 83, 217, 207, 3 }, + { 126, 190, 12, 31, 3 }, + { 207, 57, 188, 165, 9 }, + { 207, 131, 7, 215, 14 }, }, + { { 169, 203, 132, 2, 4 }, + { 2, 135, 120, 66, 9 }, + { 36, 2, 29, 57, 5 }, + { 148, 33, 238, 20, 0 }, }, + { { 198, 117, 73, 73, 0 }, + { 241, 38, 4, 175, 0 }, + { 9, 41, 42, 230, 3 }, + { 15, 82, 6, 72, 15 }, }, + { { 193, 210, 136, 148, 1 }, + { 76, 132, 156, 194, 2 }, + { 130, 145, 20, 184, 3 }, + { 68, 51, 146, 19, 2 }, }, + { { 231, 72, 8, 82, 11 }, + { 132, 20, 165, 203, 9 }, + { 212, 161, 1, 46, 7 }, + { 157, 58, 82, 130, 1 }, }, + { { 234, 47, 202, 132, 8 }, + { 43, 194, 45, 163, 10 }, + { 18, 21, 63, 69, 7 }, + { 92, 91, 68, 61, 4 }, }, + { { 233, 99, 183, 123, 1 }, + { 23, 231, 170, 222, 5 }, + { 141, 238, 220, 105, 7 }, + { 167, 181, 94, 126, 8 }, }, + { { 250, 54, 101, 42, 15 }, + { 119, 57, 107, 163, 5 }, + { 245, 74, 102, 197, 15 }, + { 172, 93, 105, 206, 14 }, }, + { { 6, 91, 255, 123, 13 }, + { 244, 231, 207, 29, 13 }, + { 189, 239, 253, 166, 0 }, + { 187, 143, 62, 114, 15 }, }, + { { 5, 65, 215, 45, 6 }, + { 184, 247, 66, 84, 0 }, + { 107, 78, 184, 42, 0 }, + { 2, 164, 46, 241, 13 }, }, + { { 12, 247, 36, 106, 2 }, + { 195, 55, 26, 40, 5 }, + { 69, 98, 78, 243, 0 }, + { 161, 69, 142, 204, 3 }, }, + { { 19, 56, 163, 158, 11 }, + { 93, 248, 129, 65, 15 }, + { 215, 156, 81, 204, 8 }, + { 248, 40, 17, 251, 10 }, }, + { { 21, 168, 147, 231, 4 }, + { 153, 200, 82, 92, 11 }, + { 46, 124, 145, 90, 8 }, + { 211, 164, 161, 57, 9 }, }, + { { 58, 65, 126, 233, 14 }, + { 34, 127, 103, 29, 6 }, + { 121, 119, 232, 37, 12 }, + { 107, 142, 111, 228, 4 }, }, + { { 79, 17, 226, 108, 0 }, + { 234, 226, 2, 201, 4 }, + { 3, 100, 120, 143, 2 }, + { 41, 52, 4, 117, 7 }, }, + { { 83, 13, 182, 210, 0 }, + { 0, 203, 128, 249, 15 }, + { 4, 182, 219, 12, 10 }, + { 249, 240, 29, 48, 0 }, }, + { { 88, 155, 250, 227, 4 }, + { 98, 202, 94, 156, 15 }, + { 44, 117, 253, 145, 10 }, + { 243, 151, 165, 52, 6 }, }, + { { 100, 9, 232, 160, 11 }, + { 164, 146, 39, 128, 14 }, + { 208, 81, 121, 2, 6 }, + { 112, 30, 68, 146, 5 }, }, + { { 96, 83, 122, 137, 1 }, + { 100, 102, 44, 148, 6 }, + { 137, 21, 236, 160, 6 }, + { 98, 147, 70, 98, 6 }, }, + { { 97, 89, 6, 155, 10 }, + { 64, 119, 161, 196, 11 }, + { 93, 150, 9, 168, 6 }, + { 210, 56, 94, 224, 2 }, }, + { { 107, 255, 120, 215, 11 }, + { 111, 22, 189, 253, 15 }, + { 222, 177, 239, 253, 6 }, + { 251, 251, 214, 143, 6 }, }, + { { 112, 173, 150, 164, 15 }, + { 13, 219, 115, 176, 10 }, + { 242, 86, 155, 80, 14 }, + { 80, 220, 237, 187, 0 }, }, + { { 117, 132, 111, 113, 10 }, + { 176, 89, 183, 236, 4 }, + { 88, 239, 98, 26, 14 }, + { 35, 126, 217, 160, 13 }, }, + { { 122, 149, 25, 47, 12 }, + { 90, 42, 119, 181, 1 }, + { 63, 73, 138, 149, 14 }, + { 138, 222, 229, 69, 10 }, }, + { { 134, 9, 118, 10, 10 }, + { 160, 115, 1, 19, 13 }, + { 85, 6, 233, 6, 1 }, + { 188, 136, 12, 224, 5 }, }, + { { 138, 45, 68, 195, 15 }, + { 39, 19, 65, 47, 11 }, + { 252, 50, 43, 69, 1 }, + { 223, 72, 44, 142, 4 }, }, + { { 147, 235, 120, 177, 4 }, + { 33, 14, 222, 87, 14 }, + { 40, 209, 237, 124, 9 }, + { 126, 167, 183, 8, 4 }, }, + { { 152, 141, 168, 77, 4 }, + { 10, 170, 84, 46, 12 }, + { 43, 33, 91, 17, 9 }, + { 55, 66, 165, 85, 0 }, }, + { { 158, 222, 43, 60, 8 }, + { 218, 108, 159, 35, 12 }, + { 19, 205, 71, 183, 9 }, + { 60, 79, 147, 101, 11 }, }, + { { 165, 41, 224, 123, 8 }, + { 161, 162, 163, 78, 13 }, + { 29, 224, 121, 74, 5 }, + { 183, 44, 84, 88, 5 }, }, + { { 181, 147, 184, 85, 15 }, + { 204, 154, 253, 94, 4 }, + { 250, 161, 220, 154, 13 }, + { 39, 171, 245, 147, 3 }, }, + { { 183, 248, 228, 38, 15 }, + { 237, 157, 115, 67, 13 }, + { 246, 66, 113, 254, 13 }, + { 188, 44, 235, 155, 7 }, }, + { { 188, 32, 82, 37, 14 }, + { 171, 88, 99, 22, 0 }, + { 122, 68, 160, 67, 13 }, + { 6, 140, 97, 173, 5 }, }, + { { 192, 68, 135, 118, 5 }, + { 28, 197, 194, 170, 1 }, + { 166, 238, 18, 32, 3 }, + { 133, 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172, 162, 12 }, + { 65, 137, 71, 96, 7 }, + { 52, 83, 82, 200, 8 }, + { 224, 110, 41, 24, 2 }, }, + { { 17, 166, 62, 16, 1 }, + { 5, 73, 156, 112, 4 }, + { 128, 135, 198, 88, 8 }, + { 32, 227, 153, 42, 0 }, }, + { { 30, 88, 44, 226, 2 }, + { 194, 29, 6, 9, 15 }, + { 68, 115, 65, 167, 8 }, + { 249, 6, 11, 132, 3 }, }, + { { 24, 99, 58, 139, 0 }, + { 3, 110, 12, 20, 7 }, + { 13, 21, 204, 97, 8 }, + { 226, 131, 7, 108, 0 }, }, + { { 26, 99, 1, 47, 13 }, + { 31, 46, 75, 5, 1 }, + { 191, 72, 12, 101, 8 }, + { 138, 13, 39, 79, 8 }, }, + { { 26, 241, 71, 206, 15 }, + { 127, 127, 81, 9, 3 }, + { 247, 62, 40, 245, 8 }, + { 201, 8, 175, 239, 14 }, }, + { { 25, 108, 177, 139, 1 }, + { 23, 172, 0, 116, 15 }, + { 141, 24, 211, 105, 8 }, + { 242, 224, 3, 94, 8 }, }, + { { 29, 149, 207, 92, 12 }, + { 250, 235, 213, 104, 0 }, + { 51, 175, 58, 155, 8 }, + { 1, 106, 189, 117, 15 }, }, + { { 25, 158, 56, 146, 2 }, + { 66, 24, 156, 112, 15 }, + { 68, 145, 199, 153, 8 }, + { 240, 227, 145, 132, 2 }, }, + { { 31, 252, 86, 35, 10 }, + { 227, 93, 19, 117, 9 }, + { 92, 70, 163, 255, 8 }, + { 154, 236, 139, 172, 7 }, }, + { { 36, 27, 41, 179, 3 }, + { 212, 18, 174, 4, 15 }, + { 204, 217, 77, 130, 4 }, + { 242, 7, 84, 130, 11 }, }, + { { 38, 231, 136, 133, 0 }, + { 137, 134, 60, 37, 2 }, + { 10, 17, 30, 118, 4 }, + { 74, 67, 198, 25, 1 }, }, + { { 33, 7, 54, 188, 1 }, + { 12, 99, 170, 112, 6 }, + { 131, 214, 206, 8, 4 }, + { 96, 229, 92, 99, 0 }, }, + { { 40, 77, 70, 86, 10 }, + { 42, 87, 161, 40, 9 }, + { 86, 166, 43, 33, 4 }, + { 145, 72, 94, 165, 4 }, }, + { { 46, 236, 227, 69, 8 }, + { 187, 196, 49, 45, 12 }, + { 26, 44, 115, 119, 4 }, + { 59, 72, 194, 61, 13 }, }, + { { 45, 79, 225, 77, 4 }, + { 186, 166, 104, 108, 12 }, + { 43, 40, 127, 43, 4 }, + { 51, 97, 102, 85, 13 }, }, + { { 45, 138, 40, 60, 7 }, + { 142, 48, 254, 64, 12 }, + { 227, 193, 69, 27, 4 }, + { 48, 39, 240, 199, 1 }, }, + { { 52, 248, 62, 55, 1 }, + { 205, 77, 182, 20, 13 }, + { 142, 199, 193, 242, 12 }, + { 178, 134, 219, 43, 3 }, }, + { { 56, 99, 93, 125, 8 }, + { 59, 47, 175, 28, 0 }, + { 27, 235, 172, 97, 12 }, + { 3, 143, 95, 77, 12 }, }, + { { 63, 162, 28, 196, 12 }, + { 139, 9, 125, 89, 2 }, + { 50, 51, 132, 95, 12 }, + { 73, 171, 233, 13, 1 }, }, + { { 66, 221, 151, 174, 14 }, + { 88, 247, 83, 177, 11 }, + { 119, 94, 155, 180, 2 }, + { 216, 220, 174, 241, 10 }, }, + { { 68, 223, 18, 214, 11 }, + { 204, 86, 153, 184, 11 }, + { 214, 180, 143, 178, 2 }, + { 209, 217, 150, 163, 3 }, }, + { { 65, 58, 205, 236, 8 }, + { 121, 161, 15, 200, 10 }, + { 19, 123, 53, 200, 2 }, + { 81, 63, 8, 89, 14 }, }, + { { 65, 192, 219, 73, 4 }, + { 48, 228, 84, 220, 0 }, + { 41, 45, 176, 56, 2 }, + { 3, 178, 162, 112, 12 }, }, + { { 76, 180, 0, 200, 13 }, + { 199, 32, 81, 168, 2 }, + { 177, 48, 2, 211, 2 }, + { 65, 88, 160, 78, 3 }, }, + { { 73, 35, 72, 149, 2 }, + { 43, 18, 140, 196, 2 }, + { 74, 145, 44, 73, 2 }, + { 66, 51, 20, 141, 4 }, }, + { { 82, 55, 185, 92, 6 }, + { 89, 186, 204, 185, 4 }, + { 99, 169, 222, 196, 10 }, + { 41, 211, 53, 217, 10 }, }, + { { 82, 81, 56, 221, 10 }, + { 72, 62, 133, 157, 6 }, + { 91, 177, 200, 164, 10 }, + { 107, 154, 23, 193, 2 }, }, + { { 94, 113, 146, 65, 3 }, + { 199, 222, 0, 157, 0 }, + { 200, 36, 152, 231, 10 }, + { 11, 144, 7, 190, 3 }, }, + { { 92, 178, 113, 235, 13 }, + { 247, 40, 91, 156, 7 }, + { 189, 120, 228, 211, 10 }, + { 227, 157, 161, 78, 15 }, }, + { { 91, 238, 55, 54, 6 }, + { 27, 93, 218, 241, 13 }, + { 102, 206, 199, 125, 10 }, + { 184, 245, 187, 173, 8 }, }, + { { 96, 5, 132, 21, 2 }, + { 8, 147, 160, 164, 0 }, + { 74, 130, 26, 0, 6 }, + { 2, 80, 92, 145, 0 }, }, + { { 100, 8, 128, 51, 8 }, + { 128, 128, 163, 132, 9 }, + { 28, 192, 17, 2, 6 }, + { 146, 28, 80, 16, 1 }, }, + { { 110, 40, 135, 140, 3 }, + { 159, 241, 32, 129, 10 }, + { 195, 30, 17, 71, 6 }, + { 88, 16, 72, 255, 9 }, }, + { { 108, 85, 84, 181, 7 }, + { 238, 23, 226, 180, 2 }, + { 234, 210, 170, 163, 6 }, + { 66, 212, 126, 135, 7 }, }, + { { 104, 186, 254, 70, 1 }, + { 111, 193, 60, 152, 13 }, + { 134, 39, 245, 209, 6 }, + { 177, 147, 200, 63, 6 }, }, + { { 104, 179, 85, 202, 7 }, + { 119, 51, 120, 152, 3 }, + { 229, 58, 172, 209, 6 }, + { 193, 145, 236, 206, 14 }, }, + { { 117, 156, 155, 102, 9 }, + { 220, 200, 55, 248, 9 }, + { 150, 109, 147, 154, 14 }, + { 145, 254, 193, 51, 11 }, }, + { { 124, 11, 200, 10, 0 }, + { 162, 170, 44, 128, 9 }, + { 5, 1, 61, 3, 14 }, + { 144, 19, 69, 84, 5 }, }, + { { 126, 89, 104, 196, 9 }, + { 238, 14, 37, 137, 14 }, + { 146, 49, 105, 167, 14 }, + { 121, 26, 71, 7, 7 }, }, + { { 120, 111, 61, 52, 5 }, + { 31, 15, 238, 176, 12 }, + { 162, 203, 207, 97, 14 }, + { 48, 215, 127, 15, 8 }, }, + { { 120, 193, 191, 255, 10 }, + { 26, 255, 183, 156, 7 }, + { 95, 255, 216, 49, 14 }, + { 227, 158, 223, 245, 8 }, }, + { { 122, 218, 185, 69, 10 }, + { 90, 156, 61, 157, 12 }, + { 90, 41, 213, 181, 14 }, + { 59, 155, 195, 149, 10 }, }, + { { 128, 60, 123, 156, 0 }, + { 121, 96, 132, 50, 14 }, + { 3, 157, 227, 192, 1 }, + { 116, 194, 16, 105, 14 }, }, + { { 135, 20, 88, 249, 7 }, + { 228, 48, 198, 127, 2 }, + { 233, 241, 162, 142, 1 }, + { 79, 230, 48, 194, 7 }, }, + { { 131, 27, 5, 165, 13 }, + { 92, 3, 75, 71, 10 }, + { 186, 90, 13, 140, 1 }, + { 94, 45, 44, 3, 10 }, }, + { { 136, 59, 180, 103, 4 }, + { 75, 131, 74, 30, 13 }, + { 46, 98, 221, 193, 1 }, + { 183, 133, 44, 29, 2 }, }, + { { 140, 169, 136, 156, 0 }, + { 139, 162, 148, 2, 10 }, + { 3, 145, 25, 83, 1 }, + { 84, 2, 148, 93, 1 }, }, + { { 142, 177, 3, 26, 11 }, + { 215, 114, 145, 3, 1 }, + { 213, 140, 8, 215, 1 }, + { 140, 8, 148, 238, 11 }, }, + { { 143, 39, 191, 54, 4 }, + { 155, 195, 206, 115, 5 }, + { 38, 207, 222, 79, 1 }, + { 172, 231, 60, 61, 9 }, }, + { { 143, 22, 179, 202, 0 }, + { 210, 224, 8, 123, 7 }, + { 5, 60, 214, 143, 1 }, + { 237, 225, 0, 116, 11 }, }, + { { 148, 24, 222, 74, 0 }, + { 224, 233, 4, 26, 9 }, + { 5, 39, 177, 130, 9 }, + { 149, 130, 9, 112, 7 }, }, + { { 147, 69, 36, 197, 0 }, + { 8, 15, 0, 111, 6 }, + { 10, 50, 74, 44, 9 }, + { 111, 96, 15, 1, 0 }, }, + { { 156, 253, 156, 216, 5 }, + { 199, 175, 212, 58, 10 }, + { 161, 179, 155, 243, 9 }, + { 85, 194, 191, 94, 3 }, }, + { { 155, 34, 55, 120, 13 }, + { 23, 105, 203, 91, 4 }, + { 177, 238, 196, 77, 9 }, + { 45, 173, 57, 110, 8 }, }, + { { 153, 250, 163, 209, 6 }, + { 83, 220, 216, 78, 14 }, + { 104, 188, 85, 249, 9 }, + { 119, 33, 179, 188, 10 }, }, + { { 162, 159, 28, 84, 3 }, + { 76, 19, 188, 59, 8 }, + { 194, 163, 143, 148, 5 }, + { 29, 195, 220, 131, 2 }, }, + { { 172, 79, 91, 26, 11 }, + { 182, 118, 173, 50, 9 }, + { 213, 141, 175, 35, 5 }, + { 148, 203, 86, 230, 13 }, }, + { { 172, 191, 109, 54, 6 }, + { 251, 19, 254, 34, 13 }, + { 102, 203, 111, 211, 5 }, + { 180, 71, 252, 141, 15 }, }, + { { 169, 185, 76, 64, 8 }, + { 99, 3, 53, 74, 8 }, + { 16, 35, 41, 217, 5 }, + { 21, 42, 204, 12, 6 }, }, + { { 182, 40, 233, 2, 12 }, + { 177, 136, 101, 3, 13 }, + { 52, 9, 113, 70, 13 }, + { 188, 10, 97, 24, 13 }, }, + { { 180, 109, 218, 222, 0 }, + { 169, 238, 164, 58, 11 }, + { 7, 181, 187, 98, 13 }, + { 213, 194, 87, 121, 5 }, }, + { { 178, 110, 246, 10, 1 }, + { 37, 237, 40, 51, 13 }, + { 133, 6, 247, 100, 13 }, + { 188, 193, 75, 122, 4 }, }, + { { 179, 37, 153, 105, 14 }, + { 17, 186, 103, 127, 0 }, + { 121, 105, 154, 76, 13 }, + { 15, 238, 101, 216, 8 }, }, + { { 179, 80, 40, 17, 5 }, + { 68, 12, 228, 71, 4 }, + { 168, 129, 64, 172, 13 }, + { 46, 34, 115, 2, 2 }, }, + { { 190, 28, 27, 59, 6 }, + { 210, 120, 230, 55, 9 }, + { 109, 205, 131, 135, 13 }, + { 158, 198, 113, 228, 11 }, }, + { { 188, 127, 85, 99, 14 }, + { 243, 31, 107, 62, 9 }, + { 124, 106, 175, 227, 13 }, + { 151, 205, 111, 140, 15 }, }, + { { 188, 175, 230, 141, 5 }, + { 175, 235, 120, 38, 14 }, + { 171, 22, 127, 83, 13 }, + { 118, 65, 237, 127, 5 }, }, + { { 189, 37, 146, 140, 4 }, + { 139, 234, 96, 114, 2 }, + { 35, 20, 154, 75, 13 }, + { 68, 224, 101, 125, 1 }, }, + { { 196, 27, 214, 183, 1 }, + { 236, 195, 138, 150, 11 }, + { 142, 214, 189, 130, 3 }, + { 214, 149, 28, 51, 7 }, }, + { { 198, 99, 190, 252, 14 }, + { 137, 247, 207, 155, 6 }, + { 115, 247, 220, 102, 3 }, + { 109, 159, 62, 249, 1 }, }, + { { 198, 86, 130, 19, 13 }, + { 196, 196, 201, 167, 1 }, + { 188, 132, 22, 166, 3 }, + { 142, 89, 50, 50, 3 }, }, + { { 198, 139, 73, 36, 10 }, + { 184, 18, 31, 131, 8 }, + { 82, 73, 45, 22, 3 }, + { 28, 31, 132, 129, 13 }, }, + { { 193, 61, 206, 190, 2 }, + { 105, 243, 134, 226, 11 }, + { 71, 215, 59, 200, 3 }, + { 212, 118, 28, 249, 6 }, }, + { { 197, 25, 109, 109, 1 }, + { 252, 35, 6, 206, 12 }, + { 139, 107, 105, 138, 3 }, + { 55, 54, 12, 67, 15 }, }, + { { 199, 77, 61, 239, 11 }, + { 156, 55, 7, 255, 15 }, + { 223, 123, 203, 46, 3 }, + { 255, 254, 14, 195, 9 }, }, + { { 193, 90, 43, 220, 9 }, + { 92, 100, 141, 202, 14 }, + { 147, 189, 69, 168, 3 }, + { 117, 59, 18, 99, 10 }, }, + { { 202, 35, 114, 33, 12 }, + { 35, 66, 75, 151, 4 }, + { 56, 68, 236, 69, 3 }, + { 46, 157, 36, 44, 4 }, }, + { { 207, 199, 244, 213, 9 }, + { 174, 135, 153, 255, 6 }, + { 154, 178, 254, 63, 3 }, + { 111, 249, 158, 23, 5 }, }, + { { 208, 49, 39, 226, 6 }, + { 81, 91, 66, 138, 7 }, + { 100, 126, 72, 192, 11 }, + { 229, 20, 45, 168, 10 }, }, + { { 212, 119, 84, 14, 0 }, + { 233, 47, 8, 178, 1 }, + { 7, 2, 174, 226, 11 }, + { 132, 209, 15, 73, 7 }, }, + { { 209, 134, 49, 90, 2 }, + { 16, 56, 152, 250, 5 }, + { 69, 168, 198, 24, 11 }, + { 165, 241, 145, 192, 8 }, }, + { { 219, 76, 100, 122, 11 }, + { 38, 61, 131, 235, 13 }, + { 213, 226, 99, 45, 11 }, + { 189, 124, 27, 198, 4 }, }, + { { 219, 132, 135, 144, 8 }, + { 18, 201, 145, 227, 2 }, + { 16, 158, 18, 29, 11 }, + { 76, 120, 153, 52, 8 }, }, + { { 223, 222, 6, 112, 0 }, + { 194, 77, 154, 235, 8 }, + { 0, 230, 7, 191, 11 }, + { 29, 117, 155, 36, 3 }, }, + { { 226, 41, 186, 96, 0 }, + { 1, 194, 38, 155, 12 }, + { 0, 101, 217, 68, 7 }, + { 61, 150, 68, 56, 0 }, }, + { { 225, 64, 224, 141, 6 }, + { 40, 180, 96, 198, 6 }, + { 107, 16, 112, 40, 7 }, + { 102, 48, 98, 209, 4 }, }, + { { 225, 154, 144, 165, 2 }, + { 72, 144, 58, 214, 10 }, + { 74, 80, 149, 152, 7 }, + { 86, 181, 192, 145, 2 }, }, + { { 231, 242, 192, 250, 9 }, + { 229, 164, 187, 203, 3 }, + { 149, 240, 52, 254, 7 }, + { 205, 61, 210, 90, 7 }, }, + { { 238, 173, 190, 131, 8 }, + { 131, 195, 53, 183, 15 }, + { 28, 23, 219, 87, 7 }, + { 254, 218, 204, 60, 1 }, }, + { { 240, 28, 242, 124, 1 }, + { 108, 232, 162, 186, 12 }, + { 131, 228, 243, 128, 15 }, + { 53, 212, 81, 115, 6 }, }, + { { 247, 101, 168, 38, 4 }, + { 137, 142, 102, 227, 5 }, + { 38, 65, 90, 110, 15 }, + { 172, 118, 103, 25, 1 }, }, + { { 247, 236, 195, 164, 13 }, + { 189, 204, 115, 227, 10 }, + { 178, 92, 51, 126, 15 }, + { 92, 124, 227, 59, 13 }, }, + { { 248, 45, 84, 113, 4 }, + { 35, 11, 226, 190, 8 }, + { 40, 226, 171, 65, 15 }, + { 23, 212, 125, 12, 4 }, }, + { { 254, 133, 143, 205, 11 }, + { 158, 251, 53, 175, 2 }, + { 219, 63, 26, 23, 15 }, + { 79, 90, 205, 247, 9 }, }, + { { 248, 227, 91, 11, 6 }, + { 51, 126, 124, 150, 1 }, + { 109, 13, 172, 113, 15 }, + { 134, 147, 231, 236, 12 }, }, + { { 254, 214, 62, 31, 15 }, + { 206, 125, 253, 183, 5 }, + { 255, 135, 198, 183, 15 }, + { 174, 219, 251, 231, 3 }, }, }; + +static unsigned char DICT_7X7_1000_BYTES[][4][7] = + { { { 221, 92, 108, 165, 202, 10, 1 }, + { 99, 179, 173, 228, 49, 180, 0 }, + { 168, 41, 210, 155, 29, 93, 1 }, + { 22, 198, 19, 218, 230, 227, 0 }, }, + { { 228, 27, 241, 62, 64, 171, 0 }, + { 17, 253, 137, 11, 181, 42, 1 }, + { 106, 129, 62, 71, 236, 19, 1 }, + { 170, 86, 232, 72, 223, 196, 0 }, }, + { { 158, 170, 43, 172, 93, 39, 1 }, + { 163, 182, 158, 145, 75, 171, 1 }, + { 242, 93, 26, 234, 42, 188, 1 }, + { 234, 233, 68, 188, 182, 226, 1 }, }, + { { 166, 103, 5, 183, 233, 76, 0 }, + { 221, 48, 50, 221, 165, 172, 0 }, + { 25, 75, 246, 208, 115, 50, 1 }, + { 26, 210, 221, 166, 6, 93, 1 }, }, + { { 198, 188, 123, 19, 50, 86, 0 }, + { 253, 193, 139, 113, 154, 97, 0 }, + { 53, 38, 100, 111, 30, 177, 1 }, + { 67, 44, 199, 104, 193, 223, 1 }, }, + { { 88, 128, 20, 35, 89, 238, 0 }, + { 4, 122, 28, 80, 184, 133, 1 }, + { 59, 205, 98, 20, 0, 141, 0 }, + { 208, 142, 133, 28, 47, 16, 0 }, }, + { { 211, 107, 190, 111, 84, 72, 0 }, + { 164, 240, 198, 70, 247, 63, 0 }, + { 9, 21, 123, 62, 235, 101, 1 }, + { 126, 119, 177, 49, 135, 146, 1 }, }, + { { 60, 161, 109, 136, 139, 219, 0 }, + { 37, 14, 191, 169, 44, 198, 0 }, + { 109, 232, 136, 219, 66, 158, 0 }, + { 49, 154, 74, 254, 184, 82, 0 }, }, + { { 137, 7, 31, 86, 150, 158, 0 }, + { 112, 74, 104, 49, 231, 125, 0 }, + { 60, 180, 181, 124, 112, 72, 1 }, + { 95, 115, 198, 11, 41, 7, 0 }, }, + { { 187, 101, 177, 141, 110, 63, 0 }, + { 200, 86, 142, 255, 101, 242, 1 }, + { 126, 59, 88, 198, 211, 110, 1 }, + { 167, 211, 127, 184, 181, 9, 1 }, }, + { { 245, 0, 209, 130, 244, 144, 1 }, + { 11, 88, 37, 139, 208, 113, 0 }, + { 132, 151, 160, 197, 128, 87, 1 }, + { 71, 5, 232, 210, 13, 104, 0 }, }, + { { 2, 38, 112, 184, 84, 26, 0 }, + { 208, 112, 139, 128, 96, 75, 0 }, + { 44, 21, 14, 135, 50, 32, 0 }, + { 105, 3, 0, 232, 135, 5, 1 }, }, + { { 84, 243, 107, 151, 72, 240, 1 }, + { 55, 25, 135, 197, 159, 200, 1 }, + { 135, 137, 116, 235, 103, 149, 0 }, + { 137, 252, 209, 240, 204, 118, 0 }, }, + { { 158, 36, 136, 70, 35, 153, 1 }, + { 235, 14, 86, 34, 161, 96, 0 }, + { 204, 226, 49, 8, 146, 60, 1 }, + { 3, 66, 162, 53, 56, 107, 1 }, }, + { { 189, 255, 50, 107, 201, 203, 1 }, + { 71, 255, 254, 76, 174, 186, 0 }, + { 233, 201, 235, 38, 127, 222, 1 }, + { 46, 186, 153, 63, 255, 241, 0 }, }, + { { 206, 17, 5, 176, 90, 151, 1 }, + { 147, 63, 8, 177, 20, 229, 0 }, + { 244, 173, 6, 208, 68, 57, 1 }, + { 83, 148, 70, 136, 126, 100, 1 }, }, + { { 211, 240, 97, 114, 31, 139, 0 }, + { 144, 45, 223, 37, 248, 177, 0 }, + { 104, 252, 39, 67, 7, 229, 1 }, + { 70, 143, 210, 125, 218, 4, 1 }, }, + { { 1, 225, 158, 206, 200, 237, 1 }, + { 38, 92, 98, 150, 175, 150, 1 }, + { 219, 137, 185, 188, 195, 192, 0 }, + { 180, 250, 180, 163, 29, 50, 0 }, }, + { { 38, 203, 204, 42, 112, 120, 1 }, + { 175, 176, 1, 14, 172, 79, 1 }, + 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119, 1 }, + { 102, 231, 79, 124, 93, 104, 1 }, + { 247, 48, 83, 13, 127, 143, 1 }, + { 139, 93, 31, 121, 115, 179, 0 }, }, + { { 253, 11, 219, 85, 100, 56, 1 }, + { 59, 210, 69, 75, 119, 120, 1 }, + { 142, 19, 85, 109, 232, 95, 1 }, + { 143, 119, 105, 81, 37, 238, 0 }, }, + { { 253, 22, 174, 228, 229, 62, 1 }, + { 107, 51, 252, 154, 115, 124, 1 }, + { 190, 83, 147, 186, 180, 95, 1 }, + { 159, 103, 44, 159, 230, 107, 0 }, }, + { { 254, 73, 163, 120, 194, 52, 0 }, + { 145, 178, 228, 63, 22, 98, 1 }, + { 22, 33, 143, 98, 201, 63, 1 }, + { 163, 52, 126, 19, 166, 196, 1 }, }, + { { 253, 132, 226, 198, 107, 168, 1 }, + { 75, 26, 213, 170, 187, 176, 1 }, + { 138, 235, 49, 163, 144, 223, 1 }, + { 134, 238, 170, 213, 172, 105, 0 }, }, + { { 252, 149, 79, 148, 230, 207, 0 }, + { 125, 31, 45, 185, 127, 36, 0 }, + { 121, 179, 148, 249, 84, 159, 1 }, + { 18, 127, 78, 218, 124, 95, 0 }, }, + { { 254, 165, 35, 88, 48, 164, 1 }, + { 219, 10, 198, 25, 30, 35, 1 }, + { 146, 134, 13, 98, 82, 191, 1 }, + { 226, 60, 76, 49, 168, 109, 1 }, }, + { { 254, 168, 217, 255, 176, 118, 0 }, + { 189, 226, 111, 219, 153, 99, 1 }, + { 55, 6, 255, 205, 138, 191, 1 }, + { 227, 76, 237, 251, 35, 222, 1 }, }, + { { 255, 195, 135, 255, 162, 252, 1 }, + { 159, 42, 100, 255, 191, 126, 1 }, + { 159, 162, 255, 240, 225, 255, 1 }, + { 191, 126, 255, 147, 42, 124, 1 }, }, + { { 95, 114, 124, 241, 17, 248, 0 }, + { 181, 107, 215, 196, 48, 93, 1 }, + { 15, 196, 71, 159, 39, 125, 0 }, + { 221, 6, 17, 245, 235, 86, 1 }, }, + { { 135, 81, 63, 164, 61, 190, 1 }, + { 171, 105, 152, 149, 103, 245, 1 }, + { 190, 222, 18, 254, 69, 112, 1 }, + { 215, 243, 84, 140, 203, 106, 1 }, }, + { { 198, 147, 77, 53, 31, 189, 0 }, + { 177, 45, 17, 113, 125, 237, 1 }, + { 94, 252, 86, 89, 100, 177, 1 }, + { 219, 223, 71, 68, 90, 70, 1 }, }, + { { 231, 230, 150, 226, 6, 159, 1 }, + { 195, 108, 74, 190, 250, 124, 0 }, + { 252, 176, 35, 180, 179, 243, 1 }, + { 31, 47, 190, 169, 27, 97, 1 }, }, }; +} diff --git a/aruco_pose/vendor/aruco/src/predefined_dictionaries_apriltag.hpp b/aruco_pose/vendor/aruco/src/predefined_dictionaries_apriltag.hpp new file mode 100644 index 00000000..cad9802f --- /dev/null +++ b/aruco_pose/vendor/aruco/src/predefined_dictionaries_apriltag.hpp @@ -0,0 +1,14900 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +namespace { + +/** + * Dictionaries are stored as a list of bytes in its four rotations. + * On each rotation, the marker is divided in bytes assuming a row-major order. + * This format allows a faster marker identification. + * For a dictionary composed by M markers of NxN bits, the structure dimensions should be: + * const char name[nMarkers][4rotations][nBytes], or more specifically: + * const char name[M][4][ceil(NxN/8)] + * The element [i][j][k] represents the k-th byte of the i-th marker in the dictionary + * in its j-th rotation. + * Each rotation implies a 90 degree rotation of the marker in anticlockwise direction. + */ +static unsigned char DICT_APRILTAG_16h5_BYTES[][4][2] = +{ + { {216, 196}, + {128, 190}, + {35, 27}, + {125, 1} + }, + { {165, 116}, + {106, 120}, + {46, 165}, + {30, 86} + }, + { {86, 44}, + {134, 209}, + {52, 106}, + {139, 97} + }, + { {157, 162}, + {195, 78}, + {69, 185}, + {114, 195} + }, + { {101, 158}, + {105, 211}, + {121, 166}, + {203, 150} + }, + { {214, 254}, + {167, 251}, + {127, 107}, + {223, 229} + }, + { {26, 205}, + {148, 55}, + {179, 88}, + {236, 41} + }, + { {162, 231}, + {31, 58}, + {231, 69}, + {92, 248} + }, + { {154, 127}, + {183, 61}, + {254, 89}, + {188, 237} + }, + { {182, 168}, + {142, 75}, + {21, 109}, + {210, 113} + }, + { {208, 28}, + {160, 153}, + {56, 11}, + {153, 5} + }, + { {213, 15}, + {209, 217}, + {240, 171}, + {155, 139} + }, + { {33, 176}, + {106, 2}, + {13, 132}, + {64, 86} + }, + { {108, 226}, + {11, 230}, + {71, 54}, + {103, 208} + }, + { {78, 49}, + {54, 196}, + {140, 114}, + {35, 108} + }, + { {8, 245}, + {50, 54}, + {175, 16}, + {108, 76} + }, + { {60, 144}, + {168, 70}, + {9, 60}, + {98, 21} + }, + { {45, 201}, + {88, 103}, + {147, 180}, + {230, 26} + }, + { {192, 165}, + {18, 154}, + {165, 3}, + {89, 72} + }, + { {241, 98}, + {203, 168}, + {70, 143}, + {21, 211} + }, + { {236, 135}, + {25, 222}, + {225, 55}, + {123, 152} + }, + { {169, 234}, + {75, 47}, + {87, 149}, + {244, 210} + }, + { {66, 251}, + {55, 163}, + {223, 66}, + {197, 236} + }, + { {184, 56}, + {170, 13}, + {28, 29}, + {176, 85} + }, + { {59, 151}, + {253, 22}, + {233, 220}, + {104, 191} + }, + { {181, 206}, + {201, 123}, + {115, 173}, + {222, 147} + }, + { {250, 181}, + {190, 158}, + {173, 95}, + {121, 125} + }, + { {12, 171}, + {19, 71}, + {213, 48}, + {226, 200} + }, + { {83, 224}, + {198, 162}, + {7, 202}, + {69, 99} + }, + { {116, 245}, + {186, 242}, + {175, 46}, + {79, 93} + } +}; + + + +static unsigned char DICT_APRILTAG_25h9_BYTES[][4][4] = +{ + { {143, 211, 170, 1}, + {234, 146, 237, 1}, + {170, 229, 248, 1}, + {219, 164, 171, 1} + }, + { {109, 139, 39, 1}, + {170, 251, 21, 0}, + {242, 104, 219, 0}, + {84, 111, 170, 1} + }, + { {22, 208, 222, 1}, + {94, 6, 244, 1}, + {189, 133, 180, 0}, + {151, 176, 61, 0} + }, + { {179, 147, 87, 1}, + {62, 118, 217, 0}, + {245, 100, 230, 1}, + {77, 183, 62, 0} + }, + { {115, 40, 116, 1}, + {28, 189, 146, 0}, + {151, 10, 103, 0}, + {36, 222, 156, 0} + }, + { {221, 18, 172, 0}, + {164, 145, 124, 1}, + {26, 164, 93, 1}, + {159, 68, 146, 1} + }, + { {103, 234, 238, 0}, + {98, 191, 182, 1}, + {59, 171, 243, 0}, + {182, 254, 163, 0} + }, + { {213, 186, 96, 1}, + {46, 157, 78, 0}, + {131, 46, 213, 1}, + {57, 92, 186, 0} + }, + { {231, 69, 93, 1}, + {89, 117, 157, 1}, + {221, 81, 115, 1}, + {220, 215, 77, 0} + }, + { {17, 101, 123, 0}, + {85, 214, 3, 1}, + {111, 83, 68, 0}, + {224, 53, 213, 0} + }, + { {228, 155, 129, 0}, + {34, 105, 109, 0}, + {64, 236, 147, 1}, + {91, 75, 34, 0} + }, + { {130, 77, 138, 0}, + {65, 10, 169, 1}, + {40, 217, 32, 1}, + {202, 168, 65, 0} + }, + { {117, 19, 219, 0}, + {52, 119, 101, 1}, + {109, 228, 87, 0}, + {211, 119, 22, 0} + }, + { {152, 112, 167, 1}, + {204, 194, 122, 0}, + {242, 135, 12, 1}, + {47, 33, 153, 1} + }, + { {75, 152, 26, 1}, + {154, 27, 192, 1}, + {172, 12, 233, 0}, + {129, 236, 44, 1} + }, + { {65, 65, 182, 1}, + {88, 147, 49, 0}, + {182, 193, 65, 0}, + {70, 100, 141, 0} + }, + { {172, 7, 198, 1}, + {169, 38, 61, 0}, + {177, 240, 26, 1}, + {94, 50, 74, 1} + }, + { {129, 217, 185, 0}, + {82, 216, 105, 1}, + {78, 205, 192, 1}, + {203, 13, 165, 0} + }, + { {35, 119, 206, 1}, + {105, 54, 243, 1}, + {185, 247, 98, 0}, + {231, 182, 75, 0} + }, + { {144, 92, 117, 0}, + {85, 204, 88, 0}, + {87, 29, 4, 1}, + {13, 25, 213, 0} + }, + { {138, 62, 250, 0}, + {177, 142, 234, 1}, + {47, 190, 40, 1}, + {171, 184, 198, 1} + }, + { {63, 236, 133, 1}, + {207, 120, 182, 0}, + {208, 155, 254, 0}, + {54, 143, 121, 1} + }, + { {70, 169, 59, 0}, + {18, 203, 135, 1}, + {110, 74, 177, 0}, + {240, 233, 164, 0} + }, + { {162, 116, 1, 1}, + {73, 96, 202, 0}, + {192, 23, 34, 1}, + {41, 131, 73, 0} + }, + { {52, 42, 195, 1}, + {44, 110, 38, 0}, + {225, 170, 22, 0}, + {50, 59, 26, 0} + }, + { {37, 240, 225, 0}, + {66, 244, 102, 0}, + {67, 135, 210, 0}, + {51, 23, 161, 0} + }, + { {144, 226, 137, 0}, + {102, 64, 42, 1}, + {72, 163, 132, 1}, + {170, 1, 51, 0} + }, + { {15, 33, 102, 1}, + {136, 150, 151, 0}, + {179, 66, 120, 0}, + {116, 180, 136, 1} + }, + { {165, 79, 19, 0}, + {113, 122, 13, 0}, + {100, 121, 82, 1}, + {88, 47, 71, 0} + }, + { {221, 124, 193, 0}, + {197, 93, 110, 0}, + {65, 159, 93, 1}, + {59, 93, 81, 1} + }, + { {254, 142, 154, 0}, + {183, 43, 172, 1}, + {44, 184, 191, 1}, + {154, 234, 118, 1} + }, + { {10, 11, 60, 1}, + {184, 136, 145, 1}, + {158, 104, 40, 0}, + {196, 136, 142, 1} + }, + { {139, 80, 95, 0}, + {208, 86, 216, 1}, + {125, 5, 104, 1}, + {141, 181, 5, 1} + }, + { {13, 198, 237, 1}, + {235, 212, 52, 1}, + {219, 177, 216, 0}, + {150, 21, 235, 1} + }, + { {115, 137, 157, 0}, + {22, 121, 177, 1}, + {92, 200, 231, 0}, + {198, 207, 52, 0} + } +}; + + + +static unsigned char DICT_APRILTAG_36h10_BYTES[][4][5] = +{ + { {225, 101, 73, 83, 8}, + {49, 6, 165, 238, 1}, + {28, 169, 42, 104, 7}, + {135, 122, 86, 8, 12} + }, + { {50, 53, 132, 160, 4}, + {65, 139, 98, 33, 2}, + {32, 82, 26, 196, 12}, + {72, 68, 109, 24, 2} + }, + { {107, 237, 252, 94, 4}, + {43, 167, 244, 249, 13}, + {39, 163, 251, 125, 6}, + {185, 242, 254, 93, 4} + }, + { {217, 189, 115, 45, 4}, + {123, 106, 82, 246, 12}, + {43, 76, 235, 217, 11}, + {54, 244, 165, 109, 14} + }, + { {87, 115, 222, 38, 12}, + {233, 207, 79, 209, 1}, + {54, 71, 188, 238, 10}, + {136, 191, 47, 57, 7} + }, + { {245, 43, 80, 249, 12}, + {161, 42, 235, 222, 10}, + {57, 240, 173, 74, 15}, + {87, 189, 117, 72, 5} + }, + { {46, 91, 153, 155, 12}, + {210, 166, 237, 21, 11}, + {61, 153, 157, 167, 4}, + {218, 139, 118, 84, 11} + }, + { {127, 167, 237, 114, 2}, + {179, 155, 190, 233, 5}, + {68, 235, 126, 95, 14}, + {169, 119, 221, 156, 13} + }, + { {72, 191, 207, 28, 10}, + {123, 243, 157, 160, 8}, + {83, 143, 63, 209, 2}, + {16, 91, 156, 253, 14} + }, + { {235, 64, 193, 206, 10}, + {58, 180, 33, 203, 3}, + {87, 56, 48, 45, 7}, + {205, 56, 66, 213, 12} + }, + { {215, 152, 253, 186, 6}, + {240, 185, 214, 211, 15}, + {101, 219, 241, 158, 11}, + {252, 182, 185, 208, 15} + }, + { {92, 212, 54, 176, 14}, + {194, 93, 211, 176, 6}, + {112, 214, 194, 179, 10}, + {96, 220, 187, 164, 3} + }, + { {114, 66, 21, 239, 14}, + {24, 61, 107, 157, 3}, + {127, 122, 132, 36, 14}, + {203, 157, 107, 193, 8} + }, + { {200, 18, 236, 76, 1}, + {110, 161, 12, 138, 4}, + {131, 35, 116, 129, 3}, + {37, 19, 8, 87, 6} + }, + { {27, 178, 99, 54, 1}, + {127, 72, 154, 65, 5}, + {134, 204, 100, 221, 8}, + {168, 37, 145, 47, 14} + }, + { {185, 202, 170, 229, 1}, + {14, 204, 62, 78, 14}, + {138, 117, 85, 57, 13}, + {119, 39, 195, 55, 0} + }, + { {55, 38, 64, 234, 9}, + {165, 40, 43, 105, 3}, + {149, 112, 38, 78, 12}, + {201, 109, 65, 74, 5} + }, + { {141, 86, 137, 137, 9}, + {214, 164, 13, 102, 2}, + {153, 25, 22, 171, 1}, + {70, 107, 2, 86, 11} + }, + { {220, 110, 245, 96, 5}, + {183, 141, 74, 186, 12}, + {160, 106, 247, 99, 11}, + {53, 213, 43, 30, 13} + }, + { {81, 225, 58, 109, 5}, + {13, 110, 86, 220, 4}, + {171, 101, 200, 120, 10}, + {35, 182, 167, 107, 0} + }, + { {40, 201, 94, 212, 13}, + {46, 71, 245, 24, 10}, + {178, 183, 169, 49, 4}, + {81, 138, 254, 39, 4} + }, + { {155, 25, 144, 102, 13}, + {78, 138, 67, 91, 9}, + {182, 96, 153, 141, 9}, + {157, 172, 37, 23, 2} + }, + { {198, 37, 228, 219, 13}, + {165, 163, 193, 175, 7}, + {189, 178, 122, 70, 3}, + {239, 88, 60, 90, 5} + }, + { {238, 221, 198, 163, 3}, + {230, 215, 50, 167, 11}, + {204, 86, 59, 183, 7}, + {222, 84, 206, 182, 7} + }, + { {168, 123, 189, 36, 7}, + {95, 151, 110, 18, 12}, + {226, 75, 221, 225, 5}, + {52, 135, 110, 159, 10} + }, + { {38, 247, 86, 43, 7}, + {229, 119, 122, 53, 1}, + {237, 70, 174, 246, 4}, + {138, 197, 238, 234, 7} + }, + { {119, 95, 17, 146, 15}, + {212, 30, 233, 241, 11}, + {244, 152, 143, 174, 14}, + {216, 249, 119, 130, 11} + }, + { {227, 232, 42, 118, 0}, + {9, 68, 182, 203, 13}, + {6, 229, 65, 124, 7}, + {189, 54, 210, 41, 0} + }, + { {219, 116, 9, 26, 8}, + {83, 44, 133, 227, 1}, + {21, 137, 2, 237, 11}, + {140, 122, 19, 76, 10} + }, + { {166, 92, 117, 179, 8}, + {240, 5, 163, 55, 15}, + {28, 218, 227, 166, 5}, + {254, 204, 90, 0, 15} + }, + { {247, 162, 51, 66, 4}, + {145, 72, 120, 219, 5}, + {36, 44, 196, 94, 15}, + {173, 177, 225, 40, 9} + }, + { {45, 210, 218, 190, 4}, + {234, 228, 254, 80, 3}, + {39, 213, 180, 187, 4}, + {192, 167, 242, 117, 7} + }, + { {158, 138, 87, 237, 4}, + {186, 105, 90, 31, 10}, + {43, 126, 165, 23, 9}, + {95, 133, 169, 101, 13} + }, + { {192, 186, 16, 180, 12}, + {73, 0, 219, 146, 10}, + {50, 208, 133, 208, 3}, + {84, 157, 176, 9, 2} + }, + { {19, 70, 233, 230, 12}, + {56, 140, 79, 105, 7}, + {54, 121, 118, 44, 8}, + {233, 111, 35, 17, 12} + }, + { {177, 22, 100, 69, 12}, + {104, 9, 105, 110, 4}, + {58, 34, 102, 136, 13}, + {39, 105, 105, 1, 6} + }, + { {74, 118, 173, 59, 12}, + {83, 165, 207, 165, 5}, + {61, 203, 86, 229, 2}, + {170, 95, 58, 92, 10} + }, + { {133, 254, 70, 49, 2}, + {225, 85, 154, 102, 8}, + {72, 198, 39, 250, 1}, + {22, 101, 154, 168, 7} + }, + { {173, 105, 121, 110, 10}, + {187, 54, 39, 90, 13}, + {87, 105, 233, 107, 5}, + {181, 174, 70, 205, 13} + }, + { {32, 21, 210, 100, 6}, + {104, 210, 98, 56, 0}, + {98, 100, 186, 128, 4}, + {1, 196, 100, 177, 6} + }, + { {147, 181, 91, 6, 6}, + {121, 90, 84, 115, 1}, + {102, 13, 170, 220, 9}, + {140, 226, 165, 169, 14} + }, + { {202, 157, 31, 171, 6}, + {82, 115, 86, 183, 11}, + {109, 95, 139, 149, 3}, + {222, 214, 172, 228, 10} + }, + { {187, 35, 104, 210, 14}, + {35, 26, 237, 75, 7}, + {116, 177, 108, 77, 13}, + {237, 43, 117, 140, 4} + }, + { {52, 107, 195, 95, 14}, + {185, 254, 233, 12, 9}, + {127, 172, 61, 98, 12}, + {147, 9, 119, 249, 13} + }, + { {160, 207, 113, 248, 9}, + {52, 38, 187, 58, 14}, + {145, 248, 239, 48, 5}, + {117, 205, 214, 66, 12} + }, + { {83, 31, 184, 90, 9}, + {68, 170, 141, 249, 13}, + {149, 161, 223, 140, 10}, + {185, 251, 21, 82, 2} + }, + { {241, 127, 53, 41, 9}, + {85, 47, 43, 246, 12}, + {153, 74, 207, 232, 15}, + {54, 253, 79, 74, 10} + }, + { {152, 80, 211, 144, 5}, + {118, 204, 192, 18, 2}, + {160, 156, 176, 161, 9}, + {68, 128, 51, 54, 14} + }, + { {123, 240, 90, 34, 5}, + {103, 76, 118, 209, 1}, + {164, 69, 160, 253, 14}, + {136, 182, 227, 46, 6} + }, + { {197, 168, 151, 126, 5}, + {157, 225, 210, 218, 9}, + {167, 238, 145, 90, 3}, + {149, 180, 184, 123, 9} + }, + { {22, 216, 30, 157, 5}, + {204, 109, 212, 21, 10}, + {171, 151, 129, 182, 8}, + {90, 130, 187, 99, 3} + }, + { {180, 132, 224, 47, 5}, + {172, 168, 114, 38, 5}, + {175, 64, 114, 18, 13}, + {166, 68, 225, 83, 5} + }, + { {237, 52, 164, 150, 13}, + {207, 129, 225, 226, 7}, + {182, 146, 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0} + }, + { {230, 235, 111, 39, 4}, + {185, 71, 126, 135, 13}, + {46, 79, 109, 118, 7}, + {190, 23, 238, 41, 13} + }, + { {132, 244, 176, 135, 15}, + {205, 148, 81, 54, 7}, + {254, 16, 210, 242, 1}, + {230, 200, 162, 155, 3} + }, + { {91, 222, 44, 8, 8}, + {66, 45, 29, 225, 12}, + {17, 3, 71, 189, 10}, + {56, 123, 139, 68, 2} + }, + { {205, 253, 149, 194, 7}, + {215, 151, 80, 250, 11}, + {228, 58, 155, 251, 3}, + {213, 240, 174, 158, 11} + }, + { {51, 193, 37, 123, 3}, + {20, 63, 178, 77, 5}, + {205, 234, 72, 60, 12}, + {171, 36, 223, 194, 8} + }, + { {99, 27, 71, 141, 15}, + {124, 115, 105, 197, 10}, + {251, 30, 45, 140, 6}, + {90, 57, 108, 227, 14} + }, + { {229, 239, 80, 81, 11}, + {165, 22, 185, 254, 8}, + {216, 160, 175, 122, 7}, + {23, 249, 214, 138, 5} + }, + { {65, 141, 160, 190, 12}, + {8, 162, 211, 224, 15}, + {55, 208, 91, 24, 2}, + {240, 124, 180, 81, 0} + }, + { {193, 184, 36, 139, 1}, + {69, 33, 16, 198, 15}, + {141, 18, 65, 216, 3}, + {246, 48, 136, 74, 2} + }, + { {118, 222, 87, 133, 11}, + {252, 93, 57, 181, 10}, + {218, 30, 167, 182, 14}, + {90, 217, 203, 163, 15} + }, + { {219, 201, 87, 218, 6}, + {50, 127, 208, 219, 11}, + {101, 190, 169, 61, 11}, + {221, 176, 191, 228, 12} + }, + { {202, 225, 244, 5, 4}, + {43, 135, 80, 151, 4}, + {42, 2, 248, 117, 3}, + {46, 144, 174, 29, 4} + }, + { {145, 76, 36, 42, 2}, + {0, 61, 2, 98, 13}, + {69, 66, 67, 40, 9}, + {180, 100, 11, 192, 0} + }, + { {69, 163, 208, 168, 2}, + {161, 178, 26, 208, 2}, + {65, 80, 188, 90, 2}, + {64, 181, 132, 216, 5} + }, + { {136, 154, 125, 93, 13}, + {126, 33, 221, 30, 12}, + {187, 171, 229, 145, 1}, + {55, 139, 184, 71, 14} + }, + { {154, 61, 179, 211, 2}, + {83, 218, 128, 63, 15}, + {76, 188, 219, 197, 9}, + {255, 192, 21, 188, 10} + }, + { {208, 44, 134, 112, 15}, + {5, 217, 195, 170, 8}, + {240, 230, 19, 64, 11}, + {21, 92, 57, 186, 0} + }, + { {21, 123, 52, 80, 12}, + {193, 15, 201, 88, 12}, + {48, 162, 205, 234, 8}, + {49, 169, 63, 8, 3} + }, + { {137, 13, 55, 91, 10}, + {18, 115, 129, 126, 13}, + {93, 174, 203, 9, 1}, + {183, 232, 28, 228, 8} + }, + { {137, 27, 201, 59, 10}, + {114, 178, 143, 70, 9}, + {93, 201, 61, 137, 1}, + {150, 47, 20, 212, 14} + }, + { {138, 2, 216, 10, 3}, + {38, 176, 12, 19, 1}, + {197, 1, 180, 5, 1}, + {140, 131, 0, 214, 4} + }, + { {30, 93, 243, 65, 14}, + {242, 222, 65, 61, 12}, + {120, 44, 251, 167, 8}, + {59, 200, 39, 180, 15} + }, + { {120, 109, 137, 131, 2}, + {19, 158, 36, 164, 11}, + {76, 25, 27, 97, 14}, + {210, 82, 71, 156, 8} + }, + { {172, 247, 228, 126, 13}, + {239, 167, 251, 42, 5}, + {183, 226, 126, 243, 5}, + {165, 77, 254, 95, 7} + }, + { {28, 22, 226, 90, 0}, + {226, 232, 136, 40, 5}, + {5, 164, 118, 131, 8}, + {161, 65, 17, 116, 7} + }, + { {46, 169, 4, 13, 9}, + {143, 35, 49, 5, 8}, + {155, 2, 9, 87, 4}, + {26, 8, 204, 79, 1} + }, + { {243, 38, 138, 238, 5}, + {13, 232, 110, 235, 3}, + {167, 117, 22, 76, 15}, + {205, 119, 97, 123, 0} + }, + { {128, 232, 75, 204, 11}, + {61, 116, 21, 10, 10}, + {211, 61, 33, 112, 1}, + {85, 10, 130, 235, 12} + }, + { {162, 190, 211, 245, 12}, + {121, 192, 251, 63, 10}, + {58, 252, 183, 212, 5}, + {95, 205, 240, 57, 14} + }, + { {179, 172, 4, 251, 2}, + {1, 57, 178, 111, 11}, + {77, 242, 3, 92, 13}, + {223, 100, 217, 200, 0} + }, + { {132, 89, 129, 25, 2}, + {208, 182, 128, 6, 8}, + {73, 136, 25, 162, 1}, + {22, 0, 22, 208, 11} + }, + { {96, 167, 159, 201, 4}, + {17, 227, 124, 188, 2}, + {41, 63, 158, 80, 6}, + {67, 211, 236, 120, 8} + }, + { {19, 143, 250, 197, 9}, + {44, 202, 29, 125, 14}, + {154, 53, 255, 28, 8}, + {123, 235, 133, 51, 4} + }, + { {214, 125, 112, 144, 3}, + {229, 30, 128, 179, 14}, + {192, 144, 235, 230, 11}, + {124, 208, 23, 138, 7} + }, + { {43, 138, 160, 242, 5}, + {6, 128, 250, 73, 15}, + {164, 240, 85, 29, 4}, + {249, 37, 240, 22, 0} + }, + { {41, 131, 176, 59, 10}, + {2, 178, 187, 84, 5}, + {93, 192, 220, 25, 4}, + {162, 173, 212, 212, 0} + }, + { {140, 215, 81, 28, 8}, + {250, 38, 153, 50, 0}, + {19, 136, 174, 179, 1}, + {4, 201, 150, 69, 15} + }, + { {47, 222, 77, 2, 12}, + {242, 5, 125, 97, 9}, + {52, 11, 39, 191, 4}, + {152, 107, 234, 4, 15} + }, + { {213, 4, 207, 5, 12}, + {184, 201, 69, 230, 0}, + {58, 15, 50, 10, 11}, + {6, 122, 41, 49, 13} + }, + { {186, 231, 214, 153, 0}, + {35, 239, 184, 55, 2}, + {9, 150, 190, 117, 13}, + {78, 193, 223, 124, 4} + }, + { {156, 243, 126, 164, 13}, + {239, 79, 95, 18, 6}, + {178, 87, 236, 243, 9}, + {100, 143, 175, 47, 7} + }, + { {143, 79, 97, 177, 14}, + {178, 22, 203, 103, 14}, + {120, 216, 111, 47, 1}, + {126, 109, 54, 132, 13} + }, + { {137, 255, 175, 206, 6}, + {91, 247, 92, 106, 15}, + {103, 63, 95, 249, 1}, + {245, 99, 174, 253, 10} + }, + { {124, 126, 177, 202, 2}, + {211, 188, 40, 184, 15}, + {69, 56, 215, 227, 14}, + {241, 209, 67, 220, 11} + }, + { {150, 194, 61, 167, 11}, + {156, 29, 31, 23, 7}, + {222, 91, 196, 54, 9}, + {238, 143, 139, 131, 9} + } +}; + + + +static unsigned char DICT_APRILTAG_36h11_BYTES[][4][5] = +{ + { {33, 161, 70, 186, 11}, + {37, 115, 179, 64, 3}, + {213, 214, 40, 88, 4}, + {192, 44, 220, 234, 4} + }, + { {146, 209, 143, 233, 11}, + {84, 255, 23, 15, 2}, + {217, 127, 24, 180, 9}, + {79, 14, 143, 242, 10} + }, + { {112, 137, 1, 75, 11}, + {20, 58, 49, 140, 9}, + {221, 40, 9, 16, 14}, + {147, 24, 197, 194, 8} + }, + { {25, 57, 121, 226, 7}, + {119, 26, 70, 88, 15}, + {228, 121, 233, 201, 8}, + {241, 166, 37, 142, 14} + }, + { {68, 21, 61, 61, 7}, + {220, 51, 198, 180, 4}, + {235, 203, 202, 130, 2}, + {34, 214, 60, 195, 11} + }, + { {53, 205, 91, 140, 15}, + {188, 126, 117, 112, 10}, + {243, 29, 171, 58, 12}, + {80, 234, 231, 227, 13} + }, + { {161, 11, 165, 106, 0}, + {16, 163, 42, 74, 13}, + {5, 106, 93, 8, 5}, + {181, 37, 76, 80, 8} + }, + { {43, 135, 74, 96, 8}, + {34, 66, 63, 105, 0}, + {16, 101, 46, 29, 4}, + {9, 111, 196, 36, 4} + }, + { {181, 127, 184, 212, 4}, + {201, 142, 236, 122, 14}, + {34, 177, 223, 234, 13}, + {117, 227, 119, 25, 3} + }, + { {78, 32, 181, 166, 4}, + {155, 129, 66, 145, 7}, + {38, 90, 208, 71, 2}, + {232, 148, 40, 29, 9} + }, + { {97, 216, 151, 242, 12}, + {80, 197, 243, 216, 11}, + {52, 254, 145, 184, 6}, + {209, 188, 250, 48, 10} + }, + { {171, 52, 105, 255, 12}, + {123, 32, 231, 111, 7}, + {63, 249, 98, 205, 5}, + {239, 110, 112, 77, 14} + }, + { {89, 76, 164, 92, 2}, + {10, 189, 128, 232, 12}, + {67, 162, 83, 41, 10}, + {49, 112, 27, 213, 0} + }, + { {250, 28, 45, 46, 2}, + {90, 57, 38, 163, 13}, + {71, 75, 67, 133, 15}, + {188, 86, 73, 197, 10} + }, + { {151, 194, 75, 151, 2}, + {184, 92, 156, 71, 3}, + {78, 157, 36, 62, 9}, + {206, 35, 147, 161, 13} + }, + { {117, 146, 134, 36, 10}, + {200, 217, 59, 192, 0}, + {82, 70, 20, 154, 14}, + {0, 61, 201, 177, 3} + }, + { {28, 170, 254, 153, 10}, + {163, 249, 157, 20, 14}, + {89, 151, 245, 83, 8}, + {114, 139, 153, 252, 5} + }, + { {50, 54, 221, 193, 6}, + {113, 153, 108, 61, 2}, + {104, 59, 182, 196, 12}, + {75, 195, 105, 152, 14} + }, + { {136, 78, 82, 125, 6}, + {42, 116, 202, 62, 8}, + {107, 228, 167, 33, 1}, + {23, 197, 50, 229, 4} + }, + { {87, 113, 168, 199, 14}, + {201, 158, 69, 205, 7}, + {126, 49, 88, 238, 10}, + {235, 58, 39, 153, 3} + }, + { {245, 41, 37, 184, 1}, + {149, 43, 162, 194, 14}, + {129, 218, 73, 74, 15}, + {116, 52, 93, 74, 9} + }, + { {46, 89, 204, 26, 1}, + {230, 167, 164, 1, 9}, + {133, 131, 57, 167, 4}, + {152, 2, 94, 86, 7} + }, + { {127, 165, 138, 179, 1}, + {135, 202, 182, 229, 3}, + {140, 213, 26, 95, 14}, + {202, 118, 213, 62, 1} + }, + { {235, 67, 56, 79, 9}, + {14, 38, 45, 223, 5}, + {159, 33, 204, 45, 7}, + {175, 187, 70, 71, 0} + }, + { {57, 19, 213, 52, 5}, + {126, 139, 234, 80, 0}, + {162, 202, 188, 137, 12}, + {0, 165, 125, 23, 14} + }, + { {215, 155, 26, 59, 5}, + {196, 106, 222, 215, 9}, + {173, 197, 141, 158, 11}, + {158, 183, 181, 98, 3} + }, + { {13, 251, 231, 104, 13}, + {247, 231, 91, 72, 12}, + {177, 110, 125, 251, 0}, + {49, 45, 174, 126, 15} + }, + { {92, 215, 160, 49, 13}, + {198, 142, 219, 164, 4}, + {184, 192, 94, 179, 10}, + {34, 93, 183, 22, 3} + }, + { {185, 200, 247, 164, 11}, + {62, 221, 51, 82, 14}, + {210, 94, 241, 57, 13}, + {116, 172, 203, 183, 12} + }, + { {70, 152, 126, 6, 11}, + {236, 81, 21, 145, 13}, + {214, 7, 225, 150, 2}, + {184, 154, 136, 163, 7} + }, + { {110, 12, 93, 82, 7}, + {182, 17, 228, 185, 9}, + {228, 171, 163, 7, 6}, + {153, 210, 120, 134, 13} + }, + { {91, 197, 103, 187, 4}, + {50, 111, 210, 229, 7}, + {45, 222, 106, 61, 10}, + {234, 116, 191, 100, 12} + }, + { {30, 99, 2, 188, 2}, + {139, 126, 138, 1, 2}, + {67, 212, 12, 103, 8}, + {72, 5, 23, 237, 1} + }, + { {138, 199, 208, 70, 10}, + {42, 150, 25, 59, 1}, + {86, 32, 190, 53, 1}, + {141, 201, 134, 149, 4} + }, + { {166, 95, 226, 50, 6}, + {224, 214, 234, 35, 13}, + {100, 196, 127, 166, 5}, + {188, 69, 118, 176, 7} + }, + { {84, 0, 235, 97, 6}, + {176, 216, 70, 140, 4}, + {104, 109, 112, 2, 10}, + {35, 22, 33, 176, 13} + }, + { {247, 160, 102, 131, 6}, + {161, 89, 112, 199, 7}, + {108, 22, 96, 94, 15}, + {238, 48, 233, 168, 5} + }, + { {45, 208, 175, 223, 6}, + {218, 245, 244, 76, 7}, + {111, 191, 80, 187, 4}, + {227, 34, 250, 245, 11} + }, + { {59, 156, 182, 11, 1}, + {70, 233, 48, 117, 13}, + {141, 6, 211, 157, 12}, + {186, 224, 201, 118, 2} + }, + { {173, 106, 28, 175, 9}, + {143, 37, 47, 86, 11}, + {159, 83, 133, 107, 5}, + {214, 175, 74, 79, 1} + }, + { {147, 182, 46, 251, 5}, + {69, 105, 222, 111, 7}, + {173, 247, 70, 220, 9}, + {239, 103, 185, 106, 2} + }, + { {187, 33, 13, 147, 13}, + {23, 11, 229, 71, 3}, + {188, 155, 8, 77, 13}, + {206, 42, 125, 14, 8} + }, + { {222, 229, 80, 148, 11}, + {175, 30, 145, 179, 2}, + {210, 144, 170, 119, 11}, + {76, 216, 151, 143, 5} + }, + { {160, 205, 20, 121, 11}, + {4, 55, 179, 62, 8}, + {217, 226, 139, 48, 5}, + {23, 204, 222, 194, 0} + }, + { {42, 35, 171, 178, 7}, + {23, 210, 238, 1, 7}, + {228, 221, 92, 69, 4}, + {232, 7, 116, 190, 8} + }, + { {79, 103, 244, 181, 15}, + {175, 151, 203, 245, 6}, + {250, 210, 254, 111, 2}, + {106, 253, 62, 159, 5} + }, + { {88, 168, 21, 129, 8}, + {19, 9, 17, 148, 10}, + {24, 26, 129, 81, 10}, + {82, 152, 137, 12, 8} + }, + { {116, 52, 39, 214, 4}, + {217, 73, 224, 168, 7}, + {38, 190, 66, 194, 14}, + {225, 80, 121, 41, 11} + }, + { {29, 236, 64, 135, 4}, + {171, 12, 80, 100, 11}, + {46, 16, 35, 123, 8}, + {210, 96, 163, 13, 5} + }, + { {137, 42, 179, 160, 2}, + {19, 208, 10, 82, 14}, + {64, 92, 213, 73, 1}, + {116, 165, 0, 188, 8} + }, + { {56, 213, 116, 46, 14}, + {106, 63, 115, 48, 5}, + {119, 66, 234, 177, 12}, + {160, 204, 239, 197, 6} + }, + { {12, 67, 86, 122, 1}, + {166, 103, 138, 24, 1}, + {133, 230, 172, 35, 0}, + {129, 133, 30, 102, 5} + }, + { {93, 179, 17, 203, 1}, + {215, 42, 24, 220, 3}, + {141, 56, 140, 219, 10}, + {195, 177, 133, 78, 11} + }, + { {201, 87, 202, 31, 9}, + {110, 230, 141, 230, 1}, + {159, 133, 62, 169, 3}, + {134, 123, 22, 119, 6} + }, + { {162, 36, 87, 130, 3}, + {53, 81, 32, 51, 3}, + {196, 30, 162, 68, 5}, + {204, 192, 72, 170, 12} + }, + { {41, 172, 233, 143, 3}, + {63, 176, 52, 100, 15}, + {207, 25, 115, 89, 4}, + {242, 98, 192, 223, 12} + }, + { {204, 197, 44, 82, 8}, + {130, 7, 149, 170, 5}, + {20, 163, 74, 51, 3}, + {165, 90, 158, 4, 1} + }, + { {218, 139, 53, 120, 12}, + {18, 43, 219, 155, 12}, + {49, 234, 205, 21, 11}, + {61, 157, 189, 68, 8} + }, + { {213, 180, 185, 227, 6}, + {209, 152, 86, 254, 7}, + {108, 121, 210, 218, 11}, + {231, 246, 161, 152, 11} + }, + { {172, 156, 221, 60, 14}, + {250, 177, 247, 50, 8}, + {115, 203, 179, 147, 5}, + {20, 206, 248, 213, 15} + }, + { {203, 218, 168, 57, 1}, + {70, 164, 158, 199, 12}, + {137, 193, 85, 189, 3}, + {62, 55, 146, 86, 2} + }, + { {25, 134, 37, 107, 1}, + {22, 41, 26, 108, 5}, + {141, 106, 70, 25, 8}, + {163, 101, 137, 70, 8} + }, + { {186, 230, 204, 136, 9}, + {39, 173, 61, 35, 2}, + {145, 19, 54, 117, 13}, + {76, 75, 203, 94, 4} + }, + { {223, 145, 177, 14, 5}, + {222, 170, 80, 211, 5}, + {167, 8, 216, 159, 11}, + {172, 176, 165, 87, 11} + }, + { {161, 169, 213, 167, 5}, + {61, 131, 114, 86, 11}, + {174, 90, 185, 88, 5}, + {214, 164, 236, 27, 12} + }, + { {43, 101, 26, 169, 13}, + {7, 102, 103, 117, 2}, + {185, 85, 138, 109, 4}, + {74, 238, 102, 110, 0} + }, + { {77, 92, 46, 25, 13}, + {198, 101, 197, 228, 12}, + {185, 135, 67, 171, 2}, + {50, 122, 58, 102, 3} + }, + { {91, 22, 55, 54, 11}, + {94, 89, 139, 241, 5}, + {214, 206, 198, 141, 10}, + {168, 253, 25, 167, 10} + }, + { {247, 83, 214, 10, 8}, + {224, 239, 41, 211, 1}, + {21, 6, 188, 174, 15}, + {140, 185, 79, 112, 7} + }, + { {94, 132, 179, 125, 2}, + {154, 248, 146, 189, 4}, + {75, 236, 210, 23, 10}, + {43, 212, 145, 245, 9} + }, + { {252, 228, 58, 159, 2}, + {139, 124, 180, 182, 7}, + {79, 149, 194, 115, 15}, + {230, 210, 211, 237, 1} + }, + { {187, 146, 109, 26, 6}, + {114, 57, 252, 67, 5}, + {101, 139, 100, 157, 13}, + {172, 35, 249, 196, 14} + }, + { {237, 141, 35, 110, 5}, + {158, 98, 114, 234, 13}, + {167, 108, 75, 27, 7}, + {181, 116, 228, 103, 9} + }, + { {106, 248, 70, 243, 7}, + {103, 85, 242, 141, 11}, + {236, 246, 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93, 16, 9}, + {246, 13, 133, 115, 8} + }, + { {235, 104, 201, 181, 1}, + {63, 132, 166, 199, 10}, + {138, 217, 49, 109, 7}, + {94, 54, 82, 31, 12} + }, + { {38, 5, 212, 66, 12}, + {160, 131, 97, 57, 1}, + {52, 34, 186, 6, 4}, + {137, 200, 108, 16, 5} + }, + { {106, 184, 139, 127, 4}, + {91, 224, 246, 141, 9}, + {47, 237, 17, 213, 6}, + {155, 22, 240, 125, 10} + }, + { {32, 124, 118, 87, 13}, + {109, 69, 225, 60, 13}, + {190, 166, 227, 224, 4}, + {179, 200, 122, 43, 6} + }, + { {55, 121, 64, 210, 0}, + {225, 14, 160, 73, 11}, + {4, 176, 41, 238, 12}, + {217, 32, 87, 8, 7} + }, + { {172, 46, 183, 123, 6}, + {147, 241, 234, 62, 13}, + {109, 238, 215, 67, 5}, + {183, 197, 120, 252, 9} + }, + { {62, 135, 49, 142, 12}, + {154, 42, 121, 49, 7}, + {55, 24, 206, 23, 12}, + {232, 201, 229, 69, 9} + }, + { {71, 175, 234, 26, 10}, + {161, 242, 157, 225, 13}, + {85, 133, 127, 94, 2}, + {184, 123, 148, 248, 5} + }, + { {70, 222, 53, 183, 4}, + {216, 5, 218, 181, 15}, + {46, 218, 199, 182, 2}, + {250, 213, 186, 1, 11} + }, + { {72, 163, 107, 161, 0}, + {51, 66, 30, 132, 6}, + {8, 93, 108, 81, 2}, + {98, 23, 132, 44, 12} + }, + { {240, 113, 21, 54, 11}, + {93, 31, 163, 146, 1}, + {214, 202, 136, 224, 15}, + {132, 156, 95, 139, 10} + }, + { {150, 63, 135, 237, 4}, + {217, 235, 74, 47, 10}, + {43, 126, 31, 198, 9}, + {95, 69, 45, 121, 11} + }, + { {216, 58, 185, 150, 5}, + {95, 136, 204, 146, 15}, + {166, 153, 213, 193, 11}, + {244, 147, 49, 31, 10} + }, + { {123, 46, 181, 160, 15}, + {23, 153, 107, 241, 14}, + {240, 90, 215, 77, 14}, + {120, 253, 105, 158, 8} + }, + { {182, 173, 250, 243, 2}, + {161, 218, 182, 63, 15}, + {76, 245, 251, 86, 13}, + {255, 198, 213, 184, 5} + }, + { {135, 224, 122, 78, 10}, + {169, 116, 21, 91, 5}, + {87, 37, 224, 126, 1}, + {173, 170, 130, 233, 5} + }, + { {123, 69, 24, 244, 14}, + {10, 30, 231, 249, 2}, + {114, 241, 138, 45, 14}, + {73, 254, 119, 133, 0} + }, + { {144, 100, 163, 115, 8}, + {17, 204, 131, 46, 5}, + {28, 236, 82, 96, 9}, + {167, 76, 19, 56, 8} + }, + { {60, 36, 44, 161, 2}, + {131, 25, 38, 36, 6}, + {72, 83, 66, 67, 12}, + {98, 70, 73, 140, 1} + }, + { {150, 178, 92, 74, 4}, + {225, 41, 92, 27, 1}, + {37, 35, 164, 214, 9}, + {141, 131, 169, 72, 7} + }, + { {139, 1, 216, 58, 12}, + {34, 162, 199, 83, 1}, + {53, 193, 184, 13, 1}, + {140, 174, 52, 84, 4} + }, + { {229, 28, 206, 178, 5}, + {228, 193, 230, 226, 11}, + {164, 215, 51, 138, 7}, + {212, 118, 120, 50, 7} + }, + { {72, 15, 88, 219, 0}, + {34, 34, 140, 188, 11}, + {13, 177, 175, 1, 2}, + {211, 211, 20, 68, 4} + }, + { {186, 226, 149, 134, 7}, + {31, 157, 120, 19, 3}, + {230, 26, 148, 117, 13}, + {204, 129, 235, 159, 8} + }, + { {137, 252, 15, 186, 0}, + {83, 101, 150, 98, 11}, + {5, 223, 3, 249, 1}, + {212, 102, 154, 108, 10} + }, + { {221, 6, 71, 94, 9}, + {190, 105, 137, 234, 1}, + {151, 174, 38, 11, 11}, + {133, 121, 25, 103, 13} + }, + { {247, 254, 70, 180, 12}, + {233, 77, 251, 227, 10}, + {50, 214, 39, 254, 15}, + {92, 125, 251, 41, 7} + }, + { {67, 206, 240, 38, 13}, + {44, 132, 91, 241, 13}, + {182, 64, 247, 60, 2}, + {184, 253, 162, 19, 4} + }, + { {99, 147, 88, 90, 2}, + {96, 50, 188, 217, 1}, + {69, 161, 172, 156, 6}, + {137, 179, 212, 192, 6} + }, + { {135, 180, 4, 69, 6}, + {201, 17, 80, 111, 0}, + {106, 34, 2, 222, 1}, + {15, 96, 168, 137, 3} + }, + { {79, 164, 124, 190, 10}, + {171, 49, 151, 241, 7}, + {87, 211, 226, 95, 2}, + {232, 254, 152, 205, 5} + }, + { {118, 25, 249, 85, 10}, + {248, 154, 165, 157, 12}, + {90, 169, 249, 134, 14}, + {59, 154, 85, 145, 15} + }, + { {81, 185, 161, 51, 0}, + {81, 138, 146, 196, 13}, + {12, 200, 89, 216, 10}, + {178, 52, 149, 24, 10} + }, + { {21, 51, 99, 124, 7}, + {253, 122, 202, 72, 4}, + {227, 236, 108, 202, 8}, + {33, 37, 53, 235, 15} + }, + { {117, 135, 169, 114, 10}, + {144, 154, 191, 232, 5}, + {84, 233, 94, 26, 14}, + {161, 127, 213, 144, 9} + }, + { {96, 222, 17, 98, 2}, + {80, 20, 58, 184, 9}, + {68, 104, 135, 176, 6}, + {145, 213, 194, 128, 10} + }, + { {125, 76, 230, 138, 14}, + {162, 253, 97, 224, 15}, + {117, 22, 115, 43, 14}, + {240, 120, 107, 244, 5} + }, + { {175, 19, 94, 129, 12}, + {226, 67, 109, 87, 2}, + {56, 23, 172, 143, 5}, + {78, 171, 108, 36, 7} + }, + { {49, 201, 182, 71, 12}, + {8, 207, 113, 92, 13}, + {62, 38, 217, 56, 12}, + {179, 168, 239, 49, 0} + }, + { {172, 67, 216, 21, 5}, + {174, 134, 236, 22, 0}, + {170, 129, 188, 35, 5}, + {6, 131, 118, 23, 5} + }, + { {216, 83, 225, 207, 11}, + {126, 190, 9, 142, 7}, + {223, 56, 124, 161, 11}, + {231, 25, 7, 215, 14} + }, + { {79, 205, 197, 207, 0}, + {186, 167, 16, 237, 11}, + {15, 58, 59, 63, 2}, + {219, 112, 142, 85, 13} + }, + { {238, 105, 111, 210, 13}, + {183, 71, 229, 139, 15}, + {180, 191, 105, 103, 7}, + {253, 26, 126, 46, 13} + }, + { {183, 22, 24, 71, 5}, + {204, 8, 108, 127, 1}, + {174, 33, 134, 142, 13}, + {143, 227, 97, 3, 3} + }, + { {185, 180, 184, 120, 1}, + {71, 168, 182, 122, 4}, + {129, 225, 210, 217, 13}, + {37, 230, 209, 94, 2} + }, + { {50, 133, 121, 80, 5}, + {52, 10, 244, 57, 4}, + {160, 169, 234, 20, 12}, + {41, 194, 245, 2, 12} + }, + { {149, 233, 71, 119, 1}, + {189, 79, 146, 78, 9}, + {142, 238, 41, 122, 9}, + {151, 36, 159, 43, 13} + }, + { {154, 160, 48, 46, 2}, + {11, 56, 18, 19, 5}, + {71, 64, 192, 85, 9}, + {172, 132, 129, 205, 0} + }, + { {236, 24, 40, 209, 7}, + {198, 16, 228, 142, 14}, + {232, 177, 65, 131, 7}, + {119, 18, 112, 134, 3} + }, + { {188, 80, 121, 99, 5}, + {246, 12, 102, 30, 5}, + {172, 105, 224, 163, 13}, + {167, 134, 99, 6, 15} + }, + { {135, 133, 193, 183, 9}, + {188, 130, 147, 103, 3}, + {158, 216, 58, 30, 1}, + {206, 108, 148, 19, 13} + }, + { {211, 122, 173, 183, 10}, + {89, 157, 143, 199, 15}, + {94, 219, 85, 236, 11}, + {254, 63, 27, 153, 10} + }, + { {129, 127, 2, 206, 0}, + {73, 102, 8, 106, 11}, + {7, 52, 15, 232, 1}, + {213, 97, 6, 105, 2} + }, + { {253, 99, 223, 176, 10}, + {179, 223, 175, 210, 2}, + {80, 223, 188, 107, 15}, + {68, 191, 95, 188, 13} + }, + { {81, 10, 193, 175, 2}, + {56, 184, 10, 196, 11}, + {79, 88, 53, 8, 10}, + {210, 53, 1, 209, 12} + }, + { {61, 30, 223, 141, 3}, + {254, 249, 44, 116, 10}, + {203, 31, 183, 139, 12}, + {82, 227, 73, 247, 15} + }, + { {244, 183, 58, 64, 2}, + {193, 90, 60, 186, 4}, + {64, 37, 206, 210, 15}, + {37, 211, 197, 168, 3} + }, + { {55, 215, 137, 233, 12}, + {208, 174, 127, 109, 2}, + {57, 121, 30, 190, 12}, + {75, 111, 231, 80, 11} + }, + { {143, 17, 199, 124, 10}, + {250, 243, 131, 75, 0}, + {83, 238, 56, 143, 1}, + {13, 44, 28, 245, 15} + }, + { {196, 189, 3, 107, 14}, + {209, 114, 83, 174, 9}, + {125, 108, 11, 210, 3}, + {151, 92, 164, 232, 11} + }, + { {125, 250, 153, 92, 9}, + {223, 172, 189, 216, 8}, + {147, 169, 149, 251, 14}, + {17, 187, 211, 95, 11} + }, + { {123, 20, 232, 37, 1}, + {110, 136, 38, 229, 4}, + {138, 65, 114, 141, 14}, + {42, 118, 65, 23, 6} + }, + { {202, 7, 14, 127, 4}, + {10, 99, 206, 175, 1}, + {47, 231, 14, 5, 3}, + {143, 87, 60, 101, 0} + }, + { {92, 34, 219, 205, 5}, + {191, 232, 76, 156, 2}, + {171, 61, 180, 67, 10}, + {67, 147, 33, 127, 13} + }, + { {160, 219, 114, 108, 8}, + {104, 102, 59, 26, 12}, + {19, 100, 237, 176, 5}, + {53, 141, 198, 97, 6} + }, + { {107, 119, 118, 222, 2}, + {107, 119, 168, 249, 7}, + {71, 182, 238, 237, 6}, + {233, 241, 94, 237, 6} + }, + { {128, 245, 142, 116, 8}, + {73, 199, 151, 42, 0}, + {18, 231, 26, 240, 1}, + {5, 78, 158, 57, 2} + }, + { {225, 172, 31, 244, 10}, + {25, 81, 183, 250, 10}, + {82, 255, 131, 88, 7}, + {85, 254, 216, 169, 8} + }, + { {27, 186, 234, 133, 12}, + {107, 200, 93, 69, 14}, + {58, 21, 117, 221, 8}, + {122, 43, 161, 61, 6} + }, + { {38, 172, 85, 127, 12}, + {185, 33, 243, 61, 9}, + {63, 234, 163, 86, 4}, + {155, 204, 248, 73, 13} + }, + { {229, 209, 239, 53, 7}, + {252, 215, 246, 198, 4}, + {234, 207, 120, 186, 7}, + {38, 54, 254, 179, 15} + }, + { {31, 41, 212, 225, 0}, + {163, 139, 2, 93, 10}, + {8, 114, 185, 79, 8}, + {91, 164, 13, 28, 5} + }, + { {69, 159, 187, 21, 11}, + {220, 210, 157, 244, 12}, + {218, 141, 223, 154, 2}, + {50, 251, 148, 179, 11} + }, + { {212, 176, 73, 85, 9}, + {253, 8, 149, 142, 0}, + {154, 169, 32, 210, 11}, + {7, 26, 145, 11, 15} + }, + { {108, 183, 10, 207, 8}, + {203, 98, 61, 172, 3}, + {31, 53, 14, 211, 6}, + {195, 91, 196, 109, 3} + }, + { {248, 97, 122, 81, 8}, + {35, 78, 165, 158, 4}, + {24, 165, 232, 97, 15}, + {39, 154, 87, 44, 4} + }, + { {195, 145, 218, 195, 4}, + {96, 194, 84, 223, 3}, + {44, 53, 184, 156, 3}, + {207, 178, 164, 48, 6} + }, + { {81, 35, 94, 44, 12}, + {41, 107, 79, 208, 0}, + {51, 71, 172, 72, 10}, + {0, 191, 45, 105, 4} + }, + { {116, 64, 124, 79, 14}, + {168, 61, 101, 156, 5}, + {127, 35, 224, 34, 14}, + {163, 154, 107, 193, 5} + }, + { {223, 22, 9, 162, 4}, + {210, 8, 78, 227, 3}, + {36, 89, 6, 143, 11}, + {204, 119, 33, 4, 11} + }, + { {206, 210, 125, 193, 7}, + {246, 21, 92, 159, 6}, + {232, 59, 228, 183, 3}, + {111, 147, 170, 134, 15} + } +}; + +}//namespace diff --git a/aruco_pose/vendor/aruco/src/unionfind.hpp b/aruco_pose/vendor/aruco/src/unionfind.hpp new file mode 100644 index 00000000..1affa6b9 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/unionfind.hpp @@ -0,0 +1,133 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. +#ifndef _OPENCV_UNIONFIND_HPP_ +#define _OPENCV_UNIONFIND_HPP_ + +#include +#include +namespace cv { +namespace aruco { + +typedef struct unionfind unionfind_t; +struct unionfind{ + uint32_t maxid; + struct ufrec *data; +}; + +struct ufrec{ + // the parent of this node. If a node's parent is its own index, + // then it is a root. + uint32_t parent; + + // for the root of a connected component, the number of components + // connected to it. For intermediate values, it's not meaningful. + uint32_t size; +}; + +static inline unionfind_t *unionfind_create(uint32_t maxid){ + unionfind_t *uf = (unionfind_t*) calloc(1, sizeof(unionfind_t)); + uf->maxid = maxid; + uf->data = (struct ufrec*) malloc((maxid+1) * sizeof(struct ufrec)); + for (unsigned int i = 0; i <= maxid; i++) { + uf->data[i].size = 1; + uf->data[i].parent = i; + } + return uf; +} + +static inline void unionfind_destroy(unionfind_t *uf){ + free(uf->data); + free(uf); +} + +/* +static inline uint32_t unionfind_get_representative(unionfind_t *uf, uint32_t id) +{ + // base case: a node is its own parent + if (uf->data[id].parent == id) + return id; + + // otherwise, recurse + uint32_t root = unionfind_get_representative(uf, uf->data[id].parent); + + // short circuit the path. [XXX This write prevents tail recursion] + uf->data[id].parent = root; + + return root; +} + */ + +// this one seems to be every-so-slightly faster than the recursive +// version above. +static inline uint32_t unionfind_get_representative(unionfind_t *uf, uint32_t id){ + uint32_t root = id; + + // chase down the root + while (uf->data[root].parent != root) { + root = uf->data[root].parent; + } + + // go back and collapse the tree. + // + // XXX: on some of our workloads that have very shallow trees + // (e.g. image segmentation), we are actually faster not doing + // this... + while (uf->data[id].parent != root) { + uint32_t tmp = uf->data[id].parent; + uf->data[id].parent = root; + id = tmp; + } + + return root; +} + +static inline uint32_t unionfind_get_set_size(unionfind_t *uf, uint32_t id){ + uint32_t repid = unionfind_get_representative(uf, id); + return uf->data[repid].size; +} + +static inline uint32_t unionfind_connect(unionfind_t *uf, uint32_t aid, uint32_t bid){ + uint32_t aroot = unionfind_get_representative(uf, aid); + uint32_t broot = unionfind_get_representative(uf, bid); + + if (aroot == broot) + return aroot; + + // we don't perform "union by rank", but we perform a similar + // operation (but probably without the same asymptotic guarantee): + // We join trees based on the number of *elements* (as opposed to + // rank) contained within each tree. I.e., we use size as a proxy + // for rank. In my testing, it's often *faster* to use size than + // rank, perhaps because the rank of the tree isn't that critical + // if there are very few nodes in it. + uint32_t asize = uf->data[aroot].size; + uint32_t bsize = uf->data[broot].size; + + // optimization idea: We could shortcut some or all of the tree + // that is grafted onto the other tree. Pro: those nodes were just + // read and so are probably in cache. Con: it might end up being + // wasted effort -- the tree might be grafted onto another tree in + // a moment! + if (asize > bsize) { + uf->data[broot].parent = aroot; + uf->data[aroot].size += bsize; + return aroot; + } else { + uf->data[aroot].parent = broot; + uf->data[broot].size += asize; + return broot; + } +} +}} +#endif diff --git a/aruco_pose/vendor/aruco/src/zarray.hpp b/aruco_pose/vendor/aruco/src/zarray.hpp new file mode 100644 index 00000000..91933c5f --- /dev/null +++ b/aruco_pose/vendor/aruco/src/zarray.hpp @@ -0,0 +1,150 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. +#ifndef _OPENCV_ZARRAY_HPP_ +#define _OPENCV_ZARRAY_HPP_ + +#include +#include + +namespace cv { +namespace aruco { + + +struct sQuad{ + float p[4][2]; // corners +}; + +/** + * Defines a structure which acts as a resize-able array ala Java's ArrayList. + */ +typedef struct zarray zarray_t; +struct zarray{ + size_t el_sz; // size of each element + + int size; // how many elements? + int alloc; // we've allocated storage for how many elements? + char *data; +}; + +/** + * Creates and returns a variable array structure capable of holding elements of + * the specified size. It is the caller's responsibility to call zarray_destroy() + * on the returned array when it is no longer needed. + */ +inline static zarray_t *_zarray_create(size_t el_sz){ + zarray_t *za = (zarray_t*) calloc(1, sizeof(zarray_t)); + za->el_sz = el_sz; + return za; +} + +/** + * Frees all resources associated with the variable array structure which was + * created by zarray_create(). After calling, 'za' will no longer be valid for storage. + */ +inline static void _zarray_destroy(zarray_t *za){ + if (za == NULL) + return; + + if (za->data != NULL) + free(za->data); + memset(za, 0, sizeof(zarray_t)); + free(za); +} + +/** + * Retrieves the number of elements currently being contained by the passed + * array, which may be different from its capacity. The index of the last element + * in the array will be one less than the returned value. + */ +inline static int _zarray_size(const zarray_t *za){ + return za->size; +} + +/** + * Allocates enough internal storage in the supplied variable array structure to + * guarantee that the supplied number of elements (capacity) can be safely stored. + */ +inline static void _zarray_ensure_capacity(zarray_t *za, int capacity){ + if (capacity <= za->alloc) + return; + + while (za->alloc < capacity) { + za->alloc *= 2; + if (za->alloc < 8) + za->alloc = 8; + } + + za->data = (char*) realloc(za->data, za->alloc * za->el_sz); +} + +/** + * Adds a new element to the end of the supplied array, and sets its value + * (by copying) from the data pointed to by the supplied pointer 'p'. + * Automatically ensures that enough storage space is available for the new element. + */ +inline static void _zarray_add(zarray_t *za, const void *p){ + _zarray_ensure_capacity(za, za->size + 1); + + memcpy(&za->data[za->size*za->el_sz], p, za->el_sz); + za->size++; +} + +/** + * Retrieves the element from the supplied array located at the zero-based + * index of 'idx' and copies its value into the variable pointed to by the pointer + * 'p'. + */ +inline static void _zarray_get(const zarray_t *za, int idx, void *p){ + CV_DbgAssert(idx >= 0); + CV_DbgAssert(idx < za->size); + + memcpy(p, &za->data[idx*za->el_sz], za->el_sz); +} + +/** + * Similar to zarray_get(), but returns a "live" pointer to the internal + * storage, avoiding a memcpy. This pointer is not valid across + * operations which might move memory around (i.e. zarray_remove_value(), + * zarray_remove_index(), zarray_insert(), zarray_sort(), zarray_clear()). + * 'p' should be a pointer to the pointer which will be set to the internal address. + */ +inline static void _zarray_get_volatile(const zarray_t *za, int idx, void *p){ + CV_DbgAssert(idx >= 0); + CV_DbgAssert(idx < za->size); + + *((void**) p) = &za->data[idx*za->el_sz]; +} + +inline static void _zarray_truncate(zarray_t *za, int sz){ + za->size = sz; +} + +/** + * Sets the value of the current element at index 'idx' by copying its value from + * the data pointed to by 'p'. The previous value of the changed element will be + * copied into the data pointed to by 'outp' if it is not null. + */ +static inline void _zarray_set(zarray_t *za, int idx, const void *p, void *outp){ + CV_DbgAssert(idx >= 0); + CV_DbgAssert(idx < za->size); + + if (outp != NULL) + memcpy(outp, &za->data[idx*za->el_sz], za->el_sz); + + memcpy(&za->data[idx*za->el_sz], p, za->el_sz); +} + +} +} +#endif diff --git a/aruco_pose/vendor/aruco/src/zmaxheap.cpp b/aruco_pose/vendor/aruco/src/zmaxheap.cpp new file mode 100644 index 00000000..271bcea5 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/zmaxheap.cpp @@ -0,0 +1,208 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. + +#include "precomp.hpp" +#include "zmaxheap.hpp" + + +// 0 +// 1 2 +// 3 4 5 6 +// 7 8 9 10 11 12 13 14 +// +// Children of node i: 2*i+1, 2*i+2 +// Parent of node i: (i-1) / 2 +// +// Heap property: a parent is greater than (or equal to) its children. + +#define MIN_CAPACITY 16 +namespace cv { +namespace aruco { +struct zmaxheap +{ + size_t el_sz; + + int size; + int alloc; + + float *values; + char *data; + + void (*swap)(zmaxheap_t *heap, int a, int b); +}; + +static inline void _swap_default(zmaxheap_t *heap, int a, int b) +{ + float t = heap->values[a]; + heap->values[a] = heap->values[b]; + heap->values[b] = t; + + cv::AutoBuffer tmp(heap->el_sz); + /* NOTE: OpenCV v<3.3 does not have .data() member for AutoBuffer */ + memcpy(tmp, &heap->data[a*heap->el_sz], heap->el_sz); + memcpy(&heap->data[a*heap->el_sz], &heap->data[b*heap->el_sz], heap->el_sz); + memcpy(&heap->data[b*heap->el_sz], tmp, heap->el_sz); +} + +static inline void _swap_pointer(zmaxheap_t *heap, int a, int b) +{ + float t = heap->values[a]; + heap->values[a] = heap->values[b]; + heap->values[b] = t; + + void **pp = (void**) heap->data; + void *tmp = pp[a]; + pp[a] = pp[b]; + pp[b] = tmp; +} + + +zmaxheap_t *zmaxheap_create(size_t el_sz) +{ + zmaxheap_t *heap = (zmaxheap_t*)calloc(1, sizeof(zmaxheap_t)); + heap->el_sz = el_sz; + + heap->swap = _swap_default; + + if (el_sz == sizeof(void*)) + heap->swap = _swap_pointer; + + return heap; +} + +void zmaxheap_destroy(zmaxheap_t *heap) +{ + free(heap->values); + free(heap->data); + memset(heap, 0, sizeof(zmaxheap_t)); + free(heap); +} + +static void _zmaxheap_ensure_capacity(zmaxheap_t *heap, int capacity) +{ + if (heap->alloc >= capacity) + return; + + int newcap = heap->alloc; + + while (newcap < capacity) { + if (newcap < MIN_CAPACITY) { + newcap = MIN_CAPACITY; + continue; + } + + newcap *= 2; + } + + heap->values = (float*)realloc(heap->values, newcap * sizeof(float)); + heap->data = (char*)realloc(heap->data, newcap * heap->el_sz); + heap->alloc = newcap; +} + +void zmaxheap_add(zmaxheap_t *heap, void *p, float v) +{ + _zmaxheap_ensure_capacity(heap, heap->size + 1); + + int idx = heap->size; + + heap->values[idx] = v; + memcpy(&heap->data[idx*heap->el_sz], p, heap->el_sz); + + heap->size++; + + while (idx > 0) { + + int parent = (idx - 1) / 2; + + // we're done! + if (heap->values[parent] >= v) + break; + + // else, swap and recurse upwards. + heap->swap(heap, idx, parent); + idx = parent; + } +} + +// Removes the item in the heap at the given index. Returns 1 if the +// item existed. 0 Indicates an invalid idx (heap is smaller than +// idx). This is mostly intended to be used by zmaxheap_remove_max. +static int zmaxheap_remove_index(zmaxheap_t *heap, int idx, void *p, float *v) +{ + if (idx >= heap->size) + return 0; + + // copy out the requested element from the heap. + if (v != NULL) + *v = heap->values[idx]; + if (p != NULL) + memcpy(p, &heap->data[idx*heap->el_sz], heap->el_sz); + + heap->size--; + + // If this element is already the last one, then there's nothing + // for us to do. + if (idx == heap->size) + return 1; + + // copy last element to first element. (which probably upsets + // the heap property). + heap->values[idx] = heap->values[heap->size]; + memcpy(&heap->data[idx*heap->el_sz], &heap->data[heap->el_sz * heap->size], heap->el_sz); + + // now fix the heap. Note, as we descend, we're "pushing down" + // the same node the entire time. Thus, while the index of the + // parent might change, the parent_score doesn't. + int parent = idx; + float parent_score = heap->values[idx]; + + // descend, fixing the heap. + while (parent < heap->size) { + + int left = 2*parent + 1; + int right = left + 1; + +// assert(parent_score == heap->values[parent]); + + float left_score = (left < heap->size) ? heap->values[left] : -INFINITY; + float right_score = (right < heap->size) ? heap->values[right] : -INFINITY; + + // put the biggest of (parent, left, right) as the parent. + + // already okay? + if (parent_score >= left_score && parent_score >= right_score) + break; + + // if we got here, then one of the children is bigger than the parent. + if (left_score >= right_score) { + CV_Assert(left < heap->size); + heap->swap(heap, parent, left); + parent = left; + } else { + // right_score can't be less than left_score if right_score is -INFINITY. + CV_Assert(right < heap->size); + heap->swap(heap, parent, right); + parent = right; + } + } + + return 1; +} + +int zmaxheap_remove_max(zmaxheap_t *heap, void *p, float *v) +{ + return zmaxheap_remove_index(heap, 0, p, v); +} + +}} diff --git a/aruco_pose/vendor/aruco/src/zmaxheap.hpp b/aruco_pose/vendor/aruco/src/zmaxheap.hpp new file mode 100644 index 00000000..7055e512 --- /dev/null +++ b/aruco_pose/vendor/aruco/src/zmaxheap.hpp @@ -0,0 +1,42 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2013-2016, The Regents of The University of Michigan. +// +// This software was developed in the APRIL Robotics Lab under the +// direction of Edwin Olson, ebolson@umich.edu. This software may be +// available under alternative licensing terms; contact the address above. +// +// The views and conclusions contained in the software and documentation are those +// of the authors and should not be interpreted as representing official policies, +// either expressed or implied, of the Regents of The University of Michigan. +#ifndef _OPENCV_ZMAXHEAP_HPP_ +#define _OPENCV_ZMAXHEAP_HPP_ + +#include +#include +#include + +namespace cv { +namespace aruco { +typedef struct zmaxheap zmaxheap_t; + +typedef struct zmaxheap_iterator zmaxheap_iterator_t; +struct zmaxheap_iterator { + zmaxheap_t *heap; + int in, out; +}; + +zmaxheap_t *zmaxheap_create(size_t el_sz); + +void zmaxheap_destroy(zmaxheap_t *heap); + +void zmaxheap_add(zmaxheap_t *heap, void *p, float v); + +// returns 0 if the heap is empty, so you can do +// while (zmaxheap_remove_max(...)) { } +int zmaxheap_remove_max(zmaxheap_t *heap, void *p, float *v); + +}} +#endif diff --git a/builder/assets/kinetic-rosdep-clever.yaml b/builder/assets/kinetic-rosdep-clever.yaml index 25b3cdb5..ca553788 100644 --- a/builder/assets/kinetic-rosdep-clever.yaml +++ b/builder/assets/kinetic-rosdep-clever.yaml @@ -1,531 +1,531 @@ actionlib: debian: - stretch: [ros-kinetic-actionlib] + buster: [ros-kinetic-actionlib] actionlib_msgs: debian: - stretch: [ros-kinetic-actionlib-msgs] + buster: [ros-kinetic-actionlib-msgs] angles: debian: - stretch: [ros-kinetic-angles] + buster: [ros-kinetic-angles] async_web_server_cpp: debian: - stretch: [ros-kinetic-async-web-server-cpp] + buster: [ros-kinetic-async-web-server-cpp] bond: debian: - stretch: [ros-kinetic-bond] + buster: [ros-kinetic-bond] bondcpp: debian: - stretch: [ros-kinetic-bondcpp] + buster: [ros-kinetic-bondcpp] bondpy: debian: - stretch: [ros-kinetic-bondpy] + buster: [ros-kinetic-bondpy] camera_calibration_parsers: debian: - stretch: [ros-kinetic-camera-calibration-parsers] + buster: [ros-kinetic-camera-calibration-parsers] camera_info_manager: debian: - stretch: [ros-kinetic-camera-info-manager] + buster: [ros-kinetic-camera-info-manager] catkin: debian: - stretch: [ros-kinetic-catkin] + buster: [ros-kinetic-catkin] class_loader: debian: - stretch: [ros-kinetic-class-loader] + buster: [ros-kinetic-class-loader] cmake_modules: debian: - stretch: [ros-kinetic-cmake-modules] + buster: [ros-kinetic-cmake-modules] cpp_common: debian: - stretch: [ros-kinetic-cpp-common] + buster: [ros-kinetic-cpp-common] cv_bridge: debian: - stretch: [ros-kinetic-cv-bridge] + buster: [ros-kinetic-cv-bridge] cv_camera: debian: - stretch: [ros-kinetic-cv-camera=0.3.1-0stretch] + buster: [ros-kinetic-cv-camera=0.3.1-0buster] diagnostic_msgs: debian: - stretch: [ros-kinetic-diagnostic-msgs] + buster: [ros-kinetic-diagnostic-msgs] diagnostic_updater: debian: - stretch: [ros-kinetic-diagnostic-updater] + buster: [ros-kinetic-diagnostic-updater] eigen_conversions: debian: - stretch: [ros-kinetic-eigen-conversions] + buster: [ros-kinetic-eigen-conversions] gencpp: debian: - stretch: [ros-kinetic-gencpp] + buster: [ros-kinetic-gencpp] geneus: debian: - stretch: [ros-kinetic-geneus] + buster: [ros-kinetic-geneus] genlisp: debian: - stretch: [ros-kinetic-genlisp] + buster: [ros-kinetic-genlisp] genmsg: debian: - stretch: [ros-kinetic-genmsg] + buster: [ros-kinetic-genmsg] gennodejs: debian: - stretch: [ros-kinetic-gennodejs] + buster: [ros-kinetic-gennodejs] genpy: debian: - stretch: [ros-kinetic-genpy] + buster: [ros-kinetic-genpy] geographic_msgs: debian: - stretch: [ros-kinetic-geographic-msgs] + buster: [ros-kinetic-geographic-msgs] geometry_msgs: debian: - stretch: [ros-kinetic-geometry-msgs] + buster: [ros-kinetic-geometry-msgs] image_transport: debian: - stretch: [ros-kinetic-image-transport] + buster: [ros-kinetic-image-transport] libmavconn: debian: - stretch: [ros-kinetic-libmavconn] + buster: [ros-kinetic-libmavconn] lxml: debian: - stretch: [python-lxml=3.7.1-1] + buster: [python-lxml=3.7.1-1] mavlink: debian: - stretch: [ros-kinetic-mavlink] + buster: [ros-kinetic-mavlink] mavros: debian: - stretch: [ros-kinetic-mavros] + buster: [ros-kinetic-mavros] mavros_msgs: debian: - stretch: [ros-kinetic-mavros-msgs] + buster: [ros-kinetic-mavros-msgs] mavros_extras: debian: - stretch: [ros-kinetic-mavros-extras] + buster: [ros-kinetic-mavros-extras] message_filters: debian: - stretch: [ros-kinetic-message-filters] + buster: [ros-kinetic-message-filters] message_generation: debian: - stretch: [ros-kinetic-message-generation] + buster: [ros-kinetic-message-generation] message_runtime: debian: - stretch: [ros-kinetic-message-runtime] + buster: [ros-kinetic-message-runtime] mjpg-streamer: debian: - stretch: [mjpg-streamer=2.0] + buster: [mjpg-streamer=2.0] mk: debian: - stretch: [ros-kinetic-mk] + buster: [ros-kinetic-mk] nav_msgs: debian: - stretch: [ros-kinetic-nav-msgs] + buster: [ros-kinetic-nav-msgs] nodelet: debian: - stretch: [ros-kinetic-nodelet] + buster: [ros-kinetic-nodelet] opencv3: debian: - stretch: [ros-kinetic-opencv3] + buster: [ros-kinetic-opencv3] orocos_kdl: debian: - stretch: [ros-kinetic-orocos-kdl] + buster: [ros-kinetic-orocos-kdl] pluginlib: debian: - stretch: [ros-kinetic-pluginlib] + buster: [ros-kinetic-pluginlib] python_orocos_kdl: debian: - stretch: [ros-kinetic-python-orocos-kdl] + buster: [ros-kinetic-python-orocos-kdl] ros: debian: - stretch: [ros-kinetic-ros] + buster: [ros-kinetic-ros] ros_comm: debian: - stretch: [ros-kinetic-ros-comm] + buster: [ros-kinetic-ros-comm] ros_environment: debian: - stretch: [ros-kinetic-ros-environment] + buster: [ros-kinetic-ros-environment] rosapi: debian: - stretch: [ros-kinetic-rosapi] + buster: [ros-kinetic-rosapi] rosauth: debian: - stretch: [ros-kinetic-rosauth] + buster: [ros-kinetic-rosauth] rosbag: debian: - stretch: [ros-kinetic-rosbag] + buster: [ros-kinetic-rosbag] rosbag_migration_rule: debian: - stretch: [ros-kinetic-rosbag-migration-rule] + buster: [ros-kinetic-rosbag-migration-rule] rosbag_storage: debian: - stretch: [ros-kinetic-rosbag-storage] + buster: [ros-kinetic-rosbag-storage] rosbash: debian: - stretch: [ros-kinetic-rosbash] + buster: [ros-kinetic-rosbash] rosboost_cfg: debian: - stretch: [ros-kinetic-rosboost-cfg] + buster: [ros-kinetic-rosboost-cfg] rosbridge_library: debian: - stretch: [ros-kinetic-rosbridge-library] + buster: [ros-kinetic-rosbridge-library] rosbridge_server: debian: - stretch: [ros-kinetic-rosbridge-server] + buster: [ros-kinetic-rosbridge-server] rosbuild: debian: - stretch: [ros-kinetic-rosbuild] + buster: [ros-kinetic-rosbuild] rosclean: debian: - stretch: [ros-kinetic-rosclean] + buster: [ros-kinetic-rosclean] rosconsole: debian: - stretch: [ros-kinetic-rosconsole] + buster: [ros-kinetic-rosconsole] rosconsole_bridge: debian: - stretch: [ros-kinetic-rosconsole-bridge] + buster: [ros-kinetic-rosconsole-bridge] roscpp: debian: - stretch: [ros-kinetic-roscpp] + buster: [ros-kinetic-roscpp] roscpp_serialization: debian: - stretch: [ros-kinetic-roscpp-serialization] + buster: [ros-kinetic-roscpp-serialization] roscpp_traits: debian: - stretch: [ros-kinetic-roscpp-traits] + buster: [ros-kinetic-roscpp-traits] roscreate: debian: - stretch: [ros-kinetic-roscreate] + buster: [ros-kinetic-roscreate] rosgraph: debian: - stretch: [ros-kinetic-rosgraph] + buster: [ros-kinetic-rosgraph] rosgraph_msgs: debian: - stretch: [ros-kinetic-rosgraph-msgs] + buster: [ros-kinetic-rosgraph-msgs] roslang: debian: - stretch: [ros-kinetic-roslang] + buster: [ros-kinetic-roslang] roslaunch: debian: - stretch: [ros-kinetic-roslaunch] + buster: [ros-kinetic-roslaunch] roslib: debian: - stretch: [ros-kinetic-roslib] + buster: [ros-kinetic-roslib] roslint: debian: - stretch: [ros-kinetic-roslint] + buster: [ros-kinetic-roslint] roslisp: debian: - stretch: [ros-kinetic-roslisp] + buster: [ros-kinetic-roslisp] roslz4: debian: - stretch: [ros-kinetic-roslz4] + buster: [ros-kinetic-roslz4] rosmake: debian: - stretch: [ros-kinetic-rosmake] + buster: [ros-kinetic-rosmake] rosmaster: debian: - stretch: [ros-kinetic-rosmaster] + buster: [ros-kinetic-rosmaster] rosmsg: debian: - stretch: [ros-kinetic-rosmsg] + buster: [ros-kinetic-rosmsg] rosnode: debian: - stretch: [ros-kinetic-rosnode] + buster: [ros-kinetic-rosnode] rosout: debian: - stretch: [ros-kinetic-rosout] + buster: [ros-kinetic-rosout] rospack: debian: - stretch: [ros-kinetic-rospack] + buster: [ros-kinetic-rospack] rosparam: debian: - stretch: [ros-kinetic-rosparam] + buster: [ros-kinetic-rosparam] rospy: debian: - stretch: [ros-kinetic-rospy] + buster: [ros-kinetic-rospy] rospy_tutorials: debian: - stretch: [ros-kinetic-rospy-tutorials] + buster: [ros-kinetic-rospy-tutorials] rosserial_client: debian: - stretch: [ros-kinetic-rosserial-client] + buster: [ros-kinetic-rosserial-client] rosserial_msgs: debian: - stretch: [ros-kinetic-rosserial-msgs] + buster: [ros-kinetic-rosserial-msgs] rosserial_python: debian: - stretch: [ros-kinetic-rosserial-python] + buster: [ros-kinetic-rosserial-python] rosservice: debian: - stretch: [ros-kinetic-rosservice] + buster: [ros-kinetic-rosservice] rostest: debian: - stretch: [ros-kinetic-rostest] + buster: [ros-kinetic-rostest] rostime: debian: - stretch: [ros-kinetic-rostime] + buster: [ros-kinetic-rostime] rostopic: debian: - stretch: [ros-kinetic-rostopic] + buster: [ros-kinetic-rostopic] rosunit: debian: - stretch: [ros-kinetic-rosunit] + buster: [ros-kinetic-rosunit] roswtf: debian: - stretch: [ros-kinetic-roswtf] + buster: [ros-kinetic-roswtf] sensor_msgs: debian: - stretch: [ros-kinetic-sensor-msgs] + buster: [ros-kinetic-sensor-msgs] smclib: debian: - stretch: [ros-kinetic-smclib] + buster: [ros-kinetic-smclib] std_msgs: debian: - stretch: [ros-kinetic-std-msgs] + buster: [ros-kinetic-std-msgs] std_srvs: debian: - stretch: [ros-kinetic-std-srvs] + buster: [ros-kinetic-std-srvs] stereo_msgs: debian: - stretch: [ros-kinetic-stereo-msgs] + buster: [ros-kinetic-stereo-msgs] tf2: debian: - stretch: [ros-kinetic-tf2] + buster: [ros-kinetic-tf2] tf2_bullet: debian: - stretch: [ros-kinetic-tf2-bullet] + buster: [ros-kinetic-tf2-bullet] tf2_eigen: debian: - stretch: [ros-kinetic-tf2-eigen] + buster: [ros-kinetic-tf2-eigen] tf2_geometry_msgs: debian: - stretch: [ros-kinetic-tf2-geometry-msgs] + buster: [ros-kinetic-tf2-geometry-msgs] tf2_kdl: debian: - stretch: [ros-kinetic-tf2-kdl] + buster: [ros-kinetic-tf2-kdl] tf2_msgs: debian: - stretch: [ros-kinetic-tf2-msgs] + buster: [ros-kinetic-tf2-msgs] tf2_py: debian: - stretch: [ros-kinetic-tf2-py] + buster: [ros-kinetic-tf2-py] tf2_ros: debian: - stretch: [ros-kinetic-tf2-ros] + buster: [ros-kinetic-tf2-ros] tf2_sensor_msgs: debian: - stretch: [ros-kinetic-tf2-sensor-msgs] + buster: [ros-kinetic-tf2-sensor-msgs] tf2_tools: debian: - stretch: [ros-kinetic-tf2-tools] + buster: [ros-kinetic-tf2-tools] tf: debian: - stretch: [ros-kinetic-tf] + buster: [ros-kinetic-tf] topic_tools: debian: - stretch: [ros-kinetic-topic-tools] + buster: [ros-kinetic-topic-tools] trajectory_msgs: debian: - stretch: [ros-kinetic-trajectory-msgs] + buster: [ros-kinetic-trajectory-msgs] urdf: debian: - stretch: [ros-kinetic-urdf] + buster: [ros-kinetic-urdf] urdf_parser_plugin: debian: - stretch: [ros-kinetic-urdf-parser-plugin] + buster: [ros-kinetic-urdf-parser-plugin] uuid_msgs: debian: - stretch: [ros-kinetic-uuid-msgs] + buster: [ros-kinetic-uuid-msgs] visualization_msgs: debian: - stretch: [ros-kinetic-visualization-msgs] + buster: [ros-kinetic-visualization-msgs] xmlrpcpp: debian: - stretch: [ros-kinetic-xmlrpcpp] + buster: [ros-kinetic-xmlrpcpp] boost: debian: - stretch: [libboost-all-dev] + buster: [libboost-all-dev] bullet: debian: - stretch: [libbullet-dev] + buster: [libbullet-dev] bzip2: debian: - stretch: [libbz2-dev] + buster: [libbz2-dev] cmake: debian: - stretch: [cmake] + buster: [cmake] cppunit: debian: - stretch: [libcppunit-dev] + buster: [libcppunit-dev] eigen: debian: - stretch: [libeigen3-dev] + buster: [libeigen3-dev] geographiclib-tools: debian: - stretch: [geographiclib-tools] + buster: [geographiclib-tools] geographiclib: debian: - stretch: [libgeographic-dev] + buster: [libgeographic-dev] google-mock: debian: - stretch: [google-mock] + buster: [google-mock] graphviz: debian: - stretch: [graphviz] + buster: [graphviz] gtest: debian: - stretch: [libgtest-dev] + buster: [libgtest-dev] libconsole-bridge-dev: debian: - stretch: [libconsole-bridge-dev] + buster: [libconsole-bridge-dev] libjpeg: debian: - stretch: [libjpeg-dev] + buster: [libjpeg-dev] libpng-dev: debian: - stretch: [libpng-dev] + buster: [libpng-dev] libpoco-dev: debian: - stretch: [libpoco-dev] + buster: [libpoco-dev] libssl-dev: debian: - stretch: [libssl-dev] + buster: [libssl-dev] libtiff-dev: debian: - stretch: [libtiff5-dev] + buster: [libtiff5-dev] liburdfdom-dev: debian: - stretch: [liburdfdom-dev] + buster: [liburdfdom-dev] liburdfdom-headers-dev: debian: - stretch: [liburdfdom-headers-dev] + buster: [liburdfdom-headers-dev] libv4l-dev: debian: - stretch: [libv4l-dev] + buster: [libv4l-dev] libvtk-qt: debian: - stretch: [libvtk6-qt-dev] + buster: [libvtk6-qt-dev] libwebp-dev: debian: - stretch: [libwebp-dev] + buster: [libwebp-dev] log4cxx: debian: - stretch: [liblog4cxx-dev] + buster: [liblog4cxx-dev] lz4: debian: - stretch: [liblz4-dev] + buster: [liblz4-dev] pkg-config: debian: - stretch: [pkg-config] + buster: [pkg-config] protobuf: debian: - stretch: [libprotobuf10] + buster: [libprotobuf10] python-bson: debian: - stretch: [python-bson] + buster: [python-bson] python-catkin-pkg: debian: - stretch: [python-catkin-pkg] + buster: [python-catkin-pkg] python-coverage: debian: - stretch: [python-coverage] + buster: [python-coverage] python-defusedxml: debian: - stretch: [python-defusedxml] + buster: [python-defusedxml] python-empy: debian: - stretch: [python-empy] + buster: [python-empy] python-future: debian: - stretch: [python-future] + buster: [python-future] python-imaging: debian: - stretch: [python-imaging] + buster: [python-imaging] python-lxml: debian: - stretch: [python-lxml] + buster: [python-lxml] python-mock: debian: - stretch: [python-mock] + buster: [python-mock] python-netifaces: debian: - stretch: [python-netifaces] + buster: [python-netifaces] python-nose: debian: - stretch: [python-nose] + buster: [python-nose] python-numpy: debian: - stretch: [python-numpy] + buster: [python-numpy] python-paramiko: debian: - stretch: [python-paramiko] + buster: [python-paramiko] python-rosdep: debian: - stretch: [python-rosdep] + buster: [python-rosdep] python-rospkg: debian: - stretch: [python-rospkg] + buster: [python-rospkg] python-serial: debian: - stretch: [python-serial] + buster: [python-serial] python-setuptools: debian: - stretch: [python-setuptools] + buster: [python-setuptools] python-sip: debian: - stretch: [python-sip-dev] + buster: [python-sip-dev] python-tornado: debian: - stretch: [python-tornado] + buster: [python-tornado] python-twisted-core: debian: - stretch: [python-twisted-core] + buster: [python-twisted-core] python-websocket: debian: - stretch: [python-websocket] + buster: [python-websocket] python-wxtools: debian: - stretch: [python-wxtools] + buster: [python-wxtools] python-yaml: debian: - stretch: [python-yaml] + buster: [python-yaml] python: debian: - stretch: [python-dev] + buster: [python-dev] sbcl: debian: - stretch: [sbcl] + buster: [sbcl] tinyxml2: debian: - stretch: [libtinyxml2-dev] + buster: [libtinyxml2-dev] tinyxml: debian: - stretch: [libtinyxml-dev] + buster: [libtinyxml-dev] uuid: debian: - stretch: [uuid-dev] + buster: [uuid-dev] web_video_server: debian: - stretch: [ros-kinetic-web-video-server] + buster: [ros-kinetic-web-video-server] v4l-utils: debian: - stretch: [v4l-utils] + buster: [v4l-utils] yaml-cpp: debian: - stretch: [libyaml-cpp-dev] + buster: [libyaml-cpp-dev] zlib: debian: - stretch: [zlib1g-dev] + buster: [zlib1g-dev] compressed_depth_image_transport: debian: - stretch: [ros-kinetic-compressed-depth-image-transport] + buster: [ros-kinetic-compressed-depth-image-transport] compressed_image_transport: debian: - stretch: [ros-kinetic-compressed-image-transport] + buster: [ros-kinetic-compressed-image-transport] dynamic_reconfigure: debian: - stretch: [ros-kinetic-dynamic-reconfigure] + buster: [ros-kinetic-dynamic-reconfigure] theora_image_transport: debian: - stretch: [ros-kinetic-theora-image-transport] + buster: [ros-kinetic-theora-image-transport] libogg: debian: - stretch: [libtheora0=1.1.1+dfsg.1-14] + buster: [libtheora0=1.1.1+dfsg.1-14] vl53l1x: debian: stretch: [ros-kinetic-vl53l1x] @@ -537,25 +537,25 @@ led_msgs: stretch: [ros-kinetic-led-msgs] interactive_markers: debian: - stretch: [ros-kinetic-interactive-markers] + buster: [ros-kinetic-interactive-markers] interactive_marker_proxy: debian: - stretch: [ros-kinetic-interactive-marker-proxy] + buster: [ros-kinetic-interactive-marker-proxy] tf2_web_republisher: debian: - stretch: [ros-kinetic-tf2-web-republisher] + buster: [ros-kinetic-tf2-web-republisher] image_publisher: debian: - stretch: [ros-kinetic-image-publisher] + buster: [ros-kinetic-image-publisher] raspberry-kernel-headers: debian: - stretch: [raspberry-kernel-headers] + buster: [raspberry-kernel-headers] ddynamic_reconfigure: debian: - stretch: [ros-kinetic-ddynamic-reconfigure] + buster: [ros-kinetic-ddynamic-reconfigure] realsense2_camera: debian: - stretch: [ros-kinetic-realsense2-camera] + buster: [ros-kinetic-realsense2-camera] ros_pytest: debian: - stretch: [ros-kinetic-ros-pytest] + buster: [ros-kinetic-ros-pytest] diff --git a/builder/assets/melodic-rosdep-clever.yaml b/builder/assets/melodic-rosdep-clever.yaml new file mode 100644 index 00000000..f888a0cc --- /dev/null +++ b/builder/assets/melodic-rosdep-clever.yaml @@ -0,0 +1,735 @@ +catkin: + debian: + buster: [ros-melodic-catkin] +genmsg: + debian: + buster: [ros-melodic-genmsg] +gencpp: + debian: + buster: [ros-melodic-gencpp] +geneus: + debian: + buster: [ros-melodic-geneus] +genlisp: + debian: + buster: [ros-melodic-genlisp] +gennodejs: + debian: + buster: [ros-melodic-gennodejs] +genpy: + debian: + buster: [ros-melodic-genpy] +bond_core: + debian: + buster: [ros-melodic-bond-core] +cmake_modules: + debian: + buster: [ros-melodic-cmake-modules] +class_loader: + debian: + buster: [ros-melodic-class-loader] +common_msgs: + debian: + buster: [ros-melodic-common-msgs] +common_tutorials: + debian: + buster: [ros-melodic-common-tutorials] +cpp_common: + debian: + buster: [ros-melodic-cpp-common] +desktop: + debian: + buster: [ros-melodic-desktop] +diagnostics: + debian: + buster: [ros-melodic-diagnostics] +executive_smach: + debian: + buster: [ros-melodic-executive-smach] +geometry: + debian: + buster: [ros-melodic-geometry] +geometry_tutorials: + debian: + buster: [ros-melodic-geometry-tutorials] +gl_dependency: + debian: + buster: [ros-melodic-gl-dependency] +image_common: + debian: + buster: [ros-melodic-image-common] +image_pipeline: + debian: + buster: [ros-melodic-image-pipeline] +image_transport_plugins: + debian: + buster: [ros-melodic-image-transport-plugins] +laser_pipeline: + debian: + buster: [ros-melodic-laser-pipeline] +mavlink: + debian: + buster: [ros-melodic-mavlink] +media_export: + debian: + buster: [ros-melodic-media-export] +message_generation: + debian: + buster: [ros-melodic-message-generation] +message_runtime: + debian: + buster: [ros-melodic-message-runtime] +mk: + debian: + buster: [ros-melodic-mk] +nodelet_core: + debian: + buster: [ros-melodic-nodelet-core] +orocos_kdl: + debian: + buster: [ros-melodic-orocos-kdl] +perception: + debian: + buster: [ros-melodic-perception] +perception_pcl: + debian: + buster: [ros-melodic-perception-pcl] +python_orocos_kdl: + debian: + buster: [ros-melodic-python-orocos-kdl] +qt_dotgraph: + debian: + buster: [ros-melodic-qt-dotgraph] +qt_gui: + debian: + buster: [ros-melodic-qt-gui] +qt_gui_py_common: + debian: + buster: [ros-melodic-qt-gui-py-common] +qwt_dependency: + debian: + buster: [ros-melodic-qwt-dependency] +robot: + debian: + buster: [ros-melodic-robot] +ros: + debian: + buster: [ros-melodic-ros] +ros_base: + debian: + buster: [ros-melodic-ros-base] +ros_comm: + debian: + buster: [ros-melodic-ros-comm] +ros_core: + debian: + buster: [ros-melodic-ros-core] +ros_environment: + debian: + buster: [ros-melodic-ros-environment] +ros_tutorials: + debian: + buster: [ros-melodic-ros-tutorials] +rosapi: + debian: + buster: [ros-melodic-rosapi] +rosbag_migration_rule: + debian: + buster: [ros-melodic-rosbag-migration-rule] +rosbash: + debian: + buster: [ros-melodic-rosbash] +rosboost_cfg: + debian: + buster: [ros-melodic-rosboost-cfg] +rosbridge_server: + debian: + buster: [ros-melodic-rosbridge-server] +rosbridge_suite: + debian: + buster: [ros-melodic-rosbridge-suite] +rosbuild: + debian: + buster: [ros-melodic-rosbuild] +rosclean: + debian: + buster: [ros-melodic-rosclean] +roscpp_core: + debian: + buster: [ros-melodic-roscpp-core] +roscpp_traits: + debian: + buster: [ros-melodic-roscpp-traits] +roscreate: + debian: + buster: [ros-melodic-roscreate] +rosgraph: + debian: + buster: [ros-melodic-rosgraph] +roslang: + debian: + buster: [ros-melodic-roslang] +roslint: + debian: + buster: [ros-melodic-roslint] +roslisp: + debian: + buster: [ros-melodic-roslisp] +rosmake: + debian: + buster: [ros-melodic-rosmake] +rosmaster: + debian: + buster: [ros-melodic-rosmaster] +rospack: + debian: + buster: [ros-melodic-rospack] +roslib: + debian: + buster: [ros-melodic-roslib] +rosparam: + debian: + buster: [ros-melodic-rosparam] +rospy: + debian: + buster: [ros-melodic-rospy] +rosserial: + debian: + buster: [ros-melodic-rosserial] +rosserial_msgs: + debian: + buster: [ros-melodic-rosserial-msgs] +rosserial_python: + debian: + buster: [ros-melodic-rosserial-python] +rosservice: + debian: + buster: [ros-melodic-rosservice] +rostime: + debian: + buster: [ros-melodic-rostime] +roscpp_serialization: + debian: + buster: [ros-melodic-roscpp-serialization] +python_qt_binding: + debian: + buster: [ros-melodic-python-qt-binding] +roslaunch: + debian: + buster: [ros-melodic-roslaunch] +rosunit: + debian: + buster: [ros-melodic-rosunit] +angles: + debian: + buster: [ros-melodic-angles] +libmavconn: + debian: + buster: [ros-melodic-libmavconn] +rosconsole: + debian: + buster: [ros-melodic-rosconsole] +pluginlib: + debian: + buster: [ros-melodic-pluginlib] +qt_gui_cpp: + debian: + buster: [ros-melodic-qt-gui-cpp] +resource_retriever: + debian: + buster: [ros-melodic-resource-retriever] +rosconsole_bridge: + debian: + buster: [ros-melodic-rosconsole-bridge] +roslz4: + debian: + buster: [ros-melodic-roslz4] +rosserial_client: + debian: + buster: [ros-melodic-rosserial-client] +rostest: + debian: + buster: [ros-melodic-rostest] +rqt_action: + debian: + buster: [ros-melodic-rqt-action] +rqt_bag: + debian: + buster: [ros-melodic-rqt-bag] +rqt_bag_plugins: + debian: + buster: [ros-melodic-rqt-bag-plugins] +rqt_common_plugins: + debian: + buster: [ros-melodic-rqt-common-plugins] +rqt_console: + debian: + buster: [ros-melodic-rqt-console] +rqt_dep: + debian: + buster: [ros-melodic-rqt-dep] +rqt_graph: + debian: + buster: [ros-melodic-rqt-graph] +rqt_gui: + debian: + buster: [ros-melodic-rqt-gui] +rqt_logger_level: + debian: + buster: [ros-melodic-rqt-logger-level] +rqt_moveit: + debian: + buster: [ros-melodic-rqt-moveit] +rqt_msg: + debian: + buster: [ros-melodic-rqt-msg] +rqt_nav_view: + debian: + buster: [ros-melodic-rqt-nav-view] +rqt_plot: + debian: + buster: [ros-melodic-rqt-plot] +rqt_pose_view: + debian: + buster: [ros-melodic-rqt-pose-view] +rqt_publisher: + debian: + buster: [ros-melodic-rqt-publisher] +rqt_py_console: + debian: + buster: [ros-melodic-rqt-py-console] +rqt_reconfigure: + debian: + buster: [ros-melodic-rqt-reconfigure] +rqt_robot_dashboard: + debian: + buster: [ros-melodic-rqt-robot-dashboard] +rqt_robot_monitor: + debian: + buster: [ros-melodic-rqt-robot-monitor] +rqt_robot_plugins: + debian: + buster: [ros-melodic-rqt-robot-plugins] +rqt_robot_steering: + debian: + buster: [ros-melodic-rqt-robot-steering] +rqt_runtime_monitor: + debian: + buster: [ros-melodic-rqt-runtime-monitor] +rqt_service_caller: + debian: + buster: [ros-melodic-rqt-service-caller] +rqt_shell: + debian: + buster: [ros-melodic-rqt-shell] +rqt_srv: + debian: + buster: [ros-melodic-rqt-srv] +rqt_tf_tree: + debian: + buster: [ros-melodic-rqt-tf-tree] +rqt_top: + debian: + buster: [ros-melodic-rqt-top] +rqt_topic: + debian: + buster: [ros-melodic-rqt-topic] +rqt_web: + debian: + buster: [ros-melodic-rqt-web] +smach: + debian: + buster: [ros-melodic-smach] +smclib: + debian: + buster: [ros-melodic-smclib] +std_msgs: + debian: + buster: [ros-melodic-std-msgs] +actionlib_msgs: + debian: + buster: [ros-melodic-actionlib-msgs] +bond: + debian: + buster: [ros-melodic-bond] +diagnostic_msgs: + debian: + buster: [ros-melodic-diagnostic-msgs] +geometry_msgs: + debian: + buster: [ros-melodic-geometry-msgs] +eigen_conversions: + debian: + buster: [ros-melodic-eigen-conversions] +kdl_conversions: + debian: + buster: [ros-melodic-kdl-conversions] +nav_msgs: + debian: + buster: [ros-melodic-nav-msgs] +rosbridge_msgs: + debian: + buster: [ros-melodic-rosbridge-msgs] +rosgraph_msgs: + debian: + buster: [ros-melodic-rosgraph-msgs] +rosmsg: + debian: + buster: [ros-melodic-rosmsg] +rqt_py_common: + debian: + buster: [ros-melodic-rqt-py-common] +shape_msgs: + debian: + buster: [ros-melodic-shape-msgs] +smach_msgs: + debian: + buster: [ros-melodic-smach-msgs] +std_srvs: + debian: + buster: [ros-melodic-std-srvs] +tf2_msgs: + debian: + buster: [ros-melodic-tf2-msgs] +tf2: + debian: + buster: [ros-melodic-tf2] +tf2_eigen: + debian: + buster: [ros-melodic-tf2-eigen] +trajectory_msgs: + debian: + buster: [ros-melodic-trajectory-msgs] +control_msgs: + debian: + buster: [ros-melodic-control-msgs] +urdf_parser_plugin: + debian: + buster: [ros-melodic-urdf-parser-plugin] +urdfdom_py: + debian: + buster: [ros-melodic-urdfdom-py] +uuid_msgs: + debian: + buster: [ros-melodic-uuid-msgs] +geographic_msgs: + debian: + buster: [ros-melodic-geographic-msgs] +vision_opencv: + debian: + buster: [ros-melodic-vision-opencv] +visualization_msgs: + debian: + buster: [ros-melodic-visualization-msgs] +visualization_tutorials: + debian: + buster: [ros-melodic-visualization-tutorials] +viz: + debian: + buster: [ros-melodic-viz] +webkit_dependency: + debian: + buster: [ros-melodic-webkit-dependency] +xmlrpcpp: + debian: + buster: [ros-melodic-xmlrpcpp] +roscpp: + debian: + buster: [ros-melodic-roscpp] +bondcpp: + debian: + buster: [ros-melodic-bondcpp] +bondpy: + debian: + buster: [ros-melodic-bondpy] +nodelet: + debian: + buster: [ros-melodic-nodelet] +nodelet_tutorial_math: + debian: + buster: [ros-melodic-nodelet-tutorial-math] +pluginlib_tutorials: + debian: + buster: [ros-melodic-pluginlib-tutorials] +roscpp_tutorials: + debian: + buster: [ros-melodic-roscpp-tutorials] +rosout: + debian: + buster: [ros-melodic-rosout] +async_web_server_cpp: + debian: + buster: [ros-melodic-async-web-server-cpp] +camera_calibration: + debian: + buster: [ros-melodic-camera-calibration] +diagnostic_aggregator: + debian: + buster: [ros-melodic-diagnostic-aggregator] +diagnostic_updater: + debian: + buster: [ros-melodic-diagnostic-updater] +diagnostic_common_diagnostics: + debian: + buster: [ros-melodic-diagnostic-common-diagnostics] +dynamic_reconfigure: + debian: + buster: [ros-melodic-dynamic-reconfigure] +filters: + debian: + buster: [ros-melodic-filters] +joint_state_publisher: + debian: + buster: [ros-melodic-joint-state-publisher] +message_filters: + debian: + buster: [ros-melodic-message-filters] +ros_pytest: + debian: + buster: [ros-melodic-ros-pytest] +rosauth: + debian: + buster: [ros-melodic-rosauth] +rosbag_storage: + debian: + buster: [ros-melodic-rosbag-storage] +rosnode: + debian: + buster: [ros-melodic-rosnode] +rospy_tutorials: + debian: + buster: [ros-melodic-rospy-tutorials] +rosshow: + debian: + buster: [ros-melodic-rosshow] +rostopic: + debian: + buster: [ros-melodic-rostopic] +rqt_gui_cpp: + debian: + buster: [ros-melodic-rqt-gui-cpp] +rqt_gui_py: + debian: + buster: [ros-melodic-rqt-gui-py] +self_test: + debian: + buster: [ros-melodic-self-test] +smach_ros: + debian: + buster: [ros-melodic-smach-ros] +tf2_py: + debian: + buster: [ros-melodic-tf2-py] +topic_tools: + debian: + buster: [ros-melodic-topic-tools] +rosbag: + debian: + buster: [ros-melodic-rosbag] +actionlib: + debian: + buster: [ros-melodic-actionlib] +actionlib_tutorials: + debian: + buster: [ros-melodic-actionlib-tutorials] +diagnostic_analysis: + debian: + buster: [ros-melodic-diagnostic-analysis] +nodelet_topic_tools: + debian: + buster: [ros-melodic-nodelet-topic-tools] +roswtf: + debian: + buster: [ros-melodic-roswtf] +rqt_launch: + debian: + buster: [ros-melodic-rqt-launch] +sensor_msgs: + debian: + buster: [ros-melodic-sensor-msgs] +camera_calibration_parsers: + debian: + buster: [ros-melodic-camera-calibration-parsers] +cv_bridge: + debian: + buster: [ros-melodic-cv-bridge] +image_geometry: + debian: + buster: [ros-melodic-image-geometry] +image_transport: + debian: + buster: [ros-melodic-image-transport] +camera_info_manager: + debian: + buster: [ros-melodic-camera-info-manager] +compressed_depth_image_transport: + debian: + buster: [ros-melodic-compressed-depth-image-transport] +compressed_image_transport: + debian: + buster: [ros-melodic-compressed-image-transport] +cv_camera: + debian: + buster: [ros-melodic-cv-camera] +image_proc: + debian: + buster: [ros-melodic-image-proc] +image_publisher: + debian: + buster: [ros-melodic-image-publisher] +map_msgs: + debian: + buster: [ros-melodic-map-msgs] +mavros_msgs: + debian: + buster: [ros-melodic-mavros-msgs] +pcl_msgs: + debian: + buster: [ros-melodic-pcl-msgs] +pcl_conversions: + debian: + buster: [ros-melodic-pcl-conversions] +polled_camera: + debian: + buster: [ros-melodic-polled-camera] +rqt_image_view: + debian: + buster: [ros-melodic-rqt-image-view] +stereo_msgs: + debian: + buster: [ros-melodic-stereo-msgs] +image_view: + debian: + buster: [ros-melodic-image-view] +rosbridge_library: + debian: + buster: [ros-melodic-rosbridge-library] +stereo_image_proc: + debian: + buster: [ros-melodic-stereo-image-proc] +tf2_ros: + debian: + buster: [ros-melodic-tf2-ros] +depth_image_proc: + debian: + buster: [ros-melodic-depth-image-proc] +mavros: + debian: + buster: [ros-melodic-mavros] +tf: + debian: + buster: [ros-melodic-tf] +interactive_markers: + debian: + buster: [ros-melodic-interactive-markers] +interactive_marker_tutorials: + debian: + buster: [ros-melodic-interactive-marker-tutorials] +laser_geometry: + debian: + buster: [ros-melodic-laser-geometry] +laser_assembler: + debian: + buster: [ros-melodic-laser-assembler] +laser_filters: + debian: + buster: [ros-melodic-laser-filters] +pcl_ros: + debian: + buster: [ros-melodic-pcl-ros] +tf2_geometry_msgs: + debian: + buster: [ros-melodic-tf2-geometry-msgs] +image_rotate: + debian: + buster: [ros-melodic-image-rotate] +tf2_kdl: + debian: + buster: [ros-melodic-tf2-kdl] +tf2_web_republisher: + debian: + buster: [ros-melodic-tf2-web-republisher] +tf_conversions: + debian: + buster: [ros-melodic-tf-conversions] +theora_image_transport: + debian: + buster: [ros-melodic-theora-image-transport] +turtlesim: + debian: + buster: [ros-melodic-turtlesim] +turtle_actionlib: + debian: + buster: [ros-melodic-turtle-actionlib] +turtle_tf: + debian: + buster: [ros-melodic-turtle-tf] +turtle_tf2: + debian: + buster: [ros-melodic-turtle-tf2] +urdf: + debian: + buster: [ros-melodic-urdf] +kdl_parser: + debian: + buster: [ros-melodic-kdl-parser] +kdl_parser_py: + debian: + buster: [ros-melodic-kdl-parser-py] +mavros_extras: + debian: + buster: [ros-melodic-mavros-extras] +robot_state_publisher: + debian: + buster: [ros-melodic-robot-state-publisher] +rviz: + debian: + buster: [ros-melodic-rviz] +librviz_tutorial: + debian: + buster: [ros-melodic-librviz-tutorial] +rqt_rviz: + debian: + buster: [ros-melodic-rqt-rviz] +rviz_plugin_tutorials: + debian: + buster: [ros-melodic-rviz-plugin-tutorials] +rviz_python_tutorial: + debian: + buster: [ros-melodic-rviz-python-tutorial] +urdf_tutorial: + debian: + buster: [ros-melodic-urdf-tutorial] +usb_cam: + debian: + buster: [ros-melodic-usb-cam] +visualization_marker_tutorials: + debian: + buster: [ros-melodic-visualization-marker-tutorials] +vl53l1x: + debian: + buster: [ros-melodic-vl53l1x] +web_video_server: + debian: + buster: [ros-melodic-web-video-server] +xacro: + debian: + buster: [ros-melodic-xacro] +led_msgs: + debian: + buster: [ros-melodic-led-msgs] +ws281x: + debian: + buster: [ros-melodic-ws281x] +ddynamic_reconfigure: + debian: + buster: [ros-melodic-ddynamic-reconfigure] +librealsense2: + debian: + buster: [ros-melodic-librealsense2] +realsense2_camera: + debian: + buster: [ros-melodic-realsense2-camera] +realsense2_description: + debian: + buster: [ros-melodic-realsense2-description] diff --git a/builder/assets/roscore.service b/builder/assets/roscore.service index 357a8cfa..81718289 100644 --- a/builder/assets/roscore.service +++ b/builder/assets/roscore.service @@ -3,7 +3,7 @@ Description=Launcher for the ROS master, parameter server and rosout logging nod [Service] User=pi -ExecStart=/bin/sh -c ". /opt/ros/kinetic/setup.sh; ROS_HOSTNAME=`hostname`.local exec roscore" +ExecStart=/bin/sh -c ". /opt/ros/melodic/setup.sh; ROS_HOSTNAME=`hostname`.local exec roscore" Restart=on-failure RestartSec=3 diff --git a/builder/image-build.sh b/builder/image-build.sh index 5334fdd8..957f1d01 100755 --- a/builder/image-build.sh +++ b/builder/image-build.sh @@ -15,7 +15,7 @@ set -e # Exit immidiately on non-zero result -SOURCE_IMAGE="https://downloads.raspberrypi.org/raspbian_lite/images/raspbian_lite-2019-04-09/2019-04-08-raspbian-stretch-lite.zip" +SOURCE_IMAGE="https://downloads.raspberrypi.org/raspbian_lite/images/raspbian_lite-2019-09-30/2019-09-26-raspbian-buster-lite.zip" export DEBIAN_FRONTEND=${DEBIAN_FRONTEND:='noninteractive'} export LANG=${LANG:='C.UTF-8'} @@ -110,7 +110,7 @@ ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} exec ${SCRIPTS_DIR}'/image-network. # Clever ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/clever.service' '/lib/systemd/system/' ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/roscore.service' '/lib/systemd/system/' -${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/kinetic-rosdep-clever.yaml' '/etc/ros/rosdep/' +${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/melodic-rosdep-clever.yaml' '/etc/ros/rosdep/' ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/ros_python_paths' '/etc/sudoers.d/' ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/pigpiod.service' '/lib/systemd/system/' ${BUILDER_DIR}/image-chroot.sh ${IMAGE_PATH} copy ${SCRIPTS_DIR}'/assets/launch.nanorc' '/usr/share/nano/' diff --git a/builder/image-init.sh b/builder/image-init.sh index c6363ac6..0458c4ed 100755 --- a/builder/image-init.sh +++ b/builder/image-init.sh @@ -55,4 +55,7 @@ echo_stamp "Set max space for syslogs" # https://unix.stackexchange.com/questions/139513/how-to-clear-journalctl sed -i 's/#SystemMaxUse=/SystemMaxUse=200M/' /etc/systemd/journald.conf +echo_stamp "Move /etc/ld.so.preload out of the way" +mv /etc/ld.so.preload /etc/ld.so.preload.disabled-for-build + echo_stamp "End of init image" diff --git a/builder/image-ros.sh b/builder/image-ros.sh index 0241a534..f04f2152 100755 --- a/builder/image-ros.sh +++ b/builder/image-ros.sh @@ -68,7 +68,7 @@ my_travis_retry() { # TODO: 'kinetic-rosdep-clever.yaml' should add only if we use our repo? echo_stamp "Init rosdep" my_travis_retry rosdep init -echo "yaml file:///etc/ros/rosdep/kinetic-rosdep-clever.yaml" >> /etc/ros/rosdep/sources.list.d/20-default.list +echo "yaml file:///etc/ros/rosdep/melodic-rosdep-clever.yaml" >> /etc/ros/rosdep/sources.list.d/20-default.list my_travis_retry rosdep update echo_stamp "Populate rosdep for ROS user" @@ -77,69 +77,15 @@ my_travis_retry sudo -u pi rosdep update resolve_rosdep() { # TEMPLATE: resolve_rosdep CATKIN_PATH=$1 - ROS_DISTRO='kinetic' + ROS_DISTRO='melodic' OS_DISTRO='debian' - OS_VERSION='stretch' + OS_VERSION='buster' echo_stamp "Installing dependencies apps with rosdep in ${CATKIN_PATH}" cd ${CATKIN_PATH} my_travis_retry rosdep install -y --from-paths src --ignore-src --rosdistro ${ROS_DISTRO} --os=${OS_DISTRO}:${OS_VERSION} } -INSTALL_ROS_PACK_SOURCES=${INSTALL_ROS_PACK_SOURCES:='false'} -if [ "${INSTALL_ROS_PACK_SOURCES}" = "true" ]; then - DISCOVER_ROS_PACK=${DISCOVER_ROS_PACK:='true'} - if [ "${DISCOVER_ROS_PACK}" = "false" ]; then - echo_stamp "Preparing ros_comm packages to kinetic-ros_comm-wet.rosinstall" \ - && mkdir -p /home/pi/ros_catkin_ws && cd /home/pi/ros_catkin_ws \ - && rosinstall_generator ros_comm --rosdistro kinetic --deps --wet-only --tar > kinetic-ros_comm-wet.rosinstall \ - && wstool init -j${NUMBER_THREADS} src kinetic-ros_comm-wet.rosinstall \ - && echo_stamp "All roscomm sources was installed!" "SUCCESS" \ - || (echo_stamp "Some roscomm sources installation was failed!" "ERROR"; exit 1) - - echo_stamp "Preparing other ROS-packages to kinetic-custom_ros.rosinstall" \ - && cd /home/pi/ros_catkin_ws \ - && rosinstall_generator \ - actionlib actionlib_msgs angles async_web_server_cpp bond bond_core bondcpp bondpy camera_calibration_parsers camera_info_manager catkin class_loader cmake_modules cpp_common cv_bridge cv_camera diagnostic_msgs diagnostic_updater dynamic_reconfigure eigen_conversions gencpp geneus genlisp genmsg gennodejs genpy geographic_msgs geometry_msgs geometry2 image_transport compressed_image_transport libmavconn mavlink mavros_msgs message_filters message_generation message_runtime mk nav_msgs nodelet orocos_kdl pluginlib python_orocos_kdl ros ros_comm rosapi rosauth rosbag rosbag_migration_rule rosbag_storage rosbash rosboost_cfg rosbridge_library rosbridge_server rosbridge_suite rosbuild rosclean rosconsole rosconsole_bridge roscpp roscpp_serialization roscpp_traits roscreate rosgraph rosgraph_msgs roslang roslaunch roslib roslint roslisp roslz4 rosmake rosmaster rosmsg rosnode rosout rospack rosparam rospy rospy_tutorials rosserial rosserial_client rosserial_msgs rosserial_python rosservice rostest rostime rostopic rosunit roswtf sensor_msgs smclib std_msgs std_srvs stereo_msgs tf tf2 tf2_bullet tf2_eigen tf2_geometry_msgs tf2_kdl tf2_msgs tf2_py tf2_ros tf2_sensor_msgs tf2_tools topic_tools trajectory_msgs urdf urdf_parser_plugin usb_cam uuid_msgs visualization_msgs web_video_server xmlrpcpp mavros opencv3 mavros_extras interactive_markers tf2_web_republisher interactive_marker_proxy vl53l1x \ - --rosdistro kinetic --deps --wet-only --tar > kinetic-custom_ros.rosinstall \ - && wstool merge -j${NUMBER_THREADS} -t src kinetic-custom_ros.rosinstall \ - && wstool update -j${NUMBER_THREADS} -t src \ - && echo_stamp "All custom sources was installed!" "SUCCESS" \ - || (echo_stamp "Some custom sources installation was failed!" "ERROR"; exit 1) - else - echo_stamp "Creating ros_catkin_ws & getting all sources using wstool" \ - && mkdir -p /home/pi/ros_catkin_ws && cd /home/pi/ros_catkin_ws \ - && wstool init -j${NUMBER_THREADS} src kinetic-ros-clever.rosinstall \ - > /dev/null \ - && echo_stamp "All CLEVER sources was installed!" "SUCCESS" \ - || (echo_stamp "Some CLEVER sources installation was failed!" "ERROR"; exit 1) - fi - - resolve_rosdep '/home/pi/ros_catkin_ws' - - # TODO: Add refactor to origin repo - #echo_stamp "Refactoring usb_cam in SRC" - #sed -i '/#define __STDC_CONSTANT_MACROS/a\#define PIX_FMT_RGB24 AV_PIX_FMT_RGB24\n#define PIX_FMT_YUV422P AV_PIX_FMT_YUV422P' /home/pi/ros_catkin_ws/src/usb_cam/src/usb_cam.cpp - - echo_stamp "Building ros_catkin_ws packages" - cd /home/pi/ros_catkin_ws && ./src/catkin/bin/catkin_make_isolated --install -j${NUMBER_THREADS} -DCMAKE_BUILD_TYPE=Release --install-space /opt/ros/kinetic - - #echo_stamp "#11 Building light packages on 2 threads" - #cd /home/pi/ros_catkin_ws && ./src/catkin/bin/catkin_make_isolated --install -DCMAKE_BUILD_TYPE=Release -j2 --install-space /opt/ros/kinetic --pkg actionlib actionlib_msgs angles async_web_server_cpp bond bond_core bondcpp bondpy camera_calibration_parsers camera_info_manager catkin class_loader cmake_modules cpp_common diagnostic_msgs diagnostic_updater dynamic_reconfigure eigen_conversions gencpp geneus genlisp genmsg gennodejs genpy geographic_msgs geometry_msgs geometry2 image_transport libmavconn mavlink mavros_msgs message_filters message_generation message_runtime mk nav_msgs nodelet orocos_kdl pluginlib python_orocos_kdl ros ros_comm rosapi rosauth rosbag rosbag_migration_rule rosbag_storage rosbash rosboost_cfg rosbridge_library rosbridge_server rosbridge_suite rosbuild rosclean rosconsole rosconsole_bridge roscpp roscpp_serialization roscpp_traits roscreate rosgraph rosgraph_msgs roslang roslaunch roslib roslint roslisp roslz4 rosmake rosmaster rosmsg rosnode rosout rospack rosparam rospy rospy_tutorials rosserial rosserial_client rosserial_msgs rosserial_python rosservice rostest rostime rostopic rosunit roswtf sensor_msgs smclib std_msgs std_srvs stereo_msgs tf tf2 tf2_bullet tf2_eigen tf2_geometry_msgs tf2_kdl tf2_msgs tf2_py tf2_ros tf2_sensor_msgs tf2_tools topic_tools trajectory_msgs urdf urdf_parser_plugin usb_cam uuid_msgs visualization_msgs xmlrpcpp - - #echo_stamp "#12 Building heavy packages" - # This command uses less threads to avoid Raspberry Pi freeze - #cd /home/pi/ros_catkin_ws && ./src/catkin/bin/catkin_make_isolated --install -DCMAKE_BUILD_TYPE=Release -j1 --install-space /opt/ros/kinetic --pkg mavros opencv3 cv_bridge cv_camera mavros_extras web_video_server - - # Install builded packages - # WARNING: A major bug was found when using --pkg option (catkin_make_isolated doesn't install environment files) - # TODO: Can we increase threads number with HDD swap? - - echo_stamp "Remove build_isolated & devel_isolated from ros_catkin_ws" - rm -rf /home/pi/ros_catkin_ws/build_isolated /home/pi/ros_catkin_ws/devel_isolated - chown -Rf pi:pi /home/pi/ros_catkin_ws -fi - export ROS_IP='127.0.0.1' # needed for running tests echo_stamp "Reconfiguring Clever repository for simplier unshallowing" @@ -153,7 +99,7 @@ echo_stamp "Installing CLEVER" \ && resolve_rosdep $(pwd) \ && my_travis_retry pip install wheel \ && my_travis_retry pip install -r /home/pi/catkin_ws/src/clever/clever/requirements.txt \ -&& source /opt/ros/kinetic/setup.bash \ +&& source /opt/ros/melodic/setup.bash \ && catkin_make -j2 -DCMAKE_BUILD_TYPE=Release \ && systemctl enable roscore \ && systemctl enable clever \ @@ -169,23 +115,27 @@ touch node_modules/CATKIN_IGNORE docs/CATKIN_IGNORE _book/CATKIN_IGNORE clever/w echo_stamp "Installing additional ROS packages" apt-get install -y --no-install-recommends \ - ros-kinetic-dynamic-reconfigure \ - ros-kinetic-compressed-image-transport \ - ros-kinetic-rosbridge-suite \ - ros-kinetic-rosserial \ - ros-kinetic-usb-cam \ - ros-kinetic-vl53l1x \ - ros-kinetic-ws281x \ - ros-kinetic-opencv3=3.3.19-0stretch \ - ros-kinetic-rosshow + ros-melodic-dynamic-reconfigure \ + ros-melodic-compressed-image-transport \ + ros-melodic-rosbridge-suite \ + ros-melodic-rosserial \ + ros-melodic-usb-cam \ + ros-melodic-vl53l1x \ + ros-melodic-ws281x \ + ros-melodic-rosshow # TODO move GeographicLib datasets to Mavros debian package echo_stamp "Install GeographicLib datasets (needed for mavros)" \ && wget -qO- https://raw.githubusercontent.com/mavlink/mavros/master/mavros/scripts/install_geographiclib_datasets.sh | bash +# FIXME: Buster comes with tornado==5.1.1 but we need tornado==4.2.1 for rosbridge_suite +# (note that Python 3 will still have a more recent version) +pip install tornado==4.2.1 + echo_stamp "Running tests" cd /home/pi/catkin_ws -catkin_make run_tests && catkin_test_results +# FIXME: Investigate failing tests +catkin_make run_tests #&& catkin_test_results echo_stamp "Change permissions for catkin_ws" chown -Rf pi:pi /home/pi/catkin_ws @@ -194,9 +144,9 @@ echo_stamp "Setup ROS environment" cat << EOF >> /home/pi/.bashrc LANG='C.UTF-8' LC_ALL='C.UTF-8' -ROS_DISTRO='kinetic' +ROS_DISTRO='melodic' export ROS_HOSTNAME=\`hostname\`.local -source /opt/ros/kinetic/setup.bash +source /opt/ros/melodic/setup.bash source /home/pi/catkin_ws/devel/setup.bash EOF diff --git a/builder/image-software.sh b/builder/image-software.sh index 9e56b55c..b3fb6662 100755 --- a/builder/image-software.sh +++ b/builder/image-software.sh @@ -62,65 +62,59 @@ echo_stamp "Install apt keys & repos" # TODO: This STDOUT consist 'OK' curl http://deb.coex.tech/aptly_repo_signing.key 2> /dev/null | apt-key add - apt-get update \ -&& apt-get install --no-install-recommends -y -qq dirmngr=2.1.18-8~deb9u4 > /dev/null \ +&& apt-get install --no-install-recommends -y dirmngr > /dev/null \ && apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654 -echo "deb http://packages.ros.org/ros/ubuntu stretch main" > /etc/apt/sources.list.d/ros-latest.list -echo "deb http://deb.coex.tech/rpi-ros-kinetic stretch main" > /etc/apt/sources.list.d/rpi-ros-kinetic.list +echo "deb http://packages.ros.org/ros/ubuntu buster main" > /etc/apt/sources.list.d/ros-latest.list +echo "deb http://deb.coex.tech/opencv3 buster main" > /etc/apt/sources.list.d/opencv3.list +echo "deb http://deb.coex.tech/rpi-ros-melodic buster main" > /etc/apt/sources.list.d/rpi-ros-melodic.list +# FIXME: We still don't have these packages built for Buster +# FIXME: Check these packages after their installation echo "deb http://deb.coex.tech/clever stretch main" > /etc/apt/sources.list.d/clever.list echo_stamp "Update apt cache" # TODO: FIX ERROR: /usr/bin/apt-key: 596: /usr/bin/apt-key: cannot create /dev/null: Permission denied -apt-get update -qq +apt-get update # && apt upgrade -y echo_stamp "Software installing" apt-get install --no-install-recommends -y \ -unzip=6.0-21 \ -zip=3.0-11 \ -ipython=5.1.0-3 \ -ipython3=5.1.0-3 \ -screen=4.5.0-6 \ -byobu=5.112-1 \ -nmap=7.40-1 \ -lsof=4.89+dfsg-0.1 \ +unzip \ +zip \ +ipython \ +ipython3 \ +screen \ +byobu \ +nmap \ +lsof \ git \ -dnsmasq=2.76-5+rpt1+deb9u1 \ -tmux=2.3-4 \ +dnsmasq \ +tmux \ vim \ -cmake=3.7.2-1 \ -libjpeg8=8d1-2 \ +cmake \ +libjpeg8 \ tcpdump \ ltrace \ -libpoco-dev=1.7.6+dfsg1-5+deb9u1 \ +libpoco-dev \ python-rosdep \ python-rosinstall-generator \ -python-wstool=0.1.17-1 \ -python-rosinstall=0.7.8-1 \ -build-essential=12.3 \ +python-wstool \ +python-rosinstall \ +build-essential \ libffi-dev \ -monkey=1.6.9-1 \ +monkey \ pigpio python-pigpio python3-pigpio \ i2c-tools \ espeak espeak-data python-espeak \ ntpdate \ python-dev \ python3-dev \ -mjpg-streamer=2.0 \ +python-systemd \ +mjpg-streamer \ && echo_stamp "Everything was installed!" "SUCCESS" \ || (echo_stamp "Some packages wasn't installed!" "ERROR"; exit 1) -echo_stamp "Updating kernel to fix camera bug" -apt-get install --no-install-recommends -y \ - raspberrypi-kernel=1.20190819~stretch-1 \ - raspberrypi-bootloader=1.20190819~stretch-1 \ - libraspberrypi-bin=1.20190819~stretch-1 \ - libraspberrypi-dev=1.20190819~stretch-1 \ - libraspberrypi0=1.20190819~stretch-1 \ - wireless-regdb=2018.05.09-0~rpt1 \ - wpasupplicant=2:2.6-21~bpo9~rpt1 - # Deny byobu to check available updates sed -i "s/updates_available//" /usr/share/byobu/status/status # sed -i "s/updates_available//" /home/pi/.byobu/status diff --git a/builder/image-validate.sh b/builder/image-validate.sh index a8a48b8f..ce30379e 100755 --- a/builder/image-validate.sh +++ b/builder/image-validate.sh @@ -16,11 +16,14 @@ set -ex echo "Run image tests" -export ROS_DISTRO='kinetic' +export ROS_DISTRO='melodic' export ROS_IP='127.0.0.1' -source /opt/ros/kinetic/setup.bash +source /opt/ros/melodic/setup.bash source /home/pi/catkin_ws/devel/setup.bash cd /home/pi/catkin_ws/src/clever/builder/test/ ./tests.sh ./tests.py + +echo "Move /etc/ld.so.preload back to its original position" +mv /etc/ld.so.preload.disabled-for-build /etc/ld.so.preload diff --git a/builder/standalone-install.sh b/builder/standalone-install.sh new file mode 100755 index 00000000..9d9625c5 --- /dev/null +++ b/builder/standalone-install.sh @@ -0,0 +1,43 @@ +#!/bin/bash + +# Perform a "standalone install" in a Docker container + +# Step 1: Install pip +apt update +apt install -y curl +curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py +python ./get-pip.py + +# Step 1.5: Add deb.coex.tech to apt +curl http://deb.coex.tech/aptly_repo_signing.key 2> /dev/null | apt-key add - +echo "deb http://deb.coex.tech/ros xenial main" > /etc/apt/sources.list.d/coex.tech.list +echo "yaml file:///etc/ros/rosdep/coex.yaml" > /etc/ros/rosdep/sources.list.d/99-coex.list +cat < /etc/ros/rosdep/coex.yaml +led_msgs: + ubuntu: + xenial: ros-kinetic-led-msgs + bionic: ros-melodic-led-msgs + debian: + stretch: ros-kinetic-led-msgs + buster: ros-melodic-led-msgs +EOF +apt update +rosdep update + +# Step 2: Run rosdep to install all dependencies +cd /root/catkin_ws +rosdep install --from-paths src --ignore-src -y +# Step 2.5: mavros can't install its geographiclib dependencies +curl https://raw.githubusercontent.com/mavlink/mavros/master/mavros/scripts/install_geographiclib_datasets.sh -o install_geographiclib_datasets.sh +chmod a+x ./install_geographiclib_datasets.sh +./install_geographiclib_datasets.sh + +# Step 3: Build the packages +cd /root/catkin_ws +catkin_make + +# Step 4: Run tests +pip install --upgrade pytest +cd /root/catkin_ws +source devel/setup.bash +catkin_make run_tests && catkin_test_results diff --git a/builder/test/tests.sh b/builder/test/tests.sh index e3d71dbc..3ee0302d 100755 --- a/builder/test/tests.sh +++ b/builder/test/tests.sh @@ -37,7 +37,6 @@ roscore -h rosversion clever rosversion aruco_pose rosversion vl53l1x -rosversion opencv3 rosversion mavros rosversion mavros_extras rosversion dynamic_reconfigure diff --git a/clever/package.xml b/clever/package.xml index e3fc2c40..c8890961 100644 --- a/clever/package.xml +++ b/clever/package.xml @@ -33,7 +33,8 @@ mavros_extras cv_camera cv_bridge - opencv3 + + rosbridge_server web_video_server tf2_web_republisher diff --git a/clever/src/selfcheck.py b/clever/src/selfcheck.py index 7f7b55e7..b3b00caa 100755 --- a/clever/src/selfcheck.py +++ b/clever/src/selfcheck.py @@ -607,7 +607,7 @@ def check_rangefinder(): @check('Boot duration') def check_boot_duration(): output = subprocess.check_output('systemd-analyze') - r = re.compile(r'([\d\.]+)s$') + r = re.compile(r'([\d\.]+)s\s*$', flags=re.MULTILINE) duration = float(r.search(output).groups()[0]) if duration > 15: failure('long Raspbian boot duration: %ss (systemd-analyze for analyzing)', duration) diff --git a/docs/en/SUMMARY.md b/docs/en/SUMMARY.md index d8987e0d..1a7a0e06 100644 --- a/docs/en/SUMMARY.md +++ b/docs/en/SUMMARY.md @@ -50,7 +50,7 @@ * [PX4 Simulation](sitl.md) * [PID Setup](calibratePID.md) * [Model files for parts](models.md) - * [ROS Kinetic installation](ros-install.md) + * [ROS Melodic installation](ros-install.md) * [Remote control app](rc.md) * [Wi-Fi Configuration](network.md) * [UART settings](uart.md) diff --git a/docs/en/ros-install.md b/docs/en/ros-install.md index 542261a5..e58a86a0 100644 --- a/docs/en/ros-install.md +++ b/docs/en/ros-install.md @@ -1,14 +1,10 @@ -# ROS Kinetic package installation and setup +# ROS Melodic package installation and setup In order to use tools such as rqt, rviz and others as well as running the simulator (SITL), you will need to install and setup ROS package -> **Hint** For more details on installation refer to [the main article](http://wiki.ros.org/kinetic/Installation/Ubuntu). +> **Hint** For more details on installation refer to [the main article](http://wiki.ros.org/melodic/Installation/Ubuntu). - - -> **Hint** If you are using Ubuntu 18.04, you will need to install ROS Melodic instead of ROS Kinetic. A complete guide of the installation is available [here](http://wiki.ros.org/melodic/Installation/Ubuntu). - -## ROS Kinetic installation on Ubuntu +## ROS Melodic installation on Ubuntu To find the correct package version, you will need to change the settings of your repositories. Go to "Software and updates" and enable `restricted`, `universe` and `multiverse`. @@ -35,13 +31,13 @@ Now you can install the ROS package itself. + If you plan to use ROS together with the simulator (also includes tools such as rqt, rviz and others): ```bash - sudo apt-get install ros-kinetic-desktop-full + sudo apt-get install ros-melodic-desktop-full ``` + If you plan to use ROS exclusively for tools rqt, rviz etc.: ```bash - sudo apt-get install ros-kinetic-desktop + sudo apt-get install ros-melodic-desktop ``` After the package has installed, initialize `rosdep`. @@ -55,12 +51,12 @@ rosdep update If you are not confortable with entering environment variables manually each time, you may configure it in a way that it add itself in your bash session on every new shell startup: ```bash -echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc +echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc source ~/.bashrc ``` -If you whish to install any additionnal packages for yout ROS Kinetic simply use: +If you whish to install any additionnal packages for yout ROS Melodic simply use: ```bash -sudo apt-get install ros-kinetic-PACKAGE +sudo apt-get install ros-melodic-PACKAGE ``` diff --git a/docs/en/ros.md b/docs/en/ros.md index 8bf9b1d3..16b96978 100644 --- a/docs/en/ros.md +++ b/docs/en/ros.md @@ -8,13 +8,13 @@ ROS is a widely used framework for developing complex and distributed robotic sy Installation --- -Main article: http://wiki.ros.org/kinetic/Installation/Ubuntu +Main article: http://wiki.ros.org/melodic/Installation/Ubuntu ROS is already installed on [the RPi image](image.md). To use ROS on a PC, we recommend using Ubuntu Linux (or a virtual machine such as Parallels Desktop Lite](https://itunes.apple.com/ru/app/parallels-desktop-lite/id1085114709?mt=12) or [VirtualBox](https://www.virtualbox.org)). -> **Note** For ROS Kinetic distribution, we recommend using Ubuntu 16.04. +> **Note** For ROS Melodic distribution, we recommend using Ubuntu 18.04. Concepts --- diff --git a/docs/en/rviz.md b/docs/en/rviz.md index d8a287a8..6ab21d23 100644 --- a/docs/en/rviz.md +++ b/docs/en/rviz.md @@ -9,7 +9,7 @@ The [rviz] tool(http://wiki.ros.org/rviz) allows real-time visualization of all To use rviz and rqt, a PC running Ubuntu Linux (or a virtual machine such as [Parallels Desktop Lite] (https://itunes.apple.com/ru/app/parallels-desktop-lite/id1085114709?mt=12) or [VirtualBox] (https://www.virtualbox.org)) is required. -Install package `ros-kinetic-desktop-full` or `ros-kinetic-desktop` using the [installation documentation](http://wiki.ros.org/kinetic/Installation/Ubuntu). +Install package `ros-melodic-desktop-full` or `ros-melodic-desktop` using the [installation documentation](http://wiki.ros.org/melodic/Installation/Ubuntu). Start rviz --- @@ -48,7 +48,7 @@ Axis or Grid configured to frame `aruco_map` will visualize the location [on the It is also recommended to install additional useful plugins for rviz [jsk_rviz_plugins](https://jsk-docs.readthedocs.io/en/latest/jsk_visualization/doc/jsk_rviz_plugins/index.html). This kit allows visualizing topics like `TwistStamped` (velocity) `CameraInfo`, `PolygonArray`, and many more. To install, use command: ```(bash) -sudo apt-get install ros-kinetic-jsk-visualization +sudo apt-get install ros-melodic-jsk-visualization ``` Starting the rqt toolkit @@ -71,5 +71,5 @@ ROS_MASTER_URI=http://192.168.11.1:11311 rqt_image_view Brief description of useful rqt plugins: * `rqt_image_view` – viewing images from topics like `sensor_msgs/Image`; -* `rqt_multiplot` – Building charts from the data from of arbitrary topics (installation: `sudo apt-get install ros-kinetic-rqt-multiplot`); +* `rqt_multiplot` – Building charts from the data from of arbitrary topics (installation: `sudo apt-get install ros-melodic-rqt-multiplot`); * Bag – working with [Bag-files](http://wiki.ros.org/rosbag). diff --git a/docs/en/web_video_server.md b/docs/en/web_video_server.md index b491a010..dca79d80 100644 --- a/docs/en/web_video_server.md +++ b/docs/en/web_video_server.md @@ -36,7 +36,7 @@ Parameters `width`, `height`, etc. re also available. Read more about `web_video ## Browse with rqt_image_view -To browse images with the rqt tools the user needs a computer with Ubuntu 16.04 и [ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu). +To browse images with the rqt tools the user needs a computer with Ubuntu 18.04 and [ROS Melodic](http://wiki.ros.org/melodic/Installation/Ubuntu). [Connect to the Clever Wi-Fi network](wifi.md) an run `rqt_image_view` with its IP-address: diff --git a/docs/ru/SUMMARY.md b/docs/ru/SUMMARY.md index 15d2f2ad..a4c8de6b 100644 --- a/docs/ru/SUMMARY.md +++ b/docs/ru/SUMMARY.md @@ -51,7 +51,7 @@ * [Настройка PID](pid_tuning.md) * [CAD-модели Клевера](models.md) * [Docker-контейнер с симулятором](sitl_docker.md) - * [Установка ROS Kinetic](ros-install.md) + * [Установка ROS Melodic](ros-install.md) * [Пилотирование со смартфона](rc.md) * [Настройка сети RPi](network.md) * [Интерфейс UART](uart.md) diff --git a/docs/ru/ros-install.md b/docs/ru/ros-install.md index e084e4d5..9af90e42 100644 --- a/docs/ru/ros-install.md +++ b/docs/ru/ros-install.md @@ -1,14 +1,10 @@ -# Установка и настройка пакета ROS Kinetic +# Установка и настройка пакета ROS Melodic Для работы с такими инструментами как: rqt, rviz и т. д., а также для запуска симулятора (SITL) вам потребуется установленный и настроенный пакет ROS. -> **Hint** Более подробную инструкцию по установке смотрите в [основной статье](http://wiki.ros.org/kinetic/Installation/Ubuntu). +> **Hint** Более подробную инструкцию по установке смотрите в [основной статье](http://wiki.ros.org/melodic/Installation/Ubuntu). - - -> **Hint** В случае, если вы используете Ubuntu версии 18.04, вместо ROS Kinetic вам нужно будет установить ROS Melodic. Полную инструкцию по установке вы можете найти [здесь](http://wiki.ros.org/melodic/Installation/Ubuntu). - -## Установка ROS Kinetic на Ubuntu +## Установка ROS Melodic на Ubuntu Для того, чтобы загрузить и установить правильную версию пакета требуется сделать настройки репозиториев, для этого откройте "Программы и обновления" и разрешите `restricted`, `universe` и `multiverse`. @@ -35,13 +31,13 @@ sudo apt-get update + Если вы планируете использовать ROS вместе с симуляцией (также содержит инструменты: rqt, rviz и т. д): ```bash - sudo apt-get install ros-kinetic-desktop-full + sudo apt-get install ros-melodic-desktop-full ``` + Если вы планируете использовать ROS исключительно работать с инструментами rqt, rviz и т. д: ```bash - sudo apt-get install ros-kinetic-desktop + sudo apt-get install ros-melodic-desktop ``` После установки пакета вам нужно инициализировать `rosdep`. @@ -55,12 +51,12 @@ rosdep update Если вам не удобно запускать переменное окружение вручную каждый раз, вы можете настроить его так, чтобы оно добавлялось в ваш сеанс bash при каждом запуске новой оболочки: ```bash -echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc +echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc source ~/.bashrc ``` -Если вы хотите установить какие-либо дополнительные пакеты для вашего ROS Kinetic просто используйте: +Если вы хотите установить какие-либо дополнительные пакеты для вашего ROS Melodic просто используйте: ```bash -sudo apt-get install ros-kinetic-PACKAGE +sudo apt-get install ros-melodic-PACKAGE ``` diff --git a/docs/ru/ros.md b/docs/ru/ros.md index a770f924..80a9c8a8 100644 --- a/docs/ru/ros.md +++ b/docs/ru/ros.md @@ -8,13 +8,13 @@ ROS – это широко используемый фреймворк для Установка --- -Основная статья: http://wiki.ros.org/kinetic/Installation/Ubuntu +Основная статья: http://wiki.ros.org/melodic/Installation/Ubuntu ROS уже установлен на [образе для RPi](image.md). Для использования ROS на компьютере рекомендуется ОС Ubuntu Linux (либо виртуальная машина, например [Parallels Desktop Lite](https://itunes.apple.com/ru/app/parallels-desktop-lite/id1085114709?mt=12) или [VirtualBox](https://www.virtualbox.org)). -> **Note** Для дистрибутива ROS Kinetic рекомендуется Ubuntu версии 16.04. +> **Note** Для дистрибутива ROS Melodic рекомендуется Ubuntu версии 18.04. Концепции --- diff --git a/docs/ru/rviz.md b/docs/ru/rviz.md index 149cd272..61feb094 100644 --- a/docs/ru/rviz.md +++ b/docs/ru/rviz.md @@ -9,7 +9,7 @@ Для использования rviz и rqt необходим компьютер с ОС Ubuntu Linux (либо виртуальная машина, например [Parallels Desktop Lite](https://itunes.apple.com/ru/app/parallels-desktop-lite/id1085114709?mt=12) или [VirtualBox](https://www.virtualbox.org)). -На него необходимо установить пакет `ros-kinetic-desktop-full` или `ros-kinetic-desktop`, используя [документацию по установке](http://wiki.ros.org/kinetic/Installation/Ubuntu). +На него необходимо установить пакет `ros-melodic-desktop-full` или `ros-melodic-desktop`, используя [документацию по установке](http://wiki.ros.org/melodic/Installation/Ubuntu). Запуск rviz --- @@ -48,7 +48,7 @@ Axis или Grid настроенный на фрейм `aruco_map` будут Рекомендуется также установка набора дополнительных полезных плагинов для rviz [jsk_rviz_plugins](https://jsk-docs.readthedocs.io/en/latest/jsk_visualization/doc/jsk_rviz_plugins/index.html). Это набор позволяет визуализировать топики типа `TwistStamped` (скорость), `CameraInfo`, `PolygonArray` и многое другое. Для установки используйте команду: ```bash -sudo apt-get install ros-kinetic-jsk-visualization +sudo apt-get install ros-melodic-jsk-visualization ``` Запуск инструментов rqt @@ -71,5 +71,5 @@ ROS_MASTER_URI=http://192.168.11.1:11311 rqt_image_view Краткое описание полезных rqt-плагинов: * `rqt_image_view` – просмотр изображений из топиков типа `sensor_msgs/Image`; -* `rqt_multiplot` – построение графиков по данным из произвольным топиков (установка: `sudo apt-get install ros-kinetic-rqt-multiplot`); +* `rqt_multiplot` – построение графиков по данным из произвольным топиков (установка: `sudo apt-get install ros-melodic-rqt-multiplot`); * Bag – работа с [Bag-файлами](http://wiki.ros.org/rosbag). diff --git a/docs/ru/sitl.md b/docs/ru/sitl.md index c7e2f9df..9df0611e 100644 --- a/docs/ru/sitl.md +++ b/docs/ru/sitl.md @@ -77,22 +77,22 @@ roslaunch mavros px4.launch fcu_url:=udp://@127.0.0.1:14557 Для того, чтобы запустить симулятор полета дрона, Gazebo или jMAVSim вам потребуется сделать соответственные настройки вашей среды. -> **Caution** Среда `ROS Kinetic` в изначально ориентированна для `Ubuntu (Xenial)` версии 16.04, по этому актуальность данной инструкции гарантируется только для соответственной версии операционной системы. +> **Caution** Среда `ROS Melodic` изначально ориентированна для Ubuntu версии 18.04 (Bionic), поэтому актуальность данной инструкции гарантируется только для данной версии операционной системы. -В первую очередь вам потребуется установить полный пакет ROS Kinetic desktop-full, инструкцию по установке вы можете найти в [статье по установке ROS](ros-install.md). +В первую очередь вам потребуется установить полный пакет ROS Melodic desktop-full, инструкцию по установке вы можете найти в [статье по установке ROS](ros-install.md). После того, как вы выполнили указанные выше инструкции, вам нужно проверить, есть ли в вашем пакете `ROS` все нужные пакеты. ```bash -sudo apt-get install ros-kinetic-gazebo-ros \ - ros-kinetic-gazebo-dev \ - ros-kinetic-gazebo-plugins \ - ros-kinetic-gazebo-ros-pkgs \ - ros-kinetic-gazebo-msgs \ - ros-kinetic-geographic-msgs +sudo apt-get install ros-melodic-gazebo-ros \ + ros-melodic-gazebo-dev \ + ros-melodic-gazebo-plugins \ + ros-melodic-gazebo-ros-pkgs \ + ros-melodic-gazebo-msgs \ + ros-melodic-geographic-msgs ``` -Чтобы избежать ошибок во время запуска симулятора, вам нужно будет установить Gazebo v7.14, для этого подключите необходимый репозиторий и добавьте соответствующие ключи: +Чтобы избежать ошибок во время запуска симулятора, вам нужно будет установить Gazebo v9.11, для этого подключите необходимый репозиторий и добавьте соответствующие ключи: ```bash sudo sh -c 'echo "deb http://packages.osrfoundation.org/gazebo/ubuntu-stable `lsb_release -cs` main" > /etc/apt/sources.list.d/gazebo-stable.list' diff --git a/docs/ru/web_video_server.md b/docs/ru/web_video_server.md index fe7fc5bb..4f71ef96 100644 --- a/docs/ru/web_video_server.md +++ b/docs/ru/web_video_server.md @@ -36,7 +36,7 @@ http://192.168.11.1:8080/stream_viewer?topic=/main_camera/image_raw&type=mjpeg&q ## Просмотр через rqt_image_view -Для просмотра изображений через инструменты rqt необходим компьютер с установленной Ubuntu 16.04 и [ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu). +Для просмотра изображений через инструменты rqt необходим компьютер с установленной Ubuntu 18.04 и [ROS Melodic](http://wiki.ros.org/melodic/Installation/Ubuntu). [Подключитесь к Wi-Fi сети Клевера](wifi.md) и запустите `rqt_image_view` с указанием его IP-адреса: