From 83be9a5425e84d1202f5dca4f6351e717f3b62b9 Mon Sep 17 00:00:00 2001 From: Aymeric DUJARDIN Date: Wed, 12 Jun 2019 15:21:55 +0200 Subject: [PATCH] Initial commit --- 6x6_1000-25.png | Bin 0 -> 2862 bytes README.md | 29 + mono/CMakeLists.txt | 43 + mono/README.md | 59 + mono/include/aruco.hpp | 20961 ++++++++++++++++++++++++++++ mono/src/aruco.cpp | 2817 ++++ mono/src/main.cpp | 139 + multi-camera/CMakeLists.txt | 63 + multi-camera/README.md | 60 + multi-camera/include/GLViewer.hpp | 287 + multi-camera/include/aruco.hpp | 20961 ++++++++++++++++++++++++++++ multi-camera/src/GLViewer.cpp | 744 + multi-camera/src/aruco.cpp | 2817 ++++ multi-camera/src/main.cpp | 253 + 14 files changed, 49233 insertions(+) create mode 100644 6x6_1000-25.png create mode 100644 README.md create mode 100644 mono/CMakeLists.txt create mode 100644 mono/README.md create mode 100644 mono/include/aruco.hpp create mode 100644 mono/src/aruco.cpp create mode 100644 mono/src/main.cpp create mode 100644 multi-camera/CMakeLists.txt create mode 100644 multi-camera/README.md create mode 100644 multi-camera/include/GLViewer.hpp create mode 100644 multi-camera/include/aruco.hpp create mode 100644 multi-camera/src/GLViewer.cpp create mode 100644 multi-camera/src/aruco.cpp create mode 100644 multi-camera/src/main.cpp diff --git a/6x6_1000-25.png b/6x6_1000-25.png new file mode 100644 index 0000000000000000000000000000000000000000..5716b581a3b7b6b31e97c6c745ad0a407342885b GIT binary patch literal 2862 zcmeAS@N?(olHy`uVBq!ia0y~yV2S`?4mP03zO)&47#J8^Go76SJe{2t3X1a6GILTH z7&Io>zVA{&JS97FU@-;fVm&gH1nL7l$q65OrF6VO8_VrSeXb+fL z_^~mfw4m_X)q|k|EcOmDF>^&?mmK-8+A6kDPUidLyL*q{wRTt`HZzUYjnQ}e*%TYK zWyab`A4K1BEMT83F>Pk*8LuEF-Q(A7Yijm(e_C_x`9GQ1tZPXP{wnhl+cJgM3;XBZ zVtZcu$Uysq)Tfvv#tBm zwm*b*nZ4(FlPxC%FYM)wi7_`x<==6K@z*?_n^R&>`UjtQ+VI`@*D{_9)!ZfPs`g&} zUigb)$%@rScnb>9?%THD++VbRz&SGG^uqAoByDx`7I;J!1EcUd2s1iq%&q_mvX^-Jy0SlJV-YYn_;zm+P#ve1r;B4q#jUqD948$z z;BmS5QuFTrQ)lJ!8&$qln{NTA0xvD!~bp!3=DbPSk8p&Lw zK*O#GlvCwrWR*6C15aZR zl_ya}I#G&{N+;aqK9VAulyeP7=X`sxZ5tm$%~Wnk>i}AmB9)TJxeF;z3|s|)y|l+2 d=o=~+f6h}oqW%7jC9omI;OXk;vd$@?2>?AsPD=m) literal 0 HcmV?d00001 diff --git a/README.md b/README.md new file mode 100644 index 0000000..6bcd914 --- /dev/null +++ b/README.md @@ -0,0 +1,29 @@ +# Stereolabs ZED - ArUco sample + +This sample shows how to reset the ZED camera tracking to a known reference using an ArUco marker. + +![http://chev.me/arucogen/](6x6_1000-25.png) + +## Mono + +The Mono camera sample located in the [mono folder](./mono) provides an easy way to reset the positional tracking using a marker as a known fixed position in space. + +## Multi Camera + +The [multi camera sample](./multi-camera) use the marker location to calibrates multiples ZED camera in space. By pointing all the camera to a unique marker, the position of each can be deduced. +The point cloud of every camera is then displayed in the same referential. + +## Other + +Feel free to modify either sample to fit your need, the marker detection is very convenient and robust and can be used to a number of application where an external position has to be known. + +## ArUco markers + +This [website](http://chev.me/arucogen/) can be used to easily display Aruco patterns. + +The sample is expecting a `6x6 Aruco` Dictionary with a 160mm marker by default. The bigger the marker, the better the camera position will be. +It's important to make sure that the real-world size of the marker matches the size set in the samples (160mm) to avoid scale issues in the tracking. + +## ArUco detection + +The Aruco detection code is taken from OpenCV Contrib module, please refer to the source files for the license information (BSD 3). diff --git a/mono/CMakeLists.txt b/mono/CMakeLists.txt new file mode 100644 index 0000000..7542177 --- /dev/null +++ b/mono/CMakeLists.txt @@ -0,0 +1,43 @@ +SET(ProjectName ZED_Reloc_Aruco) +CMAKE_MINIMUM_REQUIRED(VERSION 2.4) +PROJECT(${ProjectName}) + +option(LINK_SHARED_ZED "Link with the ZED SDK shared executable" ON) + +if (NOT LINK_SHARED_ZED AND MSVC) + message(FATAL_ERROR "LINK_SHARED_ZED OFF : ZED SDK static libraries not available on Windows") +endif() + +if(COMMAND cmake_policy) + cmake_policy(SET CMP0003 OLD) + cmake_policy(SET CMP0015 OLD) +endif(COMMAND cmake_policy) + +SET(EXECUTABLE_OUTPUT_PATH ".") + +find_package(ZED 2 REQUIRED) +find_package(OpenCV REQUIRED) +find_package(CUDA ${ZED_CUDA_VERSION} EXACT REQUIRED) + +include_directories(${CUDA_INCLUDE_DIRS}) +include_directories(${ZED_INCLUDE_DIRS}) +include_directories(${OPENCV_INCLUDE_DIRS}) +include_directories(${CMAKE_CURRENT_SOURCE_DIR}/include) + +link_directories(${ZED_LIBRARY_DIR}) +link_directories(${OpenCV_LIBRARY_DIRS}) +link_directories(${CUDA_LIBRARY_DIRS}) + +FILE(GLOB_RECURSE SRC_FILES src/*.cpp) +FILE(GLOB_RECURSE HDR_FILES include/*.hpp) + +ADD_EXECUTABLE(${ProjectName} ${HDR_FILES} ${SRC_FILES}) +add_definitions(-std=c++11 -O3) + +if (LINK_SHARED_ZED) + SET(ZED_LIBS ${ZED_LIBRARIES} ${CUDA_CUDA_LIBRARY} ${CUDA_CUDART_LIBRARY} ${CUDA_NPP_LIBRARIES_ZED}) +else() + SET(ZED_LIBS ${ZED_STATIC_LIBRARIES} ${CUDA_CUDA_LIBRARY} ${CUDA_LIBRARY}) +endif() + +TARGET_LINK_LIBRARIES(${ProjectName} ${ZED_LIBS} ${OpenCV_LIBRARIES}) diff --git a/mono/README.md b/mono/README.md new file mode 100644 index 0000000..ba49310 --- /dev/null +++ b/mono/README.md @@ -0,0 +1,59 @@ +# Stereolabs ZED - ArUco Positional Tracking sample + +This sample shows how to reset the ZED camera tracking to a known reference using an ArUco marker. + +![http://chev.me/arucogen/](../6x6_1000-25.png) + +Point the camera to this marker and press the space bar to reset the positional tracking reference. +This feature can be useful to avoid accumulating drift when moving the camera or to get multiple cameras in the same referential. + + +## Getting started + +- First, download the latest version of the ZED SDK on [stereolabs.com](https://www.stereolabs.com). +- For more information, read the ZED [API documentation](https://www.stereolabs.com/developers/documentation/API/). + +### Prerequisites + +- Windows 7 64bits or later, Ubuntu 16.04 or later +- [ZED SDK](https://www.stereolabs.com/developers/) and its dependencies ([CUDA](https://developer.nvidia.com/cuda-downloads)) + +## Build the program + +Download the sample and follow the instructions below: [More](https://www.stereolabs.com/docs/getting-started/application-development/) + +### Build for Windows + +- Create a "build" folder in the source folder +- Open cmake-gui and select the source and build folders +- Generate the Visual Studio `Win64` solution +- Open the resulting solution and change configuration to `Release` +- Build solution + +### Build for Linux + +Open a terminal in the sample directory and execute the following command: + + mkdir build + cd build + cmake .. + make + +## Run the program + +- Navigate to the build directory and launch the executable file +- Or open a terminal in the build directory and run the sample : + + ./ZED_Reloc_Aruco + + +## ArUco markers + +This [website](http://chev.me/arucogen/) can be used to easily display Aruco patterns. + +The sample is expecting a `6x6 Aruco` Dictionary with a 160mm marker by default. The bigger the marker, the better the camera position will be. +It's important to make sure that the real-world size of the marker matches the size set in the samples (160mm) to avoid scale issues in the tracking. + +## ArUco detection + +The Aruco detection code is taken from OpenCV Contrib module, please refer to the source files for the license information (BSD 3). diff --git a/mono/include/aruco.hpp b/mono/include/aruco.hpp new file mode 100644 index 0000000..c9e70a2 --- /dev/null +++ b/mono/include/aruco.hpp @@ -0,0 +1,20961 @@ +/* +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 + +/** +* @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 a 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. +* +* @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 { + + /** + * @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 Dictionary { + + public: + Mat bytesList; // marker code information + int markerSize; // number of bits per dimension + int maxCorrectionBits; // maximum number of bits that can be corrected + + + /** + */ + Dictionary(const Mat &_bytesList = Mat(), int _markerSize = 0, int _maxcorr = 0); + + + + /** + * @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 + */ + 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 + */ + static Mat getByteListFromBits(const Mat &bits); + + + /** + * @brief Transform list of bytes to matrix of bits + */ + 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: 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 + }; + + + /** + * @brief Returns one of the predefined dictionaries defined in PREDEFINED_DICTIONARY_NAME + */ + CV_EXPORTS const Dictionary &getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name); + + + /** + * @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) + * + * 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 Dictionary generateCustomDictionary(int nMarkers, int markerSize, + const Dictionary &baseDictionary = Dictionary()); + + + + + /** + * @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). + * - doCornerRefinement: do subpixel refinement or not + * - 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). + * - perpectiveRemovePixelPerCell: 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. perpectiveRemovePixelPerCell (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). + */ + struct CV_EXPORTS DetectorParameters { + + DetectorParameters(); + + int adaptiveThreshWinSizeMin; + int adaptiveThreshWinSizeMax; + int adaptiveThreshWinSizeStep; + double adaptiveThreshConstant; + double minMarkerPerimeterRate; + double maxMarkerPerimeterRate; + double polygonalApproxAccuracyRate; + double minCornerDistanceRate; + int minDistanceToBorder; + double minMarkerDistanceRate; + bool doCornerRefinement; + int cornerRefinementWinSize; + int cornerRefinementMaxIterations; + double cornerRefinementMinAccuracy; + int markerBorderBits; + int perspectiveRemovePixelPerCell; + double perspectiveRemoveIgnoredMarginPerCell; + double maxErroneousBitsInBorderRate; + double minOtsuStdDev; + double errorCorrectionRate; + }; + + + + /** + * @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. + * + * 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 void detectMarkers(InputArray image, Dictionary dictionary, OutputArrayOfArrays corners, + OutputArray ids, DetectorParameters parameters = DetectorParameters(), + OutputArrayOfArrays rejectedImgPoints = 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. + * + * 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 void estimatePoseSingleMarkers(InputArrayOfArrays corners, float markerLength, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs); + + + + /** + * @brief Board of markers + * + * A board is a set of markers in the 3D space with a common cordinate 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 Board { + + public: + // array of object points of all the marker corners in the board + // each marker include its 4 corners, i.e. for M markers, the size is Mx4 + std::vector< std::vector< Point3f > > objPoints; + + // the dictionary of markers employed for this board + Dictionary dictionary; + + // vector of the identifiers of the markers in the board (same size than objPoints) + // The identifiers refers to the board dictionary + 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 arrangment. + * The board can be drawn using drawPlanarBoard() function (@sa drawPlanarBoard) + */ + class CV_EXPORTS 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. + */ + 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 than markerLenght) + * @param dictionary dictionary of markers indicating the type of markers. + * The first markersX*markersY markers in the dictionary are used. + * @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. + */ + static GridBoard create(int markersX, int markersY, float markerLength, float markerSeparation, + Dictionary dictionary); + + /** + * + */ + Size getGridSize() const { return Size(_markersX, _markersY); } + + /** + * + */ + float getMarkerLength() const { return _markerLength; } + + /** + * + */ + 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 + * (@sa Rodrigues). + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * + * 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 int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, const Board &board, + InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, + OutputArray tvec); + + + + + /** + * @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 void refineDetectedMarkers( + InputArray image, const Board &board, InputOutputArrayOfArrays detectedCorners, + InputOutputArray detectedIds, InputOutputArray rejectedCorners, + InputArray cameraMatrix = noArray(), InputArray distCoeffs = noArray(), + float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true, + OutputArray recoveredIdxs = noArray(), DetectorParameters parameters = DetectorParameters()); + + + + /** + * @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 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. + */ + CV_EXPORTS 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 void drawMarker(Dictionary dictionary, int id, int sidePixels, OutputArray img, + int borderBits = 1); + + + + /** + * @brief Draw a planar board + * + * @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 void drawPlanarBoard(const 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 (@sa 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 flags flags Different flags for the calibration process (@sa calibrateCamera) + * @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 double calibrateCameraAruco( + InputArrayOfArrays corners, InputArray ids, InputArray counter, const Board &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 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 CharucoBoard : public Board { + + public: + // vector of chessboard 3D corners precalculated + std::vector< Point3f > chessboardCorners; + + // for each charuco corner, nearest marker id and nearest marker corner id of each marker + std::vector< std::vector< int > > nearestMarkerIdx; + 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. + */ + 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. + */ + static CharucoBoard create(int squaresX, int squaresY, float squareLength, float markerLength, + Dictionary dictionary); + + /** + * + */ + Size getChessboardSize() const { return Size(_squaresX, _squaresY); } + + /** + * + */ + float getSquareLength() const { return _squareLength; } + + /** + * + */ + 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 + * + * 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 int interpolateCornersCharuco(InputArrayOfArrays markerCorners, InputArray markerIds, + InputArray image, const CharucoBoard &board, + OutputArray charucoCorners, OutputArray charucoIds, + InputArray cameraMatrix = noArray(), + InputArray distCoeffs = noArray()); + + /** + * @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 + * (@sa Rodrigues). + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * + * 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 bool estimatePoseCharucoBoard(InputArray charucoCorners, InputArray charucoIds, + CharucoBoard &board, InputArray cameraMatrix, + InputArray distCoeffs, OutputArray rvec, OutputArray tvec); + + /** + * @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 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 flags flags Different flags for the calibration process (@sa calibrateCamera) + * @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 double calibrateCameraCharuco( + InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const CharucoBoard &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 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 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. + */ + CV_EXPORTS void drawCharucoDiamond(Dictionary dictionary, Vec4i ids, int squareLength, + int markerLength, OutputArray img, int marginSize = 0, + int borderBits = 1); + + + 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, 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187, 0 }, }, + { { 117, 210, 231, 0 }, + { 102, 247, 116, 0 }, + { 115, 165, 215, 0 }, + { 23, 119, 179, 0 }, }, + { { 117, 221, 8, 0 }, + { 71, 57, 69, 1 }, + { 8, 93, 215, 0 }, + { 209, 78, 113, 0 }, }, + { { 117, 221, 11, 1 }, + { 79, 123, 69, 1 }, + { 232, 93, 215, 0 }, + { 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, 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157, 65 }, }, + { { 216, 135 }, + { 145, 158 }, + { 225, 27 }, + { 121, 137 }, }, + { { 208, 175 }, + { 147, 155 }, + { 245, 11 }, + { 217, 201 }, }, + { { 218, 196 }, + { 132, 190 }, + { 35, 91 }, + { 125, 33 }, }, + { { 210, 12 }, + { 132, 153 }, + { 48, 75 }, + { 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 }, + { 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208, 145, 1 }, + { 218, 80, 96, 0 }, }, + { { 192, 14, 9, 1 }, + { 41, 73, 8, 1 }, + { 200, 56, 1, 1 }, + { 136, 73, 74, 0 }, }, + { { 192, 112, 254, 0 }, + { 80, 135, 122, 1 }, + { 63, 135, 1, 1 }, + { 175, 112, 133, 0 }, }, + { { 204, 116, 17, 0 }, + { 209, 65, 78, 0 }, + { 68, 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, 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{ 67, 206, 185, 144, 6 }, }, + { { 22, 162, 90, 176, 15 }, + { 165, 88, 223, 17, 2 }, + { 240, 213, 164, 86, 8 }, + { 72, 143, 177, 170, 5 }, }, + { { 16, 253, 203, 109, 14 }, + { 121, 254, 87, 44, 8 }, + { 123, 109, 59, 240, 8 }, + { 19, 78, 167, 249, 14 }, }, + { { 17, 52, 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, 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{ 138, 18, 92, 158, 93, 239, 1 }, + { 182, 95, 25, 144, 225, 175, 1 }, + { 251, 221, 60, 157, 36, 40, 1 }, }, + { { 249, 231, 61, 60, 30, 97, 1 }, + { 118, 102, 134, 45, 93, 191, 1 }, + { 195, 60, 30, 94, 115, 207, 1 }, + { 254, 221, 90, 48, 179, 55, 0 }, }, + { { 248, 255, 88, 101, 6, 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 }, }, }; + } +} + +#endif diff --git a/mono/src/aruco.cpp b/mono/src/aruco.cpp new file mode 100644 index 0000000..d082c4e --- /dev/null +++ b/mono/src/aruco.cpp @@ -0,0 +1,2817 @@ +/* +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 "aruco.hpp" +#include +#include +#include +#include + +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), + doCornerRefinement(false), + cornerRefinementWinSize(5), + cornerRefinementMaxIterations(30), + cornerRefinementMinAccuracy(0.1), + markerBorderBits(1), + perspectiveRemovePixelPerCell(4), + perspectiveRemoveIgnoredMarginPerCell(0.13), + maxErroneousBitsInBorderRate(0.35), + minOtsuStdDev(5.0), + errorCorrectionRate(0.6) {} + + + /** + * @brief Convert input image to gray if it is a 3-channels image + */ + static void _convertToGrey(InputArray _in, OutputArray _out) { + + CV_Assert(_in.getMat().channels() == 1 || _in.getMat().channels() == 3); + + _out.create(_in.getMat().size(), CV_8UC1); + if (_in.getMat().type() == CV_8UC3) + cvtColor(_in.getMat(), _out.getMat(), COLOR_BGR2GRAY); + else + _in.getMat().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 combinatios are posible + 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(); + int 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, + DetectorParameters *_params) + : grey(_grey), candidatesArrays(_candidatesArrays), contoursArrays(_contoursArrays), + params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + /** + * @brief Initial steps on finding square candidates + */ + static void _detectInitialCandidates(const Mat &grey, vector< vector< Point2f > > &candidates, + vector< vector< Point > > &contours, + DetectorParameters params) { + + 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(nScales); + vector< vector< vector< Point > > > contoursArrays(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, ¶ms)); + + // 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, OutputArrayOfArrays _candidates, + OutputArrayOfArrays _contours, DetectorParameters 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 + vector< vector< Point2f > > candidatesOut; + vector< vector< Point > > contoursOut; + _filterTooCloseCandidates(candidates, candidatesOut, contours, contoursOut, + params.minMarkerDistanceRate); + + // parse output + _candidates.create((int)candidatesOut.size(), 1, CV_32FC2); + _contours.create((int)contoursOut.size(), 1, CV_32SC2); + for (int i = 0; i < (int)candidatesOut.size(); i++) { + _candidates.create(4, 1, CV_32FC2, i, true); + Mat m = _candidates.getMat(i); + for (int j = 0; j < 4; j++) + m.ptr< Vec2f >(0)[j] = candidatesOut[i][j]; + + _contours.create((int)contoursOut[i].size(), 1, CV_32SC2, i, true); + Mat c = _contours.getMat(i); + for (unsigned int j = 0; j < contoursOut[i].size(); j++) + c.ptr< Point2i >()[j] = contoursOut[i][j]; + } + } + + + /** + * @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 + unsigned int nZ = 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 Dictionary &dictionary, InputArray _image, + InputOutputArray _corners, int &idx, DetectorParameters params) { + + CV_Assert(_corners.total() == 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); + if (borderErrors > maximumErrorsInBorder) return false; // border is wrong + + // 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; + else { + // shift corner positions to the correct rotation + if (rotation != 0) { + Mat copyPoints = _corners.getMat().clone(); + for (int j = 0; j < 4; j++) + _corners.getMat().ptr< Point2f >(0)[j] = + copyPoints.ptr< Point2f >(0)[(j + 4 - rotation) % 4]; + } + 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, InputArrayOfArrays _candidates, + InputArrayOfArrays _contours, const Dictionary *_dictionary, + vector< int > *_idsTmp, vector< char > *_validCandidates, + DetectorParameters *_params) + : grey(_grey), candidates(_candidates), contours(_contours), dictionary(_dictionary), + idsTmp(_idsTmp), validCandidates(_validCandidates), params(_params) {} + + void operator()(const Range &range) const { + const int begin = range.start; + const int end = range.end; + + for (int i = begin; i < end; i++) { + int currId; + Mat currentCandidate = candidates.getMat(i); + if (_identifyOneCandidate(*dictionary, *grey, currentCandidate, currId, *params)) { + (*validCandidates)[i] = 1; + (*idsTmp)[i] = currId; + } + } + } + + private: + IdentifyCandidatesParallel &operator=(const IdentifyCandidatesParallel &); // to quiet MSVC + + const Mat *grey; + InputArrayOfArrays candidates, contours; + const Dictionary *dictionary; + vector< int > *idsTmp; + vector< char > *validCandidates; + DetectorParameters *params; + }; + + + + /** + * @brief Identify square candidates according to a marker dictionary + */ + static void _identifyCandidates(InputArray _image, InputArrayOfArrays _candidates, + InputArrayOfArrays _contours, const Dictionary &dictionary, + OutputArrayOfArrays _accepted, OutputArray _ids, + DetectorParameters params, + OutputArrayOfArrays _rejected = noArray()) { + + int ncandidates = (int)_candidates.total(); + + vector< Mat > accepted; + vector< Mat > rejected; + vector< int > ids; + + 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, _contours, &dictionary, &idsTmp, + &validCandidates, ¶ms)); + + for (int i = 0; i < ncandidates; i++) { + if (validCandidates[i] == 1) { + accepted.push_back(_candidates.getMat(i)); + ids.push_back(idsTmp[i]); + } + else { + rejected.push_back(_candidates.getMat(i)); + } + } + + // parse output + _accepted.create((int)accepted.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < accepted.size(); i++) { + _accepted.create(4, 1, CV_32FC2, i, true); + Mat m = _accepted.getMat(i); + accepted[i].copyTo(m); + } + + _ids.create((int)ids.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < ids.size(); i++) + _ids.getMat().ptr< int >(0)[i] = ids[i]; + + if (_rejected.needed()) { + _rejected.create((int)rejected.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < rejected.size(); i++) { + _rejected.create(4, 1, CV_32FC2, i, true); + Mat m = _rejected.getMat(i); + rejected[i].copyTo(m); + } + } + } + + + /** + * @brief Final filter of markers after its identification + */ + static void _filterDetectedMarkers(InputArrayOfArrays _inCorners, InputArray _inIds, + OutputArrayOfArrays _outCorners, OutputArray _outIds) { + + CV_Assert(_inCorners.total() == _inIds.total()); + if (_inCorners.total() == 0) return; + + // mark markers that will be removed + vector< bool > toRemove(_inCorners.total(), false); + bool atLeastOneRemove = false; + + // remove repeated markers with same id, if one contains the other (doble border bug) + for (unsigned int i = 0; i < _inCorners.total() - 1; i++) { + for (unsigned int j = i + 1; j < _inCorners.total(); j++) { + if (_inIds.getMat().ptr< int >(0)[i] != _inIds.getMat().ptr< int >(0)[j]) continue; + + // check if first marker is inside second + bool inside = true; + for (unsigned int p = 0; p < 4; p++) { + Point2f point = _inCorners.getMat(j).ptr< Point2f >(0)[p]; + if (pointPolygonTest(_inCorners.getMat(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 = _inCorners.getMat(i).ptr< Point2f >(0)[p]; + if (pointPolygonTest(_inCorners.getMat(j), point, false) < 0) { + inside = false; + break; + } + } + if (inside) { + toRemove[i] = true; + atLeastOneRemove = true; + continue; + } + } + } + + // parse output + if (atLeastOneRemove) { + vector< Mat > filteredCorners; + vector< int > filteredIds; + + for (unsigned int i = 0; i < toRemove.size(); i++) { + if (!toRemove[i]) { + filteredCorners.push_back(_inCorners.getMat(i).clone()); + filteredIds.push_back(_inIds.getMat().ptr< int >(0)[i]); + } + } + + _outIds.create((int)filteredIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredIds.size(); i++) + _outIds.getMat().ptr< int >(0)[i] = filteredIds[i]; + + _outCorners.create((int)filteredCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredCorners.size(); i++) { + _outCorners.create(4, 1, CV_32FC2, i, true); + filteredCorners[i].copyTo(_outCorners.getMat(i)); + } + } + } + + + + /** + * @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, + DetectorParameters *_params) + : grey(_grey), corners(_corners), params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + + /** + */ + void detectMarkers(InputArray _image, Dictionary dictionary, OutputArrayOfArrays _corners, + OutputArray _ids, DetectorParameters params, + OutputArrayOfArrays _rejectedImgPoints) { + + CV_Assert(_image.getMat().total() != 0); + + Mat grey; + _convertToGrey(_image.getMat(), grey); + + /// STEP 1: Detect marker candidates + vector< vector< Point2f > > candidates; + vector< vector< Point > > contours; + _detectCandidates(grey, candidates, contours, params); + + /// STEP 2: Check candidate codification (identify markers) + _identifyCandidates(grey, candidates, contours, dictionary, _corners, _ids, params, + _rejectedImgPoints); + + /// STEP 3: Filter detected markers; + _filterDetectedMarkers(_corners, _ids, _corners, _ids); + + /// STEP 4: Corner refinement + if (params.doCornerRefinement) { + 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.total(); 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, (int)_corners.total()), + MarkerSubpixelParallel(&grey, _corners, ¶ms)); + } + } + + + + /** + * 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 { + 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(0, i), tvecs.at(0, 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, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs) { + + 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)); + } + + + + /** + * @brief Given a board configuration and a set of detected markers, returns the corresponding + * image points and object points to call solvePnP + */ + static void _getBoardObjectAndImagePoints(const Board &board, InputArray _detectedIds, + InputArrayOfArrays _detectedCorners, + OutputArray _imgPoints, OutputArray _objPoints) { + + CV_Assert(board.ids.size() == board.objPoints.size()); + CV_Assert(_detectedIds.total() == _detectedCorners.total()); + + int nDetectedMarkers = (int)_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 (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 + _objPoints.create((int)objPnts.size(), 1, CV_32FC3); + for (unsigned int i = 0; i < objPnts.size(); i++) + _objPoints.getMat().ptr< Point3f >(0)[i] = objPnts[i]; + + _imgPoints.create((int)objPnts.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < imgPnts.size(); i++) + _imgPoints.getMat().ptr< Point2f >(0)[i] = imgPnts[i]; + } + + + + /** + * Project board markers that are not included in the list of detected markers + */ + static void _projectUndetectedMarkers(const Board &board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, InputArray _cameraMatrix, + InputArray _distCoeffs, + OutputArrayOfArrays _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 + _undetectedMarkersIds.create((int)undetectedIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < undetectedIds.size(); i++) + _undetectedMarkersIds.getMat().ptr< int >(0)[i] = undetectedIds[i]; + + _undetectedMarkersProjectedCorners.create((int)undetectedCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < undetectedCorners.size(); i++) { + _undetectedMarkersProjectedCorners.create(4, 1, CV_32FC2, i, true); + for (int j = 0; j < 4; j++) { + _undetectedMarkersProjectedCorners.getMat(i).ptr< Point2f >()[j] = + undetectedCorners[i][j]; + } + } + } + + + + /** + * Interpolate board markers that are not included in the list of detected markers using + * global homography + */ + static void _projectUndetectedMarkers(const Board &board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, + OutputArrayOfArrays _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.create((int)undetectedMarkersIds.size(), 1, CV_32FC2); + + // for each undetected marker, apply transformation + for (unsigned int i = 0; i < undetectedMarkersObj2D.size(); i++) { + Mat projectedMarker; + perspectiveTransform(undetectedMarkersObj2D[i], projectedMarker, transformation); + + _undetectedMarkersProjectedCorners.create(4, 1, CV_32FC2, i, true); + projectedMarker.copyTo(_undetectedMarkersProjectedCorners.getMat(i)); + } + + _undetectedMarkersIds.create((int)undetectedMarkersIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < undetectedMarkersIds.size(); i++) + _undetectedMarkersIds.getMat().ptr< int >(0)[i] = undetectedMarkersIds[i]; + } + + + + /** + */ + void refineDetectedMarkers(InputArray _image, const Board &board, + InputOutputArrayOfArrays _detectedCorners, InputOutputArray _detectedIds, + InputOutputArray _rejectedCorners, InputArray _cameraMatrix, + InputArray _distCoeffs, float minRepDistance, float errorCorrectionRate, + bool checkAllOrders, OutputArray _recoveredIdxs, + DetectorParameters params) { + + CV_Assert(minRepDistance > 0); + + if (_detectedIds.total() == 0 || _rejectedCorners.total() == 0) return; + + // 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 + int maxCorrectionRecalculated = + int(double(board.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, board.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 = + board.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.doCornerRefinement) { + 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 + _detectedIds.create((int)finalAcceptedIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < finalAcceptedIds.size(); i++) + _detectedIds.getMat().ptr< int >(0)[i] = finalAcceptedIds[i]; + + _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()) { + _recoveredIdxs.create((int)recoveredIdxs.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < recoveredIdxs.size(); i++) { + _recoveredIdxs.getMat().ptr< int >()[i] = recoveredIdxs[i]; + } + } + } + } + + + + + /** + */ + int estimatePoseBoard(InputArrayOfArrays _corners, InputArray _ids, const Board &board, + InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, + OutputArray _tvec) { + + CV_Assert(_corners.total() == _ids.total()); + + // get object and image points for the solvePnP function + Mat objPoints, imgPoints; + _getBoardObjectAndImagePoints(board, _ids, _corners, imgPoints, objPoints); + + CV_Assert(imgPoints.total() == objPoints.total()); + + if (objPoints.total() == 0) // 0 of the detected markers in board + return 0; + + _rvec.create(3, 1, CV_64FC1); + _tvec.create(3, 1, CV_64FC1); + solvePnP(objPoints, imgPoints, _cameraMatrix, _distCoeffs, _rvec, _tvec); + + // 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) { + aruco::drawPlanarBoard((*this), outSize, _img, marginSize, borderBits); + } + + + + /** + */ + GridBoard GridBoard::create(int markersX, int markersY, float markerLength, float markerSeparation, + Dictionary _dictionary) { + + GridBoard res; + + CV_Assert(markersX > 0 && markersY > 0 && markerLength > 0 && markerSeparation > 0); + + res._markersX = markersX; + res._markersY = markersY; + res._markerLength = markerLength; + res._markerSeparation = markerSeparation; + res.dictionary = _dictionary; + + int totalMarkers = markersX * markersY; + res.ids.resize(totalMarkers); + res.objPoints.reserve(totalMarkers); + + // fill ids with first identifiers + for (int i = 0; i < totalMarkers; i++) + res.ids[i] = i; + + // 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) { + + CV_Assert(_image.getMat().total() != 0 && + (_image.getMat().channels() == 1 || _image.getMat().channels() == 3)); + CV_Assert(length > 0); + + // project axis points + vector< Point3f > axisPoints; + axisPoints.push_back(Point3f(0, 0, 0)); + axisPoints.push_back(Point3f(length, 0, 0)); + axisPoints.push_back(Point3f(0, length, 0)); + axisPoints.push_back(Point3f(0, 0, length)); + vector< Point2f > imagePoints; + projectPoints(axisPoints, _rvec, _tvec, _cameraMatrix, _distCoeffs, imagePoints); + + // draw axis lines + line(_image, imagePoints[0], imagePoints[1], Scalar(0, 0, 255), 3); + line(_image, imagePoints[0], imagePoints[2], Scalar(0, 255, 0), 3); + line(_image, imagePoints[0], imagePoints[3], Scalar(255, 0, 0), 3); + } + + + + /** + */ + void drawMarker(Dictionary dictionary, int id, int sidePixels, OutputArray _img, int borderBits) { + dictionary.drawMarker(id, sidePixels, _img, borderBits); + } + + + + /** + */ + void drawPlanarBoard(const Board &board, Size outSize, OutputArray _img, int marginSize, + int borderBits) { + + CV_Assert(outSize.area() > 0); + CV_Assert(marginSize >= 0); + + _img.create(outSize, CV_8UC1); + Mat out = _img.getMat(); + out.setTo(Scalar::all(255)); + Mat outNoMargins = + out.colRange(marginSize, out.cols - marginSize).rowRange(marginSize, out.rows - 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, sizeY; + sizeX = maxX - minX; + sizeY = maxY - minY; + + // proportion transformations + float xReduction = sizeX / float(outNoMargins.cols); + float yReduction = sizeY / float(outNoMargins.rows); + + // determine the zone where the markers are placed + Mat markerZone; + if (xReduction > yReduction) { + int nRows = int(sizeY / xReduction); + int rowsMargins = (outNoMargins.rows - nRows) / 2; + markerZone = outNoMargins.rowRange(rowsMargins, outNoMargins.rows - rowsMargins); + } + else { + int nCols = int(sizeX / yReduction); + int colsMargins = (outNoMargins.cols - nCols) / 2; + markerZone = outNoMargins.colRange(colsMargins, outNoMargins.cols - colsMargins); + } + + // now paint each marker + for (unsigned int m = 0; m < board.objPoints.size(); m++) { + + // transform corners to markerZone coordinates + vector< Point2f > outCorners; + outCorners.resize(4); + for (int j = 0; j < 4; j++) { + Point2f p0, p1, pf; + p0 = Point2f(board.objPoints[m][j].x, board.objPoints[m][j].y); + // remove negativity + p1.x = p0.x - minX; + p1.y = p0.y - minY; + pf.x = p1.x * float(markerZone.cols - 1) / sizeX; + pf.y = float(markerZone.rows - 1) - p1.y * float(markerZone.rows - 1) / sizeY; + outCorners[j] = pf; + } + + // get tiny marker + int tinyMarkerSize = 10 * board.dictionary.markerSize + 2; + Mat tinyMarker; + board.dictionary.drawMarker(board.ids[m], tinyMarkerSize, tinyMarker, borderBits); + + // interpolate tiny marker to marker position in markerZone + Mat inCorners(4, 1, CV_32FC2); + inCorners.ptr< Point2f >(0)[0] = Point2f(0, 0); + inCorners.ptr< Point2f >(0)[1] = Point2f((float)tinyMarker.cols, 0); + inCorners.ptr< Point2f >(0)[2] = Point2f((float)tinyMarker.cols, (float)tinyMarker.rows); + inCorners.ptr< Point2f >(0)[3] = Point2f(0, (float)tinyMarker.rows); + + // remove perspective + Mat transformation = getPerspectiveTransform(inCorners, outCorners); + Mat aux; + const char borderValue = 127; + warpPerspective(tinyMarker, aux, transformation, markerZone.size(), INTER_NEAREST, + BORDER_CONSTANT, Scalar::all(borderValue)); + + // copy only not-border pixels + for (int y = 0; y < aux.rows; y++) { + for (int x = 0; x < aux.cols; x++) { + if (aux.at< unsigned char >(y, x) == borderValue) continue; + markerZone.at< unsigned char >(y, x) = aux.at< unsigned char >(y, x); + } + } + } + } + + + + /** + */ + double calibrateCameraAruco(InputArrayOfArrays _corners, InputArray _ids, InputArray _counter, + const Board &board, Size imageSize, InputOutputArray _cameraMatrix, + InputOutputArray _distCoeffs, OutputArrayOfArrays _rvecs, + OutputArrayOfArrays _tvecs, int flags, TermCriteria criteria) { + + // for each frame, get properly processed imagePoints and objectPoints for the calibrateCamera + // function + vector< Mat > processedObjectPoints, processedImagePoints; + int nFrames = (int)_counter.total(); + int markerCounter = 0; + for (int frame = 0; frame < nFrames; frame++) { + int nMarkersInThisFrame = _counter.getMat().ptr< int >()[frame]; + vector< Mat > thisFrameCorners; + vector< int > thisFrameIds; + thisFrameCorners.reserve(nMarkersInThisFrame); + thisFrameIds.reserve(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, thisFrameIds, thisFrameCorners, currentImgPoints, + currentObjPoints); + if (currentImgPoints.total() > 0 && currentObjPoints.total() > 0) { + processedImagePoints.push_back(currentImgPoints); + processedObjectPoints.push_back(currentObjPoints); + } + } + + return calibrateCamera(processedObjectPoints, processedImagePoints, imageSize, _cameraMatrix, + _distCoeffs, _rvecs, _tvecs, flags, criteria); + } + + /** + */ + void CharucoBoard::draw(Size outSize, OutputArray _img, int marginSize, int borderBits) { + + CV_Assert(outSize.area() > 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::drawPlanarBoard((*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); + } + } + } + + + + /** + */ + CharucoBoard CharucoBoard::create(int squaresX, int squaresY, float squareLength, + float markerLength, Dictionary dictionary) { + + CV_Assert(squaresX > 1 && squaresY > 1 && markerLength > 0 && squareLength > markerLength); + CharucoBoard res; + + 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) < 0.0001) { + // 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 unsigned int _filterCornersWithoutMinMarkers(const CharucoBoard &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().ptr< int >(0)[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().ptr< int >(0)[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().ptr< Point2f >(0)[i]); + } + } + + // parse output + _filteredCharucoCorners.create((int)filteredCharucoCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredCharucoCorners.size(); i++) { + _filteredCharucoCorners.getMat().ptr< Point2f >(0)[i] = filteredCharucoCorners[i]; + } + + _filteredCharucoIds.create((int)filteredCharucoIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredCharucoIds.size(); i++) { + _filteredCharucoIds.getMat().ptr< int >(0)[i] = filteredCharucoIds[i]; + } + + return (unsigned int)filteredCharucoCorners.size(); + } + + + /** + * 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, DetectorParameters *_params) + : grey(_grey), filteredChessboardImgPoints(_filteredChessboardImgPoints), + filteredWinSizes(_filteredWinSizes), params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + + + /** + * @brief From all projected chessboard corners, select those inside the image and apply subpixel + * refinement. Returns number of valid corners. + */ + static unsigned 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().ptr< Point2f >(0)[i])) { + filteredChessboardImgPoints.push_back(_allCorners.getMat().ptr< Point2f >(0)[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.getMat().type() == CV_8UC3) + cvtColor(_image.getMat(), grey, COLOR_BGR2GRAY); + else + _image.getMat().copyTo(grey); + + DetectorParameters params; // 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, ¶ms)); + + // parse output + _selectedCorners.create((int)filteredChessboardImgPoints.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredChessboardImgPoints.size(); i++) { + _selectedCorners.getMat().ptr< Point2f >(0)[i] = filteredChessboardImgPoints[i]; + } + + _selectedIds.create((int)filteredIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredIds.size(); i++) { + _selectedIds.getMat().ptr< int >(0)[i] = filteredIds[i]; + } + + return (unsigned 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 CharucoBoard &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().ptr< Point2f >(0)[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().ptr< int >(0)[k] == markerId) { + markerIdx = k; + break; + } + } + if (markerIdx == -1) continue; + Point2f markerCorner = + markerCorners.getMat(markerIdx).ptr< Point2f >(0)[board.nearestMarkerCorners[i][j]]; + Point2f charucoCorner = charucoCorners.getMat().ptr< Point2f >(0)[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 CharucoBoard &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; + detectedBoardMarkers = + aruco::estimatePoseBoard(_markerCorners, _markerIds, board, _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 + unsigned int nRefinedCorners; + nRefinedCorners = _selectAndRefineChessboardCorners( + allChessboardImgPoints, _image, _charucoCorners, _charucoIds, subPixWinSizes); + + // to return a charuco corner, its two closes aruco markers should have been detected + nRefinedCorners = _filterCornersWithoutMinMarkers(board, _charucoCorners, _charucoIds, + _markerIds, 2, _charucoCorners, _charucoIds); + + return nRefinedCorners; + } + + + + /** + * Interpolate charuco corners using local homography + */ + static int _interpolateCornersCharucoLocalHom(InputArrayOfArrays _markerCorners, + InputArray _markerIds, InputArray _image, + const CharucoBoard &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().ptr< int >(0)[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(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().ptr< int >(0)[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 + unsigned int nRefinedCorners; + nRefinedCorners = _selectAndRefineChessboardCorners( + allChessboardImgPoints, _image, _charucoCorners, _charucoIds, subPixWinSizes); + + // to return a charuco corner, its two closes aruco markers should have been detected + nRefinedCorners = _filterCornersWithoutMinMarkers(board, _charucoCorners, _charucoIds, + _markerIds, 2, _charucoCorners, _charucoIds); + + return nRefinedCorners; + } + + + + /** + */ + int interpolateCornersCharuco(InputArrayOfArrays _markerCorners, InputArray _markerIds, + InputArray _image, const CharucoBoard &board, + OutputArray _charucoCorners, OutputArray _charucoIds, + InputArray _cameraMatrix, InputArray _distCoeffs) { + + // if camera parameters are avaible, use approximated calibration + if (_cameraMatrix.total() != 0) { + return _interpolateCornersCharucoApproxCalib(_markerCorners, _markerIds, _image, board, + _cameraMatrix, _distCoeffs, _charucoCorners, + _charucoIds); + } + // else use local homography + else { + return _interpolateCornersCharucoLocalHom(_markerCorners, _markerIds, _image, board, + _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().ptr< Point2f >(0)[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().ptr< int >(0)[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, + CharucoBoard &board, InputArray _cameraMatrix, InputArray _distCoeffs, + OutputArray _rvec, OutputArray _tvec) { + + 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().ptr< int >(0)[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); + + return true; + } + + + + + /** + */ + double calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds, + const CharucoBoard &board, Size imageSize, + InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, 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).ptr< int >(0)[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, 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 = 0.12f; + + // create Charuco board layout for diamond (3x3 layout) + CharucoBoard charucoDiamondLayout; + Dictionary dict = getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME(0)); + 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.getMat().type() == CV_8UC3) + cvtColor(_image.getMat(), grey, COLOR_BGR2GRAY); + else + _image.getMat().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++) { + perimeterSq += + (corners.ptr< Point2f >()[c].x - corners.ptr< Point2f >()[(c + 1) % 4].x) * + (corners.ptr< Point2f >()[c].x - corners.ptr< Point2f >()[(c + 1) % 4].x) + + (corners.ptr< Point2f >()[c].y - corners.ptr< Point2f >()[(c + 1) % 4].y) * + (corners.ptr< Point2f >()[c].y - corners.ptr< Point2f >()[(c + 1) % 4].y); + } + // maximum reprojection error relative to perimeter + float minRepDistance = perimeterSq * minRepDistanceRate * minRepDistanceRate; + + int currentId = _markerIds.getMat().ptr< 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; + aruco::refineDetectedMarkers(grey, charucoDiamondLayout, 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().ptr< 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 + _diamondIds.create((int)diamondIds.size(), 1, CV_32SC4); + for (unsigned int i = 0; i < diamondIds.size(); i++) + _diamondIds.getMat().ptr< Vec4i >(0)[i] = diamondIds[i]; + + _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).ptr< Point2f >()[j] = diamondCorners[i][j]; + } + } + } + } + + + + + /** + */ + void drawCharucoDiamond(Dictionary 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 + CharucoBoard 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.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 composed by four numbers + 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< Vec4i >(0)[i]; + putText(_image, s.str(), cent, FONT_HERSHEY_SIMPLEX, 0.5, textColor, 2); + } + } + } + + + /** + */ + Dictionary::Dictionary(const Mat &_bytesList, int _markerSize, int _maxcorr) { + markerSize = _markerSize; + maxCorrectionBits = _maxcorr; + bytesList = _bytesList; + } + + + + /** + */ + 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); + 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 &getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name) { + switch (name) { + + case DICT_ARUCO_ORIGINAL: + return DICT_ARUCO_DATA; + + case DICT_4X4_50: + return DICT_4X4_50_DATA; + case DICT_4X4_100: + return DICT_4X4_100_DATA; + case DICT_4X4_250: + return DICT_4X4_250_DATA; + case DICT_4X4_1000: + return DICT_4X4_1000_DATA; + + case DICT_5X5_50: + return DICT_5X5_50_DATA; + case DICT_5X5_100: + return DICT_5X5_100_DATA; + case DICT_5X5_250: + return DICT_5X5_250_DATA; + case DICT_5X5_1000: + return DICT_5X5_1000_DATA; + + case DICT_6X6_50: + return DICT_6X6_50_DATA; + case DICT_6X6_100: + return DICT_6X6_100_DATA; + case DICT_6X6_250: + return DICT_6X6_250_DATA; + case DICT_6X6_1000: + return DICT_6X6_1000_DATA; + + case DICT_7X7_50: + return DICT_7X7_50_DATA; + case DICT_7X7_100: + return DICT_7X7_100_DATA; + case DICT_7X7_250: + return DICT_7X7_250_DATA; + case DICT_7X7_1000: + return DICT_7X7_1000_DATA; + + } + return DICT_4X4_50_DATA; + } + + + /** + * @brief Generates a random marker Mat of size markerSize x markerSize + */ + static Mat _generateRandomMarker(int markerSize) { + 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 = rand() % 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; + } + + /** + */ + Dictionary generateCustomDictionary(int nMarkers, int markerSize, + const Dictionary &baseDictionary) { + + Dictionary out; + 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); + + 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; + } + + } +} diff --git a/mono/src/main.cpp b/mono/src/main.cpp new file mode 100644 index 0000000..269fcd2 --- /dev/null +++ b/mono/src/main.cpp @@ -0,0 +1,139 @@ +/////////////////////////////////////////////////////////////////////////// +// +// Copyright (c) 2019, STEREOLABS. +// +// All rights reserved. +// +// 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 COPYRIGHT +// OWNER 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. +// +/////////////////////////////////////////////////////////////////////////// + +/*********************************************************************************************** + ** This sample demonstrates how to reloc a ZED camera using an ArUco marker. ** + ** Images are captured with the ZED SDK and cameras poses is then computed from ArUco pattern ** + ** to reset ZED tracking with this known position. ** + ***********************************************************************************************/ + +// ZED includes +#include + +// Sample includes +#include "aruco.hpp" + +// OCV includes +#include + +using namespace sl; +using namespace std; + +int main(int argc, char **argv) { + + // Create a ZED camera object + Camera zed; + + // Set configuration parameters + InitParameters init_params; + init_params.camera_resolution = RESOLUTION_HD720; + init_params.coordinate_units = UNIT_METER; + init_params.camera_disable_imu = true; // for this sample, IMU (of ZED-M) is disable, we use the gravity given by the marker. + + // Open the camera + ERROR_CODE err = zed.open(init_params); + if (err != SUCCESS) { + cout << "Error, unable to open ZED camera: " << err << "\n"; + zed.close(); + return 1; // Quit if an error occurred + } + + Resolution image_size = zed.getResolution(); + Mat image_zed(image_size, MAT_TYPE_8U_C4); + cv::Mat image_ocv = cv::Mat(image_zed.getHeight(), image_zed.getWidth(), CV_8UC4, image_zed.getPtr(MEM_CPU)); + cv::Mat image_ocv_rgb; + + auto calibInfo = zed.getCameraInformation().calibration_parameters.left_cam; + cv::Matx33d camera_matrix = cv::Matx33d::eye(); + camera_matrix(0, 0) = calibInfo.fx; + camera_matrix(1, 1) = calibInfo.fy; + camera_matrix(0, 2) = calibInfo.cx; + camera_matrix(1, 2) = calibInfo.cy; + + cv::Matx dist_coeffs = cv::Vec4f::zeros(); + + float actual_marker_size_meters = 0.16f; // real marker size in meters + auto dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_100); + + cout << "Make sure the ArUco marker is a 6x6 (100), measuring " << actual_marker_size_meters * 1000 << " mm" << endl; + + Transform pose; + Pose zed_pose; + vector rvecs, tvecs; + vector ids; + vector > corners; + string position_txt; + + bool can_reset = false; + + zed.enableTracking(); + + // Loop until 'q' is pressed + char key = '.'; + while (key != 'q') { + if (zed.grab() == SUCCESS) { + // Retrieve the left image + zed.retrieveImage(image_zed, VIEW_LEFT, MEM_CPU, image_size.width, image_size.height); + + // convert to RGB + cv::cvtColor(image_ocv, image_ocv_rgb, cv::COLOR_RGBA2RGB); + // detect marker + cv::aruco::detectMarkers(image_ocv_rgb, dictionary, corners, ids); + + // get actual ZED position + zed.getPosition(zed_pose); + + // display ZED position + cv::rectangle(image_ocv_rgb, cv::Point(0, 0), cv::Point(490, 75), cv::Scalar(0, 0, 0), -1); + cv::putText(image_ocv_rgb, "Loaded dictionary : 6x6. Press 'SPACE' to reset the camera position", cv::Point(10, 15), cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(220, 220, 220)); + position_txt = "ZED x: " + to_string(zed_pose.pose_data.tx) + "; y: " + to_string(zed_pose.pose_data.ty) + "; z: " + to_string(zed_pose.pose_data.tz); + cv::putText(image_ocv_rgb, position_txt, cv::Point(10, 35), cv::FONT_HERSHEY_SIMPLEX, 0.6, cv::Scalar(236, 188, 26)); + + // if at least one marker detected + if (ids.size() > 0) { + cv::aruco::estimatePoseSingleMarkers(corners, actual_marker_size_meters, camera_matrix, dist_coeffs, rvecs, tvecs); + pose.setTranslation(sl::float3(tvecs[0](0), tvecs[0](1), tvecs[0](2))); + pose.setRotationVector(sl::float3(rvecs[0](0), rvecs[0](1), rvecs[0](2))); + pose.inverse(); + can_reset = true; + + cv::aruco::drawDetectedMarkers(image_ocv_rgb, corners, ids); + cv::aruco::drawAxis(image_ocv_rgb, camera_matrix, dist_coeffs, rvecs[0], tvecs[0], actual_marker_size_meters * 0.5f); + position_txt = "Aruco x: " + to_string(pose.tx) + "; y: " + to_string(pose.ty) + "; z: " + to_string(pose.tz); + cv::putText(image_ocv_rgb, position_txt, cv::Point(10, 60), cv::FONT_HERSHEY_SIMPLEX, 0.6, cv::Scalar(124, 252, 124)); + + } else + can_reset = false; + + // Display image + cv::imshow("Image", image_ocv_rgb); + + // Handle key event + key = cv::waitKey(10); + + // if KEY_R is pressed and aruco marker is visible, then reset ZED position + if ((key == ' ') && can_reset) + zed.resetTracking(pose); + } + } + zed.close(); + return 0; + +} \ No newline at end of file diff --git a/multi-camera/CMakeLists.txt b/multi-camera/CMakeLists.txt new file mode 100644 index 0000000..4a806fe --- /dev/null +++ b/multi-camera/CMakeLists.txt @@ -0,0 +1,63 @@ +SET(ProjectName ZED_Multi_Reloc_Aruco) +cmake_minimum_required(VERSION 3.0) +PROJECT(${ProjectName}) + +option(LINK_SHARED_ZED "Link with the ZED SDK shared executable" ON) + +if (NOT LINK_SHARED_ZED AND MSVC) + message(FATAL_ERROR "LINK_SHARED_ZED OFF : ZED SDK static libraries not available on Windows") +endif() + +if(COMMAND cmake_policy) + cmake_policy(SET CMP0003 OLD) + cmake_policy(SET CMP0015 OLD) +endif(COMMAND cmake_policy) + +SET(EXECUTABLE_OUTPUT_PATH ".") + + +find_package(ZED 2 REQUIRED) +find_package(GLUT REQUIRED) +find_package(GLEW REQUIRED) +find_package(OpenCV REQUIRED) +find_package(OpenGL REQUIRED) +find_package(CUDA ${ZED_CUDA_VERSION} EXACT REQUIRED) + +include_directories(${ZED_INCLUDE_DIRS}) +include_directories(${GLEW_INCLUDE_DIRS}) +include_directories(${GLUT_INCLUDE_PATH}) +include_directories(${CUDA_INCLUDE_DIRS}) +include_directories(${OPENCV_INCLUDE_DIRS}) +include_directories(${CMAKE_CURRENT_SOURCE_DIR}/include) + +link_directories(${ZED_LIBRARY_DIR}) +link_directories(${GLEW_LIBRARY_DIRS}) +link_directories(${GLUT_LIBRARY_DIRS}) +link_directories(${OpenCV_LIBRARY_DIRS}) +link_directories(${OpenGL_LIBRARY_DIRS}) +link_directories(${CUDA_LIBRARY_DIRS}) + +IF(NOT WIN32) + SET(SPECIAL_OS_LIBS "pthread") +ENDIF() + +FILE(GLOB_RECURSE SRC_FILES src/*.cpp) +FILE(GLOB_RECURSE HDR_FILES include/*.hpp) + +ADD_EXECUTABLE(${ProjectName} ${HDR_FILES} ${SRC_FILES}) +add_definitions(-std=c++11 -O3 -fpermissive) + +if (LINK_SHARED_ZED) + SET(ZED_LIBS ${ZED_LIBRARIES} ${CUDA_CUDA_LIBRARY} ${CUDA_CUDART_LIBRARY} ${CUDA_NPP_LIBRARIES_ZED}) +else() + SET(ZED_LIBS ${ZED_STATIC_LIBRARIES} ${CUDA_CUDA_LIBRARY} ${CUDA_LIBRARY}) +endif() + +TARGET_LINK_LIBRARIES(${ProjectName} + ${SPECIAL_OS_LIBS} + ${ZED_LIBS} + ${OpenCV_LIBRARIES} + ${OPENGL_LIBRARIES} + ${GLUT_LIBRARY} + ${GLEW_LIBRARY}) + diff --git a/multi-camera/README.md b/multi-camera/README.md new file mode 100644 index 0000000..0e9c3a1 --- /dev/null +++ b/multi-camera/README.md @@ -0,0 +1,60 @@ +# Stereolabs ZED - ArUco Multi ZED camera sample + +This sample shows how calibrates multiples ZED camera using an ArUco marker. + +![http://chev.me/arucogen/](../6x6_1000-25.png) + +Point all the ZED cameras to this marker to start the sample. Once detected, the global reference frame is computed and all the ZED cameras position are estimated. +The point cloud of every camera is then displayed in the same referential. + +To reset the position, press the space bar and point the cameras to the marker. + +## Getting started + +- First, download the latest version of the ZED SDK on [stereolabs.com](https://www.stereolabs.com). +- For more information, read the ZED [API documentation](https://www.stereolabs.com/developers/documentation/API/). + +### Prerequisites + +- Windows 7 64bits or later, Ubuntu 16.04 or later +- [ZED SDK](https://www.stereolabs.com/developers/) and its dependencies ([CUDA](https://developer.nvidia.com/cuda-downloads)) + +## Build the program + +Download the sample and follow the instructions below: [More](https://www.stereolabs.com/docs/getting-started/application-development/) + +### Build for Windows + +- Create a "build" folder in the source folder +- Open cmake-gui and select the source and build folders +- Generate the Visual Studio `Win64` solution +- Open the resulting solution and change configuration to `Release` +- Build solution + +### Build for Linux + +Open a terminal in the sample directory and execute the following command: + + mkdir build + cd build + cmake .. + make + +## Run the program + +- Navigate to the build directory and launch the executable file +- Or open a terminal in the build directory and run the sample : + + ./ZED_Multi_Reloc_Aruco + + +## ArUco markers + +This [website](http://chev.me/arucogen/) can be used to easily display Aruco patterns. + +The sample is expecting a `6x6 Aruco` Dictionary with a 160mm marker by default. The bigger the marker, the better the camera position will be. +It's important to make sure that the real-world size of the marker matches the size set in the samples (160mm) to avoid scale issues in the tracking. + +## ArUco detection + +The Aruco detection code is taken from OpenCV Contrib module, please refer to the source files for the license information (BSD 3). diff --git a/multi-camera/include/GLViewer.hpp b/multi-camera/include/GLViewer.hpp new file mode 100644 index 0000000..2c8f4f9 --- /dev/null +++ b/multi-camera/include/GLViewer.hpp @@ -0,0 +1,287 @@ +#ifndef __VIEWER_INCLUDE__ +#define __VIEWER_INCLUDE__ + +#include +#include +#include + +#include + +#include +#include +#include +#include /* OpenGL Utility Toolkit header */ + +#include +#include +#include + +#ifndef M_PI +#define M_PI 3.141592653f +#endif + +#define SAFE_DELETE( res ) if( res!=NULL ) { delete res; res = NULL; } + +#define MOUSE_R_SENSITIVITY 0.015f +#define MOUSE_UZ_SENSITIVITY 0.75f +#define MOUSE_DZ_SENSITIVITY 1.25f +#define MOUSE_T_SENSITIVITY 0.1f +#define KEY_T_SENSITIVITY 0.1f + +class CameraGL { +public: + + CameraGL() { + } + + enum DIRECTION { + UP, DOWN, LEFT, RIGHT, FORWARD, BACK + }; + CameraGL(sl::Translation position, sl::Translation direction, sl::Translation vertical = sl::Translation(0, 1, 0)); // vertical = Eigen::Vector3f(0, 1, 0) + ~CameraGL(); + + void update(); + void setProjection(float horizontalFOV, float verticalFOV, float znear, float zfar); + const sl::Transform& getViewProjectionMatrix() const; + + float getHorizontalFOV() const; + float getVerticalFOV() const; + + // Set an offset between the eye of the camera and its position + // Note: Useful to use the camera as a trackball camera with z>0 and x = 0, y = 0 + // Note: coordinates are in local space + void setOffsetFromPosition(const sl::Translation& offset); + const sl::Translation& getOffsetFromPosition() const; + + void setDirection(const sl::Translation& direction, const sl::Translation &vertical); + void translate(const sl::Translation& t); + void setPosition(const sl::Translation& p); + void rotate(const sl::Orientation& rot); + void rotate(const sl::Rotation& m); + void setRotation(const sl::Orientation& rot); + void setRotation(const sl::Rotation& m); + + const sl::Translation& getPosition() const; + const sl::Translation& getForward() const; + const sl::Translation& getRight() const; + const sl::Translation& getUp() const; + const sl::Translation& getVertical() const; + float getZNear() const; + float getZFar() const; + + static const sl::Translation ORIGINAL_FORWARD; + static const sl::Translation ORIGINAL_UP; + static const sl::Translation ORIGINAL_RIGHT; + + sl::Transform projection_; +private: + void updateVectors(); + void updateView(); + void updateVPMatrix(); + + sl::Translation offset_; + sl::Translation position_; + sl::Translation forward_; + sl::Translation up_; + sl::Translation right_; + sl::Translation vertical_; + + sl::Orientation rotation_; + + sl::Transform view_; + sl::Transform vpMatrix_; + float horizontalFieldOfView_; + float verticalFieldOfView_; + float znear_; + float zfar_; +}; + +class Shader { +public: + + Shader() { + } + Shader(GLchar* vs, GLchar* fs); + ~Shader(); + GLuint getProgramId(); + + static const GLint ATTRIB_VERTICES_POS = 0; + static const GLint ATTRIB_COLOR_POS = 1; +private: + bool compile(GLuint &shaderId, GLenum type, GLchar* src); + GLuint verterxId_; + GLuint fragmentId_; + GLuint programId_; +}; + +class Simple3DObject { +public: + + Simple3DObject() { + } + Simple3DObject(sl::Translation position, bool isStatic); + ~Simple3DObject(); + + void addPoint(float x, float y, float z, float r, float g, float b); + void pushToGPU(); + void clear(); + + void setDrawingType(GLenum type); + + void draw(); + + void translate(const sl::Translation& t); + void setPosition(const sl::Translation& p); + + void setRT(const sl::Transform& mRT); + + void rotate(const sl::Orientation& rot); + void rotate(const sl::Rotation& m); + void setRotation(const sl::Orientation& rot); + void setRotation(const sl::Rotation& m); + + const sl::Translation& getPosition() const; + + sl::Transform getModelMatrix() const; +private: + std::vector vertices_; + std::vector colors_; + std::vector indices_; + + bool isStatic_; + + GLenum drawingType_; + + GLuint vaoID_; + /* + Vertex buffer IDs: + - [0]: Vertices coordinates; + - [1]: RGB color values; + - [2]: Indices; + */ + GLuint vboID_[3]; + + sl::Translation position_; + sl::Orientation rotation_; + +}; + +class PointCloud { +public: + PointCloud(); + ~PointCloud(); + + // Initialize Opengl and Cuda buffers + // Warning: must be called in the Opengl thread + void initialize(unsigned int width, unsigned int height, CUcontext ctx); + // Push a new point cloud + // Warning: can be called from any thread but the mutex "mutexData" must be locked + void pushNewPC(sl::Mat &matXYZRGBA); + // Update the Opengl buffer + // Warning: must be called in the Opengl thread + void update(); + // Draw the point cloud + // Warning: must be called in the Opengl thread + void draw(const sl::Transform& vp); + // Close (disable update) + void close(); + + unsigned int getWidth(); + unsigned int getHeight(); + + bool lock; +private: + unsigned int width_ = 0; + unsigned int height_ = 0; + CUcontext cuda_zed_ctx; + + sl::Mat matGPU_; + bool hasNewPCL_ = false; + bool initialized_ = false; + Shader shader_; + GLuint shMVPMatrixLoc_; + size_t numBytes_; + float* xyzrgbaMappedBuf_; + GLuint bufferGLID_; + cudaGraphicsResource* bufferCudaID_; +}; + +// This class manages input events, window and Opengl rendering pipeline + +class GLViewer { +public: + GLViewer(); + ~GLViewer(); + void exit(); + bool isEnded(); + void init(int w, int h, int nb_pc); + void updatePointCloud(sl::Mat &matXYZRGBA, int id); + bool askReset(); + +private: + // Initialize OpenGL context and variables, and other Viewer's variables + void initialize(); + // Rendering loop method called each frame by glutDisplayFunc + void render(); + // Everything that needs to be updated before rendering must be done in this method + void update(); + // Once everything is updated, every renderable objects must be drawn in this method + void draw(); + // Clear and refresh inputs' data + void clearInputs(); + + static GLViewer* currentInstance_; + + // Glut functions callbacks + static void drawCallback(); + static void mouseButtonCallback(int button, int state, int x, int y); + static void mouseMotionCallback(int x, int y); + static void reshapeCallback(int width, int height); + static void keyPressedCallback(unsigned char c, int x, int y); + static void keyReleasedCallback(unsigned char c, int x, int y); + static void idle(); + + bool ended_; + // Color settings + float cr; + float cg; + float cb; + // Window size + int wnd_w; + int wnd_h; + + enum MOUSE_BUTTON { + LEFT = 0, + MIDDLE = 1, + RIGHT = 2, + WHEEL_UP = 3, + WHEEL_DOWN = 4 + }; + + enum KEY_STATE { + UP = 'u', + DOWN = 'd', + FREE = 'f' + }; + + bool mouseButton_[3]; + int mouseWheelPosition_; + int mouseCurrentPosition_[2]; + int mouseMotion_[2]; + int previousMouseMotion_[2]; + KEY_STATE keyStates_[256]; + + Simple3DObject axis_X; + Simple3DObject axis_Y; + Simple3DObject axis_Z; + std::vector pointCloud_; + bool user_action; + CameraGL camera_; + Shader shader_; + GLuint shMVPMatrixLoc_; + sl::Resolution res; + CUcontext ctx; + bool initialized_; +}; + +#endif /* __VIEWER_INCLUDE__ */ diff --git a/multi-camera/include/aruco.hpp b/multi-camera/include/aruco.hpp new file mode 100644 index 0000000..c9e70a2 --- /dev/null +++ b/multi-camera/include/aruco.hpp @@ -0,0 +1,20961 @@ +/* +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 + +/** +* @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 a 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. +* +* @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 { + + /** + * @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 Dictionary { + + public: + Mat bytesList; // marker code information + int markerSize; // number of bits per dimension + int maxCorrectionBits; // maximum number of bits that can be corrected + + + /** + */ + Dictionary(const Mat &_bytesList = Mat(), int _markerSize = 0, int _maxcorr = 0); + + + + /** + * @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 + */ + 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 + */ + static Mat getByteListFromBits(const Mat &bits); + + + /** + * @brief Transform list of bytes to matrix of bits + */ + 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: 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 + }; + + + /** + * @brief Returns one of the predefined dictionaries defined in PREDEFINED_DICTIONARY_NAME + */ + CV_EXPORTS const Dictionary &getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name); + + + /** + * @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) + * + * 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 Dictionary generateCustomDictionary(int nMarkers, int markerSize, + const Dictionary &baseDictionary = Dictionary()); + + + + + /** + * @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). + * - doCornerRefinement: do subpixel refinement or not + * - 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). + * - perpectiveRemovePixelPerCell: 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. perpectiveRemovePixelPerCell (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). + */ + struct CV_EXPORTS DetectorParameters { + + DetectorParameters(); + + int adaptiveThreshWinSizeMin; + int adaptiveThreshWinSizeMax; + int adaptiveThreshWinSizeStep; + double adaptiveThreshConstant; + double minMarkerPerimeterRate; + double maxMarkerPerimeterRate; + double polygonalApproxAccuracyRate; + double minCornerDistanceRate; + int minDistanceToBorder; + double minMarkerDistanceRate; + bool doCornerRefinement; + int cornerRefinementWinSize; + int cornerRefinementMaxIterations; + double cornerRefinementMinAccuracy; + int markerBorderBits; + int perspectiveRemovePixelPerCell; + double perspectiveRemoveIgnoredMarginPerCell; + double maxErroneousBitsInBorderRate; + double minOtsuStdDev; + double errorCorrectionRate; + }; + + + + /** + * @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. + * + * 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 void detectMarkers(InputArray image, Dictionary dictionary, OutputArrayOfArrays corners, + OutputArray ids, DetectorParameters parameters = DetectorParameters(), + OutputArrayOfArrays rejectedImgPoints = 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. + * + * 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 void estimatePoseSingleMarkers(InputArrayOfArrays corners, float markerLength, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs); + + + + /** + * @brief Board of markers + * + * A board is a set of markers in the 3D space with a common cordinate 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 Board { + + public: + // array of object points of all the marker corners in the board + // each marker include its 4 corners, i.e. for M markers, the size is Mx4 + std::vector< std::vector< Point3f > > objPoints; + + // the dictionary of markers employed for this board + Dictionary dictionary; + + // vector of the identifiers of the markers in the board (same size than objPoints) + // The identifiers refers to the board dictionary + 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 arrangment. + * The board can be drawn using drawPlanarBoard() function (@sa drawPlanarBoard) + */ + class CV_EXPORTS 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. + */ + 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 than markerLenght) + * @param dictionary dictionary of markers indicating the type of markers. + * The first markersX*markersY markers in the dictionary are used. + * @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. + */ + static GridBoard create(int markersX, int markersY, float markerLength, float markerSeparation, + Dictionary dictionary); + + /** + * + */ + Size getGridSize() const { return Size(_markersX, _markersY); } + + /** + * + */ + float getMarkerLength() const { return _markerLength; } + + /** + * + */ + 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 + * (@sa Rodrigues). + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * + * 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 int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, const Board &board, + InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, + OutputArray tvec); + + + + + /** + * @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 void refineDetectedMarkers( + InputArray image, const Board &board, InputOutputArrayOfArrays detectedCorners, + InputOutputArray detectedIds, InputOutputArray rejectedCorners, + InputArray cameraMatrix = noArray(), InputArray distCoeffs = noArray(), + float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true, + OutputArray recoveredIdxs = noArray(), DetectorParameters parameters = DetectorParameters()); + + + + /** + * @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 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. + */ + CV_EXPORTS 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 void drawMarker(Dictionary dictionary, int id, int sidePixels, OutputArray img, + int borderBits = 1); + + + + /** + * @brief Draw a planar board + * + * @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 void drawPlanarBoard(const 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 (@sa 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 flags flags Different flags for the calibration process (@sa calibrateCamera) + * @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 double calibrateCameraAruco( + InputArrayOfArrays corners, InputArray ids, InputArray counter, const Board &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 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 CharucoBoard : public Board { + + public: + // vector of chessboard 3D corners precalculated + std::vector< Point3f > chessboardCorners; + + // for each charuco corner, nearest marker id and nearest marker corner id of each marker + std::vector< std::vector< int > > nearestMarkerIdx; + 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. + */ + 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. + */ + static CharucoBoard create(int squaresX, int squaresY, float squareLength, float markerLength, + Dictionary dictionary); + + /** + * + */ + Size getChessboardSize() const { return Size(_squaresX, _squaresY); } + + /** + * + */ + float getSquareLength() const { return _squareLength; } + + /** + * + */ + 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 + * + * 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 int interpolateCornersCharuco(InputArrayOfArrays markerCorners, InputArray markerIds, + InputArray image, const CharucoBoard &board, + OutputArray charucoCorners, OutputArray charucoIds, + InputArray cameraMatrix = noArray(), + InputArray distCoeffs = noArray()); + + /** + * @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 + * (@sa Rodrigues). + * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board. + * + * 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 bool estimatePoseCharucoBoard(InputArray charucoCorners, InputArray charucoIds, + CharucoBoard &board, InputArray cameraMatrix, + InputArray distCoeffs, OutputArray rvec, OutputArray tvec); + + /** + * @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 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 flags flags Different flags for the calibration process (@sa calibrateCamera) + * @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 double calibrateCameraCharuco( + InputArrayOfArrays charucoCorners, InputArrayOfArrays charucoIds, const CharucoBoard &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 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 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. + */ + CV_EXPORTS void drawCharucoDiamond(Dictionary dictionary, Vec4i ids, int squareLength, + int markerLength, OutputArray img, int marginSize = 0, + int borderBits = 1); + + + 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 }, + { 112, 92, 16, 1 }, + { 93, 41, 64, 0 }, }, + { { 132, 29, 120, 0 }, + { 17, 140, 77, 1 }, + { 15, 92, 16, 1 }, + { 217, 24, 196, 0 }, }, + { { 132, 29, 123, 1 }, + { 25, 206, 77, 1 }, + { 239, 92, 16, 1 }, + { 217, 57, 204, 0 }, }, + { { 132, 29, 116, 1 }, + { 25, 140, 93, 0 }, + { 151, 92, 16, 1 }, + { 93, 24, 204, 0 }, }, + { { 132, 29, 119, 0 }, + { 17, 206, 93, 0 }, + { 119, 92, 16, 1 }, + { 93, 57, 196, 0 }, }, + { { 132, 28, 152, 0 }, + { 17, 8, 108, 1 }, + { 12, 156, 16, 1 }, + { 155, 8, 68, 0 }, }, + { { 132, 28, 155, 1 }, + { 25, 74, 108, 1 }, + { 236, 156, 16, 1 }, + { 155, 41, 76, 0 }, }, + { { 132, 28, 148, 1 }, + { 25, 8, 124, 0 }, + { 148, 156, 16, 1 }, + { 31, 8, 76, 0 }, }, + { { 132, 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{ { 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 }, }, + { { 102, 0 }, + { 12, 192 }, + { 0, 102 }, + { 3, 48 }, }, + { { 108, 94 }, + { 41, 245 }, + { 122, 54 }, + { 175, 148 }, }, + { { 118, 175 }, + { 159, 211 }, + { 245, 110 }, + { 203, 249 }, }, + { { 134, 139 }, + { 21, 75 }, + { 209, 97 }, + { 210, 168 }, }, + { { 176, 43 }, + { 155, 9 }, + { 212, 13 }, + { 144, 217 }, }, + { { 204, 213 }, + { 48, 254 }, + { 171, 51 }, + { 127, 12 }, }, + { { 221, 130 }, + { 193, 206 }, + { 65, 187 }, + { 115, 131 }, }, + { { 254, 71 }, + { 157, 252 }, + { 226, 127 }, + { 63, 185 }, }, + { { 148, 113 }, + { 178, 104 }, + { 142, 41 }, + { 22, 77 }, }, + { { 172, 228 }, + { 10, 126 }, + { 39, 53 }, + { 126, 80 }, }, + { { 165, 84 }, + { 104, 120 }, + { 42, 165 }, + { 30, 22 }, }, + { { 33, 35 }, + { 91, 0 }, + { 196, 132 }, + { 0, 218 }, }, + { { 52, 111 }, + { 155, 113 }, + { 246, 44 }, + { 142, 217 }, }, + { { 68, 21 }, + { 48, 208 }, + { 168, 34 }, + { 11, 12 }, }, + { { 87, 178 }, + { 231, 194 }, + { 77, 234 }, + { 67, 231 }, }, + { { 158, 207 }, + { 149, 127 }, + { 243, 121 }, + { 254, 169 }, }, + { { 240, 203 }, + { 153, 171 }, + { 211, 15 }, + { 213, 153 }, }, + { { 8, 174 }, + { 3, 23 }, + { 117, 16 }, + { 232, 192 }, }, + { { 9, 41 }, + { 82, 5 }, + { 148, 144 }, + { 160, 74 }, }, + { { 24, 117 }, + { 178, 52 }, + { 174, 24 }, + { 44, 77 }, }, + { { 4, 255 }, + { 51, 115 }, + { 255, 32 }, + { 206, 204 }, }, + { { 13, 246 }, + { 99, 118 }, + { 111, 176 }, + { 110, 198 }, }, + { { 28, 90 }, + { 161, 101 }, + { 90, 56 }, + { 166, 133 }, }, + { { 23, 24 }, + { 228, 65 }, + { 24, 232 }, + { 130, 39 }, }, + { { 42, 40 }, + { 14, 5 }, + { 20, 84 }, + { 160, 112 }, }, + { { 50, 140 }, + { 140, 19 }, + { 49, 76 }, + { 200, 49 }, }, + { { 56, 178 }, + { 171, 6 }, + { 77, 28 }, + { 96, 213 }, }, + { { 36, 232 }, + { 10, 99 }, + { 23, 36 }, + { 198, 80 }, }, + { { 46, 235 }, + { 31, 103 }, + { 215, 116 }, + { 230, 248 }, }, + { { 45, 63 }, + { 123, 85 }, + { 252, 180 }, + { 170, 222 }, }, + { { 75, 100 }, + { 70, 180 }, + { 38, 210 }, + { 45, 98 }, }, + { { 80, 46 }, + { 131, 145 }, + { 116, 10 }, + { 137, 193 }, }, + { { 80, 19 }, + { 177, 128 }, + { 200, 10 }, + { 1, 141 }, }, + { { 81, 148 }, + { 224, 146 }, + { 41, 138 }, + { 73, 7 }, }, + { { 85, 104 }, + { 194, 225 }, + { 22, 170 }, + { 135, 67 }, }, + { { 93, 65 }, + { 208, 228 }, + { 130, 186 }, + { 39, 11 }, }, + { { 95, 151 }, + { 245, 214 }, + { 233, 250 }, + { 107, 175 }, }, + { { 104, 1 }, + { 24, 132 }, + { 128, 22 }, + { 33, 24 }, }, + { { 104, 103 }, + { 27, 180 }, + { 230, 22 }, + { 45, 216 }, }, + { { 97, 36 }, + { 74, 144 }, + { 36, 134 }, + { 9, 82 }, }, + { { 97, 233 }, + { 90, 163 }, + { 151, 134 }, + { 197, 90 }, }, + { { 107, 18 }, + { 109, 132 }, + { 72, 214 }, 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}, + { 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, 0 }, + { 149, 179, 77, 1 }, + { 46, 84, 95, 1 }, }, + { { 221, 94, 185, 1 }, + { 253, 217, 108, 1 }, + { 206, 189, 93, 1 }, + { 155, 77, 223, 1 }, }, + { { 244, 234, 25, 0 }, + { 118, 105, 14, 1 }, + { 76, 43, 151, 1 }, + { 184, 75, 55, 0 }, }, + { { 243, 178, 148, 0 }, + { 54, 49, 250, 0 }, + { 20, 166, 231, 1 }, + { 47, 198, 54, 0 }, }, + { { 122, 186, 5, 0 }, + { 166, 105, 210, 0 }, + { 80, 46, 175, 0 }, + { 37, 203, 50, 1 }, }, + { { 216, 141, 41, 1 }, + { 143, 201, 9, 1 }, + { 202, 88, 141, 1 }, + { 200, 73, 248, 1 }, }, + { { 12, 103, 50, 1 }, + { 249, 130, 7, 0 }, + { 166, 115, 24, 0 }, + { 112, 32, 207, 1 }, }, + { { 21, 89, 12, 1 }, + { 76, 24, 85, 1 }, + { 152, 77, 84, 0 }, + { 213, 12, 25, 0 }, }, + { { 76, 116, 192, 1 }, + { 201, 5, 102, 0 }, + { 129, 151, 25, 0 }, + { 51, 80, 73, 1 }, }, + { { 84, 3, 14, 0 }, + { 36, 3, 21, 1 }, + { 56, 96, 21, 0 }, + { 212, 96, 18, 0 }, }, + { { 160, 208, 172, 0 }, + { 66, 160, 120, 1 }, + { 26, 133, 130, 1 }, + { 143, 2, 161, 0 }, }, + { { 194, 152, 166, 0 }, + { 2, 139, 248, 0 }, + { 50, 140, 161, 1 }, + { 15, 232, 160, 0 }, }, + { { 203, 104, 150, 0 }, + { 208, 27, 186, 0 }, + { 52, 139, 105, 1 }, + { 46, 236, 5, 1 }, }, + { { 253, 105, 209, 0 }, + { 212, 125, 47, 0 }, + { 69, 203, 95, 1 }, + { 122, 95, 21, 1 }, }, + { { 4, 145, 90, 1 }, + { 26, 6, 69, 1 }, + { 173, 68, 144, 0 }, + { 209, 48, 44, 0 }, }, + { { 12, 222, 112, 0 }, + { 243, 140, 68, 0 }, + { 7, 61, 152, 0 }, + { 17, 24, 231, 1 }, }, + { { 5, 170, 62, 0 }, + { 50, 154, 22, 1 }, + { 62, 42, 208, 0 }, + { 180, 44, 166, 0 }, }, + { { 1, 99, 183, 1 }, + { 120, 210, 51, 0 }, + { 246, 227, 64, 0 }, + { 102, 37, 143, 0 }, }, + { { 9, 145, 68, 1 }, + { 138, 20, 81, 0 }, + { 145, 68, 200, 0 }, + { 69, 20, 40, 1 }, }, + { { 9, 105, 83, 1 }, + { 216, 94, 3, 0 }, + { 229, 75, 72, 0 }, + { 96, 61, 13, 1 }, }, + { { 6, 37, 161, 1 }, + { 9, 192, 167, 0 }, + { 194, 210, 48, 0 }, + { 114, 129, 200, 0 }, }, + { { 3, 61, 226, 1 }, + { 9, 158, 227, 0 }, + { 163, 222, 96, 0 }, + { 99, 188, 200, 0 }, }, + { { 7, 213, 6, 1 }, + { 75, 18, 213, 0 }, + { 176, 85, 240, 0 }, + { 85, 164, 105, 0 }, }, + { { 15, 143, 170, 0 }, + { 163, 154, 165, 1 }, + { 42, 248, 248, 0 }, + { 210, 172, 226, 1 }, }, + { { 28, 116, 60, 1 }, + { 221, 128, 86, 1 }, + { 158, 23, 28, 0 }, + { 181, 0, 221, 1 }, }, + { { 25, 29, 145, 1 }, + { 157, 88, 97, 0 }, + { 196, 220, 76, 0 }, + { 67, 13, 92, 1 }, }, + { { 22, 27, 35, 1 }, + { 44, 202, 197, 0 }, + { 226, 108, 52, 0 }, + { 81, 169, 154, 0 }, }, + { { 22, 210, 141, 1 }, + { 110, 64, 244, 1 }, + { 216, 165, 180, 0 }, + { 151, 129, 59, 0 }, }, + { { 23, 78, 198, 1 }, + { 109, 30, 180, 0 }, + { 177, 185, 116, 0 }, + { 22, 188, 91, 0 }, }, + { { 19, 226, 177, 0 }, + { 118, 208, 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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, 84, 58, 51, 8 }, }, + { { 196, 195, 36, 37, 9 }, + { 140, 7, 27, 134, 4 }, + { 154, 66, 76, 50, 3 }, + { 38, 29, 142, 3, 1 }, }, + { { 197, 169, 27, 216, 13 }, + { 149, 98, 213, 218, 10 }, + { 177, 189, 137, 90, 3 }, + { 85, 186, 180, 106, 9 }, }, + { { 206, 115, 230, 178, 12 }, + { 227, 199, 203, 131, 7 }, + { 52, 214, 124, 231, 3 }, + { 236, 29, 62, 60, 7 }, }, + { { 205, 12, 166, 39, 2 }, + { 138, 209, 2, 230, 13 }, + { 78, 70, 83, 11, 3 }, + { 182, 116, 8, 181, 1 }, }, + { { 201, 67, 93, 68, 13 }, + { 62, 7, 77, 218, 0 }, + { 178, 43, 172, 41, 3 }, + { 5, 187, 46, 7, 12 }, }, + { { 207, 190, 128, 243, 4 }, + { 195, 128, 218, 239, 11 }, + { 44, 240, 23, 223, 3 }, + { 223, 117, 176, 28, 3 }, }, + { { 229, 125, 21, 135, 7 }, + { 221, 23, 96, 246, 11 }, + { 238, 26, 139, 234, 7 }, + { 214, 240, 110, 139, 11 }, }, + { { 239, 198, 133, 142, 9 }, + { 158, 165, 57, 227, 3 }, + { 151, 26, 22, 63, 7 }, + { 204, 121, 202, 87, 9 }, }, + { { 247, 126, 243, 119, 2 }, + { 249, 220, 170, 255, 13 }, + { 78, 236, 247, 238, 15 }, + { 191, 245, 83, 185, 15 }, }, + { { 44, 228, 63, 37, 4 }, + { 155, 69, 118, 52, 4 }, + { 42, 79, 194, 115, 4 }, + { 34, 198, 234, 45, 9 }, }, + { { 43, 220, 255, 75, 3 }, + { 118, 245, 52, 125, 13 }, + { 205, 47, 243, 189, 4 }, + { 187, 226, 202, 246, 14 }, }, + { { 55, 199, 221, 189, 10 }, + { 184, 191, 191, 117, 2 }, + { 91, 219, 190, 62, 12 }, + { 74, 239, 223, 209, 13 }, }, + { { 161, 162, 84, 224, 15 }, + { 37, 17, 123, 90, 2 }, + { 240, 114, 164, 88, 5 }, + { 69, 173, 232, 138, 4 }, }, + { { 169, 130, 193, 187, 5 }, + { 54, 160, 250, 70, 3 }, + { 173, 216, 52, 25, 5 }, + { 198, 37, 240, 86, 12 }, }, + { { 216, 27, 73, 176, 8 }, + { 114, 10, 143, 130, 10 }, + { 16, 217, 45, 129, 11 }, + { 84, 31, 21, 4, 14 }, }, + { { 3, 88, 41, 248, 6 }, + { 80, 52, 198, 73, 14 }, + { 97, 249, 65, 172, 0 }, + { 121, 38, 50, 192, 10 }, }, + { { 7, 196, 9, 95, 12 }, + { 152, 36, 213, 109, 1 }, + { 63, 169, 2, 62, 0 }, + { 139, 106, 178, 65, 9 }, }, + { { 15, 226, 102, 23, 11 }, + { 175, 85, 153, 69, 5 }, + { 222, 134, 100, 127, 0 }, + { 170, 41, 154, 175, 5 }, }, + { { 20, 72, 54, 68, 1 }, + { 140, 77, 0, 24, 12 }, + { 130, 38, 193, 34, 8 }, + { 49, 128, 11, 35, 1 }, }, + { { 16, 173, 95, 251, 7 }, + { 53, 123, 214, 60, 11 }, + { 237, 255, 171, 80, 8 }, + { 211, 198, 189, 234, 12 }, }, + { { 18, 130, 149, 83, 15 }, + { 20, 153, 217, 29, 1 }, + { 252, 170, 148, 20, 8 }, + { 139, 137, 185, 146, 8 }, }, + { { 22, 225, 49, 132, 12 }, + { 153, 14, 81, 17, 6 }, + { 50, 24, 200, 118, 8 }, + { 104, 136, 167, 9, 9 }, }, + { { 24, 122, 73, 107, 0 }, + { 115, 44, 14, 12, 9 }, + { 13, 105, 37, 225, 8 }, + { 147, 7, 3, 76, 14 }, }, + { { 26, 232, 134, 17, 2 }, + { 3, 221, 144, 5, 8 }, 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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 }, + { 143, 7, 42, 25, 233, 178, 0 }, + { 249, 26, 184, 64, 6, 250, 1 }, }, + { { 56, 125, 77, 118, 65, 19, 0 }, + { 112, 183, 95, 13, 133, 68, 0 }, + { 100, 65, 55, 89, 95, 14, 0 }, + { 17, 80, 216, 125, 118, 135, 0 }, }, + { { 58, 144, 74, 233, 225, 233, 1 }, + { 174, 63, 117, 200, 42, 2, 1 }, + { 203, 195, 203, 169, 4, 174, 0 }, + { 160, 42, 9, 215, 126, 58, 1 }, }, + { { 70, 212, 132, 123, 60, 221, 0 }, + { 221, 45, 64, 86, 248, 199, 0 }, + { 93, 158, 111, 16, 149, 177, 0 }, + { 113, 143, 181, 1, 90, 93, 1 }, }, + { { 72, 146, 167, 222, 158, 43, 1 }, + { 18, 7, 232, 163, 251, 143, 1 }, + { 234, 60, 189, 242, 164, 137, 0 }, + { 248, 239, 226, 139, 240, 36, 0 }, }, + { { 94, 118, 195, 228, 152, 168, 0 }, + { 193, 43, 103, 135, 51, 137, 1 }, + { 10, 140, 147, 225, 183, 61, 0 }, + { 200, 230, 112, 243, 106, 65, 1 }, }, + { { 116, 162, 222, 250, 47, 136, 1 }, + { 59, 104, 87, 170, 250, 142, 0 }, + { 136, 250, 47, 189, 162, 151, 0 }, + { 56, 175, 170, 245, 11, 110, 0 }, }, + { { 148, 93, 226, 40, 19, 89, 0 }, + { 69, 165, 149, 38, 38, 99, 0 }, + { 77, 100, 10, 35, 221, 20, 1 }, + { 99, 50, 50, 84, 210, 209, 0 }, }, + { { 155, 18, 149, 100, 237, 163, 1 }, + { 138, 127, 124, 3, 65, 188, 1 }, + { 226, 219, 147, 84, 164, 108, 1 }, + { 158, 193, 96, 31, 127, 40, 1 }, }, + { { 161, 212, 148, 45, 130, 248, 0 }, + { 68, 105, 32, 110, 41, 118, 1 }, + { 15, 160, 218, 20, 149, 194, 1 }, + { 183, 74, 59, 2, 75, 17, 0 }, }, + { { 187, 120, 230, 49, 108, 208, 1 }, + { 158, 187, 135, 78, 66, 244, 0 }, + { 133, 155, 70, 51, 143, 110, 1 }, + { 23, 161, 57, 112, 238, 188, 1 }, }, + { { 203, 181, 221, 203, 219, 24, 0 }, + { 224, 83, 115, 227, 188, 247, 0 }, + { 12, 109, 233, 221, 214, 233, 1 }, + { 119, 158, 227, 231, 101, 3, 1 }, }, + { { 211, 229, 238, 183, 131, 51, 0 }, + { 240, 36, 191, 230, 159, 116, 1 }, + { 102, 96, 246, 187, 211, 229, 1 }, + { 151, 124, 179, 254, 146, 7, 1 }, }, + { { 242, 148, 35, 63, 209, 156, 1 }, + { 210, 57, 180, 89, 187, 99, 0 }, + { 156, 197, 254, 98, 20, 167, 1 }, + { 99, 110, 205, 22, 206, 37, 1 }, }, + { { 253, 214, 209, 159, 59, 230, 1 }, + { 95, 75, 29, 255, 153, 187, 1 }, + { 179, 238, 124, 197, 181, 223, 1 }, + { 238, 204, 255, 220, 105, 125, 0 }, }, + { { 58, 70, 36, 238, 132, 238, 1 }, + { 198, 42, 236, 156, 225, 14, 1 }, + { 187, 144, 187, 146, 49, 46, 0 }, + { 184, 67, 156, 155, 170, 49, 1 }, }, + { { 98, 24, 126, 36, 59, 15, 0 }, + { 168, 229, 153, 56, 51, 133, 0 }, + { 120, 110, 18, 63, 12, 35, 0 }, + { 80, 230, 14, 76, 211, 138, 1 }, }, + { { 10, 205, 67, 111, 157, 195, 0 }, + { 196, 174, 121, 69, 207, 131, 0 }, + { 97, 220, 251, 97, 89, 168, 0 }, + { 96, 249, 209, 79, 58, 145, 1 }, }, + { { 14, 64, 212, 195, 142, 2, 0 }, + { 129, 66, 105, 230, 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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 }, }, }; + } +} + +#endif diff --git a/multi-camera/src/GLViewer.cpp b/multi-camera/src/GLViewer.cpp new file mode 100644 index 0000000..84bf2a2 --- /dev/null +++ b/multi-camera/src/GLViewer.cpp @@ -0,0 +1,744 @@ +#include "GLViewer.hpp" + +GLchar* VERTEX_SHADER = + "#version 330 core\n" + "layout(location = 0) in vec3 in_Vertex;\n" + "layout(location = 1) in vec3 in_Color;\n" + "uniform mat4 u_mvpMatrix;\n" + "out vec3 b_color;\n" + "void main() {\n" + " b_color = in_Color;\n" + " gl_Position = u_mvpMatrix * vec4(in_Vertex, 1);\n" + "}"; + +GLchar* FRAGMENT_SHADER = + "#version 330 core\n" + "in vec3 b_color;\n" + "layout(location = 0) out vec4 out_Color;\n" + "void main() {\n" + " out_Color = vec4(b_color, 1);\n" + "}"; + +using namespace sl; + +GLViewer* GLViewer::currentInstance_ = nullptr; + +void getColor(int num_segments, int i, float &c1, float &c2, float &c3) { + float r = fabs(1.f - (float(i)*2.f) / float(num_segments)); + c1 = (0.1f * r); + c2 = (0.3f * r); + c3 = (0.8f * r); +} + +GLViewer::GLViewer() : initialized_(false) { + if (currentInstance_ != nullptr) { + delete currentInstance_; + } + currentInstance_ = this; + + wnd_w = 1000; + wnd_h = 1000; + + cb = 0.847058f; + cg = 0.596078f; + cr = 0.203921f; + + mouseButton_[0] = mouseButton_[1] = mouseButton_[2] = false; + + clearInputs(); + previousMouseMotion_[0] = previousMouseMotion_[1] = 0; + ended_ = true; +} + +GLViewer::~GLViewer() { +} + +void GLViewer::exit() { + if (initialized_) { + for (auto &it : pointCloud_) + it.close(); + ended_ = true; + glutLeaveMainLoop(); + } +} + +bool GLViewer::isEnded() { + return ended_; +} + +void GLViewer::init(int w, int h, int nb_pc) { + res.width = w; + res.height = h; + cuCtxGetCurrent(&ctx); + + pointCloud_.resize(nb_pc); + char *argv[1]; + argv[0] = '\0'; + int argc = 1; + glutInit(&argc, argv); + glutInitWindowSize(wnd_w, wnd_h); + glutInitDisplayMode(GLUT_DOUBLE | GLUT_RGBA | GLUT_DEPTH); + glutCreateWindow("ZED 3D Viewer"); + + GLenum err = glewInit(); + if (GLEW_OK != err) + std::cout << "ERROR: glewInit failed: " << glewGetErrorString(err) << "\n"; + + glEnable(GL_DEPTH_TEST); + + for (auto &it : pointCloud_) + it.initialize((int)res.width, (int)res.height, ctx); + + // Compile and create the shader + shader_ = Shader(VERTEX_SHADER, FRAGMENT_SHADER); + shMVPMatrixLoc_ = glGetUniformLocation(shader_.getProgramId(), "u_mvpMatrix"); + + // Create the camera + camera_ = CameraGL(sl::Translation(0, 0, 0), sl::Translation(0, 0, -1)); + camera_.setOffsetFromPosition(sl::Translation(0, 0, 4)); + + // Create 3D axis + sl::Translation posStart(0, 0, 0); + axis_X = Simple3DObject(posStart, true); + axis_Y = Simple3DObject(posStart, true); + axis_Z = Simple3DObject(posStart, true); + + int num_segments = 60; + float rad = 0.10f; + float fade = 0.5f; + + for (int ii = 0; ii < num_segments; ii++) { + float c1 = (cr * fade); + float c2 = (cg * fade); + float c3 = (cb * fade); + + float theta = 2.0f * 3.1415926f * float(ii) / float(num_segments); + axis_X.addPoint(rad * cosf(theta), rad * sinf(theta), 0, c1, c2, c3); + + getColor(num_segments, ii, c1, c2, c3); + axis_Y.addPoint(0, rad * sinf(theta), rad * cosf(theta), c3, c2, c2); + + theta = 2.0f * M_PI * (float(ii) + float(num_segments) / 4.f) / float(num_segments); + theta = theta > (2.f * M_PI) ? theta - (2.f * M_PI) : theta; + getColor(num_segments, ii, c1, c2, c3); + axis_Z.addPoint(rad * cosf(theta), 0, rad * sinf(theta), c2, c3, c1); + } + + axis_X.setDrawingType(GL_LINE_LOOP); + axis_X.pushToGPU(); + axis_Y.setDrawingType(GL_LINE_LOOP); + axis_Y.pushToGPU(); + axis_Z.setDrawingType(GL_LINE_LOOP); + axis_Z.pushToGPU(); + + glutSetOption(GLUT_ACTION_ON_WINDOW_CLOSE, GLUT_ACTION_CONTINUE_EXECUTION); + + // Map glut function on this class methods + glutDisplayFunc(GLViewer::drawCallback); + glutMouseFunc(GLViewer::mouseButtonCallback); + glutMotionFunc(GLViewer::mouseMotionCallback); + glutReshapeFunc(GLViewer::reshapeCallback); + glutKeyboardFunc(GLViewer::keyPressedCallback); + glutKeyboardUpFunc(GLViewer::keyReleasedCallback); + + initialized_ = true; + ended_ = false; +} + +void GLViewer::render() { + if (!ended_) { + glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT); + + glClearColor(0.12f, 0.12f, 0.12f, 1.0f); + glLineWidth(2.f); + glPointSize(2.f); + update(); + draw(); + glutSwapBuffers(); + glutPostRedisplay(); + } +} + +void GLViewer::updatePointCloud(sl::Mat &matXYZRGBA, int id) { + while (pointCloud_[id].lock) sl::sleep_ms(1); + pointCloud_[id].pushNewPC(matXYZRGBA); +} + +bool GLViewer::askReset() { + auto ua = user_action; + user_action = false; + return ua; +} + +void GLViewer::update() { + if (keyStates_['q'] == KEY_STATE::UP || keyStates_['Q'] == KEY_STATE::UP || keyStates_[27] == KEY_STATE::UP) { + currentInstance_->exit(); + return; + } + + if (keyStates_[' '] == KEY_STATE::UP) + user_action = true; + + // Rotate camera with mouse + if (mouseButton_[MOUSE_BUTTON::LEFT]) { + camera_.rotate(sl::Rotation((float) mouseMotion_[1] * MOUSE_R_SENSITIVITY, camera_.getRight())); + camera_.rotate(sl::Rotation((float) mouseMotion_[0] * MOUSE_R_SENSITIVITY, camera_.getVertical() * -1.f)); + } + + // Translate camera with mouse + if (mouseButton_[MOUSE_BUTTON::RIGHT]) { + camera_.translate(camera_.getUp() * (float) mouseMotion_[1] * MOUSE_T_SENSITIVITY); + camera_.translate(camera_.getRight() * (float) mouseMotion_[0] * MOUSE_T_SENSITIVITY); + } + + // Zoom in with mouse wheel + if (mouseWheelPosition_ != 0) { + float distance = sl::Translation(camera_.getOffsetFromPosition()).norm(); + if (mouseWheelPosition_ > 0 && distance > camera_.getZNear()) { // zoom + camera_.setOffsetFromPosition(camera_.getOffsetFromPosition() * MOUSE_UZ_SENSITIVITY); + } else if (distance < camera_.getZFar()) {// unzoom + camera_.setOffsetFromPosition(camera_.getOffsetFromPosition() * MOUSE_DZ_SENSITIVITY); + } + } + + // Translate camera with keyboard + if (keyStates_['u'] == KEY_STATE::DOWN) { + camera_.translate((camera_.getForward()*-1.f) * KEY_T_SENSITIVITY); + } + if (keyStates_['j'] == KEY_STATE::DOWN) { + camera_.translate(camera_.getForward() * KEY_T_SENSITIVITY); + } + if (keyStates_['h'] == KEY_STATE::DOWN) { + camera_.translate(camera_.getRight() * KEY_T_SENSITIVITY); + } + if (keyStates_['k'] == KEY_STATE::DOWN) { + camera_.translate((camera_.getRight()*-1.f) * KEY_T_SENSITIVITY); + } + + // Update point cloud buffers + for (auto &it : pointCloud_) { + while (it.lock) sl::sleep_ms(1); + it.update(); + } + camera_.update(); + clearInputs(); +} + +void GLViewer::draw() { + const sl::Transform vpMatrix = camera_.getViewProjectionMatrix(); + + // Simple 3D shader for simple 3D objects + glUseProgram(shader_.getProgramId()); + // Axis + glUniformMatrix4fv(shMVPMatrixLoc_, 1, GL_FALSE, sl::Transform::transpose(vpMatrix * axis_X.getModelMatrix()).m); + axis_X.draw(); + axis_Y.draw(); + axis_Z.draw(); + glUseProgram(0); + + // Draw point cloud with its own shader + for (auto &it : pointCloud_) + it.draw(sl::Transform::transpose(vpMatrix)); +} + +void GLViewer::clearInputs() { + mouseMotion_[0] = mouseMotion_[1] = 0; + mouseWheelPosition_ = 0; + for (unsigned int i = 0; i < 256; ++i) + if (keyStates_[i] != KEY_STATE::DOWN) + keyStates_[i] = KEY_STATE::FREE; +} + +void GLViewer::drawCallback() { + currentInstance_->render(); +} + +void GLViewer::mouseButtonCallback(int button, int state, int x, int y) { + if (button < 5) { + if (button < 3) { + currentInstance_->mouseButton_[button] = state == GLUT_DOWN; + } else { + currentInstance_->mouseWheelPosition_ += button == MOUSE_BUTTON::WHEEL_UP ? 1 : -1; + } + currentInstance_->mouseCurrentPosition_[0] = x; + currentInstance_->mouseCurrentPosition_[1] = y; + currentInstance_->previousMouseMotion_[0] = x; + currentInstance_->previousMouseMotion_[1] = y; + } +} + +void GLViewer::mouseMotionCallback(int x, int y) { + currentInstance_->mouseMotion_[0] = x - currentInstance_->previousMouseMotion_[0]; + currentInstance_->mouseMotion_[1] = y - currentInstance_->previousMouseMotion_[1]; + currentInstance_->previousMouseMotion_[0] = x; + currentInstance_->previousMouseMotion_[1] = y; + glutPostRedisplay(); +} + +void GLViewer::reshapeCallback(int width, int height) { + glViewport(0, 0, width, height); + float hfov = currentInstance_->camera_.getHorizontalFOV(); + currentInstance_->camera_.setProjection(hfov, hfov * (float) height / (float) width, currentInstance_->camera_.getZNear(), currentInstance_->camera_.getZFar()); +} + +void GLViewer::keyPressedCallback(unsigned char c, int x, int y) { + currentInstance_->keyStates_[c] = KEY_STATE::DOWN; + glutPostRedisplay(); +} + +void GLViewer::keyReleasedCallback(unsigned char c, int x, int y) { + currentInstance_->keyStates_[c] = KEY_STATE::UP; +} + +void GLViewer::idle() { + glutPostRedisplay(); +} + +Simple3DObject::Simple3DObject(Translation position, bool isStatic) : isStatic_(isStatic) { + vaoID_ = 0; + drawingType_ = GL_TRIANGLES; + position_ = position; + rotation_.setIdentity(); +} + +Simple3DObject::~Simple3DObject() { + if (vaoID_ != 0) { + glDeleteBuffers(3, vboID_); + glDeleteVertexArrays(1, &vaoID_); + } +} + +void Simple3DObject::addPoint(float x, float y, float z, float r, float g, float b) { + vertices_.push_back(x); + vertices_.push_back(y); + vertices_.push_back(z); + colors_.push_back(r); + colors_.push_back(g); + colors_.push_back(b); + indices_.push_back((int) indices_.size()); +} + +void Simple3DObject::pushToGPU() { + if (!isStatic_ || vaoID_ == 0) { + if (vaoID_ == 0) { + glGenVertexArrays(1, &vaoID_); + glGenBuffers(3, vboID_); + } + glBindVertexArray(vaoID_); + glBindBuffer(GL_ARRAY_BUFFER, vboID_[0]); + glBufferData(GL_ARRAY_BUFFER, vertices_.size() * sizeof (float), &vertices_[0], isStatic_ ? GL_STATIC_DRAW : GL_DYNAMIC_DRAW); + glVertexAttribPointer(Shader::ATTRIB_VERTICES_POS, 3, GL_FLOAT, GL_FALSE, 0, 0); + glEnableVertexAttribArray(Shader::ATTRIB_VERTICES_POS); + + glBindBuffer(GL_ARRAY_BUFFER, vboID_[1]); + glBufferData(GL_ARRAY_BUFFER, colors_.size() * sizeof (float), &colors_[0], isStatic_ ? GL_STATIC_DRAW : GL_DYNAMIC_DRAW); + glVertexAttribPointer(Shader::ATTRIB_COLOR_POS, 3, GL_FLOAT, GL_FALSE, 0, 0); + glEnableVertexAttribArray(Shader::ATTRIB_COLOR_POS); + + glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, vboID_[2]); + glBufferData(GL_ELEMENT_ARRAY_BUFFER, indices_.size() * sizeof (unsigned int), &indices_[0], isStatic_ ? GL_STATIC_DRAW : GL_DYNAMIC_DRAW); + + glBindVertexArray(0); + glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, 0); + glBindBuffer(GL_ARRAY_BUFFER, 0); + } +} + +void Simple3DObject::clear() { + vertices_.clear(); + colors_.clear(); + indices_.clear(); +} + +void Simple3DObject::setDrawingType(GLenum type) { + drawingType_ = type; +} + +void Simple3DObject::draw() { + glBindVertexArray(vaoID_); + glDrawElements(drawingType_, (GLsizei) indices_.size(), GL_UNSIGNED_INT, 0); + glBindVertexArray(0); +} + +void Simple3DObject::translate(const Translation& t) { + position_ = position_ + t; +} + +void Simple3DObject::setPosition(const Translation& p) { + position_ = p; +} + +void Simple3DObject::setRT(const Transform& mRT) { + position_ = mRT.getTranslation(); + rotation_ = mRT.getOrientation(); +} + +void Simple3DObject::rotate(const Orientation& rot) { + rotation_ = rot * rotation_; +} + +void Simple3DObject::rotate(const Rotation& m) { + this->rotate(sl::Orientation(m)); +} + +void Simple3DObject::setRotation(const Orientation& rot) { + rotation_ = rot; +} + +void Simple3DObject::setRotation(const Rotation& m) { + this->setRotation(sl::Orientation(m)); +} + +const Translation& Simple3DObject::getPosition() const { + return position_; +} + +Transform Simple3DObject::getModelMatrix() const { + Transform tmp = Transform::identity(); + tmp.setOrientation(rotation_); + tmp.setTranslation(position_); + return tmp; +} + +Shader::Shader(GLchar* vs, GLchar* fs) { + if (!compile(verterxId_, GL_VERTEX_SHADER, vs)) { + std::cout << "ERROR: while compiling vertex shader" << std::endl; + } + if (!compile(fragmentId_, GL_FRAGMENT_SHADER, fs)) { + std::cout << "ERROR: while compiling fragment shader" << std::endl; + } + + programId_ = glCreateProgram(); + + glAttachShader(programId_, verterxId_); + glAttachShader(programId_, fragmentId_); + + glBindAttribLocation(programId_, ATTRIB_VERTICES_POS, "in_vertex"); + glBindAttribLocation(programId_, ATTRIB_COLOR_POS, "in_texCoord"); + + glLinkProgram(programId_); + + GLint errorlk(0); + glGetProgramiv(programId_, GL_LINK_STATUS, &errorlk); + if (errorlk != GL_TRUE) { + std::cout << "ERROR: while linking Shader :" << std::endl; + GLint errorSize(0); + glGetProgramiv(programId_, GL_INFO_LOG_LENGTH, &errorSize); + + char *error = new char[errorSize + 1]; + glGetShaderInfoLog(programId_, errorSize, &errorSize, error); + error[errorSize] = '\0'; + std::cout << error << std::endl; + + delete[] error; + glDeleteProgram(programId_); + } +} + +Shader::~Shader() { + if (verterxId_ != 0) + glDeleteShader(verterxId_); + if (fragmentId_ != 0) + glDeleteShader(fragmentId_); + if (programId_ != 0) + glDeleteShader(programId_); +} + +GLuint Shader::getProgramId() { + return programId_; +} + +bool Shader::compile(GLuint &shaderId, GLenum type, GLchar* src) { + shaderId = glCreateShader(type); + if (shaderId == 0) { + std::cout << "ERROR: shader type (" << type << ") does not exist" << std::endl; + return false; + } + glShaderSource(shaderId, 1, (const char**) &src, 0); + glCompileShader(shaderId); + + GLint errorCp(0); + glGetShaderiv(shaderId, GL_COMPILE_STATUS, &errorCp); + if (errorCp != GL_TRUE) { + std::cout << "ERROR: while compiling Shader :" << std::endl; + GLint errorSize(0); + glGetShaderiv(shaderId, GL_INFO_LOG_LENGTH, &errorSize); + + char *error = new char[errorSize + 1]; + glGetShaderInfoLog(shaderId, errorSize, &errorSize, error); + error[errorSize] = '\0'; + std::cout << error << std::endl; + + delete[] error; + glDeleteShader(shaderId); + return false; + } + return true; +} + + +GLchar* POINTCLOUD_VERTEX_SHADER = + "#version 330 core\n" + "layout(location = 0) in vec4 in_VertexRGBA;\n" + "uniform mat4 u_mvpMatrix;\n" + "out vec3 b_color;\n" + "vec4 decomposeFloat(const in float value)\n" + "{\n" + " uint rgbaInt = floatBitsToUint(value);\n" + " uint bIntValue = (rgbaInt / 256U / 256U) % 256U;\n" + " uint gIntValue = (rgbaInt / 256U) % 256U;\n" + " uint rIntValue = (rgbaInt) % 256U; \n" + " return vec4(rIntValue / 255.0f, gIntValue / 255.0f, bIntValue / 255.0f, 1.0); \n" + "}\n" + "void main() {\n" + // Decompose the 4th channel of the XYZRGBA buffer to retrieve the color of the point (1float to 4uint) + " b_color = decomposeFloat(in_VertexRGBA.a).xyz;\n" + " gl_Position = u_mvpMatrix * vec4(in_VertexRGBA.xyz, 1);\n" + "}"; + +GLchar* POINTCLOUD_FRAGMENT_SHADER = + "#version 330 core\n" + "in vec3 b_color;\n" + "layout(location = 0) out vec4 out_Color;\n" + "void main() {\n" + " out_Color = vec4(b_color, 1);\n" + "}"; + +PointCloud::PointCloud() : +hasNewPCL_(false), initialized_(false), lock(false) { +} + +PointCloud::~PointCloud() { + close(); +} + +void PointCloud::close() { + if (initialized_) { + initialized_ = false; + matGPU_.free(); + glDeleteBuffers(1, &bufferGLID_); + } +} + +void PointCloud::initialize(unsigned int width, unsigned int height, CUcontext ctx) { + lock = false; + width_ = width; + height_ = height; + cuda_zed_ctx = ctx; + glGenBuffers(1, &bufferGLID_); + glBindBuffer(GL_ARRAY_BUFFER, bufferGLID_); + glBufferData(GL_ARRAY_BUFFER, width_ * height_ * 4 * sizeof (float), 0, GL_DYNAMIC_DRAW); + glBindBuffer(GL_ARRAY_BUFFER, 0); + + // Set current Cuda context, as this function is called in a thread which doesn't handle the Cuda context + cuCtxSetCurrent(cuda_zed_ctx); + + cudaError_t err = cudaGraphicsGLRegisterBuffer(&bufferCudaID_, bufferGLID_, cudaGraphicsRegisterFlagsNone); + if (err != cudaSuccess) + std::cerr << "Error: CUDA - OpenGL Interop failed (" << err << ")" << std::endl; + + shader_ = Shader(POINTCLOUD_VERTEX_SHADER, POINTCLOUD_FRAGMENT_SHADER); + shMVPMatrixLoc_ = glGetUniformLocation(shader_.getProgramId(), "u_mvpMatrix"); + + matGPU_.alloc(width_, height_, sl::MAT_TYPE_32F_C4, sl::MEM_GPU); + initialized_ = true; +} + +void PointCloud::pushNewPC(sl::Mat &matXYZRGBA) { + if (initialized_) { + lock = true; + cuCtxSetCurrent(cuda_zed_ctx); + matGPU_.setFrom(matXYZRGBA, sl::COPY_TYPE_GPU_GPU); + hasNewPCL_ = true; + lock = false; + } +} + +void PointCloud::update() { + if (hasNewPCL_ && initialized_) { + lock = true; + cudaError_t err = cudaGraphicsMapResources(1, &bufferCudaID_, 0); + if (err != cudaSuccess) + std::cerr << "Error: CUDA MapResources (" << err << ")" << std::endl; + + err = cudaGraphicsResourceGetMappedPointer((void**) &xyzrgbaMappedBuf_, &numBytes_, bufferCudaID_); + if (err != cudaSuccess) + std::cerr << "Error: CUDA GetMappedPointer (" << err << ")" << std::endl; + + err = cudaMemcpy(xyzrgbaMappedBuf_, matGPU_.getPtr(sl::MEM_GPU), numBytes_, cudaMemcpyDeviceToDevice); + if (err != cudaSuccess) + std::cerr << "Error: CUDA MemCpy (" << err << ")" << std::endl; + + err = cudaGraphicsUnmapResources(1, &bufferCudaID_, 0); + if (err != cudaSuccess) + std::cerr << "Error: CUDA UnmapResources (" << err << ")" << std::endl; + + lock = false; + hasNewPCL_ = false; + } +} + +void PointCloud::draw(const sl::Transform& vp) { + if (initialized_) { + glUseProgram(shader_.getProgramId()); + glUniformMatrix4fv(shMVPMatrixLoc_, 1, GL_FALSE, vp.m); + + glBindBuffer(GL_ARRAY_BUFFER, bufferGLID_); + glVertexAttribPointer(Shader::ATTRIB_VERTICES_POS, 4, GL_FLOAT, GL_FALSE, 0, 0); + glEnableVertexAttribArray(Shader::ATTRIB_VERTICES_POS); + + glDrawArrays(GL_POINTS, 0, width_ * height_); + glBindBuffer(GL_ARRAY_BUFFER, 0); + glUseProgram(0); + } +} + +unsigned int PointCloud::getWidth() { + return width_; +} + +unsigned int PointCloud::getHeight() { + return height_; +} + +const sl::Translation CameraGL::ORIGINAL_FORWARD = sl::Translation(0, 0, 1); +const sl::Translation CameraGL::ORIGINAL_UP = sl::Translation(0, 1, 0); +const sl::Translation CameraGL::ORIGINAL_RIGHT = sl::Translation(1, 0, 0); + +CameraGL::CameraGL(Translation position, Translation direction, Translation vertical) { + this->position_ = position; + setDirection(direction, vertical); + + offset_ = sl::Translation(0, 0, 0); + view_.setIdentity(); + updateView(); + setProjection(60, 60, 0.01f, 100.f); + updateVPMatrix(); +} + +CameraGL::~CameraGL() { +} + +void CameraGL::update() { + if (sl::Translation::dot(vertical_, up_) < 0) + vertical_ = vertical_ * -1.f; + updateView(); + updateVPMatrix(); +} + +void CameraGL::setProjection(float horizontalFOV, float verticalFOV, float znear, float zfar) { + horizontalFieldOfView_ = horizontalFOV; + verticalFieldOfView_ = verticalFOV; + znear_ = znear; + zfar_ = zfar; + + float fov_y = verticalFOV * M_PI / 180.f; + float fov_x = horizontalFOV * M_PI / 180.f; + + projection_.setIdentity(); + projection_(0, 0) = 1.0f / tanf(fov_x * 0.5f); + projection_(1, 1) = 1.0f / tanf(fov_y * 0.5f); + projection_(2, 2) = -(zfar + znear) / (zfar - znear); + projection_(3, 2) = -1; + projection_(2, 3) = -(2.f * zfar * znear) / (zfar - znear); + projection_(3, 3) = 0; +} + +const sl::Transform& CameraGL::getViewProjectionMatrix() const { + return vpMatrix_; +} + +float CameraGL::getHorizontalFOV() const { + return horizontalFieldOfView_; +} + +float CameraGL::getVerticalFOV() const { + return verticalFieldOfView_; +} + +void CameraGL::setOffsetFromPosition(const sl::Translation& o) { + offset_ = o; +} + +const sl::Translation& CameraGL::getOffsetFromPosition() const { + return offset_; +} + +void CameraGL::setDirection(const sl::Translation& direction, const sl::Translation& vertical) { + sl::Translation dirNormalized = direction; + dirNormalized.normalize(); + this->rotation_ = sl::Orientation(ORIGINAL_FORWARD, dirNormalized * -1.f); + updateVectors(); + this->vertical_ = vertical; + if (sl::Translation::dot(vertical_, up_) < 0) + rotate(sl::Rotation(M_PI, ORIGINAL_FORWARD)); +} + +void CameraGL::translate(const sl::Translation& t) { + position_ = position_ + t; +} + +void CameraGL::setPosition(const sl::Translation& p) { + position_ = p; +} + +void CameraGL::rotate(const sl::Orientation& rot) { + rotation_ = rot * rotation_; + updateVectors(); +} + +void CameraGL::rotate(const sl::Rotation& m) { + this->rotate(sl::Orientation(m)); +} + +void CameraGL::setRotation(const sl::Orientation& rot) { + rotation_ = rot; + updateVectors(); +} + +void CameraGL::setRotation(const sl::Rotation& m) { + this->setRotation(sl::Orientation(m)); +} + +const sl::Translation& CameraGL::getPosition() const { + return position_; +} + +const sl::Translation& CameraGL::getForward() const { + return forward_; +} + +const sl::Translation& CameraGL::getRight() const { + return right_; +} + +const sl::Translation& CameraGL::getUp() const { + return up_; +} + +const sl::Translation& CameraGL::getVertical() const { + return vertical_; +} + +float CameraGL::getZNear() const { + return znear_; +} + +float CameraGL::getZFar() const { + return zfar_; +} + +void CameraGL::updateVectors() { + forward_ = ORIGINAL_FORWARD * rotation_; + up_ = ORIGINAL_UP * rotation_; + right_ = sl::Translation(ORIGINAL_RIGHT * -1.f) * rotation_; +} + +void CameraGL::updateView() { + sl::Transform transformation(rotation_, (offset_ * rotation_) + position_); + view_ = sl::Transform::inverse(transformation); +} + +void CameraGL::updateVPMatrix() { + vpMatrix_ = projection_ * view_; +} diff --git a/multi-camera/src/aruco.cpp b/multi-camera/src/aruco.cpp new file mode 100644 index 0000000..d082c4e --- /dev/null +++ b/multi-camera/src/aruco.cpp @@ -0,0 +1,2817 @@ +/* +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 "aruco.hpp" +#include +#include +#include +#include + +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), + doCornerRefinement(false), + cornerRefinementWinSize(5), + cornerRefinementMaxIterations(30), + cornerRefinementMinAccuracy(0.1), + markerBorderBits(1), + perspectiveRemovePixelPerCell(4), + perspectiveRemoveIgnoredMarginPerCell(0.13), + maxErroneousBitsInBorderRate(0.35), + minOtsuStdDev(5.0), + errorCorrectionRate(0.6) {} + + + /** + * @brief Convert input image to gray if it is a 3-channels image + */ + static void _convertToGrey(InputArray _in, OutputArray _out) { + + CV_Assert(_in.getMat().channels() == 1 || _in.getMat().channels() == 3); + + _out.create(_in.getMat().size(), CV_8UC1); + if (_in.getMat().type() == CV_8UC3) + cvtColor(_in.getMat(), _out.getMat(), COLOR_BGR2GRAY); + else + _in.getMat().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 combinatios are posible + 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(); + int 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, + DetectorParameters *_params) + : grey(_grey), candidatesArrays(_candidatesArrays), contoursArrays(_contoursArrays), + params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + /** + * @brief Initial steps on finding square candidates + */ + static void _detectInitialCandidates(const Mat &grey, vector< vector< Point2f > > &candidates, + vector< vector< Point > > &contours, + DetectorParameters params) { + + 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(nScales); + vector< vector< vector< Point > > > contoursArrays(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, ¶ms)); + + // 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, OutputArrayOfArrays _candidates, + OutputArrayOfArrays _contours, DetectorParameters 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 + vector< vector< Point2f > > candidatesOut; + vector< vector< Point > > contoursOut; + _filterTooCloseCandidates(candidates, candidatesOut, contours, contoursOut, + params.minMarkerDistanceRate); + + // parse output + _candidates.create((int)candidatesOut.size(), 1, CV_32FC2); + _contours.create((int)contoursOut.size(), 1, CV_32SC2); + for (int i = 0; i < (int)candidatesOut.size(); i++) { + _candidates.create(4, 1, CV_32FC2, i, true); + Mat m = _candidates.getMat(i); + for (int j = 0; j < 4; j++) + m.ptr< Vec2f >(0)[j] = candidatesOut[i][j]; + + _contours.create((int)contoursOut[i].size(), 1, CV_32SC2, i, true); + Mat c = _contours.getMat(i); + for (unsigned int j = 0; j < contoursOut[i].size(); j++) + c.ptr< Point2i >()[j] = contoursOut[i][j]; + } + } + + + /** + * @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 + unsigned int nZ = 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 Dictionary &dictionary, InputArray _image, + InputOutputArray _corners, int &idx, DetectorParameters params) { + + CV_Assert(_corners.total() == 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); + if (borderErrors > maximumErrorsInBorder) return false; // border is wrong + + // 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; + else { + // shift corner positions to the correct rotation + if (rotation != 0) { + Mat copyPoints = _corners.getMat().clone(); + for (int j = 0; j < 4; j++) + _corners.getMat().ptr< Point2f >(0)[j] = + copyPoints.ptr< Point2f >(0)[(j + 4 - rotation) % 4]; + } + 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, InputArrayOfArrays _candidates, + InputArrayOfArrays _contours, const Dictionary *_dictionary, + vector< int > *_idsTmp, vector< char > *_validCandidates, + DetectorParameters *_params) + : grey(_grey), candidates(_candidates), contours(_contours), dictionary(_dictionary), + idsTmp(_idsTmp), validCandidates(_validCandidates), params(_params) {} + + void operator()(const Range &range) const { + const int begin = range.start; + const int end = range.end; + + for (int i = begin; i < end; i++) { + int currId; + Mat currentCandidate = candidates.getMat(i); + if (_identifyOneCandidate(*dictionary, *grey, currentCandidate, currId, *params)) { + (*validCandidates)[i] = 1; + (*idsTmp)[i] = currId; + } + } + } + + private: + IdentifyCandidatesParallel &operator=(const IdentifyCandidatesParallel &); // to quiet MSVC + + const Mat *grey; + InputArrayOfArrays candidates, contours; + const Dictionary *dictionary; + vector< int > *idsTmp; + vector< char > *validCandidates; + DetectorParameters *params; + }; + + + + /** + * @brief Identify square candidates according to a marker dictionary + */ + static void _identifyCandidates(InputArray _image, InputArrayOfArrays _candidates, + InputArrayOfArrays _contours, const Dictionary &dictionary, + OutputArrayOfArrays _accepted, OutputArray _ids, + DetectorParameters params, + OutputArrayOfArrays _rejected = noArray()) { + + int ncandidates = (int)_candidates.total(); + + vector< Mat > accepted; + vector< Mat > rejected; + vector< int > ids; + + 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, _contours, &dictionary, &idsTmp, + &validCandidates, ¶ms)); + + for (int i = 0; i < ncandidates; i++) { + if (validCandidates[i] == 1) { + accepted.push_back(_candidates.getMat(i)); + ids.push_back(idsTmp[i]); + } + else { + rejected.push_back(_candidates.getMat(i)); + } + } + + // parse output + _accepted.create((int)accepted.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < accepted.size(); i++) { + _accepted.create(4, 1, CV_32FC2, i, true); + Mat m = _accepted.getMat(i); + accepted[i].copyTo(m); + } + + _ids.create((int)ids.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < ids.size(); i++) + _ids.getMat().ptr< int >(0)[i] = ids[i]; + + if (_rejected.needed()) { + _rejected.create((int)rejected.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < rejected.size(); i++) { + _rejected.create(4, 1, CV_32FC2, i, true); + Mat m = _rejected.getMat(i); + rejected[i].copyTo(m); + } + } + } + + + /** + * @brief Final filter of markers after its identification + */ + static void _filterDetectedMarkers(InputArrayOfArrays _inCorners, InputArray _inIds, + OutputArrayOfArrays _outCorners, OutputArray _outIds) { + + CV_Assert(_inCorners.total() == _inIds.total()); + if (_inCorners.total() == 0) return; + + // mark markers that will be removed + vector< bool > toRemove(_inCorners.total(), false); + bool atLeastOneRemove = false; + + // remove repeated markers with same id, if one contains the other (doble border bug) + for (unsigned int i = 0; i < _inCorners.total() - 1; i++) { + for (unsigned int j = i + 1; j < _inCorners.total(); j++) { + if (_inIds.getMat().ptr< int >(0)[i] != _inIds.getMat().ptr< int >(0)[j]) continue; + + // check if first marker is inside second + bool inside = true; + for (unsigned int p = 0; p < 4; p++) { + Point2f point = _inCorners.getMat(j).ptr< Point2f >(0)[p]; + if (pointPolygonTest(_inCorners.getMat(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 = _inCorners.getMat(i).ptr< Point2f >(0)[p]; + if (pointPolygonTest(_inCorners.getMat(j), point, false) < 0) { + inside = false; + break; + } + } + if (inside) { + toRemove[i] = true; + atLeastOneRemove = true; + continue; + } + } + } + + // parse output + if (atLeastOneRemove) { + vector< Mat > filteredCorners; + vector< int > filteredIds; + + for (unsigned int i = 0; i < toRemove.size(); i++) { + if (!toRemove[i]) { + filteredCorners.push_back(_inCorners.getMat(i).clone()); + filteredIds.push_back(_inIds.getMat().ptr< int >(0)[i]); + } + } + + _outIds.create((int)filteredIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredIds.size(); i++) + _outIds.getMat().ptr< int >(0)[i] = filteredIds[i]; + + _outCorners.create((int)filteredCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredCorners.size(); i++) { + _outCorners.create(4, 1, CV_32FC2, i, true); + filteredCorners[i].copyTo(_outCorners.getMat(i)); + } + } + } + + + + /** + * @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, + DetectorParameters *_params) + : grey(_grey), corners(_corners), params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + + /** + */ + void detectMarkers(InputArray _image, Dictionary dictionary, OutputArrayOfArrays _corners, + OutputArray _ids, DetectorParameters params, + OutputArrayOfArrays _rejectedImgPoints) { + + CV_Assert(_image.getMat().total() != 0); + + Mat grey; + _convertToGrey(_image.getMat(), grey); + + /// STEP 1: Detect marker candidates + vector< vector< Point2f > > candidates; + vector< vector< Point > > contours; + _detectCandidates(grey, candidates, contours, params); + + /// STEP 2: Check candidate codification (identify markers) + _identifyCandidates(grey, candidates, contours, dictionary, _corners, _ids, params, + _rejectedImgPoints); + + /// STEP 3: Filter detected markers; + _filterDetectedMarkers(_corners, _ids, _corners, _ids); + + /// STEP 4: Corner refinement + if (params.doCornerRefinement) { + 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.total(); 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, (int)_corners.total()), + MarkerSubpixelParallel(&grey, _corners, ¶ms)); + } + } + + + + /** + * 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 { + 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(0, i), tvecs.at(0, 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, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs) { + + 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)); + } + + + + /** + * @brief Given a board configuration and a set of detected markers, returns the corresponding + * image points and object points to call solvePnP + */ + static void _getBoardObjectAndImagePoints(const Board &board, InputArray _detectedIds, + InputArrayOfArrays _detectedCorners, + OutputArray _imgPoints, OutputArray _objPoints) { + + CV_Assert(board.ids.size() == board.objPoints.size()); + CV_Assert(_detectedIds.total() == _detectedCorners.total()); + + int nDetectedMarkers = (int)_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 (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 + _objPoints.create((int)objPnts.size(), 1, CV_32FC3); + for (unsigned int i = 0; i < objPnts.size(); i++) + _objPoints.getMat().ptr< Point3f >(0)[i] = objPnts[i]; + + _imgPoints.create((int)objPnts.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < imgPnts.size(); i++) + _imgPoints.getMat().ptr< Point2f >(0)[i] = imgPnts[i]; + } + + + + /** + * Project board markers that are not included in the list of detected markers + */ + static void _projectUndetectedMarkers(const Board &board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, InputArray _cameraMatrix, + InputArray _distCoeffs, + OutputArrayOfArrays _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 + _undetectedMarkersIds.create((int)undetectedIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < undetectedIds.size(); i++) + _undetectedMarkersIds.getMat().ptr< int >(0)[i] = undetectedIds[i]; + + _undetectedMarkersProjectedCorners.create((int)undetectedCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < undetectedCorners.size(); i++) { + _undetectedMarkersProjectedCorners.create(4, 1, CV_32FC2, i, true); + for (int j = 0; j < 4; j++) { + _undetectedMarkersProjectedCorners.getMat(i).ptr< Point2f >()[j] = + undetectedCorners[i][j]; + } + } + } + + + + /** + * Interpolate board markers that are not included in the list of detected markers using + * global homography + */ + static void _projectUndetectedMarkers(const Board &board, InputOutputArrayOfArrays _detectedCorners, + InputOutputArray _detectedIds, + OutputArrayOfArrays _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.create((int)undetectedMarkersIds.size(), 1, CV_32FC2); + + // for each undetected marker, apply transformation + for (unsigned int i = 0; i < undetectedMarkersObj2D.size(); i++) { + Mat projectedMarker; + perspectiveTransform(undetectedMarkersObj2D[i], projectedMarker, transformation); + + _undetectedMarkersProjectedCorners.create(4, 1, CV_32FC2, i, true); + projectedMarker.copyTo(_undetectedMarkersProjectedCorners.getMat(i)); + } + + _undetectedMarkersIds.create((int)undetectedMarkersIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < undetectedMarkersIds.size(); i++) + _undetectedMarkersIds.getMat().ptr< int >(0)[i] = undetectedMarkersIds[i]; + } + + + + /** + */ + void refineDetectedMarkers(InputArray _image, const Board &board, + InputOutputArrayOfArrays _detectedCorners, InputOutputArray _detectedIds, + InputOutputArray _rejectedCorners, InputArray _cameraMatrix, + InputArray _distCoeffs, float minRepDistance, float errorCorrectionRate, + bool checkAllOrders, OutputArray _recoveredIdxs, + DetectorParameters params) { + + CV_Assert(minRepDistance > 0); + + if (_detectedIds.total() == 0 || _rejectedCorners.total() == 0) return; + + // 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 + int maxCorrectionRecalculated = + int(double(board.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, board.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 = + board.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.doCornerRefinement) { + 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 + _detectedIds.create((int)finalAcceptedIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < finalAcceptedIds.size(); i++) + _detectedIds.getMat().ptr< int >(0)[i] = finalAcceptedIds[i]; + + _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()) { + _recoveredIdxs.create((int)recoveredIdxs.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < recoveredIdxs.size(); i++) { + _recoveredIdxs.getMat().ptr< int >()[i] = recoveredIdxs[i]; + } + } + } + } + + + + + /** + */ + int estimatePoseBoard(InputArrayOfArrays _corners, InputArray _ids, const Board &board, + InputArray _cameraMatrix, InputArray _distCoeffs, OutputArray _rvec, + OutputArray _tvec) { + + CV_Assert(_corners.total() == _ids.total()); + + // get object and image points for the solvePnP function + Mat objPoints, imgPoints; + _getBoardObjectAndImagePoints(board, _ids, _corners, imgPoints, objPoints); + + CV_Assert(imgPoints.total() == objPoints.total()); + + if (objPoints.total() == 0) // 0 of the detected markers in board + return 0; + + _rvec.create(3, 1, CV_64FC1); + _tvec.create(3, 1, CV_64FC1); + solvePnP(objPoints, imgPoints, _cameraMatrix, _distCoeffs, _rvec, _tvec); + + // 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) { + aruco::drawPlanarBoard((*this), outSize, _img, marginSize, borderBits); + } + + + + /** + */ + GridBoard GridBoard::create(int markersX, int markersY, float markerLength, float markerSeparation, + Dictionary _dictionary) { + + GridBoard res; + + CV_Assert(markersX > 0 && markersY > 0 && markerLength > 0 && markerSeparation > 0); + + res._markersX = markersX; + res._markersY = markersY; + res._markerLength = markerLength; + res._markerSeparation = markerSeparation; + res.dictionary = _dictionary; + + int totalMarkers = markersX * markersY; + res.ids.resize(totalMarkers); + res.objPoints.reserve(totalMarkers); + + // fill ids with first identifiers + for (int i = 0; i < totalMarkers; i++) + res.ids[i] = i; + + // 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) { + + CV_Assert(_image.getMat().total() != 0 && + (_image.getMat().channels() == 1 || _image.getMat().channels() == 3)); + CV_Assert(length > 0); + + // project axis points + vector< Point3f > axisPoints; + axisPoints.push_back(Point3f(0, 0, 0)); + axisPoints.push_back(Point3f(length, 0, 0)); + axisPoints.push_back(Point3f(0, length, 0)); + axisPoints.push_back(Point3f(0, 0, length)); + vector< Point2f > imagePoints; + projectPoints(axisPoints, _rvec, _tvec, _cameraMatrix, _distCoeffs, imagePoints); + + // draw axis lines + line(_image, imagePoints[0], imagePoints[1], Scalar(0, 0, 255), 3); + line(_image, imagePoints[0], imagePoints[2], Scalar(0, 255, 0), 3); + line(_image, imagePoints[0], imagePoints[3], Scalar(255, 0, 0), 3); + } + + + + /** + */ + void drawMarker(Dictionary dictionary, int id, int sidePixels, OutputArray _img, int borderBits) { + dictionary.drawMarker(id, sidePixels, _img, borderBits); + } + + + + /** + */ + void drawPlanarBoard(const Board &board, Size outSize, OutputArray _img, int marginSize, + int borderBits) { + + CV_Assert(outSize.area() > 0); + CV_Assert(marginSize >= 0); + + _img.create(outSize, CV_8UC1); + Mat out = _img.getMat(); + out.setTo(Scalar::all(255)); + Mat outNoMargins = + out.colRange(marginSize, out.cols - marginSize).rowRange(marginSize, out.rows - 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, sizeY; + sizeX = maxX - minX; + sizeY = maxY - minY; + + // proportion transformations + float xReduction = sizeX / float(outNoMargins.cols); + float yReduction = sizeY / float(outNoMargins.rows); + + // determine the zone where the markers are placed + Mat markerZone; + if (xReduction > yReduction) { + int nRows = int(sizeY / xReduction); + int rowsMargins = (outNoMargins.rows - nRows) / 2; + markerZone = outNoMargins.rowRange(rowsMargins, outNoMargins.rows - rowsMargins); + } + else { + int nCols = int(sizeX / yReduction); + int colsMargins = (outNoMargins.cols - nCols) / 2; + markerZone = outNoMargins.colRange(colsMargins, outNoMargins.cols - colsMargins); + } + + // now paint each marker + for (unsigned int m = 0; m < board.objPoints.size(); m++) { + + // transform corners to markerZone coordinates + vector< Point2f > outCorners; + outCorners.resize(4); + for (int j = 0; j < 4; j++) { + Point2f p0, p1, pf; + p0 = Point2f(board.objPoints[m][j].x, board.objPoints[m][j].y); + // remove negativity + p1.x = p0.x - minX; + p1.y = p0.y - minY; + pf.x = p1.x * float(markerZone.cols - 1) / sizeX; + pf.y = float(markerZone.rows - 1) - p1.y * float(markerZone.rows - 1) / sizeY; + outCorners[j] = pf; + } + + // get tiny marker + int tinyMarkerSize = 10 * board.dictionary.markerSize + 2; + Mat tinyMarker; + board.dictionary.drawMarker(board.ids[m], tinyMarkerSize, tinyMarker, borderBits); + + // interpolate tiny marker to marker position in markerZone + Mat inCorners(4, 1, CV_32FC2); + inCorners.ptr< Point2f >(0)[0] = Point2f(0, 0); + inCorners.ptr< Point2f >(0)[1] = Point2f((float)tinyMarker.cols, 0); + inCorners.ptr< Point2f >(0)[2] = Point2f((float)tinyMarker.cols, (float)tinyMarker.rows); + inCorners.ptr< Point2f >(0)[3] = Point2f(0, (float)tinyMarker.rows); + + // remove perspective + Mat transformation = getPerspectiveTransform(inCorners, outCorners); + Mat aux; + const char borderValue = 127; + warpPerspective(tinyMarker, aux, transformation, markerZone.size(), INTER_NEAREST, + BORDER_CONSTANT, Scalar::all(borderValue)); + + // copy only not-border pixels + for (int y = 0; y < aux.rows; y++) { + for (int x = 0; x < aux.cols; x++) { + if (aux.at< unsigned char >(y, x) == borderValue) continue; + markerZone.at< unsigned char >(y, x) = aux.at< unsigned char >(y, x); + } + } + } + } + + + + /** + */ + double calibrateCameraAruco(InputArrayOfArrays _corners, InputArray _ids, InputArray _counter, + const Board &board, Size imageSize, InputOutputArray _cameraMatrix, + InputOutputArray _distCoeffs, OutputArrayOfArrays _rvecs, + OutputArrayOfArrays _tvecs, int flags, TermCriteria criteria) { + + // for each frame, get properly processed imagePoints and objectPoints for the calibrateCamera + // function + vector< Mat > processedObjectPoints, processedImagePoints; + int nFrames = (int)_counter.total(); + int markerCounter = 0; + for (int frame = 0; frame < nFrames; frame++) { + int nMarkersInThisFrame = _counter.getMat().ptr< int >()[frame]; + vector< Mat > thisFrameCorners; + vector< int > thisFrameIds; + thisFrameCorners.reserve(nMarkersInThisFrame); + thisFrameIds.reserve(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, thisFrameIds, thisFrameCorners, currentImgPoints, + currentObjPoints); + if (currentImgPoints.total() > 0 && currentObjPoints.total() > 0) { + processedImagePoints.push_back(currentImgPoints); + processedObjectPoints.push_back(currentObjPoints); + } + } + + return calibrateCamera(processedObjectPoints, processedImagePoints, imageSize, _cameraMatrix, + _distCoeffs, _rvecs, _tvecs, flags, criteria); + } + + /** + */ + void CharucoBoard::draw(Size outSize, OutputArray _img, int marginSize, int borderBits) { + + CV_Assert(outSize.area() > 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::drawPlanarBoard((*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); + } + } + } + + + + /** + */ + CharucoBoard CharucoBoard::create(int squaresX, int squaresY, float squareLength, + float markerLength, Dictionary dictionary) { + + CV_Assert(squaresX > 1 && squaresY > 1 && markerLength > 0 && squareLength > markerLength); + CharucoBoard res; + + 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) < 0.0001) { + // 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 unsigned int _filterCornersWithoutMinMarkers(const CharucoBoard &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().ptr< int >(0)[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().ptr< int >(0)[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().ptr< Point2f >(0)[i]); + } + } + + // parse output + _filteredCharucoCorners.create((int)filteredCharucoCorners.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredCharucoCorners.size(); i++) { + _filteredCharucoCorners.getMat().ptr< Point2f >(0)[i] = filteredCharucoCorners[i]; + } + + _filteredCharucoIds.create((int)filteredCharucoIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredCharucoIds.size(); i++) { + _filteredCharucoIds.getMat().ptr< int >(0)[i] = filteredCharucoIds[i]; + } + + return (unsigned int)filteredCharucoCorners.size(); + } + + + /** + * 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, DetectorParameters *_params) + : grey(_grey), filteredChessboardImgPoints(_filteredChessboardImgPoints), + filteredWinSizes(_filteredWinSizes), params(_params) {} + + void operator()(const Range &range) const { + 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; + DetectorParameters *params; + }; + + + + + /** + * @brief From all projected chessboard corners, select those inside the image and apply subpixel + * refinement. Returns number of valid corners. + */ + static unsigned 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().ptr< Point2f >(0)[i])) { + filteredChessboardImgPoints.push_back(_allCorners.getMat().ptr< Point2f >(0)[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.getMat().type() == CV_8UC3) + cvtColor(_image.getMat(), grey, COLOR_BGR2GRAY); + else + _image.getMat().copyTo(grey); + + DetectorParameters params; // 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, ¶ms)); + + // parse output + _selectedCorners.create((int)filteredChessboardImgPoints.size(), 1, CV_32FC2); + for (unsigned int i = 0; i < filteredChessboardImgPoints.size(); i++) { + _selectedCorners.getMat().ptr< Point2f >(0)[i] = filteredChessboardImgPoints[i]; + } + + _selectedIds.create((int)filteredIds.size(), 1, CV_32SC1); + for (unsigned int i = 0; i < filteredIds.size(); i++) { + _selectedIds.getMat().ptr< int >(0)[i] = filteredIds[i]; + } + + return (unsigned 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 CharucoBoard &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().ptr< Point2f >(0)[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().ptr< int >(0)[k] == markerId) { + markerIdx = k; + break; + } + } + if (markerIdx == -1) continue; + Point2f markerCorner = + markerCorners.getMat(markerIdx).ptr< Point2f >(0)[board.nearestMarkerCorners[i][j]]; + Point2f charucoCorner = charucoCorners.getMat().ptr< Point2f >(0)[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 CharucoBoard &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; + detectedBoardMarkers = + aruco::estimatePoseBoard(_markerCorners, _markerIds, board, _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 + unsigned int nRefinedCorners; + nRefinedCorners = _selectAndRefineChessboardCorners( + allChessboardImgPoints, _image, _charucoCorners, _charucoIds, subPixWinSizes); + + // to return a charuco corner, its two closes aruco markers should have been detected + nRefinedCorners = _filterCornersWithoutMinMarkers(board, _charucoCorners, _charucoIds, + _markerIds, 2, _charucoCorners, _charucoIds); + + return nRefinedCorners; + } + + + + /** + * Interpolate charuco corners using local homography + */ + static int _interpolateCornersCharucoLocalHom(InputArrayOfArrays _markerCorners, + InputArray _markerIds, InputArray _image, + const CharucoBoard &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().ptr< int >(0)[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(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().ptr< int >(0)[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 + unsigned int nRefinedCorners; + nRefinedCorners = _selectAndRefineChessboardCorners( + allChessboardImgPoints, _image, _charucoCorners, _charucoIds, subPixWinSizes); + + // to return a charuco corner, its two closes aruco markers should have been detected + nRefinedCorners = _filterCornersWithoutMinMarkers(board, _charucoCorners, _charucoIds, + _markerIds, 2, _charucoCorners, _charucoIds); + + return nRefinedCorners; + } + + + + /** + */ + int interpolateCornersCharuco(InputArrayOfArrays _markerCorners, InputArray _markerIds, + InputArray _image, const CharucoBoard &board, + OutputArray _charucoCorners, OutputArray _charucoIds, + InputArray _cameraMatrix, InputArray _distCoeffs) { + + // if camera parameters are avaible, use approximated calibration + if (_cameraMatrix.total() != 0) { + return _interpolateCornersCharucoApproxCalib(_markerCorners, _markerIds, _image, board, + _cameraMatrix, _distCoeffs, _charucoCorners, + _charucoIds); + } + // else use local homography + else { + return _interpolateCornersCharucoLocalHom(_markerCorners, _markerIds, _image, board, + _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().ptr< Point2f >(0)[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().ptr< int >(0)[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, + CharucoBoard &board, InputArray _cameraMatrix, InputArray _distCoeffs, + OutputArray _rvec, OutputArray _tvec) { + + 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().ptr< int >(0)[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); + + return true; + } + + + + + /** + */ + double calibrateCameraCharuco(InputArrayOfArrays _charucoCorners, InputArrayOfArrays _charucoIds, + const CharucoBoard &board, Size imageSize, + InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs, + OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, 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).ptr< int >(0)[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, 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 = 0.12f; + + // create Charuco board layout for diamond (3x3 layout) + CharucoBoard charucoDiamondLayout; + Dictionary dict = getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME(0)); + 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.getMat().type() == CV_8UC3) + cvtColor(_image.getMat(), grey, COLOR_BGR2GRAY); + else + _image.getMat().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++) { + perimeterSq += + (corners.ptr< Point2f >()[c].x - corners.ptr< Point2f >()[(c + 1) % 4].x) * + (corners.ptr< Point2f >()[c].x - corners.ptr< Point2f >()[(c + 1) % 4].x) + + (corners.ptr< Point2f >()[c].y - corners.ptr< Point2f >()[(c + 1) % 4].y) * + (corners.ptr< Point2f >()[c].y - corners.ptr< Point2f >()[(c + 1) % 4].y); + } + // maximum reprojection error relative to perimeter + float minRepDistance = perimeterSq * minRepDistanceRate * minRepDistanceRate; + + int currentId = _markerIds.getMat().ptr< 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; + aruco::refineDetectedMarkers(grey, charucoDiamondLayout, 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().ptr< 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 + _diamondIds.create((int)diamondIds.size(), 1, CV_32SC4); + for (unsigned int i = 0; i < diamondIds.size(); i++) + _diamondIds.getMat().ptr< Vec4i >(0)[i] = diamondIds[i]; + + _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).ptr< Point2f >()[j] = diamondCorners[i][j]; + } + } + } + } + + + + + /** + */ + void drawCharucoDiamond(Dictionary 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 + CharucoBoard 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.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 composed by four numbers + 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< Vec4i >(0)[i]; + putText(_image, s.str(), cent, FONT_HERSHEY_SIMPLEX, 0.5, textColor, 2); + } + } + } + + + /** + */ + Dictionary::Dictionary(const Mat &_bytesList, int _markerSize, int _maxcorr) { + markerSize = _markerSize; + maxCorrectionBits = _maxcorr; + bytesList = _bytesList; + } + + + + /** + */ + 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); + 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 &getPredefinedDictionary(PREDEFINED_DICTIONARY_NAME name) { + switch (name) { + + case DICT_ARUCO_ORIGINAL: + return DICT_ARUCO_DATA; + + case DICT_4X4_50: + return DICT_4X4_50_DATA; + case DICT_4X4_100: + return DICT_4X4_100_DATA; + case DICT_4X4_250: + return DICT_4X4_250_DATA; + case DICT_4X4_1000: + return DICT_4X4_1000_DATA; + + case DICT_5X5_50: + return DICT_5X5_50_DATA; + case DICT_5X5_100: + return DICT_5X5_100_DATA; + case DICT_5X5_250: + return DICT_5X5_250_DATA; + case DICT_5X5_1000: + return DICT_5X5_1000_DATA; + + case DICT_6X6_50: + return DICT_6X6_50_DATA; + case DICT_6X6_100: + return DICT_6X6_100_DATA; + case DICT_6X6_250: + return DICT_6X6_250_DATA; + case DICT_6X6_1000: + return DICT_6X6_1000_DATA; + + case DICT_7X7_50: + return DICT_7X7_50_DATA; + case DICT_7X7_100: + return DICT_7X7_100_DATA; + case DICT_7X7_250: + return DICT_7X7_250_DATA; + case DICT_7X7_1000: + return DICT_7X7_1000_DATA; + + } + return DICT_4X4_50_DATA; + } + + + /** + * @brief Generates a random marker Mat of size markerSize x markerSize + */ + static Mat _generateRandomMarker(int markerSize) { + 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 = rand() % 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; + } + + /** + */ + Dictionary generateCustomDictionary(int nMarkers, int markerSize, + const Dictionary &baseDictionary) { + + Dictionary out; + 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); + + 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; + } + + } +} diff --git a/multi-camera/src/main.cpp b/multi-camera/src/main.cpp new file mode 100644 index 0000000..4ef223b --- /dev/null +++ b/multi-camera/src/main.cpp @@ -0,0 +1,253 @@ +/////////////////////////////////////////////////////////////////////////// +// +// Copyright (c) 2019, STEREOLABS. +// +// All rights reserved. +// +// 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 COPYRIGHT +// OWNER 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. +// +/////////////////////////////////////////////////////////////////////////// + +/*********************************************************************************************** + ** This sample demonstrates how to reloc a ZED camera using an ArUco marker. ** + ** Images are captured with the ZED SDK and cameras poses is then computed from ArUco pattern ** + ** to reset ZED tracking with this known position. ** + ***********************************************************************************************/ + +#ifdef _DEBUG +#error Please build the project in Release mode +#endif + +// Standard includes +#include +#include + +// ZED includes +#include + +// OCV includes +#include + +// Sample includes +#include "aruco.hpp" +#include "GLViewer.hpp" + +// Using std and sl namespaces +using namespace std; +using namespace sl; + +/** +Global struct to store all needed infos + */ +struct CameraData { + Camera zed; + Mat point_cloud; + Mat im_left; + cv::Mat im_left_ocv; + cv::Mat im_left_ocv_rgb; + cv::Matx33d camera_matrix = cv::Matx33d::eye(); + cv::Matx dist_coeffs = cv::Vec4f::zeros(); + int id = -1; + bool is_reloc = false; + string info; +}; + +/** +ArUco related data +*/ +struct ArucoData { + cv::aruco::Dictionary dictionary; + float marker_length; +}; + +// Global objetcts +bool quit; +GLViewer viewer; + + +// Sample functions +void run(vector &zeds, ArucoData &acuroData); +void tryReloc(CameraData &it, ArucoData &acuroData); +void displayMarker(CameraData &it, ArucoData &acuroData); +void close(); + +int main(int argc, char **argv) { + // Set configuration parameters + InitParameters initParameters; + initParameters.coordinate_units = UNIT_METER; + initParameters.depth_mode = DEPTH_MODE_ULTRA; + initParameters.camera_disable_imu = true; // for this sample, IMU (of ZED-M) is disable, we use the gravity given by the marker. + + // detect nummber of connected ZED camera. + auto zed_infos = Camera::getDeviceList(); + int nb_zeds = zed_infos.size(); + vector zeds(nb_zeds); + + // specify size for the point cloud + Resolution res(720, 404); + + // define Positional Tracking parameters + TrackingParameters trackingParameters; + trackingParameters.enable_spatial_memory = false; + + ArucoData acuroData; + acuroData.dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_100); + acuroData.marker_length = 0.15f; // Size real size of the maker in meter + + cout << "Make sure the ArUco marker is a 6x6 (100), measuring " << acuroData.marker_length * 1000 << " mm" << endl; + + int nb_zed_open = 0; + // try to open all the connected cameras + for (int i = 0; i < nb_zeds; i++) { + initParameters.camera_linux_id = zed_infos[i].id; + ERROR_CODE err = zeds[i].zed.open(initParameters); + if (err == SUCCESS) { + nb_zed_open++; + zeds[i].id = i; + zeds[i].point_cloud.alloc(res, MAT_TYPE_32F_C4, MEM_GPU); + // retrieve camera calibration information for aruco detection + auto camCalib = zeds[i].zed.getCameraInformation().calibration_parameters.left_cam; + zeds[i].camera_matrix(0, 0) = camCalib.fx; + zeds[i].camera_matrix(1, 1) = camCalib.fy; + zeds[i].camera_matrix(0, 2) = camCalib.cx; + zeds[i].camera_matrix(1, 2) = camCalib.cy; + + zeds[i].im_left.alloc(camCalib.image_size, MAT_TYPE_8U_C4); + zeds[i].im_left_ocv = cv::Mat(zeds[i].im_left.getHeight(), zeds[i].im_left.getWidth(), CV_8UC4, zeds[i].im_left.getPtr(MEM_CPU)); + zeds[i].im_left_ocv_rgb = cv::Mat(zeds[i].im_left.getHeight(), zeds[i].im_left.getWidth(), CV_8UC3); + + // start Positional tracking (will be reset with the marker position) + zeds[i].zed.enableTracking(trackingParameters); + + zeds[i].info = std::string(toString(zed_infos[i].camera_model)) + " " + to_string(zed_infos[i].id) + " SN" + std::to_string(zed_infos[i].serial_number); + cout << "Opening " << zeds[i].info << endl; + } + } + + if (nb_zed_open != nb_zeds) { + cout << "Error: Number of ZED open: " << nb_zed_open << " vs " << nb_zeds << " detected.\n"; + return 1; + } + + if (nb_zed_open == 0) { + cout << "Error: No ZED detected\n"; + return 1; + } + + // initialise 3D viewer + viewer.init(res.width, res.height, nb_zeds); + + // Start the camera thread + quit = false; + thread zed_callback(run, ref(zeds), ref(acuroData)); + + // Set the display callback + glutCloseFunc(close); + glutMainLoop(); + + // Stop callback + if (zed_callback.joinable()) + zed_callback.join(); + + // Free buffer and close the ZEDs + for (auto &it : zeds) + it.point_cloud.free(); + + for (auto &it : zeds) + it.zed.close(); + + return 0; +} + +/** + This function loops to get image and motion data from the ZED. It is similar to a callback. + Add your own code here. + **/ +void run(vector &zeds, ArucoData &acuroData) { + RuntimeParameters rt_p; + rt_p.enable_point_cloud = true; + // ask for point cloud in World Frame, then they will be displayed with the same reference + rt_p.measure3D_reference_frame = REFERENCE_FRAME_WORLD; + + while (!quit) { + for (auto &it : zeds) { // for all camera + if (it.zed.grab(rt_p) == SUCCESS) { // grab new image + it.zed.retrieveImage(it.im_left); + displayMarker(it, acuroData); + if (!it.is_reloc) { // if still ne relocated, grab left image and look for ArUco pattern + tryReloc(it, acuroData); + } else { // if relocated, grab point cloud and draw it + it.zed.retrieveMeasure(it.point_cloud, MEASURE_XYZRGBA, MEM_GPU, it.point_cloud.getWidth(), it.point_cloud.getHeight()); + viewer.updatePointCloud(it.point_cloud, it.id); + } + } + } + + if (viewer.askReset()) { // you can force a new reloc by pressing 'space' from the 3D view; + cout << "Reset asked\n"; + for (auto &it : zeds) + it.is_reloc = false; + } + sleep_ms(1); + } +} + +void tryReloc(CameraData &it, ArucoData &acuroData) { + vector ids; + vector > corners; + + cv::cvtColor(it.im_left_ocv, it.im_left_ocv_rgb, cv::COLOR_RGBA2RGB); + cv::aruco::detectMarkers(it.im_left_ocv_rgb, acuroData.dictionary, corners, ids); + + if (ids.size()) { // an ArUco marker has been detected + vector rvecs, tvecs; + cv::aruco::estimatePoseSingleMarkers(corners, acuroData.marker_length, it.camera_matrix, it.dist_coeffs, rvecs, tvecs); + + //compute a Transform based on the first marker data + Transform pose; + pose.setTranslation(sl::float3(tvecs[0](0), tvecs[0](1), tvecs[0](2))); + pose.setRotationVector(sl::float3(rvecs[0](0), rvecs[0](1), rvecs[0](2))); + pose.inverse(); + // reset the ZED Positional tracking with the position given by the marker + it.zed.resetTracking(pose); + it.is_reloc = true; + cout << "ZED " << it.id << " is relocated\n"; + } +} + +void displayMarker(CameraData &it, ArucoData &acuroData) { + vector ids; + vector > corners; + + cv::cvtColor(it.im_left_ocv, it.im_left_ocv_rgb, cv::COLOR_RGBA2RGB); + cv::aruco::detectMarkers(it.im_left_ocv_rgb, acuroData.dictionary, corners, ids); + + if (ids.size()) { // an ArUco marker has been detected + vector rvecs, tvecs; + cv::aruco::estimatePoseSingleMarkers(corners, acuroData.marker_length, it.camera_matrix, it.dist_coeffs, rvecs, tvecs); + + // draw the marker + cv::aruco::drawDetectedMarkers(it.im_left_ocv_rgb, corners, ids, cv::Scalar(236, 188, 26)); + cv::aruco::drawAxis(it.im_left_ocv_rgb, it.camera_matrix, it.dist_coeffs, rvecs[0], tvecs[0], acuroData.marker_length * 0.5f); + } + + cv::imshow(it.info, it.im_left_ocv_rgb); + cv::waitKey(10); +} + +/** + This function closes the callback (thread) and the GL viewer + **/ +void close() { + quit = true; +}