Class cv::aruco::CharucoBoard#

ChArUco board is a planar chessboard where the markers are placed inside the white squares of a chessboard. View details

#include <opencv2/objdetect/aruco_board.hpp>

Collaboration diagram for cv::aruco::CharucoBoard:

Public Member Functions#

Public Member Functions inherited from cv::aruco::Board

Return	Name	Description
	`Board()`
	`Board(` `InputArrayOfArrays objPoints,` `const Dictionary & dictionary,` `InputArray ids )`	Common Board constructor.
`void`	`generateImage(` `Size outSize,` `OutputArray img,` `int marginSize = 0,` `int borderBits = 1 )`	Draw a planar board.
`const Dictionary &`	`getDictionary()`	return the Dictionary of markers employed for this board
`const std::vector< int > &`	`getIds()`	vector of the identifiers of the markers in the board (should be the same size as objPoints)
`const std::vector< std::vector< Point3f > > &`	`getObjPoints()`	return array of object points of all the marker corners in the board.
`const Point3f &`	`getRightBottomCorner()`	get coordinate of the bottom right corner of the board, is set when calling the function create()
`void`	`matchImagePoints(` `InputArrayOfArrays detectedCorners,` `InputArray detectedIds,` `OutputArray objPoints,` `OutputArray imgPoints )`	Given a board configuration and a set of detected markers, returns the corresponding image points and object points, can be used in solvePnP()

Additional Inherited Members#

Detailed Description#

ChArUco board is a planar chessboard 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. The board image can be drawn using generateImage() method.

Constructor & Destructor Documentation#

CharucoBoard()#

cv::aruco::CharucoBoard::CharucoBoard()

Python:

cv.aruco.CharucoBoard(size, squareLength, markerLength, dictionary[, ids]) -> <aruco_CharucoBoard object>

CharucoBoard()#

cv::aruco::CharucoBoard::CharucoBoard(
const Size & size,
float squareLength,
float markerLength,
const Dictionary & dictionary,
InputArray ids = noArray() )

Python:

cv.aruco.CharucoBoard(size, squareLength, markerLength, dictionary[, ids]) -> <aruco_CharucoBoard object>

CharucoBoard constructor.

Parameters

size — number of chessboard squares in x and y directions
squareLength — squareLength chessboard square side length (normally in meters)
markerLength — marker side length (same unit than squareLength)
dictionary — dictionary of markers indicating the type of markers
ids — array of id used markers The first markers in the dictionary are used to fill the white chessboard squares.

Here is the call graph for this function:

Member Function Documentation#

checkCharucoCornersCollinear()#

bool cv::aruco::CharucoBoard::checkCharucoCornersCollinear(InputArray charucoIds)

Python:

cv.aruco.CharucoBoard.checkCharucoCornersCollinear(charucoIds) -> retval

check whether the ChArUco markers are collinear

The number of ids in charucoIDs should be <= the number of chessboard corners in the board. This functions checks whether the charuco corners are on a straight line (returns true, if so), or not (false). Axis parallel, as well as diagonal and other straight lines detected. Degenerate cases: for number of charucoIDs <= 2,the function returns true.

Parameters

charucoIds — list of identifiers for each corner in charucoCorners per frame.

Returns

bool value, 1 (true) if detected corners form a line, 0 (false) if they do not. solvePnP, calibration functions will fail if the corners are collinear (true).

getChessboardCorners()#

std::vector< Point3f > cv::aruco::CharucoBoard::getChessboardCorners()

Python:

cv.aruco.CharucoBoard.getChessboardCorners() -> retval

get CharucoBoard::chessboardCorners

getChessboardSize()#

Size cv::aruco::CharucoBoard::getChessboardSize()

Python:

cv.aruco.CharucoBoard.getChessboardSize() -> retval

getLegacyPattern()#

bool cv::aruco::CharucoBoard::getLegacyPattern()

Python:

cv.aruco.CharucoBoard.getLegacyPattern() -> retval

getMarkerLength()#

float cv::aruco::CharucoBoard::getMarkerLength()

Python:

cv.aruco.CharucoBoard.getMarkerLength() -> retval

getNearestMarkerCorners()#

std::vector< std::vector< int > > cv::aruco::CharucoBoard::getNearestMarkerCorners()

get CharucoBoard::nearestMarkerCorners, for each charuco corner, nearest marker corner id of each marker

getNearestMarkerIdx()#

std::vector< std::vector< int > > cv::aruco::CharucoBoard::getNearestMarkerIdx()

get CharucoBoard::nearestMarkerIdx, for each charuco corner, nearest marker index in ids array

getSquareLength()#

float cv::aruco::CharucoBoard::getSquareLength()

Python:

cv.aruco.CharucoBoard.getSquareLength() -> retval

setLegacyPattern()#

void cv::aruco::CharucoBoard::setLegacyPattern(bool legacyPattern)

Python:

cv.aruco.CharucoBoard.setLegacyPattern(legacyPattern)

set legacy chessboard pattern.

Legacy setting creates chessboard patterns starting with a white box in the upper left corner if there is an even row count of chessboard boxes, otherwise it starts with a black box. This setting ensures compatibility to patterns created with OpenCV versions prior OpenCV 4.6.0. See opencv/opencv#23152.

Default value: false.

Source file#

The documentation for this class was generated from the following file:

opencv2/objdetect/aruco_board.hpp