OBJDETECT Module API Reference

Complete documentation for the OBJDETECT classes, methods, and enums in OpenCV5Sharp. Equivalent to the Official OpenCV Objdetect Documentation.

📦 Classes and Structs

`CirclesGridFinderParameters`

Inherits from: DisposableOpenCVObject

Wrapper for OpenCV's native functionality.

Properties

Property	Type	Description
`DensityNeighborhoodSize`	`Size2F`	Gets or sets the densityNeighborhoodSize property.
`MinDensity`	`float`	Gets or sets the minDensity property.
`KmeansAttempts`	`int`	Gets or sets the kmeansAttempts property.
`MinDistanceToAddKeypoint`	`int`	Gets or sets the minDistanceToAddKeypoint property.
`KeypointScale`	`int`	Gets or sets the keypointScale property.
`MinGraphConfidence`	`float`	Gets or sets the minGraphConfidence property.
`VertexGain`	`float`	Gets or sets the vertexGain property.
`VertexPenalty`	`float`	Gets or sets the vertexPenalty property.
`ExistingVertexGain`	`float`	Gets or sets the existingVertexGain property.
`EdgeGain`	`float`	Gets or sets the edgeGain property.
`EdgePenalty`	`float`	Gets or sets the edgePenalty property.
`ConvexHullFactor`	`float`	Gets or sets the convexHullFactor property.
`MinRNGEdgeSwitchDist`	`float`	Gets or sets the minRNGEdgeSwitchDist property.
`GridType`	`CirclesGridFinderParametersGridType`	Gets or sets the gridType property.
`SquareSize`	`float`	Gets or sets the squareSize property.
`MaxRectifiedDistance`	`float`	Gets or sets the maxRectifiedDistance property.

Constructors

new CirclesGridFinderParameters()
- Summary: Wrapper for OpenCV's native functionality.

`FaceDetectorYN`

Inherits from: DisposableOpenCVObject

DNN-based face detector

Detailed Remarks: model download link: https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet

Methods

void SetInputSize(Size input_size)
- Summary: Set the size for the network input, which overwrites the input size of creating model. Call this method when the size of input image does not match the input size when creating model * * input_size the size of the input image
- Parameter input_size: The input_size parameter.
Size GetInputSize()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetScoreThreshold(float score_threshold)
- Summary: Set the score threshold to filter out bounding boxes of score less than the given value * * score_threshold threshold for filtering out bounding boxes
- Parameter score_threshold: The score_threshold parameter.
float GetScoreThreshold()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetNMSThreshold(float nms_threshold)
- Summary: Set the Non-maximum-suppression threshold to suppress bounding boxes that have IoU greater than the given value * * nms_threshold threshold for NMS operation
- Parameter nms_threshold: The nms_threshold parameter.
float GetNMSThreshold()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetTopK(int top_k)
- Summary: Set the number of bounding boxes preserved before NMS * * top_k the number of bounding boxes to preserve from top rank based on score
- Parameter top_k: The top_k parameter.
int GetTopK()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
int Detect(Mat image, Mat faces)
- Summary: Detects faces in the input image. Following is an example output.
- Remarks:
- Parameter image: an image to detect
- Parameter faces: detection results stored in a 2D Mat of shape [num_faces, 15]
- 0-1: x, y of bbox top left corner
- 2-3: width, height of bbox
- 4-5: x, y of right eye (blue point in the example image)
- 6-7: x, y of left eye (red point in the example image)
- 8-9: x, y of nose tip (green point in the example image)
- 10-11: x, y of right corner of mouth (pink point in the example image)
- 12-13: x, y of left corner of mouth (yellow point in the example image)
- 14: face score
Parameter image: Input image.
Parameter faces: The faces parameter.
Returns: The returned value.
FaceDetectorYN? Create(string model, string config, Size input_size, float score_threshold, float nms_threshold, int top_k, int backend_id, int target_id)
- Summary: Creates an instance of face detector class with given parameters * * model the path to the requested model * config the path to the config file for compatibility, which is not requested for ONNX models * input_size the size of the input image * score_threshold the threshold to filter out bounding boxes of score smaller than the given value * nms_threshold the threshold to suppress bounding boxes of IoU bigger than the given value * top_k keep top K bboxes before NMS * backend_id the id of backend * target_id the id of target device
- Parameter model: The model parameter.
- Parameter config: The config parameter.
- Parameter input_size: The input_size parameter.
- Parameter score_threshold: The score_threshold parameter.
- Parameter nms_threshold: The nms_threshold parameter.
- Parameter top_k: The top_k parameter.
- Parameter backend_id: The backend_id parameter.
- Parameter target_id: The target_id parameter.
- Returns: The returned value.
FaceDetectorYN? Create(string framework, IntPtr bufferModel, IntPtr bufferConfig, Size input_size, float score_threshold, float nms_threshold, int top_k, int backend_id, int target_id)
- Summary: This is an overloaded member function, provided for convenience.
- Remarks:
- Parameter framework: Name of origin framework
- Parameter bufferModel: A buffer with a content of binary file with weights
- Parameter bufferConfig: A buffer with a content of text file contains network configuration
- Parameter input_size: the size of the input image
- Parameter score_threshold: the threshold to filter out bounding boxes of score smaller than the given value
- Parameter nms_threshold: the threshold to suppress bounding boxes of IoU bigger than the given value
- Parameter top_k: keep top K bboxes before NMS
- Parameter backend_id: the id of backend
- Parameter target_id: the id of target device
Parameter framework: The framework parameter.
Parameter bufferModel: The bufferModel parameter.
Parameter bufferConfig: The bufferConfig parameter.
Parameter input_size: The input_size parameter.
Parameter score_threshold: The score_threshold parameter.
Parameter nms_threshold: The nms_threshold parameter.
Parameter top_k: The top_k parameter.
Parameter backend_id: The backend_id parameter.
Parameter target_id: The target_id parameter.
Returns: The returned value.

`FaceRecognizerSF`

Inherits from: DisposableOpenCVObject

DNN-based face recognizer

Detailed Remarks: model download link: https://github.com/opencv/opencv_zoo/tree/master/models/face_recognition_sface

Methods

void AlignCrop(Mat src_img, Mat face_box, Mat aligned_img)
- Summary: Aligns detected face with the source input image and crops it * src_img input image * face_box the detected face result from the input image * aligned_img output aligned image
- Parameter src_img: The src_img parameter.
- Parameter face_box: The face_box parameter.
- Parameter aligned_img: The aligned_img parameter.
void Feature(Mat aligned_img, Mat face_feature)
- Summary: Extracts face feature from aligned image * aligned_img input aligned image * face_feature output face feature
- Parameter aligned_img: The aligned_img parameter.
- Parameter face_feature: The face_feature parameter.
double Match(Mat face_feature1, Mat face_feature2, int dis_type)
- Summary: Calculates the distance between two face features * face_feature1 the first input feature * face_feature2 the second input feature of the same size and the same type as face_feature1 * dis_type defines how to calculate the distance between two face features with optional values "FR_COSINE" or "FR_NORM_L2"
- Parameter face_feature1: The face_feature1 parameter.
- Parameter face_feature2: The face_feature2 parameter.
- Parameter dis_type: The dis_type parameter.
- Returns: The returned value.
FaceRecognizerSF? Create(string model, string config, int backend_id, int target_id)
- Summary: Creates an instance of this class with given parameters * model the path of the onnx model used for face recognition * config the path to the config file for compatibility, which is not requested for ONNX models * backend_id the id of backend * target_id the id of target device
- Parameter model: The model parameter.
- Parameter config: The config parameter.
- Parameter backend_id: The backend_id parameter.
- Parameter target_id: The target_id parameter.
- Returns: The returned value.
FaceRecognizerSF? Create(string framework, IntPtr bufferModel, IntPtr bufferConfig, int backend_id, int target_id)
- Summary: * Creates an instance of this class from a buffer containing the model weights and configuration.
- Remarks:
- Parameter framework: Name of the framework (ONNX, etc.)
- Parameter bufferModel: A buffer containing the binary model weights.
- Parameter bufferConfig: A buffer containing the network configuration.
- Parameter backend_id: The id of the backend.
- Parameter target_id: The id of the target device.

Returns: A pointer to the created instance of FaceRecognizerSF.

Parameter framework: The framework parameter.
Parameter bufferModel: The bufferModel parameter.
Parameter bufferConfig: The bufferConfig parameter.
Parameter backend_id: The backend_id parameter.
Parameter target_id: The target_id parameter.
Returns: The returned value.

`GraphicalCodeDetector`

Inherits from: DisposableOpenCVObject

Wrapper for OpenCV's native functionality.

Methods

bool Detect(Mat img, Mat points)
- Summary: Detects graphical code in image and returns the quadrangle containing the code.
- Parameter img: grayscale or color (BGR) image containing (or not) graphical code.
- Parameter points: Output vector of vertices of the minimum-area quadrangle containing the code.
- Returns: The returned value.
string? Decode(Mat img, Mat points, Mat? straight_code)
- Summary: Decodes graphical code in image once it's found by the detect() method.
- Remarks:

Returns UTF8-encoded output string or empty string if the code cannot be decoded.

Parameter img: grayscale or color (BGR) image containing graphical code.
Parameter points: Quadrangle vertices found by detect() method (or some other algorithm).
Parameter straight_code: The optional output image containing binarized code, will be empty if not found.
Returns: The returned value.
string? DetectAndDecode(Mat img, Mat? points, Mat? straight_code)
- Summary: Both detects and decodes graphical code
- Parameter img: grayscale or color (BGR) image containing graphical code.
- Parameter points: optional output array of vertices of the found graphical code quadrangle, will be empty if not found.
- Parameter straight_code: The optional output image containing binarized code
- Returns: The returned value.
bool DetectMulti(Mat img, Mat points)
- Summary: Detects graphical codes in image and returns the vector of the quadrangles containing the codes.
- Parameter img: grayscale or color (BGR) image containing (or not) graphical codes.
- Parameter points: Output vector of vector of vertices of the minimum-area quadrangle containing the codes.
- Returns: The returned value.
bool DecodeMulti(Mat img, Mat points, IntPtr decoded_info, IntPtr straight_code)
- Summary: Decodes graphical codes in image once it's found by the detect() method.
- Parameter img: grayscale or color (BGR) image containing graphical codes.
- Parameter points: vector of Quadrangle vertices found by detect() method (or some other algorithm).
- Parameter decoded_info: UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded.
- Parameter straight_code: The optional output vector of images containing binarized codes
- Returns: The returned value.
bool DetectAndDecodeMulti(Mat img, IntPtr decoded_info, Mat? points, IntPtr straight_code)
- Summary: Both detects and decodes graphical codes
- Parameter img: grayscale or color (BGR) image containing graphical codes.
- Parameter decoded_info: UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded.
- Parameter points: optional output vector of vertices of the found graphical code quadrangles. Will be empty if not found.
- Parameter straight_code: The optional vector of images containing binarized codes - If there are QR codes encoded with a Structured Append mode on the image and all of them detected and decoded correctly, method writes a full message to position corresponds to 0-th code in a sequence. The rest of QR codes from the same sequence have empty string.
- Returns: The returned value.

`QRCodeDetector`

Inherits from: GraphicalCodeDetector

QR code detector.

Constructors

new QRCodeDetector()
- Summary: Wrapper for OpenCV's native functionality.

Methods

QRCodeDetector? SetEpsX(double epsX)
- Summary: sets the epsilon used during the horizontal scan of QR code stop marker detection.
- Parameter epsX: Epsilon neighborhood, which allows you to determine the horizontal pattern of the scheme 1:1:3:1:1 according to QR code standard.
- Returns: The returned value.
QRCodeDetector? SetEpsY(double epsY)
- Summary: sets the epsilon used during the vertical scan of QR code stop marker detection.
- Parameter epsY: Epsilon neighborhood, which allows you to determine the vertical pattern of the scheme 1:1:3:1:1 according to QR code standard.
- Returns: The returned value.
QRCodeDetector? SetUseAlignmentMarkers(bool useAlignmentMarkers)
- Summary: use markers to improve the position of the corners of the QR code * * alignmentMarkers using by default
- Parameter useAlignmentMarkers: The useAlignmentMarkers parameter.
- Returns: The returned value.
string? DecodeCurved(Mat img, Mat points, Mat? straight_qrcode)
- Summary: Decodes QR code on a curved surface in image once it's found by the detect() method.
- Remarks:

Returns UTF8-encoded output string or empty string if the code cannot be decoded.

Parameter img: grayscale or color (BGR) image containing QR code.
Parameter points: Quadrangle vertices found by detect() method (or some other algorithm).
Parameter straight_qrcode: The optional output image containing rectified and binarized QR code
Returns: The returned value.
string? DetectAndDecodeCurved(Mat img, Mat? points, Mat? straight_qrcode)
- Summary: Both detects and decodes QR code on a curved surface
- Parameter img: grayscale or color (BGR) image containing QR code.
- Parameter points: optional output array of vertices of the found QR code quadrangle. Will be empty if not found.
- Parameter straight_qrcode: The optional output image containing rectified and binarized QR code
- Returns: The returned value.
IntPtr GetEncoding(int codeIdx)
- Summary: Returns a kind of encoding for the decoded info from the latest decode or detectAndDecode call
- Parameter codeIdx: an index of the previously decoded QR code. When decode or detectAndDecode is used, valid value is zero. For decodeMulti or detectAndDecodeMulti use indices corresponding to the output order.
- Returns: The returned value.

`QRCodeDetectorAruco`

Inherits from: GraphicalCodeDetector

QR code detector based on Aruco markers detection code.

Constructors

new QRCodeDetectorAruco()
- Summary: Wrapper for OpenCV's native functionality.

Methods

IntPtr GetDetectorParameters()
- Summary: Detector parameters getter. See QRCodeDetectorAruco.Params
- Returns: The returned value.
QRCodeDetectorAruco? SetDetectorParameters(IntPtr @params)
- Summary: Detector parameters setter. See QRCodeDetectorAruco.Params
- Parameter params: The @params parameter.
- Returns: The returned value.
IntPtr GetArucoParameters()
- Summary: Aruco detector parameters are used to search for the finder patterns.
- Returns: The returned value.
void SetArucoParameters(IntPtr @params)
- Summary: Aruco detector parameters are used to search for the finder patterns.
- Parameter params: The @params parameter.

`QRCodeDetectorArucoParams`

Inherits from: DisposableOpenCVObject

Wrapper for OpenCV's native functionality.

Properties

Property	Type	Description
`MinModuleSizeInPyramid`	`float`	Gets or sets the minModuleSizeInPyramid property.
`MaxRotation`	`float`	Gets or sets the maxRotation property.
`MaxModuleSizeMismatch`	`float`	Gets or sets the maxModuleSizeMismatch property.
`MaxTimingPatternMismatch`	`float`	Gets or sets the maxTimingPatternMismatch property.
`MaxPenalties`	`float`	Gets or sets the maxPenalties property.
`MaxColorsMismatch`	`float`	Gets or sets the maxColorsMismatch property.
`ScaleTimingPatternScore`	`float`	Gets or sets the scaleTimingPatternScore property.

Constructors

new QRCodeDetectorArucoParams()
- Summary: Wrapper for OpenCV's native functionality.

`QRCodeEncoder`

Inherits from: DisposableOpenCVObject

QR code encoder.

Methods

QRCodeEncoder? Create(IntPtr parameters)
- Summary: Constructor
- Parameter parameters: QR code encoder parameters QRCodeEncoder.Params
- Returns: The returned value.
void Encode(string encoded_info, Mat qrcode)
- Summary: Generates QR code from input string.
- Parameter encoded_info: Input string to encode.
- Parameter qrcode: Generated QR code.
void EncodeStructuredAppend(string encoded_info, IntPtr qrcodes)
- Summary: Generates QR code from input string in Structured Append mode. The encoded message is splitting over a number of QR codes.
- Parameter encoded_info: Input string to encode.
- Parameter qrcodes: Vector of generated QR codes.

`QRCodeEncoderParams`

Inherits from: DisposableOpenCVObject

QR code encoder parameters.

Properties

Property	Type	Description
`Version`	`int`	Gets or sets the version property.
`CorrectionLevel`	`IntPtr`	Gets or sets the correction_level property.
`Mode`	`IntPtr`	Gets or sets the mode property.
`StructureNumber`	`int`	Gets or sets the structure_number property.

Constructors

new QRCodeEncoderParams()
- Summary: Wrapper for OpenCV's native functionality.

`ArucoArucoDetector`

Inherits from: Algorithm

The main functionality of ArucoDetector class is detection of markers in an image with detectMarkers() method. * * After detecting some markers in the image, you can try to find undetected markers from this dictionary with * refineDetectedMarkers() method. * * See also: DetectorParameters, RefineParameters

Constructors

new ArucoArucoDetector(ArucoDictionary? dictionary, ArucoDetectorParameters? detectorParams, ArucoRefineParameters? refineParams)
- Summary: Basic ArucoDetector constructor * * dictionary indicates the type of markers that will be searched * detectorParams marker detection parameters * refineParams marker refine detection parameters
- Parameter dictionary: The dictionary parameter.
- Parameter detectorParams: The detectorParams parameter.
- Parameter refineParams: The refineParams parameter.
new ArucoArucoDetector(IntPtr dictionaries, ArucoDetectorParameters? detectorParams, ArucoRefineParameters? refineParams)
- Summary: ArucoDetector constructor for multiple dictionaries * * dictionaries indicates the type of markers that will be searched. Empty dictionaries will throw an error. * detectorParams marker detection parameters * refineParams marker refine detection parameters
- Parameter dictionaries: The dictionaries parameter.
- Parameter detectorParams: The detectorParams parameter.
- Parameter refineParams: The refineParams parameter.

Methods

void DetectMarkers(Mat image, IntPtr corners, Mat ids, IntPtr rejectedImgPoints)
- Summary: Basic marker detection * * image input image * corners vector of detected marker corners. For each marker, its four corners * are provided, (e.g Point2f[][] ). For N detected markers, * the dimensions of this array is Nx4. The order of the corners is clockwise. * ids vector of identifiers of the detected markers. The identifier is of type int * (e.g. int[]). For N detected markers, the size of ids is also N. * The identifiers have the same order than the markers in the imgPoints array. * 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 first specified 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. * Note: The function does not correct lens distortion or takes it into account. It's recommended to undistort * input image with corresponding camera model, if camera parameters are known * See also: undistort, estimatePoseSingleMarkers, estimatePoseBoard
- Parameter image: Input image.
- Parameter corners: The corners parameter.
- Parameter ids: The ids parameter.
- Parameter rejectedImgPoints: The rejectedImgPoints parameter.
void DetectMarkersWithConfidence(Mat image, IntPtr corners, Mat ids, Mat markersConfidence, IntPtr rejectedImgPoints)
- Summary: Marker detection with confidence computation * * image input image * corners vector of detected marker corners. For each marker, its four corners * are provided, (e.g Point2f[][] ). For N detected markers, * the dimensions of this array is Nx4. The order of the corners is clockwise. * ids vector of identifiers of the detected markers. The identifier is of type int * (e.g. int[]). For N detected markers, the size of ids is also N. * The identifiers have the same order than the markers in the imgPoints array. * markersConfidence contains the normalized confidence [0;1] of the markers' detection, * defined as 1 minus the normalized uncertainty (percentage of incorrect pixel detections), * with 1 describing a pixel perfect detection. The confidence values are of type float * (e.g. float[]) * 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 first specified 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. * Note: The function does not correct lens distortion or takes it into account. It's recommended to undistort * input image with corresponding camera model, if camera parameters are known * See also: undistort, estimatePoseSingleMarkers, estimatePoseBoard
- Parameter image: Input image.
- Parameter corners: The corners parameter.
- Parameter ids: The ids parameter.
- Parameter markersConfidence: The markersConfidence parameter.
- Parameter rejectedImgPoints: The rejectedImgPoints parameter.
void RefineDetectedMarkers(Mat image, ArucoBoard board, IntPtr detectedCorners, Mat detectedIds, IntPtr rejectedCorners, Mat? cameraMatrix, Mat? distCoeffs, Mat? recoveredIdxs)
- Summary: Refine not detected markers based on the already detected and the board layout * * image input image * board layout of markers in the board. * detectedCorners vector of already detected marker corners. * detectedIds vector of already detected marker identifiers. * rejectedCorners vector of rejected candidates during the marker detection process. * cameraMatrix optional input 3x3 floating-point camera matrix * formula * distCoeffs optional vector of distortion coefficients * formula of 4, 5, 8 or 12 elements * recoveredIdxs Optional array to returns the indexes of the recovered candidates in the * original rejectedCorners array. * * 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. * Note: This function assumes that the board only contains markers from one dictionary, so only the * first configured dictionary is used. It has to match the dictionary of the board to work properly.
- Parameter image: Input image.
- Parameter board: The board parameter.
- Parameter detectedCorners: The detectedCorners parameter.
- Parameter detectedIds: The detectedIds parameter.
- Parameter rejectedCorners: The rejectedCorners parameter.
- Parameter cameraMatrix: The cameraMatrix parameter.
- Parameter distCoeffs: The distCoeffs parameter.
- Parameter recoveredIdxs: The recoveredIdxs parameter.
void DetectMarkersMultiDict(Mat image, IntPtr corners, Mat ids, IntPtr rejectedImgPoints, Mat? dictIndices)
- Summary: Basic marker detection * * image input image * corners vector of detected marker corners. For each marker, its four corners * are provided, (e.g Point2f[][] ). For N detected markers, * the dimensions of this array is Nx4. The order of the corners is clockwise. * ids vector of identifiers of the detected markers. The identifier is of type int * (e.g. int[]). For N detected markers, the size of ids is also N. * The identifiers have the same order than the markers in the imgPoints array. * rejectedImgPoints contains the imgPoints of those squares whose inner code has not a * correct codification. Useful for debugging purposes. * dictIndices vector of dictionary indices for each detected marker. Use getDictionaries() to get the * list of corresponding dictionaries. * * Performs marker detection in the input image. Only markers included in the specific dictionaries * 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. * Note: The function does not correct lens distortion or takes it into account. It's recommended to undistort * input image with corresponding camera model, if camera parameters are known * See also: undistort, estimatePoseSingleMarkers, estimatePoseBoard
- Parameter image: Input image.
- Parameter corners: The corners parameter.
- Parameter ids: The ids parameter.
- Parameter rejectedImgPoints: The rejectedImgPoints parameter.
- Parameter dictIndices: The dictIndices parameter.
ArucoDictionary? GetDictionary()
- Summary: Returns first dictionary from internal list used for marker detection. * Returns: The first dictionary from the configured ArucoDetector.
- Returns: The returned value.
void SetDictionary(ArucoDictionary dictionary)
- Summary: Sets and replaces the first dictionary in internal list to be used for marker detection. * * dictionary The new dictionary that will replace the first dictionary in the internal list.
- Parameter dictionary: The dictionary parameter.
IntPtr GetDictionaries()
- Summary: Returns all dictionaries currently used for marker detection as a vector. * Returns: A Dictionary[] containing all dictionaries used by the ArucoDetector.
- Returns: The returned value.
void SetDictionaries(IntPtr dictionaries)
- Summary: Sets the entire collection of dictionaries to be used for marker detection, replacing any existing dictionaries. * * dictionaries A Dictionary[] containing the new set of dictionaries to be used. * * Configures the ArucoDetector to use the provided vector of dictionaries for marker detection. * This method replaces any dictionaries that were previously set. * Note: Setting an empty vector of dictionaries will throw an error.
- Parameter dictionaries: The dictionaries parameter.
ArucoDetectorParameters? GetDetectorParameters()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetDetectorParameters(ArucoDetectorParameters detectorParameters)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter detectorParameters: The detectorParameters parameter.
ArucoRefineParameters? GetRefineParameters()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetRefineParameters(ArucoRefineParameters refineParameters)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter refineParameters: The refineParameters parameter.
void Write(FileStorage fs, string name)
- Summary: simplified API for language bindings
- Parameter fs: The fs parameter.
- Parameter name: The name parameter.
void Read(FileNode fn)
- Summary: Reads algorithm parameters from a file storage
- Parameter fn: The fn parameter.

`ArucoBoard`

Inherits from: DisposableOpenCVObject

Board of ArUco markers * * A board is a set of markers in the 3D space with a common coordinate system. * The common form of a board of marker is a planar (2D) board, however any 3D layout can be used. * A Board object is composed by: * - The object points of the marker corners, i.e. their coordinates respect to the board system. * - The dictionary which indicates the type of markers of the board * - The identifier of all the markers in the board.

Constructors

new ArucoBoard(IntPtr objPoints, ArucoDictionary dictionary, Mat ids)
- Summary: Common Board constructor * * objPoints array of object points of all the marker corners in the board * dictionary the dictionary of markers employed for this board * ids vector of the identifiers of the markers in the board
- Parameter objPoints: The objPoints parameter.
- Parameter dictionary: The dictionary parameter.
- Parameter ids: The ids parameter.

Methods

ArucoDictionary? GetDictionary()
- Summary: return the Dictionary of markers employed for this board
- Returns: The returned value.
IntPtr GetObjPoints()
- Summary: return array of object points of all the marker corners in the board. * * Each marker include its 4 corners in this order: * - objPoints[i][0] - left-top point of i-th marker * - objPoints[i][1] - right-top point of i-th marker * - objPoints[i][2] - right-bottom point of i-th marker * - objPoints[i][3] - left-bottom point of i-th marker * * Markers are placed in a certain order - row by row, left to right in every row. For M markers, the size is Mx4.
- Returns: The returned value.
IntPtr GetIds()
- Summary: vector of the identifiers of the markers in the board (should be the same size as objPoints) Returns: vector of the identifiers of the markers
- Returns: The returned value.
IntPtr GetRightBottomCorner()
- Summary: get coordinate of the bottom right corner of the board, is set when calling the function create()
- Returns: The returned value.
void MatchImagePoints(IntPtr detectedCorners, Mat detectedIds, Mat objPoints, Mat imgPoints)
- Summary: Given a board configuration and a set of detected markers, returns the corresponding * image points and object points, can be used in SolvePnP() * * detectedCorners List of detected marker corners of the board. * For Board and GridBoard the method expects Point2f[][] or Mat[] with Aruco marker corners. * For CharucoBoard the method expects Point2f[] or Mat with ChAruco corners (chess board corners matched with Aruco markers). * * detectedIds List of identifiers for each marker or charuco corner. * For any Board class the method expects int[] or Mat. * * objPoints Vector of marker points in the board coordinate space. * For any Board class the method expects Point3f[] objectPoints or Mat * * imgPoints Vector of marker points in the image coordinate space. * For any Board class the method expects Point2f[] objectPoints or Mat * * See also: SolvePnP
- Parameter detectedCorners: The detectedCorners parameter.
- Parameter detectedIds: The detectedIds parameter.
- Parameter objPoints: The objPoints parameter.
- Parameter imgPoints: The imgPoints parameter.
void GenerateImage(Size outSize, Mat img, int marginSize, int borderBits)
- Summary: Draw a planar board * * outSize size of the output image in pixels. * 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. * marginSize minimum margins (in pixels) of the board in the output image * borderBits width of the marker borders. * * This function return the image of the board, ready to be printed.
- Parameter outSize: The outSize parameter.
- Parameter img: Input image.
- Parameter marginSize: The marginSize parameter.
- Parameter borderBits: The borderBits parameter.

`ArucoCharucoBoard`

Inherits from: ArucoBoard

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

Detailed Remarks:

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.

Constructors

new ArucoCharucoBoard(Size size, float squareLength, float markerLength, ArucoDictionary dictionary, Mat? ids)
- Summary: CharucoBoard constructor * * 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.
- Parameter size: The size parameter.
- Parameter squareLength: The squareLength parameter.
- Parameter markerLength: The markerLength parameter.
- Parameter dictionary: The dictionary parameter.
- Parameter ids: The ids parameter.

Methods

void SetLegacyPattern(bool legacyPattern)
- Summary: 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 https://github.com/opencv/opencv/issues/23152. * * Default value: false.
- Parameter legacyPattern: The legacyPattern parameter.
bool GetLegacyPattern()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
Size GetChessboardSize()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
float GetSquareLength()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
float GetMarkerLength()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
IntPtr GetChessboardCorners()
- Summary: get CharucoBoard.chessboardCorners
- Returns: The returned value.
bool CheckCharucoCornersCollinear(Mat charucoIds)
- Summary: check whether the ChArUco markers are collinear * * 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). * * 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.
- Parameter charucoIds: The charucoIds parameter.
- Returns: The returned value.

`ArucoCharucoDetector`

Inherits from: Algorithm

Wrapper for OpenCV's native functionality.

Constructors

new ArucoCharucoDetector(ArucoCharucoBoard board, ArucoCharucoParameters? charucoParams, ArucoDetectorParameters? detectorParams, ArucoRefineParameters? refineParams)
- Summary: Basic CharucoDetector constructor * * board ChAruco board * charucoParams charuco detection parameters * detectorParams marker detection parameters * refineParams marker refine detection parameters
- Parameter board: The board parameter.
- Parameter charucoParams: The charucoParams parameter.
- Parameter detectorParams: The detectorParams parameter.
- Parameter refineParams: The refineParams parameter.

Methods

ArucoCharucoBoard? GetBoard()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetBoard(ArucoCharucoBoard board)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter board: The board parameter.
ArucoCharucoParameters? GetCharucoParameters()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetCharucoParameters(ArucoCharucoParameters charucoParameters)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter charucoParameters: The charucoParameters parameter.
ArucoDetectorParameters? GetDetectorParameters()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetDetectorParameters(ArucoDetectorParameters detectorParameters)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter detectorParameters: The detectorParameters parameter.
ArucoRefineParameters? GetRefineParameters()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
void SetRefineParameters(ArucoRefineParameters refineParameters)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter refineParameters: The refineParameters parameter.
void DetectBoard(Mat image, Mat charucoCorners, Mat charucoIds, IntPtr markerCorners, Mat? markerIds)
- Summary: * detect aruco markers and interpolate position of ChArUco board corners
- Remarks:
- Parameter image: input image necessary for corner refinement. Note that markers are not detected and
should be sent in corners and ids parameters.
- Parameter charucoCorners: interpolated chessboard corners.
- Parameter charucoIds: interpolated chessboard corners identifiers.
- Parameter markerCorners: vector of already detected markers corners. For each marker, its four
corners are provided, (e.g Point2f[][] ). For N detected markers, the
dimensions of this array should be Nx4. The order of the corners should be clockwise.
If markerCorners and markerCorners are empty, the function detect aruco markers and ids.
- Parameter markerIds: list of identifiers for each marker in corners.
If markerCorners and markerCorners are empty, the function detect aruco markers and ids.
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 markerCorners and markerCorners are empty, the detectMarkers() will run and detect aruco markers and ids.
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. See also: * findChessboardCorners .: info Note
After OpenCV 4.6.0, there was an incompatible change in the ChArUco pattern generation algorithm for even row counts.
Use aruco.CharucoBoard.setLegacyPattern() to ensure compatibility with patterns created using OpenCV versions prior to 4.6.0.
For more information, see the issue: https://github.com/opencv/opencv/issues/23152 .:
- Parameter image: Input image.
- Parameter charucoCorners: The charucoCorners parameter.
- Parameter charucoIds: The charucoIds parameter.
- Parameter markerCorners: The markerCorners parameter.
- Parameter markerIds: The markerIds parameter.
void DetectDiamonds(Mat image, IntPtr diamondCorners, Mat diamondIds, IntPtr markerCorners, Mat? markerIds)
- Summary: * Detect ChArUco Diamond markers
- Remarks:
- Parameter image: input image necessary for corner subpixel.
- Parameter 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 Point2f[][] ).
- Parameter 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.
- Parameter markerCorners: list of detected marker corners from detectMarkers function.
If markerCorners and markerCorners are empty, the function detect aruco markers and ids.
- Parameter markerIds: list of marker ids in markerCorners.
If markerCorners and markerCorners are empty, the function detect aruco markers and ids.
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 less accurate.
- Parameter image: Input image.
- Parameter diamondCorners: The diamondCorners parameter.
- Parameter diamondIds: The diamondIds parameter.
- Parameter markerCorners: The markerCorners parameter.
- Parameter markerIds: The markerIds parameter.

`ArucoCharucoParameters`

Inherits from: DisposableOpenCVObject

Wrapper for OpenCV's native functionality.

Properties

Property	Type	Description
`CameraMatrix`	`Mat?`	Gets or sets the cameraMatrix property.
`DistCoeffs`	`Mat?`	Gets or sets the distCoeffs property.
`MinMarkers`	`int`	Gets or sets the minMarkers property.
`TryRefineMarkers`	`bool`	Gets or sets the tryRefineMarkers property.
`CheckMarkers`	`bool`	Gets or sets the checkMarkers property.

Constructors

new ArucoCharucoParameters()
- Summary: Wrapper for OpenCV's native functionality.

`ArucoDetectorParameters`

Inherits from: DisposableOpenCVObject

struct DetectorParameters is used by ArucoDetector

Properties

Property	Type	Description
`AdaptiveThreshWinSizeMin`	`int`	Gets or sets the adaptiveThreshWinSizeMin property.
`AdaptiveThreshWinSizeMax`	`int`	Gets or sets the adaptiveThreshWinSizeMax property.
`AdaptiveThreshWinSizeStep`	`int`	Gets or sets the adaptiveThreshWinSizeStep property.
`AdaptiveThreshConstant`	`double`	Gets or sets the adaptiveThreshConstant property.
`MinMarkerPerimeterRate`	`double`	Gets or sets the minMarkerPerimeterRate property.
`MaxMarkerPerimeterRate`	`double`	Gets or sets the maxMarkerPerimeterRate property.
`PolygonalApproxAccuracyRate`	`double`	Gets or sets the polygonalApproxAccuracyRate property.
`MinCornerDistanceRate`	`double`	Gets or sets the minCornerDistanceRate property.
`MinDistanceToBorder`	`int`	Gets or sets the minDistanceToBorder property.
`MinMarkerDistanceRate`	`double`	Gets or sets the minMarkerDistanceRate property.
`MinGroupDistance`	`float`	Gets or sets the minGroupDistance property.
`CornerRefinementMethod`	`int`	Gets or sets the cornerRefinementMethod property.
`CornerRefinementWinSize`	`int`	Gets or sets the cornerRefinementWinSize property.
`RelativeCornerRefinmentWinSize`	`float`	Gets or sets the relativeCornerRefinmentWinSize property.
`CornerRefinementMaxIterations`	`int`	Gets or sets the cornerRefinementMaxIterations property.
`CornerRefinementMinAccuracy`	`double`	Gets or sets the cornerRefinementMinAccuracy property.
`MarkerBorderBits`	`int`	Gets or sets the markerBorderBits property.
`PerspectiveRemovePixelPerCell`	`int`	Gets or sets the perspectiveRemovePixelPerCell property.
`PerspectiveRemoveIgnoredMarginPerCell`	`double`	Gets or sets the perspectiveRemoveIgnoredMarginPerCell property.
`MaxErroneousBitsInBorderRate`	`double`	Gets or sets the maxErroneousBitsInBorderRate property.
`MinOtsuStdDev`	`double`	Gets or sets the minOtsuStdDev property.
`ErrorCorrectionRate`	`double`	Gets or sets the errorCorrectionRate property.
`AprilTagQuadDecimate`	`float`	Gets or sets the aprilTagQuadDecimate property.
`AprilTagQuadSigma`	`float`	Gets or sets the aprilTagQuadSigma property.
`AprilTagMinClusterPixels`	`int`	Gets or sets the aprilTagMinClusterPixels property.
`AprilTagMaxNmaxima`	`int`	Gets or sets the aprilTagMaxNmaxima property.
`AprilTagCriticalRad`	`float`	Gets or sets the aprilTagCriticalRad property.
`AprilTagMaxLineFitMse`	`float`	Gets or sets the aprilTagMaxLineFitMse property.
`AprilTagMinWhiteBlackDiff`	`int`	Gets or sets the aprilTagMinWhiteBlackDiff property.
`AprilTagDeglitch`	`int`	Gets or sets the aprilTagDeglitch property.
`DetectInvertedMarker`	`bool`	Gets or sets the detectInvertedMarker property.
`UseAruco3Detection`	`bool`	Gets or sets the useAruco3Detection property.
`MinSideLengthCanonicalImg`	`int`	Gets or sets the minSideLengthCanonicalImg property.
`MinMarkerLengthRatioOriginalImg`	`float`	Gets or sets the minMarkerLengthRatioOriginalImg property.
`ValidBitIdThreshold`	`float`	Gets or sets the validBitIdThreshold property.

Constructors

new ArucoDetectorParameters()
- Summary: Wrapper for OpenCV's native functionality.

Methods

bool ReadDetectorParameters(FileNode fn)
- Summary: Read a new set of DetectorParameters from FileNode (use FileStorage.root()).
- Parameter fn: The fn parameter.
- Returns: The returned value.
bool WriteDetectorParameters(FileStorage fs, string? name)
- Summary: Write a set of DetectorParameters to FileStorage
- Parameter fs: The fs parameter.
- Parameter name: The name parameter.
- Returns: The returned value.

`ArucoDictionary`

Inherits from: DisposableOpenCVObject

Dictionary is a set of unique ArUco markers of the same size * * bytesList storing as 2-dimensions Mat with 4-th channels (CV_8UC4 type was used) and contains the marker codewords where: * - bytesList.rows is the dictionary size * - each marker is encoded using nbytes = ceil(markerSize*markerSize/8.) bytes * - each row contains all 4 rotations of the marker, so its length is 4*nbytes * - the byte order in the bytesList[i] row: * //bytes without rotation/bytes with rotation 1/bytes with rotation 2/bytes with rotation 3// * So bytesList.ptr(i)[k*nbytes + j] is the j-th byte of i-th marker, in its k-th rotation. * Note: Python bindings generate matrix with shape of bytesList dictionary_size x nbytes x 4, * but it should be indexed like C++ version.

Properties

Property	Type	Description
`BytesList`	`Mat?`	Gets or sets the bytesList property.
`MarkerSize`	`int`	Gets or sets the markerSize property.
`MaxCorrectionBits`	`int`	Gets or sets the maxCorrectionBits property.

Constructors

new ArucoDictionary()
- Summary: Wrapper for OpenCV's native functionality.
new ArucoDictionary(Mat bytesList, int _markerSize, int maxcorr)
- Summary: Basic ArUco dictionary constructor * * bytesList bits for all ArUco markers in dictionary see memory layout in the class description * _markerSize ArUco marker size in units * maxcorr maximum number of bits that can be corrected
- Parameter bytesList: The bytesList parameter.
- Parameter _markerSize: The _markerSize parameter.
- Parameter maxcorr: The maxcorr parameter.

Methods

bool ReadDictionary(FileNode fn)
- Summary: Read a new dictionary from FileNode. * * Dictionary example in YAML format:
nmarkers: 35
markersize: 6\n * maxCorrectionBits: 5\n * marker_0: "101011111011111001001001101100000000"\n * ...\n * marker_34: "011111010000111011111110110101100101"
Parameter fn: The fn parameter.
Returns: The returned value.
void WriteDictionary(FileStorage fs, string? name)
- Summary: Write a dictionary to FileStorage, format is the same as in readDictionary().
- Parameter fs: The fs parameter.
- Parameter name: The name parameter.
bool Identify(Mat onlyBits, int idx, int rotation, double maxCorrectionRate)
- Summary: Given a matrix of bits. Returns whether if marker is identified or not. * * Returns reference to the marker id in the dictionary (if any) and its rotation.
- Parameter onlyBits: The onlyBits parameter.
- Parameter idx: The idx parameter.
- Parameter rotation: The rotation parameter.
- Parameter maxCorrectionRate: The maxCorrectionRate parameter.
- Returns: The returned value.
bool Identify(Mat onlyCellPixelRatio, int idx, int rotation, double maxCorrectionRate, float validBitIdThreshold)
- Summary: Given a matrix of pixel ratio raging from 0 to 1. Returns whether if marker is identified or not. * * Returns reference to the marker id in the dictionary (if any) and its rotation.
- Parameter onlyCellPixelRatio: The onlyCellPixelRatio parameter.
- Parameter idx: The idx parameter.
- Parameter rotation: The rotation parameter.
- Parameter maxCorrectionRate: The maxCorrectionRate parameter.
- Parameter validBitIdThreshold: The validBitIdThreshold parameter.
- Returns: The returned value.
int GetDistanceToId(Mat bits, int id, bool allRotations)
- Summary: Returns Hamming distance of the input bits to the specific id. * * If allRotations flag is set, the four possible marker rotations are considered
- Parameter bits: The bits parameter.
- Parameter id: The id parameter.
- Parameter allRotations: The allRotations parameter.
- Returns: The returned value.
void GenerateImageMarker(int id, int sidePixels, Mat _img, int borderBits)
- Summary: Generate a canonical marker image
- Parameter id: The id parameter.
- Parameter sidePixels: The sidePixels parameter.
- Parameter _img: The _img parameter.
- Parameter borderBits: The borderBits parameter.
Mat? GetByteListFromBits(Mat bits)
- Summary: Transform matrix of bits to list of bytes with 4 marker rotations
- Parameter bits: The bits parameter.
- Returns: The returned value.
Mat? GetBitsFromByteList(Mat byteList, int markerSize, int rotationId)
- Summary: Transform list of bytes to matrix of bits
- Parameter byteList: The byteList parameter.
- Parameter markerSize: The markerSize parameter.
- Parameter rotationId: The rotationId parameter.
- Returns: The returned value.
Mat? GetMarkerBits(int markerId, int rotationId)
- Summary: Get ground truth bits float
- Parameter markerId: The markerId parameter.
- Parameter rotationId: The rotationId parameter.
- Returns: The returned value.

`ArucoGridBoard`

Inherits from: ArucoBoard

Planar board with grid arrangement of markers * * More common type of board. All markers are placed in the same plane in a grid arrangement. * The board image can be drawn using generateImage() method.

Constructors

new ArucoGridBoard(Size size, float markerLength, float markerSeparation, ArucoDictionary dictionary, Mat? ids)
- Summary: * GridBoard constructor
- Parameter size: The size parameter.
- Parameter markerLength: The markerLength parameter.
- Parameter markerSeparation: The markerSeparation parameter.
- Parameter dictionary: The dictionary parameter.
- Parameter ids: The ids parameter.

Methods

Size GetGridSize()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
float GetMarkerLength()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
float GetMarkerSeparation()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.

`ArucoRefineParameters`

Inherits from: DisposableOpenCVObject

struct RefineParameters is used by ArucoDetector

Properties

Property	Type	Description
`MinRepDistance`	`float`	Gets or sets the minRepDistance property.
`ErrorCorrectionRate`	`float`	Gets or sets the errorCorrectionRate property.
`CheckAllOrders`	`bool`	Gets or sets the checkAllOrders property.

Constructors

new ArucoRefineParameters(float minRepDistance, float errorCorrectionRate, bool checkAllOrders)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter minRepDistance: The minRepDistance parameter.
- Parameter errorCorrectionRate: The errorCorrectionRate parameter.
- Parameter checkAllOrders: The checkAllOrders parameter.

Methods

bool ReadRefineParameters(FileNode fn)
- Summary: Read a new set of RefineParameters from FileNode (use FileStorage.root()).
- Parameter fn: The fn parameter.
- Returns: The returned value.
bool WriteRefineParameters(FileStorage fs, string? name)
- Summary: Write a set of RefineParameters to FileStorage
- Parameter fs: The fs parameter.
- Parameter name: The name parameter.
- Returns: The returned value.

`BarcodeBarcodeDetector`

Inherits from: GraphicalCodeDetector

Wrapper for OpenCV's native functionality.

Constructors

new BarcodeBarcodeDetector()
- Summary: Initialize the BarcodeDetector. Super resolution is disabled.
new BarcodeBarcodeDetector(string super_resolution_model_path)
- Summary: Initialize the BarcodeDetector with a Super Resolution model. * * Loads a Super Resolution DNN model in ONNX format, used to upscale small/low-quality * barcode crops before decoding for better quality. * * Note: Caffe models (sr.prototxt / sr.caffemodel) are no longer supported; convert * the model to ONNX (a converted sr.onnx is available from * https://github.com/WeChatCV/opencv_3rdparty/tree/wechat_qrcode). * * super_resolution_model_path path to a single-file ONNX Super Resolution model.
- Parameter super_resolution_model_path: The super_resolution_model_path parameter.

Methods

bool DecodeWithType(Mat img, Mat points, IntPtr decoded_info, IntPtr decoded_type)
- Summary: Decodes barcode in image once it's found by the detect() method. * * img grayscale or color (BGR) image containing bar code. * points vector of rotated rectangle vertices found by detect() method (or some other algorithm). * For N detected barcodes, the dimensions of this array should be [N][4]. * Order of four points in Point2f[] is bottomLeft, topLeft, topRight, bottomRight. * decoded_info UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded. * decoded_type vector strings, specifies the type of these barcodes Returns: true if at least one valid barcode have been found
- Parameter img: Input image.
- Parameter points: The points parameter.
- Parameter decoded_info: The decoded_info parameter.
- Parameter decoded_type: The decoded_type parameter.
- Returns: The returned value.
bool DetectAndDecodeWithType(Mat img, IntPtr decoded_info, IntPtr decoded_type, Mat? points)
- Summary: Both detects and decodes barcode
- Remarks:
- Parameter img: grayscale or color (BGR) image containing barcode.
- Parameter decoded_info: UTF8-encoded output vector of string(s) or empty vector of string if the codes cannot be decoded.
- Parameter decoded_type: vector of strings, specifies the type of these barcodes
- Parameter points: optional output vector of vertices of the found barcode rectangle. Will be empty if not found. Returns: true if at least one valid barcode have been found
- Parameter img: Input image.
- Parameter decoded_info: The decoded_info parameter.
- Parameter decoded_type: The decoded_type parameter.
- Parameter points: The points parameter.
- Returns: The returned value.
double GetDownsamplingThreshold()
- Summary: Get detector downsampling threshold. * Returns: detector downsampling threshold
- Returns: The returned value.
BarcodeBarcodeDetector? SetDownsamplingThreshold(double thresh)
- Summary: Set detector downsampling threshold. * * By default, the detect method resizes the input image to this limit if the smallest image size is is greater than the threshold. * Increasing this value can improve detection accuracy and the number of results at the expense of performance. * Correlates with detector scales. Setting this to a large value will disable downsampling. * thresh downsampling limit to apply (default 512) * See also: setDetectorScales
- Parameter thresh: The thresh parameter.
- Returns: The returned value.
void GetDetectorScales(IntPtr sizes)
- Summary: Returns detector box filter sizes. * * sizes output parameter for returning the sizes.
- Parameter sizes: The sizes parameter.
BarcodeBarcodeDetector? SetDetectorScales(IntPtr sizes)
- Summary: Set detector box filter sizes. * * Adjusts the value and the number of box filters used in the detect step. * The filter sizes directly correlate with the expected line widths for a barcode. Corresponds to expected barcode distance. * If the downsampling limit is increased, filter sizes need to be adjusted in an inversely proportional way. * sizes box filter sizes, relative to minimum dimension of the image (default [0.01, 0.03, 0.06, 0.08])
- Parameter sizes: The sizes parameter.
- Returns: The returned value.
double GetGradientThreshold()
- Summary: Get detector gradient magnitude threshold. * Returns: detector gradient magnitude threshold.
- Returns: The returned value.
BarcodeBarcodeDetector? SetGradientThreshold(double thresh)
- Summary: Set detector gradient magnitude threshold. * * Sets the coherence threshold for detected bounding boxes. * Increasing this value will generate a closer fitted bounding box width and can reduce false-positives. * Values between 16 and 1024 generally work, while too high of a value will remove valid detections. * thresh gradient magnitude threshold (default 64).
- Parameter thresh: The thresh parameter.
- Returns: The returned value.

`MccCChecker`

Inherits from: Algorithm

CChecker

Detailed Remarks:

checker object

This class contains the information about the detected checkers,i.e, their

type, the corners of the chart, the color profile, the cost, centers chart,

```
etc.
```

Methods

MccCChecker? Create()
- Summary: Create a new CChecker object. * Returns: A pointer to the implementation of the CChecker
- Returns: The returned value.
void SetTarget(MccColorChart _target)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _target: The _target parameter.
void SetBox(IntPtr _box)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _box: The _box parameter.
void SetChartsRGB(Mat _chartsRGB)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _chartsRGB: The _chartsRGB parameter.
void SetChartsYCbCr(Mat _chartsYCbCr)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _chartsYCbCr: The _chartsYCbCr parameter.
void SetCost(float _cost)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _cost: The _cost parameter.
void SetCenter(Point2f _center)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter _center: The _center parameter.
MccColorChart GetTarget()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
IntPtr GetBox()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
IntPtr GetColorCharts()
- Summary: Computes and returns the coordinates of the central parts of the charts modules. * * This method computes transformation matrix from the checkers's coordinates (CChecker.getBox()) * and find by this the coordinates of the central parts of the charts modules. * It is used in CCheckerDetector.draw() and in ChartsRGB calculation.
- Returns: The returned value.
Mat? GetChartsRGB(bool getStats)
- Summary: Wrapper for OpenCV's native functionality.
- Parameter getStats: The getStats parameter.
- Returns: The returned value.
Mat? GetChartsYCbCr()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
float GetCost()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
Point2f GetCenter()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.

`MccCCheckerDetector`

Inherits from: Algorithm

A class to find the positions of the ColorCharts in the image.

Methods

bool Process(Mat image, IntPtr regionsOfInterest, int nc)
- Summary: Find the ColorCharts in the given image. * * The found charts are not returned but instead stored in the * detector, these can be accessed later on using getBestColorChecker() * and getListColorChecker() * image image in color space BGR * regionsOfInterest regions of image to look for the chart, if * it is empty, charts are looked for in the * entire image * nc number of charts in the image, if you don't know the exact * then keeping this number high helps. Returns: true if atleast one chart is detected otherwise false
- Parameter image: Input image.
- Parameter regionsOfInterest: The regionsOfInterest parameter.
- Parameter nc: The nc parameter.
- Returns: The returned value.
bool Process(Mat image, int nc)
- Summary: Find the ColorCharts in the given image. * * Differs from the above one only in the arguments. * * This version searches for the chart in the full image. * * The found charts are not returned but instead stored in the * detector, these can be accessed later on using getBestColorChecker() * and getListColorChecker() * image image in color space BGR * nc number of charts in the image, if you don't know the exact * then keeping this number high helps. Returns: true if atleast one chart is detected otherwise false
- Parameter image: Input image.
- Parameter nc: The nc parameter.
- Returns: The returned value.
IntPtr GetBestColorChecker()
- Summary: Get the best color checker. By the best it means the one * detected with the highest confidence. Returns: checker A single colorchecker, if atleast one colorchecker * was detected, 'null' otherwise.
- Returns: The returned value.
IntPtr GetListColorChecker()
- Summary: Get the list of all detected colorcheckers Returns: checkers vector of colorcheckers
- Returns: The returned value.
MccCCheckerDetector? Create()
- Summary: Returns the implementation of the CCheckerDetector. *
- Returns: The returned value.
void Draw(IntPtr checkers, Mat img, Scalar color, int thickness)
- Summary: Draws the checker to the given image. * img image in color space BGR * checkers The checkers which will be drawn by this object. * color The color by with which the squares of the checker * will be drawn * thickness The thickness with which the sqaures will be * drawn
- Parameter checkers: The checkers parameter.
- Parameter img: Input image.
- Parameter color: Color value (BGR or BGRA).
- Parameter thickness: Line thickness.
Mat? GetRefColors()
- Summary: Gets the reference color for chart.
- Returns: The returned value.
void SetDetectionParams(MccDetectorParametersMCC @params)
- Summary: Sets the detection paramaters for mcc. * params DetectorParametersMCC structure containing detection configuration parameters.
- Parameter params: The @params parameter.
void SetColorChartType(MccColorChart chartType)
- Summary: Sets the color chart type for MCC detection. * chartType ColorChart enum specifying the type of color chart to detect.
- Parameter chartType: The chartType parameter.
MccDetectorParametersMCC? GetDetectionParams()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.
MccColorChart GetColorChartType()
- Summary: Wrapper for OpenCV's native functionality.
- Returns: The returned value.

`MccDetectorParametersMCC`

Inherits from: DisposableOpenCVObject

struct DetectorParametersMCC is used by CCheckerDetector

Properties

Property	Type	Description
`AdaptiveThreshWinSizeMin`	`int`	Gets or sets the adaptiveThreshWinSizeMin property.
`AdaptiveThreshWinSizeMax`	`int`	Gets or sets the adaptiveThreshWinSizeMax property.
`AdaptiveThreshWinSizeStep`	`int`	Gets or sets the adaptiveThreshWinSizeStep property.
`AdaptiveThreshConstant`	`double`	Gets or sets the adaptiveThreshConstant property.
`MinContoursAreaRate`	`double`	Gets or sets the minContoursAreaRate property.
`MinContoursArea`	`double`	Gets or sets the minContoursArea property.
`ConfidenceThreshold`	`double`	Gets or sets the confidenceThreshold property.
`MinContourSolidity`	`double`	Gets or sets the minContourSolidity property.
`FindCandidatesApproxPolyDPEpsMultiplier`	`double`	Gets or sets the findCandidatesApproxPolyDPEpsMultiplier property.
`BorderWidth`	`int`	Gets or sets the borderWidth property.
`B0factor`	`float`	Gets or sets the B0factor property.
`MaxError`	`float`	Gets or sets the maxError property.
`MinContourPointsAllowed`	`int`	Gets or sets the minContourPointsAllowed property.
`MinContourLengthAllowed`	`int`	Gets or sets the minContourLengthAllowed property.
`MinInterContourDistance`	`int`	Gets or sets the minInterContourDistance property.
`MinInterCheckerDistance`	`int`	Gets or sets the minInterCheckerDistance property.
`MinImageSize`	`int`	Gets or sets the minImageSize property.
`MinGroupSize`	`int`	Gets or sets the minGroupSize property.

Constructors

new MccDetectorParametersMCC()
- Summary: Wrapper for OpenCV's native functionality.

⚙️ Static Methods (Cv2)

`Cv2.FindChessboardCorners`

Signature: bool FindChessboardCorners(Mat image, Size patternSize, Mat corners, int flags)

Finds the positions of internal corners of the chessboard.

Detailed Remarks: .: info Note The function requires white space (like a square-thick border, the wider the better) around the board to make the detection more robust in various environments. Otherwise, if there is no border and the background is dark, the outer black squares cannot be segmented properly and so the square grouping and ordering algorithm fails. Use the checkerboard generator script (tutorial_camera_calibration_pattern) to create the desired checkerboard pattern. .:

Parameters:

image: Source chessboard view. It must be an 8-bit grayscale or color image.
patternSize: Number of inner corners per a chessboard row and column ( patternSize = Size(points_per_row,points_per_column) = Size(columns,rows) ).
corners: Output array of detected corners.
flags: Various operation flags that can be zero or a combination of the following values: - CALIB_CB_ADAPTIVE_THRESH Use adaptive thresholding to convert the image to black and white, rather than a fixed threshold level (computed from the average image brightness). - CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with EqualizeHist before applying fixed or adaptive thresholding. - CALIB_CB_FILTER_QUADS Use additional criteria (like contour area, perimeter, square-like shape) to filter out false quads extracted at the contour retrieval stage. - CALIB_CB_FAST_CHECK Run a fast check on the image that looks for chessboard corners, and shortcut the call if none is found. This can drastically speed up the call in the degenerate condition when no chessboard is observed. - CALIB_CB_PLAIN All other flags are ignored. The input image is taken as is. No image processing is done to improve to find the checkerboard. This has the effect of speeding up the execution of the function but could lead to not recognizing the checkerboard if the image is not previously binarized in the appropriate manner.

Returns: True if all of the corners are found and placed in a certain order (row by row, left to right in every row). Otherwise, if the function fails to find all the corners or reorder them, it returns false. The function attempts to determine whether the input image is a view of the chessboard pattern and locate the internal chessboard corners. For example, a regular chessboard has 8 x 8 squares and 7 x 7 internal corners, that is, points where the black squares touch each other. The detected coordinates are approximate, and to determine their positions more accurately, the function calls CornerSubPix. You also may use the function CornerSubPix with different parameters if returned coordinates are not accurate enough. Sample usage of detecting and drawing chessboard corners:

csharp

var patternSize = new Size(8, 6);
var gray = new Mat(); // source image
var corners = new Mat();
bool patternFound = Cv2.FindChessboardCorners(gray, patternSize, corners, 1 + 2 + 8);
if (patternFound)
{
    Cv2.CornerSubPix(gray, corners, new Size(11, 11), new Size(-1, -1), new TermCriteria(1 + 2, 30, 0.1));
}
using var img = new Mat();
Cv2.DrawChessboardCorners(img, patternSize, corners, patternFound);

`Cv2.CheckChessboard`

Signature: bool CheckChessboard(Mat img, Size size)

Checks whether the image contains chessboard of the specific size or not.

Parameters:

img: Source chessboard view.
size: Size of the chessboard.

Returns: Whether a chessboard was found.

`Cv2.FindChessboardCornersSB`

Signature: bool FindChessboardCornersSB(Mat image, Size patternSize, Mat corners, int flags, Mat meta)

Finds the positions of internal corners of the chessboard using a sector based approach.

Detailed Remarks: .: info Note The function requires a white boarder with roughly the same width as one of the checkerboard fields around the whole board to improve the detection in various environments. In addition, because of the localized radon transformation it is beneficial to use round corners for the field corners which are located on the outside of the board. The following figure illustrates a sample checkerboard optimized for the detection. However, any other checkerboard can be used as well. Use the checkerboard generator script (tutorial_camera_calibration_pattern) to create the corresponding checkerboard pattern:

Parameters:

image: Source chessboard view. It must be an 8-bit grayscale or color image.
patternSize: Number of inner corners per a chessboard row and column ( patternSize = Size(points_per_row,points_per_column) = Size(columns,rows) ).
corners: Output array of detected corners.
flags: Various operation flags that can be zero or a combination of the following values: - CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with EqualizeHist before detection. - CALIB_CB_EXHAUSTIVE Run an exhaustive search to improve detection rate. - CALIB_CB_ACCURACY Up sample input image to improve sub-pixel accuracy due to aliasing effects. - CALIB_CB_LARGER The detected pattern is allowed to be larger than patternSize (see description). - CALIB_CB_MARKER The detected pattern must have a marker (see description). This should be used if an accurate camera calibration is required.
meta: Optional output array of detected corners (CV_8UC1 and size = Size(columns,rows)). Each entry stands for one corner of the pattern and can have one of the following values: - 0 = no meta data attached - 1 = left-top corner of a black cell - 2 = left-top corner of a white cell - 3 = left-top corner of a black cell with a white marker dot - 4 = left-top corner of a white cell with a black marker dot (pattern origin in case of markers otherwise first corner) The function is analog to findChessboardCorners but uses a localized radon transformation approximated by box filters being more robust to all sort of noise, faster on larger images and is able to directly return the sub-pixel position of the internal chessboard corners. The Method is based on the paper [duda2018] "Accurate Detection and Localization of Checkerboard Corners for Calibration" demonstrating that the returned sub-pixel positions are more accurate than the one returned by CornerSubPix allowing a precise camera calibration for demanding applications. In the case, the flags CALIB_CB_LARGER or CALIB_CB_MARKER are given, the result can be recovered from the optional meta array. Both flags are helpful to use calibration patterns exceeding the field of view of the camera. These oversized patterns allow more accurate calibrations as corners can be utilized, which are as close as possible to the image borders. For a consistent coordinate system across all images, the optional marker (see image below) can be used to move the origin of the board to the location where the black circle is located.

Returns: The returned value.

`Cv2.FindChessboardCornersSB`

Signature: bool FindChessboardCornersSB(Mat image, Size patternSize, Mat corners, int flags)

This is an overloaded member function, provided for convenience.

Parameters:

image: Input image.
patternSize: The patternSize parameter.
corners: The corners parameter.
flags: Operation flags.

Returns: The returned value.

`Cv2.EstimateChessboardSharpness`

Signature: Scalar EstimateChessboardSharpness(Mat image, Size patternSize, Mat corners, float rise_distance, bool vertical, Mat? sharpness)

Estimates the sharpness of a detected chessboard.

Detailed Remarks: Image sharpness, as well as brightness, are a critical parameter for accuracte camera calibration. For accessing these parameters for filtering out problematic calibraiton images, this method calculates edge profiles by traveling from black to white chessboard cell centers. Based on this, the number of pixels is calculated required to transit from black to white. This width of the transition area is a good indication of how sharp the chessboard is imaged and should be below ~3.0 pixels.

Parameters:

image: Gray image used to find chessboard corners
patternSize: Size of a found chessboard pattern
corners: Corners found by findChessboardCornersSB
rise_distance: Rise distance 0.8 means 10% ... 90% of the final signal strength
vertical: By default edge responses for horizontal lines are calculated
sharpness: Optional output array with a sharpness value for calculated edge responses (see description) The optional sharpness array is of type CV_32FC1 and has for each calculated profile one row with the following five entries: * 0 = x coordinate of the underlying edge in the image * 1 = y coordinate of the underlying edge in the image * 2 = width of the transition area (sharpness) * 3 = signal strength in the black cell (min brightness) * 4 = signal strength in the white cell (max brightness)

Returns: Scalar(average sharpness, average min brightness, average max brightness,0)

`Cv2.Find4QuadCornerSubpix`

Signature: bool Find4QuadCornerSubpix(Mat img, Mat corners, Size region_size)

Wrapper for OpenCV's native functionality.

Parameters:

img: Input image.
corners: The corners parameter.
region_size: The region_size parameter.

Returns: The returned value.

`Cv2.DrawChessboardCorners`

Signature: void DrawChessboardCorners(Mat image, Size patternSize, Mat corners, bool patternWasFound)

Renders the detected chessboard corners.

Parameters:

image: Destination image. It must be an 8-bit color image.
patternSize: Number of inner corners per a chessboard row and column (patternSize = Size(points_per_row,points_per_column)).
corners: Array of detected corners, the output of findChessboardCorners.
patternWasFound: Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners should be passed here. The function draws individual chessboard corners detected either as red circles if the board was not found, or as colored corners connected with lines if the board was found.

`Cv2.FindCirclesGrid`

Signature: bool FindCirclesGrid(Mat image, Size patternSize, Mat centers, int flags, IntPtr blobDetector, CirclesGridFinderParameters parameters)

Finds centers in the grid of circles.

Detailed Remarks: .: info Note The function requires white space (like a square-thick border, the wider the better) around the board to make the detection more robust in various environments. .:

Parameters:

image: grid view of input circles; it must be an 8-bit grayscale or color image.
patternSize: number of circles per row and column ( patternSize = Size(points_per_row, points_per_column) ).
centers: output array of detected centers.
flags: various operation flags that can be one of the following values: - CALIB_CB_SYMMETRIC_GRID uses symmetric pattern of circles. - CALIB_CB_ASYMMETRIC_GRID uses asymmetric pattern of circles. - CALIB_CB_CLUSTERING uses a special algorithm for grid detection. It is more robust to perspective distortions but much more sensitive to background clutter.
blobDetector: feature detector that finds blobs like dark circles on light background. If blobDetector is null then image represents Point2f array of candidates.
parameters: struct for finding circles in a grid pattern. return True if all of the centers have been found and they have been placed in a certain order (row by row, left to right in every row). Otherwise, if the function fails to find all the corners or reorder them, it returns false. The function attempts to determine whether the input image contains a grid of circles. If it is, the function locates centers of the circles. Sample usage of detecting and drawing the centers of circles:

csharp

var patternSize = new Size(7, 7);
var gray = new Mat(); // source image
var centers = new Mat();
bool patternFound = Cv2.FindCirclesGrid(gray, patternSize, centers, 0, null);
using var img = new Mat();
Cv2.DrawChessboardCorners(img, patternSize, centers, patternFound);

Returns: The returned value.

`Cv2.FindCirclesGrid`

Signature: bool FindCirclesGrid(Mat image, Size patternSize, Mat centers, int flags, IntPtr blobDetector)

This is an overloaded member function, provided for convenience.

Parameters:

image: Input image.
patternSize: The patternSize parameter.
centers: The centers parameter.
flags: Operation flags.
blobDetector: The blobDetector parameter.

Returns: The returned value.

`Cv2.ArucoDrawDetectedMarkers`

Signature: void ArucoDrawDetectedMarkers(Mat image, IntPtr corners, Mat? ids, Scalar borderColor)

Draw detected markers in image * * image input/output image. It must have 1 or 3 channels. The number of channels is not altered. * corners positions of marker corners on input image. * (e.g Point2f[][] ). For N detected markers, the dimensions of * this array should be Nx4. The order of the corners should be clockwise. * ids vector of identifiers for markers in markersCorners . * Optional, if not provided, ids are not painted. * 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.

Parameters:

image: Input image.
corners: The corners parameter.
ids: The ids parameter.
borderColor: The borderColor parameter.

`Cv2.ArucoGenerateImageMarker`

Signature: void ArucoGenerateImageMarker(ArucoDictionary dictionary, int id, int sidePixels, Mat img, int borderBits)

Generate a canonical marker image * * dictionary dictionary of markers indicating the type of markers * id identifier of the marker that will be returned. It has to be a valid id in the specified dictionary. * sidePixels size of the image in pixels * img output image with the marker * borderBits width of the marker border. * * This function returns a marker image in its canonical form (i.e. ready to be printed)

Parameters:

dictionary: The dictionary parameter.
id: The id parameter.
sidePixels: The sidePixels parameter.
img: Input image.
borderBits: The borderBits parameter.

`Cv2.ArucoGetPredefinedDictionary`

Signature: ArucoDictionary? ArucoGetPredefinedDictionary(int dict)

Returns one of the predefined dictionaries referenced by DICT_*.

Parameters:

dict: The dict parameter.

Returns: The returned value.

`Cv2.ArucoExtendDictionary`

Signature: ArucoDictionary? ArucoExtendDictionary(int nMarkers, int markerSize, ArucoDictionary? baseDictionary, int randomSeed)

Extend base dictionary by new nMarkers * * nMarkers number of markers in the dictionary * markerSize number of bits per dimension of each markers * baseDictionary Include the markers in this dictionary at the beginning (optional) * randomSeed a user supplied seed for theRNG() * * This function creates a new dictionary composed by nMarkers markers and each markers composed * by markerSize x markerSize bits. If baseDictionary is provided, its markers are directly * included and the rest are generated based on them. If the size of baseDictionary is higher * than nMarkers, only the first nMarkers in baseDictionary are taken and no new marker is added.

Parameters:

nMarkers: The nMarkers parameter.
markerSize: The markerSize parameter.
baseDictionary: The baseDictionary parameter.
randomSeed: The randomSeed parameter.

Returns: The returned value.

`Cv2.ArucoDrawDetectedCornersCharuco`

Signature: void ArucoDrawDetectedCornersCharuco(Mat image, Mat charucoCorners, Mat? charucoIds, Scalar cornerColor)

Draws a set of Charuco corners

Detailed Remarks:

- Parameter image: input/output image. It must have 1 or 3 channels. The number of channels is not
altered.
- Parameter charucoCorners: vector of detected charuco corners
- Parameter charucoIds: list of identifiers for each corner in charucoCorners
- Parameter 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.

Parameters:

image: Input image.
charucoCorners: The charucoCorners parameter.
charucoIds: The charucoIds parameter.
cornerColor: The cornerColor parameter.

`Cv2.ArucoDrawDetectedDiamonds`

Signature: void ArucoDrawDetectedDiamonds(Mat image, IntPtr diamondCorners, Mat? diamondIds, Scalar borderColor)

Draw a set of detected ChArUco Diamond markers

Detailed Remarks:

- Parameter image: input/output image. It must have 1 or 3 channels. The number of channels is not
altered.
- Parameter diamondCorners: positions of diamond corners in the same format returned by
detectCharucoDiamond(). (e.g Point2f[][] ). For N detected markers,
the dimensions of this array should be Nx4. The order of the corners should be clockwise.
- Parameter diamondIds: vector of identifiers for diamonds in diamondCorners, in the same format
returned by detectCharucoDiamond() (e.g. Vec4i[]).
Optional, if not provided, ids are not painted.
- Parameter 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.

Parameters:

image: Input image.
diamondCorners: The diamondCorners parameter.
diamondIds: The diamondIds parameter.
borderColor: The borderColor parameter.

🔢 Enumerations

`CirclesGridFinderParametersGridType`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`SymmetricGrid`	`0`	SymmetricGrid
`AsymmetricGrid`	`1`	AsymmetricGrid

`FaceRecognizerSFDisType`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`Cosine`	`0`	Cosine
`NormL2`	`1`	NormL2

`QRCodeEncoderCorrectionLevel`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`L`	`0`	L
`M`	`1`	M
`Q`	`2`	Q
`H`	`3`	H

`QRCodeEncoderECIEncodings`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`ShiftJis`	`20`	ShiftJis
`Utf8`	`26`	Utf8

`QRCodeEncoderEncodeMode`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`Auto`	`-1`	Auto
`Numeric`	`1`	Numeric
`Alphanumeric`	`2`	Alphanumeric
`Byte`	`4`	Byte
`Eci`	`7`	Eci
`Kanji`	`8`	Kanji
`StructuredAppend`	`3`	StructuredAppend

`ArucoCornerRefineMethod`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`None`	`0`	None
`Subpix`	`1`	Subpix
`Contour`	`2`	Contour
`Apriltag`	`3`	Apriltag

`ArucoPredefinedDictionaryType`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`_4x450`	`0`	_4x450
`_4x4100`	`unchecked((int)(0 + 1))`	_4x4100
`_4x4250`	`unchecked((int)(0 + 2))`	_4x4250
`_4x41000`	`unchecked((int)(0 + 3))`	_4x41000
`_5x550`	`unchecked((int)(0 + 4))`	_5x550
`_5x5100`	`unchecked((int)(0 + 5))`	_5x5100
`_5x5250`	`unchecked((int)(0 + 6))`	_5x5250
`_5x51000`	`unchecked((int)(0 + 7))`	_5x51000
`_6x650`	`unchecked((int)(0 + 8))`	_6x650
`_6x6100`	`unchecked((int)(0 + 9))`	_6x6100
`_6x6250`	`unchecked((int)(0 + 10))`	_6x6250
`_6x61000`	`unchecked((int)(0 + 11))`	_6x61000
`_7x750`	`unchecked((int)(0 + 12))`	_7x750
`_7x7100`	`unchecked((int)(0 + 13))`	_7x7100
`_7x7250`	`unchecked((int)(0 + 14))`	_7x7250
`_7x71000`	`unchecked((int)(0 + 15))`	_7x71000
`ArucoOriginal`	`unchecked((int)(0 + 16))`	ArucoOriginal
`APRILTAG16h5`	`unchecked((int)(0 + 17))`	APRILTAG16h5
`APRILTAG25h9`	`unchecked((int)(0 + 18))`	APRILTAG25h9
`APRILTAG36h10`	`unchecked((int)(0 + 19))`	APRILTAG36h10
`APRILTAG36h11`	`unchecked((int)(0 + 20))`	APRILTAG36h11
`ARUCOMIP36h12`	`unchecked((int)(0 + 21))`	ARUCOMIP36h12

`MccColorChart`

Wrapper for OpenCV's native functionality.

Member	Value	Description
`Mcc24`	`0`	Mcc24
`Sg140`	`unchecked((int)(0 + 1))`	Sg140
`Vinyl18`	`unchecked((int)(0 + 2))`	Vinyl18

OBJDETECT Module API Reference ​

📦 Classes and Structs ​

CirclesGridFinderParameters ​

Properties ​

Constructors ​

FaceDetectorYN ​

Methods ​

FaceRecognizerSF ​

Methods ​

GraphicalCodeDetector ​

Methods ​

QRCodeDetector ​

Constructors ​

Methods ​

QRCodeDetectorAruco ​

Constructors ​

Methods ​

QRCodeDetectorArucoParams ​

Properties ​

Constructors ​

QRCodeEncoder ​

Methods ​

QRCodeEncoderParams ​

Properties ​

Constructors ​

ArucoArucoDetector ​

Constructors ​

Methods ​

ArucoBoard ​

Constructors ​

Methods ​

ArucoCharucoBoard ​

Constructors ​

Methods ​

ArucoCharucoDetector ​

Constructors ​

Methods ​

ArucoCharucoParameters ​

Properties ​

Constructors ​

ArucoDetectorParameters ​

Properties ​

Constructors ​

Methods ​

ArucoDictionary ​

Properties ​

Constructors ​

Methods ​

ArucoGridBoard ​

Constructors ​

Methods ​

ArucoRefineParameters ​

Properties ​

Constructors ​

Methods ​

BarcodeBarcodeDetector ​

Constructors ​

Methods ​

MccCChecker ​

Methods ​

MccCCheckerDetector ​

Methods ​

MccDetectorParametersMCC ​

Properties ​

Constructors ​

⚙️ Static Methods (Cv2) ​

Cv2.FindChessboardCorners ​

Cv2.CheckChessboard ​

Cv2.FindChessboardCornersSB ​

Cv2.FindChessboardCornersSB ​

Cv2.EstimateChessboardSharpness ​

Cv2.Find4QuadCornerSubpix ​

Cv2.DrawChessboardCorners ​

Cv2.FindCirclesGrid ​

Cv2.FindCirclesGrid ​

Cv2.ArucoDrawDetectedMarkers ​

Cv2.ArucoGenerateImageMarker ​

Cv2.ArucoGetPredefinedDictionary ​

Cv2.ArucoExtendDictionary ​

Cv2.ArucoDrawDetectedCornersCharuco ​

OBJDETECT Module API Reference

📦 Classes and Structs

`CirclesGridFinderParameters`

Properties

Constructors

`FaceDetectorYN`

Methods

`FaceRecognizerSF`

Methods

`GraphicalCodeDetector`

Methods

`QRCodeDetector`

Constructors

Methods

`QRCodeDetectorAruco`

Constructors

Methods

`QRCodeDetectorArucoParams`

Properties

Constructors

`QRCodeEncoder`

Methods

`QRCodeEncoderParams`

Properties

Constructors

`ArucoArucoDetector`

Constructors

Methods

`ArucoBoard`

Constructors

Methods

`ArucoCharucoBoard`

Constructors

Methods

`ArucoCharucoDetector`

Constructors

Methods

`ArucoCharucoParameters`

Properties

Constructors

`ArucoDetectorParameters`

Properties

Constructors

Methods

`ArucoDictionary`

Properties

Constructors

Methods

`ArucoGridBoard`

Constructors

Methods

`ArucoRefineParameters`

Properties

Constructors

Methods

`BarcodeBarcodeDetector`

Constructors

Methods

`MccCChecker`

Methods

`MccCCheckerDetector`

Methods

`MccDetectorParametersMCC`

Properties

Constructors

⚙️ Static Methods (Cv2)

`Cv2.FindChessboardCorners`

`Cv2.CheckChessboard`

`Cv2.FindChessboardCornersSB`

`Cv2.FindChessboardCornersSB`

`Cv2.EstimateChessboardSharpness`

`Cv2.Find4QuadCornerSubpix`

`Cv2.DrawChessboardCorners`

`Cv2.FindCirclesGrid`

`Cv2.FindCirclesGrid`

`Cv2.ArucoDrawDetectedMarkers`

`Cv2.ArucoGenerateImageMarker`

`Cv2.ArucoGetPredefinedDictionary`

`Cv2.ArucoExtendDictionary`

`Cv2.ArucoDrawDetectedCornersCharuco`