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| ArucoDetector () |
| Basic ArucoDetector constructor.
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| ArucoDetector (Dictionary dictionary) |
| Basic ArucoDetector constructor.
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| ArucoDetector (Dictionary dictionary, DetectorParameters detectorParams) |
| Basic ArucoDetector constructor.
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| ArucoDetector (Dictionary dictionary, DetectorParameters detectorParams, RefineParameters refineParams) |
| Basic ArucoDetector constructor.
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void | detectMarkers (Mat image, List< Mat > corners, Mat ids) |
| Basic marker detection.
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void | detectMarkers (Mat image, List< Mat > corners, Mat ids, List< Mat > rejectedImgPoints) |
| Basic marker detection.
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void | detectMarkersMultiDict (Mat image, List< Mat > corners, Mat ids) |
| Basic marker detection.
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void | detectMarkersMultiDict (Mat image, List< Mat > corners, Mat ids, List< Mat > rejectedImgPoints) |
| Basic marker detection.
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void | detectMarkersMultiDict (Mat image, List< Mat > corners, Mat ids, List< Mat > rejectedImgPoints, Mat dictIndices) |
| Basic marker detection.
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DetectorParameters | getDetectorParameters () |
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Dictionary | getDictionary () |
| Returns first dictionary from internal list used for marker detection.
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RefineParameters | getRefineParameters () |
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void | refineDetectedMarkers (Mat image, Board board, List< Mat > detectedCorners, Mat detectedIds, List< Mat > rejectedCorners) |
| Refine not detected markers based on the already detected and the board layout.
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void | refineDetectedMarkers (Mat image, Board board, List< Mat > detectedCorners, Mat detectedIds, List< Mat > rejectedCorners, Mat cameraMatrix) |
| Refine not detected markers based on the already detected and the board layout.
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void | refineDetectedMarkers (Mat image, Board board, List< Mat > detectedCorners, Mat detectedIds, List< Mat > rejectedCorners, Mat cameraMatrix, Mat distCoeffs) |
| Refine not detected markers based on the already detected and the board layout.
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void | refineDetectedMarkers (Mat image, Board board, List< Mat > detectedCorners, Mat detectedIds, List< Mat > rejectedCorners, Mat cameraMatrix, Mat distCoeffs, Mat recoveredIdxs) |
| Refine not detected markers based on the already detected and the board layout.
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void | setDetectorParameters (DetectorParameters detectorParameters) |
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void | setDictionary (Dictionary dictionary) |
| Sets and replaces the first dictionary in internal list to be used for marker detection.
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void | setRefineParameters (RefineParameters refineParameters) |
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virtual void | clear () |
| Clears the algorithm state.
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virtual bool | empty () |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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virtual string | getDefaultName () |
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IntPtr | getNativeObjAddr () |
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void | save (string filename) |
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void | Dispose () |
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void | ThrowIfDisposed () |
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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
void OpenCVForUnity.ObjdetectModule.ArucoDetector.refineDetectedMarkers |
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Mat | image, |
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Board | board, |
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List< Mat > | detectedCorners, |
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Mat | detectedIds, |
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List< Mat > | rejectedCorners ) |
Refine not detected markers based on the already detected and the board layout.
- Parameters
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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 \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) |
distCoeffs | optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) 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.
void OpenCVForUnity.ObjdetectModule.ArucoDetector.refineDetectedMarkers |
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Mat | image, |
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Board | board, |
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List< Mat > | detectedCorners, |
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Mat | detectedIds, |
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List< Mat > | rejectedCorners, |
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Mat | cameraMatrix ) |
Refine not detected markers based on the already detected and the board layout.
- Parameters
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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 \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) |
distCoeffs | optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) 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.
void OpenCVForUnity.ObjdetectModule.ArucoDetector.refineDetectedMarkers |
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Mat | image, |
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Board | board, |
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List< Mat > | detectedCorners, |
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Mat | detectedIds, |
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List< Mat > | rejectedCorners, |
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Mat | cameraMatrix, |
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Mat | distCoeffs ) |
Refine not detected markers based on the already detected and the board layout.
- Parameters
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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 \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) |
distCoeffs | optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) 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.
void OpenCVForUnity.ObjdetectModule.ArucoDetector.refineDetectedMarkers |
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Mat | image, |
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Board | board, |
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List< Mat > | detectedCorners, |
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Mat | detectedIds, |
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List< Mat > | rejectedCorners, |
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Mat | cameraMatrix, |
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Mat | distCoeffs, |
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Mat | recoveredIdxs ) |
Refine not detected markers based on the already detected and the board layout.
- Parameters
-
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 \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) |
distCoeffs | optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) 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.