mcc_DetectorParametersMCC
import { mcc_DetectorParametersMCC } from '@banou/opencv-wasm'Use after await initOpenCV(). See the initialization and named imports guide.
Native object: release it with using or delete(). Factories can return null; check before calling methods.
struct DetectorParametersMCC is used by CCheckerDetector
Constructors and members
static new
Create an owned mcc_DetectorParametersMCC object. Release native handles with using or delete().
new(): mcc_DetectorParametersMCC;The mcc_DetectorParametersMCC result.
clone
Create another handle to the same native object. This retains the object without copying its pixels or algorithm state; dispose both handles separately.
clone(): this;The this result.
adaptiveThreshWinSizeMin
minimum window size for adaptive thresholding before finding contours (default 23).
adaptiveThreshWinSizeMin: number;adaptiveThreshWinSizeMax
maximum window size for adaptive thresholding before finding contours (default 153).
adaptiveThreshWinSizeMax: number;adaptiveThreshWinSizeStep
increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 16).
adaptiveThreshWinSizeStep: number;adaptiveThreshConstant
constant for adaptive thresholding before finding contours (default 7)
adaptiveThreshConstant: number;minContoursAreaRate
determine minimum area for marker contour to be detected
This is defined as a rate respect to the area of the input image. Used only if neural network is used (default 0.03).
minContoursAreaRate: number;minContoursArea
determine minimum area for marker contour to be detected
This is defined as the actual area. Used only if neural network is used (default 100).
minContoursArea: number;confidenceThreshold
minimum confidence for a bounding box detected by neural network to classify as detection.(default 0.5) (0<=confidenceThreshold<=1)
confidenceThreshold: number;minContourSolidity
minimum solidity of a contour for it be detected as a square in the chart. (default 0.9).
minContourSolidity: number;findCandidatesApproxPolyDPEpsMultiplier
multipler to be used in ApproxPolyDP function (default 0.05)
findCandidatesApproxPolyDPEpsMultiplier: number;borderWidth
width of the padding used to pass the inital neural network detection in the succeeding system.(default 0)
borderWidth: number;B0factor
distance between two neighboring squares of the same chart as a ratio of the large dimension of a square (default 1.25).
B0factor: number;maxError
maximum allowed error in the detection of a chart (default 0.1).
maxError: number;minContourPointsAllowed
minimum points in a detected contour (default 4).
minContourPointsAllowed: number;minContourLengthAllowed
minimum length of a contour (default 100).
minContourLengthAllowed: number;minInterContourDistance
minimum distance between two contours (default 100).
minInterContourDistance: number;minInterCheckerDistance
minimum distance between two checkers (default 10000).
minInterCheckerDistance: number;minImageSize
minimum size of the smaller dimension of the image (default 1000).
minImageSize: number;minGroupSize
minimum number of squares in a chart that must be detected (default 4).
minGroupSize: number;These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.