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#ifndef __OPENCV_MCC_CHECKER_DETECTOR_HPP__
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#define __OPENCV_MCC_CHECKER_DETECTOR_HPP__
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#include <opencv2/core.hpp>
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#include "checker_model.hpp"
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#include <opencv2/dnn.hpp>
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CV_PROP_RW
int
adaptiveThreshWinSizeMin;
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CV_PROP_RW
int
adaptiveThreshWinSizeMax;
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CV_PROP_RW
int
adaptiveThreshWinSizeStep;
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CV_PROP_RW
double
adaptiveThreshConstant;
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CV_PROP_RW
double
minContoursAreaRate;
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CV_PROP_RW
double
minContoursArea;
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CV_PROP_RW
double
confidenceThreshold;
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CV_PROP_RW
double
minContourSolidity;
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CV_PROP_RW
double
findCandidatesApproxPolyDPEpsMultiplier;
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CV_PROP_RW
int
borderWidth;
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CV_PROP_RW
float
B0factor;
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CV_PROP_RW
float
maxError;
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CV_PROP_RW
int
minContourPointsAllowed;
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CV_PROP_RW
int
minContourLengthAllowed;
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CV_PROP_RW
int
minInterContourDistance;
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CV_PROP_RW
int
minInterCheckerDistance;
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CV_PROP_RW
int
minImageSize;
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CV_PROP_RW
unsigned
minGroupSize;
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process(InputArray image,
const
TYPECHART
chartType,
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const
std::vector<Rect> ®ionsOfInterest,
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const
int
nc = 1,
bool
useNet =
false,
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const
int
nc = 1,
bool
useNet =
false,
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CV_WRAP
virtual
std::vector<Ptr<CChecker>> getListColorChecker() = 0;
This is a base class for all more or less complex algorithms in OpenCV
Definition:
core.hpp:3091
This class allows to create and manipulate comprehensive artificial neural networks.
Definition:
dnn/dnn.hpp:407
A class to find the positions of the ColorCharts in the image.
Definition:
checker_detector.hpp:130
virtual CV_WRAP bool process(InputArray image, const TYPECHART chartType, const int nc=1, bool useNet=false, const Ptr< DetectorParameters > ¶ms=DetectorParameters::create())=0
Find the ColorCharts in the given image.
CV_WRAP_AS(processWithROI) virtual bool process(InputArray image
Find the ColorCharts in the given image.
TYPECHART
enum to hold the type of the checker
Definition:
checker_model.hpp:47
"black box" representation of the file storage associated with a file on disk.
Definition:
aruco.hpp:75
Definition:
cvstd_wrapper.hpp:74
Parameters for the detectMarker process:
Definition:
checker_detector.hpp:100