223 lines
9.8 KiB
C++
223 lines
9.8 KiB
C++
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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/*
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* MIT License
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*
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* Copyright (c) 2018 Pedro Diamel Marrero Fernández
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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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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//----------To view debugging output-----------------------------
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//Read the tutorial on how to use debugging in this module
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//It can be found in the documentation of 'mcc' modules,
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//Then uncomment the following line to view debugging output
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//---------------------------------------------------------------
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// #define MCC_DEBUG
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//---------------------------------------------------------------
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namespace cv
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{
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namespace mcc
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{
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//! @addtogroup mcc
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//! @{
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/**
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* @brief Parameters for the detectMarker process:
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* - int adaptiveThreshWinSizeMin : minimum window size for adaptive
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* thresholding before finding contours
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* (default 23).
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* - int adaptiveThreshWinSizeMax : maximum window size for adaptive
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* thresholding before finding contours
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* (default 153).
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* - int adaptiveThreshWinSizeStep : increments from adaptiveThreshWinSizeMin to
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* adaptiveThreshWinSizeMax during the
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* thresholding (default 16).
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* - double adaptiveThreshConstant : constant for adaptive thresholding before
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* finding contours (default 7)
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* - double minContoursAreaRate : determine minimum area for marker contour to
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* be detected. This is defined as a rate respect
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* to the area of the input image. Used only if
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* neural network is used (default 0.003).
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* - double minContoursArea : determine minimum area for marker contour to be
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* detected. This is defined as the actual area. Used
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* only if neural network is not used (default 100).
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* - double confidenceThreshold : minimum confidence for a bounding box detected
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* by neural network to classify as
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* detection.(default 0.5)
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* (0<=confidenceThreshold<=1)
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* - double minContourSolidity : minimum solidity of a contour for it be
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* detected as a square in the chart. (default
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* 0.9).
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* - double findCandidatesApproxPolyDPEpsMultiplier : multipler to be used in
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* cv::ApproxPolyDP function
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* (default 0.05)
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* - int borderWidth : width of the padding used to pass the inital neural
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* network detection in the succeeding system.(default 0)
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* - float B0factor : distance between two neighbours squares of the same chart.
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* Defined as the ratio between distance and large dimension
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* of square (default 1.25)
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* - float maxError : maximum allowed error in the detection of a chart.
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* default(0.1)
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* - int minContourPointsAllowed : minium points in a detected contour.
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* default(4)
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* - int minContourLengthAllowed : minimum length of a countour. default(100)
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* - int minInterContourDistance : minimum distance between two contours.
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* default(100)
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* - int minInterCheckerDistance : minimum distance between two checkers.
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* default(10000)
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* - int minImageSize : minimum size of the smaller dimension of the image.
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* default(1000)
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* - unsigned minGroupSize : minimum number of a squared of a chart that must be
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* detected. default(4)
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*/
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struct CV_EXPORTS_W DetectorParameters
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{
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DetectorParameters();
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CV_WRAP static Ptr<DetectorParameters> create();
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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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};
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/** @brief A class to find the positions of the ColorCharts in the image.
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*/
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class CV_EXPORTS_W CCheckerDetector : public Algorithm
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{
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public:
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/** \brief Set the net which will be used to find the approximate
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* bounding boxes for the color charts.
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*
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* It is not necessary to use this, but this usually results in
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* better detection rate.
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*
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* \param net the neural network, if the network in empty, then
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* the function will return false.
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* \return true if it was able to set the detector's network,
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* false otherwise.
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*/
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CV_WRAP virtual bool setNet(dnn::Net net) = 0;
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/** \brief Find the ColorCharts in the given image.
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*
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* The found charts are not returned but instead stored in the
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* detector, these can be accessed later on using getBestColorChecker()
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* and getListColorChecker()
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* \param image image in color space BGR
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* \param chartType type of the chart to detect
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* \param regionsOfInterest regions of image to look for the chart, if
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* it is empty, charts are looked for in the
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* entire image
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* \param nc number of charts in the image, if you don't know the exact
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* then keeping this number high helps.
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* \param useNet if it is true the network provided using the setNet()
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* is used for preliminary search for regions where chart
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* could be present, inside the regionsOfInterest provied.
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* \param params parameters of the detection system. More information
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* about them can be found in the struct DetectorParameters.
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* \return true if atleast one chart is detected otherwise false
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*/
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CV_WRAP_AS(processWithROI) virtual bool
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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 Ptr<DetectorParameters> ¶ms = DetectorParameters::create()) = 0;
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/** \brief Find the ColorCharts in the given image.
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*
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* Differs from the above one only in the arguments.
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*
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* This version searches for the chart in the full image.
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*
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* The found charts are not returned but instead stored in the
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* detector, these can be accessed later on using getBestColorChecker()
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* and getListColorChecker()
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* \param image image in color space BGR
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* \param chartType type of the chart to detect
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* \param nc number of charts in the image, if you don't know the exact
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* then keeping this number high helps.
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* \param useNet if it is true the network provided using the setNet()
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* is used for preliminary search for regions where chart
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* could be present, inside the regionsOfInterest provied.
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* \param params parameters of the detection system. More information
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* about them can be found in the struct DetectorParameters.
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* \return true if atleast one chart is detected otherwise false
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*/
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CV_WRAP virtual bool
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process(InputArray image, const TYPECHART chartType,
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const int nc = 1, bool useNet = false,
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const Ptr<DetectorParameters> ¶ms = DetectorParameters::create()) = 0;
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/** \brief Get the best color checker. By the best it means the one
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* detected with the highest confidence.
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* \return checker A single colorchecker, if atleast one colorchecker
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* was detected, 'nullptr' otherwise.
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*/
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CV_WRAP virtual Ptr<mcc::CChecker> getBestColorChecker() = 0;
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/** \brief Get the list of all detected colorcheckers
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* \return checkers vector of colorcheckers
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*/
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CV_WRAP virtual std::vector<Ptr<CChecker>> getListColorChecker() = 0;
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/** \brief Returns the implementation of the CCheckerDetector.
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*
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*/
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CV_WRAP static Ptr<CCheckerDetector> create();
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};
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//! @} mcc
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} // namespace mcc
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} // namespace cv
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#endif
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