235 lines
8.9 KiB
C++
235 lines
8.9 KiB
C++
/*
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By downloading, copying, installing or using the software you agree to this
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license. If you do not agree to this license, do not download, install,
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copy or use the software.
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License Agreement
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For Open Source Computer Vision Library
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(3-clause BSD License)
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Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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Third party copyrights are property of their respective owners.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the names of the copyright holders nor the names of the contributors
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may be used to endorse or promote products derived from this software
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without specific prior written permission.
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This software is provided by the copyright holders and contributors "as is" and
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any express or implied warranties, including, but not limited to, the implied
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warranties of merchantability and fitness for a particular purpose are
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disclaimed. In no event shall copyright holders or contributors be liable for
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any direct, indirect, incidental, special, exemplary, or consequential damages
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(including, but not limited to, procurement of substitute goods or services;
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loss of use, data, or profits; or business interruption) however caused
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and on any theory of liability, whether in contract, strict liability,
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or tort (including negligence or otherwise) arising in any way out of
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the use of this software, even if advised of the possibility of such damage.
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*/
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#include <opencv2/highgui.hpp>
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#include <opencv2/aruco.hpp>
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#include <vector>
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#include <iostream>
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using namespace std;
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using namespace cv;
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namespace {
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const char* about = "Pose estimation using a ArUco Planar Grid board";
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const char* keys =
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"{w | | Number of squares in X direction }"
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"{h | | Number of squares in Y direction }"
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"{l | | Marker side lenght (in pixels) }"
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"{s | | Separation between two consecutive markers in the grid (in pixels)}"
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"{d | | dictionary: DICT_4X4_50=0, DICT_4X4_100=1, DICT_4X4_250=2,"
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"DICT_4X4_1000=3, DICT_5X5_50=4, DICT_5X5_100=5, DICT_5X5_250=6, DICT_5X5_1000=7, "
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"DICT_6X6_50=8, DICT_6X6_100=9, DICT_6X6_250=10, DICT_6X6_1000=11, DICT_7X7_50=12,"
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"DICT_7X7_100=13, DICT_7X7_250=14, DICT_7X7_1000=15, DICT_ARUCO_ORIGINAL = 16}"
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"{c | | Output file with calibrated camera parameters }"
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"{v | | Input from video file, if ommited, input comes from camera }"
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"{ci | 0 | Camera id if input doesnt come from video (-v) }"
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"{dp | | File of marker detector parameters }"
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"{rs | | Apply refind strategy }"
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"{r | | show rejected candidates too }";
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}
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/**
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*/
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static bool readCameraParameters(string filename, Mat &camMatrix, Mat &distCoeffs) {
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FileStorage fs(filename, FileStorage::READ);
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if(!fs.isOpened())
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return false;
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fs["camera_matrix"] >> camMatrix;
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fs["distortion_coefficients"] >> distCoeffs;
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return true;
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}
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/**
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*/
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static bool readDetectorParameters(string filename, Ptr<aruco::DetectorParameters> ¶ms) {
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FileStorage fs(filename, FileStorage::READ);
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if(!fs.isOpened())
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return false;
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fs["adaptiveThreshWinSizeMin"] >> params->adaptiveThreshWinSizeMin;
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fs["adaptiveThreshWinSizeMax"] >> params->adaptiveThreshWinSizeMax;
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fs["adaptiveThreshWinSizeStep"] >> params->adaptiveThreshWinSizeStep;
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fs["adaptiveThreshConstant"] >> params->adaptiveThreshConstant;
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fs["minMarkerPerimeterRate"] >> params->minMarkerPerimeterRate;
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fs["maxMarkerPerimeterRate"] >> params->maxMarkerPerimeterRate;
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fs["polygonalApproxAccuracyRate"] >> params->polygonalApproxAccuracyRate;
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fs["minCornerDistanceRate"] >> params->minCornerDistanceRate;
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fs["minDistanceToBorder"] >> params->minDistanceToBorder;
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fs["minMarkerDistanceRate"] >> params->minMarkerDistanceRate;
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fs["cornerRefinementMethod"] >> params->cornerRefinementMethod;
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fs["cornerRefinementWinSize"] >> params->cornerRefinementWinSize;
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fs["cornerRefinementMaxIterations"] >> params->cornerRefinementMaxIterations;
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fs["cornerRefinementMinAccuracy"] >> params->cornerRefinementMinAccuracy;
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fs["markerBorderBits"] >> params->markerBorderBits;
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fs["perspectiveRemovePixelPerCell"] >> params->perspectiveRemovePixelPerCell;
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fs["perspectiveRemoveIgnoredMarginPerCell"] >> params->perspectiveRemoveIgnoredMarginPerCell;
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fs["maxErroneousBitsInBorderRate"] >> params->maxErroneousBitsInBorderRate;
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fs["minOtsuStdDev"] >> params->minOtsuStdDev;
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fs["errorCorrectionRate"] >> params->errorCorrectionRate;
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return true;
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}
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/**
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*/
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int main(int argc, char *argv[]) {
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CommandLineParser parser(argc, argv, keys);
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parser.about(about);
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if(argc < 7) {
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parser.printMessage();
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return 0;
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}
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int markersX = parser.get<int>("w");
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int markersY = parser.get<int>("h");
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float markerLength = parser.get<float>("l");
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float markerSeparation = parser.get<float>("s");
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int dictionaryId = parser.get<int>("d");
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bool showRejected = parser.has("r");
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bool refindStrategy = parser.has("rs");
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int camId = parser.get<int>("ci");
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Mat camMatrix, distCoeffs;
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if(parser.has("c")) {
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bool readOk = readCameraParameters(parser.get<string>("c"), camMatrix, distCoeffs);
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if(!readOk) {
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cerr << "Invalid camera file" << endl;
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return 0;
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}
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}
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Ptr<aruco::DetectorParameters> detectorParams = aruco::DetectorParameters::create();
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if(parser.has("dp")) {
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bool readOk = readDetectorParameters(parser.get<string>("dp"), detectorParams);
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if(!readOk) {
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cerr << "Invalid detector parameters file" << endl;
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return 0;
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}
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}
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detectorParams->cornerRefinementMethod = aruco::CORNER_REFINE_SUBPIX; // do corner refinement in markers
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String video;
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if(parser.has("v")) {
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video = parser.get<String>("v");
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}
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if(!parser.check()) {
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parser.printErrors();
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return 0;
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}
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Ptr<aruco::Dictionary> dictionary =
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aruco::getPredefinedDictionary(aruco::PREDEFINED_DICTIONARY_NAME(dictionaryId));
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VideoCapture inputVideo;
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int waitTime;
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if(!video.empty()) {
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inputVideo.open(video);
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waitTime = 0;
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} else {
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inputVideo.open(camId);
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waitTime = 10;
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}
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float axisLength = 0.5f * ((float)min(markersX, markersY) * (markerLength + markerSeparation) +
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markerSeparation);
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// create board object
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Ptr<aruco::GridBoard> gridboard =
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aruco::GridBoard::create(markersX, markersY, markerLength, markerSeparation, dictionary);
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Ptr<aruco::Board> board = gridboard.staticCast<aruco::Board>();
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double totalTime = 0;
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int totalIterations = 0;
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while(inputVideo.grab()) {
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Mat image, imageCopy;
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inputVideo.retrieve(image);
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double tick = (double)getTickCount();
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vector< int > ids;
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vector< vector< Point2f > > corners, rejected;
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Vec3d rvec, tvec;
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// detect markers
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aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);
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// refind strategy to detect more markers
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if(refindStrategy)
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aruco::refineDetectedMarkers(image, board, corners, ids, rejected, camMatrix,
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distCoeffs);
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// estimate board pose
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int markersOfBoardDetected = 0;
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if(ids.size() > 0)
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markersOfBoardDetected =
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aruco::estimatePoseBoard(corners, ids, board, camMatrix, distCoeffs, rvec, tvec);
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double currentTime = ((double)getTickCount() - tick) / getTickFrequency();
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totalTime += currentTime;
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totalIterations++;
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if(totalIterations % 30 == 0) {
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cout << "Detection Time = " << currentTime * 1000 << " ms "
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<< "(Mean = " << 1000 * totalTime / double(totalIterations) << " ms)" << endl;
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}
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// draw results
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image.copyTo(imageCopy);
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if(ids.size() > 0) {
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aruco::drawDetectedMarkers(imageCopy, corners, ids);
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}
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if(showRejected && rejected.size() > 0)
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aruco::drawDetectedMarkers(imageCopy, rejected, noArray(), Scalar(100, 0, 255));
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if(markersOfBoardDetected > 0)
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aruco::drawAxis(imageCopy, camMatrix, distCoeffs, rvec, tvec, axisLength);
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imshow("out", imageCopy);
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char key = (char)waitKey(waitTime);
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if(key == 27) break;
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}
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return 0;
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}
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