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a174a6c0b5
Add charuco pattern into calibration.cpp #23486 Added charuco pattern into calibration.cpp. Added charuco pattern with predefined aruco dictionary and with dictionary from file. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [х] I agree to contribute to the project under Apache 2 License. - [х] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [х] The PR is proposed to the proper branch - [х] There is a reference to the original bug report and related work - [х] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [х] The feature is well documented and sample code can be built with the project CMake
727 lines
29 KiB
C++
727 lines
29 KiB
C++
#include "opencv2/core.hpp"
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#include <opencv2/core/utility.hpp>
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#include "opencv2/imgproc.hpp"
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#include "opencv2/calib3d.hpp"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/videoio.hpp"
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#include "opencv2/highgui.hpp"
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#include <opencv2/objdetect/charuco_detector.hpp>
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#include <cctype>
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#include <stdio.h>
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#include <string.h>
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#include <time.h>
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#include <iostream>
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using namespace cv;
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using namespace std;
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const char * usage =
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" \nexample command line for calibration from a live feed.\n"
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" calibration -w=4 -h=5 -s=0.025 -o=camera.yml -op -oe\n"
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" \n"
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" example command line for calibration from a list of stored images:\n"
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" imagelist_creator image_list.xml *.png\n"
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" calibration -w=4 -h=5 -s=0.025 -o=camera.yml -op -oe image_list.xml\n"
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" where image_list.xml is the standard OpenCV XML/YAML\n"
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" use imagelist_creator to create the xml or yaml list\n"
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" file consisting of the list of strings, e.g.:\n"
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" \n"
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"<?xml version=\"1.0\"?>\n"
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"<opencv_storage>\n"
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"<images>\n"
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"view000.png\n"
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"view001.png\n"
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"<!-- view002.png -->\n"
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"view003.png\n"
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"view010.png\n"
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"one_extra_view.jpg\n"
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"</images>\n"
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"</opencv_storage>\n";
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const char* liveCaptureHelp =
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"When the live video from camera is used as input, the following hot-keys may be used:\n"
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" <ESC>, 'q' - quit the program\n"
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" 'g' - start capturing images\n"
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" 'u' - switch undistortion on/off\n";
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static void help(char** argv)
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{
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printf( "This is a camera calibration sample.\n"
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"Usage: %s\n"
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" -w=<board_width> # the calibration board horizontal size in inner corners "
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"for chessboard and in squares or circles for others like ChArUco or circles grid\n"
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" -h=<board_height> # the calibration board verical size in inner corners "
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"for chessboard and in squares or circles for others like ChArUco or circles grid\n"
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" [-pt=<pattern>] # the type of pattern: chessboard, charuco, circles, acircles\n"
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" [-n=<number_of_frames>] # the number of frames to use for calibration\n"
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" # (if not specified, it will be set to the number\n"
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" # of board views actually available)\n"
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" [-d=<delay>] # a minimum delay in ms between subsequent attempts to capture a next view\n"
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" # (used only for video capturing)\n"
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" [-s=<squareSize>] # square size in some user-defined units (1 by default)\n"
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" [-ms=<markerSize>] # marker size in some user-defined units (0.5 by default)\n"
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" [-ad=<arucoDict>] # Aruco dictionary name for ChArUco board. "
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"Available ArUco dictionaries: DICT_4X4_50, DICT_4X4_100, DICT_4X4_250, "
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"DICT_4X4_1000, DICT_5X5_50, DICT_5X5_100, DICT_5X5_250, DICT_5X5_1000, "
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"DICT_6X6_50, DICT_6X6_100, DICT_6X6_250, DICT_6X6_1000, DICT_7X7_50, "
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"DICT_7X7_100, DICT_7X7_250, DICT_7X7_1000, DICT_ARUCO_ORIGINAL, "
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"DICT_APRILTAG_16h5, DICT_APRILTAG_25h9, DICT_APRILTAG_36h10, DICT_APRILTAG_36h11\n"
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" [-adf=<dictFilename>] # Custom aruco dictionary file for ChArUco board\n"
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" [-o=<out_camera_params>] # the output filename for intrinsic [and extrinsic] parameters\n"
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" [-op] # write detected feature points\n"
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" [-oe] # write extrinsic parameters\n"
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" [-oo] # write refined 3D object points\n"
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" [-zt] # assume zero tangential distortion\n"
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" [-a=<aspectRatio>] # fix aspect ratio (fx/fy)\n"
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" [-p] # fix the principal point at the center\n"
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" [-v] # flip the captured images around the horizontal axis\n"
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" [-V] # use a video file, and not an image list, uses\n"
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" # [input_data] string for the video file name\n"
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" [-su] # show undistorted images after calibration\n"
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" [-ws=<number_of_pixel>] # half of search window for cornerSubPix (11 by default)\n"
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" [-fx=<X focal length>] # focal length in X-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
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" [-fy=<Y focal length>] # focal length in Y-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
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" [-cx=<X center point>] # camera center point in X-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
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" [-cy=<Y center point>] # camera center point in Y-dir as an initial intrinsic guess (if this flag is used, fx, fy, cx, cy must be set)\n"
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" [-imshow-scale # image resize scaling factor when displaying the results (must be >= 1)\n"
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" [-enable-k3=<0/1> # to enable (1) or disable (0) K3 coefficient for the distortion model\n"
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" [-dt=<distance>] # actual distance between top-left and top-right corners of\n"
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" # the calibration grid. If this parameter is specified, a more\n"
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" # accurate calibration method will be used which may be better\n"
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" # with inaccurate, roughly planar target.\n"
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" [input_data] # input data, one of the following:\n"
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" # - text file with a list of the images of the board\n"
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" # the text file can be generated with imagelist_creator\n"
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" # - name of video file with a video of the board\n"
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" # if input_data not specified, a live view from the camera is used\n"
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"\n", argv[0] );
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printf("\n%s",usage);
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printf( "\n%s", liveCaptureHelp );
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}
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enum { DETECTION = 0, CAPTURING = 1, CALIBRATED = 2 };
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enum Pattern { CHESSBOARD, CIRCLES_GRID, ASYMMETRIC_CIRCLES_GRID, CHARUCOBOARD};
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static double computeReprojectionErrors(
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const vector<vector<Point3f> >& objectPoints,
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const vector<vector<Point2f> >& imagePoints,
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const vector<Mat>& rvecs, const vector<Mat>& tvecs,
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const Mat& cameraMatrix, const Mat& distCoeffs,
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vector<float>& perViewErrors )
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{
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vector<Point2f> imagePoints2;
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int i, totalPoints = 0;
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double totalErr = 0, err;
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perViewErrors.resize(objectPoints.size());
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for( i = 0; i < (int)objectPoints.size(); i++ )
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{
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projectPoints(Mat(objectPoints[i]), rvecs[i], tvecs[i],
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cameraMatrix, distCoeffs, imagePoints2);
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err = norm(Mat(imagePoints[i]), Mat(imagePoints2), NORM_L2);
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int n = (int)objectPoints[i].size();
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perViewErrors[i] = (float)std::sqrt(err*err/n);
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totalErr += err*err;
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totalPoints += n;
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}
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return std::sqrt(totalErr/totalPoints);
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}
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static void calcChessboardCorners(Size boardSize, float squareSize, vector<Point3f>& corners, Pattern patternType = CHESSBOARD)
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{
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corners.resize(0);
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switch(patternType)
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{
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case CHESSBOARD:
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case CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float(j*squareSize),
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float(i*squareSize), 0));
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break;
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case ASYMMETRIC_CIRCLES_GRID:
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for( int i = 0; i < boardSize.height; i++ )
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for( int j = 0; j < boardSize.width; j++ )
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corners.push_back(Point3f(float((2*j + i % 2)*squareSize),
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float(i*squareSize), 0));
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break;
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case CHARUCOBOARD:
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for( int i = 0; i < boardSize.height-1; i++ )
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for( int j = 0; j < boardSize.width-1; j++ )
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corners.push_back(Point3f(float(j*squareSize),
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float(i*squareSize), 0));
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break;
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default:
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CV_Error(Error::StsBadArg, "Unknown pattern type\n");
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}
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}
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static bool runCalibration( vector<vector<Point2f> > imagePoints,
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Size imageSize, Size boardSize, Pattern patternType,
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float squareSize, float aspectRatio,
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float grid_width, bool release_object,
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int flags, Mat& cameraMatrix, Mat& distCoeffs,
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vector<Mat>& rvecs, vector<Mat>& tvecs,
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vector<float>& reprojErrs,
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vector<Point3f>& newObjPoints,
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double& totalAvgErr)
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{
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if( flags & CALIB_FIX_ASPECT_RATIO )
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cameraMatrix.at<double>(0,0) = aspectRatio;
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distCoeffs = Mat::zeros(8, 1, CV_64F);
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vector<vector<Point3f> > objectPoints(1);
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calcChessboardCorners(boardSize, squareSize, objectPoints[0], patternType);
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int offset = patternType != CHARUCOBOARD ? boardSize.width - 1: boardSize.width - 2;
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objectPoints[0][offset].x = objectPoints[0][0].x + grid_width;
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newObjPoints = objectPoints[0];
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objectPoints.resize(imagePoints.size(),objectPoints[0]);
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double rms;
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int iFixedPoint = -1;
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if (release_object)
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iFixedPoint = boardSize.width - 1;
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rms = calibrateCameraRO(objectPoints, imagePoints, imageSize, iFixedPoint,
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cameraMatrix, distCoeffs, rvecs, tvecs, newObjPoints,
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flags | CALIB_USE_LU);
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printf("RMS error reported by calibrateCamera: %g\n", rms);
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bool ok = checkRange(cameraMatrix) && checkRange(distCoeffs);
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if (release_object) {
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cout << "New board corners: " << endl;
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cout << newObjPoints[0] << endl;
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cout << newObjPoints[boardSize.width - 1] << endl;
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cout << newObjPoints[boardSize.width * (boardSize.height - 1)] << endl;
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cout << newObjPoints.back() << endl;
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}
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objectPoints.clear();
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objectPoints.resize(imagePoints.size(), newObjPoints);
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totalAvgErr = computeReprojectionErrors(objectPoints, imagePoints,
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rvecs, tvecs, cameraMatrix, distCoeffs, reprojErrs);
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return ok;
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}
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static void saveCameraParams( const string& filename,
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Size imageSize, Size boardSize,
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float squareSize, float aspectRatio, int flags,
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const Mat& cameraMatrix, const Mat& distCoeffs,
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const vector<Mat>& rvecs, const vector<Mat>& tvecs,
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const vector<float>& reprojErrs,
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const vector<vector<Point2f> >& imagePoints,
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const vector<Point3f>& newObjPoints,
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double totalAvgErr )
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{
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FileStorage fs( filename, FileStorage::WRITE );
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time_t tt;
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time( &tt );
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struct tm *t2 = localtime( &tt );
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char buf[1024];
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strftime( buf, sizeof(buf)-1, "%c", t2 );
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fs << "calibration_time" << buf;
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if( !rvecs.empty() || !reprojErrs.empty() )
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fs << "nframes" << (int)std::max(rvecs.size(), reprojErrs.size());
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fs << "image_width" << imageSize.width;
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fs << "image_height" << imageSize.height;
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fs << "board_width" << boardSize.width;
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fs << "board_height" << boardSize.height;
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fs << "square_size" << squareSize;
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if( flags & CALIB_FIX_ASPECT_RATIO )
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fs << "aspectRatio" << aspectRatio;
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if( flags != 0 )
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{
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snprintf( buf, sizeof(buf), "flags: %s%s%s%s",
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flags & CALIB_USE_INTRINSIC_GUESS ? "+use_intrinsic_guess" : "",
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flags & CALIB_FIX_ASPECT_RATIO ? "+fix_aspectRatio" : "",
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flags & CALIB_FIX_PRINCIPAL_POINT ? "+fix_principal_point" : "",
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flags & CALIB_ZERO_TANGENT_DIST ? "+zero_tangent_dist" : "" );
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//cvWriteComment( *fs, buf, 0 );
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}
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fs << "flags" << flags;
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fs << "camera_matrix" << cameraMatrix;
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fs << "distortion_coefficients" << distCoeffs;
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fs << "avg_reprojection_error" << totalAvgErr;
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if( !reprojErrs.empty() )
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fs << "per_view_reprojection_errors" << Mat(reprojErrs);
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if( !rvecs.empty() && !tvecs.empty() )
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{
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CV_Assert(rvecs[0].type() == tvecs[0].type());
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Mat bigmat((int)rvecs.size(), 6, rvecs[0].type());
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for( int i = 0; i < (int)rvecs.size(); i++ )
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{
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Mat r = bigmat(Range(i, i+1), Range(0,3));
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Mat t = bigmat(Range(i, i+1), Range(3,6));
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CV_Assert(rvecs[i].rows == 3 && rvecs[i].cols == 1);
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CV_Assert(tvecs[i].rows == 3 && tvecs[i].cols == 1);
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//*.t() is MatExpr (not Mat) so we can use assignment operator
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r = rvecs[i].t();
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t = tvecs[i].t();
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}
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//cvWriteComment( *fs, "a set of 6-tuples (rotation vector + translation vector) for each view", 0 );
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fs << "extrinsic_parameters" << bigmat;
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}
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if( !imagePoints.empty() )
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{
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Mat imagePtMat((int)imagePoints.size(), (int)imagePoints[0].size(), CV_32FC2);
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for( int i = 0; i < (int)imagePoints.size(); i++ )
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{
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Mat r = imagePtMat.row(i).reshape(2, imagePtMat.cols);
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Mat imgpti(imagePoints[i]);
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imgpti.copyTo(r);
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}
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fs << "image_points" << imagePtMat;
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}
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if( !newObjPoints.empty() )
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{
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fs << "grid_points" << newObjPoints;
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}
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}
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static bool readStringList( const string& filename, vector<string>& l )
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{
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l.resize(0);
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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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size_t dir_pos = filename.rfind('/');
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if (dir_pos == string::npos)
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dir_pos = filename.rfind('\\');
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FileNode n = fs.getFirstTopLevelNode();
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if( n.type() != FileNode::SEQ )
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return false;
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FileNodeIterator it = n.begin(), it_end = n.end();
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for( ; it != it_end; ++it )
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{
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string fname = (string)*it;
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if (dir_pos != string::npos)
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{
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string fpath = samples::findFile(filename.substr(0, dir_pos + 1) + fname, false);
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if (fpath.empty())
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{
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fpath = samples::findFile(fname);
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}
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fname = fpath;
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}
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else
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{
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fname = samples::findFile(fname);
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}
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l.push_back(fname);
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}
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return true;
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}
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static bool runAndSave(const string& outputFilename,
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const vector<vector<Point2f> >& imagePoints,
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Size imageSize, Size boardSize, Pattern patternType, float squareSize,
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float grid_width, bool release_object,
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float aspectRatio, int flags, Mat& cameraMatrix,
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Mat& distCoeffs, bool writeExtrinsics, bool writePoints, bool writeGrid )
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{
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vector<Mat> rvecs, tvecs;
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vector<float> reprojErrs;
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double totalAvgErr = 0;
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vector<Point3f> newObjPoints;
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bool ok = runCalibration(imagePoints, imageSize, boardSize, patternType, squareSize,
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aspectRatio, grid_width, release_object, flags, cameraMatrix, distCoeffs,
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rvecs, tvecs, reprojErrs, newObjPoints, totalAvgErr);
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printf("%s. avg reprojection error = %.7f\n",
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ok ? "Calibration succeeded" : "Calibration failed",
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totalAvgErr);
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if( ok )
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saveCameraParams( outputFilename, imageSize,
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boardSize, squareSize, aspectRatio,
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flags, cameraMatrix, distCoeffs,
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writeExtrinsics ? rvecs : vector<Mat>(),
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writeExtrinsics ? tvecs : vector<Mat>(),
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writeExtrinsics ? reprojErrs : vector<float>(),
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writePoints ? imagePoints : vector<vector<Point2f> >(),
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writeGrid ? newObjPoints : vector<Point3f>(),
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totalAvgErr );
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return ok;
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}
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int main( int argc, char** argv )
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{
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Size boardSize, imageSize;
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float squareSize, markerSize, aspectRatio = 1;
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Mat cameraMatrix, distCoeffs;
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string outputFilename;
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string inputFilename = "";
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int arucoDict;
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string dictFilename;
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int i, nframes;
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bool writeExtrinsics, writePoints;
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bool undistortImage = false;
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int flags = 0;
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VideoCapture capture;
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bool flipVertical;
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bool showUndistorted;
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bool videofile;
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int delay;
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clock_t prevTimestamp = 0;
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int mode = DETECTION;
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int cameraId = 0;
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vector<vector<Point2f>> imagePoints;
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vector<string> imageList;
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Pattern pattern = CHESSBOARD;
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cv::CommandLineParser parser(argc, argv,
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"{help ||}{w||}{h||}{pt|chessboard|}{n|10|}{d|1000|}{s|1|}{ms|0.5|}{ad|DICT_4X4_50|}{adf|None|}{o|out_camera_data.yml|}"
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"{op||}{oe||}{zt||}{a||}{p||}{v||}{V||}{su||}"
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"{oo||}{ws|11|}{dt||}"
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"{fx||}{fy||}{cx||}{cy||}"
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"{imshow-scale|1|}{enable-k3|0|}"
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"{@input_data|0|}");
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if (parser.has("help"))
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{
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help(argv);
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return 0;
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}
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boardSize.width = parser.get<int>( "w" );
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boardSize.height = parser.get<int>( "h" );
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if ( parser.has("pt") )
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{
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string val = parser.get<string>("pt");
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if( val == "circles" )
|
|
pattern = CIRCLES_GRID;
|
|
else if( val == "acircles" )
|
|
pattern = ASYMMETRIC_CIRCLES_GRID;
|
|
else if( val == "chessboard" )
|
|
pattern = CHESSBOARD;
|
|
else if( val == "charuco" )
|
|
pattern = CHARUCOBOARD;
|
|
else
|
|
return fprintf( stderr, "Invalid pattern type: must be chessboard or circles\n" ), -1;
|
|
}
|
|
|
|
squareSize = parser.get<float>("s");
|
|
markerSize = parser.get<float>("ms");
|
|
|
|
string arucoDictName = parser.get<string>("ad");
|
|
if (arucoDictName == "DICT_4X4_50") { arucoDict = cv::aruco::DICT_4X4_50; }
|
|
else if (arucoDictName == "DICT_4X4_100") { arucoDict = cv::aruco::DICT_4X4_100; }
|
|
else if (arucoDictName == "DICT_4X4_250") { arucoDict = cv::aruco::DICT_4X4_250; }
|
|
else if (arucoDictName == "DICT_4X4_1000") { arucoDict = cv::aruco::DICT_4X4_1000; }
|
|
else if (arucoDictName == "DICT_5X5_50") { arucoDict = cv::aruco::DICT_5X5_50; }
|
|
else if (arucoDictName == "DICT_5X5_100") { arucoDict = cv::aruco::DICT_5X5_100; }
|
|
else if (arucoDictName == "DICT_5X5_250") { arucoDict = cv::aruco::DICT_5X5_250; }
|
|
else if (arucoDictName == "DICT_5X5_1000") { arucoDict = cv::aruco::DICT_5X5_1000; }
|
|
else if (arucoDictName == "DICT_6X6_50") { arucoDict = cv::aruco::DICT_6X6_50; }
|
|
else if (arucoDictName == "DICT_6X6_100") { arucoDict = cv::aruco::DICT_6X6_100; }
|
|
else if (arucoDictName == "DICT_6X6_250") { arucoDict = cv::aruco::DICT_6X6_250; }
|
|
else if (arucoDictName == "DICT_6X6_1000") { arucoDict = cv::aruco::DICT_6X6_1000; }
|
|
else if (arucoDictName == "DICT_7X7_50") { arucoDict = cv::aruco::DICT_7X7_50; }
|
|
else if (arucoDictName == "DICT_7X7_100") { arucoDict = cv::aruco::DICT_7X7_100; }
|
|
else if (arucoDictName == "DICT_7X7_250") { arucoDict = cv::aruco::DICT_7X7_250; }
|
|
else if (arucoDictName == "DICT_7X7_1000") { arucoDict = cv::aruco::DICT_7X7_1000; }
|
|
else if (arucoDictName == "DICT_ARUCO_ORIGINAL") { arucoDict = cv::aruco::DICT_ARUCO_ORIGINAL; }
|
|
else if (arucoDictName == "DICT_APRILTAG_16h5") { arucoDict = cv::aruco::DICT_APRILTAG_16h5; }
|
|
else if (arucoDictName == "DICT_APRILTAG_25h9") { arucoDict = cv::aruco::DICT_APRILTAG_25h9; }
|
|
else if (arucoDictName == "DICT_APRILTAG_36h10") { arucoDict = cv::aruco::DICT_APRILTAG_36h10; }
|
|
else if (arucoDictName == "DICT_APRILTAG_36h11") { arucoDict = cv::aruco::DICT_APRILTAG_36h11; }
|
|
else {
|
|
cout << "Incorrect Aruco dictionary name " << arucoDictName << std::endl;
|
|
return 1;
|
|
}
|
|
|
|
dictFilename = parser.get<std::string>("adf");
|
|
nframes = parser.get<int>("n");
|
|
delay = parser.get<int>("d");
|
|
writePoints = parser.has("op");
|
|
writeExtrinsics = parser.has("oe");
|
|
bool writeGrid = parser.has("oo");
|
|
if (parser.has("a")) {
|
|
flags |= CALIB_FIX_ASPECT_RATIO;
|
|
aspectRatio = parser.get<float>("a");
|
|
}
|
|
if ( parser.has("zt") )
|
|
flags |= CALIB_ZERO_TANGENT_DIST;
|
|
if ( parser.has("p") )
|
|
flags |= CALIB_FIX_PRINCIPAL_POINT;
|
|
flipVertical = parser.has("v");
|
|
videofile = parser.has("V");
|
|
if ( parser.has("o") )
|
|
outputFilename = parser.get<string>("o");
|
|
showUndistorted = parser.has("su");
|
|
if ( isdigit(parser.get<string>("@input_data")[0]) )
|
|
cameraId = parser.get<int>("@input_data");
|
|
else
|
|
inputFilename = parser.get<string>("@input_data");
|
|
int winSize = parser.get<int>("ws");
|
|
cameraMatrix = Mat::eye(3, 3, CV_64F);
|
|
if (parser.has("fx") && parser.has("fy") && parser.has("cx") && parser.has("cy"))
|
|
{
|
|
cameraMatrix.at<double>(0,0) = parser.get<double>("fx");
|
|
cameraMatrix.at<double>(0,2) = parser.get<double>("cx");
|
|
cameraMatrix.at<double>(1,1) = parser.get<double>("fy");
|
|
cameraMatrix.at<double>(1,2) = parser.get<double>("cy");
|
|
flags |= CALIB_USE_INTRINSIC_GUESS;
|
|
std::cout << "Use the following camera matrix as an initial guess:\n" << cameraMatrix << std::endl;
|
|
}
|
|
int viewScaleFactor = parser.get<int>("imshow-scale");
|
|
bool useK3 = parser.get<bool>("enable-k3");
|
|
std::cout << "Use K3 distortion coefficient? " << useK3 << std::endl;
|
|
if (!useK3)
|
|
{
|
|
flags |= CALIB_FIX_K3;
|
|
}
|
|
|
|
float grid_width = squareSize *(pattern != CHARUCOBOARD ? (boardSize.width - 1): (boardSize.width - 2) );
|
|
bool release_object = false;
|
|
if (parser.has("dt")) {
|
|
grid_width = parser.get<float>("dt");
|
|
release_object = true;
|
|
}
|
|
if (!parser.check())
|
|
{
|
|
help(argv);
|
|
parser.printErrors();
|
|
return -1;
|
|
}
|
|
if ( squareSize <= 0 )
|
|
return fprintf( stderr, "Invalid board square width\n" ), -1;
|
|
if ( nframes <= 3 )
|
|
return printf("Invalid number of images\n" ), -1;
|
|
if ( aspectRatio <= 0 )
|
|
return printf( "Invalid aspect ratio\n" ), -1;
|
|
if ( delay <= 0 )
|
|
return printf( "Invalid delay\n" ), -1;
|
|
if ( boardSize.width <= 0 )
|
|
return fprintf( stderr, "Invalid board width\n" ), -1;
|
|
if ( boardSize.height <= 0 )
|
|
return fprintf( stderr, "Invalid board height\n" ), -1;
|
|
|
|
cv::aruco::Dictionary dictionary;
|
|
if (dictFilename == "None") {
|
|
std::cout << "Using predefined dictionary with id: " << arucoDict << std::endl;
|
|
dictionary = aruco::getPredefinedDictionary(arucoDict);
|
|
}
|
|
else {
|
|
std::cout << "Using custom dictionary from file: " << dictFilename << std::endl;
|
|
cv::FileStorage dict_file(dictFilename, cv::FileStorage::Mode::READ);
|
|
cv::FileNode fn(dict_file.root());
|
|
dictionary.readDictionary(fn);
|
|
}
|
|
|
|
cv::aruco::CharucoBoard ch_board(boardSize, squareSize, markerSize, dictionary);
|
|
std::vector<int> markerIds;
|
|
cv::aruco::CharucoDetector ch_detector(ch_board);
|
|
|
|
if( !inputFilename.empty() )
|
|
{
|
|
if( !videofile && readStringList(samples::findFile(inputFilename), imageList) )
|
|
mode = CAPTURING;
|
|
else
|
|
capture.open(samples::findFileOrKeep(inputFilename));
|
|
}
|
|
else
|
|
capture.open(cameraId);
|
|
|
|
if( !capture.isOpened() && imageList.empty() )
|
|
return fprintf( stderr, "Could not initialize video (%d) capture\n", cameraId ), -2;
|
|
|
|
if( !imageList.empty() )
|
|
nframes = (int)imageList.size();
|
|
|
|
if( capture.isOpened() )
|
|
printf( "%s", liveCaptureHelp );
|
|
|
|
namedWindow( "Image View", 1 );
|
|
|
|
for(i = 0;;i++)
|
|
{
|
|
Mat view, viewGray;
|
|
bool blink = false;
|
|
|
|
if( capture.isOpened() )
|
|
{
|
|
Mat view0;
|
|
capture >> view0;
|
|
view0.copyTo(view);
|
|
}
|
|
else if( i < (int)imageList.size() )
|
|
view = imread(imageList[i], IMREAD_COLOR);
|
|
|
|
if(view.empty())
|
|
{
|
|
if( imagePoints.size() > 0 )
|
|
runAndSave(outputFilename, imagePoints, imageSize,
|
|
boardSize, pattern, squareSize, grid_width, release_object, aspectRatio,
|
|
flags, cameraMatrix, distCoeffs,
|
|
writeExtrinsics, writePoints, writeGrid);
|
|
break;
|
|
}
|
|
|
|
imageSize = view.size();
|
|
|
|
if( flipVertical )
|
|
flip( view, view, 0 );
|
|
|
|
vector<Point2f> pointbuf;
|
|
cvtColor(view, viewGray, COLOR_BGR2GRAY);
|
|
|
|
bool found;
|
|
switch( pattern )
|
|
{
|
|
case CHESSBOARD:
|
|
found = findChessboardCorners( view, boardSize, pointbuf,
|
|
CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_FAST_CHECK | CALIB_CB_NORMALIZE_IMAGE);
|
|
break;
|
|
case CIRCLES_GRID:
|
|
found = findCirclesGrid( view, boardSize, pointbuf );
|
|
break;
|
|
case ASYMMETRIC_CIRCLES_GRID:
|
|
found = findCirclesGrid( view, boardSize, pointbuf, CALIB_CB_ASYMMETRIC_GRID );
|
|
break;
|
|
case CHARUCOBOARD:
|
|
{
|
|
ch_detector.detectBoard(view, pointbuf, markerIds);
|
|
found = pointbuf.size() == (size_t)(boardSize.width-1)*(boardSize.height-1);
|
|
break;
|
|
}
|
|
default:
|
|
return fprintf( stderr, "Unknown pattern type\n" ), -1;
|
|
}
|
|
|
|
// improve the found corners' coordinate accuracy
|
|
if( pattern == CHESSBOARD && found) cornerSubPix( viewGray, pointbuf, Size(winSize,winSize),
|
|
Size(-1,-1), TermCriteria( TermCriteria::EPS+TermCriteria::COUNT, 30, 0.0001 ));
|
|
|
|
if( mode == CAPTURING && found &&
|
|
(!capture.isOpened() || clock() - prevTimestamp > delay*1e-3*CLOCKS_PER_SEC) )
|
|
{
|
|
imagePoints.push_back(pointbuf);
|
|
prevTimestamp = clock();
|
|
blink = capture.isOpened();
|
|
}
|
|
|
|
if(found)
|
|
{
|
|
if(pattern != CHARUCOBOARD)
|
|
drawChessboardCorners( view, boardSize, Mat(pointbuf), found );
|
|
else
|
|
drawChessboardCorners( view, Size(boardSize.width-1, boardSize.height-1), Mat(pointbuf), found );
|
|
}
|
|
|
|
string msg = mode == CAPTURING ? "100/100" :
|
|
mode == CALIBRATED ? "Calibrated" : "Press 'g' to start";
|
|
int baseLine = 0;
|
|
Size textSize = getTextSize(msg, 1, 1, 1, &baseLine);
|
|
Point textOrigin(view.cols - 2*textSize.width - 10, view.rows - 2*baseLine - 10);
|
|
|
|
if( mode == CAPTURING )
|
|
{
|
|
if(undistortImage)
|
|
msg = cv::format( "%d/%d Undist", (int)imagePoints.size(), nframes );
|
|
else
|
|
msg = cv::format( "%d/%d", (int)imagePoints.size(), nframes );
|
|
}
|
|
|
|
putText( view, msg, textOrigin, 1, 1,
|
|
mode != CALIBRATED ? Scalar(0,0,255) : Scalar(0,255,0));
|
|
|
|
if( blink )
|
|
bitwise_not(view, view);
|
|
|
|
if( mode == CALIBRATED && undistortImage )
|
|
{
|
|
Mat temp = view.clone();
|
|
undistort(temp, view, cameraMatrix, distCoeffs);
|
|
}
|
|
if (viewScaleFactor > 1)
|
|
{
|
|
Mat viewScale;
|
|
resize(view, viewScale, Size(), 1.0/viewScaleFactor, 1.0/viewScaleFactor, INTER_AREA);
|
|
imshow("Image View", viewScale);
|
|
}
|
|
else
|
|
{
|
|
imshow("Image View", view);
|
|
}
|
|
|
|
char key = (char)waitKey(capture.isOpened() ? 50 : 500);
|
|
|
|
if( key == 27 )
|
|
break;
|
|
|
|
if( key == 'u' && mode == CALIBRATED )
|
|
undistortImage = !undistortImage;
|
|
|
|
if( capture.isOpened() && key == 'g' )
|
|
{
|
|
mode = CAPTURING;
|
|
imagePoints.clear();
|
|
}
|
|
|
|
if( mode == CAPTURING && imagePoints.size() >= (unsigned)nframes )
|
|
{
|
|
if( runAndSave(outputFilename, imagePoints, imageSize,
|
|
boardSize, pattern, squareSize, grid_width, release_object, aspectRatio,
|
|
flags, cameraMatrix, distCoeffs,
|
|
writeExtrinsics, writePoints, writeGrid))
|
|
mode = CALIBRATED;
|
|
else
|
|
mode = DETECTION;
|
|
if( !capture.isOpened() )
|
|
break;
|
|
}
|
|
}
|
|
|
|
if( !capture.isOpened() && showUndistorted )
|
|
{
|
|
Mat view, rview, map1, map2;
|
|
initUndistortRectifyMap(cameraMatrix, distCoeffs, Mat(),
|
|
getOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imageSize, 1, imageSize, 0),
|
|
imageSize, CV_16SC2, map1, map2);
|
|
|
|
for( i = 0; i < (int)imageList.size(); i++ )
|
|
{
|
|
view = imread(imageList[i], IMREAD_COLOR);
|
|
if(view.empty())
|
|
continue;
|
|
remap(view, rview, map1, map2, INTER_LINEAR);
|
|
if (viewScaleFactor > 1)
|
|
{
|
|
Mat rviewScale;
|
|
resize(rview, rviewScale, Size(), 1.0/viewScaleFactor, 1.0/viewScaleFactor, INTER_AREA);
|
|
imshow("Image View", rviewScale);
|
|
}
|
|
else
|
|
{
|
|
imshow("Image View", rview);
|
|
}
|
|
char c = (char)waitKey();
|
|
if( c == 27 || c == 'q' || c == 'Q' )
|
|
break;
|
|
}
|
|
}
|
|
|
|
return 0;
|
|
}
|