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Open Source Computer Vision Library
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726 lines
29 KiB
726 lines
29 KiB
#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" ) |
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pattern = CIRCLES_GRID; |
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else if( val == "acircles" ) |
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pattern = ASYMMETRIC_CIRCLES_GRID; |
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else if( val == "chessboard" ) |
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pattern = CHESSBOARD; |
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else if( val == "charuco" ) |
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pattern = CHARUCOBOARD; |
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else |
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return fprintf( stderr, "Invalid pattern type: must be chessboard or circles\n" ), -1; |
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} |
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squareSize = parser.get<float>("s"); |
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markerSize = parser.get<float>("ms"); |
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string arucoDictName = parser.get<string>("ad"); |
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if (arucoDictName == "DICT_4X4_50") { arucoDict = cv::aruco::DICT_4X4_50; } |
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else if (arucoDictName == "DICT_4X4_100") { arucoDict = cv::aruco::DICT_4X4_100; } |
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else if (arucoDictName == "DICT_4X4_250") { arucoDict = cv::aruco::DICT_4X4_250; } |
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else if (arucoDictName == "DICT_4X4_1000") { arucoDict = cv::aruco::DICT_4X4_1000; } |
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else if (arucoDictName == "DICT_5X5_50") { arucoDict = cv::aruco::DICT_5X5_50; } |
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else if (arucoDictName == "DICT_5X5_100") { arucoDict = cv::aruco::DICT_5X5_100; } |
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else if (arucoDictName == "DICT_5X5_250") { arucoDict = cv::aruco::DICT_5X5_250; } |
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else if (arucoDictName == "DICT_5X5_1000") { arucoDict = cv::aruco::DICT_5X5_1000; } |
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else if (arucoDictName == "DICT_6X6_50") { arucoDict = cv::aruco::DICT_6X6_50; } |
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else if (arucoDictName == "DICT_6X6_100") { arucoDict = cv::aruco::DICT_6X6_100; } |
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else if (arucoDictName == "DICT_6X6_250") { arucoDict = cv::aruco::DICT_6X6_250; } |
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else if (arucoDictName == "DICT_6X6_1000") { arucoDict = cv::aruco::DICT_6X6_1000; } |
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else if (arucoDictName == "DICT_7X7_50") { arucoDict = cv::aruco::DICT_7X7_50; } |
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else if (arucoDictName == "DICT_7X7_100") { arucoDict = cv::aruco::DICT_7X7_100; } |
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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; |
|
}
|
|
|