Opencv3.4 双目标定和双目匹配的demo

/* This is sample from the OpenCV book. The copyright notice is below */ /* *************** License:************************** Oct. 3, 2008 Right to use this code in any way you want without warranty, support or any guarantee of it working. BOOK: It would be nice if you cited it: Learning OpenCV: Computer Vision with the OpenCV Library by Gary Bradski and Adrian Kaehler Published by O'Reilly Media, October 3, 2008 AVAILABLE AT: http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134 Or: http://oreilly.com/catalog/9780596516130/ ISBN-10: 0596516134 or: ISBN-13: 978-0596516130 OPENCV WEBSITES: Homepage: http://opencv.org Online docs: http://docs.opencv.org Q&A forum: http://answers.opencv.org Issue tracker: http://code.opencv.org GitHub: https://github.com/opencv/opencv/ ************************************************** */ #include "opencv2/calib3d.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" #include "opencv2/imgproc.hpp" #include <vector> #include <string> #include <algorithm> #include <iostream> #include <iterator> #include <stdio.h> #include <stdlib.h> #include <ctype.h> using namespace cv; using namespace std; static int print_help() { cout << " Given a list of chessboard images, the number of corners (nx, ny)\n" " on the chessboards, and a flag: useCalibrated for \n" " calibrated (0) or\n" " uncalibrated \n" " (1: use cvStereoCalibrate(), 2: compute fundamental\n" " matrix separately) stereo. \n" " Calibrate the cameras and display the\n" " rectified results along with the computed disparity images. \n" << endl; cout << "Usage:\n ./stereo_calib -w=<board_width default=9> -h=<board_height default=6> -s=<square_size default=1.0> <image list XML/YML file default=../data/stereo_calib.xml>\n" << endl; return 0; } static void StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, bool displayCorners = false, bool useCalibrated=true, bool showRectified=true) { if( imagelist.size() % 2 != 0 ) { cout << "Error: the image list contains odd (non-even) number of elements\n"; return; } const int maxScale = 2; // ARRAY AND VECTOR STORAGE: vector<vector<Point2f> > imagePoints[2]; vector<vector<Point3f> > objectPoints; Size imageSize; int i, j, k, nimages = (int)imagelist.size()/2; imagePoints[0].resize(nimages); imagePoints[1].resize(nimages); vector<string> goodImageList; for( i = j = 0; i < nimages; i++ ) { for( k = 0; k < 2; k++ ) { const string& filename = imagelist[i*2+k]; Mat img = imread(filename, 0); if(img.empty()) break; if( imageSize == Size() ) imageSize = img.size(); else if( img.size() != imageSize ) { cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n"; break; } bool found = false; vector<Point2f>& corners = imagePoints[k][j]; for( int scale = 1; scale <= maxScale; scale++ ) { Mat timg; if( scale == 1 ) timg = img; else resize(img, timg, Size(), scale, scale, INTER_LINEAR_EXACT); found = findChessboardCorners(timg, boardSize, corners, CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE); if( found ) { if( scale > 1 ) { Mat cornersMat(corners); cornersMat *= 1./scale; } break; } } if( displayCorners ) { cout << filename << endl; Mat cimg, cimg1; cvtColor(img, cimg, COLOR_GRAY2BGR); drawChessboardCorners(cimg, boardSize, corners, found); double sf = 640./MAX(img.rows, img.cols); resize(cimg, cimg1, Size(), sf, sf, INTER_LINEAR_EXACT); imshow("corners", cimg1); char c = (char)waitKey(500); if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit exit(-1); } else putchar('.'); if( !found ) break; cornerSubPix(img, corners, Size(11,11), Size(-1,-1), TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01)); } if( k == 2 ) { goodImageList.push_back(imagelist[i*2]); goodImageList.push_back(imagelist[i*2+1]); j++; } } cout << j << " pairs have been successfully detected.\n"; nimages = j; if( nimages < 2 ) { cout << "Error: too little pairs to run the calibration\n"; return; } imagePoints[0].resize(nimages); imagePoints[1].resize(nimages); objectPoints.resize(nimages); for( i = 0; i < nimages; i++ ) { for( j = 0; j < boardSize.height; j++ ) for( k = 0; k < boardSize.width; k++ ) objectPoints[i].push_back(Point3f(k*squareSize, j*squareSize, 0)); } cout << "Running stereo calibration ...\n"; Mat cameraMatrix[2], distCoeffs[2]; cameraMatrix[0] = initCameraMatrix2D(objectPoints,imagePoints[0],imageSize,0); cameraMatrix[1] = initCameraMatrix2D(objectPoints,imagePoints[1],imageSize,0); Mat R, T, E, F; double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1], cameraMatrix[0], distCoeffs[0], cameraMatrix[1], distCoeffs[1], imageSize, R, T, E, F, CALIB_FIX_ASPECT_RATIO + CALIB_ZERO_TANGENT_DIST + CALIB_USE_INTRINSIC_GUESS + CALIB_SAME_FOCAL_LENGTH + CALIB_RATIONAL_MODEL + CALIB_FIX_K3 + CALIB_FIX_K4 + CALIB_FIX_K5, TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 100, 1e-5) ); cout << "done with RMS error=" << rms << endl; // CALIBRATION QUALITY CHECK // because the output fundamental matrix implicitly // includes all the output information, // we can check the quality of calibration using the // epipolar geometry constraint: m2^t*F*m1=0 double err = 0; int npoints = 0; vector<Vec3f> lines[2]; for( i = 0; i < nimages; i++ ) { int npt = (int)imagePoints[0][i].size(); Mat imgpt[2]; for( k = 0; k < 2; k++ ) { imgpt[k] = Mat(imagePoints[k][i]); undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]); computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]); } for( j = 0; j < npt; j++ ) { double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] + imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) + fabs(imagePoints[1][i][j].x*lines[0][j][0] + imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]); err += errij; } npoints += npt; } cout << "average epipolar err = " << err/npoints << endl; // save intrinsic parameters FileStorage fs("intrinsics.yml", FileStorage::WRITE); if( fs.isOpened() ) { fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] << "M2" << cameraMatrix[1] << "D2" << distCoeffs[1]; fs.release(); } else cout << "Error: can not sav