binCalibration.zip_Vision_vs2015双目标定_双目_双目标定_双目标定vs2015

/* 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" //flag为0，私使用标定函数标定 " uncalibrated \n" " (1: use cvStereoCalibrate(), 2: compute fundamental\n" " matrix separately) stereo. \n"//flag为1，使用立体标定函数；flag为2,分别计算重要的矩阵 " 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; } /* 立体标定函数 参数： const vector<string>& imagelist---------一个容器名叫imagelist，每个元素都是一个图片名 Size boardSize----------标定板的大小 float squareSize---------每个角点之间的距离 bool displayCorners = false---------- bool useCalibrated=true, -----使用 bool showRectified=true----显示校正后的 返回值：无 功能：核心函数，进行立体标定，得到两个摄像机之间的参数(包括单个相机的内外参和两个相机之间的外参) */ static void //在形参中赋值，那么调用时可以给它传值，也可以不传，传了就用穿了的值，没传就用形参中的值；而形参中没赋值的，那么调用时必须传值 StereoCalib(const vector<string>& imagelist, Size boardSize, float squareSize, bool displayCorners = false, bool useCalibrated = true, bool showRectified = true) { if (imagelist.size() % 2 != 0)//图片列表必须为偶数，左右才能配对成功 { 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];//定义两个像素坐标容器，它的元素仍为容器，容器存放二维坐标 vector<vector<Point3f> > objectPoints;//定义一个世界坐标容器，它的元素仍为容器，容器里存放三维坐标 Size imageSize; int i, j, k, nimages = (int)imagelist.size() / 2;//将图片的数量除以2，为每个摄像机拍摄的图片数 imagePoints[0].resize(nimages); imagePoints[1].resize(nimages);//调整左右两个容器的大小，等于总的图片数/2 vector<string> goodImageList;//存放配好对的的图片 for (i = j = 0; i < nimages; i++)//i,j表示第几对图 { for (k = 0; k < 2; k++)//k表示“对”里边的第几张图 { const string& filename = imagelist[i * 2 + k];//就是从图片列表中读取图片名，因为要匹配着来，所以有这个循环公式 Mat img = imread(filename, 0);//读取这个图片，并将这张图片转换成灰度 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; }//检查这两幅图大小是否一样 bool found = false; vector<Point2f>& corners = imagePoints[k][j];//定义一个容器存放像素坐标，初值设置为imagePoints[2]的第k个，其实可以理解成k=0是存放左摄像机的图片，k=1同理，然后j是在左摄像机里取取第k张图 //imagelist容器就是存放图片名的，而imagePoints容器分为【0】和【1】，代表左右，【0】号容器里的元素还是容器(存放图片) for (int scale = 1; scale <= maxScale; scale++)//maxScale=2，也就是说对一对图中的每一幅都进行这个操作 { Mat timg; if (scale == 1)//就把第一幅图存储到timg timg = img; else resize(img, timg, Size(), scale, scale);//调整大小，img为输入，timg为输出 found = findChessboardCorners(timg, boardSize, corners, CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE);//检测timg的角点,放到corners容器里 if (found)//找到角点后 { if (scale > 1) { Mat cornersMat(corners);//定义矩阵类型的cornersMat,矩阵值就是corners容器的值 cornersMat *= 1. / scale; } break;//scale=1，跳出这个循环了 }//scale没有机会为2 } 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);//首先将img调成灰度cimg，在cimg上绘制角点，重置cimg的大小cimg1 imshow("corners", cimg1); char c = (char)waitKey(500);//等待500ms,如果这期间有键按下，则返回该键的ASCII值，否则返回-1 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));//找亚角点，corners作为输入，也作为输出。都绘制完了，为什么还要找亚角点？*/ } //如果是同一对的第二幅图，则还需进行以下操作：也就是说通过上面的代码已经把一对的两幅图处理完了，下面把配对好的存到goodImageList容器里 if (k == 2) { goodImageList.push_back(imagelist[i * 2]); goodImageList.push_back(imagelist[i * 2 + 1]); j++; } }//所有图片的循环结束 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));//计算每幅图对应的世界坐标,跟i无关，所以每幅图对应的世界坐标是一样的 } cout << "Running stereo calibration ...\n"; Mat cameraMatrix[2], distCoeffs[2]; cameraMatrix[0] = initCameraMatrix2D(objectPoints, imagePoints[0], imageSize, 0);//初始化相机内参矩阵，这个函数只针对Zw轴为0时的标定方法有用 cameraMatrix[1] = initCameraMatrix2D(objectPoints, imagePoints[1], imageSize, 0);//调用这个函数后，则可以得到相机的内参数矩阵 Mat R, T, E, F; //没有给畸变矩阵赋值啊，怎么作为参数传给stereo