基于opencv的多路相机的相机标定C++代码

以下是基于OpenCV的多路相机的相机标定的C++代码示例：

#include <iostream>
#include <vector>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main()
{
    // 标定参数
    int chessboardWidth = 9; // 棋盘格宽度
    int chessboardHeight = 6; // 棋盘格高度
    float chessboardSize = 0.02f; // 棋盘格尺寸，单位：米
    Size chessboardSizeImg(chessboardWidth, chessboardHeight); // 棋盘格大小
    vector<vector<Point3f>> objectPoints; // 三维点
    vector<vector<Point2f>> imagePoints1, imagePoints2; // 左右相机的二维点
    vector<Point3f> objectPointsBuffer;
    vector<Point2f> corners1, corners2;
    Mat img1, img2, gray1, gray2;
    string imgPath1 = "left.png"; // 左相机图片路径
    string imgPath2 = "right.png"; // 右相机图片路径

    // 设置棋盘格的三维坐标
    for (int i = 0; i < chessboardHeight; i++)
    {
        for (int j = 0; j < chessboardWidth; j++)
        {
            objectPointsBuffer.emplace_back(Point3f(j * chessboardSize, i * chessboardSize, 0));
        }
    }

    // 读取图片
    img1 = imread(imgPath1);
    img2 = imread(imgPath2);

    // 转为灰度图
    cvtColor(img1, gray1, COLOR_BGR2GRAY);
    cvtColor(img2, gray2, COLOR_BGR2GRAY);

    // 查找棋盘格角点
    bool found1 = findChessboardCorners(gray1, chessboardSizeImg, corners1, CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + CALIB_CB_FAST_CHECK);
    bool found2 = findChessboardCorners(gray2, chessboardSizeImg, corners2, CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + CALIB_CB_FAST_CHECK);

    // 如果两个相机都找到了棋盘格角点，则保存角点
    if (found1 && found2)
    {
        objectPoints.emplace_back(objectPointsBuffer);
        imagePoints1.emplace_back(corners1);
        imagePoints2.emplace_back(corners2);
    }

    // 进行相机标定
    Mat cameraMatrix1, cameraMatrix2, distCoeffs1, distCoeffs2, R, T, E, F;
    stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, img1.size(), R, T, E, F);

    // 打印结果
    cout << "Camera Matrix 1: " << cameraMatrix1 << endl;
    cout << "Distortion Coefficients 1: " << distCoeffs1 << endl;
    cout << "Camera Matrix 2: " << cameraMatrix2 << endl;
    cout << "Distortion Coefficients 2: " << distCoeffs2 << endl;
    cout << "Rotation Matrix: " << R << endl;
    cout << "Translation Vector: " << T << endl;

    return 0;
}

注意，上述代码仅包含了相机标定的部分，实际开发中还需要考虑如何读取多个相机的图像数据、如何进行图像校正等问题。