帮我写一个双目相机标定的python代码

好的，双目相机标定的Python代码如下：

import numpy as np
import cv2

# 定义棋盘格的大小和棋盘格上每个方格的大小
board_size = (9, 6)
square_size = 0.03  # 单位为米

# 定义要标定的图像的路径
left_image_path = 'left.png'
right_image_path = 'right.png'

# 建立对象点数组
object_points = np.zeros((board_size[0]*board_size[1], 3), np.float32)
object_points[:, :2] = np.mgrid[0:board_size[0], 0:board_size[1]].T.reshape(-1, 2) * square_size

# 读取图像
left_image = cv2.imread(left_image_path)
right_image = cv2.imread(right_image_path)

# 将图像转换为灰度图
left_gray = cv2.cvtColor(left_image, cv2.COLOR_BGR2GRAY)
right_gray = cv2.cvtColor(right_image, cv2.COLOR_BGR2GRAY)

# 查找棋盘格角点
left_ret, left_corners = cv2.findChessboardCorners(left_gray, board_size)
right_ret, right_corners = cv2.findChessboardCorners(right_gray, board_size)

# 如果找到了角点，则进行标定
if left_ret and right_ret:
    # 亚像素角点精确化
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
    cv2.cornerSubPix(left_gray, left_corners, (5, 5), (-1, -1), criteria)
    cv2.cornerSubPix(right_gray, right_corners, (5, 5), (-1, -1), criteria)

    # 组合左右摄像机的角点
    image_points = np.concatenate((left_corners, right_corners), axis=1)

    # 定义相机的内参矩阵和畸变系数
    camera_matrix = np.zeros((3, 3))
    dist_coef = np.zeros((5, 1))

    # 标定相机
    ret, camera_matrix, dist_coef, rvecs, tvecs = cv2.calibrateCamera([object_points],
                                                                      [image_points],
                                                                      left_gray.shape[::-1],
                                                                      camera_matrix,
                                                                      dist_coef)

    # 标定双目相机
    flags = cv2.CALIB_FIX_INTRINSIC | cv2.CALIB_SAME_FOCAL_LENGTH
    ret, camera_matrix, dist_coef, rvecs, tvecs, E, F = cv2.stereoCalibrate([object_points],
                                                                            [left_corners],
                                                                            [right_corners],
                                                                            camera_matrix,
                                                                            dist_coef,
                                                                            camera_matrix,
                                                                            dist_coef,
                                                                            left_gray.shape[::-1],
                                                                            flags=flags,
                                                                            criteria=criteria)

    # 计算双目相机的投影矩阵
    R1, R2, P1, P2, Q, _, _ = cv2.stereoRectify(camera_matrix,
                                                 dist_coef,
                                                 camera_matrix,
                                                 dist_coef,
                                                 left_gray.shape[::-1],
                                                 np.zeros((3, 1)),
                                                 np.zeros((3, 1)),
                                                 flags=cv2.CALIB_ZERO_DISPARITY,
                                                 alpha=-1)

    # 保存结果
    np.savez('stereo_calibration.npz', camera_matrix=camera_matrix, dist_coef=dist_coef,
             R1=R1, R2=R2, P1=P1, P2=P2, Q=Q)

这段代码假定左右摄像机的图像已经分别保存在 `left.png` 和 `right.png` 中，棋盘格的大小为 `9x6`，棋盘格上每个方格的大小为 `0.03` 米。运行代码后将得到一个包含相机的内参矩阵、畸变系数和双目相机的投影矩阵等信息的文件 `stereo_calibration.npz`。