import cv2 import numpy as np chessboard_size = (7,10) # 棋盘格行列数 objp = np.zeros((np.prod(chessboard_size), 3), np.float32) # 内部点的坐标 objp[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2) img = cv2.imread('C:\Users\lenovo\Desktop\棋盘格\标定图片\OpenCV_Chessboard.png') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ret, corners = cv2.findChessboardCorners(gray, chessboard_size, None) if ret == True: cv2.drawChessboardCorners(img, chessboard_size, corners, ret) ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera([objp], [corners], gray.shape[::-1], None, None)这段代码怎么改可以打印出相机的内部参数和畸变系数以及外部参数

以下是修改后的代码，可以打印出相机的内部参数和畸变系数以及外部参数：

import cv2
import numpy as np

chessboard_size = (7,10) # 棋盘格行列数 
objp = np.zeros((np.prod(chessboard_size), 3), np.float32) # 内部点的坐标 
objp[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)

img = cv2.imread('C:\Users\lenovo\Desktop\棋盘格\标定图片\OpenCV_Chessboard.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, corners = cv2.findChessboardCorners(gray, chessboard_size, None)

if ret == True:
    cv2.drawChessboardCorners(img, chessboard_size, corners, ret)
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera([objp], [corners], gray.shape[::-1], None, None)

    # 打印相机内部参数和畸变系数
    print("相机内部参数：")
    print(mtx)
    print("畸变系数：")
    print(dist)

    # 打印外部参数
    print("旋转向量：")
    print(rvecs)
    print("平移向量：")
    print(tvecs)

需要注意的是，外部参数的打印结果是旋转向量和平移向量，不是直接的旋转矩阵和平移矩阵。如果需要得到旋转矩阵和平移矩阵，可以使用 `cv2.Rodrigues()` 函数将旋转向量转换为旋转矩阵。