无重叠视场双目相机标定的python代码

我可以回答这个问题。您可以使用OpenCV库中的cv2.stereoCalibrate()函数进行无重叠视场双目相机标定。以下是一个示例代码：

import numpy as np
import cv2

# 左右相机图像的路径
left_img_path = 'left.jpg'
right_img_path = 'right.jpg'

# 左右相机的内参矩阵和畸变系数
left_camera_matrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])
left_distortion_coefficients = np.array([k1, k2, p1, p2, k3])
right_camera_matrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])
right_distortion_coefficients = np.array([k1, k2, p1, p2, k3])

# 左右相机的外参矩阵
rotation_matrix = np.array([[r11, r12, r13], [r21, r22, r23], [r31, r32, r33]])
translation_vector = np.array([tx, ty, tz])

# 读取左右相机的图像
left_img = cv2.imread(left_img_path)
right_img = cv2.imread(right_img_path)

# 提取左右相机的角点
left_corners = cv2.findChessboardCorners(left_img, (9, 6))[1]
right_corners = cv2.findChessboardCorners(right_img, (9, 6))[1]

# 进行标定
retval, left_camera_matrix, left_distortion_coefficients, right_camera_matrix, right_distortion_coefficients, rotation_matrix, translation_vector, essential_matrix, fundamental_matrix = cv2.stereoCalibrate(
objectPoints=[np.zeros((54, 3), np.float32)], # 世界坐标系中的角点坐标
imagePoints1=[left_corners], # 左相机中的角点坐标
imagePoints2=[right_corners], # 右相机中的角点坐标
cameraMatrix1=left_camera_matrix, # 左相机的内参矩阵
distCoeffs1=left_distortion_coefficients, # 左相机的畸变系数
cameraMatrix2=right_camera_matrix, # 右相机的内参矩阵
distCoeffs2=right_distortion_coefficients, # 右相机的畸变系数
imageSize=left_img.shape[:2], # 图像的大小
flags=cv2.CALIB_FIX_INTRINSIC # 标定时固定内参矩阵和畸变系数
)

# 输出标定结果
print('左相机的内参矩阵：\n', left_camera_matrix)
print('左相机的畸变系数：\n', left_distortion_coefficients)
print('右相机的内参矩阵：\n', right_camera_matrix)
print('右相机的畸变系数：\n', right_distortion_coefficients)
print('左相机到右相机的旋转矩阵：\n', rotation_matrix)
print('左相机到右相机的平移向量：\n', translation_vector)