写一段深度相机和机械臂手眼标定的程序

好的，以下是一段深度相机和机械臂手眼标定的程序：

import numpy as np
import cv2
import glob

# 初始化机械臂和深度相机的变量
robot_pose = []
depth_pose = []
robot_pose_inv = []
depth_pose_inv = []

# 读取机械臂和深度相机的标定图像
robot_images = sorted(glob.glob('robot_calib_images/*.jpg'))
depth_images = sorted(glob.glob('depth_calib_images/*.png'))

# 从标定图像中提取角点
robot_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
depth_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
robot_objp = np.zeros((6*7,3), np.float32)
robot_objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)
depth_objp = np.zeros((6*7,3), np.float32)
depth_objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)
robot_objpoints = []
depth_objpoints = []
robot_imgpoints = []
depth_imgpoints = []
for robot_img, depth_img in zip(robot_images, depth_images):
    robot_img = cv2.imread(robot_img)
    depth_img = cv2.imread(depth_img, cv2.IMREAD_UNCHANGED)
    gray_robot = cv2.cvtColor(robot_img, cv2.COLOR_BGR2GRAY)
    gray_depth = cv2.cvtColor(depth_img, cv2.COLOR_BGR2GRAY)
    ret_robot, corners_robot = cv2.findChessboardCorners(gray_robot, (7,6), None)
    ret_depth, corners_depth = cv2.findChessboardCorners(gray_depth, (7,6), None)
    if ret_robot and ret_depth:
        robot_objpoints.append(robot_objp)
        depth_objpoints.append(depth_objp)
        corners_robot = cv2.cornerSubPix(gray_robot,corners_robot,(11,11),(-1,-1),robot_criteria)
        corners_depth = cv2.cornerSubPix(gray_depth,corners_depth,(11,11),(-1,-1),depth_criteria)
        robot_imgpoints.append(corners_robot)
        depth_imgpoints.append(corners_depth)

# 进行机械臂和深度相机的手眼标定
retval, robot_matrix, robot_distCoeffs, robot_rvecs, robot_tvecs = cv2.calibrateCamera(robot_objpoints, robot_imgpoints, gray_robot.shape[::-1], None, None)
retval, depth_matrix, depth_distCoeffs, depth_rvecs, depth_tvecs = cv2.calibrateCamera(depth_objpoints, depth_imgpoints, gray_depth.shape[::-1], None, None)
for robot_rvec, robot_tvec, depth_rvec, depth_tvec in zip(robot_rvecs, robot_tvecs, depth_rvecs, depth_tvecs):
    robot_rmat, _ = cv2.Rodrigues(robot_rvec)
    depth_rmat, _ = cv2.Rodrigues(depth_rvec)
    robot_pose.append(np.hstack((robot_rmat, robot_tvec)))
    depth_pose.append(np.hstack((depth_rmat, depth_tvec)))
    robot_pose_inv.append(np.hstack((robot_rmat.T, -robot_rmat.T.dot(robot_tvec))))
    depth_pose_inv.append(np.hstack((depth_rmat.T, -depth_rmat.T.dot(depth_tvec))))
robot_pose = np.array(robot_pose)
depth_pose = np.array(depth_pose)
robot_pose_inv = np.array(robot_pose_inv)
depth_pose_inv = np.array(depth_pose_inv)
H = np.zeros((3,3))
for i in range(len(robot_pose)):
    H += np.dot(robot_pose[i], depth_pose_inv[i])
U, S, V = np.linalg.svd(H)
R = np.dot(U, V)
T = np.dot(depth_pose.mean(axis=0)[:3], R.T) - np.dot(robot_pose.mean(axis=0)[:3], R.T)

# 输出标定结果
print('Robot camera matrix:\n', robot_matrix)
print('Robot distortion coefficients:\n', robot_distCoeffs)
print('Depth camera matrix:\n', depth_matrix)
print('Depth distortion coefficients:\n', depth_distCoeffs)
print('Rotation matrix:\n', R)
print('Translation vector:\n', T)

这段程序首先读取了机械臂和深度相机的标定图像，并从中提取出角点。然后，使用这些角点进行机械臂和深度相机的相机内参数标定，得到了相机矩阵和畸变系数。接着，使用这些角点进行机械臂和深度相机的手眼标定，得到了机械臂和深度相机之间的转换矩阵。最后，使用SVD方法求解旋转矩阵和平移向量，输出标定结果。