写出python代码open3d导入ndimage模块、读取pcd点云数据、设置NDT算法参数、运行NDT算法、提取线状目标，可视化并保存结果

以下是Python代码，用于导入Open3D和ndimage模块，读取pcd点云数据，设置NDT算法参数，运行NDT算法，提取线状目标，可视化并保存结果：

import open3d as o3d
import numpy as np
from scipy import ndimage

# 读取pcd点云数据
pcd = o3d.io.read_point_cloud("point_cloud.pcd")

# 设置NDT算法参数
voxel_size = 0.05
max_iter = 50
max_distance = 0.2

# 运行NDT算法
reg_p2l = o3d.registration.registration_ndt(
    pcd, pcd, voxel_size, np.eye(4),
    o3d.registration.TransformationEstimationPointToPlane(),
    o3d.registration.ICPConvergenceCriteria(max_iteration=max_iter, relative_fitness=1e-6, relative_rmse=1e-6, max_distance=max_distance))

# 提取线状目标
pcd_transformed = pcd.transform(reg_p2l.transformation)
labels = ndimage.label(pcd_transformed.segment_plane(distance_threshold=0.2, ransac_n=3, num_iterations=1000)[1])
lines = np.unique(labels[0][np.where(labels[0] > 0)])

# 可视化并保存结果
pcd_transformed.paint_uniform_color([0.7, 0.7, 0.7])
for line in lines:
    indices = np.where(labels[0] == line)[0]
    line_pcd = pcd_transformed.select_down_sample(indices)
    line_pcd.paint_uniform_color(np.random.rand(3))
    o3d.visualization.draw_geometries([line_pcd])
o3d.io.write_point_cloud("result.pcd", pcd_transformed)

希望这个代码能够帮到你！