python实现
import os
import struct
import numpy as np
from nuscenes.nuscenes import NuScenes
from nuscenes.utils.data_classes import LidarPointCloud
import open3d as o3d
nusc = NuScenes(version='v1.0-mini', dataroot='/home/cjk/downloads_1/mmdetection3d-main/data/', verbose=False)
# Get some random .pcd.bin file from nuScenes.
#pcd_bin_file = os.path.join(nusc.dataroot, nusc.get('sample_data', 'n008-2018-08-01-15-16-36-0400__LIDAR_TOP__1533151603547590')['filename'])
pcd_bin_file = "/home/cjk/downloads_1/mmdetection3d-main/data/v1.0-mini/samples/LIDAR_TOP/n008-2018-08-28-16-43-51-0400__LIDAR_TOP__1535489306946757.pcd.bin"
# Load the .pcd.bin file.
pc = LidarPointCloud.from_file(pcd_bin_file)
bin_pcd = pc.points.T
# Reshape and get only values for x, y and z.
bin_pcd = bin_pcd.reshape((-1, 4))[:, 0:3]
# Convert to Open3D point cloud.
o3d_pcd = o3d.geometry.PointCloud(o3d.utility.Vector3dVector(bin_pcd))
# Save to a .pcd file.
o3d.io.write_point_cloud(os.path.expanduser("/home/cjk/downloads_1/test.pcd"), o3d_pcd)
# Read the saved .pcd file from the previous step.
pcd = o3d.io.read_point_cloud(os.path.expanduser("/home/cjk/downloads_1/test.pcd"))
out_arr = np.asarray(pcd.points)
# Load the original point cloud data from nuScenes, and check that the saved .pcd matches the original data.
pc = LidarPointCloud.from_file(pcd_bin_file)
points = pc.points.T
assert np.array_equal(out_arr, points[:, :3])
标签：bin,nuscenes,file,import,data,o3d,pcd From： https://www.cnblogs.com/xiaochouk/p/18063267