点云处理：pcd到bin的格式转换与可视化

pcd到bin的格式转换

在Kitti数据集中，点云以bin的格式存储，在项目的实操中经常需要将采集得到的pcd格式点云转换成bin格式，以方便后续的模型训练或测试。以下代码使用python语言实现了点云的格式转换：

默认情况下，pcd格式的点云保存在./pcd文件夹下，生成的bin格式点云保存在./bin文件夹下。

import numpy as np
import os
import argparse
import pypcd
from tqdm import tqdm

def main():
    ## Add parser
    parser = argparse.ArgumentParser(description="Convert .pcd to .bin")
    parser.add_argument(
        "--pcd_path",
        help=".pcd file path.",
        type=str,
        default="./pcd"
    )
    parser.add_argument(
        "--bin_path",
        help=".bin file path.",
        type=str,
        default="./bin"
    )
    args = parser.parse_args()

    ## Find all pcd files
    pcd_files = []
    for (path, dir, files) in os.walk(args.pcd_path):
        for filename in files:
            # print(filename)
            ext = os.path.splitext(filename)[-1]
            if ext == '.pcd':
                pcd_files.append(path + "/" + filename)

    ## Sort pcd files by file name
    pcd_files.sort()   
    print("Finish to load point clouds!")

    ## Make bin_path directory
    try:
        if not (os.path.isdir(args.bin_path)):
            os.makedirs(os.path.join(args.bin_path))
    except OSError as e:
        if e.errno != errno.EEXIST:
            print ("Failed to create directory!!!!!")
            raise

    ## Converting Process
    print("Converting Start!")
    for pcd_file in tqdm(pcd_files):
        ## Get pcd file
        pc = pypcd.PointCloud.from_path(pcd_file)
	
        ## Generate bin file name
        ## bin_file_name = "{}_{:05d}.bin".format(args.file_name, seq)
	pcd_name = pcd_file.split('/')[2]
	bin_file_name = pcd_name.split('.')[0]+'.'+pcd_name.split('.')[1]+'.bin'
	## print bin_file_name        
	bin_file_path = os.path.join(args.bin_path, bin_file_name)
        
        ## Get data from pcd (x, y, z, intensity, ring, time)
        np_x = (np.array(pc.pc_data['x'], dtype=np.float32)).astype(np.float32)
        np_y = (np.array(pc.pc_data['y'], dtype=np.float32)).astype(np.float32)
        np_z = (np.array(pc.pc_data['z'], dtype=np.float32)).astype(np.float32)
        np_i = (np.array(pc.pc_data['intensity'], dtype=np.float32)).astype(np.float32)/256
        # np_r = (np.array(pc.pc_data['ring'], dtype=np.float32)).astype(np.float32)
        # np_t = (np.array(pc.pc_data['time'], dtype=np.float32)).astype(np.float32)

        ## Stack all data    
        points_32 = np.transpose(np.vstack((np_x, np_y, np_z, np_i)))

        ## Save bin file                                    
        points_32.tofile(bin_file_path)

    
if __name__ == "__main__":
    main()

拷贝代码写入到pcd2bin.py文件中，通过以下命令运行代码：

 # []表示可省略
python pcd2bin.py [--pcd_path=./pcd] [--bin_path=./bin]

可视化

使用如下的代码对pcd格式的点云进行可视化：

import numpy as np
import open3d as o3d
from open3d import geometry

def main():

    #创建窗口对象
    vis = o3d.visualization.Visualizer()
    #设置窗口标题
    vis.create_window(window_name="kitti")
    #设置点云大小
    vis.get_render_option().point_size = 1
    #设置颜色背景为黑色
    opt = vis.get_render_option()
    opt.background_color = np.asarray([0, 0, 0])
    #################################################################################################
    #读取点云文件，创建点云对象
    pcd = o3d.io.read_point_cloud("./test.pcd")
    #设置点的颜色为白色
    pcd.paint_uniform_color([1,1,1])
    #将点云加入到窗口中
    vis.add_geometry(pcd)

    vis.run()
    vis.destroy_window()
    
if __name__=="__main__":
    main()

使用如下代码对生成的bin格式点云进行可视化：

import numpy as np
import mayavi.mlab
 
# lidar_path换成自己的.bin文件路径
pointcloud = np.fromfile(str("./test.bin"), dtype=np.float32, count=-1).reshape([-1, 4])
 
x = pointcloud[:, 0]  # x position of point
y = pointcloud[:, 1]  # y position of point
z = pointcloud[:, 2]  # z position of point
 
r = pointcloud[:, 3]  # reflectance value of point
d = np.sqrt(x ** 2 + y ** 2)  # Map Distance from sensor
 
degr = np.degrees(np.arctan(z / d))
 
vals = 'height'
if vals == "height":
    col = z
else:
    col = d
 
fig = mayavi.mlab.figure(bgcolor=(0, 0, 0), size=(640, 500))
mayavi.mlab.points3d(x, y, z,
                     col,  # Values used for Color
                     mode="point",
                     colormap='spectral',  # 'bone', 'copper', 'gnuplot'
                     # color=(0, 1, 0),   # Used a fixed (r,g,b) instead
                     figure=fig,
                     )
 
mayavi.mlab.show()**加粗样式**