lidar 多帧点云数据 txt—＞bin—＞pcd 格式转换

txt—>bin ：

#!/usr/bin/env python
# coding: utf-8


import shutil
import numpy as np
import os
import glob
#from tqdm import tqdm
import multiprocessing
from argparse import ArgumentParser, SUPPRESS

def build_argparser():
    
    parser = ArgumentParser(add_help=False)
    args = parser.add_argument_group('Options')
    args.add_argument('-h', '--help', action='help', default=SUPPRESS, help='Show this help message and exit.')
    args.add_argument("-i", "--original_txt_path", help="Required. The absolute path of the input lidar .txt format data.", required=True, type=str)
    args.add_argument("-o", "--now_bin_path",help="Required. The absolute path of the output lidar .bin format data.", required=True, type=str)
    args.add_argument("-n", "--num_processes",help="Required. Number of processes,recommended 4-36", required=True, type=int)
    return parser

args = build_argparser().parse_args()
original_path = args.original_txt_path #后面加/
now_path      = args.now_bin_path #"/media/ls/871d73ac-db1f-4753-b7fd-32262a9e36e0/Wsl/Wsl/PointCloud/Makedata/data/cloud_txt"
num_processes = args.num_processes

def try_multiP_read_txt_create_bin(txt_path,now_path):
    
    with open(txt_path, 'r') as f:
        datas = f.readlines()
        
    txt_name = ((txt_path.split('/')[-1]).split('.')[-2]).split(' ')
    
    j = 0
    for i in range(len(datas)):
        data = datas[i].replace('n', '').split(' ')
        if len(data) == 1:
            index = i+1+int(data[0])
            bin_path = now_path + os.sep + txt_name[0] + "_"+ txt_name[1] + "_" + "%04d"%(j+1)+ "__"+ data[0]  +".bin"
            frame_datas = datas[i+1:index]
            #print(frame_datas)
            frame_datas = np.array([line.replace('n', '').split(' ') for line in frame_datas]).astype(np.float32)
            frame_datas.tofile(bin_path)
            print(bin_path)
            j += 1


def read_txt_create_bin(original_path,now_path):
    
    if os.path.exists(now_path):
        shutil.rmtree(now_path)
    os.mkdir(now_path)

    pool = multiprocessing.Pool(processes=num_processes)
    for txt_path in sorted(glob.glob(original_path + '/'+'*.txt')):
        pool.apply_async(try_multiP_read_txt_create_bin, (txt_path,now_path))
    pool.close()
    pool.join()


read_txt_create_bin(original_path,now_path)

print("All files have been processed!!!")
print("All files have been processed!!!")
print("All files have been processed!!!")

bin—>pcd ：

#!/usr/bin/env python
# coding: utf-8


import shutil
import numpy as np
import os
import glob
from tqdm import tqdm
import multiprocessing
from argparse import ArgumentParser, SUPPRESS

def build_argparser():

    parser = ArgumentParser(add_help=False)
    args = parser.add_argument_group('Options')
    args.add_argument('-h', '--help', action='help', default=SUPPRESS, help='Show this help message and exit.')
    args.add_argument("-i", "--original_bin_path", help="Required. The absolute path of the input lidar .bin format data.", required=True, type=str)
    args.add_argument("-o", "--now_pcd_path",help="Required. The absolute path of the output lidar .pcd format data.", required=True, type=str)
    args.add_argument("-n", "--num_processes",help="Required. Number of processes,recommended 4-16", required=True, type=int)

    return parser

args = build_argparser().parse_args()
original_bin_path = args.original_bin_path #后面加/
now_pcd_path      = args.now_pcd_path #"/media/ls/871d73ac-db1f-4753-b7fd-32262a9e36e0/Wsl/Wsl/PointCloud/Makedata/data/cloud_txt"
num_processes = args.num_processes

def try_multiP_read_bin_create_pcd(bin_path,now_pcd_path):
    
    save_pcd_path = now_pcd_path + '/' + (bin_path.split('/')[-1]).split('.')[-2] + '.pcd'
    datas_ls = np.fromfile(bin_path, dtype="float32").reshape(-1, 4)
    point_num = len(datas_ls)
    datas_np = np.array(datas_ls, dtype=np.float32)#.tolist()
    #print(datas_np)
    with open(save_pcd_path,"a") as f:
        f.write('# .PCD v0.7 - Point Cloud Data file formatnVERSION 0.7nFIELDS x y z intensitynSIZE 4 4 4 4nTYPE F F F FnCOUNT 1 1 1 1')
        string = 'nWIDTH ' + str(point_num)
        f.write(string)
        f.write('nHEIGHT 1nVIEWPOINT 0 0 0 1 0 0 0')
        string = 'nPOINTS ' + str(point_num)
        f.write(string)
        f.write('nDATA ascii')
        #np.savetxt(f,datas_np)
        for i in datas_np:
            string = 'n' + str(i[0]) + ' ' + str(i[1]) + ' ' + str(i[2])+ ' ' + str(i[3])
            #print(string)
            f.write(string)

        print(save_pcd_path)


def read_bin_create_pcd(original_bin_path,now_pcd_path):
    
    if os.path.exists(now_pcd_path):
        shutil.rmtree(now_pcd_path)
    os.mkdir(now_pcd_path)

    pool = multiprocessing.Pool(num_processes)
    for bin_path in sorted(glob.glob(original_bin_path + '/'+'*.bin')):
        #print(bin_path)
        pool.apply_async(try_multiP_read_bin_create_pcd, (bin_path,now_pcd_path))
    pool.close()
    pool.join()

read_bin_create_pcd(original_bin_path,now_pcd_path)

print("All files have been processed!!!")
print("All files have been processed!!!")
print("All files have been processed!!!")