commit

README.md

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+# 目录结构
+- python2-pjibot-double-camera-module：给国汽系统返回机器人数据（已废弃）
+- python2-pjibot-double-camera-module-pji：给朴津系统返回机器人数据（已废弃）
+
+
+# 一、安装 ros
+# 二、安装 pip2 并设置镜像源
+
+
+# 三、python2 安装依赖
+1. pip2 install oss2
+2. sudo apt install ffmpeg
+3. pip2 install pyntcloud
+4. pip2 install pyproj
+5. apt install pcl-tools
+6. pip2 install docker 
+7. pip2 install crypto
+
+# 四、python3
+1. pip3 install /root/opencv_python-4.2.0.32-cp36-cp36m-manylinux1_x86_64.whl
+2. pip3 install pycryptodome
+3. sudo apt install python3-pip
+4. pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
+5. pip3 install pandas
+6. pip3 install pybind11
+7. pip3 install scenariogeneration==0.3.7
+8. pip3 install matplotlib
+9. pip3 install scikit-learn
+10. pip3 install pyproj
+
+# 阿里云oss连接
+
+```
+cname：http://open-bucket.oss.icvdc.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+预设OSS路径： oss://open-bucket
+```
+
+```
+cname：http://pji-bucket1.oss.icvdc.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+预设OSS路径： oss://pji-bucket1
+```

archive/pcdtovideo_pji_lidar.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+    功能：将ROS bag文件中的点云数据转换为PCD文件，并将PCD文件转换为图像，最后生成视频。
+    输入：rosbag文件路径，输出路径
+    输出：生成的视频文件
+    注意：需要安装pyntcloud、matplotlib、opencv库
+"""
+
+from __future__ import print_function
+import sys
+import matplotlib.pyplot as plt
+import cv2
+import os
+import subprocess
+import matplotlib.pyplot as plt
+from pyntcloud import PyntCloud
+import rosbag
+import shutil
+
+
+def process_pcd_to_top_view_image(pcd_path, output_path):
+    # 使用 PyntCloud 读取点云数据
+    cloud = PyntCloud.from_file(pcd_path)
+    points = cloud.points
+
+    plt.figure(figsize=(10, 10))
+    ax = plt.axes(projection='3d')
+    ax.scatter(points['x'], points['y'], points['z'], s=1, color='blue')
+    ax.view_init(elev=90, azim=90)
+    ax.set_xlabel('X')
+    ax.set_ylabel('Y')
+    ax.set_zlabel('Z')
+    ax.set_xticks([])
+    ax.set_yticks([])
+    ax.set_zticks([])
+    plt.axis('off')  # 隐藏坐标轴
+    plt.savefig(output_path, bbox_inches='tight', pad_inches=0)
+    plt.close()
+
+
+def create_video_from_images(image_folder, output_video_path, frame_rate):
+    images = [img for img in sorted(os.listdir(image_folder)) if img.endswith(".jpg")]
+    if not images:
+        print("没有找到任何JPG图像，请检查图像文件夹！")
+        return
+
+    frame = cv2.imread(os.path.join(image_folder, images[0]))
+    height, width, layers = frame.shape
+    video = cv2.VideoWriter(output_video_path, cv2.VideoWriter_fourcc(*'mp4v'), float(frame_rate), (width, height))
+
+    for image in images:
+        frame = cv2.imread(os.path.join(image_folder, image))
+        if frame is not None:
+            video.write(frame)
+
+    video.release()
+    print("视频已成功保存在: ", output_video_path)
+
+
+def convert_bag_to_pcd(input_dir, output_dir):
+    """ 将ROS bag文件中的点云数据转换为PCD文件 """
+    command = 'rosrun pcl_ros bag_to_pcd ' + input_dir + ' /scan_map_icp_amcl_node/scan_point_transformed ' + output_dir
+    process = subprocess.run(command, shell=True, text=True, capture_output=True)
+    if process.returncode != 0:
+        print("转换失败:", process.stderr)
+    else:
+        print("PCD文件已成功生成")
+
+
+def parse(rosbag_path, output_base_path):
+    bag_base_name = rosbag_path.split('/')[-1].split('.')[0]
+
+    lidar_output_base = os.path.join(output_base_path, bag_base_name + '_pcd_lidar')
+    pcd_folder_path = os.path.join(lidar_output_base, 'pcd')
+    images_folder_path = os.path.join(lidar_output_base, 'images')
+
+    if not os.path.exists(pcd_folder_path):
+        os.makedirs(pcd_folder_path)
+    if not os.path.exists(images_folder_path):
+        os.makedirs(images_folder_path)
+
+    with rosbag.Bag(rosbag_path, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+        start_time = bag.get_start_time()
+        end_time = bag.get_end_time()
+        # 计算rosbag的持续时间
+        duration = end_time - start_time
+
+    bagtime = duration
+    hz = str(float(float(num_count) / bagtime))
+    print(hz)
+
+    # 转换ROS bag到PCD
+    convert_bag_to_pcd(rosbag_path, pcd_folder_path)
+
+    pcd_files = [f for f in os.listdir(pcd_folder_path) if f.endswith('.pcd')]
+    for file_name in pcd_files:
+        pcd_file_path = os.path.join(pcd_folder_path, file_name)
+        image_file_path = os.path.join(images_folder_path, file_name[:-4] + ".jpg")
+        process_pcd_to_top_view_image(pcd_file_path, image_file_path)
+
+    # 从图像生成视频
+    video_path = os.path.join(lidar_output_base, 'output_video.mp4')
+    create_video_from_images(images_folder_path, video_path, hz)
+
+    # 清理临时文件
+    shutil.rmtree(pcd_folder_path)
+    shutil.rmtree(images_folder_path)

archive/pcdtovideo_pji_lidar_bak.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+
+def draw_points(pic, filename):
+    f = open(filename, "r")
+    ff = f.readlines()[11:]
+
+    for i in range(0, len(ff)):
+        point = ff[i].split()[:4]
+        point_x = float(point[0])
+        point_y = -float(point[1])
+
+        if math.isnan(point_x):
+            pass
+        else:
+            cv2.circle(pic, (int(800 - point_x * 20), int(400 - point_y * 20)), 1, (250, 250, 250), 0)
+
+
+if __name__ == '__main__':
+    input_dir = sys.argv[1]
+    # input_dir = '/media/dell/BFAC-F22B/data/pujin_datareturn/pjirobot_20231207_2023-12-07-07-18-46_54.bag'
+    output_dir = sys.argv[2]
+    # output_dir='/media/dell/BFAC-F22B/data/pujin_datareturn'
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_lidar' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/scan_map_icp_amcl_node/scan_point_transformed'] + [
+        output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    # Process_rosbag = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    # Process_rosbag.wait()
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                pic = np.zeros([800, 1600, 3])
+                draw_points(pic, tempFilePath)
+                cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)    
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_lidar.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+
+
+def parse(input_dir, output_dir):
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_lidar' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + [
+        '/scan_map_icp_amcl_node/scan_point_transformed'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    # Process_rosbag = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    # Process_rosbag.wait()
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                pic = np.zeros([800, 1600, 3])
+                draw_points(pic, tempFilePath)
+                cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_lidar.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE,
+                  stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

archive/python2-algorithm-exam/README.md

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+pip2 install pymysql
+pip3 install pandas
+pip3 install matplotlib
+.bashrc 中添加 /root/competition/install/setup.bash
+
+nohup python2 main.py > log/main.out 2>&1 &
+

archive/python2-algorithm-exam/device_monitor_80.csv

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+        ""name"": ""scan_map_icp_amcl_node"",
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+        ""name"": ""pji-master.exe"",
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+]"
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+    },
+    {
+        ""pid"": 993,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 20.440907873933384,
+        ""memUsage"": 1.7955148
+    },
+    {
+        ""pid"": 998,
+        ""name"": ""sensor_fusion_node"",
+        ""cpuUsage"": 20.4225243985109,
+        ""memUsage"": 0.2824337
+    },
+    {
+        ""pid"": 995,
+        ""name"": ""trii_receive"",
+        ""cpuUsage"": 19.71625716091318,
+        ""memUsage"": 0.34486958
+    },
+    {
+        ""pid"": 994,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 19.655159217960847,
+        ""memUsage"": 1.7590685
+    },
+    {
+        ""pid"": 1076,
+        ""name"": ""srf_laser_odometry_node"",
+        ""cpuUsage"": 16.202097141232365,
+        ""memUsage"": 0.29806805
+    },
+    {
+        ""pid"": 1187,
+        ""name"": ""move_base"",
+        ""cpuUsage"": 15.759147508459334,
+        ""memUsage"": 4.5659437
+    }
+]",pjibot-P1YNYD1M229000131,192.168.1.104,2024-04-28 12:53:26,"[
+    {
+        ""pid"": 968,
+        ""name"": ""example_communication"",
+        ""cpuUsage"": 61.34223752523139,
+        ""memUsage"": 2.4526656
+    },
+    {
+        ""pid"": 1035,
+        ""name"": ""scan_map_icp_amcl_node"",
+        ""cpuUsage"": 59.594939875360346,
+        ""memUsage"": 1.1768409
+    },
+    {
+        ""pid"": 5533,
+        ""name"": ""record"",
+        ""cpuUsage"": 35.196943790088916,
+        ""memUsage"": 4.543812
+    },
+    {
+        ""pid"": 1017,
+        ""name"": ""amcl"",
+        ""cpuUsage"": 26.401950169477814,
+        ""memUsage"": 6.803687
+    },
+    {
+        ""pid"": 993,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 20.440907873933384,
+        ""memUsage"": 1.7955148
+    },
+    {
+        ""pid"": 998,
+        ""name"": ""sensor_fusion_node"",
+        ""cpuUsage"": 20.4225243985109,
+        ""memUsage"": 0.2824337
+    },
+    {
+        ""pid"": 995,
+        ""name"": ""trii_receive"",
+        ""cpuUsage"": 19.71625716091318,
+        ""memUsage"": 0.34486958
+    },
+    {
+        ""pid"": 994,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 19.655159217960847,
+        ""memUsage"": 1.7590685
+    },
+    {
+        ""pid"": 1076,
+        ""name"": ""srf_laser_odometry_node"",
+        ""cpuUsage"": 16.202097141232365,
+        ""memUsage"": 0.29806805
+    },
+    {
+        ""pid"": 1187,
+        ""name"": ""move_base"",
+        ""cpuUsage"": 15.759147508459334,
+        ""memUsage"": 4.5659437
+    }
+]","[
+    {
+        ""pid"": 945,
+        ""name"": ""gdb"",
+        ""cpuUsage"": 0.10356383218846066,
+        ""memUsage"": 7.5466237
+    },
+    {
+        ""pid"": 1017,
+        ""name"": ""amcl"",
+        ""cpuUsage"": 26.401950169477814,
+        ""memUsage"": 6.803687
+    },
+    {
+        ""pid"": 1187,
+        ""name"": ""move_base"",
+        ""cpuUsage"": 15.759147508459334,
+        ""memUsage"": 4.5659437
+    },
+    {
+        ""pid"": 5533,
+        ""name"": ""record"",
+        ""cpuUsage"": 35.196943790088916,
+        ""memUsage"": 4.543812
+    },
+    {
+        ""pid"": 968,
+        ""name"": ""example_communication"",
+        ""cpuUsage"": 61.34223752523139,
+        ""memUsage"": 2.4526656
+    },
+    {
+        ""pid"": 1128,
+        ""name"": ""gdb"",
+        ""cpuUsage"": 0.021071202494561625,
+        ""memUsage"": 2.0745983
+    },
+    {
+        ""pid"": 3679,
+        ""name"": ""pji-master.exe"",
+        ""cpuUsage"": 9.493316301742627,
+        ""memUsage"": 1.913077
+    },
+    {
+        ""pid"": 1173,
+        ""name"": ""node_map_convert"",
+        ""cpuUsage"": 0.17957344394331995,
+        ""memUsage"": 1.9013005
+    },
+    {
+        ""pid"": 993,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 20.440907873933384,
+        ""memUsage"": 1.7955148
+    },
+    {
+        ""pid"": 994,
+        ""name"": ""orbbec_camera_node"",
+        ""cpuUsage"": 19.655159217960847,
+        ""memUsage"": 1.7590685
+    }
+]"

archive/python2-algorithm-exam/main.py

@@ -0,0 +1,628 @@
+# -*- coding: utf-8 -*-
+import subprocess
+import time
+import oss2
+from rosbag import Bag, Compression
+import logging
+import pymysql
+import os
+import urllib2
+import json
+
+path1 = '/root/cicv_data_closedloop-data_processing/python2-algorithm-exam/'
+path2 = '/root/cicv_data_closedloop-data_processing/python2-algorithm-exam/json/'
+path3 = '/root/cicv_data_closedloop-data_processing/python2-algorithm-exam/bag/'
+path4 = '/root/cicv_data_closedloop-data_processing/python2-algorithm-exam/bag/merged/'
+
+logging.basicConfig(filename=path1 + 'log/algorithm-exam.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+sleep_time = 5  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+score_script_path = '/root/competition/Final_Compet_619.py'
+
+
+def merge(source_bag_files, target_bag_file, target_bag_file2):
+    try:
+        with Bag(target_bag_file, 'w', compression=compress_way) as o:
+            for i in range(len(source_bag_files)):
+                with Bag(source_bag_files[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        with Bag(target_bag_file2, 'w', compression=compress_way) as o2:
+            for i in range(len(source_bag_files)):
+                with Bag(source_bag_files[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        if topic == '/pj_vehicle_fdb_pub':
+                            o2.write(topic, msg, t)
+    except Exception as e:
+        logging.exception("bag包合并报错: %s", e)
+
+
+def convert_unix_timestamp(timestamp):
+    return time.strftime('%Y-%m-%d-%H-%M-%S', time.localtime(float(timestamp)))
+
+
+def format_timestamp(timestamp):
+    return time.strftime('%Y-%m-%d-%H-%M-%S', time.localtime(float(timestamp)))
+
+
+def seconds_between_timestamps(time_begin, time_end):
+    begin_seconds = int(time_begin)
+    end_seconds = int(time_end)
+    current_seconds = begin_seconds
+
+    formatted_times = []
+
+    while current_seconds <= end_seconds:
+        formatted_time = format_timestamp(current_seconds)
+        formatted_times.append(formatted_time)
+        current_seconds += 1
+
+    return formatted_times
+
+
+def parse_light_6(time_begin1, time_end1):
+    a = 6
+    result1 = []
+    try:
+        # 定义 API 地址
+        url = 'http://10.14.65.102:30087/event_rsu_rsu2cloud_spat_alias/_search'
+        logging.info('信号灯开始时间为: %s', str(int(time_begin1) * 1000))
+        logging.info('信号灯结束时间为: %s', str(int(time_end1) * 1000))
+        # 定义请求体
+        data1 = {
+            "query": {
+                "bool": {
+                    "must": [
+                        {
+                            "term": {
+                                "deviceId": {
+                                    "value": "R-HK0511"
+                                }
+                            }
+                        },
+                        {
+                            "range": {
+                                "timestamp": {
+                                    "gte": int(time_begin1) * 1000,
+                                    "lte": int(time_end1) * 1000
+                                }
+                            }
+                        }
+                    ]
+                }
+            },
+            "size": 1000,
+            "sort": [
+                {
+                    "timestamp": {
+                        "order": "asc"
+                    }
+                }
+            ]
+        }
+
+        # 将请求体转换为 JSON 格式
+        json_data = json.dumps(data1)
+
+        # 发起 HTTP POST 请求
+        request = urllib2.Request(url, json_data)
+        request.add_header('Content-Type', 'application/json; charset=UTF-8')
+
+        # 接收响应
+        response = urllib2.urlopen(request)
+
+        # 读取响应内容
+        response_data = response.read()
+        logging.info("信号灯数据结果为：%s", response_data)
+        # 将响应内容转换为 JSON 对象
+        json_response = json.loads(response_data)
+        hits_array = list(json_response.get('hits').get('hits'))
+        data_array = []
+        for hits in hits_array:
+            _source = hits.get('_source')
+            intersections = list(_source.get('intersections'))
+            for intersection in intersections:
+                intersectionTimestamp = intersection.get('intersectionTimestamp')
+                phases = list(intersection.get('phases'))
+                for phase in phases:
+                    if phase.get('phaseId') == a:
+                        phaseStates = list(phase.get('phaseStates'))
+                        for phaseState in phaseStates:
+                            startTime = phaseState.get('startTime')
+                            if startTime == 0:
+                                data_array.append(
+                                    {'intersectionTimestamp': intersectionTimestamp, 'light': phaseState.get('light')})
+
+        currentIntersectionTimestamp = data_array[0].get('intersectionTimestamp')
+        if data_array[0].get('light') == 2 or data_array[0].get('light') == 3:
+            currentLightCustom = 1
+        else:
+            currentLightCustom = 0
+
+        # logging.info("原始信号灯数据为 %s" % data_array)
+        # 0 绿灯 1 红灯
+        for e in data_array:
+            intersectionTimestamp = e.get('intersectionTimestamp')
+            tempLight = e.get('light')
+            if tempLight == 2 or tempLight == 3:  # 1红灯 0绿灯
+                tempCurrentLightCustom = 1
+            else:
+                tempCurrentLightCustom = 0
+            if tempCurrentLightCustom == currentLightCustom:
+                continue
+            else:
+                result1.append({'beginTime': currentIntersectionTimestamp, 'endTime': intersectionTimestamp,
+                                'light': tempCurrentLightCustom})
+                currentIntersectionTimestamp = intersectionTimestamp
+                currentLightCustom = tempCurrentLightCustom
+        if currentLightCustom == 1:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 1})
+        else:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 0})
+    except Exception as e:
+        logging.exception('无法获取信号灯数据，默认全程绿灯 %s' % str(e))
+        result1.append({'beginTime': int(time_begin1) * 1000, 'endTime': int(time_end1) * 1000 + 10000, 'light': 0})
+
+    # 打印JSON文件的内容
+    logging.info("信号灯数据为 %s" % result1)
+
+    # 定义要保存为JSON文件的列表
+
+    # 指定要保存的JSON文件路径
+    file_path = path2 + str(time_begin1) + '_6.json'
+
+    # 将列表保存为JSON文件
+    with open(file_path, "w") as json_file:
+        json.dump(result1, json_file)
+
+    logging.info("信号灯数据文件路径为 %s" % json_file)
+    return file_path
+
+
+def parse_light_13(time_begin1, time_end1):
+    a = 13
+    result1 = []
+    try:
+        # 定义 API 地址
+        url = 'http://10.14.65.102:30087/event_rsu_rsu2cloud_spat_alias/_search'
+        logging.info('信号灯开始时间为: %s', str(int(time_begin1) * 1000))
+        logging.info('信号灯结束时间为: %s', str(int(time_end1) * 1000))
+        # 定义请求体
+        data1 = {
+            "query": {
+                "bool": {
+                    "must": [
+                        {
+                            "term": {
+                                "deviceId": {
+                                    "value": "R-HK0511"
+                                }
+                            }
+                        },
+                        {
+                            "range": {
+                                "timestamp": {
+                                    "gte": int(time_begin1) * 1000,
+                                    "lte": int(time_end1) * 1000
+                                }
+                            }
+                        }
+                    ]
+                }
+            },
+            "size": 1000,
+            "sort": [
+                {
+                    "timestamp": {
+                        "order": "asc"
+                    }
+                }
+            ]
+        }
+
+        # 将请求体转换为 JSON 格式
+        json_data = json.dumps(data1)
+
+        # 发起 HTTP POST 请求
+        request = urllib2.Request(url, json_data)
+        request.add_header('Content-Type', 'application/json; charset=UTF-8')
+
+        # 接收响应
+        response = urllib2.urlopen(request)
+
+        # 读取响应内容
+        response_data = response.read()
+        # 将响应内容转换为 JSON 对象
+        json_response = json.loads(response_data)
+        hits_array = list(json_response.get('hits').get('hits'))
+        data_array = []
+        for hits in hits_array:
+            _source = hits.get('_source')
+            intersections = list(_source.get('intersections'))
+            for intersection in intersections:
+                intersectionTimestamp = intersection.get('intersectionTimestamp')
+                phases = list(intersection.get('phases'))
+                for phase in phases:
+                    if phase.get('phaseId') == a:
+                        phaseStates = list(phase.get('phaseStates'))
+                        for phaseState in phaseStates:
+                            startTime = phaseState.get('startTime')
+                            if startTime == 0:
+                                data_array.append(
+                                    {'intersectionTimestamp': intersectionTimestamp, 'light': phaseState.get('light')})
+
+        currentIntersectionTimestamp = data_array[0].get('intersectionTimestamp')
+        if data_array[0].get('light') == 2 or data_array[0].get('light') == 3:
+            currentLightCustom = 1
+        else:
+            currentLightCustom = 0
+
+        # logging.info("原始信号灯数据为 %s" % data_array)
+        # 0 绿灯 1 红灯
+        for e in data_array:
+            intersectionTimestamp = e.get('intersectionTimestamp')
+            tempLight = e.get('light')
+            if tempLight == 2 or tempLight == 3:  # 1红灯 0绿灯
+                tempCurrentLightCustom = 1
+            else:
+                tempCurrentLightCustom = 0
+            if tempCurrentLightCustom == currentLightCustom:
+                continue
+            else:
+                result1.append({'beginTime': currentIntersectionTimestamp, 'endTime': intersectionTimestamp,
+                                'light': tempCurrentLightCustom})
+                currentIntersectionTimestamp = intersectionTimestamp
+                currentLightCustom = tempCurrentLightCustom
+        if currentLightCustom == 1:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 1})
+        else:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 0})
+    except Exception as e:
+        logging.exception('无法获取信号灯数据，默认全程绿灯 %s' % str(e))
+        result1.append({'beginTime': int(time_begin1) * 1000, 'endTime': int(time_end1) * 1000 + 10000, 'light': 0})
+
+    # 打印JSON文件的内容
+    logging.info("信号灯数据为 %s" % result1)
+
+    # 定义要保存为JSON文件的列表
+
+    # 指定要保存的JSON文件路径
+    file_path = path2 + str(time_begin1) + '_13.json'
+
+    # 将列表保存为JSON文件
+    with open(file_path, "w") as json_file:
+        json.dump(result1, json_file)
+
+    logging.info("信号灯数据文件路径为 %s" % json_file)
+    return file_path
+
+
+def parse_light_1(time_begin1, time_end1):
+    a = 1
+    result1 = []
+    try:
+        # 定义 API 地址
+        url = 'http://10.14.65.102:30087/event_rsu_rsu2cloud_spat_alias/_search'
+        logging.info('信号灯开始时间为: %s', str(int(time_begin1) * 1000))
+        logging.info('信号灯结束时间为: %s', str(int(time_end1) * 1000))
+        # 定义请求体
+        data1 = {
+            "query": {
+                "bool": {
+                    "must": [
+                        {
+                            "term": {
+                                "deviceId": {
+                                    "value": "R-HK0511"
+                                }
+                            }
+                        },
+                        {
+                            "range": {
+                                "timestamp": {
+                                    "gte": int(time_begin1) * 1000,
+                                    "lte": int(time_end1) * 1000
+                                }
+                            }
+                        }
+                    ]
+                }
+            },
+            "size": 1000,
+            "sort": [
+                {
+                    "timestamp": {
+                        "order": "asc"
+                    }
+                }
+            ]
+        }
+
+        # 将请求体转换为 JSON 格式
+        json_data = json.dumps(data1)
+
+        # 发起 HTTP POST 请求
+        request = urllib2.Request(url, json_data)
+        request.add_header('Content-Type', 'application/json; charset=UTF-8')
+
+        # 接收响应
+        response = urllib2.urlopen(request)
+
+        # 读取响应内容
+        response_data = response.read()
+        # 将响应内容转换为 JSON 对象
+        json_response = json.loads(response_data)
+        hits_array = list(json_response.get('hits').get('hits'))
+        data_array = []
+        for hits in hits_array:
+            _source = hits.get('_source')
+            intersections = list(_source.get('intersections'))
+            for intersection in intersections:
+                intersectionTimestamp = intersection.get('intersectionTimestamp')
+                phases = list(intersection.get('phases'))
+                for phase in phases:
+                    if phase.get('phaseId') == a:
+                        phaseStates = list(phase.get('phaseStates'))
+                        for phaseState in phaseStates:
+                            startTime = phaseState.get('startTime')
+                            if startTime == 0:
+                                data_array.append(
+                                    {'intersectionTimestamp': intersectionTimestamp, 'light': phaseState.get('light')})
+
+        currentIntersectionTimestamp = data_array[0].get('intersectionTimestamp')
+        if data_array[0].get('light') == 2 or data_array[0].get('light') == 3:
+            currentLightCustom = 1
+        else:
+            currentLightCustom = 0
+
+        # logging.info("原始信号灯数据为 %s" % data_array)
+        # 0 绿灯 1 红灯
+        for e in data_array:
+            intersectionTimestamp = e.get('intersectionTimestamp')
+            tempLight = e.get('light')
+            if tempLight == 2 or tempLight == 3:  # 1红灯 0绿灯
+                tempCurrentLightCustom = 1
+            else:
+                tempCurrentLightCustom = 0
+            if tempCurrentLightCustom == currentLightCustom:
+                continue
+            else:
+                result1.append({'beginTime': currentIntersectionTimestamp, 'endTime': intersectionTimestamp,
+                                'light': tempCurrentLightCustom})
+                currentIntersectionTimestamp = intersectionTimestamp
+                currentLightCustom = tempCurrentLightCustom
+        if currentLightCustom == 1:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 1})
+        else:
+            result1.append(
+                {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000,
+                 'light': 0})
+    except Exception as e:
+        logging.exception('无法获取信号灯数据，默认全程绿灯 %s' % str(e))
+        result1.append({'beginTime': int(time_begin1) * 1000, 'endTime': int(time_end1) * 1000 + 10000, 'light': 0})
+
+    # 打印JSON文件的内容
+    logging.info("信号灯数据为 %s" % result1)
+
+    # 定义要保存为JSON文件的列表
+
+    # 指定要保存的JSON文件路径
+    file_path = path2 + str(time_begin1) + '_1.json'
+
+    # 将列表保存为JSON文件
+    with open(file_path, "w") as json_file:
+        json.dump(result1, json_file)
+
+    logging.info("信号灯数据文件路径为 %s" % json_file)
+    return file_path
+
+
+'''
+1-东进口左转
+2-东进口直行
+3-东进口右转
+4-东进口非机动车
+5–南进口左转
+6-南进口直行
+7-南进口右转
+8-南进口非机动车
+9-西进口左转
+10-西进口直行
+11-西进口右转
+12-西进口非机动车
+13-北进口左转
+14-北进口直行
+15-北进口右转
+16-北进口非机动车
+'''
+'''
+1.南进口直行 6
+2.北进口左转 13
+3.东进口左转 1
+'''
+if __name__ == '__main__':
+
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+
+    while True:
+
+        try:
+            # 连接到MySQL数据库
+            conn = pymysql.connect(
+                host='10.14.85.241',
+                # host='36.110.106.156',
+                port=3306,  # 默认MySQL端口为3306
+                user='root',
+                password='1qaz2wsx!',
+                database='dataclosedloop',
+                charset='utf8mb4',  # 设置字符集
+                cursorclass=pymysql.cursors.DictCursor,  # 设置游标类型为字典型
+                connect_timeout=60000,  # 连接超时，单位是秒
+                read_timeout=60000,  # 读取超时，单位是秒
+                write_timeout=60000  # 写入超时，单位是秒
+            )
+            # 创建一个游标对象
+            with conn.cursor() as cursor:
+                # 编写你的SQL查询语句，这里以连接查询为例
+                sql = """
+                SELECT *
+                FROM exam
+                where score_online = 0
+                  and (details is null or details = '')
+                  and end_time != '2006-01-02 15:04:05' 
+                """
+
+                # 执行查询
+                cursor.execute(sql)
+
+                # 获取查询结果
+                result = cursor.fetchall()
+                if len(result) == 0:
+                    logging.info("未查询到待评分的记录。")
+                    time.sleep(1)
+                    continue
+            conn.close()
+            # 输出结果
+            for row in result:
+                equipment_no = str(row['equipment_no'])  # 车辆编号
+
+                logging.info("即将对队伍 %s 进行评分。", row['team_name'].encode('utf-8'))
+                timestamp_begin = time.mktime(row['begin_time'].timetuple())
+                timestamp_end = time.mktime(row['end_time'].timetuple())
+                time_begin_for_light = str(int(timestamp_begin))
+                time_begin_for_bag = str(int(timestamp_begin) - (8 * 60 * 60))
+                time_end_for_light = str(int(timestamp_end))
+                time_end_for_bag = str(int(time_end_for_light) - (8 * 60 * 60))
+                interval = seconds_between_timestamps(time_begin_for_light, time_end_for_light)
+                interval_for_bag = seconds_between_timestamps(time_begin_for_bag, time_end_for_bag)
+                logging.info('时间戳 %s 到 %s 改为自定义格式 %s ', time_begin_for_bag, time_end_for_bag,
+                             interval_for_bag)
+                oss_bags = []
+                local_bags = []
+                local_delete_list = []
+                for time_prefix in interval_for_bag:
+                    # 添加待下载的bag列表
+                    for obj1 in oss2.ObjectIterator(bucket,
+                                                    prefix='competition/' + equipment_no + '/' + time_prefix):
+                        oss_bags.append(str(obj1.key))
+
+                # 下载准备merge
+                logging.info("合并区间内的bag包：%s -> %s，共 %s 个", interval_for_bag[0],
+                             interval_for_bag[len(interval_for_bag) - 1],
+                             len(interval_for_bag))
+                for oss_bag in oss_bags:
+                    bag_name = str(oss_bag).split('/')[-1]
+                    equipment_dir = path3 + equipment_no
+                    if not os.path.exists(equipment_dir) or not os.path.isdir(equipment_dir):
+                        os.makedirs(equipment_dir)
+                    local_bag_path = equipment_dir + '/' + bag_name
+                    bucket.get_object_to_file(oss_bag, local_bag_path)
+                    local_bags.append(local_bag_path)
+                    local_delete_list.append(local_bag_path)
+                # 3 合并
+                merged_bag_dir = path4 + str(interval[0]) + '/'
+                if not os.path.exists(merged_bag_dir) or not os.path.isdir(merged_bag_dir):
+                    os.makedirs(merged_bag_dir)
+                merged_bag_path = merged_bag_dir + str(interval[0]) + '.bag'
+                merged_bag_path2 = merged_bag_dir + str(interval[0]) + '_2.bag'
+                merge(local_bags, merged_bag_path, merged_bag_path2)
+                # 4 清理临时文件
+                if len(local_delete_list) > 0:
+                    for local_delete in local_delete_list:
+                        try:
+                            os.remove(local_delete)
+                        except Exception as e:
+                            logging.exception("删除本地临时文件报错: %s" % str(e))
+                logging.info("合并后的数据包为 %s" % merged_bag_path)
+                # 5 查询信号灯数据
+                try:
+                    json_path_6 = parse_light_6(time_begin_for_light, time_end_for_light)
+                    json_path_13 = parse_light_13(time_begin_for_light, time_end_for_light)
+                    json_path_1 = parse_light_1(time_begin_for_light, time_end_for_light)
+                except Exception as e:
+                    logging.exception("未获取信号灯数据: %s" % str(e))
+                    continue
+                # 6 调用bag解析程序
+                command1 = 'rosrun carcompetition jiexi_node ' + merged_bag_path
+                logging.info("生成csv: %s" % str(command1))
+                process1 = subprocess.Popen(command1, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+                output, error = process1.communicate()
+                if process1.returncode == 0:
+                    print("Output:", output)
+                else:
+                    print("Error:", error)
+                # 7 调用评分脚本获取评分结果
+                # command2 = 'python /root/competition/demo.py /root/candata.csv /root/gpsdata.csv'
+                command2 = 'python3 ' + score_script_path + ' ' + merged_bag_dir + 'candata.csv ' + merged_bag_dir + 'gpsdata.csv ' + json_path_6 + ' ' + json_path_13 + ' ' + json_path_1 + ' ' + merged_bag_path2
+                logging.info("执行打分命令 %s", command2)
+                process2 = subprocess.Popen(command2, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+                output, error = process2.communicate()
+                if process2.returncode == 0:
+                    text = str(output)
+                    logging.info('评分结果为：%s' % str(output))
+                    # 使用 json.loads() 方法将 JSON 字符串解析为 Python 字典
+                    data = json.loads(str(output))
+
+                    # 8 计算 TotalScore 和 DeductedScore 字段的总和
+                    total_score = 0  # 初始化总分数为 0
+                    for item in data:  # 遍历每个场景
+                        # 计算当前场景的实际分数（总分数减去扣减分数）
+                        actual_score = item['TotalScore'] + item['DeductedScore']
+                        # 累加实际分数到总分数
+                        total_score += actual_score
+
+                    conn2 = pymysql.connect(
+                        host='10.14.85.241',
+                        # host='36.110.106.156',
+                        port=3306,  # 默认MySQL端口为3306
+                        user='root',
+                        password='1qaz2wsx!',
+                        database='dataclosedloop',
+                        charset='utf8mb4',  # 设置字符集
+                        cursorclass=pymysql.cursors.DictCursor,  # 设置游标类型为字典型
+                        connect_timeout=60000,  # 连接超时，单位是秒
+                        read_timeout=60000,  # 读取超时，单位是秒
+                        write_timeout=60000  # 写入超时，单位是秒
+                    )
+                    # 9 将解析结果回传到数据库
+                    with conn2.cursor() as cursor2:
+                        # 编写UPDATE语句，更新指定字段
+                        sql = """
+                        UPDATE exam
+                        SET score_online = %s, details = %s
+                        WHERE id = %s
+                        """
+                        cursor2.execute(sql, (total_score, text, row['id']))
+                        conn2.commit()
+                    conn2.close()
+                else:
+                    print("执行命令报错:", error)
+                logging.info("队伍 %s 评分结束。", row['team_name'].encode('utf-8'))
+                # try:
+                #     os.remove(merged_bag_path)
+                # except Exception as e:
+                #     logging.exception("删除本地临时文件报错: %s" % str(e))
+        except Exception as e:
+            logging.exception("报错: %s" % str(e))
+            continue

archive/python2-algorithm-exam/rosrun.sh

@@ -0,0 +1,3 @@
+#!/usr/bin/env bash:wq
+source /root/competition/install/setup.bash
+rosrun carcompetition jiexi_node /root/scene1.bag

archive/python2-algorithm-exam/test.json

@@ -0,0 +1,458 @@
+{
+  "took": 1442,
+  "timed_out": false,
+  "_shards": {
+    "total": 5,
+    "successful": 5,
+    "skipped": 0,
+    "failed": 0
+  },
+  "hits": {
+    "total": 113,
+    "max_score": null,
+    "hits": [
+      {
+        "_index": "event_rsu_rsu2cloud_spat_2024-4",
+        "_type": "_doc",
+        "_id": "e84f5038c5dda60b05f5a306ffc5eb07",
+        "_score": null,
+        "_source": {
+          "msgType": "spat",
+          "rsuId": "R-HK0511",
+          "createTime": 1713380845858,
+          "id": "e84f5038c5dda60b05f5a306ffc5eb07",
+          "msgCnt": 56,
+          "intersections": [
+            {
+              "intersectionTimestamp": 1713380845006,
+              "regionId": 109,
+              "nodeId": 109,
+              "phases": [
+                {
+                  "phaseId": 1,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 2,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 3,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 340,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 5,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 6,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 7,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 9,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 10,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 11,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 13,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 14,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 15,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                }
+              ],
+              "status": 16
+            }
+          ],
+          "uuid": "uuid_5817998",
+          "deviceId": "R-HK0511",
+          "timestamp": 1713380845857
+        },
+        "sort": [
+          1713380845857
+        ]
+      },
+      {
+        "_index": "event_rsu_rsu2cloud_spat_2024-4",
+        "_type": "_doc",
+        "_id": "e84f5038c5dda60b05f5a306ffc5eb07",
+        "_score": null,
+        "_source": {
+          "msgType": "spat",
+          "rsuId": "R-HK0511",
+          "createTime": 1713380845858,
+          "id": "e84f5038c5dda60b05f5a306ffc5eb07",
+          "msgCnt": 56,
+          "intersections": [
+            {
+              "intersectionTimestamp": 1713380845006,
+              "regionId": 109,
+              "nodeId": 109,
+              "phases": [
+                {
+                  "phaseId": 1,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 2,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 3,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 340,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 5,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 6,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 7,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 9,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 10,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 11,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 190,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 13,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 14,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                },
+                {
+                  "phaseId": 15,
+                  "phaseStates": [
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 3,
+                      "likelyEndTime": 290,
+                      "startTime": 180
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 5,
+                      "likelyEndTime": 150,
+                      "startTime": 0
+                    },
+                    {
+                      "timeChangeDetails": 1,
+                      "light": 7,
+                      "likelyEndTime": 180,
+                      "startTime": 150
+                    }
+                  ]
+                }
+              ],
+              "status": 16
+            }
+          ],
+          "uuid": "uuid_5817998",
+          "deviceId": "R-HK0511",
+          "timestamp": 1713380845857
+        },
+        "sort": [
+          1713380845857
+        ]
+      }
+    ]
+  }
+}

archive/python2-algorithm-exam/test.py

@@ -0,0 +1,104 @@
+# -*- coding: utf-8 -*-
+
+import datetime
+import os
+import urllib2
+import json
+
+settings_phaseId = 6
+
+if __name__ == '__main__':
+    # 定义 API 地址
+    url = 'http://10.14.65.106:30087/event_rsu_rsu2cloud_spat_2024-4/_search'
+
+    # 定义请求体
+    data = {
+        "query": {
+            "bool": {
+                "must": [
+                    # {
+                    #     "term": {
+                    #         "rsuId.keyword": {
+                    #             "value": "R-HK0511"
+                    #         }
+                    #     }
+                    # },
+                    {
+                        "range": {
+                            "timestamp": {
+                                "gte": 1713861112000,
+                                "lte": 1713861273530
+                            }
+                        }
+                    }
+                ]
+            }
+        },
+        "size": 1000,
+        "sort": [
+            {
+                "timestamp": {
+                    "order": "asc"
+                }
+            }
+        ]
+    }
+
+    # 将请求体转换为 JSON 格式
+    json_data = json.dumps(data)
+
+    # 发起 HTTP POST 请求
+    request = urllib2.Request(url, json_data)
+    request.add_header('Content-Type', 'application/json; charset=UTF-8')
+
+    # 接收响应
+    response = urllib2.urlopen(request)
+
+    # 读取响应内容
+    response_data = response.read()
+    print(response_data)
+    # 将响应内容转换为 JSON 对象
+    json_response = json.loads(response_data)
+    hits_array = list(json_response.get('hits').get('hits'))
+    data_array = []
+    for hits in hits_array:
+        _source = hits.get('_source')
+        intersections = list(_source.get('intersections'))
+        for intersection in intersections:
+            intersectionTimestamp = intersection.get('intersectionTimestamp')
+            phases = list(intersection.get('phases'))
+            for phase in phases:
+                if phase.get('phaseId') == settings_phaseId:
+                    phaseStates = list(phase.get('phaseStates'))
+                    for phaseState in phaseStates:
+                        startTime = phaseState.get('startTime')
+                        if startTime == 0:
+                            data_array.append(
+                                {'intersectionTimestamp': intersectionTimestamp, 'light': phaseState.get('light')})
+
+    currentIntersectionTimestamp = data_array[0].get('intersectionTimestamp')
+    currentLight = data_array[0].get('light')
+    result = []
+    # 0 绿灯 1 红灯
+    for e in data_array:
+        intersectionTimestamp = e.get('intersectionTimestamp')
+        light = e.get('light')
+        if light == currentLight:
+            continue
+        if light != currentLight:
+            if currentLight == 2 or currentLight == 3:
+                result.append({'beginTime': currentIntersectionTimestamp, 'endTime': intersectionTimestamp, 'light': 1})
+            else:
+                result.append({'beginTime': currentIntersectionTimestamp, 'endTime': intersectionTimestamp, 'light': 0})
+            currentIntersectionTimestamp = intersectionTimestamp
+            currentLight = light
+    if currentLight == 2 or currentLight == 3:
+        result.append(
+            {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000, 'light': 1})
+    else:
+        result.append(
+            {'beginTime': currentIntersectionTimestamp, 'endTime': currentIntersectionTimestamp + 10000, 'light': 0})
+
+
+    # 打印JSON文件的内容
+    print(data_array)

archive/python2-algorithm-exam/test2.py

@@ -0,0 +1,33 @@
+# -*- coding: utf-8 -*-
+import csv
+import json
+
+if __name__ == '__main__':
+
+    # 读取CSV文件
+    csv_file = r'device_monitor_80.csv'  # 替换成你的CSV文件路径
+    json_list_8 = []
+    json_list_9 = []
+
+    # 读取CSV文件，并提取第8列和第9列的JSON字段
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        next(reader)  # 跳过标题行
+        for row in reader:
+            json_data_8 = json.loads(row[7])  # 第8列的索引为7
+            json_data_9 = json.loads(row[8])  # 第9列的索引为8
+            for item in json_data_8:
+                if 'record' in item['name']:
+                    json_list_8.append(item)
+            for item in json_data_9:
+                if 'record' in item['name']:
+                    json_list_9.append(item)
+
+    # 打印列表中的所有record字段的值
+    print("Json List from column 8:")
+    for record in json_list_8:
+        print(record)
+
+    print("\nJson List from column 9:")
+    for record in json_list_9:
+        print(record)

archive/python2-algorithm-exam/test3.py

@@ -0,0 +1,42 @@
+# -*- coding: utf-8 -*-
+import csv
+import json
+
+if __name__ == '__main__':
+
+
+    # 输入的CSV文件路径和输出的CSV文件路径
+    input_csv_file = 'device_monitor_80.csv'  # 替换成你的输入CSV文件路径
+    output_csv_file_8 = 'output_column_8.csv'
+    output_csv_file_9 = 'output_column_9.csv'
+
+    # 读取CSV文件，并提取第8列和第9列的JSON字段
+    with open(input_csv_file, 'r') as infile, \
+            open(output_csv_file_8, 'w') as outfile_8, \
+            open(output_csv_file_9, 'w') as outfile_9:
+
+        reader = csv.reader(infile)
+        writer_8 = csv.writer(outfile_8)
+        writer_9 = csv.writer(outfile_9)
+
+        # 写入CSV文件的表头
+        writer_8.writerow(["pid", "name", "cpuUsage", "memUsage"])
+        writer_9.writerow(["pid", "name", "cpuUsage", "memUsage"])
+
+        # 读取CSV文件的数据行
+        for row in reader:
+            json_data_8 = json.loads(row[7])  # 第8列的索引为7
+            json_data_9 = json.loads(row[8])  # 第9列的索引为8
+
+            # 写入第8列的数据
+            for item in json_data_8:
+                if item["name"] == "record":
+                    writer_8.writerow([item["pid"], item["name"], item["cpuUsage"], item["memUsage"]])
+
+            # 写入第9列的数据
+            for item in json_data_9:
+                if item["name"] == "record":
+                    writer_9.writerow([item["pid"], item["name"], item["cpuUsage"], item["memUsage"]])
+
+    print("CSV files generated successfully.")
+

archive/python2-kinglong-module/bagtocsv_hmi.py

@@ -0,0 +1,118 @@
+# coding: utf-8
+#!/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math 
+
+import sys
+import time
+
+
+def parsebag(input_dir, output_dir):   
+    
+
+
+    dic_object_detection = ['Time','FrameID','HeadingAngle','ID','East', 'North' ,'position_z', 'altitude', 'AbsVel','Type']
+    object_detection_file = open(output_dir + "/"+"pos_hmi.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+
+    frame_max=sys.maxsize
+    with rosbag.Bag(input_dir ,'r') as bag:
+        #flag=False
+        framenum = 1
+        hasLoc = False
+        for topic,msg,t in bag.read_messages():    #t代表时间
+            
+            if topic == "/cicv_location":#100hz
+                hasLoc = True
+                ego_speed=math.sqrt(msg.velocity_x**2+msg.velocity_y**2+msg.velocity_z**2)
+                message_location =[str(t)[:-6],framenum,msg.yaw,'-1',msg.position_x,msg.position_y,msg.position_z,msg.altitude,ego_speed,'2']
+
+                global  pos_x ,pos_y,pos_z
+                pos_x=msg.position_x
+                pos_y=msg.position_y
+                pos_z=msg.position_z
+                egocar_yaw=msg.yaw
+                
+                
+            if topic == "/tpperception/hmi": # 10hz
+                output_type=' '
+                if not hasLoc :
+                    # print("666")
+                    continue
+                #global  pos_x ,pos_y,pos_z
+                m=msg.header.sequence_num
+                if m<frame_max:
+                    frame_max=m 
+
+                msg_l=len(msg.objs)
+                #print(msg_l)
+                #seq=msg.header.sequence_num-frame_max+1
+                for i in range(msg_l):
+                    
+                    obj_x=msg.objs[i].xabs
+                    obj_y=msg.objs[i].yabs
+                    obj_z=msg.objs[i].z+pos_z
+                    # print(msg.objs[i].type)
+
+                    if msg.objs[i].type==0:
+                        output_type='2' #乘用车/轿车
+                    elif msg.objs[i].type==1:
+                        output_type='4' # 货车/皮卡
+                    elif msg.objs[i].type==2:
+                        output_type='7' #行人
+                    elif msg.objs[i].type==3:
+                        output_type='8' #两轮车
+                    elif msg.objs[i].type==4:
+                        output_type='10' #other
+                    elif msg.objs[i].type==5:
+                        output_type='103' #other
+                    message_obj=[message_location[0], framenum, msg.objs[i].heading, str(msg.objs[i].id), obj_x, obj_y, obj_z,message_location[-3], msg.objs[i].speed, output_type]
+                    writer_object_detection.writerow(message_obj)                  
+                writer_object_detection.writerow(message_location)
+                framenum+=1
+                #hasLoc = False
+                #data_read_flag=False
+                
+    # driving_status_file.close()
+        object_detection_file.close()
+
+if __name__ == "__main__":
+#    print("Input the path of file...."+'\n')
+
+   input_dir = sys.argv[1]
+   #input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   output_dir = sys.argv[2]
+   #output_dir='/media/dell/新加卷/bag'
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   #parsebag(input_dir, output_dir)
+
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+   except Exception as e:
+       print(e)
+
+def parse(input_dir, output_dir):
+#    print("Input the path of file...."+'\n')
+
+   #input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   #output_dir='/media/dell/新加卷/bag'
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   #parsebag(input_dir, output_dir)
+
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+       return output_dir
+   except Exception as e:
+       print(e)

archive/python2-kinglong-module/bagtocsv_orig.py

@@ -0,0 +1,117 @@
+# coding: utf-8
+#!/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math 
+
+import sys
+import time
+
+
+def parsebag(input_dir, output_dir):   
+
+    dic_object_detection = ['Time','FrameID','HeadingAngle','ID','East', 'North' ,'position_z', 'altitude', 'AbsVel','Type']
+    object_detection_file = open(output_dir + "/"+"pos_orig.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+
+    frame_max=sys.maxsize
+    with rosbag.Bag(input_dir ,'r') as bag:
+        #flag=False
+        framenum = 1
+        hasLoc = False
+        for topic,msg,t in bag.read_messages():    #t代表时间
+            
+            if topic == "/cicv_location":#100hz
+                hasLoc = True
+                ego_speed=math.sqrt(msg.velocity_x**2+msg.velocity_y**2+msg.velocity_z**2)
+                message_location =[str(t)[:-6],framenum,msg.yaw,'-1',msg.position_x,msg.position_y,msg.position_z,msg.altitude,ego_speed,'2']
+
+                global  pos_x ,pos_y,pos_z
+                pos_x=msg.position_x
+                pos_y=msg.position_y
+                pos_z=msg.position_z
+                egocar_yaw=msg.yaw
+                
+                
+            if topic == "/tpperception": # 10hz
+                output_type=' '
+                if not hasLoc :
+                    # print("666")
+                    continue
+                #global  pos_x ,pos_y,pos_z
+                m=msg.header.sequence_num
+                if m<frame_max:
+                    frame_max=m 
+
+                msg_l=len(msg.objs)
+                #print(msg_l)
+                #seq=msg.header.sequence_num-frame_max+1
+                for i in range(msg_l):
+                    
+                    obj_x=msg.objs[i].xabs
+                    obj_y=msg.objs[i].yabs
+                    obj_z=msg.objs[i].z+pos_z
+                    # print(msg.objs[i].type)
+
+                    if msg.objs[i].type==0:
+                        output_type='2' #乘用车/轿车
+                    elif msg.objs[i].type==1:
+                        output_type='4' # 货车/皮卡
+                    elif msg.objs[i].type==2:
+                        output_type='7' #行人
+                    elif msg.objs[i].type==3:
+                        output_type='8' #两轮车
+                    elif msg.objs[i].type==4:
+                        output_type='10' #other
+                    elif msg.objs[i].type==5:
+                        output_type='103' #other
+                    message_obj=[message_location[0], framenum, msg.objs[i].heading, str(msg.objs[i].id), obj_x, obj_y, obj_z,message_location[-3], msg.objs[i].speed, output_type]
+                    writer_object_detection.writerow(message_obj)                  
+                writer_object_detection.writerow(message_location)
+                framenum+=1
+                #hasLoc = False
+                #data_read_flag=False
+                
+    # driving_status_file.close()
+        object_detection_file.close()
+
+if __name__ == "__main__":
+#    print("Input the path of file...."+'\n')
+
+   input_dir = sys.argv[1]
+   #input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   output_dir = sys.argv[2]
+   #output_dir='/media/dell/新加卷/bag'
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   #parsebag(input_dir, output_dir)
+
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+   except Exception as e:
+       print(e)
+
+
+def parse(input_dir, output_dir):
+#    print("Input the path of file...."+'\n')
+
+   #input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   #output_dir='/media/dell/新加卷/bag'
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   #parsebag(input_dir, output_dir)
+
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+       return output_dir
+   except Exception as e:
+       print(e)

archive/python2-kinglong-module/get_drive.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Dec 25 17:35:56 2023
+
+@author: dell
+"""
+
+# coding: utf-8
+# !/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math
+
+import sys
+import time
+
+
+def parsebag(input_dir, output_dir):
+    dic_object_detection = ['Time', 'Strg_Angle', 'Accel_Pos', 'BrkPel_Pos', 'Real_Speed', 'latitude', 'longitude']
+    object_detection_file = open(output_dir + "/" + "drive.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+    frame_max = sys.maxsize
+    count = 1
+    with rosbag.Bag(input_dir, 'r') as bag:
+        flag = False
+
+        for topic, msg, t in bag.read_messages():  # t代表时间
+            if topic == "/cicv_location":
+                flag = True
+                latitude = msg.latitude
+                longitude = msg.longitude
+
+            if topic == "/data_read":  # 10hz
+                count += 1
+                if count % 10 == 0 and flag:
+                    message_location = [str(t)[:-6], msg.Strg_Angle_Real_Value, msg.VCU_Accel_Pos_Value,
+                                        msg.VCU_BrkPel_Pos_Value,
+                                        msg.VCU_Real_Speed * 3.6, latitude, longitude]
+
+                    writer_object_detection.writerow(message_location)
+
+        object_detection_file.close()
+
+
+if __name__ == "__main__":
+    #    print("Input the path of file...."+'\n')
+
+    # input_dir = sys.argv[1]
+    input_dir = '/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+    bagname = input_dir.split('/')[-1].split('.')[0]
+    # output_dir = sys.argv[2]
+    output_dir = '/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/'
+    output_dir = os.path.join(output_dir, bagname)
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    parsebag(input_dir, output_dir)
+    '''
+    try:
+        parsebag(input_dir, output_dir)
+        print('successfully analysis '+input_dir)
+    except Exception as e:
+        print(e)
+    '''
+
+
+def parse(input_dir, output_dir):
+    bagname = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bagname)
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    parsebag(input_dir, output_dir)
+    return output_dir

archive/python2-kinglong-module/kinglong_callback.py

@@ -0,0 +1,154 @@
+# -*- coding: utf-8 -*-
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+
+key1 = 'kinglong/'
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'open-bucket'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    count = 1
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        upload_completed_prefix_list = []
+        # 4 获取即将被合并的bag目录
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            if 'callback.json' in str(obj1.key):
+                prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                pos_orig_csv = False
+                pos_hmi_csv = False
+                drive_csv = False
+                camera_mp4 = False
+                pcd_forwardlook_mp4 = False
+                pcd_overlook_mp4 = False
+                scenario_orig_xosc = False
+                scenario_hmi_xosc = False
+                scenario_orig_mp4 = False
+                scenario_hmi_mp4 = False
+                camera_bag = False
+                fusion_bag = False
+                plan_bag = False
+                control_bag = False
+                print '检测是否文件完整：', prefix
+                for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if 'pos_orig.csv' in str(obj2.key):
+                        pos_orig_csv = True
+                    if 'pos_hmi.csv' in str(obj2.key):
+                        pos_hmi_csv = True
+                    if 'drive.csv' in str(obj2.key):
+                        drive_csv = True
+                    if 'camera.mp4' in str(obj2.key):
+                        camera_mp4 = True
+                    if 'pcd_forwardlook.mp4' in str(obj2.key):
+                        pcd_forwardlook_mp4 = True
+                    if 'pcd_overlook.mp4' in str(obj2.key):
+                        pcd_overlook_mp4 = True
+                    if 'scenario_orig.xosc' in str(obj2.key):
+                        scenario_orig_xosc = True
+                    if 'scenario_hmi.xosc' in str(obj2.key):
+                        scenario_hmi_xosc = True
+                    if 'scenario_orig.mp4' in str(obj2.key):
+                        scenario_orig_mp4 = True
+                    if 'scenario_hmi.mp4' in str(obj2.key):
+                        scenario_hmi_mp4 = True
+                    if 'camera.bag' in str(obj2.key):
+                        camera_bag = True
+                    if 'fusion.bag' in str(obj2.key):
+                        fusion_bag = True
+                    if 'plan.bag' in str(obj2.key):
+                        plan_bag = True
+                    if 'control.bag' in str(obj2.key):
+                        control_bag = True
+                if not pos_orig_csv or not pos_hmi_csv or not drive_csv or not camera_mp4 or not pcd_forwardlook_mp4 or not pcd_overlook_mp4 or not scenario_orig_xosc or not scenario_hmi_xosc or not scenario_orig_mp4 or not scenario_hmi_mp4:
+                    continue
+                time.sleep(2)
+                print '发送：', str(obj1.key)
+                # 1 获取json内容
+                json_content = bucket.get_object(str(obj1.key)).read()
+                # 2 获取token
+                json_object = json.loads(json_content)
+                data1 = {
+                    "equipmentNo": json_object['equipmentNo'],
+                    "secretKey": json_object['secretKey']
+                }
+                json_data1 = json.dumps(data1)
+                request1 = urllib2.Request("http://139.9.199.227:30991/device/auth", json_data1,
+                                           headers={'Content-Type': 'application/json'})
+                response1 = urllib2.urlopen(request1)
+                result_json1 = response1.read()
+                result_object1 = json.loads(result_json1)
+                access_token = result_object1.get('data').get('accessToken')
+                try:
+                    print 'bag文件为：', json_object['rosBagPath']
+                    old_date = json_object['dataName']
+                    data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                    equipment_no = json_object['equipmentNo']
+                    old_file_path = json_object['filePath']
+                    old_ros_bag_path = json_object['rosBagPath']
+                    task_id = json_object['taskId']
+                    trigger_id = json_object['triggerId']
+                except Exception as e:
+                    print 'callback报错：%s' % str(e)
+                    continue
+                # 将时区统一
+                new_date = add_hour(old_date, 8)
+                old_delete_list = []
+                for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                    old_delete_list.append(str(obj_old.key))
+                    if 'callback.json' in str(obj_old.key):
+                        bucket.copy_object(bucket_name, str(obj_old.key),
+                                           str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                'callback_done.json'))
+                    else:
+                        bucket.copy_object(bucket_name, str(obj_old.key), str(obj_old.key).replace(old_date, new_date))
+                bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                bucket.delete_object(old_ros_bag_path)
+                bucket.batch_delete_objects(old_delete_list)
+
+                # triggerId = json_object['triggerId']
+                data2 = {
+                    "dataName": new_date,
+                    "dataSize": data_size,
+                    "equipmentNo": equipment_no,
+                    "filePath": old_file_path.replace(old_date, new_date),
+                    "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                    "taskId": task_id,
+                    "triggerId": ["1744180835122155522", "1744178775815360514"]
+                }
+                json_data2 = json.dumps(data2)
+                request2 = urllib2.Request("http://139.9.199.227:30991/device/data/callback", json_data2,
+                                           headers={'Content-Type': 'application/json',
+                                                    'authorization': access_token})
+
+                response2 = urllib2.urlopen(request2)
+                result_json2 = response2.read()
+                result_object2 = json.loads(result_json2)
+        time.sleep(3)

archive/python2-kinglong-module/kinglong_camera.py

@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import xml.etree.ElementTree as ET
+from rosbag import Bag, Compression
+import shutil
+import docker
+import bagtocsv_orig
+import bagtocsv_hmi
+import get_drive
+import parse_jinlong_image
+import pcdtovideo_jilong_overlook
+import pcdtovideo_jilong_forwardlook
+
+key1 = 'kinglong/'
+path1 = '/root/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_mp4(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        local_mp4_dir = parse_jinlong_image.parse(merged_bag_file_path, local_parse_dir)
+        local_delete_list.append(local_mp4_dir + '/camera.mp4')
+        oss_csv_object_key = parse_prefix + 'camera.mp4'
+        print '上传摄像头视频到 %s' % oss_csv_object_key
+        bucket.put_object_from_file(oss_csv_object_key, local_mp4_dir + '/camera.mp4')
+    except Exception as e:
+        # 当出现异常时执行的代码
+        print "生成摄像头视频报错: %s" % str(e)
+        # print(f'生成摄像头视频报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取合并后的包
+            merged_bag_object_key = str(obj1.key)
+            # print(f'判断1{merged_bag_object_key}')
+            if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                merged_bag_object_key_split = merged_bag_object_key.split('/')
+                merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                camera_done = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                    if '/camera.mp4' in str(obj2.key):
+                        camera_done = True
+                if camera_done:
+                    continue
+                # print(f'需要解析{merged_bag_object_key}')
+                local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_full_name = merged_bag_object_key_split[-1]
+                merged_bag_name = merged_bag_full_name.split('.')[0]
+                bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                local_delete_list.append(local_merged_bag_path)
+                # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                parse_to_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "捕获到一个异常: %s" % str(e)
+                    # print(f'删除本地临时文件{e}')
+
+        time.sleep(sleep_time)

archive/python2-kinglong-module/kinglong_csv.py

@@ -0,0 +1,111 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import xml.etree.ElementTree as ET
+from rosbag import Bag, Compression
+import shutil
+import docker
+import bagtocsv_orig
+import bagtocsv_hmi
+import get_drive
+import parse_jinlong_image
+import pcdtovideo_jilong_overlook
+import pcdtovideo_jilong_forwardlook
+
+key1 = 'kinglong/'
+path1 = '/root/'
+sleep_time = 5  # 每多少秒扫描一次
+
+
+def parse_to_csv(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        local_csv_dir = bagtocsv_orig.parse(merged_bag_file_path, local_parse_dir)
+        local_csv_dir = bagtocsv_hmi.parse(merged_bag_file_path, local_parse_dir)
+        local_csv_dir = get_drive.parse(merged_bag_file_path, local_parse_dir)
+        csv_file_name1 = 'pos_orig'
+        csv_file_name2 = 'pos_hmi'
+        csv_file_name3 = 'drive'
+        local_delete_list.append(local_csv_dir + '/' + csv_file_name1 + '.csv')
+        local_delete_list.append(local_csv_dir + '/' + csv_file_name2 + '.csv')
+        local_delete_list.append(local_csv_dir + '/' + csv_file_name3 + '.csv')
+        oss_csv_object_key1 = parse_prefix + csv_file_name1 + '.csv'
+        oss_csv_object_key2 = parse_prefix + csv_file_name2 + '.csv'
+        oss_csv_object_key3 = parse_prefix + csv_file_name3 + '.csv'
+        # print(f'上传文件到{oss_csv_object_key1}，{oss_csv_object_key2},{oss_csv_object_key3}')
+        bucket.put_object_from_file(oss_csv_object_key1, local_csv_dir + '/' + csv_file_name1 + '.csv')
+        bucket.put_object_from_file(oss_csv_object_key2, local_csv_dir + '/' + csv_file_name2 + '.csv')
+        bucket.put_object_from_file(oss_csv_object_key3, local_csv_dir + '/' + csv_file_name3 + '.csv')
+        return local_parse_dir
+    except Exception as e:
+        print "生成csv报错: %s" % str(e)
+        # print(f'生成csv报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取合并后的包
+            merged_bag_object_key = str(obj1.key)
+            # print(f'判断1{merged_bag_object_key}')
+            if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                # print(f'需要解析{merged_bag_object_key}')
+                merged_bag_object_key_split = merged_bag_object_key.split('/')
+                merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                csv1_done = False
+                csv2_done = False
+                csv3_done = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                    if '/pos_orig.csv' in str(obj2.key):
+                        csv1_done = True
+                    if '/pos_hmi.csv' in str(obj2.key):
+                        csv2_done = True
+                    if '/drive.csv' in str(obj2.key):
+                        csv3_done = True
+                if csv1_done and csv2_done and csv3_done:
+                    continue
+                print "需要解析: %s" % merged_bag_object_key
+                # print(f'需要解析{merged_bag_object_key}')
+                local_merged_bag_path = path1 +'csv/'+ merged_bag_object_key
+                local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_full_name = merged_bag_object_key_split[-1]
+                merged_bag_name = merged_bag_full_name.split('.')[0]
+                bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                local_delete_list.append(local_merged_bag_path)
+                # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                parse_to_csv(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "删除本地临时文件: %s" % str(e)
+                    # print(f'删除本地临时文件{e}')
+        time.sleep(sleep_time)

archive/python2-kinglong-module/kinglong_merge.py

@@ -0,0 +1,182 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from rosbag import Bag, Compression
+import subprocess
+
+key1 = 'kinglong/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+path1 = '/root/'
+sleep_time = 5  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+camera_topics = ['/camera_image', '/cam_res']
+fusion_topics = ['/fusion/vis/velocity', '/cicv/lidartracking_moving_objects', '/cicv_location',
+                 '/cicv/lidarfusionmovingobject', '/cicv/lidardeeplearning_moving_objects',
+                 '/cicv/lidarcluster_moving_objects', '/cam_objects', '/points_concat', '/f_radar_objects',
+                 '/fusion/vis/box']
+plan_topics = ['/cicv_amr_trajectory', '/cicv_location', '/map_polygon', '/reference_trajectory', '/tpperception',
+               '/tprouteplan', '/jinlong_control_pub', '/vehicle_info ', '/tftrafficlight']
+control_topics = ['/cicv_location_JL', '/jinlong_flag_pub', '/car_wheel', '/nodefault_info', '/AutoModeStatus',
+                  '/vehicle_info']
+
+
+def is_upload_completed(bucket, prefix):
+    target_number = str(prefix).split('_')[-1][:-1]
+    count = 0
+    for obj in oss2.ObjectIterator(bucket, prefix=prefix):
+        if obj.key != prefix:
+            count += 1
+    return int(count) == int(target_number)
+
+
+def merge(local_bags, merged_prefix, local_merged_dir, merged_bag_name):
+    try:
+        parse_prefix = str(merged_prefix).replace('data_merge', 'data_parse')
+        all_bag_path = local_merged_dir + merged_bag_name
+        camera_bag_path = local_merged_dir + 'camera.bag'
+        fusion_bag_path = local_merged_dir + 'fusion.bag'
+        plan_bag_path = local_merged_dir + 'plan.bag'
+        control_bag_path = local_merged_dir + 'control.bag'
+
+        with Bag(all_bag_path, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        bucket.put_object_from_file(merged_prefix + merged_bag_name, all_bag_path)
+
+        with Bag(camera_bag_path, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        if topic in camera_topics:
+                            o.write(topic, msg, t)
+        bucket.put_object_from_file(parse_prefix + 'camera.bag', camera_bag_path)
+
+        with Bag(fusion_bag_path, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        if topic in fusion_topics:
+                            o.write(topic, msg, t)
+        bucket.put_object_from_file(parse_prefix + 'fusion.bag', fusion_bag_path)
+
+        with Bag(plan_bag_path, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        if topic in plan_topics:
+                            o.write(topic, msg, t)
+        bucket.put_object_from_file(parse_prefix + 'plan.bag', plan_bag_path)
+
+        with Bag(control_bag_path, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        if topic in control_topics:
+                            o.write(topic, msg, t)
+        bucket.put_object_from_file(parse_prefix + 'control.bag', control_bag_path)
+
+        return all_bag_path, camera_bag_path, fusion_bag_path, plan_bag_path, control_bag_path
+    except Exception as e:
+        print "bag包合并报错: %s" % str(e)
+        # print(f'bag包合并报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取未合并的bag包，合并 -------
+if __name__ == '__main__':
+
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    turn = 1
+    while True:
+        # print(f'当前轮次{turn}扫描开始。')
+
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        upload_completed_prefix_list_node1 = []
+        upload_completed_prefix_list_node2 = []
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1, delimiter='/'):
+            if str(obj1.key).count('/') == 2:  # pujin/robot-01/
+                # print(f'{obj1.key}')
+                for obj2 in oss2.ObjectIterator(bucket, prefix=str(obj1.key) + key2, delimiter='/'):
+                    if str(obj2.key).count('/') == 4:  # pujin/robot-01/data/node1_2023-12-20-02-16-56_obction_10/
+                        if is_upload_completed(bucket, obj2.key):
+                            if 'node1' in obj2.key:
+                                upload_completed_prefix_list_node1.append(obj2.key)
+                            if 'node2' in obj2.key:
+                                upload_completed_prefix_list_node2.append(obj2.key)
+        # 3 如果两个节点都上传完成则进行后续处理
+        for prefix_node1 in upload_completed_prefix_list_node1:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_node2 = prefix_node1.replace('node1', 'node2')
+            if prefix_node2 in upload_completed_prefix_list_node2:
+                # print(f'需要合并{prefix_node1}和{prefix_node2}')
+                # 获取要处理的包
+                oss_bags = []
+                local_bags = []
+                for obj in oss2.ObjectIterator(bucket, prefix=prefix_node1):
+                    if str(obj.key).endswith('.bag'):
+                        oss_bags.append(str(obj.key))
+                for obj in oss2.ObjectIterator(bucket, prefix=prefix_node2):
+                    if str(obj.key).endswith('.bag'):
+                        oss_bags.append(str(obj.key))
+                split_list = prefix_node1.replace(key2, key3).replace("node1_", "").split('/')
+                merged_prefix = '/'.join(split_list[0:-2]) + '/'
+                local_merged_dir = path1 + merged_prefix
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                parse_prefix = ('/'.join(split_list[0:-2]) + '/').replace(key3, key4)
+                local_parse_dir = path1 + parse_prefix
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_name = split_list[-2]
+                parse_prefix = parse_prefix + merged_bag_name + '/'
+                merged_bag_full_name = merged_bag_name + '.bag'
+                local_bag_dir = path1 + '/'.join(split_list[0:-1]) + '/'
+                if not os.path.exists(local_bag_dir):
+                    os.makedirs(local_bag_dir)
+                # 下载
+                for oss_bag in oss_bags:
+                    bag_name = str(oss_bag).split('/')[-1]
+                    local_bag_path = local_bag_dir + bag_name
+                    bucket.get_object_to_file(oss_bag, local_bag_path)
+                    local_bags.append(local_bag_path)
+                    local_delete_list.append(local_bag_path)
+                    oss_delete_list.append(oss_bag)
+                # 1 合并bag
+                all_bag_path, camera_bag_path, fusion_bag_path, plan_bag_path, control_bag_path = merge(local_bags,
+                                                                                                        merged_prefix,
+                                                                                                        local_merged_dir,
+                                                                                                        merged_bag_full_name)
+                local_delete_list = local_delete_list + [all_bag_path, camera_bag_path, fusion_bag_path, plan_bag_path,
+                                                         control_bag_path]
+                # 删除本地临时文件
+                if len(local_delete_list) > 0:
+                    for local_delete in local_delete_list:
+                        try:
+                            os.remove(local_delete)
+                        except Exception as e:
+                            print "删除本地临时文件: %s" % str(e)
+                            # print(f'删除本地临时文件{e}')
+
+                # 删除oss原始文件
+                if len(oss_delete_list) > 0:
+                    bucket.batch_delete_objects(oss_delete_list)
+        turn = turn + 1
+        time.sleep(sleep_time)

archive/python2-kinglong-module/kinglong_pcd.py

@@ -0,0 +1,97 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import pcdtovideo_jilong_overlook
+import pcdtovideo_jilong_forwardlook
+
+key1 = 'kinglong/'
+path1 = '/root/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        print '生成点云视频 %s' % merged_bag_file_path
+        local_pcd_dir_overlook = pcdtovideo_jilong_overlook.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_dir_forward = pcdtovideo_jilong_forwardlook.parse(merged_bag_file_path, local_parse_dir)
+        pcd_mp4_file_name1 = 'pcd_overlook'
+        pcd_mp4_file_name2 = 'pcd_forwardlook'
+        local_delete_list.append(local_pcd_dir_overlook + '/' + pcd_mp4_file_name1 + '.mp4')
+        local_delete_list.append(local_pcd_dir_forward + '/' + pcd_mp4_file_name2 + '.mp4')
+        oss_csv_object_key1 = parse_prefix + pcd_mp4_file_name1 + '.mp4'
+        oss_csv_object_key2 = parse_prefix + pcd_mp4_file_name2 + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_dir_overlook + '/' + pcd_mp4_file_name1 + '.mp4')
+        print '上传点云视频到 %s' % oss_csv_object_key1
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_dir_forward + '/' + pcd_mp4_file_name2 + '.mp4')
+        print '上传点云视频到 %s' % oss_csv_object_key2
+    except Exception as e:
+        print "生成点云视频报错: %s" % str(e)
+        # print(f'生成点云视频报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取合并后的包
+            merged_bag_object_key = str(obj1.key)
+            # print(f'判断1{merged_bag_object_key}')
+            if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                merged_bag_object_key_split = merged_bag_object_key.split('/')
+                merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                pcd1_done = False
+                pcd2_done = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                    if 'pcd_overlook.mp4' in str(obj2.key):
+                        pcd1_done = True
+                    if 'pcd_forwardlook.mp4' in str(obj2.key):
+                        pcd2_done = True
+                if pcd1_done and pcd2_done:
+                    continue
+                print '需要解析：%s' % merged_bag_object_key
+                # print(f'需要解析{merged_bag_object_key}')
+                local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_full_name = merged_bag_object_key_split[-1]
+                merged_bag_name = merged_bag_full_name.split('.')[0]
+                bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                local_delete_list.append(local_merged_bag_path)
+                # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                parse_to_pcd_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                    print "删除本地临时文件: %s" % local_delete
+                except Exception as e:
+                    print "删除本地临时文件报错: %s" % str(e)
+                    # print(f'删除本地临时文件报错{e}')
+
+        time.sleep(sleep_time)

archive/python2-kinglong-module/kinglong_simulation.py

@@ -0,0 +1,249 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import xml.etree.ElementTree as ET
+from rosbag import Bag, Compression
+import shutil
+import docker
+import bagtocsv_orig
+import bagtocsv_hmi
+import get_drive
+import parse_jinlong_image
+import pcdtovideo_jilong_overlook
+import pcdtovideo_jilong_forwardlook
+
+key1 = 'kinglong/'
+path1 = '/scenarios/'
+sleep_time = 5  # 每多少秒扫描一次
+
+
+def move_xosc_before_simulation(root_path1, root_path2):
+    try:
+
+        xodr1 = 'thq.xodr'
+        xodr2 = 'OpenDRIVE.xodr'
+        xodr3 = 'gelan.xodr'
+        osgb1 = 'thq.opt.osgb'
+        osgb2 = 'GJBM_20km_0822.opt.osgb'
+        osgb3 = 'gelan.opt.osgb'
+
+        tree1 = ET.parse(root_path1 + 'scenario_orig.xosc')
+        root1 = tree1.getroot()
+        for node0 in root1:
+            if node0.tag == 'RoadNetwork':
+                for node1 in node0:
+                    # 打印根元素的标签名
+                    src_file_prefix = '/root/rosmerge/resource/'
+                    if 'LogicFile' == node1.tag:
+                        if xodr1 in node1.get('filepath'):
+                            dst_file = root_path1 + xodr1
+                            shutil.copy(src_file_prefix + xodr1, dst_file)
+                            node1.set('filepath', dst_file)
+                        if xodr2 in node1.get('filepath'):
+                            dst_file = root_path1 + xodr2
+                            shutil.copy(src_file_prefix + xodr2, dst_file)
+                            node1.set('filepath', dst_file)
+                        if xodr3 in node1.get('filepath'):
+                            dst_file = root_path1 + xodr3
+                            shutil.copy(src_file_prefix + xodr3, dst_file)
+                            node1.set('filepath', dst_file)
+                    if 'SceneGraphFile' == node1.tag:
+                        if osgb1 in node1.get('filepath'):
+                            dst_file = root_path1 + osgb1
+                            shutil.copy(src_file_prefix + osgb1, dst_file)
+                            node1.set('filepath', dst_file)
+                        if osgb2 in node1.get('filepath'):
+                            dst_file = root_path1 + osgb2
+                            shutil.copy(src_file_prefix + osgb2, dst_file)
+                            node1.set('filepath', dst_file)
+                        if osgb3 in node1.get('filepath'):
+                            dst_file = root_path1 + osgb3
+                            shutil.copy(src_file_prefix + osgb3, dst_file)
+                            node1.set('filepath', dst_file)
+            if node0.tag == 'Entities':
+                for node1 in node0:
+                    if node1.get("name") == 'Ego':
+                        for node2 in node1:
+                            if node2.tag == 'Vehicle':
+                                node2.set('name', 'KingLong_snow white')
+        tree1.write(root_path1 + 'openx0.xosc')
+
+        tree2 = ET.parse(root_path2 + 'scenario_hmi.xosc')
+        root2 = tree2.getroot()
+        for node0 in root2:
+            if node0.tag == 'RoadNetwork':
+                for node1 in node0:
+                    # 打印根元素的标签名
+                    src_file_prefix = '/root/rosmerge/resource/'
+                    if 'LogicFile' == node1.tag:
+                        if xodr1 in node1.get('filepath'):
+                            dst_file = root_path2 + xodr1
+                            shutil.copy(src_file_prefix + xodr1, dst_file)
+                            node1.set('filepath', dst_file)
+                        if xodr2 in node1.get('filepath'):
+                            dst_file = root_path2 + xodr2
+                            shutil.copy(src_file_prefix + xodr2, dst_file)
+                            node1.set('filepath', dst_file)
+                        if xodr3 in node1.get('filepath'):
+                            dst_file = root_path2 + xodr3
+                            shutil.copy(src_file_prefix + xodr3, dst_file)
+                            node1.set('filepath', dst_file)
+                    if 'SceneGraphFile' == node1.tag:
+                        if osgb1 in node1.get('filepath'):
+                            dst_file = root_path2 + osgb1
+                            shutil.copy(src_file_prefix + osgb1, dst_file)
+                            node1.set('filepath', dst_file)
+                        if osgb2 in node1.get('filepath'):
+                            dst_file = root_path2 + osgb2
+                            shutil.copy(src_file_prefix + osgb2, dst_file)
+                            node1.set('filepath', dst_file)
+                        if osgb3 in node1.get('filepath'):
+                            dst_file = root_path2 + osgb3
+                            shutil.copy(src_file_prefix + osgb3, dst_file)
+                            node1.set('filepath', dst_file)
+            if node0.tag == 'Entities':
+                for node1 in node0:
+                    if node1.get("name") == 'Ego':
+                        for node2 in node1:
+                            if node2.tag == 'Vehicle':
+                                node2.set('name', 'KingLong_snow white')
+        tree2.write(root_path2 + 'openx0.xosc')
+
+    except Exception as e:
+        print "修改xosc报错: %s" % str(e)
+        # print(f'修改xosc报错：{e}')
+
+
+def delete_files_in_dir(dir_path):
+    # 遍历目录下的所有文件和子目录
+    for root, dirs, files in os.walk(dir_path):
+        for file in files:
+            file_path = os.path.join(root, file)
+            try:
+                os.remove(file_path)
+            except OSError as e:
+                print("删除文件时出错：", file_path, "-", e.strerror)
+            # 扫描目录上传mp4
+
+
+def upload_simulation(parse_prefix, mp41, mp42):
+    try:
+        bucket.put_object_from_file(parse_prefix + 'scenario_orig.mp4', mp41)
+        print '上传仿真视频到 %s' % parse_prefix + 'scenario_orig.mp4'
+        bucket.put_object_from_file(parse_prefix + 'scenario_hmi.mp4', mp42)
+        print '上传仿真视频到 %s' % parse_prefix + 'scenario_hmi.mp4'
+        shutil.rmtree(path1)
+    except Exception as e:
+        print "上传视频报错: %s" % str(e)
+        # print(f'上传视频报错{e}')
+
+
+def simulation(parse_prefix, mp41, mp42):
+    try:
+        os.system("docker start vtd")
+        # 实例化Docker客户端
+        client = docker.from_env()
+        while True:
+            time.sleep(5)
+            # 获取容器列表
+            containers = client.containers.list()
+            run = False
+            # 打印容器列表
+            for container in containers:
+                if 'vtd' == container.name:
+                    run = True
+                    break
+            if not run:
+                break
+        time.sleep(5)
+        upload_simulation(parse_prefix, mp41, mp42)
+    except Exception as e:
+        print "生成仿真视频报错: %s" % str(e)
+        # print(f'生成仿真视频报错{e}')
+
+
+def is_upload_completed(bucket, prefix):
+    target_number = str(prefix).split('_')[-1][:-1]
+    count = 0
+    for obj in oss2.ObjectIterator(bucket, prefix=prefix):
+        if obj.key != prefix:
+            count += 1
+    return int(count) == int(target_number)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        all_prefix_set = set()
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取csv
+            if 'data_parse' in str(obj1.key) and str(obj1.key).count('/') == 4:
+                all_prefix_set.add('/'.join(str(obj1.key).split('/')[:-1]) + '/')
+        for obj2_key in all_prefix_set:
+            xosc1_done = False
+            xosc2_done = False
+            mp41_done = False
+            mp42_done = False
+            for obj3 in oss2.ObjectIterator(bucket, prefix=obj2_key):
+                if '/scenario_orig.xosc' in str(obj3.key):
+                    xosc1_done = True
+                if '/scenario_hmi.xosc' in str(obj3.key):
+                    xosc2_done = True
+                if '/scenario_orig.mp4' in str(obj3.key):
+                    mp41_done = True
+                if '/scenario_hmi.mp4' in str(obj3.key):
+                    mp42_done = True
+            if not xosc1_done or not xosc2_done:
+                continue
+            if mp41_done and mp42_done:
+                continue
+
+            # print(f'需要生成xosc：{obj2_key}')
+            print "需要生成仿真视频: %s" % obj2_key
+            parse_prefix_full = obj2_key
+            local_dir_full = path1 + parse_prefix_full
+            if not os.path.exists(local_dir_full):
+                os.makedirs(local_dir_full)
+            # 下载两个csv
+            root_path1 = local_dir_full + 'orig/'
+            root_path2 = local_dir_full + 'hmi/'
+            if not os.path.exists(root_path1):
+                os.makedirs(root_path1)
+            if not os.path.exists(root_path2):
+                os.makedirs(root_path2)
+
+            bucket.get_object_to_file(parse_prefix_full + 'scenario_orig.xosc', root_path1 + 'scenario_orig.xosc')
+            bucket.get_object_to_file(parse_prefix_full + 'scenario_hmi.xosc', root_path2 + 'scenario_hmi.xosc')
+            local_delete_list.append(root_path1 + 'scenario_orig.xosc')
+            local_delete_list.append(root_path2 + 'scenario_hmi.xosc')
+            move_xosc_before_simulation(root_path1, root_path2)
+            simulation(parse_prefix_full, root_path1 + 'simulation.mp4', root_path2 + 'simulation.mp4')
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "删除本地临时文件报错: %s" % str(e)
+                    # print(f'删除本地临时文件报错{e}')
+
+        time.sleep(sleep_time)

archive/python2-kinglong-module/kinglong_xosc.py

@@ -0,0 +1,109 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import xml.etree.ElementTree as ET
+from rosbag import Bag, Compression
+import shutil
+import docker
+import bagtocsv_orig
+import bagtocsv_hmi
+import get_drive
+import parse_jinlong_image
+import pcdtovideo_jilong_overlook
+import pcdtovideo_jilong_forwardlook
+
+key1 = 'kinglong/'
+path1 = '/root/'
+sleep_time = 5  # 每多少秒扫描一次
+
+
+
+def generate_xosc(parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        # 切换到指定目录
+        os.chdir('/root/rosmerge/python3/')
+
+        # 使用subprocess.run()执行命令，注意输入的目录不以斜杠结尾
+        os.system('python3 simulation_new.py ' + local_parse_dir[:-1])
+
+        # 输出命令执行结果
+        local_xosc_path1 = local_parse_dir + 'simulation_orig/xosc/openx0.xosc'
+        local_xosc_path2 = local_parse_dir + 'simulation_hmi/xosc/openx0.xosc'
+        bucket.put_object_from_file(parse_prefix + 'scenario_orig.xosc', local_xosc_path1)
+        bucket.put_object_from_file(parse_prefix + 'scenario_hmi.xosc', local_xosc_path2)
+        local_delete_list.append(local_xosc_path1)
+        local_delete_list.append(local_xosc_path2)
+        return local_xosc_path1, local_xosc_path2
+    except Exception as e:
+        print "生成xosc报错: %s" % str(e)
+        # print(f'生成xosc报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        all_prefix_set = set()
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取csv
+            if 'data_parse' in str(obj1.key) and str(obj1.key).count('/') == 4:
+                all_prefix_set.add('/'.join(str(obj1.key).split('/')[:-1])+'/')
+        for obj2_key in all_prefix_set:
+            xosc1_done = False
+            xosc2_done = False
+            csv1_done = False
+            csv2_done = False
+            for obj3 in oss2.ObjectIterator(bucket, prefix=obj2_key):
+                if '/scenario_orig.xosc' in str(obj3.key):
+                    xosc1_done = True
+                if '/scenario_hmi.xosc' in str(obj3.key):
+                    xosc2_done = True
+                if '/pos_orig.csv' in str(obj3.key):
+                    csv1_done = True
+                if '/pos_hmi.csv' in str(obj3.key):
+                    csv2_done = True
+            if xosc1_done and xosc2_done:
+                continue
+            if not csv1_done and not csv2_done:
+                continue
+            # print(f'需要生成xosc：{obj2_key}')
+            print "需要生成xosc: %s" % obj2_key
+            parse_prefix_full = obj2_key
+            local_dir_full = path1 + parse_prefix_full
+            if not os.path.exists(local_dir_full):
+                os.makedirs(local_dir_full)
+            # 下载两个csv
+            bucket.get_object_to_file(parse_prefix_full+'pos_orig.csv', local_dir_full+'pos_orig.csv')
+            bucket.get_object_to_file(parse_prefix_full+'pos_hmi.csv', local_dir_full+'pos_hmi.csv')
+            local_delete_list.append(local_dir_full+'pos_orig.csv')
+            local_delete_list.append(local_dir_full+'pos_orig.csv')
+            generate_xosc(parse_prefix_full, local_dir_full, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "删除本地临时文件报错: %s" % str(e)
+                    # print(f'删除本地临时文件报错{e}')
+
+
+        time.sleep(sleep_time)

archive/python2-kinglong-module/parse_jinlong_image.py

@@ -0,0 +1,102 @@
+# -*- coding: utf-8 -*-
+
+import sys
+
+import os
+import rospy
+import rosbag
+import csv
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+import argparse
+import struct
+import subprocess
+from subprocess import Popen, PIPE
+
+bridge = CvBridge()
+
+
+def parsebag(f, output_dir, target_topic):
+    rosbag_name = f[f.rindex("/"):-4]
+    output_path = output_dir + rosbag_name
+
+    with rosbag.Bag(f, 'r') as bag:
+        count = 0
+        for key, val in bag.get_type_and_topic_info()[1].items():
+            if val[0] == 'sensor_msgs/Image':
+
+                for topic, msg, t in bag.read_messages(key):
+                    if topic == target_topic:
+                        img = bridge.imgmsg_to_cv2(msg, 'bgr8')
+                        # img = bridge.compressed_imgmsg_to_cv2(msg, 'bgr8')
+                        timestr = msg.header.stamp.to_nsec()
+                        image_name = str(timestr) + ".jpg"
+                        if not os.path.exists(output_path + '_' + 'image'):
+                            os.makedirs(output_path + '_' + 'image')
+                        output_path_img = os.path.join(output_path + '_' + 'image', image_name)
+                        cv2.imwrite(output_path_img, img)
+                        # print(count)
+                        count = count + 1
+    return count
+
+
+def main():
+    input_dir = sys.argv[1]
+    # input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+    output_dir = sys.argv[2]
+    # output_dir = '/media/dell/新加卷/样例及代码/金龙车/样例'
+    topic = '/camera_image'  # /camera/color/image_raw
+
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    # print(dirt)
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+
+
+if __name__ == '__main__':
+    main()
+
+def parse(input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    # input_dir = '/media/dell/BFAC-F22B/rapid_accel_2023-11-15-10-33-50.bag'
+    output_dir = output_mp4_dir
+    # output_dir = '/media/dell/新加卷/样例及代码/金龙车/样例'
+    topic = '/camera_image'  # /camera/color/image_raw
+
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    # print(dirt)
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+    return dirt

archive/python2-kinglong-module/pcdtovideo_jilong_forwardlook.py

@@ -0,0 +1,286 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+
+def draw_points(pic, filename):
+    f = open(filename, "r")
+    ff = f.readlines()[11:]
+
+    for i in range(0, len(ff)):
+        point = ff[i].split()[:4]
+        point_x = float(point[0])
+        point_y = -float(point[1])
+
+        if math.isnan(point_x):
+            pass
+        else:
+            cv2.circle(pic, (int(200 - point_x * 10), int(100 - point_y * 10)), 1, (250, 250, 250), 2)
+
+
+def rotx(t):
+    """Rotation about the x-axis."""
+    c = np.cos(t)
+    s = np.sin(t)
+    return np.array([[1, 0, 0],
+                     [0, c, -s],
+                     [0, s, c]])
+
+
+def roty(t):
+    """Rotation about the y-axis."""
+    c = np.cos(t)
+    s = np.sin(t)
+    return np.array([[c, 0, s],
+                     [0, 1, 0],
+                     [-s, 0, c]])
+
+
+def rotz(t):
+    """Rotation about the z-axis."""
+    c = np.cos(t)
+    s = np.sin(t)
+    return np.array([[c, -s, 0],
+                     [s, c, 0],
+                     [0, 0, 1]])
+
+
+def transform_from_rot_trans(R, t):
+    """Transforation matrix from rotation matrix and translation vector."""
+    R = R.reshape(3, 3)
+    t = t.reshape(3, 1)
+    return np.vstack((np.hstack([R, t]), [0, 0, 0, 1]))
+
+
+def view(rx, ry, rz, tx, ty, tz):
+    mx = rotx(rx)
+    my = roty(ry)
+    mz = rotz(rz)
+    rotation = np.dot(mz, np.dot(my, mx))
+    translation = np.array([tx, ty, tz])
+    return transform_from_rot_trans(rotation, translation)
+
+
+# if __name__ == '__main__':
+#     input_dir = sys.argv[1]
+#     # input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+#     output_dir = sys.argv[2]
+#     # output_dir = '/media/dell/新加卷/样例及代码/金龙车/样例'
+#     a = view(0, 30, 0, -10, 0, 5)
+#     colormap = np.array([[128, 130, 120],
+#                          [235, 0, 205],
+#                          [0, 215, 0],
+#                          [235, 155, 0]]) / 255.0
+
+#     bag_name = input_dir.split('/')[-1].split('.')[0]
+#     output_dir = os.path.join(output_dir, bag_name + '_pcd_forwardlook' + '/pcd')
+#     if not os.path.exists(output_dir):
+#         os.makedirs(output_dir)
+
+#     with rosbag.Bag(input_dir, 'r') as bag:
+#         num_count = 0
+#         for topic, msg, t in bag.read_messages():
+#             if topic == "/points_concat":  # /camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+#                 num_count += 1
+
+#     bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+#     hz = str(float(num_count) / bagtime)
+
+#     #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+#     command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/points_concat'] + [output_dir]
+#     command = ' '.join(command)
+#     os.system(command)
+#     file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+#     file2 = os.path.join(output_dir[0:-4], 'jpg')
+#     if not os.path.exists(file1):
+#         os.makedirs(file1)
+#     if not os.path.exists(file2):
+#         os.makedirs(file2)
+
+#     #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+#     for root, dirs, files in os.walk(output_dir[0:-4]):
+
+#         # find .pcd files and do the transfer twice
+#         for file in files:
+#             if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+#                 inputFilePath = root + "/" + file
+#                 tempFilePath = root[:-3] + "pcd_ascii/" + file
+#                 outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+#                 # transfer pcd_utf-8 to pcd_ascii
+#                 command = "pcl_convert_pcd_ascii_binary " + \
+#                           inputFilePath + \
+#                           " " + \
+#                           tempFilePath + \
+#                           " 0"
+#                 # print(command)
+#                 os.system(command)
+
+#                 # make sure the temp file exist, invalid input file may cause this issue
+#                 if not os.path.exists(tempFilePath):
+#                     continue
+
+#                 # transfer pcd_ascii to jpg
+#                 # pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+#                 # draw_points(pic, tempFilePath)
+#                 # cv2.imwrite(outputFilePath, pic)
+#                 # print("jpg generated: ", outputFilePath) 
+#                 # pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+#                 pic = np.zeros([800, 1600, 3])
+#                 f = open(tempFilePath, "r")
+#                 ff = f.readlines()[11:]
+
+#                 for i in range(0, len(ff)):
+#                     point = ff[i].split()[:4]
+#                     point_x = float(point[0])
+#                     point_y = float(point[1])
+#                     point_z = float(point[2])
+#                     points_intensity = float(point[2])
+#                     t = np.dot(np.linalg.inv(a), np.array([point_x, point_y, point_z, 1]))
+#                     x = t[0]
+#                     y = t[1]
+
+#                     if math.isnan(point_x):
+#                         pass
+#                     else:
+#                         cv2.circle(pic, (int(800 - y * 40), int(400 - x * 40)), 0,
+#                                    colormap[int(points_intensity) % colormap.shape[0]] * 255, 0)
+
+#                 cv2.imwrite(outputFilePath, pic)
+#             else:
+#                 break
+
+#     #######################将转化的点云jpg合成视频#######################
+#     jpg_list = os.listdir(file2)
+#     if not jpg_list == []:
+#         command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+#                                                                                                            'avc1',
+#                                                                                                            '-y'] + [
+#                       'pcd_forwardlook.mp4']
+#         result_string = " ".join(command)
+#         p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+#         p.wait()
+#     shutil.rmtree(file1)
+#     shutil.rmtree(file2)
+#     shutil.rmtree(output_dir)
+
+
+def parse(input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    # input_dir='/media/dell/BFAC-F22B/bizhang_2023-11-15-10-35-21.bag'
+    output_dir = output_mp4_dir
+    # output_dir='/media/dell/BFAC-F22B'
+    # output_dir = '/media/dell/新加卷/样例及代码/金龙车/样例'
+    a = view(0, 30, 0, -10, 0, 5)
+    colormap = np.array([[128, 130, 120],
+                         [235, 0, 205],
+                         [0, 215, 0],
+                         [235, 155, 0]]) / 255.0
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_forwardlook' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/points_concat":  # /camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count) / bagtime)
+
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/points_concat'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                # pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+                # draw_points(pic, tempFilePath)
+                # cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+                # pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+                pic = np.zeros([800, 1600, 3])
+                f = open(tempFilePath, "r")
+                ff = f.readlines()[11:]
+
+                for i in range(0, len(ff)):
+                    point = ff[i].split()[:4]
+                    point_x = float(point[0])
+                    point_y = float(point[1])
+                    point_z = float(point[2])
+                    points_intensity = float(point[2])
+                    t = np.dot(np.linalg.inv(a), np.array([point_x, point_y, point_z, 1]))
+                    x = t[0]
+                    y = t[1]
+
+                    if math.isnan(point_x):
+                        pass
+                    else:
+                        cv2.circle(pic, (int(800 - y * 40), int(400 - x * 40)), 0,
+                                   colormap[int(points_intensity) % colormap.shape[0]] * 255, 0)
+
+                cv2.imwrite(outputFilePath, pic)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_forwardlook.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

archive/python2-kinglong-module/pcdtovideo_jilong_overlook.py

@@ -0,0 +1,202 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+
+def draw_points(pic, filename):
+    colormap = np.array([[128, 130, 120],
+                         [235, 0, 205],
+                         [0, 215, 0],
+                         [235, 155, 0]]) / 255.0
+    f = open(filename, "r")
+    ff = f.readlines()[11:]
+
+    for i in range(0, len(ff)):
+        point = ff[i].split()[:4]
+        point_x = float(point[0])
+        point_y = -float(point[1])
+        point_z = float(point[2])
+        points_intensity = float(point[2])
+        if math.isnan(point_x):
+            pass
+        else:
+            cv2.circle(pic, (int(800 - point_x * 10), int(400 - point_y * 10)), 0,
+                       colormap[int(points_intensity) % colormap.shape[0]] * 255, 2)
+
+
+# if __name__ == '__main__':
+#     input_dir = sys.argv[1]
+#     # input_dir='/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116/jinlong_data_merge_2023-12-13-05-59-34_TTC_7.bag'
+#     output_dir = sys.argv[2]
+#     # output_dir = '/media/dell/BFAC-F22B/data/jinlong_datareturn/test_1116'
+#
+#     bag_name = input_dir.split('/')[-1].split('.')[0]
+#     output_dir = os.path.join(output_dir, bag_name + '_pcd_overlook' + '/pcd')
+#     if not os.path.exists(output_dir):
+#         os.makedirs(output_dir)
+#
+#     with rosbag.Bag(input_dir, 'r') as bag:
+#         num_count = 0
+#         for topic, msg, t in bag.read_messages():
+#             if topic == "/points_concat":  # /camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+#                 num_count += 1
+#
+#     bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+#     hz = str(float(num_count / bagtime))
+#     print(hz)
+#
+#     #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+#     command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/points_concat'] + [output_dir]
+#     command = ' '.join(command)
+#     os.system(command)
+#     file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+#     file2 = os.path.join(output_dir[0:-4], 'jpg')
+#     if not os.path.exists(file1):
+#         os.makedirs(file1)
+#     if not os.path.exists(file2):
+#         os.makedirs(file2)
+#
+#     #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+#     for root, dirs, files in os.walk(output_dir[0:-4]):
+#
+#         # find .pcd files and do the transfer twice
+#         for file in files:
+#             if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+#
+#                 inputFilePath = root + "/" + file
+#                 tempFilePath = root[:-3] + "pcd_ascii/" + file
+#                 outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+#
+#                 # transfer pcd_utf-8 to pcd_ascii
+#                 command = "pcl_convert_pcd_ascii_binary " + \
+#                           inputFilePath + \
+#                           " " + \
+#                           tempFilePath + \
+#                           " 0"
+#                 # print(command)
+#                 os.system(command)
+#
+#                 # make sure the temp file exist, invalid input file may cause this issue
+#                 if not os.path.exists(tempFilePath):
+#                     continue
+#
+#                 # transfer pcd_ascii to jpg
+#                 pic = np.zeros([800, 1600, 3])  # pic = np.zeros([800, 1600, 3])
+#                 draw_points(pic, tempFilePath)
+#                 cv2.imwrite(outputFilePath, pic)
+#                 # print("jpg generated: ", outputFilePath)
+#             else:
+#                 break
+#
+#     #######################将转化的点云jpg合成视频#######################
+#     jpg_list = os.listdir(file2)
+#     if not jpg_list == []:
+#         # command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+#         #                                                                                                    'avc1',
+#         #                                                                                                    '-y'] + [
+#         #               'pcd_overlook.mp4']
+#         command = ['ffmpeg', '-f', 'image2', '-t', bagtime, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + [
+#             '-tag:v', 'avc1', '-y'] + ['pcd_overlook.mp4']
+#         result_string = " ".join(command)
+#         p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+#         p.wait()
+#     shutil.rmtree(file1)
+#     shutil.rmtree(file2)
+#     shutil.rmtree(output_dir)
+
+
+def parse(input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    # input_dir='/media/dell/BFAC-F22B/bizhang_2023-11-15-10-35-21.bag'
+    output_dir = output_mp4_dir
+    # output_dir='/media/dell/BFAC-F22B'
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_overlook' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/points_concat":  # /camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    # hz = str(float(num_count / bagtime))
+    hz = str(float(num_count) / bagtime)
+
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/points_concat'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                pic = np.zeros([800, 1600, 3])  # pic = np.zeros([800, 1600, 3])
+                draw_points(pic, tempFilePath)
+                cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_overlook.mp4']
+
+        # command = ['ffmpeg', '-f', 'image2', '-t', bagtime, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + [
+        #     '-tag:v', 'avc1', '-y'] + ['pcd_overlook.mp4']
+        result_string = " ".join(command)
+        print '执行视频生成命令：%s' % result_string
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

archive/python2-kinglong-module/resource/get_drive_jinlong.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Dec 25 17:35:56 2023
+
+@author: dell
+"""
+
+# coding: utf-8
+#!/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math 
+
+import sys
+import time
+
+
+def parsebag(input_dir, output_dir):   
+    
+
+    dic_object_detection = ['Time','Strg_Angle','Accel_Pos','BrkPel_Pos','Real_Speed','latitude','longitude']
+
+    object_detection_file = open(output_dir + "/"+"drive.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+    frame_max=sys.maxsize
+    count_data_read=1
+    count_cicv_location=1
+    with rosbag.Bag(input_dir ,'r') as bag:
+      latitude=0
+      longitude=0
+      speed=0
+      Strg_Angle_Real_Value=0
+      VCU_Accel_Pos_Value=0
+      VCU_BrkPel_Pos_Value=0
+      for topic,msg,t in bag.read_messages():    #t代表时间
+            #print(topic)
+            #print('-------------------------------------------------')
+            if topic == "/cicv_location": #/pji_gps #/cicv_location
+                count_cicv_location+=1
+                latitude=msg.latitude
+                longitude=msg.longitude
+                speed=pow(pow(msg.velocity_x,2)+pow(msg.velocity_y,2),0.5)*3.6
+                if count_cicv_location%10==0:
+                    message_location=[str(t)[:-6],Strg_Angle_Real_Value,VCU_Accel_Pos_Value,VCU_BrkPel_Pos_Value,speed,latitude,longitude]
+                    writer_object_detection.writerow(message_location)
+             
+            if topic == "/data_read": # 10hz
+                Strg_Angle_Real_Value=msg.Strg_Angle_Real_Value
+                VCU_Accel_Pos_Value=msg.VCU_Accel_Pos_Value
+                VCU_BrkPel_Pos_Value=msg.VCU_BrkPel_Pos_Value
+                count_data_read+=1
+                if count_data_read%10==0:
+                    message_data =[str(t)[:-6],msg.Strg_Angle_Real_Value,msg.VCU_Accel_Pos_Value,msg.VCU_BrkPel_Pos_Value,speed,latitude,longitude]
+                 
+                    writer_object_detection.writerow(message_data)
+
+    object_detection_file.close()
+if __name__ == "__main__":
+#    print("Input the path of file...."+'\n')
+
+   input_dir = sys.argv[1]
+   #input_dir='/media/dell/56FAD34BFAD32651/data/jinlong_datareturn/test_1116/data_merge_2023-11-21-14-17-19_brake_12.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   output_dir = sys.argv[2]
+   #output_dir='/media/dell/56FAD34BFAD32651/data/jinlong_datareturn/test_1116/'
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   parsebag(input_dir, output_dir)
+   '''
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+   except Exception as e:
+       print(e)
+   '''
+   #msg.Strg_Angle_Real_Value,msg.VCU_Accel_Pos_Value,msg.VCU_BrkPel_Pos_Value

archive/python2-kinglong-module/test/callback.py

@@ -0,0 +1,159 @@
+# -*- coding: utf-8 -*-
+
+
+# 造数据
+
+
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+
+key1 = 'kinglong/'
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'open-bucket'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    count = 1
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        upload_completed_prefix_list = []
+        # 4 获取即将被合并的bag目录
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            if 'callback.json' in str(obj1.key):
+                prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                pos_orig_csv = False
+                pos_hmi_csv = False
+                drive_csv = False
+                camera_mp4 = False
+                pcd_forwardlook_mp4 = False
+                pcd_overlook_mp4 = False
+                scenario_orig_xosc = False
+                scenario_hmi_xosc = False
+                scenario_orig_mp4 = False
+                scenario_hmi_mp4 = False
+                camera_bag = False
+                fusion_bag = False
+                plan_bag = False
+                control_bag = False
+                print '检测是否文件完整：', prefix
+                for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if 'pos_orig.csv' in str(obj2.key):
+                        pos_orig_csv = True
+                    if 'pos_hmi.csv' in str(obj2.key):
+                        pos_hmi_csv = True
+                    if 'drive.csv' in str(obj2.key):
+                        drive_csv = True
+                    if 'camera.mp4' in str(obj2.key):
+                        camera_mp4 = True
+                    if 'pcd_forwardlook.mp4' in str(obj2.key):
+                        pcd_forwardlook_mp4 = True
+                    if 'pcd_overlook.mp4' in str(obj2.key):
+                        pcd_overlook_mp4 = True
+                    if 'scenario_orig.xosc' in str(obj2.key):
+                        scenario_orig_xosc = True
+                    if 'scenario_hmi.xosc' in str(obj2.key):
+                        scenario_hmi_xosc = True
+                    if 'scenario_orig.mp4' in str(obj2.key):
+                        scenario_orig_mp4 = True
+                    if 'scenario_hmi.mp4' in str(obj2.key):
+                        scenario_hmi_mp4 = True
+                    if 'camera.bag' in str(obj2.key):
+                        camera_bag = True
+                    if 'fusion.bag' in str(obj2.key):
+                        fusion_bag = True
+                    if 'plan.bag' in str(obj2.key):
+                        plan_bag = True
+                    if 'control.bag' in str(obj2.key):
+                        control_bag = True
+                if not pos_orig_csv or not pos_hmi_csv or not drive_csv or not camera_mp4 or not pcd_forwardlook_mp4 or not pcd_overlook_mp4 or not scenario_orig_xosc or not scenario_hmi_xosc or not scenario_orig_mp4 or not scenario_hmi_mp4:
+                    continue
+                time.sleep(2)
+                print '发送：', str(obj1.key)
+                # 1 获取json内容
+                json_content = bucket.get_object(str(obj1.key)).read()
+                # 2 获取token
+                json_object = json.loads(json_content)
+                data1 = {
+                    "equipmentNo": json_object['equipmentNo'],
+                    "secretKey": json_object['secretKey']
+                }
+                json_data1 = json.dumps(data1)
+                request1 = urllib2.Request("http://139.9.199.227:30991/device/auth", json_data1,
+                                           headers={'Content-Type': 'application/json'})
+                response1 = urllib2.urlopen(request1)
+                result_json1 = response1.read()
+                result_object1 = json.loads(result_json1)
+                access_token = result_object1.get('data').get('accessToken')
+                try:
+                    print 'bag文件为：', json_object['rosBagPath']
+                    old_date = json_object['dataName']
+                    data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                    equipment_no = json_object['equipmentNo']
+                    old_file_path = json_object['filePath']
+                    old_ros_bag_path = json_object['rosBagPath']
+                    task_id = json_object['taskId']
+                    trigger_id = json_object['triggerId']
+                except Exception as e:
+                    print 'callback报错：%s' % str(e)
+                    continue
+                # 将时区统一
+                new_date = add_hour(old_date, 8)
+                old_delete_list = []
+                for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                    old_delete_list.append(str(obj_old.key))
+                    if 'callback.json' in str(obj_old.key):
+                        bucket.copy_object(bucket_name, str(obj_old.key),
+                                           str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                'callback_done.json'))
+                    else:
+                        bucket.copy_object(bucket_name, str(obj_old.key), str(obj_old.key).replace(old_date, new_date))
+                bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                bucket.delete_object(old_ros_bag_path)
+                bucket.batch_delete_objects(old_delete_list)
+
+                # triggerId = json_object['triggerId']
+                data2 = {
+                    "dataName": new_date,
+                    "dataSize": data_size,
+                    "equipmentNo": equipment_no,
+                    "filePath": old_file_path.replace(old_date, new_date),
+                    "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                    "taskId": task_id,
+                    "triggerId": ["1744180835122155522", "1744178775815360514"]
+                }
+                json_data2 = json.dumps(data2)
+                request2 = urllib2.Request("http://139.9.199.227:30991/device/data/callback", json_data2,
+                                           headers={'Content-Type': 'application/json',
+                                                    'authorization': access_token})
+
+                response2 = urllib2.urlopen(request2)
+                result_json2 = response2.read()
+                result_object2 = json.loads(result_json2)
+        time.sleep(3)

archive/python2-pjibot-single-camera-module/pjibot_callback.py

@@ -0,0 +1,128 @@
+# -*- coding: utf-8 -*-
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+
+key1 = 'pji/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+path1 = '/root/'
+path2 = 'data/'
+path3 = 'data_merge/'
+path4 = 'data_parse/'
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'open-bucket'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        upload_completed_prefix_list = []
+        # 4 获取即将被合并的bag目录
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            if 'callback.json' in str(obj1.key):
+                prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                camera_mp4 = False
+                pcd_depthcamera_mp4 = False
+                pcd_lidar_mp4 = False
+                # print '检测是否文件完整：', prefix
+                for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if '/camera.mp4' in str(obj2.key):
+                        camera_mp4 = True
+                    if '/pcd_depthcamera.mp4' in str(obj2.key):
+                        pcd_depthcamera_mp4 = True
+                    if '/pcd_lidar.mp4' in str(obj2.key):
+                        pcd_lidar_mp4 = True
+                if not camera_mp4 or not pcd_depthcamera_mp4 or not pcd_lidar_mp4:
+                    continue
+                time.sleep(1)
+                print '发送：', str(obj1.key)
+                # 1 获取json内容
+                json_content = bucket.get_object(str(obj1.key)).read()
+                # 2 获取token
+                json_object = json.loads(json_content)
+                data1 = {
+                    "equipmentNo": json_object['equipmentNo'],
+                    "secretKey": json_object['secretKey']
+                }
+                json_data1 = json.dumps(data1)
+                request1 = urllib2.Request("http://139.9.199.227:30991/device/auth", json_data1,
+                                           headers={'Content-Type': 'application/json'})
+                response1 = urllib2.urlopen(request1)
+                result_json1 = response1.read()
+                result_object1 = json.loads(result_json1)
+                access_token = result_object1.get('data').get('accessToken')
+                # 要发送的JSON参数
+                try:
+                    print 'bag文件为：', json_object['rosBagPath']
+                    old_date = json_object['dataName']
+                    data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                    equipment_no = json_object['equipmentNo']
+                    old_file_path = json_object['filePath']
+                    old_ros_bag_path = json_object['rosBagPath']
+                    task_id = json_object['taskId']
+                    trigger_id = json_object['triggerId']
+                except Exception as e:
+                    print 'callback报错：%s' % str(e)
+                    continue
+
+                # 将时区统一
+                new_date = add_hour(old_date, 8)
+                old_delete_list = []
+                for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                    old_delete_list.append(str(obj_old.key))
+                    if 'callback.json' in str(obj_old.key):
+                        bucket.copy_object(bucket_name, str(obj_old.key),
+                                           str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                'callback_done.json'))
+                    else:
+                        bucket.copy_object(bucket_name, str(obj_old.key), str(obj_old.key).replace(old_date, new_date))
+                bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                bucket.delete_object(old_ros_bag_path)
+                bucket.batch_delete_objects(old_delete_list)
+
+                data2 = {
+                    "dataName": new_date,
+                    "dataSize": data_size,
+                    "equipmentNo": equipment_no,
+                    "filePath": old_file_path.replace(old_date, new_date),
+                    "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                    "taskId": task_id,
+                    "triggerId": trigger_id
+                }
+                json_data2 = json.dumps(data2)
+                request2 = urllib2.Request("http://139.9.199.227:30991/device/data/callback", json_data2,
+                                           headers={'Content-Type': 'application/json',
+                                                    'authorization': access_token})
+
+                response2 = urllib2.urlopen(request2)
+                result_json2 = response2.read()
+                result_object2 = json.loads(result_json2)
+        time.sleep(2)

archive/python2-pjibot-single-camera-module/pjibot_camera.py

@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+import parse_pji_image
+
+key1 = 'pji/'
+path1 = '/root/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_mp4(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        local_mp4_dir = parse_pji_image.parse(merged_bag_file_path, local_parse_dir)
+        mp4_file_name = 'camera'
+        local_mp4_file_path = local_mp4_dir + '/' + mp4_file_name + '.mp4'
+        local_delete_list.append(local_mp4_file_path)
+        oss_csv_object_key = parse_prefix + mp4_file_name + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key, local_mp4_file_path)
+    except Exception, e:
+        # 当出现异常时执行的代码
+        print "捕获到一个异常: %s" % str(e)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取合并后的包
+            merged_bag_object_key = str(obj1.key)
+            # print(f'判断1{merged_bag_object_key}')
+            if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                merged_bag_object_key_split = merged_bag_object_key.split('/')
+                merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                camera_done = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                    if '/camera.mp4' in str(obj2.key):
+                        print '%s 存在摄像头视频。' % str(obj2.key)
+                        camera_done = True
+                if camera_done:
+                    print '%s 存在摄像头视频。' % parse_prefix_full
+                    continue
+                print '%s 不存在摄像头视频：' % parse_prefix_full
+                # print(f'需要解析{merged_bag_object_key}')
+                local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_full_name = merged_bag_object_key_split[-1]
+                merged_bag_name = merged_bag_full_name.split('.')[0]
+                try:
+                    bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                except Exception as e:
+                    print "下载合并后的bag包失败: %s" % str(e)
+                    # print(f'删除本地临时文件{e}')
+
+                local_delete_list.append(local_merged_bag_path)
+                # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                print '生成视频：%s' % str(obj1.key)
+                parse_to_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "捕获到一个异常: %s" % str(e)
+                    # print(f'删除本地临时文件{e}')
+        time.sleep(sleep_time)

archive/python2-pjibot-single-camera-module/pjibot_merge.py

@@ -0,0 +1,120 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from rosbag import Bag, Compression
+
+key1 = 'pji/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+path1 = '/root/'
+sleep_time = 5  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+
+
+def merge(local_bags, merged_prefix, local_merged_dir, merged_bag_name):
+    try:
+        output_bag_file = local_merged_dir + merged_bag_name
+        with Bag(output_bag_file, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        bucket.put_object_from_file(merged_prefix + merged_bag_name, output_bag_file)
+        return output_bag_file
+    except Exception as e:
+        print "bag包合并报错: %s" % str(e)
+        # print(f'bag包合并报错{e}')
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取未合并的bag包，合并 -------
+if __name__ == '__main__':
+
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    turn = 1
+    while True:
+        # print(f'当前轮次{turn}扫描开始。')
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        upload_completed_prefix_list = []
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1, delimiter='/'):
+            bag_list = []
+            target_path = ''
+            if str(obj1.key).count('/') == 2:  # pujin/robot-01/
+                # 6 校验bag包个数
+                for obj2 in oss2.ObjectIterator(bucket, prefix=str(obj1.key) + key2, delimiter='/'):
+                    if str(obj2.key).count('/') == 4:  # pujin/robot-01/data/2023-12-20-02-16-56_obstacledetection_10/
+                        bag_need = str(obj2.key).split('_')[-1][:-1]
+                        count_bag = 0
+                        for obj3 in oss2.ObjectIterator(bucket, prefix=str(obj2.key)):
+                            if obj3.key[-3:] == 'bag':
+                                count_bag = count_bag + 1
+                        if bag_need == str(count_bag):
+                            upload_completed_prefix_list.append(obj2.key)
+        # 处理
+        for prefix in upload_completed_prefix_list:
+            local_delete_list = []
+            oss_delete_list = []
+            # 获取要处理的包
+            oss_bags = []
+            local_bags = []
+            for obj in oss2.ObjectIterator(bucket, prefix=prefix):
+                if str(obj.key).endswith('.bag'):
+                    oss_bags.append(str(obj.key))
+            split_list = prefix.replace(key2, key3).split('/')
+            merged_prefix = '/'.join(split_list[0:-2]) + '/'
+            local_merged_dir = path1 + merged_prefix
+            print '合并文件上传key前缀为：', merged_prefix
+            if not os.path.exists(local_merged_dir):
+                os.makedirs(local_merged_dir)
+            parse_prefix = ('/'.join(split_list[0:-2]) + '/').replace(key3, key4)
+            local_parse_dir = path1 + parse_prefix
+            print '解析文件上传key前缀为：', parse_prefix
+            if not os.path.exists(local_parse_dir):
+                os.makedirs(local_parse_dir)
+            merged_bag_name = split_list[-2]
+            parse_prefix = parse_prefix + merged_bag_name + '/'
+            merged_bag_full_name = merged_bag_name + '.bag'
+            local_bag_dir = path1 + '/'.join(split_list[0:-1]) + '/'
+            if not os.path.exists(local_bag_dir):
+                os.makedirs(local_bag_dir)
+            # 下载
+            for oss_bag in oss_bags:
+                bag_name = str(oss_bag).split('/')[-1]
+                local_bag_path = local_bag_dir + bag_name
+                bucket.get_object_to_file(oss_bag, local_bag_path)
+                local_bags.append(local_bag_path)
+                local_delete_list.append(local_bag_path)
+                oss_delete_list.append(oss_bag)
+
+            # 1 合并bag
+            merged_bag_file_path = merge(local_bags, merged_prefix, local_merged_dir, merged_bag_full_name)
+            local_delete_list.append(merged_bag_file_path)
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        print "删除本地临时文件: %s" % str(e)
+                        # print(f'删除本地临时文件{e}')
+
+            # 删除oss原始文件
+            if len(oss_delete_list) > 0:
+                bucket.batch_delete_objects(oss_delete_list)
+
+        turn = turn + 1
+        time.sleep(sleep_time)

archive/python2-pjibot-single-camera-module/pjibot_pcd.py

@@ -0,0 +1,95 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import pcdtovideo_pji_deepcamera
+import pcdtovideo_pji_lidar
+
+key1 = 'pji/'
+path1 = '/root/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        local_pcd_mp4_dir1 = pcdtovideo_pji_deepcamera.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_mp4_dir2 = pcdtovideo_pji_lidar.parse(merged_bag_file_path, local_parse_dir)
+        pcd_mp4_file_name1 = 'pcd_depthcamera'
+        pcd_mp4_file_name2 = 'pcd_lidar'
+        local_delete_list.append(local_pcd_mp4_dir1 + '/' + pcd_mp4_file_name1 + '.mp4')
+        local_delete_list.append(local_pcd_mp4_dir2 + '/' + pcd_mp4_file_name2 + '.mp4')
+        oss_csv_object_key1 = parse_prefix + pcd_mp4_file_name1 + '.mp4'
+        oss_csv_object_key2 = parse_prefix + pcd_mp4_file_name2 + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_dir1 + '/' + pcd_mp4_file_name1 + '.mp4')
+        print '上传点云视频到 %s' % oss_csv_object_key1
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_dir2 + '/' + pcd_mp4_file_name2 + '.mp4')
+        print '上传点云视频到 %s' % oss_csv_object_key2
+    except Exception, e:
+        print "生成点云视频报错: %s" % str(e)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        local_delete_list = []
+        oss_delete_list = []
+        prefix_list = []
+        # 2 获取已经上传完成的所有目录并分组
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            # 获取合并后的包
+            merged_bag_object_key = str(obj1.key)
+            # print(f'判断1{merged_bag_object_key}')
+            if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                merged_bag_object_key_split = merged_bag_object_key.split('/')
+                merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                pcd1_done = False
+                pcd2_done = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                    if '/pcd_depthcamera.mp4' in str(obj2.key):
+                        pcd1_done = True
+                    if '/pcd_lidar.mp4' in str(obj2.key):
+                        pcd2_done = True
+                if pcd1_done and pcd2_done:
+                    print '%s 存在点云视频 pcd_depthcamera.mp4 和 pcd_lidar.mp4。' % parse_prefix_full
+                    continue
+                print '%s 缺少点云视频 pcd_depthcamera.mp4 和 pcd_lidar.mp4。' % parse_prefix_full
+                # print(f'需要解析{merged_bag_object_key}')
+                local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                if not os.path.exists(local_parse_dir):
+                    os.makedirs(local_parse_dir)
+                merged_bag_full_name = merged_bag_object_key_split[-1]
+                merged_bag_name = merged_bag_full_name.split('.')[0]
+                bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                local_delete_list.append(local_merged_bag_path)
+                # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                parse_to_pcd_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+        # 删除本地临时文件
+        if len(local_delete_list) > 0:
+            for local_delete in local_delete_list:
+                try:
+                    os.remove(local_delete)
+                except Exception as e:
+                    print "删除本地临时文件报错: %s" % str(e)
+                    # print(f'删除本地临时文件报错{e}')
+        time.sleep(sleep_time)

archive/python2-pjibot-single-camera-module/resource/bagtocsv_robot.py

@@ -0,0 +1,88 @@
+# coding: utf-8
+#!/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math 
+
+import sys
+import time
+import numpy as np
+
+def parsebag(input_dir, output_dir):   
+    def quaternion_to_euler(x, y, z, w):
+        # 将四元数归一化
+        try:
+            length = np.sqrt(x**2 + y**2 + z**2 + w**2)
+            x /= length
+            y /= length
+            z /= length
+            w /= length
+        
+            # 计算欧拉角
+            #roll = np.arctan2(2*(w*x + y*z), 1 - 2*(x**2 + y**2))
+            #pitch = np.arcsin(2*(w*y - z*x))
+            yaw = np.arctan2(2*(w*z + x*y), 1 - 2*(y**2 + z**2))  
+            return  yaw
+        except :
+            return 0
+
+
+    dic_object_detection = ['Time','FrameID','HeadingAngle','X', 'Y' ,'Z']
+    object_detection_file = open(output_dir + "/"+"pos_pji.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+
+    frame_max=sys.maxsize
+    with rosbag.Bag(input_dir ,'r') as bag:
+        #flag=False
+        framenum = 1
+        #hasLoc = False
+        for topic,msg,t in bag.read_messages():    #t代表时间
+            
+            if topic == "/amcl_pose":#100hz  /odom
+                poseX=msg.pose.pose.position.x
+                poseY=msg.pose.pose.position.y
+                poseZ=msg.pose.pose.position.z
+                orientationX=msg.pose.pose.orientation.x
+                orientationY=msg.pose.pose.orientation.y
+                orientationZ=msg.pose.pose.orientation.z
+                orientationW=msg.pose.pose.orientation.w
+                egoyaw=quaternion_to_euler(orientationX,orientationY,orientationZ,orientationW)
+                
+                
+
+                message_location =[str(t)[:-6],framenum,egoyaw,poseX,poseY,poseZ]
+
+       
+                
+                
+                  
+                writer_object_detection.writerow(message_location)
+                framenum+=1
+                #hasLoc = False
+                #data_read_flag=False
+                
+    # driving_status_file.close()
+        object_detection_file.close()
+
+if __name__ == "__main__":
+#    print("Input the path of file...."+'\n')
+
+   #input_dir = sys.argv[1]
+   input_dir='/media/dell/BFAC-F22B/data/pujin_datareturn/pjirobot_20231207_2023-12-07-07-18-46_54.bag'
+   bagname=input_dir.split('/')[-1].split('.')[0]
+   #output_dir = sys.argv[2]
+   output_dir='/media/dell/BFAC-F22B/data/pujin_datareturn'
+
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   #parsebag(input_dir, output_dir)
+
+   try:
+       parsebag(input_dir, output_dir)
+       print('successfully analysis '+input_dir)
+   except Exception as e:
+       print(e)

archive/python2-pjibot-single-camera-module/resource/parse_pji_image.py

@@ -0,0 +1,102 @@
+# coding: utf-8
+
+import sys
+
+import os
+import rospy
+import rosbag
+import csv
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+import argparse
+import struct
+import subprocess
+from subprocess import Popen, PIPE
+
+bridge = CvBridge()
+
+
+def parsebag(f, output_dir, target_topic):
+    rosbag_name = f[f.rindex("/"):-4]
+    output_path = output_dir + rosbag_name
+
+    with rosbag.Bag(f, 'r') as bag:
+        count = 0
+        for key, val in bag.get_type_and_topic_info()[1].items():
+            if val[0] == 'sensor_msgs/Image':
+
+                for topic, msg, t in bag.read_messages(key):
+                    if topic== target_topic:
+                        img = bridge.imgmsg_to_cv2(msg, 'bgr8')
+                        # img = bridge.compressed_imgmsg_to_cv2(msg, 'bgr8')
+                        timestr = msg.header.stamp.to_nsec()
+                        image_name = str(timestr) + ".jpg"
+                        if not os.path.exists(output_path + '_' + 'image'):
+                            os.makedirs(output_path + '_' + 'image')
+                        output_path_img = os.path.join(output_path + '_' + 'image', image_name)
+                        cv2.imwrite(output_path_img, img)
+                        # print(count)
+                        count = count + 1
+    return count
+
+def main():
+    input_dir = sys.argv[1]
+    #input_dir='/media/dell/BFAC-F22B/data/pujin_datareturn/pujin_robot-01_data_merge_2023-12-20-02-22-18_obstacledetection_10.bag'
+    output_dir = sys.argv[2]
+    #output_dir = '/media/dell/BFAC-F22B/data/pujin_datareturn'
+    topic = '/camera/color/image_raw'  # /camera/color/image_raw
+
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    # print(dirt)
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+
+
+if __name__ == '__main__':
+    main()
+
+
+def parse(input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    # input_dir = '/media/dell/BFAC-F22B/rapid_accel_2023-11-15-10-33-50.bag'
+    output_dir = output_mp4_dir
+    # output_dir = '/media/dell/BFAC-F22B/'
+    topic = '/camera/color/image_raw'
+
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    # print(dirt)
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+    return dirt

archive/python2-pjibot-single-camera-module/resource/pcdtovideo_pji_deepcamera.py

@@ -0,0 +1,220 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+
+
+
+if __name__ == '__main__':
+    input_dir = sys.argv[1]
+    #input_dir = '/media/dell/BFAC-F22B/data/pujin_datareturn/pujin_robot-01_data_merge_2023-12-20-02-22-18_obstacledetection_10.bag'
+    output_dir = sys.argv[2]
+    #output_dir='/media/dell/BFAC-F22B/data/pujin_datareturn'
+
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_depthcamera' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/camera/depth/points": #/camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/camera/depth/points'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+    
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                #pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+                #draw_points(pic, tempFilePath)
+                #cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath) 
+                #pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+                pic = np.zeros([800, 1600, 3])
+                f = open(tempFilePath, "r")
+                ff = f.readlines()[11:]
+        
+                for i in range(0, len(ff)):
+                    point = ff[i].split()[:4]
+                    point_x = float(point[0])
+                    point_y = float(point[1])
+                    point_z = float(point[2])
+                    points_intensity = float(point[2])
+                    #t = np.dot(np.linalg.inv(a),np.array([point_x,point_y,point_z,1]))
+                    #x = t[0]
+                    #y = t[1]
+                    x = -point_x
+                    y = -point_y
+        
+                    if math.isnan(point_x):
+                        pass
+                    else:
+                        cv2.circle(pic, (int(800 - x * 60), int(400 - y * 60)), 0, (255,255,255), 0)
+
+                
+                cv2.imwrite(outputFilePath, pic)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_depthcamera.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+
+def parse(input_dir, output_dir):
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_depthcamera' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/camera/depth/points":  # /camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/camera/depth/points'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                # pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+                # draw_points(pic, tempFilePath)
+                # cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+                # pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+                pic = np.zeros([800, 1600, 3])
+                f = open(tempFilePath, "r")
+                ff = f.readlines()[11:]
+
+                for i in range(0, len(ff)):
+                    point = ff[i].split()[:4]
+                    point_x = float(point[0])
+                    point_y = float(point[1])
+                    point_z = float(point[2])
+                    points_intensity = float(point[2])
+                    # t = np.dot(np.linalg.inv(a),np.array([point_x,point_y,point_z,1]))
+                    # x = t[0]
+                    # y = t[1]
+                    x = -point_x
+                    y = -point_y
+
+                    if math.isnan(point_x):
+                        pass
+                    else:
+                        cv2.circle(pic, (int(800 - x * 60), int(400 - y * 60)), 0, (255, 255, 255), 0)
+
+                cv2.imwrite(outputFilePath, pic)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_depthcamera.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

archive/python2-pjibot-single-camera-module/resource/pcdtovideo_pji_lidar.py

@@ -0,0 +1,190 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+
+def draw_points(pic, filename):
+    f = open(filename, "r")
+    ff = f.readlines()[11:]
+
+    for i in range(0, len(ff)):
+        point = ff[i].split()[:4]
+        point_x = float(point[0])
+        point_y = -float(point[1])
+
+        if math.isnan(point_x):
+            pass
+        else:
+            cv2.circle(pic, (int(800 - point_x * 20), int(400 - point_y * 20)), 1, (250, 250, 250), 0)
+
+
+if __name__ == '__main__':
+    input_dir = sys.argv[1]
+    # input_dir = '/media/dell/BFAC-F22B/data/pujin_datareturn/pjirobot_20231207_2023-12-07-07-18-46_54.bag'
+    output_dir = sys.argv[2]
+    # output_dir='/media/dell/BFAC-F22B/data/pujin_datareturn'
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_lidar' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/scan_map_icp_amcl_node/scan_point_transformed'] + [
+        output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    # Process_rosbag = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    # Process_rosbag.wait()
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                pic = np.zeros([800, 1600, 3])
+                draw_points(pic, tempFilePath)
+                cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)    
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_lidar.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+
+
+def parse(input_dir, output_dir):
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_lidar' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + [
+        '/scan_map_icp_amcl_node/scan_point_transformed'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    # Process_rosbag = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    # Process_rosbag.wait()
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                pic = np.zeros([800, 1600, 3])
+                draw_points(pic, tempFilePath)
+                cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_lidar.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE,
+                  stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

archive/python3-pjiusv/20231214/openx.py

@@ -0,0 +1,933 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar 14 15:44:01 2022
+
+@author: lxj
+"""
+import xml.etree.ElementTree as ET
+from scenariogeneration import xodr
+from scenariogeneration import xosc
+from scenariogeneration import ScenarioGenerator
+from scenariogeneration.xodr import RoadSide, Object, ObjectType, Dynamic, Orientation
+import math, os
+from xodr_generator2 import road_detector_new
+from datetime import datetime
+import traceback
+import json
+import pandas as pd
+from enum import Enum
+import elevation_0323 as el
+
+import warnings
+
+warnings.filterwarnings("ignore")
+
+# xodr_list = ['/home/hancheng/taiheqiao_map/thq_1116.xodr', '/home/hancheng/gongyuanbeihuan_map/OD/OpenDRIVE.xodr','/home/hancheng/glyt_map/OpenDRIVE2.xodr']
+# osgb_list = ['/home/hancheng/taiheqiao_map/thq_1116.opt.osgb', '/home/hancheng/gongyuanbeihuan_map/osgb/GJBM_20km_0822.opt.osgb', '/home/hancheng/glyt_map/OSGB/jinlong_20231129_2_guazai.opt.osgb']
+xodr_list = ['/root/rosmerge/resource/thq.xodr', '/root/rosmerge/resource/OpenDRIVE.xodr',
+             '/root/rosmerge/resource/gelan.xodr']
+osgb_list = ['/root/rosmerge/resource/thq.opt.osgb', '/root/rosmerge/resource/GJBM_20km_0822.opt.osgb',
+             '/root/rosmerge/resource/gelan.opt.osgb']
+
+
+class Scenario(ScenarioGenerator):
+    def __init__(self, gps, obs, gps_time, ego_speed, work_mode, period, abspath, timeofday, map_id):
+        ScenarioGenerator.__init__(self)
+        self.gps = gps
+        self.obs = obs
+        self.gps_time = gps_time
+        self.ego_speed = ego_speed
+        self.work_mode = work_mode
+        self.period = period  # 场景持续的时间
+        self.abspath = abspath
+        self.weather = xosc.PrecipitationType.dry  # 默认是晴天
+        self.visual_fog_range = 20000  # 正常的能见度，没有雾
+        self.time = timeofday  # 用于判断白天还是黑夜
+        self.map_id = map_id
+        # self.ObjectID = ObjectID
+        # self.Speed = Speed
+
+    def road(self, **kwargs):
+        positionEgo = self.gps
+        planview = xodr.PlanView()
+
+        for i in range(len(positionEgo) - 1):
+            x = 0.000001 if abs(positionEgo[i].x) < 0.000001 else positionEgo[i].x
+            y = 0.000001 if abs(positionEgo[i].y) < 0.000001 else positionEgo[i].y
+            nextx = 0.000001 if abs(positionEgo[i + 1].x) < 0.000001 else positionEgo[i + 1].x
+            nexty = 0.000001 if abs(positionEgo[i + 1].y) < 0.000001 else positionEgo[i + 1].y
+            h = float(positionEgo[i].h)
+
+            planview.add_fixed_geometry(xodr.Line(math.sqrt(math.pow(nextx - x, 2) + math.pow(nexty - y, 2))), x, y, h)
+
+        planview.add_fixed_geometry(xodr.Line(100), nextx, nexty, h)
+        # create two different roadmarkings
+        rm_solid = xodr.RoadMark(xodr.RoadMarkType.solid, 0.2)
+        rm_dashed = xodr.RoadMark(xodr.RoadMarkType.broken, 0.2)
+
+        # create simple lanes
+        lanes = xodr.Lanes()
+        lanesection1 = xodr.LaneSection(0, xodr.standard_lane(offset=1.75, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_solid))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_solid))
+        lanes.add_lanesection(lanesection1)
+        lanes.add_laneoffset(xodr.LaneOffset(a=1.75))
+
+        road = xodr.Road(0, planview, lanes)
+        odr = xodr.OpenDrive('myroad')
+        # 静态元素
+        tree = ET.parse(os.getcwd() + '/models/static_object_models.xodr')
+        root = tree.getroot()
+        objects_dict = root.iter(tag='object')
+        road = create_static_object(road, objects_dict)
+
+        # road = create_static_object(road, object_id=0, object_type=ObjectType.railing, repeat_flag=1)
+        odr.add_road(road)
+        odr.adjust_roads_and_lanes()
+        return odr
+
+    def get_section(self, left_lanemark):
+
+        return None
+
+    def split_road_section(self, enu_file, lane_file):
+        lane_content = pd.read_csv(lane_file)
+        # 把车道分割开来，一个车道段，多种geometry
+        # 首先判断车道线数值是否有断裂，断裂处根据自车轨迹生成道路参数
+        left_lanemark = lane_content[lane_content['LaneID'] == 1][['Time', 'FrameID', 'LanePosition', 'LaneQuality']]
+        right_lanemark = lane_content[lane_content['LaneID'] == 2][['Time', 'FrameID', 'LanePosition', 'LaneQuality']]
+
+        left_break_section = self.get_section(left_lanemark, 1)
+        right_break_section = self.get_section(right_lanemark, 1)
+        break_section = []
+        normal_section = []
+
+        # 判断是否变道，然后判断是否弯道
+
+        # 最终目标是得到多个geometry参数，确定每个连接线处的s/t偏移量?，以及左右道路的个数和宽度
+
+        return None
+
+    def check_outliers_and_modify(self, datalist):
+        for index in datalist.index:
+            if index < 3:
+                datalist.loc[index] = datalist[index] if abs(
+                    datalist[index] - datalist[index + 1:index + 3].mean()) < 0.5 else 2 * datalist[
+                    index + 1] - datalist[index + 1:index + 3].mean()
+            elif 3 <= index < len(datalist) - 3:
+                datalist.loc[index] = datalist[index] if abs(
+                    datalist[index] - datalist[index + 1:index + 3].mean()) < 0.5 or abs(
+                    datalist[index] - datalist[index - 3:index].mean()) < 0.5 else (datalist[index - 1] + datalist[
+                    index + 1]) / 2
+            else:
+                datalist.loc[index] = datalist[index] if abs(
+                    datalist[index] - datalist[index - 3:index].mean()) < 0.5 else 2 * datalist[index - 1] - datalist[
+                                                                                                             index - 3:index].mean()
+        return datalist
+
+    def get_new_LaneID(self, change_flag, laneID, frameid, item):
+        '''
+        修改laneID，change_list包含了每个变道片段
+
+        '''
+        if item[0] <= frameid < item[1]:
+            return laneID + change_flag
+        else:
+            return laneID
+
+    def get_lane_width(self, data1, data2):
+        lane_union = pd.merge(data1, data2, on=['FrameID'])
+        lane_union['width'] = lane_union['LanePosition_y'] - lane_union['LanePosition_x']
+        a = lane_union["width"].quantile(0.75)
+        b = lane_union["width"].quantile(0.25)
+        lane_width = abs((a + b) / 2)
+        return lane_width
+
+    def road_pre_study(self, label_file, lane_file):
+        laneDF = pd.read_csv(lane_file)
+        road_label = ''
+        flag = 0  # flag = 0 can use road_ego to generate .xodr, flag = 1 better use road to generate .xodr
+        with open(label_file) as f:
+            label = json.load(f)
+
+            ego_actions = label['自车行为']
+            for item in ego_actions:
+                if ('变道' in item['type_']) or ('转成功' in item['type_']) or ('掉头' in item['type_']):
+                    road_label = item['type_']
+                    flag = 1
+                    break
+                else:
+                    road_label = item['type_']
+
+        if road_label == '向左变道成功':
+            # 查找变道标记点
+            change_flag = 1
+            lane_1 = laneDF[(laneDF['LaneID'] == 1) & (laneDF['LaneQuality'] > 1)]
+            lane_1 = lane_1.reset_index(drop=True)
+            leftlanepositon = lane_1['LanePosition']
+            lane_1['LanePosition'] = self.check_outliers_and_modify(leftlanepositon)
+            lane_1['last_Position'] = lane_1[['LanePosition']].shift(axis=0, periods=1)  # axis指定移动的轴：0为行,1为列
+            lane_1['last_FrameID'] = lane_1[['FrameID']].shift(axis=0, periods=1)  # axis指定移动的轴：0为行,1为列
+            lane_1['change_flag'] = lane_1.apply(
+                lambda x: change_flag if (x['LanePosition'] - x['last_Position'] <= -3) and (
+                            x['FrameID'] - x['last_FrameID'] == 1) else 0, axis=1)  # 默认情况下 axis=0 表示按列，axis=1 表示按行。
+            lane_1['split_flag'] = lane_1.apply(lambda x: 99 if x['FrameID'] - x['last_FrameID'] > 1 else 0, axis=1)
+
+            lane_2 = laneDF[(laneDF['LaneID'] == 2) & (laneDF['LaneQuality'] > 1)]
+            lane_2 = lane_2.reset_index(drop=True)
+            rightlanepositon = lane_2['LanePosition']
+            lane_2['LanePosition'] = self.check_outliers_and_modify(rightlanepositon)
+            lane_2['last_Position'] = lane_2[['LanePosition']].shift(axis=0, periods=1)  # axis指定移动的轴：0为行,1为列
+            lane_2['last_FrameID'] = lane_2[['FrameID']].shift(axis=0, periods=1)  # axis指定移动的轴：0为行,1为列
+            lane_2['change_flag'] = lane_2.apply(
+                lambda x: change_flag if (x['LanePosition'] - x['last_Position'] <= -3) and (
+                            x['FrameID'] - x['last_FrameID'] == 1) else 0, axis=1)  # 默认情况下 axis=0 表示按列，axis=1 表示按行。
+            lane_2['split_flag'] = lane_2.apply(lambda x: 99 if x['FrameID'] - x['last_FrameID'] > 1 else 0, axis=1)
+
+            lane_width = self.get_lane_width(lane_1[['FrameID', 'LanePosition']], lane_2[['FrameID', 'LanePosition']])
+            # 左变道用左车道线数据靠谱，不会有他车遮挡，找到变道数据段
+            change_lane_point = list(lane_1[lane_1['change_flag'] == change_flag]['change_flag'].index) + [
+                list(lane_1.index)[-1]]
+            change_lane_section = [
+                (lane_1.loc[change_lane_point[i], 'FrameID'], lane_1.loc[change_lane_point[i + 1], 'FrameID']) for i in
+                range(len(change_lane_point) - 1)]
+
+            for item in change_lane_section:
+                # 变道后修改原始laneID
+                # laneDF['LaneID'] = laneDF.apply(lambda x: x['LaneID'] - change_flag if item[0] <= x['FrameID'] < item[1] else x['LaneID'], axis=1)
+                # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition'] - change_flag * lane_width if item[0] <= x['FrameID'] < item[1] else x['LanePosition'], axis=1)
+                # laneDF['LaneID'] = laneDF.apply(lambda x: x['LaneID'] - change_flag if x['FrameID'] == max(laneDF['FrameID']) else x['LaneID'], axis=1)
+                # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition'] - change_flag * lane_width if x['FrameID'] == max(laneDF['FrameID']) else x['LanePosition'], axis=1)
+
+                # 修正左左车道线和右右车道线数值
+                if change_flag == 1:
+                    lane_0 = laneDF[
+                        (laneDF['LaneID'] == 0) & (laneDF['LaneQuality'] > 1) & (laneDF['FrameID'] < item[0])]
+                    if not lane_0.empty:
+                        left_lane_width = self.get_lane_width(lane_0[['FrameID', 'LanePosition']],
+                                                              lane_1[['FrameID', 'LanePosition']])
+                    else:
+                        left_lane_width = lane_width
+                    print(left_lane_width)
+                    # new_lane_1 = laneDF[laneDF['LaneID'] == 1][['FrameID','LanePosition']]
+                    # new_lane_1.rename(columns={'LanePosition':'LanePosition2'},inplace=True)
+                    # laneDF = pd.merge(laneDF, new_lane_1, on=['FrameID'])
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if (item[0] <= x['FrameID'] < item[1]) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if x['FrameID'] == max(laneDF['FrameID']) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if (item[0] <= x['FrameID'] < item[1]) and (x['LaneID'] == -1) else x['LanePosition'], axis=1)
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if x['FrameID'] == max(laneDF['FrameID']) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+                    # laneDF['LaneID'] = laneDF.apply(lambda x: 3 if x['LaneID'] == -1 else x['LaneID'], axis=1)
+                # 缺右车道线right_lane_width处理
+
+                print(laneDF[laneDF['FrameID'] > 1860][['FrameID', 'LaneID', 'LanePosition']].head(50))
+        print('road_label: ', road_label)
+
+        return laneDF
+
+    def road_new(self, **kwargs):
+        polyfit_fig_path = os.path.join(self.abspath, 'simulation', 'polyfit.jpg')
+
+        # run road detector
+        enu_file = os.path.join(self.abspath, 'pos.csv')
+        lane_file = os.path.join(self.abspath, 'lane.csv')
+        label_file = os.path.join(self.abspath, 'label.json')
+
+        # study road style: straight\curve\split-line; ego action: change-lane\no-change\cross-turn
+        lane_content = self.road_pre_study(label_file, lane_file)
+
+        # road split sections
+        # self.split_road_section(enu_file, lane_file)
+
+        try:
+            laneid_tuple = [0, 1, 2, 3]
+            uv_coord_info, road_info, left_lane_info, right_lane_info = road_detector_new(enu_file, lane_content,
+                                                                                          laneid_tuple,
+                                                                                          polyfit_fig_path)
+        except:
+            print('road detection failed!!!!  Use ego trail road.')
+            error = {'time': datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3], 'traceback': traceback.format_exc()}
+            with open('error.log', 'a+') as f:
+                json.dump(error, f, indent=4)
+                f.write('\n')
+            return self.road_ego()
+
+        origin_x = uv_coord_info[0]
+        origin_y = uv_coord_info[1]
+        uv_coord_hdg = uv_coord_info[2]
+
+        reference_line_offset = road_info[0]
+        model_u = road_info[1]  # in fomrat [c3, c2, c1, c0]
+        model_v = road_info[2]  # in fomrat [c3, c2, c1, c0]
+        road_length = road_info[3]
+        print(uv_coord_info)
+        print(road_info)
+        # generate xodr file
+        planview = xodr.PlanView(origin_x, origin_y, uv_coord_hdg)
+
+        # Create geometry and add it to the planview 
+        # parampoly3 = xodr.ParamPoly3(au=model_u[3], bu=model_u[2], cu=model_u[1], du=model_u[0], av=model_v[3], bv=model_v[2], cv=model_v[1], dv=model_v[0], prange='arcLength',length=road_length)
+        parampoly3 = xodr.ParamPoly3(au=0, bu=model_u[2], cu=model_u[1], du=model_u[0], av=0, bv=model_v[2],
+                                     cv=model_v[1], dv=model_v[0], prange='arcLength', length=road_length)
+        planview.add_geometry(parampoly3)
+
+        # create two different roadmarkings
+        rm_solid = xodr.RoadMark(xodr.RoadMarkType.solid, 0.2)
+        rm_dashed = xodr.RoadMark(xodr.RoadMarkType.broken, 0.2, laneChange=xodr.LaneChange.both)
+
+        ##4. Create centerlane 
+        centerlane = xodr.Lane(a=reference_line_offset)
+        centerlane.add_roadmark(rm_dashed)
+
+        ##5. Create lane section form the centerlane
+        lanesec = xodr.LaneSection(0, centerlane)
+
+        ##6. Create left and right lanes
+        lane_id = 0
+        for lane in left_lane_info:
+            lane_id += 1
+            lane_width = lane[0]
+            spd_limit = lane[1]
+            lane_left = xodr.Lane(a=lane_width)
+            lane_left.add_roadmark(rm_dashed)
+            # Add lanes to lane section 
+            lanesec.add_left_lane(lane_left)
+
+        lane_id = 0
+        for lane in right_lane_info:
+            lane_id -= 1
+            lane_width = lane[0]
+            spd_limit = lane[1]
+            lane_right = xodr.Lane(a=lane_width)
+            lane_right.add_roadmark(rm_dashed)
+            # Add lanes to lane section 
+            lanesec.add_right_lane(lane_right)
+
+        ##8. Add lane section to Lanes 
+        lanes = xodr.Lanes()
+        lanes.add_laneoffset(xodr.LaneOffset(s=0, a=reference_line_offset))
+        lanes.add_lanesection(lanesec)
+
+        ##9. Create Road from Planview and Lanes
+        road = xodr.Road(1, planview, lanes)
+
+        ##10. Create the OpenDrive class (Master class)
+        odr = xodr.OpenDrive('myroad')
+
+        ##11. Finally add roads to Opendrive 
+        odr.add_road(road)
+
+        ##12. Adjust initial positions of the roads looking at succ-pred logic 
+        odr.adjust_roads_and_lanes()
+
+        # ##13. Print the .xodr file
+        # xodr.prettyprint(odr.get_element())
+
+        # ##14. Run the .xodr with esmini 
+        # xodr.run_road(odr,os.path.join('..','pyoscx','esmini'))
+
+        return odr
+
+    def getXoscPosition(egodata, t, e, n, h, z, obj_type, offset_x, offset_y, offset_h, start_time):
+        '将dataframe的轨迹转换为场景文件的轨迹数据, Time, ego_e, ego_n, headinga'
+
+        position = []
+        time = []
+        # cur_time = 0.0
+        egodata = egodata[[t, e, n, h, z, obj_type]]
+        egodata = egodata.reset_index(drop=True)
+        # egodata[t] = egodata.index / 10
+        egodata[t] = (egodata[t] - start_time) / 1000
+        egodata[e] = egodata[e] + offset_x
+        egodata[n] = egodata[n] + offset_y
+        egodata[h] = egodata[h] + offset_h
+        egodata[h] = egodata.apply(lambda x: x[h] if x[h] < 360 else x[h] - 360, axis=1)
+        type_list = list(egodata[obj_type])
+        ego_type = int(max(type_list, key=type_list.count))
+
+        lasth = float(egodata.at[0, h])
+        init_flag = True
+
+        # two method to set z value
+        zflag = 0  # 1
+        if zflag:
+            # 根据地图的xy值计算z值
+            zfile = '/home/hancheng/weihao/gongyuanbei_elevation.csv'
+            # zfile = '/home/hancheng/simulation_dynamic/elevation_df_taiheqiao.csv'
+            zdata = pd.read_csv(zfile)
+
+            for row in egodata.iterrows():
+                hhh = math.radians(row[1][h])
+                xodr_z = el.cal_elevation(zdata, float(row[1][e]), float(row[1][n]))
+                if init_flag:
+                    position.append(
+                        xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=xodr_z, h=hhh, p=0, r=0))
+                    init_flag = False
+                else:
+                    if float(row[1][h]) - lasth > 300:
+                        hhh = math.radians(float(row[1][h]) - 360)
+                    elif float(row[1][h]) - lasth < -300:
+                        hhh = math.radians(float(row[1][h]) + 360)
+                    position.append(
+                        xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=xodr_z, h=hhh, p=0, r=0))
+                    lasth = hhh
+                time.append(float(row[1][t]))
+                # time.append(cur_time)
+                # cur_time += 0.1
+            return position, time, ego_type
+        else:
+            # z = 0
+            for row in egodata.iterrows():
+                hhh = math.radians(row[1][h])
+                if init_flag:
+                    position.append(
+                        xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=float(row[1][z]), h=hhh, p=0, r=0))
+                    init_flag = False
+                else:
+                    if float(row[1][h]) - lasth > 300:
+                        hhh = math.radians(float(row[1][h]) - 360)
+                    elif float(row[1][h]) - lasth < -300:
+                        hhh = math.radians(float(row[1][h]) + 360)
+                    position.append(
+                        xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=float(row[1][z]), h=hhh, p=0, r=0))
+                    lasth = hhh
+                time.append(float(row[1][t]))
+                # time.append(cur_time)
+                # cur_time += 0.1
+            return position, time, ego_type
+
+    def scenario(self, **kwargs):
+        road = xosc.RoadNetwork(roadfile=xodr_list[self.map_id], scenegraph=osgb_list[self.map_id])
+        catalog = xosc.Catalog()
+        catalog.add_catalog('VehicleCatalog', 'Distros/Current/Config/Players/Vehicles')
+        catalog.add_catalog('PedestrianCatalog', 'Distros/Current/Config/Players/Pedestrians')
+        catalog.add_catalog('ControllerCatalog', 'Distros/Current/Config/Players/driverCfg.xml')
+
+        pbb = xosc.BoundingBox(0.5, 0.5, 1.8, 2.0, 0, 0.9)
+        mbb = xosc.BoundingBox(1, 2, 1.7, 1.5, 0, 0.9)
+        bb = xosc.BoundingBox(2.1, 4.5, 1.8, 1.5, 0, 0.9)
+        bus_bb = xosc.BoundingBox(2.55, 10.5, 3.1, 5.1, 0, 1.45)
+        bus_fa = xosc.Axle(0.48, 0.91, 2.5, 4.5, 1.5)
+        bus_ba = xosc.Axle(0, 0.91, 2.5, 4.5, 1.5)
+        truck_bb = xosc.BoundingBox(2.8, 8.744, 3.78, 4.372, 0, 1.89)
+        truck_fa = xosc.Axle(0.48, 1, 2.8, 4.372, 1.5)
+        truck_ba = xosc.Axle(0, 1, 2.8, 4.372, 1.5)
+        fa = xosc.Axle(0.5, 0.6, 1.8, 3.1, 0.3)
+        ba = xosc.Axle(0, 0.6, 1.8, 0, 0.3)
+        red_veh = xosc.Vehicle('Audi_A3_2009_black', xosc.VehicleCategory.car, bb, fa, ba, 69.444, 200, 10)
+        red_veh.add_property(name='control', value='external')
+        white_veh = xosc.Vehicle('Audi_A3_2009_red', xosc.VehicleCategory.car, bb, fa, ba, 69.444, 200, 10)
+        male_ped = xosc.Pedestrian('Christian', 'male adult', 70, xosc.PedestrianCategory.pedestrian, pbb)
+        motorcycle = xosc.Vehicle('Kawasaki_ZX-9R_black', xosc.VehicleCategory.motorbike, mbb, fa, ba, 69.444, 200, 10)
+        truck = xosc.Vehicle('MANTGS_11_Black', xosc.VehicleCategory.truck, truck_bb, truck_fa,
+                             truck_ba, 26.4, 10, 10)
+        bus = xosc.Vehicle('MercedesTravego_10_ArcticWhite', xosc.VehicleCategory.bus, bus_bb, bus_fa, bus_ba, 29, 10,
+                           10)
+
+        prop = xosc.Properties()
+        cnt = xosc.Controller('DefaultDriver', prop)
+        cnt2 = xosc.Controller('No Driver', prop)
+
+        # 添加自车实体
+        egoname = 'Ego'
+        entities = xosc.Entities()
+        entities.add_scenario_object(egoname, red_veh, cnt)
+
+        # 添加目标车实体
+        objname = 'Player'
+        ped_type, car_type, bicycle_motor_type, bus_type, truct_type = get_obj_type(self.work_mode)
+        positionEgo = self.gps
+        positionObj = self.obs
+        for i, row in enumerate(positionObj):
+            if len(row[1]) < 10:
+                continue
+            obj_type = row[2]  # 根据目标物类型添加对应的实体
+
+            if obj_type in ped_type:
+                entities.add_scenario_object(objname + str(i), male_ped)
+            elif obj_type in car_type:
+                entities.add_scenario_object(objname + str(i), white_veh, cnt2)
+            elif obj_type in bicycle_motor_type:
+                entities.add_scenario_object(objname + str(i), motorcycle, cnt2)
+            elif obj_type in bus_type:
+                entities.add_scenario_object(objname + str(i), bus, cnt2)
+            elif obj_type in truct_type:
+                entities.add_scenario_object(objname + str(i), truck, cnt2)
+
+        # 初始化
+        init = xosc.Init()
+        step_time = xosc.TransitionDynamics(xosc.DynamicsShapes.step, xosc.DynamicsDimension.time, 0)
+        egospeed = xosc.AbsoluteSpeedAction(self.ego_speed, step_time)
+
+        # 设置初始环境要素，例如天气时间等
+        default_precipitation = xosc.PrecipitationType.dry
+        default_cloudstate = xosc.CloudState.free
+
+        # json_path = os.path.join(self.abspath, 'label.json')
+        # with open(json_path, 'r', encoding='utf-8') as f:
+        #     sc_json = json.load(f)
+        #     weather = sc_json['天气情况'][0]['type_'] #['自然环境']
+        #     if weather == '晴':
+        #         f.close()
+        #     elif weather == '多云':
+        #         default_cloudstate = xosc.CloudState.cloudy
+        #     elif weather == '阴':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #     elif weather == '雨':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #         default_precipitation = xosc.PrecipitationType.rain
+        #     elif weather == '雪':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #         default_precipitation = xosc.PrecipitationType.snow
+        #     elif weather == '雾霾' or weather == '沙尘':
+        #         self.visual_fog_range = 700
+        #         default_cloudstate = xosc.CloudState.cloudy
+
+        init.add_global_action(
+            xosc.EnvironmentAction(name="InitEnvironment", environment=xosc.Environment(
+                xosc.TimeOfDay(True, 2019, 12, 19, 12, 0, 0),
+                xosc.Weather(
+                    sun_intensity=2000, sun_azimuth=40, sun_elevation=20,
+                    cloudstate=default_cloudstate,
+                    precipitation=default_precipitation,
+                    precipitation_intensity=1,
+                    visual_fog_range=self.visual_fog_range),
+                xosc.RoadCondition(friction_scale_factor=0.7))))
+
+        # ego car init
+        ego_init_h = positionEgo[0].h
+        init.add_init_action(egoname, xosc.TeleportAction(
+            xosc.WorldPosition(x=positionEgo[0].x, y=positionEgo[0].y, z=positionEgo[0].z, h=ego_init_h, p=0, r=0)))
+        init.add_init_action(egoname, egospeed)
+
+        # ego car trail
+        trajectory = xosc.Trajectory('egoTrajectory', False)
+        polyline = xosc.Polyline(self.gps_time, positionEgo)
+        trajectory.add_shape(polyline)
+
+        speedaction = xosc.FollowTrajectoryAction(trajectory, xosc.FollowMode.position, xosc.ReferenceContext.absolute,
+                                                  1, 0)
+        trigger = xosc.ValueTrigger('drive_start_trigger', 0, xosc.ConditionEdge.rising,
+                                    xosc.SimulationTimeCondition(0, xosc.Rule.greaterThan))
+        trigger_init = xosc.ValueTrigger(name='init_trigger', delay=0, conditionedge=xosc.ConditionEdge.rising,
+                                         valuecondition=xosc.SimulationTimeCondition(value=0,
+                                                                                     rule=xosc.Rule.greaterThan))
+
+        event_init = xosc.Event('Event_init', xosc.Priority.overwrite)
+        action_light = xosc.CustomCommandAction(0, 0, 0, 0, 1, 0, 0)
+        light_flag = 'auto'
+        if self.time == 64800:
+            light_flag = 'true'
+        text = f'<Environment><TimeOfDay headlights="{light_flag}" timezone="8" value="{self.time}" /></Environment>'
+        node = ET.Element("CustomCommandAction")
+        node.attrib = {'type': 'scp'}
+        node.text = f"<![CDATA[\n{text}]\n]>"
+        action_light.add_element(node)
+        event_init.add_action('headlight', action_light)
+        event_init.add_trigger(trigger_init)
+
+        event = xosc.Event('Event1', xosc.Priority.overwrite)
+        event.add_trigger(trigger)
+        event.add_action('newspeed', speedaction)
+        man = xosc.Maneuver('my maneuver')
+        man.add_event(event_init)
+        man.add_event(event)
+
+        mangr = xosc.ManeuverGroup('mangroup', selecttriggeringentities=True)
+        mangr.add_actor('Ego')
+        mangr.add_maneuver(man)
+
+        trigger0 = xosc.Trigger('start')
+        act = xosc.Act('Act1', trigger0)
+        act.add_maneuver_group(mangr)
+
+        ego_story = xosc.Story('mystory_ego')
+        ego_story.add_act(act)
+
+        stop_trigger = xosc.ValueTrigger('stop_trigger', 0, xosc.ConditionEdge.none,
+                                         xosc.SimulationTimeCondition(self.period, xosc.Rule.greaterThan), 'stop')
+        sb = xosc.StoryBoard(init, stoptrigger=stop_trigger)
+        sb.add_story(ego_story)
+
+        # object car trail
+        if positionObj:
+            for i, row in enumerate(positionObj):
+                name = objname + str(i)
+                if len(row[1]) < 10:
+                    continue
+                obj_type = row[2]
+
+                # 根据目标车需要动态创建实体
+                x = row[0][0].x
+                y = row[0][0].y
+                z = row[0][0].z
+                h = row[0][0].h
+                start_time = row[1][0]
+                init_position = xosc.WorldPosition(x=x, y=y, z=z, h=h, p=0, r=0)
+                newentity = xosc.AddEntityAction(name, init_position)
+                newentity_trigger = xosc.ValueTrigger(name='newentity_trigger', delay=0,
+                                                      conditionedge=xosc.ConditionEdge.rising,
+                                                      valuecondition=xosc.SimulationTimeCondition(value=start_time,
+                                                                                                  rule=xosc.Rule.equalTo))
+                newentity_event = xosc.Event('Event_newentity', xosc.Priority.overwrite)
+                newentity_event.add_trigger(newentity_trigger)
+                newentity_event.add_action('newentity_action', newentity)
+                man_obj = xosc.Maneuver('my maneuver')
+                man_obj.add_event(newentity_event)
+
+                # 添加目标车轨迹
+                trajectoryM = xosc.Trajectory('objectTrajectory', False)
+                polylineM = xosc.Polyline(row[1], row[0])
+                trajectoryM.add_shape(polylineM)
+                obj_trail_action = xosc.FollowTrajectoryAction(trajectory=trajectoryM,
+                                                               following_mode=xosc.FollowMode.position,
+                                                               reference_domain=xosc.ReferenceContext.absolute,
+                                                               scale=1, offset=0, initialDistanceOffset=0)
+
+                obj_trail_event = xosc.Event('Event1', xosc.Priority.overwrite)
+                # obj_start_trigger = xosc.EntityTrigger("obj-start-trigger", 0, xosc.ConditionEdge.rising, xosc.SpeedCondition(0, xosc.Rule.greaterThan),'Ego')
+                obj_start_trigger = xosc.ValueTrigger('obj_start_trigger', 0, xosc.ConditionEdge.rising,
+                                                      xosc.SimulationTimeCondition(start_time, xosc.Rule.greaterThan))
+                obj_trail_event.add_trigger(obj_start_trigger)
+                obj_trail_event.add_action('trail_action', obj_trail_action)
+                # if obj_type in ped_type:
+                # walp_trigger =  xosc.EntityTrigger('ped_walp_trigger', 0, xosc.ConditionEdge.rising,\
+                # xosc.TimeToCollisionCondition(self.intersectime, xosc.Rule.lessThan, entity=name), 'Ego')
+                # obj_trail_event.add_trigger(walp_trigger)
+
+                man_obj.add_event(obj_trail_event)
+
+                # 行人特有的事件
+                if obj_type in ped_type:
+                    ped_event = xosc.Event('Event_ped', xosc.Priority.overwrite)
+                    ped_event.add_trigger(obj_start_trigger)
+                    ped_action = xosc.CustomCommandAction(0, 0, 0, 0, 1, 0, 0)
+                    ped_action.add_element(self.createUDAction(name))
+                    ped_event.add_action('ped_trail_action', ped_action)
+                    man_obj.add_event(ped_event)
+
+                    # finish_trigger = xosc.EntityTrigger('finish_trigger', 0, xosc.ConditionEdge.rising, xosc.ReachPositionCondition(position=row[1][0],tolerance=1),name)
+                    # event4 = xosc.Event('Event_ped',xosc.Priority.overwrite)
+                    # event4.add_trigger(finish_trigger)
+                    # be_still_action = xosc.AbsoluteSpeedAction(0, xosc.TransitionDynamics(xosc.DynamicsShapes.step, xosc.DynamicsDimension.time, 1))
+                    # event4.add_action('ped_be_still_action',be_still_action)
+                    # man_obj.add_event(event4)
+
+                # 轨迹最后删除实体
+                last_time = row[1][-1]
+                del_action = xosc.DeleteEntityAction(name)
+                del_trigger = xosc.ValueTrigger(name='entity_del_trigger', delay=0,
+                                                conditionedge=xosc.ConditionEdge.rising,
+                                                valuecondition=xosc.SimulationTimeCondition(value=last_time,
+                                                                                            rule=xosc.Rule.greaterThan))
+                del_event = xosc.Event('Event_del', xosc.Priority.overwrite)
+                del_event.add_trigger(del_trigger)
+                del_event.add_action('del_action', del_action)
+                man_obj.add_event(del_event)
+
+                obj_mangroup = xosc.ManeuverGroup('mangroup', selecttriggeringentities=True)
+                obj_mangroup.add_actor(name)
+                obj_mangroup.add_maneuver(man_obj)
+
+                obj_act = xosc.Act('Act2', trigger0)
+                obj_act.add_maneuver_group(obj_mangroup)
+
+                obj_story = xosc.Story('mystory_' + name)
+                obj_story.add_act(obj_act)
+
+                sb.add_story(obj_story)
+
+        # prettyprint(sb.get_element())
+
+        paramet = xosc.ParameterDeclarations()
+
+        sce = xosc.Scenario('my scenario', 'Maggie', paramet, entities, sb, road, catalog)
+        return sce
+
+    def createUDAction(self, name):
+        # tree = ET.parse('./models/ped_CDATA.xosc')
+        # root = tree.getroot()
+        # ele = root[5][2][1][0][1][1][0][0][0]
+        # newnode = ET.Element("CustomCommandAction")
+        # newnode.attrib = {'type': 'scp'}
+        # newnode.text = '<![CDATA[\n' + ele.text + ']\n]>'
+        speed = 3
+        motion = 'walk'
+        text = f'<Traffic>\n     <ActionMotion actor="{name}" move="{motion}" speed="{speed}" force="false" ' \
+               f'rate="0" delayTime="0.0" activateOnExit="false"/>\n</Traffic>'
+        newnode = ET.Element("CustomCommandAction")
+        newnode.attrib = {'type': 'scp'}
+        newnode.text = f"<![CDATA[\n{text}]\n]>"
+        return newnode
+
+
+class WorkMode(Enum):
+    cicv = 0  # CICV车端
+    roadside = 1  # 车网路端
+    car = 2  # 车网车端
+    merge = 3  # 车网车端路端融合
+
+
+def get_obj_type(mode):
+    if mode == WorkMode.cicv.value:
+        # CICV车端
+        ped_type = [7]
+        car_type = [2]
+        bicycle_motor_type = [8]
+        bus_type = [3]
+        truct_type = [4]
+    elif mode == WorkMode.roadside.value:
+        # 车网路端
+        ped_type = [0]
+        car_type = [2]
+        bicycle_motor_type = [1, 3]
+        bus_type = [5]
+        truct_type = [7]
+    elif mode == WorkMode.car.value:
+        # 车网车端
+        ped_type = [1]
+        car_type = [6]
+        bicycle_motor_type = [2, 3, 4, 5]
+        bus_type = [7, 8]
+        truct_type = [9]
+    else:
+        # 车网车端路端融合
+        ped_type = [1]
+        car_type = [6]
+        bicycle_motor_type = [2, 3, 4, 5]
+        bus_type = [7, 8]
+        truct_type = [9]
+    return ped_type, car_type, bicycle_motor_type, bus_type, truct_type
+
+
+# 创建道路旁静止的场景
+def create_static_object(road, object_dict):
+    for single_object in object_dict:
+        for k, v in ObjectType.__members__.items():
+            if k == single_object.attrib['type']:
+                single_object.attrib['type'] = v
+                break
+
+        road_object = Object(
+            s=single_object.attrib['s'],
+            t=single_object.attrib['t'],
+            Type=single_object.attrib['type'],
+            dynamic=Dynamic.no,
+            id=single_object.attrib['id'],
+            name=single_object.attrib['name'],
+            zOffset=single_object.attrib['zOffset'],
+            validLength=single_object.attrib['validLength'],
+            orientation=Orientation.none,
+            length=single_object.attrib['length'],
+            width=single_object.attrib['width'],
+            height=single_object.attrib['height'],
+            pitch=single_object.attrib['pitch'],
+            roll=single_object.attrib['roll']
+        )
+
+        # 判断此object是否是重复的元素
+        repeat = single_object.find('repeat')
+        if repeat is not None:
+            road.add_object_roadside(road_object_prototype=road_object, repeatDistance=0, side=RoadSide.left,
+                                     tOffset=1.75)
+            road.add_object_roadside(road_object_prototype=road_object, repeatDistance=0, side=RoadSide.right,
+                                     tOffset=-1.755)
+        else:
+            road.add_object(road_object)
+    return road
+
+
+def change_CDATA(filepath):
+    '行人场景特例，对xosc文件内的特殊字符做转换'
+    f = open(filepath, "r", encoding="UTF-8")
+    txt = f.readline()
+    all_line = []
+    # txt是否为空可以作为判断文件是否到了末尾
+    while txt:
+        txt = txt.replace("&lt;", "<").replace("&gt;", ">").replace("&amp;", "&").replace("&quot;", '"').replace(
+            "&apos;", "'")
+        all_line.append(txt)
+        # 读取文件的下一行
+        txt = f.readline()
+    f.close()
+    f1 = open(filepath, 'w', encoding="UTF-8")
+    for line in all_line:
+        f1.write(line)
+    f1.close()
+
+
+def path_changer(xosc_path, xodr_path, osgb_path):
+    """
+    provided by Dongpeng Ding
+    :param xosc_path:
+    :param xodr_path:
+    :param osgb_path:
+    :return:
+    """
+    tree = ET.parse(xosc_path)
+    treeRoot = tree.getroot()
+
+    # for OpenScenario v0.9, v1.0
+    for RoadNetwork in treeRoot.findall('RoadNetwork'):
+
+        for Logics in RoadNetwork.findall('LogicFile'):
+            Logics.attrib['filepath'] = xodr_path
+        for SceneGraph in RoadNetwork.findall('SceneGraphFile'):
+            SceneGraph.attrib['filepath'] = osgb_path
+
+        for Logics in RoadNetwork.findall('Logics'):
+            Logics.attrib['filepath'] = xodr_path
+        for SceneGraph in RoadNetwork.findall('SceneGraph'):
+            SceneGraph.attrib['filepath'] = osgb_path
+
+    # for VTD xml
+    for Layout in treeRoot.findall('Layout'):
+        Layout.attrib['File'] = xodr_path
+        Layout.attrib['Database'] = osgb_path
+
+    tree.write(xosc_path, xml_declaration=True)
+
+
+def readXML(xoscPath):
+    xodrFileName = ""
+    osgbFileName = ""
+
+    tree = ET.parse(xoscPath)
+    treeRoot = tree.getroot()
+
+    for RoadNetwork in treeRoot.findall('RoadNetwork'):
+
+        for Logics in RoadNetwork.findall('LogicFile'):
+            xodrFileName = Logics.attrib['filepath']
+        for SceneGraph in RoadNetwork.findall('SceneGraphFile'):
+            osgbFileName = SceneGraph.attrib['filepath']
+
+        for Logics in RoadNetwork.findall('Logics'):
+            xodrFileName = Logics.attrib['filepath']
+        for SceneGraph in RoadNetwork.findall('SceneGraph'):
+            osgbFileName = SceneGraph.attrib['filepath']
+
+    return xodrFileName[xodrFileName.rindex("/") + 1:], osgbFileName[osgbFileName.rindex("/") + 1:]
+
+
+def formatThree(rootDirectory):
+    """
+    xodr and osgb file path are fixed
+    :return:
+    """
+
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if ".xosc" == file[-5:]:
+                # xodrFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Rd_001.xodr" # 泛化效果好的场景用的
+                # osgbFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Rd_001.osgb" # 泛化效果好的场景用的
+                # xodrFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Cross.xodr"  # 泛化效果好的场景用的
+                # osgbFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Cross.osgb"  # 泛化效果好的场景用的
+                xodrFilePath = "/home/hancheng/hc_project/2023-08-08-10-50-16_jsons1/2023-08-08-10-50-16_jsons_0/2023-08-08-10-50-16_jsons_0.xodr"  # 直路，泛化好用
+                osgbFilePath = "/home/hancheng/VIRES/VTD.2022.1/Runtime/Tools/RodDistro_7001_Rod4.6.3/DefaultProject/Database/json0.opt.osgb"  # 直路，泛化好用
+                # xodrFilePath = "/home/lxj/wendang_lxj/L4/L4_scenarios/piliang_model/China_Crossing_002.xodr"       # 十字路口，泛化好用
+                # osgbFilePath = "/home/lxj/wendang_lxj/L4/L4_scenarios/piliang_model/China_Crossing_002.opt.osgb"   # 十字路口，泛化好用
+                # xodrFilePath = "/home/lxj/wendang_lxj/Sharing_VAN/homework/test/DF_yuexiang_1224.xodr"       # Sharing-van还原用的
+                # osgbFilePath = "/home/lxj/wendang_lxj/Sharing_VAN/homework/test/DF_yuexiang_1224.opt.osgb"   # Sharing-van还原用的
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def formatTwo(rootDirectory):
+    """
+    data format:
+    simulation
+        file.xosc
+        file.xodr
+        file.osgb
+    :return:
+    """
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if ".xosc" == file[-5:]:
+
+                xodrFilePath = ""
+                osgbFilePath = ""
+
+                for odrFile in os.listdir(root):
+                    if ".xodr" == odrFile[-5:]:
+                        xodrFilePath = root + "/" + odrFile
+                        break
+
+                for osgbFile in os.listdir(root):
+                    if ".osgb" == osgbFile[-5:]:
+                        osgbFilePath = root + "/" + osgbFile
+                        break
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def formatOne(rootDirectory):
+    """
+    data format:
+        openx
+            xosc
+                file.xosc
+            xodr
+                file.xodr
+            osgb
+                file.osgb
+    :return:
+    """
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if "xosc" == file[-4:]:
+
+                xodrFilePath = ""
+                osgbFilePath = ""
+
+                for odrFile in os.listdir(root[:-4] + "xodr"):
+                    if "xodr" == odrFile[-4:]:
+                        xodrFilePath = root[:-4] + "xodr/" + odrFile
+                        break
+
+                for osgbFile in os.listdir(root[:-4] + "osgb"):
+                    if "osgb" == osgbFile[-4:]:
+                        osgbFilePath = root[:-4] + "osgb/" + osgbFile
+                        break
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def chongQingFormat(rootDirectory):
+    """
+    supporting file format: chong qing folder format
+    :return:
+    """
+
+    counter = 1
+
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if "xosc" == file[-4:]:
+                if "ver1.0.xosc" == file[-11:]:
+
+                    xodrFileName, osgbFileName = readXML(root + "/" + file)
+
+                    xodrFilePath = "/Xodrs/" + xodrFileName
+                    osgbFilePath = "/Databases/" + osgbFileName
+
+                    path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                    print(counter, "Change success: " + root + "/" + file)
+                else:
+                    xodrFileName, osgbFileName = readXML(root + "/" + file)
+
+                    xodrFilePath = "/Xodrs/" + xodrFileName
+                    osgbFilePath = "/Databases/" + osgbFileName
+
+                    path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                    print(counter, "Change success: " + root + "/" + file)
+                counter += 1

archive/python3-pjiusv/20231214/simulation_new.py

@@ -0,0 +1,276 @@
+import os
+import sys
+from datetime import datetime
+import traceback
+import json
+import math
+import pandas as pd
+import subprocess
+import time
+import multiprocessing   # 导入进程模块
+from functools import partial # 导入偏函数
+import warnings
+warnings.filterwarnings("ignore")
+from openx import Scenario, formatThree, formatTwo, change_CDATA
+import osgbGenerator
+from utils import smooth_1, get_coordinate_cow, get_map_name, reverse_gyb_gps
+
+
+class Batchrun:
+    def __init__(self, path, keyFileName):
+        """"初始化方法"""
+        self.path = path 
+        self.keyFileName = keyFileName 
+
+    def getFile(self, path, keyFileName):
+        '''
+        获得可以进行轨迹提取的所有片段文件夹路径
+    
+        Parameters
+        ----------
+        path : TYPE
+            DESCRIPTION.
+    
+        Returns
+        -------
+        FileList : TYPE
+            可以进行轨迹提取的所有片段文件夹路径.
+    
+        '''
+        files = os.listdir(path)  # 得到文件夹下的所有文件，包含文件夹名称
+        
+        FileList = []
+        if keyFileName not in files:
+            for name in files:
+                if os.path.isdir(path +'/'+name):
+                    FileList.extend(self.getFile(path +'/'+name, keyFileName)) #回调函数，对所有子文件夹进行搜索
+        else: 
+            FileList.append(path)
+        FileList = list(set(FileList))
+        
+        return FileList
+    
+            
+    def generateScenarios_raw(self, absPath, param):
+        '''
+        原始自然驾驶场景还原
+        '''
+        
+        # 读取自车数据
+        posPath = os.path.join(absPath, 'pos.csv')  # 用来生成场景中自车和他车的路径
+        posdata = pd.read_csv(posPath)
+
+        # 读取仿真地图数据
+        offset_x_gyb = -446403.548
+        offset_y_gyb = -4403799.286
+        offset_x_thq = -456256.260152
+        offset_y_thq = -4397809.886833
+        offset_x_glyt = -457000
+        offset_y_glyt = -4400000
+        #offset_h = 90 # 初始headinga 和 VTD 有 90偏角
+        offset_h = 0
+
+
+        thqPath = '/root/rosmerge/resource/thq_path.csv'
+        # thqPath = os.path.join(absPath, 'thq_path.csv')
+        thqdata = pd.read_csv(thqPath)
+        thqdata['posX'] -= offset_x_thq
+        thqdata['posY'] -= offset_y_thq
+
+        gybPath = '/root/rosmerge/resource/gybhl_path.csv'
+        # gybPath = os.path.join(absPath, 'gybhl_path.csv')
+        gybdata = pd.read_csv(gybPath)
+        gybdata['posX'] -= offset_x_gyb
+        gybdata['posY'] -= offset_y_gyb
+        reverse_east, reverse_north = reverse_gyb_gps(gybdata)
+        gybdata['East'] = reverse_east
+        gybdata['North'] = reverse_north
+
+        glytPath = '/root/rosmerge/resource/glyt_path.csv'
+        # glytPath = os.path.join(absPath, 'glyt_path.csv')
+        glytdata = pd.read_csv(glytPath)
+        glytdata['posX'] -= offset_x_glyt
+        glytdata['posY'] -= offset_y_glyt
+
+        init_x = posdata.iloc[0]['East']
+        init_y = posdata.iloc[0]['North']
+
+        map_id = get_map_name(init_x, init_y, thqdata, gybdata, glytdata)
+
+        # 对感知数据进行后处理
+        # 对公园北环路进行坐标转换
+        if map_id == 0:
+            offset_x = offset_x_thq
+            offset_y = offset_y_thq
+        elif map_id == 1:
+            new_east, new_north = get_coordinate_cow(posdata)
+            posdata['East'] = new_east
+            posdata['North'] = new_north
+            offset_x = offset_x_gyb
+            offset_y = offset_y_gyb
+        else:
+            offset_x = offset_x_glyt
+            offset_y = offset_y_glyt
+
+        # 根据pos文件规范时间戳
+        posdata['Time'] = posdata['Time'].apply(lambda x: (x // 100) * 100)
+        # 绝对高程与相对高程的差值
+        posdata['altitude'] = posdata['altitude'] - 9.1
+
+        pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type']]
+        # pos_ego[['East', 'North']] = pos_ego.apply(get_coordinate_cow, axis=1)
+        # pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        pos_ego = pos_ego.reset_index(drop=True)
+        
+        # offset_x = -float(pos_ego.at[0, 'East'])  # 初始East 设为0
+        # offset_y = -float(pos_ego.at[0, 'North']) # 初始North 设为0
+
+        start_time = pos_ego.at[0, 'Time']
+        ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'East', 'North', 'HeadingAngle', 'altitude','Type', offset_x, offset_y, offset_h,start_time)
+        # ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'Type', offset_x, offset_y, offset_h, start_time)
+        
+        # 读取目标数据
+        pos_obs = posdata[posdata['Type'] != 10]  # 排除非目标物的物体
+        # pos_obs = posdata[posdata['Type'] != 10]  # 排除非目标物的物体
+        pos_obs = pos_obs.loc[pos_obs['ID'] != -1, ['Time', 'ID', 'East', 'North', 'HeadingAngle', 'AbsVel', 'altitude', 'Type']]
+        # pos_obs = pos_obs.loc[pos_obs['ID'] != -1, ['Time', 'ID', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        #!!!!自定义修改
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_y'] -= 2
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_y'] -= 1
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'type'] = 4
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_x'] = 456319
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_y'] = 4397979
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'HeadingAngle'] = 1
+        # offset_h = 30
+        # pos_obs.loc[pos_obs['ID'] == 1194, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1188, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1189, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1195, 'type'] = 2
+        # obsPath = os.path.join(absPath, 'obs.csv') # 用来筛选场景中不需要的他车
+        # obsdata = pd.read_csv(obsPath)
+        # obsdata = obsdata[(obsdata['ObjectPosY'] < 5) & (obsdata['ObjectPosY'] > -5) & (obsdata['ObjectPosX'] > -10) & (obsdata['ObjectPosX'] < 100)]  # 排除车道线范围外且前向距离较远的目标物
+        # idlist = obsdata['ObjectID'].tolist()  # 筛选出符合条件的的目标物ID
+        # pos_obs = pos_obs[(pos_obs['ID'].isin(idlist))]
+        pos_obs = pos_obs.reset_index(drop=True)
+        
+        groups = pos_obs.groupby('ID')
+        object_points = []
+        for key, value in groups:
+            if len(value) < 5:
+                continue
+            # value = smooth_1(value)
+            object_points.append(Scenario.getXoscPosition(value, 'Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type', offset_x, offset_y, offset_h,start_time))
+            # object_points.append(Scenario.getXoscPosition(value, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'type', offset_x, offset_y, offset_h,start_time))
+            
+        ego_speed = 5    
+        period = math.ceil(gps_time[-1] - gps_time[0])
+        work_mode = 0 # 0为CICV车端数据
+
+        hour = int(absPath.split('/')[-1].split('-')[3])
+        if hour + 8 >= 24:
+            hour = hour - 16
+        else:
+            hour = hour + 8
+        time_of_day = hour * 3600
+        # 没有路灯防止天过暗
+        if time_of_day >= 64800:
+            time_of_day = 64800
+        s = Scenario(ego_points, object_points, gps_time, ego_speed, work_mode, period, absPath, time_of_day, map_id)
+        filename = absPath + '/simulation'
+        files = s.generate(filename)
+        change_CDATA(files[0][0])
+        print(files)      
+        
+        # 生成osgb
+        # osgbGenerator.formatTwo(filename)
+        
+        # 修改xosc路径
+        # formatThree(filename)
+        # # # 生成每个场景的描述文件 json
+        # # getLabel(output_path, scenario_series['场景编号'], scenario_series['场景名称'])
+        
+        # 拷贝到vtd路径下
+        # vtd_path = os.path.join('/home/lxj/VIRES/VTD.2021.3/Data/Projects/Current/Scenarios/myScenario', datetime.now().strftime("%Y%m%d%H%M%S"))
+        # if not os.path.exists(vtd_path):
+        #     os.makedirs(vtd_path)
+        # os.system('cp '+ files[0][0] + ' ' + vtd_path + '/')
+        
+        
+    
+    def multiRun(self, path, param):  
+        files = self.getFile(path, self.keyFileName)
+        
+        print('程序开始，%s 个数据包' % len(files))
+        
+        t1 = time.time()
+        # 无参数时，使用所有cpu核;  有参数时，使用CPU核数量为参数值
+        pool = multiprocessing.Pool(processes = 10)
+        pfunc = partial(self.generateScenarios_raw, param)
+        pool.map(pfunc, files)
+        # 调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束
+        pool.close()
+        pool.join()
+        t2 = time.time()
+        print ("程序结束，并行执行时间：%s s" % int(t2 - t1))
+        
+    def batchRun(self, path, param):
+        files = self.getFile(path, self.keyFileName)
+        
+        print('程序开始，%s 个数据包' % len(files))    
+    
+        for di, absPath in enumerate(sorted(files)):
+            print(absPath)
+            # try:
+            self.generateScenarios_raw(absPath, param)
+            # except:
+            #     print('Augmentation failed!!!!')
+            #     error = {'time':datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],'traceback':traceback.format_exc()}
+            #     with open('error.log','a+') as f:
+            #         json.dump(error, f, indent=4)
+            #         f.write('\n')
+            # print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
+        return None
+
+    def GenerateVideo(self, root_path):
+        # 批量生成视频
+        imagelist = self.getFile(root_path, 'image')
+        for item in imagelist:
+            strs = item.split('/')
+            respath = os.path.join(item,"video.mp4")
+            # respath = os.path.join(res_path,strs[-3],strs[-2],"video.mp4")
+            print('---------------------')
+            # os.makedirs(os.path.join(res_path,strs[-3],strs[-2]))
+            command = "ffmpeg -f image2 -r 10 -pattern_type glob -i '" + item + "/image/*.jpg" + "' -y '" + respath + "'"
+            print(command)
+            process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+            process.wait()
+
+
+
+# if __name__ == "__main__":
+#     rootPath = "/home/hancheng/test_1116/data_merge_2023-11-21-14-15-25_overspeed_12"  #  跟车
+#
+#     # 生成场景
+#     a = Batchrun(rootPath, "pos.csv")
+#     a.batchRun(rootPath, 0) # 0为占位参数
+#     # a.multiRun(rootPath, 0)
+#
+#     # 生成视频
+#     # a.GenerateVideo(rootPath)
+
+############################### mlx #########################################
+
+if __name__ == "__main__":
+    rootPath = sys.argv[1]  # 跟车
+
+    # 生成场景
+    a = Batchrun(rootPath, "pos.csv")
+    a.batchRun(rootPath, 0)  # 0为占位参数
+    # a.multiRun(rootPath, 0)
+
+    # 生成视频
+    # a.GenerateVideo(rootPath)

archive/python3-pjiusv/20240102/simulation_new.py

@@ -0,0 +1,263 @@
+import os
+import math
+import sys
+
+import pandas as pd
+import subprocess
+import time
+import multiprocessing  # 导入进程模块
+from functools import partial  # 导入偏函数
+import warnings
+
+warnings.filterwarnings("ignore")
+from openx import Scenario, change_CDATA
+from utils import get_coordinate_cow, get_map_name, reverse_gyb_gps
+
+
+class Batchrun:
+    def __init__(self, path, keyFileName):
+        """"初始化方法"""
+        self.path = path
+        self.keyFileName = keyFileName
+
+    def getFile(self, path, keyFileName):
+        '''
+        获得可以进行轨迹提取的所有片段文件夹路径
+
+        Parameters
+        ----------
+        path : TYPE
+            DESCRIPTION.
+
+        Returns
+        -------
+        FileList : TYPE
+            可以进行轨迹提取的所有片段文件夹路径.
+
+        '''
+        files = os.listdir(path)  # 得到文件夹下的所有文件，包含文件夹名称
+
+        FileList = []
+        if keyFileName not in files:
+            for name in files:
+                if os.path.isdir(path + '/' + name):
+                    FileList.extend(self.getFile(path + '/' + name, keyFileName))  # 回调函数，对所有子文件夹进行搜索
+        else:
+            FileList.append(path)
+        FileList = list(set(FileList))
+
+        return FileList
+
+    def generateScenarios_raw(self, absPath, param):
+        '''
+        原始自然驾驶场景还原
+        '''
+
+        # 读取自车数据
+        posPath = os.path.join(absPath, 'pos.csv')  # 用来生成场景中自车和他车的路径
+        posdata = pd.read_csv(posPath)
+
+        # 读取仿真地图数据
+        offset_x_gyb = -446403.548
+        offset_y_gyb = -4403799.286
+        offset_x_thq = -456256.260152
+        offset_y_thq = -4397809.886833
+        offset_x_glyt = -457000
+        offset_y_glyt = -4400000
+        # offset_h = 90 # 初始headinga 和 VTD 有 90偏角
+        offset_h = 0
+
+        thqPath = '/root/rosmerge/resource/thq_path.csv'
+        thqdata = pd.read_csv(thqPath)
+        thqdata['posX'] -= offset_x_thq
+        thqdata['posY'] -= offset_y_thq
+
+        gybPath = '/root/rosmerge/resource/gybhl_path.csv'
+        gybdata = pd.read_csv(gybPath)
+        gybdata['posX'] -= offset_x_gyb
+        gybdata['posY'] -= offset_y_gyb
+        reverse_east, reverse_north = reverse_gyb_gps(gybdata)
+        gybdata['East'] = reverse_east
+        gybdata['North'] = reverse_north
+
+        glytPath = '/root/rosmerge/resource/glyt_path.csv'
+        glytdata = pd.read_csv(glytPath)
+        glytdata['posX'] -= offset_x_glyt
+        glytdata['posY'] -= offset_y_glyt
+
+        init_x = posdata.iloc[0]['East']
+        init_y = posdata.iloc[0]['North']
+
+        map_id = get_map_name(init_x, init_y, thqdata, gybdata, glytdata)
+
+        # 对感知数据进行后处理
+        # 对公园北环路进行坐标转换
+        if map_id == 0:
+            offset_x = offset_x_thq
+            offset_y = offset_y_thq
+        elif map_id == 1:
+            new_east, new_north = get_coordinate_cow(posdata)
+            posdata['East'] = new_east
+            posdata['North'] = new_north
+            offset_x = offset_x_gyb
+            offset_y = offset_y_gyb
+        else:
+            offset_x = offset_x_glyt
+            offset_y = offset_y_glyt
+
+        # 根据pos文件规范时间戳
+        posdata['Time'] = posdata['Time'].apply(lambda x: (x // 100) * 100)
+        # 绝对高程与相对高程的差值
+        posdata['altitude'] = posdata['altitude'] - 9.1
+
+        pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type']]
+        # pos_ego[['East', 'North']] = pos_ego.apply(get_coordinate_cow, axis=1)
+        # pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        pos_ego = pos_ego.reset_index(drop=True)
+
+        # offset_x = -float(pos_ego.at[0, 'East'])  # 初始East 设为0
+        # offset_y = -float(pos_ego.at[0, 'North']) # 初始North 设为0
+
+        start_time = pos_ego.at[0, 'Time']
+        ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'East', 'North', 'HeadingAngle',
+                                                                  'altitude', 'Type', offset_x, offset_y, offset_h,
+                                                                  start_time)
+        # ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'Type', offset_x, offset_y, offset_h, start_time)
+
+        # 读取目标数据
+        # pos_obs = posdata[posdata['Type'] != 10]  # 排除非目标物的物体
+        # pos_obs = posdata[posdata['Type'] != 10]  # 排除非目标物的物体
+        posdata['Type'].replace([103, 10], 7, inplace=True)
+        pos_obs = posdata.copy()
+        pos_obs = pos_obs.loc[
+            pos_obs['ID'] != -1, ['Time', 'ID', 'East', 'North', 'HeadingAngle', 'AbsVel', 'altitude', 'Type']]
+        # pos_obs = pos_obs.loc[pos_obs['ID'] != -1, ['Time', 'ID', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        # !!!!自定义修改
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_y'] -= 2
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_y'] -= 1
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'type'] = 4
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_x'] = 456319
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_y'] = 4397979
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'HeadingAngle'] = 1
+        # offset_h = 30
+        # pos_obs.loc[pos_obs['ID'] == 1194, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1188, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1189, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1195, 'type'] = 2
+        # obsPath = os.path.join(absPath, 'obs.csv') # 用来筛选场景中不需要的他车
+        # obsdata = pd.read_csv(obsPath)
+        # obsdata = obsdata[(obsdata['ObjectPosY'] < 5) & (obsdata['ObjectPosY'] > -5) & (obsdata['ObjectPosX'] > -10) & (obsdata['ObjectPosX'] < 100)]  # 排除车道线范围外且前向距离较远的目标物
+        # idlist = obsdata['ObjectID'].tolist()  # 筛选出符合条件的的目标物ID
+        # pos_obs = pos_obs[(pos_obs['ID'].isin(idlist))]
+        pos_obs = pos_obs.reset_index(drop=True)
+
+        groups = pos_obs.groupby('ID')
+        object_points = []
+        for key, value in groups:
+            if len(value) < 1:
+                continue
+            # value = smooth_1(value)
+            object_points.append(
+                Scenario.getXoscPosition(value, 'Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type', offset_x,
+                                         offset_y, offset_h, start_time))
+            # object_points.append(Scenario.getXoscPosition(value, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'type', offset_x, offset_y, offset_h,start_time))
+
+        ego_speed = 5
+        period = math.ceil(gps_time[-1] - gps_time[0])
+        work_mode = 0  # 0为CICV车端数据
+
+        hour = int(absPath.split('/')[-1].split('-')[3])
+        if hour + 8 >= 24:
+            hour = hour - 16
+        else:
+            hour = hour + 8
+        time_of_day = hour * 3600
+        # 没有路灯防止天过暗
+        if time_of_day >= 64800:
+            time_of_day = 64800
+        s = Scenario(ego_points, object_points, gps_time, ego_speed, work_mode, period, absPath, time_of_day, map_id)
+        filename = absPath + '/simulation'
+        print(filename)
+        files = s.generate(filename)
+        change_CDATA(files[0][0])
+        print(files)
+
+        # 生成osgb
+        # osgbGenerator.formatTwo(filename)
+
+        # 修改xosc路径
+        # formatThree(filename)
+        # # # 生成每个场景的描述文件 json
+        # # getLabel(output_path, scenario_series['场景编号'], scenario_series['场景名称'])
+
+        # 拷贝到vtd路径下
+        # vtd_path = os.path.join('/home/lxj/VIRES/VTD.2021.3/Data/Projects/Current/Scenarios/myScenario', datetime.now().strftime("%Y%m%d%H%M%S"))
+        # if not os.path.exists(vtd_path):
+        #     os.makedirs(vtd_path)
+        # os.system('cp '+ files[0][0] + ' ' + vtd_path + '/')
+
+    def multiRun(self, path, param):
+        files = self.getFile(path, self.keyFileName)
+
+        print('程序开始，%s 个数据包' % len(files))
+
+        t1 = time.time()
+        # 无参数时，使用所有cpu核;  有参数时，使用CPU核数量为参数值
+        pool = multiprocessing.Pool(processes=10)
+        pfunc = partial(self.generateScenarios_raw, param)
+        pool.map(pfunc, files)
+        # 调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束
+        pool.close()
+        pool.join()
+        t2 = time.time()
+        print("程序结束，并行执行时间：%s s" % int(t2 - t1))
+
+    def batchRun(self, path, param):
+        files = self.getFile(path, self.keyFileName)
+
+        print('程序开始，%s 个数据包' % len(files))
+
+        for di, absPath in enumerate(sorted(files)):
+            print(absPath)
+            # try:
+            self.generateScenarios_raw(absPath, param)
+            # except:
+            #     print('Augmentation failed!!!!')
+            #     error = {'time':datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],'traceback':traceback.format_exc()}
+            #     with open('error.log','a+') as f:
+            #         json.dump(error, f, indent=4)
+            #         f.write('\n')
+            # print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
+        return None
+
+    def GenerateVideo(self, root_path):
+        # 批量生成视频
+        imagelist = self.getFile(root_path, 'image')
+        for item in imagelist:
+            strs = item.split('/')
+            respath = os.path.join(item, "video.mp4")
+            # respath = os.path.join(res_path,strs[-3],strs[-2],"video.mp4")
+            print('---------------------')
+            # os.makedirs(os.path.join(res_path,strs[-3],strs[-2]))
+            command = "ffmpeg -f image2 -r 10 -pattern_type glob -i '" + item + "/image/*.jpg" + "' -y '" + respath + "'"
+            print(command)
+            process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+            process.wait()
+
+
+if __name__ == "__main__":
+    rootPath = sys.argv[1]  # 跟车
+
+    # 生成场景
+    a = Batchrun(rootPath, "pos.csv")
+    a.batchRun(rootPath, 0)  # 0为占位参数
+    # a.multiRun(rootPath, 0)
+
+    # 生成视频
+    # a.GenerateVideo(rootPath)
+
+# -*-ing:utf-8-*-

archive/python3-pjiusv/20240807/openx.py

@@ -0,0 +1,932 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar 14 15:44:01 2022
+
+@author: lxj
+"""
+import xml.etree.ElementTree as ET
+from scenariogeneration import xodr
+from scenariogeneration import xosc
+from scenariogeneration import ScenarioGenerator
+from scenariogeneration.xodr import RoadSide, Object, ObjectType, Dynamic, Orientation
+import math, os
+from xodr_generator2 import road_detector_new
+from datetime import datetime
+import traceback
+import json
+import pandas as pd
+from enum import Enum
+import elevation_0323 as el
+from xml.sax.saxutils import escape
+
+import warnings
+warnings.filterwarnings("ignore")
+#
+# #xodr_list = ['/home/hancheng/taiheqiao_map/thq_1116.xodr', '/home/hancheng/gongyuanbeihuan_map/OD/OpenDRIVE.xodr','/home/hancheng/glyt_map/OpenDRIVE/OpenDRIVE2.xodr']
+# #osgb_list = ['/home/hancheng/taiheqiao_map/thq_1116.opt.osgb', '/home/hancheng/gongyuanbeihuan_map/osgb/GJBM_20km_0822.opt.osgb', '/home/hancheng/glyt_map/OSGB/jinlong_20231129_2_guazai.opt.osgb']
+# xodr_list = ['/root/rosmerge/resource/thq.xodr', '/root/rosmerge/resource/OpenDRIVE.xodr','/root/rosmerge/resource/gelan.xodr']
+# osgb_list = ['/root/rosmerge/resource/thq.opt.osgb', '/root/rosmerge/resource/GJBM_20km_0822.opt.osgb', '/root/rosmerge/resource/gelan.opt.osgb']
+
+class Scenario(ScenarioGenerator):
+    def __init__(self, gps, obs, gps_time, ego_speed, work_mode, period, abspath, timeofday):
+        ScenarioGenerator.__init__(self)
+        self.gps = gps
+        self.obs = obs
+        self.gps_time = gps_time
+        self.ego_speed = ego_speed
+        self.work_mode = work_mode
+        self.period = period # 场景持续的时间
+        self.abspath = abspath
+        self.weather = xosc.PrecipitationType.dry  # 默认是晴天
+        self.visual_fog_range = 20000  # 正常的能见度，没有雾
+        self.time = 43200  # 强制为白天
+        # self.map_id = map_id
+        # self.ObjectID = ObjectID
+        # self.Speed = Speed
+        
+    def road(self, **kwargs):
+        positionEgo = self.gps
+        planview = xodr.PlanView()
+
+        nextx = positionEgo[0].x
+        nexty = positionEgo[0].y
+        h = float(positionEgo[0].h)
+
+        # for i in range(len(positionEgo) - 1):
+        #     x = 0.000001 if abs(positionEgo[i].x) < 0.000001 else positionEgo[i].x
+        #     y = 0.000001 if abs(positionEgo[i].y) < 0.000001 else positionEgo[i].y
+        #     nextx = 0.000001 if abs(positionEgo[i + 1].x) < 0.000001 else positionEgo[i + 1].x
+        #     nexty = 0.000001 if abs(positionEgo[i + 1].y) < 0.000001 else positionEgo[i + 1].y
+        #     h = float(positionEgo[i].h)
+        #
+        #     planview.add_fixed_geometry(xodr.Line(math.sqrt(math.pow(nextx - x, 2) + math.pow(nexty - y, 2))), x, y, h)
+
+        planview.add_fixed_geometry(xodr.Line(100), nextx, nexty, h)
+        # create two different roadmarkings
+        rm_solid = xodr.RoadMark(xodr.RoadMarkType.solid, 0.2)
+        rm_dashed = xodr.RoadMark(xodr.RoadMarkType.broken, 0.2)
+
+        # create simple lanes
+        lanes = xodr.Lanes()
+        lanesection1 = xodr.LaneSection(0, xodr.standard_lane(offset=1.75, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_left_lane(xodr.standard_lane(offset=3.5, rm=rm_solid))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_dashed))
+        lanesection1.add_right_lane(xodr.standard_lane(offset=3.5, rm=rm_solid))
+        lanes.add_lanesection(lanesection1)
+        lanes.add_laneoffset(xodr.LaneOffset(a=1.75))
+
+        road = xodr.Road(0, planview, lanes)
+        odr = xodr.OpenDrive('myroad')
+        # 静态元素
+        tree = ET.parse(os.getcwd() + '/models/static_object_models.xodr')
+        root = tree.getroot()
+        objects_dict = root.iter(tag='object')
+        road = create_static_object(road, objects_dict)
+
+        # road = create_static_object(road, object_id=0, object_type=ObjectType.railing, repeat_flag=1)
+        odr.add_road(road)
+        odr.adjust_roads_and_lanes()
+        return odr
+    
+    def get_section(self, left_lanemark):
+        
+        return None
+        
+    
+    def split_road_section(self, enu_file, lane_file):
+        lane_content = pd.read_csv(lane_file)
+        # 把车道分割开来，一个车道段，多种geometry
+        # 首先判断车道线数值是否有断裂，断裂处根据自车轨迹生成道路参数
+        left_lanemark = lane_content[lane_content['LaneID'] == 1][['Time','FrameID','LanePosition','LaneQuality']]
+        right_lanemark = lane_content[lane_content['LaneID'] == 2][['Time','FrameID','LanePosition','LaneQuality']]
+        
+        left_break_section = self.get_section(left_lanemark, 1)
+        right_break_section = self.get_section(right_lanemark, 1)
+        break_section = []
+        normal_section = []
+        
+        # 判断是否变道，然后判断是否弯道
+        
+        
+        # 最终目标是得到多个geometry参数，确定每个连接线处的s/t偏移量?，以及左右道路的个数和宽度
+        
+        
+        return None
+    
+    def check_outliers_and_modify(self, datalist):
+        for index in datalist.index:
+            if index < 3:
+                datalist.loc[index] = datalist[index] if abs(datalist[index] - datalist[index + 1:index + 3].mean()) < 0.5 else 2 * datalist[index + 1] - datalist[index + 1:index + 3].mean()
+            elif 3 <= index < len(datalist) - 3:
+                datalist.loc[index] = datalist[index] if abs(datalist[index] - datalist[index + 1:index + 3].mean()) < 0.5 or abs(datalist[index] - datalist[index - 3:index].mean()) < 0.5 else (datalist[index - 1] + datalist[index + 1]) / 2
+            else:
+                datalist.loc[index] = datalist[index] if abs(datalist[index] - datalist[index - 3:index].mean()) < 0.5 else 2 * datalist[index - 1] - datalist[index - 3:index].mean()
+        return datalist
+    
+   
+    def get_new_LaneID(self, change_flag, laneID, frameid, item):
+        '''
+        修改laneID，change_list包含了每个变道片段
+
+        '''
+        if item[0] <= frameid < item[1]:
+            return laneID + change_flag
+        else:
+            return laneID
+        
+    def get_lane_width(self, data1, data2):
+        lane_union = pd.merge(data1, data2, on=['FrameID'])
+        lane_union['width'] = lane_union['LanePosition_y'] - lane_union['LanePosition_x']
+        a = lane_union["width"].quantile(0.75)
+        b = lane_union["width"].quantile(0.25)
+        lane_width = abs((a + b) / 2)
+        return lane_width
+    
+    def road_pre_study(self, label_file, lane_file):
+        laneDF = pd.read_csv(lane_file)
+        road_label = ''
+        flag = 0 # flag = 0 can use road_ego to generate .xodr, flag = 1 better use road to generate .xodr
+        with open(label_file) as f:
+            label = json.load(f)
+            
+            ego_actions = label['自车行为']
+            for item in ego_actions:
+                if ('变道' in item['type_']) or ('转成功' in item['type_']) or ('掉头' in item['type_']):
+                    road_label = item['type_']
+                    flag = 1
+                    break
+                else:
+                    road_label = item['type_']
+        
+        if road_label == '向左变道成功':
+            # 查找变道标记点
+            change_flag = 1
+            lane_1 = laneDF[(laneDF['LaneID'] == 1) & (laneDF['LaneQuality'] > 1)]
+            lane_1 = lane_1.reset_index(drop=True)
+            leftlanepositon = lane_1['LanePosition']
+            lane_1['LanePosition'] = self.check_outliers_and_modify(leftlanepositon)
+            lane_1['last_Position'] = lane_1[['LanePosition']].shift(axis = 0, periods = 1) #axis指定移动的轴：0为行,1为列
+            lane_1['last_FrameID'] = lane_1[['FrameID']].shift(axis = 0, periods = 1) #axis指定移动的轴：0为行,1为列
+            lane_1['change_flag'] = lane_1.apply(lambda x: change_flag if (x['LanePosition'] - x['last_Position'] <= -3) and (x['FrameID'] - x['last_FrameID'] == 1) else 0, axis=1) # 默认情况下 axis=0 表示按列，axis=1 表示按行。
+            lane_1['split_flag'] = lane_1.apply(lambda x: 99 if x['FrameID'] - x['last_FrameID'] > 1 else 0, axis=1)
+            
+            lane_2 = laneDF[(laneDF['LaneID'] == 2) & (laneDF['LaneQuality'] > 1)]
+            lane_2 = lane_2.reset_index(drop=True)
+            rightlanepositon = lane_2['LanePosition']
+            lane_2['LanePosition'] = self.check_outliers_and_modify(rightlanepositon)
+            lane_2['last_Position'] = lane_2[['LanePosition']].shift(axis = 0, periods = 1) #axis指定移动的轴：0为行,1为列
+            lane_2['last_FrameID'] = lane_2[['FrameID']].shift(axis = 0, periods = 1) #axis指定移动的轴：0为行,1为列
+            lane_2['change_flag'] = lane_2.apply(lambda x: change_flag if (x['LanePosition'] - x['last_Position'] <= -3) and (x['FrameID'] - x['last_FrameID'] == 1) else 0, axis=1) # 默认情况下 axis=0 表示按列，axis=1 表示按行。
+            lane_2['split_flag'] = lane_2.apply(lambda x: 99 if x['FrameID'] - x['last_FrameID'] > 1 else 0, axis=1)
+            
+            lane_width = self.get_lane_width(lane_1[['FrameID','LanePosition']], lane_2[['FrameID','LanePosition']])
+            # 左变道用左车道线数据靠谱，不会有他车遮挡，找到变道数据段
+            change_lane_point = list(lane_1[lane_1['change_flag'] == change_flag]['change_flag'].index) + [list(lane_1.index)[-1]]
+            change_lane_section = [(lane_1.loc[change_lane_point[i], 'FrameID'], lane_1.loc[change_lane_point[i+1], 'FrameID']) for i in range(len(change_lane_point)-1)]
+            
+            for item in change_lane_section:
+                # 变道后修改原始laneID
+                # laneDF['LaneID'] = laneDF.apply(lambda x: x['LaneID'] - change_flag if item[0] <= x['FrameID'] < item[1] else x['LaneID'], axis=1)
+                # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition'] - change_flag * lane_width if item[0] <= x['FrameID'] < item[1] else x['LanePosition'], axis=1)
+                # laneDF['LaneID'] = laneDF.apply(lambda x: x['LaneID'] - change_flag if x['FrameID'] == max(laneDF['FrameID']) else x['LaneID'], axis=1)
+                # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition'] - change_flag * lane_width if x['FrameID'] == max(laneDF['FrameID']) else x['LanePosition'], axis=1)
+                
+                # 修正左左车道线和右右车道线数值
+                if change_flag == 1:
+                    lane_0 = laneDF[(laneDF['LaneID'] == 0) & (laneDF['LaneQuality'] > 1) & (laneDF['FrameID'] < item[0])]
+                    if not lane_0.empty:
+                        left_lane_width = self.get_lane_width(lane_0[['FrameID','LanePosition']], lane_1[['FrameID','LanePosition']])
+                    else:
+                        left_lane_width = lane_width
+                    print(left_lane_width)
+                    # new_lane_1 = laneDF[laneDF['LaneID'] == 1][['FrameID','LanePosition']]
+                    # new_lane_1.rename(columns={'LanePosition':'LanePosition2'},inplace=True)
+                    # laneDF = pd.merge(laneDF, new_lane_1, on=['FrameID'])
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if (item[0] <= x['FrameID'] < item[1]) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if x['FrameID'] == max(laneDF['FrameID']) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+                    
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if (item[0] <= x['FrameID'] < item[1]) and (x['LaneID'] == -1) else x['LanePosition'], axis=1)
+                    # laneDF['LanePosition'] = laneDF.apply(lambda x: x['LanePosition2'] - left_lane_width if x['FrameID'] == max(laneDF['FrameID']) and (x['LaneID'] == 0) else x['LanePosition'], axis=1)
+                    # laneDF['LaneID'] = laneDF.apply(lambda x: 3 if x['LaneID'] == -1 else x['LaneID'], axis=1)
+                # 缺右车道线right_lane_width处理
+                
+                print(laneDF[laneDF['FrameID']>1860][['FrameID', 'LaneID', 'LanePosition']].head(50))
+        print('road_label: ', road_label)
+        
+        
+        return laneDF
+        
+    def road_new(self, **kwargs):
+        polyfit_fig_path = os.path.join(self.abspath, 'simulation','polyfit.jpg')
+    
+        # run road detector
+        enu_file = os.path.join(self.abspath, 'pos.csv')
+        lane_file = os.path.join(self.abspath, 'lane.csv')
+        label_file = os.path.join(self.abspath, 'label.json')
+        
+        # study road style: straight\curve\split-line; ego action: change-lane\no-change\cross-turn
+        lane_content = self.road_pre_study(label_file, lane_file)
+        
+        # road split sections
+        # self.split_road_section(enu_file, lane_file)
+        
+        try:
+            laneid_tuple = [0, 1, 2, 3]
+            uv_coord_info, road_info, left_lane_info, right_lane_info = road_detector_new(enu_file, lane_content, laneid_tuple, polyfit_fig_path)
+        except:
+            print('road detection failed!!!!  Use ego trail road.')
+            error = {'time':datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],'traceback':traceback.format_exc()}
+            with open('error.log','a+') as f:
+                json.dump(error, f, indent=4)
+                f.write('\n')
+            return self.road_ego()
+            
+        origin_x = uv_coord_info[0]
+        origin_y = uv_coord_info[1]
+        uv_coord_hdg = uv_coord_info[2]
+    
+        reference_line_offset = road_info[0]
+        model_u = road_info[1] # in fomrat [c3, c2, c1, c0]
+        model_v = road_info[2] # in fomrat [c3, c2, c1, c0]
+        road_length = road_info[3]
+        print(uv_coord_info)
+        print(road_info)
+        # generate xodr file
+        planview = xodr.PlanView(origin_x, origin_y, uv_coord_hdg)
+        
+        # Create geometry and add it to the planview 
+        # parampoly3 = xodr.ParamPoly3(au=model_u[3], bu=model_u[2], cu=model_u[1], du=model_u[0], av=model_v[3], bv=model_v[2], cv=model_v[1], dv=model_v[0], prange='arcLength',length=road_length)
+        parampoly3 = xodr.ParamPoly3(au=0, bu=model_u[2], cu=model_u[1], du=model_u[0], av=0, bv=model_v[2], cv=model_v[1], dv=model_v[0], prange='arcLength',length=road_length)
+        planview.add_geometry(parampoly3)
+        
+        # create two different roadmarkings
+        rm_solid = xodr.RoadMark(xodr.RoadMarkType.solid,0.2)
+        rm_dashed = xodr.RoadMark(xodr.RoadMarkType.broken,0.2,laneChange=xodr.LaneChange.both)
+        
+        ##4. Create centerlane 
+        centerlane = xodr.Lane(a=reference_line_offset)
+        centerlane.add_roadmark(rm_dashed)
+        
+        ##5. Create lane section form the centerlane
+        lanesec = xodr.LaneSection(0,centerlane)
+        
+        ##6. Create left and right lanes
+        lane_id = 0
+        for lane in left_lane_info:
+            lane_id += 1
+            lane_width = lane[0]
+            spd_limit = lane[1]
+            lane_left = xodr.Lane(a=lane_width)
+            lane_left.add_roadmark(rm_dashed)
+            # Add lanes to lane section 
+            lanesec.add_left_lane(lane_left)
+        
+        lane_id = 0
+        for lane in right_lane_info:
+            lane_id -= 1
+            lane_width = lane[0]
+            spd_limit = lane[1]  
+            lane_right = xodr.Lane(a=lane_width)
+            lane_right.add_roadmark(rm_dashed)
+            # Add lanes to lane section 
+            lanesec.add_right_lane(lane_right)
+        
+        ##8. Add lane section to Lanes 
+        lanes = xodr.Lanes()
+        lanes.add_laneoffset(xodr.LaneOffset(s = 0, a=reference_line_offset))
+        lanes.add_lanesection(lanesec)
+        
+        
+        ##9. Create Road from Planview and Lanes
+        road = xodr.Road(1,planview,lanes)
+        
+        ##10. Create the OpenDrive class (Master class)
+        odr = xodr.OpenDrive('myroad')
+        
+        ##11. Finally add roads to Opendrive 
+        odr.add_road(road)
+        
+        ##12. Adjust initial positions of the roads looking at succ-pred logic 
+        odr.adjust_roads_and_lanes()
+        
+        # ##13. Print the .xodr file
+        # xodr.prettyprint(odr.get_element())
+        
+        # ##14. Run the .xodr with esmini 
+        # xodr.run_road(odr,os.path.join('..','pyoscx','esmini'))
+        
+        return odr
+    
+    def getXoscPosition(egodata, t, e, n, h, z, obj_type, offset_x, offset_y, offset_h, start_time):
+        '将dataframe的轨迹转换为场景文件的轨迹数据, Time, ego_e, ego_n, headinga'
+
+        position = []
+        time = []
+        # cur_time = 0.0
+        egodata = egodata[[t, e, n, h, z, obj_type]]
+        egodata = egodata.reset_index(drop=True)
+        # egodata[t] = egodata.index / 10
+        egodata[t] = (egodata[t] - start_time) / 1000
+        egodata[e] = egodata[e] + offset_x
+        egodata[n] = egodata[n] + offset_y
+        egodata[h] = egodata[h] + offset_h
+        egodata[h] = egodata.apply(lambda x: x[h] if x[h] < 360 else x[h] - 360, axis=1)
+        type_list = list(egodata[obj_type])
+        ego_type = int(max(type_list, key=type_list.count))
+        
+        lasth = float(egodata.at[0, h])
+        init_flag = True
+    
+        # two method to set z value
+        zflag = 0 # 1
+        if zflag:
+            # 根据地图的xy值计算z值
+            zfile = '/home/hancheng/weihao/gongyuanbei_elevation.csv'
+            # zfile = '/home/hancheng/simulation_dynamic/elevation_df_taiheqiao.csv'
+            zdata = pd.read_csv(zfile)
+
+            for row in egodata.iterrows():
+                hhh = math.radians(row[1][h])
+                xodr_z = el.cal_elevation(zdata, float(row[1][e]), float(row[1][n]))
+                if init_flag:
+                    position.append(xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=xodr_z, h=hhh, p=0, r=0))
+                    init_flag = False
+                else:
+                    if float(row[1][h]) - lasth > 300:
+                        hhh = math.radians(float(row[1][h]) - 360)
+                    elif float(row[1][h]) - lasth < -300:
+                        hhh = math.radians(float(row[1][h]) + 360)
+                    position.append(xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=xodr_z, h=hhh, p=0, r=0))
+                    lasth = float(row[1][h])
+                time.append(float(row[1][t]))
+                # time.append(cur_time)
+                # cur_time += 0.1
+            return position, time, ego_type
+        else:
+            # z = 0
+            for row in egodata.iterrows():
+                hhh = math.radians(row[1][h])
+                if init_flag:
+                    position.append(xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=float(row[1][z]), h=hhh, p=0, r=0))
+                    init_flag = False
+                else:
+                    if float(row[1][h]) - lasth > 300:
+                        hhh = math.radians(float(row[1][h]) - 360)
+                    elif float(row[1][h]) - lasth < -300:
+                        hhh = math.radians(float(row[1][h]) + 360)
+                    position.append(xosc.WorldPosition(x=float(row[1][e]), y=float(row[1][n]), z=float(row[1][z]), h=hhh, p=0, r=0))
+                    lasth = float(row[1][h])
+                time.append(float(row[1][t]))
+                # time.append(cur_time)
+                # cur_time += 0.1
+            return position, time, ego_type
+
+    def scenario(self, **kwargs):
+        road = xosc.RoadNetwork(roadfile='/root/rosmerge/resource/OpenDRIVE2_add_stop_line_marking_20231229.xodr', scenegraph='/root/rosmerge/resource/jinlong_all_addtrafficlight_20240226_5_guazai_2.opt.osgb')
+        catalog = xosc.Catalog()
+        catalog.add_catalog('VehicleCatalog', 'Distros/Current/Config/Players/Vehicles')
+        catalog.add_catalog('PedestrianCatalog', 'Distros/Current/Config/Players/Pedestrians')
+        catalog.add_catalog('MiscObjectCatalog', 'Distros/Current/Config/Players/Objects')
+        catalog.add_catalog('ControllerCatalog', 'Distros/Current/Config/Players/driverCfg.xml')
+
+        pbb = xosc.BoundingBox(0.5, 0.5, 1.8, 2.0, 0, 0.9)
+        mbb = xosc.BoundingBox(1, 2, 1.7, 1.5, 0, 0.9)
+        bb = xosc.BoundingBox(2.1, 4.5, 1.8, 1.5, 0, 0.9)
+        bus_bb = xosc.BoundingBox(2.55, 10.5, 3.1, 5.1, 0, 1.45)
+        bus_fa = xosc.Axle(0.48, 0.91, 2.5, 4.5, 1.5)
+        bus_ba = xosc.Axle(0, 0.91, 2.5, 4.5, 1.5)
+        truck_bb = xosc.BoundingBox(2.8, 8.744, 3.78, 4.372, 0, 1.89)
+        truck_fa = xosc.Axle(0.48, 1, 2.8, 4.372, 1.5)
+        truck_ba = xosc.Axle(0, 1, 2.8, 4.372, 1.5)
+        fa = xosc.Axle(0.5, 0.6, 1.8, 3.1, 0.3)
+        ba = xosc.Axle(0, 0.6, 1.8, 0, 0.3)
+        cone_bb = xosc.BoundingBox(0.5, 0.5, 1.0, 2.0, 0, 0.9)
+
+        red_veh = xosc.Vehicle('Audi_A3_2009_black', xosc.VehicleCategory.car, bb, fa, ba, 69.444, 200, 10)
+        red_veh.add_property(name='control', value='external')
+        segway = xosc.Vehicle('Segway', xosc.VehicleCategory.car, pbb, fa, ba, 69.444, 200, 10)
+        segway.add_property(name='control', value='external')
+        white_veh = xosc.Vehicle('Audi_A3_2009_red', xosc.VehicleCategory.car, bb, fa, ba, 69.444, 200, 10)
+        male_ped = xosc.Pedestrian('Christian', 'male_adult', 70, xosc.PedestrianCategory.pedestrian, pbb)
+        motorcycle = xosc.Vehicle('Kawasaki_ZX-9R_black', xosc.VehicleCategory.motorbike, mbb, fa, ba, 69.444, 200, 10)
+        motorcycle.add_property(name='control', value='external')
+        truck = xosc.Vehicle('MANTGS_11_Black', xosc.VehicleCategory.truck, truck_bb, truck_fa,
+                             truck_ba, 26.4, 10, 10)
+        bus = xosc.Vehicle('MercedesTravego_10_ArcticWhite', xosc.VehicleCategory.bus, bus_bb, bus_fa, bus_ba, 29, 10,
+                           10)
+        cone = xosc.MiscObject('RdMiscPylon03-32cm', 10, xosc.MiscObjectCategory.obstacle, cone_bb)
+
+        prop = xosc.Properties()
+        cnt = xosc.Controller('DefaultDriver', prop)
+        cnt2 = xosc.Controller('No Driver', prop)
+
+        # 添加自车实体
+        egoname = 'Ego'
+        entities = xosc.Entities()
+        entities.add_scenario_object(egoname, segway, cnt)
+
+        # 添加目标车实体
+        objname = 'Player'
+        ped_type, car_type, bicycle_motor_type, bus_type, truct_type, cone_type = get_obj_type(self.work_mode)
+        positionEgo = self.gps
+        positionObj = self.obs
+        for i, row in enumerate(positionObj):
+            if len(row[1]) < 1:
+                continue
+            obj_type = row[2]  # 根据目标物类型添加对应的实体
+
+            if obj_type in ped_type:
+                entities.add_scenario_object(objname + str(i), male_ped)
+            elif obj_type in car_type:
+                entities.add_scenario_object(objname + str(i), white_veh, cnt2)
+            elif obj_type in bicycle_motor_type:
+                entities.add_scenario_object(objname + str(i), motorcycle, cnt2)
+            elif obj_type in bus_type:
+                entities.add_scenario_object(objname + str(i), bus, cnt2)
+            elif obj_type in truct_type:
+                entities.add_scenario_object(objname + str(i), truck, cnt2)
+            elif obj_type in cone_type:
+                entities.add_scenario_object(objname + str(i), cone)
+
+        # 初始化
+        init = xosc.Init()
+        step_time = xosc.TransitionDynamics(xosc.DynamicsShapes.step, xosc.DynamicsDimension.time, 0)
+        egospeed = xosc.AbsoluteSpeedAction(self.ego_speed, step_time)
+
+        # 设置初始环境要素，例如天气时间等
+        default_precipitation = xosc.PrecipitationType.dry
+        default_cloudstate = xosc.CloudState.free
+
+        # json_path = os.path.join(self.abspath, 'label.json')
+        # with open(json_path, 'r', encoding='utf-8') as f:
+        #     sc_json = json.load(f)
+        #     weather = sc_json['天气情况'][0]['type_'] #['自然环境']
+        #     if weather == '晴':
+        #         f.close()
+        #     elif weather == '多云':
+        #         default_cloudstate = xosc.CloudState.cloudy
+        #     elif weather == '阴':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #     elif weather == '雨':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #         default_precipitation = xosc.PrecipitationType.rain
+        #     elif weather == '雪':
+        #         default_cloudstate = xosc.CloudState.overcast
+        #         default_precipitation = xosc.PrecipitationType.snow
+        #     elif weather == '雾霾' or weather == '沙尘':
+        #         self.visual_fog_range = 700
+        #         default_cloudstate = xosc.CloudState.cloudy
+
+        init.add_global_action(
+            xosc.EnvironmentAction(name="InitEnvironment", environment=xosc.Environment(
+                xosc.TimeOfDay(True, 2019, 12, 19, 12, 0, 0),
+                xosc.Weather(
+                    sun_intensity=2000, sun_azimuth=40, sun_elevation=20,
+                    cloudstate=default_cloudstate,
+                    precipitation=default_precipitation,
+                    precipitation_intensity=1,
+                    visual_fog_range=self.visual_fog_range),
+                xosc.RoadCondition(friction_scale_factor=0.7))))
+
+
+        # ego car init
+        ego_init_h = positionEgo[0].h
+        init.add_init_action(egoname, xosc.TeleportAction(
+            xosc.WorldPosition(x=positionEgo[0].x, y=positionEgo[0].y, z=positionEgo[0].z, h=ego_init_h, p=0, r=0)))
+        init.add_init_action(egoname, egospeed)
+
+        # ego car trail
+        trajectory = xosc.Trajectory('egoTrajectory', False)
+        polyline = xosc.Polyline(self.gps_time, positionEgo)
+        trajectory.add_shape(polyline)
+
+        speedaction = xosc.FollowTrajectoryAction(trajectory, xosc.FollowMode.position, xosc.ReferenceContext.absolute,
+                                                  1, 0)
+        trigger = xosc.ValueTrigger('drive_start_trigger', 0, xosc.ConditionEdge.rising,
+                                    xosc.SimulationTimeCondition(0, xosc.Rule.greaterThan))
+        trigger_init = xosc.ValueTrigger(name='init_trigger', delay=0, conditionedge=xosc.ConditionEdge.rising,
+                                         valuecondition=xosc.SimulationTimeCondition(value=0,
+                                                                                     rule=xosc.Rule.greaterThan))
+
+        event_init = xosc.Event('Event_init', xosc.Priority.overwrite)
+        action_light = xosc.CustomCommandAction(0, 0, 0, 0, 1, 0, 0)
+        light_flag = 'auto'
+        if self.time == 64800:
+            light_flag = 'true'
+        text = f'<Environment><TimeOfDay headlights="{light_flag}" timezone="8" value="{self.time}" /></Environment>'
+        node = ET.Element("CustomCommandAction")
+        node.attrib = {'type': 'scp'}
+        node.text = f"<![CDATA[\n{text}]\n]>"
+        action_light.add_element(node)
+        event_init.add_action('headlight', action_light)
+        event_init.add_trigger(trigger_init)
+
+        event = xosc.Event('Event1', xosc.Priority.overwrite)
+        event.add_trigger(trigger)
+        event.add_action('newspeed', speedaction)
+        man = xosc.Maneuver('my maneuver')
+        man.add_event(event_init)
+        man.add_event(event)
+
+        mangr = xosc.ManeuverGroup('mangroup', selecttriggeringentities=True)
+        mangr.add_actor('Ego')
+        mangr.add_maneuver(man)
+
+        trigger0 = xosc.Trigger('start')
+        act = xosc.Act('Act1', trigger0)
+        act.add_maneuver_group(mangr)
+
+        ego_story = xosc.Story('mystory_ego')
+        ego_story.add_act(act)
+
+        stop_trigger = xosc.ValueTrigger('stop_trigger', 0, xosc.ConditionEdge.none,
+                                         xosc.SimulationTimeCondition(self.period, xosc.Rule.greaterThan), 'stop')
+        sb = xosc.StoryBoard(init, stoptrigger=stop_trigger)
+        sb.add_story(ego_story)
+
+        # object car trail
+        if positionObj:
+            for i, row in enumerate(positionObj):
+                name = objname + str(i)
+                if len(row[1]) < 2:
+                    continue
+                obj_type = row[2]
+                # 根据目标车需要动态创建实体
+                x = row[0][0].x
+                y = row[0][0].y
+                z = row[0][0].z
+                h = row[0][0].h
+                start_time = row[1][0]
+                init_position = xosc.WorldPosition(x=x, y=y, z=z, h=h, p=0, r=0)
+                newentity = xosc.AddEntityAction(name, init_position)
+                newentity_trigger = xosc.ValueTrigger(name='newentity_trigger', delay=0,
+                                                      conditionedge=xosc.ConditionEdge.rising,
+                                                      valuecondition=xosc.SimulationTimeCondition(value=start_time,
+                                                                                                  rule=xosc.Rule.greaterThan))
+                newentity_event = xosc.Event('Event_newentity', xosc.Priority.overwrite)
+                newentity_event.add_trigger(newentity_trigger)
+                newentity_event.add_action('newentity_action', newentity)
+                man_obj = xosc.Maneuver('my maneuver')
+                man_obj.add_event(newentity_event)
+                if obj_type != 103:
+                    # 添加目标车轨迹
+                    trajectoryM = xosc.Trajectory('objectTrajectory', False)
+                    polylineM = xosc.Polyline(row[1], row[0])
+                    trajectoryM.add_shape(polylineM)
+                    obj_trail_action = xosc.FollowTrajectoryAction(trajectory=trajectoryM,
+                                                                   following_mode=xosc.FollowMode.position,
+                                                                   reference_domain=xosc.ReferenceContext.absolute,
+                                                                   scale=1, offset=0, initialDistanceOffset=0)
+
+                    obj_trail_event = xosc.Event('Event1', xosc.Priority.overwrite)
+                    # obj_start_trigger = xosc.EntityTrigger("obj-start-trigger", 0, xosc.ConditionEdge.rising, xosc.SpeedCondition(0, xosc.Rule.greaterThan),'Ego')
+                    obj_start_trigger = xosc.ValueTrigger('obj_start_trigger', 0, xosc.ConditionEdge.rising,
+                                                          xosc.SimulationTimeCondition(start_time, xosc.Rule.greaterThan))
+                    obj_trail_event.add_trigger(obj_start_trigger)
+                    obj_trail_event.add_action('trail_action', obj_trail_action)
+                    # if obj_type in ped_type:
+                    # walp_trigger =  xosc.EntityTrigger('ped_walp_trigger', 0, xosc.ConditionEdge.rising,\
+                    # xosc.TimeToCollisionCondition(self.intersectime, xosc.Rule.lessThan, entity=name), 'Ego')
+                    # obj_trail_event.add_trigger(walp_trigger)
+
+                    man_obj.add_event(obj_trail_event)
+
+                    # 行人特有的事件
+                    if obj_type in ped_type:
+                        ped_event = xosc.Event('Event_ped', xosc.Priority.overwrite)
+                        ped_event.add_trigger(obj_start_trigger)
+                        ped_action = xosc.CustomCommandAction(0, 0, 0, 0, 1, 0, 0)
+                        ped_action.add_element(self.createUDAction(name))
+                        ped_event.add_action('ped_trail_action', ped_action)
+                        man_obj.add_event(ped_event)
+
+                        # finish_trigger = xosc.EntityTrigger('finish_trigger', 0, xosc.ConditionEdge.rising, xosc.ReachPositionCondition(position=row[1][0],tolerance=1),name)
+                        # event4 = xosc.Event('Event_ped',xosc.Priority.overwrite)
+                        # event4.add_trigger(finish_trigger)
+                        # be_still_action = xosc.AbsoluteSpeedAction(0, xosc.TransitionDynamics(xosc.DynamicsShapes.step, xosc.DynamicsDimension.time, 1))
+                        # event4.add_action('ped_be_still_action',be_still_action)
+                        # man_obj.add_event(event4)
+
+
+                # 轨迹最后删除实体
+                last_time = row[1][-1]
+                del_action = xosc.DeleteEntityAction(name)
+                del_trigger = xosc.ValueTrigger(name='entity_del_trigger', delay=0,
+                                                conditionedge=xosc.ConditionEdge.rising,
+                                                valuecondition=xosc.SimulationTimeCondition(value=last_time,
+                                                                                            rule=xosc.Rule.greaterThan))
+                del_event = xosc.Event('Event_del', xosc.Priority.overwrite)
+                del_event.add_trigger(del_trigger)
+                del_event.add_action('del_action', del_action)
+                man_obj.add_event(del_event)
+
+                obj_mangroup = xosc.ManeuverGroup('mangroup', selecttriggeringentities=True)
+                obj_mangroup.add_actor(name)
+                obj_mangroup.add_maneuver(man_obj)
+
+                obj_act = xosc.Act('Act2', trigger0)
+                obj_act.add_maneuver_group(obj_mangroup)
+
+                obj_story = xosc.Story('mystory_' + name)
+                obj_story.add_act(obj_act)
+
+                sb.add_story(obj_story)
+
+        # prettyprint(sb.get_element())
+
+        paramet = xosc.ParameterDeclarations()
+
+        sce = xosc.Scenario('my scenario', 'Maggie', paramet, entities, sb, road, catalog)
+        return sce
+    
+    def createUDAction(self, name):
+        # tree = ET.parse('./models/ped_CDATA.xosc')
+        # root = tree.getroot()
+        # ele = root[5][2][1][0][1][1][0][0][0]
+        # newnode = ET.Element("CustomCommandAction")
+        # newnode.attrib = {'type': 'scp'}
+        # newnode.text = '<![CDATA[\n' + ele.text + ']\n]>'
+        speed = 3
+        motion = 'walk'
+        # text = f'<Traffic>\n     <ActionMotion actor="{name}" move="{motion}" speed="{speed}" force="false" ' \
+        #        f'rate="0" delayTime="0.0" activateOnExit="false"/>\n</Traffic>'
+        text = '<Traffic>\n     <ActionMotion actor="{}" move="{}" speed="{}" force="false" \
+               rate="0" delayTime="0.0" activateOnExit="false"/>\n</Traffic>'.format(name, motion, speed)
+        # text = '&lt;Traffic&gt;     &lt;ActionMotion actor=&quot;Player0&quot; move=&quot;walk&quot; speed=&quot;3&quot; force=&quot;false&quot;rate=&quot;0&quot; delayTime=&quot;0.0&quot; activateOnExit=&quot;false&quot;/&gt;&lt;/Traffic&gt;'.format(name, motion, speed)
+        newnode = ET.Element("CustomCommandAction")
+        newnode.attrib = {'type': 'scp'}
+        newnode.text = "<![CDATA[\n{}]\n]>".format(text)
+        return newnode
+
+class WorkMode(Enum):
+    cicv = 0  # CICV车端
+    roadside = 1  # 车网路端
+    car = 2  # 车网车端
+    merge = 3  # 车网车端路端融合
+    
+def get_obj_type(mode):
+    if mode == WorkMode.cicv.value:
+        # CICV车端
+        ped_type = [7]
+        car_type = [2]
+        bicycle_motor_type = [8]
+        bus_type = [3]
+        truct_type = [4]
+        cone_type = [103]
+    elif mode == WorkMode.roadside.value:
+        # 车网路端
+        ped_type = [0]
+        car_type = [2]
+        bicycle_motor_type = [1, 3]
+        bus_type = [5]
+        truct_type = [7]
+        cone_type = [103]
+    elif mode == WorkMode.car.value:
+        # 车网车端
+        ped_type = [1]
+        car_type = [6]
+        bicycle_motor_type = [2, 3, 4, 5]
+        bus_type = [7, 8]
+        truct_type = [9]
+        cone_type = [103]
+    else:
+        # 车网车端路端融合
+        ped_type = [1]
+        car_type = [6]
+        bicycle_motor_type = [2, 3, 4, 5]
+        bus_type = [7, 8]
+        truct_type = [9]
+        cone_type = [103]
+    return ped_type, car_type, bicycle_motor_type, bus_type, truct_type, cone_type
+
+# 创建道路旁静止的场景
+def create_static_object(road, object_dict):
+    for single_object in object_dict:
+        for k, v in ObjectType.__members__.items():
+            if k == single_object.attrib['type']:
+                single_object.attrib['type'] = v
+                break
+
+        road_object = Object(
+            s=single_object.attrib['s'],
+            t=single_object.attrib['t'],
+            Type=single_object.attrib['type'],
+            dynamic=Dynamic.no,
+            id=single_object.attrib['id'],
+            name=single_object.attrib['name'],
+            zOffset=single_object.attrib['zOffset'],
+            validLength=single_object.attrib['validLength'],
+            orientation=Orientation.none,
+            length=single_object.attrib['length'],
+            width=single_object.attrib['width'],
+            height=single_object.attrib['height'],
+            pitch=single_object.attrib['pitch'],
+            roll=single_object.attrib['roll']
+        )
+
+        # 判断此object是否是重复的元素
+        repeat = single_object.find('repeat')
+        if repeat is not None:
+            road.add_object_roadside(road_object_prototype=road_object, repeatDistance=0, side=RoadSide.left,
+                                     tOffset=1.75)
+            road.add_object_roadside(road_object_prototype=road_object, repeatDistance=0, side=RoadSide.right,
+                                     tOffset=-1.755)
+        else:
+            road.add_object(road_object)
+    return road
+
+
+def change_CDATA(filepath):
+    '行人场景特例，对xosc文件内的特殊字符做转换'
+    f = open(filepath, "r", encoding="UTF-8")
+    txt = f.readline()
+    all_line = []
+    # txt是否为空可以作为判断文件是否到了末尾
+    while txt:
+        txt = txt.replace("&lt;", "<").replace("&gt;", ">").replace("&amp;", "&").replace("&quot;", '"').replace(
+            "&apos;", "'")
+        all_line.append(txt)
+        # 读取文件的下一行
+        txt = f.readline()
+    f.close()
+    f1 = open(filepath, 'w', encoding="UTF-8")
+    for line in all_line:
+        f1.write(line)
+    f1.close()
+    
+    
+def path_changer(xosc_path, xodr_path, osgb_path):
+    """
+    provided by Dongpeng Ding
+    :param xosc_path:
+    :param xodr_path:
+    :param osgb_path:
+    :return:
+    """
+    tree = ET.parse(xosc_path)
+    treeRoot = tree.getroot()
+
+    # for OpenScenario v0.9, v1.0
+    for RoadNetwork in treeRoot.findall('RoadNetwork'):
+
+        for Logics in RoadNetwork.findall('LogicFile'):
+            Logics.attrib['filepath'] = xodr_path
+        for SceneGraph in RoadNetwork.findall('SceneGraphFile'):
+            SceneGraph.attrib['filepath'] = osgb_path
+
+        for Logics in RoadNetwork.findall('Logics'):
+            Logics.attrib['filepath'] = xodr_path
+        for SceneGraph in RoadNetwork.findall('SceneGraph'):
+            SceneGraph.attrib['filepath'] = osgb_path
+
+    # for VTD xml
+    for Layout in treeRoot.findall('Layout'):
+        Layout.attrib['File'] = xodr_path
+        Layout.attrib['Database'] = osgb_path
+
+    tree.write(xosc_path, xml_declaration=True)
+    
+    
+def readXML(xoscPath):
+    xodrFileName = ""
+    osgbFileName = ""
+
+    tree = ET.parse(xoscPath)
+    treeRoot = tree.getroot()
+
+    for RoadNetwork in treeRoot.findall('RoadNetwork'):
+
+        for Logics in RoadNetwork.findall('LogicFile'):
+            xodrFileName = Logics.attrib['filepath']
+        for SceneGraph in RoadNetwork.findall('SceneGraphFile'):
+            osgbFileName = SceneGraph.attrib['filepath']
+
+        for Logics in RoadNetwork.findall('Logics'):
+            xodrFileName = Logics.attrib['filepath']
+        for SceneGraph in RoadNetwork.findall('SceneGraph'):
+            osgbFileName = SceneGraph.attrib['filepath']
+
+    return xodrFileName[xodrFileName.rindex("/") + 1:], osgbFileName[osgbFileName.rindex("/") + 1:]
+
+
+def formatThree(rootDirectory):
+    """
+    xodr and osgb file path are fixed
+    :return:
+    """
+
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if ".xosc" == file[-5:]:
+                # xodrFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Rd_001.xodr" # 泛化效果好的场景用的
+                # osgbFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Rd_001.osgb" # 泛化效果好的场景用的
+                # xodrFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Cross.xodr"  # 泛化效果好的场景用的
+                # osgbFilePath = "/volume4T/goodscenarios/generalization/toyiqi/model/Cross.osgb"  # 泛化效果好的场景用的
+                xodrFilePath = "/home/hancheng/hc_project/2023-08-08-10-50-16_jsons1/2023-08-08-10-50-16_jsons_0/2023-08-08-10-50-16_jsons_0.xodr"     # 直路，泛化好用
+                osgbFilePath = "/home/hancheng/VIRES/VTD.2022.1/Runtime/Tools/RodDistro_7001_Rod4.6.3/DefaultProject/Database/json0.opt.osgb" # 直路，泛化好用
+                # xodrFilePath = "/home/lxj/wendang_lxj/L4/L4_scenarios/piliang_model/China_Crossing_002.xodr"       # 十字路口，泛化好用
+                # osgbFilePath = "/home/lxj/wendang_lxj/L4/L4_scenarios/piliang_model/China_Crossing_002.opt.osgb"   # 十字路口，泛化好用
+                # xodrFilePath = "/home/lxj/wendang_lxj/Sharing_VAN/homework/test/DF_yuexiang_1224.xodr"       # Sharing-van还原用的
+                # osgbFilePath = "/home/lxj/wendang_lxj/Sharing_VAN/homework/test/DF_yuexiang_1224.opt.osgb"   # Sharing-van还原用的
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def formatTwo(rootDirectory):
+    """
+    data format:
+    simulation
+        file.xosc
+        file.xodr
+        file.osgb
+    :return:
+    """
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if ".xosc" == file[-5:]:
+
+                xodrFilePath = ""
+                osgbFilePath = ""
+
+                for odrFile in os.listdir(root):
+                    if ".xodr" == odrFile[-5:]:
+                        xodrFilePath = root + "/" + odrFile
+                        break
+
+                for osgbFile in os.listdir(root):
+                    if ".osgb" == osgbFile[-5:]:
+                        osgbFilePath = root + "/" + osgbFile
+                        break
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def formatOne(rootDirectory):
+    """
+    data format:
+        openx
+            xosc
+                file.xosc
+            xodr
+                file.xodr
+            osgb
+                file.osgb
+    :return:
+    """
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if "xosc" == file[-4:]:
+
+                xodrFilePath = ""
+                osgbFilePath = ""
+
+                for odrFile in os.listdir(root[:-4] + "xodr"):
+                    if "xodr" == odrFile[-4:]:
+                        xodrFilePath = root[:-4] + "xodr/" + odrFile
+                        break
+
+                for osgbFile in os.listdir(root[:-4] + "osgb"):
+                    if "osgb" == osgbFile[-4:]:
+                        osgbFilePath = root[:-4] + "osgb/" + osgbFile
+                        break
+
+                path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                print("Change success: " + root + "/" + file)
+
+
+def chongQingFormat(rootDirectory):
+    """
+    supporting file format: chong qing folder format
+    :return:
+    """
+
+    counter = 1
+
+    for root, dirs, files in os.walk(rootDirectory):
+        for file in files:
+            if "xosc" == file[-4:]:
+                if "ver1.0.xosc" == file[-11:]:
+
+                    xodrFileName, osgbFileName = readXML(root + "/" + file)
+
+                    xodrFilePath = "/Xodrs/" + xodrFileName
+                    osgbFilePath = "/Databases/" + osgbFileName
+
+                    path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                    print(counter, "Change success: " + root + "/" + file)
+                else:
+                    xodrFileName, osgbFileName = readXML(root + "/" + file)
+
+                    xodrFilePath = "/Xodrs/" + xodrFileName
+                    osgbFilePath = "/Databases/" + osgbFileName
+
+                    path_changer(root + "/" + file, xodrFilePath, osgbFilePath)
+                    print(counter, "Change success: " + root + "/" + file)
+                counter += 1
+

archive/python3-pjiusv/20240807/simulation_hmi.py

@@ -0,0 +1,227 @@
+# -*-ing:utf-8-*-
+import os
+import sys
+from datetime import datetime
+import traceback
+import json
+import math
+import pandas as pd
+import subprocess
+import time
+import multiprocessing  # 导入进程模块
+from functools import partial  # 导入偏函数
+import warnings
+
+warnings.filterwarnings("ignore")
+from openx import Scenario, formatThree, formatTwo, change_CDATA
+import osgbGenerator
+from utils import smooth_1, get_coordinate_cow, get_map_name, reverse_gyb_gps
+
+
+class Batchrun:
+    def __init__(self, path, keyFileName):
+        """"初始化方法"""
+        self.path = path
+        self.keyFileName = keyFileName
+
+    def getFile(self, path, keyFileName):
+        '''
+        获得可以进行轨迹提取的所有片段文件夹路径
+
+        Parameters
+        ----------
+        path : TYPE
+            DESCRIPTION.
+
+        Returns
+        -------
+        FileList : TYPE
+            可以进行轨迹提取的所有片段文件夹路径.
+
+        '''
+        files = os.listdir(path)  # 得到文件夹下的所有文件，包含文件夹名称
+
+        FileList = []
+        if keyFileName not in files:
+            for name in files:
+                if os.path.isdir(path + '/' + name):
+                    FileList.extend(self.getFile(path + '/' + name, keyFileName))  # 回调函数，对所有子文件夹进行搜索
+        else:
+            FileList.append(path)
+        FileList = list(set(FileList))
+
+        return FileList
+
+    def generateScenarios_raw(self, absPath, param):
+        '''
+        原始自然驾驶场景还原
+        '''
+
+        # 读取自车数据
+        posPath = os.path.join(absPath, param)  # 用来生成场景中自车和他车的路径
+        posdata = pd.read_csv(posPath)
+
+        # 读取仿真地图数据
+        offset_x = -457000.0
+        offset_y = -4400000.0
+        # offset_h = 90 # 初始headinga 和 VTD 有 90偏角
+        offset_h = 0
+
+        # 对感知数据进行后处理
+        # 对公园北环路进行坐标转换
+
+        # 根据pos文件规范时间戳
+        posdata['Time'] = posdata['Time'].apply(lambda x: (x // 100) * 100)
+        # 绝对高程与相对高程的差值
+        posdata['altitude'] = 19.27
+
+        # posdata['Type'].replace({8:2, 10:2}, inplace=True)
+
+        pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type']]
+        # pos_ego[['East', 'North']] = pos_ego.apply(get_coordinate_cow, axis=1)
+        # pos_ego = posdata.loc[posdata['ID'] == -1, ['Time', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        pos_ego = pos_ego.reset_index(drop=True)
+
+        # offset_x = -float(pos_ego.at[0, 'East'])  # 初始East 设为0
+        # offset_y = -float(pos_ego.at[0, 'North']) # 初始North 设为0
+
+        start_time = pos_ego.at[0, 'Time']
+        ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'East', 'North', 'HeadingAngle',
+                                                                  'altitude', 'Type', offset_x, offset_y, offset_h,
+                                                                  start_time)
+        # ego_points, gps_time, ego_type = Scenario.getXoscPosition(pos_ego, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'Type', offset_x, offset_y, offset_h, start_time)
+
+        # 读取目标数据
+        pos_obs = posdata  # 排除非目标物的物体
+        # pos_obs = posdata[posdata['Type'] != 10]  # 排除非目标物的物体
+        pos_obs = pos_obs.loc[
+            pos_obs['ID'] != -1, ['Time', 'ID', 'East', 'North', 'HeadingAngle', 'AbsVel', 'altitude', 'Type']]
+        # pos_obs = pos_obs.loc[pos_obs['ID'] != -1, ['Time', 'ID', 'position_x', 'position_y', 'HeadingAngle', 'Type']]
+        # !!!!自定义修改
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1200, 'position_y'] -= 2
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_x'] += 1
+        # pos_obs.loc[pos_obs['ID'] == 1197, 'position_y'] -= 1
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'type'] = 4
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_x'] = 456319
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'position_y'] = 4397979
+        # pos_obs.loc[pos_obs['ID'] == 1203, 'HeadingAngle'] = 1
+        # offset_h = 30
+        # pos_obs.loc[pos_obs['ID'] == 1194, 'type'] = 7
+        # pos_obs.loc[pos_obs['ID'] == 1188, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1189, 'type'] = 2
+        # pos_obs.loc[pos_obs['ID'] == 1195, 'type'] = 2
+        # obsPath = os.path.join(absPath, 'obs.csv') # 用来筛选场景中不需要的他车
+        # obsdata = pd.read_csv(obsPath)
+        # obsdata = obsdata[(obsdata['ObjectPosY'] < 5) & (obsdata['ObjectPosY'] > -5) & (obsdata['ObjectPosX'] > -10) & (obsdata['ObjectPosX'] < 100)]  # 排除车道线范围外且前向距离较远的目标物
+        # idlist = obsdata['ObjectID'].tolist()  # 筛选出符合条件的的目标物ID
+        # pos_obs = pos_obs[(pos_obs['ID'].isin(idlist))]
+        pos_obs = pos_obs.reset_index(drop=True)
+
+        groups = pos_obs.groupby('ID')
+        object_points = []
+        for key, value in groups:
+            if len(value) < 5:
+                continue
+            # value = smooth_1(value)
+            object_points.append(
+                Scenario.getXoscPosition(value, 'Time', 'East', 'North', 'HeadingAngle', 'altitude', 'Type', offset_x,
+                                         offset_y, offset_h, start_time))
+            # object_points.append(Scenario.getXoscPosition(value, 'Time', 'position_x', 'position_y', 'HeadingAngle', 'type', offset_x, offset_y, offset_h,start_time))
+
+        ego_speed = 5
+        period = math.ceil(gps_time[-1] - gps_time[0])
+        work_mode = 0  # 0为CICV车端数据
+        hour = int(absPath.split('/')[-1].split('-')[3])
+        if hour + 8 >= 24:
+            hour = hour - 16
+        else:
+            hour = hour + 8
+        time_of_day = hour * 3600
+        # 没有路灯防止天过暗
+        if time_of_day >= 64800:
+            time_of_day = 64800
+        s = Scenario(ego_points, object_points, gps_time, ego_speed, work_mode, period, absPath, time_of_day)
+        filename = absPath + '/simulation' + '_' + param.split("_")[1].split(".")[0]
+        files = s.generate(filename)
+
+        change_CDATA(files[0][0])
+        print(files)
+
+        # 生成osgb
+        # osgbGenerator.formatTwo(filename)
+
+        # 修改xosc路径
+        # formatThree(filename)
+        # # # 生成每个场景的描述文件 json
+        # # getLabel(output_path, scenario_series['场景编号'], scenario_series['场景名称'])
+
+        # 拷贝到vtd路径下
+        # vtd_path = os.path.join('/home/lxj/VIRES/VTD.2021.3/Data/Projects/Current/Scenarios/myScenario', datetime.now().strftime("%Y%m%d%H%M%S"))
+        # if not os.path.exists(vtd_path):
+        #     os.makedirs(vtd_path)
+        # os.system('cp '+ files[0][0] + ' ' + vtd_path + '/')
+
+    def multiRun(self, path, param):
+        files = self.getFile(path, self.keyFileName)
+
+        print('程序开始，%s 个数据包' % len(files))
+
+        t1 = time.time()
+        # 无参数时，使用所有cpu核;  有参数时，使用CPU核数量为参数值
+        pool = multiprocessing.Pool(processes=10)
+        pfunc = partial(self.generateScenarios_raw, param)
+        pool.map(pfunc, files)
+        # 调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束
+        pool.close()
+        pool.join()
+        t2 = time.time()
+        print("程序结束，并行执行时间：%s s" % int(t2 - t1))
+
+    def batchRun(self, path, param):
+        files = self.getFile(path, self.keyFileName)
+
+        print('程序开始，%s 个数据包' % len(files))
+
+        for di, absPath in enumerate(sorted(files)):
+            print(absPath)
+            # try:
+            self.generateScenarios_raw(absPath, param)
+            # except:
+            #     print('Augmentation failed!!!!')
+            #     error = {'time':datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],'traceback':traceback.format_exc()}
+            #     with open('error.log','a+') as f:
+            #         json.dump(error, f, indent=4)
+            #         f.write('\n')
+            # print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
+        return None
+
+    def GenerateVideo(self, root_path):
+        # 批量生成视频
+        imagelist = self.getFile(root_path, 'image')
+        for item in imagelist:
+            strs = item.split('/')
+            respath = os.path.join(item, "video.mp4")
+            # respath = os.path.join(res_path,strs[-3],strs[-2],"video.mp4")
+            print('---------------------')
+            # os.makedirs(os.path.join(res_path,strs[-3],strs[-2]))
+            command = "ffmpeg -f image2 -r 10 -pattern_type glob -i '" + item + "/image/*.jpg" + "' -y '" + respath + "'"
+            print(command)
+            process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
+            process.wait()
+
+
+if __name__ == "__main__":
+    # rootPath = "/media/hancheng/Simulation5/pjisuv_pjisuv95_data_merge_2024-01-31-07-53-50_TTC_11"  # 跟车
+    rootPath = sys.argv[1]  # 跟车
+    # 生成场景
+    a = Batchrun(rootPath, "pos_orig.csv")
+    a.batchRun(rootPath, 'pos_orig.csv')
+    # a.batchRun(rootPath, 'pos_hmi.csv')
+    # a.multiRun(rootPath, 0)
+
+    # 生成视频
+    # a.GenerateVideo(rootPath)
+

src/python2/pjibot_delivery/README.md

@@ -0,0 +1,13 @@
+
+
+# pjibot
+nohup python2 pjibot_merge.py > log/pjibot_merge.out 2>&1 &
+nohup python2 pjibot_csv.py > log/pjibot_csv.log 2>&1 &
+nohup python2 pjibot_camera.py > log/pjibot_camera.log 2>&1 &
+nohup python2 pjibot_pcd.py > log/pjibot_pcd.log 2>&1 &
+nohup python2 pjibot_callback.py > log/pjibot_callback.log 2>&1 &
+
+
+
+# 轨迹生成工具部署
+source /root/workspace/devel/setup.bash

src/python2/pjibot_delivery/csv-.py

@@ -0,0 +1,138 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import bagtocsv_robot
+
+import logging
+
+path1 = '/mnt/disk001/dcl_data_process/src/python2/pjibot_delivery/'
+path2 = '/mnt/disk001/dcl_data_process/test/run/'
+logging.basicConfig(filename=path1 + 'log/csv.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot_delivery/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_csv(data_bag, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        bagtocsv_robot.parse(data_bag, local_parse_dir + '/csv/')
+        bagname = data_bag.split('/')[-1].split('.')[0]
+        local_csv_dir = os.path.join(local_parse_dir + '/csv/', bagname)  # 最终生成四个csv文件的目录
+
+        csv_file_name1 = 'trajectory_pji'
+        local_csv_file_path1 = str(local_csv_dir) + '/' + str(csv_file_name1) + '.csv'
+        oss_csv_object_key1 = parse_prefix + csv_file_name1 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key1, local_csv_file_path1)
+
+        csv_file_name2 = 'ego_pji'
+        local_csv_file_path2 = str(local_csv_dir) + '/' + str(csv_file_name2) + '.csv'
+        local_delete_list.append(local_csv_file_path2)
+        oss_csv_object_key2 = parse_prefix + csv_file_name2 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key2, local_csv_file_path2)
+
+        csv_file_name3 = 'pos_pji'
+        local_csv_file_path3 = str(local_csv_dir) + '/' + str(csv_file_name3) + '.csv'
+        oss_csv_object_key3 = parse_prefix + csv_file_name3 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key3, local_csv_file_path3)
+
+        csv_file_name4 = 'objects_pji'
+        local_csv_file_path4 = str(local_csv_dir) + '/' + str(csv_file_name4) + '.csv'
+        oss_csv_object_key4 = parse_prefix + csv_file_name4 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key4, local_csv_file_path4)
+
+        # 生成并上传csv之后，调用
+        os.chdir(path2)
+        command1 = './pji_outdoor_real ' + str(local_csv_dir) + '/ ' + str(local_csv_dir) + '/ ' + str(
+            local_csv_dir) + '/trajectory.png ' + bagname
+        logging.info("调用生成pdf 报告命令: %s" % str(command1))
+        os.system(command1)
+        oss_csv_object_key5 = parse_prefix + 'report.pdf'
+        bucket.put_object_from_file(oss_csv_object_key5, str(local_csv_dir) + '/report.pdf')
+
+        # 记得删除
+        local_delete_list.append(local_csv_file_path1)
+        local_delete_list.append(local_csv_file_path2)
+        local_delete_list.append(local_csv_file_path3)
+        local_delete_list.append(local_csv_file_path4)
+        local_delete_list.append(str(local_csv_dir) + '/report.pdf')
+
+    except Exception as e2:
+        # 当出现异常时执行的代码
+        logging.exception("生成csv报错: %s", e2)
+
+
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    while True:
+        logging.info("开始新一轮扫描")
+        time.sleep(sleep_time)
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                # 获取合并后的包
+                merged_bag_object_key = str(obj1.key)
+                # print(f'判断1{merged_bag_object_key}')
+                if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                    merged_bag_object_key_split = merged_bag_object_key.split('/')
+                    merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                    parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                    parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                    csv1_done = False
+                    csv2_done = False
+                    csv3_done = False
+                    csv4_done = False
+                    callback_undone = False
+                    for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                        if '/callback.json' in str(obj2.key):
+                            callback_undone = True
+                        if '/trajectory_pji.csv' in str(obj2.key):
+                            csv1_done = True
+                        if '/ego_pji.csv' in str(obj2.key):
+                            csv2_done = True
+                        if '/pos_pji.csv' in str(obj2.key):
+                            csv3_done = True
+                        if '/objects_pji.csv' in str(obj2.key):
+                            csv4_done = True
+                    if not callback_undone:  # 没有 callback.json
+                        continue
+                    if csv1_done and csv2_done and csv3_done and csv4_done:
+                        continue
+
+                    logging.info("开始生成场景还原csv: %s" % str(obj1.key))
+                    local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                    local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                    local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                    if not os.path.exists(local_merged_dir):
+                        os.makedirs(local_merged_dir)
+                    if not os.path.exists(local_parse_dir):
+                        os.makedirs(local_parse_dir)
+                    merged_bag_full_name = merged_bag_object_key_split[-1]
+                    merged_bag_name = merged_bag_full_name.split('.')[0]
+                    try:
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                    except Exception as e:
+                        logging.exception("下载合并后的bag包失败: %s" % str(e))
+
+                    local_delete_list.append(local_merged_bag_path)
+                    # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                    parse_csv(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        logging.exception("捕获到一个异常: %s" % str(e))
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_delivery/csv-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 csv-.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjibot_delivery/csv-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 csv-.py > log/csv.out 2>&1 &

src/python2/pjibot_delivery/csv-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/csv.log

src/python2/pjibot_delivery/merge-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 merge.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjibot_delivery/merge-nohup.sh

@@ -0,0 +1,3 @@
+#!/bin/bash
+mkdir ./log
+nohup python2 merge.py > log/merge.out 2>&1 &

src/python2/pjibot_delivery/merge-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/merge.log

src/python2/pjibot_delivery/merge.py

@@ -0,0 +1,125 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from rosbag import Bag, Compression
+import logging
+import rosbag
+from std_msgs.msg import Header
+import rospy
+
+path1 = '/mnt/disk001/dcl_data_process/src/python2/pjibot_delivery/'
+
+logging.basicConfig(filename=path1 + 'log/merge.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot_delivery/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+
+sleep_time = 5  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+
+
+# local_bags 合并前的包
+# merged_prefix oss路径
+# local_merged_dir 本地路径
+# 包名
+def merge(local_bags, merged_prefix, local_merged_dir, merged_bag_name):
+    try:
+        output_bag_file = local_merged_dir + merged_bag_name
+        with Bag(output_bag_file, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        bucket.put_object_from_file(merged_prefix + merged_bag_name, output_bag_file)
+        return output_bag_file
+    except Exception as e:
+        logging.exception("bag包合并报错: %s" % str(e))
+
+
+'''
+cname：http://pji-bucket1.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+oss桶名： pji-bucket1
+oss桶名： oss://pji-bucket1
+'''
+# ------- 获取未合并的bag包，合并 -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    while True:
+        logging.info("开始新一轮扫描")
+        try:
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            upload_completed_prefix_list = []
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1, delimiter='/'):
+                bag_list = []
+                target_path = ''
+                if str(obj1.key).count('/') == 2:  # pujin/robot-01/
+                    # 6 校验bag包个数
+                    for obj2 in oss2.ObjectIterator(bucket, prefix=str(obj1.key) + key2, delimiter='/'):
+                        if str(obj2.key).count(
+                                '/') == 4:  # pujin/robot-01/data/2023-12-20-02-16-56_obstacledetection_10/
+                            bag_need = str(obj2.key).split('_')[-1][:-1]
+                            count_bag = 0
+                            for obj3 in oss2.ObjectIterator(bucket, prefix=str(obj2.key)):
+                                if obj3.key[-3:] == 'bag':
+                                    count_bag = count_bag + 1
+                            if bag_need == str(count_bag):
+                                upload_completed_prefix_list.append(obj2.key)
+            # 处理
+            for prefix in upload_completed_prefix_list:
+                local_delete_list = []
+                oss_delete_list = []
+                # 获取要处理的包
+                oss_bags = []
+                local_bags = []
+                for obj in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if str(obj.key).endswith('.bag'):
+                        oss_bags.append(str(obj.key))
+                split_list = prefix.replace(key2, key3).split('/')
+                merged_prefix = '/'.join(split_list[0:-2]) + '/'
+                local_merged_dir = path1 + merged_prefix
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                merged_bag_name = split_list[-2]
+                merged_bag_full_name = merged_bag_name + '.bag'
+                local_bag_dir = path1 + '/'.join(split_list[0:-1]) + '/'
+                if not os.path.exists(local_bag_dir):
+                    os.makedirs(local_bag_dir)
+
+                # 下载
+                for oss_bag in oss_bags:
+                    bag_name = str(oss_bag).split('/')[-1]
+                    local_bag_path = local_bag_dir + bag_name
+                    bucket.get_object_to_file(oss_bag, local_bag_path)
+                    local_bags.append(local_bag_path)
+                    local_delete_list.append(local_bag_path)
+                    oss_delete_list.append(oss_bag)
+
+                # 1 合并bag
+                logging.info("合并文件，key前缀为: %s" % str(local_merged_dir))
+                merged_bag_file_path = merge(local_bags, merged_prefix, local_merged_dir, merged_bag_full_name)
+                local_delete_list.append(merged_bag_file_path)
+                # 删除本地临时文件
+                if len(local_delete_list) > 0:
+                    for local_delete in local_delete_list:
+                        try:
+                            os.remove(local_delete)
+                        except Exception as e:
+                            logging.exception("删除本地临时文件报错: %s" % str(e))
+
+                # 删除oss原始文件
+                if len(oss_delete_list) > 0:
+                    bucket.batch_delete_objects(oss_delete_list)
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_delivery/pcd-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 pcd.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjibot_delivery/pcd-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 pcd.py > log/pcd.out 2>&1 &

src/python2/pjibot_delivery/pcd-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/pcd.log

src/python2/pjibot_delivery/pcd.py

@@ -0,0 +1,97 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import pcdtovideo_monitor_overlook
+
+import logging
+
+path1 = '/mnt/disk001/dcl_data_process/src/python2/pjibot_delivery/'
+logging.basicConfig(filename=path1 + 'log/pcd.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot_delivery/'
+path1 = '/root/'
+sleep_time = 30  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path, parse_prefix2, local_parse_dir, local_delete_list):
+    global bucket
+    try:
+        local_pcd_mp4_dir = pcdtovideo_monitor_overlook.parse(merged_bag_file_path, local_parse_dir + '/pcd/')
+        pcd_mp4_file_name = 'pcd_overlook'
+        local_delete_list.append(str(local_pcd_mp4_dir) + '/pcd_overlook.mp4')
+        oss_csv_object_key3 = parse_prefix2 + pcd_mp4_file_name + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key3, str(local_pcd_mp4_dir) + '/' + pcd_mp4_file_name + '.mp4')
+        logging.info("上传点云视频到: %s", oss_csv_object_key3)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    while True:
+        logging.info("开始新一轮扫描")
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        pcd_done = False
+                        callback_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if '/callback.json' in str(obj2.key):
+                                callback_done = True
+                            if '/pcd_overlook.mp4' in str(obj2.key):
+                                pcd_done = True
+                        if not callback_done:
+                            continue
+                        if pcd_done:
+                            continue
+                        logging.info("%s 需要生成点云视频 pcd_overlook.mp4" % str(parse_prefix_full))
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                        parse_to_pcd_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+                except Exception as e:
+                    logging.exception("报错: %s" % str(e))
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        logging.exception("删除本地临时文件报错: %s" % str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s" % str(e))

src/python2/pjibot_delivery/pjibot_callback.py

@@ -0,0 +1,170 @@
+# -*- coding: utf-8 -*-
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+
+logging.basicConfig(filename=path1 + 'log/pjibot_callback.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+path2 = 'data/'
+path3 = 'data_merge/'
+path4 = 'data_parse/'
+# url1_public = "http://1.202.169.139:9081/device/auth"
+url1_private = "http://10.14.86.147:9081/device/auth"
+# url2_public = " http://1.202.169.139:9081/device/data/callback"
+url2_private = "http://10.14.86.147:9081/device/data/callback"
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'pji-bucket1'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            upload_completed_prefix_list = []
+            # 4 获取即将被合并的bag目录
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    if 'callback.json' in str(obj1.key):
+                        prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                        done1 = False
+                        done2 = False
+                        done3 = False
+                        done4 = False
+                        done5 = False
+                        done6 = False
+                        done7 = False
+                        done8 = False
+                        done9 = False
+                        # print '检测是否文件完整：', prefix
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                            if '/EgoState_pji.csv' in str(obj2.key):
+                                done1 = True
+                            if '/build_map.bag' in str(obj2.key):
+                                done2 = True
+                            if '/camera.mp4' in str(obj2.key):
+                                done3 = True
+                            if '/camera2.mp4' in str(obj2.key):
+                                done4 = True
+                            if '/costmap.bag' in str(obj2.key):
+                                done5 = True
+                            if '/map.bag' in str(obj2.key):
+                                done6 = True
+                            if '/pcd_lidar.mp4' in str(obj2.key):
+                                done7 = True
+                            if '/tfstatic.bag' in str(obj2.key):
+                                done8 = True
+                            if '/report.pdf' in str(obj2.key):
+                                done9 = True
+                        if not done1 or not done2 or not done3 or not done4 or not done5 or not done6 or not done7 or not done8 or not done9:
+                            continue
+                        time.sleep(1)
+                        logging.info("发送： %s", str(obj1.key))
+                        # 1 获取json内容
+                        json_content = bucket.get_object(str(obj1.key)).read()
+                        # 2 获取token
+                        json_object = json.loads(json_content)
+                        data1 = {
+                            "equipmentNo": json_object['equipmentNo'],
+                            "secretKey": json_object['secretKey']
+                        }
+                        json_data1 = json.dumps(data1)
+                        logging.info("授权接口请求中： %s" % url1_private)
+                        logging.info("授权发送参数为： %s" % str(data1))
+                        request1 = urllib2.Request(url1_private, json_data1,
+                                                   headers={'Content-Type': 'application/json'})
+                        response1 = urllib2.urlopen(request1)
+                        result_json1 = response1.read()
+                        result_object1 = json.loads(result_json1)
+                        logging.info("授权接口请求结果为： %s", result_object1)
+                        access_token = result_object1.get('data').get('accessToken')
+                        # 要发送的JSON参数
+                        try:
+                            # logging.info("bag文件为： %s", json_object['rosBagPath'])
+                            old_date = json_object['dataName']
+                            data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                            equipment_no = json_object['equipmentNo']
+                            old_file_path = json_object['filePath']
+                            old_ros_bag_path = json_object['rosBagPath']
+                            task_id = json_object['taskId']
+                            trigger_id = json_object['triggerId']
+                        except Exception as e:
+                            logging.exception("callback报错：%s", str(e))
+                            continue
+
+                        # 将时区统一
+                        new_date = add_hour(old_date, 8)
+                        old_delete_list = []
+                        for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                            old_delete_list.append(str(obj_old.key))
+                            if 'callback.json' in str(obj_old.key):
+                                bucket.copy_object(bucket_name, str(obj_old.key),
+                                                   str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                        'callback_done.json'))
+                            else:
+                                bucket.copy_object(bucket_name, str(obj_old.key),
+                                                   str(obj_old.key).replace(old_date, new_date))
+                        bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                        bucket.delete_object(old_ros_bag_path)
+                        bucket.batch_delete_objects(old_delete_list)
+
+                        data2 = {
+                            "dataName": new_date,
+                            "dataSize": data_size,
+                            "equipmentNo": equipment_no,
+                            "filePath": old_file_path.replace(old_date, new_date),
+                            "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                            "taskId": task_id,
+                            "triggerId": trigger_id
+                        }
+                        json_data2 = json.dumps(data2)
+                        logging.info("回调接口请求中：%s" % url2_private)
+                        request2 = urllib2.Request(url2_private, json_data2,
+                                                   headers={'Content-Type': 'application/json',
+                                                            'authorization': access_token})
+                        response2 = urllib2.urlopen(request2)
+                        result_json2 = response2.read()
+                        result_object2 = json.loads(result_json2)
+                        logging.info("回调接口请求结果为： %s", result_object2)
+                except Exception as e:
+                    logging.exception("局部异常处理: %s" % str(e))
+            time.sleep(2)
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_delivery/resource/bagtocsv_robot.py

@@ -0,0 +1,214 @@
+# coding: utf-8
+#!/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math 
+import rospy
+import sys
+import time
+import numpy as np
+from datetime import datetime
+import argparse
+import pandas as pd
+
+
+def quaternion_to_euler(x, y, z, w):
+    # 将四元数归一化
+    try:
+        length = np.sqrt(x**2 + y**2 + z**2 + w**2)
+        x /= length
+        y /= length
+        z /= length
+        w /= length
+    
+        # 计算欧拉角
+        #roll = np.arctan2(2*(w*x + y*z), 1 - 2*(x**2 + y**2))
+        #pitch = np.arcsin(2*(w*y - z*x))
+        yaw = np.arctan2(2*(w*z + x*y), 1 - 2*(y**2 + z**2))  
+        return  yaw
+    except :
+        return 0
+
+
+
+def parsehancheng(input_dir, output_dir):   
+    dic_trajectory = ['Time','simTime','simFrame','PointNumber','posX','posY','posZ','posH',
+    'TargetX','TargetY','TargetZ','TargetH']
+    trajectory_file = open(output_dir + "/"+"trajectory_pji.csv", 'w')
+    writer_trajectory = csv.writer(trajectory_file)
+    writer_trajectory.writerow(dic_trajectory)
+    
+    dic_EgoState = ['Time','simTime','simFrame','posX','posY','posZ','posH','speedX','speedH','cmd_speedX','cmd_speedH','obstacle','task_error_code']
+    
+    EgoState_file = open(output_dir + "/"+"ego_pji.csv", 'w')
+    
+    writer_EgoState = csv.writer(EgoState_file)
+    writer_EgoState.writerow(dic_EgoState)
+
+    dic_robot_pos = ['Time','simtime','FrameID','HeadingAngle','X', 'Y' ,'Z']
+    robot_pos_file = open(output_dir + "/"+"pos_pji.csv", 'w')
+    writer_robot_pos = csv.writer(robot_pos_file)
+    writer_robot_pos.writerow(dic_robot_pos)
+
+    dic_objects = ['Time','simtime','FrameID','playerId','posH','posX', 'posY' ,'posZ','label','dimX','dimY','dimZ',
+                   'speedX','speedY','speedZ','speedH_X','speedH_Y','speedH_Z','accelX','accelY','accelZ','accelH_X','accelH_Y','accelH_Z']
+    objects_file = open(output_dir + "/"+"objects_pji.csv", 'w')
+    writer_objects = csv.writer(objects_file)
+    writer_objects.writerow(dic_objects)
+
+    frame_max=sys.maxsize
+    with rosbag.Bag(input_dir ,'r') as bag:
+        #wheel_odom_flag=False
+        #cmd_vel_flag=False
+        first_message_time = None
+        Frame_robot_pose=1
+        obstacle_state=0
+        speed_linear=0
+        speed_angular=0
+        cmd_speed_angular=0
+        cmd_speed_linear=0
+        first_message_time = None
+        framenum_ego = 1
+        task_error_code=0
+        #framenum_obj = 1
+        locationsimtime=' '
+        date_time=' '
+        simFrame=1
+        ego_posx,ego_posy,ego_posz,ego_posH=0,0,0,0
+        for topic,msg,t in bag.read_messages(topics=['/obstacle_detection','/wheel_odom','/cmd_vel','/robot_pose','/tracking/objects','/nav/task_feedback_info','/robot/final_trajectory']):   
+            
+            if first_message_time is None:  
+                first_message_time = t
+                first_message_time = rospy.Time.to_sec(first_message_time)
+                first_message_time = datetime.fromtimestamp(first_message_time)
+            
+            if topic == "/obstacle_detection":
+                obstacle_state=msg.data
+                #print(msg.data)
+
+
+            if topic == "/wheel_odom": 
+                #wheel_odom_flag=True 
+                speed_linear=msg.twist.twist.linear.x*3.6
+                speed_angular=msg.twist.twist.angular.z
+
+                
+            if topic == "/cmd_vel": 
+                #cmd_vel_flag=True
+                cmd_speed_linear=msg.linear.x*3.6
+                cmd_speed_angular=msg.angular.z
+                
+            if topic == "/nav/task_feedback_info":
+                task_error_code=msg.task_error_code
+                
+            if topic == "/robot_pose":
+                
+                timestamp = rospy.Time.to_sec(t)
+                date_time = datetime.fromtimestamp(timestamp)
+                locationsimtime=(date_time-first_message_time).total_seconds()
+                ego_posx=msg.pose.position.x
+                poseX=ego_posx-88.96626338170609
+                ego_posy=msg.pose.position.y
+                poseY=ego_posy-40.553671177476645
+                poseZ=msg.pose.position.z
+                orientationX=msg.pose.orientation.x
+                orientationY=msg.pose.orientation.y
+                orientationZ=msg.pose.orientation.z
+                orientationW=msg.pose.orientation.w
+                egoyaw=quaternion_to_euler(orientationX,orientationY,orientationZ,orientationW)
+                message_location =[date_time,locationsimtime,framenum_ego,egoyaw,poseX,poseY,poseZ]    
+                #print(f'date_time={date_time},  locationtime={locationsimtime}')
+                writer_robot_pos.writerow(message_location)
+                #if wheel_odom_flag and cmd_vel_flag:
+                message_EgoState =[date_time,locationsimtime,Frame_robot_pose,poseX,poseY,poseZ,egoyaw,
+                                   speed_linear,speed_angular,cmd_speed_linear,cmd_speed_angular,obstacle_state,task_error_code]
+             
+                writer_EgoState.writerow(message_EgoState)
+                framenum_ego+=1
+                Frame_robot_pose+=1
+
+        
+            if topic == "/tracking/objects":
+                msg_l = len(msg.objects)
+                if msg_l and (locationsimtime != ' ') and (date_time != ' '):
+                    #timestamp = rospy.Time.to_sec(t)
+                    #date_time = datetime.fromtimestamp(timestamp)
+                    #simtime=(date_time-first_message_time).total_seconds()
+                    for i in range(msg_l):
+                        obj_ID = msg.objects[i].id
+                        obj_x = msg.objects[i].pose.position.x-88.96626338170609
+                        obj_y = msg.objects[i].pose.position.y-40.553671177476645
+                        obj_z = msg.objects[i].pose.position.z
+                        obj_orientationX=msg.objects[i].pose.orientation.x
+                        obj_orientationY=msg.objects[i].pose.orientation.y
+                        obj_orientationZ=msg.objects[i].pose.orientation.z
+                        obj_orientationW=msg.objects[i].pose.orientation.w
+                        objyaw=quaternion_to_euler(obj_orientationX,obj_orientationY,obj_orientationZ,obj_orientationW)
+                        obj_lable=msg.objects[i].label
+                        obj_dimX=msg.objects[i].dimensions.x
+                        obj_dimY=msg.objects[i].dimensions.y
+                        obj_dimZ=msg.objects[i].dimensions.z
+                        velocity_linear_x=msg.objects[i].velocity.linear.x
+                        velocity_linear_y=msg.objects[i].velocity.linear.y
+                        velocity_linear_z=msg.objects[i].velocity.linear.z
+                        
+                        velocity_angular_x=msg.objects[i].velocity.angular.x
+                        velocity_angular_y=msg.objects[i].velocity.angular.y
+                        velocity_angular_z=msg.objects[i].velocity.angular.z
+                        
+                        acceleration_linear_x=msg.objects[i].acceleration.linear.x
+                        acceleration_linear_y=msg.objects[i].acceleration.linear.y
+                        acceleration_linear_z=msg.objects[i].acceleration.linear.z
+                        
+                        acceleration_angular_x=msg.objects[i].acceleration.angular.x
+                        acceleration_angular_y=msg.objects[i].acceleration.angular.y
+                        acceleration_angular_z=msg.objects[i].acceleration.angular.z
+                        
+                        message_obj =[date_time,locationsimtime,Frame_robot_pose,obj_ID,objyaw,obj_x,obj_y,obj_z,obj_lable,obj_dimX,obj_dimY,obj_dimZ,
+                                      velocity_linear_x,velocity_linear_y,velocity_linear_z,velocity_angular_x,velocity_angular_y,
+                                      velocity_angular_z,acceleration_linear_x,acceleration_linear_y,acceleration_linear_z,
+                                      acceleration_angular_x,acceleration_angular_y,acceleration_angular_z]
+                        #print(f'{date_time},  {locationsimtime}')
+                        writer_objects.writerow(message_obj)
+                    #framenum_obj+=1 
+            if topic == "/robot/final_trajectory":
+                PointNumber=1
+                timestamp1 = rospy.Time.to_sec(t)
+                date_time1 = datetime.fromtimestamp(timestamp1)
+                locationsimtime1=(date_time1-first_message_time).total_seconds()
+                if ego_posx!=0 or ego_posy!=0:
+                    for i in range(len(msg.waypoints)):
+                        Targetx=msg.waypoints[i].pose.pose.position.x
+                        Targety=msg.waypoints[i].pose.pose.position.y
+                        Targetz=msg.waypoints[i].pose.pose.position.z
+                        orientationX=msg.waypoints[i].pose.pose.orientation.x
+                        orientationY=msg.waypoints[i].pose.pose.orientation.y
+                        orientationZ=msg.waypoints[i].pose.pose.orientation.z
+                        orientationW=msg.waypoints[i].pose.pose.orientation.w
+                        TargetH=quaternion_to_euler(orientationX,orientationY,orientationZ,orientationW)
+                        message_trajectory =[date_time1,locationsimtime1,simFrame,PointNumber,ego_posx,ego_posy,poseZ,egoyaw,Targetx,Targety,Targetz,TargetH]
+                        writer_trajectory.writerow(message_trajectory)
+                        PointNumber+=1
+                    simFrame+=1
+                
+        robot_pos_file.close()
+        objects_file.close()
+        EgoState_file.close()
+        trajectory_file.close()
+        
+        
+
+def parse(input_dir, output_dir):
+   #input_dir='/media/dell/HIKSEMI/pji_DGNC/pjioutrobot_2024-08-21-15-12-04.bag'
+   #output_dir='/media/dell/HIKSEMI/pji_DGNC'
+   # input_dir=sys.argv[1]
+   # output_dir = sys.argv[2]
+   bagname=input_dir.split('/')[-1].split('.')[0]
+
+   
+   output_dir=os.path.join(output_dir, bagname)
+   if not os.path.exists(output_dir):
+       os.makedirs(output_dir)
+   parsehancheng(input_dir, output_dir)
+

src/python2/pjibot_delivery/resource/pcdtovideo_monitor_overlook.py

@@ -0,0 +1,132 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+from __future__ import print_function
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+from multiprocessing import Pool
+import datetime
+
+
+def draw_points(pic, filename):
+    colormap = np.array([[128, 130, 120], 
+             [235, 0, 205], 
+             [0, 215, 0], 
+             [235, 155, 0]]) / 255.0 
+    f = open(filename, "r")
+    ff = f.readlines()[11:]
+
+    for i in range(0, len(ff)):
+        point = ff[i].split()[:4]
+        point_x = float(point[0])
+        point_y = -float(point[1])
+        point_z = float(point[2])
+        points_intensity = float(point[2])
+        if math.isnan(point_x):
+            pass
+        else:
+            cv2.circle(pic, (int(800 - point_x * 10), int(400 - point_y * 10)), 0, colormap[int(points_intensity) % colormap.shape[0]]*255, 2)
+
+def process_file(file):
+
+    root = file[0]
+    inputFilePath = root + "/" + file[1]
+    tempFilePath = root[:-3] + "pcd_ascii/" + file[1]
+    outputFilePath = root[:-3] + "jpg/" + file[1][:-3] + "jpg"
+
+    command = "pcl_convert_pcd_ascii_binary " + inputFilePath + " " + tempFilePath + " 0"
+    os.system(command)
+
+    if not os.path.exists(tempFilePath):
+        return
+
+    pic = np.zeros([800, 1600, 3])
+    draw_points(pic, tempFilePath)
+    cv2.imwrite(outputFilePath, pic)
+
+
+
+
+def parse(input_dir, output_dir):
+    s_time=datetime.datetime.now()
+    #input_dir = sys.argv[1]
+    # input_dir='/media/dell/HIKSEMI/2024-09-06-11-54-36.bag'
+    #output_dir = sys.argv[2]
+    # output_dir = '/media/dell/HIKSEMI'
+
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/velodyne_points": #/camera/depth/points   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+        start_time = bag.get_start_time()
+        end_time = bag.get_end_time()
+        # 计算rosbag的持续时间
+        duration = end_time - start_time
+
+    bagtime = duration
+    hz = str(float(float(num_count) / bagtime))
+    print(hz)
+    
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + ['/velodyne_points'] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+    
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    # Create a list of files to be processed
+    files_to_process = []
+    for root, dirs, files in os.walk(output_dir[:-4]):
+        for file in files:
+            if file.endswith(".pcd"):
+                files_to_process.append((root, file))
+    
+
+    num_processes = 4
+
+    pool = Pool(num_processes)
+    pool.map(process_file, files_to_process)
+    pool.close()
+    pool.join()
+    
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_overlook.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    
+    e_time=datetime.datetime.now()
+    print("using "+str(e_time-s_time)+ "s")
+    #shutil.rmtree(file1)
+    #shutil.rmtree(file2)
+    #shutil.rmtree(output_dir)
+    return output_dir[0:-4]
+

src/python2/pjibot_delivery/xosc-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 xosc.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjibot_delivery/xosc-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 xosc.py > log/xosc.out 2>&1 &

src/python2/pjibot_delivery/xosc-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/xosc.log

src/python2/pjibot_delivery/xosc.py

@@ -0,0 +1,97 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+import logging
+
+path1 = '/mnt/disk001/dcl_data_process/src/python2/pjibot_delivery/'
+path2 = '/mnt/disk001/dcl_data_process/src/python3/pjibot_outdoor/'
+
+logging.basicConfig(filename=path1 + 'log/xosc.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot_delivery/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def generate_xosc(parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        os.chdir(path2)
+        command2 = 'python3 jiqiren_outdoor.py ' + local_parse_dir[:-1] + ' 0'  # 配送机器人0 巡检机器人1
+        logging.info("调用命令2: %s" % str(command2))
+        os.system(command2)
+        local_xosc_path2 = local_parse_dir + 'simulation/xosc/openx_outdoor0.xosc'
+        bucket.put_object_from_file(parse_prefix + 'simulation.xosc', local_xosc_path2)
+        logging.info("上传 simulation.xosc 成功: %s" % str(parse_prefix + 'simulation.xosc'))
+        local_delete_list.append(local_xosc_path2)
+    except Exception as e:
+        logging.exception("生成xosc报错: %s" % str(e))
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        xosc_done = False
+                        csv1_done = False
+                        csv2_done = False
+                        for obj3 in oss2.ObjectIterator(bucket, prefix=str(parse_prefix_full)):
+                            if '/simulation.xosc' in str(obj3.key):
+                                xosc_done = True
+                            if '/objects_pji.csv' in str(obj3.key):
+                                csv1_done = True
+                            if '/pos_pji.csv' in str(obj3.key):
+                                csv2_done = True
+                        if xosc_done:
+                            logging.info("存在simulation.xosc: %s" % str(parse_prefix_full))
+                            continue
+                        if not csv1_done:
+                            logging.info("不存在/objects_pji.csv: %s" % str(parse_prefix_full))
+                            continue
+                        if not csv2_done:
+                            logging.info("不存在/pos_pji.csv: %s" % str(parse_prefix_full))
+                            continue
+                        logging.info("需要生成simulation.xosc: %s" % str(parse_prefix_full))
+                        local_dir_full = path1 + parse_prefix_full
+                        if not os.path.exists(local_dir_full):
+                            os.makedirs(local_dir_full)
+                        bucket.get_object_to_file(parse_prefix_full + 'objects_pji.csv', local_dir_full + 'objects_pji.csv')
+                        bucket.get_object_to_file(parse_prefix_full+'pos_pji.csv', local_dir_full+'pos_pji.csv')
+                        generate_xosc(parse_prefix_full, local_dir_full, local_delete_list)
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        logging.exception("删除本地临时文件报错: %s" % str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjibot_guide/README.md

@@ -0,0 +1,13 @@
+
+
+# pjibot
+nohup python2 pjibot_merge.py > log/pjibot_merge.out 2>&1 &
+nohup python2 pjibot_csv.py > log/pjibot_csv.log 2>&1 &
+nohup python2 pjibot_camera.py > log/pjibot_camera.log 2>&1 &
+nohup python2 pjibot_pcd.py > log/pjibot_pcd.log 2>&1 &
+nohup python2 pjibot_callback.py > log/pjibot_callback.log 2>&1 &
+
+
+
+# 轨迹生成工具部署
+source /root/workspace/devel/setup.bash

src/python2/pjibot_guide/pjibot_callback.py

@@ -0,0 +1,170 @@
+# -*- coding: utf-8 -*-
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+
+logging.basicConfig(filename=path1 + 'log/pjibot_callback.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+path2 = 'data/'
+path3 = 'data_merge/'
+path4 = 'data_parse/'
+# url1_public = "http://1.202.169.139:9081/device/auth"
+url1_private = "http://10.14.86.147:9081/device/auth"
+# url2_public = " http://1.202.169.139:9081/device/data/callback"
+url2_private = "http://10.14.86.147:9081/device/data/callback"
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'pji-bucket1'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            upload_completed_prefix_list = []
+            # 4 获取即将被合并的bag目录
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    if 'callback.json' in str(obj1.key):
+                        prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                        done1 = False
+                        done2 = False
+                        done3 = False
+                        done4 = False
+                        done5 = False
+                        done6 = False
+                        done7 = False
+                        done8 = False
+                        done9 = False
+                        # print '检测是否文件完整：', prefix
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                            if '/EgoState_pji.csv' in str(obj2.key):
+                                done1 = True
+                            if '/build_map.bag' in str(obj2.key):
+                                done2 = True
+                            if '/camera.mp4' in str(obj2.key):
+                                done3 = True
+                            if '/camera2.mp4' in str(obj2.key):
+                                done4 = True
+                            if '/costmap.bag' in str(obj2.key):
+                                done5 = True
+                            if '/map.bag' in str(obj2.key):
+                                done6 = True
+                            if '/pcd_lidar.mp4' in str(obj2.key):
+                                done7 = True
+                            if '/tfstatic.bag' in str(obj2.key):
+                                done8 = True
+                            if '/report.pdf' in str(obj2.key):
+                                done9 = True
+                        if not done1 or not done2 or not done3 or not done4 or not done5 or not done6 or not done7 or not done8 or not done9:
+                            continue
+                        time.sleep(1)
+                        logging.info("发送： %s", str(obj1.key))
+                        # 1 获取json内容
+                        json_content = bucket.get_object(str(obj1.key)).read()
+                        # 2 获取token
+                        json_object = json.loads(json_content)
+                        data1 = {
+                            "equipmentNo": json_object['equipmentNo'],
+                            "secretKey": json_object['secretKey']
+                        }
+                        json_data1 = json.dumps(data1)
+                        logging.info("授权接口请求中： %s" % url1_private)
+                        logging.info("授权发送参数为： %s" % str(data1))
+                        request1 = urllib2.Request(url1_private, json_data1,
+                                                   headers={'Content-Type': 'application/json'})
+                        response1 = urllib2.urlopen(request1)
+                        result_json1 = response1.read()
+                        result_object1 = json.loads(result_json1)
+                        logging.info("授权接口请求结果为： %s", result_object1)
+                        access_token = result_object1.get('data').get('accessToken')
+                        # 要发送的JSON参数
+                        try:
+                            # logging.info("bag文件为： %s", json_object['rosBagPath'])
+                            old_date = json_object['dataName']
+                            data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                            equipment_no = json_object['equipmentNo']
+                            old_file_path = json_object['filePath']
+                            old_ros_bag_path = json_object['rosBagPath']
+                            task_id = json_object['taskId']
+                            trigger_id = json_object['triggerId']
+                        except Exception as e:
+                            logging.exception("callback报错：%s", str(e))
+                            continue
+
+                        # 将时区统一
+                        new_date = add_hour(old_date, 8)
+                        old_delete_list = []
+                        for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                            old_delete_list.append(str(obj_old.key))
+                            if 'callback.json' in str(obj_old.key):
+                                bucket.copy_object(bucket_name, str(obj_old.key),
+                                                   str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                        'callback_done.json'))
+                            else:
+                                bucket.copy_object(bucket_name, str(obj_old.key),
+                                                   str(obj_old.key).replace(old_date, new_date))
+                        bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                        bucket.delete_object(old_ros_bag_path)
+                        bucket.batch_delete_objects(old_delete_list)
+
+                        data2 = {
+                            "dataName": new_date,
+                            "dataSize": data_size,
+                            "equipmentNo": equipment_no,
+                            "filePath": old_file_path.replace(old_date, new_date),
+                            "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                            "taskId": task_id,
+                            "triggerId": trigger_id
+                        }
+                        json_data2 = json.dumps(data2)
+                        logging.info("回调接口请求中：%s" % url2_private)
+                        request2 = urllib2.Request(url2_private, json_data2,
+                                                   headers={'Content-Type': 'application/json',
+                                                            'authorization': access_token})
+                        response2 = urllib2.urlopen(request2)
+                        result_json2 = response2.read()
+                        result_object2 = json.loads(result_json2)
+                        logging.info("回调接口请求结果为： %s", result_object2)
+                except Exception as e:
+                    logging.exception("局部异常处理: %s" % str(e))
+            time.sleep(2)
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_guide/pjibot_camera.py

@@ -0,0 +1,120 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import parse_pji_image
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+
+logging.basicConfig(filename=path1 + 'log/pjibot_camera.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_mp4(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        local_mp4_dir1 = parse_pji_image.parse1('/ob_camera_01/color/image_raw', merged_bag_file_path,
+                                                local_parse_dir + '/camera1/')
+        mp4_file_name1 = 'camera'
+        local_mp4_file_path1 = local_mp4_dir1 + '/' + mp4_file_name1 + '.mp4'
+        local_delete_list.append(local_mp4_file_path1)
+        oss_csv_object_key1 = parse_prefix + mp4_file_name1 + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key1, local_mp4_file_path1)
+
+        local_mp4_dir2 = parse_pji_image.parse2('/ob_camera_02/color/image_raw', merged_bag_file_path,
+                                                local_parse_dir + '/camera2/')
+        mp4_file_name2 = 'camera2'
+        local_mp4_file_path2 = local_mp4_dir2 + '/' + mp4_file_name2 + '.mp4'
+        local_delete_list.append(local_mp4_file_path2)
+        oss_csv_object_key2 = parse_prefix + mp4_file_name2 + '.mp4'
+        bucket.put_object_from_file(oss_csv_object_key2, local_mp4_file_path2)
+
+    except Exception as e2:
+        # 当出现异常时执行的代码
+        logging.exception("生成摄像头视频报错: %s", e2)
+        # logging.exception("生成摄像头视频报错，删除脏数据: %s", e2)
+        # for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix):
+        #     bucket.delete_object(obj.key)
+
+
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                # 获取合并后的包
+                merged_bag_object_key = str(obj1.key)
+                # print(f'判断1{merged_bag_object_key}')
+                if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                    merged_bag_object_key_split = merged_bag_object_key.split('/')
+                    merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                    parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                    parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                    camera_done = False
+                    camera2_done = False
+                    callback_done = False
+                    for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                        if '/callback.json' in str(obj2.key):
+                            callback_done = True
+                        if '/camera.mp4' in str(obj2.key):
+                            # logging.info("存在摄像头视频: %s" % str(obj2.key))
+                            camera_done = True
+                        if '/camera2.mp4' in str(obj2.key):
+                            # logging.info("存在摄像头视频: %s" % str(obj2.key))
+                            camera2_done = True
+                    if camera_done and camera2_done:
+                        # logging.info("存在摄像头视频: %s" % str(parse_prefix_full))
+                        continue
+                    if not callback_done:  # 不存在存在callback.json的就不处理了
+                        # logging.info("数据已回调完成，不需要处理: %s" % str(parse_prefix_full))
+                        continue
+
+                    local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                    local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                    local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                    if not os.path.exists(local_merged_dir):
+                        os.makedirs(local_merged_dir)
+                    if not os.path.exists(local_parse_dir):
+                        os.makedirs(local_parse_dir)
+                    merged_bag_full_name = merged_bag_object_key_split[-1]
+                    merged_bag_name = merged_bag_full_name.split('.')[0]
+                    try:
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                    except Exception as e:
+                        logging.exception("下载合并后的bag包失败: %s" % str(e))
+
+                    local_delete_list.append(local_merged_bag_path)
+                    # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                    logging.info("生成视频: %s" % str(obj1.key))
+                    parse_to_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        pass
+                        # logging.exception("捕获到一个异常: %s" % str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_guide/pjibot_csv.py

@@ -0,0 +1,157 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import bagtocsv_rebot
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+path2 = '/mnt/disk001/run'
+path3 = '/mnt/disk001/cicv-data-closedloop/python3-pjibot-module'
+path4 = '/mnt/disk001/cicv-data-closedloop/python3-pjibot-module/filter_pos.py'
+pgm_path = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/resource/shiyanshi_newpgm_20240416.pgm'
+
+logging.basicConfig(filename=path1 + 'log/pjibot_csv.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_csv(costmap_bag, data_bag, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        bagtocsv_rebot.parse(costmap_bag, data_bag, local_parse_dir + '/csv/')
+        bagname = data_bag.split('/')[-1].split('.')[0]
+        local_csv_dir = os.path.join(local_parse_dir + '/csv/', bagname)
+        csv_file_name1 = 'pos_pji'
+        local_csv_file_path1 = str(local_csv_dir) + '/' + str(csv_file_name1) + '.csv'
+        local_delete_list.append(local_csv_file_path1)
+        oss_csv_object_key1 = parse_prefix + csv_file_name1 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key1, local_csv_file_path1)
+
+        csv_file_name2 = 'EgoState_pji'
+        local_csv_file_path2 = str(local_csv_dir) + '/' + str(csv_file_name2) + '.csv'
+        local_delete_list.append(local_csv_file_path2)
+        oss_csv_object_key2 = parse_prefix + csv_file_name2 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key2, local_csv_file_path2)
+
+        # 下载 track.png
+        track_png_key = parse_prefix + 'track.png'
+        bucket.get_object_to_file(track_png_key, str(local_csv_dir) + '/track1.png')
+        # 生成pdf 报告
+        os.chdir(path2)
+        command1 = './pji_single ' + str(local_csv_dir) + '/ ' + str(local_csv_dir) + '/ ' + str(
+            local_csv_dir) + '/track1.png ' + data_bag.split('/')[-1].split('.')[0]
+        logging.info("调用生成pdf 报告命令: %s" % str(command1))
+        os.system(command1)
+        bucket.put_object_from_file(parse_prefix + 'report.pdf',
+                                    str(local_csv_dir) + '/report.pdf')
+        local_delete_list.append(str(local_csv_dir) + '/report.pdf')
+
+        # ---------------------------------------------------
+        csv_file_name3 = 'merged_obstacles'
+        local_csv_file_path3 = str(local_csv_dir) + '/' + str(csv_file_name3) + '.csv'
+        oss_csv_object_key3 = parse_prefix + csv_file_name3 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key3, local_csv_file_path3)
+
+        # 根据 merged_obstacles 和 机器人指定的pgm文件 生成新的 merged_obstacles 文件
+        os.chdir(path3)
+        command2 = 'python3 ' + path4 + ' ' + pgm_path + ' ' + local_csv_file_path3
+        logging.info("调用命令merged_obstacles_new.csv生成命令: %s" % str(command2))
+        os.system(command2)
+        time.sleep(2)
+        bucket.put_object_from_file(oss_csv_object_key3.replace('merged_obstacles', 'merged_obstacles_new'),
+                                    local_csv_file_path3)  # 因为生成的文件是同名覆盖的
+        # todo 暂时不删除 排查问题
+        local_delete_list.append(local_csv_file_path3)
+
+        # 这里不要删除了，不然无法复现pdf
+        # bucket.delete_object(track_png_key)
+    except Exception as e2:
+        # 当出现异常时执行的代码
+        logging.exception("生成csv报错: %s", e2)
+
+
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        time.sleep(sleep_time)
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                # 获取合并后的包
+                merged_bag_object_key = str(obj1.key)
+                # print(f'判断1{merged_bag_object_key}')
+                if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                    merged_bag_object_key_split = merged_bag_object_key.split('/')
+                    merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                    parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                    parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                    csv1_done = False
+                    csv2_done = False
+                    csv3_done = False
+                    callback_undone = False
+                    for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                        if '/callback.json' in str(obj2.key):
+                            callback_undone = True
+                        if '/pos_pji.csv' in str(obj2.key):
+                            csv1_done = True
+                        if '/EgoState_pji.csv' in str(obj2.key):
+                            csv2_done = True
+                        if '/merged_obstacles.csv' in str(obj2.key):
+                            csv3_done = True
+                    if not callback_undone:  # 没有 callback.json
+                        # logging.info("数据已回调完成，不需要处理: %s" % str(parse_prefix_full))
+                        continue
+                    if csv1_done and csv2_done and csv3_done:
+                        # logging.info("存在场景还原csv: %s" % str(parse_prefix_full))
+                        continue
+
+                    logging.info("开始生成场景还原csv: %s" % str(obj1.key))
+                    # print(f'需要解析{merged_bag_object_key}')
+                    local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                    local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                    local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                    if not os.path.exists(local_merged_dir):
+                        os.makedirs(local_merged_dir)
+                    if not os.path.exists(local_parse_dir):
+                        os.makedirs(local_parse_dir)
+                    merged_bag_full_name = merged_bag_object_key_split[-1]
+                    merged_bag_name = merged_bag_full_name.split('.')[0]
+                    try:
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                    except Exception as e:
+                        logging.exception("下载合并后的bag包失败: %s" % str(e))
+
+                    local_delete_list.append(local_merged_bag_path)
+                    # 下载costmap.bag
+                    costmap_key = merged_prefix.replace('data_merge', '') + 'costmap.bag'
+                    logging.info("costmap.bag包的key为: %s" % str(costmap_key))
+                    bucket.get_object_to_file(costmap_key, local_merged_dir + 'costmap.bag')
+                    # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                    parse_csv(local_merged_dir + 'costmap.bag', local_merged_bag_path, parse_prefix_full,
+                              local_parse_dir, local_delete_list)
+
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        logging.exception("捕获到一个异常: %s" % str(e))
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_guide/pjibot_merge.py

@@ -0,0 +1,187 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from rosbag import Bag, Compression
+import logging
+import rosbag
+from std_msgs.msg import Header
+import rospy
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+
+logging.basicConfig(filename=path1 + 'log/pjibot_merge.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+
+sleep_time = 5  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+
+
+def merge(local_bags, merged_prefix, local_merged_dir, merged_bag_name):
+    try:
+        parse_prefix = merged_prefix.replace('data_merge', 'data_parse') + merged_bag_name.split('.')[0] + '/'
+        output_bag_file = local_merged_dir + merged_bag_name
+        with Bag(output_bag_file, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags)):
+                with Bag(local_bags[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        bucket.put_object_from_file(merged_prefix + merged_bag_name, output_bag_file)
+
+        # 获取只有1帧率的数据包
+        output_bag_file2 = local_merged_dir + merged_bag_name + '.merge'
+        tfstatic_key = merged_prefix.replace('data_merge/', '') + 'tfstatic.bag'
+        local_tfstatic_path = local_merged_dir + 'tfstatic.bag'
+        logging.info("tfstatic.bag包的key为: %s" % str(tfstatic_key))
+        bucket.get_object_to_file(tfstatic_key, local_tfstatic_path)
+
+        bag_a = rosbag.Bag(output_bag_file)
+        bag_b = rosbag.Bag(local_merged_dir + 'tfstatic.bag')
+
+        # compression_a = bag_a.get_compression()
+
+        tf_msg = None
+        for topic, msg, t in bag_b.read_messages(topics=['/tf_static']):
+            tf_msg = msg
+
+        if tf_msg:
+            first_timestamp = bag_a.get_start_time()
+            print(first_timestamp)
+            header = Header()
+            header.stamp = rospy.Time.from_sec(first_timestamp)
+            for transform in tf_msg.transforms:
+                transform.header.stamp = header.stamp
+            with rosbag.Bag(output_bag_file2, 'w') as outbag:
+                for topic, msg, t in bag_a.read_messages():
+                    outbag.write(topic, msg, t=rospy.Time.from_sec(t.to_sec()))
+                outbag.write('/tf_static', tf_msg, t=header.stamp)
+        bag_a.close()
+        bag_b.close()
+        build_map_key = parse_prefix + 'build_map.bag'
+        bucket.put_object_from_file(build_map_key, output_bag_file2)
+        # 根据合并后的包和map.bag 生成轨迹图片
+        # 获取只有1帧率的数据包
+        map_key = merged_prefix.replace('data_merge/', '') + 'map.bag'
+        local_map_path = local_merged_dir + 'map.bag'
+        logging.info("map.bag包的key为: %s" % str(map_key))
+        bucket.get_object_to_file(map_key, local_map_path)
+        jpg_file = local_merged_dir + merged_bag_name.split('.')[0] + '.jpg'
+        command1 = 'rosrun trajectory demo_node ' + local_map_path + ' ' + output_bag_file + ' ' + jpg_file
+        logging.info("调用命令轨迹图片生成命令: %s" % str(command1))
+        os.system(command1)
+        jpg_key = parse_prefix + 'track.png'
+        bucket.put_object_from_file(jpg_key, jpg_file)
+
+        costmap_key = merged_prefix.replace('data_merge/', '') + 'costmap.bag'
+        logging.info("costmap.bag包的key为: %s" % str(costmap_key))
+        local_costmap_path = local_merged_dir + 'costmap.bag'
+        bucket.get_object_to_file(costmap_key, local_costmap_path)
+
+        # 将三个单帧的包复制到指定采集数据目录一份
+        bucket.put_object_from_file(parse_prefix + 'tfstatic.bag', local_tfstatic_path)
+        bucket.put_object_from_file(parse_prefix + 'map.bag', local_map_path)
+        bucket.put_object_from_file(parse_prefix + 'costmap.bag', local_costmap_path)
+
+        return output_bag_file, output_bag_file2, jpg_file
+
+    except Exception as e:
+        logging.exception("bag包合并报错: %s" % str(e))
+
+
+'''
+cname：http://pji-bucket1.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+oss桶名： pji-bucket1
+oss桶名： oss://pji-bucket1
+'''
+# ------- 获取未合并的bag包，合并 -------
+if __name__ == '__main__':
+
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        try:
+            # print(f'当前轮次{turn}扫描开始。')
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            upload_completed_prefix_list = []
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1, delimiter='/'):
+                bag_list = []
+                target_path = ''
+                if str(obj1.key).count('/') == 2:  # pujin/robot-01/
+                    # 6 校验bag包个数
+                    for obj2 in oss2.ObjectIterator(bucket, prefix=str(obj1.key) + key2, delimiter='/'):
+                        if str(obj2.key).count(
+                                '/') == 4:  # pujin/robot-01/data/2023-12-20-02-16-56_obstacledetection_10/
+                            bag_need = str(obj2.key).split('_')[-1][:-1]
+                            count_bag = 0
+                            for obj3 in oss2.ObjectIterator(bucket, prefix=str(obj2.key)):
+                                if obj3.key[-3:] == 'bag':
+                                    count_bag = count_bag + 1
+                            if bag_need == str(count_bag):
+                                upload_completed_prefix_list.append(obj2.key)
+            # 处理
+            for prefix in upload_completed_prefix_list:
+                local_delete_list = []
+                oss_delete_list = []
+                # 获取要处理的包
+                oss_bags = []
+                local_bags = []
+                for obj in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if str(obj.key).endswith('.bag'):
+                        oss_bags.append(str(obj.key))
+                split_list = prefix.replace(key2, key3).split('/')
+                merged_prefix = '/'.join(split_list[0:-2]) + '/'
+                local_merged_dir = path1 + merged_prefix
+                if not os.path.exists(local_merged_dir):
+                    os.makedirs(local_merged_dir)
+                merged_bag_name = split_list[-2]
+                merged_bag_full_name = merged_bag_name + '.bag'
+                local_bag_dir = path1 + '/'.join(split_list[0:-1]) + '/'
+                if not os.path.exists(local_bag_dir):
+                    os.makedirs(local_bag_dir)
+
+                # 下载
+                for oss_bag in oss_bags:
+                    bag_name = str(oss_bag).split('/')[-1]
+                    local_bag_path = local_bag_dir + bag_name
+                    bucket.get_object_to_file(oss_bag, local_bag_path)
+                    local_bags.append(local_bag_path)
+                    local_delete_list.append(local_bag_path)
+                    oss_delete_list.append(oss_bag)
+
+                # 1 合并bag
+                logging.info("合并文件，key前缀为: %s" % str(local_merged_dir))
+                merged_bag_file_path, build_map_bag_local_path, jpg_file = merge(local_bags, merged_prefix,
+                                                                                 local_merged_dir, merged_bag_full_name)
+                local_delete_list.append(merged_bag_file_path)
+                local_delete_list.append(build_map_bag_local_path)
+                local_delete_list.append(jpg_file)
+                # 删除本地临时文件
+                if len(local_delete_list) > 0:
+                    for local_delete in local_delete_list:
+                        try:
+                            os.remove(local_delete)
+                        except Exception as e:
+                            logging.exception("删除本地临时文件报错: %s" % str(e))
+
+                # 删除oss原始文件
+                if len(oss_delete_list) > 0:
+                    bucket.batch_delete_objects(oss_delete_list)
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局错误处理: %s" % str(e))

src/python2/pjibot_guide/pjibot_pcd.py

@@ -0,0 +1,139 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+
+from resource import pcdtovideo_pji_deepcamera
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/'
+path2 = '/mnt/disk001/cicv-data-closedloop/python2-pjibot-double-camera-module-pji/resource/'
+logging.basicConfig(filename=path1 + 'log/pjibot_pcd.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjibot/'
+path1 = '/root/'
+sleep_time = 2  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path, parse_prefix2, local_parse_dir, local_delete_list):
+    global bucket
+    try:
+        # local_pcd_mp4_dir1 = pcdtovideo_pji_deepcamera.parse1('/ob_camera_01/depth/points', merged_bag_file_path,
+        #                                                       local_parse_dir + '/depth1/')
+        # local_pcd_mp4_dir2 = pcdtovideo_pji_deepcamera.parse2('/ob_camera_02/depth/points', merged_bag_file_path,
+        #                                                       local_parse_dir + '/depth2/')
+
+        os.chdir(path2)
+        command1 = 'sh run.sh ' + merged_bag_file_path + ' ' + local_parse_dir
+        logging.info("调用命令lidar视频生成命令: %s" % str(command1))
+        os.system(command1)
+
+        file_name_with_extension = os.path.basename(merged_bag_file_path)
+        file_name_without_extension = os.path.splitext(file_name_with_extension)[0]
+        parent_directory = os.path.dirname(merged_bag_file_path)
+        local_pcd_mp4_dir3 = parent_directory.replace('data_merge',
+                                                      'data_parse') + '/' + file_name_without_extension + '_pcd_lidar'
+        # local_pcd_mp4_dir3 = pcdtovideo_pji_lidar.parse(merged_bag_file_path, local_parse_dir + '/lidar/')
+
+        # pcd_mp4_file_name1 = 'pcd_depthcamera'
+        # pcd_mp4_file_name2 = 'pcd_depthcamera2'
+        pcd_mp4_file_name3 = 'pcd_lidar'
+        # local_delete_list.append(local_pcd_mp4_dir1 + '/' + pcd_mp4_file_name1 + '.mp4')
+        # local_delete_list.append(local_pcd_mp4_dir2 + '/' + pcd_mp4_file_name2 + '.mp4')
+        local_delete_list.append(local_pcd_mp4_dir3 + '/output_video_converted.mp4')
+        # oss_csv_object_key1 = parse_prefix2 + pcd_mp4_file_name1 + '.mp4'
+        # oss_csv_object_key2 = parse_prefix2 + pcd_mp4_file_name2 + '.mp4'
+        oss_csv_object_key3 = parse_prefix2 + pcd_mp4_file_name3 + '.mp4'
+        # bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_dir1 + '/' + pcd_mp4_file_name1 + '.mp4')
+        # logging.info("上传点云视频到: %s", oss_csv_object_key1)
+        # bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_dir2 + '/' + pcd_mp4_file_name2 + '.mp4')
+        # logging.info("上传点云视频到: %s", oss_csv_object_key2)
+        bucket.put_object_from_file(oss_csv_object_key3, local_pcd_mp4_dir3 + '/output_video_converted.mp4')
+        logging.info("上传点云视频到: %s", oss_csv_object_key3)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+        # for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix2):
+        #     bucket.delete_object(obj.key)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'pji-bucket1')
+    turn = 1
+    while True:
+        logging.info("当前轮次: %s" % str(turn))
+        turn += 1
+        try:
+            local_delete_list = []
+            oss_delete_list = []
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        # pcd1_done = False
+                        # pcd2_done = False
+                        pcd3_done = False
+                        callback_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if '/callback.json' in str(obj2.key):
+                                callback_done = True
+                            # if '/pcd_depthcamera.mp4' in str(obj2.key):
+                            #     pcd1_done = True
+                            if '/pcd_lidar.mp4' in str(obj2.key):
+                                pcd3_done = True
+                        if pcd3_done:
+                            # logging.info( "%s 存在点云视频 pcd_depthcamera.mp4 和 pcd_lidar.mp4" % str(parse_prefix_full))
+                            # logging.info("%s 存在点云视频 pcd_lidar.mp4 " % str(parse_prefix_full))
+                            continue
+                        if not callback_done:
+                            # logging.info("数据已回调完成，不需要处理: %s" % str(parse_prefix_full))
+                            continue
+                        logging.info("%s 缺少点云视频 pcd_depthcamera.mp4 和 pcd_lidar.mp4" % str(parse_prefix_full))
+                        # print(f'需要解析{merged_bag_object_key}')
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                        parse_to_pcd_mp4(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+                except Exception as e:
+                    logging.exception("报错: %s" % str(e))
+            # 删除本地临时文件
+            if len(local_delete_list) > 0:
+                for local_delete in local_delete_list:
+                    try:
+                        os.remove(local_delete)
+                    except Exception as e:
+                        logging.exception("删除本地临时文件报错: %s" % str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s" % str(e))

src/python2/pjibot_guide/resource/bagtocsv_rebot.py

@@ -0,0 +1,336 @@
+# coding: utf-8
+# !/usr/bin/env python2
+import os
+import rosbag
+import csv
+import math
+import rospy
+import sys
+import time
+import numpy as np
+from datetime import datetime
+import argparse
+import pandas as pd
+
+# from nav_msgs.msg import OccupancyGrid
+
+
+global_height, global_costmap, global_origin, global_resolution = None, None, None, None
+
+
+def calculate_start_index(g_h, local_origin, global_origin, resolution):
+    print(global_origin.position.x, global_origin.position.y)
+    x = g_h - 100 - int((local_origin.position.y - global_origin.position.y) / resolution) - 2
+    y = int((local_origin.position.x - global_origin.position.x) / resolution) + 1
+    return x, y
+
+
+def compare_costmaps(local_costmap, global_costmap, start_x, start_y):
+    dynamic_obstacles = []
+    # print("global_costmap.shape[0]:", global_costmap.shape[0])
+    # print("global_costmap.shape[1]:", global_costmap.shape[1])
+    for i in range(100):
+        for j in range(100):
+            global_x = start_x + i
+            global_y = start_y + j
+            if global_x < 0 or global_y < 0 or global_x >= global_costmap.shape[0] or global_y >= global_costmap.shape[
+                1]:
+                continue
+            if global_costmap[global_x][global_y] < 50 and local_costmap[i][j] >= 50:
+                dynamic_obstacles.append((global_x, global_y))
+    return dynamic_obstacles
+
+
+def process_global_rosbag(bagfile, global_topic):
+    global global_costmap, global_origin, global_resolution, global_height
+    with rosbag.Bag(bagfile, 'r') as bag:
+        for g_topic, g_msg, g_t in bag.read_messages(topics=global_topic):
+            global_costmap = np.array(g_msg.data).reshape(g_msg.info.height, g_msg.info.width)
+            global_costmap = np.flipud(global_costmap)  # Flip the global costmap vertically
+            global_origin = g_msg.info.origin
+            global_resolution = g_msg.info.resolution
+            global_height = g_msg.info.height
+            break
+
+
+def process_local_rosbag(bagfile, local_topic):
+    global global_costmap, global_origin, global_resolution, global_height
+    all_dynamic_obstacles = []
+    detected_obstacles = set()
+    is_first_frame = True
+
+    local_messages = []
+    with rosbag.Bag(bagfile, 'r') as bag:
+        start_time = bag.get_start_time()
+        end_time = bag.get_end_time()
+        total_time = end_time - start_time
+        print("total_time:", total_time)
+        for topic, msg, t in bag.read_messages(topics=local_topic):
+            local_messages.append((msg, t))
+
+        local_interval = total_time / len(local_messages)
+
+        for index, (msg, t) in enumerate(local_messages):
+            local_costmap = np.array(msg.data).reshape(msg.info.height, msg.info.width)
+            local_costmap = np.flipud(local_costmap)  # Flip local costmap vertically
+            local_origin = msg.info.origin
+            start_x, start_y = calculate_start_index(global_costmap.shape[0], local_origin, global_origin,
+                                                     msg.info.resolution)
+            frame_time = index * local_interval
+            dynamic_obstacles = compare_costmaps(local_costmap, global_costmap, start_x, start_y)
+            if is_first_frame:
+                all_dynamic_obstacles.extend([(frame_time, x, y) for x, y in dynamic_obstacles])
+                detected_obstacles.update((x, y) for x, y in dynamic_obstacles)
+                is_first_frame = False
+            else:
+                filtered_obstacles = [(frame_time, x, y) for x, y in dynamic_obstacles if
+                                      (x, y) not in detected_obstacles]
+                all_dynamic_obstacles.extend(filtered_obstacles)
+                detected_obstacles.update((x, y) for _, x, y in filtered_obstacles)
+
+    df = pd.DataFrame(all_dynamic_obstacles, columns=['frame_time', 'x', 'y'])
+
+    return df
+
+
+def merge_obstacles(df, global_height):
+    df.sort_values(by=['frame_time', 'x', 'y'], inplace=True)
+
+    merged_time = []
+    merged_rows = []
+    merged_columns = []
+    merged_counts = []
+    merge_count = 1
+
+    for i in range(1, len(df)):
+        if df.iloc[i]['frame_time'] == df.iloc[i - 1]['frame_time'] and df.iloc[i]['x'] == df.iloc[i - 1]['x'] + 1 and \
+                df.iloc[i]['y'] == df.iloc[i - 1]['y']:
+            merge_count += 1
+        else:
+            mid_frame_time = df.iloc[i - 1]['frame_time']
+            mid_row = df.iloc[i - (merge_count // 2 + 1)]['x']
+            mid_column = df.iloc[i - 1]['y']
+            merged_time.append(mid_frame_time)
+            merged_rows.append(mid_row)
+            merged_columns.append(mid_column)
+            merged_counts.append(merge_count)
+            merge_count = 1
+
+    mid_frame_time = df.iloc[-1]['frame_time']
+    mid_row = df.iloc[-1 - (merge_count // 2)]['x']
+    mid_column = df.iloc[-1]['y']
+    merged_time.append(mid_frame_time)
+    merged_rows.append(mid_row)
+    merged_columns.append(mid_column)
+    merged_counts.append(merge_count)
+
+    result_df = pd.DataFrame({'Time': merged_time, 'x': merged_rows, 'y': merged_columns, 'Count': merged_counts})
+    result_df['pos_x'] = result_df['y'].apply(lambda x: (x - 1) * 0.05 + 0.05 if x % 2 != 0 else (x - 1) * 0.05 + 0.025)
+    result_df['pos_y'] = (global_height - result_df['x']) * 0.05 + 0.025  # ????? height
+    print("global_height:", global_height)
+    result_df['Scaling_x'] = result_df['Count'] * 0.05
+    result_df['Scaling_y'] = 0.05
+    return result_df
+
+
+def parsezihao(input_dir, output_dir):
+    dic_EgoState = ['Time', 'simTime', 'simFrame', 'posX', 'posY', 'posZ', 'speedX', 'speedY', 'speedZ', 'accelX',
+                    'accelY', 'accelZ',
+                    'dimX', 'dimY', 'dimZ', 'obstacle', 'traveledDist']
+    # dic_DriverCtrl=['Time','simTime','simFrame','tarspeedX','tarspeedY','tarspeedZ','tardimX','tardimY','tardimZ']
+    EgoState_file = open(output_dir + "/" + "EgoState_pji.csv", 'w')
+    # DriverCtrl_file = open(output_dir + "/"+"DriverCtrl_pji.csv", 'w')
+    writer_EgoState = csv.writer(EgoState_file)
+    writer_EgoState.writerow(dic_EgoState)
+    # writer_DriverCtrl = csv.writer(DriverCtrl_file)
+    # writer_DriverCtrl.writerow(dic_DriverCtrl)
+
+    frame_max = sys.maxsize
+    count = 1
+    with rosbag.Bag(input_dir, 'r') as bag:
+        odom_flag = False
+        first_message_time = None
+        Frame_imu = 1
+        Frame_cmd_vel = 1
+        obstacle_state = 0
+        cur_mileage = ''
+
+        for topic, msg, t in bag.read_messages():  # t代表时间
+
+            if first_message_time is None:
+                first_message_time = t
+                first_message_time = rospy.Time.to_sec(first_message_time)
+                first_message_time = datetime.fromtimestamp(first_message_time)
+
+            if topic == "/obstacle_detection":
+                obstacle_state = msg.data
+                # print(msg.data)
+
+            if topic == "/sys_info":
+                cur_mileage = msg.cur_mileage
+
+            if topic == "/odom":
+                odom_flag = True
+                posX = msg.pose.pose.position.x
+                posY = msg.pose.pose.position.y
+                posZ = msg.pose.pose.position.z
+                speedX = msg.twist.twist.linear.x * 3.6
+                speedY = msg.twist.twist.linear.y * 3.6
+                speedZ = msg.twist.twist.linear.z * 3.6
+                dimX = msg.twist.twist.angular.x
+                dimY = msg.twist.twist.angular.y
+                dimZ = msg.twist.twist.angular.z
+
+            if topic == "/imu":
+
+                if odom_flag:
+                    accelX = msg.linear_acceleration.x
+                    accelY = msg.linear_acceleration.y
+                    accelZ = msg.linear_acceleration.z
+                    timestamp = rospy.Time.to_sec(t)
+                    date_time_imu = datetime.fromtimestamp(timestamp)
+                    simtime_imu = (date_time_imu - first_message_time).total_seconds()
+
+                    message_EgoState = [date_time_imu, simtime_imu, Frame_imu, posX, posY, posZ, speedX, speedY, speedZ,
+                                        accelX, accelY,
+                                        accelZ, dimX, dimY, dimZ, obstacle_state, cur_mileage]
+
+                    writer_EgoState.writerow(message_EgoState)
+                    Frame_imu += 1
+                else:
+                    print('6666')
+            '''        
+            if topic =='/cmd_vel':
+                timestamp = rospy.Time.to_sec(t)
+                date_time_cmd_vel = datetime.fromtimestamp(timestamp)
+                simtime_cmd_vel=(date_time_cmd_vel-first_message_time).total_seconds()
+                message_DriverCtrl =[date_time_cmd_vel,simtime_cmd_vel,Frame_cmd_vel,msg.linear.x*3.6,msg.linear.y*3.6,msg.linear.z*3.6,
+                                     msg.angular.x,msg.angular.y,msg.angular.z]
+                
+                                     
+                writer_DriverCtrl.writerow(message_DriverCtrl)
+                Frame_cmd_vel+=1
+            '''
+
+        EgoState_file.close()
+        # DriverCtrl_file.close()
+
+
+def parsehancheng(input_dir, output_dir):
+    def quaternion_to_euler(x, y, z, w):
+        # 将四元数归一化
+        try:
+            length = np.sqrt(x ** 2 + y ** 2 + z ** 2 + w ** 2)
+            x /= length
+            y /= length
+            z /= length
+            w /= length
+
+            # 计算欧拉角
+            # roll = np.arctan2(2*(w*x + y*z), 1 - 2*(x**2 + y**2))
+            # pitch = np.arcsin(2*(w*y - z*x))
+            yaw = np.arctan2(2 * (w * z + x * y), 1 - 2 * (y ** 2 + z ** 2))
+            return yaw
+        except:
+            return 0
+
+    dic_object_detection = ['Time', 'FrameID', 'HeadingAngle', 'X', 'Y', 'Z']
+    object_detection_file = open(output_dir + "/" + "pos_pji.csv", 'w')
+    writer_object_detection = csv.writer(object_detection_file)
+    writer_object_detection.writerow(dic_object_detection)
+
+    frame_max = sys.maxsize
+    with rosbag.Bag(input_dir, 'r') as bag:
+        # flag=False
+        framenum = 1
+        # hasLoc = False
+        for topic, msg, t in bag.read_messages():  # t代表时间
+
+            if topic == "/amcl_pose":  # 100hz  /odom
+                poseX = msg.pose.pose.position.x
+                poseY = msg.pose.pose.position.y
+                poseZ = msg.pose.pose.position.z
+                orientationX = msg.pose.pose.orientation.x
+                orientationY = msg.pose.pose.orientation.y
+                orientationZ = msg.pose.pose.orientation.z
+                orientationW = msg.pose.pose.orientation.w
+                egoyaw = quaternion_to_euler(orientationX, orientationY, orientationZ, orientationW)
+                message_location = [str(t)[:-6], framenum, egoyaw, poseX, poseY, poseZ]
+
+                writer_object_detection.writerow(message_location)
+                framenum += 1
+                # hasLoc = False
+                # data_read_flag=False
+
+        # driving_status_file.close()
+        object_detection_file.close()
+
+
+if __name__ == "__main__":
+
+    global_bagfile = sys.argv[1]  # 全局地图的rosbag包
+    # global_bagfile = '/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428/costmap.bag'
+    input_dir = sys.argv[2]  # 触发采集的rosbag包
+    # input_dir='/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428/2024-04-25-15-58-27_obstacledetection_30.bag'
+    bagname = input_dir.split('/')[-1].split('.')[0]
+    output_dir = sys.argv[3]  # 输出文件路径
+    # output_dir='/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428'
+    global_topic = '/move_base/global_costmap/costmap'
+    local_topic = '/move_base/local_costmap/costmap'
+
+    output_dir = os.path.join(output_dir, bagname)
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    '''
+    df, global_height = process_rosbag(input_dir, global_topic, local_topic)
+    result_df = merge_obstacles(df, global_height)
+    result_df.to_csv(os.path.join(output_dir,'merged_obstacles.csv'), index=False)
+    parsehancheng(input_dir, output_dir)
+    parsezihao(input_dir, output_dir)
+    print('successfully analysis '+input_dir)
+    '''
+
+    try:
+        process_global_rosbag(global_bagfile, global_topic)
+        df = process_local_rosbag(input_dir, local_topic)
+        result_df = merge_obstacles(df, global_height)
+        result_df.to_csv(os.path.join(output_dir, 'merged_obstacles.csv'), index=False)
+        parsehancheng(input_dir, output_dir)
+        parsezihao(input_dir, output_dir)
+        print('successfully analysis ' + input_dir)
+    except Exception as e:
+        print(e)
+
+
+def parse(costmap_bag, data_bag, output_dir):
+    global_bagfile = costmap_bag  # 全局地图的rosbag包
+    # global_bagfile = '/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428/costmap.bag'
+    input_dir = data_bag  # 触发采集的rosbag包
+    # input_dir='/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428/2024-04-25-15-58-27_obstacledetection_30.bag'
+    bagname = input_dir.split('/')[-1].split('.')[0]
+    # output_dir='/media/dell/56FAD34BFAD32651/data/pujin_datareturn/20240428'
+    global_topic = '/move_base/global_costmap/costmap'
+    local_topic = '/move_base/local_costmap/costmap'
+
+    output_dir = os.path.join(output_dir, bagname)
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    '''
+    df, global_height = process_rosbag(input_dir, global_topic, local_topic)
+    result_df = merge_obstacles(df, global_height)
+    result_df.to_csv(os.path.join(output_dir,'merged_obstacles.csv'), index=False)
+    parsehancheng(input_dir, output_dir)
+    parsezihao(input_dir, output_dir)
+    print('successfully analysis '+input_dir)
+    '''
+
+    try:
+        process_global_rosbag(global_bagfile, global_topic)
+        df = process_local_rosbag(input_dir, local_topic)
+        result_df = merge_obstacles(df, global_height)
+        result_df.to_csv(os.path.join(output_dir, 'merged_obstacles.csv'), index=False)
+        parsehancheng(input_dir, output_dir)
+        parsezihao(input_dir, output_dir)
+        print('successfully analysis ' + input_dir)
+    except Exception as e:
+        print(e)

src/python2/pjibot_guide/resource/convert_rosbag_to_pcd.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import sys
+import os
+import subprocess
+import multiprocessing
+import rosbag
+
+
+def convert_bag_to_pcd(input_dir, output_dir):
+    command = 'rosrun pcl_ros bag_to_pcd {} /scan_map_icp_amcl_node/scan_point_transformed {}'.format(input_dir,
+                                                                                                      output_dir)
+    process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    stdout, stderr = process.communicate()
+
+
+def calculate_frame_rate(rosbag_path):
+    with rosbag.Bag(rosbag_path, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == "/scan_map_icp_amcl_node/scan_point_transformed":
+                num_count += 1
+        duration = bag.get_end_time() - bag.get_start_time()
+        frame_rate = num_count / float(duration) if duration > 0 else 0
+    return frame_rate
+
+
+def save_frame_rate(lidar_output_base, frame_rate):
+    frame_rate_file = os.path.join(lidar_output_base, 'frame_rate.txt')
+    with open(frame_rate_file, 'w') as file:
+        file.write(str(frame_rate))
+
+
+def process_file(file):
+    root, filename = file
+    inputFilePath = os.path.join(root, filename)
+    ascii_folder = os.path.join(root, '../pcd_ascii')
+    try:
+        os.makedirs(ascii_folder)
+    except Exception:
+        print '创建目录失败 %s' % ascii_folder
+        pass
+    tempFilePath = os.path.join(ascii_folder, filename)
+
+    command = "pcl_convert_pcd_ascii_binary {} {} 0".format(inputFilePath, tempFilePath)
+    os.system(command)
+
+
+def main():
+    rosbag_path = sys.argv[1]
+    output_base_path = sys.argv[2]
+    bag_base_name = os.path.basename(rosbag_path).split('.')[0]
+    lidar_output_base = os.path.join(output_base_path, bag_base_name + '_pcd_lidar')
+    pcd_folder_path = os.path.join(lidar_output_base, 'pcd')
+
+    if not os.path.exists(pcd_folder_path):
+        os.makedirs(pcd_folder_path)
+
+    # Convert ROS bag to PCD
+    convert_bag_to_pcd(rosbag_path, pcd_folder_path)
+
+    # Calculate and save frame rate
+    frame_rate = calculate_frame_rate(rosbag_path)
+    save_frame_rate(lidar_output_base, frame_rate)
+
+    # Process files in parallel
+    files_to_process = []
+    for root, dirs, files in os.walk(pcd_folder_path):
+        for file in files:
+            if file.endswith(".pcd"):
+                files_to_process.append((root, file))
+
+    num_processes = 4
+    pool = multiprocessing.Pool(num_processes)
+    pool.map(process_file, files_to_process)
+    pool.close()
+    pool.join()
+
+
+if __name__ == '__main__':
+    main()

src/python2/pjibot_guide/resource/create_video_from_pcd.py

@@ -0,0 +1,86 @@
+import sys
+import matplotlib.pyplot as plt
+import cv2
+import os
+import numpy as np
+from pyntcloud import PyntCloud
+import subprocess
+
+
+def find_global_min_max(pcd_folder_path):
+    min_x, max_x = np.inf, -np.inf
+    min_y, max_y = np.inf, -np.inf
+    min_z, max_z = np.inf, -np.inf
+    pcd_files = [os.path.join(pcd_folder_path, f) for f in os.listdir(pcd_folder_path) if f.endswith('.pcd')]
+    for pcd_path in pcd_files:
+        cloud = PyntCloud.from_file(pcd_path)
+        points = cloud.points
+        min_x, max_x = min(min_x, points['x'].min()), max(max_x, points['x'].max())
+        min_y, max_y = min(min_y, points['y'].min()), max(max_y, points['y'].max())
+        min_z, max_z = min(min_z, points['z'].min()), max(max_z, points['z'].max())
+    return (min_x, max_x), (min_y, max_y), (min_z, max_z)
+
+
+def process_pcd_to_top_view_image(pcd_path, output_path, axis_limits):
+    cloud = PyntCloud.from_file(pcd_path)
+    points = cloud.points
+    fig = plt.figure(figsize=(10, 10))
+    ax = fig.add_subplot(111, projection='3d')
+    ax.scatter(points['x'], points['y'], points['z'], s=1, color='white')
+    ax.view_init(elev=90, azim=90)
+    ax.set_xlim(axis_limits[0])
+    ax.set_ylim(axis_limits[1])
+    ax.set_zlim(axis_limits[2])
+    ax.set_facecolor('black')
+    fig.patch.set_facecolor('black')
+    plt.axis('off')
+    plt.savefig(output_path, bbox_inches='tight', pad_inches=0)
+    plt.close()
+
+
+def create_video_from_images(image_folder, output_video_path, frame_rate):
+    images = [img for img in sorted(os.listdir(image_folder)) if img.endswith(".jpg")]
+    frame = cv2.imread(os.path.join(image_folder, images[0]))
+    height, width, layers = frame.shape
+    video = cv2.VideoWriter(output_video_path, cv2.VideoWriter_fourcc(*'mp4v'), float(frame_rate), (width, height))
+    for image in images:
+        frame = cv2.imread(os.path.join(image_folder, image))
+        video.write(frame)
+    video.release()
+    print(f"Video successfully saved to: {output_video_path}")
+    convert_video(output_video_path)
+
+
+def convert_video(input_video_path):
+    output_video_path = input_video_path.replace(".mp4", "_converted.mp4")
+    command = f"ffmpeg -i {input_video_path} -c:v libx264 -preset fast -crf 23 {output_video_path}"
+    subprocess.run(command, shell=True)
+    os.remove(input_video_path)
+    print(f"Converted video saved as {output_video_path} and original video deleted.")
+
+
+if __name__ == '__main__':
+    bag_base_name = sys.argv[1]
+    output_base_path = sys.argv[2]
+
+    lidar_output_base = os.path.join(output_base_path, bag_base_name + '_pcd_lidar')
+    pcd_folder_path = os.path.join(lidar_output_base, 'pcd_ascii')
+    images_folder_path = os.path.join(lidar_output_base, 'images')
+    video_path = os.path.join(lidar_output_base, 'output_video.mp4')
+    frame_rate_file = os.path.join(output_base_path, bag_base_name + '_pcd_lidar', 'frame_rate.txt')
+
+    if not os.path.exists(images_folder_path):
+        os.makedirs(images_folder_path)
+
+    with open(frame_rate_file, 'r') as file:
+        frame_rate = file.read().strip()
+
+    axis_limits = find_global_min_max(pcd_folder_path)
+
+    pcd_files = [f for f in os.listdir(pcd_folder_path) if f.endswith('.pcd')]
+    for file_name in pcd_files:
+        pcd_file_path = os.path.join(pcd_folder_path, file_name)
+        image_file_path = os.path.join(images_folder_path, file_name.replace('.pcd', '.jpg'))
+        process_pcd_to_top_view_image(pcd_file_path, image_file_path, axis_limits)
+
+    create_video_from_images(images_folder_path, video_path, frame_rate)

src/python2/pjibot_guide/resource/create_video_from_pcd_bak.py

@@ -0,0 +1,85 @@
+import sys
+import matplotlib.pyplot as plt
+import cv2
+import os
+import numpy as np
+from pyntcloud import PyntCloud
+
+
+def find_global_min_max(pcd_folder_path):
+    min_x, max_x = np.inf, -np.inf
+    min_y, max_y = np.inf, -np.inf
+    min_z, max_z = np.inf, -np.inf
+    pcd_files = [os.path.join(pcd_folder_path, f) for f in os.listdir(pcd_folder_path) if f.endswith('.pcd')]
+    for pcd_path in pcd_files:
+        cloud = PyntCloud.from_file(pcd_path)
+        points = cloud.points
+        min_x, max_x = min(min_x, points['x'].min()), max(max_x, points['x'].max())
+        min_y, max_y = min(min_y, points['y'].min()), max(max_y, points['y'].max())
+        min_z = 0
+        max_z = 0.1
+        # min_z, max_z = min(min_z, points['z'].min()), max(max_z, points['z'].max())
+    return (min_x, max_x), (min_y, max_y), (min_z, max_z)
+
+
+def process_pcd_to_top_view_image(pcd_path, output_path, axis_limits):
+    cloud = PyntCloud.from_file(pcd_path)
+    points = cloud.points
+    plt.figure(figsize=(10, 10))
+    ax = plt.axes(projection='3d')
+    ax.scatter(points['x'], points['y'], points['z'], s=1, color='blue')
+    ax.view_init(elev=90, azim=90)
+
+    # Set the axis limits
+    ax.set_xlim(axis_limits[0])
+    ax.set_ylim(axis_limits[1])
+    ax.set_zlim(axis_limits[2])
+
+    plt.axis('off')
+    plt.savefig(output_path, bbox_inches='tight', pad_inches=0)
+    plt.close()
+
+
+def create_video_from_images(image_folder, output_video_path, frame_rate):
+    images = [img for img in sorted(os.listdir(image_folder)) if img.endswith(".jpg")]
+    frame = cv2.imread(os.path.join(image_folder, images[0]))
+    height, width, layers = frame.shape
+    video = cv2.VideoWriter(output_video_path, cv2.VideoWriter_fourcc(*'mp4'), float(frame_rate), (width, height))
+    for image in images:
+        frame = cv2.imread(os.path.join(image_folder, image))
+        video.write(frame)
+    video.release()
+    print(f"视频已成功保存在：{output_video_path}")
+
+
+if __name__ == '__main__':
+    bag_base_name = sys.argv[1]
+    output_base_path = sys.argv[2]
+
+    print(f"base路径为：{bag_base_name}")
+    lidar_output_base = os.path.join(output_base_path, bag_base_name + '_pcd_lidar')
+    pcd_folder_path = os.path.join(lidar_output_base, 'pcd_ascii')
+    images_folder_path = os.path.join(lidar_output_base, 'images')
+    video_path = os.path.join(lidar_output_base, 'output_video.mp4')
+    frame_rate_file = os.path.join(output_base_path, bag_base_name + '_pcd_lidar', 'frame_rate.txt')
+
+    # 确保图片目录存在
+    if not os.path.exists(images_folder_path):
+        os.makedirs(images_folder_path)
+
+    # 读取帧率
+    with open(frame_rate_file, 'r') as file:
+        frame_rate = file.read().strip()
+
+    # Determine the axis limits based on all PCD files
+    axis_limits = find_global_min_max(pcd_folder_path)
+
+    # 处理每个PCD文件生成图像
+    pcd_files = [f for f in os.listdir(pcd_folder_path) if f.endswith('.pcd')]
+    for file_name in pcd_files:
+        pcd_file_path = os.path.join(pcd_folder_path, file_name)
+        image_file_path = os.path.join(images_folder_path, file_name.replace('.pcd', '.jpg'))
+        process_pcd_to_top_view_image(pcd_file_path, image_file_path, axis_limits)
+
+    # 从图像生成视频
+    create_video_from_images(images_folder_path, video_path, frame_rate)

src/python2/pjibot_guide/resource/parse_pji_image.py

@@ -0,0 +1,116 @@
+# coding: utf-8
+
+import sys
+
+import os
+import rospy
+import rosbag
+import csv
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+import argparse
+import struct
+import subprocess
+from subprocess import Popen, PIPE
+
+bridge = CvBridge()
+
+
+def parsebag(f, output_dir, target_topic):
+    rosbag_name = f[f.rindex("/"):-4]
+    output_path = output_dir + rosbag_name
+
+    with rosbag.Bag(f, 'r') as bag:
+        count = 0
+        for key, val in bag.get_type_and_topic_info()[1].items():
+            if val[0] == 'sensor_msgs/Image':
+
+                for topic, msg, t in bag.read_messages(key):
+                    if topic == target_topic:
+                        img = bridge.imgmsg_to_cv2(msg, 'bgr8')
+                        # img = bridge.compressed_imgmsg_to_cv2(msg, 'bgr8')
+                        timestr = msg.header.stamp.to_nsec()
+                        image_name = str(timestr) + ".jpg"
+                        if not os.path.exists(output_path + '_' + 'image'):
+                            os.makedirs(output_path + '_' + 'image')
+                        output_path_img = os.path.join(output_path + '_' + 'image', image_name)
+                        cv2.imwrite(output_path_img, img)
+                        # print(count)
+                        count = count + 1
+    return count
+
+
+def main():
+    input_dir = sys.argv[1]
+    # input_dir='/media/dell/BFAC-F22B/data/pujin_datareturn/pujin_robot-01_data_merge_2023-12-20-02-22-18_obstacledetection_10.bag'
+    output_dir = sys.argv[2]
+    # output_dir = '/media/dell/BFAC-F22B/data/pujin_datareturn'
+    topic = '/camera/color/image_raw'  # /camera/color/image_raw
+
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    # print(dirt)
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+
+
+if __name__ == '__main__':
+    main()
+
+
+def parse1(topic, input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    output_dir = output_mp4_dir
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+    return dirt
+
+def parse2(topic, input_bag_file, output_mp4_dir):
+    input_dir = input_bag_file
+    output_dir = output_mp4_dir
+    num_count = parsebag(input_dir, output_dir, topic)
+    print("解析完成")
+    dirt = os.path.join(output_dir, input_dir.split('/')[-1].split('.')[0] + '_' + 'image')
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+    command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + [dirt + '/*.jpg'] + ['-tag:v',
+                                                                                                         'avc1',
+                                                                                                         '-y'] + [
+                  dirt + '/camera2.mp4']
+    p = Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    p.communicate()
+    list1 = os.listdir(dirt)
+    for i in list1:
+        if i.split('.')[-1] == 'jpg':
+            os.remove(os.path.join(dirt, i))
+    return dirt

src/python2/pjibot_guide/resource/pcdtovideo_pji_deepcamera.py

@@ -0,0 +1,213 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Nov  1 13:38:28 2023
+
+@author: dell
+"""
+import subprocess
+from subprocess import Popen, PIPE
+import os
+import sys
+import math
+import cv2
+import numpy as np
+import shutil
+import rosbag
+
+def parse1(topic_name,input_dir, output_dir):
+
+
+
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_depthcamera' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == topic_name:    # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + [topic_name] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                # pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+                # draw_points(pic, tempFilePath)
+                # cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+                # pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+                pic = np.zeros([800, 1600, 3])
+                f = open(tempFilePath, "r")
+                ff = f.readlines()[11:]
+
+                for i in range(0, len(ff)):
+                    point = ff[i].split()[:4]
+                    point_x = float(point[0])
+                    point_y = float(point[1])
+                    point_z = float(point[2])
+                    points_intensity = float(point[2])
+                    # t = np.dot(np.linalg.inv(a),np.array([point_x,point_y,point_z,1]))
+                    # x = t[0]
+                    # y = t[1]
+                    x = -point_x
+                    y = -point_y
+
+                    if math.isnan(point_x):
+                        pass
+                    else:
+                        cv2.circle(pic, (int(800 - x * 60), int(400 - y * 60)), 0, (255, 255, 255), 0)
+
+                cv2.imwrite(outputFilePath, pic)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_depthcamera.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]
+
+def parse2(topic_name,input_dir, output_dir):
+    bag_name = input_dir.split('/')[-1].split('.')[0]
+    output_dir = os.path.join(output_dir, bag_name + '_pcd_depthcamera' + '/pcd')
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    with rosbag.Bag(input_dir, 'r') as bag:
+        num_count = 0
+        for topic, msg, t in bag.read_messages():
+            if topic == topic_name:   # /scan_map_icp_amcl_node/scan_point_transformed
+                num_count += 1
+
+    bagtime = int(input_dir.split('/')[-1].split('.')[0].split('_')[-1])
+    hz = str(float(num_count / bagtime))
+    print(hz)
+
+    #######################解析rosbag中的点云point_concat话题，获得原始pcd文件#######################
+    command = ['rosrun', 'pcl_ros', 'bag_to_pcd'] + [input_dir] + [topic_name] + [output_dir]
+    command = ' '.join(command)
+    os.system(command)
+    file1 = os.path.join(output_dir[0:-4], 'pcd_ascii')
+    file2 = os.path.join(output_dir[0:-4], 'jpg')
+    if not os.path.exists(file1):
+        os.makedirs(file1)
+    if not os.path.exists(file2):
+        os.makedirs(file2)
+
+    #######################将原始pcd文件转化成pcd-ascii格式,并生成jpg文件#######################
+    for root, dirs, files in os.walk(output_dir[0:-4]):
+
+        # find .pcd files and do the transfer twice
+        for file in files:
+            if "pcd" == root[-3:] and ".pcd" == file[-4:]:
+
+                inputFilePath = root + "/" + file
+                tempFilePath = root[:-3] + "pcd_ascii/" + file
+                outputFilePath = root[:-3] + "jpg/" + file[:-3] + "jpg"
+
+                # transfer pcd_utf-8 to pcd_ascii
+                command = "pcl_convert_pcd_ascii_binary " + \
+                          inputFilePath + \
+                          " " + \
+                          tempFilePath + \
+                          " 0"
+                # print(command)
+                os.system(command)
+
+                # make sure the temp file exist, invalid input file may cause this issue
+                if not os.path.exists(tempFilePath):
+                    continue
+
+                # transfer pcd_ascii to jpg
+                # pic = np.zeros([200, 400, 3])  #pic = np.zeros([800, 1600, 3])
+                # draw_points(pic, tempFilePath)
+                # cv2.imwrite(outputFilePath, pic)
+                # print("jpg generated: ", outputFilePath)
+                # pcd_path = "D:/文件/2-课题/科技部3.2/影子模式/pcd/data/pcd_ascii/1666841252.226625000.pcd"
+                pic = np.zeros([800, 1600, 3])
+                f = open(tempFilePath, "r")
+                ff = f.readlines()[11:]
+
+                for i in range(0, len(ff)):
+                    point = ff[i].split()[:4]
+                    point_x = float(point[0])
+                    point_y = float(point[1])
+                    point_z = float(point[2])
+                    points_intensity = float(point[2])
+                    # t = np.dot(np.linalg.inv(a),np.array([point_x,point_y,point_z,1]))
+                    # x = t[0]
+                    # y = t[1]
+                    x = -point_x
+                    y = -point_y
+
+                    if math.isnan(point_x):
+                        pass
+                    else:
+                        cv2.circle(pic, (int(800 - x * 60), int(400 - y * 60)), 0, (255, 255, 255), 0)
+
+                cv2.imwrite(outputFilePath, pic)
+            else:
+                break
+
+    #######################将转化的点云jpg合成视频#######################
+    jpg_list = os.listdir(file2)
+    if not jpg_list == []:
+        command = ['ffmpeg', '-f', 'image2', '-r', hz, '-pattern_type', 'glob', '-i'] + ['"jpg/*.jpg"'] + ['-tag:v',
+                                                                                                           'avc1',
+                                                                                                           '-y'] + [
+                      'pcd_depthcamera2.mp4']
+        result_string = " ".join(command)
+        p = Popen(result_string, shell=True, cwd=output_dir[0:-4] + '/', stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        p.wait()
+    shutil.rmtree(file1)
+    shutil.rmtree(file2)
+    shutil.rmtree(output_dir)
+    return output_dir[0:-4]

src/python2/pjibot_guide/resource/run.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+
+
+python2 convert_rosbag_to_pcd.py "$1" "$2"
+python3 create_video_from_pcd.py "$(basename $1 .bag)"  "$2"
+

src/python2/pjisuv/README.md

@@ -0,0 +1,18 @@
+# pjisuv-module
+nohup python2 pjisuv_merge.py > log/pjisuv_merge.out 2>&1 &
+nohup python2 pjisuv_csv.py > log/pjisuv_csv.out 2>&1 &
+nohup python2 pjisuv_camera.py > log/pjisuv_camera.out 2>&1 &
+nohup python2 pjisuv_pcd.py > log/pjisuv_pcd.out 2>&1 & 
+nohup python2 pjisuv_xosc.py > log/pjisuv_xosc.out 2>&1 &
+nohup python2 pjisuv_simulation.py > log/pjisuv_simulation.out 2>&1 &
+nohup python2 pjisuv_callback.py > log/pjisuv_callback.out 2>&1 &
+
+# 
+多功能车没有hmi，之前采取的方案是用orig.csv生成相同但不同名的两个xosc，我觉得不合理，现在只生成一个orig
+
+
+# oss 配置
+cname：http://open-bucket.oss.icvdc.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+预设OSS路径： oss://open-bucket

src/python2/pjisuv/callback-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 callback.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjisuv/callback-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 allback.py > log/callback.out 2>&1 &

src/python2/pjisuv/callback-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/callback.log

src/python2/pjisuv/callback.py

@@ -0,0 +1,162 @@
+# -*- coding: utf-8 -*-
+import json
+import time
+import urllib2
+import oss2
+from datetime import datetime, timedelta
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/callback.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/'
+sleep_time = 60  # 每多少秒扫描一次
+
+url1_public = "http://1.202.169.139:9081/device/auth"
+url1_private = "http://10.14.86.127:9081/device/auth"
+url2_public = " http://1.202.169.139:9081/device/data/callback"
+url2_private = "http://10.14.86.127:9081/device/data/callback"
+
+
+def add_hour(date_string, hour_number):
+    original_date = datetime.strptime(date_string, "%Y-%m-%d-%H-%M-%S")
+    new_date = original_date + timedelta(hours=hour_number)
+    return new_date.strftime("%Y-%m-%d-%H-%M-%S")
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+if __name__ == '__main__':
+    # 1 登录验证 。
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+
+    # 2 填写自定义域名，例如example.com。获取桶。
+    # 3 填写Bucket名称，并设置is_cname=True来开启CNAME。CNAME是指将自定义域名绑定到存储空间。
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket_name = 'open-bucket'
+    bucket = oss2.Bucket(auth, endpoint, bucket_name)
+
+    while True:
+        logging.info("开始新一轮扫描")
+        local_delete_list = []
+        oss_delete_list = []
+        upload_completed_prefix_list = []
+        # 4 获取即将被合并的bag目录
+        logging.info("开始扫描目录： %s" % str(key1))
+        for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+            if 'callback.json' in str(obj1.key):
+                time.sleep(1)
+                prefix = '/'.join(str(obj1.key).split('/')[:-1])
+
+                pos_orig_csv = False
+                pos_hmi_csv = False
+                drive_csv = False
+                camera_mp4 = False
+                pcd_forwardlook_mp4 = False
+                pcd_overlook_mp4 = False
+                scenario_orig_xosc = False
+                scenario_hmi_xosc = False
+                scenario_orig_mp4 = False
+                scenario_hmi_mp4 = False
+                camera_bag = False
+                fusion_bag = False
+                plan_bag = False
+                control_bag = False
+                callback_json = False
+                for obj2 in oss2.ObjectIterator(bucket, prefix=prefix):
+                    if 'callback.json' in str(obj2.key):
+                        callback_json = True
+                    if 'camera.mp4' in str(obj2.key):
+                        camera_mp4 = True
+                    if 'drive.csv' in str(obj2.key):
+                        drive_csv = True
+                    if 'pcd_forwardlook.mp4' in str(obj2.key):
+                        pcd_forwardlook_mp4 = True
+                    if 'pcd_overlook.mp4' in str(obj2.key):
+                        pcd_overlook_mp4 = True
+                    if 'pos_orig.csv' in str(obj2.key):
+                        pos_orig_csv = True
+                    if 'scenario_orig.mp4' in str(obj2.key):
+                        scenario_orig_mp4 = True
+                    if 'scenario_orig.xosc' in str(obj2.key):
+                        scenario_orig_xosc = True
+
+                if not callback_json or not camera_mp4 or not drive_csv or not pcd_forwardlook_mp4 or not pcd_overlook_mp4 or not pos_orig_csv or not scenario_orig_mp4 or not scenario_orig_xosc:
+                    continue
+                time.sleep(2)
+                logging.info("发送： %s" % str(obj1.key))
+                # 1 获取json内容
+                json_content = bucket.get_object(str(obj1.key)).read()
+                # 2 获取token
+                json_object = json.loads(json_content)
+                data1 = {
+                    "equipmentNo": json_object['equipmentNo'],
+                    "secretKey": json_object['secretKey']
+                }
+                json_data1 = json.dumps(data1)
+                logging.info("授权接口请求中： %s" % url1_private)
+                request1 = urllib2.Request(url1_private, json_data1,
+                                           headers={'Content-Type': 'application/json'})
+                response1 = urllib2.urlopen(request1)
+                result_json1 = response1.read()
+                result_object1 = json.loads(result_json1)
+                logging.info("授权接口请求结果为： %s", result_object1)
+                try:
+                    access_token = result_object1.get('data').get('accessToken')
+                    logging.info("bag文件为： %s" % str(json_object['rosBagPath']))
+                    old_date = json_object['dataName']
+                    data_size = bucket.get_object_meta(json_object['rosBagPath']).content_length
+                    equipment_no = json_object['equipmentNo']
+                    old_file_path = json_object['filePath']
+                    old_ros_bag_path = json_object['rosBagPath']
+                    task_id = json_object['taskId']
+                    trigger_id = json_object['triggerId']
+                except Exception as e:
+                    logging.exception("callback报错： %s" % str(e))
+                    continue
+                # 将时区统一
+                new_date = add_hour(old_date, 8)
+                old_delete_list = []
+                for obj_old in oss2.ObjectIterator(bucket, prefix=old_file_path):
+                    old_delete_list.append(str(obj_old.key))
+                    if 'callback.json' in str(obj_old.key):
+                        bucket.copy_object(bucket_name, str(obj_old.key),
+                                           str(obj_old.key).replace(old_date, new_date).replace('callback.json',
+                                                                                                'callback_done.json'))
+                    else:
+                        bucket.copy_object(bucket_name, str(obj_old.key), str(obj_old.key).replace(old_date, new_date))
+                bucket.copy_object(bucket_name, old_ros_bag_path, old_ros_bag_path.replace(old_date, new_date))
+                bucket.delete_object(old_ros_bag_path)
+                bucket.batch_delete_objects(old_delete_list)
+
+                triggerId = json_object['triggerId']
+                data2 = {
+                    "dataName": new_date,
+                    "dataSize": data_size,
+                    "equipmentNo": equipment_no,
+                    "filePath": old_file_path.replace(old_date, new_date),
+                    "rosBagPath": old_ros_bag_path.replace(old_date, new_date),
+                    "taskId": task_id,
+                    # "triggerId": ["1744180835122155522", "1744178775815360514"]
+                    "triggerId": triggerId
+                }
+                json_data2 = json.dumps(data2)
+                logging.info("回调接口请求中：%s" % url2_private)
+                request2 = urllib2.Request(url2_private, json_data2,
+                                           headers={'Content-Type': 'application/json',
+                                                    'authorization': access_token})
+
+                response2 = urllib2.urlopen(request2)
+                result_json2 = response2.read()
+                result_object2 = json.loads(result_json2)
+                logging.info("回调接口请求结果为： %s", result_object2)
+        time.sleep(sleep_time)

src/python2/pjisuv/camera-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 camera.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjisuv/camera-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 camera.py > log/camera.out 2>&1 &

src/python2/pjisuv/camera-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/camera.log

src/python2/pjisuv/camera.py

@@ -0,0 +1,143 @@
+# -*- coding: utf-8 -*-
+import os
+import shutil
+import time
+import zipfile
+
+import oss2
+from resource import camera_mp4
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/camera.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def zip_jpg_files(directory):
+    # 获取指定目录下的所有.jpg 文件路径
+    jpg_files = [os.path.join(directory, f) for f in os.listdir(directory) if f.endswith('.jpg')]
+
+    # 创建或覆盖同目录下的 camera.zip 压缩包
+    with zipfile.ZipFile(os.path.join(directory, 'camera.zip'), 'w') as zipf:
+        for file1 in jpg_files:
+            zipf.write(file1, os.path.basename(file1))
+
+
+def parse_to_mp4(bucket, merged_bag_object_key, merged_bag_file_path, parse_prefix_full1, local_parse_dir, data_name):
+    try:
+        # 1 解析
+        local_mp4_dir, hz = camera_mp4.parse(merged_bag_file_path, local_parse_dir)
+        logging.info("已生成图片jpg和视频mp4到目录: %s", local_mp4_dir)
+        oss_mp4_key1 = parse_prefix_full1 + 'camera.mp4'
+        oss_mp4_key2 = parse_prefix_full1 + 'camera_' + data_name + '_' + str(hz) + '.mp4'
+        local_mp4_path = local_mp4_dir + '/camera.mp4'
+        oss_zip_key = parse_prefix_full1 + 'camera_' + data_name + '_' + str(hz) + '.zip'
+        local_zip_path = local_mp4_dir + '/camera.zip'
+        # 2 上传 camera.mp4 文件
+        bucket.put_object_from_file(oss_mp4_key1, local_mp4_path)
+        bucket.put_object_from_file(oss_mp4_key2, local_mp4_path)
+        logging.info("已上传图像视频到: %s", oss_mp4_key2)
+        # 3 删除本地 camera.mp4
+        try:
+            os.remove(local_mp4_path)
+        except Exception as e:
+            logging.exception("临时文件删除报错: %s", str(e))
+        # 4 打包图片文件并上传压缩包
+        zip_jpg_files(local_mp4_dir)
+        bucket.put_object_from_file(oss_zip_key, local_zip_path)
+        try:
+            os.remove(local_zip_path)
+        except Exception as e:
+            logging.exception("临时文件删除报错: %s", str(e))
+        logging.info("已上传摄像头图片压缩包到: %s", oss_zip_key)
+        # 5 目录
+        try:
+            shutil.rmtree(local_mp4_dir)
+        except Exception as e:
+            logging.exception("临时目录报错: %s", str(e))
+    except Exception as e2:
+        # 当出现异常时执行的代码
+        logging.exception("生成摄像头视频报错: %s", e2)
+        # 删除 data_parse 路径
+        # 删除多个文件。
+        for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix_full1):
+            bucket.delete_object(obj.key)
+        # 删除 bag包
+        bucket.delete_object(merged_bag_object_key)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    local_delete_list = []
+                    oss_delete_list = []
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        camera_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if '/camera_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                camera_done = True
+                        if camera_done:
+                            continue
+
+                        local_merged_bag_path = path1 + 'camera/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        data_name = merged_bag_object_key_split[-1].split('.')[0].split('_')[0]
+                        try:
+                            bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                            logging.info("解析bag包图像【%s】->【%s】", str(merged_bag_object_key),
+                                         str(local_merged_bag_path), )
+                        except Exception as e1:
+                            logging.exception("bag包下载报错: %s", e1)
+                        local_delete_list.append(local_merged_bag_path)
+                        logging.info("生成 camera.mp4: %s" % parse_prefix_full)
+                        parse_to_mp4(bucket, merged_bag_object_key, local_merged_bag_path, parse_prefix_full,
+                                     local_parse_dir,
+                                     data_name)
+
+                        # 删除本地临时文件
+                        if len(local_delete_list) > 0:
+                            for local_delete in local_delete_list:
+                                try:
+                                    os.remove(local_delete)
+                                except Exception as e:
+                                    logging.exception("临时文件删除报错: %s", str(e))
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/csv-.py

@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from resource import pos_orig_csv
+from resource import drive_csv
+
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/csv.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_to_csv(merged_bag_file_path, parse_prefix, local_parse_dir, local_delete_list):
+    try:
+        logging.info("开始解析 pos_orig.csv: %s" % str(merged_bag_file_path))
+        pos_orig_csv.parse(merged_bag_file_path, local_parse_dir)
+        logging.info("开始解析 drive.csv: %s" % str(merged_bag_file_path))
+        local_csv_dir = drive_csv.parse(merged_bag_file_path, local_parse_dir)
+        local_file_name1 = 'pos'
+        local_file_name2 = 'drive'
+        local_path1 = str(local_csv_dir) + '/' + local_file_name1 + '.csv'
+        local_path2 = str(local_csv_dir) + '/' + local_file_name2 + '.csv'
+        oss_file_name1 = 'pos_orig'
+        oss_file_name2 = 'drive'
+        # 删除本地文件
+        local_delete_list.append(local_path1)
+        local_delete_list.append(local_path2)
+        oss_csv_object_key1 = parse_prefix + oss_file_name1 + '.csv'
+        oss_csv_object_key2 = parse_prefix + oss_file_name2 + '.csv'
+        bucket.put_object_from_file(oss_csv_object_key1, local_path1)
+        logging.info("上传csv成功: %s" % str(oss_csv_object_key1))
+        bucket.put_object_from_file(oss_csv_object_key2, local_path2)
+        logging.info("上传csv成功: %s" % str(oss_csv_object_key2))
+        return local_parse_dir
+    except Exception as e:
+        logging.exception("生成csv报错: %s" % str(e))
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                local_delete_list = []
+                oss_delete_list = []
+                try:
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        # print(f'需要解析{merged_bag_object_key}')
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        csv1_done = False
+                        # csv2_done = False
+                        csv3_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if '/pos_orig.csv' in str(obj2.key):
+                                csv1_done = True
+                            # if '/pos_hmi.csv' in str(obj2.key):
+                            #     csv2_done = True
+                            if '/drive.csv' in str(obj2.key):
+                                csv3_done = True
+                        if csv1_done and csv3_done:
+                            # if csv1_done and csv2_done and csv3_done:
+                            continue
+                        logging.info("需要解析: %s" % merged_bag_object_key)
+                        local_merged_bag_path = path1 + 'csv/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        logging.info("开始下载合并后的 bag 包: %s" % merged_bag_object_key)
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        logging.info("下载合并后的 bag 包完成: %s" % merged_bag_object_key)
+                        local_delete_list.append(local_merged_bag_path)
+                        # 2 生成 pos_orig.csv 和 pos_hmi.csv
+                        logging.info("生成 pos_orig.csv 和 pos_hmi.csv: %s" % parse_prefix_full)
+                        parse_to_csv(local_merged_bag_path, parse_prefix_full, local_parse_dir, local_delete_list)
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+                # 删除本地临时文件
+                if len(local_delete_list) > 0:
+                    for local_delete in local_delete_list:
+                        try:
+                            os.remove(local_delete)
+                        except Exception as e:
+                            logging.exception("删除本地临时文件: %s" % str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/csv-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 csv-.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjisuv/csv-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 csv-.py > log/csv.out 2>&1 &

src/python2/pjisuv/csv-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/csv.log

src/python2/pjisuv/merge-kill.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+ps aux | grep 'python2 merge.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjisuv/merge-nohup.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+nohup python2 merge.py > log/merge.out 2>&1 &

src/python2/pjisuv/merge-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/merge.log

src/python2/pjisuv/merge.py

@@ -0,0 +1,207 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from rosbag import Bag, Compression
+import logging
+import json
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/merge.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/'
+key2 = 'data/'
+key3 = 'data_merge/'
+key4 = 'data_parse/'
+sleep_time = 60  # 每多少秒扫描一次
+compress_way = Compression.BZ2
+car_list = ['pjisuv-004','pjisuv-007', 'pjisuv-012', 'pjisuv-013']
+
+
+# 判断是否在done_list 中
+def is_upload_completed(prefix, done_list):
+    for time in done_list:
+        if time in prefix:
+            return True
+    return True
+
+
+def merge(local_bags1, merged_prefix1, local_merged_dir1, merged_bag_name1):
+    try:
+        all_bag_path1 = local_merged_dir1 + merged_bag_name1
+        with Bag(all_bag_path1, 'w', compression=compress_way) as o:
+            for i in range(len(local_bags1)):
+                with Bag(local_bags1[i], 'r') as ib:
+                    for topic, msg, t in ib:
+                        o.write(topic, msg, t)
+        bucket.put_object_from_file(merged_prefix1 + merged_bag_name1, all_bag_path1)
+        logging.info('上传合并包到 %s' % merged_prefix1 + merged_bag_name1)
+        return all_bag_path1
+    except Exception as e1:
+        logging.exception("bag包合并报错: %s", e1)
+
+
+def remove_element_of_oss_json(oss_json_key, remove_time):
+    logging.info('删除时间 %s' % remove_time)
+    temp_file_path_remove = 'remove-node1Done.json'
+    # 1 读取oss的json文件为列表
+    bucket.get_object_to_file(oss_json_key, temp_file_path_remove)
+    with open(temp_file_path_remove, 'r') as f_remove:
+        remove_node_done_list = json.load(f_remove)
+    # logging.info('列表为 %s' % remove_node_done_list)
+    remove_node_done_list.remove(str(remove_time))
+    json_str = json.dumps(remove_node_done_list, indent=4, ensure_ascii=False)
+    bucket.put_object(oss_json_key, json_str.encode('utf-8'))
+    os.remove(temp_file_path_remove)
+    time.sleep(2)
+
+
+def extract_datetime(path):
+    # 分割字符串以找到 'node1_' 后面的部分
+    parts = path.split('node1_')
+    if len(parts) > 1:
+        # 分割找到的部分以获取日期时间
+        datetime_part = parts[1].split('_')[0]
+        return datetime_part
+    return None
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+预设OSS路径： oss://open-bucket
+
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+'''
+# ------- 获取未合并的bag包，合并 -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            for car in car_list:
+                prefix_list = []
+                upload_completed_prefix_list_node1 = []
+                upload_completed_prefix_list_node2 = []
+                # todo 如何往回更新json需要确认一下，直接更新会和上传程序出现数据竞争
+                node1_done_json_key = 'pjisuv/' + car + '/' + key2 + 'node1Done.json'
+                node2_done_json_key = 'pjisuv/' + car + '/' + key2 + 'node2Done.json'
+                # 1 判断两个json是否存在
+                exist = bucket.object_exists(node1_done_json_key)
+                if not exist:
+                    logging.info('不存在文件 %s' % node1_done_json_key)
+                    time.sleep(2)
+                    continue
+                exist = bucket.object_exists(node2_done_json_key)
+                if not exist:
+                    logging.info('不存在文件 %s' % node2_done_json_key)
+                    time.sleep(2)
+                    continue
+                # 2 读取两个json为数组
+                temp_file_path1 = car + '-node1Done.json'
+                temp_file_path2 = car + '-node2Done.json'
+                try:
+                    # node1
+                    bucket.get_object_to_file(node1_done_json_key, temp_file_path1)
+                    with open(temp_file_path1, 'r') as f1:
+                        node1_done_list = json.load(f1)
+                except Exception as e1:
+                    logging.exception("下载json文件【%s】报错: 【%s】", node1_done_json_key, str(e1))
+                    time.sleep(2)
+                    continue
+                try:
+                    # node2
+                    bucket.get_object_to_file(node2_done_json_key, temp_file_path2)
+                    with open(temp_file_path2, 'r') as f2:
+                        node2_done_list = json.load(f2)
+                except Exception as e2:
+                    logging.exception("下载json文件【%s】报错: 【%s】", node2_done_json_key, str(e2))
+                    time.sleep(2)
+                    continue
+                os.remove(temp_file_path1)
+                os.remove(temp_file_path2)
+
+                logging.info("扫描车辆【%s】的数据", car)
+                for obj1 in oss2.ObjectIterator(bucket, prefix=key1 + car + "/" + key2, delimiter='/'):
+                    if str(obj1.key).count('/') == 4:  # pjisuv/pjisuv-007/data/node1_2023-12-20-02-16-56_obction_10/
+                        if 'node1' in obj1.key:
+                            if is_upload_completed(obj1.key, node1_done_list):
+                                upload_completed_prefix_list_node1.append(obj1.key)
+                        if 'node2' in obj1.key:
+                            if is_upload_completed(obj1.key, node2_done_list):
+                                upload_completed_prefix_list_node2.append(obj1.key)
+
+                # 3 如果两个节点都上传完成则进行后续处理
+                for prefix_node1 in upload_completed_prefix_list_node1:
+                    try:
+                        local_delete_list = []
+                        oss_delete_list = []
+                        prefix_node2 = prefix_node1.replace('node1', 'node2')
+                        if prefix_node2 in upload_completed_prefix_list_node2:
+                            logging.info("需要合并【%s】和【%s】", prefix_node1, prefix_node2)
+                            # 1 从对应的 node1Done.json 和 node2Done.json里删除
+                            logging.info("从对应的 node1Done.json 和 node2Done.json里删除 【%s】和【%s】", car)
+                            time1 = extract_datetime(prefix_node1)
+                            time2 = extract_datetime(prefix_node2)
+                            # todo 这里报错
+                            # remove_element_of_oss_json(node1_done_json_key, time1)
+                            # remove_element_of_oss_json(node2_done_json_key, time2)
+
+                            # 2 获取要处理的包
+                            oss_bags = []
+                            local_bags = []
+                            for obj in oss2.ObjectIterator(bucket, prefix=prefix_node1):
+                                if str(obj.key).endswith('.bag'):
+                                    oss_bags.append(str(obj.key))
+                            for obj in oss2.ObjectIterator(bucket, prefix=prefix_node2):
+                                if str(obj.key).endswith('.bag'):
+                                    oss_bags.append(str(obj.key))
+                            split_list = prefix_node1.replace(key2, key3).replace("node1_", "").split('/')
+                            merged_prefix = '/'.join(split_list[0:-2]) + '/'
+                            local_merged_dir = path1 + merged_prefix
+                            if not os.path.exists(local_merged_dir):
+                                os.makedirs(local_merged_dir)
+                            parse_prefix = ('/'.join(split_list[0:-2]) + '/').replace(key3, key4)
+                            local_parse_dir = path1 + parse_prefix
+                            if not os.path.exists(local_parse_dir):
+                                os.makedirs(local_parse_dir)
+                            merged_bag_name = split_list[-2]
+                            parse_prefix = parse_prefix + merged_bag_name + '/'
+                            merged_bag_full_name = merged_bag_name + '.bag'
+                            local_bag_dir = path1 + '/'.join(split_list[0:-1]) + '/'
+                            if not os.path.exists(local_bag_dir):
+                                os.makedirs(local_bag_dir)
+                            # 下载
+                            for oss_bag in oss_bags:
+                                bag_name = str(oss_bag).split('/')[-1]
+                                local_bag_path = local_bag_dir + bag_name
+                                bucket.get_object_to_file(oss_bag, local_bag_path)
+                                local_bags.append(local_bag_path)
+                                local_delete_list.append(local_bag_path)
+                                oss_delete_list.append(oss_bag)
+                            # 1 合并bag
+                            logging.info("开始合并bag包: %s", str(merged_prefix + merged_bag_full_name))
+                            all_bag_path = merge(local_bags, merged_prefix, local_merged_dir, merged_bag_full_name)
+                            local_delete_list = local_delete_list + [all_bag_path]
+                            # 删除本地临时文件
+                            if len(local_delete_list) > 0:
+                                for local_delete in local_delete_list:
+                                    try:
+                                        os.remove(local_delete)
+                                    except Exception as e:
+                                        pass
+                            # 删除oss原始文件
+                            if len(oss_delete_list) > 0:
+                                bucket.batch_delete_objects(oss_delete_list)
+                    except Exception as e:
+                        logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/pcd-kill.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+ps aux | grep 'python2 pcd_pjisuv-004.py' | grep -v grep | awk '{print $2}' | xargs kill -9
+ps aux | grep 'python2 pcd_pjisuv-007.py' | grep -v grep | awk '{print $2}' | xargs kill -9
+ps aux | grep 'python2 pcd_pjisuv-012.py' | grep -v grep | awk '{print $2}' | xargs kill -9
+ps aux | grep 'python2 pcd_pjisuv-013.py' | grep -v grep | awk '{print $2}' | xargs kill -9

src/python2/pjisuv/pcd-nohup.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+nohup python2 pcd_pjisuv-004.py > log/pcd_pjisuv-004.out 2>&1 &
+nohup python2 pcd_pjisuv-007.py > log/pcd_pjisuv-007.out 2>&1 &
+nohup python2 pcd_pjisuv-012.py > log/pcd_pjisuv-012.out 2>&1 &
+nohup python2 pcd_pjisuv-013.py > log/pcd_pjisuv-012.out 2>&1 &

src/python2/pjisuv/pcd-tail.sh

@@ -0,0 +1,2 @@
+#!/bin/bash
+tail -f log/pcd_pjisuv-004.log log/pcd_pjisuv-007.log log/pcd_pjisuv-012.log log/pcd_pjisuv-013.log

src/python2/pjisuv/pcd_pjisuv-004.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from resource import pcd_overlook_mp4
+from resource import pcd_forwardlook_mp4
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/pcd_pjisuv-004.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/pjisuv-004/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path,merged_bag_object_key1, parse_prefix_full1, local_parse_dir, local_delete_list):
+    try:
+        logging.info('生成点云视频 %s' % merged_bag_file_path)
+        local_pcd_dir_overlook, hz = pcd_overlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_dir_forward, hz = pcd_forwardlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_mp4_file_overlook = local_pcd_dir_overlook + '/pcd_overlook.mp4'
+        local_pcd_mp4_file_forwardlook = local_pcd_dir_forward + '/pcd_forwardlook.mp4'
+        oss_csv_object_key1 = parse_prefix_full1 + 'pcd_overlook_' + str(hz) + '.mp4'
+        oss_csv_object_key11 = parse_prefix_full1 + 'pcd_overlook.mp4'
+        oss_csv_object_key2 = parse_prefix_full1 + 'pcd_forwardlook_' + str(hz) + '.mp4'
+        oss_csv_object_key21 = parse_prefix_full1 + 'pcd_forwardlook.mp4'
+        local_delete_list.append(local_pcd_mp4_file_overlook)
+        local_delete_list.append(local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_file_overlook)
+        bucket.put_object_from_file(oss_csv_object_key11, local_pcd_mp4_file_overlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key1)
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key21, local_pcd_mp4_file_forwardlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key2)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+        # 删除多个文件。
+        for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix_full1):
+            bucket.delete_object(obj.key)
+        # 删除 bag包
+        bucket.delete_object(merged_bag_object_key1)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    local_delete_list = []
+                    oss_delete_list = []
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        pcd1_done = False
+                        pcd2_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if 'pcd_overlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd1_done = True
+                            if 'pcd_forwardlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd2_done = True
+                        if pcd1_done and pcd2_done:
+                            continue
+                        logging.info('需要解析：%s' % merged_bag_object_key)
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        parse_to_pcd_mp4(local_merged_bag_path,merged_bag_object_key, parse_prefix_full, local_parse_dir, local_delete_list)
+
+                        # 删除本地临时文件
+                        if len(local_delete_list) > 0:
+                            for local_delete in local_delete_list:
+                                try:
+                                    os.remove(local_delete)
+                                    logging.info("删除本地临时文件: %s" % local_delete)
+                                except Exception as e:
+                                    logging.exception("删除本地临时文件报错: %s" % str(e))
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/pcd_pjisuv-007.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from resource import pcd_overlook_mp4
+from resource import pcd_forwardlook_mp4
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/pcd_pjisuv-007.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/pjisuv-007/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path,merged_bag_object_key1, parse_prefix_full1, local_parse_dir, local_delete_list):
+    try:
+        logging.info('生成点云视频 %s' % merged_bag_file_path)
+        local_pcd_dir_overlook, hz = pcd_overlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_dir_forward, hz = pcd_forwardlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_mp4_file_overlook = local_pcd_dir_overlook + '/pcd_overlook.mp4'
+        local_pcd_mp4_file_forwardlook = local_pcd_dir_forward + '/pcd_forwardlook.mp4'
+        oss_csv_object_key1 = parse_prefix_full1 + 'pcd_overlook_' + str(hz) + '.mp4'
+        oss_csv_object_key11 = parse_prefix_full1 + 'pcd_overlook.mp4'
+        oss_csv_object_key2 = parse_prefix_full1 + 'pcd_forwardlook_' + str(hz) + '.mp4'
+        oss_csv_object_key21 = parse_prefix_full1 + 'pcd_forwardlook.mp4'
+        local_delete_list.append(local_pcd_mp4_file_overlook)
+        local_delete_list.append(local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_file_overlook)
+        bucket.put_object_from_file(oss_csv_object_key11, local_pcd_mp4_file_overlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key1)
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key21, local_pcd_mp4_file_forwardlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key2)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+        # 删除多个文件。
+        for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix_full1):
+            bucket.delete_object(obj.key)
+        # 删除 bag包
+        bucket.delete_object(merged_bag_object_key1)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    local_delete_list = []
+                    oss_delete_list = []
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        pcd1_done = False
+                        pcd2_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if 'pcd_overlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd1_done = True
+                            if 'pcd_forwardlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd2_done = True
+                        if pcd1_done and pcd2_done:
+                            continue
+                        logging.info('需要解析：%s' % merged_bag_object_key)
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        parse_to_pcd_mp4(local_merged_bag_path,merged_bag_object_key, parse_prefix_full, local_parse_dir, local_delete_list)
+
+                        # 删除本地临时文件
+                        if len(local_delete_list) > 0:
+                            for local_delete in local_delete_list:
+                                try:
+                                    os.remove(local_delete)
+                                    logging.info("删除本地临时文件: %s" % local_delete)
+                                except Exception as e:
+                                    logging.exception("删除本地临时文件报错: %s" % str(e))
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/pcd_pjisuv-012.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from resource import pcd_overlook_mp4
+from resource import pcd_forwardlook_mp4
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/pcd_pjisuv-012.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/pjisuv-012/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path,merged_bag_object_key1, parse_prefix_full1, local_parse_dir, local_delete_list):
+    try:
+        logging.info('生成点云视频 %s' % merged_bag_file_path)
+        local_pcd_dir_overlook, hz = pcd_overlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_dir_forward, hz = pcd_forwardlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_mp4_file_overlook = local_pcd_dir_overlook + '/pcd_overlook.mp4'
+        local_pcd_mp4_file_forwardlook = local_pcd_dir_forward + '/pcd_forwardlook.mp4'
+        oss_csv_object_key1 = parse_prefix_full1 + 'pcd_overlook_' + str(hz) + '.mp4'
+        oss_csv_object_key11 = parse_prefix_full1 + 'pcd_overlook.mp4'
+        oss_csv_object_key2 = parse_prefix_full1 + 'pcd_forwardlook_' + str(hz) + '.mp4'
+        oss_csv_object_key21 = parse_prefix_full1 + 'pcd_forwardlook.mp4'
+        local_delete_list.append(local_pcd_mp4_file_overlook)
+        local_delete_list.append(local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_file_overlook)
+        bucket.put_object_from_file(oss_csv_object_key11, local_pcd_mp4_file_overlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key1)
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key21, local_pcd_mp4_file_forwardlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key2)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+        # 删除多个文件。
+        for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix_full1):
+            bucket.delete_object(obj.key)
+        # 删除 bag包
+        bucket.delete_object(merged_bag_object_key1)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    local_delete_list = []
+                    oss_delete_list = []
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        pcd1_done = False
+                        pcd2_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if 'pcd_overlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd1_done = True
+                            if 'pcd_forwardlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd2_done = True
+                        if pcd1_done and pcd2_done:
+                            continue
+                        logging.info('需要解析：%s' % merged_bag_object_key)
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        parse_to_pcd_mp4(local_merged_bag_path,merged_bag_object_key, parse_prefix_full, local_parse_dir, local_delete_list)
+
+                        # 删除本地临时文件
+                        if len(local_delete_list) > 0:
+                            for local_delete in local_delete_list:
+                                try:
+                                    os.remove(local_delete)
+                                    logging.info("删除本地临时文件: %s" % local_delete)
+                                except Exception as e:
+                                    logging.exception("删除本地临时文件报错: %s" % str(e))
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))

src/python2/pjisuv/pcd_pjisuv-013.py

@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+import os
+import time
+import oss2
+from resource import pcd_overlook_mp4
+from resource import pcd_forwardlook_mp4
+import logging
+
+path1 = '/mnt/disk001/cicv-data-closedloop/python2-pjisuv-module/'
+
+logging.basicConfig(filename=path1 + 'log/pcd_pjisuv-013.log', level=logging.INFO,
+                    format='%(asctime)s - %(levelname)s - %(message)s')
+
+key1 = 'pjisuv/pjisuv-013/'
+sleep_time = 60  # 每多少秒扫描一次
+
+
+def parse_to_pcd_mp4(merged_bag_file_path,merged_bag_object_key1, parse_prefix_full1, local_parse_dir, local_delete_list):
+    try:
+        logging.info('生成点云视频 %s' % merged_bag_file_path)
+        local_pcd_dir_overlook, hz = pcd_overlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_dir_forward, hz = pcd_forwardlook_mp4.parse(merged_bag_file_path, local_parse_dir)
+        local_pcd_mp4_file_overlook = local_pcd_dir_overlook + '/pcd_overlook.mp4'
+        local_pcd_mp4_file_forwardlook = local_pcd_dir_forward + '/pcd_forwardlook.mp4'
+        oss_csv_object_key1 = parse_prefix_full1 + 'pcd_overlook_' + str(hz) + '.mp4'
+        oss_csv_object_key11 = parse_prefix_full1 + 'pcd_overlook.mp4'
+        oss_csv_object_key2 = parse_prefix_full1 + 'pcd_forwardlook_' + str(hz) + '.mp4'
+        oss_csv_object_key21 = parse_prefix_full1 + 'pcd_forwardlook.mp4'
+        local_delete_list.append(local_pcd_mp4_file_overlook)
+        local_delete_list.append(local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key1, local_pcd_mp4_file_overlook)
+        bucket.put_object_from_file(oss_csv_object_key11, local_pcd_mp4_file_overlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key1)
+        bucket.put_object_from_file(oss_csv_object_key2, local_pcd_mp4_file_forwardlook)
+        bucket.put_object_from_file(oss_csv_object_key21, local_pcd_mp4_file_forwardlook)
+        logging.info('上传点云视频到 %s' % oss_csv_object_key2)
+    except Exception as e:
+        logging.exception("生成点云视频报错: %s" % str(e))
+        # 删除多个文件。
+        for obj in oss2.ObjectIterator(bucket, prefix=parse_prefix_full1):
+            bucket.delete_object(obj.key)
+        # 删除 bag包
+        bucket.delete_object(merged_bag_object_key1)
+
+
+'''
+cname：http://open-bucket.oss.icvdc.com
+内网endpoint: oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com
+oss桶名： open-bucket
+keyid：n8glvFGS25MrLY7j
+secret：xZ2Fozoarpfw0z28FUhtg8cu0yDc5d
+'''
+# ------- 获取合并之后的bag包，解析出csv -------
+if __name__ == '__main__':
+    # 1 创建阿里云对象
+    auth = oss2.Auth('n8glvFGS25MrLY7j', 'xZ2Fozoarpfw0z28FUhtg8cu0yDc5d')
+    # cname = 'http://open-bucket.oss.icvdc.com'
+    # bucket = oss2.Bucket(auth, cname, 'open-bucket', is_cname=True)
+    endpoint = 'oss-cn-beijing-gqzl-d01-a.ops.gqzl-cloud.com'
+    bucket = oss2.Bucket(auth, endpoint, 'open-bucket')
+    while True:
+        try:
+            logging.info("开始新一轮扫描")
+            prefix_list = []
+            # 2 获取已经上传完成的所有目录并分组
+            for obj1 in oss2.ObjectIterator(bucket, prefix=key1):
+                try:
+                    local_delete_list = []
+                    oss_delete_list = []
+                    # 获取合并后的包
+                    merged_bag_object_key = str(obj1.key)
+                    # print(f'判断1{merged_bag_object_key}')
+                    if 'data_merge' in str(obj1.key) and str(obj1.key).endswith('.bag'):
+                        merged_bag_object_key_split = merged_bag_object_key.split('/')
+                        merged_prefix = '/'.join(merged_bag_object_key_split[:-1])
+                        parse_prefix = merged_prefix.replace('data_merge', 'data_parse')
+                        parse_prefix_full = merged_bag_object_key.replace('data_merge', 'data_parse')[:-4] + '/'
+                        pcd1_done = False
+                        pcd2_done = False
+                        for obj2 in oss2.ObjectIterator(bucket, prefix=parse_prefix_full):
+                            if 'pcd_overlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd1_done = True
+                            if 'pcd_forwardlook_' in str(obj2.key) and str(obj2.key).endswith('.mp4'):
+                                pcd2_done = True
+                        if pcd1_done and pcd2_done:
+                            continue
+                        logging.info('需要解析：%s' % merged_bag_object_key)
+                        local_merged_bag_path = path1 + 'pcd/' + merged_bag_object_key
+                        local_merged_dir = '/'.join(local_merged_bag_path.split('/')[:-1])
+                        local_parse_dir = local_merged_dir.replace('data_merge', 'data_parse')
+                        if not os.path.exists(local_merged_dir):
+                            os.makedirs(local_merged_dir)
+                        if not os.path.exists(local_parse_dir):
+                            os.makedirs(local_parse_dir)
+                        merged_bag_full_name = merged_bag_object_key_split[-1]
+                        merged_bag_name = merged_bag_full_name.split('.')[0]
+                        bucket.get_object_to_file(merged_bag_object_key, local_merged_bag_path)
+                        local_delete_list.append(local_merged_bag_path)
+                        parse_to_pcd_mp4(local_merged_bag_path,merged_bag_object_key, parse_prefix_full, local_parse_dir, local_delete_list)
+
+                        # 删除本地临时文件
+                        if len(local_delete_list) > 0:
+                            for local_delete in local_delete_list:
+                                try:
+                                    os.remove(local_delete)
+                                    logging.info("删除本地临时文件: %s" % local_delete)
+                                except Exception as e:
+                                    logging.exception("删除本地临时文件报错: %s" % str(e))
+                except Exception as e:
+                    logging.exception("局部异常处理: %s", str(e))
+            time.sleep(sleep_time)
+        except Exception as e:
+            logging.exception("全局异常处理: %s", str(e))