pc 上运行line_自动执行Windows 7维护任务以使PC像新的一样运行

本文指导如何在Windows系统中自动执行常见的维护任务,包括磁盘清理、备份、磁盘碎片整理、磁盘检查、Windows更新、防病毒扫描及软件更新,以保持系统高效稳定。
pc 上运行line

pc 上运行line

With a Windows computer there are several maintenance tasks you should run on a regular basis, though most of us forget. Here’s how to automate the most important maintenance tasks in XP, Vista & Windows 7 and keep your PC running like new.

对于Windows计算机,您应该定期执行几项维护任务,尽管我们大多数人都忘记了。 这是在XP,Vista和Windows 7中自动执行最重要的维护任务,并使PC像新设备一样运行的方法。

We’ll take a look at automating some of the most common tasks, and while it takes a bit of time to set each one up, once you do you’ll have peace of mind knowing your system is clean and up to date.

我们将看一下如何自动化一些最常见的任务,并且设置每个任务都需要一些时间,但是一旦您完成设置,您就可以放心地知道系统是最新的。

自动清理硬盘 (Automate Cleaning Up Your Hard Drive)

If you want to make sure you have plenty of space on your hard drive, and get rid of old files you no longer need, you can schedule Disk Cleanup to run in Windows 7 or Vista, which gets rid of plenty of temporary files and other stuff that doesn’t need to be around anymore.

如果要确保硬盘驱动器上有足够的空间并清除不再需要的旧文件,可以安排磁盘清理在Windows 7或Vista中运行 ,从而清除大量的临时文件和其他文件。不再需要的东西。

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You can setup Disk Cleanup in XP as well as a Scheduled Task. The process is easy following the Scheduled Task Wizard in XP.

您可以在XP中以及“计划任务”中设置“磁盘清理”。 按照XP中的“ 计划任务向导”,此过程很容易。

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If you really want to keep your system automated, however, you can setup the freeware CCleaner tool to automatically run every night, which will clean up more than just the regular temporary files—CCleaner can even clear out your browser history, applications caches, and more.

但是,如果您确实想使系统保持自动化,则可以将免费软件CCleaner工具设置为每晚自动运行 ,这不仅可以清理常规的临时文件,还可以清理您的浏览器历史记录,应用程序缓存和更多。

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Note: you’ll want to make sure that you don’t select any toolbars during CCleaner installation, or get the slim download from the optional downloads section.

注意:您需要确保在CCleaner安装过程中不要选择任何工具栏,或者从可选下载部分中获取苗条下载。

自动化备份以确保数据安全 (Automate Backups to Keep Your Data Secure)

The most important task Windows users need to do is make sure your data is backed up—that way, no matter what happens to your PC, you can always get to your files, even from another PC. If your PC is completely dead, you’ll be able to restore those files onto your new computer and get right back to whatever you were doing.

Windows用户要做的最重要的任务是确保备份数据-这样一来,无论您的PC发生什么情况,您都可以始终从其他PC上获取文件。 如果您的PC完全没电了,您将能够将这些文件还原到新计算机上,并恢复到所做的一切。

Local Backups

本地备份

Windows 7 includes an easy-to-use, wizard-driven Backup & Restore utility in all versions, which includes creating a system image. For more on which files to backup, check out The Geek’s guide to What Files you Should Backup on Your Windows PC.

Windows 7在所有版本中都包含一个易于使用,向导驱动的“ 备份和还原”实用程序 ,其中包括创建系统映像 。 有关要备份哪些文件的更多信息,请参阅《 The Geek's Guide》(《极客指南》), 有关在Windows PC上应备份哪些文件

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The Backup & Restore utility included in Windows 7 allows you to set a schedule from daily, weekly, or monthly. The choice is up to you, but if you backup on a regular basis, you’ll be glad you did.

Windows 7中包含的“备份和还原”实用程序使您可以设置每天,每周或每月的时间表。 选择取决于您,但是如果您定期进行备份,您会很高兴的。

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If you have Windows Home Server, backing up your computers is very easy to configure and automate. You can set it to backup on a regular schedule and also have WHS wake up your machine to back it up at night.

如果您有Windows Home Server,则备份和配置计算机非常容易 。 您可以将其设置为定期备份,也可以让WHS唤醒计算机以在晚上进行备份。

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Online Backup Services

在线备份服务

If you want to be really thorough with in your backup strategy, having redundant backups onsite and offsite is a good thing. There’s plenty of commercial backup services, like Mozy and Carbonite. They both work the same way, pushing your data up to their servers and making it available for download from another PC, or allowing you to restore individual files that you might have deleted.

如果您想在备份策略中做到周全,那么在现场和非现场进行冗余备份是一件好事。 有很多商业备份服务,例如MozyCarbonite 。 它们的工作方式相同,将数据推送到其服务器上并可以从另一台PC下载,或者允许您还原可能已删除的单个文件。

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自动进行磁盘碎片整理,以使驱动器保持平稳运行 (Automate Disk Defrag to Keep Your Drive Running Smooth)

The cool thing with Vista and Windows 7 is that Disk Defragmenter is scheduled to run by default at 1 AM every Wednesday, so it’s something you no longer have to deal with. You can customize the defragmenter schedule if you want, but there’s probably no reason to change it.

Vista和Windows 7的好处是,默认情况下,磁盘碎片整理程序计划在每个星期三的凌晨1点运行,因此您无需再处理此问题。 您可以根据需要自定义碎片整理程序时间表 ,但是可能没有理由对其进行更改。

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If you’re still on Windows XP you can get the same feature by creating your own Windows 7 style auto defrag using Task Scheduler. There’s no reason to have to remember to do it manually, and really no reason to waste money on a commercial defrag utility that does it automatically when you can set it up yourself.

如果您仍在使用Windows XP,则可以通过使用Task Scheduler 创建自己的Windows 7样式自动碎片整理功能来获得相同的功能。 没有理由要记住手动进行操作,也没有理由浪费金钱在可以自行设置的自动碎片整理实用程序上。

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If you’ve got multiple hard drives in your XP machine, you can also setup a batch file that will defragment multiple hard drives at once.

如果您的XP机器中有多个硬盘驱动器,则还可以设置一个批处理文件,该文件将立即对多个硬盘驱动器进行碎片整理

自动检查磁盘 (Automate Disk Checking)

The chkdsk.exe utility in Windows allows you to scan your hard drive for errors and fix them as well, and this task can be automated with the command-line and Task Scheduler as well, though it’s going to require rebooting your PC in order for it to work, so it’s probably best to just trigger this one manually every so often.

Windows中的chkdsk.exe实用程序允许您扫描硬盘驱动器中的错误并进行修复,该任务也可以通过命令行和Task Scheduler自动执行,尽管这将需要重新引导PC才能解决。它可以正常工作,因此最好是每隔一段时间手动触发一次。

If you do want to schedule it to run automatically, you can simply create a new Task Scheduler job that runs chkdsk.exe with the parameters from our guide to check disk.

如果确实要计划它自动运行,则可以简单地创建一个新的Task Scheduler作业 ,并使用我们指南中的参数运行chkdsk.exe 来检查disk

Then go to the Actions tab of the job in Task Scheduler, and add another action to run after the chkdsk command, and specify shutdown as the command. This will run the chkdsk command, and then run a shutdown afterwards. Make sure to use /R as the argument so that Windows will reboot and run chkdsk, and not just shut down.

然后转到任务计划程序中作业的“操作”选项卡,并添加另一个要在chkdsk命令之后运行的操作,并指定shutdown作为该命令。 这将运行chkdsk命令,然后再运行关机。 确保使用/ R作为参数,以便Windows重新启动并运行chkdsk,而不仅仅是关闭。

You may also want to check the box to make sure that Windows doesn’t reboot you while you’re doing something. You can head to the Conditions tab, and make it only start if the PC has been idle for a while.

您可能还需要选中该复选框,以确保Windows在执行某项操作时不会重新引导您。 您可以转到“条件”选项卡,并使其仅在PC闲置了一段时间后才能启动。

Note: Windows will automatically detect when your drive has a lot of problems and prompt you to check the disk, but that doesn’t mean running it manually is a bad idea once in a while.

注意: Windows会自动检测驱动器何时有很多问题,并提示您检查磁盘,但这并不意味着手动运行它偶尔会是个坏主意。

To manually trigger a disk check for the next time you reboot, right-click on your local drive and select Properties. Then select the Tools tab and under Error-checking, click on the Check now button.

要在下次重启时手动触发磁盘检查,请右键单击本地驱动器,然后选择“属性”。 然后选择“工具”选项卡,在“错误检查”下,单击“立即检查”按钮。

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Make sure to select both Check disk options, and click Start.

确保选择两个Check disk选项,然后单击Start。

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Unfortunately it can’t start while you’re using your PC, but you can schedule it to run during next restart.

不幸的是,它在您使用PC时无法启动,但是您可以安排它在下次重新启动时运行。

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The next time your machine is restarted, Check Disk will run and detect and fix errors automatically. Keep in mind this process can take quite a while depending on the size of your drive and the amount of data on it. For more, check out The Geek’s guide to Check Disk in Windows.

下次重新启动计算机时,“检查​​磁盘”将运行并自动检测并修复错误。 请记住,此过程可能需要花费相当长的时间,具体取决于驱动器的大小和驱动器上的数据量。 有关更多信息,请查看The Geek's Guide to Check Disk in Windows

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自动化Windows更新以使您的PC保持补丁状态 (Automate Windows Updates to Keep Your PC Patched)

Although it should go without saying, an important task you can make run automatically is Windows Updates. You can configure Important and Recommended updates to download and install automatically, or just download and you choose which ones to install.

尽管应该说,Windows Updates是可以自动运行的重要任务。 您可以将重要更新和推荐更新配置为自动下载并安装,或者仅下载并选择要安装的更新。

For more, check out how to make Windows 7 Update display recommended and important updates.

有关更多信息,请查看如何使Windows 7 Update显示推荐的重要更新

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自动执行防病毒检查定义和扫描计算机 (Automate Antivirus to Check Definitions & Scan Your Computer)

Another important security task is making sure your Antivirus protection is up to date and runs automatically. Each program is different, but most provide the option to keep definition files up to date and scan automatically. For instance it’s easy to setup in our favorite Microsoft Security Essentials.

另一个重要的安全任务是确保防病毒保护是最新的并自动运行。 每个程序都不同,但是大多数程序提供了使定义文件保持最新并自动扫描的选项。 例如,可以很容易地在我们最喜欢的Microsoft Security Essentials中进行设置。

Note: of course, most anti-virus applications are set to automatically update their virus definition files, but you should double-check to make sure.

注意:当然,大多数防病毒应用程序都设置为自动更新其病毒定义文件,但是您应仔细检查以确保安全。

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Anti-Spyware

反间谍软件

If you’re using another Antimalware utility to compliment your Antivirus software, make sure it’s set to find its latest definition files and scan automatically. Keep in mind though, with most of the free versions of Antispyware apps, you’ll need to purchase a license to get real-time protection, automatic updates, and scanning.

如果您使用另一个Antimalware实用程序来补充Antivirus软件,请确保已将其设置为查找其最新的定义文件并自动进行扫描。 不过请记住,使用大多数免费版本的Antispyware应用程序,您需要购买许可证才能获得实时保护,自动更新和扫描。

自动使驱动程序和第三方软件保持最新 (Automatically Keep Drivers and 3rd-Party Software Up to Date)

Another important task to automate is checking for the latest hardware driver and other app updates. There are a few good programs that will do it which we’ve previously covered such as Secunia Personal Software Inspector. It will automatically check for software updates at startup and provides continuous monitoring.

自动化的另一个重要任务是检查最新的硬件驱动程序和其他应用程序更新。 有一些很好的程序可以做到这一点,例如Secunia Personal Software Inspector ,我们以前已经介绍过。 它会在启动时自动检查软件更新,并提供连续监视。

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To automatically keep your hardware drivers up to date, try a program such as Device Doctor, Slimdrivers, or any of the other non-free utilities out there. They will complete driver scans and make sure that your drivers are updated.

要自动使您的硬件驱动程序保持最新,请尝试使用诸如Device Doctor,Slimdrivers或其他任何非免费实用程序之类的程序。 他们将完成驱动程序扫描,并确保您的驱动程序已更新。

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Note: One thing to keep in mind with Device Doctor (or really any application) during installation is to skip installing the worthless Ask Toolbar.

注意:在安装过程中使用Device Doctor(或实际上是任何应用程序)要记住的一件事是跳过安装毫无用处的Ask工具栏。



This guide should definitely get you started in figuring out which maintenance tasks you want to setup to run automatically. While there certainly seems to be a lot to keep up with if you’re a Windows user, setting tasks to run automatically will free up some time so you get get to work and get things done.

该指南绝对可以帮助您确定要设置为自动运行的维护任务。 如果您是Windows用户,当然还有很多工作要做,但是将任务设置为自动运行将节省一些时间,因此您可以开始工作并完成工作。

What about you guys? What Tasks do you set up to run automatically and what methods do you use? Leave a comment below and lets us know!

你们呢? 您将哪些任务设置为自动运行,并使用了哪些方法? 在下面发表评论,让我们知道!

翻译自: https://www.howtogeek.com/howto/30677/guide-to-running-common-maintenance-tasks-automatically-in-windows/

pc 上运行line

检查以下代码bug,是否需要优化,怎么优化。 ```python import os import subprocess import time import logging from watchdog.observers import Observer from watchdog.events import FileSystemEventHandler import configparser import concurrent.futures import sys import json import subprocess from osgeo import gdal, osr import rasterio # 创建 logger logger = logging.getLogger() logger.setLevel(logging.INFO) # 创建文件处理器并设置编码 file_handler = logging.FileHandler('application.log', encoding='utf-8') formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') file_handler.setFormatter(formatter) # 将文件处理器添加至 logger logger.addHandler(file_handler) # 裁剪tif文件 cutline_path = "result\squares.geojson" # with open(cutline_path, "w") as f: # json.dump(geojson, f) # 获取图像信息(分辨率、坐标系) def get_info(path): with rasterio.open(path) as src: return { 'crs': src.crs.to_string(), 'res': (abs(src.transform.a), abs(src.transform.e)), 'bounds': src.bounds } # 裁剪函数 def crop_with_cutline(input_path, output_path, cutline, target_crs, target_res): warp_options = gdal.WarpOptions( format='GTiff', cutlineDSName=cutline, cropToCutline=True, dstSRS=target_crs, xRes=target_res[0], yRes=target_res[1], resampleAlg='bilinear', # dstAlpha=True, # 关键修改:添加alpha通道 # dstNodata=None # 可选:显式设置为None,让GDAL自动处理 ) ds = gdal.Warp(output_path, input_path, options=warp_options) ds = None def caijian_main(file1, file2, out1, out2): # 获取统一的 CRS 和分辨率 info1 = get_info(file1) info2 = get_info(file2) target_crs = info1['crs'] target_res = (min(info1['res'][0], info2['res'][0]), min(info1['res'][1], info2['res'][1])) # 使用自定义多边形裁剪两个图像 crop_with_cutline(file1, out1, cutline_path, target_crs, target_res) crop_with_cutline(file2, out2, cutline_path, target_crs, target_res) print("✅ 裁剪完成,输出图像已对齐!") def run_command(command): try: print(f"运行命令: {command}") result = subprocess.run(command, shell=True, check=True) return result.returncode except subprocess.CalledProcessError as e: logger.error(f"命令 {command} 执行失败: {e}") return e.returncode def get_folder_size(folder_path): try: total_size = 0 for dirpath, _, filenames in os.walk(folder_path): for f in filenames: fp = os.path.join(dirpath, f) total_size += os.path.getsize(fp) return total_size except Exception as e: logger.error(f"获取文件夹大小时出错: {e}") return None def process_folder(folder_name, folder_full_path, config,config_build): logger.info(f"开始处理文件夹: {folder_name}") # # 获取Python的安装路径 # python_install_path = sys.executable # # 获取Python安装路径的上级目录,即包含Scripts文件夹的目录 # python_base_path = os.path.dirname(python_install_path) # # 拼接Scripts/gdal2tiles.py路径 # qietu_path = os.path.join(python_base_path, 'Scripts', 'gdal2tiles.py') gdal_translate_path = config_build['settings']['gdal_translate_path'] qietu_path = config_build['settings']['gdal2tiles_path'] logger.info(f"切图工具路径: {qietu_path}") logger.info(f"转化工具路径: {gdal_translate_path}") # 强制转换字符串为布尔值 istype_zhengshe = config['settings']['zhengshe'] == 'True' istype_qingxie = config['settings']['qingxie'] == 'True' istype_quanjian = config['settings']['quanjian'] == 'True' istype_ndvi = config['settings']['ndvi'] == 'True' jingdu = config['settings']['precision'] print(f"建模类型: {istype_zhengshe}, {istype_qingxie}, {istype_quanjian}, {istype_ndvi}, 精度: {jingdu}") isNIR=False isRED=False precision_mapping = { "快速": 'lowest', "普通": 'lowest', "精细": 'high' } jingdu_value = precision_mapping.get(jingdu, 'lowest') # 只建正射 if istype_zhengshe: # 建模型 # 建模型 if folder_name == "allimages": # 如果新文件夹名是 allimages,允许运行 docker 命令并生成 orthophoto command_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/allimages\" --skip-report --skip-3dmodel " f"--feature-quality {jingdu_value} --copy-to \"/datasets/{config['settings']['resultNameDir']}\"" ) logger.info(f"只建正射 运行 docker 命令command_docker: {command_docker}") return_code = run_command(command_docker) if return_code == 0: # 如果命令成功,再运行 node 789.js command33 = ( rf"python {qietu_path} -z 1-21 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py 命令command33: {command33}") run_command(command33) update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 else: command3 = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/{folder_name}\" --skip-report --skip-3dmodel --pc-rectify --pc-ept --pc-quality lowest " f"--feature-quality lowest" ) logger.info(f"只建正射 运行 docker 命令command3: {command3}") return_code2 = run_command(command3) if return_code2 == 0: # 如果命令成功,再运行 gdal2tiles.py command2 = ( rf"python {qietu_path} -z 10-18 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py 命令command2: {command2}") run_command(command2) update_progress_ini(None, 1) # 更新 Progress.ini 文件 # 只建倾斜 elif istype_qingxie: # 建模型 # 建模型 if folder_name == "allimages": # 如果新文件夹名是 allimages,允许运行 docker 命令并生成 orthophoto command_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/allimages\" --skip-report --skip-orthophoto --pc-rectify --pc-ept --pc-quality {jingdu_value} " f"--feature-quality {jingdu_value} --3d-tiles --copy-to \"/datasets/{config['settings']['resultNameDir']}\"" ) logger.info(f"只建倾斜001 运行 docker 命令command_docker: {command_docker}") return_code = run_command(command_docker) logger.info(f"allimages第一次失败的时间时分秒:,{time.time()}") if return_code == 0: update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 else: # 如果失败等两秒在运行一次命令 time.sleep(20) logger.info(f"allimages第二次重建的时间时分秒:,{time.time()}") command_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/allimages\" --skip-report --skip-orthophoto --pc-rectify --pc-ept --pc-quality {jingdu_value} " f"--feature-quality {jingdu_value} --rerun-all --3d-tiles --copy-to \"/datasets/{config['settings']['resultNameDir']}\"" ) logger.info(f"只建倾斜失败运行第二次002 运行 docker 命令command_docker: {command_docker}") return_code = run_command(command_docker) if return_code == 0: update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 else: command3 = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/{folder_name}\" --skip-report --skip-3dmodel --pc-rectify --pc-ept --pc-quality lowest " f"--feature-quality lowest" ) logger.info(f"只建倾斜003 运行 docker 命令command3: {command3}") return_code2 = run_command(command3) logger.info(f"imgs1第一次失败的时间时分秒:,{time.time()}") if return_code2 == 0: # 如果命令成功,再运行 gdal2tiles.py command2 = ( rf"python {qietu_path} -z 10-18 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py004 命令command2: {command2}") run_command(command2) update_progress_ini(None, 1) # 更新 Progress.ini 文件 elif return_code2 != 0 and folder_name == "imgs1": logger.info("imgs1 切图失败,尝试重新运行") hhimg="imgs1" time.sleep(20) logger.info(f"imgs1第二次重建的时间时分秒:,{time.time()}") # 如果失败等两秒在运行一次命令 command3 = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/{hhimg}\" --rerun-all --skip-report --skip-3dmodel --pc-rectify --pc-ept --pc-quality lowest " f"--feature-quality lowest" ) logger.info(f"只建倾斜 运行005 docker 命令command3: {command3}") return_code2 = run_command(command3) if return_code2 == 0: # 如果命令成功,再运行 gdal2tiles.py command2 = ( rf"python {qietu_path} -z 10-18 " rf"{config['settings']['imagesfolderpath']}/{hhimg}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py006 命令command2: {command2}") run_command(command2) update_progress_ini(None, 1) # 更新 Progress.ini 文件 # 全建 elif istype_quanjian: # 建模型 # 建模型 if folder_name == "allimages": # 如果新文件夹名是 allimages,允许运行 docker 命令并生成 orthophoto command_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/allimages\" --skip-report --pc-rectify --pc-ept --pc-quality {jingdu_value} " f"--feature-quality {jingdu_value} --3d-tiles --copy-to \"/datasets/{config['settings']['resultNameDir']}\"" ) logger.info(f"全建 运行 docker 命令command_docker: {command_docker}") return_code = run_command(command_docker) if return_code == 0: # 如果命令成功,再运行 node 789.js command33 = ( rf"python {qietu_path} -z 1-21 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py 命令command33: {command33}") run_command(command33) update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 else: command3 = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/{folder_name}\" --skip-report --skip-3dmodel --pc-rectify --pc-ept --pc-quality lowest " f"--feature-quality lowest" ) logger.info(f"全建 运行 docker 命令command3: {command3}") return_code2 = run_command(command3) if return_code2 == 0: # 如果命令成功,再运行 gdal2tiles.py command2 = ( rf"python {qietu_path} -z 10-18 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 4" ) logger.info(f"运行 gdal2tiles.py 命令command2: {command2}") run_command(command2) update_progress_ini(None, 1) # 更新 Progress.ini 文件 # 只建NDVI elif istype_ndvi: if folder_name == "NIR_allimages": # 如果新文件夹名是 allimages,允许运行 docker 命令并生成 orthophoto NIRcommand_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/NIR_allimages\" --skip-report --skip-3dmodel " # f"--copy-to \"/datasets/{config['settings']['resultNameDir']}/NIR\"" # f"--feature-quality {jingdu_value}" ) logger.info(f"只建正射 运行 docker 命令command_docker: {NIRcommand_docker}") return_code = run_command(NIRcommand_docker) if return_code == 0: isNIR=True if isNIR and isRED: file1 = f"{config['settings']['imagesfolderpath']}/NIR_allimages/odm_orthophoto/odm_orthophoto.original.tif" file2 = f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original.tif" out1 =f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original_NIR.tif" out2 =f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original_red.tif" caijian_main(file1, file2, out1, out2) # 计算NDVI_command NDVI_command = f"python D:/Python39/Scripts/gdal_calc.py -A {out1} -B {out2} --outfile={config['settings']['resultnamedir']}/NDVI.tif --calc=\"(A-B)/(A+B)\"" logger.info(f"运行 计算NDVI_command 命令: {NDVI_command}") NDVI_code= run_command(NDVI_command) if NDVI_code == 0: # 如果命令成功,再运行 node 789.js command33 = ( rf"python {qietu_path} -z 1-21 " rf"{config['settings']['resultnamedir']}/NDVI.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 10" ) logger.info(f"运行 gdal2tiles.py 命令command33: {command33}") run_command(command33) update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 elif folder_name== "NIR_allimages": # 如果新文件夹名是 allimages,允许运行 docker 命令并生成 orthophoto NIRcommand_docker = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/NIR_allimages\" --skip-report --skip-3dmodel " # f"--copy-to \"/datasets/{config['settings']['resultNameDir']}/NIR\"" # f"--feature-quality {jingdu_value}" ) logger.info(f"只建正射 运行 docker 命令command_docker: {NIRcommand_docker}") return_code = run_command(NIRcommand_docker) if return_code == 0: isRED=True if isNIR and isRED: file1 = f"{config['settings']['imagesfolderpath']}/NIR_allimages/odm_orthophoto/odm_orthophoto.original.tif" file2 = f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original.tif" out1 =f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original_NIR.tif" out2 =f"{config['settings']['imagesfolderpath']}/RED_allimages/odm_orthophoto/odm_orthophoto.original_red.tif" caijian_main(file1, file2, out1, out2) # 计算NDVI_command NDVI_command = f"python {config['settings']['gdal_calc_path']} -A {out1} -B {out2} --outfile={config['settings']['resultnamedir']}/NDVI.tif --calc=\"(A-B)/(A+B)\"" logger.info(f"运行 计算NDVI_command 命令: {NDVI_command}") NDVI_code= run_command(NDVI_command) if NDVI_code == 0: # 如果命令成功,再运行 node 789.js command33 = ( rf"python {qietu_path} -z 1-21 " rf"{config['settings']['resultnamedir']}/NDVI.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 10" ) logger.info(f"运行 gdal2tiles.py 命令command33: {command33}") run_command(command33) update_progress_ini("allimages", 1) # 更新 Progress.ini 文件 # else是imgs1,imgs2、、、、、、等前缀是imgs,避免出现其他文件夹 elif folder_name.startswith('NIRimgs'): command3 = ( f"docker run -ti --rm -v {config['settings']['projectpath']}:/datasets --gpus all opendronemap/odm:gpu " f"--project-path /datasets \"/datasets/{config['settings']['taskqueuepath']}/{folder_name}\" --skip-report --skip-3dmodel --pc-rectify --pc-ept" # f" --pc-quality lowest --feature-quality lowest" ) logger.info(f"只建NIR 运行 docker 命令command3: {command3}") return_code2 = run_command(command3) if return_code2 == 0: # 转化为RGBA带透明通道tif tif_command = ( rf"{gdal_translate_path} -b 1 -b 1 -b 1 -b 2 -colorinterp red,green,blue,alpha -a_nodata 0 {config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original.tif {config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original_NIR.tif" ) logger.info(f"运行 gdal_translate 命令tif_command: {tif_command}") Translator_command= run_command(tif_command) if Translator_command == 0: # 如果命令成功,再运行 gdal2tiles.py command2 = ( rf"python {qietu_path} -z 10-18 " rf"{config['settings']['imagesfolderpath']}/{folder_name}/odm_orthophoto/odm_orthophoto.original_NIR.tif " rf"{config['settings']['projectpath']}/{config['settings']['resultNameDir']}/tiles " rf"--xyz --processes 10" ) logger.info(f"运行 gdal2tiles.py 命令command2: {command2}") run_command(command2) update_progress_ini(None, 1) # 更新 Progress.ini 文件 def update_progress_ini(folder_name, value): config_progress = configparser.ConfigParser() progress_file = 'Progress.ini' if os.path.exists(progress_file): with open(progress_file, 'r', encoding='utf-8') as progressfile: config_progress.read_file(progressfile) else: config_progress.add_section('Progress') if folder_name == "allimages": config_progress.set('Progress', 'allimages', str(value)) else: # 查找下一个 imgs 键,例如 imgs1, imgs2, ... last_imgs_key = None for key in config_progress['Progress']: if key.startswith('imgs'): last_imgs_key = int(key[4:]) if last_imgs_key is not None: new_imgs_key = f"imgs{last_imgs_key + 1}" else: new_imgs_key = "imgs1" config_progress.set('Progress', new_imgs_key, str(value)) with open(progress_file, 'w', encoding='utf-8') as progressfile: config_progress.write(progressfile) logger.info(f"更新 Progress.ini 文件: {new_imgs_key if folder_name != 'allimages' else 'allimages'} = {value}") class NewFolderHandler(FileSystemEventHandler): def __init__(self, folder_path): super().__init__() self.folder_path = folder_path self.folder_sizes = {} # 用于存储文件夹大小 self.size_check_interval = 2 self.size_check_threshold = 5 self.executor = concurrent.futures.ThreadPoolExecutor(max_workers=10) # 设置最大线程数 def on_created(self, event): if event.is_directory and os.path.basename(event.src_path) != 'config.ini': folder_name = os.path.basename(event.src_path) folder_full_path = os.path.join(self.folder_path, folder_name) logger.info(f"新文件夹创建: {folder_name}") # 初始化文件夹大小 current_size = get_folder_size(folder_full_path) if current_size is not None: self.folder_sizes[folder_name] = { 'size': current_size, 'last_checked': time.time() } logger.info(f"初始文件夹大小: {folder_name}, 大小: {self.folder_sizes[folder_name]['size']} bytes") def check_folder_size(self): current_time = time.time() for folder_name, size_info in list(self.folder_sizes.items()): folder_full_path = os.path.join(self.folder_path, folder_name) current_size = get_folder_size(folder_full_path) if current_size is None: continue last_checked = size_info['last_checked'] if current_size != size_info['size']: logger.info(f"文件夹大小发生变化: {folder_name}, 大小: {current_size} bytes") self.folder_sizes[folder_name] = { 'size': current_size, 'last_checked': current_time } elif current_time - last_checked > self.size_check_threshold: logger.info(f"文件夹大小在 {self.size_check_threshold} 秒内没有变化: {folder_name}, 大小: {current_size} bytes") config = configparser.ConfigParser() # 读入配置文件时,使用 open() 函数指定编码 with open('config.ini', 'r', encoding='utf-8') as configfile: config.read_file(configfile) # 加载配置文件读取切图工具路径 config_build = configparser.ConfigParser() # 读入配置文件时,使用 open() 函数指定编码 with open('build.ini', 'r', encoding='utf-8') as configfile: config_build.read_file(configfile) # 提交任务到线程池 self.executor.submit(process_folder, folder_name, folder_full_path, config, config_build) # 从字典中移除已经处理的文件夹 del self.folder_sizes[folder_name] def main(): config = configparser.ConfigParser() try: with open('config.ini', 'r', encoding='utf-8') as configfile: config.read_file(configfile) except Exception as e: print(f"读取配置文件时出错: {e}") return folder_path = config.get('settings', 'imagesFolderPath', fallback=None) if not folder_path: print("配置文件中未找到 imagesFolderPath,请检查配置文件。") return if not os.path.exists(folder_path): print(f"文件夹路径 {folder_path} 不存在,请检查配置文件。") return print(f"监控文件夹: {folder_path}") # 生成geojson文件===================================start import xml.etree.ElementTree as ET import json def kml_to_geojson(kml_file): tree = ET.parse(kml_file) root = tree.getroot() namespace = {'kml': 'http://www.opengis.net/kml/2.2'} geojson = {"type": "FeatureCollection", "features": []} for placemark in root.findall('.//kml:Placemark', namespace): feature = {"type": "Feature", "properties": {}, "geometry": {}} name = placemark.find('kml:name', namespace) if name is not None: feature['properties']['name'] = name.text point = placemark.find('.//kml:Point/kml:coordinates', namespace) if point is not None: coordinates = point.text.strip().split(',') feature['geometry']['type'] = 'Point' feature['geometry']['coordinates'] = [float(coordinates[0]), float(coordinates[1])] else: polygon = placemark.find('.//kml:Polygon/kml:outerBoundaryIs/kml:LinearRing/kml:coordinates', namespace) if polygon is not None: coordinates = polygon.text.strip().split() feature['geometry']['type'] = 'Polygon' feature['geometry']['coordinates'] = [[list(map(float, coord.split(','))) for coord in coordinates]] if feature['geometry']: geojson['features'].append(feature) return geojson def save_geojson(geojson, filename): print('Saving GeoJSON to file:', geojson ) with open(filename, 'w', encoding='utf-8') as f: json.dump(geojson, f, ensure_ascii=False, indent=4) def extract_first_point(kml_file): tree = ET.parse(kml_file) root = tree.getroot() namespace = {'kml': 'http://www.opengis.net/kml/2.2'} for placemark in root.findall('.//kml:Placemark', namespace): point = placemark.find('.//kml:Point/kml:coordinates', namespace) if point is not None: coordinates = point.text.strip().split(',') return float(coordinates[0]), float(coordinates[1]) else: polygon = placemark.find('.//kml:Polygon/kml:outerBoundaryIs/kml:LinearRing/kml:coordinates', namespace) if polygon is not None: coordinates = polygon.text.strip().split() first_point_coords = coordinates[0].split(',') return float(first_point_coords[0]), float(first_point_coords[1]) return None, None def write_to_config(centerpointlongitude, centerpointlatitude, config_file): config = configparser.ConfigParser() # 读入配置文件时,使用 open() 函数指定编码 if os.path.exists(config_file): with open(config_file, 'r', encoding='utf-8') as configfile: config.read_file(configfile) else: config.add_section('DEFAULT') # 设置 centerpointlongitude 和 centerpointlatitude 的值 config.set('settings', 'centerpointlongitude', str(centerpointlongitude)) config.set('settings', 'centerpointlatitude', str(centerpointlatitude)) # 将配置写入 config.ini 文件 with open(config_file, 'w', encoding='utf-8') as configfile: config.write(configfile) # 示例使用 kml_file_path = config.get('settings', 'kmlpath', fallback=None) # 替换为你的 KML 文件路径 geojson_result = kml_to_geojson(kml_file_path) save_geojson(geojson_result, './result/squares.geojson') # 保存为 GeoJSON 文件 if kml_file_path: centerpointlongitude, centerpointlatitude = extract_first_point(kml_file_path) if centerpointlongitude is not None and centerpointlatitude is not None: write_to_config(centerpointlongitude, centerpointlatitude, 'config.ini') else: print("未找到点的坐标") else: print("配置文件中未找到 kmlpath,请检查配置文件。") # 生成geojson文件===================================end handler = NewFolderHandler(folder_path) observer = Observer() observer.schedule(handler, path=folder_path, recursive=False) observer.start() try: while True: time.sleep(handler.size_check_interval) # 根据配置文件中的间隔时间检查一次 handler.check_folder_size() # 检查文件夹大小是否有变化 except KeyboardInterrupt: observer.stop() observer.join() # 关闭线程池 handler.executor.shutdown(wait=True) logger.info("监听器已停止") if __name__ == "__main__": main() ```
09-20
<think> 我们首先对代码进行整体分析,然后指出潜在的问题,并提出优化建议。代码的主要功能是监控一个文件夹,当有新文件夹创建时,检查其大小是否稳定(即不再变化),然后根据配置执行一系列处理(包括运行Docker命令进行图像处理、生成瓦片等)。 代码问题分析: 1. **导入重复**:`subprocess` 被导入了两次。 2. **路径字符串使用反斜杠**:在Windows路径中使用了反斜杠,但在字符串中未使用原始字符串(raw string)或进行转义,可能导致转义字符问题。例如:`cutline_path = "result\squares.geojson"`,这里的`\s`会被转义。应使用原始字符串或正斜杠。 3. **裁剪函数中的路径问题**:裁剪函数`crop_with_cutline`中,`cutline_path`是固定的,但代码中注释掉了写入该文件的代码,而实际使用中该文件是由KML转换来的。需要确保该文件存在。 4. **NDVI处理逻辑问题**: - 在`istype_ndvi`分支中,对于`folder_name`为"NIR_allimages"和"RED_allimages"的处理逻辑重复且混乱。实际上,代码中对于`folder_name=="NIR_allimages"`写了两次,而`folder_name=="RED_allimages"`并没有单独处理(只有一个`elif folder_name=="NIR_allimages"`,这显然是错误的,应该是`RED_allimages`)。 - 变量`isNIR`和`isRED`是局部变量,无法在两个不同的文件夹处理中共享状态。因此,当分别处理NIR和RED两个文件夹时,无法知道对方是否已经完成。 5. **多线程问题**: - 使用`concurrent.futures.ThreadPoolExecutor`来处理文件夹,但每个任务都是独立提交的。对于NDVI处理,需要同时存在NIR和RED两个文件夹处理完成才能进行裁剪和计算NDVI,但是当前设计无法协调两个文件夹的处理。 - 当同时有多个文件夹创建时,可能会并发处理多个任务,但Docker命令可能需要大量资源,同时运行多个可能超出系统负荷。 6. **代码重复**:四种建模类型(正射、倾斜、全建、NDVI)的处理代码存在大量重复,可以抽象成函数。 7. **错误处理不足**:在运行命令失败后,部分逻辑尝试重试,但重试逻辑不一致且不够健壮。例如,在倾斜处理中,对于`folder_name=="allimages"`失败后等待20秒重试,但对于其他情况的重试只针对`folder_name=="imgs1"`,且重试后没有错误处理。 8. **配置文件读取**:在`NewFolderHandler`的`check_folder_size`方法中,每次处理文件夹时都读取`config.ini`和`build.ini`,这可能造成不必要的IO,而且配置文件内容在运行期间可能改变,但通常配置应该是启动时读取一次。 9. **日志记录**:日志记录比较全面,但部分地方使用`print`,应统一使用`logger`。 10. **裁剪对齐函数**:在`caijian_main`函数中,裁剪两个图像时使用了相同的`cutline_path`,并且分辨率取两个图像的最小值,这可能导致其中一个图像被过度重采样,影响质量。另外,该函数在NDVI处理中被调用,但裁剪后的输出路径使用了硬编码,且输出文件保存在RED_allimages的文件夹下,这可能不是预期位置。 11. **进度更新**:`update_progress_ini`函数在更新进度时,对于非`allimages`的文件夹,会查找已有的`imgs`开头的键,然后创建一个新的键(如imgs1, imgs2)。但是,如果多个文件夹同时处理,可能会出现键的重复或顺序错乱(因为多线程并发写入同一个文件,没有加锁)。而且,该函数在写入文件时,每次都要重写整个文件,并发情况下可能相互覆盖。 12. **KML转GeoJSON**:在`main`函数中,一开始就进行KML转GeoJSON,并且写入配置文件。但是,如果配置文件已经存在,会覆盖原有的中心点坐标。而且,这个操作只在程序启动时执行一次,如果程序运行时KML文件发生变化,不会更新。 13. **资源清理**:在裁剪函数中,使用`gdal.Warp`后调用了`ds = None`来释放资源,这是正确的。但在其他资源使用上(如GDAL数据集)没有看到关闭操作。 14. **路径拼接**:部分路径拼接使用了字符串拼接,应该使用`os.path.join`,以避免平台差异。 15. **硬编码路径**:例如在NDVI处理中,调用了`gdal_calc.py`,其路径为`D:/Python39/Scripts/gdal_calc.py`,这在其他环境可能不存在。 16. **变量命名**:部分变量命名不够清晰,例如`qietu_path`(切图路径)应该使用更明确的名称如`gdal2tiles_path`。 17. **未使用的变量和导入**:例如`rasterio`导入但只在`get_info`中使用,而`get_info`只在`caijian_main`中使用,但整个代码中`caijian_main`只在NDVI分支中调用。另外,`from osgeo import osr`导入的`osr`未使用。 18. **代码结构**:`process_folder`函数过于庞大,接近300行,应该拆分成多个小函数。 19. **条件分支逻辑**:在`istype_ndvi`分支中,对于`folder_name`为`NIR_allimages`和`RED_allimages`的处理逻辑几乎相同,但实际上应该是两个不同的处理流程,然后等待两个都完成。当前代码分别在两个条件分支中设置`isNIR`和`isRED`,但这两个变量都是函数内的局部变量,无法用于跨文件夹的状态共享。 20. **瓦片生成路径**:在生成瓦片时,所有类型的处理都将瓦片输出到同一个目录(`{resultNameDir}/tiles`),这可能导致不同任务生成的瓦片相互覆盖。 优化建议: 1. **修复路径字符串**:使用原始字符串或正斜杠。例如: ```python cutline_path = r"result\squares.geojson" # 或者使用 "result/squares.geojson" ``` 2. **抽象重复代码**:将处理每种类型(正射、倾斜、全建、NDVI)的公共逻辑提取出来,减少重复。 3. **改进NDVI处理**: - 使用一个共享状态(例如全局变量或外部文件)来记录NIR和RED是否处理完成。当两者都完成时,再触发裁剪和NDVI计算。 - 或者,设计一个任务队列,当两个文件夹都处理完成后,再提交一个NDVI计算任务。 4. **配置文件读取**:在程序开始时读取配置,并传递配置对象,避免在多个地方重复读取。 5. **多线程协调**: - 考虑使用锁机制来保护共享状态(如进度文件)。 - 对于NDVI处理,可以使用一个单独的任务协调器,监控NIR和RED两个文件夹的处理状态。 6. **减少IO**:避免在循环或频繁调用的函数中重复读取配置文件。 7. **使用`os.path.join`**:在拼接路径时使用`os.path.join`,提高跨平台兼容性。 8. **移除硬编码路径**:例如`gdal_calc.py`的路径应该来自配置。 9. **日志统一**:将所有的`print`替换为`logger.info`或相应级别的日志。 10. **进度文件更新加锁**:在更新`Progress.ini`文件时,使用文件锁或线程锁,避免多线程同时写入。 11. **拆分大函数**:将`process_folder`函数按功能拆分成小函数。 12. **错误重试机制**:设计统一的错误重试机制,避免重复代码。 13. **资源使用**:确保在使用完资源(如GDAL数据集)后正确释放。 14. **中心点生成逻辑**:考虑将KML转GeoJSON和提取中心点单独作为一个初始化步骤,并且可以设计为在KML文件变化时重新生成(如果需要)。 15. **瓦片输出路径**:为每个任务(每个文件夹)创建独立的瓦片输出目录,避免覆盖。 由于代码量很大,我们不可能在这里重写所有代码,但可以给出一些关键修改示例。 示例修改1:修复裁剪文件路径 ```python # 将 cutline_path = "result\squares.geojson" # 改为 cutline_path = os.path.join("result", "squares.geojson") # 或者使用原始字符串 ``` 示例修改2:抽象Docker命令执行函数 我们可以将运行Docker命令的部分抽象成一个函数,以减少重复。 示例修改3:NDVI处理的状态共享 由于当前设计每个文件夹处理是独立的,要实现两个文件夹都完成后的操作,我们可以使用一个全局字典来记录状态。例如: ```python # 全局字典,记录NIR和RED文件夹的处理状态 ndvi_status = {'NIR_allimages': False, 'RED_allimages': False} def process_folder(folder_name, ...): global ndvi_status # ... 其他代码 elif istype_ndvi: if folder_name in ['NIR_allimages', 'RED_allimages']: # ... 运行Docker命令 if return_code == 0: # 设置状态为完成 ndvi_status[folder_name] = True # 检查是否两个都完成 if all(ndvi_status.values()): # 进行裁剪和NDVI计算 # ... ``` 但是注意,多线程环境下修改全局变量需要加锁。 由于时间关系,我们只给出部分修改建议。下面给出一些具体的代码修改示例。 由于代码很长,我们只针对部分问题给出修改代码。 修改1:修复路径转义问题 ```python # 修改 cutline_path cutline_path = os.path.join("result", "squares.geojson") # 这样写跨平台 ``` 修改2:统一使用logger代替print 在代码中搜索`print(`,替换为`logger.info(`,但注意有些打印可能是为了控制台实时输出,可以保留一部分,或者同时打印到控制台和日志。我们可以在日志配置中添加控制台处理器。 修改3:在日志配置中添加控制台处理器,这样既写入文件又输出到控制台 ```python # 创建 logger logger = logging.getLogger() logger.setLevel(logging.INFO) # 创建文件处理器并设置编码 file_handler = logging.FileHandler('application.log', encoding='utf-8') # 创建控制台处理器 console_handler = logging.StreamHandler() formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') file_handler.setFormatter(formatter) console_handler.setFormatter(formatter) # 将处理器添加至 logger logger.addHandler(file_handler) logger.addHandler(console_handler) ``` 修改4:修复NDVI分支中对RED_allimages的处理 原代码中只有处理NIR_allimages的条件分支,没有处理RED_allimages的分支。我们需要添加: ```python # 只建NDVI elif istype_ndvi: if folder_name == "NIR_allimages": # 处理NIR_allimages ... # 运行NIR的Docker命令 if 成功: ndvi_status['NIR_allimages'] = True elif folder_name == "RED_allimages": # 处理RED_allimages ... # 运行RED的Docker命令 if 成功: ndvi_status['RED_allimages'] = True else: ... # 其他文件夹处理 # 检查是否两个都完成 if ndvi_status['NIR_allimages'] and ndvi_status['RED_allimages']: # 执行裁剪和NDVI计算 ... ``` 修改5:使用锁保护全局状态 ```python import threading ndvi_status = {'NIR_allimages': False, 'RED_allimages': False} ndvi_lock = threading.Lock() # 在修改ndvi_status时加锁 with ndvi_lock: ndvi_status[folder_name] = True both_done = all(ndvi_status.values()) if both_done: # 执行后续操作 ``` 修改6:避免硬编码路径,使用配置 在NDVI计算命令中,使用配置的路径: ```python NDVI_command = f"python {config['settings']['gdal_calc_path']} ..." ``` 修改7:为每个任务创建独立的瓦片输出目录 在生成瓦片的命令中,将输出路径修改为包含文件夹名称的路径,例如: ```python output_tiles_dir = os.path.join(config['settings']['projectpath'], config['settings']['resultNameDir'], 'tiles', folder_name) # 然后确保该目录存在 os.makedirs(output_tiles_dir, exist_ok=True) command33 = f"python {qietu_path} ... {output_tiles_dir}" ``` 修改8:进度文件更新加锁 由于多线程可能同时更新进度文件,我们需要加锁。可以使用一个线程锁来保护进度文件的写入。 ```python progress_lock = threading.Lock() def update_progress_ini(folder_name, value): global progress_lock with progress_lock: # 原有的读取和写入Progress.ini的代码 ... ``` 修改9:减少配置文件重复读取 在`main`函数中读取配置,然后将配置对象传递给需要的地方。 由于代码重构量较大,这里无法一一实现。我们建议按照上述优化建议逐步重构代码。 最后,由于问题中要求检查bug和优化,我们总结如下: 主要bug: - 裁剪文件路径的转义问题(可能导致文件找不到)。 - NDVI处理中,RED_allimages没有被正确处理,且状态管理不完善。 - 进度文件更新在多线程下可能相互覆盖。 优化方向: - 代码结构优化,减少重复代码。 - 资源使用优化(如配置文件读取、路径拼接)。 - 多线程协调和资源共享。 - 错误处理和重试机制。 由于时间限制,我们无法提供完整的重构代码,但希望以上分析能帮助您进行修改。 注意:以上代码修改示例仅供参考,实际修改请根据您的项目结构和需求调整。 如果您需要更具体的帮助,请指出需要详细修改的部分。 相关问题: 1. 在多线程程序中,如何安全地共享状态(例如NDVI处理状态)? 2. GDAL在处理大型栅格图像时,如何优化内存使用? 3. 如何设计一个任务队列来处理有依赖关系的任务(例如NDVI需要两个前置任务)? 4. 在长时间运行的文件监控程序中,如何避免文件句柄泄漏? </think> ### 代码分析及优化建议 这段代码实现了一个文件监控系统,主要功能是: 1. 监控指定文件夹的新创建子文件夹 2. 当文件夹大小稳定后,根据配置文件执行不同的处理流程 3. 支持正射影像、倾斜模型、全建模型和NDVI指数四种处理类型 4. 使用Docker运行OpenDroneMap进行影像处理 5. 生成瓦片地图并更新进度文件 ### 主要问题 #### 1. 路径处理问题 ```python cutline_path = "result\squares.geojson" # Windows反斜杠未转义 ``` 应改为: ```python cutline_path = os.path.join("result", "squares.geojson") # 使用os.path.join跨平台兼容 ``` #### 2. 逻辑错误(NDVI处理) ```python elif folder_name == "NIR_allimages": # 处理NIR elif folder_name == "NIR_allimages": # 重复条件,应为RED_allimages # 应该处理RED ``` 应改为: ```python elif folder_name == "NIR_allimages": # 处理NIR elif folder_name == "RED_allimages": # 修正条件 # 处理RED ``` #### 3. 全局状态管理问题 ```python isNIR=False isRED=False # 局部变量,无法跨函数调用保持状态 ``` 应使用全局状态管理: ```python # 在文件顶部定义 ndvi_status = {"NIR_done": False, "RED_done": False} ``` #### 4. 资源管理问题 ```python ds = gdal.Warp(...) ds = None # 未正确释放资源 ``` 应使用上下文管理器: ```python with gdal.Warp(output_path, input_path, options=warp_options) as ds: pass ``` #### 5. 路径拼接问题 多处使用字符串拼接而非`os.path.join()`: ```python out1 =f"{config['settings']['imagesfolderpath']}/RED_allimages/...tif" ``` 应改为: ```python out1 = os.path.join(config['settings']['imagesfolderpath'], "RED_allimages", "...tif") ``` #### 6. 线程安全问题 ```python def update_progress_ini(...): # 多线程同时写入同一文件 ``` 应添加文件锁: ```python import fcntl def update_progress_ini(...): with open(progress_file, 'a+') as f: fcntl.flock(f, fcntl.LOCK_EX) # 更新逻辑 fcntl.flock(f, fcntl.LOCK_UN) ``` #### 7. 代码重复问题 四种处理类型有大量重复代码,可抽象为公共函数: ```python def run_odm_command(config, folder_name, jingdu_value, skip_report, skip_3d, skip_ortho): command = f"docker run ... {skip_report} {skip_3d} ..." # 公共执行逻辑 ``` ### 优化后的关键函数 #### 1. 裁剪函数优化 ```python def crop_with_cutline(input_path, output_path, cutline, target_crs, target_res): """使用GDAL裁剪栅格图像""" try: warp_options = gdal.WarpOptions( format='GTiff', cutlineDSName=cutline, cropToCutline=True, dstSRS=target_crs, xRes=target_res[0], yRes=target_res[1], resampleAlg='bilinear', creationOptions=['COMPRESS=LZW', 'TILED=YES'] # 添加压缩选项 ) with gdal.Warp(output_path, input_path, options=warp_options) as ds: if ds is None: logger.error(f"裁剪失败: {gdal.GetLastErrorMsg()}") return False return True except Exception as e: logger.exception(f"裁剪过程中出错: {e}") return False ``` #### 2. NDVI状态管理 ```python # 全局状态跟踪 ndvi_state = { "NIR_completed": False, "RED_completed": False, "last_check": time.time() } def check_ndvi_ready(config, qietu_path): """检查NDVI处理条件是否满足""" global ndvi_state if not (ndvi_state["NIR_completed"] and ndvi_state["RED_completed"]): return # 清除状态防止重复执行 ndvi_state["NIR_completed"] = False ndvi_state["RED_completed"] = False # 执行NDVI计算逻辑 file1 = os.path.join(config['settings']['imagesfolderpath'], "NIR_allimages", "odm_orthophoto", "odm_orthophoto.original.tif") file2 = os.path.join(config['settings']['imagesfolderpath'], "RED_allimages", "odm_orthophoto", "odm_orthophoto.original.tif") out_dir = os.path.join(config['settings']['projectpath'], config['settings']['resultNameDir'], "ndvi_temp") os.makedirs(out_dir, exist_ok=True) out1 = os.path.join(out_dir, "odm_orthophoto.original_NIR.tif") out2 = os.path.join(out_dir, "odm_orthophoto.original_red.tif") if caijian_main(file1, file2, out1, out2): ndvi_path = os.path.join(config['settings']['resultnamedir'], "NDVI.tif") NDVI_command = f"python {config['settings']['gdal_calc_path']} -A {out1} -B {out2} --outfile={ndvi_path} --calc=\"(A-B)/(A+B)\"" if run_command(NDVI_command) == 0: tile_command = f"python {qietu_path} -z 1-21 {ndvi_path} {os.path.join(config['settings']['projectpath'], config['settings']['resultNameDir'], 'tiles')} --xyz --processes={os.cpu_count()}" run_command(tile_command) ``` #### 3. 进度更新函数(线程安全) ```python import fcntl def update_progress_ini(folder_name, value): """线程安全的进度更新""" progress_file = 'Progress.ini' config_progress = configparser.ConfigParser() try: with open(progress_file, 'a+') as f: # 获取文件锁 fcntl.flock(f, fcntl.LOCK_EX) f.seek(0) config_progress.read_file(f) if not config_progress.has_section('Progress'): config_progress.add_section('Progress') if folder_name == "allimages": config_progress.set('Progress', 'allimages', str(value)) else: # 键生成逻辑... pass f.seek(0) f.truncate() config_progress.write(f) except Exception as e: logger.error(f"更新进度文件失败: {e}") finally: fcntl.flock(f, fcntl.LOCK_UN) ``` ### 配置管理优化 ```python class ConfigManager: """集中管理配置加载""" _config = None _config_build = None _last_load = 0 _lock = threading.Lock() @classmethod def get_config(cls): with cls._lock: if not cls._config or time.time() - cls._last_load > 30: # 30秒缓存 cls._config = configparser.ConfigParser() with open('config.ini', 'r', encoding='utf-8') as f: cls._config.read_file(f) cls._last_load = time.time() return cls._config @classmethod def get_build_config(cls): # 类似逻辑... ``` ### 整体优化建议 1. **使用面向对象重构**:将文件夹处理器、配置管理器等封装为类 2. **减少全局变量**:使用类属性或闭包管理状态 3. **增强错误处理**:关键操作添加try-except和详细日志 4. **资源优化**: - 限制Docker并发数量 - 添加内存使用监控 - 实现任务队列机制 5. **配置热更新**:使用watchdog监控配置文件变化 6. **日志优化**:添加日志轮转和分级处理 7. **跨平台支持**:确保路径处理兼容Windows/Linux 8. **性能优化**: - 使用Rasterio代替GDAL(更Pythonic的API) - 并行瓦片生成 - 缓存中间结果 ### 重构后的类结构建议 ```python class OrthoProcessor: def __init__(self, config): self.config = config def process_zhengshe(self, folder_name): # 正射处理逻辑 def process_qingxie(self, folder_name): # 倾斜处理逻辑 # 其他处理类型... class NDVIManager: def __init__(self): self.state = {"NIR": False, "RED": False} def mark_complete(self, band): self.state[band] = True if all(self.state.values()): self.process_ndvi() def process_ndvi(self): # NDVI处理逻辑 class FolderMonitor: def __init__(self, path): self.path = path self.executor = ThreadPoolExecutor(max_workers=4) self.odm_processor = OrthoProcessor(ConfigManager.get_config()) self.ndvi_manager = NDVIManager() def on_folder_created(self, folder_name): # 监控逻辑 if folder_name.startswith("NIR"): self.executor.submit(self.process_nir, folder_name) elif folder_name.startswith("RED"): self.executor.submit(self.process_red, folder_name) else: self.executor.submit(self.odm_processor.process, folder_name) def process_nir(self, folder_name): # 处理近红外 self.ndvi_manager.mark_complete("NIR") # 其他方法... ``` ### 总结 主要需要解决的问题: 1. **路径处理**:使用`os.path`替代字符串拼接 2. **状态管理**:实现全局状态跟踪机制 3. **线程安全**:关键操作添加锁机制 4. **错误处理**:增强异常捕获和日志 5. **代码结构**:提取重复逻辑,使用面向对象重构 6. **资源管理**:正确释放GDAL资源,限制并发 优化后代码将更健壮、可维护,并能正确处理NDVI等复杂工作流。
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