秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

SegmentAnythingModel2（SAM2）作为Meta公司发布的SegmentAnythingModel（SAM）的升级版本，在图像和视频分割领域展现出了显著的优点和特性。论文连接：https://arxiv.org/pdf/2408.00714Demo:https://sam2.metademolab.comCode:https://github.com/facebookresearch/segme

秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

Yolov8源码解析（五）comments:truedescription:LearnhowtorunYOLOv8onAzureML.QuickstartinstructionsforterminalandnotebookstoharnessAzure'scloudcomputingforefficientmodeltraining.keywords:YOLOv8,AzureML,machinelearning,cloudcom

Yolov8源码解析（十二）comments:truedescription:LearntosimplifytheloggingofYOLOv8trainingwithCometML.Thisguidecoversinstallation,setup,real-timeinsights,andcustomlogging.keywords:YOLOv8,CometML,logging,machinelearning,training,mo

Yolov8源码解析（十）comments:truedescription:Learnhowtoensurethread-safeYOLOmodelinferenceinPython.Avoidraceconditionsandrunyourmulti-threadedtasksreliablywithbestpractices.keywords:YOLOmodels,thread-safe,Pythonthreading,modeli

Yolov8源码解析（十一）comments:truedescription:LearnhowtoruninferenceusingtheUltralyticsHUBInferenceAPI.IncludesexamplesinPythonandcURLforquickintegration.keywords:Ultralytics,HUB,InferenceAPI,Python,cURL,RESTAPI,YOLO,imagepro

Yolov8源码解析（十七）comments:truedescription:HarnessthepowerofUltralyticsYOLOv8forreal-time,high-speedinferenceonvariousdatasources.Learnaboutpredictmode,keyfeatures,andpracticalapplications.keywords:Ultralytics,YOLOv8,modelpred

Yolov8源码解析（六）comments:truedescription:MasterhyperparametertuningforUltralyticsYOLOtooptimizemodelperformancewithourcomprehensiveguide.Elevateyourmachinelearningmodelstoday!.keywords:UltralyticsYOLO,hyperparametertuning,machi

Yolov8源码解析（九）comments:truedescription:LearnhowtoestimateobjectspeedusingUltralyticsYOLOv8forapplicationsintrafficcontrol,autonomousnavigation,andsurveillance.keywords:UltralyticsYOLOv8,speedestimation,objecttracking,computer

Yolov8源码解析（二十六）.\yolov8\tests\test_engine.py#导入所需的模块和库importsys#系统模块fromunittestimportmock#导入mock模块#导入自定义模块和类fromtestsimportMODEL#导入tests模块中的MODEL对象fromultralyticsimportYOLO#导入ul

Yolov8源码解析（八）comments:truedescription:LearnhowtomanageandoptimizequeuesusingUltralyticsYOLOv8toreducewaittimesandincreaseefficiencyinvariousreal-worldapplications.keywords:queuemanagement,YOLOv8,Ultralytics,reducewaittime

1.win10cmd命令行训练 要先激活虚拟环境，命令如下：D:cdD:\\ultralytics-main\\venv\\Scriptsactivate.batcd..\\..yolotraindata=D:\\ultralytics-main\\datasets\\zmbh.yamlmodel=D:\\ultralytics-main\\yolov8mepochs=5000imgsz=640batch=2workers=

 秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

 秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

 秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

默认已安装Anaconda（一个类似于环境管理器的软件，前面出过anaconda安装教程）1.创建激活环境打开AnacondaPrompt，创建yolov8环境condacreate-nyolov8python=3.8激活环境activateyolov82.下载yolov8安装包 下载链接：https://github.com/ultralytics/ultralytics同时可

1、本地上传至个人数据下的自定义文件夹（例yolov8)中本地Windows+R输入cmdosslogin输入账号密码登录cpD:\ultralytics-main.ziposs://yolov8/ （注意更换自己文件夹路径）2、从个人数据下载到hy-tmp文件夹中服务器终端osslogin输入账号密码登录osscposs://yolov8/ul

 秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

秋招面试专栏推荐 ：深度学习算法工程师面试问题总结【百面算法工程师】——点击即可跳转

Ultralytics中文文档（一）首页原文：docs.ultralytics.com/中文|한국어|日本語|Русский|Deutsch|Français|Español|Português|Türkçe|TiếngViệt|हिन्दी|العربية介绍UltralyticsYOLOv8，这是备受赞誉的实时目标检测

Ultralytics中文文档（四）移动端任意分割（MobileSAM）原文：docs.ultralytics.com/models/mobile-sam/MobileSAM的论文现已在arXiv上发布。可以通过此演示链接访问MobileSAM在CPU上运行的演示。在Maci5CPU上，每张图片大约需要3秒。在HuggingFace的演示中，界面和性能较

Ultralytics中文文档（十一）使用UltralyticsYOLOv8进行队列管理

Ultralytics中文文档（十五）ExplorerGUI原文：docs.ultralytics.com/datasets/explorer/dashboard/ExplorerGUI类似于使用UltralyticsExplorerAPI构建的游乐场。它允许你运行语义/向量相似度搜索、SQL查询，甚至使用我们由LLMs提供支持的自然语言查询功能。www.youtube

Ultralytics中文文档（十三）使用DeepStreamSDK和TensorRT在NVIDIAJetson上的UltralyticsYOLOv8原文：docs.ultralytics.com/guides/deepstream-nvidia-jetson/这份详尽的指南提供了在NVIDIAJetson设备上使用DeepStreamSDK和TensorRT部署UltralyticsYOLOv8的详