zh/models/yolo26/ #22219
Replies: 18 comments 17 replies
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除了监督模型,我还期待着ultralytics可以推出高效准确易用的非监督瑕疵检测模型! |
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👋 Hello, thanks for opening this discussion and for your interest in Ultralytics 🚀! This is an automated response to help you get started quickly—an Ultralytics engineer will also follow up here soon. We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many common questions may already be answered. If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it. If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results. Join the Ultralytics community where it suits you best. For real-time chat, head to Discord 🎧. Prefer in-depth discussions? Check out Discourse. Or dive into threads on our Subreddit to share knowledge with the community. UpgradeUpgrade to the latest pip install -U ultralyticsEnvironmentsYOLO may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled): -Notebooks with free GPU: StatusIf this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLO Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit. |
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表述有问题 |
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最迟不晚于什么时间开源呢 |
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除了检测、分类、分割、姿态、旋转框以外 ,希望ultralytics增加视频类的任务,比如集成行为识别模型的训练和推理,最好是能支持多目标行为识别的检测。我知道目前是有提供一些样例,但不体系,希望像检测任务一样,提供原生的整体解决方案。谢谢! |
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真不错,期待开源 |
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2025年10月23日来过,感谢yolo支持我从硕士毕了业到找到第一份工作,以后的方向期待yolo能有更大的发展,哈哈哈 |
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报道说10月底发布模型,今天最后一天了,还没影,骗子啊...... |
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11月3号了,让我对Yolo26的信任下降,发布商怎么能这么不诚信,你在发布前就造势,结果现在影子都没有 |
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延迟了10天了,还没动静 |
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马勒个巴子的不发布你在这画nm的饼。你上nm的会议吹呢。两个月了你没做好你回家蹲着行吗。 |
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YOLOv26是如何解决多个任务之间的负向迁移的问题呢?这点似乎在论文中没有提到 |
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thanks for your work. where can i download YOLOE-26 weights? |
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https://github.com/li2390893/yolo26-rk3588-cpp.git |
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提到有推理速度提升,但是看到模型结构(det)与11相比没有变化,那么提升速度的来源是什么 |
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笑不活了
发自我的iPhone
…------------------ Original ------------------
From: Melt ***@***.***>
Date: Thu,Jan 15,2026 2:02 PM
To: ultralytics/ultralytics ***@***.***>
Cc: Barrett Moor ***@***.***>, Comment ***@***.***>
Subject: Re: [ultralytics/ultralytics] zh/models/yolo26/ (Discussion #22219)
他把nms和dfl都去掉了,肯定快啊
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Reply to this email directly, view it on GitHub, or unsubscribe.
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想要采用yolo26进行语义分割,推荐么 |
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目前在实际使用测试中,26的使用并没有很好,甚至他的额检测精度下降的很多,全系模型都不是很好,不知道是不是我的使用问题,同样的代码,11模型能检测到,26完全检测不到。 |
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zh/models/yolo26/
Ultralytics 的 YOLO26 提供更快、更简单、端到端无 NMS 的对象检测功能,并针对边缘和低功耗设备进行了优化。
https://docs.ultralytics.com/zh/models/yolo26/
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