tasks/

[giscus[bot]]

tasks/

Explore Ultralytics YOLOv8 for detection, segmentation, classification, OBB, and pose estimation with high accuracy and speed. Learn how to apply each task.

https://docs.ultralytics.com/tasks/

[hrbjoern]

Would be nice to have examples for tracking, too ...

[glenn-jocher]

@hrbjoern thank you for your suggestion! We currently have tracking examples in our documentation. You can explore them for more insights on implementing tracking with YOLOv8.

[hrbjoern]

OK, thanks. I just figured that since it's mentioned in the beginning of the page (photo), it should also be explained ...

[glenn-jocher]

Yes sorry for the confusion. We've placed the Tracking docs under Modes rather than Tasks here: https://docs.ultralytics.com/modes/track/

[NasserAlqeifi]

Hi there! Could anyone point me to the papers for YOLOv8 and YOLOv11 Instance Segmentation? Thank you!

[glenn-jocher]

@NasserAlqeifi hello! The YOLOv8 and YOLOv11 models don't have specific papers yet. For detailed information, please refer to the Ultralytics documentation. If you have further questions, feel free to ask!

[NasserAlqeifi]

Hi @glenn-jocher ,

Thank you for the information! I'm a master's student currently using the YOLOv8 Instance Segmentation model for my thesis. I've also tried using YOLOv11 and noticed that the documentation mentions it utilizes a variant of the U-Net architecture for segmentation.

I would love to know more about how segmentation and object detection work in YOLOv11, as well as the key differences between YOLOv8 and YOLOv11 in these tasks. Any additional insights would be greatly appreciated!

Thank you!

[glenn-jocher]

Thank you for your interest! YOLOv11 uses a variant of the U-Net architecture for segmentation, enhancing accuracy and speed. The key difference from YOLOv8 is the architectural improvements for better performance across tasks. For more details, please refer to the Ultralytics documentation.

[DukeZacharia]

Good, Afternoon, does Yolo work for Human Action Detection in realtime?

[glenn-jocher]

@DukeZacharia good afternoon! YOLO can be used for real-time human action detection through pose estimation. For more details, please explore the pose estimation section in the Ultralytics documentation.

[AashishThakur1321]

how can I provide different object ids in videos to same types of objects like there are 5 persons in a video frame, then how to provide different ids to these persons such that it tracks these objects with same id throughout the videos

[glenn-jocher]

@AashishThakur1321 to track multiple persons with unique IDs in videos using YOLO11, utilize the built-in tracking mode with tracker=bot-sort.yaml or tracker=bytetrack.yaml configuration. Example CLI command:
yolo track model=yolo11n.pt source=video.mp4
This automatically assigns unique IDs to each person and maintains them across frames. For customization, see our tracking documentation.

[Saimul-Shanto]

Can I use XAI with YOLOv11 or YOLOv9 ? If so, how can I apply it to an object detection task?

[DukeZacharia]

Yes, you can utilize Explainable AI (XAI) with YOLOv9 or YOLOv11, even though these versions are unofficial or experimental extensions beyond YOLOv8. YOLO is fundamentally a convolutional neural network (CNN), which means that many XAI techniques applicable to CNNs or object detection models can be adapted for use with these versions.

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On Thu, 12 Jun 2025 at 17:27, Md Saimul Haque Shanto < ***@***.***> wrote: Can I use XAI with YOLOv11 or YOLOv9 ? If so, how can I apply it to an object detection task? — Reply to this email directly, view it on GitHub <#16241 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AGZSZVZYSGD2CDV75M5O7KD3DE2XNAVCNFSM6AAAAABOCSRMJGVHI2DSMVQWIX3LMV43URDJONRXK43TNFXW4Q3PNVWWK3TUHMYTGNBUGMZTENY> . You are receiving this because you were mentioned.Message ID: ***@***.*** com>

[adhinajay]

I quantized a YOLOv8 model. Now I want to fine tune it, so how can I convert the ONNX file back to a .pt file?