Update YOLO11 comparison plots (#17097)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 1 month ago committed by GitHub
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  1. 2
      README.md
  2. 2
      README.zh-CN.md
  3. 2
      docs/en/models/index.md
  4. 2
      docs/en/models/yolo11.md

@ -26,7 +26,7 @@ We hope that the resources here will help you get the most out of YOLO. Please b
To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license). To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license).
<img width="100%" src="https://github.com/user-attachments/assets/a311a4ed-bbf2-43b5-8012-5f183a28a845" alt="YOLO11 performance plots"></a> <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png" alt="YOLO11 performance plots"></a>
<div align="center"> <div align="center">
<a href="https://github.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="Ultralytics GitHub"></a> <a href="https://github.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="Ultralytics GitHub"></a>

@ -26,7 +26,7 @@
想申请企业许可证,请完成 [Ultralytics Licensing](https://www.ultralytics.com/license) 上的表单。 想申请企业许可证,请完成 [Ultralytics Licensing](https://www.ultralytics.com/license) 上的表单。
<img width="100%" src="https://github.com/user-attachments/assets/a311a4ed-bbf2-43b5-8012-5f183a28a845" alt="YOLO11 performance plots"></a> <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png" alt="YOLO11 performance plots"></a>
<div align="center"> <div align="center">
<a href="https://github.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="Ultralytics GitHub"></a> <a href="https://github.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="Ultralytics GitHub"></a>

@ -8,7 +8,7 @@ keywords: Ultralytics, supported models, YOLOv3, YOLOv4, YOLOv5, YOLOv6, YOLOv7,
Welcome to Ultralytics' model documentation! We offer support for a wide range of models, each tailored to specific tasks like [object detection](../tasks/detect.md), [instance segmentation](../tasks/segment.md), [image classification](../tasks/classify.md), [pose estimation](../tasks/pose.md), and [multi-object tracking](../modes/track.md). If you're interested in contributing your model architecture to Ultralytics, check out our [Contributing Guide](../help/contributing.md). Welcome to Ultralytics' model documentation! We offer support for a wide range of models, each tailored to specific tasks like [object detection](../tasks/detect.md), [instance segmentation](../tasks/segment.md), [image classification](../tasks/classify.md), [pose estimation](../tasks/pose.md), and [multi-object tracking](../modes/track.md). If you're interested in contributing your model architecture to Ultralytics, check out our [Contributing Guide](../help/contributing.md).
![Ultralytics YOLO11 Comparison Plots](https://github.com/user-attachments/assets/a311a4ed-bbf2-43b5-8012-5f183a28a845) ![Ultralytics YOLO11 Comparison Plots](https://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png)
## Featured Models ## Featured Models

@ -10,7 +10,7 @@ keywords: YOLO11, state-of-the-art object detection, YOLO series, Ultralytics, c
YOLO11 is the latest iteration in the [Ultralytics](https://www.ultralytics.com/) YOLO series of real-time object detectors, redefining what's possible with cutting-edge [accuracy](https://www.ultralytics.com/glossary/accuracy), speed, and efficiency. Building upon the impressive advancements of previous YOLO versions, YOLO11 introduces significant improvements in architecture and training methods, making it a versatile choice for a wide range of [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks. YOLO11 is the latest iteration in the [Ultralytics](https://www.ultralytics.com/) YOLO series of real-time object detectors, redefining what's possible with cutting-edge [accuracy](https://www.ultralytics.com/glossary/accuracy), speed, and efficiency. Building upon the impressive advancements of previous YOLO versions, YOLO11 introduces significant improvements in architecture and training methods, making it a versatile choice for a wide range of [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks.
![Ultralytics YOLO11 Comparison Plots](https://github.com/user-attachments/assets/a311a4ed-bbf2-43b5-8012-5f183a28a845) ![Ultralytics YOLO11 Comparison Plots](hhttps://raw.githubusercontent.com/ultralytics/assets/refs/heads/main/yolo/performance-comparison.png)
<p align="center"> <p align="center">
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