update yolo26 readme docs to update task picture and main text

README.md

@@ -48,11 +48,11 @@ model-index:
 
 [![Run on Gradient](https://img.shields.io/badge/Run_on-Gradient-blue?logo=paperspace&logoColor=white)](https://console.paperspace.com/github/ultralytics/ultralytics) [![Open In Colab](https://img.shields.io/badge/Open_in-Colab-blue?logo=googlecolab&logoColor=white)](https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb) [![Open In Kaggle](https://img.shields.io/badge/Open_in-Kaggle-blue?logo=kaggle&logoColor=white)](https://www.kaggle.com/models/ultralytics/yolo26) [![Launch Binder](https://img.shields.io/badge/Launch-Binder-blue?logo=jupyter&logoColor=white)](https://mybinder.org/v2/gh/ultralytics/ultralytics/HEAD?labpath=examples%2Ftutorial.ipynb)
 
-[Ultralytics](https://www.ultralytics.com/) creates cutting-edge, state-of-the-art (SOTA) [YOLO models](https://www.ultralytics.com/yolo) built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are **fast**, **accurate**, and **easy to use**. They excel at [object detection](https://docs.ultralytics.com/tasks/detect), [tracking](https://docs.ultralytics.com/modes/track), [instance segmentation](https://docs.ultralytics.com/tasks/segment), [semantic segmentation](https://docs.ultralytics.com/tasks/semantic), [image classification](https://docs.ultralytics.com/tasks/classify), and [pose estimation](https://docs.ultralytics.com/tasks/pose) tasks.
+[Ultralytics](https://www.ultralytics.com/?utm_source=huggingface&utm_medium=referral&utm_content=homepage) creates cutting-edge, state-of-the-art (SOTA) [YOLO models](https://www.ultralytics.com/yolo?utm_source=huggingface&utm_medium=referral&utm_content=homepage) built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use. They excel at [object detection](https://docs.ultralytics.com/tasks/detect?utm_source=huggingface&utm_medium=referral&utm_content=homepage), [instance segmentation](https://docs.ultralytics.com/tasks/segment?utm_source=huggingface&utm_medium=referral&utm_content=homepage), [semantic segmentation](https://docs.ultralytics.com/tasks/semantic?utm_source=huggingface&utm_medium=referral&utm_content=homepage), [image classification](https://docs.ultralytics.com/tasks/classify?utm_source=huggingface&utm_medium=referral&utm_content=homepage), [depth estimation](https://docs.ultralytics.com/tasks/depth?utm_source=huggingface&utm_medium=referral&utm_content=homepage) and [pose estimation](https://docs.ultralytics.com/tasks/pose?utm_source=huggingface&utm_medium=referral&utm_content=homepage) tasks, and can [track](https://docs.ultralytics.com/modes/track?utm_source=huggingface&utm_medium=referral&utm_content=homepage) detected objects across video frames.
 
-Find detailed documentation in the [Ultralytics Docs](https://docs.ultralytics.com/). Get support via [GitHub Issues](https://github.com/ultralytics/ultralytics/issues/new/choose). Join discussions on [Discord](https://discord.com/invite/ultralytics), [Reddit](https://www.reddit.com/r/ultralytics/), and the [Ultralytics Community Forums](https://community.ultralytics.com/)!
+Find detailed documentation in the [Ultralytics Docs](https://docs.ultralytics.com/?utm_source=huggingface&utm_medium=referral&utm_content=homepage). Get support via [GitHub Issues](https://github.com/ultralytics/ultralytics/issues/new/choose?utm_source=huggingface&utm_medium=referral&utm_content=homepage). Join discussions on [Discord](https://discord.com/invite/ultralytics?utm_source=huggingface&utm_medium=referral&utm_content=homepage), [Reddit](https://www.reddit.com/r/ultralytics/?utm_source=huggingface&utm_medium=referral&utm_content=homepage), and the [Ultralytics Community Forums](https://community.ultralytics.com/?utm_source=huggingface&utm_medium=referral&utm_content=homepage)!
 
-Request an Enterprise License for commercial use at [Ultralytics Licensing](https://www.ultralytics.com/license).
+Request an Enterprise License for commercial use at [Ultralytics Licensing](https://www.ultralytics.com/license?utm_source=huggingface&utm_medium=referral&utm_content=homepage).
 
 Read the technical details on our [official YOLO26 paper](https://arxiv.org/abs/2606.03748).
 
@@ -133,7 +133,7 @@ Discover more examples in the YOLO [Python Docs](https://docs.ultralytics.com/us
 Ultralytics supports a wide range of YOLO models, from early versions like [YOLOv3](https://docs.ultralytics.com/models/yolov3) to the latest [YOLO26](https://docs.ultralytics.com/models/yolo26). The tables below showcase YOLO26 models pretrained on [COCO](https://docs.ultralytics.com/datasets/detect/coco) for [Detection](https://docs.ultralytics.com/tasks/detect), [Segmentation](https://docs.ultralytics.com/tasks/segment), and [Pose Estimation](https://docs.ultralytics.com/tasks/pose). [Semantic Segmentation](https://docs.ultralytics.com/tasks/semantic) models are pretrained on [Cityscapes](https://docs.ultralytics.com/datasets/semantic/cityscapes), and [Classification](https://docs.ultralytics.com/tasks/classify) models are pretrained on [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet). [Tracking](https://docs.ultralytics.com/modes/track) mode is compatible with Detection, Segmentation, and Pose models. All [Models](https://docs.ultralytics.com/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) on first use.
 
 <a href="https://docs.ultralytics.com/tasks" target="_blank">
-    <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/docs/ultralytics-yolov8-tasks-banner.avif" alt="Ultralytics YOLO supported tasks">
+    <img width="100%" src="https://cdn.ul.run/i/c99d914c3958d0755b5a3d7204b6f24a.avif" alt="Ultralytics YOLO supported tasks">
 </a>
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