<ahref="https://console.paperspace.com/github/ultralytics/ultralytics"><imgsrc="https://assets.paperspace.io/img/gradient-badge.svg"alt="Run Ultralytics on Gradient"></a>
@ -22,7 +22,7 @@
[Ultralytics](https://www.ultralytics.com/) [YOLO11](https://github.com/ultralytics/ultralytics) is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLO11 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
We hope that the resources here will help you get the most out of YOLO. Please browse the Ultralytics <ahref="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/ultralytics/issues/new/choose">GitHub</a> for support, questions, or discussions, become a member of the Ultralytics <ahref="https://ultralytics.com/discord">Discord</a>, <ahref="https://reddit.com/r/ultralytics">Reddit</a> and <ahref="https://community.ultralytics.com">Forums</a>!
We hope that the resources here will help you get the most out of YOLO. Please browse the Ultralytics <ahref="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/ultralytics/issues/new/choose">GitHub</a> for support, questions, or discussions, become a member of the Ultralytics <ahref="https://discord.com/invite/ultralytics">Discord</a>, <ahref="https://reddit.com/r/ultralytics">Reddit</a> and <ahref="https://community.ultralytics.com/">Forums</a>!
To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license).
@ -41,7 +41,7 @@ To request an Enterprise License please complete the form at [Ultralytics Licens
@ -210,7 +210,7 @@ See [OBB Docs](https://docs.ultralytics.com/tasks/obb/) for usage examples with
Our key integrations with leading AI platforms extend the functionality of Ultralytics' offerings, enhancing tasks like dataset labeling, training, visualization, and model management. Discover how Ultralytics, in collaboration with [Roboflow](https://roboflow.com/?ref=ultralytics), ClearML, [Comet](https://bit.ly/yolov8-readme-comet), Neural Magic and [OpenVINO](https://docs.ultralytics.com/integrations/openvino/), can optimize your AI workflow.
<imgwidth="100%"src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png"alt="Ultralytics active learning integrations"></a>
<br>
<br>
@ -237,7 +237,7 @@ Our key integrations with leading AI platforms extend the functionality of Ultra
Experience seamless AI with [Ultralytics HUB](https://www.ultralytics.com/hub) ⭐, the all-in-one solution for data visualization, YOLO11 🚀 model training and deployment, without any coding. Transform images into actionable insights and bring your AI visions to life with ease using our cutting-edge platform and user-friendly [Ultralytics App](https://www.ultralytics.com/app-install). Start your journey for **Free** now!
<ahref="https://console.paperspace.com/github/ultralytics/ultralytics"><imgsrc="https://assets.paperspace.io/img/gradient-badge.svg"alt="Run Ultralytics on Gradient"></a>
@ -41,7 +41,7 @@ Raspberry Pi is a small, affordable, single-board computer. It has become popula
## What is Raspberry Pi OS?
[Raspberry Pi OS](https://www.raspberrypi.com/software) (formerly known as Raspbian) is a Unix-like operating system based on the Debian GNU/Linux distribution for the Raspberry Pi family of compact single-board computers distributed by the Raspberry Pi Foundation. Raspberry Pi OS is highly optimized for the Raspberry Pi with ARM CPUs and uses a modified LXDE desktop environment with the Openbox stacking window manager. Raspberry Pi OS is under active development, with an emphasis on improving the stability and performance of as many Debian packages as possible on Raspberry Pi.
[Raspberry Pi OS](https://www.raspberrypi.com/software/) (formerly known as Raspbian) is a Unix-like operating system based on the Debian GNU/Linux distribution for the Raspberry Pi family of compact single-board computers distributed by the Raspberry Pi Foundation. Raspberry Pi OS is highly optimized for the Raspberry Pi with ARM CPUs and uses a modified LXDE desktop environment with the Openbox stacking window manager. Raspberry Pi OS is under active development, with an emphasis on improving the stability and performance of as many Debian packages as possible on Raspberry Pi.
## Flash Raspberry Pi OS to Raspberry Pi
@ -249,7 +249,7 @@ To reproduce the above Ultralytics benchmarks on all [export formats](../modes/e
## Use Raspberry Pi Camera
When using Raspberry Pi for Computer Vision projects, it can be essentially to grab real-time video feeds to perform inference. The onboard MIPI CSI connector on the Raspberry Pi allows you to connect official Raspberry PI camera modules. In this guide, we have used a [Raspberry Pi Camera Module 3](https://www.raspberrypi.com/products/camera-module-3) to grab the video feeds and perform inference using YOLOv8 models.
When using Raspberry Pi for Computer Vision projects, it can be essentially to grab real-time video feeds to perform inference. The onboard MIPI CSI connector on the Raspberry Pi allows you to connect official Raspberry PI camera modules. In this guide, we have used a [Raspberry Pi Camera Module 3](https://www.raspberrypi.com/products/camera-module-3/) to grab the video feeds and perform inference using YOLOv8 models.
!!! tip
@ -257,7 +257,7 @@ When using Raspberry Pi for Computer Vision projects, it can be essentially to g
!!! note
Raspberry Pi 5 uses smaller CSI connectors than the Raspberry Pi 4 (15-pin vs 22-pin), so you will need a [15-pin to 22pin adapter cable](https://www.raspberrypi.com/products/camera-cable) to connect to a Raspberry Pi Camera.
Raspberry Pi 5 uses smaller CSI connectors than the Raspberry Pi 4 (15-pin vs 22-pin), so you will need a [15-pin to 22pin adapter cable](https://www.raspberrypi.com/products/camera-cable/) to connect to a Raspberry Pi Camera.
<palign="center"><ahref="https://vimeo.com/639236696">ROS Introduction (captioned)</a> from <ahref="https://vimeo.com/osrfoundation">Open Robotics</a> on <ahref="https://vimeo.com">Vimeo</a>.</p>
<palign="center"><ahref="https://vimeo.com/639236696">ROS Introduction (captioned)</a> from <ahref="https://vimeo.com/osrfoundation">Open Robotics</a> on <ahref="https://vimeo.com/">Vimeo</a>.</p>
@ -56,7 +56,7 @@ To quickly get a glimpse of the code coverage status of the `ultralytics` python
In the sunburst graphic below, the innermost circle is the entire project, moving away from the center are folders then, finally, a single file. The size and color of each slice is representing the number of statements and the coverage, respectively.
<ahref="https://github.com/ultralytics/hub/actions/workflows/ci.yaml"><imgsrc="https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg"alt="CI CPU"></a><ahref="https://colab.research.google.com/github/ultralytics/hub/blob/main/hub.ipynb"><imgsrc="https://colab.research.google.com/assets/colab-badge.svg"alt="Open In Colab"></a><ahref="https://ultralytics.com/discord"><imgalt="Discord"src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a><ahref="https://community.ultralytics.com"><imgalt="Ultralytics Forums"src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a><ahref="https://reddit.com/r/ultralytics"><imgalt="Ultralytics Reddit"src="https://img.shields.io/reddit/subreddit-subscribers/ultralytics?style=flat&logo=reddit&logoColor=white&label=Reddit&color=blue"></a>
<ahref="https://github.com/ultralytics/hub/actions/workflows/ci.yaml"><imgsrc="https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg"alt="CI CPU"></a><ahref="https://colab.research.google.com/github/ultralytics/hub/blob/main/hub.ipynb"><imgsrc="https://colab.research.google.com/assets/colab-badge.svg"alt="Open In Colab"></a><ahref="https://discord.com/invite/ultralytics"><imgalt="Discord"src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a><ahref="https://community.ultralytics.com/"><imgalt="Ultralytics Forums"src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a><ahref="https://reddit.com/r/ultralytics"><imgalt="Ultralytics Reddit"src="https://img.shields.io/reddit/subreddit-subscribers/ultralytics?style=flat&logo=reddit&logoColor=white&label=Reddit&color=blue"></a>
</div>
👋 Hello from the [Ultralytics](https://www.ultralytics.com/) Team! We've been working hard these last few months to launch [Ultralytics HUB](https://www.ultralytics.com/hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀 models from one spot!
We hope that the resources here will help you get the most out of HUB. Please browse the HUB <ahref="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <ahref="https://ultralytics.com/discord">Discord</a> community for questions and discussions!
We hope that the resources here will help you get the most out of HUB. Please browse the HUB <ahref="https://docs.ultralytics.com/">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <ahref="https://discord.com/invite/ultralytics">Discord</a> community for questions and discussions!
<divalign="center">
<br>
@ -44,7 +44,7 @@ We hope that the resources here will help you get the most out of HUB. Please br
@ -61,7 +61,7 @@ We hope that the resources here will help you get the most out of HUB. Please br
<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB
</p>
We hope that the resources here will help you get the most out of HUB. Please browse the HUB <ahref="https://docs.ultralytics.com/hub">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <ahref="https://ultralytics.com/discord">Discord</a> community for questions and discussions!
We hope that the resources here will help you get the most out of HUB. Please browse the HUB <ahref="https://docs.ultralytics.com/hub/">Docs</a> for details, raise an issue on <ahref="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <ahref="https://discord.com/invite/ultralytics">Discord</a> community for questions and discussions!
- [**Quickstart**](quickstart.md): Start training and deploying models in seconds.
- [**Datasets**](datasets.md): Learn how to prepare and upload your datasets.
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@ -49,7 +49,7 @@ Explore the Ultralytics Docs, a comprehensive resource designed to help you unde
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.
<imgwidth="100%"src="https://github.com/ultralytics/docs/releases/download/0/ultralytics-active-learning-loop.avif"alt="Ultralytics active learning"></a>