https://github.com/ultralytics/assets

Ultralytics assets
https://github.com/ultralytics/assets

app computer-vision docs hub machine-learning models ultralytics website yolo yolo11 yolo26 yolov5 yolov8

Last synced: about 1 month ago
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Ultralytics assets

• Host: GitHub
• URL: https://github.com/ultralytics/assets
• Owner: ultralytics
• License: agpl-3.0
• Created: 2022-08-06T00:21:29.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2026-01-27T00:32:22.000Z (about 1 month ago)
• Last Synced: 2026-01-27T09:39:48.647Z (about 1 month ago)
• Topics: app, computer-vision, docs, hub, machine-learning, models, ultralytics, website, yolo, yolo11, yolo26, yolov5, yolov8
• Homepage: https://ultralytics.com
• Size: 86.5 MB
• Stars: 493
• Watchers: 8
• Forks: 39
• Open Issues: 18
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Security: docs/security-alarm-system-ultralytics-yolov8.avif

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README

          


# 🌟 Welcome to the Ultralytics Assets Repository

Welcome! You've arrived at the [Ultralytics](https://www.ultralytics.com/) Assets repository, your central hub for visual assets, powerful pre-trained models, and curated datasets. These resources are designed to complement the Ultralytics YOLO ecosystem, supporting tasks like [object detection](https://docs.ultralytics.com/tasks/detect/), [instance segmentation](https://docs.ultralytics.com/tasks/segment/), [image classification](https://docs.ultralytics.com/tasks/classify/), [pose estimation](https://docs.ultralytics.com/tasks/pose/), and [object tracking](https://docs.ultralytics.com/modes/track/).

[![Ultralytics Actions](https://github.com/ultralytics/assets/actions/workflows/format.yml/badge.svg)](https://github.com/ultralytics/assets/actions/workflows/format.yml)

[![Ultralytics Discord](https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue)](https://discord.com/invite/ultralytics)

[![Ultralytics Forums](https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue)](https://community.ultralytics.com/)

[![Ultralytics Reddit](https://img.shields.io/reddit/subreddit-subscribers/ultralytics?style=flat&logo=reddit&logoColor=white&label=Reddit&color=blue)](https://reddit.com/r/ultralytics)

## 🛠️ Features at a Glance

- **🖼 Visual Assets**: Access our collection of banners and logos for use in your applications or collaborations involving Ultralytics tools.

- **🤖 Models at Your Fingertips**: Leverage pre-trained models, ready for deployment after [fine-tuning](https://www.ultralytics.com/glossary/fine-tuning). These models are optimized for a variety of [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks.

- **📦 Datasets Ready for Action**: Enhance your [machine learning](https://www.ultralytics.com/glossary/machine-learning-ml) projects with our repositories of [annotated data](https://www.ultralytics.com/glossary/data-labeling), prepared for model training, validation, and testing. Explore available datasets in our [datasets documentation](https://docs.ultralytics.com/datasets/).

## 💡 Getting Started with Usage

### 📥 Download Pretrained Models Seamlessly

Ultralytics YOLO frameworks automatically download required pre-trained models from this repository if they are not found locally.

```python

from ultralytics import YOLO

# Load a pre-trained Ultralytics YOLO model

model = YOLO("yolo26n.pt")  # Model automatically downloaded if not present

# Define the source image path

source = "path/to/image.jpg"

# Perform inference

results = model(source)  # Returns detection results

```

### 🌐 Embrace the Visuals

All visual assets are available on the main branch and can be downloaded directly for your projects, presentations, or documentation needs.

### 📚 Explore Our Datasets

Our datasets are accessible through repository releases. Each dataset includes a README file with usage instructions. Please review the specific licenses and guidelines for each dataset to ensure compliance with your project requirements.

## 🤝 Contribute

We encourage contributions from the community! Whether it's fixing bugs, adding new features, or improving documentation, your input is valuable. Check out our [Contributing Guide](https://docs.ultralytics.com/help/contributing/) to learn how to get started. We also appreciate feedback on your experience with Ultralytics products; please consider filling out our [Survey](https://www.ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey). A huge 🙏 thank you to all our contributors!

[![Ultralytics open-source contributors](https://raw.githubusercontent.com/ultralytics/assets/main/im/image-contributors.png)](https://github.com/ultralytics/ultralytics/graphs/contributors)

## ©️ License

Ultralytics offers two licensing options:

- **AGPL-3.0 License**: An [OSI-approved](https://opensource.org/license/agpl-v3) open-source license ideal for students and enthusiasts, promoting open collaboration and knowledge sharing. See the [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for details.

- **Enterprise License**: Designed for commercial use, this license permits the integration of Ultralytics software and AI models into commercial products without the open-source stipulations of AGPL-3.0. If your project involves commercial applications, please contact us through [Ultralytics Licensing](https://www.ultralytics.com/license).

## 📬 Contact Us

For bug reports, feature requests, and contributions, please use [GitHub Issues](https://github.com/ultralytics/assets/issues). For questions and discussions about this project or other Ultralytics initiatives, join our vibrant community on [Discord](https://discord.com/invite/ultralytics)!