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Introducing Ultralytics YOLOv8

Discover YOLOv8, the latest advancement from Ultralytics for real-time object detection, segmentation, and classification. Explore the revolution in AI.

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Our latest release in the YOLO family of architectures, YOLOv8 is the best in the world at what it does: real-time object detection, segmentation, and classification. YOLOv8 has well-documented workflows, spotless code written from the ground up, the easiest models to use ever, and flexible solutions to fit every user's needs with support for all YOLO versions.

For us, YOLOv8 represents the culmination of years of research, development, and testing; and our team has worked hard to ensure that YOLOv8 is not only feature-rich but intuitive and easy to use. Whether you are a seasoned professional or new to the field, we’ve created YOLOv8 so that anyone can get started with our open-source tool.

And as we continue to improve YOLOv8, we encourage your suggestions, PRs, bug fixes, and issues. For professional support please fill out a contact form. As an open-source tool, the community’s feedback is vital to us. Our community has been our greatest asset and why we can keep creating and innovating.

So without further adieu, let’s dive into YOLOv8!

What Makes YOLOv8, YOLOv8?

We’re excited to claim YOLOv8 as the latest release in the YOLO family of architectures. It’s an honor to be a part of a community that has put in countless hours and effort to create models that are universally loved and used.

YOLOv8 is secured as the next in line in the YOLO family due to building on the successes of previous YOLO versions. We’ve included many new features and improvements, which significantly increase performance and flexibility.
One key aspect of YOLOv8 is its extensibility, as it is designed as a framework that is compatible with all previous versions of YOLO. This allows users to easily switch between different versions and compare their performance, making YOLOv8 a suitable choice for those who want to take advantage of the latest YOLO technology while still utilizing their existing YOLO models.

YOLOv8 Vision AI new capabilities

YOLOv5 vs. YOLOv8

We've taken note of the demand for accessible AI tools, and folded this into our R&D process. And with simplicity and usability at the forefront, it's no secret that YOLOv5 has experienced widespread adoption. However, YOLOv8 takes this even further.

What’s new?

  • YOLOv8 is State-of-the-Art. Although YOLOv5 was fast, easy, and accurate, it never was the best in the world at what it did. YOLOv8 changes this: it is faster and more accurate than all other models available
  • YOLOv8 is even simpler. With YOLOv5, it was necessary to clone the repo and set up your environment manually. While this is still an option for those who enjoy getting their hands dirty, to get started with YOLOv8, you can install the repo as a pip package.

  • YOLOv8 becomes a platform. Migrating away from a single architecture, YOLOv8 supports every single YOLO version, including those of our competitors.

  • YOLOv8 will have a paper. A point of contention with YOLOv5 was always the lack of scientific paper. With YOLOv8, expect a paper to be published in the coming weeks.

What’s the same?

  • Clearly-documented workflows. With YOLOv8, we’ve maintained the documented workflows that have proven valuable in YOLOv5. However, with YOLOv8 we’ve folded improvements into them to make them even simpler.

  • The creators. If you haven’t gotten it by now, no worries! Our team here at Ultralytics are the creators of both YOLOv5 and YOLOv8.
  • The integrations. YOLOv8 will also continue supporting our partners' tools.

What else can we expect?

The next two big releases with YOLOv8 that you can expect are:

  • The paper. We expect to publish the scientific paper shortly after YOLOv8 goes live. This time, we promise.

  • Performance tracking with Ultralytics HUB. We are in the works to provide a direct, tight integration between YOLOv8 and Ultralytics HUB, which will automatically allow users to visualize their model metrics and losses, preview predictions, and compare against other models, public or private. In Ultralytics HUB, YOLOv8 models can be exported to many formats, including ONNX, OpenVINO, TensorRT, TFLite, CoreML, and many more.

Be sure to check out the new YOLOv8 repo and give us a star!

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