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Ultralytics YOLOv8 Turns One! 🎉 A Year of Breakthroughs and Innovations   ➜
Ultralytics YOLOv8 Docs
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ultralytics/ultralytics
 * v8.1.0
 * 18.4k
 * 3.7k

 * Home
 * Quickstart
 * Modes
 * Tasks
 * Models
 * Datasets
 * NEW 🚀 Explorer
 * Guides
 * Integrations
 * HUB
 * Reference
 * Help

Ultralytics YOLOv8 Docs
ultralytics/ultralytics
 * v8.1.0
 * 18.4k
 * 3.7k

 * Home
   Home
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 * Models
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    * YOLOv3
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    * YOLOv6
    * YOLOv7
    * YOLOv8
    * SAM (Segment Anything Model)
    * MobileSAM (Mobile Segment Anything Model)
    * FastSAM (Fast Segment Anything Model)
    * YOLO-NAS (Neural Architecture Search)
    * RT-DETR (Realtime Detection Transformer)

 * Datasets
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    * NEW 🚀 Explorer
      NEW 🚀 Explorer
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 * NEW 🚀 Explorer
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 * Guides
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       * Security Alarm System
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    * Minimum Reproducible Example (MRE) Guide
    * Code of Conduct
    * Environmental, Health and Safety (EHS) Policy
    * Security Policy
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Table of contents
 * Where to Start
 * YOLO: A Brief History
 * YOLO Licenses: How is Ultralytics YOLO licensed?


HOME






Introducing Ultralytics YOLOv8, the latest version of TEST NEW WORDS ADDED HERE,
test the latest version i'm writing a whole new paragraph here, the acclaimed
real-time object detection and image segmentation model. YOLOv8 is built on
cutting-edge advancements in deep learning and computer vision, offering
unparalleled performance in terms of speed and accuracy. Its streamlined design
makes it suitable for various applications and easily adaptable to different
hardware platforms, from edge devices to cloud APIs.

Explore the YOLOv8 Docs, a comprehensive resource designed to help you
understand and utilize its features and capabilities. Whether you are a seasoned
machine learning practitioner or new to the field, this hub aims to maximize
YOLOv8's potential in your projects


WHERE TO START

 * Install ultralytics with pip and get up and running in minutes   Get Started
 * Predict new images and videos with YOLOv8   Predict on Images
 * Train a new YOLOv8 model on your own custom dataset   Train a Model
 * Tasks YOLOv8 tasks like segment, classify, pose and track   Explore Tasks
 * NEW 🚀 Explore datasets with advanced semantic and SQL search   Explore a
   Dataset



Watch: How to Train a YOLOv8 model on Your Custom Dataset in Google Colab.


YOLO: A BRIEF HISTORY

YOLO (You Only Look Once), a popular object detection and image segmentation
model, was developed by Joseph Redmon and Ali Farhadi at the University of
Washington. Launched in 2015, YOLO quickly gained popularity for its high speed
and accuracy.

 * YOLOv2, released in 2016, improved the original model by incorporating batch
   normalization, anchor boxes, and dimension clusters.
 * YOLOv3, launched in 2018, further enhanced the model's performance using a
   more efficient backbone network, multiple anchors and spatial pyramid
   pooling.
 * YOLOv4 was released in 2020, introducing innovations like Mosaic data
   augmentation, a new anchor-free detection head, and a new loss function.
 * YOLOv5 further improved the model's performance and added new features such
   as hyperparameter optimization, integrated experiment tracking and automatic
   export to popular export formats.
 * YOLOv6 was open-sourced by Meituan in 2022 and is in use in many of the
   company's autonomous delivery robots.
 * YOLOv7 added additional tasks such as pose estimation on the COCO keypoints
   dataset.
 * YOLOv8 is the latest version of YOLO by Ultralytics. As a cutting-edge,
   state-of-the-art (SOTA) model, YOLOv8 builds on the success of previous
   versions, introducing new features and improvements for enhanced performance,
   flexibility, and efficiency. YOLOv8 supports a full range of vision AI tasks,
   including detection, segmentation, pose estimation, tracking, and
   classification. This versatility allows users to leverage YOLOv8's
   capabilities across diverse applications and domains.


YOLO LICENSES: HOW IS ULTRALYTICS YOLO LICENSED?

Ultralytics offers two licensing options to accommodate diverse use cases:

 * AGPL-3.0 License: This OSI-approved open-source license is ideal for students
   and enthusiasts, promoting open collaboration and knowledge sharing. See the
   LICENSE file for more details.
 * Enterprise License: Designed for commercial use, this license permits
   seamless integration of Ultralytics software and AI models into commercial
   goods and services, bypassing the open-source requirements of AGPL-3.0. If
   your scenario involves embedding our solutions into a commercial offering,
   reach out through Ultralytics Licensing.

Our licensing strategy is designed to ensure that any improvements to our
open-source projects are returned to the community. We hold the principles of
open source close to our hearts ❤️, and our mission is to guarantee that our
contributions can be utilized and expanded upon in ways that are beneficial to
all.




Created 2023-11-12, Updated 2024-01-10
Authors: AyushExel (3), glenn.jocher@ultralytics.com (3)
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