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Title[redir]:
Home - Ultralytics YOLO Docs
Description:
Discover Ultralytics YOLO - the latest in real-time object detection and image segmentation. Learn its features and maximize its potential in your projects.

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🌟 Strong Traffic: 100k - 200k visitors per month

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Keywords {🔍}

yolo, ultralytics, object, model, detection, models, train, tracking, license, tasks, yolov, dataset, licensing, realtime, performance, custom, vision, applications, agpl, introducing, quickstart, pose, start, installation, latest, segmentation, explore, commercial, training, home, track, started, options, computer, accuracy, designed, features, capabilities, pip, running, open, enhanced, improvements, opensource, task, 한국어, 日本語, русский, deutsch, français,

Topics {✒️}

tiếng việt ultralytics docs hub aims osi-approved open-source license solutions 한국어 日本語 русский deutsch français español português türkçe pre-trained yolo model art yolo11 models vision ai tasks real-time object detection real-time object tracking customizable multi-object tracking quickstart page popular export formats anchor-free detection head yolo track command speed-accuracy trade-offs track mode documentation ultralytics yolo licensed ultralytics python package multiple tasks real-time scenarios ai models efficient backbone network object detection task computer vision research detect segment classify obb improve object detection popular object detection including object detection introducing innovations automatic export allowing seamless integration object detection faq yolo gained popularity real-world applications ultralytics yolo cutting-edge advancements streamlined design makes spatial pyramid pooling

Questions {❓}

How can I get started with YOLO installation and setup?
How can I train a custom YOLO model on my dataset?
How can Ultralytics YOLO be used for real-time object tracking?
What are the licensing options available for Ultralytics YOLO?
What is Ultralytics YOLO and how does it improve object detection?
YOLO Licenses: How is Ultralytics YOLO licensed?

Schema {🗺️}

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      headline:Home
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      datePublished:2023-11-12 02:49:37 +0100
      dateModified:2025-06-22 19:21:22 +0100
      author:
            type:Organization
            name:Ultralytics
            url:https://ultralytics.com/
      abstract:Discover Ultralytics YOLO - the latest in real-time object detection and image segmentation. Learn its features and maximize its potential in your projects.
      mainEntity:
            type:Question
            name:What is Ultralytics YOLO and how does it improve object detection?
            acceptedAnswer:
               type:Answer
               text:Ultralytics YOLO is the latest advancement in the acclaimed YOLO (You Only Look Once) series for real-time object detection and image segmentation. It builds on previous versions by introducing new features and improvements for enhanced performance, flexibility, and efficiency. YOLO supports various vision AI tasks such as detection, segmentation, pose estimation, tracking, and classification. Its state-of-the-art architecture ensures superior speed and accuracy, making it suitable for diverse applications, including edge devices and cloud APIs.
            type:Question
            name:How can I get started with YOLO installation and setup?
            acceptedAnswer:
               type:Answer
               text:Getting started with YOLO is quick and straightforward. You can install the Ultralytics package using pip and get up and running in minutes. Here's a basic installation command: For a comprehensive step-by-step guide, visit our Quickstart page. This resource will help you with installation instructions, initial setup, and running your first model.
            type:Question
            name:How can I train a custom YOLO model on my dataset?
            acceptedAnswer:
               type:Answer
               text:Training a custom YOLO model on your dataset involves a few detailed steps: Here's example code for the Object Detection Task: For a detailed walkthrough, check out our Train a Model guide, which includes examples and tips for optimizing your training process.
            type:Question
            name:What are the licensing options available for Ultralytics YOLO?
            acceptedAnswer:
               type:Answer
               text:Ultralytics offers two licensing options for YOLO: For more details, visit our Licensing page.
            type:Question
            name:How can Ultralytics YOLO be used for real-time object tracking?
            acceptedAnswer:
               type:Answer
               text:Ultralytics YOLO supports efficient and customizable multi-object tracking. To utilize tracking capabilities, you can use the yolo track command, as shown below: For a detailed guide on setting up and running object tracking, check our Track Mode documentation, which explains the configuration and practical applications in real-time scenarios.
Organization:
      name:Ultralytics
      url:https://ultralytics.com/
Question:
      name:What is Ultralytics YOLO and how does it improve object detection?
      acceptedAnswer:
         type:Answer
         text:Ultralytics YOLO is the latest advancement in the acclaimed YOLO (You Only Look Once) series for real-time object detection and image segmentation. It builds on previous versions by introducing new features and improvements for enhanced performance, flexibility, and efficiency. YOLO supports various vision AI tasks such as detection, segmentation, pose estimation, tracking, and classification. Its state-of-the-art architecture ensures superior speed and accuracy, making it suitable for diverse applications, including edge devices and cloud APIs.
      name:How can I get started with YOLO installation and setup?
      acceptedAnswer:
         type:Answer
         text:Getting started with YOLO is quick and straightforward. You can install the Ultralytics package using pip and get up and running in minutes. Here's a basic installation command: For a comprehensive step-by-step guide, visit our Quickstart page. This resource will help you with installation instructions, initial setup, and running your first model.
      name:How can I train a custom YOLO model on my dataset?
      acceptedAnswer:
         type:Answer
         text:Training a custom YOLO model on your dataset involves a few detailed steps: Here's example code for the Object Detection Task: For a detailed walkthrough, check out our Train a Model guide, which includes examples and tips for optimizing your training process.
      name:What are the licensing options available for Ultralytics YOLO?
      acceptedAnswer:
         type:Answer
         text:Ultralytics offers two licensing options for YOLO: For more details, visit our Licensing page.
      name:How can Ultralytics YOLO be used for real-time object tracking?
      acceptedAnswer:
         type:Answer
         text:Ultralytics YOLO supports efficient and customizable multi-object tracking. To utilize tracking capabilities, you can use the yolo track command, as shown below: For a detailed guide on setting up and running object tracking, check our Track Mode documentation, which explains the configuration and practical applications in real-time scenarios.
Answer:
      text:Ultralytics YOLO is the latest advancement in the acclaimed YOLO (You Only Look Once) series for real-time object detection and image segmentation. It builds on previous versions by introducing new features and improvements for enhanced performance, flexibility, and efficiency. YOLO supports various vision AI tasks such as detection, segmentation, pose estimation, tracking, and classification. Its state-of-the-art architecture ensures superior speed and accuracy, making it suitable for diverse applications, including edge devices and cloud APIs.
      text:Getting started with YOLO is quick and straightforward. You can install the Ultralytics package using pip and get up and running in minutes. Here's a basic installation command: For a comprehensive step-by-step guide, visit our Quickstart page. This resource will help you with installation instructions, initial setup, and running your first model.
      text:Training a custom YOLO model on your dataset involves a few detailed steps: Here's example code for the Object Detection Task: For a detailed walkthrough, check out our Train a Model guide, which includes examples and tips for optimizing your training process.
      text:Ultralytics offers two licensing options for YOLO: For more details, visit our Licensing page.
      text:Ultralytics YOLO supports efficient and customizable multi-object tracking. To utilize tracking capabilities, you can use the yolo track command, as shown below: For a detailed guide on setting up and running object tracking, check our Track Mode documentation, which explains the configuration and practical applications in real-time scenarios.

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