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YOLOv8-16bit/docs/hub/index.md

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true Ultralytics HUB: Train & deploy YOLO models from one spot! Use drag-and-drop interface with templates & pre-training models. Check quickstart, datasets, and more. Ultralytics HUB, YOLOv5, YOLOv8, object detection, instance segmentation, classification, drag-and-drop interface, pre-trained models, integrations, mobile app, Inference API, datasets, projects, models

Ultralytics HUB




👋 Hello from the Ultralytics Team! We've been working hard these last few months to launch Ultralytics HUB, a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀 models from one spot!

Introduction

HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to easily upload their data and train new models quickly. It offers a range of pre-trained models and templates to choose from, making it easy for users to get started with training their own models. Once a model is trained, it can be easily deployed and used for real-time object detection, instance segmentation and classification tasks.

We hope that the resources here will help you get the most out of HUB. Please browse the HUB Docs for details, raise an issue on GitHub for support, and join our Discord community for questions and discussions!

  • Quickstart. Start training and deploying YOLO models with HUB in seconds.
  • Datasets: Preparing and Uploading. Learn how to prepare and upload your datasets to HUB in YOLO format.
  • Projects: Creating and Managing. Group your models into projects for improved organization.
  • Models: Training and Exporting. Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
  • Integrations: Options. Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
  • Ultralytics HUB App. Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
    • iOS. Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
    • Android. Explore TFLite acceleration on mobile devices.
  • Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.