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41 lines
2.8 KiB
41 lines
2.8 KiB
---
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comments: true
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---
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# Ultralytics HUB
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<a href="https://bit.ly/ultralytics_hub" target="_blank">
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<img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/ultralytics-hub.png"></a>
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<br>
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<br>
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<div align="center">
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<a href="https://github.com/ultralytics/hub/actions/workflows/ci.yaml">
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<img src="https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg" alt="CI CPU"></a>
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<a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
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</div>
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<br>
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👋 Hello from the [Ultralytics](https://ultralytics.com/) Team! We've been working hard these last few months to
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launch [Ultralytics HUB](https://bit.ly/ultralytics_hub), a new web tool for training and deploying all your YOLOv5 and YOLOv8 🚀
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models from one spot!
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## Introduction
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HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to
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easily upload their data and train new models quickly. It offers a range of pre-trained models and
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templates to choose from, making it easy for users to get started with training their own models. Once a model is
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trained, it can be easily deployed and used for real-time object detection, instance segmentation and classification tasks.
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We hope that the resources here will help you get the most out of HUB. Please browse the HUB <a href="https://docs.ultralytics.com/hub">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/hub/issues/new/choose">GitHub</a> for support, and join our <a href="https://discord.gg/n6cFeSPZdD">Discord</a> community for questions and discussions!
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- [**Quickstart**](./quickstart.md). Start training and deploying YOLO models with HUB in seconds.
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- [**Datasets: Preparing and Uploading**](./datasets.md). Learn how to prepare and upload your datasets to HUB in YOLO format.
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- [**Projects: Creating and Managing**](./projects.md). Group your models into projects for improved organization.
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- [**Models: Training and Exporting**](./models.md). Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
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- [**Integrations: Options**](./integrations.md). Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
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- [**Ultralytics HUB App**](./app/index.md). Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
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* [**iOS**](./app/ios.md). Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
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* [**Android**](./app/android.md). Explore TFLite acceleration on mobile devices.
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- [**Inference API**](./inference_api.md). Understand how to use the Inference API for running your trained models in the cloud to generate predictions. |