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Add https://youtu.be/qE-dfbB5Sis to docs (#18207)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Muhammad Rizwan Munawar 2024-12-12 22:06:38 +05:00 • committed by GitHub
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2
docs/en/hub/datasets.md
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@ -17,7 +17,7 @@ Once uploaded, datasets can be immediately utilized for model training. This int
allowfullscreen> allowfullscreen>
</iframe> </iframe>
<br> <br>
<strong>Watch:</strong> Watch: Upload Datasets to Ultralytics HUB | Complete Walkthrough of Dataset Upload Feature <strong>Watch:</strong> Upload Datasets to Ultralytics HUB | Complete Walkthrough of Dataset Upload Feature
</p> </p>
## Upload Dataset ## Upload Dataset

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docs/en/hub/index.md
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@ -52,13 +52,13 @@ We hope that the resources here will help you get the most out of HUB. Please br
[Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, [object detection](https://www.ultralytics.com/glossary/object-detection), and [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks. [Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, [object detection](https://www.ultralytics.com/glossary/object-detection), and [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks.
<p align="center"> <p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6" <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/qE-dfbB5Sis"
title="YouTube video player" frameborder="0" title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen> allowfullscreen>
</iframe> </iframe>
<br> <br>
<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB <strong>Watch:</strong> How to train Ultralytics YOLO11 on Custom Dataset using Ultralytics HUB | HUB Datasets 🚀
</p> </p>
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.com/invite/ultralytics">Discord</a> community for questions and discussions! 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.com/invite/ultralytics">Discord</a> community for questions and discussions!

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docs/en/hub/quickstart.md
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@ -9,13 +9,13 @@ keywords: Ultralytics HUB, Quickstart, YOLO models, dataset upload, project mana
[Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, [object detection](https://www.ultralytics.com/glossary/object-detection), and [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks. [Ultralytics HUB](https://www.ultralytics.com/hub) is designed to be user-friendly and intuitive, allowing users to quickly upload their datasets and train new YOLO models. It also offers a range of pre-trained models to choose from, making it extremely easy for users to get started. Once a model is trained, it can be effortlessly previewed in the [Ultralytics HUB App](app/index.md) before being deployed for real-time classification, [object detection](https://www.ultralytics.com/glossary/object-detection), and [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks.
<p align="center"> <p align="center">
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/lveF9iCMIzc?si=_Q4WB5kMB5qNe7q6" <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/qE-dfbB5Sis"
title="YouTube video player" frameborder="0" title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen> allowfullscreen>
</iframe> </iframe>
<br> <br>
<strong>Watch:</strong> Train Your Custom YOLO Models In A Few Clicks with Ultralytics HUB <strong>Watch:</strong> How to train Ultralytics YOLO11 on Custom Dataset using Ultralytics HUB | HUB Datasets 🚀
</p> </p>
## Get Started ## Get Started

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docs/mkdocs_github_authors.yaml
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@ -84,7 +84,6 @@
username: Skillnoob username: Skillnoob
79740115+0xSynapse@users.noreply.github.com: 79740115+0xSynapse@users.noreply.github.com:
avatar: https://avatars.githubusercontent.com/u/79740115?v=4 avatar: https://avatars.githubusercontent.com/u/79740115?v=4
# Note original username deleted: 0xSynapse
username: github username: github
8401806+wangzhaode@users.noreply.github.com: 8401806+wangzhaode@users.noreply.github.com:
avatar: https://avatars.githubusercontent.com/u/8401806?v=4 avatar: https://avatars.githubusercontent.com/u/8401806?v=4