Kaggle integration

[dantetemplar]

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• [X] I have searched the HUB issues and found no similar feature requests.

Description

Add opportunity to work with datasets from Kaggle supporting different popular data formats (at least COCO).

Use case

No response

Additional

No response

[UltralyticsAssistant]

👋 Hello @dantetemplar, thank you for suggesting an integration with Kaggle for Ultralytics HUB 🚀!

Please check out our HUB Docs to learn more about our current features:

• Quickstart. Begin training and deploying YOLO models with HUB in no time.
• Datasets: Preparing and Uploading. Discover how to prepare and upload datasets to HUB in YOLO format, and keep an eye out for updates on additional formats!
• Projects: Creating and Managing. Organize your models seamlessly within projects.
• Models: Training and Exporting. Train YOLOv5 and YOLOv8 on your datasets and explore various export options.
• Integrations. Check out our integration options for deploying your models with different frameworks.
• Ultralytics HUB App. Discover our mobile app for iOS and Android, enabling you to deploy models on your device.
  • iOS. Utilize YOLO models with Apple's CoreML.
  • Android. Leverage TFLite for mobile acceleration.
• Inference API. Utilize the API for cloud-based model inference.

If this is a 🐛 Bug Report or there's a need for further assistance, kindly provide detailed steps for a minimum reproducible example.

This is an automated response to acknowledge your request. An Ultralytics engineer will review and assist you soon. Thanks for your input and patience! 🌟

[pderrenger]

@dantetemplar hello! 😊

Thank you for your suggestion regarding Kaggle integration with Ultralytics HUB. This is a fantastic idea, and supporting datasets from Kaggle, especially in popular formats like COCO, could indeed enhance the flexibility and usability of the platform.

While we don't currently have direct integration with Kaggle, you can still manually download datasets from Kaggle and upload them to Ultralytics HUB. Ensure your dataset is structured correctly, with the YAML file placed inside the root directory, and that the directory and ZIP file share the same name. This will allow you to seamlessly use your Kaggle datasets for model training on the HUB.

We appreciate your input and are always looking for ways to improve our platform. Feel free to share any more ideas or feedback you might have!