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Add https://youtu.be/eHuzCNZeu0g to docs and integration updates (#9525)

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Muhammad Rizwan Munawar 2024-04-03 17:08:33 +05:00 • committed by GitHub
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docs/en/integrations/tf-graphdef.md
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@ -10,6 +10,10 @@ When you are deploying cutting-edge computer vision models, like YOLOv8, in diff
In this guide, we'll walk you step by step through how to export your [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics) models to the TF GraphDef model format. By converting your model, you can streamline deployment and use YOLOv8's computer vision capabilities in a broader range of applications and platforms.
<p align="center">
<img width="640" src="https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/2d793b51-19f2-49e0-bf4b-5208f2eb5993" alt="TensorFlow GraphDef">
</p>
## Why Should You Export to TF GraphDef?
TF GraphDef is a powerful component of the TensorFlow ecosystem that was developed by Google. It can be used to optimize and deploy models like YOLOv8. Exporting to TF GraphDef lets us move models from research to real-world applications. It allows models to run in environments without the full TensorFlow framework.