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Add TF GraphDef Docs Integrations Page (#9203)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Abirami Vina 2024-03-22 22:44:02 +05:30 • committed by GitHub
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docs/en/integrations/index.md
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@ -63,6 +63,8 @@ Welcome to the Ultralytics Integrations page! This page provides an overview of
- [CoreML](coreml.md): CoreML, developed by [Apple](https://www.apple.com/), is a framework designed for efficiently integrating machine learning models into applications across iOS, macOS, watchOS, and tvOS, using Apple's hardware for effective and secure model deployment.
- [TF GraphDef](tf-graphdef.md): Developed by [Google](https://www.google.com), GraphDef is TensorFlow's format for representing computation graphs, enabling optimized execution of machine learning models across diverse hardware.
- [TFLite](tflite.md): Developed by [Google](https://www.google.com), TFLite is a lightweight framework for deploying machine learning models on mobile and edge devices, ensuring fast, efficient inference with minimal memory footprint.
- [TFLite Edge TPU](edge-tpu.md): Developed by [Google](https://www.google.com) for optimizing TensorFlow Lite models on Edge TPUs, this model format ensures high-speed, efficient edge computing.