Add TF.js Docs Integrations Page

[abirami-vina]

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Now you can take your Ultralytics YOLOv8 models to the web with TensorFlow.js (TF.js) support! 🚀

📊 Key Changes

• Added documentation on how to export Ultralytics YOLOv8 models to the TF.js format, enabling browser and Node.js deployments. 🌐
• Introduced a new TF.js guide under the integrations section to make your models shine on web platforms. 💡
• Highlighted the benefits of TF.js, including cross-platform support, multiple backend compatibilities, and offline capabilities. 🛠

🎯 Purpose & Impact

• Enhancing Deployability: By supporting TF.js, Ultralytics makes YOLOv8 models more versatile, allowing them to run directly in web browsers or Node.js environments. This opens up endless possibilities for interactive web and server applications. 🕸
• Improving User Experience: Running models locally in a browser reduces latency, enhances privacy, and even allows applications to operate offline. Ideal for creating responsive, fast, and secure web applications. 🔒
• Expanding Developer Toolkit: Provides developers with more options for deployment scenarios, including in-browser applications, Node.js applications, and even Chrome extensions, making it easier to integrate advanced machine learning models into various projects. 🛠

This update paves the way for innovative web-based machine learning applications, bringing the power of YOLOv8's object detection capabilities to a broader audience. 🌍

[glenn-jocher]

@abirami-vina nice work on this TF.js page!