TensorFlow Mobile Deployment: Lite & JS Guide

There are typically two methods for deploying models to mobile devices in TensorFlow.

1. TensorFlow Lite is a lightweight solution for running machine learning models on mobile and embedded devices. It allows you to convert trained TensorFlow models into a format suitable for running on mobile devices, making the models more lightweight while maintaining accuracy. TensorFlow Lite supports both Android and iOS platforms.
2. If your mobile app is based on web technologies, you can use TensorFlow.js to run machine learning models in the browser. With TensorFlow.js, you can load and run TensorFlow models directly in JavaScript without relying on specific platforms or operating systems. You can load TensorFlow.js models directly in the browser of your mobile device and utilize technologies like WebGL for acceleration.

No matter which method you choose, you’ll need to first convert your TensorFlow model into a format suitable for running on a mobile device before integrating it into your mobile application. TensorFlow Lite and TensorFlow.js both offer tools and APIs to assist you in this process. You can choose the appropriate deployment method based on your specific needs and scenarios.