You can retrain the model using frozen graphs and TFLite models . If you get new training data and want to update the model in your app, try hosting it using Firebase MLKit.
Read moreHow do you verify a TFLite model?
You may use TensorFlow Lite Python interpreter to test your tflite model. It allows you to feed input data in python shell and read the output directly like you are just using a normal tensorflow model.
Read moreWhat models does TFLite support?
TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile devices. It works cross-Platform and is supported on Java, C++ (WIP), and Swift (WIP) .
Read moreHow do I create a TensorFlow model?
Create your model
Read moreWhat is a TFLite model?
TensorFlow Lite is Google’s machine learning framework to deploy machine learning models on multiple devices and surfaces such as mobile (iOS and Android), desktops and other edge devices.
Read moreHow do I use TensorFlow Lite on Android?
Use Android Studio ML Model Binding
Read moreWhat is TensorFlow Lite in Android?
TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices . It lets you run machine-learned models on mobile devices with low latency, so you can take advantage of them to do classification, regression or anything else you might want without necessarily incurring a round trip to a server.
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