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 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 moreWhat is TFLite model maker?
It uses transfer learning to reduce the amount of training data required and shorten the training time. This guide walks you through creating a custom object detector and deploying it on Android.
Read moreCan you train a TFLite model?
This tutorial shows you how to construct a TensorFlow Lite model that can be incrementally trained and improved within an installed Android app. Note: The on-device training technique can be added to existing TensorFlow Lite implementations, provided the devices you are targeting support local file storage.
Read moreWhat is 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 run a TensorFlow model?
These are the steps we are going to do:
Read moreWhat is a Tflite file?
Tensorflow Lite Converter converts a Tensorflow model to Tensorflow Lite flat buffer file (. tflite). Tensorflow Lite flat buffer file is deployed to the client, which in our cases can be a mobile device running on iOS or Android or an embedded device.
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