TF Lite Interpreter (Part 2)

We can define, compile, and train a DL model using the TF framework. To deploy the model to mobile devices, we use the TF Lite converter to convert this model to the FlatBuffers format. TF Lite provides us with an interpreter that can execute TF Lite models on various platforms and mobile devices to make inferences. Let’s apply the TF Lite interpreter to perform image classification using a trained TF Lite model.

Image classification using TF Lite

The code below demonstrates how to use the TF Lite interpreter to classify test images. It uses the TF Lite Interpreter, allocates input/output tensors, checks their details, and uses the invoke method to classify images. It also displays the classification result.