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 moreHow do I run a TensorFlow model on Raspberry Pi?
These are the steps needed to set up TensorFlow Lite:
Read moreHow do I run a TensorFlow model on Raspberry Pi?
These are the steps needed to set up TensorFlow Lite:
Read moreWhat is TFLite_Detection_PostProcess?
TFLite_Detection_PostProcess is custom op which produces final 4 outputs – (classes, scores, bboxes and num_outputs)
Read more