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 does a TFLite file contain?
1 Answer. TFLite flatbuffer files contain the model structure as well. For example, there are a subgraph concept in TFLite, which corresponds to the function concept in the programming language and the operator nodes also represent a graph node, which takes inputs and generates outputs.
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 moreHow do you train a Tflite model?
From a high level, in order to train our custom object detection model, we take the following steps in the Colab Notebook to Train TensorFlow Lite Model: Install TensorFlow object detection library and dependencies . Import dataset from Roboflow in TFRecord format . Write custom model configuration .
Read moreHow do I run a TensorFlow model on Raspberry Pi?
These are the steps needed to set up TensorFlow Lite:
Read moreHow do you make a Tflite?
Detailed Process
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