The differences between TensorFlow Lite and TensorFlow Mobile are as follows: It is the next version of TensorFlow mobile . Generally, applications developed on TensorFlow Lite will have better performance and less binary file size than TensorFlow mobile.
Read moreHow do I import a TensorFlow Lite in python?
To fix it, edit this line of the file:
Read moreHow do I load a TensorFlow Lite model?
Running a TensorFlow Lite model involves a few simple steps:
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:
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