The pre-trained models we provide are trained to detect 90 classes of objects . For a full list of classes, see the labels file in the model metadata. You can use a technique known as transfer learning to re-train a model to recognize classes not in the original set.18 May 2021
Read moreHow do you use a TFLite model?
Running a TensorFlow Lite model involves a few simple steps:
Read moreHow do you evaluate 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 moreHow do I run TensorFlow on Raspberry Pi?
The TensorFlow team recommends cross-compiling a Python wheel (a type of binary Python package) for Raspberry Pi [1]. For example, you can build a TensorFlow wheel for a 32-bit or 64-bit ARM processor on a computer running an x86 CPU instruction set.
Read moreCan you use TensorFlow on Raspberry Pi?
You can execute TensorFlow on a Raspberry Pi 4 , but don’t expect miracles. It can run your models, if not too complex, but it will not be able to train new models. Nor can it perform the so-called transfer learning.12 Ara 2021
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 moreHow do I use TensorFlow Lite on Android?
Use Android Studio ML Model Binding
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