That being said, your TFLite interpreter can run CPU models too (all we did was add the experimental delegate to handle that edgetpu-custom-op). To run the CPU version, simply pass the CPU version of the model (before it was compiled).
Read moreHow do I make a model of object detection?
In order to build our object detection system in a more structured way, we can follow the below steps:
Read moreHow do I make a custom TensorFlow Lite model?
Detailed Process
Read moreHow do you train a model in TensorFlow Lite?
This is when TensorFlow Lite comes in.
Read moreWhat can TensorFlow Lite detect?
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.
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