TensorFlow Lite is a lightweight version of TensorFlow that can be used on mobile and embedded devices. This guide shows you how to install TensorFlow Lite on a Raspberry Pi.
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TensorFlow Lite is TensorFlow’s lightweight solution for running machine learning models on mobile and embedded devices. It enables on-device machine learning inference with low latency and a small binary size.
This guide shows you how to install and run TensorFlow Lite on Raspberry Pi devices. You’ll learn how to:
– Install TensorFlow Lite on Raspberry Pi.
– Run the example TensorFlow Lite classification model on an image, using the Python TensorFlow Lite Interpreter.
– Run the example TensorFlow Lite classification model on live video, using the Java TensorFlow Lite Interpreter.
What is TensorFlow Lite?
TensorFlow Lite is a light-weight version of TensorFlow that can be used on mobile devices such as phones and embedded devices such as the Raspberry Pi. It is designed to run TensorFlow models on small devices with low power consumption.
You can install TensorFlow Lite on the Raspberry Pi using a pre-built binary or by building it from source.
The simplest way to install TensorFlow Lite on the Raspberry Pi is to use a pre-built binary. You can download the latest binary from the TensorFlow Lite website.
To install the binary, simply unzip it and copy the contents to your home directory. For example:
tar -xzvf tensorflow-lite-1.13.1+pi0-cp34-none-linux_armv6l.whl
sudo cp -r tensorflow-1.13.1+pi0-cp34-none-linux_armv6l /usr/local/lib/python3.4/site-packages/tensorflow
Building from source
Alternatively, you can build TensorFlow Lite from source on the Raspberry Pi 3 Model B+. This process will take several hours, but will allow you to use the latest features and bug fixes.
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Why Use TensorFlow Lite?
TensorFlow Lite is an open source deep learning framework for on-device inference. It enables low-latency inference of on-device machine learning models. TensorFlow Lite supports a wide variety of devices, including the Raspberry Pi, and can run on either the CPU or the GPU.
There are many reasons to use TensorFlow Lite on the Raspberry Pi. The first is that it is very easy to use. You don’t need any special hardware or software to get started. All you need is a Raspberry Pi and a bit of time.
Another reason to use TensorFlow Lite is that it is very efficient. It can run on the CPU or the GPU, so you can choose which one is best for your needs. And, since it is open source, there are no licensing fees.
Finally, TensorFlow Lite is widely supported. There are many different types of devices that it can run on, including the Raspberry Pi. So, regardless of which type of device you have, you should be able to find a way to use TensorFlow Lite.
TensorFlow Lite on Raspberry Pi
TensorFlow Lite is an open source deep learning framework for on-device inference. It’s provided as a Python library that you can download and install using pip. You can then use the TensorFlow Lite Converter to convert your models to the TensorFlow Lite format.
This guide shows you how to install TensorFlow Lite on Raspberry Pi so you can run inference on local models.
To install TensorFlow Lite on Raspberry Pi, you need:
– A Raspberry Pi 3 Model B or B+ (this is the latest model as of February 2019)
– A microSD card with Raspbian Stretch Lite installed
Install TensorFlow Lite
Raspberry Pi is a tiny, affordable computer that you can use to learn programming and electronics. In this tutorial, you will learn how to install TensorFlow Lite on Raspberry Pi and get started with its Python API.
Before you begin, make sure that your Raspberry Pi is running the latest version of Raspbian or Debian. You can check this by running the following command:
sudo apt-get update && sudo apt-get upgrade
Once your system is up to date, you can install TensorFlow Lite using the pip package manager:
sudo pip install tensorflow==2.0.0b1
Now that TensorFlow Lite is installed, you can test it out by running the following Python code:
import tensorflow as tf
TensorFlow Lite on Raspberry Pi
TensorFlow Lite is an open source project to help you run TensorFlow models on mobile, embedded devices. You can use TensorFlow Lite on the Raspberry Pi if you want to run machine learning models on the device. This guide show you how to install TensorFlow Lite on a Raspberry Pi and run a simple example.
In this guide, we’ve shown you how to install TensorFlow Lite on your Raspberry Pi. You can now use TensorFlow Lite to run machine learning models on your Raspberry Pi.
– Official TensorFlow Lite installation guide: https://www.tensorflow.org/lite/guide/python
Keyword: How to Install TensorFlow Lite on Raspberry Pi