Use TensorFlow AI on Raspberry Pi

Use TensorFlow AI on Raspberry Pi

Google TensorFlow is a powerful open-source software framework used to power AI projects around the globe. TensorFlow is used for machine learning and the creation of neural networks. These make it possible for computers to perform increasingly complex tasks, such as image recognition and text analysis. When it comes to AI, most people think of powerful supercomputers crunching billions of numbers in giant databanks. But there are two parts to machine learning. There is a train/test part, where you use a lot of data to build a model. And there’s deployment, where you take a model and use it as part of a project. And that’s where the Raspberry Pi fits in. Although Raspberry Pi isn’t officially supported by Google, there are example models included for the Raspberry Pi and it can be fun (if a bit hacky) to get TensorFlow up and running on a Pi. And there are lots of interesting community projects around that put TensorFlow to good use. Using TensorFlow can give you a good understanding of how AI works, and how to put AI to practical use in your projects. STEP-01 Install TensorFlow with pip TensorFlow can be incredibly easy to install on a Raspberry Pi, or something of a nightmare. It depends on the current build and which version of Raspbian OS you are running. Installation is often troublesome, but we’ve had recent success with building it directly using pip. Open a Terminal window and enter:sudo apt-get update && sudo apt-get upgrade sudo apt-get install python3-pip python3-dev pip3 install tensorflowSTEP-02 Build from wheel If pip doesn’t work, you can try to build TensorFlow using the wheel file. In a Terminal, enter:sudo pip3 install –upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp34-cp34m-linux_x86_64.whlAlternatively, you can use a nightly wheel built for Raspberry Pi, which is available from magpi.cc/xKLBzu. Download the wheel file and run it, like this:sudo pip3 install –upgrade tensorflow-1.9.0rc0-cp34-none-linux_armv7l.whlTake a look at TensorFlow’s Install Sources page or Common Installation Problems page. STEP-03 Build from source If pip fails, you could always build TensorFlow from source; Sam Abrahams has written detailed instructions on doing so (magpi.cc/oCYtme). You will need a spare USB stick (1GB or higher) to extend the amount of swap space on your Raspberry Pi and be sure to follow the instructions carefully. It takes around six hours to build, but we have gone through the steps and they do work. STEP-04 Hello TensorFlow Hopefully, you now have TensorFlow up…
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