Once the network is trained, you can then deploy the neural network to your Raspberry Pi. Instead, you should first train your network on your laptop, desktop, or deep learning environment. With the Raspberry Pi there just isn’t enough RAM.Īnd in general it’s not the right hardware for heavy computational processes. You should not be training neural networks on the Raspberry Pi (unless you’re using the Pi to do the “Hello, World” equivalent of neural networks - but again, I would still argue that your laptop/desktop is a better fit). That said, you can deploy efficient, shallow neural networks to the Raspberry Pi and use them to classify input images.Īgain, I cannot stress this point enough: You’re much better off training the network on your laptop, desktop, or even GPU (if you have one available). You should never be training a neural network on the Raspberry Pi - it’s far too underpowered. The question really depends on what you mean by “do”. I have a question: Can I do deep learning on the Raspberry Pi? What are the steps?Īnd almost always, I have the same response: You’ve really made deep learning accessible and easy to understand. Hey Adrian, thanks for all the tutorials on deep learning. Most of the questions go something like this: I’ve received a number of emails from PyImageSearch readers who are interested in performing deep learning in their Raspberry Pi. Click here to download the source code to this post
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