<p>It's completely possible.</p>
<h3>Hardware</h3>
<p>Following main hardware specs need to be considered when you're deploying your model on edge devices like raspberry, banana pi, ...</p>
<ul>
<li><strong>Memory</strong></li>
<li><strong>Processing Speed</strong></li>
</ul>
<p><strong>Memory</strong> - Random Access Memory(RAM). RAM allows you to deploy bigger models on your edge device and also in case of processing, the CPU is also most important one.
Raspberry Pi versions RAMs:</p>
<ol>
<li>The Raspberry Pi 2 has <strong>1 GiB</strong> of RAM.</li>
<li>The Raspberry Pi 3 has <strong>1 GiB</strong> of RAM in the <strong>B</strong> and <strong>B+</strong> models, and <strong>512 MiB</strong> of RAM in the A+ model. The Raspberry Pi Zero and Zero W have <strong>512 MiB</strong> of RAM.</li>
<li>The Raspberry Pi 4 is available with <strong>2, 4 or 8 GiB of RAM</strong>. A 1 GiB model was originally available at launch in June 2019 but was discontinued in March 2020, and the <strong>8 GiB</strong> model was introduced in May 2020.</li>
</ol>
<h3>Model Optimization</h3>
<p>If you have one of the version of a Raspberry Pi so then you can't change it's capability however you can optimize your model by updating your neural network. So you need think about using efficient networks, such as <a href="https://arxiv.org/abs/1905.11946" rel="nofollow noreferrer">EfficientNet</a>, <a href="https://arxiv.org/abs/1704.04861" rel="nofollow noreferrer">MobileNet</a>, <a href="https://arxiv.org/abs/1602.07360" rel="nofollow noreferrer">SqueezeNet</a>, <a href="https://arxiv.org/abs/1911.11907" rel="nofollow noreferrer">GhostNet</a>.
For object detection purposes, I have used <strong>Raspberry Pi 2 B</strong> model with tiny Yolo with quite low FPS (frame per second).</p>
<p>I hope, from now you can consider according to your task which Raspberry Pi device is suitable for you.</p>
Could I use raspberry pi to use a pretrained CNN model for prediction?
<p>Firstly, I'm going to train a CNN model on my computer (image classification program), then I'm gonna save it to be used in raspberry pi</p>
<p>After that, I'm gonna give the raspberry pi some images, I want it to predict the images using the trained model</p>
<p>Finally, according to the result (the prediction) , i want it to take an action.</p>
<p>So, is it possible to do that? if yes, what specifications should i keep in mind when i buy the raspberry pi ?</p>