As we have covered previously, the Raspberry Pi is an extremely versatile single-board computer (SBC). The Raspberry Pi 4 is powerful enough to be used in ways that previous Raspberry Pi units cannot too, such as resource-intensive machine learning.
To that end, a project has on Adafruit shows how to deploy a Raspberry Pi 4 for AI object recognition. The 4 GB model is recommended because of its added performance headroom, for reference.
In addition to a Raspberry Pi 4, you will need a Raspberry Pi Camera Board v2, a display and the corresponding cables to connect all the components. The project recommends using an active cooler or a heatsink, too.
The project uses TensorFlow 2.0 and TensorFlow Lite, along with Raspbian Lite for an OS. Melissa LeBlanc-Williams, the project creator, has published a detailed walkthrough if you are interested in recreating the project. The results seem encouraging too, with the Raspberry Pi able to tell you what it computes that it is detecting, which it also displays onscreen. The total project should cost less than US$150, including the price of the Raspberry Pi 4.
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