Here's a cool project that uses a Raspberry Pi and Tensorflow to classify objects for recycling. A Raspberry Pi camera is used to capture an image of the item on the tray. Based on the output of the model, the robot will choose one of three bins and use a couple stepper motors to drop it in. It's surprisingly fast for a single board computer!
There is also an "active training" mode which sends images up to a server for future training data. It looks like there is some sort of UI for manual data annotation. Since training takes quite a bit of computing power, it's no surprise that he chose to do it on a powerful machine in the cloud.
I was curious how he was able to load Tensorflow on the pi, so I did some digging and found a couple cool projects on Github.
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