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Visual Raspberry Pi with Node-Red and TensorFlow

If you prefer to draw boxes instead of writing code, you may have tried IBM’s Node-RED to create logic with drag-and-drop flows. A recent [TensorFlow] video shows an interview between [Jason Mayes] and [Paul Van Eck] about using TensorFlow.js with Node-RED to create machine learning applications for Raspberry Pi visually. You can see the video, below.

The video doesn’t go into much detail since it is only ten minutes long. But it does show how easy it is to do things like identify images using an existing TensorFlow model. There is a more detailed tutorial available, as well as a corresponding video, which you can see below.

As a concrete example, [Paul] uses a simple sensor to identify his cat and then rings a doorbell to frighten the cat off the table. In a more topical example, a system sprays down anyone not wearing a face mask.

Perhaps a more practical example shows a garage door opener that identifies a car by its license plate number. We aren’t sure if it would open for a piece of posterboard with the license plate number written on it, or a picture of the plate.

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