Build a machine learning (ML) package detector that sends you a notification when a package is left at your door!

You can also use this tutorial to train a model to notify you for any kind of event. For example, lets you know when your dog is at the door, your favorite parking spot is open, or if there are birds at your bird feeder.

We'll use Lobe to train our model and then deploy it to a Raspberry Pi 4. We'll use the BrainCraft HAT to interface with the Pi to collect images and preview what the camera is seeing. Next, we'll setup an applet on If This Then That to send us an e-mail alert whenever a package is detected. Finally, we'll improve our model by collecting more training data in situations where the model gets confused.

This tutorial is part of a series which includes:

Background Knowledge

New to Lobe? At a minimum, we recommend following the introductory Tutorial 1 above. 

To be successful with this project, you'll need some experience with the following:

  1. Setting up and using the Raspberry Pi
  2. Some familiarity with using the terminal window
  3. Installing the Pi Camera

This guide was first published on Mar 30, 2021. It was last updated on 2021-03-30 15:53:33 -0400.

This page (Overview) was last updated on Sep 15, 2021.

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