Before we can train an ML model, we need to collect some images. For this model, we'll need two categories: images that have a package in them and images that don't.

To make our model more accurate under various weather conditions and other situations, it's useful to have lots of pictures in both categories at different times of day and in different lighting conditions.

Install your Pi with the Camera pointing towards a package drop-off spot.

I installed my Pi just inside the door frame, with the camera outside and pointing down.

Open a terminal window and connect to your Pi via SSH.

In terminal, run the lobe-capture.py program with the following commands:

Collect training images

Upload all the pictures to your computer using FTP, and put them in a folder called Package Detector.

Inside of that folder create two more folders called no package and package. Sort your images into those two folders.