This is the first in a multiple part series on adding some object detection to my Raspberry Pi.
I am going to recreate a really cool object detection project I found by Leigh Johnson (also a fellow ML GDE). Her project is called Portable Computer Vision: TensorFlow 2.0 on a Raspberry Pi. Now, she went WAY above and beyond what I am planning to do but we will see how it all works out.
I am going to use a version 3 and a camera that I had from a few years ago. I used it to create a baby monitor when my youngest was a baby. I created a python script that would take an image every 60 seconds and post it to a network drive. This drive would then feed an internal web site I created.
I am going to skip the process of training my own model and use an existing model (MobileNetV2).
I will take the existing model and use “transfer learning” and retrain with a custom classifier. I think I might even get frisky and have it do something special when it sees me!
As is standard practice with me, I will be using TensorFlow and Keras with the pretrained model. I will then convert the model to TensorFlow Lite.
In my next post I will work through getting the Raspberry Pi set up.