Uploading the model to the Pi

In terminal, connect to your Pi using SSH and create a directory named model via the following commands:

cd ~
mkdir model
The IP address is on the screen of your BrainCraft Hat

Open an FTP connection and transfer the model.tflite and signature.json files exported from Lobe into the model directory on the Pi.

Run the Package Detector Code

Run the package detector code with the following commands:

cd ~
cd lobe-adafruit-kit
python3 lobe-package-detector.py

Next, go look at your Pi! The BrainCraft screen should now show you what the camera is seeing along with a prediction label.

Try putting a package (or an empty box) in the camera field-of-view and see if the Pi detects the package.

If the model does not recognize the package, add more training images to your model.

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

This page (Get Predictions on the Pi) was last updated on Apr 10, 2021.

Text editor powered by tinymce.