In the dialog that appears, choose TensorFlow and be sure the SavedModel button is selected, as shown below.
Then, click Download my model. After a minute or two, your browser will save a converted_savedmodel.zip file.
Running the model on the Pi
When you clicked the Download my model button in the last step, your browser should have saved a file called converted_savedmodel.zip. Now you need to place this on your Raspberry Pi.
You can transfer the model to the Raspberry Pi using scp:
$ scp <<PATH_TO_DOWNLOADS>>/converted_savedmodel.zip [email protected]:~
NOTE: You might need to adjust the first path in the command above to point to your Downloads folder.
Now, SSH to your Pi and run:
$ cd rpi-vision
$ sudo bash
# source .venv/bin/activate
# python3 tests/pitft_teachablemachine.py ../converted_savedmodel.zip
It will take some time to load the model into memory. During this time, you'll see the BrainCraft logo appear on the display. Afterwards, point your rpi camera and try it out!
Be sure to follow these steps to get a file called pitft_teachablemachine.py. This file is not in the project GitHub repo, it is made from the training and part of the process noted above.
If you get an error that a module like pygame or rpi_vision isn't found, please use pip or pip3 to load the module for Python use.
Page last edited July 23, 2025
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