Machine Learning 101 with Lobe and BrainCraft

by Adi Azulay and

published March 30, 2021, last updated March 08, 2024

posted in Adafruit Products Sensors/ Camera Raspberry Pi Programming/ Python Machine Learning

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Beginner

Product guide

Get Predictions on the Pi

1. Connect your Pi to a power source and wait for it boot up.

You should see a solid red light and an intermittently flashing green light.

2. Open command prompt on a PC or terminal on Mac/Linux and connect to your Pi using SSH.

Type the following command but replace the bolded number below with IP address of your Pi:

ssh pi@192.168.0.22

Your Pi's IP address is on the screen of the BrainCraft. You can also use the hostname address, e.g. "raspberrypi.local" ([email protected])

3. Download the GitHub folder.

Run the following commands to download the sample code from GitHub:

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cd ~
git clone https://github.com/lobe/lobe-adafruit-kit.git

cd ~
git clone https://github.com/lobe/lobe-adafruit-kit.git

4. Create a new folder called `model` in the home directory.

Type the following commands:

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cd ~
mkdir model

cd ~
mkdir model

5. Open the FTP connection from the previous step.

6. Copy `saved_model.tflite` and `signature.json` from your exported Lobe model to the `model` directory on the Pi.

7. In terminal on the Pi, run the following script to install Lobe and all it's dependences:

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cd ~
wget https://raw.githubusercontent.com/lobe/lobe-python/master/scripts/lobe-rpi-install.sh
sudo bash lobe-rpi-install.sh

cd ~
wget https://raw.githubusercontent.com/lobe/lobe-python/master/scripts/lobe-rpi-install.sh
sudo bash lobe-rpi-install.sh

8. In terminal on the Pi, run the Python program `lobe-basic-prediction.py`

Type the following commands:

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cd ~
cd lobe-adafruit-kit
python3 lobe-basic-prediction.py

cd ~
cd lobe-adafruit-kit
python3 lobe-basic-prediction.py

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Machine Learning 101 with Lobe and BrainCraft

Get Predictions on the Pi

1. Connect your Pi to a power source and wait for it boot up.

2. Open command prompt on a PC or terminal on Mac/Linux and connect to your Pi using SSH.

3. Download the GitHub folder.

4. Create a new folder called `model` in the home directory.

5. Open the FTP connection from the previous step.

6. Copy `saved_model.tflite` and `signature.json` from your exported Lobe model to the `model` directory on the Pi.

7. In terminal on the Pi, run the following script to install Lobe and all it's dependences:

8. In terminal on the Pi, run the Python program `lobe-basic-prediction.py`

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Get Predictions on the Pi

1. Connect your Pi to a power source and wait for it boot up.

2. Open command prompt on a PC or terminal on Mac/Linux and connect to your Pi using SSH.

3. Download the GitHub folder.

4. Create a new folder called model in the home directory.

5. Open the FTP connection from the previous step.

6. Copy saved_model.tflite and signature.json from your exported Lobe model to the model directory on the Pi.

7. In terminal on the Pi, run the following script to install Lobe and all it's dependences:

8. In terminal on the Pi, run the Python program lobe-basic-prediction.py

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4. Create a new folder called `model` in the home directory.

6. Copy `saved_model.tflite` and `signature.json` from your exported Lobe model to the `model` directory on the Pi.

8. In terminal on the Pi, run the Python program `lobe-basic-prediction.py`