A tiny framework for doing machine learning on Raspberry Pi.

Download the latest version of Raspbian and flash your micro SD card with Etcher

Add blank file called ssh into the root of the SD disk and a file called wpa_supplicant.conf containing the following (replace with your wifi details):

ctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev
update_config=1

network={
    ssid="YOUR_WIFI_NETWORK"
    psk="YOUR_WIFI_PASSWORD"
}

In terminal ssh into the pi:

sudo ssh [email protected]

Default password is 'raspberry'. To change password use the passwd command.

Update the pi:

sudo apt-get update && sudo apt-get upgrade

Install nodejs:

sudo apt-get install nodejs npm git-core

Optional: install nettalk for easy file sharing:

sudo apt-get install netatalk

Reboot:

sudo reboot

Install pre-requisites:

sudo apt install libatlas-base-dev libjasper-dev libqtgui4 libqt4-test libhdf5-dev

Make sure you enable your camera through sudo raspi-config. Reboot again afterwards.

Clone this library:

git clone https://github.com/ml4a/ml4pi

Install all the required python libraries:

cd ml4pi
pip3 install -r requirements.txt 

Try running the interactive trainer:

python3 train_webcam.py

• get picamera at faster fps
• train from a directory of images
• saving/loading models
• deployment script (load model, then continuously predict samples)

(not finished yet)

Example is using a dataset which can be obtained:

wget http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz
tar -xzf 101_ObjectCategories.tar.gz