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