In this project I will show you how to train an image classification model with TensorFlow and deploy it on a Raspberry Pi Zero. The model can count how many fingers you show to the camera. You can use this as a base for further projects, for example to adjust volume of your speakers or lighting in a room based on inputs from 0 to 5.
In this post I am going to detail how to create a real time data pipeline for processing sensor data. First we will connect the sensor and create the code to read it. I will use the DHT22 temperature and humidity sensor on the Raspberry Pi Zero WH. Then we’ll setup the real time data flow with Python and RabbitMQ. Finally we will use Flask and D3.js to display the data in a live dashboard in a browser.
Configure the Kodi app
In this post we will learn how to develop a Kodi add-on in Python. You can run the add-on in OpenELEC or LibreELEC on the Orange Pi or Raspberry Pi, or as a matter of fact on any device that can run Kodi. The add-on will read data from various sources, such as an API for the current Bitcoin price, and show it on the main screen.