institut-galilee / 2022-ml-iot-lab-2

This repo contains activities that will be useful for the machine learning part of the final project, including, activity recognition and machine vision. These activities will allow you to build ML models and adapt them to constrained devices like smartphones.

ML-IoT labs

Part one

• Setting-up the development environment and discovering the SHL dataset

Part Two

• Building our first activity recognition models

Part Three

• https://www.tensorflow.org/lite/guide/android
• An example application for TensorFlow Lite on Android that uses Image classification to continuously classify whatever it sees from the device's back camera. Inference is performed using the TensorFlow Lite Java API. The demo app classifies frames in real-time, displaying the top most probable classifications.