A little while back, I started building a raspberry pi camera security system, using openCV’s deep neural network module for object detection. (Thanks pyimagesearch for the great introductory resources!)
Unfortunately the pi was only able to handle around 0.8 frames of object detection per second using that approach. While my frame rate requirements are modest, that wasn’t going to cut it. Shortly after that I discovered the Coral USB accelerator, a low power, edge device that can do blazing fast tensor flow lite model inference, and its api is really simple to use!
Setup is extremely straightforward.
cd ~/ wget…
I recently discovered Snips, an amazing privacy-preserving voice assistant that runs entirely on device!! It’s also simple to set up and use.
Let’s install Snips on a raspberry pi & use it to turn on/off a light fitted with a sonoff switch.
The sonoff will be flashed with custom firmware so everything runs locally over MQTT , the same transport layer used by Snips. No cloud required, no cloud desired.
The Snips documentation is good with easy to follow guides at https://docs.snips.ai/getting-started but we’ll run through the install process.
The easiest way to get started with Snips is by using…
Mobile web div.loper & mountain junkie.