The Android Things flower that smiles with you
Smile, and the world smiles with you — or, in this case, a laser-cut flower running Android Things on a Raspberry Pi does.
Expression Flower
The aim of the Expression Flower is to “challenge the perception of what robotics can be while exploring the possibility for a whimsical experience that is engaging, natural, and fun.”
Tl;dr: cute interactive flower. No Skynet.
Android Things
The flower is powered by Google’s IoT platform Android Things, running on a Raspberry Pi, and it has a camera mounted in the centre. It identifies facial expressions using the ML Kit machine learning package, also from Google. The software categorises expressions, and responds with a specific action: smile at the flower, and it will open up its petals with a colourful light show; wink at it, and its petals will close up bashfully.
The build is made of laser-cut and 3D-printed parts, alongside off-the-shelf components. The entire build protocol, including video, parts, and code, is available on hackster.io, so all makers can give Expression Flower a go.
Seriously, this may be the easiest-to-follow tutorial we’ve ever seen. So many videos. So much helpful information. It’s pure perfection!
Machine learning and Android Things
For more Raspberry Pi–based machine learning projects, see:
- Build your own Pokédex, for Pokémon-hunting funtimes
- The Santa detector, for detecting Santa, obviously
- There’s Waldo, for hunting Waldo/Wally in a crowd
And for more Android Things projects, we highly recommend:
- BrailleBox, for displaying the latest news in Braille
- The Android Things Candy Dispenser, for candy…at a price
- The Augmented-reality projection lamp, for, well, it does a lot of stuff, so check it out
Aaaand, for getting started with all things Android on your Raspberry Pi, check out issue 71 of The MagPi!
4 comments
Raspberry Pi Staff Janina Ander
Alex Bate
Hahahahahaaaaa
Julien de la Bruère-Terreault
Great to see different projects using machine learning on the Pi!
Check-out the Rock-Paper-Scissors game I made using python machine learning libraries and running 100% on the Pi (no pre-trained ML model from Google or others): https://github.com/DrGFreeman/rps-cv (shameless plug…)
Alex Bate
This is awesome. So awesome that I am currently writing it up for today’s blog post. Thank you!