Reinforce Happy Faces With Marshmallows And Computer Vision

Bing Crosby famously sang “Just let a smile be your umbrella.” George Carlin, though, said, “Let a smile be your umbrella, and you’ll end up with a face full of rain.” [BebBrabyn] probably agrees more with the former and used a Raspberry Pi with Open CV to detect a smile, a feature some digital cameras have had for a long time. This project however doesn’t take a snapshot. It launches a marshmallow using a motor-driven catapult. We wondered if he originally tried lemon drops until too many people failed to catch them properly.

This wouldn’t be a bad project for a young person — as seen in the video below — although you might have to work a bit to duplicate it. The catapult was upcycled from a broken kid’s toy. You might have to run to the toy store or rig something up yourself. Perhaps you could 3D print it or replace it with a trebuchet or compressed air.

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Raspberry Pi Foosball Scoreboard

Foosball, also known as table football, is a classic game from the 1920s that is completely devoid of the bells and whistles of modern gaming. Players control stoic little figures with the most simplistic of input devices in order to move a tiny ball to and fro on the playing field. So naturally, somebody thought they should add a Raspberry Pi to it and drag the whole thing kicking and screaming into the 21st century.

The team at [Matmi] spend a good portion of their down time huddled over a foosball table, but they found the experience was significantly less exciting for the spectators than the players. To add a little more pomp to their sessions they added a flashy display that not only shows the current score, but makes individual scores a bit more exciting by showing some celebratory confetti.

Micro switches mounted in the ball return tubes of the table allow the Raspberry Pi to know who scored and when. This information is picked up by the web-based scoreboard written in Vue.js and served out by nginx. The actual scoreboard is being displayed by a laptop that’s connected to the Pi over Wi-Fi.

If the software setup seems a bit convoluted, it’s because the project itself was something of a learning experience for HTML5 and web programming in general. Further updates are planned to streamline the system a bit to make it more self-contained, as well as adding more features to the scoreboard such as tournaments and randomized matches.

Interestingly, we’ve seen quite a few foosball hacks over the years. It seems these tables are somewhat ubiquitous in offices and hackerspaces. From turning it into an online-enabled experience to building an AI table you can play against, there’s plenty of ways to inject some new life into this nearly 100-year-old game.

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OTTO: A Pi Based Open Source Music Production Box

Want an open source portable synth workstation that won’t break the bank? Check out OTTO. [Topisani] started OTTO as a clone of the well-known Teenage Engineering OP-1. However, soon [Topisani] decided to branch away from simply cloning the OP-1 — instead, they’re taking a lot of inspiration from it in terms of form factor, but the UI will eventually be quite different.

On the hardware side, the heart of the OTTO is a Raspberry Pi 3. The all-important audio interface is a Fe-Pi Audio Z V2, though a USB interface can be used. The 48 switches and four rotary encoders are wrangled by a pair of Arduino pro micros which pass the data on to the Pi. Data is related to the user through a 320×200 LCD.

The software is being written from scratch in C++17. If you’re not a hardcore C++ developer, don’t worry. The synth engines, audio effects, and other DSP software is written in Faust, which is a bit easier to learn.

OTTO is actively being developed, with synth engines already running, a prototype in progress, and fleshed out guidelines for programming the UI. If you’re into creating music, this one is worth checking out, as is Zynthian, another Raspberry Pi based synth.

Mechanical Issues For A Pi CNC

The Raspberry Pi platform has become popular in the maker community for various CNC projects. The single board computers are readily suited to acting as a server for a small CNC setup or 3D printer, though it’s fair to say that for heavy work they probably aren’t quite up to the task of driving the steppers in a serious rig directly. [Danny] set out to try to build a CNC plotter of his own, using a Pi Zero, and learned a few things along the way.

The plotter uses 3D printed parts combined with brushed DC motors which are geared down. Potentiometers are added to allow the Pi to keep track of the location of the pen. This enables the position to be corrected through feedback.

While the plotter does move and accept commands, it does have some issues. There is significant play in the gear train which [Danny] suspects of causing the poor output results. If you’ve got any ideas as to how this could be improved or overcome, throw them down in the comments!

We’ve seen another take on CNC control with the Raspberry Pi, too. Video after the break.

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Feast Your Eyeballs On This Mechanical Eyeball

Most of us, if we have bought a single board computer with the capability  to support a camera, will have succumbed to temptation and shelled out for that peripheral in the hope that we can coax our new toy into having sight. We’ll have played with the command line tool and taken a few random images of our bench, but then what? There is so much possibility in a camera that our colleague [Steven Dufresne] wanted to explore with his Raspberry Pi, so he built a motorised eyeball mount with which to do so.

Pan & tilt mounts using RC servos are nothing especially new, but in this one he’s put some design effort that maybe some of the others lack. A lot of effort has gone in to ensuring no interference between the two axes, and in a slightly macabre twist until you remember it’s a model he’s talking about, the unit has been designed to fit inside a human head.

The servos are driven from the Pi using a servo driver board he’s discussed in another video, so once he’s described the assembly with a few design tweaks thrown in he has a quick look at the software demo he’s written emulating neurons for eye tracking. He promises that will be put up somewhere for download in due course.

If you’re in the market for a pan & tilt mount for your Pi, this one could make a lot of sense to throw at your 3D printer. It’s certainly more accomplished than this previous one we’ve shown you.

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Raspberry Pi On The Go Powers Car System

Most new cars have GPS, rear cameras, and all the other wonders an on-board system can bring. But what if you have an old car? [Fabrice Aneche] has a 2011 vehicle, and wanted a rearview camera. He started with a touch screen, a Raspberry Pi 3, and a camera. But you know how these projects take on a life of their own. So far, the project has two entries in his blog.

It wasn’t long before he couldn’t resist the urge to add a GPS. But that’s no fun without maps. Plus you need turn-by-turn directions. [Fabrice] did a lot of the user interface using Qt5 and QML. He started out running it with X11 but that was slow. It turns out though that Qt5 can drive the Pi’s video directly without using X11, so that’s what he wound up doing. The code that isn’t in QML — mainly dealing with the GPS location — is written in Go, while the code for MOCS (My Own Car System) is on GitHub.

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Object Detection, With TensorFlow

Getting computers to recognize objects has been a historically difficult problem in computer science, but with the rise of machine learning it is becoming easier to solve. One of the tools that can be put to work in object recognition is an open source library called TensorFlow, which [Evan] aka [Edje Electronics] has put to work for exactly this purpose.

His object recognition software runs on a Raspberry Pi equipped with a webcam, and also makes use of Open CV. [Evan] notes that this opens up a lot of creative low-cost detection applications for the Pi, such as setting up a camera that detects when a pet is waiting at the door to be let inside or outside, counting the number of bees entering and exiting a beehive, or monitoring parking spaces at an office.

This project uses a number of other toolkits as well, including Protobuf. It also makes extensive use of Python scripts, but if you’re comfortable with that and you have an application for computer vision, [Evan]’s tutorial will get you started.

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