It has been a cold winter for Tom Shaffner, and since he is working from home and leaving the heating on all day, he decided it was finally time to see where his house’s insulation could be improved.
An affordable solution
His first thought was to get a thermal IR (infrared) camera, but he found the price hasn’t yet come down as much as he’d hoped. They range from several thousand dollars down to a few hundred, with a $50 option just to rent one from a hardware store for 24 hours.
When he saw the $50 option, he realised he could just buy the $60 (£54) MLX90640 Thermal Camera from Pimoroni and attach it to a Raspberry Pi. Tom used a Raspberry Pi 4 for this project. Problem affordably solved.
A joint open source effort
Once Tom’s hardware arrived, he took advantage of the opportunity to combine elements of several other projects that had caught his eye into a single, consolidated Python library that can be downloaded via pip and run both locally and as a web server. Tom thanks Валерий Курышев, Joshua Hrisko, and Adrian Rosebrock for their work, on which this solution was partly based.
Tom has also published everything on GitHub for further open source development by any enterprising individuals who are interested in taking this even further.
The big question, though, was whether the image quality would be good enough to be of real use. A few years back, the best cheap thermal IR camera had only an 8×8 resolution – not great. The magic of the MLX90640 Thermal Camera is that for the same price the resolution jumps to 24×32, giving each frame 768 different temperature readings.
Add a bit of interpolation and image enlargement and the end result gets the job done nicely. Stream the video over your local wireless network, and you can hold the camera in one hand and your phone in the other to use as a screen.
Bonus security feature
Bonus: If you leave the web server running when you’re finished thermal imaging, you’ve got yourself an affordable infrared security camera.
Documentation on the setup, installation, and results are all available on Tom’s GitHub, along with more pictures of what you can expect.
We shared Dennis Mellican’s overly effective anti-burglary project last month. Now he’s back with something a whole lot more musical and mini.
Dennis was inspired by other jukebox projects that use Raspberry Pi, NFC readers, and tags to make music play. Particularly this one by Mark Hank, which we shared on the blog last year. The video below shows Dennis’s first attempt at creating an NFC Raspberry Pi music player, similar to Mark’s.
After some poking around, Dennis realised that the LEGO Dimensions toy pad is a three-in-one NFC reader with its own light show. He hooked it up to a Raspberry Pi and developed a Python application to play music when LEGO Dimension Minifigures are placed on the toy pad. So, if an Elvis minifigure is placed on the reader, you’ll hear Elvis’s music.
The Raspberry Pi is hooked up to the LEGO Dimensions toy pad, with Musicfig (Dennis’s name for his creation) playing tracks via Spotify over Bluetooth. The small screen behind the minifigures is displaying the Musicfig web application which, like the Spotify app, displays the album art for the track that’s currently playing.
No Spotify or LEGO? No problem!
Spotify playback is optional, as you can use your own MP3 music file collection instead. You also don’t have to use LEGO Minifigures: most NFC-enabled devices or tags can be used, including Disney Infinity, Nintendo Amiibo, and Skylander toy characters.
Dennis thought Musicfig could be a great marketable LEGO product for kids and grown-ups alike, and and he submitted it to the LEGO Ideas website. Unfortunately, he had tinkered a little too much (we approve) and it wasn’t accepted, due to rules that don’t allow non-LEGO parts or customisations.
Want to build one?
The LEGO Dimensions toy pad was discontinued in 2017, but Dennis has seen some sets on sale at a few department stores, and even more cheaply on second-hand market sites like Bricklink. We’ve spotted them on eBay and Amazon too. Dennis also advises that the toy pad often sells for less than a dedicated NFC reader.
Watch Dennis’s seven-year-old son Benny show you how it all works, from Elvis through to Prodigy via Daft Punk and Queen.
There are some really simple step-by-step instructions for a quick install here, as well as a larger gallery of Musicfig rigs. And Dennis hosts a more detailed walkthrough of the project, plus code examples, here.
You can find all things Dennis-related, including previous Raspberry Pi projects, here.
The upside of headless is that my Raspberry Pi can be anywhere, not tied to a monitor, keyboard and mouse. The downside is programming and debugging it – do you plug your Raspberry Pi into a monitor and run the full Raspberry Pi OS desktop, or do you use Raspberry Pi OS Lite and try to program and debug over SSH using the command line? Or is there a better way?
Remote development with VS Code to the rescue
There is a better way – using Visual Studio Code remote development! Visual Studio Code, or VS Code, is a free, open source, developer’s text editor with a whole swathe of extensions to support you coding in multiple languages, and provide tools to support your development. I practically live day to day in VS Code: whether I’m writing blog posts, documentation or Python code, or programming microcontrollers, it’s my work ‘home’. You can run VS Code on Windows, macOS, and of course on a Raspberry Pi.
One of the extensions that helps here is the Remote SSH extension, part of a pack of remote development extensions. This extension allows you to connect to a remote device over SSH, and run VS Code as if you were running on that remote device. You see the remote file system, the VS Code terminal runs on the remote device, and you access the remote device’s hardware. When you are debugging, the debug session runs on the remote device, but VS Code runs on the host machine.
For example – I can run VS Code on my MacBook Pro, and connect remotely to a Raspberry Pi 4 that is running headless. I can access the Raspberry Pi file system, run commands on a terminal connected to it, access whatever hardware my Raspberry Pi has, and debug on it.
Remote SSH needs a Raspberry Pi 3 or 4. It is not supported on older Raspberry Pis, or on Raspberry Pi Zero.
Set up remote development on Raspberry Pi
For remote development, your Raspberry Pi needs to be connected to your network either by ethernet or WiFi, and have SSH enabled. The Raspberry Pi documentation has a great article on setting up a headless Raspberry Pi if you don’t already know how to do this.
You also need to know either the IP address of the Raspberry Pi, or its hostname. If you don’t know how to do this, it is also covered in the Raspberry Pi documentation.
Connect to the Raspberry Pi from VS Code
Once the Raspberry Pi is set up, you can connect from VS Code on your Mac or PC.
From inside VS Code, you will need to install the Remote SSH extension. Select the Extensions tab from the sidebar menu, then search for Remote development. Select the Remote Development extension, and select the Install button.
Next you can connect to your Raspberry Pi. Launch the VS Code command palette using Ctrl+Shift+P on Linux or Windows, or Cmd+Shift+P on macOS. Search for and select Remote SSH: Connect current window to host (there’s also a connect to host option that will create a new window).
Enter the SSH connection details, using user@host. For the user, enter the Raspberry Pi username (the default is pi). For the host, enter the IP address of the Raspberry Pi, or the hostname. The hostname needs to end with .local, so if you are using the default hostname of raspberrypi, enter raspberrypi.local.
The .local syntax is supported on macOS and the latest versions of Windows or Linux. If it doesn’t work for you then you can install additional software locally to add support. On Linux, install Avahi using the command sudo apt-get install avahi-daemon. On Windows, install either Bonjour Print Services for Windows, or iTunes for Windows.
For example, to connect to my Raspberry Pi 400 with a hostname of pi-400 using the default pi user, I enter email@example.com.
The first time you connect, it will validate the fingerprint to ensure you are connecting to the correct host. Select Continue from this dialog.
Enter your Raspberry Pi’s password when promoted. The default is raspberry, but you should have changed this (really, you should!).
VS Code will then install the relevant tools on the Raspberry Pi and configure the remote SSH connection.
You will now be all set up and ready to code on your Raspberry Pi. Start by opening a folder or cloning a git repository and away you go coding, debugging and deploying your applications.
In the remote session, not all extensions you have installed locally will be available remotely. Any extensions that change the behavior of VS Code as an application, such as themes or tools for managing cloud resources, will be available.
Things like language packs and other programming tools are not installed in the remote session, so you’ll need to re-install them. When you install these extensions, you’ll see the Install button has changed to Install in SSH:< hostname > to show it’s being installed remotely.
Do you remember the Danger Shed? New Orleans-based Raspberry Pi-powered home brewing monitoring set up in a… shed? Well, Patrick Murphy and his brewing crew are back with a new toy.
What is it?
It’s called Keg Punk – inventory software written in Python, specifically for running on Raspberry Pi and the 7″ Raspberry Pi Touch Display. You mount the touchscreen station in a convenient place and run the program on an embedded Raspberry Pi 4.
Keg Punk is written in Python and is about 2500 lines of code. Since the program is small with a simple interface, it runs on anything from Raspberry Pi Zero to Raspberry Pi 4.
Who needs it?
As a manager at a local craft brewery, Patrick hated not knowing (or not being able to remember) how many kegs of each beer were left in the cellar.
So he started developing a cellar inventory program with the intention of being able to run it within arm’s reach of the beer taps.
The station needed to have a touchscreen and be tough enough to cope with harsh environments (beer gets EVERYWHERE). Raspberry Pi is the perfect platform for the job as it’s small and easy to connect a touchscreen to.
It can be mounted discreetly close to workstations, so bartenders can quickly see how much stock is left without needing to go down to the cellar.
While requirements in a professional setting inspired the idea of Keg Punk, it was developed with the home brewer in mind. The touchscreen station can easily be mounted to a kegerator (a portmanteau of keg and refrigerator) and the tap display can be configured to your setup.
Three installation options
One of the things the Danger Shed team admire most about Raspberry Pi users is their willingness to do a little hands-on tinkering. With that in mind, they launched Keg Punk in three packages, so you can choose an option based on how much of that you’d like to do:
The Taproom Package: This is a full plug-in-and-go setup for those who don’t have a Raspberry Pi or who simply do not have time to tinker while also running a bar.
Keg Punk pre-loaded SD card: Perfect for beer slingers who already have a Raspberry Pi but don’t want to install on their current SD card or deal with the hassle of installation.
Keg Punk software only: If you already have a Raspberry Pi and don’t mind a fair bit of tinkering, you can download the Keg Punk software and manually install.
Microsoft’s Visual Studio Code is an excellent C development environment, and now it’s an easy install on Raspberry Pi. Here’s Jim Bennett from Microsoft to show you all how to get VS Code up and running on our tiny computer. Take it away, Jim…
There are a few products in the tech sphere that get me really excited. One of them is Raspberry Pi (obviously), and the other is Visual Studio Code or VS Code. I always hoped that the two would come together one day — and now, to my great pleasure, they have!
For example my VS Code setup includes a Python extension so I can code and debug in Python, a set of Microsoft Azure extensions so I can manage my cloud services, PlatformIO to allow me to program micro-controllers like Arduino boards coupled with a C++ extension to support coding in C and C++, and even some Docker support. Not a bad setup for a completely free developer tool.
I’ve been hoping for years VS Code would come to Raspberry Pi, and finally it’s here. As well as supporting Debian Linux on x64, there are now builds for ARM and ARM64 – both of which can run on Raspberry Pi OS (the ARM build on Raspberry Pi OS, the ARM64 on the beta of the 64-bit Raspberry Pi OS). And yes — I am writing this right now on a Raspberry Pi 400 running VS Code!
Why am I so excited about this?
Well, there are a couple of reasons.
Firstly, it brings an exceptional developer tool to Raspberry Pi. There are already some great editors, but nothing of the calibre of VS Code. I can take my $35 computer, plug it into a keyboard and mouse, connect a monitor and a TV and code in a wide range of languages from the same place.
I see kids learning Python at school using one tool, then learning web development in an after-school coding club with a different tool. They can now do both in the same application, reducing the cognitive load – they only have to learn one tool, one debugger, one setup. Combine this with the new Raspberry Pi 400 and you have an all-in-one solution to learning to code, reminiscent of my ZX Spectrum of decades ago, but so much more powerful.
The second reason is to me the most important — it allows kids to share the same development environment as their grown-ups. Imagine the joy of a 10-year-old coding Python using VS Code on their Raspberry Pi plugged into the family TV, then seeing their Mum working from home coding Python in exactly the same tool on her work laptop as part of her job as an AI engineer or data scientist. It also makes it easier when Mum has to inevitably help with unblocking the issues that always come up with learners.
As a young child it was mind-blowing when my Dad brought home a work PC so he could write reports and I could use it to write up my school work – I was using what Dad used at work, making me feel important. I see this with my seven-year-old daughter, seeing her excitement that I use Microsoft Teams for work, the same as she uses for her virtual schooling (she’s even offered to teach me how to use it if I get stuck). To be able to bring that unadulterated joy of using ‘grown-up tools’ to our young learners is priceless.
Installing VS Code
The great news is VS Code is now available as part of the Raspberry Pi OS apt packages. Launch the Raspberry Pi Terminal and run the following commands:
sudo apt update
sudo apt install code -y
This will download and install VS Code. If you’ve got your hands on a Pico, then you may not even need to do this – VS Code is installed as part of the Pico setup from the Getting Started guide.
After installing VS Code, you can run it from the Programming folder in the Raspberry Pi menu.
Brilliant Jim Bennett shares loads of Raspberry Pi builds and tutorials over on Expecting Someone Geekier and tweets @jimbobbennett. He also works in Developer Relations at Microsoft. You can learn pretty much everything there is to know about him on github.
Raspberry Pi is at the heart of this AI–powered, automated sorting machine that is capable of recognising and sorting any LEGO brick.
And its maker Daniel West believes it to be the first of its kind in the world!
This mega-machine was two years in the making and is a LEGO creation itself, built from over 10,000 LEGO bricks.
It can sort any LEGO brick you place in its input bucket into one of 18 output buckets, at the rate of one brick every two seconds.
While Daniel was inspired by previous LEGO sorters, his creation is a huge step up from them: it can recognise absolutely every LEGO brick ever created, even bricks it has never seen before. Hence the ‘universal’ in the name ‘universal LEGO sorting machine’.
What makes Daniel’s project a ‘world first’ is that he trained his classifier using 3D model images of LEGO bricks, which is how the machine can classify absolutely any LEGO brick it’s faced with, even if it has never seen it in real life before.
Daniel has made a whole extra video (above) explaining how the AI in this project works. He shouts out all the open source software he used to run the Raspberry Pi Camera Module and access 3D training images etc. at this point in the video.
LEGO brick separation
Daniel needed the input bucket to carefully pick out a single LEGO brick from the mass he chucks in at once.
This is achieved with a primary and secondary belt slowly pushing parts onto a vibration plate. The vibration plate uses a super fast LEGO motor to shake the bricks around so they aren’t sitting on top of each other when they reach the scanner.