Shot on a Raspberry Pi Camera Module, this stop-motion sequence is made up of 180 photos that took two hours to shoot and another hour to process.
The trick lies in the Camera Module enabling you to change the alpha transparency of the overlay image, which is the previous frame. It’s all explained in the official documentation, but basically, the Camera Module’s preview permits multiple layers to be rendered simultaneously: text, image, etc. Being able to change the transparency from the command line means this maker could see how the next frame (or the object) should be aligned. In 2D animation, this process is called ‘onion skinning’.
So why the Raspberry Pi Camera Module? Redditor /DIY_Maxwell aka Yuksel Temiz explains: “I make stop-motion animations as a hobby, using either my SLR or phone with a remote shutter. In most cases I didn’t need precision, but some animations like this are very challenging because I need to know the exact position of my object (the boat in this case) in each frame. The Raspberry Pi camera was great because I could overlay the previously captured frame into the live preview, and I could quickly change the transparency of the overlay to see how precise the location and how smooth the motion.”
You can easily make simple, linear stop-motion videos by just capturing your 3D printer while it’s doing its thing. Yuksel created a bolting horse (above) in that way. The boat sequence was more complicated though, because it rotates, and because pieces had to be added and removed.
The official docs are really comprehensive and span basic to advanced skill levels. Yuksel even walks you through getting started with the installation of Raspberry Pi OS.
We’ve seen Yuksel’s handiwork before, and this new project was made in part by modifying the code from the open-source microscope (above) they made using Raspberry Pi and LEGO. They’re now planning to make a nice GUI and share the project as an open-source stop-motion animation tool.
I’ve always wanted a Hayes Chronograph, but have never been able to acquire one, so I finally broke down and just made my own. The Hayes Chronograph was a compliment to Hayes line of smart modems, and implemented a real time clock for computers that didn’t have a built-in clock. They were popular in the early 1980s, and became less popular as computers began to either come with clocks built in, or add-on boards with clocks became popular. My “remake” keeps the theme of having a Vacuum Fluorescent Display (VFD), but switches to a GPS as a source of time synchronization. A raspberry pi is used as control — this thing could be used as an NTP server!. My design retains the DB25 for communication with the host computer, and attempts to replicate the original Hayes protocol.
μSim is a lightweight PIC CPU and ALU simulator. This simulator supports the PICmicro mid-range instruction set and designed to work on both PC and Arduino platforms. Compare with most of the other emulators, μSim does not provide all MCU features and peripherals. This simulator design as a minimalistic system, and based on the requirements, it can extend with additional peripherals and features.
This rotary phone features a built-in Raspberry Pi that communicates with radiooooo.com (a musical time machine) and an Arduino working behind the map to control the selection of the country. Just pick up the phone, choose a country and a decade, and listen to some great music!
How does it work?
The Raspberry Pi:
Plays music through radiooooo.com
Detects when the handset is picked up/put down
Detects the numbers that are dialled in
Detects which country is selected on the map (via jack connectors)
Sends the info to the Raspberry Pi over serial
We saw this project on hackster.io and loved how maker Caroline Buttet dug into the finer detail of an old-fashioned rotary phone’s pick-up/put-down mechanism, as well as how the phone knows which numbers you’re dialling. She goes into more detail about that aspect in the second build video, above.
Some countries have a jack pin – this is how you select the music
Other bits you’ll need
As well as a Raspberry Pi 4 and Arduino UNO, you’ll need a world map (obviously) and something to mount it on which can be drilled into. This is because the jack pins you can see in the image above need to poke out of different countries.
Caroline’s grandma donated the old rotary phone she used for this project. You should be able to pick one up from a second-hand shop or, if you can get a new handset made in the retro style online.
The shopping list for this build also includes: jumper wires; audio/video cable assembly; LED, breadboard; jack socket 3-pin; resistors
A simplified visual representation of how everything works
In her original post, Caroline explains in detail how to connect the rotary phone’s switches to the pins on your Raspberry Pi, how to build in audio sockets on the board you glue your map to, how to run the necessary Python script from the command line, and what a Chrome extension to use to make radiooooo.com work with your Raspberry Pi.
The Raspberry Pi inside the rotary phone
And yes, Caroline is one of those most magical of makers who deposits all the code needed for this build on GitHub!
And here’s the Arduino mounted onto the back of the map, with the audio jacks taped up to the holes drilled into different countries
App note from FTDI/Bridgetek demonstrating LED control over Ethernet. Link here (PDF)
In an increasingly connected world, more and more devices are going online. To enable online connectivity typically requires an MCU with Ethernet or Wi-Fi capabilities. To demonstrate the principle, this Application Note describes an implementation of a web server which allows for control of 2 WS2812 serial addressable LEDs. A web server is implemented on an FT90X device which when connected to a Local Area Network (LAN) allows a web browser to control the LEDs on an MM900EVxA board from a graphical web page.
Join us for Digital Making at Home: this week, young people can learn about using the Sense HAT — or its emulator — with us! With Digital Making at Home, we invite kids all over the world to code along with us and our new videos every week.
We’ve all been able to check on our kitties’ outdoor activities for a while now, thanks to motion-activated cameras. And the internet’s favourite cat flap even live-tweets when it senses paws through the door.
“Did you already make dinner? I stopped on the way home to pick this up for you.”
But what’s eluded us “owners” of felines up until now is the ability to stop our furry companions from bringing home mauled presents we neither want nor asked for.
A cat flap bouncer powered by deep learning
Now this Raspberry Pi–powered machine learning build, shared by reddit user u/eee_bume, can help us out: at its heart, there’s a convolutional neural network cascade that detects whether a cat is trying to enter a cat flap with something in its maw. (No word from the creators on how many half-consumed rodents the makers had to dispose of while training the machine learning model.)
The neural network first detects the whole cat in an image; then it hones in on the cat’s maw. Image classification is performed to detect whether there is anything in or around the maw. If the network thinks the cat is trying to smuggle caught contraband into the house, it’s a “no” from this virtual door bouncer.
The system runs on Raspberry Pi 4 with an infrared camera at an average detection rate of around 1 FPS. The PC-Val value, representing the certainty of the prey classification => prey/no_prey certainty threshold, is 0.5.
The infrared camera setup, powered by Raspberry Pi
How to get enough training data
This project formed Nicolas Baumann’s and Michael Ganz’s spring semester thesis at the Swiss Federal Institute of Technology. One of the problems they ran into while trying to train their device is that cats are only expected to enter the cat flap carrying prey 3% of the time, which leads to a largely imbalanced classification problem. It would have taken a loooong time if they had just waited for Nicolas and Michael’s pets to bring home enough decomposing gifts.
The cutest mugshots you ever did see
To get around this, they custom-built a scalable image data gathering network to simplify and maximise the collection of training data. It features multiple distributed Camera Nodes (CN), a centralised main archive, and a custom labeling tool. As a result of the data gathering network, 40GB of training data have been amassed.
What is my cat eating?!
The makers also took the time to train their neural network to classify different types of prey. So far, it recognises mice, lizards, slow-worms, and birds.
“Come ooooon, it’s not even a *whole* mouse, let me in!”
It’s still being tweaked, but at the moment the machine learning model correctly detects when a cat has prey in its mouth 93% of the time. But it still falsely accuses kitties 28% of the time. We’ll leave it to you to decide whether your feline companion will stand for that kind of false positive rate, or whether it’s more than your job’s worth.
Couple of years ago I purchased from a local store 100 MHz crystal resonator and tried several times to make a working schematic on breadboard using standard circuits I found on the internet. It never worked good enough, usually oscillating at 33.3 MHz instead of 100 MHz. Finally, I found that the crystal is third overtone type.
The closure of schools has called attention to the digital divide, which sees poorer families struggling or unable to access education*. The coronavirus pandemic didn’t cause this divide, but it has highlighted it and its impact on many people in our society.
As our Foundation CEO Philip outlined back in April, part of our response to the pandemic and social distancing measures is to send free Raspberry Pi computers to students who currently lack the technology to complete their school work at home. Generously funded by the Bloomfield Trust, we have started to distribute Raspberry Pis in the UK.
Who is receiving Raspberry Pis?
Our approach for this initiative is to work with partner charities that help us identify the right recipients for the computers; we want them to go to young people who don’t have a suitable device for completing their schoolwork in their home.
The first partner charity we’ve been working with, whose team has been so patient as we’ve learned together how to do this, are the incredible School Home Support, a youth organisation working to improve school attendance, behaviour, and engagement in learning. With their help, we’ve so far distributed more than 120 Raspberry Pi 4 computers (with 2GB RAM), together with all the peripherals including a screen. School Home Support were also able to secure funding to provide high-speed internet access to the recipients’ home so students can reliably connect to their schools.
How are we helping them set up?
The young people set up their Raspberry Pis themselves, and we provide detailed instructions to guide them through this process. Most of the families have never used a computer like Raspberry Pi, so they need encouragement and support to get up and running. This is being provided both by the excellent School Home Support practitioners, and by Raspberry Pi team members, who answer questions when recipients get stuck.
“My mum was confused by the setup at first, but having a call to explain it really helped, and now we see how easy it is to set up and use.”
Raspberry Pi recipient
Recipients are already benefiting
Before receiving these computers, many of the young people only had occasional access to their parents’ phone to find out what school work had been set for them, and to complete it.
“It’s much easier to do my schoolwork now on the bigger screen. I feel like I’m learning more.”
Raspberry Pi recipient
We’re getting feedback that the Raspberry Pis help recipients focus on their work; they now have their own space to work in and more time to complete schoolwork, as they’re no longer rushing to share a device with other family members.
“I don’t always enjoy doing homework, but it’s better now that I have my own computer to do my work.”
Raspberry Pi recipient
Having a Raspberry Pi has increased the students’ motivation, and it has reduced stress — for parents as well as children:
“The Raspberry Pi kit came at a time when I really needed it. Up until that point, T had to do his homework and access the school’s home learning using my phone, which was not very practical at all. This was made worse by the fact that he had to share my phone with his sister, which ended up causing a lot of arguments. He was so pleased to receive a computer he could use. At first he had a lot of fun playing different games on it, and I was surprised about how well he was able to understand and help me set it up. The only negative was that he enjoyed playing games on it a bit too much! I feel relieved that he has his own computer which he can use. It was very stressful and frustrating having to use my mobile phone. There were times when T would be using my phone to do his work and he would be interrupted if I got a phone call, which meant that he would have to log in again, and sometimes would lose his work.”
Parent of a Raspberry Pi recipient
What are we doing next?
It’s wonderful to hear stories like this of how our computers make a difference in people’s lives. We’re still learning lots: while many families have been able to get up and running easily and quickly, others are still overwhelmed because they are unfamiliar with the device. We know we need to do more to build their confidence.
As we’re learning, we’re also talking to our next charity partners in the UK to help us identify more recipients, and to help the recipients get set up on their new Raspberry Pi devices.
If you are part of an organisation that could partner with us to support families in need of access to technology, please email us at email@example.com. Be aware that your organisation would need to fund the families’ internet access.
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