Modifying Old Fonts In The Name Of Baseball

May 11, 2022 by Kristina Panos 4 Comments

Baseball is in full swing again, and having recently accepted a position with Major League Baseball, [Ty Porter] is warming up with a big contribution to the MLB LED Scoreboard project — modifying 20-some old fonts to support baseball’s ‘ꓘ’ character that indicates a special strikeout with a called third strike (meaning the batter didn’t take a swing).

The problem is that Major League Baseball-the-entity recently deprecated the original data source for the scoreboard project. This called for a huge refactor of the codebase, including previously-patched fonts which were now showing either the font’s default no-character character, or nothing at all.

Fortunately, BDF font files are fairly human-readable and make reference to bitmap, which is an actual bitmap in hex. [Ty] settled on Unicode A4D8 (ꓘ), a character from the Tibeto-Burman language Lisu that certainly looks good enough to this baseball fan. Then it became a matter of mirroring the bitmap for ‘K’. [Ty] tried a few things like reversing the nibbles and looking up each one in a table, but that also mirrors the padding, which is bad news.

Then he tried not reversing the nibbles and just looked them up in a table, but this approach dropped and added bits unintentionally. Finally, he tried reversing the order, looking up the reversed nibble, and shifting each byte until there was no padding. This worked for most of the 20 fonts [Ty] patched. The others fell in line with some manual work.

Not much of a baseball fan? You’re almost guaranteed to like this one, especially if you hate mayo.

A modern Tamagotchi PCB design and built-up prototype

Classic Tamagotchi Is Reincarnated In Modern Hardware

May 8, 2022 by Robin Kearey 25 Comments

If you thought that Tamagotchis were a late ’90s fad that has faded from most people’s memory by now, you’d be wrong: the franchise is still alive and well today, with new models being released regularly. But even the original model from 1996, known as Tamagotchi P1, is being kept alive by a small group of enthusiasts. When ROM dumps of the original hardware began floating around the internet a couple of years ago, even those without the real thing could run these virtual pets in an emulator.

But the whole idea of the Tamagotchi hardware was that it was portable enough to carry around anywhere. If you’re among those who missed that part of the Tamagotchi experience, you’ll be pleased to know that [JC] designed OpenTama: a portable hardware platform that runs an emulated version of the original Tamagotchi P1 software. It’s about as close as it gets to those first-generation virtual pets, but with several additions that make your life easier.

The software platform is [JC]’s TamaLib which we featured last year; in effect it’s an open-source emulator that allows the Tamagotchi ROM to run on a variety of modern hardware platforms. It also contains several additional options like the ability to save and restore your progress or to select customized ROMs. The OpenTama hardware, meanwhile, is a proper 21st-century reimplementation of the original: a small, egg-sized PCB sporting an STM32 microcontroller driving an LCD or OLED display, powered by a 100 mAh battery that can be recharged through a USB-C port.

OpenTama is not limited to the TamaLib software, either: as an open-source general-purpose platform, it can also be used as a learning tool for embedded programming, so if you’ve always wanted to program your own virtual pet, or are simply looking to build a fancy egg timer, OpenTama’s GitHub page is the way to go. We’ve seen quite a few neat Tamagotchi-like projects recently: this 3D-printed one comes with a nice retro LCD screen, while this one’s giant size ensures you don’t forget to feed it.

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How To Hide A Photo In A Photo

May 1, 2022 by Jenny List 32 Comments

If you’ve ever read up on the basics of cryptography, you’ll be aware of steganography, the practice of hiding something inside something else. It’s a process that works with digital photographs and is the subject of an article by [Aryan Ebrahimpour]. It describes the process at a high level that’s easy to understand for non-maths-wizards. We’re sure Hackaday readers have plenty of their own ideas after reading it.

The process relies on the eye’s inability to see small changes at the LSB level to each pixel. In short, small changes in colour or brightness across an image are imperceptible to the naked eye but readable from the raw file with no problems. Thus the bits of a smaller bitmap can be placed in the LSB of each byte in a larger one, and the viewer is none the wiser.

We’re guessing that the increased noise in the image data would be detectable through mathematical analysis, but this should be enough to provide some fun. If you’d like a closer look, there’s even some code to play with. Meanwhile as we’re on the topic, this isn’t the first time Hackaday have touched on steganography.

Hacking Toy RC Cars With The HackRF One

April 30, 2022 by Ryan Flowers 3 Comments

The origin story for many who’d call themselves a member of the hacker community usually starts with taking things apart as a child just to see how they worked. For [Radoslav], that trend doesn’t seem to have slowed down, and he’s continued taking toys apart. Although since it’s his daughters little radio controlled car, he stuck to a non-destructive teardown. The result? He’s able to control the car with his laptop through a HackRF One SDR transceiver as shown in the video below the break.

[Radoslav] is no stranger to reverse engineering embedded devices, IoT gadgets, and probably more. So he started with what information was publicly available about the radio control interface in use. Many electronic devices sold in the US must be certified by the FCC (Federal Communications Commission) and prominently display their ID number, and this toy was no exception. The FCC database gave [Radoslav] enough information to know that the communication protocol is modulated with GFSK, a type of Frequency Shift Keying.

He fired up his favorite radio signal analysis tool and and got to work on the protocol itself. Along the way he found that communication between the car and controller is bidirectional but also very easy to get around. The result is that he can drive the car around with his laptop- definitely a cool hack, but for this one, the journey was surely the goal, not the destination.

If hacking on RC cars really gets your wheels turning, you might like this little RC car that can drive on the ceiling. Or if you’re feeling a bit hungry, check out how you can use the HackRF to nab a table at your local restaurant.

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Tiny RISC Virtual Machine Is Built For Speed

April 28, 2022 by Bryan Cockfield 13 Comments

Most of us are familiar with virtual machines (VMs) as a way to test out various operating systems, reliably deploy servers and other software, or protect against potentially malicious software. But virtual machines aren’t limited to running full server or desktop operating systems. This tiny VM is capable of deploying software on less powerful systems like the Raspberry Pi or AVR microcontrollers, and it is exceptionally fast as well.

The virtual machine is built from scratch, including the RISC processor with only 61 opcodes, a 64 bit core, and runs code written in his own programming language called “Brackets” or in assembly. It’s designed to be modular, so only those things needed for a given application are loaded into the VM. With these design criteria it turns out to be up to seven times as fast as comparably small VMs like NanoVM. The project’s creator, [koder77], has even used its direct mouse readout and joystick functionality to control a Raspberry Pi 3D camera robot.

For anyone looking to add an efficient VM to a small computing environment, [koder77] has made the project open-source on his GitHub page. This also includes all of the modules he has created so far which greatly expand the project’s capabilities. For some further reading on exceedingly tiny virtual machines, we featured this project way back in 2012 which allows users to run Java on similar hardware.

Stanislaw playing notes on his MIDI keyboard, with the LEDs on the LED strip lighting up right above the note he's playing, driven by the Raspberry Pi that runs a script based on the Pianolizer toolkit

Pianolizer Helps Your Musical Projects Distinguish Notes

April 26, 2022 by Arya Voronova 9 Comments

[Stanislaw Pusep] has gifted us with the Pianolizer project – an easy-to-use toolkit for music exploration and visualization, an audio spectrum analyzer helping you turn sounds into piano notes. You can run his toolkit on a variety of different devices, from Raspberry Pi and PCs, to any browser-equipped device including smartphones, and use its note output however your heart desires. To show off his toolkit in action, he set it up on a Raspberry Pi, with Python code taking the note data and sending color information to the LED strip, displaying the notes in real time as he plays them on a MIDI keyboard! He also created a browser version that you can use with a microphone input or an audio file of your choosing, so you only need to open a webpage to play with this toolkit’s capabilities.

He took time to make sure you can build your projects with this toolkit’s help, providing usage instructions with command-line and Python examples, and even shared all the code used in the making of the demonstration video. Thanks to everything that he’s shared, now you can add piano note recognition to any project of yours! Pianolizer is a self-contained library implemented in JavaScript and C++ (which in turn compiles into WebAssembly), and the examples show how it can be used from Python or some other language.

[Stanislaw] also documented the principles behind the code, explaining how the note recognition does its magic in simple terms, yet giving many insights. We are used to Fast Fourier Transform (FFT) being our go-to approach for spectral analysis, aka, recognizing different frequencies in a stream of data. However, a general-purpose FFT algorithm is not as good for musical notes, since intervals between note frequencies become wider as frequency increases, and you need to do more work to distinguish the notes. In this toolkit, he used a Sliding Discrete Fourier Transform (SDFT) algorithm, and explains to us how he derived the parameters for it from musical note frequencies. In the end of the documentation, he also gives you a lot of useful references if you would like to explore this topic further!

What are you going to build with this? Maybe, a box that records you playing the flute and instantly turns it into sheet music? Or, perhaps, an AI that continues the song for you when you stop?

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Scanning Receipts Proves Trickier Than Anticipated

April 21, 2022 by Tom Nardi 25 Comments

It’s one of those things that certainly sounds simple enough: take a picture of a receipt, run it through optical character recognition (OCR), and send the resulting information to whatever expense-tracking website or software you wish. There are companies that offer such a service, so it can’t be too difficult to replicate on your own…right?

That’s what [Marcel Robitaille] thought when he set out to create his homebrew “Receipt Ingestion” system, anyway. But in reality it took so much time to troubleshoot and implement that he says it would have been faster to just enter in all his receipts by hand. We’re happy he stuck with it though, otherwise you wouldn’t be reading about it on Hackaday, and we wouldn’t be able to learn anything from the detailed account he’s provided.

It only took an evening to hack together a rough demo, and the initial results were very promising. The code could detect the edges of the receipt, rotate the captured image appropriately, and then pull out the critical information such as date, total amount, business name, etc. He was then able to decipher the API for Splitwise, an online service for splitting bills, by capturing the data sent by his browser while adding a new bill. With this information, writing up some Python code to push his captured data into the service was trivial. So far, so good.

But like so many horror films that begin with a happy family starting a new life in a beautiful home, there was a monster lurking in the shadows. It’s one thing to capture data from perfectly clean and flat receipts, but quite another to get any useful info out of one that spent half the day crumpled up in your back pocket. The promising proof of concept that worked a treat under controlled conditions failed completely in the real-world, with [Marcel] reporting that only 1 in 5 receipts he tried to scan actually went through.

In the end, [Marcel] realized that the best way to handle the unreliable condition of the receipts was to focus on a different object in the image. He came up with a QR code marker that he could put on the table with the receipt to be scanned, which his software can use as a known point of reference. This greatly improves the reliability of the image rotation and transformation, which in turn makes the OCR more reliable. It also makes it much easier to tell which images need to be scanned — if there’s no QR code found, the software just skips that shot and keeps looking.

The unique challenges of digitizing large amounts of printed content using OCR makes for some fascinating problem solving, and we’re glad [Marcel] shared this particular story with us. While there’s still some edge cases that need chasing down, he’s using the software on a nearly daily basis, and has posted it up on GitHub for anyone who might wish to build on his efforts.