[Dominic Szablewski] was tinkering around with compressing RGB images, when he stumbled upon idea of how to make a simple lossless compression algorithm, resulting in the Quite OK Image Format, which seems to offer comparable file sizes to the PNG format but is so simple it runs up to 50 times faster for compression and up to four times faster for decompression. Implementation can be achieved with a miniscule 300 lines of C. Need a bit more detail on the real-world performance? Well [Dominic] has that covered too, with a complete set of benchmarks for your perusal.
Image formats are one of those things these days that are designed by consortium, with so much complexity wedged in making it hard to implement with limited resources, so we find it very refreshing to see someone going back to basics and producing something super lightweight, and plenty good enough in practical terms.
Other uses for the algorithm could be for super simple video compression, for applications where resource is tight and some low-effort bandwidth reduction would be beneficial. Implementation in a small FPGA would also be quite straightforward, since the memory requirement is quite low also.
The project is very new and already there are some tweaks happening to the format, so the GitHub project code may change without warning to reflect any corrections [Dominic] feels necessary.
There’s going to be a new Matrix movie in theaters next month, and you know what that means: we’re about to see a whole new generation get obsessed with the franchise’s iconic “Digital Rain” effect. Thanks to modern advertisement technology, expect to see lines of glittering text pouring down the displays of everything from billboards to gas pumps pretty soon.
Doesn’t get much easier than that.
For those of us who’ve just been looking for an excuse to break out the old Matrix screensavers, you might as well get a jump on things using this handy Arduino library for the ESP8266 and ESP32. Developed by [Eric Nam], it lets you start up a digital rainstorm on displays supported by the TFT_eSPI library as easily as running digitalRainAnim.loop().
You can even install the library through the Arduino IDE, just open the Library Manager and search for “Digital Rain” to get started. You’ve still got to hook the display up to your microcontroller, but come on, [Eric] can’t do it all for you.
Looking at the examples, it seems like various aspects of the animation like color and speed can be configured by initializing the library with different values. Unfortunately we’re not seeing much in the way of documentation for this project, but by comparing the different examples, you should be able to get the high points.
While our first choice would certainly be a wall of green alphanumeric LED displays, we can’t help but be impressed with how easy this project makes it to spin up your own little slice of the Matrix on the workbench.
People tend to obsess over making computer software faster. You can, of course, just crank up the clock speed and add more processors, but often the most powerful way to make something faster is to find a better way to do it. Sometimes those methods are very different from how a human being would do the same task, but it suits the computer’s capabilities. [Nemean] has a video explaining a better multiplication algorithm known as Karatsuba’s algorithm and it is actually quite clever. You can see the video below.
To help you understand the algorithm, the video shows a simple two-digit by two-digit multiplication. You can see that the first and last digits are essentially the result of one multiplication. It is all the intermediate digits that add together. The only thing that might change the first digit is a carry.
[Ben Bartlett] recently got engaged, and the proposal had a unique bit of help in the form of a 3D-printed hexagonal mirror array, whose mirrors are angled just right to spell out a message with the reflections. A small test is shown above projecting a heart, but the real deal was a bigger version reflecting the message “MARRY ME?” into sand at sunset. Who could say no to something like that? Luckily for all of us, [Ben] shared all the details of what went into designing and building such a thoughtful and fascinating device.
Mirrors on the 3D-printed array are angled just right to reflect light into a message.
Essentially, the array of mirrors works a bit like a projector. Each individual reflection can be can be thought of as a pixel, and the projected position of each can be modified by the precise angle of each mirror. With the help of some Python code, [Ben] calculated the exact angles needed to spell out “MARRY ME?” and generated the necessary 3D model. A smaller-scale test (shown in the header image above) was successful, and after that it was just a matter of printing the array and gluing on some mirrors.
Of course, that’s the short version. In practice there were quite a few troublesome issues that demonstrated the value of using early tests to discover hidden problems. For one thing, mirror angle and alignment is crucial, which meant that anything that could affect the shape of the array was a potential problem. Glue that expands or otherwise changes shape as it dries or cures could slightly change a mirror’s angle, so cyanoacrylate (CA) glue was preferred. However, the tiniest bit of CA glue will mess up a mirror’s surface in a hurry, so care was needed during assembly.
Another gotcha was when [Ben] suddenly realized, twenty hours into printing the final assembly, that the message needed to be reversed! As designed, the array he was printing would project “?EM YRRAM” and this wasn’t caught during testing because the test pattern (a heart) was symmetrical. Fortunately there was time to correct the error and start again, but it was close. [Ben]’s code has an optional visualization function, which was invaluable for verifying that things would actually turn out as expected. As it happens, the project took right up to the last minute to complete and there wasn’t quite time to check everything 100% before the big moment, but it all turned out alright. What’s life without a little mystery and danger, anyway?
The pictures are great, but you won’t regret taking the time to read through the project page (don’t miss the annotated Python code) because [Ben] goes into just the right level of detail. The end result looks fantastic, and makes an excellent keepsake with a charming story.
If you’ve looked into GPU-accelerated machine learning projects, you’re certainly familiar with NVIDIA’s CUDA architecture. It also follows that you’ve checked the prices online, and know how expensive it can be to get a high-performance video card that supports this particular brand of parallel programming.
But what if you could run machine learning tasks on a GPU using nothing more exotic than OpenGL? That’s what [lnstadrum] has been working on for some time now, as it would allow devices as meager as the original Raspberry Pi Zero to run tasks like image classification far faster than they could using their CPU alone. The trick is to break down your computational task into something that can be performed using OpenGL shaders, which are generally meant to push video game graphics.
An example of X2’s neural net upscaling.
[lnstadrum] explains that OpenGL releases from the last decade or so actually include so-called compute shaders specifically for running arbitrary code. But unfortunately that’s not an option on boards like the Pi Zero, which only meets the OpenGL for Embedded Systems (GLES) 2.0 standard from 2007.
Constructing the neural net in such a way that it would be compatible with these more constrained platforms was much more difficult, but the end result has far more interesting applications to show for it. During tests, both the Raspberry Pi Zero and several older Android smartphones were able to run a pre-trained image classification model at a respectable rate.
Truth be told, we’re a bit behind the ball on this one, as Beatmup made its first public release back in April of this year. It might have flown under the radar until now, but we think there’s a lot of potential for this project, and hope to see more of it once word gets out about the impressive results it can wring out of even the lowliest hardware.
VHDL and Verilog are hardware description languages, used to describe and define logic circuits. They’re typically used to design ASICs and to program FPGAs, essentially using software to define hardware. However, [Tim] has done something altogether quite creative, creating tools to take VHDL and Verilog and spit out PCB designs for discrete logic.
Yes, you read that correctly. The basic idea is to take VHDL source code, and then make a PCB layout that implements the desired logic using resistor-transistor logic. From there, the PCB design files can be shipped off to a manufacturer for pick-and-place assembly at a fraction of the cost of producing a bespoke ASIC.
The drawbacks are obvious; tons of individual discrete parts are required, the size penalty is hilariously bad, and power usage is almost certainly orders of magnitude higher than doing the same logic on an ASIC or even FPGA. Oh, and everything’s much slower, too.
However, as an academic exercise or simply for fun, it’s an awesome bit of work. The idea that one can define a complicated logic circuit and have a PCB implementing the logic whipped up by automated tools is amazing, and we absolutely want to see more of this type of thing.
We’ve seen similar work done with VHDL synthesis into 74-series logic design. If you’ve been developing your own fancy digital-logic-fu, be sure to drop us a line!
We know you like soldering irons, we’re quite fond of them ourselves. But the reality is, modular components and highly capable development boards allow the modern hardware hacker to get things done with far less solder smoke then ever before. In fact, sometimes all you need to finish your project is the right code.
Case in point, check out the slick electronic paper weather display that [Danko Bertović] shows off in the latest Volos Projects video. While it certainly fits the description of a DIY project, he didn’t have to put any of the hardware together himself. The M5Paper is an ESP32 development kit designed around a crisp 4.7″, 960 x 540 e-paper panel that includes everything from environmental sensors to an internal 1150 mAh battery. To make your handheld e-paper dreams come true, the only thing you need to provide is the software.
The weather display code provided by [Danko] should certainly get you going in the right direction. Now don’t get us wrong, there’s certainly no shame in just flashing his code to the device and plunking it on your desk. It’s a gorgeous looking interface, and we all know that a sprinkling of open source code is often all it takes to make a standard consumer device extraordinary. But by using the code he’s provided as a launching point, you can take this turn-key device and really make it your own.
