Count YouTube Subscribers with this Red Play Button Award

Professional YouTubers live and die by the number of subscribers they have. It seems like a brutal way to make a living to us, but to each his own. Still, if you’re going to do it, you might as well do it right, and keeping track of how you’re doing with this Play Button Award subscriber counter might make sense. Or it might drive you nuts.

YouTuber [ibuynewstuff] has reached the vaunted 100,000 subscriber mark, the number required to earn the Silver Play Button award. Sadly, 100k is the bare minimum needed to get YouTube’s attention, and tales of waiting for months for the award to arrive are not uncommon. [ibuynewstuff] worked around the issue by 3D-printing his own temporary play button badge. Mounted to a picture frame with an ESP8266 and an 8 x 80 LED display behind a diffuser, [ibuynewstuff] can keep track of his progress toward the Gold Play Button award at 1,000,000 subs. Hopefully, his Silver award will arrive before then.

Want to replicate this but would rather have something a little more permanent than a plastic play button? Try casting your own Copper Play Button award.

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[Ben Krasnow] Hacks E-Paper For Fastest Refresh Rate

[Ben Krasnow] is known for his clear explanations alongside awesome hardware, being one of only a few hackers who owns an electron microscope. This time he’s explaining how E-paper works while modifying the firmware of a 4.2 inch E-paper module to get a higher refresh rate. As for the awesome hardware, he also analyses the signals going to the E-paper using an ultra-fancy loaner oscilloscope.

E-paper explanation diagram
E-paper explanation diagram

After starting out with a demo of the firmware in action before and after his modification, he explains how the E-paper works. The display is made up of many isolated chambers, each containing charged particles in a liquid. For example, the positive particles might be black and the negative might be white. By putting an electric field across each chamber, the white particles would be attracted to one end while the black would be attracted to the other, which could be the end you’re looking at. He also explains how it’s possible to get a third color by using different sized particles along with some extra manipulation of the electric field. And he talks about the issue of burn-in and how to avoid it.

Having given us that background, he then walks us through some of the firmware and shows how he modified it to make it faster, namely by researching various datasheets and subsequently modifying some look-up-tables.

Turning back to the hardware, he shows how he scratches out some traces so that he can attach scope probes. This alone seems like a notable achievement, though he points out that the conductive layer holds up well to his scratching. At that point he analyses the signals while running some demos.

The result is the very informative, interesting and entertaining video which you can watch below.

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10 Year Old Bug Crushed By Hacker on a Mission

PCI pass through is the ability of a virtualized guest system to directly access PCI hardware. Pass through for dedicated GPUs has just recently been added to the Linux kernel-based virtual machine. Soon afterward, users began to find that switching on nested page tables (NPT), a technology intended to provide hardware acceleration for virtual machines, had the opposite effect on AMD platforms and slowed frame rate down to a crawl.

Annoyed by this [gnif] set out to to fix the problem. His first step was to run graphics benchmarks to isolate the source of the problem. Having identified the culprit in the GPU, [gnif] began to read up on the involved technology stack. Three days of wrapping his head around technical docs allowed [gnif] to find the single line of code that resulted in a faulty memory set up and to implement a basic fix. He then passed the work on to [Paolo Bonzini] at patchwork.kernel.org, who released a more refined patch.

The bug affecting PCI pass through had been around for ten years and had received little attention from the manufacturer. It gained prominence when graphics cards were affected. In the end it took one very dedicated user three days to fix it, and then another day to roll out a patch for Open Source operating systems. In his notes [gnif] points out how helpful AMDs documentation was. With the right to repair in debate, DRMed technical docs and standards locked behind paywalls, [gnif]’s story is a reminder of the importance of accessible quality documentation.

Interactive Visual Programming With vvvv

Did you ever feel the urge to turn the power of image processing and OCR into music? Maybe you wanted to use motion capture to illustrate the dynamic movement of a kung-fu master in stunning images like the one above?  Both projects were created with the same software.

vvvv -pronounced ‘four vee’, ‘vee four’ and sometimes even ‘veeveeveevee’- calls itself ‘a multi purpose framework’, which is as vague and correct as calling a computer ‘a device that performs calculations’. What can it do, and what does the framework look like? I’d like to show you.

Since its first release in 1998 the project has never officially left beta stage. This doesn’t mean the recent beta releases are unstable, it’s just that the people behind vvvv refrain from declaring their software ‘finished’. It also provides an excuse for some quirks, such as requiring 7-zip to unpack the binaries and the UI that takes some getting used to. vvvv requires DirectX and as such is limited to Windows.

With the bad stuff out of the way, let’s take a look what vvvv can do. First, as implied by the close relationship with DirectX, it’s really good at producing graphics. An example for interactive video is embedded below the break. With its data flow/ visual programming approach it also lends itself to rapid prototyping or live coding. Modifications to a patch, as programs are called in this context, immediately affect the output.

The name ‘patch’ harkens back to the times of analog synthesizers and working with vvvv has indeed some similarities with signal processing that will make the DSP nerds among you feel right at home.

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Solving Mazes with Graphics Cards

What if we told you that you are likely to have more computers than you think? And we are not talking about things that are computers while not looking like one, like most modern cars or certain lightbulbs. We are talking about the powerful machines hiding in your desktop computer called ‘graphics card’. In the ordinary gaming rig graphics cards that are much more powerful than the machine they’re built into are a common occurrence. In his tutorial [Viktor Chlumský] demonstrates how to harness your GPU’s power to solve a maze.

Software that runs on a GPU is called a shader. In this example a shader is shown that finds the way through a maze. We also get to catch a glimpse at the limitations that make this field of software special: [Viktor]’s solution has to work with only four variables, because all information is stored in the red, green, blue and alpha channels of an image. The alpha channel represents the boundaries of the maze. Red and green channels are used to broadcast waves from the beginning and end points of the maze. Where these two waves meet is the shortest solution, a value which is captured through the blue channel.

Despite having tons of cores and large memory, programming shaders feels a lot like working on microcontrollers. See for yourself in the maze solving walk through below.

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Neural Network Gimbal Is Always Watching

[Gabriel] picked up a GoPro to document his adventures on the slopes and trails of Montreal, but quickly found he was better in front of the camera than behind it. Turns out he’s even better seated behind his workbench, as the completely custom auto-tracking gimbal he came up with is nothing short of a work of art.

There’s quite a bit going on here, and as you might expect, it took several iterations before [Gabriel] got all the parts working together. The rather GLaDOS-looking body of the gimbal is entirely 3D printed, and holds the motors, camera, and a collection of ultrasonic receivers. The Nvidia Jetson TX1 that does the computational heavy lifting is riding shotgun in its own swanky looking 3D printed enclosure, but [Gabriel] notes a future revision of the hardware should be able to reunite them.

In the current version of the system, the target wears an ultrasonic emitter that is picked up by the sensors in the gimbal. The rough position information provided by the ultrasonics is then refined by the neural network running on the Jetson TX1 so that the camera is always focused on the moving object. Right now the Jetson TX1 gets the video feed from the camera over WiFi, and commands the gimbal hardware over Bluetooth. Once the Jetson is inside the gimbal however, some of the hardware can likely be directly connected, and [Gabriel] says the ultrasonics may be deleted from the design completely in favor of tracking purely in software. He plans on open sourcing the project, but says he’s got some internal house keeping to do before he takes the wraps off it.

From bare bones to cushy luxury, scratch-built camera gimbals have become something of a right of passage for the photography hacker. But with this project, it looks like the bar got set just a bit higher.

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Video Streaming Like Your Raspberry Pi Depended On It

The Raspberry Pi is an incredibly versatile computing platform, particularly when it comes to embedded applications. They’re used in all kinds of security and monitoring projects to take still shots over time, or record video footage for later review. It’s remarkably easy to do, and there’s a wide variety of tools available to get the job done.

However, if you need live video with as little latency as possible, things get more difficult. I was building a remotely controlled vehicle that uses the cellular data network for communication. Minimizing latency was key to making the vehicle easy to drive. Thus I set sail for the nearest search engine and begun researching my problem.

My first approach to the challenge was the venerable VLC Media Player. Initial experiments were sadly fraught with issues. Getting the software to recognize the webcam plugged into my Pi Zero took forever, and when I did get eventually get the stream up and running, it was far too laggy to be useful. Streaming over WiFi and waving my hands in front of the camera showed I had a delay of at least two or three seconds. While I could have possibly optimized it further, I decided to move on and try to find something a little more lightweight.

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