Computer Vision Extracts Lightning From Footage

Lightning is one of the more mysterious and fascinating phenomenon on the planet. Extremely powerful, but each strike on average only has enough energy to power an incandescent bulb for an hour. The exact mechanism that starts a lightning strike is still not well understood. Yet it happens 45 times per second somewhere on the planet. While we may not gain a deeper scientific appreciation of lightning anytime soon, but we can capture it in various photography thanks to this project which leverages computer vision machine learning to pull out the best frames of lightning.

The project’s creator, [Liam], built this as a tool for stormchasers and photographers so that they can film large amounts of time and not have to go back through their footage manually to pull out the frames with lightning strikes. The project borrows from a similar project, but this one adds Python 3 capabilities and runs on a tiny netbook for more easy field deployment. It uses OpenCV for object recognition, using video files as the source data, and features different modes to recognize different types of lightning.

The software is free and open source, and releases are supported for both Windows and Linux. So far, [Liam] has been able to capture all kinds of electrical atmospheric phenomenon with it including lightning, red sprites, and elves. We don’t see too many projects involving lightning around here, partly because humans can only generate a fraction of the voltage potential needed for the average lightning strike.

No Tool Left Behind With The Help Of Homemade Shadow Boards

Shadowed tool storage — where a tool outline shows at a glance what’s missing from storage — is a really smart way to keep your shop neat. They’re also super important for cases where a tool left behind could be a tragedy. Think, where’s-that-10-mm-socket-while-working-on-a-jet-engine? important. (It’s always the 10-mm socket.)

But just because shadow boards are smart, doesn’t mean they’re easy to make. That’s why [Scott Prince] came up with this semi-automated method for making toolbox shadow boards. The job of tracing around each tool on some sort of suitable material and cutting out the shapes seems straightforward, but the trick comes in organizing the outlines given the space available and the particular collection of tools.

[Scott]’s method starts with capturing images of each individual tool. He used a PiCam and a lightbox housed, strangely enough, in a storage bench; we’d love to hear the full story behind that, but pretty much any digital camera would do for the job. After compensating for distortion with OpenCV, cropping the images, and turning the image into a vector outline of the tool, [Scott] was left with the task of putting the tools into logical groups and laying them out sensibly. After tweaking the tool outlines and adding finger cutouts for easy pickup, [Scott] put his CNC router to work. He chose to use a high-density polyethylene product made by his employer, which looks fantastic, but MDF would work fine too.

We have to admit to a fair degree of toolbox envy now that we’ve seen what shadow boards can do. We’re a bit torn, though — [Zach Friedman]’s Gridfinity storage system has a lot going for it, too.

PyScript: Python In The Web Browser

A chainsaw can make short work of clearing out the back forty. It can also make a good horror movie. So while some people will say we don’t need another tool to allow more malicious scripting in the browser, we also know that, like any tool, you can use it or abuse it. That tool? PyScript, which is, of course, Python in the browser.

The tool is in the early experimental phase, so the project doesn’t suggest using it in a production environment yet. However, if it works well, the promise is not just that you can write browser-based applications in Python — you’ll have a handy way to reuse existing Python code and even be able to run the same code on the browser that currently runs on the server. This has a lot of implications for improved client/server applications, or cases where you want to be able to run against a local backend when disconnected and a remote backend when you do have a connection. Of course, you can interoperate with JavaScript, too.

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Remote Screen Viewer Is Text-Only

Have you been slowly falling down a rabbit hole of Stallman-like paranoia of computers ever since installing Ubuntu for the first time in 2007? Do you now abhor anything with a GUI, including browsers? Do you check your mail with the command line even though you’re behind seven proxies? But, do you still want to play Minecraft? If so, this command-line-only screen viewer might just be the tool to use a GUI without technically using one.

This remote screen viewer is built in Python by [louis-e] and, once installed, allows the client to view the screen of the server even if the client is a text-only console. [louis-e] demonstrates this from within a Windows command prompt. The script polls the server screen and then displays it in the console using the various colors and textures available. As a result, the resolution and refresh rate are both quite low, but it is still functional enough to play Minecraft and do other GUI-based tasks as long as there’s no fine text to read anywhere.

The video below only shows a demonstration of the remote screen viewer, and we can imagine plenty of uses beyond this proof-of concept game demonstration. Installing a desktop environment and window manager is not something strictly necessary for all computers, so this is a functional workaround if you don’t want to waste time and resources installing either of those components. If you’re looking for remote desktop software for a more specific machine, though, take a look at this software which enables remote desktop on antique Macs.

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AI Attempts Converting Python Code To C++

[Alexander] created codex_py2cpp as a way of experimenting with Codex, an AI intended to translate natural language into code. [Alexander] had slightly different ideas, however, and created codex_py2cpp as a way to play with the idea of automagically converting Python into C++. It’s not really intended to create robust code conversions, but as far as experiments go, it’s pretty neat.

The program works by reading a Python script as an input file, setting up a few parameters, then making a request to OpenAI’s Codex API for the conversion. It then attempts to compile the result. If compilation is successful, then hopefully the resulting executable actually works the same way the input file did. If not? Well, learning is fun, too. If you give it a shot, maybe start simple and don’t throw it too many curveballs.

Codex is an interesting idea, and this isn’t the first experiment we’ve seen that plays with the concept of using machine learning in this way. We’ve seen a project that generates Linux commands based on a verbal description, and our own [Maya Posch] took a close look at GitHub Copilot, a project high on promise and concept, but — at least at the time — considerably less so when it came to actual practicality or usefulness.

This Week In Security: IPhone Unpowered, Python Unsandboxed, And Wizard Spider Unmasked

As conspiracy theories go, one of the more plausible is that a cell phone could be running malicious firmware on its baseband processor, and be listening and transmitting data even when powered off. Nowadays, this sort of behavior is called a feature, at least if your phone is made by Apple, with their Find My functionality. Even with the phone off, the Bluetooth chip runs happily in a low-power state, making these features work. The problem is that this chip doesn’t do signed firmware. All it takes is root-level access to the phone’s primary OS to load a potentially malicious firmware image to the Bluetooth chip.

Researchers at TU Darmstadt in Germany demonstrated the approach, writing up a great paper on their work (PDF). There are a few really interesting possibilities this research suggests. The simplest is hijacking Apple’s Find My system to track someone with a powered down phone. The greater danger is that this could be used to keep surveillance malware on a device even through power cycles. Devices tend to be secured reasonably well against attacks from the outside network, and hardly at all from attacks originating on the chips themselves. Unfortunately, since unsigned firmware is a hardware limitation, a security update can’t do much to mitigate this, other than the normal efforts to prevent attackers compromising the OS.
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Network Time Protocol On The ESP32

Network Time Protocol (NTP) is one of the best ways to keep networked computers synchronized to the same time. It’s simple, lightweight, and not only allows computers to maintain a time standard together, but it also allows some computer manufacturers to save some money on hardware costs. The Raspberry Pi is perhaps the most well-known example of a low-cost computer without the extra expense of a real-time clock (RTC). While the Pi sets up NTP essentially automatically, other microcontrollers like the ESP32 don’t, but it is possible to configure them to use this time standard with some work.

For this project the MicroPython implementation for the ESP32 is required. MicroPython is a way of running Python code on microcontrollers or other embedded systems without all of the overhead that Python would normally require. Luckily enough, the NTP libraries are built right in so once MicroPython is running on the ESP32 it’s nearly as easy as calling the library. Of course you will have to make sure there is an internet connection, and then grab the time, sync it to the machine, and then set the timezone.

For a bonus exercise, the project’s creator [Bhavesh] suggests attempting to configure Daylight Savings Time, although this can be a surprisingly difficult problem to solve. In the meantime, there are a few other ways of installing a clock on a microcontroller like this one. An RTC module is an obvious choice, but you can also get incredibly accurate time by using a GPS module as well.