FreeCAD Debugging

November 16, 2020 by Al Williams 20 Comments

Powerful software programs often have macro programming languages that you can use, and if you know how to program, you probably appreciate them. However, sometimes the program’s built-in debugging facilities are lacking or even nonexistent If it were just the language, that wouldn’t be such a problem, but you can’t just grab a, for example, VBA macro from Microsoft Word and run it in a normal Basic interpreter. Your program will depend on all sorts of facilities provided by Word and its supporting libraries. [CrazyRobMiles] was frustrated with trying to debug Python running inside FreeCAD, so he decided to do something about it.

[Rob’s] simple library, FakeFreeCad, gives enough support that you can run a FreeCAD script in your normal Python development environment. It only provides a rude view of what you are drawing, but it lets you explore the flow of the macro, examine variables, and more.

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Micropython On Microcontrollers

November 14, 2020 by Bryan Cockfield 54 Comments

There are plenty of small microcontrollers available for all kinds of tasks, each one with its unique set of features and capabilities. However, not all of us want to spend time mucking about in C or assembly to learn the intricacies of each different chip. If you prefer the higher planes of Python instead, it’s not impossible to import Python on even the smallest of microcontrollers thanks to MicroPython, which [Rob] shows us in this project based on the ESP32.

[Rob] has been working on a small robot called Marty which uses an ESP32 as its brain, so the small microcontroller is already tasked with WiFi/Bluetooth communications and driving the motors in the robot. Part of the problem of getting Python to run on a platform like this is that MicroPython is designed to be essentially the only thing running on the device at any one point, but since the ESP32 is more powerful than the minimum requirements for MicroPython he wanted to see if he could run more than just Python code. He eventually settled on a “bottum-up” approach to build a library for the platform, rather than implementing MicroPython directly as a firmware image for the ESP32.

The blog post is an interesting take on running Python code on a small platform, and goes into some details with the shortcomings of MicroPython itself which [Rob] ended up working around for this project. He’s also released the source code for his work on his GitHub page. Of course, for a different approach to running Python and C on the same small processor, there are some libraries that accomplish that as well.

Homebrew Slide Rule Gets Back To Mathematical Basics

November 11, 2020 by Dan Maloney 49 Comments

In the grand scheme of things, it really wasn’t all that long ago that a slide rule was part of an engineer’s every day equipment. Long before electronic calculators came along, a couple of sticks of wood inscribed with accurate scales was all it took to do everything from simple multiplication to logarithms and trig functions.

While finding a slide rule these days isn’t impossible, it’s still not exactly easy, and buying one off the shelf isn’t as fun or as instructive as building one yourself. [JavierL90]’s slide rule build started, ironically enough, on the computer, with a Python program designed to graphically plot the various scales needed for the fixed sections of the slide rules (the “stators”) and the moving bit (the “slide”). His first throught was to laser-engrave the scales, but the route of printing them onto self-adhesive vinyl stock proved to be easier.

With the scale squared away, work turned to the mechanism itself. He chose walnut for the wood, aluminum for the brackets, and a 3D-printed frame holding a thin acrylic window for the sliding cursor. The woodworking is simple but well-done, as is the metalwork. We especially like the method used to create the cursor line — a simple line scored into the acrylic with a razor, which was then filled with red inks. The assembled slide rule is a thing of beauty, looking for all the world like a commercial model, especially when decked out with its custom faux leather carry case.

We have to admit that the use of a slide rule is a life skill that passed us by, but seeing this puts us in the mood for another try. We might have to start really, really simple and work up from there.

Learning SDR And DSP Hack Chat

November 9, 2020 by Dan Maloney No comments

Join us on Wednesday, November 11th at noon Pacific for Learning SDR and DSP Hack Chat with Marc Lichtman!

“Revolution” is a term thrown about with a lot less care than it probably should be, especially in fields like electronics. It’s understandable, though — the changes to society that have resulted from the “Transistor Revolution” or the “PC Revolution” or more recently, the “AI Revolution” have been transformative, often for good and sometimes for ill. The common thread, though, is that once these revolutions came about, nothing was ever the same afterward.

Such is the case with software-defined radio (SDR) and digital signal processing (DSP). These two related fields may not seem as transformative as some of the other electronic revolutions, but when you think about it, they really have transformed the world of radio communications. SDR means that complex radio transmitters and receivers, no longer have to be implemented strictly in hardware as a collection of filters, mixers, detectors, and amplifiers; instead, they can be reduced to a series of algorithms running on a computer.

Teamed with DSP, SDR has resulted in massive shifts in the RF field, with powerful, high-bandwidth radio links being built into devices almost as an afterthought. But the concepts can be difficult to wrap one’s head around, at least when digging beyond the basics and really trying to learn how SDR and DSP work. Thankfully, Dr. Marc Lichtman, an Adjunct Professor at the University of Maryland, literally wrote the book on the subject. “PySDR: A Guide to SDR and DSP using Python” is a fantastic introduction to SDR and DSP that’s geared toward those looking to learn how to put SDR and DSP to work in practical systems. Dr. Lichtman will stop by the Hack Chat to talk about his textbook, to answer your questions on how best to learn about SDR and DSP, and to discuss what the next steps are once you conquer the basics.

Our Hack Chats are live community events in the Hackaday.io Hack Chat group messaging. This week we’ll be sitting down on Wednesday, November 11 at 12:00 PM Pacific time. If time zones baffle you as much as us, we have a handy time zone converter.

Click that speech bubble to the right, and you’ll be taken directly to the Hack Chat group on Hackaday.io. You don’t have to wait until Wednesday; join whenever you want and you can see what the community is talking about.

[Banner image credit: Dsimic, CC BY-SA 4.0, via Wikimedia Commons]

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Robots Can Finally Answer, Are You Talking To Me?

November 8, 2020 by Matthew Carlson 25 Comments

Voice Assistants, love them, or hate them, are becoming more and more commonplace. One problem for voice assistants is the situation of multiple devices listening in the same place. When a command is given, which device should answer? Researchers at CMU’s Future Interfaces Group [Karan Ahuja], [Andy Kong], [Mayank Goel], and [Chris Harrison] have an answer; smart assistants should try to infer if the user is facing the device they want to talk to. They call it direction-of-voice or DoV.

Currently, smart assistants use a simple race to see who heard it first. The reasoning is that the device you are closest to will likely hear it first. However, in situations with echos or when you’re equidistant from multiple devices, the outcome can seem arbitrary to a user.

The implementation of DoV uses an Extra-Trees Classifier from the python sklearn toolkit. Several other machine learning algorithms were considered, but ultimately efficiency won out and Extra-Trees was selected. Another interesting facet of the research was determining what facing really means. The team had humans ‘listeners’ stand in for smart assistants. A ‘talker’ would speak the key phrase while the ‘listener’ determined if the talker was facing them or not. Based on their definition of facing, the system can determine if someone is facing the device with 90% accuracy that rises to 93% with per-room calibration.

Their algorithm as well as the data they collected has been open-sourced on GitHub. Perhaps when you’re building your own voice assistant, you can incorporate DoV to improve wake-word accuracy.

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E-Paper Weather Display Is A Great Base To Build From

November 3, 2020 by Tom Nardi 26 Comments

As e-paper modules have become more affordable, we’ve started to see them pop up more and more in hacker projects. It used to be that you had to force a second-hand Kindle to do your bidding, but now you can buy just the screen itself complete with a header to plug right into your Raspberry Pi. It will still cost you as much as a used Kindle…but at least it comes with some documentation and there are Python libraries to talk to it.

But where to start? If you need some inspiration, and perhaps a little source code, this very slick weather display put together by [James Howard] is a great as baseline. Not that it really needs any additional refinement, as we think it already looks gorgeous. But rather than starting from scratch for your own project, it would be much easier to graft some additional functionality onto his code.

A lot of that has to do with how concise and well commented his code is. We’ve seen enough of these projects to know the kind of spaghetti that’s often running on the backend, but there’s none of that here. [James] assembles the display using the powerful Pillow graphics library, which lets you draw primitives and drop in text and icons with just a couple lines of code.

Once all the data is plugged in, the entire screen is saved as an image file which is then opened up on the e-paper display. Even if you aren’t a Python expert, you should be able to understand what’s happening and how to bend it to your will.

We’ve always had high hopes for electronic paper, and it seems the technology might finally be hitting critical mass. While it’s still a bit expensive, we’ve started seeing it pop up in unexpected places to great effect. Hopefully projects like this one will inspire others to take the B&W plunge.

Computer Vision Maps Christmas Lights

November 3, 2020 by Bryan Cockfield 27 Comments

There’s a small but dedicated group of folks out there who spend all year planning their Christmas decorations. These aren’t simple lawn ornaments or displays, either, but have evolved into complex lightning performances that require quite a bit of computer control. For some things, hooking up a relay to a microcontroller can get the job done, but [Andy] has turned to computer vision to solve some of the more time-consuming aspects of these displays.

Specifically, [Andy] has a long string of programmable RGB LED lights to wrap around a Christmas tree, but didn’t want to spend time manually mapping out each light’s location. So he used OpenCV to register the locations of the LEDs from three different camera angles, and then used a Python script to calculate their position in the 3D space. This means that he will easily be able to take the LEDs down at the end of the holidays and string them back up next year without having to do the tedious manual mapping ever again.

While [Andy] notes that he may have spent more time writing the software to map out the LEDs than manually doing it himself, but year-after-year it may save him a lot of time and effort, not to mention the benefits of a challenge like writing this software in the first place. If you want to get started on your own display this year, all you really need is some lights and a MIDI controller.