LED Spectrum Visualizer Driven By Raspberry Pi

Back in the 1980s, spectrum displays on audio equipment were absolutely must have, and the aesthetic came to define the era. This lingered on through the 1990s, and remains a cool look even to this day. [Arduino Guy] decided to put together such a display using a Raspberry Pi and a large LED display.

The LED display in question is of the 64×64 RGB type, available from Aliexpress and other electronics suppliers online. To run the display, an Adafruit RGB Matrix Hat is used with the Raspberry Pi 3B, which makes driving the panel a cinch. The visual effect is run via a Python script, which plays a wave file and produces the spectrum graphics via a Fast Fourier Transform.

While the code isn’t able to act as a general-purpose equalizer display for any content played on the Raspberry Pi, creating such a script could be an entertaining exercise for the reader. Alternatively, the Pi could be hooked up to a microphone to run the display based on ambient room noise. In any case, we’ve seen great projects like this before, such as this laser-based display. Video after the break.

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FPGA Powers Blazingly Fast LED Matrix Audio Visualizer

[Sam Miller], [Sahil Gupta], and [Mashrur Mohiuddin] worked together on a very fast LED matrix display for their final project in ECE 5760 at Cornell University.

Real time!
Real time!

They started, as any good engineering students, by finding a way to make their lives easier. [Sam] had built a 32×32 LED matrix for another class. So, they made three more and ended up with a larger and more impressive 64×64 LED display.

They claim their motivation was the love of music, but we have a suspicion that the true reason was the love all EEs share for unnaturally bright LEDs; just look at any appliance at night and try not be blinded.

The brains of the display is an Altera DE2-115 FPGA board. The code is all pure Verilog. The FFT and LED control are implemented in hardware on the FPGA; none of that Altera core stuff. To generate images and patterns they wrote a series of python scripts. But for us it’s the particle test shown in the video below that really turns our head. This system is capable of tracking and reacting to a lot of different elements on the fly why scanning the display at about 310 FPS. They have tested display scanning at twice that speed but some screen-wrap artifacts need to be worked out before that’s ready for prime time.

The team has promised to upload all the code to GitHub, but it will likely be a while before the success hangover blows over and they can approach the project again. You can view a video interview and samples of the visualizations in the videos after the break.

Thanks to their Professor, [Bruce Land], for submitting the tip! His students are always doing cool things. You can even watch some of his excellent courses online if you like: Here’s one on the AVR micro-controller.

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More 555 Projects To Enjoy

We love all of the projects that are coming out for the 555 design contest, so we thought we would share a couple more that have caught our collective eye.  Have a 555 project of your own? Be sure to share it with us, and keep an eye out for the contest submission dates. Read on for a few of our project picks.

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Music Visualizer (oscilloscope)

musicscopetv

The Music visualizer is actually a second build based on an earlier design[Thanks Roger]. The build was influenced by Zyra’s How to make an oscilloscope out of a television. The hack is quite simple, patch the output of an amplifier into the vertical deflection coils of the CRT. This is a good use for that old TV you may have laying around  but don’t want to recycle it just yet. While on the subject we had covered the Mac SE/30 audio visualizer in 2006. For those looking for something a little more hard core, here is a bit about Homemade cathode ray tubes.

Advanced Beauty Generative Video Art

advbeau

Advanced Beauty is a collection of 18 “sound sculptures” pairing artists and programmers to create a collaborative work visualizing sound. The styles run a broad range from fluid simulations to manipulating cell animation. The demos were built using Processing. While all of these were built using human input, we see potential for them to help improve standard visualizers. Hopefully, to bring out more information about what’s actually being played. Below is just one of the videos in the series. You can find more on Vimeo. Continue reading “Advanced Beauty Generative Video Art”