Raspberry Pi Spectrum Analyzer, w/ Python & RGB LED Strip
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- Опубліковано 14 жов 2024
- music: / 320036531622 Documentation: www.instructabl... Realtime FFT of MP3s in Python code, levels sent to RGB LED strip from adafruit. Some people call this a Graphic Equalizer, too. Music by Sharkara, on album Lights.
Dang it. You beat me to this! I had this as an idea for months (but I bought the wrong kind of RGB's. Needed Common Anode, not common Cathode. )
Oh well. That open source brilliance though. Good job on the project!
thanks! myself and the LightShow Pi community would love any improvements you can make. The strip I used is pretty expensive.
is there a version of your code for regular RGB led strips that do not have addressing or what would I need to modify? Also is there a way to connect this into spotify?
pilotkid2011 you need adressable leds, they have a small chip between each led which makes them controllable. to modify them you eould need to attach a small chip to every led which would cost you more time and money (ubless you are a chinese working in a led factory. you could connect it to spotify as it uses whatever music or sound it hears, i havent looked into the code but if you run it from your pc it should be possible.
Is It possible if I use SMD3528 RGB LED Strip
? Please Reply ASAP.. badly needed
I can't find this music anywhere!
Nice that looks very good
does this work with WS2812 3pol adressable RGB ?
How did you index that number of lights when the output of a Rasbery Pi is less than that? Thats something I have been wondering in building my spectrum analyzer.
The entire LED strip is controlled by two pins. Each LED is attached to an addressable chip in the strip.
This looks like as nice Pi Project to try :-)
still trying to find the music
this is soooooooooooooooooooooo cool, Pi 2 ... it is possible to do it with it?>
Please link to the music! I can't find it :((
link added to desc.
Cool
why do 2048 points if you only use 5 strips? do 64 points and save on energy . . . .
there's almost more time in getting the audio data into a numpy array than than actually doing the fft, so decreasing the fft size doesn't necessarily speed it up, since you end up doing more prep work. You're right that 2048 is unnecessary. Either changing the fft size or just doing 5 band-pass filters might be faster.