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Realtime_PyAudio_FFT

A simple package to do realtime audio analysis in native Python, using PyAudio and Numpy to extract and visualize FFT features from a live audio stream.

Demo Video

The basic pipeline:

  • Starts a stream_reader that pulls live audio data from any source using PyAudio (soundcard, microphone, ...)
  • Reads data from this stream many times per second (eg 1000 updates per second) and stores that data in a fifo buffer
  • When triggered by .get_audio_features(), the stream_analyzer, applies a Fast-Fourier-Transform to the most recent audio window in the buffer
  • When visualize is enabled, the visualizer displays these FFT features in realtime using a PyGame GUI (I made two display modes: 2D and 3D)

Requirements:

pip install -r requirements.txt

You also might have to sudo apt install libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 (tested on Ubuntu)

I developped this code on my local machine --> it has not been properly tested on other setups.. If something doesn't work, please first try to fix it yourself and post an issue/solution when appropriate!

  • Tested on Ubuntu 18.04
  • Other platforms like Mac/Windows should work if PyGame can find your display and Python finds your audio card (these can be tricky with WSL)
  • For Mac OSX (tested on Catalina 10.15.4), please make sure you run with Python downloaded from Python.org (pygame doesn't work well with the default/Homebrew Python)

Tested with:

  • Python 3.6.3
  • pygame --> Version: 1.9.6 &
  • pyaudio --> Version: 0.2.11
  • scipy --> Version: 1.4.1

Alternatively to pyaudio, you can use sounddevice which might be more compatible with Windows/Mac

  • just run python3 -m pip install sounddevice
  • Tested on Ubuntu 18.04 with sounddevice version 0.3.15
  • The code to switch between the two sound interfaces is in the __init__ function of the Stream_Analyzer class

Usage:

just run python run_FFT_analyzer.py and play a sound on your machine!

  • I have personally learned A LOT about sound by watching this realtime visualization while listening to music
  • You can run the stream_analyzer in headless mode and use the FFT features in any Python Application that requires live musical features

Teaser image

ToDo:

  • Implement realtime beat detection / melody extraction on top of FFT features (eg using Harmonic/Percussive decomposition)
  • The pygame.transform operations sometimes cause weird visual artifacts (boxes) for some resolution settings --> fix??
  • Remove the matplotlib dependency since it's only needed for the colormap of the vis..
  • Slow bars decay speed currently depends on how often .get_audio_features() is called --> fix