Visualizing various aspects of music: CQT, channel differences, spectrums, waves, power, and volumes.
- Download this repository and save it to your machine (e.g. ~/code/Music-Visualizer)
- Install FFmpeg on your machine, if it is not already installed.
- Take a look at all the available options
python Music-Visualizer -h
- Single file
python Music-Visualizer -i music.mp3
With custom output dir:python Music-Visualizer -i full/path/to/the/music.m4a
With custom ffmpeg:python Music-Visualizer -i music.wav -o abs/path/to/the/folder
python Music-Visualizer -i music.wav -ff ~/ffmpeg/bin/ffmpeg.exe
- Multiple files
python Music-Visualizer -i folder/of/music
- Using GPU
- AMD:
python Music-Visualizer -i folder/of/music -g a
- NVIDIA:
python Music-Visualizer -i folder/of/music -g n
python Music-Visualizer -i folder/of/music -g n -q 0
- AMD:
- 60 frames per second
python Music-Visualizer -i music.m4a -r 60
- custom title font:
- Linux:
python Music-Visualizer -i music.m4a -tf ~/.fonts/Arial.ttf
- Windows:
python Music-Visualizer -i music.m4a -tf C\:/Windows/Fonts/Arial.ttf
- MacOS:
python Music-Visualizer -i music.m4a -tf /Library/Fonts/Arial.ttf
- Linux:
- color scheme:
python Music-Visualizer -i music.m4a -pc #fafbfa -wcl #3280c9 -wcr #32c958 -vc #ee2020
- The only resolution option available is HD (1280x720)
- if you encounter this error message
Option 'rate' not found
, search for "#BUG" inmain/main.py
and follow the written instructions - if
--vol_color
showing wrong color, check the comments near the end of the filemain/arg_parser.py
This project is licensed under the MIT license.