https://github.com/zak-45/wledaudiosyncrtmood
Real Time Music mood detection. Generating colors based on. Send data to OSC server.
https://github.com/zak-45/wledaudiosyncrtmood
mood music osc real-time
Last synced: 15 days ago
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Real Time Music mood detection. Generating colors based on. Send data to OSC server.
- Host: GitHub
- URL: https://github.com/zak-45/wledaudiosyncrtmood
- Owner: zak-45
- License: mit
- Created: 2023-10-17T14:35:25.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-23T09:37:25.000Z (over 1 year ago)
- Last Synced: 2025-03-24T22:51:13.039Z (about 1 month ago)
- Topics: mood, music, osc, real-time
- Language: Python
- Homepage:
- Size: 6.69 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# WLEDAudioSyncRTMood
Real Time Music mood detection. Generating colors based on. Send data to OSC server.
---
[](https://github.com/zak-45/WLEDAudioSyncRTMood/actions/workflows/manual.yml)
---
This python script capture sound and - when music is detected - it estimates the underlying mood (emotion). Based on that it generates a respective color. If available, it can even set your Yeelight Bulb color (again based on the detected musical mood).
See this repo : https://github.com/tyiannak/color_your_music_mood for more informations. Thanks to @tyiannak for this great work.
Additional to that, some features has been added and the main one is to send datas & color to OSC server.
Just enter :
```
python main.py -h
```
to see all options.
```
usage: main.py [-h] [-d DEVICES [DEVICES ...]] [-cs [2-20]] [-bs {0.25,0.5,0.75,1}]
[-fs {4000,8000,16000,32000,44100}] [-sc {Y,N}] [-srv SERVER] [-p [1-65536]] [-s {Y,N}] [-v {Y,N}]
[-r [0-3600]]
Real time audio mood analysis sent via OSC
optional arguments:
-h, --help show this help message and exit
-d DEVICES [DEVICES ...], --devices DEVICES [DEVICES ...]
IPs to Yeelight device(s) to use
-cs [2-20], --capture [2-20]
Number of second to capture, default to 5
-bs {0.25,0.5,0.75,1}, --blocksize {0.25,0.5,0.75,1}
Recording block size, default to 1
-fs {4000,8000,16000,32000,44100}, --samplingrate {4000,8000,16000,32000,44100}
Sample rate, default to 8KHz
-sc {Y,N}, --screen {Y,N}
display color window, default to N
-srv SERVER, --server SERVER
IP of the OSC server, default to 127.0.0.1
-p [1-65536], --port [1-65536]
port number, default to 12000
-s {Y,N}, --send {Y,N}
send to OSC, default to Y
-v {Y,N}, --verbose {Y,N}
display verbose informations, default to N
-r [0-3600], --restart [0-3600]
Number of x * 5s before restarting prog , 0 for never.. default to 0'
```
## Install
Windows / Mac / Linux :
Go to : https://github.com/zak-45/WLEDAudioSyncRTMood/releases
```
Download WLEDAudioSyncRTMood file for your OS.
This is a Portable application (no need to be installed) with Python v3.x.x and all necessary modules,
so you can have it running in few minutes.
```
Manual (all OS) :
```
you need python 3.8.x (other version should work but need to be investigated)
For linux :
sudo apt-get update
sudo apt-get install libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0
sudo apt-get install ffmpeg
For macOs :
brew update
brew install portaudio
Create a folder and put this repository on it.
install all modules with ** (required) by using pip command.
you can do : pip install -r requirements.txt
```
## Run it
For all WLEDAudioSyncRTMood portable version:
```
Put your donwloaded file on a nice folder (stay organized) and ...
just run it !
```
Windows example:
For Manual install:
Any OS:
```
python main.py -v Y -sc Y
```
## Demo
https://github.com/zak-45/WLEDAudioSyncRTMood/assets/121941293/75f0d9dd-4aa1-4d72-91fd-24a6bf756cdd
More on Youtube : https://youtu.be/x5OvCFWevbo?feature=shared
### Python modules
This is the name and version of python modules found on the Windows portable version
```
colorama 0.4.6
contourpy 1.1.1
coverage 5.5
cycler 0.12.1
deprecation 2.1.0
enum-compat 0.0.3
** eyed3 0.9.7
filetype 1.2.0
fonttools 4.43.1
future 0.18.3
importlib-resources 6.1.0
** joblib 1.2.0
kiwisolver 1.4.5
** matplotlib 3.5.0
msvc-runtime 14.28.29910
** numpy 1.19.0
** opencv-python 4.8.1.78
packaging 23.2
Pillow 10.1.0
pip 23.3
** plotly 5.17.0
** PyAudio 0.2.13
** pyAudioAnalysis 0.3.6
** pydub 0.25.1
** pyparsing 3.1.1
pypiwin32 223
python-dateutil 2.8.2
** python-osc 1.8.3
pywin32 306
** scikit-learn 0.23.2
** scipy 1.5.2
setuptools 68.2.2
setuptools-scm 8.0.4
six 1.16.0
sqlite-bro 0.9.1
tenacity 8.2.3
threadpoolctl 3.2.0
toml 0.10.2
tomli 2.0.1
** tqdm 4.66.1
typing_extensions 4.8.0
```
### Infos:
Trained models scikit-learn==0.23.2
A 5 seconds delay is present, necessary time to capture and estimate mood. This is by default but can be changed with option -cs.
Confirmed to work with python 3.8.9, other versions need deep analysis.
Compiled versions made with [Nuitka](https://github.com/Nuitka/Nuitka)
```
First time you run WLEDAudioSyncRTMood-{OS}, this will create folder ./WLEDAudioSyncRTMood and extract all files on it.
To save some space and time, you can then delete WLEDAudioSyncRTMood-* and run the app from created folder.
```