KO
|
EN
gitlite — search
Search
#python
#java
#python3
#arduino
#golang
#machine-learning
#rust
#html
#flask
#javascript
#seismology
#nodejs
ChromaTune
★ 11
Open GitHub ↗
Musical quality visualizer
Download README (.md)
Explore Similar Repositories
orientacoes
:
Um repositório com trabalhos de orientandos já concluídos
MLKit-in-actions
:
ML Kit in actions
dougscore
:
No description available.
gin-throttle
:
gin-throttle is a rate limiter for Gin framework.
copy-bibtex-to-clipboard
:
A Chrome extension that boost your paper writing (especially the literature review part).
// repository documentation
Was this content helpful?
★ 0
(0 ratings)
Select Rating:
★
★
★
★
★
Submit Feedback
Recent Feedback
×
Download README
Do you want to download the
README.md
file for
ChromaTune
?
Download (.md)
The goal of this project is to visualize musical qualities of songs in a playlist in a 3 dimensional space. The most readily quantifiable qualities used here are valence (emotional tone), energy level, and composition (e.g. acousticness). The colorsphere is a visual model with 3 dimensions of visual information (hue, saturation, and lightness), on to which the musical qualities can be mapped. Here valence is represented by hue, energy level by saturation, and composition by lightness.  The musical qualities are obtained from the Echo Nest/Spotify API, and plotted with Dash by Plot.ly. The API's audio features endpoint returns scores for many valuables tags of a track, including: danceability, energy, key, loudness, mode, speechiness, acousticness, instrumentalness, liveness, valence, tempo and time signature. Special thanks to <a href="https://github.com/mari-linhares/spotify-flask">Marianne Linhares</a> for work developing towards a Flask interface for the Spotify API.