Comments (2)
Also dependencies could be simplified. Considering that ideally all audio analysis tools of Audio Commons could be unified in a single tool, it would be good that they had similar dependencies.
In https://github.com/AudioCommons/ac-audio-extractor he have included a single audio extractor for musical properties of music samples which in the future could be extended to incorporate all annotation tools. In this repo we provide a Docker image to simplify the problems with dependencies. This docker image already has Essentia bundled in it (and the python bindings). A way to simplify the current timbral models would be to use essentia
for loading audio (instead of soundfile
) and for onset detection (instead of librosa
). In this way it would be easier to bundle all tools in a single container.
Nevertheless it should be first tested if the obtained results are the same (or very similar) after these change of dependencies.
Audio files can be loaded in essentia using one of its loaders, for example:
from essentia.standard import *
audio = MonoLoader(filename = filename)()
Onsets can be computed using the OnsetDetection
and Onsets
algorithm as shown in this example: https://github.com/MTG/essentia/blob/master/src/examples/tutorial/example_onsetdetection.py.
from timbral_models.
I've added text in the README about dependencies and how they can be installed.
In a future update, the code will be restructured so that it can be downloaded with pip install
. This will take care of all dependencies and help with dissemination.
I will also look into replacing the librosa library with essentia after the deliverable is finished; however, I'm concerned that since there isn't a pip install version, this may make the dissemination harder.
from timbral_models.
Related Issues (8)
- features meaning
- Timbral_Warmth.py:217: RuntimeWarning: divide by zero encountered in log10
- [line 253:] segment returns a empty list when a sound file has too short attack time. HOT 3
- slice indices must be integers or None or have an __index__ method [in timbral_brightness and timbral_hardness] HOT 2
- name 'audio_stimuli_name' is not defined HOT 1
- Missing dependency on the documentation: pyfilterbank HOT 1
- all_hp_centroid instead of all_hp_centroid_tpower in Timbral_Brightness.py HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from timbral_models.