TimeSide : audio processing framework for the web

TimeSide is a python framework enabling low and high level audio analysis, imaging, transcoding, streaming and labelling. Its high-level API is designed to enable complex processing on very large datasets of any audio or video assets with a plug-in architecture, a secure scalable backend and an extensible dynamic frontend.

Use cases

Scaled audio computing
Pseudo-realtime streaming
Plugin prototyping
Audio metadata management and visualization
Automatic segmentation and labelling synchronized with audio events.

Goals

Do asynchronous and fast audio processing with Python,
Decode audio frames from any audio or video media format into numpy arrays,
Analyze audio content with some state-of-the-art audio feature extraction libraries like Aubio, Yaafe and VAMP as well as some pure python processors
Visualize sounds with various fancy waveforms, spectrograms and other cool graphers,
Transcode audio data in various media formats and stream them through web apps,
Serialize feature analysis data through various portable formats,
Playback and interact on demand through a smart high-level HTML5 extensible player,
Index, tag and annotate audio archives with semantic metadata (see Telemeta which embed TimeSide).

Funding and support

To fund the project and continue our fast development process, we need your explicit support. So if you use TimeSide in production or even in development, please let us know:

star or fork the project on GitHub
tweet something to @parisson_studio or @yomguy
drop us an email <[email protected]>

Thanks for your help!

Architecture

The streaming architecture of TimeSide relies on 2 main parts: a processing engine including various plugin processors written in pure Python and a user interface providing some web based visualization and playback tools in pure HTML5.

Dive in

Let's produce a really simple audio analysis of an audio file. First, list all available plugins:

>>> import timeside.core
>>> timeside.core.list_processors()

Define some processors:

>>> from timeside.core import get_processor
>>> from timeside.core.tools.test_samples import samples
>>> wavfile = samples['sweep.wav']
>>> decoder  =  get_processor('file_decoder')(wavfile)
>>> grapher  =  get_processor('waveform_simple')()
>>> analyzer =  get_processor('level')()
>>> encoder  =  get_processor('vorbis_encoder')('sweep.ogg')

Then run the magic pipeline:

>>> (decoder | grapher | analyzer | encoder).run()

Render the grapher results:

>>> grapher.render(output='waveform.png')

Show the analyzer results:

Level: {'level.max': AnalyzerResult(...)}

So, in only one pass, the audio file has been decoded, analyzed, graphed and transcoded.

For more extensive examples, please see the full documentation.

News

0.8

Analyzer Result : fix and improve some results containers and add export to Elan files.
Add Docker support for easy installation of TimeSide across any OS platform
Start the development of a web service and API (experimental) with docker-compose support based on Django REST Framework, Celery, Angular and WavesJS.
Various bugfixes

0.7.1

fix django version to 1.6.10 (sync with Telemeta 1.5)

0.7

Code refactoring:
- Create a new module timeside.plugins and move processors therein: timeside.plugins.decoder,analyzer, timeside.plugins.encoder, timeside.plugins.fx
- WARNING: to properly manage the namespace packages structure, the TimeSide main module is now timeside.core and code should now be initialized with import timeside.core
- timeside.plugins is now a namespace package enabling external plugins to be automatically plugged into TimeSide (see for example timeside-diadems). This now makes TimeSide a real plugin host, yeah!
- A dummy timeside plugin will soon be provided for easy development start.
Move all analyzers developped by the partners of the Diadems project to a new repository: timeside-diadems
Many fixes for a better processing by Travis-CI
Add a dox file to test the docker building continously on various distributions

For older news, please visit: https://github.com/Parisson/TimeSide/blob/master/NEWS.rst

API / Documentation

General : http://files.parisson.com/timeside/doc/
Tutorial : http://files.parisson.com/timeside/doc/tutorial/index.html
API : http://files.parisson.com/timeside/doc/api/index.html
Publications : https://github.com/Parisson/Telemeta-doc
Player / UI : https://github.com/Parisson/TimeSide/wiki/Ui-Guide (see also "Web player")
Notebooks : http://nbviewer.ipython.org/github/thomasfillon/Timeside-demos/tree/master/
Example : http://archives.crem-cnrs.fr/archives/items/CNRSMH_E_2004_017_001_01/

Install

Any platform - with Docker

Thanks to Docker, TimeSide is now fully available as a docker image ready to work. The image includes all the necessary applications, modules and volumes to start your project in a few minutes.

First install Docker then just pull our latest master image:

docker pull parisson/timeside:latest

and then run the docker container as an interactive shell:

docker run -it --name timeside -v $(pwd):/home/timeside parisson/timeside:latest /bin/bash

In this shell, you have access to python and ipython to play with TimeSide. And you have access to the current working directory inside the container in the /home/timeside directory.

Debian, Ubuntu

For Debian based distributions, we provide a safe public repository giving all additional binary dependencies that are not included in Debian yet. They ensure TimeSide to be installed natively although the setup is not trivial. Please follow the instructions on this page and the old NOT up to date install howto.

Advanced (and experimental) usage

TimeSide now includes an experimental web service and API. To test this new environnement please install Git and docker-compose, then copy these commands in a terminal and hit ENTER:

git clone https://github.com/Parisson/TimeSide.git
cd TimeSide
docker-compose up

That's it! You can now browse the TimeSide API: http://localhost:8000/api/

and the admin: http://localhost:8000/admin (admin/admin)

To process some data by hand, you can also start a python shell session into the sandbox:

docker-compose run app python examples/sandbox/manage.py shell

To build your own audio project on top of TimeSide, just pull our latest master image:

docker pull parisson/timeside:latest

More infos about the TimeSide docker image: https://registry.hub.docker.com/u/parisson/timeside/

Deploying

Our docker composition already bundles some powerfull containers and bleeding edge frameworks like: Nginx, MySQL, RabbitMQ, Celery, Python and Django. It thus provides a safe way to deploy your project from the development stage to a massive production setup very easily.

WARNING: Before any serious production usecase, you must modify all the passwords and secret keys in the configuration files of the sandbox.

Scaling

Thanks to Celery, each TimeSide worker of the server will process each task asynchronously over independant threads so that you can load all the cores of your CPU.

To scale it up through your cluster, Docker provides some nice tools for orchestrating it very easily: Machine and Swarm.

User Interfaces

Python

Of course all the TimeSide are available in our beloved python envionment. As IPython is really great for discovering objects with completion, writing notebooks, we strongly advise to install and use it:

sudo apt-get install ipython
ipython
>>> import timeside.core

Shell

Of course, TimeSide can be used in any python environment. But, a shell script is also provided to enable preset based and recursive processing through your command line interface:

timeside-launch -h
Usage: scripts/timeside-launch [options] -c file.conf file1.wav [file2.wav ...]
 help: scripts/timeside-launch -h

Options:
 -h, --help            show this help message and exit
 -v, --verbose         be verbose
 -q, --quiet           be quiet
 -C <config_file>, --conf=<config_file>
                       configuration file
 -s <samplerate>, --samplerate=<samplerate>
                       samplerate at which to run the pipeline
 -c <channels>, --channels=<channels>
                       number of channels to run the pipeline with
 -b <blocksize>, --blocksize=<blocksize>
                       blocksize at which to run the pipeline
 -a <analyzers>, --analyzers=<analyzers>
                       analyzers in the pipeline
 -g <graphers>, --graphers=<graphers>
                       graphers in the pipeline
 -e <encoders>, --encoders=<encoders>
                       encoders in the pipeline
 -R <formats>, --results-formats=<formats>
                       list of results output formats for the analyzers
                       results
 -I <formats>, --images-formats=<formats>
                       list of graph output formats for the analyzers results
 -o <outputdir>, --ouput-directory=<outputdir>
                       output directory

Find some preset examples in examples/presets/

Web player

TimeSide comes with a smart and pure HTML5 audio player.

Features:

embed it in any audio web application
stream, playback and download various audio formats on the fly
synchronize sound with text, bitmap and vectorial events
seek through various semantic, analytic and time synced data
fully skinnable with CSS style

Examples of the player embeded in the Telemeta open web audio CMS:

Development documentation:

https://github.com/Parisson/TimeSide/wiki/Ui-Guide

TODO list:

zoom
layers

Web server

An EXPERIMENTAL web server based on Django has been added to the package from version 0.5.5. The goal is to provide a full REST API to TimeSide to enable new kinds of audio processing web services.

A sandbox is provided in timeside/server/sandbox and you can initialize it and test it like this:

cd examples/sandbox
./manage.py syncdb
./manage.py migrate
./manage.py runserver

and browse http://localhost:8000/api/

At the moment, this server is NOT connected to the player using TimeSide alone. Please use Telemeta.

Development

The easiest way to develop with TimeSide framework is to use our DevBox

Docker (recommended)

Docker is a great tool for developing and deploying processing environments. We provide a docker image which contains TimeSide and all the necessary packages (nginx, uwsgi, etc) to run it either in development or in production stages.

First, install Docker: https://docs.docker.com/installation/

Then, simply pull the image and run it:

docker pull parisson/timeside
docker run -p 9000:80 parisson/timeside

You can now browse the TimeSide API: http://localhost:9000/api/

or get a shell session:

docker run -ti parisson/timeside bash

To start a new development, it is advised to checkout the dev branch in the container:

cd /opt/TimeSide
git checkout dev

or get our latest-dev image:

docker pull parisson/timeside:latest-dev

More infos: https://registry.hub.docker.com/u/parisson/timeside/

Sponsors and Partners

Parisson
CNRS (National Center of Science Research, France)
Huma-Num (big data equipment for digital humanities, ex TGE Adonis)
CREM (french National Center of Ethomusicology Research, France)
Université Pierre et Marie Curie (UPMC Paris, France)
ANR (CONTINT 2012 project : DIADEMS)
MNHN : Museum National d'Histoire Naturelle (Paris, France)

Related projects

Telemeta : open web audio platform
Sound archives of the CNRS, CREM and the "Musée de l'Homme" in Paris, France.
The DIADEMS project sponsored by the ANR.

Copyrights

License

TimeSide is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.

TimeSide is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

See LICENSE for more details.

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