open web audio processing framework
Project description
TimeSide is a set of python components enabling low and high level audio analysis, imaging, transcoding and streaming. Its high-level API is designed to enable complex processing on large datasets of audio and video assets of any format. Its simple plug-in architecture can be adapted to various use cases.
TimeSide also includes a smart interactive HTML5 player which provides various streaming playback functions, formats selectors, fancy audio visualizations, segmentation and semantic labelling synchronized with audio events. It is embeddable in any web application.
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,
Organize, serialize and save 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 <support@parisson.com>
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
To 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(...)}
The encoded OGG file should also be there…
For more extensive examples, please see the full documentation.
News
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
0.6.2
Bugfix release for #63 #64 #68
0.6.1
Fix various minor bugs
Fix docker sandbox
Auto build docker image (https://registry.hub.docker.com/u/parisson/timeside/)
0.6
WARNING! some processor ids have changed. Please see the full list below.
NEW analyzers: IRIT Monopoly (see Processors)
NEW graphers: IRIT Start/Session segmentation
Add extensible buffering thanks to pytables (NEW dependency)
Add typed parameters in processors and server thanks to traits (NEW dependency)
Add a graph model to the pipe thanks to networkx (NEW dependency)
Add test sample generators based on GStreamer
Add a background image option for rendering analyzers
Add on-the-fly filtering decorators
Add a Docker development image and a Dockerfile
Add a Vagrant development box
Update the Debian package installation procedure
Results are now stored in pipe.results as as dictionnary of AnalyzerResults
Update various processors
Prevent duplication of processor in the pipe (i.e. processors sharing the same class and parameters). This also fix #60.
Update of Travis CI scripts https://travis-ci.org/Parisson/TimeSide/
0.5.6
Bugfix release
Fix analyzer instanciation as parent for some graphers
Store analyzer’s results in pipe.results by uuid instead of id (fix #24)
For older news, please visit: https://github.com/Parisson/TimeSide/blob/master/NEWS.rst
Processors
IEncoder
live_encoder : Gstreamer-based Audio Sink
flac_encoder : FLAC encoder based on Gstreamer
aac_encoder : AAC encoder based on Gstreamer
mp3_encoder : MP3 encoder based on Gstreamer
vorbis_encoder : OGG Vorbis encoder based on Gstreamer
opus_encoder : Opus encoder based on Gstreamer
wav_encoder : WAV encoder based on Gstreamer
webm_encoder : WebM encoder based on Gstreamer
IDecoder
array_decoder : Decoder taking Numpy array as input
file_decoder : File Decoder based on Gstreamer
live_decoder : Live source Decoder based on Gstreamer
IGrapher
grapher_aubio_pitch : Image representing Aubio Pitch
grapher_onset_detection_function : Image representing Onset detection function
grapher_waveform : Image representing Waveform from Analyzer
spectrogram_log : Logarithmic scaled spectrogram (level vs. frequency vs. time).
spectrogram_lin : Linear scaled spectrogram (level vs. frequency vs. time).
waveform_simple : Simple monochrome waveform image.
waveform_centroid : Waveform where peaks are colored relatively to the spectral centroids of each frame buffer.
waveform_contour_black : Black amplitude contour waveform.
waveform_contour_white : an white amplitude contour wavform.
waveform_transparent : Transparent waveform.
IAnalyzer
mean_dc_shift : Mean DC shift analyzer
level : Audio level analyzer
aubio_melenergy : Aubio Mel Energy analyzer
aubio_mfcc : Aubio MFCC analyzer
aubio_pitch : Aubio Pitch estimation analyzer
aubio_specdesc : Aubio Spectral Descriptors collection analyzer
aubio_temporal : Aubio Temporal analyzer
yaafe : Yaafe feature extraction library interface analyzer
spectrogram_analyzer : Spectrogram image builder with an extensible buffer based on tables
onset_detection_function : Onset Detection Function analyzer
spectrogram_analyzer_buffer : Spectrogram image builder with an extensible buffer based on tables
waveform_analyzer : Waveform analyzer
IEffect
fx_gain : Gain effect processor
API / Documentation
General : http://files.parisson.com/timeside/doc/
Tutorial : http://files.parisson.com/timeside/doc/tutorial/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
The TimeSide engine is intended to work on all Linux and Unix like platforms. It depends on several other python modules and compiled libraries like GStreamer.
Debian, Ubuntu
For Debian based distributions, we provide a safe repository giving additional dependencies that are not included in Debian yet. Please follow the instructions on this page.
Other Linux distributions
On other Linux platforms, you need to install all dependencies listed in Dependencies finding all equivalent package names for your distribution.
Then, use pip:
sudo pip install timeside
OSX / Windows
Native install is hard at the moment but you can either run our Vagrant or Docker images (see Development).
Dependencies
Needed:
python (>=2.7) python-setuptools python-numpy python-scipy python-h5py python-matplotlib python-imaging python-simplejson python-yaml python-mutagen libhdf5-serial-dev python-tables python-gst0.10 gstreamer0.10-gnonlin gstreamer0.10-plugins-good gstreamer0.10-plugins-bad gstreamer0.10-plugins-ugly
Optional:
aubio (>=0.4.1) yaafe python-aubio python-yaafe vamp-examples django (>=1.4) django-south djangorestframework django-extensions
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
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
- Screenshot:
- Examples of the player embeded in the Telemeta open web audio CMS:
- Development documentation:
- 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
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/
VirtualBox and Vagrant (deprecated)
We also provide a vagrant box to install a virtual Debian system including TimeSide and all other dependencies. First, install Vagrant and VirtualVox:
sudo apt-get install vagrant virtualbox
On other OS, we need to install the packages correponding to your system:
VirtualBox: https://www.virtualbox.org/wiki/Downloads
Then setup our image box like this in a terminal:
vagrant box add parisson/timeside-wheezy64 http://files.parisson.com/vagrant/timeside/parisson-timeside-wheezy64.box vagrant init parisson/timeside-wheezy64 vagrant up vagrant ssh
To stop the virtual box:
exit vagrant halt
Native
First, install TimeSide (see Install).
Then:
sudo apt-get build-dep python-timeside sudo apt-get install git git clone https://github.com/Parisson/TimeSide.git cd TimeSide git checkout dev sudo pip install -e . echo "export PYTHONPATH=$PYTHONPATH:`pwd`" >> ~/.bashrc source ~/.bashrc tests/run_all_tests
Sponsors and Partners
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)
Copyrights
Copyright (c) 2006, 2014 Parisson Sarl
Copyright (c) 2006, 2014 Guillaume Pellerin
Copyright (c) 2010, 2014 Paul Brossier
Copyright (c) 2013, 2014 Thomas Fillon
Copyright (c) 2013, 2014 Maxime Lecoz
Copyright (c) 2013, 2014 David Doukhan
Copyright (c) 2006, 2010 Olivier Guilyardi
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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