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.
Build status
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).
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.
Processors
IDecoder
FileDecoder [gst_dec]
ArrayDecoder [array_dec]
LiveDecoder [gst_live_dec]
IAnalyzer
AubioTemporal [aubio_temporal]
AubioPitch [aubio_pitch]
AubioMfcc [aubio_mfcc]
AubioMelEnergy [aubio_melenergy]
AubioSpecdesc [aubio_specdesc]
Yaafe [yaafe]
Spectrogram [spectrogram_analyzer]
Waveform [waveform_analyzer]
VampSimpleHost [vamp_simple_host]
IRITSpeechEntropy [irit_speech_entropy]
IRITSpeech4Hz [irit_speech_4hz]
OnsetDetectionFunction [odf]
LimsiSad [limsi_sad]
IValueAnalyzer
Level [level]
MeanDCShift [mean_dc_shift]
IGrapher
Waveform [waveform_simple]
WaveformCentroid [waveform_centroid]
WaveformTransparent [waveform_transparent]
WaveformContourBlack [waveform_contour_black]
WaveformContourWhite [waveform_contour_white]
SpectrogramLog [spectrogram_log]
SpectrogramLinear [spectrogram_lin]
Display.aubio_pitch.pitch [grapher_aubio_pitch]
Display.odf [grapher_odf]
Display.waveform_analyzer [grapher_waveform]
Display.irit_speech_4hz.segments [grapher_irit_speech_4hz_segments]
IEncoder
VorbisEncoder [gst_vorbis_enc]
WavEncoder [gst_wav_enc]
Mp3Encoder [gst_mp3_enc]
FlacEncoder [gst_flac_enc]
AacEncoder [gst_aac_enc]
WebMEncoder [gst_webm_enc]
OpusEncoder [gst_opus_enc]
AudioSink [gst_audio_sink_enc]
News
0.5.6
Bugfix release
Fix analyzer instanciation as parent for some graphers
0.5.5
All processor folders (decoder, analyzer, grapher, encoder) are now real plugin repositories : you can just drop processors in it and play!
TimeSide can be installed without Aubio, Yaafe nor Vamp : it should be easier to install on old distributions for which those librairies are difficult or impossible to compile
Encoder : add an Opus encoder
Experimental : add a django web server with a REST API (see “Web server”)
AubioPitch: prevent NaN in result by converting them to zero
Yaafe analyzer: simplify adaptation of process frames from TimeSide to Yaafe
LimsiSad: add a default value for parameter sad_model
Fix various NaN and Inf and PEP8 issues also many PyFlake warnings
Full Travis integration with tests and test coverage through coveralls.io
Thanks to all contributors!
WARNING: some of the processor paths used in your app could have moved between 0.5.4 and 0.5.5. Check them with timeside.core.processors(). Note that it is now advised to use the timeside.core.get_processor() method to instantiate the processors with their respective id as argument.
UPGRADING from the sources: please remove all .pyc files from your repository.
0.5.4
Encoder : transcoded streams where broken. Now fixed with some smart thread controls.
Analyzer : update VAMP plugin example in sandbox
Analyzer : new experimental plugin : Limsi Speech Activity Detection Systems (limsi_sad)
Decoder : process any media in streaming mode giving its URL
Install : fix some setup requirements
0.5.3
Make Analyzer rendering more generic and easy to implement
Analyzer : implement rendering capability for event and segment + add some more analyzer graphers
Analyzer : refactoring the results rendering method. + Capability to use matplotlib in environnement with no display
Decoder : Add a Live decoder to get data from the soundcard
Decoder : add support for 96kHz sampling rate
Encoder: live AudioSink encoder, encoder that plays the audio stream through the soundcard
Grapher : add a generic Class to display Analyzers through their ‘render’ method. Add the new grapher file
Grapher : add a generic Class to display Analyzers through their ‘render’ method. For now, it only support FrameValueResult analyzer
Core : add a condition to catch signal only if a LiveDecoder source is used
Various bugfixes
0.5.2
Add a general launch script “timeside-launch” (see “Shell interface”)
Add some decorators to filter the inputs of processes (see analyzer.waveform for ex)
Add a “stack” option to the FileDecoder to accumulate audio data allowing multipass processes
Add beat confidence to aubio_temporal
Add AAC encoder (gstreamer voaacenc plugin needed)
Add UUIDs to the file URI and to all processors
Add a Debian repository with all dependencies for i386 and amd64 architectures
Fix buggy WebM encoder
Fix buggy MP3 muxing
Fix various minor bugs
0.5.1
Add parent processor list to Processor
Simplify and optimize the grapher system
Add Grapher abstract generic class
Add a UUID property to Processor
Add a SpectrogramLinear grapher
Add WaveformTransparent grapher
Fix some assignment issues regarding immutable type in for Analyzer Result
Simplify analyzer results implementation by introducing a Factory and multiple classes and subclasses to handle the 8 different kinds of results
Add doctests and improve the unit tests
Add a OnsetDetectionFunction analyzer
Update documentation
Various cleanups
Various bugfixes
0.5.0
Deep refactoring of the analyzer API to handle various new usecases, specifically audio feature extraction
Add serializable global result container (NEW dependency to h5py, json, yaml)
Add new audio feature extraction analyzers thanks to the Aubio library providing beat & BPM detection, pitch dectection and other cool stuff (NEW dependency on aubio)
Add new audio feature extraction analyzers thanks to the Yaafe library (NEW dependency on yaafe)
Add new IRIT speech detection analyzers (NEW dependency on scipy)
EXPERIMENTAL : add new audio feature extraction thanks to the VAMP plugin library (NEW dependency on some vamp toold)
Add new documentation : http://files.parisson.com/timeside/doc/
New Debian repository for instant install
Various bugfixes
Comptatible with Python >=2.7
WARNING : no longer compatible with Telemeta 1.4.5
Dive in
To list all available plugins:
>>> import timeside >>> timeside.core.list_processors()
Define some processors:
>>> from timeside.core import get_processor >>> decoder = get_processor('gst_dec')('sweep.wav') >>> grapher = get_processor('waveform_simple') >>> analyzer = get_processor('level') >>> encoder = get_processor('gst_vorbis_enc')('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:
>>> print 'Level:', analyzer.results
The encoded OGG file should also be there…
Note you can also instanciate each processor with its own class:
>>> decoder = timeside.decoder.file.FileDecoder('sweep.wav') >>> grapher = timeside.grapher.waveform_simple.Waveform() >>> analyzer = timeside.analyzer.level.Level() >>> encoder = timeside.encoder.ogg.VorbisEncoder('sweep.ogg')
For more extensive examples, please see the full documentation.
API / Documentation
General : http://files.parisson.com/timeside/doc/
Tutorial : http://files.parisson.com/timeside/doc/tutorial/index.html
Player / UI : https://github.com/yomguy/TimeSide/wiki/Ui-Guide (see also “Web player”)
Examples:
Install
The TimeSide engine is intended to work on all Linux and Unix like platforms.
It depends on several other python modules and compiled librairies like GStreamer.
Debian, Ubuntu
For Debian based distributions, we provide a safe repository which provides all additional dependencies that are not included in Debian yet. Please follow the instructions on this page.
Note you can also use pip if you already have already satisfied all the dependencies:
$ sudo pip install timeside
Other Linux distributions
On other Linux platforms, you need to install all dependencies listed in the paragraph “Dependencies” (find all equivalent package names for your distribution).
Then, use pip:
$ sudo pip install timeside
OSX
The installation on OSX platforms is pretty hard at the moment because all dependencies are not in brew. But, it will be fully documented in the next release 0.5.6.
Dependencies
Needed:
python (>=2.7) python-setuptools python-numpy python-scipy python-h5py python-matplotlib pillow python-simplejson python-yaml python-mutagen libhdf5-serial-dev 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
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
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 timeside/server/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
For versions >=0.5 on Debian 7 Wheezy:
$ echo "deb http://debian.parisson.com/debian/ stable main" | sudo tee -a /etc/apt/sources.list $ echo "deb-src http://debian.parisson.com/debian/ stable main" | sudo tee -a /etc/apt/sources.list $ sudo apt-get update $ sudo apt-get install git $ sudo apt-get build-dep python-timeside $ git clone https://github.com/yomguy/TimeSide.git $ cd TimeSide $ git checkout dev $ sudo pip install -e . $ python 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 Samalyse SARL
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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