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https://github.com/hiveeyes/saraswati
Saraswati is a robust, multi-channel audio recording, transmission and storage system
https://github.com/hiveeyes/saraswati
audio audio-mux audio-recorder audio-recording earth-observations environmental-monitoring field-recording multi-channel multi-channel-audio
Last synced: 2 days ago
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Saraswati is a robust, multi-channel audio recording, transmission and storage system
- Host: GitHub
- URL: https://github.com/hiveeyes/saraswati
- Owner: hiveeyes
- License: agpl-3.0
- Created: 2018-04-21T20:52:17.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2021-07-24T22:14:38.000Z (over 3 years ago)
- Last Synced: 2024-10-13T21:39:45.603Z (about 1 month ago)
- Topics: audio, audio-mux, audio-recorder, audio-recording, earth-observations, environmental-monitoring, field-recording, multi-channel, multi-channel-audio
- Language: Python
- Homepage: https://community.hiveeyes.org/t/developing-saraswati-a-robust-multi-channel-audio-recording-transmission-and-storage-system/924
- Size: 4.09 MB
- Stars: 10
- Watchers: 3
- Forks: 2
- Open Issues: 6
-
Metadata Files:
- Readme: README.rst
- Changelog: CHANGES.rst
- License: LICENSE
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README
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|
#########
Saraswati
#########
*****
About
*****
Saraswati is a robust, multi-channel audio recording, transmission and storage
system. The system is designed for flexible field recording of audio signals in
environmental monitoring systems.
Saraswati is developed by an independent community of scientists from different
domains working collaboratively on this project. You are welcome to join our
efforts.
Etymology
=========
`Saraswati `_ is the
Hindu goddess of knowledge, music, art, wisdom and learning.
Technologies
============
The software is based on GStreamer_ and the `GStreamer Python Bindings`_, in
turn using the fine PyGObject_ under the hood. It is designed to run on
`Single-board computer (SBC)`_ systems as well as larger machines.
Status
======
The software was tested successfully with Python 3.7-3.9, GStreamer 1.10.4,
1.14.4, 1.16.2 and 1.18.4, on both Linux (Debian 10 buster, Debian 11 bullseye,
Linux Mint 20.2) and macOS (Catalina 10.15.7).
*****
Setup
*****
This part of the documentation covers the basic installation of Saraswati.
The first step to using any software package is getting it properly installed.
Please read this section carefully.
When aiming to run Saraswati autonomously in a production setup, please also
consider reading the documentation about `running Saraswati in production`_.
Install prerequisites
=====================
As Saraswati is based on GStreamer_ and, optionally, ALSA_, let's install the
relevant packages.
Debian-based systems
--------------------
::
sudo apt-get update
sudo apt-get install --yes libgstreamer1.0 gstreamer1.0-tools gstreamer1.0-alsa gstreamer1.0-plugins-base gstreamer1.0-plugins-good
sudo apt-get install --yes python3 python3-pip python3-gst-1.0 python3-gi python3-tz
sudo apt-get install --yes alsa-utils mkvtoolnix flac
macOS systems
-------------
::
brew install gstreamer gst-python gst-libav gst-plugins-base gst-plugins-good
brew install mkvtoolnix flac
Configure system
================
Synchronize system time with NTP, this is important for appropriate timestamping::
sudo timedatectl set-ntp true
Install Saraswati
=================
Install ``saraswati`` package from PyPI::
pip install saraswati
To quickly verify the installation, invoke::
saraswati record --channel="testdrive source=autoaudiosrc"
*****
Usage
*****
This part of the documentation covers how to run Saraswati interactively.
Please read this section carefully.
When aiming to run Saraswati autonomously in a production setup, please also
consider reading the documentation about `running Saraswati in production`_.
Recording audio
===============
``saraswati record`` is an implementation to
- ingest audio from a GStreamer audio source element,
- run it through ``flacenc`` to encode audio with the FLAC lossless audio
encoder, and
- finally store it using ``splitmuxsink``, a GStreamer component which
multiplexes incoming streams into multiple time- or size-limited files
Each audio fragment will be timestamped with the current date/time
information in an ISO8601-like format, using a qualified UTC offset of ``+0000``.
In order to learn about the command line syntax, please invoke
``saraswati --help`` or ``saraswati record --help``.
Uploading audio
===============
When the ``--upload=`` option is given, Saraswati will attempt to upload
its spool directory to an rsync target. By default, it will do this each
5 minutes.
Please note ``rsync`` will be invoked using the ``--remove-source-files``
option. So, after successful upload, the spooled files on the local machine
will get purged.
Example
=======
Invoke::
saraswati record --channel="testdrive source=autoaudiosrc"
This will yield audio fragments in chunks worth of 5 minutes each::
recording_testdrive_20210621T155817+0000_0000.mka
recording_testdrive_20210621T160317+0000_0001.mka
recording_testdrive_20210621T160817+0000_0002.mka
recording_testdrive_20210621T161317+0000_0003.mka
recording_testdrive_20210621T161817+0000_0004.mka
Display segment metadata information embedded into the Matroska container file::
mkvinfo recording_testdrive_20210620T122642+0000_0065.mka | grep -E 'Codec|Date|duration'
| + Date: Sun Jun 20 12:26:42 2021 UTC
| + Default duration: 00:00:00.104489796 (9.570 frames/fields per second for a video track)
| + Codec ID: A_FLAC
Extract audio track::
mkvextract recording_testdrive_20210621T155817+0000_0000.mka tracks 0:audio_20210621T155817.flac
flac --decode audio_20210621T155817.flac
file recording_testdrive_20210621T155817+0000_0000.mka
Matroska data
file audio_20210621T155817.flac
FLAC audio bitstream data, 16 bit, mono, 48 kHz, length unknown
file audio_20210621T155817.wav
RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, mono 48000 Hz
*******************
Project information
*******************
Background
==========
This software gets developed for the "Bee Observer" (BOB) project, a joint
endeavour initiated by the `Cognitive neuroinformatics group at the
University of Bremen`_ and the people of the independent research and
development project `Hiveeyes`_. See also:
- `hiverize.org - Vernetzt. Smart. Imkern. `_
- `The Hiveeyes Project `_
- `Uni Bremen und Hiveeyes werden als Citizen-Science-Projekte vom Forschungsministerium unterstützt `_
- `System für kontinuierliche Audio-Aufzeichnung (BOB Projekt, Phase 1) `_
Details
=======
The "Saraswati" program is released under the GNU AGPL license.
Its source code lives on `GitHub `_ and
the Python package is published to `PyPI `_.
You might also want to have a look at the `documentation `_.
If you'd like to contribute you're most welcome!
Spend some time taking a look around, locate a bug, design issue or
spelling mistake and then send us a pull request or create an issue.
Thanks in advance for your efforts, we really appreciate any help or feedback.
Code license
============
The code is licensed under the GNU AGPL license. See LICENSE_ file for details.
----
Have fun!
.. _ALSA: https://alsa-project.org/
.. _Cognitive neuroinformatics group at the University of Bremen: http://www.cognitive-neuroinformatics.com/en/
.. _flac-timestamp-chunked.py: https://github.com/hiveeyes/saraswati/blob/master/python/examples/flac-timestamp-chunked.py
.. _GStreamer: https://gstreamer.freedesktop.org/
.. _GStreamer Python Bindings: https://cgit.freedesktop.org/gstreamer/gst-python
.. _Hiveeyes: https://hiveeyes.org/
.. _LICENSE: https://github.com/hiveeyes/saraswati/blob/master/LICENSE
.. _PyGObject: http://pygobject.readthedocs.io/
.. _running Saraswati in production: https://github.com/hiveeyes/saraswati/blob/main/doc/setup-production.rst
.. _Single-board computer (SBC): https://en.wikipedia.org/wiki/Single-board_computer