Transform underwater acoustic data into training data for machine learning.
Project description
Tehom - Machine Learning on Underwater Acoustics
This package facilitates the creation of machine learning training data on
underwater acoustics. While the raw data is available from Marine Cadastre and
Ocean Networks Canada (via the onc package), tehom tracks downloads that it conducts
and exposes more useful queries for data exploration and sampling. e.g.:
"What hydrophones outside Vancouver have data during April-June, 2017?"
"Where have I downloaded time/geo overlapping data?"
"Give me acoustic snippets as numpy arrays, labeled with whether a container ship was close to the hydrophone that recorded the snippet."
Requirements
sqlite3available as a command line program- Create Ocean Networks Canada account and get your API token here
How to:
example.ipynb shows the basic data access and navivgation. Before working with any ONC data, you must once run
python -m tehom save-token <token>
Useful additional commands to start with:
tehom.download_shipstehom.download_acousticstehom.downloads.get_ais_downloadstehom.downloads.get_onc_downloadstehom.downloads.get_audio_availabilitytehom.downloads.show_available_data(plotting, use Jupyter terminal)tehom.sample(in progress!)
In addition to save-token, when run as a module/CLI, tehom can also download data.
About
"Tehom" is the Hebrew word for abyss, specifically the dark, chaotic oceans from which order and the world emerged.
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