Python implementation of audformat
Project description
Specification and reference implementation of audformat.
audformat stores media data, such as audio or video, together with corresponding annotations in a pre-defined way. This makes it easy to combine or replace databases in machine learning projects.
An audformat database is a folder that contains media files together with a header YAML file and one or several files storing the annotations. The database is represented as an audformat.Database object and can be loaded with audformat.Database.load() or written to disk with audformat.Database.save().
Have a look at the installation and usage instructions and the format specifications as a starting point.
Changelog
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
Version 0.9.6 (2021-01-28)
Fixed: implemented audformat.Database.__eq__ and return True for identical databases
Version 0.9.5 (2021-01-14)
Changed: use nullable Pandas’ type 'boolean' for bool schemes
Fixed: Scheme.draw() generates boolean values if scheme is bool
Version 0.9.4 (2021-01-11)
Changed: add arguments num_workers and verbose to audformat.Database.load()
Version 0.9.3 (2021-01-07)
Fixed: avoid sphinx syntax in CHANGELOG
Version 0.9.2 (2021-01-07)
Changed: add arguments num_workers and verbose to audformat.Database.drop_files(), audformat.Database.map_files(), audformat.Database.pick_files(), audformat.Database.save()
Changed: audformat.segmented_index() support int and float, which will be interpreted as seconds
Fixed: audformat.utils.to_segmented_index() returns correct index type for NaT
Version 0.9.1 (2020-12-21)
Fixed: add column name to HTML Series output in docs
Fixed: removed mentioning of NotConformToUnifiedFormat error and RedundantArgumentError error
Fixed: add missing errors to docstring of audformat.Table.set() and audformat.Column.set()
Version 0.9.0 (2020-12-18)
Added: initial release public release
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