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annote's Introduction

ANNOTE

Annotation of Time-series Events

alt text Annotation of Time-series Events (ANNOTE) is a new annotation software. It enables the loading of longitudinal, time-series data from audio files or CSV files. It provides visualization of up to three one-dimensional data signals, such as audio or sensor data, allowing users to select regions to indicate event start and end points. Dynamic label adjustments adapt to user requirements, while the user-friendly nature of the software ensures accessibility for professionals and non-professionals alike. ANNOTE's streamlined annotation process accelerates the development of models and applications that rely on annotated time-series data.

Highlights

  • Load audio files or CSV files
  • Visualize up to three one-dimensional data signals
  • Annotate start and end points of events
  • Dynamic label adjustments

Demo

For a demo you can watch our youtube video where we demonstrate the use of ANNOTE.

Contents

Getting started

We provide:

Requirements

To use ANNOTE, you need to have Python 3.8 on your system. It was only tested on this Python version.

Install with pip

pip install git+https://github.com/ankilab/ANNOTE.git

Build from source

git clone https://github.com/ankilab/ANNOTE.git
cd ANNOTE
pip install -r requirements.txt
cd src
python main.py

Loading annotations from .annote

To save annotations we use the flammkuchen package. The saved files can be accessed in the following way:

import flammkuchen as fl
annotations = fl.load('path/to/file.annote')
print(annotations)

Troubleshooting common issues

  • Using Ubuntu: If you get an error message like qt.qpa.plugin: Could not load the Qt platform plugin "xcb" in "" even though it was found. you can try to install the following sudo apt install libxcb-cursor0.

Authors

License

The project is licensed under the MIT License. See the LICENSE file for details.

Citation

If you use ANNOTE in your research, please cite our paper:

@article{,
    title = {ANNOTE: Annotation of Time-series Events},
    journal = {},
    volume = {},
    pages = {},
    year = {2023},
    issn = {},
    doi = {},
    url = {},
    author = {Groh, René; Li, Jiu Yu; Li-Jessen, Nicole Y. K.; Kist, Andreas M.},
    keywords = {}
}

annote's People

Contributors

rgroh1996 avatar

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