https://github.com/janclemenslab/das

Deep Audio Segmenter
https://github.com/janclemenslab/das

annotation classification deep-learning segmentation song tensorflow

Last synced: about 1 month ago
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Deep Audio Segmenter

• Host: GitHub
• URL: https://github.com/janclemenslab/das
• Owner: janclemenslab
• Created: 2019-09-26T19:11:24.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-05-29T07:59:31.000Z (8 months ago)
• Last Synced: 2024-05-29T16:16:27.539Z (8 months ago)
• Topics: annotation, classification, deep-learning, segmentation, song, tensorflow
• Language: Python
• Homepage: http://janclemenslab.org/das/
• Size: 86.1 MB
• Stars: 26
• Watchers: 5
• Forks: 8
• Open Issues: 5
• Metadata Files:
  • Readme: README.md

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README

        


# Deep Audio Segmenter

_DAS_ is a method for automatically annotating song from raw audio recordings based on a deep neural network. _DAS_ can be used with a graphical user interface, from the terminal, or from within python scripts.

If you have questions, feedback, or find bugs please raise an [issue](https://github.com/janclemenslab/das/issues).

Please cite _DAS_ as:

Elsa Steinfath, Adrian Palacios, Julian Rottschäfer, Deniz Yuezak, Jan Clemens (2021).

_Fast and accurate annotation of acoustic signals with deep neural networks._

[eLife](https://doi.org/10.7554/eLife.68837)

## Installation

### Pre-requisites

_Anaconda_: _DAS_ is installed using an anaconda environment. For that, first install the [anaconda python distribution](https://docs.anaconda.com/anaconda/install/) (or [miniconda](https://docs.conda.io/en/latest/miniconda.html)). If you have conda already installed, make sure you have at least conda v23.10.0. If not, update from an older version with `conda update conda -n base`.

_Libsoundfile on linux_: The graphical user interface (GUI) reads audio data using [soundfile](http://pysoundfile.readthedocs.io/), which relies on `libsndfile`. `libsndfile` will be automatically installed on Windows and macOS. On Linux, the library needs to be installed manually with: `sudo apt-get install libsndfile1`. Note that _DAS_ will work w/o `libsndfile` but will not be able to load exotic audio formats.

### Install _DAS_

Create an anaconda environment called `das` that contains all the required packages.

On windows:

```shell

conda create python=3.10 das=0.32.4 -c conda-forge -c ncb -c nvidia -n das -y

```

On Linux or MacOS (arm only):

```shell

conda create python=3.11 das=0.32.4 -c conda-forge -c ncb -c nvidia -c apple -n das -y

```

## Usage

To start the graphical user interface:

```shell

conda activate das

das gui

```

The documentation at [https://janclemenslab.org/das/](https://janclemenslab.org/das/) provides information on the usage of _DAS_:

- A [quick start tutorial](https://janclemenslab.org/das/quickstart.html) walks through all steps from manually annotating song, over training a network, to generating new annotations.

- How to use the [graphical user interface](https://janclemenslab.org/das/tutorials_gui/tutorials_gui.html).

- How to use _DAS_ [from the terminal or from python scripts](https://janclemenslab.org/das/tutorials/tutorials.html).

## Acknowledgements

The following packages were modified and integrated into das:

- Keras implementation of TCN models modified from [keras-tcn](https://github.com/philipperemy/keras-tcn) (in `das.tcn`)

- Trainable STFT layer implementation modified from [kapre](https://github.com/keunwoochoi/kapre) (in `das.kapre`)

See the sub-module directories for the original READMEs.