https://github.com/tdewolff/manatees
AI4Climate, ECOSUR
https://github.com/tdewolff/manatees
Last synced: 3 months ago
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AI4Climate, ECOSUR
- Host: GitHub
- URL: https://github.com/tdewolff/manatees
- Owner: tdewolff
- Created: 2024-01-30T00:30:24.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-07-26T00:53:44.000Z (11 months ago)
- Last Synced: 2025-01-29T06:51:22.680Z (5 months ago)
- Language: Python
- Size: 59.6 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Manatee audio classification
Detect manatee vocalisations recorded by hydrophones using the [audio spectrogram transformer model](https://github.com/YuanGongND/ast). This project is a joint effort of the Initiative for Data & AI (Universidad de Chile), AI4Climate (C-MINDS) and ECOSUR, with funding from Google.
## Citing Us
If you use this repository, please cite the following paper:
> [Stefano Schiappacasse, Taco de Wolff, Yann Henaut, Regina Cervera, Aviva Charles, Felipe Tobar. "Detection of manatee vocalisations using the Audio Spectrogram Transformer." In *Proc. of the IEEE International Workshop on Machine Learning for Signal Processing* (2024). In press.](https://arxiv.org/abs/2407.18083)
```
@inproceedings{schiappacasse2024mlsp,
title={Detection of manatee vocalisations using the Audio Spectrogram Transformer},
author={Stefano Schiappacasse and Taco de Wolff and Yann Henaut and Regina Cervera and Aviva Charles and Felipe Tobar},
booktitle={Proc. of the International Workshop on Machine Learning for Signal Processing},
year={2024},
note = {In press}
}
```
## Usage
To pre-process the data set and train the model, run:
```bash
python manatee.py train
```
Note that your must have the Beauval dataset in the `data` directory.
Once a model has been trained, you can run using test mode or evaluation mode. Test mode uses pre-processed data to extract key performance metrics of the model (e.g. on a test data set), while evaluation mode will detect manatee vocalisations in a new audio file using the trained model (for example, `python manatee.py eval --sound soundfile.wav`).
See `python manatee.py --help` for more information:
```
usage: Manatee model training and evaluation [-h] [--epochs EPOCHS] [--split SPLIT] [--batch BATCH]
[--lr LR] [--lr-step LR_STEP] [--lr-decay LR_DECAY]
[--model MODEL] [--positive-split POSITIVE_SPLIT]
[--data [DATA ...]] [--sound [SOUND ...]]
[--report REPORT] [-n N]
[{train,test,eval}]
positional arguments:
{train,test,eval}
options:
-h, --help show this help message and exit
--epochs=3 Number of epochs to run training
--split=0.5 Training/validation split
--batch=16 Batch size
--lr=1e-6 Initial learning rate
--lr-step=5 Learning rate scheduler epoch step
--lr-decay=0.5 Learning rate scheduler step decay
--model=model.pth Output filename for trained model
--positive-split=0.5 Percentage of positive samples (by adding negative samples)
--data=[data.pkl] Input filename for preprocessed data
--sound=[] Input filename for sound file for evaluation
--report=report.pkl Report filename
-n=1 Number of times to train
```