https://github.com/hahnec/stofnet

StofNet: Super-resolution Time of Flight Network (ICASSP 2024)
https://github.com/hahnec/stofnet

acoustic audio deep-learning icassp icassp2024 learning localization multilateration neural non-destructive-testing round-trip super-resolution time-of-arrival time-of-flight tof trilateration ultrasound

Last synced: 4 days ago
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StofNet: Super-resolution Time of Flight Network (ICASSP 2024)

• Host: GitHub
• URL: https://github.com/hahnec/stofnet
• Owner: hahnec
• Created: 2023-06-17T16:50:48.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-02-22T13:35:52.000Z (9 months ago)
• Last Synced: 2024-02-22T14:42:16.951Z (9 months ago)
• Topics: acoustic, audio, deep-learning, icassp, icassp2024, learning, localization, multilateration, neural, non-destructive-testing, round-trip, super-resolution, time-of-arrival, time-of-flight, tof, trilateration, ultrasound
• Language: Python
• Homepage:
• Size: 19.3 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# StofNet - Super-resolution time of flight Network

[![arXiv paper link](https://img.shields.io/badge/paper-arXiv:2308.12009-red)](https://arxiv.org/pdf/2308.12009.pdf)






## Installation

`$ python3 -m venv venv`

`$ source venv/bin/activate`

`$ python3 -m pip install -r requirements.txt`

`$ unzip datasets/stof_chirp101_dataset.zip -d datasets/`

## Training

`$ python3 main.py evaluate=False logging=train model=stofnet data_dir=./datasets/stof_chirp101_dataset th=Null rf_scale_factor=10` 

## Inference

`$ python3 main.py evaluate=True batch_size=1 etol=1 model=stofnet model_file=different-armadillo data_dir=./datasets/stof_chirp101_dataset logging=Null rf_scale_factor=10 th=Null`

**Note**: More information on commands and settings are found in [config.yaml](config.yaml) or [bash_scripts](bash_scripts).

## Results














If you use this project for your work, please cite the original [paper](https://arxiv.org/pdf/2308.12009.pdf):

```

@inproceedings{stofnet,

 title={StofNet: Super-resolution Time of Flight Network}, 

 author={Christopher Hahne and Michel Hayoz and Raphael Sznitman},

 booktitle={Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},

 year={2024},

}

```