Update README.md
Browse files
README.md
CHANGED
|
@@ -1,60 +1,13 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
Clone the repository:
|
| 15 |
-
```
|
| 16 |
-
git clone git@github.com:JHU-LCAP/FlexSED.git
|
| 17 |
-
```
|
| 18 |
-
Install the dependencies:
|
| 19 |
-
```
|
| 20 |
-
cd FlexSED
|
| 21 |
-
pip install -r requirements.txt
|
| 22 |
-
```
|
| 23 |
-
|
| 24 |
-
## Usage
|
| 25 |
-
```python
|
| 26 |
-
from api import FlexSED
|
| 27 |
-
import torch
|
| 28 |
-
import soundfile as sf
|
| 29 |
-
|
| 30 |
-
# load model
|
| 31 |
-
flexsed = FlexSED(device='cuda')
|
| 32 |
-
|
| 33 |
-
# run inference
|
| 34 |
-
events = ["Dog"]
|
| 35 |
-
preds = flexsed.run_inference("example.wav", events)
|
| 36 |
-
|
| 37 |
-
# visualize prediciton
|
| 38 |
-
flexsed.to_multi_plot(preds, events, fname="example2")
|
| 39 |
-
|
| 40 |
-
# (Optional) visualize prediciton by video
|
| 41 |
-
# flexsed.to_multi_video(preds, events, audio_path="example2.wav", fname="example2")
|
| 42 |
-
```
|
| 43 |
-
|
| 44 |
-
## Training
|
| 45 |
-
|
| 46 |
-
WIP
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
## Reference
|
| 50 |
-
|
| 51 |
-
If you find the code useful for your research, please consider citing:
|
| 52 |
-
|
| 53 |
-
```bibtex
|
| 54 |
-
@article{hai2025flexsed,
|
| 55 |
-
title={FlexSED: Towards Open-Vocabulary Sound Event Detection},
|
| 56 |
-
author={Hai, Jiarui and Wang, Helin and Guo, Weizhe and Elhilali, Mounya},
|
| 57 |
-
journal={arXiv preprint arXiv:2509.18606},
|
| 58 |
-
year={2025}
|
| 59 |
-
}
|
| 60 |
-
```
|
|
|
|
| 1 |
+
---
|
| 2 |
+
title: FlexSED
|
| 3 |
+
emoji: 🎧
|
| 4 |
+
colorFrom: green
|
| 5 |
+
colorTo: indigo
|
| 6 |
+
sdk: gradio
|
| 7 |
+
sdk_version: 5.31.0
|
| 8 |
+
app_file: app.py
|
| 9 |
+
pinned: false
|
| 10 |
+
license: mit
|
| 11 |
+
short_description: State-of-the-art target speech extractor
|
| 12 |
+
tags: ["sound-event-detection"]
|
| 13 |
+
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|