Metadata-Version: 2.4
Name: wavesurfer
Version: 0.2.4
Summary: wavesurfer
Home-page: https://github.com/pengzhendong/wavesurfer
Author: Zhendong Peng
Author-email: pzd17@tsinghua.org.cn
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: audiolab
Requires-Dist: jinja2
Requires-Dist: lhotse
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

# wavesurfer

## Usage

```bash
$ pip install wavesurfer
```

- display wave file

```python
from wavesurfer import display

display("data/test_16k.wav")
```

- display waveform

```python
import torchaudio
from wavesurfer import display

waveform, rate = torchaudio.load("data/test_16k.wav")
display(waveform, rate, enable_spectrogram=True)
```

![](images/test_16k.png)

- display streaming waveform

```python
import time
import torchaudio
from wavesurfer import display

def audio_generator():
    waveform, rate = torchaudio.load("data/test_16k.wav")
    chunk_size_s = 0.3
    chunk_size = int(chunk_size_s * rate)
    for i in range(0, waveform.size(1), chunk_size):
        time.sleep(0.1)  # RTF: 0.1/0.3 < 1
        yield waveform[:, i:i + chunk_size]

display(audio_generator(), rate=16000)
```
