# Interactive app

`pykanto` includes a web application that allows you to interactively explore
your data. It can be launched using a method from the `KantoData` class:

```python
dataset.open_label_app()
```

This will open a new tab in your browser: you can follow the instructions in the app to explore and label your data.

![webapp](../custom/web_pykantoapp.png)

Once you are done checking the automatically assigned labels you need to reload
the updated dataset, which has been automatically saved to disk:

```python
dataset = dataset.reload()
```

***

You can also use the app to check and correct labels assigned through any other
means, for example after training a deep learning classifier model. To do this,
you simply need to add your custom labels to the dataframe containing your data.

For example, if your {py:class}`~pykanto.dataset.KantoData` object is called `dataset`, you
can overwrite the `auto_class` column in `dataset.data` with your own labels
(`type: str`). This will work when `dataset.parameters.song_level = True`; if you want
to do this at the note or unit level please open an issue on GitHub and I'll add
this functionality.

````{admonition} Note:
:class: note

Running the web application requires having run the following methods on your `KantoData` object:

```python
dataset.segment_into_units()
dataset.get_units()
dataset.cluster_ids()
dataset.prepare_interactive_data()
```

These find distinct units in each vocalisation, label them, and create lightweight representations of the sounds. See the entire process in the [basic workflow page](./basic-workflow.ipynb) for more details.
````