https://github.com/janfreyberg/ipyannotations

Data annotations in python using jupyter notebooks
https://github.com/janfreyberg/ipyannotations

Last synced: 2 months ago
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Data annotations in python using jupyter notebooks

• Host: GitHub
• URL: https://github.com/janfreyberg/ipyannotations
• Owner: janfreyberg
• License: mit
• Created: 2018-11-16T11:44:01.000Z (about 6 years ago)
• Default Branch: main
• Last Pushed: 2023-02-04T16:12:03.000Z (almost 2 years ago)
• Last Synced: 2024-10-12T15:53:55.634Z (3 months ago)
• Language: Python
• Homepage: https://ipyannotations.readthedocs.io/
• Size: 10.3 MB
• Stars: 53
• Watchers: 3
• Forks: 7
• Open Issues: 14
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        

# ipyannotations

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[![PyPI version](https://badge.fury.io/py/ipyannotations.svg)](https://badge.fury.io/py/ipyannotations)

Create rich adata annotations in jupyter notebooks.

ipyannotations provides interactive UI elements, based on ipywidgets, to allow

developers and scientists to label data right in the notebook.

ipyannotations supports many common data labelling tasks, such as image and text

classification and annotation. It also supports custom data presentation by

leveraging the Jupyter ecosystem.

[![interface](https://user-images.githubusercontent.com/4092425/132008979-2fa43ec2-1add-4376-aba9-7836509b8e8f.png)](https://user-images.githubusercontent.com/4092425/132008979-2fa43ec2-1add-4376-aba9-7836509b8e8f.png)

## Installation

You can install using `pip`:

```bash

pip install ipyannotations

```

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable

the nbextension:

```bash

jupyter nbextension enable --py [--sys-prefix|--user|--system] ipyannotations

```

## Development Installation

Create a dev environment:

```bash

conda create -n ipyannotations-dev -c conda-forge nodejs yarn python jupyterlab

conda activate ipyannotations-dev

```

Install the python. This will also build the TS package.

```bash

pip install -e ".[test, examples]"

```

When developing your extensions, you need to manually enable your extensions with the

notebook / lab frontend. For lab, this is done by the command:

```

jupyter labextension develop --overwrite .

yarn run build

```

For classic notebook, you need to run:

```

jupyter nbextension install --sys-prefix --symlink --overwrite --py ipyannotations

jupyter nbextension enable --sys-prefix --py ipyannotations

```

Note that the `--symlink` flag doesn't work on Windows, so you will here have to run

the `install` command every time that you rebuild your extension. For certain installations

you might also need another flag instead of `--sys-prefix`, but we won't cover the meaning

of those flags here.

### How to see your changes

#### Typescript:

If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different

terminals to watch for changes in the extension's source and automatically rebuild the widget.

```bash

# Watch the source directory in one terminal, automatically rebuilding when needed

yarn run watch

# Run JupyterLab in another terminal

jupyter lab

```

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

#### Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.