setmlvis

A new visualization method for comparing different models for bounding box detection.

Installation

You can install using pip:

pip install setmlvis

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

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

Development Installation

Create a dev environment:

1. Conda

   conda create -n setmlvis-dev -c conda-forge nodejs yarn python jupyterlab
   conda activate setmlvis-dev

2. venv

   py -m venv env
   .\env\Scripts\activate

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

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

You will need jupyter lab 3.x or jupyter notebook installed. If you don't have it, run, e.g.:

pip install jupyterlab<4

When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. You need yarn installed first. If you don't, run:

npm install yarn

Then, to enable the extensions for lab, run the command:

jupyter labextension develop --overwrite .

and

yarn run build

or

.\node_modules\yarn\bin\yarn run build

For classic notebook, you need to run:

jupyter nbextension install --sys-prefix --symlink --overwrite --py setmlvis
jupyter nbextension enable --sys-prefix --py setmlvis

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.

# 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.

Updating the version

To update the version, install tbump and use it to bump the version. By default it will also create a tag.

pip install tbump
tbump <new-version>