Bootstrapper
A plugin to quickly generate dense ground truth with sparse labels
Introduction
napari-bootstrapper
is a tool to quickly generate dense 3D labels using sparse 2D labels within napari.
Dense 3D segmentations are generated using the 2D->3D method described in the preprint titled Sparse Annotation is Sufficient for Bootstrapping Dense Segmentation. In the preprint, we show sparse 2D annotations made in ~10 minutes on a single section can generate dense 3D segmentations that are reasonably good starting points for refining or bootstrapping.
This plugin is limited to the 2D->3D method and is intended for small volumes that can fit in memory. For more complex bootstrapping workflows, dedicated 3D models, and block-wise processing of large volumes, we recommend using the Bootstrapper CLI tool.
Installation
We recommend installing napari-bootstrapper
via conda and pip:
- Create a new environment called
napari-bootstrapper
:
conda create -n napari-bootstrapper -c conda-forge python==3.11 napari pyqt
- Activate the newly-created environment:
conda activate napari-bootstrapper
- You can install
napari-bootstrapper
via pip:
pip install napari-bootstrapper
- Or you can install the latest development version from github:
pip install git+https://github.com/ucsdmanorlab/napari-bootstrapper.git
Getting Started
Run the following in your terminal:
conda activate napari-bootstrapper
napari
Citation
If you find Bootstrapper useful in your research, please consider citing our preprint:
@article {Thiyagarajan2024.06.14.599135,
author = {Thiyagarajan, Vijay Venu and Sheridan, Arlo and Harris, Kristen M. and Manor, Uri},
title = {Sparse Annotation is Sufficient for Bootstrapping Dense Segmentation},
year = {2024},
doi = {10.1101/2024.06.14.599135},
URL = {https://www.biorxiv.org/content/10.1101/2024.06.14.599135v2},
}
Issues
If you encounter any problems, please file an issue along with a detailed description.
Funding
Chan-Zuckerberg Imaging Scientist Award DOI https://doi.org/10.37921/694870itnyzk from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation (funder DOI 10.13039/100014989).
NSF NeuroNex Technology Hub Award (1707356), NSF NeuroNex2 Award (2014862)
Version:
- 0.2.0
Last updated:
- 2025-06-02
First released:
- 2025-05-23
License:
- Copyright (c) 2025, Vijay Venu...
Supported data:
- Information not submitted
Plugin type:
Open extension:
Save extension:
Python versions supported:
Operating system:
- Information not submitted
Requirements:
- numpy
- scipy
- scikit-image
- torch
- numba
- gunpowder
- magicgui
- qtpy
- pyqtgraph
- matplotlib
- napari
- tqdm
- lsds
- mwatershed
- tox; extra == "testing"
- pytest; extra == "testing"
- pytest-cov; extra == "testing"
- pytest-qt; extra == "testing"
- napari; extra == "testing"
- pyqt5; extra == "testing"