napari-UniSPAC
A Unified Segmentation framework for Proofreading and Annotation in Connectomics (UniSPAC)!
The napari plugin for UniSPAC [A Unified Segmentation framework for Proofreading and Annotation in Connectomics]. UniSPAC provides interactive 3D neuron segmentation. Neuron segmentation, proofreading and tracking can be done with just mouse clicks, which is much more efficient than existing tools.
Requirements¶
A system with enough GPU memory and pytorch installed. The size of the GPU memory is related to the size of the vEM image that can be processed. For test_roi1_sub_z0-100.tiff
with a shape of 800x800x100, the recommended minimum GPU memory is 12GB.
Installation¶
Step 1: install napari via pip:
pip install -U 'napari[all]'
Step 2: install napari-UniSPAC
git clone https://github.com/ddd9898/napari-UniSPAC.git
cd napari-UniSPAC
pip install -e .
Step 3: run napari:
napari
You can familiarise yourself with how UniSPAC's napari plugin operates by labeling test_roi1_sub_z0-100.tiff
, which is an example of Drosophila vEM images.
Supported data:
- Information not submitted
Plugin type:
GitHub activity:
- Stars: 2
- Forks: 0
- Issues + PRs: 0