From 6a85f4210ab79666509855a1c7e31af36acdca1b Mon Sep 17 00:00:00 2001
From: Mackenzie Mathis <mathis@rowland.harvard.edu>
Date: Mon, 24 Mar 2025 19:08:15 +0100
Subject: [PATCH 1/2] Update README.md

- update link
---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index bbbe8ffa..0e405cd8 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 # CellSeg3D: self-supervised (and supervised) 3D cell segmentation, primarily for mesoSPIM data!
-[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-cellseg3d)](https://www.napari-hub.org/plugins/napari-cellseg3d)
+[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari_cellseg3d)](https://www.napari-hub.org/plugins/napari_cellseg3d)
 [![PyPI](https://img.shields.io/pypi/v/napari-cellseg3d.svg?color=green)](https://pypi.org/project/napari-cellseg3d)
 [![Downloads](https://static.pepy.tech/badge/napari-cellseg3d)](https://pepy.tech/project/napari-cellseg3d)
 [![Downloads](https://static.pepy.tech/badge/napari-cellseg3d/month)](https://pepy.tech/project/napari-cellseg3d)
@@ -7,7 +7,7 @@
 [![codecov](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3D/branch/main/graph/badge.svg?token=hzUcn3XN8F)](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3D)
 <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
 
-<img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/838605d0-9723-4e43-83cd-6dbfe4adf36b/cellseg-logo.png?format=1500w" title="cellseg3d" alt="cellseg3d logo" width="350" align="right" vspace = "80"/>
+<img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/838605d0-9723-4e43-83cd-6dbfe4adf36b/cellseg-logo.png?format=1500w" title="cellseg3d" alt="cellseg3d logo" width="150" align="right" vspace = "80"/>
 
 
 **A package for 3D cell segmentation with deep learning, including a napari plugin**: training, inference, and data review. In particular, this project was developed for analysis of confocal and mesoSPIM-acquired (cleared tissue + lightsheet) tissue datasets, but is not limited to this type of data. [Check out our preprint for more information!](https://www.biorxiv.org/content/10.1101/2024.05.17.594691v1)

From d7718ef9dfa7610cf1001f5410db81991aa53ad2 Mon Sep 17 00:00:00 2001
From: Mackenzie Mathis <mathis@rowland.harvard.edu>
Date: Mon, 24 Mar 2025 19:10:30 +0100
Subject: [PATCH 2/2] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0e405cd8..23729c3f 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,7 @@ To use the plugin, please run:
 ```
 napari
 ```
-Then go into `Plugins > napari-cellseg3d`, and choose which tool to use.
+Then go into `Plugins > napari_cellseg3d`, and choose which tool to use. 
 
 - **Review (label)**: This module allows you to review your labels, from predictions or manual labeling, and correct them if needed. It then saves the status of each file in a csv, for easier monitoring.
 - **Inference**: This module allows you to use pre-trained segmentation algorithms on volumes to automatically label cells and compute statistics.