napari plugin#


Make sure to have a running napari installation.

Via pip#

In the environment with your napari installation run:

$ pip install merge-stardist-masks

Within napari#

Within napari go to Plugins -> Install/Uninstall Plugins... and search for napari-merge-stardist-masks in the lower list. Then click on the blue install button.

After installation#

Make sure to restart napari after the installation. If you do not find the plugins, go to Plugins -> Install/Uninstall Plugins... and toggle the checkboxes in the upper list for stardist-napari and napari-merge-stardist-masks.



Download one of the pre-trained StarDist models from here and unzip the file.

Run a segmentation#

  1. Load sample data with File -> Open sample -> StarDist OPP sample data

  2. Click Plugins -> StarDist OPP. Two widgets will open, the StarDist plugin and this plugin.

  3. All the parameters in the StarDist plugin should be correctly set already. Make sure that the axes in the field Image Axes are correct, for a 3D image it should be ZYX.

  4. Select Custom 2D/3D in the field Model Type and choose the directory where you unzipped the pre-trained model in the Custom Model field. See the image below for the correct settings.
  1. Hit Run. And wait until the CNN calculates the outputs. The outputs of the CNN are displayed once they are calculated.

  2. In the StarDist OPP widget, select again the path to the unzipped pre-trained model in the field model path. Then select StarDist distances (data) and StarDist probability (data) for the dists and probs fields, respectively.

  3. You can play around with the other fields. However, this might lead to errors. For 3D images, you should set subtract dist to 1.00 the other settings are already fine. See the following image for proper settings.
  1. Hit Run in the StarDist OPP widget. The post-processing starts and might take some time (on our machine it takes ~10 minutes). Once the post-processing is done, the label image will be shown in the viewer.