Interactive image visualization with napari#
napari is a python-based image viewer. This notebook demonstrates how to remote control it from python.
See also
For opening an image, we still use scikit-image:
import napari
from skimage.io import imread
import napari_segment_blobs_and_things_with_membranes as nsbatm
import napari_skimage_regionprops as nsr
# Create an empty viewer
viewer = napari.Viewer()
First we load an image and show it in the viewer.
image = imread('../../data/nuclei.tif')
viewer.add_image(image)
<Image layer 'image' at 0x1e423868df0>
With this command, we can make a screenshot of napari and save it in our notebook.
napari.utils.nbscreenshot(viewer)
Cell segmentation#
We can also segment the nuclei and show them on top of the image.
label_image = nsbatm.voronoi_otsu_labeling(image, spot_sigma=9)
# add labels to viewer
label_layer = viewer.add_labels(label_image)
You can visualize labelled objects as overlay (per default)
napari.utils.nbscreenshot(viewer)
… or as opaque contours
label_layer.contour = 2
label_layer.opacity = 1
napari.utils.nbscreenshot(viewer)
Quantitative measurements#
We can also derive quantitative measurements and attach them to the napari viewer.
nsr.regionprops_table(image, label_image, napari_viewer=viewer)
napari.utils.nbscreenshot(viewer)
Napari status bar display of label properties disabled because https://github.com/napari/napari/issues/5417 and https://github.com/napari/napari/issues/4342
