Using the points layer¶
In this document, you will learn about the napari
Points
layer, including
displaying spots over an image that have been found in an automated fashion, or
manually annotating an image with points. You will also understand how to add a
points layer and edit it from the GUI and from the console.
When to use the points layer¶
The points layer allows you to display an NxD
array of N
points in D
coordinates. You can adjust the size, face color, and edge color of all the
points independently. You can also adjust the opactiy, edge width, and symbol
representing all the points simultaneously.
Each data point can have annotations associated with it using the
Points.properties
dictionary. These properties can be used to set the face and
edge colors of the points. For example, when displaying points of different
classes/types, one could automatically set color the individual points by their
respective class/type. For more details on point properties, see the “setting
point edge and face color with properties” below or the point annotation
tutorial.
A simple example¶
You can create a new viewer and add a set of points in one go using the
napari.view_points
method, or if you already have an existing viewer, you can
add points to it using viewer.add_points
. The api of both methods is the same.
In these examples we’ll mainly use add_points
to overlay points onto on an
existing image.
In this example, we will overlay some points on the image of an astronaut:
import napari
import numpy as np
from skimage import data
viewer = napari.view_image(data.astronaut(), rgb=True)
points = np.array([[100, 100], [200, 200], [300, 100]])
points_layer = viewer.add_points(points, size=30)
from napari.utils import nbscreenshot
nbscreenshot(viewer, alt_text="3 points overlaid on an astronaut image")