stackview on google colab¶
Interactive image stack viewing in jupyter notebooks based on ipycanvas and ipywidgets.
In this notebook we demonstate its usage on google colab.
Run this notebook in google colab
Installation¶
After starting a new session on google colab, you need to install stackview first.
Also note: The make stackview work in google colab, you need to install ipycanvas==0.11 (read why).
In [1]:
!pip install stackview==0.16.0 ipycanvas==0.11
Requirement already satisfied: stackview==0.16.0 in /usr/local/lib/python3.11/dist-packages (0.16.0) Requirement already satisfied: ipycanvas==0.11 in /usr/local/lib/python3.11/dist-packages (0.11.0) Requirement already satisfied: numpy!=1.19.4 in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (2.0.2) Requirement already satisfied: ipywidgets in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (7.7.1) Requirement already satisfied: scikit-image in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (0.25.2) Requirement already satisfied: ipyevents in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (2.0.2) Requirement already satisfied: toolz in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (0.12.1) Requirement already satisfied: matplotlib in /usr/local/lib/python3.11/dist-packages (from stackview==0.16.0) (3.10.0) Requirement already satisfied: ipykernel in /usr/local/lib/python3.11/dist-packages (from 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If you ran this for the first time, you need to restart your session.
Usage¶
First we test the installation by importing the libraries we're going to use
In [2]:
import stackview
from imageio.v3 import imread
from skimage.filters import gaussian
In [3]:
# Activate widgets in google colab
from google.colab import output
output.enable_custom_widget_manager()
Starting point is a 3D image dataset provided as numpy array.
In [4]:
image_stack = imread('https://github.com/clEsperanto/clesperanto_example_data/raw/main/Haase_MRT_tfl3d1.tif?raw=true')
image_stack.shape
Out[4]:
(120, 160, 160)
In [5]:
stackview.insight(image_stack)
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Out[5]:
Slicing¶
We can explore the dataset interactively using stackview.slice.
In [6]:
stackview.slice(image_stack, zoom_factor=2)
HBox(children=(VBox(children=(VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=320, width=320),…
In [7]:
foggy_brain = gaussian(image_stack, sigma=1)
stackview.curtain(image_stack, foggy_brain, zoom_factor=2)
HBox(children=(VBox(children=(VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=320, width=320),…
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