This notebook serves testing if rectangular images are shown properly
In [1]:
import stackview
from skimage.io import imread, imshow
from skimage.filters import gaussian, threshold_otsu, sobel
from skimage.measure import label
In [2]:
image = imread('data/Haase_MRT_tfl3d1.tif')[:,80:120,:80]
In [3]:
stackview.insight(image)
Out[3]:
|
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When working with small images, the view may be suboptimal.
In [4]:
image.shape
Out[4]:
(120, 40, 80)
In [5]:
stackview.slice(image)
Out[5]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=40, width=80),)),)), IntSlider(value=60, conti…
In [6]:
s = stackview.slice(image)
s.data = image
s
Out[6]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=40, width=80),)),)), IntSlider(value=60, conti…
In [7]:
stackview.slice(image[60])
Out[7]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=40, width=80),)),)), IntSlider(value=20, conti…
In [8]:
stackview.curtain(image[60], gaussian(image[60], sigma=5))
Out[8]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=40, width=80),)),)), IntSlider(value=20, conti…
In [9]:
stackview.curtain(image, gaussian(image, sigma=5))
Out[9]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=40, width=80),)),)), IntSlider(value=60, conti…
In [10]:
slice_image = imread('data/blobs.tif')
from skimage.filters import threshold_otsu
binary = (slice_image > threshold_otsu(slice_image))
In [11]:
stackview.curtain(slice_image, binary, continuous_update=True)
Out[11]:
VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=254, width=256),)),)), IntSlider(value=127, de…
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