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Superpixel segmentation

In this exercise, you will apply unsupervised segmentation to the same image, before it's passed to a face detection machine learning model.

So you will reduce this image from \(265 \times 191 = 50,615\) pixels down to \(400\) regions.

Young woman
Already preloaded as face_image.

The show_image() function has been preloaded for you as well.

Diese Übung ist Teil des Kurses

Image Processing in Python

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Anleitung zur Übung

  • Import the slic() function from the segmentation module.
  • Import the label2rgb() function from the color module.
  • Obtain the segmentation with 400 regions using slic().
  • Put segments on top of original image to compare with label2rgb().

Interaktive Übung zum Anfassen

Probieren Sie diese Übung aus, indem Sie diesen Beispielcode ausführen.

# Import the slic function from segmentation module
from skimage.____ import ____

# Import the label2rgb function from color module
from skimage.____ import ____

# Obtain the segmentation with 400 regions
segments = ____(____, ____= ____)

# Put segments on top of original image to compare
segmented_image = ____(____, ____, kind='avg')

# Show the segmented image
show_image(segmented_image, "Segmented image, 400 superpixels")
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