z = "hello world" print(z)
Before docing anything else, we need to install some libraries we'll be using:
%%bash pip install scikit-image
Once it's installed, we cab build a simple UI for performing basic image manipulation with scikit-image.
from IPython.html.widgets import interact, interactive, fixed from IPython.display import display
import skimage from skimage import data, filter, io
i = data.coffee()
io.Image(i)
def edit_image(image, sigma=0.1, r=1.0, g=1.0, b=1.0): new_image = filter.gaussian_filter(image, sigma=sigma, multichannel=True) new_image[:,:,0] = r*new_image[:,:,0] new_image[:,:,1] = g*new_image[:,:,1] new_image[:,:,2] = b*new_image[:,:,2] new_image = io.Image(new_image) display(new_image) return new_image
lims = (0.0,1.0,0.01) w = interactive(edit_image, image=fixed(i), sigma=(0.0,10.0,0.1), r=lims, g=lims, b=lims) display(w)
w.result
In Python 3, you can use the new function annotation syntax to describe widgets for interact:
lims = (0.0,1.0,0.01) @interact def edit_image(image: fixed(i), sigma:(0.0,10.0,0.1)=0.1, r:lims=1.0, g:lims=1.0, b:lims=1.0): new_image = filter.gaussian_filter(image, sigma=sigma, multichannel=True) new_image[:,:,0] = r*new_image[:,:,0] new_image[:,:,1] = g*new_image[:,:,1] new_image[:,:,2] = b*new_image[:,:,2] new_image = io.Image(new_image) display(new_image) return new_image