The Pipeline module provides a class with the same name which is used to represent a Pipeline.

Pipelines can be applied to Images exactly like Transforms. They consist of a series of Transforms applied in order. They can also be saved/loaded for later use.


Create simple Pipeline

The following script creates a simple pipeline and applies it to a previously loaded image. Info on how to load images can be found here.

from easycv import Pipeline
from easycv.transforms import Blur, Grayscale

pipeline = Pipeline([Grayscale(), Blur(sigma=50)])
img = img.apply(pipeline)

This is the same as doing the following (applying each transform separately):

img = img.apply(Grayscale())
img = img.apply(Blur(sigma=50))

Save and load Pipeline

The following script saves and loads the pipeline created in the last example.


loaded = Pipeline('example.pipe')
img = img.apply(loaded)


If you are running Easycv inside a jupyter notebook there is no need to call show() , the image will be displayed if you evaluate it.

Pipeline Class