A Beginners Guide to Pipelines

What is a Pipeline???

In short, its everything that happens from your raw data to your results. All scripts and algorithms can be represented as a pipeline. If your background is computer science, you may have heard this concept referred to as a “graph”. ImagePypelines at it’s core is just a library to construct pipelines. Let’s teach by example.

y = mx + b

Let’s say we need to make a function to apply a linear transform. Good old y=mx+b

import imagepypelines as ip

# let's build a linear function
def y(m,x,b):
    return m*x + b

tasks = {
        # inputs
        'm' : ip.Input(0),
        'x' : ip.Input(1),
        'b' : ip.Input(2),
        # linear transformer
        'y' : (y, 'm','x','b'),
pipeline = ip.Pipeline(tasks)