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
@ip.blockify()
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)