Getting Started

The imagepypelines package is a pipeline processing library for scientists who want to make their code more scalable and sharable with their colleagues. It’s designed with scientists in mind, not software engineers.

ImagePypelines contains tools to turn scripts into robust processing pipelines which can be visualized, saved, copied, or deployed to a server easily.


build coverage python versions pypi package status

ImagePypelines is python3 only, so this might be "pip3" on your machine :p
(remove --user to install systemwide)
pip install imagepypelines[all] --user
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**Note: remove the [all] if you don't wish to install default plugins or opencv-python.

coming soon!
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ImagePypelines is python3 only, so this might be "python3" on your machine :p
git clone
cd imagepypelines
python install
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**Note: This will not install the official ImagePypelines plugins. See the Advanced Startup section below to manually install the Image and Astro plugins.

ImagePypelines Makes Your Scripts More Powerful

placeholder until my capstone code is done

Without ImagePypelines

With ImagePypelines

import numpy as np

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

m = np.ones(500) * 5
x = np.arange(500)
b = np.ones(500) * 12

y = y(m,x,b)
import numpy as np
import imagepypelines as ip

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

m = np.ones(500) * 5
x = np.arange(500)
b = np.ones(500) * 12

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)

y = pipeline.process_and_grab(m,x,b,fetch='y')

I’m a boring normal script

I can be saved to disk, deployed to a server,

or monitored remotely!

Using the Dashboard

<include video here>


Setting up a Virtual Environment

If you have permissions-related installation issues, sometimes a virtual environment can help

To set one up:

python -m venv venv

And activate it with:

# Windows

# Linux

You should now be able to follow the installation steps above without issue. Deactivate your virtual environment with:


Configuring Your ImagePypelines Installation

Image Plugin

ImagePypelines requires OpenCV bindings by default for use in the official image plugin. If you do not have a local OpenCV installation compiled from source, you may install opencv-python on your system or in a virtual environment alongside imagepypelines. Careful though! opencv-python WILL overwrite your own local OpenCV bindings, so proceed with caution!

without opencv

pip install imagepypelines_image

with opencv

pip install imagepypelines_image[cv]

Astro Plugin

Likewise, install our official astronomy plugin via

this is installed by default with imagepypelines[all]

pip install imagepypelines_astro


Brief overview of our various messaging, dashboard, and runtime backends. Currently not a very long list and should reflect vanilla IP. As example redis vs current TCP implementation for messaging


You may want to verify your installation by running the hello-world test pipeline:

imagepypelines hello-world

# Output: Hello World!

If your output matches then you’re ready to code! See our Examples for help converting your script.

ImagePypelines Command Line Interface Overview

More in depth than above. Go over all commands in great detail with example use cases

For Developers

All the developer centric goodies relating to ImagePypelines. Installation, Contribution Guidelines, etc

Installing Docker

While not required, installing Docker will make it easier to run our Dashboard.

You can invoke this containerized version with