Intro
Today, I’m excited to open up and share a small part of the customized automation tools I’ve been building behind the scenes to power CanvaMagnet — my personalized photo magnet business. One of the most repetitive challenges in preparing customer orders was manually resizing and formatting each image for production.
To solve this, I developed a Python CLI tool named SoftCropper, designed to automatically square images and add blurred borders, making them perfectly print-ready. After using it internally to streamline our order prep and reduce production time, I decided to open source it so others can benefit too.
The Problem
CanvasMagnet prints square photo magnets — but most customer-submitted photos are vertical or horizontal. Cropping them loses content, padding them looks bad, and doing it by hand slows things down.
The Solution
With OpenCV and NumPy, I built two core functions:
make_square()— adds black padding to make any image squareadd_blurred_borders()— extracts edge pixels, expands them, and applies Gaussian blur
The result: a beautiful soft-bordered square that looks pro — and prints perfectly.
➡️
Packaging It
I wrapped the logic in a CLI tool, made it pip-installable, added setup.py, cli.py, and a clean project structure.
Testing and CI
- ✅ I added unit tests using real
.webpand.jpgimages - ✅ GitHub Actions now runs those tests on each push
- ✅ I even automated patch-version bumping using
Makefile
Published on PyPI
You can now install it with:
pip install softcropper
Use it like:
softcropper ./input_photos ./output_ready
It will:
- Detect all supported images
- Make them square
- Blur the padding
- Save them for print
What’s Next
I’ll likely expose more internal tools that help automate the production pipeline at CanvaMagnet. If you’re prepping images for print, e-commerce, or social, this tool might save you hours.