SoftCropper Development for CanvasMagnet by Khaled AlamSoftCropper Development for CanvasMagnet by Khaled Alam

SoftCropper Development for CanvasMagnet

Khaled Alam

Completed work

Software Engineer

OpenCV

Python

Photography

SoftCropper

SoftCropper is a powerful CLI tool that transforms rectangular images into square, print-ready formats with aesthetic borders and customizable text annotations — built for precision and automation.

Actively used by CanvasMagnet for order prep and A4 layout automation.

📸 Example Results

Before ➡️ After Baby.webp (600×900)

Output (900×900)

Kid.jpg (1100×733)

Output (1100×1100)

A4:

🚀 Features

✅ Auto-square images with optional blurred/solid/gradient padding

🖼️ Add customizable rounded borders around photos

✍️ Annotate left/right/top/bottom with vertical or centered text (great for branding)

📄 Generate auto-arranged A4 collage pages from processed photos

📐 Resize final output by target size (e.g. --size 5.5x5.5cm or --size 55x55mm)

🧪 Includes CLI, Makefile, tests, and PyPI packaging

📦 Requirements

Python >= 3.7

opencv-python

numpy

🔧 Installation

pip install softcropper

For local development:

make venv
make install

⚙️ CLI Usage

softcropper ./input_photos --mode blur --border --text \
  --left "@CanvaMagnet" \
  --right "+971 545800462" \
  --top "Preview" \
  --bottom "www.CanvaMagnet.com" \
  --size 5.5x5.5cm \
  --a4

Options

Flag Description --mode One of: blur (default), solid, gradient --border Add rounded frame around photo --text Enable text mode (requires at least one --left/right/top/bottom) --left Vertical text on left side --right Vertical text on right side --top Centered text above the image --bottom Centered text below the image --size Resize output image (supports mm or cm, e.g. 55x55mm) --a4 Generate A4 page(s) from processed images

✅ Testing

make test

Or manually:

PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 pytest tests/ -v

🛠️ Makefile Commands

make venv         # Create .venv
make install      # Install locally in editable mode
make test         # Run tests
make build        # Build wheel and source dist
make deploy       # Deploy to PyPI
make clean        # Remove virtualenv + build artifacts