Stickerinator!

A small project that I started on a whim when I got annoyed manually cropping images from online. Let's say we had a perfectly cute clipart that we wanted to put into our presentation:

I mean I can boot up good ol' Photoshop, spend a couple minutes fiddling around with the magic select tool, select the background, invert the selection, grow the selection to a couple of pixels, cut the image and paste it on a new file, crop the image, then save it with a transparency layer, buttttt who wants to do that???

Well, I certainly didn't. So that's why I have this "simple" script that allows you to easily remove the background, crop, and even add a white border to this cute little sticker! Here's the output of my program:

Pretty good huh! This was all done through a Google Colab notebook, and that's really the only other file in this repo for now. I'm hoping to be able to continue this with more features that I'll list below.

What It Does

So basically this script will remove the background and add a border while cropping it to a normalized size. However, there are some caveats: The input images need to have a uniform solid-colored background or else the script cannot floodfill properly. Additionally, the filling algorithm will need to have its threshold adjusted for some images as lighter-colored subjects may not have as well distinguished borders.

How to Use

Jupiter Notebook

Simply open up the notebook in Google Colab and run the 2 function initializers. Then, under the Runner section, you can use the FILE_NAME variable to set the file name to input. The 2 functions are already written and can be modified as needed to crop your image!

The program should output the images to the processed folder on Colab.

Python Script

To use the script, you need to install all the required packages. The suggested way to do this is in a virtual environment. Here is the way I would do it: create a venv, activate it, and install packages from requirements.txt.

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

To actually run the program, there are a few important folders:

• /margins will contain the images outputted by the add margins function
• /processed will contain the images outputted by the process images function
• /image* contains input images, these folders are user-created (will be excluded from Git)

NOTE: To leave the virtual environment, simply type deactivate.

Technologies Used

• Google Colab: Great platform for coding and running python notebooks!
• Numpy: Although I've touched it in the past, this project has made me much more familiar with manipulating numpy arrays
• Python Pillow: A cool image manipulation tool that made this whole project possible, with tools like actually reading in the image, flood filling an area with color, Gaussian blurs, and so much more!

Future Ideas/Extensions

• Create a native python script that can be run with any python interpreter (needs command line arguments mostly)
• Add the ability to crop images without solid light colored background -> this is very very very hard TT