A python script to organize your images by similarity.
It uses a k-means algorithm to separatem them in clusters.
Watch it working below.
It was about one year since I made the switch from Windows to Linux, and I wanted to get better at the terminal. I always thought it was cool to master it. To make a long story short, one day I did mount a linux image on my external backup drive instead of the pen drive. Some basic /dev/sd* confusion. Anyway's, I overwrited all my photos; so I used Foremost (which is a great tool) to recover them. It recovered 350.000 images; miniatures, textures, profile pictures, wallpapers... and among all that my personal photos. So I wrote a little script to divide the images in folders, 1000 images per folder, if I'm not mistaken. I went through all the folders separating my photos from the random images that weren't important. To end the story, I came up with this script to "cluster" the photos by similiraty and makes things a little easier for me.
How to use
Install the requirements.txt
pip install -r requirements.txt
Add the groupimg to your scripts folder and give it execute permission.
Call the script passing the image folder you want to organize.
groupimg -f /home/user/Pictures/
-f folder where your images are (use absolute path).
groupimg -f /home/user/Pictures
-k number of folders you want to separate your images.
groupimg -f /home/user/Pictures -k 5
-m if you want to move your images instead of just copy them.
-s if you want the algorithm to consider the size of the images as a feature.
Add multiprocessing Rewrite how the script handles the OS calls (find images, navigate to folders...)
Add new ways to break down the image as features
Test it cross platform
Resample the image before processing it
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