Principal Component Analysis and Fashion. This is a fork of https://github.com/graceavery/Eigenstyle.

This repo might differ a lot from the original, as I want to make some experiments with it. I won't be sending pull requests for this reason.

• Training image names do not need to be prefixed by Image.
• Added an other folder where you can dump images to train only the principal components.
• Improved support for small datasets.
• Add support for multiple colorspaces: RGB, BW (naive), BW (BT.709 Luma) and CIE XYZ.

• Find a bunch of images.
• Put the ones you like in the "like" folder, the ones you dislike in the "dislike" folder and everything else in the "other" folder.
• In terminal, run

python visuals.py

You'll see the principal components in the "eigendresses" folder (examples shown are from my dataset; yours will be different).

In the "history" folder, you'll see a known dress being rebuilt from its components.

In the "recreatedDresses" folder, you can see just the end product of this process for different dresses.

In the "notableDresses" folder, you'll see the prettiest dresses, the ugliest dresses, the most extreme dresses (those that had high scores on many components), etc.

In the "createdDresses" folder, you'll find completely new dresses that were made from choosing random values for the principal components.