Skip to content

고양이의 어린 시절을 보여주는 프로젝트 based StyleGAN2

Notifications You must be signed in to change notification settings

noooey/AntiAginGAN-for-Cat

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 

Repository files navigation

Anti-AginGAN for CAT

🐱

Cat Anti-aging Project based StyleGAN2

process

Introduction

😼 We will make a childhood image of the cat for you who adopted an abandoned cat!

Background of topic

Recently, pet shops have emerged as a big social problem in the concept of buying and selling living things for money.
We want to prevent this phenomenon and encourage adoption of abandoned cats.
If a cat is adopted from an abandoned cat center, there are no childhood photos of the cat, u_u
I think we can make that memory for them!

Project Objectives

Encouraging adoption of abandoned cats

Problem Definition

  • The cat's species must not change.
  • The resulting product should resemble the cat in the input image.
  • The result should look young.

Considering the above problems ,
various experiments were conducted to transform cat into kitten.

Environment

  • OS : Ubuntu 18.04 or Colab
  • GPU : Tesla V100-32GB

Data Preparation

  • Web crawling (Crawler)
  • Resizing images to 256*256
  • Image cleaning (Cleaner)

StyleGAN2 ADA

Training StyleGAN2 ADA tf model with custom dataset.

Detail

project11

StyleGAN2 ADA + FreezeD

Fine-tuning the StyleGAN2-ADA tf model pre-trained with afhq cat using custom dataset.

Detail

project3

StyleMixing

Disentangled features can be identified through the result that changes according to the layer being swapped.

ezgif com-gif-maker

PCA

PCA for Latent Space Exploration

Detail


eyes

ears

mouth

face features

Apply to real image

Partially adjust latent vector of Images projected into the latent space, with components found through PCA.

Detail


cat image

projected image

adjust latent vector

Conclusion

We created a kitten generate model through the Stylegan2-ada model.
We explored the latent space to find a latent vector that affects a specific feature.
Using this vector, the projected latent vector was further adjusted to generate the desired images.

In conclusion, we can convert cat into a kitten by combining and applying the components.

References

https://github.com/NVlabs/stylegan2-ada
https://github.com/harskish/ganspace
https://github.com/orpatashnik/StyleCLIP


@BOAZ-bigdata 17th Big Data Conference

About

고양이의 어린 시절을 보여주는 프로젝트 based StyleGAN2

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published