I trained VAEs on 3 datasets extracted from the Describable Textures Dataset (DTD).
- Two 50x50 images datasets:
cracked
(43 images from thecracked
category of the DTD) andhoney
(30 images from thehoneycombed
category) - One 100x100 images dataset:
honey-large
(30 images, same as thehoney
)
Explore the latent space of these pretrained VAE using an intuitive GUI !
Read the report.pdf
file to learn more about this project.
This project was developed in Python 3. The GUI uses matplotlib interactive features and sklearn to compute PCA.
For the VAE, I used the keras (v. 2.3 or higher, running on tensorflow). The original VAE implementation used can be found here.
This project was developed as part of the Computer Graphics and Digital Images course from the computer science first year of Master at ENS de Lyon.