https://github.com/brain-to/vae-gan-celeba
Code and notebooks related to the paper: "Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks" by VanRullen & Reddy, 2019
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
○DOI references
-
✓Academic publication links
Links to: arxiv.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (6.8%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
Repository
Code and notebooks related to the paper: "Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks" by VanRullen & Reddy, 2019
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Fork of rufinv/VAE-GAN-CelebA
Created over 5 years ago
· Last pushed over 6 years ago
https://github.com/BRAIN-TO/VAE-GAN-CelebA/blob/master/
# VAE-GAN-CelebA
Python code related to the paper: ["Reconstructing Faces from fMRI Patterns using Deep Generative Neural Networks"](https://arxiv.org/abs/1810.03856) by VanRullen & Reddy (2019)
### This folder contains:
* a [link to a pre-trained VAE-GAN model checkpoint 'vaegan_celeba.ckpt'](http://depotcerco.univ-tlse3.fr/vmcca78o) (~15 epochs on CelebA dataset=50,000 batches of 64 images)
* a set of .py functions for the VAE-GAN face decomposition/reconstruction model, in particular:
* VAEGAN_image2latent.py => goes from any image file to the corresponding 1024D latent encoding (saved as a Matlab .mat file)
* VAEGAN_latent2image.py => goes from a 1024D latent encoding (Matlab .mat file) to the corresponding image(s)
* (optional) [a link to download the fMRI datasets](https://openneuro.org/datasets/ds001761) (4 subjects, each saw > 8,000 faces in the scanner) and some Matlab analysis code
### Example usage:
VAEGAN_image2latent.py -i example.jpg #this will create example_z.mat with the 1024 latent vars
VAEGAN_latent2image.py -i example_z.mat #this will generate example_z_g.jpg (and also example_z_g.mat)
### Requirements:
* Python >= 3.4
* Tensorflow >= 1.8
* matplotlib, numpy, scipy, skimage
Owner
- Name: Brain Research in Advanced Imaging and Neuromodeling - Toronto
- Login: BRAIN-TO
- Kind: organization
- Repositories: 4
- Profile: https://github.com/BRAIN-TO