Code from paper "Natural language supervision with a large and diverse dataset builds better models of human high-level visual cortex"
git clone https://github.com/ariaaay/clip2brain.git
cd clip2brain
You will also need to install the natural scene datasets. For downstream analysis you might also need to download coco annotations. It is optional for just running encoding models. The one used for analysis are: 2017 Train/Val annotations (241MB).
(OPTIONAL) Models in comparison to CLIP (SimCLR, SLIP) can be downloaded at: https://github.com/facebookresearch/SLIP?tab=readme-ov-file, under ViT-base structure.
(OPTIONAL) Pycortex DB for the NSD subjects can be downloaded here: https://drive.google.com/drive/folders/1YXAYggtlsfFxMtiqWs0UrMihxI125MHb?usp=sharing
Requirements.txt contains the necessary package for to run the code in this project.
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
Install torch
and torchvision
from PyTorch according to your own system setup.
config.cfg
Modify config.cfg
to reflect local paths to NSD data and COCO annotations.
See current config.cfg
for an example.
Note: project_commands.sh
by default runs all models for all subjects. If you would like to speed up the process and only test out certain model, please comment out models you don't need.
sh project_commands.sh