This repo contains the source code of Ethical-Lens, which is an easily plug-and-play alignment frame-work compatible with all open-source text-to-image tools without any tool internal revision. Ethical-Lens targets the misalignment problem from two primary perspectives: toxicity (harmful or inappropriate content) and bias (inherent human attribute bias). See our paper for details.
First clone this repo.
git clone https://github.com/yuzhu-cai/Ethical-Lens.git
cd EthicalLens
conda create -n valign python=3.8
conda activate valign
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install jax==0.3.25 jaxlib==0.3.25+cuda11.cudnn805 -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
pip install -r requirements.txt
The installation is the same as FairFace. Please go through the following steps.
cd common/fairface
# Download the pretrained models from https://drive.google.com/drive/folders/1F_pXfbzWvG-bhCpNsRj6F_xsdjpesiFu?usp=sharing
# Save it in the folder 'fair_face_model'.
# Two models are included, race_4 model predicts race as White, Black, Asian and Indian and race_7 model predicts races as White, Black, Latino_Hispanic, East, Southeast Asian, Indian, Middle Eastern.
cd common/AdaTrans
# The pre-trained models can be downloaded at:
# 1. Google Drive: https://drive.google.com/drive/folders/1T5y6l5Byl4pDzFCcDRXDOmmXde2HGg5U?usp=sharing
# 2. Baidu Disk: https://pan.baidu.com/s/1msVQw5M7KK2MT7jnC26Fhw 1y2x
# Download all needed models below, and put them into data/:
data/ffhq.pkl
data/e4e_ffhq_encode.pt
data/r34_a40_age_256_classifier.pth
data/deeplab_model.pth
data/ckpt/15/save_models/model-latest
data/ckpt/20/save_models/model-latest
data/ckpt/31/save_models/model-latest
data/ckpt/Age/save_models/model-latest
data/ckpt/8_9_11/save_models/model-latest
data/ckpt/32_33/save_models/model-latest
Here is a video which showcases the performance of Ethical Lens in various scenarios.
