johnamit/sit-faf-generate-edit

SiT FAF Generation & Editing

This repository contains the trained model weights for the SiT FAF Generation and Editing project. See the Github repository here

File Structure

sit/

• sit_checkpoint_0110000.pt: Main SiT model checkpoint (1.1M steps).
  • Architecture: SiT-XL/2
  • Resolution: 256x256
  • Dataset: FAF Retinal Scans

stylegan/

• stylegan_checkpoint.pkl: Pre-trained StyleGAN2-ADA model.
  • Used for baseline comparisons and FID calculation.

judges/

• 10k_age_judge.pt: Regression model used to evaluate age preservation.
• laterality_judge.pt: Classification model used to evaluate eye laterality (Left/Right) preservation.

Usage

These weights are designed to be used with the scripts in the GitHub repository.

# Example: Generate Synthetic Dataset of 10k Samples
python scripts/prepare_datasets/generate_synthetic_dataset.py \
    --ckpt {path to sit/sit_checkpoint_0110000.pt} \
    --data-path data/images_256_cleaned/metadata_cleaned_256.csv \
    --mapping-file data/class_mapping.json \
    --output-dir data/synthetic_10kSamples \
    --num-samples 10000 \
    --batch-size 32 \
    --cfg-scale 4.0 \
    --seed 42