Sit Faf Generate Edit

--- license: mit tags: - medical - image-generation - diffusion - flow-matching pipeline_tag: unconditional-image-generation --- # SiT FAF Generation & Editing This repository contains the trained model weights for the **SiT FAF Generation and Editing** project. See the Github repository [here](https://github.com/johnamit/sit-faf-generate-edit) ## 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. ```bash # 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 ```

Source context: 0 downloads · 0 likes · Pipeline unconditional-image-generation · Repo johnamit/sit-faf-generate-edit