SePPO

KO | EN

gitlite — search

#python #hacktoberfest #ai #llm #android #rust #linux #macos #nodejs #java #cli #vue #awesome-list #mcp

(★ 18)

Code for "SePPO: Semi-Policy Preference Optimization for Diffusion Alignment."

SePPO Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# SePPO: Semi-Policy Preference Optimization for Diffusion Alignment.

This is the official repository for the paper: [SePPO: Semi-Policy Preference Optimization for Diffusion Alignment]().

# Visualization
<p align="center"><img src="assets/seppo.png"/ width="100%"><br></p>

Prompts are: 
(1) Photo of a pigeon in a well **tailored suit** getting a cup of coffee in a cafe in the morning; 
(2) Ginger Tabby cat **watercolor** with flowers; 
(3) An image of a peaceful mountain landscape at sunset, with **a small cabin nestled** in the trees and a winding river in the foreground; 
(4) Space dog; 
(5) b\&w photo of 42 y.o man in **white clothes**, bald, face, half body, body, high detailed skin, skin pores, **coastline**, overcast weather.

# Structure

- `utils/` has the scoring models for evaluation or AI feedback (PickScore, HPSv2, Aesthetics, CLIP).
- `valid_scores.py` is score results from the pretrained model.
- `requirements.txt` Basic pip requirements.
- `test.py` You can write your prompt in this file to get an image result output by our trained model.

# Setup

`pip install -r requirements.txt`

# Score Validation

1. Download the pretained SD-1.5 unet checkpoint from [DwanZhang/SePPO](https://huggingface.co/DwanZhang/SePPO) to the weight folder

2. Then download the HPSv2 test data from [HPSv2](https://github.com/tgxs002/HPSv2?tab=readme-ov-file). Put it at any where you want.

Then run:

```
python valid_scores.py --token 'your hf token' --unet_checkpoint '/SePPO/weight' --dataset_name 'pickapic_valid'
```
or
```
python valid_scores.py --token 'your hf token' --unet_checkpoint '/SePPO/weight' --dataset_name 'parti_prompt'
```
or
```
python valid_scores.py --token 'your hf token' --unet_checkpoint '/SePPO/weight' --json_path 'your hpsv2 json filepath' --dataset_name 'hpsv2'
```
## Important Args

- `--token` your huggingface token
- `--unet_checkpoint` the path to pretrained unet weight
- `--dataset_name` dataset you want to evaluate, can be choosed from ["pickapic_valid", "parti_prompt", 'hpsv2']

# Prompt Testing

Run

```
python test.py --unet_checkpoint '/SePPO/weight' --prompt 'your prompt'
```
The output image will be saved to main directory.

# Acknowledge

Thanks to [DiffusionDPO](https://github.com/SalesforceAIResearch/DiffusionDPO) and [diffusers](https://github.com/huggingface/diffusers).

SePPO

SePPO Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

SePPO

SePPO Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README