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[CVPR 2025] Consistency Posterior Sampling for Diverse Image Synthesis

This is the official PyTorch implementation of Consistency Posterior Sampling for Diverse Image Synthesis [Paper]

Alt text

🛠 Setup

conda create -n cps_diverse python=3.11 -y
conda activate cps_diverse
pip install -r requirements.txt

Download pretrained diffusion and consistency models from following links and place them in 'pretrained_models' folder -

Dataset Diffusion Model Consistency Model
LSUN-Bedroom LSUN-Bedroom-DM LSUN-Bedroom-CM
ImageNet ImageNet-DM ImageNet-CM

Download datasets from OpenAI repo and place them in 'sample_dataset' folder.

⚙️ Fidelity Experiments

#------------------------------------ LSUN-Beadroom (256 x 256) ------------------------------------

## 8x Super-Resolution
CPS_Diverse/scripts/fidelity_exps/solve_SR_our_method_CD_LPIPS_8x_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_SR_our_method_CD_LPIPS_8x_multi_step.sh

## Gaussian Deblur
CPS_Diverse/scripts/fidelity_exps/solve_GD_our_method_CD_LPIPS_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_GD_our_method_CD_LPIPS_multi_step.sh

## Random pixel inpainting (10%)
CPS_Diverse/scripts/fidelity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_10_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_10_multi_step.sh


#------------------------------------ ImageNet (64 x 64) ------------------------------------ 

## 4x Super-Resolution
CPS_Diverse/scripts/fidelity_exps/solve_SR_our_method_CD_LPIPS_4x_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_SR_our_method_CD_LPIPS_4x_multi_step.sh

## Gaussian Deblur
CPS_Diverse/scripts/fidelity_exps/solve_ImNet_GD_our_method_CD_LPIPS_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_ImNet_GD_our_method_CD_LPIPS_multi_step.sh

## Random pixel inpainting (20%)
CPS_Diverse/scripts/fidelity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_20_one_step.sh
CPS_Diverse/scripts/fidelity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_20_multi_step.sh

⚙️ Diversity Experiments

# LSUN-Beadroom (256 x 256)

## 8x Super-Resolution
CPS_Diverse/scripts/diversity_exps/solve_SR_our_method_CD_LPIPS_8x_one_step.sh
CPS_Diverse/scripts/diversity_exps/solve_SR_our_method_CD_LPIPS_8x_multi_step.sh

## Gaussian Deblur
CPS_Diverse/scripts/diversity_exps/solve_GD_our_method_CD_LPIPS_one_step.sh
CPS_Diverse/scripts/diversity_exps/solve_GD_our_method_CD_LPIPS_multi_step.sh

## Random pixel inpainting (10%)
CPS_Diverse/scripts/diversity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_10_one_step.sh
CPS_Diverse/scripts/diversity_exps/solve_pixel_inpaint_our_method_CD_LPIPS_10_multi_step.sh

Acknowledgments

Thanks for open source efforts Cosistency Models codebase. Our code is also built using DPS.