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PyTorch implementation for Conditional Image Generation via Score-Based Diffusion Generative Models

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Conditional Image Generation with Score-Based Diffusion Models

This repository is an extension of the code base provided by Yang Song for the paper Score-Based Generative Modeling through Stochastic Differential Equations. The code depends on pytorch and pytorch-lightning.

We have extended the code to support multi speed/sde diffusion. Multi speed diffusion opens the avenue for further research in conditional generation and hierarchical represenation learning using the score-based diffusion framework.

In this paper, we use multi speed diffusion to derive the CMDE and VS-CMDE estimators of conditional score. Those estimators are used for conditional image generation. We also provide the code for training conditional score models using the conditional denoising estimator (CDE).

Instructions:

All the information for every experiment is stored in configurational python files. We used the ml_collections python library for constructing the configurational files. Once you have re-written the relevant sections of the configuration you can simply train or test the configuration using the following command:

python -m main.py --mode train or test --config path_to_config

We have included all the configurations for all the experiments presented in this paper under the folder: configs/ve/inverse_problems.

For super-resolution:

VS-CMDE: configs/ve/inverse_problems/super_resolution/celebA_ours_DV_160.py
CMDE: configs/ve/inverse_problems/super_resolution/celebA_ours_NDV_160.py
CDiffE: configs/ve/inverse_problems/super_resolution/celebA_song_160.py
CDE: configs/ve/inverse_problems/super_resolution/celebA_SR3_160.py

For inpainting:

VS-CMDE: configs/ve/inverse_problems/inpainting/celebA_ours_DV.py
CMDE: configs/ve/inverse_problems/inpainting/celebA_ours_NDV.py
CDiffE: configs/ve/inverse_problems/inpainting/celebA_song.py
CDE: configs/ve/inverse_problems/inpainting/celebA_SR3.py

For edge to photo translation:

VS-CMDE: configs/ve/inverse_problems/image_to_image_translation/edges2shoes_ours_DV.py
CMDE: configs/ve/inverse_problems/image_to_image_translation/edges2shoes_ours_NDV.py
CDiffE: configs/ve/inverse_problems/image_to_image_translation/edges2shoes_song.py
CDE: configs/ve/inverse_problems/image_to_image_translation/edges2shoes_SR3.py

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