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Implicit Diffusion Models for Continuous Super-Resolution

This repository is an offical implementation of the paper "Implicit Diffusion Models for Continuous Super-Resolution" from CVPR 2023.

This repository is still under development.

Updates:

The pre-trained model for 8X face continuous SR has been updated in link.

Environment configuration

The codes are based on python3.7+, CUDA version 11.0+. The specific configuration steps are as follows:

  1. Create conda environment

    conda create -n idm python=3.7.10
conda activate idm

  2. Install pytorch

    conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3

  3. Installation profile

    pip install -r requirements.txt
python setup.py develop

Data preparation

Firstly, download the datasets used.

Then, resize to get LR_IMGS and HR_IMGS.

python data/prepare_data.py  --path [dataset root]  --out [output root] --size 16,128 -l

Pre-trained checkpoints

The pre-trained checkpoints can be found at the following: link.

Training and Validation

Run the following command for the training and validation:

sh run.sh

Add the command "-use_ddim" to implement DDIM sampling.

Acknowledgements

This code is mainly built on SR3, stylegan2-ada-pytorch, and LIIF.