dark_infer_collections

Here are the low-light image enhancement inference code collections.

Why this project?

Thanks to the researchers for contributing to facilitating the low-light image enhancement field. Nevertheless, I find that there are still many inconveniences for followers due to various factors:

• Framework: Some of the models were implemented by Tensorflow, and some were by Pytorch. On the other hand, early works used old-version frameworks, which is not suitable for the recent ones.

• Coding style: Different coders have different coding styles. It occasionally makes the code reading difficult.

• Closed source: Some researchers have not released their codes publicly. For newbies, reproducing codes is hard.

Therefore, I want to create a unified codes repository for low-light image enhancement by the latest PyTorch framework. This repository includes the inference code collections. If I have more time, I will organize training codes later. Welcome to join the project!

Recent updates

2022.5.2 add RUAS

2022.4.30 add DSLR

2022.4.29 add ReLLIE (need to improve)

2022.4.19 add DALE

2022.4.17 add DRBN(stage1, stage2) & SGM

2022.4.16 add EnlightenGAN

2022.4.14 add ZeroDCE & ZeroDCE++

2022.4.12 start project

Requirements

install

python 3.6+
pillow
torch
torchvision

or

pip install -r requirements.txt

How to run

Download the pre-trained models(OneDrive Password:ymshi) and put "weights" folder into the "dark_infer_collections" fodler.

If testing only one model, e.g., ZeroDCE, you can run the code as follows:

python ZeroDCE/infer.py

Then you can see the results in the folder "output".

TODO

License

The codes are made available for academic research purpose only.

Other links

Lighting-the-Darkness-in-the-Deep-Learning-Era-Open