The official code implementation of WACV2023 paper "Pik-Fix: Restoring and Colorizing Old Photos".
Due to copyright restrictions, our real old photo dataset is only available upon personal inquiry. To request access, please email derrickxu1994@gmail.com with the subject "Pik-Fix Data Inquiry" and include your name and affiliation in the message. Then we will reply to you with the download link in 3 days.
There will be three folders in the shared data link: real_old_data
, real_old_ref
, and texture2
. The first one contains
200 image pair with old photos and the repared ones. The second folder contains the reference images we used in our paper. The third folder
contains the necessary texture files you will need to generate fake old photos. These files should be orgnaized as follows:
- Pik-Fix
- data
- real_old_data
- real_old_ref
- texture2
- models
- datasets
- utils
- ...
conda create -n pikfix python=3.7
conda activate pikfix
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch
pip install -r requirements.txt
python setup.py develop
There are two ways
To generate synthetic old photos from good quality images, please first change
the configuration file in hypes_yaml/data_generation.yaml
to modify your data
path, output path, and generation configurations. Next, run the following command:
python utils/data_generation.py --hypes_yaml hypes_yaml/data_generation.yaml