paper]
Unaligned Guided Thermal Image Super-Resolution [Authors: Honey Gupta and Kaushik Mitra, IIT Madras
For queries, contact: hn.gpt1@gmail.com
Installation
Required packages:
pip install -r requirements.txt
Preparing the data
Create a test.csv file that contains a list of the input images and the corresponding guide images and place it in the input
folder for inside the method directories.
You can use the create_dataset.py
script to create the csv files.
A sample .csv
file can be found in the input
folder for the images stored in datasets
folder.
Code Usage
Sample testing scripts:
python main.py --checkpoint_dir=checkpoint/flir --log_dir=output/flir_test --config_filename=../configs/test.json
python main.py --checkpoint_dir=checkpoint/cats --log_dir=output/cats_test --config_filename=../configs/test.json
Note: Make sure to modify the configs/test.json
with the appropriate dataset
The results will be stored in --log_dir
folder in the form of a html file. The imgs
folder will contain all the raw inputs and outputs.
More details on the training and testing procedure coming soon!
Cite Us
@article{gupta2021toward,
title={Toward Unaligned Guided Thermal Super-Resolution},
author={Gupta, Honey and Mitra, Kaushik},
journal={IEEE Transactions on Image Processing},
volume={31},
pages={433--445},
year={2021},
publisher={IEEE}
}