Unaligned Guided Thermal Image Super-Resolution [paper]

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}
}