For queries, contact: hn.gpt1@gmail.com
Required packages:
pip install -r requirements.txt
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.
To replicate our results, extract multi-level edge-maps from an RGB using the code for Richer Convolutional Features for Edge Detection.
A sample .csv
file can be found in the input
folder for the images stored in the datasets
folder.
Model trained on the cats model for 8x super-resolution can be downloaded here
Sample testing scripts:
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.
@inproceedings{gupta2020pyramidal,
title={Pyramidal Edge-Maps and Attention Based Guided Thermal Super-Resolution},
author={Gupta, Honey and Mitra, Kaushik},
booktitle={European Conference on Computer Vision},
pages={698--715},
year={2020},
organization={Springer}
}