HASN

Overview framework

Dependencies and Installation

## git clone this repository
git clone https://github.com/nathan66666/HASN.git
cd HASN

# create an environment with python=3.9
conda create -n hasn python=3.9.17
conda activate hasn
pip install -r requirements.txt

Quick Inference

Step 1: Download the pretrained models

You can put the HASN model in the experiments.

Step 2: Prepare testing data

You can put the testing images in the datasets/test_datasets.

Step 3: Running testing command

python basicsr/test.py -opt options/test/test_HASN.yml

Train

Step1: Prepare training data

• Download the training data from (https://github.com/XPixelGroup/BasicSR/blob/master/docs/DatasetPreparation.md)

Step2: Training for HASN

CUDA_VISIBLE_DEVICES=0 python basicsr/train.py -opt /options/train/HASN/train_HASN.yml

Acknowledgments

This project is based on BasicSR.

📧 Contact

If you have any questions, please feel free to contact: [email protected]