Awesome
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: xyan_lei@163.com