Underwater image enhancement

Related tags

Deep Learning LANet
Overview

LANet

Our work proposes an adaptive learning attention network (LANet) to solve the problem of color casts and low illumination in underwater images.

Dependencies

The code runs with Python=3.6 and requires Pytorch of version 1.7 or higher. Please pip install the following packages:

  • numpy=1.20.2
  • torchvision=0.8.0
  • matplotlib=3.4.2
  • opencv-python=4.5.2.54
  • scipy=1.7.0

Training

1. Download the code
2. run Python train.py --input_images-path ./data/trainA/ --label_images_path ./data/trainB/ 
3. Find checkpoint in the "./checkpoints/" folder
The training data includes input data and label data. input data are in the "./data/trainA" folder, label data are in the "./data/trainB" folder

Testing

1. pre-trained models in the "./checkpoints/" folder
2. Put your testing images in the "./data/test/" folder 
3. run Python test.py --test_pth ./data/test/ --snapshot_pth ./checkpoints/model_epoch_40.pk
4. Find the result in "./results" folder

Contact

If you have any questions, please contact Shiben Liu at [email protected].

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