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PyTorch implementation of some single image dehazing networks.

Currently Implemented: AOD-Net: An extremely lightweight model (< 10 KB). Results are good.


  1. Python 3
  2. Pytorch 0.4


  1. Create folder "data".
  2. Download and extract the dataset into "data" from the original author's project page. (


  1. Run The script will automatically dump some validation results into the "samples" folder after every epoch. The model snapshots are dumped in the "snapshots" folder.


  1. Run The script takes images in the "test_images" folder and dumps the dehazed images into the "results" folder. A pre-trained snapshot has been provided in the snapshots folder.

Evaluation: WIP.
Some qualitative results are shown below:

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