/Learnbale_Bandpass_Filter

Image Demoireing with Learnable Bandpass Filters. (CVPR, 2020)(Keras+TensorFlow)

Primary LanguagePython

Learnbale_Bandpass_Filter

Image Demoireing with Learnable Bandpass Filters, CVPR2020

If you find this work is helpful, please cite:

@inProceedings{zheng2020,
author={B. Zheng and S. Yuan and G. Slabaugh and A. Leonardis},
booktitle={IEEE Conference on Computer Vision and Pattern Recongnition},
title={Image Demoireing with Learnable Bandpass Filters},
year={2020},
}

You can now get this paper at Arxiv preprint: https://arxiv.org/abs/2004.00406

Run the code

This project requires:

  • Tensorflow >1.10
  • Keras > 2.0
  • opencv > 2.0
  • skImage

You can get the weight file for AIM2019 via:
https://1drv.ms/u/s!ArU0YIIFiFuHilwyuwHZjSpvPUBz?e=iZ70Ga
or via Baidu Disk:
https://pan.baidu.com/s/1wsJYyYbQO-ETL5Jq4fN6hw code:jiae

You can get AIM2019 LCDMoire2019 dataset via: validation:
Moire: https://data.vision.ee.ethz.ch/timofter/AIM19demoire/ValidationMoire.zip
Clean: https://data.vision.ee.ethz.ch/timofter/AIM19demoire/ValidationClear.zip

testing:
https://data.vision.ee.ethz.ch/timofter/AIM19demoire/TestingMoire.zip

Then,

  1. edit the 'main_multiscale.py' by: replacing the 'test_path', 'valid_gt_path', 'valid_ns_path' and 'weight_path' with your own settings.

  2. make the dirs 'testing_result' and 'validation_result' at current path.

  3. python main_multiscale.py.