The official repository for BaMBNet

Related tags

Deep Learning BaMBNet
Overview

BaMBNet-Pytorch

Paper: https://arxiv.org/abs/2105.14766 (arXiv)

The code is for the work:

@article{liang2021BaMBNet,
  title={BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring},
  author={Pengwei Liang, Junjun Jiang, Xianming Liu, and Jiayi Ma},
  journal={submitted to IEEE Transactions on Computational Imaging},
  volume={},
  number={},
  pages={},
  year={2021},
}

Requirements

pytorch == 1.7.1
kornia == 0.4.1
opencv == 4.4.0

Dataset

Please refer to the official repo at Defocus deblurring using dual-pixel data.

Train

  • Step 1: train COC network to estimate the blur amounts of DP data.

    python blur_train.py -opt option/train/COC_Dataset_Train.yaml

  • Step 2: prepare the COC maps for deblurring training.

    python blur_test.py -opt option/test/COC_Dataset_Test.yaml

  • Step 3: train the deblurred network.

    python train.py -opt option/train/Deblur_Dataset_Trained.yaml

Test

python test.py -opt option/test/Deblur_Dataset_Test.yaml

License

This project is under the CC-BY-NC 4.0 license. See LICENSE for details.

Comments
  • About first step COCMap training?

    About first step COCMap training?

    Thanks for projects again! I used the config you given to train 20 epochs Cocmap on dataset of Canon by the preprocessing code 'image_to_patch_filter.py' , and the inference results are shown in the figure below Figure 1, all pixels is black with the value >1000.There are several questions: 1.The pixel value of the image is uint16, and the effect of the sub-area described in the paper cannot be seen. I would like to know whether my training is wrong or yours is the same. 2.Why three channel and not a single channel, and what's the meaning of the pixel value on each result graph? In addition, I modified the config "niter: 500000 epoch: 300 #20" , trained it at about 45 epoch(70 000 iter), and the phenomenon of unsupervised loss=0 would appear. Then, the test results were shown in Figure 2, is that normal? image

    opened by pingjun18-li 14
  • How to update the thresholds r2, r3, r4 in your code?

    How to update the thresholds r2, r3, r4 in your code?

    In Section III C of your paper, the thresholds r2-4 are updated by adaptively learning from a small amountof meta-data. However, I don't find this part in your code. I only find you give four static_kernel_size . ”Combined with the model training process, generatingthe defocus mask is a nested optimization“ Where is the nested optimization?

    opened by FlyFish-space 5
  • The input of model in train.py and test.py

    The input of model in train.py and test.py

    1. In your code train.py, the model input is (l_img, r_img, b_img). Is b_img COC map of train dataset? But b_img is not obtained in your blur_train.py. So do I need to change your code blur_test.py to obtain b_img?
    2. In your code test.py, the model input is (l_img, r_img, r_img).If there’s been a mistake？Why do you concatnate two r_img?
    opened by FlyFish-space 3
  • Cannot open the arxiv paper

    Cannot open the arxiv paper

    Hi Guys,

    Want to read your paper but seems the arXiv link cannot be opened by me. Could you check it or send it to me offline ([email protected]) ? Thanks.

    opened by xytmhy 1
  • Input for model in test.py

    Input for model in test.py

    Many thanks for your work. I am confused about the input for model in test.py. It seems that the COC maps are not used as input for model in test.py. While the COC maps ARE used as input for model in train.py. Is it used for ablation study or a wrong setting. Many thanks.

    opened by yarqian 1
  • About pretrained model ?

    About pretrained model ?

    Thanks for providing the code for the BaMBNet, I think it’s a very interesting method! However , it only can be train by single GPU, it will take a lot of time to reproduce the performance. I just want to see the results generated by the model, can you provide your pretrained model ? Thanks again for your help!

    opened by pingjun18-li 1
Owner
Junjun Jiang
He is a Professor at HIT, Harbin, China.
Junjun Jiang
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