Official implementation of Deep Convolutional Dictionary Learning for Image Denoising.

Z80

Last update: Dec 21, 2022

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Deep Learning DCDicL_denoising

Overview

DCDicL for Image Denoising

Hongyi Zheng*, Hongwei Yong*, Lei Zhang, "Deep Convolutional Dictionary Learning for Image Denoising," in CVPR 2021. (* Equal contribution)

[paper] [supp]

The implementation of DCDicL is based on the awesome Image Restoration Toolbox [KAIR].

Requirement

PyTorch 1.6+
prettytable
tqdm

Testing

Step 1

Download pretrained models from [OneDrive].
Unzip downloaded file and put the folders into ./release/denoising

Step 2

Configure options/test_denoising.json. Important settings:

task: task name.
path/root: path to save the tasks
path/pretrained_netG: path to the folder containing the pretrained models.
data/n_channels: 1 for greyscale and 3 for color.
test/visualize: true for saving the noisy input/predicted dictionaries.

Step 3

python test_dcdicl.py

Training

Training code will be released soon.

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Comments

Can you please update the readme.md file to reflect the correct Training script

Hi,

While checking I noticed a typo in your Readme file where you have given

-> python train_dcdicl.py

But the actual file name in the repo is train_dncsc.py

opened by nik-steel 1
Getting isuues during training the network

Traceback (most recent call last): File "train_dncsc.py", line 154, in main() File "train_dncsc.py", line 93, in main model.train() File "C:\Users\Downloads\DCDicL_denoising-main\DCDicL_denoising-main\models\model.py", line 214, in train dxs, self.d = self.net(self.y, self.sigma) File "C:\Users\anaconda3\envs\pygpucuda\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:\Users\anaconda3\envs\pygpucuda\lib\site-packages\torch\nn\parallel\data_parallel.py", line 166, in forward return self.module(*inputs[0], **kwargs[0]) File "C:\Users\anaconda3\envs\pygpucuda\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:\Users\Downloads\DCDicL_denoising-main\DCDicL_denoising-main\models\network_denoising.py", line 378, in forward x, d = self.body(x, d, y, Y, alpha_x, beta_x, alpha_d, beta_d, 0.001) File "C:\Users\anaconda3\envs\pygpucuda\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:\Users\Downloads\DCDicL_denoising-main\DCDicL_denoising-main\models\network_denoising.py", line 60, in forward x = self.net_x(torch.cat([x, beta_x],dim=1)) RuntimeError: Tensors must have same number of dimensions: got 5 and 4

opened by amitsoniR 0

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