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View Code? Open in Web Editor NEW[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark
License: Other
[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark
License: Other
Hello, your network, lednet.pth and lednet_ retrain_ 500000. pth These two networks are both through train_ Is LEDNet.yml the network for training?
What is the difference between the two? What adjustments are needed to obtain the two network models?
What type of machine was used in your training model at that time, and how many days would it take to train?
thank you
The path in argument parse, file generate_low_ligh_imgs.py:
parser.add_argument('--test_path', type=str, default='/mnt/lustre/sczhou/datasets/deblurring/LOLBlur/high_sharp_scaled')
should be generic and not include the developer's filesystem path.
If those arguments are required, it's a good practice not to include a default value, or provide a value that will work in all envirnoments.
wonderful work,please release dataset and code soon!!...
Great work!
I am very interested about the raw data which are untreated by ISP. Could you release and upload them?
could you please release the code of data synthesis pipeline?you have release the code of Darken,but seem to no other part of the pipe
Hello, thanks for your works.
I wanted to train the Conditional Zero-DCE
on a new dataset but finally failed after several attempts. The structure of Conditional Zero-DCE
has some inconsistencies with the original model, and I don't know how to make the loss functions work.
Could you please release the training code of Conditional Zero-DCE
? I'm looking forward to your reply.
Hello,
I'm trying to get the metrics shown in the paper (NRQM NIQE) but could not.
I used pyiqa library and tested with 3 different weight files provided in this repo.
Would you happen to know why? Thank you!
Different from Zero-DCE that uses different curves for RGB channels, CurveNLU applies the same curve to different channels in the feature domain.
Are you fitting all the pixel points with a curve to get the best curve parameters?
I don't really understand that CurveNLU applies the same curve to different channels in the feature domain.
Could you explain this knowledge?
Sorry for any interruptions.
thank you
Hi, do you provide the blur kernel for this dataset? I found some blur parameters in the JSON file but I am unsure how they are used.
Thank you!
I want to export the model using onnx,I met an error when export the model,as onnx cann't support dynamic conv.Do you have any suggestions about solving this error?
This is a great work!
I'm very interested in the data of LOL-Blur without synthetic blur and low light processing and wondering if you could share it.
I followed the step-by-step installation, and did everything needed including installing pytorch and downloaded the pre-trained model.
As I'm trying the very first test:
# test LEDNet (paper model)
python inference_lednet.py --model lednet --test_path ./inputs
I get this error:
python inference_lednet.py --model lednet --test_path ./inputs
Traceback (most recent call last):
File "inference_lednet.py", line 54, in <module>
ckpt_path = load_file_from_url(url=pretrain_model_url['args.model'],
KeyError: 'args.model'
Maybe I missed something in the installation?
Can you please explain how do I fix that?
Thanks ahead! 🙏
I get 404 while downloading lednetgan.pth using included python script. and on Releases section this model does not exist. Where can i download this model?
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