Comments (1)
The lednet.pth
model is the version used in our paper and it was trained using a different framework. The lednet_retrain_500000.pth
model, on the other hand, is a version retrained under the BasicSR framework, making it more practical for further development and usage. Both models were trained with similar settings, resulting in only minor differences between them.
The training process for both models took around 2-3 days on one V100 GPU.
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Related Issues (20)
- please release soon HOT 1
- Please release soon,I want try in my data and test effects. HOT 2
- code HOT 1
- For the dataset, I download fail in train data set,Could it please give other link likes baidu network disk?thanks HOT 2
- KeyError: 'args.model' HOT 2
- Raw data of LOL-Blur HOT 1
- Is the picture here in the paper drawn incorrectly?
- cann't export using onnx for dynamic conv HOT 2
- Default path in generate_low_light_imgs.py should be generic HOT 2
- 404 when using download pretrained model script HOT 1
- the code of our data synthesis pipeline
- lednetgan.pth not found HOT 2
- Training Code of the Conditional Zero-DCE
- About CurveNLU
- the number of GPUs you used in the training process and the GPU's video memory size
- Raw data of LOL-Blur without synthetic blur and low light processing
- Training problem
- blur kernel
- Inconsistant Metrics
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