Comments (7)
It seems you have already trained for 50 epochs. Delete the folder "model_64_25_Res_Bnorm_Adam", then you can retrain the model.
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I already deleted the folder and train the model again but got the same error.
``
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Run "GenerateTrainingPatches.m" to generate training data first.
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My bad. I just recognized that I don't have Train400 folder. How to have this data then? Do I have to copy images to there?
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Just as DnCNN_TrainingCodes_v1.0 .
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@AtenaKid
Have you solved this problem? I have Train400 and Run "GenerateTrainingPatches.m" firstly.Butdatasize remain NAN.
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Are you sure that you add the train400 to your matlab. What is the display when you run the GenerateTrainingPatches?
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Related Issues (20)
- The Wrong when I using the \DnCNN\TrainingCodes\DnCNN_TrainingCodes_v1.1\Demo_Train_model_64_25_Res_Bnorm_Adam.m
- 提供训练集
- params_updates中adam算法的参数更新好像有误
- Size of input images
- Version of DnCNN that is compatible with tensorflow 2.0
- How to resolve this bug? could you please tell me?maybe I solved above problem,but I met the follow problem :
- bug in usage of OpenCV resize function
- Batch Normalization gives worse perfromence
- ERROR: Could not find a version that satisfies the requirement torch==0.4.1 ERROR: No matching distribution found for torch==0.4.1 HOT 1
- Data Preparation for DnCNN3
- vl_argparse(opts, varargin);No function or variable is defined—— 'vl_argparse'。And I can't find matlab code about this function
- Are there any files missing?Such as vl_simplenn_move.m and vl_argparse.m
- main_test.py
- Sigma=45 model in .h5
- If I want to input my own image for deep learning,but i don't need add to Gassian noise level,what should I do? HOT 1
- Lower depth yields same performance
- Repetitive Dataset and DataLoader Creation in PyTorch version
- About Testing
- About image shape debug HOT 2
- The wrng
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