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we pay more attention to the visual effects rather than psnr in daily work, which is hard to be validated. surely validating is necessary in analysis, I will add it to the scripts.
@wen04141321 I tried validating when training, depart some data from training set as validation set ,and make eval.h5 for your validation set, when training ,you can add code for validating with feed_dict your validation data.
Hello, I want to ask if you don't need to train and validate when you do the experiment? So how do you find the best model?
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