YeNet-Pytorch
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Caenorst
Pytorch implementation of "Deep Learning Hierarchical Representations for Image Steganalysis"
Dear author: Thanks for your implementation about YeNet. However, I want to know whether your source code don't include the part of incorporating the knowledge of selection-channel? In other words....
Dear author I'm using the BOSSbase_1.01 dataset, WOW algorithm 0.4bpp 4000 train, 1000 validation. I train the model but I get valid_accuracy=0.5 could you help me what went wrong?
the dataloaditer is out of date in pytorch1.0, how should I rewrite it or do something to instead? I use the dataloadFolder instead without pair, but the network seems didn't...
when I run the program,I meet blow error: RuntimeError :Expected 4-dimensional input for 4-dimensional weight [30,1,5,5],but got 5- dimensional input of size [16,2,1,256,256] instead I don't know why?please help me!
If the pair_constraint = false, the code will use DatasetNoPair. Like DatasetPair, the DatasetNoPair also can call transform (RandomRot, RandomFlip). In paired mode, the cover and stego images will be...
in train_loader, pair_constraint=not(args.use_batch_norm), Why set pair_constraint as False when use batch normalization? In your implementation, the image don't be normalized to [0.0,1.0]?