steganogan.encoders module¶
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class
steganogan.encoders.
BasicEncoder
(data_depth, hidden_size)[source]¶ Bases:
torch.nn.modules.module.Module
The BasicEncoder module takes an cover image and a data tensor and combines them into a steganographic image.
Input: (N, 3, H, W), (N, D, H, W) Output: (N, 3, H, W)
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add_image
= False¶
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forward
(image, data)[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
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class
steganogan.encoders.
DenseEncoder
(data_depth, hidden_size)[source]¶ Bases:
steganogan.encoders.BasicEncoder
The DenseEncoder module takes an cover image and a data tensor and combines them into a steganographic image.
Input: (N, 3, H, W), (N, D, H, W) Output: (N, 3, H, W)
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add_image
= True¶
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class
steganogan.encoders.
ResidualEncoder
(data_depth, hidden_size)[source]¶ Bases:
steganogan.encoders.BasicEncoder
The ResidualEncoder module takes an cover image and a data tensor and combines them into a steganographic image.
Input: (N, 3, H, W), (N, D, H, W) Output: (N, 3, H, W)
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add_image
= True¶
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