@@ -103,7 +103,7 @@ The user can now build a U-Net with a specified number of input channels and num
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First include the Lasagne layers needed to define the U-Net architecture :
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- .. literalinclude:: ../code/Unet_lasagne_recipes.py
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+ .. literalinclude:: ../code/unet/ Unet_lasagne_recipes.py
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:start-after: start-snippet-1
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:end-before: end-snippet-1
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@@ -113,25 +113,25 @@ This is needed to be able to concatenate the feature maps from the contracting t
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First the contracting path :
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- .. literalinclude:: ../code/Unet_lasagne_recipes.py
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+ .. literalinclude:: ../code/unet/ Unet_lasagne_recipes.py
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:start-after: start-snippet-downsampling
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:end-before: end-snippet-downsampling
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And then the bottleneck :
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- .. literalinclude:: ../code/Unet_lasagne_recipes.py
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+ .. literalinclude:: ../code/unet/ Unet_lasagne_recipes.py
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:start-after: start-snippet-bottleneck
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:end-before: end-snippet-bottleneck
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Followed by the expanding path :
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- .. literalinclude:: ../code/Unet_lasagne_recipes.py
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+ .. literalinclude:: ../code/unet/ Unet_lasagne_recipes.py
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:start-after: start-snippet-upsampling
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:end-before: end-snippet-upsampling
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And finally the output path (to obtain *number of classes* feature maps):
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- .. literalinclude:: ../code/Unet_lasagne_recipes.py
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+ .. literalinclude:: ../code/unet/ Unet_lasagne_recipes.py
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:start-after: start-snippet-output
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:end-before: end-snippet-output
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