niftynet.layer.pad module¶
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class
PadLayer
(image_name, border, name='pad', mode='minimum', pad_to=(0, ))[source]¶ Bases:
niftynet.layer.base_layer.Layer
,niftynet.layer.base_layer.Invertible
This class defines a padding operation: pad 2*border pixels from spatial dims of the input (numpy array), and return the padded input.
This function is used at volume level (as a preprocessor in image reader) therefore assumes the input has at least three spatial dims.
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__init__
(image_name, border, name='pad', mode='minimum', pad_to=(0, ))[source]¶ Parameters: - image_name – the name of the relevant key in the data dictionary
- border – the dimensions of the desired border around the image.
- name – name of the PadLayer in the tensorflow graph.
- mode – how to choose the padding values for the np.pad operation.
- pad_to – this determines a desired size of the padded image (useful for inconsistent input sizes or for making inference efficient). If it == (0, ) (DEFAULT), it will use the constant padding mode determined by ‘border’
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