SUNet¶

Inheritance Diagram

class ashpy.models.convolutional.unet.SUNet(input_res, min_res, kernel_size, initial_filters, filters_cap, channels, use_dropout_encoder=True, use_dropout_decoder=True, dropout_prob=0.3, encoder_non_linearity=<class 'tensorflow.python.keras.layers.advanced_activations.LeakyReLU'>, decoder_non_linearity=<class 'tensorflow.python.keras.layers.advanced_activations.ReLU'>, use_attention=False)[source]¶

Bases: ashpy.models.convolutional.unet.UNet

Semantic UNet

Methods

__init__(input_res, min_res, kernel_size, …)

Args: input_res: input resolution min_res: minimum resolution reached after decode kernel_size: kernel size used in the network initial_filters: number of filter of the initial convolution filters_cap: maximum number of filters channels: number of output channels use_dropout_encoder: whether to use dropout in the encoder module use_dropout_decoder: whether to use dropout in the decoder module dropout_prob: probability of dropout encoder_non_linearity: non linearity of encoder decoder_non_linearity: non linearity of decoder last_activation: last activation function, tanh or softmax (for semantic images) use_attention: whether to use attention

Attributes

`activity_regularizer`	Optional regularizer function for the output of this layer.
`dtype`
`dynamic`
`inbound_nodes`	Deprecated, do NOT use! Only for compatibility with external Keras.
`input`	Retrieves the input tensor(s) of a layer.
`input_mask`	Retrieves the input mask tensor(s) of a layer.
`input_shape`	Retrieves the input shape(s) of a layer.
`input_spec`	Gets the network’s input specs.
`layers`
`losses`	Losses which are associated with this Layer.
`metrics`	Returns the model’s metrics added using compile, add_metric APIs.
`metrics_names`	Returns the model’s display labels for all outputs.
`name`	Returns the name of this module as passed or determined in the ctor.
`name_scope`	Returns a tf.name_scope instance for this class.
`non_trainable_variables`
`non_trainable_weights`
`outbound_nodes`	Deprecated, do NOT use! Only for compatibility with external Keras.
`output`	Retrieves the output tensor(s) of a layer.
`output_mask`	Retrieves the output mask tensor(s) of a layer.
`output_shape`	Retrieves the output shape(s) of a layer.
`run_eagerly`	Settable attribute indicating whether the model should run eagerly.
`sample_weights`
`state_updates`	Returns the updates from all layers that are stateful.
`stateful`
`submodules`	Sequence of all sub-modules.
`trainable`
`trainable_variables`	Sequence of variables owned by this module and it’s submodules.
`trainable_weights`
`updates`
`variables`	Returns the list of all layer variables/weights.
`weights`	Returns the list of all layer variables/weights.