dlpy.layers.Segmentation¶
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class
dlpy.layers.Segmentation(name=None, act=None, error=None, target_scale=1.0, src_layers=None, output_image_type=None, output_image_prob=None, **kwargs)¶ Bases: dlpy.layers.Layer
Segmentation layer
Parameters: - name : string, optional
Specifies the name of the layer.
- act : string, optional
Specifies the activation function. possible values: [ AUTO, IDENTITY, LOGISTIC, SIGMOID, TANH, RECTIFIER, RELU, SOFPLUS, ELU, LEAKY, FCMP ]
Default: AUTO- fcmp_act : string, optional
Specifies the FCMP activation function for the layer.
- src_layers : iterable Layer, optional
Specifies the layers directed to this layer.
- height : int, required
Specifies the height of the input data. By default the height is determined automatically when the model training begins.
- width : int, required
Specifies the width of the input data. By default the width is determined automatically when the model training begins.
- depth : int, required
Specifies the depth of the feature maps.
- target_scale : double
Specifies the factor used to scale target values for a segmentation layer.
- src_layers : iterable Layer, optional
Specifies the layers directed to this layer.
- output_image_type: string, optional
Specifies the output image type of this layer. possible values: [ WIDE, PNG, BASE64 ]
Default: WIDE- output_image_prob: bool, options
Does not include probabilities if doing classification (default).
Returns: -
__init__(name=None, act=None, error=None, target_scale=1.0, src_layers=None, output_image_type=None, output_image_prob=None, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__([name, act, error, target_scale, …]) Initialize self. count_instances() format_name([block_num, local_count]) Format the name of the layer get_number_of_instances() to_model_params() Convert the model configuration to CAS action parameters