Shape¶
-
class
menpo.shape.base.
Shape
[source]¶ Bases:
Vectorizable
,Transformable
,Landmarkable
,LandmarkableViewable
,Viewable
Abstract representation of shape. Shapes are
Transformable
,Vectorizable
,Landmarkable
,LandmarkableViewable
andViewable
. This base class handles transforming landmarks when the shape is transformed. Therefore, implementations ofShape
have to implement the abstract_transform_self_inplace()
method that handles transforming theShape
itself.-
as_vector
(**kwargs)¶ Returns a flattened representation of the object as a single vector.
Returns: vector ((N,) ndarray) – The core representation of the object, flattened into a single vector. Note that this is always a view back on to the original object, but is not writable.
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copy
()¶ Generate an efficient copy of this object.
Note that Numpy arrays and other
Copyable
objects onself
will be deeply copied. Dictionaries and sets will be shallow copied, and everything else will be assigned (no copy will be made).Classes that store state other than numpy arrays and immutable types should overwrite this method to ensure all state is copied.
Returns: type(self)
– A copy of this object
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from_vector
(vector)¶ Build a new instance of the object from it’s vectorized state.
self
is used to fill out the missing state required to rebuild a full object from it’s standardized flattened state. This is the default implementation, which is which is adeepcopy
of the object followed by a call tofrom_vector_inplace()
. This method can be overridden for a performance benefit if desired.Parameters: vector ( (n_parameters,)
ndarray) – Flattened representation of the object.Returns: object ( type(self)
) – An new instance of this class.
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from_vector_inplace
(vector)¶ Update the state of this object from a vector form.
Parameters: vector ( (n_parameters,)
ndarray) – Flattened representation of this object
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has_nan_values
()¶ Tests if the vectorized form of the object contains
nan
values or not. This is particularly useful for objects with unknown values that have been mapped tonan
values.Returns: has_nan_values (bool) – If the vectorized object contains nan
values.
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n_dims
()¶ The total number of dimensions.
Type: int
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has_landmarks
¶ Whether the object has landmarks.
Type: bool
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landmarks
¶ The landmarks object.
Type: LandmarkManager
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n_landmark_groups
¶ The number of landmark groups on this object.
Type: int
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n_parameters
¶ The length of the vector that this object produces.
Type: int
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