MultilevelFittingResult

class menpo.fitmultilevel.fittingresult.MultilevelFittingResult(image, multiple_fitter, fitting_results, affine_correction, gt_shape=None, error_type='me_norm')

Bases: FittingResult

Object that holds the state of a MultipleFitter object (to which it is linked) after it has fitted a particular image.

Parameters:

image: :class:`menpo.image.masked.MaskedImage` :

The fitted image.

multiple_fitter: :class:`menpo.fitter.base.Fitter` :

The fitter object used to fitter the image.

fitting_results: :class:`menpo.fitter.fittingresult.FittingResult` list :

A list of basic fitting objects.

affine_correction: :class: `menpo.transforms.affine.Affine` :

An affine transform that maps the result of the top resolution fitting level to the space scale of the original image.

gt_shape: class:`menpo.shape.PointCloud`, optional :

The ground truth shape associated to the image.

Default: None

error_type: ‘me_norm’, ‘me’ or ‘rmse’, optional. :

Specifies the way in which the error between the fitted and ground truth shapes is to be computed.

Default: ‘me_norm’

plot_error(figure_id=None, new_figure=False, **kwargs)

Plots the error evolution throughout the fitting.

shapes(as_points=False)

Generates a list containing the shapes obtained at each fitting iteration.

Parameters:

as_points: boolean, optional :

Whether the results is returned as a list of PointClouds or ndarrays.

Default: False

Returns:

shapes: :class:`menpo.shape.PointCoulds or ndarray list :

A list containing the shapes obtained at each fitting iteration.

view(**kwargs)

View the object using the default rendering engine figure handling. For example, the default behaviour for Matplotlib is that all draw commands are applied to the same figure object.

Parameters:

kwargs : dict

Passed through to specific rendering engine.

Returns:

viewer : Renderer

The renderer instantiated.

view_final_fitting(figure_id=None, new_figure=False, **kwargs)

Displays the final fitting result.

view_ground_truth(figure_id=None, new_figure=False, **kwargs)

Displays the ground truth annotation.

view_initialization(figure_id=None, new_figure=False, **kwargs)

Displays the initialization from which the fitting started.

view_new(**kwargs)

View the object on a new figure.

Parameters:

kwargs : dict

Passed through to specific rendering engine.

Returns:

viewer : Renderer

The renderer instantiated.

view_on(figure_id, **kwargs)

View the object on a a specific figure specified by the given id.

Parameters:

figure_id : object

A unique identifier for a figure.

kwargs : dict

Passed through to specific rendering engine.

Returns:

viewer : Renderer

The renderer instantiated.

algorithm

Returns the name of the algorithm used by the Fitter.

downscale

Returns the downscale factor used by the multiple fitter.

error_type

Return the type of error.

errors

Returns a list containing the error at each fitting iteration.

final_error

Returns the final fitting error.

Type:float

final_shape

Returns the final fitted shape.

fitted

Returns the fitted state of each fitting object.

gt_shape

Returns the original ground truth shape associated to the image.

initial_error

Returns the initial fitting error.

Type:float

initial_shape

Returns the initial shape from which the fitting started.

n_iters

Returns the total number of iterations used to fitter the image.

n_levels

Returns the number of levels of the fitter object.

scaled_levels

Returns True if the shape results returned by the basic fitting_results must be scaled.