MultilevelFitter¶
- class menpo.fitmultilevel.base.MultilevelFitter[source]¶
Bases: Fitter
Mixin that all MultilevelFitter objects must implement.
- fit(image, initial_shape, max_iters=50, gt_shape=None, error_type='me_norm', verbose=False, view=False, **kwargs)[source]¶
Fits a single image.
Parameters: image: :class:`menpo.image.masked.MaskedImage` :
The image to be fitted.
initial_shape: :class:`menpo.shape.PointCloud` :
The initial shape estimate from which the fitting procedure will start.
max_iters: int or list, optional :
The maximum number of iterations. If int, then this will be the overall maximum number of iterations for all the pyramidal levels. If list, then a maximum number of iterations is specified for each pyramidal level.
Default: 50
gt_shape: PointCloud :
The groundtruth shape of 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’
verbose: boolean, optional :
If True, it prints information related to the fitting results (such as: final error, convergence, ...).
Default: False
view: boolean, optional :
If True, the final fitting result will be visualized.
Default: False
**kwargs: :
Returns: fitting_list: :map:`FittingResultList` :
A fitting result object.
- get_parameters(shape)¶
Abstract method that gets the parameters.
- obtain_shape_from_bb(bounding_box)[source]¶
Generates an initial shape given a bounding box detection.
Parameters: bounding_box: (2, 2) ndarray :
The bounding box specified as:
np.array([[x_min, y_min], [x_max, y_max]])
Returns: initial_shape: :class:`menpo.shape.PointCloud` :
The initial shape.
- perturb_shape(gt_shape, noise_std=0.04, rotation=False)[source]¶
Generates an initial shape by adding gaussian noise to the perfect similarity alignment between the ground truth and reference_shape.
Parameters: gt_shape: :class:`menpo.shape.PointCloud` :
The ground truth shape.
noise_std: float, optional :
The standard deviation of the gaussian noise used to produce the initial shape.
Default: 0.04
rotation: boolean, optional :
Specifies whether ground truth in-plane rotation is to be used to produce the initial shape.
Default: False
Returns: initial_shape: :class:`menpo.shape.PointCloud` :
The initial shape.
- algorithm¶
Returns the name of the fitter object.