Inverse

class menpofit.aps.Inverse(aps_interface, eps=1e-05)

Bases: GaussNewton

Inverse Gauss-Newton algorithm for APS.

run(image, initial_shape, gt_shape=None, max_iters=20, return_costs=False)

Execute the optimization algorithm.

Parameters:

• image (menpo.image.Image) – The input test image.
• initial_shape (menpo.shape.PointCloud) – The initial shape from which the optimization will start.
• gt_shape (menpo.shape.PointCloud or None, optional) – The ground truth shape of the image. It is only needed in order to get passed in the optimization result object, which has the ability to compute the fitting error.
• max_iters (int, optional) – The maximum number of iterations. Note that the algorithm may converge, and thus stop, earlier.
• return_costs (bool, optional) – If True, then the cost function values will be computed during the fitting procedure. Then these cost values will be assigned to the returned fitting_result. Note that the costs computation increases the computational cost of the fitting. The additional computation cost depends on the fitting method. Only use this option for research purposes.

Returns:

fitting_result (APSAlgorithmResult) – The parametric iterative fitting result.

appearance_model

Returns the appearance GMRF model.

Type:menpo.model.GMRFModel

deformation_model

Returns the deformation GMRF model.

Type:menpo.model.GMRFModel

template

Returns the template (usually the mean appearance).

Type:menpo.image.Image

transform

Returns the motion model.

Type:OrthoPDM