InverseCompositional

class menpofit.atm.InverseCompositional(atm_interface, eps=1e-05)

Bases: Compositional

Inverse Compositional (IC) Gauss-Newton algorithm.

run(image, initial_shape, gt_shape=None, max_iters=20, return_costs=False, map_inference=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.
  • map_inference (bool, optional) – If True, then the solution will be given after performing MAP inference.
Returns:

fitting_result (ParametricIterativeResult) – The parametric iterative fitting result.
template

Returns the template of the ATM.

Type:menpo.image.Image or subclass
transform

Returns the model driven differential transform object of the AAM, e.g. DifferentiablePiecewiseAffine or DifferentiableThinPlateSplines.

Type:subclass of DL and DX