Forward Gauss-Newton algorithm for APS.
The Forward optimization is too slow. It is not recommended to be used for fitting an APS and is only included for comparison purposes. Use Inverse instead.
run(image, initial_shape, gt_shape=None, max_iters=20, return_costs=False)¶
Execute the optimization algorithm.
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.
APSAlgorithmResult) – The parametric iterative fitting result.
Returns the appearance GMRF model.
Returns the deformation GMRF model.
Returns the template (usually the mean appearance).