InverseCompositional¶
-
class
menpofit.lk.
InverseCompositional
(template, transform, residual, eps=1e-10)[source]¶ Bases:
LucasKanade
Inverse Compositional (IC) Lucas-Kanade algorithm
- Parameters
template (menpo.image.Image or subclass) – The image template.
transform (subclass of
DP
andDX
, optional) – A differential affine transform object, e.g.DifferentiableAlignmentAffine
.residual (class subclass, optional) –
The residual that will get applied. All possible residuals are:
Class
Description
Sum of Squared Differences
Sum of Squared Differences on Fourier domain
Enhanced Correlation Coefficient
Image Gradient
Gradient Correlation
eps (float, optional) – Value for checking the convergence of the optimization.
-
run
(image, initial_shape, gt_shape=None, max_iters=20, return_costs=False)[source]¶ 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 (
LucasKanadeAlgorithmResult
) – The parametric iterative fitting result.
-
warped_images
(image, shapes)¶ Given an input test image and a list of shapes, it warps the image into the shapes. This is useful for generating the warped images of a fitting procedure stored within a
LucasKanadeResult
.- Parameters
image (menpo.image.Image or subclass) – The input image to be warped.
shapes (list of menpo.shape.PointCloud) – The list of shapes in which the image will be warped. The shapes are obtained during the iterations of a fitting procedure.
- Returns
warped_images (list of menpo.image.MaskedImage or ndarray) – The warped images.