LandmarksMask

class lib.align.aligned_mask.LandmarksMask(area: T.Literal['eye', 'mouth', 'face', 'face_extended'], landmark_type: LandmarkType, landmarks: npt.NDArray[np.float32], size: int, dilation: float = 0.0, blur_kernel: int = 0, blur_type: T.Literal['gaussian', 'normalized'] | None = 'gaussian', blur_passes: int = 1)

Bases: object

Create a single channel mask from aligned landmark points.

Landmarks masks are created on the fly, so the stored centering and size should be the same as the aligned face that the mask will be applied to. As the masks are created on the fly, blur + dilation is applied to the mask at creation (prior to compression) rather than after decompression when requested.

Note

Threshold is not used for Landmarks mask as the mask is binary

Parameters:

  • area (T.Literal['eye', 'mouth', 'face', 'face_extended']) – The type of mask to obtain. face is a full face mask, face_extended is a face mask that extends above the eyebrows. The others are masks for those specific areas

  • landmark_type (LandmarkType) – The type of landmarks that this mask is being created from

  • landmarks (npt.NDArray[np.float32]) – The landmarks to generate the mask from

  • size (int) – The size (in pixels) that the compressed mask should be

  • dilation (float) – The amount of dilation to apply to the mask. as a percentage of the mask size. Default: 0.0

  • blur_kernel (int) – The kernel size, in pixels to apply gaussian blurring to the mask. Set to 0 for no blurring. Should be odd, if an even number is passed in (outside of 0) then it is rounded up to the next odd number. Default: 0

  • blur_type (T.Literal['gaussian', 'normalized'] | None) – The blur type to use. gaussian or normalized box filter. Default: gaussian

  • blur_passes (int) – The number of passed to perform when blurring. Default: 1

Methods Summary

generate_mask()

Generate the mask.

Methods Documentation

generate_mask() → npt.NDArray[np.uint8]

Generate the mask.

Creates the mask applying any requested dilation and blurring

Return type:

The landmarks based mask

blur_kernel

The kernel size, in pixels to apply gaussian blurring to the mask. Set to 0 for no blurring. Should be odd, if an even number is passed in (outside of 0) then it is rounded up to the next odd number. Default: 0

blur_passes

1

Type:

The number of passed to perform when blurring. Default

blur_type: T.Literal['gaussian', 'normalized'] | None

The blur type to use. gaussian, normalized box filter or None for no blur. Default: gaussian

dilation

The amount of dilation to apply to the mask. as a percentage of the mask size. Default: 0.0

generate_mask() → npt.NDArray[np.uint8]

Generate the mask.

Creates the mask applying any requested dilation and blurring

Return type:

The landmarks based mask

mask

The mask at the size of size with any requested blurring, threshold amount and centering applied.