                                        "\nL|none: An array of all ones is created to provide a 4th "
                                        "channel that will not mask any portion of the image."
                                        "\nL|components: Mask designed to provide facial "
                                        "segmentation based on the positioning of landmark "
                                        "locations. A convenx hull is constructed around the "
                                        "exterior of the landmarks to create a mask."
                                        "\nL|extended: Mask designed to provide facial segmentation "
                                        "based on the positioning of landmark locations. A convenx "
                                        "hull is constructed around the exterior of the landmarks "
                                        "and the mask is extended upwards onto the forehead."
 
</s> remove                                       "based on the positioning of landmark locations. A convenx "
 </s> add                                       "based on the positioning of landmark locations. A convex " </s> remove     "UNET_DFL options. Mask designed to provide smart segmentation of mostly frontal faces. "
 </s> add     "UNET_DFL options. Mask designed to provide smart segmentation of mostly frontal faces.\n" </s> remove     "VGG_Obstructed options. Mask designed to provide smart segmentation of mostly frontal faces. "
    "The mask model has been specifically trained to recognize some facial obstructions ( "
    "hands and eyeglasses ). Profile faces may result in sub-par performance."
 </s> add     "VGG_Obstructed options. Mask designed to provide smart segmentation of mostly frontal "
    "faces.\nThe mask model has been specifically trained to recognize some facial obstructions "
    "(hands and eyeglasses). Profile faces may result in sub-par performance." </s> remove     "of obstructions.  Profile faces and obstructions may result in sub-par performance."
 </s> add     "of obstructions.\nProfile faces and obstructions may result in sub-par performance." </s> remove                  landmarks_xy=None, filename=None):
 </s> add                  landmarks_xy=None, mask=None, filename=None):
                                      "locations. A convex hull is constructed around the "
                                        "\nL|none: An array of all ones is created to provide a 4th "
                                        "channel that will not mask any portion of the image."
                                        "\nL|components: Mask designed to provide facial "
                                        "segmentation based on the positioning of landmark "
                                      "locations. A convex hull is constructed around the "
                                        "exterior of the landmarks to create a mask."
                                        "\nL|extended: Mask designed to provide facial segmentation "
                                        "based on the positioning of landmark locations. A convenx "
                                        "hull is constructed around the exterior of the landmarks "
                                        "and the mask is extended upwards onto the forehead."
keep keep keep keep replace keep keep keep keep keep
 Mask plugin cleanup

- PEP8 Fixes
- Remove config for non NN Masks
- Tidy up defaults helptext
- cli.py fix typos
- Remove unused imports and functions _base.py
- Standardize input_size param
- Enable and update documentation
- Change references from `aligner` to `masker`
- Change  input_size, output_size and coverage_ratio from kwargs to params
- Move load_aligned to batch input iterator
- Remove unnecessary self.input param
- Add softmax layer append function to KSession
- Remove references to KSession protected objects
- Standardize plugin output into finalize method
- Make masks full frame and add to lib.faces_detect
- Add masks to alignments.json (temporary zipped base64 solution) 
lib/cli.py