  import logging
  
  from lib.config import FaceswapConfig
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  MASK_TYPES = get_available_masks()
  MASK_INFO = ("The mask to be used for training:"
 
</s> remove MASK_TYPES = ["none", "dfaker", "dfl_full", "components"]
 </s> add MASK_TYPES = get_available_masks() </s> remove from lib.umeyama import umeyama

 </s> add  </s> remove              "\n\tnone: Doesn't use any mask."
             "\n\tdfaker: A basic face hull mask using a facehull of all 68 landmarks."
             "\n\tdfl_full: An improved face hull mask using a facehull of 3 facial parts"
             "\n\tcomponents: An improved face hull mask using a facehull of 8 facial parts")
 </s> add              "\n\t none: Doesn't use any mask."
             "\n\t components: An improved face hull mask using a facehull of 8 facial parts"
             "\n\t dfl_full: An improved face hull mask using a facehull of 3 facial parts"
             "\n\t facehull: Face cutout based on landmarks")
from lib.model.masks import get_available_masks
  import logging
  
  from lib.config import FaceswapConfig
from lib.model.masks import get_available_masks
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  
  MASK_TYPES = get_available_masks()
  MASK_INFO = ("The mask to be used for training:"
keep keep add keep keep keep keep keep
 Convert refactor (#703)

* Separate predict and implement pool

* Add check and raise error to multithreading

Box functions to config. Add crop box option.

* All masks to mask module. Refactor convert masks

Predicted mask passed from model. Cli update

* Intesect box with mask and fixes

* Use raw NN output for convert

Use raw mask for face adjustments. Split adjustments to pre and post warp

* Separate out adjustments. Add unmask sharpen

* Set sensible defaults. Pre PR Testing

* Fix queue sizes. Move masked.py to lib

* Fix Skip Frames. Fix GUI Config popup

* Sensible queue limits. Add a less resource intensive single processing mode

* Fix predicted mask. Amend smooth box defaults

* Deterministic ordering for video output

* Video to Video convert implemented

* Fixups

- Remove defaults from folders across all stages
- Move match-hist and aca into color adjustments selectable
- Handle crashes properly for pooled processes
- Fix output directory does not exist error when creating a new output folder
- Force output to frames if input is not a video

* Add Color Transfer adjustment method

Wrap info text in GUI plugin configure popup

* Refactor image adjustments. Easier to create plugins

Start implementing config options for video encoding

* Add video encoding config options

Allow video encoding for frames input (must pass in a reference video)
Move video and image output writers to plugins

* Image writers config options

Move scaling to cli
Move draw_transparent to images config
Add config options for cv2 writer
Add Pillow image writer

* Add gif filetype to Pillow. Fix draw transparent for Pillow

* Add Animated GIF writer

standardize opencv/pillow defaults

* [speedup] Pre-encode supported writers in the convert pool (opencv, pillow)

Move scaling to convert pool
Remove dfaker mask

* Fix default writer

* Bugfixes

* Better custom argparse formatting 
plugins/train/_config.py