  import cv2
  import numpy
  
  from lib.aligner import get_align_mat
  
  class Convert():
      def __init__(self, encoder, trainer, blur_size=2, seamless_clone=False, mask_type="facehullandrect", erosion_kernel_size=None, match_histogram=False, sharpen_image=None, draw_transparent=False, **kwargs):
          self.encoder = encoder
          self.trainer = trainer
 
</s> remove                  **kwargs):
 </s> add                  draw_transparent=False, **kwargs): </s> remove         
        mask_b, mask_g, mask_r = cv2.split(image_mask)
        face_b, face_g, face_r = cv2.split(new_face)

        alpha_mask = numpy.ones(mask_b.shape, dtype=mask_b.dtype) * 50
        alpha_face = numpy.ones(face_b.shape, dtype=face_b.dtype) * 50

        image_mask = cv2.merge((mask_b, mask_g, mask_r, alpha_mask))
        new_face = cv2.merge((face_b, face_g, face_r, alpha_face))
 </s> add         image_mask = add_alpha_channel(image_mask, 100)
        new_face = add_alpha_channel(new_face, 100)
 </s> remove 
 </s> add             print(unitMask.shape)
            print(new_image.shape)
            print(base_image.shape)

from lib.utils import add_alpha_channel

  import cv2
  import numpy
  
  from lib.aligner import get_align_mat
from lib.utils import add_alpha_channel
  
  class Convert():
      def __init__(self, encoder, trainer, blur_size=2, seamless_clone=False, mask_type="facehullandrect", erosion_kernel_size=None, match_histogram=False, sharpen_image=None, draw_transparent=False, **kwargs):
          self.encoder = encoder
          self.trainer = trainer
keep keep keep add keep keep keep keep keep
 add draw transparent to adjust. Disable seamless clone with -dt flag 
plugins/convert/Convert_Masked.py