  import numpy
  import os
  
  class Convert(object):
      def __init__(self, autoencoder):
          self.autoencoder = autoencoder
           
          self.use_smooth_mask=True
          self.use_avg_color_adjust=True
  
      def patch_image( self, original, face_detected ):
 
</s> remove # Based on: https://gist.github.com/anonymous/d3815aba83a8f79779451262599b0955

 </s> add  </s> remove     def __init__(self, autoencoder):
        self.autoencoder = autoencoder
 </s> add     def __init__(self, encoder):
        self.encoder = encoder
 </s> remove from lib.utils import get_image_paths, get_folder, load_images
 </s> add from pathlib import Path
from lib.FaceFilter import FaceFilter
from lib.faces_detect import detect_faces
from lib.utils import get_image_paths, get_folder </s> remove 
class DetectedFace(object):
    def __init__(self, image, x, w, y, h, landmarks):
        self.image = image
        self.x = x
        self.w = w
        self.y = y
        self.h = h
        self.landmarks = landmarks </s> add 
    def __init__(self, encoder):
        self.encoder = encoder
  import numpy
  import os
  
  class Convert(object):
    def __init__(self, encoder):
        self.encoder = encoder
    def __init__(self, encoder):
        self.encoder = encoder
           
          self.use_smooth_mask=True
          self.use_avg_color_adjust=True
  
      def patch_image( self, original, face_detected ):
keep keep keep keep replace replace keep keep keep keep keep
 Adding models as plugins + Face filtering (#53) + #39 + #43 + #44 + #49 (#61)

* Making Models as plugins

* Do not reload model on each image #39 + Adding FaceFilter #53

* Adding @lukaville PR for #43 and #44 (possibly)

* Training done in a separate thread

* Better log for plugin load

* Adding a prefetch to train.py #49
(Note that we prefetch 2 batches of images, due to the queue behavior)
+ More compact logging with verbose info included

* correction of DirectoryProcessor signature

* adding missing import

* Convert with parallel preprocessing of files

* Added coverage var for trainer

Added a var with comment. Feel free to add it as argument

* corrections

* Modifying preview and normalization of image + correction

* Cleanup 
plugins/Convert_Adjust.py