  import cv2
  import numpy
  
  from pathlib import Path
  from scandir import scandir
  
  
 
</s> remove from lib.model import autoencoder_A
from lib.model import autoencoder_B
from lib.model import encoder, decoder_A, decoder_B

 </s> add  </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 from lib.training_data import get_training_data, stack_images
from lib.utils import get_image_paths, get_folder, load_images

from lib.model import autoencoder_A, autoencoder_B
from lib.model import encoder, decoder_A, decoder_B
 </s> add from lib.utils import get_image_paths
import argparse

import argparse
import argparse
  
  from pathlib import Path
  from scandir import scandir
  
  
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 
lib/utils.py