  # AutoEncoder base classes
  
  import time
  import numpy
  from lib.training_data import minibatchAB, stack_images
  
  encoderH5 = '/encoder.h5'
  decoder_AH5 = '/decoder_A.h5'
  decoder_BH5 = '/decoder_B.h5'
  
 
</s> remove from tqdm import tqdm
 </s> add  </s> remove from lib.faces_detect import detect_faces
 </s> add  </s> remove image_extensions = [".jpg", ".jpeg", ".png"]
 </s> add image_extensions = [".jpg", ".jpeg", ".png", ".tif", ".tiff"] </s> remove def detect_faces(frame):
    face_locations = face_recognition.face_locations(frame)
 </s> add def detect_faces(frame, model="hog"):
    face_locations = face_recognition.face_locations(frame, model=model)
from lib.training_data import TrainingDataGenerator, stack_images

  # AutoEncoder base classes
  
  import time
  import numpy
from lib.training_data import TrainingDataGenerator, stack_images
  
  encoderH5 = '/encoder.h5'
  decoder_AH5 = '/decoder_A.h5'
  decoder_BH5 = '/decoder_B.h5'
  
keep keep keep keep replace keep keep keep keep keep
 Misc updates on master before GAN. Added multithreading + mmod face detector (#109)

* Preparing GAN plugin

* Adding multithreading for extract

* Adding support for mmod human face detector

* Adding face filter argument

* Added process number argument to multiprocessing extractor.

Fixed progressbar for multiprocessing.

* Added tiff as image type.
compression artefacts hurt my feelings.

* Cleanup 
lib/ModelAE.py