  
  autoencoder = autoencoder_B
  
  def convert_one_image( image ):
      assert image.shape == (256,256,3)
      crop = slice(48,208)
      face = image[crop,crop]
      face = cv2.resize( face, (64,64) )
 
</s>
# landmark file can be found in http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
# unzip it in the same folder as the main scripts
aligner = Aligner("shape_predictor_68_face_landmarks.dat")

  
  autoencoder = autoencoder_B
  
# landmark file can be found in http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
# unzip it in the same folder as the main scripts
aligner = Aligner("shape_predictor_68_face_landmarks.dat")

  def convert_one_image( image ):
      assert image.shape == (256,256,3)
      crop = slice(48,208)
      face = image[crop,crop]
      face = cv2.resize( face, (64,64) )
keep keep add keep keep keep keep keep
 Adding dlib landmarks warping for better overlap
Note: You will need to add the shape_predictor_68_face_landmarks.dat file in the root for this to work. Url is provided in aligner.py
lib/faces_process.py