      img_new[crop,crop] = mask/255*img_new + (1-mask/255)*img_old
  
      face_A = '/decoder_A.h5' if not swap_model else '/decoder_B.h5'
      face_B = '/decoder_B.h5' if not swap_model else '/decoder_A.h5'
  
      encoder.load_weights(model_dir + "/encoder.h5")
 
</s> remove def convert_one_image(image, model_dir="models", swap_model=False, use_aligner=False):
 </s> add def smooth_mask(img_old,img_new):
    w,h,c = img_new.shape
    crop = slice(0,w)
    mask = numpy.zeros_like(img_new)
    mask[h//15:-h//15,w//15:-w//15,:] = 255
    mask = cv2.GaussianBlur(mask,(15,15),10)
    img_new[crop,crop] = mask/255*img_new + (1-mask/255)*img_old
def convert_one_image(image, 
                      model_dir="models",
                      swap_model=False,
                      use_aligner=False,
                      use_smooth_mask=True,
                      use_avg_color_adjust=True):
      img_new[crop,crop] = mask/255*img_new + (1-mask/255)*img_old
  
def convert_one_image(image, 
                      model_dir="models",
                      swap_model=False,
                      use_aligner=False,
                      use_smooth_mask=True,
                      use_avg_color_adjust=True):
      face_A = '/decoder_A.h5' if not swap_model else '/decoder_B.h5'
      face_B = '/decoder_B.h5' if not swap_model else '/decoder_A.h5'
  
      encoder.load_weights(model_dir + "/encoder.h5")
keep add keep keep keep keep
 Adjust color average and smooth mask (#31) 
lib/faces_process.py