  #!/usr/bin/env python3
  """ Process training data for model training """
  
  import logging
  
  from hashlib import sha1
  from random import random, shuffle, choice
 
</s> remove from random import random, shuffle, choice
 </s> add from random import shuffle, choice </s> remove import subprocess
 </s> add  </s> remove from hashlib import sha1
 </s> add  </s> remove         image = cv2_read_img(self.images["a"][0], raise_error=True)
 </s> add         image = read_image(self.images["a"][0], raise_error=True) </s> remove from lib.utils import cv2_read_img
 </s> add from lib.image import read_image

""" Handles Data Augmentation for feeding Faceswap Models """
  #!/usr/bin/env python3
""" Handles Data Augmentation for feeding Faceswap Models """
  
  import logging
  
  from hashlib import sha1
  from random import random, shuffle, choice
keep replace keep keep keep keep keep
 Optimize Data Augmentation (#881)

* Move image utils to lib.image
* Add .pylintrc file
* Remove some cv2 pylint ignores
* TrainingData: Load images from disk in batches
* TrainingData: get_landmarks to batch
* TrainingData: transform and flip to batches
* TrainingData: Optimize color augmentation
* TrainingData: Optimize target and random_warp
* TrainingData - Convert _get_closest_match for batching
* TrainingData: Warp To Landmarks optimized
* Save models to threadpoolexecutor
* Move stack_images, Rename ImageManipulation. ImageAugmentation Docstrings
* Masks: Set dtype and threshold for lib.masks based on input face
* Docstrings and Documentation 
lib/training_data.py