                 "batch-size: {}".format(length, self.batchsize))
          assert length >= self.batchsize, msg
  
      @staticmethod
      def minibatch(side, is_timelapse, load_process):
          """ A generator function that yields epoch, batchsize of warped_img
              and batchsize of target_img from the load queue """
          logger.debug("Launching minibatch generator for queue (side: '%s', is_timelapse: %s)",
                       side, is_timelapse)
          for batch_wrapper in load_process:
 
</s> remove         logger.debug("Launching minibatch generator for queue (side: '%s', is_timelapse: %s)",
                     side, is_timelapse)
 </s> add         logger.debug("Launching minibatch generator for queue (side: '%s', is_display: %s)",
                     side, is_display) </s> remove         logger.debug("Finished batching: (epoch: %s, side: '%s', is_timelapse: %s)",
                     epoch, side, is_timelapse)
 </s> add         logger.debug("Finished batching: (epoch: %s, side: '%s', is_display: %s)",
                     epoch, side, is_display) </s> remove                              "is_timelapse: %s)",
                             len(batch), [item.shape for item in batch], side, is_timelapse)
 </s> add                              "is_display: %s)",
                             len(batch), [item.shape for item in batch], side, is_display) </s> remove         logger.debug("Finished minibatch generator for queue: (side: '%s', is_timelapse: %s)",
                     side, is_timelapse)
 </s> add         logger.debug("Finished minibatch generator for queue: (side: '%s', is_display: %s)",
                     side, is_display) </s> remove     def process_face(self, filename, side, is_timelapse):
 </s> add     def process_face(self, filename, side, is_display):
    def minibatch(side, is_display, load_process):
                 "batch-size: {}".format(length, self.batchsize))
          assert length >= self.batchsize, msg
  
      @staticmethod
    def minibatch(side, is_display, load_process):
          """ A generator function that yields epoch, batchsize of warped_img
              and batchsize of target_img from the load queue """
          logger.debug("Launching minibatch generator for queue (side: '%s', is_timelapse: %s)",
                       side, is_timelapse)
          for batch_wrapper in load_process:
keep keep keep keep replace keep keep keep keep keep
 Color Augmentation method (#752)

* Color Augmentation: Implement testing code

* Tweak Contrast and Lighting augmentation amounts

* Prevent color augmentation from entering timelapse

* Remove all augmentations from preview images 
lib/training_data.py