          self.coverage = coverage
          self.scale = scale
          self.zoom = zoom
  
      def minibatchAB(self, images, batchsize):
          batch = BackgroundGenerator(self.minibatch(images, batchsize), 1)
          for ep1, warped_img, target_img in batch.iterator():
              yield ep1, warped_img, target_img
  
      # A generator function that yields epoch, batchsize of warped_img and batchsize of target_img
      def minibatch(self, data, batchsize):
 
</s> remove     def minibatch(self, data, batchsize):
 </s> add     def minibatch(self, data, batchsize, doShuffle=True):
 </s> remove         shuffle(data)
 </s> add         if doShuffle:
            shuffle(data)
 </s> remove                 shuffle(data)
 </s> add                 if doShuffle:
                    shuffle(data)
 </s> remove from .utils import BackgroundGenerator
from .umeyama import umeyama
 </s> add import lib.utils
from lib.umeyama import umeyama

    def minibatchAB(self, images, batchsize, doShuffle=True):
        batch = lib.utils.BackgroundGenerator(self.minibatch(images, batchsize, doShuffle), 1)

          self.coverage = coverage
          self.scale = scale
          self.zoom = zoom
  
    def minibatchAB(self, images, batchsize, doShuffle=True):
        batch = lib.utils.BackgroundGenerator(self.minibatch(images, batchsize, doShuffle), 1)
    def minibatchAB(self, images, batchsize, doShuffle=True):
        batch = lib.utils.BackgroundGenerator(self.minibatch(images, batchsize, doShuffle), 1)
          for ep1, warped_img, target_img in batch.iterator():
              yield ep1, warped_img, target_img
  
      # A generator function that yields epoch, batchsize of warped_img and batchsize of target_img
      def minibatch(self, data, batchsize):
keep keep keep keep replace replace keep keep keep keep keep
 Add timelapse functionality (#512)

* add new cli options

* add timelapse script

* add batch size on image generation

* fix circular dependency

* add attribute check

* refactor to 3 parameters

* fix some typos

* do not shuffle the set

* default to models folder when no timelapse output supplied

* almost forgot this 
lib/training_data.py