code: def __init__(
      self,
      ignore_index,
      sigma=8,
      ignore_stuff_in_offset=False,
      small_instance_area=0,
      small_instance_weight=1,
      ignore_crowd_in_semantic=False,
      num_classes=1,
  ):
      self.ignore_index = ignore_index
      self.ignore_stuff_in_offset = ignore_stuff_in_offset
      self.small_instance_area = small_instance_area
      self.small_instance_weight = small_instance_weight
      self.ignore_crowd_in_semantic = ignore_crowd_in_semantic
      self.num_classes = num_classes
  
      # Generate the default Gaussian image for each center
      self.sigma = sigma
      size = 6 * sigma + 3
      x = np.arange(0, size, 1, float)
      y = x[:, np.newaxis]
      x0, y0 = 3 * sigma + 1, 3 * sigma + 1
      self.g = np.exp(
          -((x - x0) ** 2 + (y - y0) ** 2) / (2 * sigma**2)
      )
  
imports: import numpy
  from paddlepanseg.cvlibs import manager
label_desc: Use image node_id 1 to create a new GeneratePanopticDeepLabTrainTargets object from inherited base classes: object with example: obj = GeneratePanopticDeepLabTrainTargets(ignore_index, sigma, ignore_stuff_in_offset, small_instance_area, small_instance_weight, ignore_crowd_in_semantic, num_classes)