class_docstr: Generator the panoptc ground truth for evaluation, where values are 0,1,2,3,...
      11000, 11001, ..., 18000, 18001, ignore_index(general 255).
  
  Args:
      ignore_index (int): The ignore label for semantic segmentation.
      rgb2id (function): Function, panoptic label is encoded in a colored image, this function convert color to the
          corresponding panoptic label.
      label_divisor(int, optional): An Integer, used to convert panoptic id = semantic id * label_divisor + instance_id. Default: 1000.
class_docstr_tok: ["Generator","the","panoptc","ground","truth","for","evaluation",",","where","values","are","0,1,2,3",",","...","11000",",","11001",",","...",",","18000",",","18001",",","ignore_index","(","general","255",")",".","Args",":","ignore_index","(","int",")",":","The","ignore","label","for","semantic","segmentation",".","rgb2id","(","function",")",":","Function",",","panoptic","label","is","encoded","in","a","colored","image",",","this","function","convert","color","to","the","corresponding","panoptic","label",".","label_divisor","(","int",",","optional",")",":","An","Integer",",","used","to","convert","panoptic","id","=","semantic","id","*","label_divisor","+","instance_id",".","Default",":","1000","."]
code: def __init__(self, ignore_index, rgb2id, label_divisor=1000):
      self.ingore_index = ignore_index
      self.rgb2id = rgb2id
      self.label_divisor = label_divisor
  
file_path: PaddleSeg/contrib/PanopticDeepLab/transforms/target_transforms.py
imports: import numpy
label_desc: Use image node_id 1 to create a new RawPanopticTargetGenerator object from inherited base classes: object with example: obj = RawPanopticTargetGenerator(ignore_index, rgb2id, label_divisor)