code: def __init__(
      self,
      prop_range,
      n_boxes=1,
      random_aspect_ratio=True,
      prop_by_area=True,
      within_bounds=True,
      invert=False,
  ):
      if isinstance(prop_range, float):
          prop_range = (prop_range, prop_range)
  
      self.prop_range = prop_range
      self.n_boxes = n_boxes
      self.random_aspect_ratio = random_aspect_ratio
      self.prop_by_area = prop_by_area
      self.within_bounds = within_bounds
      self.invert = invert
  
file_path: PaddleSeg/contrib/CrossPseudoSupervision/batch_transforms/mask_gen.py
imports: import numpy
  from cvlibs import manager
label_desc: Use image node_id 1 to create a new BoxMaskGenerator object from inherited base classes: MaskGenerator with example: obj = BoxMaskGenerator(prop_range, n_boxes, random_aspect_ratio, prop_by_area, within_bounds, invert)