class_docstr: Attribute:
      polygons (list[ndarray]): list[ndarray]: polygons for this mask.
          Each ndarray has format [x, y, x, y, ...]
      mask (ndarray): a binary mask
code: def mask_to_polygons(self, mask):
      if cv2 is None:
          raise ImportError("Unable to import cv2")
      # cv2.RETR_CCOMP flag retrieves all the contours and arranges them to a 2-level
      # hierarchy. External contours (boundary) of the object are placed in hierarchy-1.
      # Internal contours (holes) are placed in hierarchy-2.
      # cv2.CHAIN_APPROX_NONE flag gets vertices of polygons from contours.
      mask = np.ascontiguousarray(
          mask
      )  # some versions of cv2 does not support incontiguous arr
      res = cv2.findContours(
          mask.astype("uint8"), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE
      )
      hierarchy = res[-1]
      if hierarchy is None:  # empty mask
          return [], False
      has_holes = (hierarchy.reshape(-1, 4)[:, 3] >= 0).sum() > 0
      res = res[-2]
      res = [x.flatten() for x in res]
      # These coordinates from OpenCV are integers in range [0, W-1 or H-1].
      # We add 0.5 to turn them into real-value coordinate space. A better solution
      # would be to first +0.5 and then dilate the returned polygon by 0.5.
      res = [x + 0.5 for x in res if len(x) >= 6]
      return res, has_holes
  
imports: import colorsys
  import logging
  import math
  from enum import Enum, unique
  import numpy
  import matplotlib
  import matplotlib.colors
  import matplotlib.figure
  import torch
  from matplotlib.backends.backend_agg import FigureCanvasAgg
  from PIL import Image
  from ..data.registry.catalog import MetadataCatalog
  from ..data.structures import BitMasks, Boxes, BoxMode, Keypoints, PolygonMasks
label_desc: Use image node_id 5 for calling the GenericMask obj's underlying member method code with example usage: obj.mask_to_polygons(mask) and returns: res,  has_holes, list,  False