code: def _patch_overlaps_any_abnormality_above_threshold(
      y,
      x,
      patch_size,
      abnormalities_masks,
      abnormalities_areas,
      min_overlap_threshold,
  ):
      """Return True if the given patch overlaps significantly with any abnormality.
  
      Given a patch and a single abnormality, the overlap between the two is
      significant if, and only if, the relative area of the intersection of the two
      w.r.t. the area of the patch is above `min_overlap_threshold` OR the
      area of the intersection w.r.t. the total abnormality area is above
      `min_overlap_threshold`.
  
      Args:
        y: Top-most coordinate of the patch.
        x: Left-most coordinate of the patch.
        patch_size: Tuple with (height, width) of the patch.
        abnormalities_masks: List with the binary mask of each abnormality.
        abnormalities_areas: List with the total area of each abnormality.
        min_overlap_threshold:
  
      Returns:
        Returns True if the above condition is met for any of the given
        abnormalities, or False otherwise.
      """
      patch_area = patch_size[0] * patch_size[1]
      for abnorm_mask, abnorm_area in zip(
          abnormalities_masks, abnormalities_areas
      ):
          abnorm_in_patch_area = np.sum(
              abnorm_mask[
                  y : (y + patch_size[0]), x : (x + patch_size[1])
              ]
              > 0
          )
          abnorm_in_patch_wrt_patch = abnorm_in_patch_area / patch_area
          abnorm_in_patch_wrt_abnorm = (
              abnorm_in_patch_area / abnorm_area
          )
          if (
              abnorm_in_patch_wrt_patch > min_overlap_threshold
              or abnorm_in_patch_wrt_abnorm > min_overlap_threshold
          ):
              return True
      return False
  
imports: import csv
  import os
  import re
  from absl import logging
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 9 for calling a global function with example usage: _patch_overlaps_any_abnormality_above_threshold(y, x, patch_size, abnormalities_masks, abnormalities_areas, min_overlap_threshold) and returns: False, True