code: def describe_diff(
      channels: List[np.ndarray], diff_fraction_threshold: float = 0.01
  ) -> Diff:
      """Describes a pileup image by its diff channel, including nearby variants.
  
      Returns Diff.MANY_DIFFS if the fraction of differences outside potential
      nearby variants is above the diff_fraction_threshold, which is usually
      indicative of sequencing errors. Otherwise return Diff.NEARBY_VARIANTS if
      there are five or more of these, or Diff.FEW_DIFFS if neither of these
      special cases apply.
  
      Args:
          channels: A list of channels of a DeepVariant pileup image. This only uses
            channels[5], the 'differs from ref' channel.
          diff_fraction_threshold: Fraction of total bases of all reads that can
            differ, above which the pileup will be designated as 'many_diffs'.
            Differences that appear due to nearby variants (neater columns) do not
            count towards this threshold. The default is set by visual curation of
            Illumina reads, so it may be necessary to increase this for higher-error
            sequencing types.
  
      Returns:
          One Diff value.
      """
      diff_fraction, nearby_variants = analyze_diff_and_nearby_variants(
          channels
      )
      # Thresholds were chosen by visual experimentation, i.e. human curation.
      if diff_fraction > diff_fraction_threshold:
          return Diff.MANY_DIFFS
      elif nearby_variants >= 5:
          return Diff.NEARBY_VARIANTS
      else:
          return Diff.FEW_DIFFS
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import enum
  import math
  from typing import List, NamedTuple, Tuple
  from etils import epath
  from IPython import display
  import numpy
  from PIL import Image
  from PIL import ImageDraw
  from third_party.nucleus.protos import variants_pb2
label_desc: Use image node_id 28 for calling a global function with example usage: describe_diff(channels, diff_fraction_threshold) and returns: Diff, Diff, Diff