class_docstr: Provide various chord evaluation scores.
  
  Parameters
  ----------
  detections : str
      File containing chords detections.
  annotations : str
      File containing chord annotations.
  name : str, optional
      Name of the evaluation object (e.g., the name of the song).
class_docstr_tok: ["Provide","various","chord","evaluation","scores",".","Parameters","--","--","--","--","--","detections",":","str","File","containing","chords","detections",".","annotations",":","str","File","containing","chord","annotations",".","name",":","str",",","optional","Name","of","the","evaluation","object","(","e.g.",",","the","name","of","the","song",")","."]
code: def __init__(self, detections, annotations, name=None, **kwargs):
      self.name = name or ""
      self.ann_chords = merge_chords(encode(annotations))
      self.det_chords = merge_chords(
          adjust(encode(detections), self.ann_chords)
      )
      (
          self.annotations,
          self.detections,
          self.durations,
      ) = evaluation_pairs(self.det_chords, self.ann_chords)
      self._underseg = None
      self._overseg = None
  
imports: import numpy
  from .None import evaluation_io, EvaluationMixin
  from ..io import load_chords
label_desc: Use image node_id 1 to create a new ChordEvaluation object from inherited base classes: EvaluationMixin with example: obj = ChordEvaluation(detections, annotations, name)