class_docstr: Apply Equalize transformation to image. The bboxes, masks and
  segmentations are not modified.
  
  Args:
      prob (float): The probability for performing Equalize transformation.
class_docstr_tok: ["Apply","Equalize","transformation","to","image",".","The","bboxes",",","masks","and","segmentations","are","not","modified",".","Args",":","prob","(","float",")",":","The","probability","for","performing","Equalize","transformation","."]
docstr: Equalizes the histogram of one image.
docstr_tok: ["Equalizes","the","histogram","of","one","image","."]
code: def _imequalize(self, results):
      """Equalizes the histogram of one image."""
      for key in results.get("img_fields", ["img"]):
          img = results[key]
          results[key] = mmcv.imequalize(img).astype(img.dtype)
  
imports: import copy
  import cv2
  import mmcv
  import numpy
  from ..builder import PIPELINES
  from .compose import Compose
label_desc: Use image node_id 2 for calling the EqualizeTransform obj's underlying member method code with example usage: obj._imequalize(results) without return types