class_docstr: Read images from image path.
  
  Args:
      to_rgb (bool, optional): If converting image to RGB color space. Default: True.
class_docstr_tok: ["Read","images","from","image","path",".","Args",":","to_rgb","(","bool",",","optional",")",":","If","converting","image","to","RGB","color","space",".","Default",":","True","."]
code: def __call__(self, data: dict) -> dict:
      if isinstance(data["img"], str):
          data["img"] = cv2.imread(data["img"])
  
      for key in data.get("gt_fields", []):
          if isinstance(data[key], str):
              data[key] = cv2.imread(data[key], cv2.IMREAD_UNCHANGED)
          # if alpha and trimap has 3 channels, extract one.
          if key in ["alpha", "trimap"]:
              if len(data[key].shape) > 2:
                  data[key] = data[key][:, :, 0]
  
      if self.to_rgb:
          data["img"] = cv2.cvtColor(data["img"], cv2.COLOR_BGR2RGB)
          for key in data.get("gt_fields", []):
              if len(data[key].shape) == 2:
                  continue
              data[key] = cv2.cvtColor(data[key], cv2.COLOR_BGR2RGB)
  
      return data
  
imports: import random
  import base64
  from typing import Callable, Union, List, Tuple
  import cv2
  import numpy
  import paddle
  import paddle.nn.functional
  from paddleseg.transforms import functional
  from PIL import Image
label_desc: Use image node_id 2 for calling the LoadImages obj's underlying member method code with example usage: obj.__call__(data) and returns: data