class_docstr: Convert color space from LAB to RGB.
class_docstr_tok: ["Convert","color","space","from","LAB","to","RGB","."]
docstr: Convert color space from XYZ to RGB.
  
  Args:
     img(np.ndarray): Original XYZ image.
  
  Return:
      img(np.ndarray): Converted RGB image.
code: def xyz2rgb(self, xyz: np.ndarray) -> np.ndarray:
      """
      Convert color space from XYZ to RGB.
  
      Args:
         img(np.ndarray): Original XYZ image.
  
      Return:
          img(np.ndarray): Converted RGB image.
      """
      r = (
          3.24048134 * xyz[:, 0, :, :]
          - 1.53715152 * xyz[:, 1, :, :]
          - 0.49853633 * xyz[:, 2, :, :]
      )
      g = (
          -0.96925495 * xyz[:, 0, :, :]
          + 1.87599 * xyz[:, 1, :, :]
          + 0.04155593 * xyz[:, 2, :, :]
      )
      b = (
          0.05564664 * xyz[:, 0, :, :]
          - 0.20404134 * xyz[:, 1, :, :]
          + 1.05731107 * xyz[:, 2, :, :]
      )
      rgb = np.concatenate(
          (r[:, None, :, :], g[:, None, :, :], b[:, None, :, :]), axis=1
      )
      rgb = np.maximum(
          rgb, 0
      )  # sometimes reaches a small negative number, which causes NaNs
      mask = (rgb > 0.0031308).astype(np.float32)
      np.seterr(invalid="ignore")
      out = (
          1.055 * (rgb ** (1.0 / 2.4)) - 0.055
      ) * mask + 12.92 * rgb * (1 - mask)
      out = np.nan_to_num(out)
      return out
  
imports: import random
  from typing import Callable, Union, List, Tuple
  import cv2
  import PIL
  import numpy
  import paddlehub.vision.functional
label_desc: Use image node_id 2 for calling the LAB2RGB obj's underlying member method code with example usage: obj.xyz2rgb(xyz) and returns: out