class_docstr: Convert a PIL image to LAB tensor of shape C x H x W
  This transform was proposed in Colorization - https://arxiv.org/abs/1603.08511
  
  The input image is PIL Image. We first convert it to tensor
  HWC which has channel order RGB. We then convert the RGB to BGR
  and use OpenCV to convert the image to LAB. The LAB image is
  8-bit image in range > L [0, 255], A [0, 255], B [0, 255]. We
  rescale it to: L [0, 100], A [-128, 127], B [-128, 127]
  
  The output is image torch tensor.
docstr: Instantiates ImgPil2LabTensor from configuration.
  
  Args:
      config (Dict): arguments for for the transform
  
  Returns:
      ImgPil2LabTensor instance.
code: def from_config(cls, config: Dict[str, Any]) -> "ImgPil2LabTensor":
      """
      Instantiates ImgPil2LabTensor from configuration.
  
      Args:
          config (Dict): arguments for for the transform
  
      Returns:
          ImgPil2LabTensor instance.
      """
      indices = config.get("indices", [])
      return cls(indices=indices)
  
file_path: vissl/vissl/data/ssl_transforms/img_pil_to_lab_tensor.py
imports: from typing import Any, Dict
  import numpy
  import torch
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
  from vissl.utils.misc import is_opencv_available
label_desc: Use image node_id 4 for calling the ImgPil2LabTensor obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls