code: def serve_load_sample(self, data: str) -> Dict:
      encoded_with_padding = (data + "===").encode("ascii")
      img = base64.b64decode(encoded_with_padding)
      buffer = BytesIO(img)
      img = Image.open(buffer, mode="r")
      w, h = img.size
      return {
          DataKeys.INPUT: img,
          DataKeys.METADATA: {
              "size": (h, w),
          },
      }
  
imports: import base64
  from io import BytesIO
  from pathlib import Path
  from typing import Any, Dict, List
  import torch
  import flash
  from flash.core.data.io.input import DataKeys, Input, ServeInput
  from flash.core.data.utilities.loading import IMG_EXTENSIONS, NP_EXTENSIONS, load_image
  from flash.core.data.utilities.paths import PATH_TYPE, filter_valid_files
  from flash.core.data.utilities.samples import to_samples
  from flash.core.utilities.imports import _TORCHVISION_AVAILABLE, Image, requires
label_desc: Use image node_id 1 for calling the ImageDeserializer obj's underlying member method code with example usage: obj.serve_load_sample(data) and returns: dict