class_docstr: Load an image from file.
  
  Required keys are "img_prefix" and "img_info" (a dict that must contain the
  key "filename"). Added or updated keys are "filename", "img", "img_shape",
  "ori_shape" (same as `img_shape`), "pad_shape" (same as `img_shape`),
  "scale_factor" (1.0) and "img_norm_cfg" (means=0 and stds=1).
  
  Args:
      to_float32 (bool): Whether to convert the loaded image to a float32
          numpy array. If set to False, the loaded image is an uint8 array.
          Defaults to False.
      color_type (str): The flag argument for :func:`mmcv.imfrombytes`.
          Defaults to 'color'.
      file_client_args (dict): Arguments to instantiate a FileClient.
          See :class:`mmcv.fileio.FileClient` for details.
          Defaults to ``dict(backend='disk')``.
      imdecode_backend (str): Backend for :func:`mmcv.imdecode`. Default:
          'cv2'
code: def __init__(
      self,
      to_float32=False,
      color_type="color",
      file_client_args=dict(backend="disk"),
      imdecode_backend="cv2",
  ):
      self.to_float32 = to_float32
      self.color_type = color_type
      self.file_client_args = file_client_args.copy()
      self.file_client = None
      self.imdecode_backend = imdecode_backend
  
file_path: lavis/lavis/common/annotator/uniformer/mmseg/datasets/pipelines/loading.py
imports: import os.path
  import annotator.uniformer.mmcv
  import numpy
  from ..builder import PIPELINES
label_desc: Use image node_id 1 to create a new LoadImageFromFile object from inherited base classes: object with example: obj = LoadImageFromFile(to_float32, color_type, file_client_args, imdecode_backend)