  torch.Tensor or a Detectron2.structures.ImageList. You don't need to normalize the channels, as this is
  done by the model. Important to note is that the visual backbone expects BGR channels instead of RGB, as all models
  in Detectron2 are pre-trained using the BGR format. The bbox input are the bounding boxes (i.e. 2D-positions)
  of the input text tokens. This is identical to [LayoutLMModel]. These can be obtained using an
  external OCR engine such as Google's Tesseract (there's a Python
  wrapper available). Each bounding box should be in (x0, y0, x1, y1)
  format, where (x0, y0) corresponds to the position of the upper left corner in the bounding box, and (x1, y1)
  represents the position of the lower right corner. Note that one first needs to normalize the bounding boxes to be on
