      """ apply non-maximum suppression on ROIs in same scale(matrix version)
  
  
      """
      if not np.any(rectangles):
          return rectangles, scores
      bboxes = rectangles[..., :4].T
 
</s> remove     def process_output(self, batch):
        """ Post process the detected faces """
 </s> add     def process_output(self, batch: dict) -> dict:
        """ MTCNN performs no post processing so the original batch is returned

        Parameters
        ----------
        batch: dict
            Contains the batch to apply postprocessing to

        Returns
        -------
        dict
            The originally received batch
        """ </s> remove             return
 </s> add             return retval </s> remove     def init_model(self):
        """ Initialize S3FD Model"""
 </s> add     def init_model(self) -> None:
        """ Initialize MTCNN Model. """
    Parameters
    ----------
    rectangles: :class:`np.ndarray`
        The [b, l, t, r, b] bounding box detection candidates
    threshold: float
        Threshold for succesful match
    method: str, optional
        "iom" method or default. Defalt: "iom"

    Returns
    -------
    rectangles: :class:`np.ndarray`
        The [b, l, t, r, b] bounding boxes
    scores :class:`np.ndarray`
        The associated scores for the rectangles
      """ apply non-maximum suppression on ROIs in same scale(matrix version)
  
    Parameters
    ----------
    rectangles: :class:`np.ndarray`
        The [b, l, t, r, b] bounding box detection candidates
    threshold: float
        Threshold for succesful match
    method: str, optional
        "iom" method or default. Defalt: "iom"

    Returns
    -------
    rectangles: :class:`np.ndarray`
        The [b, l, t, r, b] bounding boxes
    scores :class:`np.ndarray`
        The associated scores for the rectangles
  
      """
      if not np.any(rectangles):
          return rectangles, scores
      bboxes = rectangles[..., :4].T
keep add keep keep keep keep keep
 Add CPU option to BiSeNet and MTCNN
  - Add CPU option to KSession
  - MTCNN optimizations
  - Update docs for bisenet + mtcnn 
plugins/extract/detect/mtcnn.py