class_docstr: ObjectDetection dataset as DataFrame.
  
  Parameters
  ----------
  data : the input for pd.DataFrame
      The input data.
  dataset_type : str, optional
      The dataset type, can be voc/coco or more, used to annotate the optional fields.
  classes : list of str, optional
      The class synsets for this dataset, if `None`, it will infer from the data.
class_docstr_tok: ["ObjectDetection","dataset","as","DataFrame",".","Parameters","--","--","--","--","--","data",":","the","input","for","pd.DataFrame","The","input","data",".","dataset_type",":","str",",","optional","The","dataset","type",",","can","be","voc\/coco","or","more",",","used","to","annotate","the","optional","fields",".","classes",":","list","of","str",",","optional","The","class","synsets","for","this","dataset",",","if","`","None","`",",","it","will","infer","from","the","data","."]
docstr: Convert image-centric entries to object-centric entries.
  Where single entry carries multiple objects, stored in `rois` column.
  
  The length of returned dataframe is the number of objects in the dataset.
code: def unpack(self):
      """Convert image-centric entries to object-centric entries.
      Where single entry carries multiple objects, stored in `rois` column.
  
      The length of returned dataframe is the number of objects in the dataset.
      """
      if not self.is_packed():
          return self
      orig_classes = self.classes
      new_df = self.explode("rois")
      new_df = pd.concat(
          [
              new_df.drop(["rois"], axis=1),
              new_df["rois"].apply(pd.Series),
          ],
          axis=1,
      )
      new_df = pd.concat(
          [
              new_df.drop(["image_attr"], axis=1),
              new_df["image_attr"].apply(pd.Series),
          ],
          axis=1,
      )
      new_df = self.__class__(new_df.reset_index(drop=True))
      new_df.classes = orig_classes
      return new_df
  
imports: import logging
  import os
  from pathlib import Path
  import warnings
  import numpy
  import pandas
  import matplotlib.pyplot
  from PIL import Image
  import cv2
  from ..data import is_url, url_data
  from ...utils.filesystem import import_try_install
  from ...utils.bbox import bbox_xywh_to_xyxy, bbox_clip_xyxy
label_desc: Use image node_id 8 for calling the ObjectDetectionDataset obj's underlying member method code with example usage: obj.unpack() and returns: new_df, self