class_docstr: Box collection.
  
  BoxList represents a list of bounding boxes as numpy array, where each
  bounding box is represented as a row of 4 numbers,
  [y_min, x_min, y_max, x_max].  It is assumed that all bounding boxes within a
  given list correspond to a single image.
  
  Optionally, users can add additional related fields (such as
  objectness/classification scores).
docstr: Add data to a specified field.
  
  Args:
    field: a string parameter used to speficy a related field to be accessed.
    field_data: a numpy array of [N, ...] representing the data associated
        with the field.
  Raises:
    ValueError: if the field is already exist or the dimension of the field
        data does not matches the number of boxes.
code: def add_field(self, field, field_data):
      """Add data to a specified field.
  
      Args:
        field: a string parameter used to speficy a related field to be accessed.
        field_data: a numpy array of [N, ...] representing the data associated
            with the field.
      Raises:
        ValueError: if the field is already exist or the dimension of the field
            data does not matches the number of boxes.
      """
      if self.has_field(field):
          raise ValueError("Field " + field + "already exists")
      if (
          len(field_data.shape) < 1
          or field_data.shape[0] != self.num_boxes()
      ):
          raise ValueError("Invalid dimensions for field data")
      self.data[field] = field_data
  
file_path: SlowFast/ava_evaluation/np_box_list.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import numpy
label_desc: Use image node_id 5 for calling the BoxList obj's underlying member method code with example usage: obj.add_field(field, field_data) without return types