class_docstr: An abstract class for all EvaDB object trackers.
class_docstr_tok: ["An","abstract","class","for","all","EvaDB","object","trackers","."]
docstr: Args:
      frame_id (numpy.ndarray): the frame id of current frame
      frame (numpy.ndarray): the input frame with shape (C, H, W)
      labels (numpy.ndarray): Corresponding labels for each box
      bboxes (numpy.ndarray): Array of shape `(n, 4)` or of shape `(4,)` where
      each row contains `(xmin, ymin, width, height)`.
      scores (numpy.ndarray): Corresponding scores for each box
  Returns:
      track_ids (numpy.ndarray): Corresponding track id for each box
      track_labels (numpy.ndarray): Corresponding labels for each box
      track_bboxes (numpy.ndarray):  Array of shape `(n, 4)` of tracked objects
      track_scores (numpy.ndarray): Corresponding scores for each box
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code: def forward(
      self,
      frame_id: numpy.ndarray,
      frame: numpy.ndarray,
      labels: numpy.ndarray,
      bboxes: numpy.ndarray,
      scores: numpy.ndarray,
  ) -> typing.Tuple[
      numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray
  ]:
      """
      Args:
          frame_id (numpy.ndarray): the frame id of current frame
          frame (numpy.ndarray): the input frame with shape (C, H, W)
          labels (numpy.ndarray): Corresponding labels for each box
          bboxes (numpy.ndarray): Array of shape `(n, 4)` or of shape `(4,)` where
          each row contains `(xmin, ymin, width, height)`.
          scores (numpy.ndarray): Corresponding scores for each box
      Returns:
          track_ids (numpy.ndarray): Corresponding track id for each box
          track_labels (numpy.ndarray): Corresponding labels for each box
          track_bboxes (numpy.ndarray):  Array of shape `(n, 4)` of tracked objects
          track_scores (numpy.ndarray): Corresponding scores for each box
      """
      raise NotImplementedError
  
file_path: evadb/evadb/functions/abstract/tracker_abstract_function.py
imports: import typing
  import numpy
  import pandas
  from evadb.catalog.catalog_type import NdArrayType
  from evadb.functions.abstract.abstract_function import AbstractFunction
  from evadb.functions.decorators.decorators import forward, setup
  from evadb.functions.decorators.io_descriptors.data_types import PandasDataframe
label_desc: Use image node_id 3 for calling the EvaDBTrackerAbstractFunction obj's underlying member method code with example usage: obj.forward(frame_id, frame, labels, bboxes, scores) without return types