class_docstr: Implementation of the ObjectSeeker certifiable robust defense applied to object detection models.
  The original implementation is https://github.com/inspire-group/ObjectSeeker
  
  | Paper link: https://arxiv.org/abs/2202.01811
class_docstr_tok: ["Implementation","of","the","ObjectSeeker","certifiable","robust","defense","applied","to","object","detection","models",".","The","original","implementation","is","https",":","\/\/github.com\/inspire-group\/ObjectSeeker","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/2202.01811"]
docstr: Create an ObjectSeeker wrapper.
  
  :param num_lines: The number of divisions both vertically and horizontally to make masked predictions.
  :param confidence_threshold: The confidence threshold to discard bounding boxes.
  :param iou_threshold: The IoU threshold to discard overlapping bounding boxes.
  :param prune_threshold: The IoA threshold for pruning and duplicated bounding boxes.
  :param epsilon: The maximum distance between bounding boxes when merging using DBSCAN.
  :param verbose: Show progress bars.
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code: def __init__(
      self,
      *args,
      num_lines: int = 3,
      confidence_threshold: float = 0.3,
      iou_threshold: float = 0.5,
      prune_threshold: float = 0.5,
      epsilon: float = 0.1,
      verbose: bool = False,
      **kwargs,
  ) -> None:
      """
      Create an ObjectSeeker wrapper.
  
      :param num_lines: The number of divisions both vertically and horizontally to make masked predictions.
      :param confidence_threshold: The confidence threshold to discard bounding boxes.
      :param iou_threshold: The IoU threshold to discard overlapping bounding boxes.
      :param prune_threshold: The IoA threshold for pruning and duplicated bounding boxes.
      :param epsilon: The maximum distance between bounding boxes when merging using DBSCAN.
      :param verbose: Show progress bars.
      """
      super().__init__(*args, **kwargs)  # type: ignore
      self.num_lines = num_lines
      self.confidence_threshold = confidence_threshold
      self.iou_threshold = iou_threshold
      self.prune_threshold = prune_threshold
      self.epsilon = epsilon
      self.verbose = verbose
  
file_path: adversarial-robustness-toolbox/art/estimators/certification/object_seeker/object_seeker.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import abc
  import logging
  from typing import Dict, List, Tuple
  import numpy
  from sklearn.cluster import DBSCAN
  from tqdm.auto import tqdm
  from art.utils import intersection_over_area, non_maximum_suppression
label_desc: Use image node_id 1 to create a new ObjectSeekerMixin object from inherited base classes: abc with example: obj = ObjectSeekerMixin()