class_docstr: Metric util function mixin.
class_docstr_tok: ["Metric","util","function","mixin","."]
docstr: Get a single result from group_class_detection_label and return a matrix of IoUs.
docstr_tok: ["Get","a","single","result","from","group_class_detection_label","and","return","a","matrix","of","IoUs","."]
code: def calc_pairwise_ious(
      self, detections, labels
  ) -> t.Dict[int, np.ndarray]:
      """Get a single result from group_class_detection_label and return a matrix of IoUs."""
      pass
  
file_path: deepchecks/deepchecks/vision/metrics_utils/metric_mixin.py
imports: import typing
  from abc import abstractmethod
  import numpy
  from deepchecks.vision.metrics_utils.iou_utils import compute_pairwise_ious, group_class_detection_label, jaccard_iou
label_desc: Use image node_id 2 for calling the MetricMixin obj's underlying member method code with example usage: obj.calc_pairwise_ious(detections, labels) without return types