code: def _create_dummy_results(self):
      bboxes = np.array(
          [
              [1330, 317, 418, 1338],
              [792, 24, 723, 2017],
              [693, 291, 307, 894],
              [522, 290, 285, 826],
              [728, 336, 175, 602],
              [92, 337, 267, 681],
          ]
      )
      bboxes[:, 2:4] += bboxes[:, 0:2]
      scores = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
      return dict(
          bboxes=torch.from_numpy(bboxes),
          scores=torch.from_numpy(scores),
      )
  
file_path: mmdetection/tests/test_evaluation/test_metrics/test_crowdhuman_metric.py
imports: import os.path
  import tempfile
  from unittest import TestCase
  import numpy
  import torch
  from mmdet.evaluation import CrowdHumanMetric
label_desc: Use image node_id 1 for calling the TestCrowdHumanMetric obj's underlying member method code with example usage: obj._create_dummy_results() and returns: dict