code: def test_distance_t(filter_factory):
      #
      # Test a moving object with a small distance threshold
      #
      tracker = Tracker(
          "euclidean",
          initialization_delay=1,
          distance_threshold=1,
          filter_factory=filter_factory,
      )
  
      # should not match because the distance is too large
      assert (
          len(tracker.update([Detection(points=np.array([[1, 1]]))]))
          == 0
      )
      assert (
          len(tracker.update([Detection(points=np.array([[1, 2]]))]))
          == 0
      )
      assert (
          len(tracker.update([Detection(points=np.array([[1, 3]]))]))
          == 0
      )
      assert (
          len(tracker.update([Detection(points=np.array([[1, 4]]))]))
          == 0
      )
      # a closer point should match
      tracked_objects = tracker.update(
          [Detection(points=np.array([[1, 4.1]]))]
      )
      assert len(tracked_objects) == 1
  
      # check that the estimated position makes sense
      assert tracked_objects[0].estimate[0][0] == 1
      assert 4 < tracked_objects[0].estimate[0][1] <= 4.5
  
file_path: norfair/tests/test_tracker.py
imports: import numpy
  import pytest
  from norfair import Detection, FilterPyKalmanFilterFactory, OptimizedKalmanFilterFactory, Tracker
  from norfair.utils import validate_points
label_desc: Use image node_id 4 for calling a global function with example usage: test_distance_t(filter_factory) without return types