code: def make_streamlines(return_seeds=False):
      streamlines = [
          np.array(
              [[0, 0, 0], [1, 1, 1], [2, 2, 2], [5, 10, 12]], "float"
          ),
          np.array(
              [[1, 2, 3], [3, 2, 0], [5, 20, 33], [40, 80, 120]],
              "float",
          ),
      ]
      seeds = [
          np.array([0.0, 0.0, 0.0], "float"),
          np.array([1.0, 2.0, 3.0], "float"),
      ]
      if return_seeds:
          return streamlines, seeds
      else:
          return streamlines
  
imports: import warnings
  import numpy
  import pytest
  from dipy.tracking import metrics
  from dipy.tracking.streamline import transform_streamlines
  from dipy.tracking.utils import connectivity_matrix, density_map, length, ndbincount, reduce_labels, seeds_from_mask, random_seeds_from_mask, target, target_line_based, unique_rows, near_roi, reduce_rois, path_length, _min_at, max_angle_from_curvature, min_radius_curvature_from_angle
  from dipy.tracking._utils import _to_voxel_coordinates
  from dipy.tracking.vox2track import streamline_mapping
  import numpy.testing
  from dipy.testing import assert_true
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 1 for calling a global function with example usage: make_streamlines(return_seeds) and returns: streamlines,  seeds, streamlines