code: def test_region_extractor_high_resolution_image(affine_eye):
      n_regions = 9
      maps, _ = generate_maps(
          shape=MAP_SHAPE, n_regions=n_regions, affine=0.2 * affine_eye
      )
  
      extract_ratio = RegionExtractor(
          maps,
          thresholding_strategy="ratio_n_voxels",
          smoothing_fwhm=0.6,
          min_region_size=0.4,
      )
      extract_ratio.fit()
  
      assert extract_ratio.regions_img_ != ""
      assert extract_ratio.regions_img_.shape[-1] >= 9
  
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from scipy.ndimage import label
  from nilearn._utils.data_gen import generate_labeled_regions, generate_maps
  from nilearn._utils.exceptions import DimensionError
  from nilearn.conftest import _affine_eye, _img_4d_zeros, _shape_3d_default
  from nilearn.image import get_data
  from nilearn.regions import RegionExtractor, connected_label_regions, connected_regions
  from nilearn.regions.region_extractor import _remove_small_regions, _threshold_maps_ratio
label_desc: Use image node_id 19 for calling a global function with example usage: test_region_extractor_high_resolution_image(affine_eye) without return types