code: def mock_svhn_dataset(tmpdir_factory, mock_image_stream):
      root = tmpdir_factory.mktemp("datasets")
      svhn_root = root.mkdir("svhn")
      file = BytesIO(mock_image_stream)
      # ascii image names
      first = np.array(
          [[49], [46], [112], [110], [103]], dtype=np.int16
      )  # 1.png
      second = np.array(
          [[50], [46], [112], [110], [103]], dtype=np.int16
      )  # 2.png
      third = np.array(
          [[51], [46], [112], [110], [103]], dtype=np.int16
      )  # 3.png
      # labels: label is also ascii
      label = {
          "height": [35, 35, 35, 35],
          "label": [1, 1, 3, 7],
          "left": [116, 128, 137, 151],
          "top": [27, 29, 29, 26],
          "width": [15, 10, 17, 17],
      }
  
      matcontent = {
          "digitStruct": {
              "name": [first, second, third],
              "bbox": [label, label, label],
          }
      }
      # Mock train data
      train_root = svhn_root.mkdir("train")
      hdf5storage.write(
          matcontent, filename=train_root.join("digitStruct.mat")
      )
      for i in range(3):
          fn = train_root.join(f"{i + 1}.png")
          with open(fn, "wb") as f:
              f.write(file.getbuffer())
      # Packing data into an archive to simulate the real data set and bypass archive extraction
      archive_path = root.join("svhn_train.tar")
      shutil.make_archive(
          root.join("svhn_train"), "tar", str(svhn_root)
      )
      return str(archive_path)
  
imports: import json
  import shutil
  import tempfile
  from io import BytesIO
  import cv2
  import hdf5storage
  import numpy
  import pytest
  import requests
  import scipy.io
  from PIL import Image
  from doctr.datasets.generator.base import synthesize_text_img
  from doctr.io import reader
  from doctr.utils import geometry
label_desc: Use image node_id 15 for calling a global function with example usage: mock_svhn_dataset(tmpdir_factory, mock_image_stream) and returns: str