code: def get_test_data():
      """
      Create 5 all white images and 5 all black images. Then add some noise to
      each image.
      """
      from PIL import Image
  
      DIM = 224
  
      # Five all white images
      data = []
      for _ in range(5):
          data.append(np.full((DIM, DIM, 3), 255, dtype=np.uint8))
  
      # Five all black images
      for _ in range(5):
          data.append(np.full((DIM, DIM, 3), 0, dtype=np.uint8))
  
      # Add some random noise to each images
      random = np.random.RandomState(100)
      for cur_image in data:
          for _ in range(1000):
              x, y = random.randint(DIM), random.randint(DIM)
              rand_pixel_value = (
                  random.randint(255),
                  random.randint(255),
                  random.randint(255),
              )
              cur_image[x][y] = rand_pixel_value
  
      # Convert to an array of tc.Images
      images = []
      for cur_data in data:
          pil_image = Image.fromarray(cur_data)
          image_data = bytearray(
              [z for l in pil_image.getdata() for z in l]
          )
          image_data_size = len(image_data)
          tc_image = tc.Image(
              _image_data=image_data,
              _width=DIM,
              _height=DIM,
              _channels=3,
              _format_enum=2,
              _image_data_size=image_data_size,
          )
          images.append(tc_image)
  
      labels = ["white"] * 5 + ["black"] * 5
      data_dict = {"awesome_image": images, "awesome_label": labels}
      data = tc.SFrame(data_dict)
  
      return data
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import os
  import platform
  import sys
  import tempfile
  import unittest
  from turicreate.toolkits._main import ToolkitError
  from turicreate.toolkits._internal_utils import _mac_ver, _raise_error_if_not_sframe, _raise_error_if_not_sarray
  from turicreate.toolkits.image_analysis.image_analysis import MODEL_TO_FEATURE_SIZE_MAPPING, get_deep_features
  from .None import util
  import numpy
  import turicreate
label_desc: Use image node_id 1 for calling a global function with example usage: get_test_data() and returns: data