code: def test_draw_bounding_box():
      """Test case for draw_bounding_box."""
      width = 560
      height = 320
      channels = 4
  
      with open(
          os.path.join(
              os.path.dirname(os.path.abspath(__file__)),
              "test_image",
              "small-00.png",
          ),
          "rb",
      ) as f:
          png_contents = f.read()
      with open(
          os.path.join(
              os.path.dirname(os.path.abspath(__file__)),
              "test_image",
              "small-bb.png",
          ),
          "rb",
      ) as f:
          ex_png_contents = f.read()
      ex_image_p = tf.image.decode_png(
          ex_png_contents, channels=channels
      )
      # TODO: Travis seems to have issues with different rendering. Skip for now.
      # ex_image_v = ex_image_p.eval()
      _ = tf.expand_dims(ex_image_p, 0)
  
      bb = [[[0.1, 0.2, 0.5, 0.9]]]
      image_v = tf.image.decode_png(png_contents, channels=channels)
      assert image_v.shape == (height, width, channels)
      image_p = tf.image.convert_image_dtype(image_v, tf.float32)
      image_p = tf.expand_dims(image_p, 0)
      bb_image_p = tfio.experimental.image.draw_bounding_boxes(
          image_p, bb, ["hello world!"]
      )
      # TODO: Travis seems to have issues with different rendering. Skip for now.
      # self.assertAllEqual(bb_image_v, ex_image_v)
      _ = tf.image.convert_image_dtype(bb_image_p, tf.uint8)
  
imports: import os
  import numpy
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 4 for calling a global function with example usage: test_draw_bounding_box() without return types