code: def test_convert_to_rgb(self):
      # Test that an RGBA image is converted to RGB
      image = np.array([[[1, 2, 3, 4], [5, 6, 7, 8]]], dtype=np.uint8)
      pil_image = PIL.Image.fromarray(image)
      self.assertEqual(pil_image.mode, "RGBA")
      self.assertEqual(pil_image.size, (2, 1))
  
      # For the moment, numpy images are returned as is
      rgb_image = convert_to_rgb(image)
      self.assertEqual(rgb_image.shape, (1, 2, 4))
      self.assertTrue(np.allclose(rgb_image, image))
  
      # And PIL images are converted
      rgb_image = convert_to_rgb(pil_image)
      self.assertEqual(rgb_image.mode, "RGB")
      self.assertEqual(rgb_image.size, (2, 1))
      self.assertTrue(
          np.allclose(
              np.array(rgb_image),
              np.array([[[1, 2, 3], [5, 6, 7]]], dtype=np.uint8),
          )
      )
  
      # Test that a grayscale image is converted to RGB
      image = np.array([[0, 255]], dtype=np.uint8)
      pil_image = PIL.Image.fromarray(image)
      self.assertEqual(pil_image.mode, "L")
      self.assertEqual(pil_image.size, (2, 1))
      rgb_image = convert_to_rgb(pil_image)
      self.assertEqual(rgb_image.mode, "RGB")
      self.assertEqual(rgb_image.size, (2, 1))
      self.assertTrue(
          np.allclose(
              np.array(rgb_image),
              np.array([[[0, 0, 0], [255, 255, 255]]], dtype=np.uint8),
          )
      )
  
imports: import unittest
  import numpy
  from parameterized import parameterized
  from transformers.testing_utils import require_flax, require_tf, require_torch, require_vision
  from transformers.utils.import_utils import is_flax_available, is_tf_available, is_torch_available, is_vision_available
label_desc: Use image node_id 17 for calling the ImageTransformsTester obj's underlying member method code with example usage: obj.test_convert_to_rgb() without return types