code: def test_image_processor_no_masks(self):
      image_processor = self.get_image_processor()
  
      processor = SamProcessor(image_processor=image_processor)
  
      image_input = self.prepare_image_inputs()
  
      input_feat_extract = image_processor(
          image_input, return_tensors="np"
      )
      input_processor = processor(
          images=image_input, return_tensors="np"
      )
  
      for key in input_feat_extract.keys():
          self.assertAlmostEqual(
              input_feat_extract[key].sum(),
              input_processor[key].sum(),
              delta=1e-2,
          )
  
      for image in input_feat_extract.pixel_values:
          self.assertEqual(image.shape, (3, 1024, 1024))
  
      for original_size in input_feat_extract.original_sizes:
          np.testing.assert_array_equal(
              original_size, np.array([30, 400])
          )
  
      for (
          reshaped_input_size
      ) in input_feat_extract.reshaped_input_sizes:
          np.testing.assert_array_equal(
              reshaped_input_size, np.array([77, 1024])
          )
  
imports: import shutil
  import tempfile
  import unittest
  import numpy
  from transformers.testing_utils import is_pt_tf_cross_test, require_tf, require_torch, require_torchvision, require_vision
  from transformers.utils import is_tf_available, is_torch_available, is_vision_available
label_desc: Use image node_id 7 for calling the SamProcessorTest obj's underlying member method code with example usage: obj.test_image_processor_no_masks() without return types