code: def test_dataset_with_image_feature_from_np_array():
      import PIL.Image
  
      image_array = np.arange(640 * 480, dtype=np.int32).reshape(
          480, 640
      )
      data = {"image": [image_array]}
      features = Features({"image": Image()})
      dset = Dataset.from_dict(data, features=features)
      item = dset[0]
      assert item.keys() == {"image"}
      assert isinstance(item["image"], PIL.Image.Image)
  
      np.testing.assert_array_equal(
          np.array(item["image"]), image_array
      )
      assert item["image"].filename == ""
      assert item["image"].format in ["PNG", "TIFF"]
      assert item["image"].size == (640, 480)
      batch = dset[:1]
      assert len(batch) == 1
      assert batch.keys() == {"image"}
      assert isinstance(batch["image"], list) and all(
          isinstance(item, PIL.Image.Image) for item in batch["image"]
      )
      np.testing.assert_array_equal(
          np.array(batch["image"][0]), image_array
      )
      assert batch["image"][0].filename == ""
      assert batch["image"][0].format in ["PNG", "TIFF"]
      assert batch["image"][0].size == (640, 480)
      column = dset["image"]
      assert len(column) == 1
      assert isinstance(column, list) and all(
          isinstance(item, PIL.Image.Image) for item in column
      )
      np.testing.assert_array_equal(np.array(column[0]), image_array)
      assert column[0].filename == ""
      assert column[0].format in ["PNG", "TIFF"]
      assert column[0].size == (640, 480)
  
imports: import os
  import tarfile
  import warnings
  import numpy
  import pandas
  import pyarrow
  import pytest
  from datasets import Dataset, Features, Image, Sequence, Value, concatenate_datasets, load_dataset
  from datasets.features.image import encode_np_array, image_to_bytes
  from ..utils import require_pil
label_desc: Use image node_id 9 for calling a global function with example usage: test_dataset_with_image_feature_from_np_array() without return types