scikit-learn · lesteve · Mar 18, 2022 · Mar 9, 2022 · Mar 17, 2022
diff --git a/sklearn/conftest.py b/sklearn/conftest.py
@@ -9,7 +9,6 @@
 
 from sklearn.utils import _IS_32BIT
 from sklearn.utils._openmp_helpers import _openmp_effective_n_threads
-from sklearn.externals import _pilutil
 from sklearn._min_dependencies import PYTEST_MIN_VERSION
 from sklearn.utils.fixes import parse_version
 from sklearn.datasets import fetch_20newsgroups
@@ -169,7 +168,14 @@ def pytest_collection_modifyitems(config, items):
                 # details.
                 if item.name != "sklearn._config.config_context":
                     item.add_marker(skip_marker)
-    elif not _pilutil.pillow_installed:
+    try:
+        import PIL  # noqa
+
+        pillow_installed = True
+    except ImportError:
+        pillow_installed = False
+
+    if not pillow_installed:
         skip_marker = pytest.mark.skip(reason="pillow (or PIL) not installed!")
         for item in items:
             if item.name in [

diff --git a/sklearn/datasets/_base.py b/sklearn/datasets/_base.py
@@ -1387,8 +1387,15 @@ def load_sample_images():
     >>> first_img_data.dtype               #doctest: +SKIP
     dtype('uint8')
     """
-    # import PIL only when needed
-    from ..externals._pilutil import imread
+    try:
+        from PIL import Image
+    except ImportError:
+        raise ImportError(
+            "The Python Imaging Library (PIL) is required to load data "
+            "from jpeg files. Please refer to "
+            "https://pillow.readthedocs.io/en/stable/installation.html "
+            "for installing PIL."
+        )
 
     descr = load_descr("README.txt", descr_module=IMAGES_MODULE)
 
@@ -1397,7 +1404,8 @@ def load_sample_images():
         if filename.endswith(".jpg"):
             filenames.append(filename)
             with resources.open_binary(IMAGES_MODULE, filename) as image_file:
-                image = imread(image_file)
+                pil_image = Image.open(image_file)
+                image = np.asarray(pil_image)
             images.append(image)
 
     return Bunch(images=images, filenames=filenames, DESCR=descr)

diff --git a/sklearn/datasets/_lfw.py b/sklearn/datasets/_lfw.py
@@ -116,8 +116,15 @@ def _check_fetch_lfw(data_home=None, funneled=True, download_if_missing=True):
 
 def _load_imgs(file_paths, slice_, color, resize):
     """Internally used to load images"""
-    # import PIL only when needed
-    from ..externals._pilutil import imread, imresize
+    try:
+        from PIL import Image
+    except ImportError:
+        raise ImportError(
+            "The Python Imaging Library (PIL) is required to load data "
+            "from jpeg files. Please refer to "
+            "https://pillow.readthedocs.io/en/stable/installation.html "
+            "for installing PIL."
+        )
 
     # compute the portion of the images to load to respect the slice_ parameter
     # given by the caller
@@ -151,17 +158,19 @@ def _load_imgs(file_paths, slice_, color, resize):
 
         # Checks if jpeg reading worked. Refer to issue #3594 for more
         # details.
-        img = imread(file_path)
-        if img.ndim == 0:
+        pil_img = Image.open(file_path)
+        pil_img.crop((w_slice.start, h_slice.start, w_slice.stop, h_slice.stop))
+        if resize is not None:
+            pil_img = pil_img.resize((w, h))
+        face = np.asarray(pil_img, dtype=np.float32)
+
+        if face.ndim == 0:
             raise RuntimeError(
                 "Failed to read the image file %s, "
                 "Please make sure that libjpeg is installed" % file_path
             )
 
-        face = np.asarray(img[slice_], dtype=np.float32)
         face /= 255.0  # scale uint8 coded colors to the [0.0, 1.0] floats
-        if resize is not None:
-            face = imresize(face, resize)
         if not color:
             # average the color channels to compute a gray levels
             # representation

diff --git a/sklearn/datasets/tests/test_base.py b/sklearn/datasets/tests/test_base.py
@@ -30,8 +30,6 @@
 from sklearn.utils._testing import SkipTest
 from sklearn.datasets.tests.test_common import check_as_frame
 
-from sklearn.externals._pilutil import pillow_installed
-
 
 def _remove_dir(path):
     if os.path.isdir(path):
@@ -226,11 +224,9 @@ def test_load_sample_image():
 
 
 def test_load_missing_sample_image_error():
-    if pillow_installed:
-        with pytest.raises(AttributeError):
-            load_sample_image("blop.jpg")
-    else:
-        warnings.warn("Could not load sample images, PIL is not available.")
+    pytest.importorskip("PIL")
+    with pytest.raises(AttributeError):
+        load_sample_image("blop.jpg")
 
 
 def test_load_diabetes_raw():

diff --git a/sklearn/datasets/tests/test_lfw.py b/sklearn/datasets/tests/test_lfw.py
@@ -15,12 +15,10 @@
 import numpy as np
 import pytest
 from functools import partial
-from sklearn.externals._pilutil import pillow_installed, imsave
 from sklearn.datasets import fetch_lfw_pairs
 from sklearn.datasets import fetch_lfw_people
 
 from sklearn.utils._testing import assert_array_equal
-from sklearn.utils._testing import SkipTest
 from sklearn.datasets.tests.test_common import check_return_X_y
 
 
@@ -41,8 +39,7 @@
 
 def setup_module():
     """Test fixture run once and common to all tests of this module"""
-    if not pillow_installed:
-        raise SkipTest("PIL not installed.")
+    Image = pytest.importorskip("PIL.Image")
 
     global SCIKIT_LEARN_DATA, SCIKIT_LEARN_EMPTY_DATA, LFW_HOME
 
@@ -69,10 +66,8 @@ def setup_module():
         for i in range(n_faces):
             file_path = os.path.join(folder_name, name + "_%04d.jpg" % i)
             uniface = np_rng.randint(0, 255, size=(250, 250, 3))
-            try:
-                imsave(file_path, uniface)
-            except ImportError:
-                raise SkipTest("PIL not installed")
+            img = Image.fromarray(uniface.astype(np.uint8))
+            img.save(file_path)
 
     # add some random file pollution to test robustness
     with open(os.path.join(LFW_HOME, "lfw_funneled", ".test.swp"), "wb") as f: