Keep ImageOps.contain() from rounding thin images to zero pixels

Tests/test_imageops.py

@@ -142,6 +142,22 @@ def test_contain_round() -> None:
     assert new_im.height == 5
 
 
+def test_contain_narrow_image() -> None:
+    im = Image.new("RGB", (100, 1), "red")
+    new_im = ImageOps.contain(im, (10, 10))
+    assert new_im.size == (10, 1)
+
+    im = Image.new("RGB", (1, 100), "red")
+    new_im = ImageOps.contain(im, (10, 10))
+    assert new_im.size == (1, 10)
+
+
+def test_pad_narrow_image() -> None:
+    im = Image.new("RGB", (100, 1), "red")
+    new_im = ImageOps.pad(im, (10, 10))
+    assert new_im.size == (10, 10)
+
+
 @pytest.mark.parametrize(
     "image_name, expected_size",
     (

docs/releasenotes/13.0.0.rst

@@ -228,3 +228,10 @@ position or contents.
 
 :py:meth:`~PIL.Image.Image.tobytes` also now explicitly cleans up its encoder on
 both success and failure, rather than relying on object destruction.
+
+Fixed ImageOps.contain() for very thin images
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+:py:func:`~PIL.ImageOps.contain` and :py:func:`~PIL.ImageOps.pad` no longer raise
+``ValueError`` when a very thin image rounds the shorter side to zero pixels. The
+calculated dimension is now kept at least one pixel.

src/PIL/ImageOps.py

@@ -300,11 +300,11 @@ def contain(
 
     if im_ratio != dest_ratio:
         if im_ratio > dest_ratio:
-            new_height = round(image.height / image.width * size[0])
+            new_height = max(1, round(image.height / image.width * size[0]))
             if new_height != size[1]:
                 size = (size[0], new_height)
         else:
-            new_width = round(image.width / image.height * size[1])
+            new_width = max(1, round(image.width / image.height * size[1]))
             if new_width != size[0]:
                 size = (new_width, size[1])
     return image.resize(size, resample=method)