highlevel api

PIL/ImageOps.py

@@ -441,3 +441,20 @@ def unsharp_mask(im, radius=None, percent=None, threshold=None):
     return im.im.unsharp_mask(radius, percent, threshold)
 
 usm = unsharp_mask
+
+
+def box_blur(image, radius):
+    """
+    Apply box blur to given image. Box blur is operation where
+    each pixel becomes the average value of pixels in given radius.
+    Supports float radius and very large ones. Fast implementation,
+    works in linear time relative to the radius.
+
+    :param image: The image to blur.
+    :param radius: Size of the box in one direction. Radius 0 does not blur,
+    radius 1 takes 1 pixel in all directions, i.e. 9 pixels in total.
+    :return: An image.
+    """
+    image.load()
+
+    return image._new(image.im.box_blur(radius))

Tests/test_box_blur.py

@@ -1,6 +1,6 @@
 from helper import unittest, PillowTestCase
 
-from PIL import Image, ImageFilter
+from PIL import Image, ImageOps
 
 
 sample = Image.new("L", (7, 5))
@@ -14,7 +14,12 @@ sample.putdata(sum([
 
 
 class TestBoxBlurApi(PillowTestCase):
-    pass
+
+    def test_imageops(self):
+        i = ImageOps.box_blur(sample, 1)
+        self.assertEqual(i.mode, sample.mode)
+        self.assertEqual(i.size, sample.size)
+        self.assertIsInstance(i, Image.Image)
 
 
 class TestBoxBlur(PillowTestCase):

libImaging/BoxBlur.c

@@ -229,8 +229,8 @@ ImagingBoxBlur(Imaging im, Imaging imOut, float radius)
         HorizontalBoxBlur32(im, temp, radius);
     }
 
-    /* Blur in same direction transposed result from previout step.
-       Reseult will be transposes again. We'll get original image
+    /* Blur transposed result from previout step in same direction.
+       Reseult will be transposed again. We'll get original image
        blurred in both directions. */
     if (strcmp(im->mode, "L") == 0) {
         HorizontalBoxBlur8(temp, imOut, radius);