def gaussian_blur(cls, self, radius, n=3):
if self.mode == 'RGBA':
return cls.gaussian_blur(self.convert('RGBa'), radius,
n).convert('RGBA')
if self.mode == 'LA':
return cls.gaussian_blur(self.convert('La'), radius,
n).convert('LA')
if not hasattr(self.im, 'box_blur'):
# Pillow 2.6 used different radius formula
return self._new(ImageOps.gaussian_blur(self, radius * 2.5))
# https://www.mia.uni-saarland.de/Publications/gwosdek-ssvm11.pdf
# [7] Box length.
L = math.sqrt(12.0 * float(radius) * radius / n + 1.0)
# [11] Box radius.
l = (L - 1.0) / 2.0
# Integer part.
li = math.floor(l)
# Reduce the fractional part in accordance with tests.
a = math.e**(2.5 * (l - li) / (li + 1)) - 1
a /= math.e**(2.5 / (li + 1)) - 1
box_radius = li + a
self.load()
return self._new(self.im.box_blur(box_radius, n))
def test_ops_api(self):
i = ImageOps.gaussian_blur(im, 2.0)
self.assertEqual(i.mode, "RGB")
self.assertEqual(i.size, (128, 128))
# i.save("blur.bmp")
i = ImageOps.unsharp_mask(im, 2.0, 125, 8)
self.assertEqual(i.mode, "RGB")
self.assertEqual(i.size, (128, 128))
def test_ops_api(self):
i = ImageOps.gaussian_blur(im, 2.0)
self.assertEqual(i.mode, "RGB")
self.assertEqual(i.size, (128, 128))
# i.save("blur.bmp")
i = ImageOps.usm(im, 2.0, 125, 8)
self.assertEqual(i.mode, "RGB")
self.assertEqual(i.size, (128, 128))
def test_ops_api():
i = ImageOps.gaussian_blur(im, 2.0)
assert_equal(i.mode, "RGB")
assert_equal(i.size, (128, 128))
# i.save("blur.bmp")
i = ImageOps.usm(im, 2.0, 125, 8)
assert_equal(i.mode, "RGB")
assert_equal(i.size, (128, 128))
def test_blur_accuracy(self):
i = snakes._new(ImageOps.gaussian_blur(snakes, .4))
# These pixels surrounded with pixels with 255 intensity.
# They must be very close to 255.
for x, y, c in [(1, 0, 1), (2, 0, 1), (7, 8, 1), (8, 8, 1), (2, 9, 1),
(7, 3, 0), (8, 3, 0), (5, 8, 0), (5, 9, 0), (1, 3, 0),
(4, 3, 2), (4, 2, 2)]:
self.assertGreaterEqual(i.im.getpixel((x, y))[c], 250)
# Fuzzy match.
gp = lambda x, y: i.im.getpixel((x, y))
self.assertTrue(236 <= gp(7, 4)[0] <= 239)
self.assertTrue(236 <= gp(7, 5)[2] <= 239)
self.assertTrue(236 <= gp(7, 6)[2] <= 239)
self.assertTrue(236 <= gp(7, 7)[1] <= 239)
self.assertTrue(236 <= gp(8, 4)[0] <= 239)
self.assertTrue(236 <= gp(8, 5)[2] <= 239)
self.assertTrue(236 <= gp(8, 6)[2] <= 239)
self.assertTrue(236 <= gp(8, 7)[1] <= 239)
def test_blur_accuracy(self):
i = snakes._new(ImageOps.gaussian_blur(snakes, .4))
# These pixels surrounded with pixels with 255 intensity.
# They must be very close to 255.
for x, y, c in [(1, 0, 1), (2, 0, 1), (7, 8, 1), (8, 8, 1), (2, 9, 1),
(7, 3, 0), (8, 3, 0), (5, 8, 0), (5, 9, 0), (1, 3, 0),
(4, 3, 2), (4, 2, 2)]:
self.assertGreaterEqual(i.im.getpixel((x, y))[c], 250)
# Fuzzy match.
gp = lambda x, y: i.im.getpixel((x, y))
self.assertTrue(236 <= gp(7, 4)[0] <= 239)
self.assertTrue(236 <= gp(7, 5)[2] <= 239)
self.assertTrue(236 <= gp(7, 6)[2] <= 239)
self.assertTrue(236 <= gp(7, 7)[1] <= 239)
self.assertTrue(236 <= gp(8, 4)[0] <= 239)
self.assertTrue(236 <= gp(8, 5)[2] <= 239)
self.assertTrue(236 <= gp(8, 6)[2] <= 239)
self.assertTrue(236 <= gp(8, 7)[1] <= 239)
