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Pillow/Tests/test_image_resample.py

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from __future__ import division, print_function
from contextlib import contextmanager
from PIL import Image, ImageDraw
from .helper import PillowTestCase, hopper, unittest
class TestImagingResampleVulnerability(PillowTestCase):
# see https://github.com/python-pillow/Pillow/issues/1710
def test_overflow(self):
im = hopper("L")
size_too_large = 0x100000008 // 4
size_normal = 1000 # unimportant
for xsize, ysize in (
(size_too_large, size_normal),
(size_normal, size_too_large),
):
with self.assertRaises(MemoryError):
# any resampling filter will do here
im.im.resize((xsize, ysize), Image.BILINEAR)
def test_invalid_size(self):
im = hopper()
# Should not crash
im.resize((100, 100))
with self.assertRaises(ValueError):
im.resize((-100, 100))
with self.assertRaises(ValueError):
im.resize((100, -100))
def test_modify_after_resizing(self):
im = hopper("RGB")
# get copy with same size
copy = im.resize(im.size)
# some in-place operation
copy.paste("black", (0, 0, im.width // 2, im.height // 2))
# image should be different
self.assertNotEqual(im.tobytes(), copy.tobytes())
class TestImagingCoreResampleAccuracy(PillowTestCase):
def make_case(self, mode, size, color):
"""Makes a sample image with two dark and two bright squares.
For example:
e0 e0 1f 1f
e0 e0 1f 1f
1f 1f e0 e0
1f 1f e0 e0
"""
case = Image.new("L", size, 255 - color)
rectangle = ImageDraw.Draw(case).rectangle
rectangle((0, 0, size[0] // 2 - 1, size[1] // 2 - 1), color)
rectangle((size[0] // 2, size[1] // 2, size[0], size[1]), color)
return Image.merge(mode, [case] * len(mode))
def make_sample(self, data, size):
"""Restores a sample image from given data string which contains
hex-encoded pixels from the top left fourth of a sample.
"""
data = data.replace(" ", "")
sample = Image.new("L", size)
s_px = sample.load()
w, h = size[0] // 2, size[1] // 2
for y in range(h):
for x in range(w):
val = int(data[(y * w + x) * 2 : (y * w + x + 1) * 2], 16)
s_px[x, y] = val
s_px[size[0] - x - 1, size[1] - y - 1] = val
s_px[x, size[1] - y - 1] = 255 - val
s_px[size[0] - x - 1, y] = 255 - val
return sample
def check_case(self, case, sample):
s_px = sample.load()
c_px = case.load()
for y in range(case.size[1]):
for x in range(case.size[0]):
if c_px[x, y] != s_px[x, y]:
message = "\nHave: \n{}\n\nExpected: \n{}".format(
self.serialize_image(case), self.serialize_image(sample)
)
self.assertEqual(s_px[x, y], c_px[x, y], message)
def serialize_image(self, image):
s_px = image.load()
return "\n".join(
" ".join("{:02x}".format(s_px[x, y]) for x in range(image.size[0]))
for y in range(image.size[1])
)
def test_reduce_box(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (8, 8), 0xE1)
case = case.resize((4, 4), Image.BOX)
# fmt: off
data = ("e1 e1"
"e1 e1")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_reduce_bilinear(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (8, 8), 0xE1)
case = case.resize((4, 4), Image.BILINEAR)
# fmt: off
data = ("e1 c9"
"c9 b7")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_reduce_hamming(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (8, 8), 0xE1)
case = case.resize((4, 4), Image.HAMMING)
# fmt: off
data = ("e1 da"
"da d3")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_reduce_bicubic(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (12, 12), 0xE1)
case = case.resize((6, 6), Image.BICUBIC)
# fmt: off
data = ("e1 e3 d4"
"e3 e5 d6"
"d4 d6 c9")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (6, 6)))
def test_reduce_lanczos(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (16, 16), 0xE1)
case = case.resize((8, 8), Image.LANCZOS)
# fmt: off
data = ("e1 e0 e4 d7"
"e0 df e3 d6"
"e4 e3 e7 da"
"d7 d6 d9 ce")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (8, 8)))
def test_enlarge_box(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (2, 2), 0xE1)
case = case.resize((4, 4), Image.BOX)
# fmt: off
data = ("e1 e1"
"e1 e1")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_enlarge_bilinear(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (2, 2), 0xE1)
case = case.resize((4, 4), Image.BILINEAR)
# fmt: off
data = ("e1 b0"
"b0 98")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_enlarge_hamming(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (2, 2), 0xE1)
case = case.resize((4, 4), Image.HAMMING)
# fmt: off
data = ("e1 d2"
"d2 c5")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (4, 4)))
def test_enlarge_bicubic(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (4, 4), 0xE1)
case = case.resize((8, 8), Image.BICUBIC)
# fmt: off
data = ("e1 e5 ee b9"
"e5 e9 f3 bc"
"ee f3 fd c1"
"b9 bc c1 a2")
# fmt: on
for channel in case.split():
self.check_case(channel, self.make_sample(data, (8, 8)))
def test_enlarge_lanczos(self):
for mode in ["RGBX", "RGB", "La", "L"]:
case = self.make_case(mode, (6, 6), 0xE1)
case = case.resize((12, 12), Image.LANCZOS)
data = (
"e1 e0 db ed f5 b8"
"e0 df da ec f3 b7"
"db db d6 e7 ee b5"
"ed ec e6 fb ff bf"
"f5 f4 ee ff ff c4"
"b8 b7 b4 bf c4 a0"
)
for channel in case.split():
self.check_case(channel, self.make_sample(data, (12, 12)))
class CoreResampleConsistencyTest(PillowTestCase):
def make_case(self, mode, fill):
im = Image.new(mode, (512, 9), fill)
return im.resize((9, 512), Image.LANCZOS), im.load()[0, 0]
def run_case(self, case):
channel, color = case
px = channel.load()
for x in range(channel.size[0]):
for y in range(channel.size[1]):
if px[x, y] != color:
message = "{} != {} for pixel {}".format(px[x, y], color, (x, y))
self.assertEqual(px[x, y], color, message)
def test_8u(self):
im, color = self.make_case("RGB", (0, 64, 255))
r, g, b = im.split()
self.run_case((r, color[0]))
self.run_case((g, color[1]))
self.run_case((b, color[2]))
self.run_case(self.make_case("L", 12))
def test_32i(self):
self.run_case(self.make_case("I", 12))
self.run_case(self.make_case("I", 0x7FFFFFFF))
self.run_case(self.make_case("I", -12))
self.run_case(self.make_case("I", -1 << 31))
def test_32f(self):
self.run_case(self.make_case("F", 1))
self.run_case(self.make_case("F", 3.40282306074e38))
self.run_case(self.make_case("F", 1.175494e-38))
self.run_case(self.make_case("F", 1.192093e-07))
class CoreResampleAlphaCorrectTest(PillowTestCase):
def make_levels_case(self, mode):
i = Image.new(mode, (256, 16))
px = i.load()
for y in range(i.size[1]):
for x in range(i.size[0]):
pix = [x] * len(mode)
pix[-1] = 255 - y * 16
px[x, y] = tuple(pix)
return i
def run_levels_case(self, i):
px = i.load()
for y in range(i.size[1]):
used_colors = {px[x, y][0] for x in range(i.size[0])}
self.assertEqual(
256,
len(used_colors),
"All colors should present in resized image. "
"Only {} on {} line.".format(len(used_colors), y),
)
@unittest.skip("current implementation isn't precise enough")
def test_levels_rgba(self):
case = self.make_levels_case("RGBA")
self.run_levels_case(case.resize((512, 32), Image.BOX))
self.run_levels_case(case.resize((512, 32), Image.BILINEAR))
self.run_levels_case(case.resize((512, 32), Image.HAMMING))
self.run_levels_case(case.resize((512, 32), Image.BICUBIC))
self.run_levels_case(case.resize((512, 32), Image.LANCZOS))
@unittest.skip("current implementation isn't precise enough")
def test_levels_la(self):
case = self.make_levels_case("LA")
self.run_levels_case(case.resize((512, 32), Image.BOX))
self.run_levels_case(case.resize((512, 32), Image.BILINEAR))
self.run_levels_case(case.resize((512, 32), Image.HAMMING))
self.run_levels_case(case.resize((512, 32), Image.BICUBIC))
self.run_levels_case(case.resize((512, 32), Image.LANCZOS))
def make_dirty_case(self, mode, clean_pixel, dirty_pixel):
i = Image.new(mode, (64, 64), dirty_pixel)
px = i.load()
xdiv4 = i.size[0] // 4
ydiv4 = i.size[1] // 4
for y in range(ydiv4 * 2):
for x in range(xdiv4 * 2):
px[x + xdiv4, y + ydiv4] = clean_pixel
return i
def run_dirty_case(self, i, clean_pixel):
px = i.load()
for y in range(i.size[1]):
for x in range(i.size[0]):
if px[x, y][-1] != 0 and px[x, y][:-1] != clean_pixel:
message = "pixel at ({}, {}) is differ:\n{}\n{}".format(
x, y, px[x, y], clean_pixel
)
self.assertEqual(px[x, y][:3], clean_pixel, message)
def test_dirty_pixels_rgba(self):
case = self.make_dirty_case("RGBA", (255, 255, 0, 128), (0, 0, 255, 0))
self.run_dirty_case(case.resize((20, 20), Image.BOX), (255, 255, 0))
self.run_dirty_case(case.resize((20, 20), Image.BILINEAR), (255, 255, 0))
self.run_dirty_case(case.resize((20, 20), Image.HAMMING), (255, 255, 0))
self.run_dirty_case(case.resize((20, 20), Image.BICUBIC), (255, 255, 0))
self.run_dirty_case(case.resize((20, 20), Image.LANCZOS), (255, 255, 0))
def test_dirty_pixels_la(self):
case = self.make_dirty_case("LA", (255, 128), (0, 0))
self.run_dirty_case(case.resize((20, 20), Image.BOX), (255,))
self.run_dirty_case(case.resize((20, 20), Image.BILINEAR), (255,))
self.run_dirty_case(case.resize((20, 20), Image.HAMMING), (255,))
self.run_dirty_case(case.resize((20, 20), Image.BICUBIC), (255,))
self.run_dirty_case(case.resize((20, 20), Image.LANCZOS), (255,))
class CoreResamplePassesTest(PillowTestCase):
@contextmanager
def count(self, diff):
count = Image.core.get_stats()["new_count"]
yield
self.assertEqual(Image.core.get_stats()["new_count"] - count, diff)
def test_horizontal(self):
im = hopper("L")
with self.count(1):
im.resize((im.size[0] - 10, im.size[1]), Image.BILINEAR)
def test_vertical(self):
im = hopper("L")
with self.count(1):
im.resize((im.size[0], im.size[1] - 10), Image.BILINEAR)
def test_both(self):
im = hopper("L")
with self.count(2):
im.resize((im.size[0] - 10, im.size[1] - 10), Image.BILINEAR)
def test_box_horizontal(self):
im = hopper("L")
box = (20, 0, im.size[0] - 20, im.size[1])
with self.count(1):
# the same size, but different box
with_box = im.resize(im.size, Image.BILINEAR, box)
with self.count(2):
cropped = im.crop(box).resize(im.size, Image.BILINEAR)
self.assert_image_similar(with_box, cropped, 0.1)
def test_box_vertical(self):
im = hopper("L")
box = (0, 20, im.size[0], im.size[1] - 20)
with self.count(1):
# the same size, but different box
with_box = im.resize(im.size, Image.BILINEAR, box)
with self.count(2):
cropped = im.crop(box).resize(im.size, Image.BILINEAR)
self.assert_image_similar(with_box, cropped, 0.1)
class CoreResampleCoefficientsTest(PillowTestCase):
def test_reduce(self):
test_color = 254
for size in range(400000, 400010, 2):
i = Image.new("L", (size, 1), 0)
draw = ImageDraw.Draw(i)
draw.rectangle((0, 0, i.size[0] // 2 - 1, 0), test_color)
px = i.resize((5, i.size[1]), Image.BICUBIC).load()
if px[2, 0] != test_color // 2:
self.assertEqual(test_color // 2, px[2, 0])
def test_nonzero_coefficients(self):
# regression test for the wrong coefficients calculation
# due to bug https://github.com/python-pillow/Pillow/issues/2161
im = Image.new("RGBA", (1280, 1280), (0x20, 0x40, 0x60, 0xFF))
histogram = im.resize((256, 256), Image.BICUBIC).histogram()
# first channel
self.assertEqual(histogram[0x100 * 0 + 0x20], 0x10000)
# second channel
self.assertEqual(histogram[0x100 * 1 + 0x40], 0x10000)
# third channel
self.assertEqual(histogram[0x100 * 2 + 0x60], 0x10000)
# fourth channel
self.assertEqual(histogram[0x100 * 3 + 0xFF], 0x10000)
class CoreResampleBoxTest(PillowTestCase):
def test_wrong_arguments(self):
im = hopper()
for resample in (
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
):
im.resize((32, 32), resample, (0, 0, im.width, im.height))
im.resize((32, 32), resample, (20, 20, im.width, im.height))
im.resize((32, 32), resample, (20, 20, 20, 100))
im.resize((32, 32), resample, (20, 20, 100, 20))
with self.assertRaisesRegex(TypeError, "must be sequence of length 4"):
im.resize((32, 32), resample, (im.width, im.height))
with self.assertRaisesRegex(ValueError, "can't be negative"):
im.resize((32, 32), resample, (-20, 20, 100, 100))
with self.assertRaisesRegex(ValueError, "can't be negative"):
im.resize((32, 32), resample, (20, -20, 100, 100))
with self.assertRaisesRegex(ValueError, "can't be empty"):
im.resize((32, 32), resample, (20.1, 20, 20, 100))
with self.assertRaisesRegex(ValueError, "can't be empty"):
im.resize((32, 32), resample, (20, 20.1, 100, 20))
with self.assertRaisesRegex(ValueError, "can't be empty"):
im.resize((32, 32), resample, (20.1, 20.1, 20, 20))
with self.assertRaisesRegex(ValueError, "can't exceed"):
im.resize((32, 32), resample, (0, 0, im.width + 1, im.height))
with self.assertRaisesRegex(ValueError, "can't exceed"):
im.resize((32, 32), resample, (0, 0, im.width, im.height + 1))
def resize_tiled(self, im, dst_size, xtiles, ytiles):
def split_range(size, tiles):
scale = size / tiles
for i in range(tiles):
yield (int(round(scale * i)), int(round(scale * (i + 1))))
tiled = Image.new(im.mode, dst_size)
scale = (im.size[0] / tiled.size[0], im.size[1] / tiled.size[1])
for y0, y1 in split_range(dst_size[1], ytiles):
for x0, x1 in split_range(dst_size[0], xtiles):
box = (x0 * scale[0], y0 * scale[1], x1 * scale[0], y1 * scale[1])
tile = im.resize((x1 - x0, y1 - y0), Image.BICUBIC, box)
tiled.paste(tile, (x0, y0))
return tiled
def test_tiles(self):
im = Image.open("Tests/images/flower.jpg")
self.assertEqual(im.size, (480, 360))
dst_size = (251, 188)
reference = im.resize(dst_size, Image.BICUBIC)
for tiles in [(1, 1), (3, 3), (9, 7), (100, 100)]:
tiled = self.resize_tiled(im, dst_size, *tiles)
self.assert_image_similar(reference, tiled, 0.01)
def test_subsample(self):
# This test shows advantages of the subpixel resizing
# after supersampling (e.g. during JPEG decoding).
im = Image.open("Tests/images/flower.jpg")
self.assertEqual(im.size, (480, 360))
dst_size = (48, 36)
# Reference is cropped image resized to destination
reference = im.crop((0, 0, 473, 353)).resize(dst_size, Image.BICUBIC)
# Image.BOX emulates supersampling (480 / 8 = 60, 360 / 8 = 45)
supersampled = im.resize((60, 45), Image.BOX)
with_box = supersampled.resize(dst_size, Image.BICUBIC, (0, 0, 59.125, 44.125))
without_box = supersampled.resize(dst_size, Image.BICUBIC)
# error with box should be much smaller than without
self.assert_image_similar(reference, with_box, 6)
with self.assertRaisesRegex(AssertionError, r"difference 29\."):
self.assert_image_similar(reference, without_box, 5)
def test_formats(self):
for resample in [Image.NEAREST, Image.BILINEAR]:
for mode in ["RGB", "L", "RGBA", "LA", "I", ""]:
im = hopper(mode)
box = (20, 20, im.size[0] - 20, im.size[1] - 20)
with_box = im.resize((32, 32), resample, box)
cropped = im.crop(box).resize((32, 32), resample)
self.assert_image_similar(cropped, with_box, 0.4)
def test_passthrough(self):
# When no resize is required
im = hopper()
for size, box in [
((40, 50), (0, 0, 40, 50)),
((40, 50), (0, 10, 40, 60)),
((40, 50), (10, 0, 50, 50)),
((40, 50), (10, 20, 50, 70)),
]:
try:
res = im.resize(size, Image.LANCZOS, box)
self.assertEqual(res.size, size)
self.assert_image_equal(res, im.crop(box))
except AssertionError:
print(">>>", size, box)
raise
def test_no_passthrough(self):
# When resize is required
im = hopper()
for size, box in [
((40, 50), (0.4, 0.4, 40.4, 50.4)),
((40, 50), (0.4, 10.4, 40.4, 60.4)),
((40, 50), (10.4, 0.4, 50.4, 50.4)),
((40, 50), (10.4, 20.4, 50.4, 70.4)),
]:
try:
res = im.resize(size, Image.LANCZOS, box)
self.assertEqual(res.size, size)
with self.assertRaisesRegex(AssertionError, r"difference \d"):
# check that the difference at least that much
self.assert_image_similar(res, im.crop(box), 20)
except AssertionError:
print(">>>", size, box)
raise
def test_skip_horizontal(self):
# Can skip resize for one dimension
im = hopper()
for flt in [Image.NEAREST, Image.BICUBIC]:
for size, box in [
((40, 50), (0, 0, 40, 90)),
((40, 50), (0, 20, 40, 90)),
((40, 50), (10, 0, 50, 90)),
((40, 50), (10, 20, 50, 90)),
]:
try:
res = im.resize(size, flt, box)
self.assertEqual(res.size, size)
# Borders should be slightly different
self.assert_image_similar(res, im.crop(box).resize(size, flt), 0.4)
except AssertionError:
print(">>>", size, box, flt)
raise
def test_skip_vertical(self):
# Can skip resize for one dimension
im = hopper()
for flt in [Image.NEAREST, Image.BICUBIC]:
for size, box in [
((40, 50), (0, 0, 90, 50)),
((40, 50), (20, 0, 90, 50)),
((40, 50), (0, 10, 90, 60)),
((40, 50), (20, 10, 90, 60)),
]:
try:
res = im.resize(size, flt, box)
self.assertEqual(res.size, size)
# Borders should be slightly different
self.assert_image_similar(res, im.crop(box).resize(size, flt), 0.4)
except AssertionError:
print(">>>", size, box, flt)
raise
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