mirror of
https://github.com/python-pillow/Pillow.git
synced 2024-12-27 10:26:19 +03:00
4de5477b61
With the introduction and use of pytest, it is simple and easy to execute specific tests in isolation through documented command line arguments. Either by specifying the module path or through the `-k EXPRESSION` argument. There is no longer any need to provide the boilerplate: if __name__ == '__main__': unittest.main() To every test file. It is simply noise. The pattern remains in test files that aren't named with `test_*` as those files are not discovered and executed by pytest by default.
547 lines
21 KiB
Python
547 lines
21 KiB
Python
from __future__ import division, print_function
|
|
|
|
from contextlib import contextmanager
|
|
|
|
from .helper import unittest, PillowTestCase, hopper
|
|
from PIL import Image, ImageDraw
|
|
|
|
|
|
class TestImagingResampleVulnerability(PillowTestCase):
|
|
# see https://github.com/python-pillow/Pillow/issues/1710
|
|
def test_overflow(self):
|
|
im = hopper('L')
|
|
xsize = 0x100000008 // 4
|
|
ysize = 1000 # unimportant
|
|
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)
|
|
data = ('e1 e1'
|
|
'e1 e1')
|
|
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)
|
|
data = ('e1 c9'
|
|
'c9 b7')
|
|
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)
|
|
data = ('e1 da'
|
|
'da d3')
|
|
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)
|
|
data = ('e1 e3 d4'
|
|
'e3 e5 d6'
|
|
'd4 d6 c9')
|
|
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)
|
|
data = ('e1 e0 e4 d7'
|
|
'e0 df e3 d6'
|
|
'e4 e3 e7 da'
|
|
'd7 d6 d9 ce')
|
|
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)
|
|
data = ('e1 e1'
|
|
'e1 e1')
|
|
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)
|
|
data = ('e1 b0'
|
|
'b0 98')
|
|
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)
|
|
data = ('e1 d2'
|
|
'd2 c5')
|
|
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)
|
|
data = ('e1 e5 ee b9'
|
|
'e5 e9 f3 bc'
|
|
'ee f3 fd c1'
|
|
'b9 bc c1 a2')
|
|
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', 3.40282306074e+38))
|
|
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
|