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63729766c4
In Python 3, the division operator is floating point division. No longer need to coerce integers to floating point numbers before division.
245 lines
8.7 KiB
Python
245 lines
8.7 KiB
Python
from PIL import Image, ImageMath, ImageMode
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from .helper import PillowTestCase, convert_to_comparable
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class TestImageReduce(PillowTestCase):
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# There are several internal implementations
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remarkable_factors = [
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# special implementations
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1,
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2,
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3,
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4,
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5,
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6,
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# 1xN implementation
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(1, 2),
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(1, 3),
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(1, 4),
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(1, 7),
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# Nx1 implementation
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(2, 1),
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(3, 1),
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(4, 1),
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(7, 1),
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# general implementation with different paths
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(4, 6),
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(5, 6),
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(4, 7),
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(5, 7),
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(19, 17),
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]
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@classmethod
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def setUpClass(cls):
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cls.gradients_image = Image.open("Tests/images/radial_gradients.png")
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cls.gradients_image.load()
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def test_args_factor(self):
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im = Image.new("L", (10, 10))
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self.assertEqual((4, 4), im.reduce(3).size)
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self.assertEqual((4, 10), im.reduce((3, 1)).size)
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self.assertEqual((10, 4), im.reduce((1, 3)).size)
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with self.assertRaises(ValueError):
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im.reduce(0)
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with self.assertRaises(TypeError):
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im.reduce(2.0)
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with self.assertRaises(ValueError):
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im.reduce((0, 10))
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def test_args_box(self):
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im = Image.new("L", (10, 10))
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self.assertEqual((5, 5), im.reduce(2, (0, 0, 10, 10)).size)
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self.assertEqual((1, 1), im.reduce(2, (5, 5, 6, 6)).size)
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with self.assertRaises(TypeError):
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im.reduce(2, "stri")
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with self.assertRaises(TypeError):
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im.reduce(2, 2)
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with self.assertRaises(ValueError):
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im.reduce(2, (0, 0, 11, 10))
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with self.assertRaises(ValueError):
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im.reduce(2, (0, 0, 10, 11))
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with self.assertRaises(ValueError):
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im.reduce(2, (-1, 0, 10, 10))
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with self.assertRaises(ValueError):
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im.reduce(2, (0, -1, 10, 10))
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with self.assertRaises(ValueError):
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im.reduce(2, (0, 5, 10, 5))
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with self.assertRaises(ValueError):
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im.reduce(2, (5, 0, 5, 10))
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def test_unsupported_modes(self):
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im = Image.new("P", (10, 10))
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with self.assertRaises(ValueError):
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im.reduce(3)
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im = Image.new("1", (10, 10))
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with self.assertRaises(ValueError):
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im.reduce(3)
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im = Image.new("I;16", (10, 10))
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with self.assertRaises(ValueError):
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im.reduce(3)
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def get_image(self, mode):
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mode_info = ImageMode.getmode(mode)
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if mode_info.basetype == "L":
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bands = [self.gradients_image]
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for _ in mode_info.bands[1:]:
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# rotate previous image
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band = bands[-1].transpose(Image.ROTATE_90)
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bands.append(band)
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# Correct alpha channel by transforming completely transparent pixels.
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# Low alpha values also emphasize error after alpha multiplication.
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if mode.endswith("A"):
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bands[-1] = bands[-1].point(lambda x: int(85 + x / 1.5))
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im = Image.merge(mode, bands)
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else:
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assert len(mode_info.bands) == 1
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im = self.gradients_image.convert(mode)
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# change the height to make a not-square image
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return im.crop((0, 0, im.width, im.height - 5))
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def compare_reduce_with_box(self, im, factor):
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box = (11, 13, 146, 164)
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reduced = im.reduce(factor, box=box)
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reference = im.crop(box).reduce(factor)
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self.assertEqual(reduced, reference)
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def compare_reduce_with_reference(self, im, factor, average_diff=0.4, max_diff=1):
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"""Image.reduce() should look very similar to Image.resize(BOX).
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A reference image is compiled from a large source area
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and possible last column and last row.
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+-----------+
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|..........c|
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|..........c|
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|..........c|
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|rrrrrrrrrrp|
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+-----------+
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"""
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reduced = im.reduce(factor)
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if not isinstance(factor, (list, tuple)):
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factor = (factor, factor)
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reference = Image.new(im.mode, reduced.size)
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area_size = (im.size[0] // factor[0], im.size[1] // factor[1])
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area_box = (0, 0, area_size[0] * factor[0], area_size[1] * factor[1])
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area = im.resize(area_size, Image.BOX, area_box)
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reference.paste(area, (0, 0))
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if area_size[0] < reduced.size[0]:
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self.assertEqual(reduced.size[0] - area_size[0], 1)
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last_column_box = (area_box[2], 0, im.size[0], area_box[3])
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last_column = im.resize((1, area_size[1]), Image.BOX, last_column_box)
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reference.paste(last_column, (area_size[0], 0))
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if area_size[1] < reduced.size[1]:
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self.assertEqual(reduced.size[1] - area_size[1], 1)
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last_row_box = (0, area_box[3], area_box[2], im.size[1])
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last_row = im.resize((area_size[0], 1), Image.BOX, last_row_box)
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reference.paste(last_row, (0, area_size[1]))
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if area_size[0] < reduced.size[0] and area_size[1] < reduced.size[1]:
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last_pixel_box = (area_box[2], area_box[3], im.size[0], im.size[1])
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last_pixel = im.resize((1, 1), Image.BOX, last_pixel_box)
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reference.paste(last_pixel, area_size)
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self.assert_compare_images(reduced, reference, average_diff, max_diff)
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def assert_compare_images(self, a, b, max_average_diff, max_diff=255):
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self.assertEqual(a.mode, b.mode, "got mode %r, expected %r" % (a.mode, b.mode))
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self.assertEqual(a.size, b.size, "got size %r, expected %r" % (a.size, b.size))
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a, b = convert_to_comparable(a, b)
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bands = ImageMode.getmode(a.mode).bands
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for band, ach, bch in zip(bands, a.split(), b.split()):
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ch_diff = ImageMath.eval("convert(abs(a - b), 'L')", a=ach, b=bch)
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ch_hist = ch_diff.histogram()
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average_diff = sum(i * num for i, num in enumerate(ch_hist)) / (
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a.size[0] * a.size[1]
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)
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self.assertGreaterEqual(
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max_average_diff,
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average_diff,
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(
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"average pixel value difference {:.4f} > expected {:.4f} "
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"for '{}' band"
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).format(average_diff, max_average_diff, band),
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)
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last_diff = [i for i, num in enumerate(ch_hist) if num > 0][-1]
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self.assertGreaterEqual(
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max_diff,
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last_diff,
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"max pixel value difference {} > expected {} for '{}' band".format(
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last_diff, max_diff, band
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),
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)
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def test_mode_L(self):
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im = self.get_image("L")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_LA(self):
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im = self.get_image("LA")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor, 0.8, 5)
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# With opaque alpha, an error should be way smaller.
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im.putalpha(Image.new("L", im.size, 255))
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_La(self):
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im = self.get_image("La")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_RGB(self):
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im = self.get_image("RGB")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_RGBA(self):
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im = self.get_image("RGBA")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor, 0.8, 5)
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# With opaque alpha, an error should be way smaller.
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im.putalpha(Image.new("L", im.size, 255))
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_RGBa(self):
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im = self.get_image("RGBa")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_I(self):
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im = self.get_image("I")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor)
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self.compare_reduce_with_box(im, factor)
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def test_mode_F(self):
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im = self.get_image("F")
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for factor in self.remarkable_factors:
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self.compare_reduce_with_reference(im, factor, 0, 0)
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self.compare_reduce_with_box(im, factor)
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