Pillow/Tests/test_image_resize.py

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"""
Tests for resize functionality.
"""
from itertools import permutations
from .helper import PillowTestCase, hopper
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from PIL import Image
class TestImagingCoreResize(PillowTestCase):
def resize(self, im, size, f):
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# Image class independent version of resize.
im.load()
return im._new(im.im.resize(size, f))
def test_nearest_mode(self):
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for mode in [
"1",
"P",
"L",
"I",
"F",
"RGB",
"RGBA",
"CMYK",
"YCbCr",
"I;16",
]: # exotic mode
im = hopper(mode)
r = self.resize(im, (15, 12), Image.NEAREST)
self.assertEqual(r.mode, mode)
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self.assertEqual(r.size, (15, 12))
self.assertEqual(r.im.bands, im.im.bands)
def test_convolution_modes(self):
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self.assertRaises(
ValueError, self.resize, hopper("1"), (15, 12), Image.BILINEAR
)
self.assertRaises(
ValueError, self.resize, hopper("P"), (15, 12), Image.BILINEAR
)
self.assertRaises(
ValueError, self.resize, hopper("I;16"), (15, 12), Image.BILINEAR
)
for mode in ["L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr"]:
im = hopper(mode)
r = self.resize(im, (15, 12), Image.BILINEAR)
self.assertEqual(r.mode, mode)
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self.assertEqual(r.size, (15, 12))
self.assertEqual(r.im.bands, im.im.bands)
def test_reduce_filters(self):
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for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
r = self.resize(hopper("RGB"), (15, 12), f)
self.assertEqual(r.mode, "RGB")
self.assertEqual(r.size, (15, 12))
def test_enlarge_filters(self):
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for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
r = self.resize(hopper("RGB"), (212, 195), f)
self.assertEqual(r.mode, "RGB")
self.assertEqual(r.size, (212, 195))
def test_endianness(self):
# Make an image with one colored pixel, in one channel.
# When resized, that channel should be the same as a GS image.
# Other channels should be unaffected.
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# The R and A channels should not swap, which is indicative of
# an endianness issues.
samples = {
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"blank": Image.new("L", (2, 2), 0),
"filled": Image.new("L", (2, 2), 255),
"dirty": Image.new("L", (2, 2), 0),
}
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samples["dirty"].putpixel((1, 1), 128)
for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
# samples resized with current filter
references = {
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name: self.resize(ch, (4, 4), f) for name, ch in samples.items()
}
for mode, channels_set in [
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("RGB", ("blank", "filled", "dirty")),
("RGBA", ("blank", "blank", "filled", "dirty")),
("LA", ("filled", "dirty")),
]:
for channels in set(permutations(channels_set)):
# compile image from different channels permutations
im = Image.merge(mode, [samples[ch] for ch in channels])
resized = self.resize(im, (4, 4), f)
for i, ch in enumerate(resized.split()):
# check what resized channel in image is the same
# as separately resized channel
self.assert_image_equal(ch, references[channels[i]])
def test_enlarge_zero(self):
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for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
r = self.resize(Image.new("RGB", (0, 0), "white"), (212, 195), f)
self.assertEqual(r.mode, "RGB")
self.assertEqual(r.size, (212, 195))
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self.assertEqual(r.getdata()[0], (0, 0, 0))
def test_unknown_filter(self):
self.assertRaises(ValueError, self.resize, hopper(), (10, 10), 9)
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class TestImageResize(PillowTestCase):
def test_resize(self):
def resize(mode, size):
out = hopper(mode).resize(size)
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self.assertEqual(out.mode, mode)
self.assertEqual(out.size, size)
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for mode in "1", "P", "L", "RGB", "I", "F":
resize(mode, (112, 103))
resize(mode, (188, 214))
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# Test unknown resampling filter
im = hopper()
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self.assertRaises(ValueError, im.resize, (10, 10), "unknown")