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"""
Tests for resize functionality.
"""
from itertools import permutations
import pytest
from PIL import Image
from .helper import assert_image_equal, assert_image_similar, hopper
class TestImagingCoreResize:
def resize(self, im, size, f):
# Image class independent version of resize.
im.load()
return im._new(im.im.resize(size, f))
def test_nearest_mode(self):
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)
assert r.mode == mode
assert r.size == (15, 12)
assert r.im.bands == im.im.bands
def test_convolution_modes(self):
with pytest.raises(ValueError):
self.resize(hopper("1"), (15, 12), Image.BILINEAR)
with pytest.raises(ValueError):
self.resize(hopper("P"), (15, 12), Image.BILINEAR)
with pytest.raises(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)
assert r.mode == mode
assert r.size == (15, 12)
assert r.im.bands == im.im.bands
def test_reduce_filters(self):
for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
r = self.resize(hopper("RGB"), (15, 12), f)
assert r.mode == "RGB"
assert r.size == (15, 12)
def test_enlarge_filters(self):
for f in [
Image.NEAREST,
Image.BOX,
Image.BILINEAR,
Image.HAMMING,
Image.BICUBIC,
Image.LANCZOS,
]:
r = self.resize(hopper("RGB"), (212, 195), f)
assert r.mode == "RGB"
assert 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.
# The R and A channels should not swap, which is indicative of
# an endianness issues.
samples = {
"blank": Image.new("L", (2, 2), 0),
"filled": Image.new("L", (2, 2), 255),
"dirty": Image.new("L", (2, 2), 0),
}
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 = {
name: self.resize(ch, (4, 4), f) for name, ch in samples.items()
}
for mode, channels_set in [
("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
assert_image_equal(ch, references[channels[i]])
def test_enlarge_zero(self):
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)
assert r.mode == "RGB"
assert r.size == (212, 195)
assert r.getdata()[0] == (0, 0, 0)
def test_unknown_filter(self):
with pytest.raises(ValueError):
self.resize(hopper(), (10, 10), 9)
@pytest.fixture
def gradients_image():
im = Image.open("Tests/images/radial_gradients.png")
im.load()
try:
yield im
finally:
im.close()
class TestReducingGapResize:
def test_reducing_gap_values(self, gradients_image):
ref = gradients_image.resize((52, 34), Image.BICUBIC, reducing_gap=None)
im = gradients_image.resize((52, 34), Image.BICUBIC)
assert_image_equal(ref, im)
with pytest.raises(ValueError):
gradients_image.resize((52, 34), Image.BICUBIC, reducing_gap=0)
with pytest.raises(ValueError):
gradients_image.resize((52, 34), Image.BICUBIC, reducing_gap=0.99)
def test_reducing_gap_1(self, gradients_image):
for box, epsilon in [
(None, 4),
((1.1, 2.2, 510.8, 510.9), 4),
((3, 10, 410, 256), 10),
]:
ref = gradients_image.resize((52, 34), Image.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.BICUBIC, box=box, reducing_gap=1.0
)
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
assert_image_similar(ref, im, epsilon)
def test_reducing_gap_2(self, gradients_image):
for box, epsilon in [
(None, 1.5),
((1.1, 2.2, 510.8, 510.9), 1.5),
((3, 10, 410, 256), 1),
]:
ref = gradients_image.resize((52, 34), Image.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.BICUBIC, box=box, reducing_gap=2.0
)
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
assert_image_similar(ref, im, epsilon)
def test_reducing_gap_3(self, gradients_image):
for box, epsilon in [
(None, 1),
((1.1, 2.2, 510.8, 510.9), 1),
((3, 10, 410, 256), 0.5),
]:
ref = gradients_image.resize((52, 34), Image.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.BICUBIC, box=box, reducing_gap=3.0
)
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
assert_image_similar(ref, im, epsilon)
def test_reducing_gap_8(self, gradients_image):
for box in [None, (1.1, 2.2, 510.8, 510.9), (3, 10, 410, 256)]:
ref = gradients_image.resize((52, 34), Image.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.BICUBIC, box=box, reducing_gap=8.0
)
assert_image_equal(ref, im)
def test_box_filter(self, gradients_image):
for box, epsilon in [
((0, 0, 512, 512), 5.5),
((0.9, 1.7, 128, 128), 9.5),
]:
ref = gradients_image.resize((52, 34), Image.BOX, box=box)
im = gradients_image.resize((52, 34), Image.BOX, box=box, reducing_gap=1.0)
assert_image_similar(ref, im, epsilon)
class TestImageResize:
def test_resize(self):
def resize(mode, size):
out = hopper(mode).resize(size)
assert out.mode == mode
assert out.size == size
for mode in "1", "P", "L", "RGB", "I", "F":
resize(mode, (112, 103))
resize(mode, (188, 214))
# Test unknown resampling filter
with hopper() as im:
with pytest.raises(ValueError):
im.resize((10, 10), "unknown")
def test_default_filter(self):
for mode in "L", "RGB", "I", "F":
im = hopper(mode)
assert im.resize((20, 20), Image.BICUBIC) == im.resize((20, 20))
for mode in "1", "P":
im = hopper(mode)
assert im.resize((20, 20), Image.NEAREST) == im.resize((20, 20))
|
