Pillow/Tests/test_image_resize.py

290 lines
9.6 KiB
Python
Raw Normal View History

"""
Tests for resize functionality.
"""
from itertools import permutations
import pytest
from PIL import Image
from .helper import (
assert_image_equal,
assert_image_equal_tofile,
assert_image_similar,
hopper,
2022-04-20 04:05:12 +03:00
skip_unless_feature,
)
2020-03-28 04:51:28 +03:00
class TestImagingCoreResize:
def resize(self, im, size, f):
2014-11-19 11:26:02 +03:00
# Image class independent version of resize.
im.load()
return im._new(im.im.resize(size, f))
2022-08-23 14:41:32 +03:00
@pytest.mark.parametrize(
"mode", ("1", "P", "L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr", "I;16")
)
def test_nearest_mode(self, mode):
im = hopper(mode)
r = self.resize(im, (15, 12), Image.Resampling.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):
2022-01-15 01:02:31 +03:00
self.resize(hopper("1"), (15, 12), Image.Resampling.BILINEAR)
with pytest.raises(ValueError):
2022-01-15 01:02:31 +03:00
self.resize(hopper("P"), (15, 12), Image.Resampling.BILINEAR)
with pytest.raises(ValueError):
2022-01-15 01:02:31 +03:00
self.resize(hopper("I;16"), (15, 12), Image.Resampling.BILINEAR)
for mode in ["L", "I", "F", "RGB", "RGBA", "CMYK", "YCbCr"]:
im = hopper(mode)
2022-01-15 01:02:31 +03:00
r = self.resize(im, (15, 12), Image.Resampling.BILINEAR)
assert r.mode == mode
assert r.size == (15, 12)
assert r.im.bands == im.im.bands
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"resample",
(
2022-01-15 01:02:31 +03:00
Image.Resampling.NEAREST,
Image.Resampling.BOX,
Image.Resampling.BILINEAR,
Image.Resampling.HAMMING,
Image.Resampling.BICUBIC,
Image.Resampling.LANCZOS,
2022-08-24 03:37:40 +03:00
),
)
def test_reduce_filters(self, resample):
r = self.resize(hopper("RGB"), (15, 12), resample)
assert r.mode == "RGB"
assert r.size == (15, 12)
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"resample",
(
2022-01-15 01:02:31 +03:00
Image.Resampling.NEAREST,
Image.Resampling.BOX,
Image.Resampling.BILINEAR,
Image.Resampling.HAMMING,
Image.Resampling.BICUBIC,
Image.Resampling.LANCZOS,
2022-08-24 03:37:40 +03:00
),
)
def test_enlarge_filters(self, resample):
r = self.resize(hopper("RGB"), (212, 195), resample)
assert r.mode == "RGB"
assert r.size == (212, 195)
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"resample",
(
Image.Resampling.NEAREST,
Image.Resampling.BOX,
Image.Resampling.BILINEAR,
Image.Resampling.HAMMING,
Image.Resampling.BICUBIC,
Image.Resampling.LANCZOS,
),
)
@pytest.mark.parametrize(
"mode, channels_set",
(
("RGB", ("blank", "filled", "dirty")),
("RGBA", ("blank", "blank", "filled", "dirty")),
("LA", ("filled", "dirty")),
),
)
def test_endianness(self, resample, mode, channels_set):
# 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.
2015-05-29 07:59:54 +03:00
# The R and A channels should not swap, which is indicative of
# an endianness issues.
samples = {
2019-06-13 18:54:24 +03:00
"blank": Image.new("L", (2, 2), 0),
"filled": Image.new("L", (2, 2), 255),
"dirty": Image.new("L", (2, 2), 0),
}
2019-06-13 18:54:24 +03:00
samples["dirty"].putpixel((1, 1), 128)
2022-08-24 03:37:40 +03:00
# samples resized with current filter
references = {
name: self.resize(ch, (4, 4), resample) for name, ch in samples.items()
}
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), resample)
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]])
@pytest.mark.parametrize(
"resample",
(
2022-01-15 01:02:31 +03:00
Image.Resampling.NEAREST,
Image.Resampling.BOX,
Image.Resampling.BILINEAR,
Image.Resampling.HAMMING,
Image.Resampling.BICUBIC,
Image.Resampling.LANCZOS,
2022-08-24 03:37:40 +03:00
),
)
def test_enlarge_zero(self, resample):
r = self.resize(Image.new("RGB", (0, 0), "white"), (212, 195), resample)
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)
def test_cross_platform(self, tmp_path):
# This test is intended for only check for consistent behaviour across
# platforms. So if a future Pillow change requires that the test file
# be updated, that is okay.
im = hopper().resize((64, 64))
temp_file = str(tmp_path / "temp.gif")
im.save(temp_file)
with Image.open(temp_file) as reloaded:
assert_image_equal_tofile(reloaded, "Tests/images/hopper_resized.gif")
2014-06-10 13:10:47 +04:00
2020-03-28 04:51:28 +03:00
@pytest.fixture
def gradients_image():
2021-11-25 15:16:07 +03:00
with Image.open("Tests/images/radial_gradients.png") as im:
im.load()
2020-03-28 04:51:28 +03:00
try:
yield im
finally:
im.close()
2019-12-20 17:10:40 +03:00
2020-03-28 04:51:28 +03:00
class TestReducingGapResize:
def test_reducing_gap_values(self, gradients_image):
2022-01-15 01:02:31 +03:00
ref = gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, reducing_gap=None
)
im = gradients_image.resize((52, 34), Image.Resampling.BICUBIC)
assert_image_equal(ref, im)
2019-12-20 17:10:40 +03:00
with pytest.raises(ValueError):
2022-01-15 01:02:31 +03:00
gradients_image.resize((52, 34), Image.Resampling.BICUBIC, reducing_gap=0)
2019-12-20 17:10:40 +03:00
with pytest.raises(ValueError):
2022-01-15 01:02:31 +03:00
gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, reducing_gap=0.99
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"box, epsilon",
((None, 4), ((1.1, 2.2, 510.8, 510.9), 4), ((3, 10, 410, 256), 10)),
)
def test_reducing_gap_1(self, gradients_image, box, epsilon):
ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=1.0
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
assert_image_similar(ref, im, epsilon)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"box, epsilon",
((None, 1.5), ((1.1, 2.2, 510.8, 510.9), 1.5), ((3, 10, 410, 256), 1)),
)
def test_reducing_gap_2(self, gradients_image, box, epsilon):
ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=2.0
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
assert_image_similar(ref, im, epsilon)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"box, epsilon",
((None, 1), ((1.1, 2.2, 510.8, 510.9), 1), ((3, 10, 410, 256), 0.5)),
)
def test_reducing_gap_3(self, gradients_image, box, epsilon):
ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=3.0
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
with pytest.raises(AssertionError):
assert_image_equal(ref, im)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
assert_image_similar(ref, im, epsilon)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize("box", (None, (1.1, 2.2, 510.8, 510.9), (3, 10, 410, 256)))
def test_reducing_gap_8(self, gradients_image, box):
ref = gradients_image.resize((52, 34), Image.Resampling.BICUBIC, box=box)
im = gradients_image.resize(
(52, 34), Image.Resampling.BICUBIC, box=box, reducing_gap=8.0
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
assert_image_equal(ref, im)
2019-12-20 20:30:23 +03:00
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"box, epsilon",
(((0, 0, 512, 512), 5.5), ((0.9, 1.7, 128, 128), 9.5)),
)
def test_box_filter(self, gradients_image, box, epsilon):
ref = gradients_image.resize((52, 34), Image.Resampling.BOX, box=box)
im = gradients_image.resize(
(52, 34), Image.Resampling.BOX, box=box, reducing_gap=1.0
)
2019-12-20 17:10:40 +03:00
2022-08-24 03:37:40 +03:00
assert_image_similar(ref, im, epsilon)
2019-12-20 17:10:40 +03:00
2020-03-28 04:51:28 +03:00
class TestImageResize:
2014-06-10 13:10:47 +04:00
def test_resize(self):
def resize(mode, size):
out = hopper(mode).resize(size)
assert out.mode == mode
assert out.size == size
2019-06-13 18:54:24 +03:00
2014-06-10 13:10:47 +04:00
for mode in "1", "P", "L", "RGB", "I", "F":
resize(mode, (112, 103))
resize(mode, (188, 214))
2014-06-10 13:10:47 +04:00
2017-09-01 13:36:51 +03:00
# Test unknown resampling filter
Improve handling of file resources Follow Python's file object semantics. User code is responsible for closing resources (usually through a context manager) in a deterministic way. To achieve this, remove __del__ functions. These functions used to closed open file handlers in an attempt to silence Python ResourceWarnings. However, using __del__ has the following drawbacks: - __del__ isn't called until the object's reference count reaches 0. Therefore, resource handlers remain open or in use longer than necessary. - The __del__ method isn't guaranteed to execute on system exit. See the Python documentation: https://docs.python.org/3/reference/datamodel.html#object.__del__ > It is not guaranteed that __del__() methods are called for objects > that still exist when the interpreter exits. - Exceptions that occur inside __del__ are ignored instead of raised. This has the potential of hiding bugs. This is also in the Python documentation: > Warning: Due to the precarious circumstances under which __del__() > methods are invoked, exceptions that occur during their execution > are ignored, and a warning is printed to sys.stderr instead. Instead, always close resource handlers when they are no longer in use. This will close the file handler at a specified point in the user's code and not wait until the interpreter chooses to. It is always guaranteed to run. And, if an exception occurs while closing the file handler, the bug will not be ignored. Now, when code receives a ResourceWarning, it will highlight an area that is mishandling resources. It should not simply be silenced, but fixed by closing resources with a context manager. All warnings that were emitted during tests have been cleaned up. To enable warnings, I passed the `-Wa` CLI option to Python. This exposed some mishandling of resources in ImageFile.__init__() and SpiderImagePlugin.loadImageSeries(), they too were fixed.
2019-05-25 19:30:58 +03:00
with hopper() as im:
with pytest.raises(ValueError):
im.resize((10, 10), "unknown")
2022-04-20 04:05:12 +03:00
@skip_unless_feature("libtiff")
2022-04-08 12:11:27 +03:00
def test_load_first(self):
# load() may change the size of the image
# Test that resize() is calling it before getting the size
with Image.open("Tests/images/g4_orientation_5.tif") as im:
im = im.resize((64, 64))
assert im.size == (64, 64)
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize("mode", ("L", "RGB", "I", "F"))
def test_default_filter_bicubic(self, mode):
im = hopper(mode)
assert im.resize((20, 20), Image.Resampling.BICUBIC) == im.resize((20, 20))
2022-08-24 03:37:40 +03:00
@pytest.mark.parametrize(
"mode", ("1", "P", "I;16", "I;16L", "I;16B", "BGR;15", "BGR;16")
)
def test_default_filter_nearest(self, mode):
im = hopper(mode)
assert im.resize((20, 20), Image.Resampling.NEAREST) == im.resize((20, 20))