mirror of
https://github.com/python-pillow/Pillow.git
synced 2024-12-26 01:46:18 +03:00
Merge pull request #6531 from Yay295/parametrize
This commit is contained in:
Hugo van Kemenade
GitHub
commit
7cff8227d0
|
|
@ -5,53 +5,62 @@ from PIL import Image, ImageFilter
|
|||
from .helper import assert_image_equal, hopper
|
||||
|
||||
|
||||
def test_sanity():
|
||||
def apply_filter(filter_to_apply):
|
||||
for mode in ["L", "RGB", "CMYK"]:
|
||||
@pytest.mark.parametrize(
|
||||
"filter_to_apply",
|
||||
(
|
||||
ImageFilter.BLUR,
|
||||
ImageFilter.CONTOUR,
|
||||
ImageFilter.DETAIL,
|
||||
ImageFilter.EDGE_ENHANCE,
|
||||
ImageFilter.EDGE_ENHANCE_MORE,
|
||||
ImageFilter.EMBOSS,
|
||||
ImageFilter.FIND_EDGES,
|
||||
ImageFilter.SMOOTH,
|
||||
ImageFilter.SMOOTH_MORE,
|
||||
ImageFilter.SHARPEN,
|
||||
ImageFilter.MaxFilter,
|
||||
ImageFilter.MedianFilter,
|
||||
ImageFilter.MinFilter,
|
||||
ImageFilter.ModeFilter,
|
||||
ImageFilter.GaussianBlur,
|
||||
ImageFilter.GaussianBlur(5),
|
||||
ImageFilter.BoxBlur(5),
|
||||
ImageFilter.UnsharpMask,
|
||||
ImageFilter.UnsharpMask(10),
|
||||
),
|
||||
)
|
||||
@pytest.mark.parametrize("mode", ("L", "RGB", "CMYK"))
|
||||
def test_sanity(filter_to_apply, mode):
|
||||
im = hopper(mode)
|
||||
out = im.filter(filter_to_apply)
|
||||
assert out.mode == im.mode
|
||||
assert out.size == im.size
|
||||
|
||||
apply_filter(ImageFilter.BLUR)
|
||||
apply_filter(ImageFilter.CONTOUR)
|
||||
apply_filter(ImageFilter.DETAIL)
|
||||
apply_filter(ImageFilter.EDGE_ENHANCE)
|
||||
apply_filter(ImageFilter.EDGE_ENHANCE_MORE)
|
||||
apply_filter(ImageFilter.EMBOSS)
|
||||
apply_filter(ImageFilter.FIND_EDGES)
|
||||
apply_filter(ImageFilter.SMOOTH)
|
||||
apply_filter(ImageFilter.SMOOTH_MORE)
|
||||
apply_filter(ImageFilter.SHARPEN)
|
||||
apply_filter(ImageFilter.MaxFilter)
|
||||
apply_filter(ImageFilter.MedianFilter)
|
||||
apply_filter(ImageFilter.MinFilter)
|
||||
apply_filter(ImageFilter.ModeFilter)
|
||||
apply_filter(ImageFilter.GaussianBlur)
|
||||
apply_filter(ImageFilter.GaussianBlur(5))
|
||||
apply_filter(ImageFilter.BoxBlur(5))
|
||||
apply_filter(ImageFilter.UnsharpMask)
|
||||
apply_filter(ImageFilter.UnsharpMask(10))
|
||||
|
||||
@pytest.mark.parametrize("mode", ("L", "RGB", "CMYK"))
|
||||
def test_sanity_error(mode):
|
||||
with pytest.raises(TypeError):
|
||||
apply_filter("hello")
|
||||
im = hopper(mode)
|
||||
im.filter("hello")
|
||||
|
||||
|
||||
def test_crash():
|
||||
|
||||
# crashes on small images
|
||||
im = Image.new("RGB", (1, 1))
|
||||
im.filter(ImageFilter.SMOOTH)
|
||||
|
||||
im = Image.new("RGB", (2, 2))
|
||||
im.filter(ImageFilter.SMOOTH)
|
||||
|
||||
im = Image.new("RGB", (3, 3))
|
||||
# crashes on small images
|
||||
@pytest.mark.parametrize("size", ((1, 1), (2, 2), (3, 3)))
|
||||
def test_crash(size):
|
||||
im = Image.new("RGB", size)
|
||||
im.filter(ImageFilter.SMOOTH)
|
||||
|
||||
|
||||
def test_modefilter():
|
||||
def modefilter(mode):
|
||||
@pytest.mark.parametrize(
|
||||
"mode, expected",
|
||||
(
|
||||
("1", (4, 0)),
|
||||
("L", (4, 0)),
|
||||
("P", (4, 0)),
|
||||
("RGB", ((4, 0, 0), (0, 0, 0))),
|
||||
),
|
||||
)
|
||||
def test_modefilter(mode, expected):
|
||||
im = Image.new(mode, (3, 3), None)
|
||||
im.putdata(list(range(9)))
|
||||
# image is:
|
||||
|
|
@ -61,16 +70,20 @@ def test_modefilter():
|
|||
mod = im.filter(ImageFilter.ModeFilter).getpixel((1, 1))
|
||||
im.putdata([0, 0, 1, 2, 5, 1, 5, 2, 0]) # mode=0
|
||||
mod2 = im.filter(ImageFilter.ModeFilter).getpixel((1, 1))
|
||||
return mod, mod2
|
||||
|
||||
assert modefilter("1") == (4, 0)
|
||||
assert modefilter("L") == (4, 0)
|
||||
assert modefilter("P") == (4, 0)
|
||||
assert modefilter("RGB") == ((4, 0, 0), (0, 0, 0))
|
||||
assert (mod, mod2) == expected
|
||||
|
||||
|
||||
def test_rankfilter():
|
||||
def rankfilter(mode):
|
||||
@pytest.mark.parametrize(
|
||||
"mode, expected",
|
||||
(
|
||||
("1", (0, 4, 8)),
|
||||
("L", (0, 4, 8)),
|
||||
("RGB", ((0, 0, 0), (4, 0, 0), (8, 0, 0))),
|
||||
("I", (0, 4, 8)),
|
||||
("F", (0.0, 4.0, 8.0)),
|
||||
),
|
||||
)
|
||||
def test_rankfilter(mode, expected):
|
||||
im = Image.new(mode, (3, 3), None)
|
||||
im.putdata(list(range(9)))
|
||||
# image is:
|
||||
|
|
@ -80,15 +93,21 @@ def test_rankfilter():
|
|||
minimum = im.filter(ImageFilter.MinFilter).getpixel((1, 1))
|
||||
med = im.filter(ImageFilter.MedianFilter).getpixel((1, 1))
|
||||
maximum = im.filter(ImageFilter.MaxFilter).getpixel((1, 1))
|
||||
return minimum, med, maximum
|
||||
assert (minimum, med, maximum) == expected
|
||||
|
||||
assert rankfilter("1") == (0, 4, 8)
|
||||
assert rankfilter("L") == (0, 4, 8)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"filter", (ImageFilter.MinFilter, ImageFilter.MedianFilter, ImageFilter.MaxFilter)
|
||||
)
|
||||
def test_rankfilter_error(filter):
|
||||
with pytest.raises(ValueError):
|
||||
rankfilter("P")
|
||||
assert rankfilter("RGB") == ((0, 0, 0), (4, 0, 0), (8, 0, 0))
|
||||
assert rankfilter("I") == (0, 4, 8)
|
||||
assert rankfilter("F") == (0.0, 4.0, 8.0)
|
||||
im = Image.new("P", (3, 3), None)
|
||||
im.putdata(list(range(9)))
|
||||
# image is:
|
||||
# 0 1 2
|
||||
# 3 4 5
|
||||
# 6 7 8
|
||||
im.filter(filter).getpixel((1, 1))
|
||||
|
||||
|
||||
def test_rankfilter_properties():
|
||||
|
|
@ -110,7 +129,8 @@ def test_kernel_not_enough_coefficients():
|
|||
ImageFilter.Kernel((3, 3), (0, 0))
|
||||
|
||||
|
||||
def test_consistency_3x3():
|
||||
@pytest.mark.parametrize("mode", ("L", "LA", "RGB", "CMYK"))
|
||||
def test_consistency_3x3(mode):
|
||||
with Image.open("Tests/images/hopper.bmp") as source:
|
||||
with Image.open("Tests/images/hopper_emboss.bmp") as reference:
|
||||
kernel = ImageFilter.Kernel(
|
||||
|
|
@ -125,14 +145,14 @@ def test_consistency_3x3():
|
|||
source = source.split() * 2
|
||||
reference = reference.split() * 2
|
||||
|
||||
for mode in ["L", "LA", "RGB", "CMYK"]:
|
||||
assert_image_equal(
|
||||
Image.merge(mode, source[: len(mode)]).filter(kernel),
|
||||
Image.merge(mode, reference[: len(mode)]),
|
||||
)
|
||||
|
||||
|
||||
def test_consistency_5x5():
|
||||
@pytest.mark.parametrize("mode", ("L", "LA", "RGB", "CMYK"))
|
||||
def test_consistency_5x5(mode):
|
||||
with Image.open("Tests/images/hopper.bmp") as source:
|
||||
with Image.open("Tests/images/hopper_emboss_more.bmp") as reference:
|
||||
kernel = ImageFilter.Kernel(
|
||||
|
|
@ -149,7 +169,6 @@ def test_consistency_5x5():
|
|||
source = source.split() * 2
|
||||
reference = reference.split() * 2
|
||||
|
||||
for mode in ["L", "LA", "RGB", "CMYK"]:
|
||||
assert_image_equal(
|
||||
Image.merge(mode, source[: len(mode)]).filter(kernel),
|
||||
Image.merge(mode, reference[: len(mode)]),
|
||||
|
|
|
|||
|
|
@ -38,58 +38,64 @@ gradients_image = Image.open("Tests/images/radial_gradients.png")
|
|||
gradients_image.load()
|
||||
|
||||
|
||||
def test_args_factor():
|
||||
@pytest.mark.parametrize(
|
||||
"size, expected",
|
||||
(
|
||||
(3, (4, 4)),
|
||||
((3, 1), (4, 10)),
|
||||
((1, 3), (10, 4)),
|
||||
),
|
||||
)
|
||||
def test_args_factor(size, expected):
|
||||
im = Image.new("L", (10, 10))
|
||||
|
||||
assert (4, 4) == im.reduce(3).size
|
||||
assert (4, 10) == im.reduce((3, 1)).size
|
||||
assert (10, 4) == im.reduce((1, 3)).size
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(0)
|
||||
with pytest.raises(TypeError):
|
||||
im.reduce(2.0)
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce((0, 10))
|
||||
assert expected == im.reduce(size).size
|
||||
|
||||
|
||||
def test_args_box():
|
||||
@pytest.mark.parametrize(
|
||||
"size, expected_error", ((0, ValueError), (2.0, TypeError), ((0, 10), ValueError))
|
||||
)
|
||||
def test_args_factor_error(size, expected_error):
|
||||
im = Image.new("L", (10, 10))
|
||||
|
||||
assert (5, 5) == im.reduce(2, (0, 0, 10, 10)).size
|
||||
assert (1, 1) == im.reduce(2, (5, 5, 6, 6)).size
|
||||
|
||||
with pytest.raises(TypeError):
|
||||
im.reduce(2, "stri")
|
||||
with pytest.raises(TypeError):
|
||||
im.reduce(2, 2)
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (0, 0, 11, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (0, 0, 10, 11))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (-1, 0, 10, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (0, -1, 10, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (0, 5, 10, 5))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(2, (5, 0, 5, 10))
|
||||
with pytest.raises(expected_error):
|
||||
im.reduce(size)
|
||||
|
||||
|
||||
def test_unsupported_modes():
|
||||
@pytest.mark.parametrize(
|
||||
"size, expected",
|
||||
(
|
||||
((0, 0, 10, 10), (5, 5)),
|
||||
((5, 5, 6, 6), (1, 1)),
|
||||
),
|
||||
)
|
||||
def test_args_box(size, expected):
|
||||
im = Image.new("L", (10, 10))
|
||||
assert expected == im.reduce(2, size).size
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"size, expected_error",
|
||||
(
|
||||
("stri", TypeError),
|
||||
((0, 0, 11, 10), ValueError),
|
||||
((0, 0, 10, 11), ValueError),
|
||||
((-1, 0, 10, 10), ValueError),
|
||||
((0, -1, 10, 10), ValueError),
|
||||
((0, 5, 10, 5), ValueError),
|
||||
((5, 0, 5, 10), ValueError),
|
||||
),
|
||||
)
|
||||
def test_args_box_error(size, expected_error):
|
||||
im = Image.new("L", (10, 10))
|
||||
with pytest.raises(expected_error):
|
||||
im.reduce(2, size).size
|
||||
|
||||
|
||||
@pytest.mark.parametrize("mode", ("P", "1", "I;16"))
|
||||
def test_unsupported_modes(mode):
|
||||
im = Image.new("P", (10, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(3)
|
||||
|
||||
im = Image.new("1", (10, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(3)
|
||||
|
||||
im = Image.new("I;16", (10, 10))
|
||||
with pytest.raises(ValueError):
|
||||
im.reduce(3)
|
||||
|
||||
|
||||
def get_image(mode):
|
||||
mode_info = ImageMode.getmode(mode)
|
||||
|
|
@ -197,61 +203,67 @@ def test_mode_L():
|
|||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_LA():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_LA(factor):
|
||||
im = get_image("LA")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor, 0.8, 5)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_LA_opaque(factor):
|
||||
im = get_image("LA")
|
||||
# With opaque alpha, an error should be way smaller.
|
||||
im.putalpha(Image.new("L", im.size, 255))
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_La():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_La(factor):
|
||||
im = get_image("La")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_RGB():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_RGB(factor):
|
||||
im = get_image("RGB")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_RGBA():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_RGBA(factor):
|
||||
im = get_image("RGBA")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor, 0.8, 5)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_RGBA_opaque(factor):
|
||||
im = get_image("RGBA")
|
||||
# With opaque alpha, an error should be way smaller.
|
||||
im.putalpha(Image.new("L", im.size, 255))
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_RGBa():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_RGBa(factor):
|
||||
im = get_image("RGBa")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_I():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_I(factor):
|
||||
im = get_image("I")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
||||
def test_mode_F():
|
||||
@pytest.mark.parametrize("factor", remarkable_factors)
|
||||
def test_mode_F(factor):
|
||||
im = get_image("F")
|
||||
for factor in remarkable_factors:
|
||||
compare_reduce_with_reference(im, factor, 0, 0)
|
||||
compare_reduce_with_box(im, factor)
|
||||
|
||||
|
|
|
|||
|
|
@ -75,12 +75,15 @@ class TestImageTransform:
|
|||
|
||||
assert_image_equal(transformed, scaled)
|
||||
|
||||
def test_fill(self):
|
||||
for mode, pixel in [
|
||||
["RGB", (255, 0, 0)],
|
||||
["RGBA", (255, 0, 0, 255)],
|
||||
["LA", (76, 0)],
|
||||
]:
|
||||
@pytest.mark.parametrize(
|
||||
"mode, expected_pixel",
|
||||
(
|
||||
("RGB", (255, 0, 0)),
|
||||
("RGBA", (255, 0, 0, 255)),
|
||||
("LA", (76, 0)),
|
||||
),
|
||||
)
|
||||
def test_fill(self, mode, expected_pixel):
|
||||
im = hopper(mode)
|
||||
(w, h) = im.size
|
||||
transformed = im.transform(
|
||||
|
|
@ -90,8 +93,7 @@ class TestImageTransform:
|
|||
Image.Resampling.BILINEAR,
|
||||
fillcolor="red",
|
||||
)
|
||||
|
||||
assert transformed.getpixel((w - 1, h - 1)) == pixel
|
||||
assert transformed.getpixel((w - 1, h - 1)) == expected_pixel
|
||||
|
||||
def test_mesh(self):
|
||||
# this should be a checkerboard of halfsized hoppers in ul, lr
|
||||
|
|
@ -222,14 +224,12 @@ class TestImageTransform:
|
|||
with pytest.raises(ValueError):
|
||||
im.transform((100, 100), None)
|
||||
|
||||
def test_unknown_resampling_filter(self):
|
||||
@pytest.mark.parametrize("resample", (Image.Resampling.BOX, "unknown"))
|
||||
def test_unknown_resampling_filter(self, resample):
|
||||
with hopper() as im:
|
||||
(w, h) = im.size
|
||||
for resample in (Image.Resampling.BOX, "unknown"):
|
||||
with pytest.raises(ValueError):
|
||||
im.transform(
|
||||
(100, 100), Image.Transform.EXTENT, (0, 0, w, h), resample
|
||||
)
|
||||
im.transform((100, 100), Image.Transform.EXTENT, (0, 0, w, h), resample)
|
||||
|
||||
|
||||
class TestImageTransformAffine:
|
||||
|
|
@ -239,7 +239,16 @@ class TestImageTransformAffine:
|
|||
im = hopper("RGB")
|
||||
return im.crop((10, 20, im.width - 10, im.height - 20))
|
||||
|
||||
def _test_rotate(self, deg, transpose):
|
||||
@pytest.mark.parametrize(
|
||||
"deg, transpose",
|
||||
(
|
||||
(0, None),
|
||||
(90, Image.Transpose.ROTATE_90),
|
||||
(180, Image.Transpose.ROTATE_180),
|
||||
(270, Image.Transpose.ROTATE_270),
|
||||
),
|
||||
)
|
||||
def test_rotate(self, deg, transpose):
|
||||
im = self._test_image()
|
||||
|
||||
angle = -math.radians(deg)
|
||||
|
|
@ -271,77 +280,65 @@ class TestImageTransformAffine:
|
|||
)
|
||||
assert_image_equal(transposed, transformed)
|
||||
|
||||
def test_rotate_0_deg(self):
|
||||
self._test_rotate(0, None)
|
||||
|
||||
def test_rotate_90_deg(self):
|
||||
self._test_rotate(90, Image.Transpose.ROTATE_90)
|
||||
|
||||
def test_rotate_180_deg(self):
|
||||
self._test_rotate(180, Image.Transpose.ROTATE_180)
|
||||
|
||||
def test_rotate_270_deg(self):
|
||||
self._test_rotate(270, Image.Transpose.ROTATE_270)
|
||||
|
||||
def _test_resize(self, scale, epsilonscale):
|
||||
@pytest.mark.parametrize(
|
||||
"scale, epsilon_scale",
|
||||
(
|
||||
(1.1, 6.9),
|
||||
(1.5, 5.5),
|
||||
(2.0, 5.5),
|
||||
(2.3, 3.7),
|
||||
(2.5, 3.7),
|
||||
),
|
||||
)
|
||||
@pytest.mark.parametrize(
|
||||
"resample,epsilon",
|
||||
(
|
||||
(Image.Resampling.NEAREST, 0),
|
||||
(Image.Resampling.BILINEAR, 2),
|
||||
(Image.Resampling.BICUBIC, 1),
|
||||
),
|
||||
)
|
||||
def test_resize(self, scale, epsilon_scale, resample, epsilon):
|
||||
im = self._test_image()
|
||||
|
||||
size_up = int(round(im.width * scale)), int(round(im.height * scale))
|
||||
matrix_up = [1 / scale, 0, 0, 0, 1 / scale, 0, 0, 0]
|
||||
matrix_down = [scale, 0, 0, 0, scale, 0, 0, 0]
|
||||
|
||||
for resample, epsilon in [
|
||||
(Image.Resampling.NEAREST, 0),
|
||||
(Image.Resampling.BILINEAR, 2),
|
||||
(Image.Resampling.BICUBIC, 1),
|
||||
]:
|
||||
transformed = im.transform(size_up, self.transform, matrix_up, resample)
|
||||
transformed = transformed.transform(
|
||||
im.size, self.transform, matrix_down, resample
|
||||
)
|
||||
assert_image_similar(transformed, im, epsilon * epsilonscale)
|
||||
assert_image_similar(transformed, im, epsilon * epsilon_scale)
|
||||
|
||||
def test_resize_1_1x(self):
|
||||
self._test_resize(1.1, 6.9)
|
||||
|
||||
def test_resize_1_5x(self):
|
||||
self._test_resize(1.5, 5.5)
|
||||
|
||||
def test_resize_2_0x(self):
|
||||
self._test_resize(2.0, 5.5)
|
||||
|
||||
def test_resize_2_3x(self):
|
||||
self._test_resize(2.3, 3.7)
|
||||
|
||||
def test_resize_2_5x(self):
|
||||
self._test_resize(2.5, 3.7)
|
||||
|
||||
def _test_translate(self, x, y, epsilonscale):
|
||||
@pytest.mark.parametrize(
|
||||
"x, y, epsilon_scale",
|
||||
(
|
||||
(0.1, 0, 3.7),
|
||||
(0.6, 0, 9.1),
|
||||
(50, 50, 0),
|
||||
),
|
||||
)
|
||||
@pytest.mark.parametrize(
|
||||
"resample, epsilon",
|
||||
(
|
||||
(Image.Resampling.NEAREST, 0),
|
||||
(Image.Resampling.BILINEAR, 1.5),
|
||||
(Image.Resampling.BICUBIC, 1),
|
||||
),
|
||||
)
|
||||
def test_translate(self, x, y, epsilon_scale, resample, epsilon):
|
||||
im = self._test_image()
|
||||
|
||||
size_up = int(round(im.width + x)), int(round(im.height + y))
|
||||
matrix_up = [1, 0, -x, 0, 1, -y, 0, 0]
|
||||
matrix_down = [1, 0, x, 0, 1, y, 0, 0]
|
||||
|
||||
for resample, epsilon in [
|
||||
(Image.Resampling.NEAREST, 0),
|
||||
(Image.Resampling.BILINEAR, 1.5),
|
||||
(Image.Resampling.BICUBIC, 1),
|
||||
]:
|
||||
transformed = im.transform(size_up, self.transform, matrix_up, resample)
|
||||
transformed = transformed.transform(
|
||||
im.size, self.transform, matrix_down, resample
|
||||
)
|
||||
assert_image_similar(transformed, im, epsilon * epsilonscale)
|
||||
|
||||
def test_translate_0_1(self):
|
||||
self._test_translate(0.1, 0, 3.7)
|
||||
|
||||
def test_translate_0_6(self):
|
||||
self._test_translate(0.6, 0, 9.1)
|
||||
|
||||
def test_translate_50(self):
|
||||
self._test_translate(50, 50, 0)
|
||||
assert_image_similar(transformed, im, epsilon * epsilon_scale)
|
||||
|
||||
|
||||
class TestImageTransformPerspective(TestImageTransformAffine):
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user