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parametrize tests

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Yay295 2022-08-24 07:43:49 -05:00 committed by GitHub
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159
Tests/test_image_transform.py
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@ -75,23 +75,25 @@ 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)],
]:
im = hopper(mode)
(w, h) = im.size
transformed = im.transform(
im.size,
Image.Transform.EXTENT,
(0, 0, w * 2, h * 2),
Image.Resampling.BILINEAR,
fillcolor="red",
)
assert transformed.getpixel((w - 1, h - 1)) == pixel
@pytest.mark.parametrize(
"mode,pixel",
(
("RGB", (255, 0, 0)),
("RGBA", (255, 0, 0, 255)),
("LA", (76, 0)),
),
)
def test_fill(self, mode, pixel):
im = hopper(mode)
(w, h) = im.size
transformed = im.transform(
im.size,
Image.Transform.EXTENT,
(0, 0, w * 2, h * 2),
Image.Resampling.BILINEAR,
fillcolor="red",
)
assert transformed.getpixel((w - 1, h - 1)) == 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
)
with pytest.raises(ValueError):
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,epsilonscale",
(
(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, epsilonscale, 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 [
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)
@pytest.mark.parametrize(
"x,y,epsilonscale",
(
(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, 2),
(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_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):
),
)
def test_translate(self, x, y, epsilonscale, 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)
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)
class TestImageTransformPerspective(TestImageTransformAffine):