本文整理汇总了Python中imgaug.augmenters.Sharpen方法的典型用法代码示例。如果您正苦于以下问题：Python augmenters.Sharpen方法的具体用法？Python augmenters.Sharpen怎么用？Python augmenters.Sharpen使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类imgaug.augmenters的用法示例。
在下文中一共展示了augmenters.Sharpen方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: chapter_augmenters_sometimes
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def chapter_augmenters_sometimes():
aug = iaa.Sometimes(0.5, iaa.GaussianBlur(sigma=2.0))
run_and_save_augseq(
"sometimes.jpg", aug,
[ia.quokka(size=(64, 64)) for _ in range(16)], cols=8, rows=2,
seed=2
)
aug = iaa.Sometimes(
0.5,
iaa.GaussianBlur(sigma=2.0),
iaa.Sequential([iaa.Affine(rotate=45), iaa.Sharpen(alpha=1.0)])
)
run_and_save_augseq(
"sometimes_if_else.jpg", aug,
[ia.quokka(size=(64, 64)) for _ in range(16)], cols=8, rows=2
) 示例2: chapter_augmenters_sharpen
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def chapter_augmenters_sharpen():
aug = iaa.Sharpen(alpha=(0.0, 1.0), lightness=(0.75, 2.0))
run_and_save_augseq(
"sharpen.jpg", aug,
[ia.quokka(size=(64, 64)) for _ in range(16)], cols=8, rows=2
)
#alphas = [1/8*i for i in range(8)]
alphas = np.linspace(0, 1.0, num=8)
run_and_save_augseq(
"sharpen_vary_alpha.jpg",
[iaa.Sharpen(alpha=alpha, lightness=1.0) for alpha in alphas],
[ia.quokka(size=(64, 64)) for _ in range(8)], cols=8, rows=1,
quality=90
)
#lightnesses = [1/8*i for i in range(8)]
lightnesses = np.linspace(0.75, 1.5, num=8)
run_and_save_augseq(
"sharpen_vary_lightness.jpg",
[iaa.Sharpen(alpha=1.0, lightness=lightness) for lightness in lightnesses],
[ia.quokka(size=(64, 64)) for _ in range(8)], cols=8, rows=1,
quality=90
) 示例3: test_alpha_zero
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_zero(self):
aug = iaa.Sharpen(alpha=0, lightness=1)
observed = aug.augment_image(self.base_img)
expected = self.base_img
assert np.allclose(observed, expected) 示例4: test_alpha_one
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_one(self):
aug = iaa.Sharpen(alpha=1.0, lightness=1)
observed = aug.augment_image(self.base_img)
expected = self.base_img_sharpened
assert np.allclose(observed, expected) 示例5: test_alpha_050
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_050(self):
aug = iaa.Sharpen(alpha=0.5, lightness=1)
observed = aug.augment_image(self.base_img)
expected = self._compute_sharpened_base_img(
0.5*1, 0.5 * self.m_noop + 0.5 * self.m)
assert np.allclose(observed, expected.astype(np.uint8)) 示例6: test_alpha_075
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_075(self):
aug = iaa.Sharpen(alpha=0.75, lightness=1)
observed = aug.augment_image(self.base_img)
expected = self._compute_sharpened_base_img(
0.75*1, 0.25 * self.m_noop + 0.75 * self.m)
assert np.allclose(observed, expected) 示例7: test_alpha_is_stochastic_parameter
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_is_stochastic_parameter(self):
aug = iaa.Sharpen(alpha=iap.Choice([0.5, 1.0]), lightness=1)
observed = aug.augment_image(self.base_img)
expected1 = self._compute_sharpened_base_img(
0.5*1, 0.5 * self.m_noop + 0.5 * self.m)
expected2 = self._compute_sharpened_base_img(
1.0*1, 0.0 * self.m_noop + 1.0 * self.m)
assert (
np.allclose(observed, expected1)
or np.allclose(observed, expected2)
) 示例8: test_alpha_1_lightness_2
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_1_lightness_2(self):
aug = iaa.Sharpen(alpha=1.0, lightness=2)
observed = aug.augment_image(self.base_img)
expected = self._compute_sharpened_base_img(1.0*2, self.m)
assert np.allclose(observed, expected) 示例9: test_alpha_1_lightness_3
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_1_lightness_3(self):
aug = iaa.Sharpen(alpha=1.0, lightness=3)
observed = aug.augment_image(self.base_img)
expected = self._compute_sharpened_base_img(1.0*3, self.m)
assert np.allclose(observed, expected) 示例10: test_alpha_1_lightness_is_stochastic_parameter
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_alpha_1_lightness_is_stochastic_parameter(self):
aug = iaa.Sharpen(alpha=1.0, lightness=iap.Choice([1.0, 1.5]))
observed = aug.augment_image(self.base_img)
expected1 = self._compute_sharpened_base_img(1.0*1.0, self.m)
expected2 = self._compute_sharpened_base_img(1.0*1.5, self.m)
assert (
np.allclose(observed, expected1)
or np.allclose(observed, expected2)
) 示例11: test_failure_if_lightness_has_bad_datatype
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_failure_if_lightness_has_bad_datatype(self):
# don't use assertRaisesRegex, because it doesnt exist in 2.7
got_exception = False
try:
_ = iaa.Sharpen(alpha=1.0, lightness="test")
except Exception as exc:
assert "Expected " in str(exc)
got_exception = True
assert got_exception
# this part doesnt really work so far due to nonlinearities resulting
# from clipping to uint8 示例12: test_pickleable
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def test_pickleable(self):
aug = iaa.Sharpen(alpha=(0.0, 1.0), lightness=(1, 3), seed=1)
runtest_pickleable_uint8_img(aug, iterations=20) 示例13: __init__
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def __init__(self, alpha=(0.2, 0.5), lightness=(0.5, 1.), prob=0.5):
super().__init__(prob)
self.processor = iaa.Sharpen(alpha, lightness) 示例14: chapter_augmenters_someof
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def chapter_augmenters_someof():
aug = iaa.SomeOf(2, [
iaa.Affine(rotate=45),
iaa.AdditiveGaussianNoise(scale=0.2*255),
iaa.Add(50, per_channel=True),
iaa.Sharpen(alpha=0.5)
])
run_and_save_augseq(
"someof.jpg", aug,
[ia.quokka(size=(128, 128)) for _ in range(8)], cols=4, rows=2
)
aug = iaa.SomeOf((0, None), [
iaa.Affine(rotate=45),
iaa.AdditiveGaussianNoise(scale=0.2*255),
iaa.Add(50, per_channel=True),
iaa.Sharpen(alpha=0.5)
])
run_and_save_augseq(
"someof_0_to_none.jpg", aug,
[ia.quokka(size=(128, 128)) for _ in range(8)], cols=4, rows=2
)
aug = iaa.SomeOf(2, [
iaa.Affine(rotate=45),
iaa.AdditiveGaussianNoise(scale=0.2*255),
iaa.Add(50, per_channel=True),
iaa.Sharpen(alpha=0.5)
], random_order=True)
run_and_save_augseq(
"someof_random_order.jpg", aug,
[ia.quokka(size=(128, 128)) for _ in range(8)], cols=4, rows=2
) 示例15: chapter_augmenters_oneof
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import Sharpen [as 别名]
def chapter_augmenters_oneof():
aug = iaa.OneOf([
iaa.Affine(rotate=45),
iaa.AdditiveGaussianNoise(scale=0.2*255),
iaa.Add(50, per_channel=True),
iaa.Sharpen(alpha=0.5)
])
run_and_save_augseq(
"oneof.jpg", aug,
[ia.quokka(size=(128, 128)) for _ in range(8)], cols=4, rows=2
)