本文整理汇总了Python中imgaug.augmenters.AverageBlur方法的典型用法代码示例。如果您正苦于以下问题:Python augmenters.AverageBlur方法的具体用法?Python augmenters.AverageBlur怎么用?Python augmenters.AverageBlur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.AverageBlur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: test_kernel_size_is_tuple
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_is_tuple(self):
# k as (3, 4)
aug = iaa.AverageBlur(k=(3, 4))
nb_iterations = 100
nb_seen = [0, 0]
for i in sm.xrange(nb_iterations):
observed = aug.augment_image(self.base_img)
if np.array_equal(observed, self.blur3x3):
nb_seen[0] += 1
elif np.array_equal(observed, self.blur4x4):
nb_seen[1] += 1
else:
raise Exception("Unexpected result in AverageBlur@1")
p_seen = [v/nb_iterations for v in nb_seen]
assert 0.4 <= p_seen[0] <= 0.6
assert 0.4 <= p_seen[1] <= 0.6
示例2: test_kernel_size_is_stochastic_parameter
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_is_stochastic_parameter(self):
# k as stochastic parameter
aug = iaa.AverageBlur(k=iap.Choice([3, 5]))
nb_iterations = 100
nb_seen = [0, 0]
for i in sm.xrange(nb_iterations):
observed = aug.augment_image(self.base_img)
if np.array_equal(observed, self.blur3x3):
nb_seen[0] += 1
elif np.array_equal(observed, self.blur5x5):
nb_seen[1] += 1
else:
raise Exception("Unexpected result in AverageBlur@3")
p_seen = [v/nb_iterations for v in nb_seen]
assert 0.4 <= p_seen[0] <= 0.6
assert 0.4 <= p_seen[1] <= 0.6
示例3: test_kernel_size_is_tuple_of_tuples
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_is_tuple_of_tuples(self):
# k as ((3, 5), (3, 5))
aug = iaa.AverageBlur(k=((3, 5), (3, 5)))
possible = dict()
for kh in [3, 4, 5]:
for kw in [3, 4, 5]:
key = (kh, kw)
if kh == 0 or kw == 0:
possible[key] = np.copy(self.base_img)
else:
possible[key] = cv2.blur(
self.base_img, (kh, kw))[..., np.newaxis]
nb_iterations = 250
nb_seen = dict([(key, 0) for key, val in possible.items()])
for i in sm.xrange(nb_iterations):
observed = aug.augment_image(self.base_img)
for key, img_aug in possible.items():
if np.array_equal(observed, img_aug):
nb_seen[key] += 1
# dont check sum here, because 0xX and Xx0 are all the same, i.e. much
# higher sum than nb_iterations
assert np.all([v > 0 for v in nb_seen.values()])
示例4: test_zero_sized_axes
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_zero_sized_axes(self):
shapes = [
(0, 0),
(0, 1),
(1, 0),
(0, 1, 0),
(1, 0, 0),
(0, 1, 1),
(1, 0, 1)
]
for shape in shapes:
with self.subTest(shape=shape):
image = np.zeros(shape, dtype=np.uint8)
image_aug = iaa.AverageBlur(k=3)(image=image)
assert image_aug.shape == image.shape
示例5: __init__
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def __init__(self):
self.seq = iaa.Sequential([
iaa.Sometimes(0.5, iaa.OneOf([
iaa.GaussianBlur((0, 3.0)), # blur images with a sigma between 0 and 3.0
iaa.AverageBlur(k=(2, 7)), # blur image using local means with kernel sizes between 2 and 7
iaa.MedianBlur(k=(3, 11)), # blur image using local medians with kernel sizes between 2 and 7
])),
iaa.Sometimes(0.5, iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05 * 255), per_channel=0.5)),
iaa.Sometimes(0.5, iaa.Add((-10, 10), per_channel=0.5)),
iaa.Sometimes(0.5, iaa.AddToHueAndSaturation((-20, 20))),
iaa.Sometimes(0.5, iaa.FrequencyNoiseAlpha(
exponent=(-4, 0),
first=iaa.Multiply((0.5, 1.5), per_channel=True),
second=iaa.LinearContrast((0.5, 2.0))
)),
iaa.Sometimes(0.5, iaa.PiecewiseAffine(scale=(0.01, 0.05))),
iaa.Sometimes(0.5, iaa.PerspectiveTransform(scale=(0.01, 0.1)))
], random_order=True)
示例6: __init__
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def __init__(self, augmentation_rate):
self.augs = iaa.Sometimes(
augmentation_rate,
iaa.SomeOf(
(4, 7),
[
iaa.Affine(rotate=(-10, 10)),
iaa.Fliplr(0.2),
iaa.AverageBlur(k=(2, 10)),
iaa.Add((-10, 10), per_channel=0.5),
iaa.Multiply((0.75, 1.25), per_channel=0.5),
iaa.ContrastNormalization((0.5, 2.0), per_channel=0.5),
iaa.Crop(px=(0, 20))
],
random_order=True
)
)
示例7: main
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def main():
image = data.astronaut()
image = ia.imresize_single_image(image, (64, 64))
print("image shape:", image.shape)
print("Press any key or wait %d ms to proceed to the next image." % (TIME_PER_STEP,))
k = [
1,
2,
4,
8,
16,
(8, 8),
(1, 8),
((1, 1), (8, 8)),
((1, 16), (1, 16)),
((1, 16), 1)
]
cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
cv2.resizeWindow("aug", 64*NB_AUGS_PER_IMAGE, 64)
for ki in k:
aug = iaa.AverageBlur(k=ki)
img_aug = [aug.augment_image(image) for _ in range(NB_AUGS_PER_IMAGE)]
img_aug = np.hstack(img_aug)
print("dtype", img_aug.dtype, "averages", np.average(img_aug, axis=tuple(range(0, img_aug.ndim-1))))
title = "k=%s" % (str(ki),)
img_aug = ia.draw_text(img_aug, x=5, y=5, text=title)
cv2.imshow("aug", img_aug[..., ::-1]) # here with rgb2bgr
cv2.waitKey(TIME_PER_STEP)
示例8: test_kernel_size_0
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_0(self):
# no blur, shouldnt change anything
aug = iaa.AverageBlur(k=0)
observed = aug.augment_image(self.base_img)
assert np.array_equal(observed, self.base_img)
示例9: test_kernel_size_3
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_3(self):
# k=3
aug = iaa.AverageBlur(k=3)
observed = aug.augment_image(self.base_img)
assert np.array_equal(observed, self.blur3x3)
示例10: test_kernel_size_5
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_kernel_size_5(self):
# k=5
aug = iaa.AverageBlur(k=5)
observed = aug.augment_image(self.base_img)
assert np.array_equal(observed, self.blur5x5)
示例11: test_more_than_four_channels
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_more_than_four_channels(self):
shapes = [
(1, 1, 4),
(1, 1, 5),
(1, 1, 512),
(1, 1, 513)
]
for shape in shapes:
with self.subTest(shape=shape):
image = np.zeros(shape, dtype=np.uint8)
image_aug = iaa.AverageBlur(k=3)(image=image)
assert image_aug.shape == image.shape
示例12: test_keypoints_dont_change
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_keypoints_dont_change(self):
kps = [ia.Keypoint(x=0, y=0), ia.Keypoint(x=1, y=1),
ia.Keypoint(x=2, y=2)]
kpsoi = [ia.KeypointsOnImage(kps, shape=(11, 11, 1))]
aug = iaa.AverageBlur(k=3)
aug_det = aug.to_deterministic()
observed = aug.augment_keypoints(kpsoi)
expected = kpsoi
assert keypoints_equal(observed, expected)
observed = aug_det.augment_keypoints(kpsoi)
expected = kpsoi
assert keypoints_equal(observed, expected)
示例13: test_failure_on_invalid_dtypes
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_failure_on_invalid_dtypes(self):
# assert failure on invalid dtypes
aug = iaa.AverageBlur(k=3)
for dt in [np.uint32, np.uint64, np.int32, np.int64]:
got_exception = False
try:
_ = aug.augment_image(np.zeros((1, 1), dtype=dt))
except Exception as exc:
assert "forbidden dtype" in str(exc)
got_exception = True
assert got_exception
示例14: test_pickleable
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def test_pickleable(self):
aug = iaa.AverageBlur((1, 11), seed=1)
runtest_pickleable_uint8_img(aug, iterations=10)
示例15: main
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import AverageBlur [as 别名]
def main():
image = data.astronaut()
image = ia.imresize_single_image(image, (64, 64))
print("image shape:", image.shape)
print("Press any key or wait %d ms to proceed to the next image." % (TIME_PER_STEP,))
k = [
1,
2,
4,
8,
16,
(8, 8),
(1, 8),
((1, 1), (8, 8)),
((1, 16), (1, 16)),
((1, 16), 1)
]
cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
cv2.resizeWindow("aug", 64*NB_AUGS_PER_IMAGE, 64)
#cv2.imshow("aug", image[..., ::-1])
#cv2.waitKey(TIME_PER_STEP)
for ki in k:
aug = iaa.AverageBlur(k=ki)
img_aug = [aug.augment_image(image) for _ in range(NB_AUGS_PER_IMAGE)]
img_aug = np.hstack(img_aug)
print("dtype", img_aug.dtype, "averages", np.average(img_aug, axis=tuple(range(0, img_aug.ndim-1))))
#print("dtype", img_aug.dtype, "averages", img_aug.mean(axis=range(1, img_aug.ndim)))
title = "k=%s" % (str(ki),)
img_aug = ia.draw_text(img_aug, x=5, y=5, text=title)
cv2.imshow("aug", img_aug[..., ::-1]) # here with rgb2bgr
cv2.waitKey(TIME_PER_STEP)