def _test_augmenter(cls, augmenter_name, func_expected,
dependent_on_seed):
# this test verifies:
# - called function seems to be the expected function
# - images produced by augmenter match images produced by function
# - a different seed (and sometimes severity) will lead to a
# different image
# - augmenter can be pickled
severity = 5
aug_cls = getattr(iaa.imgcorruptlike, augmenter_name)
image = np.mod(
np.arange(32*32*3), 256
).reshape((32, 32, 3)).astype(np.uint8)
with iap.no_prefetching():
rng = iarandom.RNG(1)
# Replay sampling of severities.
# Even for deterministic values this is required as currently
# there is an advance() at the end of each draw_samples().
_ = iap.Deterministic(1).draw_samples((1,), rng)
# As for the functions above, we can't just change the seed value
# to get different augmentations as many functions are dependend
# only on the severity. So we change only for some functions only
# the seed and for the others severity+seed.
image_aug1 = aug_cls(severity=severity, seed=1)(image=image)
image_aug2 = aug_cls(severity=severity, seed=1)(image=image)
if dependent_on_seed:
image_aug3 = aug_cls(severity=severity, seed=2)(
image=image)
else:
image_aug3 = aug_cls(severity=severity-1, seed=2)(
image=image)
image_aug_exp = func_expected(
image,
severity=severity,
seed=rng.generate_seed_())
assert aug_cls(severity=severity).func is func_expected
assert np.array_equal(image_aug1, image_aug_exp)
assert np.array_equal(image_aug2, image_aug_exp)
assert not np.array_equal(image_aug3, image_aug2)
# pickling test
aug = aug_cls(severity=(1, 5))
runtest_pickleable_uint8_img(aug, shape=(32, 32, 3))
def test_pickleable(self):
aug = iaa.Cartoon(seed=1)
runtest_pickleable_uint8_img(aug, iterations=6)
def test_pickleable(self):
aug = iaa.Rain(random_state=1)
runtest_pickleable_uint8_img(aug, iterations=3, shape=(20, 20, 3))
def test_pickleable(self):
aug = iaa.FastSnowyLandscape(lightness_threshold=(50, 150),
lightness_multiplier=(1.0, 3.0),
random_state=1)
runtest_pickleable_uint8_img(aug)
def test_pickleable(self):
aug = self.augmenter((1, 7), random_state=1)
runtest_pickleable_uint8_img(aug, iterations=10, shape=(25, 25, 1))
def test_pickleable(self):
aug = iaa.Emboss(alpha=(0.0, 1.0), strength=(1, 3), seed=1)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable(self):
aug = iaa.Sharpen(alpha=(0.0, 1.0), lightness=(1, 3), seed=1)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable__callback_function(self):
aug = iaa.Convolve(_convolve_pickleable_matrix_generator, seed=1)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable__identity_matrix(self):
identity_matrix = np.int64([[1]])
aug = iaa.Convolve(identity_matrix, seed=1)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable(self):
aug = iaa.Canny(random_state=1)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable(self):
aug = self.create_aug(0.5)
runtest_pickleable_uint8_img(aug, iterations=20)
def test_pickleable(self):
aug = iaa.Snowflakes(seed=1)
runtest_pickleable_uint8_img(aug, iterations=3, shape=(20, 20, 3))
def test_pickleable(self):
aug = iaa.RandAugment(m=(0, 10), n=(1, 2))
runtest_pickleable_uint8_img(aug, iterations=50)
