def test_ImageAugmentizer_BadParameter(self):
with self.assertRaises(TypeError):
ImageAugmentizer("pxr_config.ini")
with self.assertRaises(TypeError):
ImageAugmentizer(5566)
with self.assertRaises(TypeError):
ImageAugmentizer(NormalizeConfig("augment_config_noaug.ini"))
def test_ImageAugmentizer_Aug_UD_4D(self):
ia0 = ImageAugmentizer(self.conf_ud)
image_aug = ia0.augmentize(self.image0_1)
diff = self.image0_1 - image_aug
self.assertFalse((diff == np.zeros_like(diff)).all())
image_aug = ia0.augmentize(self.imagecxr0_1)
diff = self.imagecxr0_1 - image_aug
self.assertFalse((diff == np.zeros_like(diff)).all())
def test_ImageAugmentizer_Aug_LR(self):
ia0 = ImageAugmentizer(self.conf_lr)
image0_aug = ia0.augmentize(self.image0)
diff = self.image0 - image0_aug
self.assertFalse((diff == np.zeros_like(diff)).all())
image0_aug = ia0.augmentize(self.imagecxr0)
diff = self.imagecxr0 - image0_aug
self.assertFalse((diff == np.zeros_like(diff)).all())
def test_ImageAugmentizer_Aug_Prob(self):
ia0 = ImageAugmentizer(self.conf_prob)
flipped_times = 0
test_runs = 10000
for i in range(test_runs):
image0_aug = ia0.augmentize(self.image0)
diff = self.image0 - image0_aug
if not (diff == np.zeros_like(diff)).all():
flipped_times += 1
self.assertTrue(abs(flipped_times / test_runs - self.conf_prob.flip_prob) < 0.01)
def test_wrong_dimension(self):
with self.assertRaises(ValueError):
ia0 = ImageAugmentizer(self.conf)
ia0.augmentize(np.random.rand(1, 1))
with self.assertRaises(ValueError):
ia0 = ImageAugmentizer(self.conf)
ia0.augmentize(np.random.rand(1))
def batch_generator(image_filenames,
labels,
image_config,
mode="train",
verbosity=0):
"""
:param image_filenames:
:param labels:
:param image_config:
:param mode:
:type image_config: ImageConfig
:param verbosity:
:return:
"""
aug_enable = (image_config.AugmentConfig.train_augmentation and mode
== "train") or (image_config.AugmentConfig.dev_augmentation
and mode == "dev")
norm_enable = (mode != "raw")
augmentizer = ImageAugmentizer(
image_config.AugmentConfig) if aug_enable else None
normalizer = ImageNormalizer(
image_config.NormalizeConfig) if norm_enable else None
inputs = image_generator(image_filenames=image_filenames,
image_config=image_config,
mode=mode,
aug=augmentizer,
norm=normalizer,
verbosity=verbosity)
targets = np.array(labels)
if image_config.class_mode == 'multibinary':
targets = np.swapaxes(labels, 0, 1)
targets = [
np.array(targets[i, :]) for i in range(np.shape(targets)[0])
]
print(f"(input, targets) = ({np.shape(inputs)}, {np.shape(targets)})"
) if verbosity > 2 else None
print(f"targets = {targets}") if verbosity > 2 else None
return inputs, targets
def test_ImageAugmentizer_NoAug(self):
ia0 = ImageAugmentizer(self.conf_noaug)
image0_aug = ia0.augmentize(self.image0)
self.assertTrue((self.image0 == image0_aug).all())
def test_ImageAugmentizer_NoArgument(self):
with self.assertRaises(TypeError):
ImageAugmentizer()
def test_ImageAugmentizer(self):
ia0 = ImageAugmentizer(self.conf)
self.assertTrue(isinstance(ia0, ImageAugmentizer))