def box_segmentation_aug():
return Compose([
OneOf([
RandomBrightnessContrast(brightness_limit=0.2, p=0.5),
RandomGamma(gamma_limit=50, p=0.5),
ChannelShuffle(p=0.5)
]),
OneOf([
ImageCompression(quality_lower=0, quality_upper=20, p=0.5),
MultiplicativeNoise(multiplier=(0.3, 0.8),
elementwise=True,
per_channel=True,
p=0.5),
Blur(blur_limit=(15, 15), p=0.5)
]),
OneOf([
CenterCrop(height=1000, width=1000, p=0.1),
RandomGridShuffle(grid=(3, 3), p=0.2),
CoarseDropout(max_holes=20,
max_height=100,
max_width=100,
fill_value=53,
p=0.2)
]),
OneOf([
GridDistortion(p=0.5, num_steps=2, distort_limit=0.2),
ElasticTransform(alpha=157, sigma=80, alpha_affine=196, p=0.5),
OpticalDistortion(distort_limit=0.5, shift_limit=0.5, p=0.5)
]),
OneOf([
VerticalFlip(p=0.5),
HorizontalFlip(p=0.5),
Rotate(limit=44, p=0.5)
])
])
def strong_aug(p=0.5):
return Compose([
RandomGridShuffle((2, 2), p=0.75),
OneOf([
ShiftScaleRotate(shift_limit=0.125),
Transpose(),
RandomRotate90(),
VerticalFlip(),
HorizontalFlip(),
IAAAffine(shear=0.1)
]),
OneOf([GaussNoise(),
GaussianBlur(),
MedianBlur(),
MotionBlur()]),
OneOf([RandomBrightnessContrast(),
CLAHE(), IAASharpen()]),
Cutout(10, 2, 2, 127),
],
p=p)
def augmentation_hardcore(size_image, p=0.8):
'''
Only use for second model
About albumentation, p in compose mean the prob that all transform in Compose work
'''
return Compose([
Resize(size_image, size_image),
CenterCrop(height=200, width=200, p=0.5),
Cutout(),
RandomShadow(shadow_dimension=3),
OneOf([
Flip(),
VerticalFlip(),
HorizontalFlip(),
], p=0.5),
OneOf([
RandomRotate90(),
Transpose(),
], p=0.5),
OneOf([GaussNoise(), GaussianBlur(blur_limit=9),
Blur()], p=0.5),
OneOf([
HueSaturationValue(
hue_shift_limit=10, sat_shift_limit=25, val_shift_limit=20),
RGBShift(),
RandomBrightness(brightness_limit=0.4),
RandomContrast(),
RandomBrightnessContrast(),
],
p=0.5),
OneOf([ShiftScaleRotate(),
ElasticTransform(),
RandomGridShuffle()],
p=0.5)
],
p=p)
def transform(image, mask, image_name, mask_name):
x, y = image, mask
rand = random.uniform(0, 1)
if (rand > 0.5):
images_name = [f"{image_name}"]
masks_name = [f"{mask_name}"]
images_aug = [x]
masks_aug = [y]
it = iter(images_name)
it2 = iter(images_aug)
imagedict = dict(zip(it, it2))
it = iter(masks_name)
it2 = iter(masks_aug)
masksdict = dict(zip(it, it2))
return imagedict, masksdict
mask_density = np.count_nonzero(y)
## Augmenting only images with Gloms
if (mask_density > 0):
try:
h, w, c = x.shape
except Exception as e:
image = image[:-1]
x, y = image, mask
h, w, c = x.shape
aug = Blur(p=1, blur_limit=3)
augmented = aug(image=x, mask=y)
x0 = augmented['image']
y0 = augmented['mask']
# aug = CenterCrop(p=1, height=32, width=32)
# augmented = aug(image=x, mask=y)
# x1 = augmented['image']
# y1 = augmented['mask']
## Horizontal Flip
aug = HorizontalFlip(p=1)
augmented = aug(image=x, mask=y)
x2 = augmented['image']
y2 = augmented['mask']
aug = VerticalFlip(p=1)
augmented = aug(image=x, mask=y)
x3 = augmented['image']
y3 = augmented['mask']
# aug = Normalize(p=1)
# augmented = aug(image=x, mask=y)
# x4 = augmented['image']
# y4 = augmented['mask']
aug = Transpose(p=1)
augmented = aug(image=x, mask=y)
x5 = augmented['image']
y5 = augmented['mask']
aug = RandomGamma(p=1)
augmented = aug(image=x, mask=y)
x6 = augmented['image']
y6 = augmented['mask']
## Optical Distortion
aug = OpticalDistortion(p=1, distort_limit=2, shift_limit=0.5)
augmented = aug(image=x, mask=y)
x7 = augmented['image']
y7 = augmented['mask']
## Grid Distortion
aug = GridDistortion(p=1)
augmented = aug(image=x, mask=y)
x8 = augmented['image']
y8 = augmented['mask']
aug = RandomGridShuffle(p=1)
augmented = aug(image=x, mask=y)
x9 = augmented['image']
y9 = augmented['mask']
aug = HueSaturationValue(p=1)
augmented = aug(image=x, mask=y)
x10 = augmented['image']
y10 = augmented['mask']
# aug = PadIfNeeded(p=1)
# augmented = aug(image=x, mask=y)
# x11 = augmented['image']
# y11 = augmented['mask']
aug = RGBShift(p=1)
augmented = aug(image=x, mask=y)
x12 = augmented['image']
y12 = augmented['mask']
## Random Brightness
aug = RandomBrightness(p=1)
augmented = aug(image=x, mask=y)
x13 = augmented['image']
y13 = augmented['mask']
## Random Contrast
aug = RandomContrast(p=1)
augmented = aug(image=x, mask=y)
x14 = augmented['image']
y14 = augmented['mask']
#aug = MotionBlur(p=1)
#augmented = aug(image=x, mask=y)
# x15 = augmented['image']
# y15 = augmented['mask']
aug = MedianBlur(p=1, blur_limit=5)
augmented = aug(image=x, mask=y)
x16 = augmented['image']
y16 = augmented['mask']
aug = GaussianBlur(p=1, blur_limit=3)
augmented = aug(image=x, mask=y)
x17 = augmented['image']
y17 = augmented['mask']
aug = GaussNoise(p=1)
augmented = aug(image=x, mask=y)
x18 = augmented['image']
y18 = augmented['mask']
aug = GlassBlur(p=1)
augmented = aug(image=x, mask=y)
x19 = augmented['image']
y19 = augmented['mask']
aug = CLAHE(clip_limit=1.0,
tile_grid_size=(8, 8),
always_apply=False,
p=1)
augmented = aug(image=x, mask=y)
x20 = augmented['image']
y20 = augmented['mask']
aug = ChannelShuffle(p=1)
augmented = aug(image=x, mask=y)
x21 = augmented['image']
y21 = augmented['mask']
aug = ToGray(p=1)
augmented = aug(image=x, mask=y)
x22 = augmented['image']
y22 = augmented['mask']
aug = ToSepia(p=1)
augmented = aug(image=x, mask=y)
x23 = augmented['image']
y23 = augmented['mask']
aug = JpegCompression(p=1)
augmented = aug(image=x, mask=y)
x24 = augmented['image']
y24 = augmented['mask']
aug = ImageCompression(p=1)
augmented = aug(image=x, mask=y)
x25 = augmented['image']
y25 = augmented['mask']
aug = Cutout(p=1)
augmented = aug(image=x, mask=y)
x26 = augmented['image']
y26 = augmented['mask']
# aug = CoarseDropout(p=1, max_holes=8, max_height=32, max_width=32)
# augmented = aug(image=x, mask=y)
# x27 = augmented['image']
# y27 = augmented['mask']
# aug = ToFloat(p=1)
# augmented = aug(image=x, mask=y)
# x28 = augmented['image']
# y28 = augmented['mask']
aug = FromFloat(p=1)
augmented = aug(image=x, mask=y)
x29 = augmented['image']
y29 = augmented['mask']
## Random Brightness and Contrast
aug = RandomBrightnessContrast(p=1)
augmented = aug(image=x, mask=y)
x30 = augmented['image']
y30 = augmented['mask']
aug = RandomSnow(p=1)
augmented = aug(image=x, mask=y)
x31 = augmented['image']
y31 = augmented['mask']
aug = RandomRain(p=1)
augmented = aug(image=x, mask=y)
x32 = augmented['image']
y32 = augmented['mask']
aug = RandomFog(p=1)
augmented = aug(image=x, mask=y)
x33 = augmented['image']
y33 = augmented['mask']
aug = RandomSunFlare(p=1)
augmented = aug(image=x, mask=y)
x34 = augmented['image']
y34 = augmented['mask']
aug = RandomShadow(p=1)
augmented = aug(image=x, mask=y)
x35 = augmented['image']
y35 = augmented['mask']
aug = Lambda(p=1)
augmented = aug(image=x, mask=y)
x36 = augmented['image']
y36 = augmented['mask']
aug = ChannelDropout(p=1)
augmented = aug(image=x, mask=y)
x37 = augmented['image']
y37 = augmented['mask']
aug = ISONoise(p=1)
augmented = aug(image=x, mask=y)
x38 = augmented['image']
y38 = augmented['mask']
aug = Solarize(p=1)
augmented = aug(image=x, mask=y)
x39 = augmented['image']
y39 = augmented['mask']
aug = Equalize(p=1)
augmented = aug(image=x, mask=y)
x40 = augmented['image']
y40 = augmented['mask']
aug = Posterize(p=1)
augmented = aug(image=x, mask=y)
x41 = augmented['image']
y41 = augmented['mask']
aug = Downscale(p=1)
augmented = aug(image=x, mask=y)
x42 = augmented['image']
y42 = augmented['mask']
aug = MultiplicativeNoise(p=1)
augmented = aug(image=x, mask=y)
x43 = augmented['image']
y43 = augmented['mask']
aug = FancyPCA(p=1)
augmented = aug(image=x, mask=y)
x44 = augmented['image']
y44 = augmented['mask']
# aug = MaskDropout(p=1)
# augmented = aug(image=x, mask=y)
# x45 = augmented['image']
# y45 = augmented['mask']
aug = GridDropout(p=1)
augmented = aug(image=x, mask=y)
x46 = augmented['image']
y46 = augmented['mask']
aug = ColorJitter(p=1)
augmented = aug(image=x, mask=y)
x47 = augmented['image']
y47 = augmented['mask']
## ElasticTransform
aug = ElasticTransform(p=1,
alpha=120,
sigma=512 * 0.05,
alpha_affine=512 * 0.03)
augmented = aug(image=x, mask=y)
x50 = augmented['image']
y50 = augmented['mask']
aug = CropNonEmptyMaskIfExists(p=1, height=22, width=32)
augmented = aug(image=x, mask=y)
x51 = augmented['image']
y51 = augmented['mask']
aug = IAAAffine(p=1)
augmented = aug(image=x, mask=y)
x52 = augmented['image']
y52 = augmented['mask']
# aug = IAACropAndPad(p=1)
# augmented = aug(image=x, mask=y)
# x53 = augmented['image']
# y53 = augmented['mask']
aug = IAAFliplr(p=1)
augmented = aug(image=x, mask=y)
x54 = augmented['image']
y54 = augmented['mask']
aug = IAAFlipud(p=1)
augmented = aug(image=x, mask=y)
x55 = augmented['image']
y55 = augmented['mask']
aug = IAAPerspective(p=1)
augmented = aug(image=x, mask=y)
x56 = augmented['image']
y56 = augmented['mask']
aug = IAAPiecewiseAffine(p=1)
augmented = aug(image=x, mask=y)
x57 = augmented['image']
y57 = augmented['mask']
aug = LongestMaxSize(p=1)
augmented = aug(image=x, mask=y)
x58 = augmented['image']
y58 = augmented['mask']
aug = NoOp(p=1)
augmented = aug(image=x, mask=y)
x59 = augmented['image']
y59 = augmented['mask']
# aug = RandomCrop(p=1, height=22, width=22)
# augmented = aug(image=x, mask=y)
# x61 = augmented['image']
# y61 = augmented['mask']
# aug = RandomResizedCrop(p=1, height=22, width=20)
# augmented = aug(image=x, mask=y)
# x63 = augmented['image']
# y63 = augmented['mask']
aug = RandomScale(p=1)
augmented = aug(image=x, mask=y)
x64 = augmented['image']
y64 = augmented['mask']
# aug = RandomSizedCrop(p=1, height=22, width=20, min_max_height = [32,32])
# augmented = aug(image=x, mask=y)
# x66 = augmented['image']
# y66 = augmented['mask']
# aug = Resize(p=1, height=22, width=20)
# augmented = aug(image=x, mask=y)
# x67 = augmented['image']
# y67 = augmented['mask']
aug = Rotate(p=1)
augmented = aug(image=x, mask=y)
x68 = augmented['image']
y68 = augmented['mask']
aug = ShiftScaleRotate(p=1)
augmented = aug(image=x, mask=y)
x69 = augmented['image']
y69 = augmented['mask']
aug = SmallestMaxSize(p=1)
augmented = aug(image=x, mask=y)
x70 = augmented['image']
y70 = augmented['mask']
images_aug.extend([
x, x0, x2, x3, x5, x6, x7, x8, x9, x10, x12, x13, x14, x16, x17,
x18, x19, x20, x21, x22, x23, x24, x25, x26, x29, x30, x31, x32,
x33, x34, x35, x36, x37, x38, x39, x40, x41, x42, x43, x44, x46,
x47, x50, x51, x52, x54, x55, x56, x57, x58, x59, x64, x68, x69,
x70
])
masks_aug.extend([
y, y0, y2, y3, y5, y6, y7, y8, y9, y10, y12, y13, y14, y16, y17,
y18, y19, y20, y21, y22, y23, y24, y25, y26, y29, y30, y31, y32,
y33, y34, y35, y36, y37, y38, y39, y40, y41, y42, y43, y44, y46,
y47, y50, y51, y52, y54, y55, y56, y57, y58, y59, y64, y68, y69,
y70
])
idx = -1
images_name = []
masks_name = []
for i, m in zip(images_aug, masks_aug):
if idx == -1:
tmp_image_name = f"{image_name}"
tmp_mask_name = f"{mask_name}"
else:
tmp_image_name = f"{image_name}_{smalllist[idx]}"
tmp_mask_name = f"{mask_name}_{smalllist[idx]}"
images_name.extend(tmp_image_name)
masks_name.extend(tmp_mask_name)
idx += 1
it = iter(images_name)
it2 = iter(images_aug)
imagedict = dict(zip(it, it2))
it = iter(masks_name)
it2 = iter(masks_aug)
masksdict = dict(zip(it, it2))
return imagedict, masksdict
transform = RandomSizedCrop(always_apply=True, height=500, width=500,
min_max_height=[200, 200])
transformed_image = transform(image=image)['image']
## Distortion
elif augmentation == 'grid_distortion':
transform = GridDistortion(always_apply=True, distort_limit=0.5)
transformed_image = transform(image=image)['image']
elif augmentation == 'optical_distortion':
transform = OpticalDistortion(always_apply=True, distort_limit=0.5)
transformed_image = transform(image=image)['image']
elif augmentation == 'random_grid_shuffle':
transform = RandomGridShuffle(always_apply=True, grid=(5, 5))
transformed_image = transform(image=image)['image']
elif augmentation == 'elastic_transformation':
transform = iaa.ElasticTransformation(alpha=(0, 10.0), sigma=0.25)
transformed_image = transform(image=image)
elif augmentation == 'elastic_transform':
transform = iaa.imgcorruptlike.ElasticTransform(severity=5)
transformed_image = transform(image=image)
elif augmentation == 'with_polar_warping':
transform = iaa.WithPolarWarping(iaa.CropAndPad(percent=(-0.1, 0.1)))
transformed_image = transform(image=image)
elif augmentation == 'jigsaw':
def train_transform(self):
height, width = self.img_size
transforms_list = [Resize(height, width), Flip()]
# random_grid_shuffle
if self.random_grid_shuffle['enable']:
grid = self.random_grid_shuffle['grid']
grid = (grid, grid)
transforms_list.append(RandomGridShuffle((grid)))
# channel_shuffle
if self.channel_shuffle['enable']:
transforms_list.append(ChannelShuffle(p=1))
# channel_dropout
if self.channel_dropout['enable']:
drop_range = self.channel_dropout.drop_range
fill_value = self.channel_dropout.fill_value
transforms_list.append(ChannelDropout(drop_range, fill_value, p=1))
# noise
if self.noise['enable']:
transforms_list.append(
OneOf([
IAAAdditiveGaussianNoise(),
GaussNoise(),
], p=1))
# blur
if self.blur['enable']:
transforms_list.append(
OneOf([
MotionBlur(),
Blur(blur_limit=3, ),
], p=1))
# rotate
if self.rotate['enable']:
params = {
key: value
for key, value in self.rotate.items() if key != 'enable'
}
transforms_list.append(ShiftScaleRotate(**params))
# distortion
if self.distortion['enable']:
transforms_list.append(
OneOf([
OpticalDistortion(p=0.3),
GridDistortion(p=.3),
], p=1))
# bright
if self.bright['enable']:
transforms_list.append(
OneOf([
CLAHE(clip_limit=self.bright['clip_limit']),
RandomBrightnessContrast(p=0.8),
],
p=1))
# hue color
if self.hue['enable']:
transforms_list.append(HueSaturationValue(p=0.3))
# cutout
if self.cutout['enable']:
num_holes = self.cutout['num_holes']
size = self.cutout['size']
fill_value = self.cutout['fill_value']
transforms_list.append(Cutout(num_holes, size, size, fill_value,
1))
transforms_list.append(self.normalize)
transforms_list.append(ToTensor())
return Compose(transforms_list)
def train_transform(self):
# albumentations transforms cfg
at_cfg = self.cfg.abtfs
height, width = self.img_size
transforms_list = [Resize(height, width), Flip()]
# random_grid_shuffle
if at_cfg.random_grid_shuffle.enable:
grid = at_cfg.random_grid_shuffle.grid
grid = (grid, grid)
transforms_list.append(RandomGridShuffle((grid)))
# channel_shuffle
if at_cfg.channel_shuffle.enable:
transforms_list.append(ChannelShuffle(p=1))
# channel_dropout
if at_cfg.channel_dropout.enable:
drop_range = at_cfg.channel_dropout.drop_range
fill_value = at_cfg.channel_dropout.fill_value
transforms_list.append(ChannelDropout(drop_range, fill_value, p=1))
# noise
if at_cfg.noise.enable:
transforms_list.append(
OneOf([
IAAAdditiveGaussianNoise(),
GaussNoise(),
], p=1))
# blur
if at_cfg.blur.enable:
transforms_list.append(
OneOf([
MotionBlur(),
Blur(blur_limit=3, ),
], p=1))
# rotate
if at_cfg.rotate.enable:
transforms_list.append(
ShiftScaleRotate(shift_limit=0.0625,
scale_limit=0.2,
rotate_limit=45,
p=1))
# distortion
if at_cfg.distortion.enable:
transforms_list.append(
OneOf([
OpticalDistortion(p=0.3),
GridDistortion(p=.3),
], p=1))
# bright
if at_cfg.bright.enable:
transforms_list.append(
OneOf([
CLAHE(clip_limit=2),
RandomBrightnessContrast(p=0.8),
],
p=1))
# hue color
if at_cfg.hue.enable:
transforms_list.append(HueSaturationValue(p=0.3))
# cutout
if at_cfg.cutout.enable:
num_holes = at_cfg.cutout.num_holes
size = at_cfg.cutout.size
fill_value = at_cfg.cutout.fill_value
transforms_list.append(Cutout(num_holes, size, size, fill_value,
1))
transforms_list.append(self.normalize)
transforms_list.append(ToTensor())
return Compose(transforms_list)