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augmentations.py
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augmentations.py
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import random
import PIL, PIL.ImageOps, PIL.ImageEnhance, PIL.ImageDraw
import numpy as np
random_mirror = True
def ShearX(img, v): # [-0.3, 0.3]
assert -0.3 <= v <= 0.3
if random_mirror and random.random() > 0.5:
v = -v
return img.transform(img.size, PIL.Image.AFFINE, (1, v, 0, 0, 1, 0))
def ShearY(img, v): # [-0.3, 0.3]
assert -0.3 <= v <= 0.3
if random_mirror and random.random() > 0.5:
v = -v
return img.transform(img.size, PIL.Image.AFFINE, (1, 0, 0, v, 1, 0))
def TranslateX(img, v): # [-150, 150] => percentage: [-0.45, 0.45]
assert -0.45 <= v <= 0.45
if random_mirror and random.random() > 0.5:
v = -v
v = v * img.size[0]
return img.transform(img.size, PIL.Image.AFFINE, (1, 0, v, 0, 1, 0))
def TranslateY(img, v): # [-150, 150] => percentage: [-0.45, 0.45]
assert -0.45 <= v <= 0.45
if random_mirror and random.random() > 0.5:
v = -v
v = v * img.size[1]
return img.transform(img.size, PIL.Image.AFFINE, (1, 0, 0, 0, 1, v))
def TranslateXAbs(img, v): # [-150, 150] => percentage: [-0.45, 0.45]
assert 0 <= v <= 10
if random.random() > 0.5:
v = -v
return img.transform(img.size, PIL.Image.AFFINE, (1, 0, v, 0, 1, 0))
def TranslateYAbs(img, v): # [-150, 150] => percentage: [-0.45, 0.45]
assert 0 <= v <= 10
if random.random() > 0.5:
v = -v
return img.transform(img.size, PIL.Image.AFFINE, (1, 0, 0, 0, 1, v))
def Rotate(img, v): # [-30, 30]
assert -30 <= v <= 30
if random_mirror and random.random() > 0.5:
v = -v
return img.rotate(v)
def AutoContrast(img, _):
return PIL.ImageOps.autocontrast(img)
def Invert(img, _):
return PIL.ImageOps.invert(img)
def Equalize(img, _):
return PIL.ImageOps.equalize(img)
def Flip(img, _):
return PIL.ImageOps.mirror(img)
def Solarize(img, v): # [0, 256]
assert 0 <= v <= 256
return PIL.ImageOps.solarize(img, v)
def Posterize(img, v): # [4, 8]
assert 4 <= v <= 8
v = int(v)
return PIL.ImageOps.posterize(img, v)
def Posterize2(img, v): # [0, 4]
assert 0 <= v <= 4
v = int(v)
return PIL.ImageOps.posterize(img, v)
def Contrast(img, v): # [0.1,1.9]
assert 0.1 <= v <= 1.9
return PIL.ImageEnhance.Contrast(img).enhance(v)
def Color(img, v): # [0.1,1.9]
assert 0.1 <= v <= 1.9
return PIL.ImageEnhance.Color(img).enhance(v)
def Brightness(img, v): # [0.1,1.9]
assert 0.1 <= v <= 1.9
return PIL.ImageEnhance.Brightness(img).enhance(v)
def Sharpness(img, v): # [0.1,1.9]
assert 0.1 <= v <= 1.9
return PIL.ImageEnhance.Sharpness(img).enhance(v)
def Cutout(img, v): # [0, 60] => percentage: [0, 0.2]
assert 0.0 <= v <= 0.2
if v <= 0.:
return img
v = v * img.size[0]
return CutoutAbs(img, v)
def CutoutAbs(img, v): # [0, 60] => percentage: [0, 0.2]
# assert 0 <= v <= 20
if v < 0:
return img
w, h = img.size
x0 = np.random.uniform(w)
y0 = np.random.uniform(h)
x0 = int(max(0, x0 - v / 2.))
y0 = int(max(0, y0 - v / 2.))
x1 = min(w, x0 + v)
y1 = min(h, y0 + v)
xy = (x0, y0, x1, y1)
color = (125, 123, 114)
# color = (0, 0, 0)
img = img.copy()
PIL.ImageDraw.Draw(img).rectangle(xy, color)
return img
def SamplePairing(imgs): # [0, 0.4]
def f(img1, v):
i = np.random.choice(len(imgs))
img2 = PIL.Image.fromarray(imgs[i])
return PIL.Image.blend(img1, img2, v)
return f
def augment_list(for_autoaug=True): # 16 operations and their ranges
l = [
(ShearX, -0.3, 0.3), # 0
(ShearY, -0.3, 0.3), # 1
(TranslateX, -0.45, 0.45), # 2
(TranslateY, -0.45, 0.45), # 3
(Rotate, -30, 30), # 4
(AutoContrast, 0, 1), # 5
(Invert, 0, 1), # 6
(Equalize, 0, 1), # 7
(Solarize, 0, 256), # 8
(Posterize, 4, 8), # 9
(Contrast, 0.1, 1.9), # 10
(Color, 0.1, 1.9), # 11
(Brightness, 0.1, 1.9), # 12
(Sharpness, 0.1, 1.9), # 13
(Cutout, 0, 0.2), # 14
# (SamplePairing(imgs), 0, 0.4), # 15
]
if for_autoaug:
l += [
(CutoutAbs, 0, 20), # compatible with auto-augment
(Posterize2, 0, 4), # 9
(TranslateXAbs, 0, 10), # 9
(TranslateYAbs, 0, 10), # 9
]
return l
augment_dict = {fn.__name__: (fn, v1, v2) for fn, v1, v2 in augment_list()}
def get_augment(name):
return augment_dict[name]
def apply_augment(img, name, level):
augment_fn, low, high = get_augment(name)
return augment_fn(img.copy(), level * (high - low) + low)