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augement_policy.py
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augement_policy.py
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from PIL import Image, ImageEnhance, ImageOps
import random
class Policy(object):
""" Randomly choose one of the best 24 Sub-policies on ImageNet.
Example:
policy = ImageNetPolicy()
transformed = policy(image)
Example as a PyTorch Transform:
transform = transforms.Compose([
transforms.Resize(256),
ImageNetPolicy(),
transforms.ToTensor()])
"""
def __init__(self, args, searched_policies, fillcolor=(128, 128, 128)):
probs = np.linspace(0., 1.0, 11)
self.policies = []
for i in range(args.subpolicy_num):
prob_1, prob_2 = probs[searched_policies[i][0]['prob']], probs[searched_policies[i][1]['prob']]
op_1, op_2 = searched_policies[i][0]['op'], searched_policies[i][1]['op']
magnitude_1, magnitude_2 = searched_policies[i][0]['magnitude'], searched_policies[i][1]['magnitude']
self.policies.append(SubPolicy(prob_1, op_1, magnitude_1, prob_2, op_2, magnitude_2, fillcolor))
def __call__(self, img):
policy_idx = random.randint(0, len(self.policies) - 1)
return self.policies[policy_idx](img)
def __repr__(self):
return "AutoAugment ImageNet Policy"
class SubPolicy(object):
def __init__(self,
p1,
operation1,
magnitude_idx1,
p2,
operation2,
magnitude_idx2,
fillcolor=(128, 128, 128)):
ranges = {
"shearX": np.linspace(0, 0.3, 10),
"shearY": np.linspace(0, 0.3, 10),
"translateX": np.linspace(0, 150 / 331, 10),
"translateY": np.linspace(0, 150 / 331, 10),
"rotate": np.linspace(0, 30, 10),
"color": np.linspace(0.0, 0.9, 10),
"posterize": np.round(np.linspace(8, 4, 10), 0).astype(np.int),
"solarize": np.linspace(256, 0, 10),
"contrast": np.linspace(0.0, 0.9, 10),
"sharpness": np.linspace(0.0, 0.9, 10),
"brightness": np.linspace(0.0, 0.9, 10),
"autocontrast": [0] * 10,
"equalize": [0] * 10,
"invert": [0] * 10}
# from https://stackoverflow.com/questions/5252170/specify-image
# -filling-color-when-rotating-in-python-with-pil-and-setting-expand
def rotate_with_fill(img, magnitude):
rot = img.convert("RGBA").rotate(magnitude)
return Image.composite(
rot, Image.new("RGBA", rot.size, (128,) * 4), rot)\
.convert(img.mode)
func = {
"shearX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, magnitude * random.choice([-1, 1]), 0, 0, 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"shearY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, magnitude * random.choice([-1, 1]), 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"translateX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, magnitude * img.size[0] * \
random.choice([-1, 1]), 0, 1, 0),
fillcolor=fillcolor),
"translateY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, 0, 1, magnitude * \
img.size[1] * random.choice([-1, 1])),
fillcolor=fillcolor),
"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
# "rotate": lambda img, magnitude: \
# img.rotate(magnitude * random.choice([-1, 1])),
"color": lambda img, magnitude: \
ImageEnhance.Color(img).enhance(
1 + magnitude * random.choice([-1, 1])),
"posterize": lambda img, magnitude: \
ImageOps.posterize(img, magnitude),
"solarize": lambda img, magnitude: \
ImageOps.solarize(img, magnitude),
"contrast": lambda img, magnitude: \
ImageEnhance.Contrast(img).enhance(
1 + magnitude * random.choice([-1, 1])),
"sharpness": lambda img, magnitude: \
ImageEnhance.Sharpness(img).enhance(
1 + magnitude * random.choice([-1, 1])),
"brightness": lambda img, magnitude: \
ImageEnhance.Brightness(img).enhance(
1 + magnitude * random.choice([-1, 1])),
"autocontrast": lambda img, magnitude: ImageOps.autocontrast(img),
"equalize": lambda img, magnitude: ImageOps.equalize(img),
"invert": lambda img, magnitude: ImageOps.invert(img)
}
# self.name = "{}_{:.2f}_and_{}_{:.2f}".format(
# operation1, ranges[operation1][magnitude_idx1],
# operation2, ranges[operation2][magnitude_idx2])
self.p1 = p1
self.operation1 = func[operation1]
self.magnitude1 = ranges[operation1][magnitude_idx1]
self.p2 = p2
self.operation2 = func[operation2]
self.magnitude2 = ranges[operation2][magnitude_idx2]
def __call__(self, img):
if random.random() < self.p1:
img = self.operation1(img, self.magnitude1)
if random.random() < self.p2:
img = self.operation2(img, self.magnitude2)
return img