| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264 |
- # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # This code is based on https://github.com/DeepVoltaire/AutoAugment/blob/master/autoaugment.py
- from PIL import Image, ImageEnhance, ImageOps
- import numpy as np
- import random
- class ImageNetPolicy(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, fillcolor=(128, 128, 128)):
- self.policies = [
- SubPolicy(0.4, "posterize", 8, 0.6, "rotate", 9, fillcolor),
- SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
- SubPolicy(0.8, "equalize", 8, 0.6, "equalize", 3, fillcolor),
- SubPolicy(0.6, "posterize", 7, 0.6, "posterize", 6, fillcolor),
- SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
- SubPolicy(0.4, "equalize", 4, 0.8, "rotate", 8, fillcolor),
- SubPolicy(0.6, "solarize", 3, 0.6, "equalize", 7, fillcolor),
- SubPolicy(0.8, "posterize", 5, 1.0, "equalize", 2, fillcolor),
- SubPolicy(0.2, "rotate", 3, 0.6, "solarize", 8, fillcolor),
- SubPolicy(0.6, "equalize", 8, 0.4, "posterize", 6, fillcolor),
- SubPolicy(0.8, "rotate", 8, 0.4, "color", 0, fillcolor),
- SubPolicy(0.4, "rotate", 9, 0.6, "equalize", 2, fillcolor),
- SubPolicy(0.0, "equalize", 7, 0.8, "equalize", 8, fillcolor),
- SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
- SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor),
- SubPolicy(0.8, "rotate", 8, 1.0, "color", 2, fillcolor),
- SubPolicy(0.8, "color", 8, 0.8, "solarize", 7, fillcolor),
- SubPolicy(0.4, "sharpness", 7, 0.6, "invert", 8, fillcolor),
- SubPolicy(0.6, "shearX", 5, 1.0, "equalize", 9, fillcolor),
- SubPolicy(0.4, "color", 0, 0.6, "equalize", 3, fillcolor),
- SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
- SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
- SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
- SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor),
- SubPolicy(0.8, "equalize", 8, 0.6, "equalize", 3, fillcolor)
- ]
- def __call__(self, img, policy_idx=None):
- if policy_idx is None or not isinstance(policy_idx, int):
- policy_idx = random.randint(0, len(self.policies) - 1)
- else:
- policy_idx = policy_idx % len(self.policies)
- return self.policies[policy_idx](img)
- def __repr__(self):
- return "AutoAugment ImageNet Policy"
- class CIFAR10Policy(object):
- """ Randomly choose one of the best 25 Sub-policies on CIFAR10.
- Example:
- >>> policy = CIFAR10Policy()
- >>> transformed = policy(image)
- Example as a PyTorch Transform:
- >>> transform=transforms.Compose([
- >>> transforms.Resize(256),
- >>> CIFAR10Policy(),
- >>> transforms.ToTensor()])
- """
- def __init__(self, fillcolor=(128, 128, 128)):
- self.policies = [
- SubPolicy(0.1, "invert", 7, 0.2, "contrast", 6, fillcolor),
- SubPolicy(0.7, "rotate", 2, 0.3, "translateX", 9, fillcolor),
- SubPolicy(0.8, "sharpness", 1, 0.9, "sharpness", 3, fillcolor),
- SubPolicy(0.5, "shearY", 8, 0.7, "translateY", 9, fillcolor),
- SubPolicy(0.5, "autocontrast", 8, 0.9, "equalize", 2, fillcolor),
- SubPolicy(0.2, "shearY", 7, 0.3, "posterize", 7, fillcolor),
- SubPolicy(0.4, "color", 3, 0.6, "brightness", 7, fillcolor),
- SubPolicy(0.3, "sharpness", 9, 0.7, "brightness", 9, fillcolor),
- SubPolicy(0.6, "equalize", 5, 0.5, "equalize", 1, fillcolor),
- SubPolicy(0.6, "contrast", 7, 0.6, "sharpness", 5, fillcolor),
- SubPolicy(0.7, "color", 7, 0.5, "translateX", 8, fillcolor),
- SubPolicy(0.3, "equalize", 7, 0.4, "autocontrast", 8, fillcolor),
- SubPolicy(0.4, "translateY", 3, 0.2, "sharpness", 6, fillcolor),
- SubPolicy(0.9, "brightness", 6, 0.2, "color", 8, fillcolor),
- SubPolicy(0.5, "solarize", 2, 0.0, "invert", 3, fillcolor),
- SubPolicy(0.2, "equalize", 0, 0.6, "autocontrast", 0, fillcolor),
- SubPolicy(0.2, "equalize", 8, 0.8, "equalize", 4, fillcolor),
- SubPolicy(0.9, "color", 9, 0.6, "equalize", 6, fillcolor),
- SubPolicy(0.8, "autocontrast", 4, 0.2, "solarize", 8, fillcolor),
- SubPolicy(0.1, "brightness", 3, 0.7, "color", 0, fillcolor),
- SubPolicy(0.4, "solarize", 5, 0.9, "autocontrast", 3, fillcolor),
- SubPolicy(0.9, "translateY", 9, 0.7, "translateY", 9, fillcolor),
- SubPolicy(0.9, "autocontrast", 2, 0.8, "solarize", 3, fillcolor),
- SubPolicy(0.8, "equalize", 8, 0.1, "invert", 3, fillcolor),
- SubPolicy(0.7, "translateY", 9, 0.9, "autocontrast", 1, fillcolor)
- ]
- def __call__(self, img, policy_idx=None):
- if policy_idx is None or not isinstance(policy_idx, int):
- policy_idx = random.randint(0, len(self.policies) - 1)
- else:
- policy_idx = policy_idx % len(self.policies)
- return self.policies[policy_idx](img)
- def __repr__(self):
- return "AutoAugment CIFAR10 Policy"
- class SVHNPolicy(object):
- """ Randomly choose one of the best 25 Sub-policies on SVHN.
- Example:
- >>> policy = SVHNPolicy()
- >>> transformed = policy(image)
- Example as a PyTorch Transform:
- >>> transform=transforms.Compose([
- >>> transforms.Resize(256),
- >>> SVHNPolicy(),
- >>> transforms.ToTensor()])
- """
- def __init__(self, fillcolor=(128, 128, 128)):
- self.policies = [
- SubPolicy(0.9, "shearX", 4, 0.2, "invert", 3, fillcolor),
- SubPolicy(0.9, "shearY", 8, 0.7, "invert", 5, fillcolor),
- SubPolicy(0.6, "equalize", 5, 0.6, "solarize", 6, fillcolor),
- SubPolicy(0.9, "invert", 3, 0.6, "equalize", 3, fillcolor),
- SubPolicy(0.6, "equalize", 1, 0.9, "rotate", 3, fillcolor),
- SubPolicy(0.9, "shearX", 4, 0.8, "autocontrast", 3, fillcolor),
- SubPolicy(0.9, "shearY", 8, 0.4, "invert", 5, fillcolor),
- SubPolicy(0.9, "shearY", 5, 0.2, "solarize", 6, fillcolor),
- SubPolicy(0.9, "invert", 6, 0.8, "autocontrast", 1, fillcolor),
- SubPolicy(0.6, "equalize", 3, 0.9, "rotate", 3, fillcolor),
- SubPolicy(0.9, "shearX", 4, 0.3, "solarize", 3, fillcolor),
- SubPolicy(0.8, "shearY", 8, 0.7, "invert", 4, fillcolor),
- SubPolicy(0.9, "equalize", 5, 0.6, "translateY", 6, fillcolor),
- SubPolicy(0.9, "invert", 4, 0.6, "equalize", 7, fillcolor),
- SubPolicy(0.3, "contrast", 3, 0.8, "rotate", 4, fillcolor),
- SubPolicy(0.8, "invert", 5, 0.0, "translateY", 2, fillcolor),
- SubPolicy(0.7, "shearY", 6, 0.4, "solarize", 8, fillcolor),
- SubPolicy(0.6, "invert", 4, 0.8, "rotate", 4, fillcolor),
- SubPolicy(
- 0.3, "shearY", 7, 0.9, "translateX", 3, fillcolor), SubPolicy(
- 0.1, "shearX", 6, 0.6, "invert", 5, fillcolor), SubPolicy(
- 0.7, "solarize", 2, 0.6, "translateY", 7,
- fillcolor), SubPolicy(0.8, "shearY", 4, 0.8, "invert",
- 8, fillcolor), SubPolicy(
- 0.7, "shearX", 9, 0.8,
- "translateY", 3,
- fillcolor), SubPolicy(
- 0.8, "shearY", 5, 0.7,
- "autocontrast", 3,
- fillcolor),
- SubPolicy(0.7, "shearX", 2, 0.1, "invert", 5, fillcolor)
- ]
- def __call__(self, img, policy_idx=None):
- if policy_idx is None or not isinstance(policy_idx, int):
- policy_idx = random.randint(0, len(self.policies) - 1)
- else:
- policy_idx = policy_idx % len(self.policies)
- return self.policies[policy_idx](img)
- def __repr__(self):
- return "AutoAugment SVHN 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.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
|