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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# 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.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from PIL import Image, ImageEnhance, ImageOps
import numpy as np
import random
import six
class RawRandAugment(object):
def __init__(self,
num_layers=2,
magnitude=5,
fillcolor=(128, 128, 128),
**kwargs):
self.num_layers = num_layers
self.magnitude = magnitude
self.max_level = 10
abso_level = self.magnitude / self.max_level
self.level_map = {
"shearX": 0.3 * abso_level,
"shearY": 0.3 * abso_level,
"translateX": 150.0 / 331 * abso_level,
"translateY": 150.0 / 331 * abso_level,
"rotate": 30 * abso_level,
"color": 0.9 * abso_level,
"posterize": int(4.0 * abso_level),
"solarize": 256.0 * abso_level,
"contrast": 0.9 * abso_level,
"sharpness": 0.9 * abso_level,
"brightness": 0.9 * abso_level,
"autocontrast": 0,
"equalize": 0,
"invert": 0
}
# 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)
rnd_ch_op = random.choice
self.func = {
"shearX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, magnitude * rnd_ch_op([-1, 1]), 0, 0, 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"shearY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, magnitude * rnd_ch_op([-1, 1]), 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"translateX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, magnitude * img.size[0] * rnd_ch_op([-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] * rnd_ch_op([-1, 1])),
fillcolor=fillcolor),
"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(
1 + magnitude * rnd_ch_op([-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 * rnd_ch_op([-1, 1])),
"sharpness": lambda img, magnitude:
ImageEnhance.Sharpness(img).enhance(
1 + magnitude * rnd_ch_op([-1, 1])),
"brightness": lambda img, magnitude:
ImageEnhance.Brightness(img).enhance(
1 + magnitude * rnd_ch_op([-1, 1])),
"autocontrast": lambda img, magnitude:
ImageOps.autocontrast(img),
"equalize": lambda img, magnitude: ImageOps.equalize(img),
"invert": lambda img, magnitude: ImageOps.invert(img)
}
def __call__(self, img):
avaiable_op_names = list(self.level_map.keys())
for layer_num in range(self.num_layers):
op_name = np.random.choice(avaiable_op_names)
img = self.func[op_name](img, self.level_map[op_name])
return img
class RandAugment(RawRandAugment):
""" RandAugment wrapper to auto fit different img types """
def __init__(self, prob=0.5, *args, **kwargs):
self.prob = prob
if six.PY2:
super(RandAugment, self).__init__(*args, **kwargs)
else:
super().__init__(*args, **kwargs)
def __call__(self, data):
if np.random.rand() > self.prob:
return data
img = data['image']
if not isinstance(img, Image.Image):
img = np.ascontiguousarray(img)
img = Image.fromarray(img)
if six.PY2:
img = super(RandAugment, self).__call__(img)
else:
img = super().__call__(img)
if isinstance(img, Image.Image):
img = np.asarray(img)
data['image'] = img
return data
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