144 lines
5.3 KiB
Python
144 lines
5.3 KiB
Python
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from PIL import Image, ImageEnhance, ImageOps
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import numpy as np
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import random
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import six
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class RawRandAugment(object):
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def __init__(self,
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num_layers=2,
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magnitude=5,
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fillcolor=(128, 128, 128),
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**kwargs):
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self.num_layers = num_layers
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self.magnitude = magnitude
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self.max_level = 10
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abso_level = self.magnitude / self.max_level
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self.level_map = {
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"shearX": 0.3 * abso_level,
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"shearY": 0.3 * abso_level,
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"translateX": 150.0 / 331 * abso_level,
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"translateY": 150.0 / 331 * abso_level,
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"rotate": 30 * abso_level,
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"color": 0.9 * abso_level,
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"posterize": int(4.0 * abso_level),
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"solarize": 256.0 * abso_level,
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"contrast": 0.9 * abso_level,
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"sharpness": 0.9 * abso_level,
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"brightness": 0.9 * abso_level,
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"autocontrast": 0,
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"equalize": 0,
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"invert": 0
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}
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# from https://stackoverflow.com/questions/5252170/
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# specify-image-filling-color-when-rotating-in-python-with-pil-and-setting-expand
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def rotate_with_fill(img, magnitude):
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rot = img.convert("RGBA").rotate(magnitude)
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return Image.composite(rot,
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Image.new("RGBA", rot.size, (128, ) * 4),
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rot).convert(img.mode)
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rnd_ch_op = random.choice
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self.func = {
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"shearX": lambda img, magnitude: img.transform(
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img.size,
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Image.AFFINE,
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(1, magnitude * rnd_ch_op([-1, 1]), 0, 0, 1, 0),
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Image.BICUBIC,
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fillcolor=fillcolor),
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"shearY": lambda img, magnitude: img.transform(
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img.size,
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Image.AFFINE,
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(1, 0, 0, magnitude * rnd_ch_op([-1, 1]), 1, 0),
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Image.BICUBIC,
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fillcolor=fillcolor),
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"translateX": lambda img, magnitude: img.transform(
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img.size,
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Image.AFFINE,
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(1, 0, magnitude * img.size[0] * rnd_ch_op([-1, 1]), 0, 1, 0),
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fillcolor=fillcolor),
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"translateY": lambda img, magnitude: img.transform(
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img.size,
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Image.AFFINE,
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(1, 0, 0, 0, 1, magnitude * img.size[1] * rnd_ch_op([-1, 1])),
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fillcolor=fillcolor),
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"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
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"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(
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1 + magnitude * rnd_ch_op([-1, 1])),
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"posterize": lambda img, magnitude:
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ImageOps.posterize(img, magnitude),
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"solarize": lambda img, magnitude:
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ImageOps.solarize(img, magnitude),
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"contrast": lambda img, magnitude:
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ImageEnhance.Contrast(img).enhance(
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1 + magnitude * rnd_ch_op([-1, 1])),
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"sharpness": lambda img, magnitude:
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ImageEnhance.Sharpness(img).enhance(
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1 + magnitude * rnd_ch_op([-1, 1])),
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"brightness": lambda img, magnitude:
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ImageEnhance.Brightness(img).enhance(
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1 + magnitude * rnd_ch_op([-1, 1])),
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"autocontrast": lambda img, magnitude:
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ImageOps.autocontrast(img),
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"equalize": lambda img, magnitude: ImageOps.equalize(img),
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"invert": lambda img, magnitude: ImageOps.invert(img)
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}
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def __call__(self, img):
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avaiable_op_names = list(self.level_map.keys())
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for layer_num in range(self.num_layers):
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op_name = np.random.choice(avaiable_op_names)
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img = self.func[op_name](img, self.level_map[op_name])
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return img
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class RandAugment(RawRandAugment):
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""" RandAugment wrapper to auto fit different img types """
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def __init__(self, prob=0.5, *args, **kwargs):
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self.prob = prob
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if six.PY2:
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super(RandAugment, self).__init__(*args, **kwargs)
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else:
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super().__init__(*args, **kwargs)
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def __call__(self, data):
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if np.random.rand() > self.prob:
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return data
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img = data['image']
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if not isinstance(img, Image.Image):
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img = np.ascontiguousarray(img)
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img = Image.fromarray(img)
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if six.PY2:
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img = super(RandAugment, self).__call__(img)
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else:
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img = super().__call__(img)
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if isinstance(img, Image.Image):
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img = np.asarray(img)
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data['image'] = img
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return data
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