478 lines
19 KiB
Python
478 lines
19 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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# This code is based on https://github.com/heartInsert/randaugment
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# reference: https://arxiv.org/abs/1909.13719
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import random
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from .operators import RawColorJitter
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from .timm_autoaugment import _pil_interp
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from paddle.vision.transforms import transforms as T
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import numpy as np
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from PIL import Image, ImageEnhance, ImageOps
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def solarize_add(img, add, thresh=128, **__):
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lut = []
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for i in range(256):
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if i < thresh:
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lut.append(min(255, i + add))
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else:
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lut.append(i)
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if img.mode in ("L", "RGB"):
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if img.mode == "RGB" and len(lut) == 256:
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lut = lut + lut + lut
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return img.point(lut)
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else:
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return img
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def cutout(image, pad_size, replace=0):
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image_np = np.array(image)
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image_height, image_width, _ = image_np.shape
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# Sample the center location in the image where the zero mask will be applied.
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cutout_center_height = np.random.randint(0, image_height + 1)
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cutout_center_width = np.random.randint(0, image_width + 1)
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lower_pad = np.maximum(0, cutout_center_height - pad_size)
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upper_pad = np.maximum(0, image_height - cutout_center_height - pad_size)
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left_pad = np.maximum(0, cutout_center_width - pad_size)
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right_pad = np.maximum(0, image_width - cutout_center_width - pad_size)
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cutout_shape = [
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image_height - (lower_pad + upper_pad),
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image_width - (left_pad + right_pad)
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]
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padding_dims = [[lower_pad, upper_pad], [left_pad, right_pad]]
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mask = np.pad(np.zeros(
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cutout_shape, dtype=image_np.dtype),
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padding_dims,
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constant_values=1)
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mask = np.expand_dims(mask, -1)
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mask = np.tile(mask, [1, 1, 3])
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image_np = np.where(
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np.equal(mask, 0),
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np.full_like(
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image_np, fill_value=replace, dtype=image_np.dtype),
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image_np)
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return Image.fromarray(image_np)
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class RandAugment(object):
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def __init__(self, num_layers=2, magnitude=5, fillcolor=(128, 128, 128)):
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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, _:
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ImageOps.autocontrast(img),
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"equalize": lambda img, _: ImageOps.equalize(img),
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"invert": lambda img, _: 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 RandomApply(object):
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def __init__(self, p, transforms):
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self.p = p
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ts = []
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for t in transforms:
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for key in t.keys():
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ts.append(eval(key)(**t[key]))
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self.trans = T.Compose(ts)
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def __call__(self, img):
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if self.p < np.random.rand(1):
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return img
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timg = self.trans(img)
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return timg
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## RandAugment_EfficientNetV2 code below ##
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class RandAugmentV2(RandAugment):
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"""Customed RandAugment for EfficientNetV2"""
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def __init__(self,
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num_layers=2,
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magnitude=5,
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progress_magnitude=None,
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fillcolor=(128, 128, 128)):
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super().__init__(num_layers, magnitude, fillcolor)
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self.progress_magnitude = progress_magnitude
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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": 100.0 * abso_level,
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"translateY": 100.0 * abso_level,
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"rotate": 30 * abso_level,
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"color": 1.8 * abso_level + 0.1,
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"posterize": int(4.0 * abso_level),
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"solarize": int(256.0 * abso_level),
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"solarize_add": int(110.0 * abso_level),
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"contrast": 1.8 * abso_level + 0.1,
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"sharpness": 1.8 * abso_level + 0.1,
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"brightness": 1.8 * abso_level + 0.1,
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"autocontrast": 0,
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"equalize": 0,
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"invert": 0,
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"cutout": int(40 * abso_level)
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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.NEAREST,
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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.NEAREST,
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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 * rnd_ch_op([-1, 1]), 0, 1, 0),
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Image.NEAREST,
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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 * rnd_ch_op([-1, 1])),
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Image.NEAREST,
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fillcolor=fillcolor),
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"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude * rnd_ch_op([-1, 1])),
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"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(magnitude),
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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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"solarize_add": lambda img, magnitude:
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solarize_add(img, magnitude),
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"contrast": lambda img, magnitude:
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ImageEnhance.Contrast(img).enhance(magnitude),
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"sharpness": lambda img, magnitude:
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ImageEnhance.Sharpness(img).enhance(magnitude),
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"brightness": lambda img, magnitude:
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ImageEnhance.Brightness(img).enhance(magnitude),
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"autocontrast": lambda img, _:
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ImageOps.autocontrast(img),
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"equalize": lambda img, _: ImageOps.equalize(img),
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"invert": lambda img, _: ImageOps.invert(img),
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"cutout": lambda img, magnitude: cutout(img, magnitude, replace=fillcolor[0])
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}
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class RandAugmentV3(RandAugment):
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"""Customed RandAugment for MobileViTV2"""
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def __init__(self,
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num_layers=2,
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magnitude=3,
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fillcolor=(0, 0, 0),
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interpolation="bicubic"):
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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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interpolation = _pil_interp(interpolation)
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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 / 331.0 * abso_level,
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"translateY": 150.0 / 331.0 * abso_level,
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"rotate": 30 * abso_level,
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"color": 0.9 * abso_level,
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"posterize": 8 - int(4.0 * abso_level),
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"solarize": 255.0 * (1 - 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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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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interpolation,
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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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interpolation,
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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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interpolation,
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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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interpolation,
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fillcolor=fillcolor),
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"rotate": lambda img, magnitude: img.rotate(
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magnitude * rnd_ch_op([-1, 1]),
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interpolation,
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fillcolor=fillcolor),
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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, _:
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ImageOps.autocontrast(img),
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"equalize": lambda img, _: ImageOps.equalize(img),
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"invert": lambda img, _: ImageOps.invert(img)
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}
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class SubPolicyV2(object):
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"""Custom SubPolicy for ML-Decoder"""
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def __init__(self,
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p1,
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operation1,
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magnitude_idx1,
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p2,
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operation2,
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magnitude_idx2,
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fillcolor=(128, 128, 128)):
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ranges = {
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"shearX": np.linspace(0, 0.3, 10),
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"shearY": np.linspace(0, 0.3, 10),
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"translateX": np.linspace(0, 150 / 331, 10),
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"translateY": np.linspace(0, 150 / 331, 10),
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"rotate": np.linspace(0, 30, 10),
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"color": np.linspace(0.0, 0.9, 10),
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"posterize": np.round(np.linspace(8, 4, 10), 0).astype(np.int_),
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"solarize": np.linspace(256, 0, 10),
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"contrast": np.linspace(0.0, 0.9, 10),
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"sharpness": np.linspace(0.0, 0.9, 10),
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"brightness": np.linspace(0.0, 0.9, 10),
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"autocontrast": [0] * 10,
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"equalize": [0] * 10,
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"invert": [0] * 10,
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"cutout": np.round(np.linspace(0, 20, 10), 0).astype(np.int_),
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}
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# from https://stackoverflow.com/questions/5252170/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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func = {
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"shearX": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, magnitude * random.choice([-1, 1]), 0, 0, 1, 0),
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Image.BICUBIC, fillcolor=fillcolor),
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"shearY": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, 0, 0, magnitude * random.choice([-1, 1]), 1, 0),
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Image.BICUBIC, fillcolor=fillcolor),
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"translateX": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, 0, magnitude * img.size[0] * random.choice([-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, Image.AFFINE, (1, 0, 0, 0, 1, magnitude * img.size[1] * random.choice([-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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# "rotate": lambda img, magnitude: img.rotate(magnitude * random.choice([-1, 1])),
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"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(1 + magnitude * random.choice([-1, 1])),
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"posterize": lambda img, magnitude: ImageOps.posterize(img, magnitude),
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"solarize": lambda img, magnitude: ImageOps.solarize(img, magnitude),
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"contrast": lambda img, magnitude: ImageEnhance.Contrast(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"sharpness": lambda img, magnitude: ImageEnhance.Sharpness(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"brightness": lambda img, magnitude: ImageEnhance.Brightness(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"autocontrast": lambda img, magnitude: 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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"cutout": lambda img, magnitude: cutout(img, magnitude),
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}
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self.p1 = p1
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self.operation1 = func[operation1]
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self.magnitude1 = ranges[operation1][magnitude_idx1]
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self.p2 = p2
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self.operation2 = func[operation2]
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self.magnitude2 = ranges[operation2][magnitude_idx2]
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def __call__(self, img):
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if random.random() < self.p1:
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img = self.operation1(img, self.magnitude1)
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if random.random() < self.p2:
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img = self.operation2(img, self.magnitude2)
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return img
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class RandAugmentV4(object):
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"""Custom RandAugment for ML-Decoder"""
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def __init__(self) -> None:
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super().__init__()
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self._policies = self.get_rand_policies()
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@classmethod
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def get_trans_list(cls):
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trans_list = [
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"shearX",
|
|
"shearY",
|
|
"translateX",
|
|
"translateY",
|
|
"rotate",
|
|
"color",
|
|
"posterize",
|
|
"solarize",
|
|
"contrast",
|
|
"sharpness",
|
|
"brightness",
|
|
"autocontrast",
|
|
"equalize",
|
|
"invert",
|
|
"cutout",
|
|
]
|
|
return trans_list
|
|
|
|
@classmethod
|
|
def get_rand_policies(cls):
|
|
op_list = []
|
|
for trans in cls.get_trans_list():
|
|
for magnitude in range(1, 10):
|
|
op_list += [(0.5, trans, magnitude)]
|
|
policies = []
|
|
for op_1 in op_list:
|
|
for op_2 in op_list:
|
|
policies += [[op_1, op_2]]
|
|
return policies
|
|
|
|
def __call__(self, img):
|
|
randomly_chosen_policy = self._policies[
|
|
random.randint(0, len(self._policies) - 1)]
|
|
policy = SubPolicyV2(*randomly_chosen_policy[0],
|
|
*randomly_chosen_policy[1])
|
|
img = policy(img)
|
|
return img
|