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Mike
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upgrade ConvMLP
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‎image_classification/ConvMLP/auto_augment.py

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# Copyright (c) 2021 PPViT Authors. All Rights Reserved.
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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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"""Auto Augmentation"""
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import random
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import numpy as np
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from PIL import Image, ImageEnhance, ImageOps
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def auto_augment_policy_original():
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"""ImageNet auto augment policy"""
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policy = [
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[('Posterize', 0.4, 8), ('Rotate', 0.6, 9)],
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[('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
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[('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
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[('Posterize', 0.6, 7), ('Posterize', 0.6, 6)],
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[('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
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[('Equalize', 0.4, 4), ('Rotate', 0.8, 8)],
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[('Solarize', 0.6, 3), ('Equalize', 0.6, 7)],
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[('Posterize', 0.8, 5), ('Equalize', 1.0, 2)],
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[('Rotate', 0.2, 3), ('Solarize', 0.6, 8)],
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[('Equalize', 0.6, 8), ('Posterize', 0.4, 6)],
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[('Rotate', 0.8, 8), ('Color', 0.4, 0)],
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[('Rotate', 0.4, 9), ('Equalize', 0.6, 2)],
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[('Equalize', 0.0, 7), ('Equalize', 0.8, 8)],
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[('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
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[('Color', 0.6, 4), ('Contrast', 1.0, 8)],
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[('Rotate', 0.8, 8), ('Color', 1.0, 2)],
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[('Color', 0.8, 8), ('Solarize', 0.8, 7)],
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[('Sharpness', 0.4, 7), ('Invert', 0.6, 8)],
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[('ShearX', 0.6, 5), ('Equalize', 1.0, 9)],
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[('Color', 0.4, 0), ('Equalize', 0.6, 3)],
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[('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
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[('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
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[('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
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[('Color', 0.6, 4), ('Contrast', 1.0, 8)],
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[('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
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]
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policy = [[SubPolicy(*args) for args in subpolicy] for subpolicy in policy]
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return policy
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class AutoAugment():
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"""Auto Augment
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Randomly choose a tuple of augment ops from a list of policy
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Then apply the tuple of augment ops to input image
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"""
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def __init__(self, policy):
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self.policy = policy
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def __call__(self, image, policy_idx=None):
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if policy_idx is None:
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policy_idx = random.randint(0, len(self.policy)-1)
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sub_policy = self.policy[policy_idx]
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for op in sub_policy:
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image = op(image)
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return image
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class SubPolicy:
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"""Subpolicy
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Read augment name and magnitude, apply augment with probability
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Args:
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op_name: str, augment operation name
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prob: float, if prob > random prob, apply augment
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magnitude_idx: int, index of magnitude in preset magnitude ranges
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"""
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def __init__(self, op_name, prob, magnitude_idx):
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# ranges of operations' magnitude
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ranges = {
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'ShearX': np.linspace(0, 0.3, 10), # [-0.3, 0.3] (by random negative)
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'ShearY': np.linspace(0, 0.3, 10), # [-0.3, 0.3] (by random negative)
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'TranslateX': np.linspace(0, 150 / 331, 10), #[-0.45, 0.45] (by random negative)
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'TranslateY': np.linspace(0, 150 / 331, 10), #[-0.45, 0.45] (by random negative)
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'Rotate': np.linspace(0, 30, 10), #[-30, 30] (by random negative)
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'Color': np.linspace(0, 0.9, 10), #[-0.9, 0.9] (by random negative)
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'Posterize': np.round(np.linspace(8, 4, 10), 0).astype(np.int), #[0, 4]
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'Solarize': np.linspace(256, 0, 10), #[0, 256]
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'Contrast': np.linspace(0, 0.9, 10), #[-0.9, 0.9] (by random negative)
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'Sharpness': np.linspace(0, 0.9, 10), #[-0.9, 0.9] (by random negative)
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'Brightness': np.linspace(0, 0.9, 10), #[-0.9, 0.9] (by random negative)
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'AutoContrast': [0] * 10, # no range
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'Equalize': [0] * 10, # no range
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'Invert': [0] * 10, # no range
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}
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# augmentation operations
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# Lambda is not pickleable for DDP
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#image_ops = {
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# 'ShearX': lambda image, magnitude: shear_x(image, magnitude),
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# 'ShearY': lambda image, magnitude: shear_y(image, magnitude),
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# 'TranslateX': lambda image, magnitude: translate_x(image, magnitude),
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# 'TranslateY': lambda image, magnitude: translate_y(image, magnitude),
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# 'Rotate': lambda image, magnitude: rotate(image, magnitude),
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# 'AutoContrast': lambda image, magnitude: auto_contrast(image, magnitude),
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# 'Invert': lambda image, magnitude: invert(image, magnitude),
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# 'Equalize': lambda image, magnitude: equalize(image, magnitude),
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# 'Solarize': lambda image, magnitude: solarize(image, magnitude),
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# 'Posterize': lambda image, magnitude: posterize(image, magnitude),
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# 'Contrast': lambda image, magnitude: contrast(image, magnitude),
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# 'Color': lambda image, magnitude: color(image, magnitude),
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# 'Brightness': lambda image, magnitude: brightness(image, magnitude),
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# 'Sharpness': lambda image, magnitude: sharpness(image, magnitude),
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#}
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image_ops = {
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'ShearX': shear_x,
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'ShearY': shear_y,
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'TranslateX': translate_x_relative,
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'TranslateY': translate_y_relative,
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'Rotate': rotate,
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'AutoContrast': auto_contrast,
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'Invert': invert,
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'Equalize': equalize,
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'Solarize': solarize,
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'Posterize': posterize,
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'Contrast': contrast,
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'Color': color,
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'Brightness': brightness,
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'Sharpness': sharpness,
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}
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self.prob = prob
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self.magnitude = ranges[op_name][magnitude_idx]
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self.op = image_ops[op_name]
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def __call__(self, image):
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if self.prob > random.random():
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image = self.op(image, self.magnitude)
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return image
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# PIL Image transforms
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# https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.transform
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def shear_x(image, magnitude, fillcolor=(128, 128, 128)):
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factor = magnitude * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, factor, 0, 0, 1, 0), fillcolor=fillcolor)
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def shear_y(image, magnitude, fillcolor=(128, 128, 128)):
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factor = magnitude * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, 0, 0, factor, 1, 0), fillcolor=fillcolor)
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def translate_x_relative(image, magnitude, fillcolor=(128, 128, 128)):
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pixels = magnitude * image.size[0]
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pixels = pixels * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, 0, pixels, 0, 1, 0), fillcolor=fillcolor)
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def translate_y_relative(image, magnitude, fillcolor=(128, 128, 128)):
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pixels = magnitude * image.size[0]
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pixels = pixels * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, 0, 0, 0, 1, pixels), fillcolor=fillcolor)
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def translate_x_absolute(image, magnitude, fillcolor=(128, 128, 128)):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, 0, magnitude, 0, 1, 0), fillcolor=fillcolor)
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def translate_y_absolute(image, magnitude, fillcolor=(128, 128, 128)):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return image.transform(image.size, Image.AFFINE, (1, 0, 0, 0, 1, magnitude), fillcolor=fillcolor)
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def rotate(image, magnitude):
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rot = image.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(image.mode)
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def auto_contrast(image, magnitude=None):
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return ImageOps.autocontrast(image)
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def invert(image, magnitude=None):
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return ImageOps.invert(image)
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def equalize(image, magnitude=None):
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return ImageOps.equalize(image)
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def solarize(image, magnitude):
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return ImageOps.solarize(image, magnitude)
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def posterize(image, magnitude):
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return ImageOps.posterize(image, magnitude)
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def contrast(image, magnitude):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return ImageEnhance.Contrast(image).enhance(1 + magnitude)
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def color(image, magnitude):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return ImageEnhance.Color(image).enhance(1 + magnitude)
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def brightness(image, magnitude):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return ImageEnhance.Brightness(image).enhance(1 + magnitude)
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def sharpness(image, magnitude):
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magnitude = magnitude * random.choice([-1, 1]) # random negative
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return ImageEnhance.Sharpness(image).enhance(1 + magnitude)
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