stm32-modelzoo-app / image_classification /pt /src /datasets /augmentations /autoaugment /autoaugment.py
| # /*--------------------------------------------------------------------------------------------- | |
| # * Code modified from: https://github.com/uoguelph-mlrg/Cutout | |
| # * Copyright (c) 2025 STMicroelectronics. | |
| # * All rights reserved. | |
| # * This software is licensed under terms that can be found in the LICENSE file in | |
| # * the root directory of this software component. | |
| # * If no LICENSE file comes with this software, it is provided AS-IS. | |
| # *--------------------------------------------------------------------------------------------*/ | |
| import random | |
| import numpy as np | |
| from PIL import Image, ImageEnhance, ImageOps | |
| class ImageNetPolicy: | |
| """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 = random.randint(0, len(self.policies) - 1) | |
| return self.policies[policy_idx](img) | |
| def __repr__(self): | |
| return "AutoAugment imagenet Policy" | |
| class CIFAR10Policy: | |
| """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, 0.6, "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 = random.randint(0, len(self.policies) - 1) | |
| return self.policies[policy_idx](img) | |
| def __repr__(self): | |
| return "AutoAugment CIFAR10 Policy" | |
| class SVHNPolicy: | |
| """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 = random.randint(0, len(self.policies) - 1) | |
| return self.policies[policy_idx](img) | |
| def __repr__(self): | |
| return "AutoAugment SVHN Policy" | |
| class SubPolicy: | |
| 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": rotate_with_fill, | |
| "color": lambda img, magnitude: ImageEnhance.Color(img).enhance( | |
| 1 + magnitude * random.choice([-1, 1]) | |
| ), | |
| "posterize": ImageOps.posterize, | |
| "solarize": ImageOps.solarize, | |
| "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 | |