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import torch |
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import torchvision.transforms as transforms |
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class AddGaussianNoise: |
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def __init__(self, mean=0., std=1.): |
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self.std = std |
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self.mean = mean |
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def __call__(self, img): |
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return img + torch.randn(img.size()) * self.std + self.mean |
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def __repr__(self): |
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return self.__class__.__name__ + '(mean={0}, std={1})'.format(self.mean, self.std) |
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def transform_back_image(): |
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return transforms.Compose([ |
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transforms.RandomAffine(degrees=0, translate=(0.1, 0.1)), |
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transforms.RandomRotation((-5, 5)), |
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transforms.Pad(padding=10, fill=0, padding_mode='constant'), |
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transforms.ToTensor(), |
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AddGaussianNoise(0., 0.1) |
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]) |
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