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Augmentations.py
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Wed, Oct 2, 17:34

Augmentations.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Aug 19 15:24:26 2022
@author: srpv
"""
import torch
import torch.nn as nn
import torchvision.transforms as torch_tf
import torchvision
class Solarization(nn.Module):
def __call__(self, x):
return torch_tf.functional.solarize(x, threshold=0.5)
def augmentation_tau_prime(p_blur=0.1, p_solarize=0.2):
return nn.Sequential(
torch_tf.RandomApply(torch.nn.ModuleList([torch_tf.RandomRotation(degrees=(0, 180),interpolation=torchvision.transforms.InterpolationMode.NEAREST,fill=0.065)]), p=0.75),
torch_tf.RandomHorizontalFlip(p=0.75),
torch_tf.RandomVerticalFlip(p=0.75),
)
def augmentation_tau():
return nn.Sequential(
torch_tf.RandomApply(torch.nn.ModuleList([torch_tf.RandomRotation(degrees=(0, 90),interpolation=torchvision.transforms.InterpolationMode.NEAREST,fill=0.065)]), p=0.25),
torch_tf.RandomHorizontalFlip(p=0.25),
torch_tf.RandomVerticalFlip(p=0.25),
)

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