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26 lines
719 B
Python
26 lines
719 B
Python
import cv2
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import numpy as np
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np.random.seed(0)
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class GaussianBlur(object):
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# Implements Gaussian blur as described in the SimCLR paper
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def __init__(self, kernel_size, min=0.1, max=2.0):
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self.min = min
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self.max = max
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# kernel size is set to be 10% of the image height/width
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self.kernel_size = kernel_size
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def __call__(self, sample):
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sample = np.array(sample)
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# blur the image with a 50% chance
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prob = np.random.random_sample()
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if prob < 0.5:
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sigma = (self.max - self.min) * np.random.random_sample() + self.min
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sample = cv2.GaussianBlur(sample, (self.kernel_size, self.kernel_size), sigma)
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return sample
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