56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# encoding: utf-8
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"""
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@author: liaoxingyu
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@contact: liaoxingyu2@jd.com
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"""
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import math
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import random
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class RandomErasing(object):
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""" Randomly selects a rectangle region in an image and erases its pixels.
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'Random Erasing Data Augmentation' by Zhong et al.
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See https://arxiv.org/pdf/1708.04896.pdf
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Args:
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probability: The probability that the Random Erasing operation will be performed.
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sl: Minimum proportion of erased area against input image.
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sh: Maximum proportion of erased area against input image.
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r1: Minimum aspect ratio of erased area.
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mean: Erasing value.
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"""
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def __init__(self, probability=0.5, sl=0.02, sh=0.4, r1=0.3, mean=(0.4914, 0.4822, 0.4465)):
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self.probability = probability
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self.mean = mean
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self.sl = sl
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self.sh = sh
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self.r1 = r1
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def __call__(self, img):
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if random.uniform(0, 1) >= self.probability:
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return img
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for attempt in range(100):
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area = img.size()[1] * img.size()[2]
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target_area = random.uniform(self.sl, self.sh) * area
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aspect_ratio = random.uniform(self.r1, 1 / self.r1)
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h = int(round(math.sqrt(target_area * aspect_ratio)))
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w = int(round(math.sqrt(target_area / aspect_ratio)))
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if w < img.size()[2] and h < img.size()[1]:
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x1 = random.randint(0, img.size()[1] - h)
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y1 = random.randint(0, img.size()[2] - w)
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if img.size()[0] == 3:
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img[0, x1:x1 + h, y1:y1 + w] = self.mean[0]
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img[1, x1:x1 + h, y1:y1 + w] = self.mean[1]
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img[2, x1:x1 + h, y1:y1 + w] = self.mean[2]
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else:
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img[0, x1:x1 + h, y1:y1 + w] = self.mean[0]
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return img
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return img
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