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