Python数据增强(data augmentation)库--Augmentor 使用介绍

Augmentor 使用介绍

原图

1.random_distortion(probability, grid_height, grid_width, magnitude)

最终选择参数为

  • p.random_distortion(probability=0.8, grid_height=3, grid_width=3, magnitude=6)

其他参数效果:

magnitudegrid_width,grid_height越大,扭曲程度越大


  • p.random_distortion(probability=0.6, grid_height=6, grid_width=6, magnitude=5)
  • p.random_distortion(probability=0.6, grid_height=6, grid_width=6, magnitude=9)
  • p.random_distortion(probability=0.6, grid_height=10, grid_width=10, magnitude=5)

2.random_erasing(probability, rectangle_area)

rectangle_area表示覆盖区域的比例,值越大比例越大。但是设置为1的时候并不是全覆盖,不知道为什么,反正也没必要弄清楚

  • p.random_erasing(1,1)

3.zoom_random(probability, percentage_area)

放大图片,然后按照percenta_area的比例对图片进行crop。

  • p.zoom_random(probability=1, percentage_area=0.2)
  • p.zoom_random(probability=1, percentage_area=0.8)

4.zoom(probability, min_factor, max_factor)

  • p.zoom(probability=1, min_factor=1.1, max_factor=1.5)
  • p.zoom(probability=1, min_factor=2, max_factor=2)

组合操作

p.rotate_random_90(probability=0.8)
p.random_distortion(probability=0.8, grid_height=3, grid_width=3, magnitude=6)
p.random_erasing(0.3, 0.2)
p.zoom(probability=0.4, min_factor=1.1, max_factor=1.5)
p.sample(6)


MARSGGBO原创





2018-4-1



转载于:https://www.cnblogs.com/marsggbo/p/8687103.html

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