安装

安装请参考https://github.com/aleju/imgaug

在安装时，如果Shapely这个库安装不上，请到https://pypi.org/project/Shapely/#history下载whl文件，然后使用命令

pip install xxx_shaplely.whl

进行安装

施加单种变换

from imgaug import augmenters as iaa

import imgaug as ia

import numpy as np

from scipy import misc

import os

def createdir(path):

if not os.path.exists(path):

os.mkdir(path)

def apply_aug(image):

images = []

flipper = iaa.Fliplr(1.0) # always horizontally flip each input image

images.append(flipper.augment_image(image)) # horizontally flip image 0

vflipper = iaa.Flipud(1) # vertically flip each input image with 90% probability

images.append(vflipper.augment_image(image)) # probably vertically flip image 1

blurer = iaa.GaussianBlur(sigma=(0, 3.0))

images.append(blurer.augment_image(image)) # blur image 2 by a sigma of 3.0

crop_and_pad = iaa.CropAndPad(px=(0, 30)) # crop images from each side by 0 to 16px (randomly chosen)

images.append(crop_and_pad.augment_image(image))

# inverter = iaa.Invert(0.05)

# images.append(inverter.augment_image(image))

contrast_normalization = iaa.ContrastNormalization((0.5, 2.0))

images.append(contrast_normalization.augment_image(image))

add_process = iaa.Add((-10, 10), per_channel=0.5)

images.append(add_process.augment_image(image))

sharpen_process = iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5))

images.append(sharpen_process.augment_image(image))

emboss_process = iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)) # emboss images

images.append(emboss_process.augment_image(image))

rot_process_1 = iaa.Rot90(1)

images.append(rot_process_1.augment_image(image))

rot_process_2 = iaa.Rot90(2)

images.append(rot_process_2.augment_image(image))

rot_process_3 = iaa.Rot90(3)

images.append(rot_process_3.augment_image(image))

elastic_transformation_process = iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)

images.append(elastic_transformation_process.augment_image(image))

perspectivetransform_process = iaa.PerspectiveTransform(scale=(0.01, 0.1))

images.append(perspectivetransform_process.augment_image(image))

averageblur_process = iaa.AverageBlur(k=(2, 7))

images.append(averageblur_process.augment_image(image))

medianblur_process = iaa.MedianBlur(k=(3, 11))

images.append(medianblur_process.augment_image(image))

return np.array(images, dtype=np.uint8)

'''

文件夹格式：

根文件夹"D:\smj\data"

类别文件夹"D:\smj\data\dog"和"D:\smj\data\cat"

图片文件夹"D:\smj\data\dog\1.png"和"D:\smj\data\cat\1.png"

'''

root_path = r"D:\smj\data"

root_save_path = r"D:\smj\data\aug"

class_dirs = os.listdir(root_path)

for class_dir in class_dirs:

class_dir_path = root_path + "\\" + class_dir

img_names = os.listdir(class_dir_path)

class_save_dir_path = root_save_path + "\\" + class_dir

createdir(class_save_dir_path)

for img_name in img_names:

img_path = class_dir_path + "\\" + img_name

img = misc.imread(img_path)

images = apply_aug(np.array(img, dtype=np.uint8))

for i in range(images.shape[0]):

save_path = class_save_dir_path + "\\" + img_name.split(".")[0] + "====" + str(i) + ".png"

misc.imsave(save_path, images[i,:,:,:])

单个图片同时施加多种变换

from imgaug import augmenters as iaa

import imgaug as ia

import numpy as np

from scipy import misc

import os

seq = iaa.Sequential([

iaa.CropAndPad(

px=(0, 30)), # crop images from each side by 0 to 16px (randomly chosen)

iaa.Fliplr(1), # horizontally flip 50% of the images

iaa.Flipud(1),

iaa.GaussianBlur(sigma=(0, 3.0)), # blur images with a sigma of 0 to 3.0

# # iaa.Affine(

# # scale={"x": (0.8, 1.2), "y": (0.8, 1.2)}, # scale images to 80-120% of their size, individually per axis

# # translate_percent={"x": (-0.2, 0.2), "y": (-0.2, 0.2)}, # translate by -20 to +20 percent (per axis)

# # rotate=(-45, 45), # rotate by -45 to +45 degrees

# # shear=(-16, 16), # shear by -16 to +16 degrees

# # order=[0, 1], # use nearest neighbour or bilinear interpolation (fast)

# # cval=(0, 255), # if mode is constant, use a cval between 0 and 255

# # mode=ia.ALL # use any of scikit-image's warping modes (see 2nd image from the top for examples)

# # ),

iaa.Invert(0.05, per_channel=True),

iaa.ContrastNormalization((0.5, 2.0), per_channel=0.5),

# iaa.AddToHueAndSaturation((-20, 20)), #############commonly error

iaa.Add((-10, 10), per_channel=0.5),

iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)),

iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)), # emboss images

iaa.Rot90(1),

iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25),

iaa.Rot90(2),

iaa.Rot90(3),

])

root_path = r"F:\data"

class_dirs = os.listdir(root_path)

for class_dir in class_dirs:

class_dir_path = root_path + "\\" + class_dir

img_names = os.listdir(class_dir_path)

for img_name in img_names:

img_path = class_dir_path + "\\" + img_name

img = misc.imread(img_path)

img = img[np.newaxis,:,:,:]

img = np.array(img, dtype=np.uint8)

images_aug = seq.augment_images(img) # done by the library

print("img_name")