【深度学习实战（37）】雨、雾、雪 数据增强

参考：https://imgaug.readthedocs.io/en/latest/source/overview_of_augmenters.html

一、代码

import cv2
from imgaug import augmenters as iaa
import os


seq = iaa.Sequential([
    #iaa.Rain(drop_size=(0.10, 0.20), speed=(0.2, 0.3)),  # 雨
    #iaa.MotionBlur(k=15),  # 运动模糊
    #iaa.Clouds(),  # 云雾
    #iaa.imgcorruptlike.Fog(severity=1),  # 多雾/霜
    iaa.imgcorruptlike.Snow(severity=2),  # 下雨、大雪
    #iaa.Cutout(nb_iterations=(3, 5), size=0.2, squared=False)
    #iaa.FastSnowyLandscape(lightness_threshold=[128, 200],lightness_multiplier=(1.5, 3.5))
    #iaa.Rain(speed=(0.3, 0.5)),  # 雨
    #iaa.Snowflakes(flake_size=(0.6, 0.7), speed=(0.02, 0.03)), # 雪点
    #iaa.imgcorruptlike.Spatter(severity=2),  # 溅 123水滴、45泥
    #iaa.contrast.LinearContrast((0.5, 2.0), per_channel=0.5),# 对比度变为原来的一半或者二倍
    #iaa.imgcorruptlike.Brightness(severity=2),  # 亮度增加
    #iaa.imgcorruptlike.Saturate(severity=3),  # 色彩饱和度
    #iaa.FastSnowyLandscape(lightness_threshold=(100, 255),lightness_multiplier=(1.5, 2.0)), # 雪地   亮度阈值是从 uniform(100, 255)（每张图像）和来自 uniform(1.5, 2.0)（每张图像）的乘数采样的。
    #iaa.Cartoon(blur_ksize=3, segmentation_size=1.0, saturation=2.0, edge_prevalence=1.0), # 卡通
])

path = './input/'
savedpath = './img_out/'

imglist = []
filelist = os.listdir(path)

for item in filelist:
    img = cv2.imread(path + item)
    print('item is ',item)
    print('img is ',img)
    imglist.append(img)
print('all the picture have been appent to imglist')

# 对文件夹中的图片进行增强操作，循环1次
for count in range(1):
    images_aug = seq.augment_images(imglist)
    for index in range(len(images_aug)):
        # filename = str(count) + str(index) + '.jpg'
        # 保存图片
        filename = str(filelist[index])
        cv2.imwrite(savedpath + filename, images_aug[index])
        print('image of count%s index%s has been writen' % (count, index))

二、效果