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在神经网络准备训练集的时候，经常需要从文件夹中读取全部图片。经常遇到的有两种方式
1 os.listdir()
os.listdir()是列举文件夹中所有文件名。然后通过os.path.join()函数将文件夹的地址和文件夹名称连接起来获得绝对地址。
import os files=os.listdir('./T91_HR') print(type(files)) print(files) for i
in files: path=os.path.join('./T91_HR/'+i) print(path)
2 glob
glob是用于匹配符合指定模式的文件集合的一种语言
返回所有匹配的文件路径列表。它只有一个参数pathname，定义了文件路径匹配规则，这里可以是绝对路径，也可以是相对路径
glob.glob()
这里返回的是一个列表
from glob import glob import os path=os.path.join('./T91_HR/*.png')
files=glob(path) print(type(files)) for i in files: print(i)
glob.iglob()
这个函数与glob.glob()函数的功能类似，也只有pathname一个参数，但是这个函数返回一个迭代器，也就是说一次只返回一个路径，相比于glob.glob()会占用更少的内存。
from glob import iglob import os path=os.path.join('./T91_HR/*.png')
files=iglob(path) print(type(files))
自然排序
from natsort import natsorted a = ['1.png', '3.png', '10.png', '2.png'] ##常规排序
a.sort() print(a) ##自然排序 b = natsorted(a) print(b)
