使用pytorch进行图像的顺序读取方法

dataset = dset.ImageFolder( 
 root='./folder1', 
 transform=transforms.Compose([ 
  transforms.ToTensor(), 
  transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5)), # bring images to (-1,1) 
 ]) 
) 
dataloader1 = torch.utils.data.DataLoader(dataset, batch_size=opt.batchSize, shuffle=True, num_workers=opt.workers) 
iterator1 = iter(dataloader1)
for i in range(1,1001):
data = iterator1.next() 
data2 = iterator2.next()

from PIL import Image
pathDir = os.listdir('./folder') #获取文件夹内所有文件的名称，生成数组 
 pathDir.sort() #对所有文件名进行排序
 for allDir in pathDir: 
 child = os.path.join('%s/%s' % ('./folder', allDir))#合成文件名 
 fopen = Image.open(child).convert('RGB') #通过PIL读取文件
 transform_list = [transforms.ToTensor(), 
    transforms.Normalize((0.5, 0.5, 0.5), 
  (0.5, 0.5, 0.5))] 
 transform = transforms.Compose(transform_list)#将PIL格式的文件转换成 tensor
 image = transform(fopen) #转换

for i in range(1,1001): 
 drain = irain.next() 
 dnorain = iground.next() 
 drain = os.path.join('%s/图像%s' % ('./rainy_img', i)) #跟上面一样，不过因为已经知道文件的取名顺序，所以拼出需要访问的文件名
 fopen = Image.open(drain).convert('RGB') 
 drain = transform(fopen) 
 print(drain)