port torch as t
from PIL import Image
from torch.utils import data
import os
import numpy as np

class DogCat(data.Dataset):
    
    def __init__(self,root):
        
        imgs=os.listdir(root)
        self.imgs=[os.path.join(root,img) for img in imgs]
        
    
    # test1: data/test1/8973.jpg
    # train: data/train/cat.10004.jpg
    def __getitem__(self,index):
        
        img_path=self.imgs[index]
        
        label=1 if 'dog' in img_path.split('/')[-1] else 0
        
        pil_img=Image.open(img_path)
        array=np.asarray(pil_img)
        
        data=t.from_numpy(array)
        
        return data,label
    
    def __len__(self):
        return len(self.imgs)
    

datasets=DogCat('./data/train')


    
for img,label in datasets:
    print(img.size(),img.float().mean(),label)
    
 

索引的時候，會自動呼叫__getitem__方法，然後單張的讀取圖片。