pytorch(ch5

读取数据集：：
# -*- coding: utf-8 -*-
import torch as t
from torch.utils import data
import os
from PIL import Image
import numpy as np

class DogCat(data.Dataset):
 def __init__(self,root):
 imgs=os.listdir(root)
 #所有图片的绝对路径
 #这里不实际加载图片，只是指定路径，当调用__getitem__时才会真正读图片
 self.imgs=[os.path.join(root, img) for img in imgs]

 def __getitem__(self, index):
 img_path=self.imgs[index]
 #dog->1, cat->0
 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.image)

dataset=DogCat('data/train')
img,label=dataset[0]#相当于调用dataset.__getitem__(0)
for img,label in dataset:
 print(img.size(),img.float().mean(),label)