请问train_imgs[i][0]和train_imgs[-i-1][0]代表的是数据集中哪些图片？

data_dir = 'hotdog'
os.listdir(os.path.join(data_dir, "hotdog")) # ['train', 'test']
train_imgs = ImageFolder(os.path.join(data_dir, 'hotdog/train'))
test_imgs  = ImageFolder(os.path.join(data_dir, 'hotdog/test'))
hotdogs = [train_imgs[i][0] for i in range(8)]
not_hotdogs = [train_imgs[-i-1][0] for i in range(8)]  #not_hotdogs文件夹里从后面读回来
print(train_imgs[1])     #'tuple' object
print(train_imgs[1][0])  #'Image' object
d2l.show_images(hotdogs + not_hotdogs, 2, 8, scale=1.4)

请问train_imgs[i][0]和train_imgs[-i-1][0]代表的是数据集中哪些图片？

首先
print(train_imgs.shape)
看看数组的形状
train_imgs[i][0]是最后一个维度*i

train_imgs[-i-1][0]是从后往前数，第 最后一个维度*(i+1)