torchvision 笔记：transforms.Compose()

torchvision.transforms.Compose()类的主要作用是串联多个transforms列表里面的transform操作

比如，在torchvision 笔记：transforms.Normalize()_UQI-LIUWJ的博客-CSDN博客 中的代码，可以用Compose来代替

不变的部分

from PIL import Image from torchvision import transforms, utils a=Image.open(b+'img/00000.jpg') a

 Compose的部分

t=transforms.Compose([transforms.ToTensor(),transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ]) a=t(a) a ''' tensor([[[1.9235, 1.9235, 1.9235, ..., 1.8893, 1.8893, 1.8893],[1.9235, 1.9235, 1.9235, ..., 1.8893, 1.8893, 1.8893],[1.9235, 1.9235, 1.9235, ..., 1.8893, 1.8893, 1.8893],...,[1.3242, 1.3242, 1.3242, ..., 1.3413, 1.3413, 1.3413],[1.3242, 1.3242, 1.3242, ..., 1.3413, 1.3413, 1.3413],[1.3242, 1.3242, 1.3242, ..., 1.3413, 1.3413, 1.3413]],[[2.0959, 2.0959, 2.0959, ..., 2.0784, 2.0784, 2.0784],[2.0959, 2.0959, 2.0959, ..., 2.0784, 2.0784, 2.0784],[2.0959, 2.0959, 2.0959, ..., 2.0784, 2.0784, 2.0784],...,[1.5182, 1.5182, 1.5182, ..., 1.5007, 1.5007, 1.5007],[1.5182, 1.5182, 1.5182, ..., 1.5007, 1.5007, 1.5007],[1.5182, 1.5182, 1.5182, ..., 1.5007, 1.5007, 1.5007]],[[2.3088, 2.3088, 2.3088, ..., 2.3263, 2.3263, 2.3263],[2.3088, 2.3088, 2.3088, ..., 2.3263, 2.3263, 2.3263],[2.3088, 2.3088, 2.3088, ..., 2.3263, 2.3263, 2.3263],...,[1.7163, 1.7163, 1.7163, ..., 1.7511, 1.7511, 1.7511],[1.7163, 1.7163, 1.7163, ..., 1.7511, 1.7511, 1.7511],[1.7163, 1.7163, 1.7163, ..., 1.7511, 1.7511, 1.7511]]]) '''

 

一样的效果

 

总结

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