torchvision 笔记:transforms.Compose()
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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
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