1 ToTensor

將shape為(H, W, C)的numpy.ndarray或img轉為shape為(C, H, W)的tensor

在一定條件下，將每一個數(shù)值歸一化到[0,1]，歸一化方法比較簡單，直接除以255即可。（一定條件后面會說明）

1.1 Ndarray

只有Ndarray是np.uint8 類型的時候，才會歸一化

1.1.1?np.uint8 類型

看得出來確實歸一化了

import torchvision.transforms as transforms import numpy as npa=np.array([[100,200],[400,500],[700,800]],dtype=np.uint8)a=a.reshape(3,2,1) a.shape #(3, 2, 1)t=transforms.ToTensor() ta=t(a) print(a) ''' [[[100][200]][[144][244]][[188] '''print(ta) ''' tensor([[[0.3922, 0.7843],[0.5647, 0.9569],[0.7373, 0.1255]]]) '''print(ta.shape) #torch.Size([1, 3, 2])

1.1.2 非np.uint8 類型

沒有歸一化

import torchvision.transforms as transforms import numpy as npa=np.array([[100,200],[400,500],[700,800]],dtype=np.uint8)a=a.reshape(3,2,1) a.shape,a.dtype ((3, 2, 1), dtype('int32'))t=transforms.ToTensor() ta=t(a) print(a) ''' [[[100][200]][[144][244]][[188] '''print(ta) ''' tensor([[[100, 200],[400, 500],[700, 800]]], dtype=torch.int32) '''print(ta.shape) #torch.Size([1, 3, 2])

1.2 圖片

以DeepFasion數(shù)據集里面的一張圖片為例：

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

?

y=transforms.ToTensor() a=y(a) a ''' tensor([[[0.9255, 0.9255, 0.9255, ..., 0.9176, 0.9176, 0.9176],[0.9255, 0.9255, 0.9255, ..., 0.9176, 0.9176, 0.9176],[0.9255, 0.9255, 0.9255, ..., 0.9176, 0.9176, 0.9176],...,[0.7882, 0.7882, 0.7882, ..., 0.7922, 0.7922, 0.7922],[0.7882, 0.7882, 0.7882, ..., 0.7922, 0.7922, 0.7922],[0.7882, 0.7882, 0.7882, ..., 0.7922, 0.7922, 0.7922]],[[0.9255, 0.9255, 0.9255, ..., 0.9216, 0.9216, 0.9216],[0.9255, 0.9255, 0.9255, ..., 0.9216, 0.9216, 0.9216],[0.9255, 0.9255, 0.9255, ..., 0.9216, 0.9216, 0.9216],...,[0.7961, 0.7961, 0.7961, ..., 0.7922, 0.7922, 0.7922],[0.7961, 0.7961, 0.7961, ..., 0.7922, 0.7922, 0.7922],[0.7961, 0.7961, 0.7961, ..., 0.7922, 0.7922, 0.7922]],[[0.9255, 0.9255, 0.9255, ..., 0.9294, 0.9294, 0.9294],[0.9255, 0.9255, 0.9255, ..., 0.9294, 0.9294, 0.9294],[0.9255, 0.9255, 0.9255, ..., 0.9294, 0.9294, 0.9294],...,[0.7922, 0.7922, 0.7922, ..., 0.8000, 0.8000, 0.8000],[0.7922, 0.7922, 0.7922, ..., 0.8000, 0.8000, 0.8000],[0.7922, 0.7922, 0.7922, ..., 0.8000, 0.8000, 0.8000]]]) '''

總結

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