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pytorch 如何实现HWC转CHW

作者:高颜值的杀生丸

这篇文章主要介绍了pytorch HWC转CHW的实现方式,具有很好的参考价值,希望对大家有所帮助。如有错误或未考虑完全的地方,望不吝赐教

看代码吧~

import torch
import numpy as np
from torchvision.transforms import ToTensor 
t = torch.tensor(np.arange(24).reshape(2,4,3))
print(t)
 
#HWC 转CHW
print(t.transpose(0,2).transpose(1,2)) 
print(t.permute(2,0,1)) 
print(ToTensor()(t.numpy()))

D:\anaconda\python.exe C:/Users/liuxinyu/Desktop/pytorch_test/day3/hwc转chw.py
tensor([[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]],

[[12, 13, 14],
[15, 16, 17],
[18, 19, 20],
[21, 22, 23]]], dtype=torch.int32)
tensor([[[ 0, 3, 6, 9],
[12, 15, 18, 21]],

[[ 1, 4, 7, 10],
[13, 16, 19, 22]],

[[ 2, 5, 8, 11],
[14, 17, 20, 23]]], dtype=torch.int32)
tensor([[[ 0, 3, 6, 9],
[12, 15, 18, 21]],

[[ 1, 4, 7, 10],
[13, 16, 19, 22]],

[[ 2, 5, 8, 11],
[14, 17, 20, 23]]], dtype=torch.int32)
tensor([[[ 0, 3, 6, 9],
[12, 15, 18, 21]],

[[ 1, 4, 7, 10],
[13, 16, 19, 22]],

[[ 2, 5, 8, 11],
[14, 17, 20, 23]]], dtype=torch.int32)

Process finished with exit code 0

补充:opencv python 把图(cv2下)BGR转RGB,且HWC转CHW

如下所示:

img = cv2.imread("001.jpg")
img_ = img[:,:,::-1].transpose((2,0,1))

① 在opencv里,图格式HWC,其余都是CHW,故transpose((2,0,1))

② img[:,:,::-1]对应H、W、C,彩图是3通道,即C是3层。opencv里对应BGR,故通过C通道的 ::-1 就是把BGR转为RGB

注: [::-1] 代表顺序相反操作

③ 若不涉及C通道的BGR转RGB,如Img[:,:,0]代表B通道,也就是蓝色分量图像;Img[:,:,1]代表G通道,也就是绿色分量图像;

Img[:,:,2]代表R通道,也就是红色分量图像。

补充:python opencv 中将图像由BGR转换为CHW用于后期的深度训练

BGR HWC -> CHW 12 -> HCW 01 -> CHW

import cv2 as cv
import  numpy as np
img = cv.imread("lenna.png")
#BGR HWC -> CHW  12 -> HCW 01 -> CHW
transform_img = img.swapaxes(1,2).swapaxes(0,1)
print(img.shape)
print(transform_img.shape)
cv.imshow("image0 ",transform_img[0])
cv.imshow("image1",transform_img[1])
cv.imshow("image2",transform_img[2])
cv.waitKey(0)
cv.destroyAllWindows()

以上为个人经验,希望能给大家一个参考,也希望大家多多支持脚本之家。

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