The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0

from torchvision import transforms
from PIL import Image
from torch.utils.tensorboard import SummaryWriter

image_path='images/pytorch.jpeg'
img=Image.open(image_path)
print(type(img))

writer=SummaryWriter('logs')

#归一化
print(tensor_img[0][0][0])
trans_norm=transforms.Normalize([0.5,0.5,0.5],[0.5,0.5,0.5])
norm_img=trans_norm(tensor_img)
print(norm_img[0][0][0])

writer.add_image('norm_img',norm_img,1)
writer.close()

因为该图片有4通道，需要处理。

方法一（转换成rgb）：

img=img.convert('rgb')

方法二（归一化时加上一个维度）：

trans_norm=transforms.Normalize([0.5,0.5,0.5,0.5],[0.5,0.5,0.5,0.5])

from torchvision import transforms
from PIL import Image
from torch.utils.tensorboard import SummaryWriter

image_path='images/pytorch.jpeg'
img=Image.open(image_path)
img=img.conver('rgb')
print(type(img))

writer=SummaryWriter('logs')

#归一化
print(tensor_img[0][0][0])
#trans_norm=transforms.Normalize([0.5,0.5,0.5,0.5],[0.5,0.5,0.5,0.5])
trans_norm=transforms.Normalize([0.5,0.5,0.5],[0.5,0.5,0.5])
norm_img=trans_norm(tensor_img)
print(norm_img[0][0][0])

writer.add_image('norm_img',norm_img,1)
writer.close()