在 Udacity 学习 AI 类(class)时,我在迁移学习部分遇到了这个错误。这是似乎引起问题的代码:
import torch
from torch import nn
from torch import optim
import torch.nn.functional as F
from torchvision import datasets, transforms, models
data_dir = 'filename'
# TODO: Define transforms for the training data and testing data
train_transforms= transforms.Compose([transforms.Resize((224,224)), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), transforms.ToTensor()])
test_transforms= transforms.Compose([transforms.Resize((224,224)), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), transforms.ToTensor()])
# Pass transforms in here, then run the next cell to see how the transforms look
train_data = datasets.ImageFolder(data_dir + '/train', transform=train_transforms)
test_data = datasets.ImageFolder(data_dir + '/test', transform=test_transforms)
trainloader = torch.utils.data.DataLoader(train_data, batch_size=64, shuffle=True)
testloader = torch.utils.data.DataLoader(test_data, batch_size=32)
最佳答案
问题在于转换的顺序。 ToTensor
转换应该在 Normalize
转换之前进行,因为后者需要张量,但 Resize
转换返回图像。更改错误行的正确代码:
train_transforms = transforms.Compose([
transforms.Resize((224,224)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
test_transforms = transforms.Compose([
transforms.Resize((224,224)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
关于python - 类型错误 : tensor is not a torch image,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51807040/