pytorchは自分で画像訓練セットのテストセットコードを作成することを実現する(二)

from torchvision.datasets import ImageFolder
from torchvision import transforms

ROOT_TRAIN = r'D:/pycharm/pychanrm /data/ ' # 
ROOT_TEST = r'D:/pycharm/pychanrm /data/ '    # 

train_transform = transforms.Compose([
    transforms.Resize((1000)), 
    #T.RandomVerticalFlip(), #  
    transforms.CenterCrop(1000),
    transforms.ToTensor(), 
    transforms.Normalize([.5, .5, .5], [.5, .5, .5])])
    
test_transform = transforms.Compose([
    transforms.Resize((1000)),
    #T.RandomVerticalFlip(), #  
    transforms.CenterCrop(1000),
    transforms.ToTensor(), 
    transforms.Normalize([.5, .5, .5], [.5, .5, .5])])

# 
train_dataset = ImageFolder(ROOT_TRAIN, transform=train_transform)
test_dataset = ImageFolder(ROOT_TEST, transform=test_transform)

# 
data_loader_train = t.utils.data.DataLoader(dataset=train_dataset,
                                            batch_size=1,   
                                            shuffle=True,
                                            num_workers=0)

data_loader_test = t.utils.data.DataLoader(dataset=test_dataset,
                                            batch_size=1,
                                            shuffle=True,
                                            num_workers=0)