from torchvision import datasets, transforms
from torch.utils.data import DataLoader

def get_data_loaders(train_dir, test_dir, batch_size=32):
    transform = transforms.Compose([
        transforms.Resize((224, 224)),
        transforms.ToTensor(),
        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    ])

    train_dataset = datasets.ImageFolder(train_dir, transform=transform)
    test_dataset = datasets.ImageFolder(test_dir, transform=transform)

    train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)
    test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False)
    
    return train_loader, test_loader