from torchvision import transforms

def get_transforms(train=True):
    if train:
        return transforms.Compose([
            transforms.Resize((150, 150)),
            transforms.RandomHorizontalFlip(),
            transforms.ToTensor(),
            transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])
        ])
    else:
        return transforms.Compose([
            transforms.Resize((150, 150)),
            transforms.ToTensor(),
            transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])
        ])