from torchvision.transforms import Normalize, Compose, RandomResizedCrop, InterpolationMode, ToTensor, Resize, \
    CenterCrop


def _convert_to_rgb(image):
    return image.convert('RGB')


def image_transform(
        image_size: int,
        is_train: bool,
        mean=(0.48145466, 0.4578275, 0.40821073),
        std=(0.26862954, 0.26130258, 0.27577711)
):
    normalize = Normalize(mean=mean, std=std)
    if is_train:
        return Compose([
            RandomResizedCrop(image_size, scale=(0.9, 1.0), interpolation=InterpolationMode.BICUBIC),
            _convert_to_rgb,
            ToTensor(),
            normalize,
        ])
    else:
        return Compose([
            Resize(image_size, interpolation=InterpolationMode.BICUBIC),
            CenterCrop(image_size),
            _convert_to_rgb,
            ToTensor(),
            normalize,
        ])

from torchvision.transforms import Normalize, Compose, RandomResizedCrop, InterpolationMode, ToTensor, Resize, \
    CenterCrop


def _convert_to_rgb(image):
    return image.convert('RGB')


def image_transform(
        image_size: int,
        is_train: bool,
        mean=(0.48145466, 0.4578275, 0.40821073),
        std=(0.26862954, 0.26130258, 0.27577711)
):
    normalize = Normalize(mean=mean, std=std)
    if is_train:
        return Compose([
            RandomResizedCrop(image_size, scale=(0.9, 1.0), interpolation=InterpolationMode.BICUBIC),
            _convert_to_rgb,
            ToTensor(),
            normalize,
        ])
    else:
        return Compose([
            Resize(image_size, interpolation=InterpolationMode.BICUBIC),
            CenterCrop(image_size),
            _convert_to_rgb,
            ToTensor(),
            normalize,
        ])
